Planetary Science (Advances in Geosciences)

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A d v a n c e s

i n

Geosciences Volume 19: Planetary Science (PS)

ADVANCES IN GEOSCIENCES Editor-in-Chief: Wing-Huen Ip (National Central University, Taiwan) A 5-Volume Set

A 6-Volume Set

Volume 1: Solid Earth (SE) ISBN-10 981-256-985-5 Volume 2: Solar Terrestrial (ST) ISBN-10 981-256-984-7 Volume 3: Planetary Science (PS) ISBN-10 981-256-983-9 Volume 4: Hydrological Science (HS) ISBN-10 981-256-982-0 Volume 5: Oceans and Atmospheres (OA) ISBN-10 981-256-981-2

Volume 16: Atmospheric Science (AS) ISBN-13 978-981-283-809-4 ISBN-10 981-283-809-0 Volume 17: Hydrological Science (HS) ISBN-13 978-981-283-811-7 ISBN-10 981-283-811-2 Volume 18: Ocean Science (OS) ISBN-13 978-981-283-813-1 ISBN-10 981-283-813-9 Volume 19: Planetary Science (PS) ISBN-13 978-981-283-815-5 ISBN-10 981-283-815-5 Volume 20: Solid Earth (SE) ISBN-13 978-981-283-817-9 ISBN-10 981-283-817-1 Volume 21: Solar Terrestrial (ST) ISBN-13 978-981-283-819-3 ISBN-10 981-283-819-8

A 4-Volume Set Volume 6: Hydrological Science (HS) ISBN-13 978-981-270-985-1 ISBN-10 981-270-985-1 Volume 7: Planetary Science (PS) ISBN-13 978-981-270-986-8 ISBN-10 981-270-986-X Volume 8: Solar Terrestrial (ST) ISBN-13 978-981-270-987-5 ISBN-10 981-270-987-8 Volume 9: Solid Earth (SE), Ocean Science (OS) & Atmospheric Science (AS) ISBN-13 978-981-270-988-2 ISBN-10 981-270-988-6 A 6-Volume Set Volume 10: Atmospheric Science (AS) ISBN-13 978-981-283-611-3 ISBN-10 981-283-611-X Volume 11: Hydrological Science (HS) ISBN-13 978-981-283-613-7 ISBN-10 981-283-613-6 Volume 12: Ocean Science (OS) ISBN-13 978-981-283-615-1 ISBN-10 981-283-615-2 Volume 13: Solid Earth (SE) ISBN-13 978-981-283-617-5

ISBN-10 981-283-617-9 Volume 14: Solar Terrestrial (ST) ISBN-13 978-981-283-619-9 ISBN-10 981-283-619-5 Volume 15: Planetary Science (PS) ISBN-13 978-981-283-621-2 ISBN-10 981-283-621-7

A d v a n c e s

i n

Geosciences Volume 19: Planetary Science (PS)

Editor-in-Chief

Wing-Huen Ip

National Central University, Taiwan

Volume Editor-in-Chief

Anil Bhardwaj

Space Physics Laboratory Vikram Sarabhai Space Centre, India

World Scientific NEW JERSEY

•

LONDON

•

SINGAPORE

•

BEIJING

•

SHANGHAI

•

HONG KONG

•

TA I P E I

•

CHENNAI

Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.

ADVANCES IN GEOSCIENCES A 6-Volume Set Volume 19: Planetary Science (PS) Copyright © 2010 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher.

For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher.

ISBN-13 ISBN-10 ISBN-13 ISBN-10

978-981-283-808-7 981-283-808-2 978-981-283-815-5 981-283-815-5

(Set) (Set) (Vol. 19) (Vol. 19)

Typeset by Stallion Press Email: [email protected] Printed in Singapore.

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EDITORS

Editor-in-Chief:

Wing-Huen Ip

Volume 16: Atmospheric Science (AS) Editor-in-Chief: Jai Ho Oh Editors: G. P. Singh C. C. Wu K.-J. Ha Volume 17: Hydrological Science (HS) Editor-in-Chief: Namsik Park Editors: Ji Chen Joong-Hoon Kim Jinping Liu Young-Il Moon Sanjay Patil Ashok Kumar Rastogi Simon Toze Volume 18: Ocean Science (OS) Editor-in-Chief: Jianping Gan Editors: Minhan Dai Anne Mueller Murty Vadiamani Volume 19: Planetary Science (PS) Editor-in-Chief: Anil Bhardwaj Editors: Yasumasa Kasaba Guillermo Manuel Mu˜ noz Caro Takashi Ito Paul Hartogh C. Y. Robert Wu S. A. Haider v

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REVIEWERS

The Editors of Volume 19 (Planetary Science) would like to acknowledge the following referees who have helped to review the manuscript published in this volume: Hoe Teck Tan C. Y. Robert Wu Hauke Hussmann Guillermo Manuel Mu˜ noz Caro B. L. Deekshatulu K. I. Oyama Alexander Kutepov Alexandr Feigin Yuriy Ivanov Sachchida Nand Tripathi Ozgur Karatekin Takeshi Kuroda Alexander Medvedev Keran O’Brien Naoki Terada Shinobu Machida Tatsuaki Okada Juergen Oberst Tony Gabriel Gianni de Angelis Geronimo Villanueva Rafael Escribano Ricardo Vidal D. Banerjee Manabu Kato Angela Ciaravella Hiromu Nakagawa Hiroaki Shiraishi vii

Frank Sohl Miriam Rengel Luke Moore Ram´ on Luna C. K. Shum Koji Matsumoto Daniel Santos-Costa Patrick Galopeau Tadashi Mukai Greg Neumann Kosuke Heki Glenn Stark Jan B. Nee Takanori Sasaki Shinsuke Abe Michael Mendillo Martin Hilchenbach Philippe Baron Conor Nixon Esa Kallio S. A. Haider Tai-Sone Yih David L. Huestis Dominique Delcourt J.-A. Sauvaud Donald Shemansky Martin Hilchenbach Urs Mall

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Reviewers

Richard Fallows Masayoshi Kojima Claude d’Uston Frederick Partey Florencio Ballesteros Ram K. Tripathi Varun Sheel G¨ unter Kargl Murthy Gudipati Herve Abgrall Brenton Lewis Francois Leblanc

Oleg Korablev Christopher Jarchow Donald Malocha Masahiro Hoshino Takeshi Imamura Alexander Medvedev Christophe Risacher Luisa Lara Nikolay Ignatiev Miriam Rengel Yoshifumi Saito Stefano Orsini

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PREFACE The present volume set of Advances in Geosciences (ADGEO) contain papers from the Busan annual meeting in 2008 and some from the Singapore annual meeting in 2009. As Editor-in-Chief, I must apologize to the AOGS members and authors for this delay. Since 2006 we have published 20 volumes in total. This publication project has been supported by the AOGS Council, World Scientiﬁc Publication Company (WSPC), the team of hard working editors and the broad membership and participants of AOGS. As with the main purpose of the Society, ADGEO is meant to promote information exchange and to forge scientiﬁc cooperation in the area of Earth science and environmental study. As witnessed by the negotiation eﬀorts at the United Nations Climate Change Conference in Copenhagen in December 2009, all these issues have become more and more important and vital in the Asia-Paciﬁc region. It is not a matter of exaggeration in saying that the solution to global warming, if there is one, has to come from the emerging economies and developing countries covered by AOGS. By design, ADGEO has its fundamental role to play. In practical terms, it is actually a diﬃcult task because of many factors involved in deciding the quality of manuscripts, editorial and review processes, publication procedure, scientiﬁc impacts, readership, policy of the AOGS Council, and last but not least, marketing from the point of view of the publisher. Any small mishap in this long chain of interactive steps could lead to a major discontinuity. We have encountered such a situation with the publication of the Busan manuscripts. It is only with the cooperation of the authors, the ADGEO editorial team, WSPC, and the AOGS Secretariat Oﬃce, that we are able to produce these volumes, albeit a long delay. With this lesson learned, we hope to consolidate the ADGEO management and editorial system so that it would become an essential publication in our understanding of Earth and space science and information tool books in the battle against climate change. Finally, I would like to take this opportunity to thank the Volume Editors-in-Chief who are the driving force in making ADGEO possible: A. Bhardwaj (Planetary Science), M. Duldig (Solar and Terrestrial Science), J.P. Gan (Ocean Science), J.H. Oh (Atmospheric ix

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Preface

Science), N.S. Park (Hydrological Science), K. Satake and C.H. Lo (Solid Earth). They have to work very hard to ensure both the quantity and quality of the published papers in ADGEO. Of equal importance, the support from WSPC is essential and its foresight in identifying the academic and social values of Earth science and environmental study to be sustained and articulated by ADGEO is very much appreciated.

Wing-Huen Ip Editor-in-Chief

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PREFACE TO PS VOLUME The ﬁfth and sixth Annual Meetings of the Asia Oceania Geosciences Society (AOGS) were held in Busan (Korea) in 2008 and in Singapore in 2009, respectively. Roughly one-ﬁfth of the total number of papers at these two annual meetings was presented in diﬀerent Planetary Science (PS) sessions. The present PS volume of Advances in Geosciences (ADGEO) contains papers from the Busan and some from the Singapore annual meetings, and present some of the highlights reported in these sessions. They cover diﬀerent planets in the solar system, their satellites, as well as minor bodies and ice and dust. The papers deal with observation, modeling, laboratory measurements, simulations, instrumentation, and missions. A whole range of planetary sciences activities are covered in these papers, including surfaces, interiors, atmospheres, ionospheres, exospheres, magnetospheres, and solar wind interaction. We are conﬁdent that this issue will be a high-quality contribution that would serve the purpose of disseminating science to the planetary science community. Putting together this volume was only possible with the cooperation of the authors, the ADGEO PS editorial team, the AOGS Secretariat Oﬃce, in particular Zaiyi Guo, the referees, and the overall Editor-in-Chief Wing-Huen Ip. I take this opportunity to thank the Editors of this Planetary Science Volume who are the driving force in making AdGeo possible: Y. Kasaba (Tohoku University, Japan), Guillermo Manuel Mu˜ noz Caro (Centro de Astrobiolog´ıa, Spain), Takashi Ito (National Astronomical Observatory of Japan), Paul Hartogh (Max-Planck-Institute for Solar System Research, Germany), C. Y. Robert Wu (University of Southern California, USA), and S. A. Haider (Physical Research Laboratory, India). They have worked very hard to ensure both the quantity and quality of the published papers in this PS volume of ADGEO. On behalf of the Planetary Science editorial team, I greatly appreciate the eﬀorts of the referees in providing timely and careful reviews. Anil Bhardwaj PS Volume Editor-in-Chief xi

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Editors

Volume 20: Solid Earth (SE) Editor-in-Chief: Kenji Satake Volume 21: Solar & Terrestrial Science (ST) Editor-in-Chief: Marc Duldig Editors: P. K. Manoharan Andrew W. Yau Q.-G. Zong

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CONTENTS

Editors

v

Reviewers

vii

Preface

ix

Preface to PS Volume

xi

A Comparison of the Exospheres of Mercury and the Moon

1

Wing-Huen Ip and Yung-Ching Wang Charged Particle Acceleration in the Hermean Magnetosphere: The Comparison of Contributions of Diﬀerent Mechanisms

9

Zelenyi Lev, Malova Helmi, Korzhov Alexey, Popov Victor, Dominique Delcourt and Artemyev Anton A Model Study on Observation Modes of MIA/MMO Based on the EM Design

29

W. Miyake and Y. Saito Distributions of K and Th on the Moon: The Initial Results from Observations by Selene GRS Yuzuru Karouji, Nobuyuki Hasebe, Osamu Okudaira, Naoyuki Yamashita, Shingo Kobayashi, Makoto Hareyama, Takashi Miyachi, Satoshi, Kodaira, Kazuya Iwabuchi, Kanako Hayatsu, Shinpei Nemoto, Yuko Takeda, xiii

43

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Koichi Tsukada, Hiroshi Nagaoka, Masanori Kobayasi, Eido Shibamura, Mitsuru Ebihara, Takeshi Hihara, Tomoko Arai, Takamitsu Sugihara, Hiroshi Takeda, Claude D’uston, Sylvestre Maurice, Olivier Gasnault, Olivier Forni, Benedicte Diez, Robert C. Reedy, Kyeong J. Kim, Takeshi Takashima, Yuichi Iijima and Hisashi Otake Lunar Gamma-Ray Observation by Kaguya GRS

57

N. Hasebe, N. Yamashita, Y. Karouji, S. Kobayashi, M. Hareyama, S. Komatsu, K. Hayatsu, K. Nemoto, K. Iwabuchi, Y. Takeda, H. Nagaoka, K. Tsukada, J. Machida, O. Okudaira, S. Sakurai, E. Shibamura, M.-N. Kobayashi, M. Ebihara, T. Hihara, T. Arai, T. Sugihara, H. Takeda, C. d’uston, O. Gasnault, B. Diez, O. Forni, S. Maurice, R. C. Reedy and K. J. Kim The Ambient Dose Equivalent from Lunar Gamma-Rays Observed by Kaguya Gamma-Ray Spectrometer

69

Y. Takeda, K. Hayatsu, S. Kobayashi, M. Hareyama, N. Hasebe, S. Kodaira and K. J. Kim Computational Geology for Lunar Data Analysis from LISM on KAGUYA

77

Noriaki Asada, Naru Hirata, Hirohide Demura, Naoto Harada, Yuto Shibata, Shota Kikuchi, Tomoki Hodokuma, Junichi Haruyama, Makiko Ohtake, Yasuhiro Yokota, Tomokatsu Morota, Chikatoshi Honda, Tsuneo Matsunaga, Yoshiko Ogawa, Masaya Torii, Tokuhiro Nimura, Hiroshi Araki and Seiichi Tazawa Modeling of the Radiation Environment on the Moon Giovanni De Angelis, Francis F. Badavi, John M. Clem, Steve R. Blattnig, Martha S. Clowdsley, Ram K. Tripathi and John W. Wilson

89

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Telescope of Extreme Ultraviolet Boarded on KAGUYA: Science from the Moon

xv

109

Ichiro Yoshikawa, Go Murakami, Fukuhiro Ezawa, Kazuo Yoshioka, Yuki Obana, Makoto Taguchi, Atsushi Yamazaki, Shingo Kameda, Masato Nakamura, Masayuki Kikuchi, Masato Kagitani, Shoichi Okano, Kazuo Shiokawa and Wataru Miyake Assessment of VLBI Data for Chang’E-1 Precision Orbit Determination

123

Yan Jianguo, Ping Jingsong, Li Fei and Huang Qian Chang’E-1 Laser Altimetry Data Processing

137

Qian Huang, Jingsong Ping, Jianguo Yan, Jianfeng Cao, Geshi Tang and Rong Shu The SUB-KEV Atom Reﬂecting Analyzer (SARA) Experiment Aboard Chandrayaan-1 Mission: Instrument and Observations

151

Anil Bhardwaj, M. B. Dhanya, R. Sridharan, Martin Wieser, Stas Barabash, Futaana Yoshifumi, Mats Holmstr¨ om, Peter Wurz, Audrey Schaufelberger and Asamura Kazushi The Doppler-Sonnemann Eﬀect (DSE) on the Photochemistry on Mars

163

M. Grygalashvyly, P. Hartogh, G. R. Sonnemann and A. S. Medvedev A New Coupled 3D-Model of the Dynamics and Chemistry of the Martian Atmosphere

177

G. R. Sonnemann, P. Hartogh, M. Grygalashvyly and A. S. Medvedev Changes in Mass Flow Caused by CO2 Condensation in the Martian Atmosphere K. Ogohara and T. Satomura

195

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Modeling of the Radiation Environment on Mars

207

Giovanni De Angelis, Francis F. Badavi, Steve R. Blattnig, Martha S. Clowdsley, Garry D. Qualls, Robert C. Singleterry Jr., Ram K. Tripathi and John W. Wilson Zonal Variability of Neutral Density, Temperature and Ion Production Rates in the Martian Troposphere

225

Varun Sheel, S. A. Haider, V. Singh, W. C. Maguire and G. J. Molina-Cuberos Scientiﬁc and Technical Aspects of the ESA MarsNEXT Mission

235

A. Chicarro, J. D. Carpenter, R. Fisackerly, A. Santovincenzo, D. Breuer, E. Chassefiere, V. Dehant, M. Grady, P. Pinet and A. P. Rossi Study on the O+ Ion Distribution and Escape in Martian Atmosphere

251

Jiankui Shi, Zhenxing Liu, Klaus Torkar, Tielong Zhang and Malcolm Dunlop Wind Velocities of Diﬀerent Seasons and Dust Opacities on Mars: Comparison Between Microwave Observations and Simulations by General Circulation Models

261

Takeshi Kuroda and Paul Hartogh Retrieval Simulations of the Vertical Proﬁles of Water Vapour and Other Chemical Species in the Martian Atmosphere using PACS

271

G. Portyankina, N. Thomas, P. Hartogh and H. Sagawa Near-Infrared Lightcurves of a Very Young Asteroid, Karin Takashi Ito and Fumi Yoshida

285

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Development of a Light-Weight and Large-Area Parallel-Plate Impact Ionization Detector for In Situ Measurement of Dust/Debris

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295

Takayuki Hirai, Hideo Ohashi, Sho Sasaki, Hiromi Shibata, Ken-Ichi Nogami, Takeo Iwai and Ralf Srama Application of Penetrators Within the Solar System

307

Alan Smith, Robert A. Gowen, Kerrin Rees, Craig Theobald, Patrick Brown, William T. Pike, Toby Hopf, Sunil Kumar, Philip Church, Yang Gao, Adrian Jones, Katherine H. Joy, Ian A. Crawford, Simon Sheridan, Axel Hagermann, Simeon J. Barber, Andrew J. Ball and Nigel Wells Duty Cycle Weighting using e-Beam Lithography in RACs for Chirp Transform Spectrometers

321

Xianyi Li, Paul Hartogh, Leonhard Reindl, Thomas Weimann and Victor Plessky Retrieval Simulations of Atmospheric Gases from Herschel observations of Titan

335

M. Rengel, H. Sagawa and P. Hartogh Do Galilean Satellites of Jupiter Have Isochemical Compositions?

349

V. A. Kronrod and O. L. Kuskov Internal Structure of the Icy Satellites of Jupiter

365

O. L. Kuskov, V. A. Kronrod and A. P. Zhidikova Jupiter Thermospheric General Circulation Model (JTGCM): Global Thermal Balances and Thermospheric Wind — A Review Tariq Majeed, J. Hunter Waite, Jr., G. Randall Gladstone and Stephen W. Bougher

377

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The Saturn Hot Atomic Hydrogen Plume: Quantum Mechanical Investigation of H2 Dissociation Mechanisms

405

Xianming Liu, D. E. Shemansky, P. V. Johnson, C. P. Malone, H. Melin, J. A. Young and I. Kanik VUV Absorption Properties of Gaseous and Solid C2 H2 : Relevance to Outer Planetary Atmospheres Research

427

C. Y. Robert Wu, F. Z. Chen, D. L. Judge and B. M. Cheng Excited States of N2 for Planetary Airglow: A Laboratory Study

445

Jan B. Nee and H. S. Fung Vacuum-Ultraviolet Absorption Spectra of Small Molecules in the Solid Phase

453

H.-C. Lu, H.-K. Chen, Y.-J. Wu, B.-M. Cheng and J. F. Ogilvie Photoabsorption Spectra of Some Organic Molecules for Planetary Interests

465

Jan. B. Nee C2 H2 Absorption Cross-Section Measurements at Extreme Low Temperature — A Windowless Technique

475

J. I. Lo, Y. C. Lin, T. S. Yih, C. Y. R. Wu, D. L. Judge and H. S. Fung Vacuum Ultraviolet Photodissociation of Ethene Isolated in Solid Neon

489

Yu-Jong Wu, Meng-Yeh Lin, Sheng-Chuan Hsu, Hsiao-Chi Lu, Hong-Kai Chen and Bing-Ming Cheng Irreversible Thermodynamics of a Gas-Liquid Interface Daniel M. Packwood and Leon F. Phillips

499

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Laboratory Models for ICES in Comet Nuclei

xix

511

Rafael Escribano, Oscar G´ alvez, Bel´en Mat´e and V´ıctor J. Herrero Studies in the Laboratory on the Structure of CO2 Ice. Astrophysical Implications

527

R. Luna The Interstellar Astrochemistry Chamber (ISAC) ´ Mart´ın-Gago, C. Rogero, G. M. Mu˜ noz Caro, J. A.

541

A. Jim´enez-Escobar, J. M. Sobrado, C. Atienza and S. Puertas Reliability of Mass Spectroscopy Under HV Conditions to Study Retaining Mechanisms of ICES ´ Satorre, C. Mill´ R. Luna, M. A. an and J. Cant´ o A New, High-performance, Heterodyne Spectrometer for Ground-based Remote Sensing of Mesospheric Water Vapour

557

569

K. Hallgren, P. Hartogh and C. Jarchow Extreme Ultraviolet Spectroscope for Exospheric Dynamics Explore (Exceed)

579

Ichiro Yoshikawa, Kazuo Yoshioka, Go Murakami, Atsushi Yamazaki, Shingo Kameda, Munetaka Ueno, Naoki Terada, Fuminori Tsuchiya, Masato Kagitani and Yasumasa Kasaba Common Errors in the Calculation of Aircrew Doses from Cosmic Rays

593

Keran O’Brien, Ernst Felsberger and Peter Kindl Multi-Frequency Total ﬂux Measurements of Jupiter’s Synchrotron Radiation in 2007 F. Tsuchiya, H. Misawa, K. Imai, A. Morioka and T. Kondo

601

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Studies of the Interior Structure of Planetary Bodies by Laser Altimetry

613

C. Koch, R. Kallenbach, U. R. Christensen and M. Hilchenbach Regional Centres for Space Science and Technology Education Aﬃliated to the United Nations

633

A. J. A. Aquino and H. J. Haubold Asia-Paciﬁc Region Water Boosted Rocket Events K.-I. Oyama, A. Hidayat, E. Sofyan, H. S. S. Sinha, K. Herudi, T. Kubota, S. Sukkarieh, J. L. Arban, D. M. Chung, I. Medagangoda, Z. B. Mohd, S. Pitan, C. Chin and F. R. Sarkar

639

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

A COMPARISON OF THE EXOSPHERES OF MERCURY AND THE MOON WING-HUEN IP∗ and YUNG-CHING WANG Institutes of Astronomy and Space Science, National Central University, Taiwan ∗ [email protected]

Ground-based optical studies of the similarities and dissimilarities of the sodium emissions of Mercury and the Moon have provided a lot of important information on the basic structures and dynamics of these two surface-bound exospheric systems. There are a number of key issues to be clariﬁed. These include the relative importance of ion sputtering in producing sodium atoms (and hence other gas species) comparison to meteoroid impact and photodesoption eﬀect, and the potential importance of magnetic anomalies (if exist) in modifying the space weathering eﬀect of Mercury’s surface. The new observations from the MESSENGER spacecraft at Mercury and the several lunar orbiters including Kaguya of Japan, Chang’e-1 of China and Chandrayaan-1 of India are expected to bring us answers and, certainly, far more questions to these two atmospheres of unique importance in comparative planetology.

1. Introduction After so many years of waiting in line, the study of the exospheres of Mercury and the Moon has ﬁnally been ushered into the limelight. The new generation of plasma instruments onboard the Kaguya lunar orbiter of JAXA and the MESSENGER spacecraft of NASA have already yielded a wealth of information on the dynamics and compositions of the pickup ions created by surface interactions. For example, Zurbuchen et al.1 reported that in Mercury’s magnetosphere traversed by the MESSENGER spacecraft, the ions with mass-to-charge (m/q) ratio between 3.8 and 42 are dominated by metallic ions (i.e. Na+ , Mg+ , S+ , Si+ , K+, Ca+ , etc) ejected from the planetary surface. Preliminary reports of plasma measurements on the Kaguya lunar orbiter showed the presence of pickup ions of similar chemical composition.2 1

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W.-H. Ip and Y.-C. Wang

Fig. 1. A summary of the three major source mechanisms of the sodium atoms on Mercury: (a) the production process with the meteoroid impact is uniformly distributed; (b) the production process with the photon sputtering is distributed as cosn θ centered around the sub-solar point; (c) the production process with the solar wind ion sputtering is conﬁned in a ﬁnite ara a high latitude. Note that the whole sunward hemisphere will be source region in the case of the Moon. (After Wang and Ip4 )

Figure 1 illustrates the three main source mechanisms which are believed to be responsible for the production of the surface-bound exospheres of both Mercury and the Moon.3,4 As depicted, the photonstimulated desorption eﬀect has strong dependence on the zenith angle of the Sun. On the other hand, the meteoroid impact mechanism is generally assumed to be uniform across the planetary surface. The ion sputtering process could have strong asymmetry if solar wind particles are the main agent in ejecting neutral atoms from the surface material. In eﬀect, both Mercury and the Moon are subject to strong surface interaction with planetary magnetospheric plasma. The only diﬀerence is that Mercury has its own intrinsic magnetic ﬁeld while the Moon would go in and out of Earth’s magnetosphere. It is also important to note that meteoroid impact could bring in volatile molecules like H2 O and CO2 from outside. There are major uncertainties in the relative importance of the various source mechanisms. The situation is particularly murky in the case of Mercury. Because of its exceptional brightness, the optical D-line emissions of the sodium atoms at 5890 A and 5896 A have been used as a tracer for planetary and satellitary atmospheres. An excellent example is the sodium cloud of the Jovian moon, Io.5 The sodium emissions from Mercury and the Moon have played the same role and much useful information on the nature of their atmospheres has been obtained by ground-based observations. A number of excellent reviews on Mercury’s exosphere have been produced just prior to the ﬁrst encounter of the MESSENGER spacecraft on January 7, 2008.6,7 Note that it is common to consider the lunar atmosphere to be just a copy of Mercury’s (or vice versa). This is likely a misconception because there are

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A Comparison of the Exospheres of Mercury and the Moon

3

probably many important diﬀerences ranging from the physical properties of the surface materials of both planetary bodies to the interaction of their dust and regolith layers with the corresponding plasma and thermal environments. On the other hand, these two exospheric systems do share some major similarities in their origin and dynamics. It is therefore timely to compare the similarities and dissimilarities of these two surface-bound exospheres so that the basic questions to be addressed can be highlighted. We will focus on three issues here, namely, (1) the formation of the extended atomic sodium comas and tail structures; (2) the time variability, and (3) the existence of surface magnetic anomalies.

2. Extended Sodium Comas and Tails Immediately after the ﬁrst report of the discovery of Mercury’s strong optical D-line emission of the sodium atoms by Potter and Morgan,8 Ip9 and Smyth10 produced theoretical models to show the possible formation of an extended sodium coma and tail because of the action of the solar radiation pressure force. To achieve this, the initial emission speed of the sodium atoms has to exceed a threshold value of about 2 km s−1 . It was only recently that the presence of such a sodium tail was reported by Potter et al.,11 Potter and Killen,12 Kameda et al.13 and Baumgardner et al.14 The wide-ﬁeld imaging observations of Baumgardner et al.14 showed that the length of the sodium tail could be as long as 1,600 RM (1 RM = one Mercury’s radius). The formation of an extended sodium coma surrounding the Moon was also predicted15 subsequent to its discovery.16 Once again, the full size of the lunar sodium exosphere was revealed by the wide-ﬁeld imaging observations of the Boston group.17 The images taken during lunar eclipses (in order to reduce the glare of the lunar disk) indicated that the radius of the exospheric halo could be as large as 12 lunar radii. This means that the Moon should also possess a tail made up of Na atoms.15 To produce escaping Na atoms from Mercury requires the production of exospheric atoms at emission speed exceeding 2 km s−1 and somewhat less for the Moon.9,10 Therefore ion sputtering must play an important role since both photonstimulated desorption and meteoroid impact evaporation would only create atoms of emission speed mostly at 0.9 km s−1 and 1.4 km s−1 , respectively, according to Bruno et al.18 As a result, we should expect the production rate of the extended sodium halo/tail to be controlled by solar wind activity or the interplanetary condition. From this point of view, it is interesting

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to note that Smith et al.19 and Wilson et al.20 reported the detection of a distant lunar sodium tail associated with the surface impact bombardment of the Leonid meteor shower on the Moon in 1998. In these narrow-band imaging measurements, the peak sodium atom production rate increased by a factor of about 4 from 7 × 1021 atoms s−1 to 2.5 × 1022 atoms s−1 . In addition, the ejection velocity was estimated to be above 2.1 km s−1 which was considerably larger than the Bruno et al. value of 0.9 km s−1 and 1.4 km s−1 . There are thus still many uncertainties in the surface emission mechanisms of the lunar sodium atoms. 3. Time Variability One noteworthy feature of the sodium emission from Mercury’s disk has to do with its night-to-night brightness variation sometimes observed.21,22 In addition, the brightness enhancement tended to appear in the high-altitude region, especially in the polar area.11 Similar pattern of polar enhancement was reported in the imaging observations of Baumgardner et al.14 This eﬀect gives the impression that magnetospheric dynamics must be the controlling factor. That is, the cusp regions of the polar magnetosphere tend to provide open access of the solar wind particles to the planetary surface (see Fig. 1c). As for the persistent north-south asymmetry, we believe that it might be the result of an anomaly of the surface magnetic ﬁeld which allows more charged particle to precipitate in the north (with weaker ﬁeld). Certainly, this hypothesis will be tested by the MESSENGER observations in near future. Space measurements will also permit the examination of the dependence of the sodium production rate on the photosputtering eﬀect. At Mercury, a major source mechanism of the Na atoms is due to the irradiation of the solar ultraviolet photons.18,23 It is therefore quite likely that the production rate of the Na atoms will suddenly increase following a solar ﬂare. A coordinated observation program to monitor the variability of sodium brightness of the planetary disk and the sodium tail and their correlation with solar activity and interplanetary condition near Mercury will provide deﬁnitive answer to these basic questions. It is important to point out that the three source mechanisms depicted in Fig. 1, namely, ion sputtering, photon-stimulated desorption, and meteoroid impact, can be coupled via magnetospheric process. This is because the exospheric neutrals supplied by these mechanisms will be partly ionized and be fed into Mercury’s magnetosphere. Trapping and acceleration of the Na+ , Mg+ , S+ , Si+ , K+ , Ca+ pickup ions might

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lead to re-impact of these energetic ions on the planetary surface thus producing yet another population of exospheric neutrals.24,25 This sequence of events is both complex and highly interrelated and we have no clues yet on how it would work at Mercury. But ground-based observations of the lunar corona of sodium atoms have given us a glimpse of what might happen as far as the basic process is concerned. In their detailed investigation of the behavior of the Moon’s extended sodium atmosphere during lunar eclipses, Mendillo et al.16 suggested that solar wind sputtering is not an important source of the sodium atoms because the halo did not subside after the Moon entered Earth’s magnetospheric tail where the solar wind ﬂux is highly reduced. On the basis of this unique set of observations, these authors concluded that photon-stimulated desorption should provide about 85% of the exospheric sodium atoms while the rest (about 15%) should come from meteoroid impact evaporation. This result is consistent with the theoretical calculation of Wurz et al.23 But in a subsequent re-analysis of the full-moon observational data, Wilson et al.26 found that the brightness of the lunar sodium exosphere has good correlation with the Moon’s passage through the Earth’s plasma sheet in the magnetotail. They therefore suggested that surface interaction with the plasma sheet ions could lead to a higher level of photo-desorption. On the other hand, it is to be investigated whether the higher ﬂux of energetic charged particles in the magnetospheric plasma sheet could lead to enhanced surface sputtering rate of the sodium atoms. This problem can be best attacked by coordinated observations combining groundbased observations and spacecraft in-situ measurements by the lunar orbiters. Sarantos et al.27 re-examined an event of lunar passage of the magnetospheric plasma sheet based on the spectroscopic measurements of the sodium line emission above the equator from 100 to 4,000 km attitudes by the McMath-Pierce Solar Telescope.28 They concluded that the observed short-term decrease of the sodium emission which was accompanied by an increase of the exospheric temperature from 1,200 K to 3,000 K could not be explained by the chancy impact of a 0.5-m radius meteoroid on the lunar surface. The above discussion demonstrated clearly the complexity of the exospheric origins and the uncertainties still remain in our understanding of the Moon (and Mercury by implication) with its space environment and the interplanetary meteoroid complex. The joint in-situ measurements by Kaguya, Chang’e-1, Chandrayaan-1 and any other future lunar missions (such as LADEE of NASA), supported by ground-based observations will

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bring new insights to the origin and temporal evolution of the lunar atmosphere. 4. Magnetic Anomalies The MESSENGER spacecraft, after its Mercury Orbit Insertion (MOI), will begin the phase of detailed mapping of the planetary surface and its magnetic environment. From the point of view of comparative planetology, it would be of interest to infer possible magnetic features based on the lunar magnetic ﬁeld measurements from previous missions like Apollo 16 and Lunar Prospector. A case in point is about the existence of magnetic anomalies (i.e. high ﬁeld regions on the Moon which appear to be correlated with antipodal young lunar basins like Imbrium, Orientale, Serenitatis, and Crisium.29−32 The theory developed by Hide31 and subsequently by Hood,34 Hood and Huang33 and Hood and Avtemieva36 is based on the idea that the convergence of shock wave of the dust clouds and plasma from a

Fig. 2. A schematic illustration of the possible existence and origin of magnetic anomalies from the basin-forming impact of the Caloris basin on Mercury. The expansion and convergence of the impact plasma cloud would carry the ambient magnetic ﬁeld of the interplanetary medium and/or the intrinsic planetary magnetic ﬁeld to the antipodal pint resulting in a strong ﬁeld region. (After Lin et al.31 )

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basin-forming impact on the antipodal region will lead to an enhancement of the surface magnetic ﬁeld. These magnetic anomalies have important eﬀects on shielding some local areas from solar wind protons thus modifying the surface weathering process.37 It is likely that the trapping and escaping of the exospheric pickup ions are also inﬂuenced by the magnetic anomalies. In this context, Mercury could serve as a testing ground of the antipodal impact shock theory.33,34 That is, the antipodal region of the Caloris impact basin would be expected to be characterized by high surface ﬁeld strength.

5. Summary and Discussion In this review, we have made a brief description of the structures and time variability of the sodium exospheres of Mercury and the Moon as observed from ground-based telescope facilities. Even though we seem to have some ideas on the cause and eﬀect of the dynamics and highly complex behaviors of these two surface-bound exospheres, the essential information is still missing and no deﬁnitive conclusion can be drawn. The next few years will be remembered as the break-through years of the studies of the lunar and Hermean atmospheres analogous to the revolutionary impact of the Giotto encounter with comet Halley on cometary research. On the other hand, it is tempting to speculate that if the surface magnetic anomalies of the Moon can be explained by the basin-forming impact theory, we probably will ﬁnd similar magnetic anomalies on the antipodal side of the Caloris basin.

Acknowledgments I thank Dr. Drew Potter, Dr. Rosemary Killen and the two anonymous reviewers for useful comments on the manuscript. This work was partially supported by NSC 97-2112-M-008-011-MY3 and NSC 97-2111-M-008-018MY3 and a grant of NCU 5500 Top University Program.

References 1. 2. 3. 4. 5.

T. H. Zurbuchen, J. M. Raines, G. Gloeckler et al., Science 321 (2008) 90. Y. Saito, S. Yokota, K. Asamura et al., Earth Planets Space 60 (2008) 375. R. Killen and W.-H. Ip, Rev. Geophys. 37 (1999) 361. Y. C. Wang and W.-H. Ip, Adv. Space Res. 42 (2008) 34. N. Thomas, F. Bagenal, T. W. Hill, J. K. Wilson, in Jupiter, Eds. F. Bagenal, T. E. Dowling, and W. B. McKinnon, pp.561–592, Cambridge University Press (2004).

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6. M. Fujimoto, W. Baumjohann, K. Kabin, R. Nakamura, J. A. Slavin, N. Terada and L. Zelenyi, Space Sci. Rev. 132 (2007) 529. 7. R. Killen, G. Cremonese, H. Lammer et al., Space Sci. Rev. 132 (2007) 433. 8. A. E. Potter and T. H. Morgan, Science 229 (1985) 651. 9. W.-H. Ip, Geophys. Res. Lett. 13 (1986) 423. 10. W. H. Smyth, Nature 323 (1986) 696. 11. A. E. Potter, R. M. Killen and T. H. Morgan, Meteorit. Planet. Sci. 37 (2002) 1165. 12. A. H. Potter and R. M. Killen, Icarus 194 (2008) 1. 13. S. Kameda, M. Kagitani, S. Okano, I. Yoshikawa and J. Ono, Adv. Space Sci. 41 (2008) 1381. 14. J. Baumgardner, J. Wilson and M. Mendillo, Geophys. Res. Lett. 35 (2008) L03201. 15. W.-H. Ip, Geophys. Res. Lett. 18 (1991) 2093. 16. A. H. Potter and T. H. Morgan, Science 241 (1988) 675. 17. M. Mendillo and J. Baumgardner, Nature 377 (1995) 404. 18. M. Bruno, G. Cremonese and S. Marchi, Planet. Space Sci. 55 (2007) 1491. 19. S. M. Smith, J. K. Wilson, J. Baumgardner and M. Mendillo, Geophys. Res. Lett. 26 (1999) 1649. 20. J. K. Wilson, S. M. Smith, J. Baumgardner and M. Mendillo, Geophys. Res. Lett. 26 (1999) 1645. 21. A. E. Potter and T. H. Morgan, Science 248 (1990) 835. 22. A. E. Potter, R. M. Killen and T. H. Morgan, Planet. Space Sci. 47 (1999) 1441. 23. P. Wurz, U. Rohner, J. A. Whitby et al., Icarus 191 (2007) 486. 24. W.-H. Ip, Icarus 71 (1987) 441. 25. D. C. Delcourt, T. E. Moore, S. Orsini, A. Millio and J.-A. Sauvard, Geophys. Res. Lett. 29 (2002) 32. 26. J. K. Wilson, M. Mendillo and H. E. Spence, J. Geophys. Res. 111 (2006) A07207. 27. M. Sarantos, R. M. Killen, A. S. Sharma and J. A. Slavin, Geophys. Res. Lett. 35 (2008) L04105. 28. A. E. Potter, R. M. Killen and T. H. Morgan, J. Geophys. Res. 105 (2000) 15073. 29. L. L. Hood, P. J. Coleman, Jr., C. T. Russell and D. E. Wilhelms, Phys. Earth Planet. Int. 20 (1979) 291. 30. L. L. Hood, A. Zakharian, J. Halekas, D. Mitchell, R. Lin, M. Acuna and A. Binder, J. Geophys. Res. 106 (2001) 27825. 31. R. P. Lin, K. A. Anderson and L. L. Hood, Icarus 74 (1988) 529. 32. D. L. Mitchell, J. S. Halekas, R. P. Lin et al. Icarus 194 (2008) 401. 33. R. Hide, The Moon 4 (1972) 39. 34. L. L. Hood, Geophys. Res. Lett. 14 (1987) 844. 35. L. L. Hood and Z. Huang, J. Geophys. Res. 96 (1991) 9837. 36. L. L. Hood and N. A. Artemieva, Icarus 193 (2008) 485. 37. N. C. Richmond, L. L. Hood and E. M. Harnett, LPSC 39 (2008) 2005.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

CHARGED PARTICLE ACCELERATION IN THE HERMEAN MAGNETOSPHERE: THE COMPARISON OF CONTRIBUTIONS OF DIFFERENT MECHANISMS∗ ZELENYI LEV Space Research Institutes RAS Moscow, 117997, Russia [email protected] MALOVA HELMI Nuclear Physics Institute Moscow State University, Moscow, Russia KORZHOV ALEXEY Moscow Engineering Physics Institute Moscow, Russia POPOV VICTOR Physics Department Moscow State University, Moscow, Russia DOMINIQUE DELCOURT Laboratoire de Physique des Plasma CNRS, Saint-Maur-des Fosses, France ARTEMYEV ANTON Space Research Institutes RAS Moscow, 117997, Russia

Several important mechanisms of plasma particle acceleration and heating in the Hermean magnetosphere were investigated in a frame of diﬀerent numerical models. It is shown that the most eﬀective acceleration mechanisms for Mercury are particle scattering on magnetic turbulence in the magnetotail and one of multiple dipolarizations during substorm activity. The comparison with plasma processes in the Earth’s magnetosphere demonstrate that the role of these mechanisms is more important near Mercury because of its small magnetosphere and the close distance to the Sun.

∗ This

work is supported by RFBR grants 09-02-00407, 06-02-72561 and HIII 472.2008.2. 9

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1. Introduction The magnetic ﬁeld of Mercury, the ﬁrst planet of the solar system was discovered in 1974 during Mariner-10 ﬂyby near the planet. Due to Mariner10 mission across the Hermean magnetosphere (the region where the own planetary magnetic ﬁeld dominate) the ﬁrst data about the structure and dynamics of the magnetosphere were obtained, that reveal the great interest to investigations of Mercury and its plasma envelope.1 Now Mariner-10 is not a single spacecraft to study Mercury. The American probe Messenger launched in 2004 towards Mercury, has done two ﬂyby near Mercury the 14 January and the 4 October 2008. The next ﬂight is expected the 29 September 2009 y., after this in March 2011 this spacecraft will go the stationary orbit around the planet to systematic exploration.2 In 2014 the launch of two Japanese-European spacecraft BEPI Colombo is planned, that reach the orbit of Mercury in 2020 and then become its constant satellites.3 The measurements of the magnetic ﬁelds and particle composition near the planet by Mariner-10 were quite contradictory and provoked many questions, answers for which might be obtained only in the course of new measurements.4,5 This problem is very important because of future space missions to Mercury and proposed detailed measurements near it. To understand what mechanisms of charged particle acceleration might eﬀectively exist in the Hermean magnetosphere, let us remind its essential parameters. The strength of the magnetic ﬁeld at the planetary surface is 100 times weaker than in the Earth’s one. From the site of the Sun the magnetosphere of Mercury is strongly stressed by the solar wind ﬂow, otherwise, from the night side it is strongly elongated and have well expressed tail structure (Fig. 1). The volume of the Hermean magnetosphere is only 5% from the Earth’s one, the magnetopause in the lobe point is situated at the distance only 1.1-1.5 RM (RM ≈ 2400 km) from the center of the planet. Contrary to the Earth the Mercury occupies the larger relative volume of the magnetosphere, this is a reason of its more simple structure with absent both ionosphere and atmosphere, but existing exosphere. Exosphere consists essentially from neutral atoms He, protons, ions Na, K, Ca, Si, and water molecules (discovered recently by spacecraft Messenger), observed in the tail area at distances to 20000 km and more in anti-sun direction. The density of Na+ ions in the tail, accordingly to Messenger data, is estimated as 10−2-10−1 sm−3 in the morning and evening sectors.6

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Fig. 1. The scheme of the Hermean magnetosphere is shown with approximate distances of most important magnetospheric regions to the center of the planet. We have chosen the GSM system of reference where Z-axis is directed along the magnetic moment of the planet and X-axis is directed from the center of Mercury in Sun direction. The dashed line shows the position of the magnetopause. Line N1 is the neutral line at the subsolar point magnetopause where the reconnection of magnetic ﬁeld lines of solar wind and the intrinsic magnetic ﬁeld of Mercury occurs. At the night side one can see the general structure of the magnetosphere during geomagnetic perturbation when the neutral line N2 appears near Mercury. The possible thickness of current sheet L is shown. In the area of the distant neutral line N3 the process of magnetic reconnection is denoted, which is followed by reversed disconnection of magnetic ﬁeld lines of solar wind from magnetic ﬁeld lines of the Hermean magnetosphere. Downward from the ﬂow (at the right from the line N3 ) the inﬂuence of the magnetic ﬁeld is weakened and there the region of a strong turbulence should exist likely the Earth’s one.

Accordingly the principle of similarity based on the topological resemblance of the Earth’s and Hermean magnetospheres,7−9 the scale of space processes in the last one is about 1:8 from the Earth’s ones, the scales of temporal processes relatively terrestrial ones are about 1:30. Figure 1, accordingly to the similarity principle demonstrates the approximate scales of the planetary magnetosphere and the mutual position of neutral lines in it. The observations of Mariner-10 demonstrated that the current sheet in the magnetotail is very thin with thickness about several hundreds

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of kilometers.9 This signiﬁes that particle motion in magnetotail might be non-adiabatic.10 Plasma particles might be demagnetized in current sheet and go with characteristic “serpentine-like” or “meandering” motion from morning to evening sector and might be accelerated by the cross-tail electric ﬁeld. Due to very small magnetic moment of the planet and the strong ﬂow of falling solar wind, the Hermean magnetosphere is expected to be very dynamical, quickly changing and turbulent.6 Accordingly to Mariner-10 data, the characteristic scales of temporal changes of Hermean magnetic ﬁeld are about several minutes,9 the perturbations being followed by appearance of fast and strong ﬂows of energy particles with energies more than 35 keV.11 These data might testify about the large frequency of substorm perturbations in Mercurian magnetosphere5,7 and reconnection processes in the magnetotail.6,7 The analysis of experimental data of Mariner-10 the electron ﬂows were discovered with energies up to 300 keV7,11 or 600 KeB5 and protons with energies from 500 keV to 1.9 MeV. The estimate of proton energy from another satellite Helios-212 gives diapason 87 −176 keV. Simultaneous observations of energy protons and electrons in the Hermean magnetosphere provoked many questions. The essential critic was directed against observation of energy protons. Thus, Armstrong et al. (1975) supposed that any accelerated protons were present; the simple explanation is the wrong interpretation of measurements of proton detector. Christon et al.13 and later Eraker and Simpson5 concluded that accelerated electrons obviously are the result of explosive energy release during substorms, whereas the data of proton detector are not clear, therefore the question about accelerated protons is open. Later conclusion by Christon8 was even more categorical: no accelerated proton ﬂows were registered in the Hermean magnetosphere. The theoretical analysis by Zelenyi et al.14 of particle acceleration by inductive electric ﬁeld during multiple sporadic reconnections has shown that the upper limit of particle energies can not exceed 50-60 keV. Later this assumption was conﬁrmed by Ip15 in his model where the ion acceleration during large-scale magnetospheric reconﬁguration reached several tens of keV. For comparison, in the Earth’s magnetosphere the ion and electron populations might be accelerated to energies about 1 MeV. Messenger ﬂied across the Hermean plasma sheet where plasma density is about 1 sm−3 and had registered the energy particles with energies no less than several hundreds eV16 , also the electrons with energies from 1 to 10 keV were registered. To date, no observation show evidences of hot ions in magnetosphere of Mercury, although in the region of magnetosheath

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(located between magnetopause and the bow shock) one expects to see hot Na+ ions of planetary origin with energies 10-100 keV, that should be accelerated by turbulent electric ﬁelds.17 The aim of this work is the comparison of two essential mechanisms of particle acceleration in the magnetotail of Mercury, based on the models of particle acceleration as a result of multiple dipolarizations and as a result of particle scattering on plasma turbulence. These results are compared with another estimates of the eﬀectiveness of diﬀerent acceleration mechanisms that might contribute in terrestrial conditions, but (as we propose) can not play essential role in Mercury conditions. Finally in our work we have done a prognosis of possible character of energy spectra of charged particles that are expected to register in future measurements of satellites Messenger and BEPI Colombo.

2. Comparison of Mechanisms of Particle Acceleration in Magnetospheres of the Mercury and the Earth: The Similarity and Diﬀerence. Basis of the problem In the Earth’s magnetosphere the essential role in particle acceleration might be played by following mechanisms,18 collected in the Table 1: 1. The acceleration by induction electric ﬁelds during substorm dipolarizations19 ; 2. The stochastic acceleration of charged particles in turbulent magnetic ﬁelds, i.e. Fermi acceleration20; 3. non-adiabatic acceleration in stationary conﬁgurations with minimum of magnetic ﬁeld in the current sheet of magnetotail by “dawn-dusk” electric ﬁeld; during reconnection processes near X-lines14,21 ; 4. Plasma particles heating on ULF waves22,23 ; 5. Nonadiabatic heating and acceleration on bow shock and magnetopause.2 The ﬁrst acceleration mechanism in terrestrial mechanism has the peculiarity: the interval between storms is from one to several days. During this interval many particles have a time or to escape the Earth’s magnetosphere or to move to another regions of magnetosphere (e.g., to be trapped in the dipole magnetic ﬁeld or to escape from the lobes of magnetosphere through the magnetopause etc), therefore at the next substorm cycle the most part of particle population should be changed.

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Table 1. The essential mechanisms of charged particle acceleration and heating in the Earth’s magnetosphere. The last two mechanisms are not included in the Table because there are not reliable estimates about their importance in magnetotail observation of accelerated particles. N

Mechanism

Authors

Gain of energy

1

Acceleration of O+ by inductive electric ﬁelds

Delcourt et al.19

2

Stochastic acceleration

Zelenyi et al.41

3a

Nonadiabatic acceleration

3b

Inductive acceleration of p+ near X-line

Ashour-Abdalla et al.,30 (and references therein); Delcourt and Martin, Ref. [21] Zelenyi et al.,14

from several tens eV to more than hundreds keV up to 30 times relatively the initial energy About several tens of keV

From 1 keV to 1.6 meV

It is shown that for the Earth’s magnetosphere the mechanism of plasma acceleration due to single substorm dipolarization is very eﬀective ([24], and references therein). Another situation is in Mercury magnetosphere were, as we mentioned above, the global magnetic perturbations might follow with interval several minutes,15,19 i.e. one can expect th during several consequent dipolarizations. We suppose that multiple dipolarizations here might be one of the most eﬀective mechanisms of particle acceleration and we present in this article the results of corresponding calculations. The second mechanism mentioned in the Table 1 plays an important role in the space physics. The pioneerwork in this area belongs to Fermi,25 which proposed that charged particles colliding with chaotically moving obstacles (interstellar and intergalactic clouds) might be accelerated to high energies; this allowed to explain the nature of cosmic rays with ultrarelativistic energies. In th near-Earth region of the magnetosphere where the ordered dipole magnetic ﬁeld dominates, Fermi acceleration can not play substantial role. At the same time in the distant regions of the Earth’s magnetosphere (at distances about or more 100 RE from the planet) the normal component of the magnetic ﬁeld Bz (so called residual dipole ﬁeld) becomes neglectively small, then the role of low-frequency plasma turbulence in particle acceleration might be very eﬀective.20,26,27 Contrary to the Earth, particle acceleration on turbulent electric and magnetic ﬁelds of Mercury might take place in magnetotail quite close to the planet. It is due to the small size of magnetic Hermean dipole and to

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2

2

1

1

Y

Z

Charged Particle Acceleration in the Hermean Magnetosphere

0 -1

0

1

2

3

15

0 -1

4

0

X -1

-1

-2

-2

1

2

3

X4

Fig. 2. Two projections of trajectories of two test ions accelerated by convective electric ﬁeld in the Hermean magnetotail.

powerful dynamical variations of the solar wind ﬂow that inﬂuences the Hermean magnetosphere more strongly than the Earth’s one. One should expect that the problem of a spatial scale necessary for particle to be accelerated during “chaotic walk” is more important for Mercury having a small and dynamic magnetosphere. In this work we try to estimate the maximum gain of energy for plasma particles due to Fermi acceleration on low-frequency plasma turbulence. The third mechanism of nonadiabatic acceleration in a neutral sheet of magnetotail shown in Fig. 2, plays very important role in the Earth’s magnetosphere; there it is quite well investigated.28−30 Charged particles are demagnetized near the neutral sheet and go along meandering orbits10 in the ﬁeld Bz (x) (here we consider the special solar-magnetospheric system of reference where X axis is directed from the Mercury to anti- Sun direction, Y axis is directed from dawn to dusk), during this motion particles are accelerated by large-scale electric ﬁeld Ey across the tail. Moving together with convective ﬂow with some average velocity vd , particles are demagnetized in a neutral plane and return to the planet as it is shown in Fig. 2. Every time when particle cross the neutral sheet, non-adiabatic ions are accelerated by the electric ﬁeld. Energy gain when particle move along magnetotail (X-direction) is estimated as31 : W (x) = 2mi c2 Ey2 /Bz2 (x)

(1)

The comparison of parameters of nonadiabatic proton acceleration in a neutral sheet and corresponding gain of energy for the Earth and Mercury

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are presented in Table 2: Planet Characteristic energies p+ , keV Cross-tail electric ﬁeld Ey , mV/m Strength of the magnetic ﬁeld H, nT Potential jump across the magnetotail ∆φ, keV Characteristic scale across the magnetotail, km Gain of energy ∆W , keV Relative gain of energy ∆W/W0

Earth

Mercury

0.1–1 0.1 20 Up to 120

0.1 5 40 from 20 to 50

25 RE ∼ 160000

4 RM ∼ 10000

few tens 50

Up to 10 10

The electron population regardless small scales of the Hermean magnetosphere should be magnetized therefore the nonadiabatic acceleration is not substantial for it, contrary to protons. The estimate of magnetospheric ion acceleration by inductive electric ﬁelds near X-line were done in works by Eraker and Simpson5 and Baker et al.,32 where the possibility of electron acceleration due to reconnection to 100 eV in the Hermean magnetotail is supposed. The theoretical estimate of proton acceleration is done in paper by Zelenyi et al.14 1D model of multiple sporadic reconnections of magnetic ﬁeld B(t)is used in the form: B(t) = B0x tanh(z/L)ex + Bz (t) sin kx · ez

(2)

where B = Bz (t) = B0z /(1 − t/τr ); B0z = Bz (0). The last term in expression (2) is the regular part of magnetic ﬁeld that describes the appearance of magnetic isles during a characteristic time τr . It was shown that proton energy gain in the Earth’s magnetosphere at the ratio B0z /B0 = 0.1 (B0z and B0 are, correspondingly, the normal and the total components of the magnetic ﬁeld) is approximately ≈1.6 MeV. At the same time for the Hermean magnetosphere the energy gain is several times less and it is about ≈50–60 keV. Therefore this mechanism can not be essential in charged particle acceleration and heating in Mercury. The mechanisms of particle heating at ultra low frequency waves (ULF) and at the bow hock of Mercury (number 4th and 5ve in the Table 2) undoubtedly are interesting for near-Earth investigations. However for the Earth’s magnetosphere the acceleration and the scattering of particles due to these mechanisms play the general role near radiation belts. As we have mentioned radiation belts are absent near Mercury. The ULF waves

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were observed by Messenger at dayside near the planet.6 These waves are observed presumably at the dayside of Mercury, therefore they not substantially inﬂuence particle acceleration in the Hermean magnetotail. Therefore, from our point of view, the essential attention in investigations of general mechanisms of acceleration should be paid to ones that were not well studied for Mercury, i.e. the acceleration due to multiple substorm dipolarizations and acceleration on plasma turbulences. To do this we developed and investigated corresponding theoretical methods. Below we present their description. 3. The Model of Charged Particle Acceleration Due to Multiple Substorm Dipolarizations

Z/RM

The modeling of charge particle acceleration in Mercury magnetosphere is actual due to planned satellite missions MESSENGER and Bepi Colombo. The one of the dipolarization characteristic events during magnetospheric substorm is a magnetotail evolution from very elongated state to dipole-like one (Fig. 3). It was shown in 2D model of the Hermean magnetosphere15 that proton and He+ acceleration for on cycle of magnetic ﬁeld dipolarization reached energy about 20 keV. The study of electron acceleration in the adapted for Mercury model T-89 was done in paper by Delcour et al.19 It was demonstrated that electrons with initial energies up to several hundreds eV can no be accelerated to energy several keV and more. However, no one of abovementioned models canons not explain high-energy (above hundreds of keV) registered by Mariner-10 (see Introduction). In paragraph 3.1. we have considered the model of a Hermean magnetosphere analogical to Lui and Rostoker,33 Luhmann and Friesen,34

X/RM Fig. 3.

Scheme of Hermean magnetotail.

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model, where electrons and ions might be accelerated due to multiple dipolarizations, where the gain of energy is quite large. Paragraph 3.2. concerns the eﬀects of particle acceleration in magnetic clouds.20,35 3.1. The model of electric and magnetic fields during multiple dipolarization Particle tracing is done in the modiﬁed Luhmann and Friesen34 global magnetospheric model of Mercury that is as a superposition of magnetic dipole and Harris current sheet36 : Bx =

z 3µzx , + B tanh 0 r5 L

By =

3µzy , r5

Bz = µ

2z 2 − x2 − y 2 r5

(3)

The changes of magnetic ﬁeld geometry, i.e. dipolarization, is cyclic. The duration of the dipolarization phase (when the dipole magnetic ﬁeld dominates) is chosen as τm1 = 5 s, one of compression phase (when the magnetotail becomes to be very elongated), is taken as τm1 = 25 s. The characteristic thickness of the magnetosphere L(t) and the electric ﬁeld Ey in the expansion phase (marked by index “1”, 0 ≤ t ≤ τm1 ) and in the compression phase (index “2”, τm1 ≤ t ≤ τm2 ) are shown in Fig. 4.

t,sec Fig. 4.

Electric ﬁeld as a function of time.

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Analogically to work19 at τm1 = 5 and the amplitude of the electric ﬁeld about 20 mV/m. We have estimated the maximum of the gained energy in the expansion phase in dimensional form: Wion ≈

e2 B02 L20 mi c2

[ln(2)(ξ − 1)]2

(4)

Here current sheet thickness is L0 ≤ L ≤ ξL0 and parameters L0 , ξ are taken analogically to work.19 The estimate (4) is correct for the ions with mass mi and some initial energy, that have not time to escape from the magnetosphere at the time τm1 . For electrons which go across the magnetosphere faster than τm1 , the estimate (4) can not be applied. We obtain the following estimate of electron energy: Welect ≈

32 ln(2)(ξ − 1)L0 RM eB0 √ c π erf(2)

(5)

The estimate (5) is correct at X > 9RM . The values of particle energies, calculated accordingly formulas (4) and (5) and the maximum energies during all modeling cycles are presented in the Table 3. These results lead to conclusion that the mechanism of multiple dipolarizations is eﬀective for heavy exospheric ions. These charged particles, as electrons, as protons having the solar wind as a source are presumably accelerated during the ﬁrst cycle (it concerns in the ﬁrst place the electrons).

−

The maximum energy at the ﬁrst cycle

The maximum of registered energy in the model

e p He+ O+ Na+ S+ K+

230 keV 135 keV 34 keV 9 keV 6 keV 4 keV 3.5 keV

220KeV-1st cycle 160KeV-2-nd cycle 160KeV-5nd cycle 80KeV-10nd cycle 62KeV-8th cycle 52KeV-6th cycle 45KeV-5th cycle

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3.2. Particle acceleration on “magnetic clouds” in a global model of the Hermean magnetosphere Particle acceleration and transport in the Earth’s magnetotail depends on the properties of a plasma turbulence generated by ensemble of multiple eigenmodes of magnetotail current sheet. This turbulence might be described, for example, as a set of electric and magnetic waves with arbitrary set of phases and amplitudes in plasma. Another way to investigate a turbulent plasma motion in the magnetotail is the study of particle transport and acceleration on magnetic bubbles, oscillating around some average position. In this paragraph we present the results of particle acceleration in the Hermean magnetosphere with help of the Luhmann and Friesen34 model, adapted to Mercury by Delcourt et al.19 and modiﬁed for our studies in this work. Magnetic perturbation in the form of oscillating bubbles was added in a spatial region at the night side in magnetotail. The contribution of this mechanism of plasma acceleration is compared with acceleration processes in the model of arbitrary propagating wave packets, considered in the next paragraph. It is supposed that the magnetotail region, limited in {x,y,z} directions (L0x < x < L0x + ∆Lx , |y| < ∆Ly , |z| < ∆Lz ), is ﬁlled by round 3D magnetic bubbles having for simplicity the single spatial sizes λ = {λx , λy , λz }, where λx = λy = λz . The vector potential of the magnetic perturbation of a single i-th bubble (i = 1, 2 . . . N ) is taken in the form: A=δ

N

exp{−s2 },

s = (r − r0i − a cos ωt)/|λ|

(6)

i=1

where δ is the normalization coeﬃcient of the vector potential, x0i = L0x + ∆Lx αx , y0i = ∆Ly (2αy − 1) and z0i = ∆Lz (2αz − 1) are positions of i-th center of oscillating bubbles, a are amplitudes of spatial bubble oscillations that are chosen equal, α are arbitrary values, homogeneously distributed in the interval [0, 1]. Figure 5 demonstrates 2D distribution of magnetic bubbles in the magnetotail of Mercury, initiated in the box xi ∈ [1, 20], yi ∈ [−4, 4], zi ∈ [−0.5, 0.5]. The size of bubbles was taken quite realistic for magnetotail conditions, i.e. about proton gyroradius. The typical trajectory of proton in the planetary magnetotail where the bubble region is extended at [−0.35, +0.35] in Z-direction is shown in Fig. 6 in three projections. One can clearly see that in this region its motion is chaotic due to scattering

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4 3 2

Y, Rm

1 0 -1 -2 -3 2

3

4

5

6

7

8

9

10

X, Rm Fig. 5.

The distribution of magnetic perturbations in the magnetotail of Mercury.

Z, Rm

0.8 0.4 0 -0.4

6

8

Y,Rm

12

14

16

X, Rm

-0.8 0 -0.5

10

6

8

-1

10

12

14

16

-0.5

0

X, Rm

-1.5 -2 -2.5 0.8

Z, Rm

0.4 0 -0.4 -2.5

-2

-1.5

-1

Y, Rm -0.8 Fig. 6. Three projections of characteristic p+ trajectory in the presence of magnetic and electric bubbles in magnetotail neutral sheet.

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processes. After 80 s of travel proton leaves the region of chaotic scattering, correspondingly the gain of energy is ended. In a Table 4 we show the results of acceleration of diﬀerent ion populations that were more frequently registered in the exosphere and magnetosphere of Mercury: H+ , He+ , O+ , Na+ , S+ and K+ . Initial energies of particles were 500 eV (in some calculations the initial energy 10 eV was tested, but it does not change the ﬁnal gain of energy on moving bubbles). In each calculation particles were initially distributed homogeneously over the Hermean magnetotail. The results in Table 1 demonstrate the averaged and the maximum energies over particle populations in magnetospheric conﬁguration without magnetic bubbles and in the presence of them, the time of averaged half-life of particles in the system and the maximum of ion life time in the magnetosphere. One can see from the Table that without bubbles particle acceleration is several times smaller than in the presence of bubbles. The high limit of energy is determined by the energy when ion gyroradius become large in comparison with characteristic sizes of magnetosphere and leave it. Averaged ﬁnal energies of particles accelerated in magnetosphere without bubbles are about several keV (due to nonadiabatic acceleration in a neutral sheet), in the presence of bubbles they reach about several tens of keV due to scattering on bubbles, that also substantially increase the life time of ions Tmax in the system.

Efin &Emax , keV

Ion

no bubbles H+ He+ O+ Na+ S+ K+

Efin 6,5 6,9 6,1 5,63 5,5 5,7

Emax 16,8 14,5 14,9 13,6 9,7 13,8

Thalf -life , s

bubbles Efin 6,4 6,6 5,3 6 5,7 6,2

Emax 17 14,3 13 15,1 10,3 10,2

Tmax , s

no bub.

bub.

no bub.

bub.

28 27,3 34,5 41 44 49,5

32,5 23 32,9 41,1 46 49

205 274 364 500 592 583

217 358 506 748 513 428

3.3. The model of charged particles acceleration and thermalization in a turbulent plasma of a magnetotail Along with a global model of the Hermean magnetosphere we consider in this work the model of ion acceleration and dispersion in turbulent electromagnetic ﬁelds in plasma sheet that might appear as a result of

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E, eV

16,000 12,000 8,000 4,000 0 0

20

40

60

80

100

time,s Fig. 7.

The gain of energy by proton, presented in previous Fig. 6.

the development of plasma sheet instabilities. The current sheet of the magnetotail has diﬀerent modes of unstable perturbations, that might develop turbulent electric and magnetic ﬁelds. Particularly, the drift modes37,38 are the source of plasma oscillations that propagate in a form of waves with the limited phase velocities. The diﬀerent modiﬁcations of a tearing-mode39,40 support the local regions of the zero magnetic ﬁeld Bz . Their mutual interaction and saturation lead to the development of a turbulent electromagnetic ﬁeld.20,27 We investigated the dispersion and acceleration of ions in 1D magnetotail conﬁguration with the turbulent ﬁeld (δB, δE). This model is the natural generalization of the equatorial approximation, in a frame of which the mechanisms of the transport and acceleration were investigated in Ref. [41]. Let us consider the magnetic component of the turbulent ﬁeld δB in the form of the wave ensemble: δBx = δBy =

k

k

δB(k) kk⊥ gk (r) δB(k)

ky kx k⊥ k gk (r)

+

kz k⊥ hk (r)

(7)

ky z kx g (r) − h (r) δBz = k δB(k) −k k k⊥ k k⊥ k Here gk = cos(kr+φ2k −tωk ), hk = sin(kr+φ1k −tωk ), k⊥ = (kz2 +ky2 )1/2 . The ﬁeld δB has the form that the condition δB = 0 is satisﬁed. The initial phases φ1k and φ2k are the random values with a homogeneous distribution on the interval [0, 2π]. The frequency ωk for each harmonics is chosen in such a way that the phase velocity ωk /k = vφ of all waves are the same. The wave amplitude δB(k) is chosen accordingly to Ref. [27]. Using the

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Fig. 8. Energy spectra of diﬀerent kinds of ions in the system with two diﬀerent levels of turbulence.

system (7) and the condition of the absence of free charges one can ﬁnd the components of the electric ﬁelds from Maxwell equations. Now let us determine the relations between the parameters of the system. The constant magnetic ﬁeld is taken from the modiﬁed Harris model36 B = B0 tanh(z/L)ex + Bz ez . The value Bz /B0 = 0.1 is taken for calculation. We use dimensionless magnitude of turbulent magnetic ﬁeld δ = δB2 1/2 /B0 . The ions are traced from the upper and down limits of the current sheet. The initial distribution function on energies is taken as Maxwellian distribution with temperature mv 20 /2. To calculate the averaged gain of energy of ions we use the following scheme. The time of modeling is limited by the time when all particles escape from the current sheet. After collection of particle parameters at the boundaries of the modeling region one can obtain the corresponding energy spectra of particles. The examples of these spectra at several values of parameter δ and several kinds of ions are presented in Fig. 8. One can see that in all cases of interaction of protons with a turbulent electromagnetic ﬁeld the “tail” of energetic distribution appears. Generally the new distribution of protons at high energies has a power dependence f ∼ ε−κ (the corresponding values of κ are also shown in ﬁgure). Therefore the group of protons with energies ε ∼ (102 − 103 )ε0 appears in the system. The analogous results are obtained for He+ ions. The oxygen ions form a power spectra at quite strong level of turbulence.

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Fig. 9.

25

The values of an average and maximum energy for diﬀerent kinds of ions.

More heavy ions also increase an average energy ε, but the power spectra is not formed. The eﬀect of the growth of average ion energy is presented in Fig. 9. In this ﬁgure one can see also the values of maximum ion energy that are generalized in the Table 5. Taking into account the amplitude of the magnetic ﬁeld of current sheet B0 ∼ 20 nT and its thickness in proton gyroradius, one can receive the value ε0 ∼ 1 − 5 keV. Generally one can say that the mechanism of ion thermalization by the turbulent electromagnetic ﬁeld is more eﬀective for p+ and He+ ions than the mechanism of multiple dipolarization (their maximum energies are correspondingly ∼1500 keV and ∼420 keV). For heavier ions as O+ the mechanism of a turbulent acceleration is not so eﬀective as ones presented in the Table 5. The mechanism of a “turbulent” acceleration has limits due to limited space parameters of the system. Thus the cross-tail distance of current sheet of Mercury is about ∼104 km. At the same time this mechanism is the most eﬀective if the scale of particle gyroradius in the center (where |B0 | ∼ 10 − 5 nT) were less or about the Larmor gyroradius in the center of current sheet where protons with energies 102 keV will have Larmor radius about ∼104 km. The despite the potential possibility to be accelerated to 1 MεB, plasma protons might be accelerated only to 200 keV in the Hermean magnetosphere. For another kind of more heavier particles the gain of energy will be lesser (the Larmor radius is proportional the root square from the mass). For example, ions K+ with energies about 30 keV escape

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from the magnetosphere because their Larmor radius is larger than the scale of current sheet.

The maximum of obtained energy at δ = 0.7 p He+ O+ Na+ S+ K+

1500 KeV 140 KeV 70 KeV 30 KeV 20 KeV 16 KeV

4. Conclusions Small scales of plasma processes in the Hermean magnetosphere in comparison with the Earth’s one are the reason of some diﬀerence between the mechanisms of particle accelerations in their magnetotails. The role of nonadiabatic eﬀects of particle motion near Mercury is expected to be more pronounced in comparison with the Earth. Our numerical calculations demonstrated that the contribution of nonadiabatic acceleration across current sheet and particle heating due to scattering on moving magnetic bubbles might give similar contributions (energy gain about several tens keV) to the energy distributions of plasma in the magnetotail of Mercury. The mechanism of multiple substorm dipolarizations in Mercury magnetosphere might be more eﬀective than in the Earth’s one due to more high substorm activity in the Hermean magnetosphere. Particle acceleration to high energies is eﬀective during the ﬁrst 1-2 substorm cycles, after this the particles go out from the magnetosphere. Heavy particles as O+ , Na+ , S+ , K+ might be accelerated during several cycles of dipolarization, acquiring the ﬁnal energies about several tens of keV. Generally this mechanism plasma acceleration might favorize the observation of ions with limiting energies ∼100 keV and hot electrons with energies ∼200 keV at distances about ∼RM in the magnetotail. Mechanisms of particle scattering on electric and magnetic waves can play an important role in both ions and electrons heating. We estimated electron energies in Mercury magnetosphere up to 300 keV. Because magnetic ﬁeld of Mercury is weaker than the Earth’s one should expect that for Mercury the role of ﬂuctuations will be large contrary to the Earth where their role is signiﬁcant in the region down stream from the

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distant X-line. Our estimates demonstrate that the turbulence in current sheet can increase the averaged energy of protons approximately in 102 −104 times. Generally, the combination of both these mechanisms of particle acceleration that might be realized under diﬀerent conditions in the Hermean magnetosphere might support particle heating with an upper limit about several hundreds keV, that is smaller than in the Earth due to small size of the Hermean magnetosphere. The particles with higher energies might not be trapped inside the last one; the most part of them escape to the solar wind. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.

N. F. Ness, K. W. Behannon and R. P. Lepping, Nature 255 (1975) 204. J. A. Slavin, M. H. Acuna, B. J. Anderson et al., Science 321 (2008) 85. D. C. Delcourt, Y. Saito, J. M. Illiano et al., Adv. Space Res. 43 (2009) 869. T. Armstrong, S. Krimigis and L. Lanzerotti, J. Geophys. Res. 80 (1975) 4015. J. H. Eraker and J. A. Simpson, J.Geophys. Res. 91 (1986) 9973. J. A. Slavin, M. H. Acuna, B.J. Anderson et al., Science 324 (2009) 606. G. L. Siscoe, N. F. Ness and C. M. Yeates, J. Geophys. Res. 80 (1975) 4359. S. P. Christon, Icarus 71 (1987) 448. W.-H. Ip, Icarus 71 (1987) 441. J. B¨ uchner and L. M. Zelenyi, J. Geophys. Res. 94 (1989) 11821. J. A. Simpson, J. H. Eraker, J.E. Lamport et al., Science 185 (1974) 160. E. Kirsh and A. K. Richter Ann. Geophys. 3 (1985) 13. S. P. Christon, S. F. Daly, J. Eraker et al., J. Geophys. Res. 84 (1979) 4277. L. M. Zelenyi, J. Lominadze and A. Taktakishvili, J. Geophys. Res. 95 (1990) 3883. W.-H. Ip, Adv. Space Res. 19 (1997) 1615. T. H. Zurbuchen, J. M. Raines, G. Gloeckler et al., 40th Lunar and Planetary Science Conference (2009), id. 2141. M. Sarantos, J. A. Slavin, M. Benna et al., Geophys. Res. Lett. 36 (2009) L04106. L. M. Zelenyi, M. Oka, H. V. Malova et al., Sp. Sci. Rev. 132 (2007) 593. D. C. Delcourt, K. Seki, N. Terada et al. Ann. Geophys. 23 (2005) 3389. L. M. Zelenyi and A. V. Milovanov, Uspehi. 174 (2004) 809. D. C. Delcourt and R. F. Martin J. Geophys. Res. 99 (1994) 23583. K.-H. Glassmeier, N. Mager and D. Klimushkin, Geophys. Res. Lett. 30 (2003) 1928. W. Baumjohann, A. Matsuoka, K.-H. Glassmeier et al., Adv. Space Res. 38 (2006) 604. D. C. Delcourt, J. Atmosp. Sol.-Terr. Phys. 64 (2002) 551. E. Fermi, Phys. Rev. 75 (1949) 1169.

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26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41.

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M. Hoshino, A. Nishida et al., Geophys. Res. Lett. 21 (1994) 2935. P. Veltri, G. Zimbardo et al., J. Geophys. Res. 103 (1998) 14897. L. R. Lyons and T. W. Speiser, J. Geophys. Res. 87 (1982) 2276. M. Ashour-Abdalla, J. P. Berchem, J. Buechner et al., Geophys. Res. Lett. 17 (1990) 2317. M. Ashour-Abdalla, J. P. Berchem, J. Buechner et al., J. Geophys. Res. 98 (1993) 5651. T. W. Speiser, J. Geophys. Res. 70 (1965) 1717. D. N. Baker, J. Borovsky, J. Burns et al. J. Geophys. Res. 92 (1987) 4707. W. W. Liu and G. Rostoker, J. Geophys. Res. 100 (1995) 21897. J. G. Luhmann and L. M. Friesen, J. Geophys. Res. 84 (1979) 4405. S. Perri, F. Lepreti, V. Carbone et al., Europhys. Lett. 78 (2007) 40003. E. G. Harris, Nuovo Chimento 23 (1962) 115. W. Daughton, Phys. Plasmas 6 (1999) 1329. L. M. Zelenyi, A. V. Artemyev, A. A. Petrukovich et al., Ann. Geophys. 27 (2009) 861. B. Coppi, G. Laval, R. Pellat, Phys. Rev. Lett. 16 (1966) 1207. L. M. Zelenyi, A. V. Artemyev, H. V. Malova et al., J. Atmosp. Sol.-Terr. Phys. 70 (2008) 325. L. M. Zelenyi, A. V. Artemyev, ´I. V. Malova et al., Phys. Lett. A 372 (2008) 6284.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

A MODEL STUDY ON OBSERVATION MODES OF MIA/MMO BASED ON THE EM DESIGN W. MIYAKE Department of Aeronautics and Astronautics, Tokai University, 1117 Kitakaname, Hiratsuka, Kanagawa 259-1292, Japan [email protected] Y. SAITO Institute of Space and Astronautical Science, 3-1-1, Yoshinodai, Sagamihara, Kanagawa 229-8510, Japan

The Mercury Ion Analyzer (MIA) is one of the plasma instruments on board the Mercury Magnetopsheric Orbiter (MMO) and measures 3-dimensional distribution function of ions around Mercury with energy range of 5 eV up to 30 keV. MIA is designed to make observations both in the magnetosphere and in the solar wind. We simulate here the telemetry output of MIA based on the design of the Engineering Model (EM), from which we derive the original plasma parameters, such as bulk velocity, density, and temperature of protons, expected around Mercury. We conclude that under the current design of the sensor and observation modes MIA works well with suﬃcient accuracy to understand the various plasma environments around Mercury, ranging from the hot and cold plasma sheet in the magnetosphere to the solar wind between 0.3 and 0.47 from the sun.

1. Introduction The Mercury Magnetopsheric Orbiter (MMO)1,2 is one of the spacecraft of the BepiColombo mission; the mission is scheduled for launch in 2014 and plans to revisit Mercury with modern instrumentation. MMO is to elucidate the detailed plasma structure and dynamics around Mercury, one of the least-explored planets in our solar system. The Mercury Plasma Particle Experiment (MPPE)3 on board MMO is a comprehensive instrument package for plasma, high-energy particle, and energetic neutral particle atom measurements. The Mercury Ion Analyzer (MIA)4 is one of the plasma instruments of MPPE, and is a top-hat type electrostatic analyzer to measure 3-dimensional distribution function of ions around Mercury with 29

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energy range of 5 eV up to 30 keV. The scientiﬁc objectives of low-energy ion measurement on Mercury orbit are to understand the (1) structure of the Mercury magnetosphere, (2) plasma dynamics of the Mercury magnetosphere, (3) Mercury — solar wind interaction, (4) atmospheric abundances, structure, and generation/loss processes, and (5) solar wind between 0.3 and 0.47 AU. In order to realize the required observations, MIA should measure the three-dimensional distribution of solar wind ions around Mercury and the Mercury magnetospheric ions simultaneously. By combining both the mechanical and electrical sensitivity control, MIA has a wide dynamic range of count rate for proton ﬂux expected around Mercury,5 ranging from 106 to 1012 cm−2 sec−1 str−1 keV−1 , in the solar wind between 0.3 and 0.47 AU from the sun, and in both the hot and cold plasma sheet of Mercury’s magnetosphere. We have just completed the Engineering Model (EM) fabrication, which is now under various ground tests towards the launch of MMO in 2014. One of the crucial issues to be examined before the completion of the Flight Model design is the observation mode of MIA for measuring a wide range of various plasma parameters. By combining the sensor characteristics and observation modes, we examine the energy, angle, and time resolutions of ion measurement to understand the plasma environment. The purpose of the present paper is to report our current plan of observation modes of MIA and to demonstrate its capability of the ion measurement. We simulate here telemetry output of the MIA sensor under an observation mode of MIA and an assumed plasma environment, ranging from the solar wind to the magnetosphere. From the simulated telemetry data, we derive original plasma parameters. We discuss the capability of MIA observation modes by examining the accuracy and resolution of the derived plasma parameters.

2. Measurement Principle and Sensor Design Before we present our model calculations, we describe the basic sensor design of MIA here. A schematic view of the sensor is shown in the left side of Fig. 1. MIA employs a top-hat type of electrostatic analyzer with a ﬁeld of view of 2π perpendicular to its symmetry axis. With the spin motion of the spacecraft, a three-dimensional ion distribution function is obtained. The ions passing through the electrostatic analyzer plates enter the Z-stack MCP and are ampliﬁed to detectable charge pulses. The charge pulses are received by a 62-channel discrete anode. The most suitable choice for the fast position-sensitive anode is a multi-discrete anode. The

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Fig. 1. Schematic drawings of the MIA sensor with a few trajectories of incident particles (left) and explanation of spin sector and anode channel (right). The spin axis is perpendicular to the ecliptic plane. Combining the spin motion of the sensor (i.e. the anode channel plane), 3-dimensional distribution is obtained. There are 64 spin sectors and 64 anode channels. Therefore, the resolution for both is 5.625◦ . Due to the limit of telemetry, counts of two or four sectors/channels are usually summed up.

position where the charge pulses are detected corresponds to the incident azimuthal direction of the ions. The signals from the multi-discrete anode are processed by a newly developed Application Speciﬁc Integrated Circuit (ASIC)6 installed on the anode. The estimated dynamic range of the low-energy ion ﬂux around Mercury including both intense solar wind ions and weak magnetospheric ions is as wide as 106 .5 In order to measure both solar wind ions without saturation and Mercury magnetospheric ions with enough counting statistics, MIA has a function to change geometrical factor electrically. Sensitivity of the analyzer is controlled by changing the high voltage applied to the “top-hat” part. The center of the “top-hat” part is insulated from the surrounding structures. By applying high voltage between 0 V and 5 kV, geometrical factor can be reduced down to 1/50. In addition to the electrical geometrical factor control, attenuation grid is placed at limited sector (±45◦ ) of the entrance part of the analyzer in order to further reduce geometrical factor for solar wind ion measurement. The total reduction reaches the order of 10−3. Some speciﬁcations of the MIA sensor are summarized in Table 1. Details of the sensor design are described elsewhere.4 The spacecraft spin axis is perpendicular to the ecliptic plane (see the right side of Fig. 1). The angular width of each anode is 5.625◦; this

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32 Table 1.

Some speciﬁcations of the MIA sensor.

Energy range

5 eV/q–30 keV/q

Energy resolution

12.0% (sensitivity control: OFF) 2.7% (sensitivity control: ON)

Analyzer constant

5.93 (sensitivity control: OFF) 6.58 (sensitivity control: ON)

Field of view

4.4 deg × 360 deg (sensitivity control: OFF) 1.0 deg × 360 deg (sensitivity control: ON)

Geometric factor

5.0 × 10−4 cm2 str keV/keV (sensitivity control: OFF) 1.0 × 10−7 cm2 str keV/keV (sensitivity control: ON)

Mass Dimension

1.55 kg 146 × 289 × 146 mm

determines the highest angular resolution of incident ions measured from the ecliptic plane. The count for the magnetospheric ion measurement is summed up from two or four anodes and the nominal angular resolution is 11.25◦ or 22.5◦. We usually adopt the full 5.625◦ resolution to measure the solar wind ions when high telemetry output is available, whereas lower angular resolution, like the magnetospheric ion measurement, can be selected under lower telemetry condition. 3. Model Calculation of MIA Observation Modes 3.1. Nominal operation modes After Mercury orbit insertion, MIA starts observation during all the orbital phases except the period of orbital/attitude maneuvering. MIA has three operation modes: (1) magnetospheric high angular resolution mode, (2) magnetospheric low angular resolution mode, and (3) solar sind mode. In the magnetospheric high angular resolution mode, the entire (4π str) ﬁeld of view is divided into 32 anode channels and 32 spin sectors, which means angular resolution of 11.25◦ × 11.25◦. The raw data rate is 139,264 bps with 16 bits/data. In the magnetopsheric low angular resolution mode, the number of both the anode channels and spin sectors is reduced to half. Then the angular resolution is 22.5◦ × 22.5◦, and the raw data rate is 36,864 bps. MIA has 6 patterns of high voltage sweep waveform applied to the inner curved plate of the analyzer, which determines the energy of ion measurement. Table 2 shows the list of high voltage sweep waveforms. The spin period of MMO is 4 sec and the time interval of each energy step is about 2 msec. The waveform can be switched every 8 sectors, assuming

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Measurement

33

High voltage sweep waveform of MIA. Sensitivity control

Spin/cycle

Energy range 100 eV/q–10 keV/q 100 eV/q–10 keV/q 5 eV/q–300 eV/q (32 steps) 3 keV/q–30 keV/q (32steps) 5 eV/q–30 keV/q 5 eV/q–5 keV/q 5 keV/q–30 keV/q

0 1 2

Solar wind Solar wind Solar wind

OFF ON OFF

4 (128 steps) 4 (128 steps) 2 (64 steps)

3 4 5

Magnetosphere Magnetosphere Magnetosphere

OFF OFF OFF

1 (32 steps) 1 (32 steps) 1 (32 steps)

64 sectors/spin. MIA has 3 types of pattern for measurement in the solar wind and 3 types in the magnetosphere. In the magnetosphere, the entire energy range is basically covered in a spin period. Type 3 is the nominal operation mode, whereas Type 4 and Type 5 should be used when we need high energy resolution. The solar wind mode is rather complex. Since the large ﬂux of solar wind ions is steeply collimated along the sun — spacecraft line, the observation mode should be changed cyclically during a spin. There are 4 spin phases, in which 3 types of observation mode are employed as shown in Fig. 2. The solar wind ions are actually measured in one of the 4 spin phases, in which the attenuation grid to reduce the geometrical factor is headed toward the sun, and the Type 1 sweep pattern is used activating the electrical sensitivity control. The geometrical factor is reduced to 1.0 × 10−7 cm2 str keV/keV. The full angular resolution of 5.625◦ × 5.625◦ is usually used in 90◦ of spin phase and ±45◦ of anode channel from the ecliptic plane where the mechanical attenuation grid is placed. The sharp collimation of the ion ﬂux also takes place in energy. Therefore, large number of energy steps is required for obtaining detailed velocity distribution. We divide the entire energy range for the solar wind protons (i.e. 100 eV up to 10 keV) into 128 steps, which it takes 4 spin periods (16 sec) to cover. In the other spin phases, MIA turns oﬀ the electrical sensitivity control, increases its geometrical factor up to 5.0 × 10−4 cm2 str keV/keV, and measures minor ion components in the solar wind, such as pick-up ions and accelerated ions around both the bow and interplanetary shocks, which have generally a large gyration radius and, therefore, do not come from the sun’s direction. The angular resolution of the anode channel is also reduced to 22.5◦ during the measurement of minor ion components. Large ﬂux of

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Fig. 2. Nominal energy sweep pattern for the solar wind ion measurement. The three types of measurement in Table 2 are used cyclically during a spin period as indicated in the ﬁgure. The entire energy range of 128 steps is measured during 4 spin periods (16 sec) for Type 0 and Type 1. The solar wind ions are actually measured by Type 1. The solar wind protons are excluded in Type II (anti-SW). Minor ion components like pick-up ions are the target of Type 0 and 2 measurement.

the solar wind ions comes into the sensor when the entrance of the opposite side of the attenuation grid is headed toward the sun. MIA uses Type 2 of high voltage sweep during this spin phase in order to avoid the energy range of the solar wind protons and to measure minor ion components in the solar wind. The average raw data rate results in 98,304 bps in the solar wind. 3.2. Procedure of model calculation First, we assume an isotropic Mawellian velocity distribution of protons both in the magnetosphere and in the solar wind. Then, we set the plasma parameters, such as bulk velocity, ﬂow directions, number density, and temperature. The count of each sampling is calculated based on the spin phase, anode channel, energy step, and sensitivity control ON/OFF at the sampling. The count data are accumulated during 1 spin period for

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magnetospheric ions and during 4 spin periods for solar wind ions. The count distribution in 3 dimensions, then, is converted into phase space density distribution and macroscopic parameters are derived by means of moment calculation. We obtain number density from the 0th order moment, bulk velocity in 3 dimensions from the 1st order moment, and temperature from the 2nd order moment, respectively. Finally we compare the derived parameters with the original ones and evaluate the accuracy of measurement. 3.3. Magnetospheric ion measurement Mercury is one of the least explored planets in our solar system.7 Our observational bases of study are limited to ground-based telescopes, the Marineer-10 ﬂy-bys almost 30 years ago, and recent MESSENGER ﬂybys.8 The magnetopsheric plasma is so unknown that we adopt the plasma parameters derived from a scaling law5 in the hot and cold plasma sheet cases. The typical proton density and temperature are expected to be 0.5 cm−3 and 8.0 × 107 K in the hot plasma sheet, whereas they are 13.0 cm−3 and 0.5 × 107 K in the cold plasma sheet. We further add bulk motion of plasma ranging from 0 to 300 km/s. We assume no heavy ions included. An example of the contours of proton ﬂux and data sampling in the ecliptic plane are shown in Fig. 3. The contours are drawn for protons in the hot plasma sheet with number density of 0.5 cm−3 , temperature of 8.0× 107 K, and bulk velocity of 100 km/s. The distance from the origin gives the energy of particles. The colored area indicates the analyzer measurement4 and the red point is the center of the analyzer transmission characteristics. Counts of the adjacent two/four measurement points of the same energy are summed up for the magnetospheric high/low angular resolution mode. When we adopt the low resolution mode and integrate the count data over 4 spin periods, the derived number density, temperature and bulk velocity are 0.47 cm−3 , 7.9 × 107 K, and 96.9 km/s, respectively, which are in good agreement with the original ones. They become 0.41 cm−3 , 8.3 × 107 K, and 119.4 km/s for the high resolution mode, which are less accurate than for the low resolution mode. Since the integration range over angle is four times larger in the low resolution mode, the counts are larger for the wide distribution of particle ﬂux just like in the hot plasma sheet. This leads to higher accuracy with statistically signiﬁcant count level. When we integrate the count data of the high resolution mode over 16 spin periods

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Fig. 3. An example of data sampling for magnetospheric ion measurements (Type 3 in Table 2). The contours show proton ﬂux distributions in the ecliptic plane. The colored area indicates the analyzer transmission characteristics (i.e. measurement range) normalized by its peak values. The red point is the peak and center of the analyzer transmission characteristics.

(64 sec), then the derived number density, temperature and bulk velocity are 0.47 cm−3 , 7.8 × 107 K, and 98.3 km/s. The accuracy is much improved with increase of statistically signiﬁcant count level. Next we consider the typical cold plasma sheet in which proton number density and temperature are 13.0 cm−3 and 0.5 × 107 K, with bulk velocity of 50 km/s. When we adopt the low resolution mode and integrate the count data over 4 spin periods, the derived number density, temperature and bulk velocity are 13.0 cm−3 , 0.51 × 107 K, and 50.0 km/s, respectively. They are 12.6 cm−3 , 0.51 × 107 K, and 52.0 km/s for the high resolution mode. The accuracy becomes lower, but not as much as in the hot plasma sheet case. Since the number density, and then particle ﬂux, are higher in the cold plasma sheet, larger count levels are obtained in a 11.25◦ × 11.25◦ angular bin of the high resolution mode. When we integrate count data over 16 spin periods, the accuracy is improved again and the derived parameters are 13.0 cm−3 , 0.50×107 K, and 50.7 km/s, respectively. Table 3 summarizes the comparison of original and reproduced plasma parameters for various observation modes.

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Table 3. Comparison of original and reproduced plasma parameters for various observation modes in the magnetosphere.

Np (/cc) Tp (×107 K) V (km/s)

Original in Hot PS/Cold PS

High ang. res. over 4 spins

Low ang. res. over 4 spins

High ang. res. over 16 spins

0.5/13.0 8.0/0.5 100.0/50.0

0.41/12.6 8.3/0.51 119.4/52.0

0.47/13.0 7.9/0.51 96.9/50.0

0.47/13.0 7.8/0.50 98.3/50.7

3.4. Solar wind ion measurement The solar wind ions are highly collimated in contrast with the magnetospheric ions. Therefore, higher resolution in both angle and energy is, in general, required. Figure 4 shows an example of data sampling for the solar wind ions with Type 1 sweep pattern in Table 2. We assume a bi-Maxwellian velocity distribution of protons and α particles. The proton number density, temperature, and bulk velocity are 300 cm−3 , 0.5 × 104 K, and 350 km/s, respectively, which are typical values in the slow solar wind between 0.3 and 0.5 AU from the sun.9 The density ratio of α particles to protons is 1% and the temperature ratio is 4, as is typical in the solar wind.

Fig. 4. An example of data sampling, for solar wind ion measurements (Type 1 in Table 2), where the electrostatic sensitivity control is activated. The format of the ﬁgure is the same as used in Fig. 3. We assume a bi-Maxwellian distribution of protons and α particles.

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The entire energy range (100 eV–10 keV) is divided into 128 steps, so that it takes 4 spin periods to cover the entire energy range and the measurement points are more concentrated than those of the magnetospheric observation in Fig. 3. In order to see accuracy dependence on the observation mode quickly, we generate a time series of various solar wind conditions ranging from the slow to the fast streams and compare the derived parameters with the original ones. Figure 5 shows an example of time series of given plasma parameters (solid black lines) and derived ones (broken lines) from the virtual MIA observation in the solar wind. From the top, the panels reveal proton parameters: bulk velocity, ﬂow direction in the ecliptic plane (phi), ﬂow direction in the meridian plane (theta), number density, and temperature, respectively. The red, green, and blue lines indicate the cases of high (5.625◦ × 5.625◦), medium (11.25◦ × 11.25◦ ), and low (22.5◦ × 22.5◦ ) angular resolutions, respectively. The proton parameters are derived every 4 spin periods, so that the time resolution is 16 seconds. The bulk velocity is derived most accurately with any angular resolution mode, since the energy resolution is unchanged among all the angular resolution modes and 128 steps for the range of 100 eV–10 keV provide suﬃcient resolution as shown in Fig. 4. The ﬂow directions are fairly well reproduced with the high and medium angular resolutions, whereas the deviation from the original becomes large with the low angular resolution mode. The 22.5◦ × 22.5◦ resolution is apparently not enough to derive the ﬂow direction correctly because of the high collimation of the solar wind protons (see the contour lines in Fig. 4). The number density is well derived, but some deviation from the original values is sometimes apparent with the high angular resolution mode. The deviation becomes large when the density is low. The count is too low under the combination of the narrow (5.625◦ × 5.625◦) integration range and low density, and is, therefore, not statistically enough for accurate measurement. When we integrate the counts over a long time period, accuracy becomes suﬃcient, even in the low-density solar wind, with the high angular resolution mode. For example, 4 times longer integration (i.e. 64 seconds) gives larger counts equivalent to the medium angular resolution mode. The temperature shows largest deviation from the original values. The deviation becomes larger for lower angular resolution. The reason is the same as for the ﬂow direction. The high angular resolution is required to derive correctly temperature of highly collimated protons in the solar wind

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Fig. 5. Time series of given plasma parameters (solid black line) and derived ones (broken lines) from the virtual MIA observation in the solar wind.

by means of the 3-dimensional moment calculation. Even with the high angular resolution mode, some deviation is apparent when the density is low. This is due to too low count, as is the same as for the case of number density. When we take longer integration time, the accuracy is increased to a suﬃcient level.

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4. Summary and Discussion We simulated here telemetry output of the MIA sensor under a given plasma environment, ranging from the solar wind to the magnetosphere expected around Mercury, and under various observation modes of MIA. We found that the observation modes currently planned generally work well and original plasma parameters are fairly derived from the data. However, in some cases, long integration time is required to derive accurately the parameters. In the magnetospheric ion observation, the low angular resolution (22.5◦ × 22.5◦ ) provides suﬃcient measurement for the plasma sheet protons. When we take the high angular resolution (11.25◦ × 11.25◦), hot and tenuous protons in the hot plasma sheet requires longer integration time to be measured accurately. We should set our priority of time and angular resolutions depending on the scientiﬁc objectives. The low angular resolution seems enough for the plasma sheet observations, but there are lots of possible events, like ﬁeld-aligned ion beams, in which the ion distribution is narrowly collimated and the high angular resolution may be needed. Similar priority selections take place in the solar wind observation. The high angular resolution (5.625◦ × 5.625◦) with a long integration time may seem a best choice for solar wind proton measurement based on the results in the former section. However, higher time resolution is more essential for the boundary regions between the solar wind and the magnetosphere. Since the Mercury’s magnetosphere is so small that the boundary region is thin and high time resolution, even with lower angular resolution, is required to resolve the structure. Therefore, it is still worth having observation mode of low angular resolution. We conclude that MIA works well under the current design of observation modes and will achieve its mission for various plasma environments around Mercury. By selecting priority between time and angular resolutions, MIA has a potential to investigate speciﬁc plasma conditions at Mercury, which cannot be anticipated from the current state of knowledge.

Acknowledgment We would like to express our sincere thanks to all the members of MIA team for their extensive support.

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References 1. H. Yamakawa, H. Ogawa, Y. Kasaba, H. Hayakawa and T. Mukai, Adv. Space Res. 33 (2004) 2133. 2. H. Hayakawa, Y. Kasaba, H. Yamakawa, H. Ogawa and T. Mukai, Adv. Space Res. 33 (2004) 2142. 3. Y. Saito et al., Planet. Space Sci. (2009) (in press). 4. W. Miyake et al., Adv. Space Res. 43 (2009) 1986. 5. T. Mukai, K. Ogasawara and Y. Saito, Adv. Space Res. 33 (2004) 2166. 6. M. Saito, Y. Saito, T. Mukai and K. Asamura, AIP Conference Proceedings 1144 (2009) 48. 7. P. E. Clark, Dynamic Planet (Springer) (2007) 139. 8. J. A. Slavin et al., Geophys. Res. Lett. 36 (2009), doi:10.1029/2008GL036158. 9. L. F. Burlaga, Planet. Space Sci. 49 (2001) 1691.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

DISTRIBUTIONS OF K AND TH ON THE MOON: THE INITIAL RESULTS FROM OBSERVATIONS BY SELENE GRS YUZURU KAROUJI∗ , NOBUYUKI HASEBE, OSAMU OKUDAIRA, NAOYUKI YAMASHITA, SHINGO KOBAYASHI, MAKOTO HAREYAMA, TAKASHI MIYACHI, SATOSHI, KODAIRA, KAZUYA IWABUCHI, KANAKO HAYATSU, SHINPEI NEMOTO, YUKO TAKEDA, KOICHI TSUKADA and HIROSHI NAGAOKA Research Institute for Science and Engineering, Waseda University, 3-4-1, Okubo, Shinjuku, Tokyo 169-8555, Japan ∗ [email protected] MASANORI KOBAYASI Nippon Medical School, Kawasaki 211-0063, Japan EIDO SHIBAMURA College of Health Science, Saitama Prefectural University, Saitama 343-8540, Japan MITSURU EBIHARA and TAKESHI HIHARA Department of Chemistry, Tokyo Metropolitan University, Tokyo 192-0397, Japan TOMOKO ARAI National Institute of Polar Research, Tokyo 173-8515, Japan TAKAMITSU SUGIHARA Japan Agency for Marine-Science and Technology, Yokohama 236-0001, Japan HIROSHI TAKEDA University of Tokyo, Graduate School of Science, Tokyo, 113-0033, Japan CLAUDE D’USTON, SYLVESTRE MAURICE, OLIVIER GASNAULT, OLIVIER FORNI and BENEDICTE DIEZ Centre d’Etude Spatiale des Rayonnements, Universit´ e de Toulouse, Toulouse, 31028, France

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ROBERT C. REEDY Institute of Meteoritics, University of New Mexico, New Mexico, 87131-1126, USA KYEONG J. KIM Korea Institute of Geoscience & Mineral Resources, Daejeon 305-350, Korea TAKESHI TAKASHIMA, YUICHI IIJIMA and HISASHI OTAKE Japan Aerospace Exploration Agency (JAXA), Sagamihara 229-8510, Japan

The high precision gamma-ray spectrometer (GRS) onboard the Japanese lunar explorer, SELENE (KAGUYA) consists of a large Ge crystal as the main detector and massive BGO and plastic scintillators as anticoincidence detectors. After a series of initial health checks, it started regular observation oﬃcially on December 21, 2007. Energy spectra of lunar gamma rays were obtained by GRS with very good energy resolution being 0.6% at 1.46 MeV over the lunar surface. Many peaks of gamma rays from major elements and natural radioactive elements in the lunar surface have been observed. Individual gamma-ray lines emitted from the lunar surface have been identiﬁed. Here, we report the initial results obtained practically during the period from December 14, 2007 to February 17, 2008. Global maps of K and Th gamma-ray intensities are reported using count rates in several energy bands.

1. Introduction Determining the distribution of major elements and natural radioactive trace elements on the lunar surface is essential in lunar science. These elements provide the clues clarifying the conditions during the formation of the Moon and evolution of the lunar crust. Planetological studies of the distributions of elements on the lunar surface are very useful in improving our understanding of the evolution of the terrestrial planets including the Earth. From a viewpoint of remote chemical analysis of the Moon, gammaray spectroscopy is suited for measuring elemental composition on the lunar surface. The surfaces of planets and satellites with little or no atmospheres are continuously irradiated with galactic cosmic rays (GCR).1 As a result of nuclear interactions with lunar material, GCRs produce secondary neutrons that induce emission of line gamma rays through either nonelastic scattering or radiative neutron capture reactions.2 The energy of a gamma ray is characteristic of nuclei. Naturally radioactive nuclides also emit characteristic line gamma rays.2 These gamma ray intensities provide

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information on the elemental abundance of the material in the top few tens centimeters of the surface of the planetary bodies.3 Planetary missions with gamma-ray spectrometers (GRS) have proved themselves to be a powerful tool that provide precious information on the chemical abundance of the surface of planetary bodies. However, previous lunar missions, Apollo4 and Lunar Prospector,5 have employed detectors with limited energy resolutions.6 Energy resolution of gamma-ray detector severely aﬀects the scientiﬁc outcome. In SELENE (KAGUYA) mission, therefore, a germanium (Ge) detector was adopted as the main detector of its GRS for the ﬁrst time in lunar missions because of its supreme energy resolution.7,8 SELENE GRS will provide precise global abundance of the elements on the lunar surface by remote sensing and also provide data for the future utilization of lunar resources. The Japanese lunar mission SELENE consisting of main orbiter KAGUYA and two small daughter satellites (relay satellite OKINA and VRAD satellite OUNA), and was successfully launched from Tanegashima Space Center on September 14, 2007.9 The oﬃcial regular observation was started on December 21, 2007. The main orbiter carries a GRS with a large Ge semiconductor detector as a main detector and bismuth germinate (BGO) and plastic scintillators as active shieldings.7 With the highest energy resolution, the GRS provides the concentrations of the major and natural radioactive elements of the lunar surface. In this paper, the initial results of the GRS obtained during the period from December 14, 2007 to February 17, 2008 are discussed below.

2. Observation The GRS on board the KAGUYA, which is the main orbiter of the SELENE mission, observes lunar gamma rays to obtain chemical composition with high precision over the entire lunar surface. In order to carry out such gamma-ray spectroscopy, we have designed and developed the GRS schematically drawn in Fig. 1. The GRS consists of three subsystems, Gamma-ray Detector (GRD), Cooler Driving Unit (CDU), and Gammaray and Particle detectors Electronics (GPE). The GRD subsystem looking at the nadir is placed on the lunar side of the spacecraft, and the others are installed inside the spacecraft. The CDU controlled by the GPE subsystem drives a cryocooler to cool a large Ge semiconductor crystal below 90 K.8 The GPE contains analogue and digital boards for data processing and analyzing, and CPU boards for data handling, transmitting

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Fig. 1. Schematic drawing of the Gamma-Ray Detector (GRD) of the Gamma-Ray Spectrometer (GRS) for SELENE mission. It consists of a large Ge detector as a main detector cooled with a Stirling cooler, and BGO and plastic scintillators as an anticoincidence counter.

and command analysis. The detail of the GRS is described in Hasebe et al. (2008).7 The SELENE satellites were injected into the lunar polar orbit on October 4, 2007. After the separation of the daughter satellites and the injection of the main orbiter into the circular orbit at 100 km altitude on October 19, 2007, a series of health and function checks were made for the GRS as well as the other scientiﬁc instruments. Initial checkouts for the GRS have been made in the following order. First, the cooling system was turned on and a driving voltage of the cooler was increased step by step to cool the Ge detector to 90 K or below. Then all the electronic functions of the Ge detector and scintillators were checked without applying high voltages to the detectors. Next, the BGO and plastic scintillators were operated by applying high voltages from 0 to 1.1 kV with 6 V steps to photomultiplier tubes (PMTs). The Ge detector system was then checked by applying high voltages from 0 to 3.1 kV with 13.7 V steps without anticoincidence functionality. Finally, with all the detectors operating with high voltages, the anti-coincidence operation was checked. All the function tests showed the healthiness of the GRS system, and it was conﬁrmed that the system was ready for the measurement of lunar gamma rays. The GRS started its normal observation of the Moon on December 14, 2007, which was started before the oﬃcial regular observation by one week.

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Fig. 2. Energy spectra of gamma rays observed by SELENE GRS with and without anticoincidence operation. The counting rates of the spectrum baseline are greatly reduced by using anti-coincidence, increasing the sensitivity of the GRS signiﬁcantly (see the main text). From the spectrum on the bottom, individual peaks from elements on the lunar surface can be uniquely identiﬁed.

In-ﬂight energy spectra of gamma rays with the energies from 100 keV to 12 MeV obtained by the Ge GRS with or without operation of the anti-coincidence system are shown in Fig. 2. The upper spectrum (eﬀective time was 1.5 hours.) was obtained with no operation of anti-coincidence, although some background gamma rays, especially from the spacecraft body, are absorbed by the thick BGO scintillator. The lower spectrum (eﬀective time was 682 hours.) was obtained from the Ge using the anticoincidence system. From the comparison of these spectra, a remarkable reduction of the gamma-ray continuum was made by the anti-coincidence operation due to Compton suppression. Many peaks of gamma-ray lines can be seen in the anti-coincidence spectrum of gamma rays, while the upper spectrum does not have peaks except for intense lines of gamma rays. The level of background continuum in the energy range over 2 MeV is decreased by a factor of 5 to 20. Because the signal to noise ratio as to lower spectrum is higher than that to upper spectrum, it becomes clear that the anti-coincidence operation is very eﬀective for the peak detection.

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3. Results and Discussion Gamma rays emitted from the lunar surface were measured with GRS on the SELENE at around 100 km in altitude. Gamma-ray events are collected every 17 seconds. Those gamma-ray data accumulated during the regular observation from December 14, 2007 to February 17, 2008 were used in the analysis. Those spectra were measured with anti-coincidence operation of BGO and plastic scintillators. SELENE GRS observes gamma-ray peaks from various elements: potassium, thorium, uranium, oxygen, magnesium, aluminum, silicon, calcium, titanium, and iron (Fig. 2). Many gamma rays are from the material around the GRS, especially from the structural Al of the GRS and from other local elements (such as Ti). These interference background gamma rays are removed to large extent by anti-coincidence system. However, the background gamma rays are not removed completely only by an anti-coincidence system. In order to properly estimate on these elemental abundances on the lunar surface, the gamma ray intensities from these elements originated by spacecraft body must be removed as background gamma rays. The measurements of such gamma ray intensities are now in progress, but the correction of the intensities cannot be neglected even at present. Clear peaks emitted from the decay of natural radioisotopes of 40 K, 232 Th and 238 U are found in each energy spectrum of gamma rays from the whole Moon. The energy resolutions of 8.8 keV (FWHM) at 1,461 keV (40 K) and 33 keV (FWHM) at 2,615 keV (Th) have been obtained. These resolutions have been degraded from time of the laboratory test.7 There are low energy tails on gamma-ray peaks (Fig. 3). Therefore, it is thought that the degradation changed by the eﬀect of radiation damage. The local diﬀerence among their concentrations over the lunar surface crust is very important to deduce constraints for the formation and thermal histories of the lunar crust. The intensities of 40 K and 208 Tl (232 Th decay chain) gamma rays, as a typical example, are plotted in Fig. 3 for both hemispheres, the nearside and farside of the Moon. Figure 3 show that both abundances of the incompatible elements K and Th have considerably regional variations. As regards the nearside region, there are strong potassium and thorium peaks at 1.46 MeV and 2.61 MeV, respectively. In contrast, these gammaray intensities of farside are lower than those of nearside. This variation is consistent with the observation made by Lunar Prospector,10 in which it is reported that both of K and Th are primarily concentrated within and around the western-most maria on the nearside.

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Fig. 3. Comparison of (a) 40 K (1461 keV) and (b) 232 Th (2615 keV) gamma-ray peak intensities from the nearside and farside hemispheres. Both solid lines indicate spectra obtained from the nearside, and broken lines indicate spectra obtained from the farside. A nuclide with a asterisk indicates that the gamma ray can be produced by several processes. Many of the 24 Mg gamma rays were made in the structural Al around the GRS.

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The global maps on potassium and thorium (Fig. 4) were derived by applying the following procedure. First, all the spectra were corrected for gain and dead time variations as a function of time, but they were not corrected for cosmic ray variations because the solar activity remained steady during the observation period (Dec. 14, 2007 to Feb. 17, 2008). Next, the obtained GRS spectra were summed into 5 degree by 5 degree latitude/longitude bins. Counts were summed within energy bands around the central gamma-ray peaks.11 For potassium, the energy band was from 1.44 to 1.47 MeV; for thorium, the energy band was from 2.54 to 2.63 MeV (to be compared to the broader Th band of Lawrence et al., 2002: 2.4–2.8 MeV). The correction made in reducing the escape peak and Compton continuum gamma-rays for the spectra as shown in Fig. 3 was not considered in this preliminary mapping analysis. This analytical method (called “band analysis”) is simple and appropriate for relative evaluation of gamma-ray intensities in each area.11 After continuum subtraction and normalization to ground truth, this method may be used to estimate the absolute abundances (Lawrence et al., 2002). These maps show that potassium and thorium are concentrated primarily around the Procellarum KREEP Terrane (PKT).12 Region of the highest counting rates for K and Th extends from the southern edge of Mare Imbrium near the Copernicus to the Fra Mauro region with the landing site of Apollo 14. Regions of high counting rates for K and Th also surround the rim of Mare Imbrium. Relatively high concentrations of these elements are seen on the farside in the South Pole-Aitken basin (SPA). These characteristics of potassium and thorium counting rate maps obtained by SELENE GRS are consistent with those of the concentration maps obtained by Lunar Prospector.13 On the Moon, potassium and thorium are highly concentrated in KREEP-rich materials.14 Returned soil and rock samples show that K and Th concentrations are correlated from each other.14 A linear relationship was also found with the SELENE GRS measurements (Fig. 5), in good agreement with sample observations. These gamma-ray intensities of K and Th are strongly correlated. Although the counting rate in this paper was provided by band analysis, which is summed within continuum background, the measured potassium counts may be somewhat biased from a low-level background because of overlapping with Compton continuum gamma-rays produced from higher energy thorium lines. Thorium counting rates obtained by SELENE GRS roughly correspond to reasonable values estimated from Apollo and Luna thorium

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Fig. 4. (a) The global map of K gamma-ray counting rate (in counts per second) as measured by SELENE GRS. The data are divided to the size as 5 × 5 degrees in latitude and longitude. (b). The global map of Th gamma-ray counting rate as measured by SELENE GRS. The pixel size is the same as that of the K map. (c) Surface expressions of major lunar crustal terranes delineated on the Clementine albedo image using global simple cylindrical projection.15

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Fig. 5. Plot of potassium counting rate versus thorium counting rate as measured by SELENE GRS.

concentrations of regolith samples16,17 (Fig. 6). However, there are some disagreements between SELENE GRS measurements and sample data. It is probable that some disagreement is caused because the Apollo and Luna regolith samples simply do not represent an accurate measure of composition for the 5 degree radius (about 150 km) footprint seen by SELENE GRS. Furthermore, the data presented in this work were obtained by the band analysis, which cannot segregate gamma-ray continuum intensities below peaks or from surrounding materials. The Apollo 15 and 17 data were excluded in this ﬁgure, because the Apollo 15 and 17 landing sites are near a boundary of mare and highland, where the compositions of the soils are heterogeneous. Therefore, the 150-km-radius pixel size might be too large for comparisons with the ground truth data obtained by Apollo and Luna samples. It will be possible to providing the concentration map of Th by calibration method with ground truth, if count rates from smaller pixel size are used. In this paper, global count rate maps of K and Th were acquired from ﬁrst 2 months observation data of SELENE GRS. These maps are in good agreement with Lunar Prospector concentration maps.13 In the near future, on the base of SELENE GRS data accumulated for a longer observation periods, it will be possible to determine the detailed distributions of these

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Fig. 6. A relation of measured SELENE GRS thorium counting rate with regolith abundances in parts per million (ppm) derived for various Apollo and Luna landing sites. The Th concentrations for average regoliths at lunar landing sites are taken from the data set by Korotev (1998)16 and Korotev et al. (2000).17 The SELENE GRS measurements are taken from the 5 degree by 5 degree pixel covering each landing site. Errors of horizontal axis are due to those related to the total counts (the square root of counts).

elements. This paper focused only K and Th, but many other peaks from major and radioactive elements were conﬁrmed by whole Moon spectrum (Fig. 2). Several peaks of U are observed in the whole Moon spectrum by SELENE GRS, and we will provide a global U map in the near future.

4. Conclusions SELENE (KAGUYA) Gamma-Ray Spectrometer consists of a large germanium crystal actively cooled to 90 K or below. Lunar gamma-rays were collected for every 17 seconds. The energy spectra of lunar gamma rays were obtained with the observed data accumulated for 682 hours from December 14, 2007 to February 17, 2008. Many peaks of K, Th, U, O, Mg, Al, Si, Ca, Ti, and Fe features were observed in the spectrum. The data presented here have been corrected for gain and dead time variations, but uncorrected for cosmic-ray variations.

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The intensities of gamma rays from 40 K and 208 Tl (232 Th decay chain) were distinguishable between the nearside and the farside on the lunar surface. The global gamma-ray intensity maps of potassium and thorium were drawn using band analysis. The features of these maps obtained by SELENE GRS are in good agreement with those of concentration maps obtained by Lunar Prospector GRS. In the near future, on the basis of SELENE GRS data accumulated for longer observation periods will make it possible to determine the detailed distributions of the elements, K and Th over the lunar surface. In addition, it will be possible to provide the global map of U on the basis of peaks of each U spectrum over the Moon. Global mapping data of concentrations of other elements in the lunar surface will be provided after a careful calibration and correction of data and a vigorous numerical simulation of gamma-ray emission from the Moon. Joint study on the geological survey by the GRS, mineralogical results from visible and infrared from the Lunar Imager/Spectrometer system (LISM) and other instruments will be very useful in performing cross calibration and reference to improve the reliability of their results. Together with the cooperative programs of several scientiﬁc instruments onboard SELENE (KAGUYA), geochemical maps should give insight to the nature of the formation and evolution of the Moon and the detailed horizontal and vertical structure of the Moon. Moreover, the global maps of chemical abundance on the lunar surface obtained from the GRS observations are essential for the utilization of lunar resources in order to make the progress of human activities in space possible. Acknowledgments We would like to express our deepest gratitude to JAXA SELENE project staﬀ for obtaining invaluable observation data from the Moon. We are grateful for their dedication and devotion they’ve given to the operation of the SELENE gamma ray spectrometer. References 1. 2. 3. 4. 5. 6.

J. A. Simpson, Annu. Rev. Nucl. Part. Sci. 33 (1983) 323. R. C. Reedy, Proc. Lunar Planet. Sci. Conf. 9 (1978) 2961. N. Yamashita et al., Earth, Planets and Space 60 (2008) 313. M. J. Bielefeld et al., Proc. Lunar Planet. Sci. Conf. 7 (1976) 2661. W. C. Feldman et al., Nucl. Inst. Methods A422 (1999) 562. D. J. Lawrence et al., J. Geophys. Res. 109 (2004) E07S05.

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N. Hasebe et al., Earth, Planets and Space 60 (2008) 299. M. Kobayashi et al., Nucl. Inst. Methods in Phys. Res. A548 (2005) 401. JAXA home page, http://www.jaxa.jp/index e.html. D. J. Lawrence et al., Science 281 (1998) 1489. Metzger et al., Science 179 (1973) 800. B. L. Jolliﬀ et al., J. Geophys. Res. 105(E2) (2000) 4197. T. H. Prettyman et al., J. Geophys. Res. 111 (2006) E12007. G. H. Heiken et al., “Lunar Sourcebook: A User’s Guide to the Moon”. Cambridge University Press, Cambridge (1991). 15. Clementine-UGSG Images, http://astrogeology.usgs.gov/Projects/Clementine/ 16. R. L. Korotev, J. Geophys. Res. 103(E1) (1998) 1691. 17. R.L. Korotev et al., Lunar Planet. Sci. 31 (2000) 1363.

7. 8. 9. 10. 11. 12. 13. 14.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

LUNAR GAMMA-RAY OBSERVATION BY KAGUYA GRS N. HASEBE, N. YAMASHITA, Y. KAROUJI∗ , S. KOBAYASHI, M. HAREYAMA, S. KOMATSU, K. HAYATSU, K. NEMOTO, K. IWABUCHI, Y. TAKEDA, H. NAGAOKA, K.TSUKADA, J. MACHIDA, O. OKUDAIRA and S. SAKURAI Waseda University, Japan ∗ [email protected] E. SHIBAMURA Saitama Prefectural University, Japan M.-N. KOBAYASHI Nippon Medical School, Japan M. EBIHARA and T. HIHARA Tokyo Metropolitan University, Japan T. ARAI University of Tokyo, Japan T. SUGIHARA JAMSTEC, Japan H. TAKEDA Chiba Institute of Technology, Japan C. d’USTON, O. GASNAULT, B. DIEZ, O. FORNI and S. MAURICE CESR, France R. C. REEDY Planetary Science Institute, USA K. J. KIM KIGAM, Korea

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The high precision Gamma-Ray Spectrometer (GRS) was carried on the first Japan’s large-scale lunar orbiter, SELENE (KAGUYA). The GRS employed a Ge detector with high energy resolution. Since the regular observation by the KAGUYA GRS started on December 14, 2007, gamma-ray data had been accumulated over the Moon. Many elements were identified: O, Mg, Al, Si, K, Ca, Ti, Fe, Th and U. The regular GRS observation at 100 km altitude let us create global distribution maps of chemical abundances on the lunar surface, which showed considerable regional variations. Special operations were conducted in December 2008 in order to measure background gamma rays from materials of the spacecraft body and the GRS detector itself, and to anneal the Ge crystal for about two days at 85 ± 5 degrees Celsius in order to recover the resolution of the Ge crystal that had been degraded due to radiation damage in space. Its energy resolution was improved to the level at the initial phase of the mission. Results from the special operations and regular observation of the Moon are described.

1. Introduction The measurement of gamma rays coming from the lunar surface is a powerful method to infer the composition of material in the top several tens of centimeters of the surface. When those gamma rays are remotely measured from a spacecraft in orbit, the gamma-ray energies identify chemical elements from which they were emitted, and their ﬂuxes are closely related to their elemental concentration. The energy resolution of the gamma-ray detector is closely related with the scientiﬁc outcome. Lunar missions such as Apollo,1 Lunar Prospector,2 and Chang’E-13 employed scintillation gamma-ray detectors, NaI(Tl), BGO and CsI(Tl), respectively, with poor energy resolutions. An excellent energy resolution and high sensitivity are highly required for the complex gamma rays from the surface of the Moon. Japan’s large lunar orbiter, SELENE (KAGUYA),4 was launched by an H-IIA rocket in 2007. It covered the whole lunar surface by its polar orbit at a nominal altitude of 100 km and observed the lunar surface with high precision by three axis stabilized attitude control. The major objectives are to understand the origin of the Moon and its evolution, and to observe the Moon in various ways in order to utilize it in the future. A high performance Gamma Ray Spectrometer (GRS) onboard SELENE (KAGUYA) observed the entire surface of the Moon.5 The GRS consisted of a large germanium (Ge) crystal as a main detector and massive bismuth germanate (BGO) crystals and a plastic scintillator (PS) as anticoincidence detectors. The GRS measured gamma-ray spectra that have been and will be used to determine precise global abundances of natural radioactive nuclides such

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as K, Th and U, and major elements such as O, Mg, Al, Si, Ca, Ti and Fe in the lunar subsurface by remote sensing, which will be useful and important data for the future utilization of lunar resources.6 In this paper, some special operations of the measurement of background gamma rays, annealing the Ge crystal conducted in December, 2008, and recent results of regular observation are presented and discussed.

2. The Gamma-Ray Spectrometer We employed a high-purity Ge detector with an excellent energy resolution. The GRS consisted of three subsystems, GRD (Gamma-Ray Detector), CDU (Cooler Driving Unit) and GPE (Gamma-ray and Particle Electronics). The GRD was the Ge detector (EURISYS) with a volume of 252 cm3 , which was cooled to around 80 K by a Stirling cycle cryocooler and was surrounded by a horseshoe-shaped BGO (BICRON) and a PS (BICRON) to reduce the background gamma rays and charged particles. The detailed conﬁguration of the GRS and cooling system is found elsewhere.5 The CDU supplies electronic power (maximum of 55 W, frequency 52 Hz AC) for the Stirling cycle cryocooler. The temperature of the Ge crystal was controlled by the GPE via the CDU. The signal of Ge detector was fed to a charge-sensitive preampliﬁer whose ﬁrst stage ﬁeld-eﬀect transistor (FET) and feedback elements were cooled together with the Ge crystal. The output from the preampliﬁer went to two diﬀerent shaping ampliﬁers with time constants of 2 µs: one for a low energy range from 0.2 to 3 MeV; the other for a full energy range from 0.2 to 12 MeV. The two energy spectra were recorded as 8192 channel-data every 17 seconds. Two photomultipliers coupled to the BGO and one photo-multiplier coupled to the PS produced veto signals for Ge signals when operated as an active anticoincidence system. The GRS started its regular observation on December 14, 2007. Figure 1 shows energy spectra of gamma rays with the energies from 100 keV to 12 MeV obtained by the Ge detector of the GRS in lunar orbit with and without the anti-coincidence system. The upper spectrum was obtained with no anti-coincidence. Some background gamma rays, especially from the spacecraft body, were signiﬁcantly absorbed by the thick BGO scintillator. The lower spectrum was obtained from the Ge using the anti-coincidence system. From the comparison of these spectra, a remarkable reduction of gamma-ray continuum was made by the anti-coincidence operation due to

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2000

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Energy [keV] Fig. 1. In-flight energy spectra of gamma rays obtained with (lower) and without (upper) operation of the anti-coincidence system.

Compton suppression. The level of background continuum in the energy range above 2 MeV was decreased by factors of 4 to 35. 3. Some Operations of the GRS Instrument 3.1. Regular operation From the end of December 2007, the GRS observed lunar gamma rays at a polar orbit of 100 km in average altitude for 10 months for the nominal mission, which ended in October 2008. After the nominal mission, an extended mission followed. The observation was continuously made except interruptions to reset the satellite’s reaction wheels accompanied by thruster operations. In addition, observation was stopped for four months from March 2008 to solve problems in the HV system of the GRS. The average dead time in observation was about 23% due to the processing time of Ge signals and anti-coincidence signals from BGO and PS. To remove radiation damage in the Ge detector that made the energy resolution bad, the Ge detector was annealed at high temperatures on December 16–24, 2008. The GRS made gamma-ray observations with the better energy resolution from February 10, 2009, to May 29, 2009. Since the middle of January, the spacecraft orbit was shifted from 100 km to 50 km

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in altitude. During this period, the spacecraft altitude ﬂuctuated between 30 km and 80 km, so that the careful correction of altitude was required to derive absolute abundances of elements of the Moon. 3.2. Measurement of background gamma rays A gamma ray energy spectrum consists of peaks from gamma-ray lines above a smooth continuum of counts from many sources. The gamma rays from O, Si, K, Ca, Ti, Fe, Th, and U appear to mainly come from the Moon, although there are probably local backgrounds from materials of spacecraft and detector itself. The peaks from Al are mostly attributed to the Al structure of the GRS and its surroundings. Many peaks originate from the Ge and the BGO crystals. Background measurement of gamma rays and the detailed simulation of gamma ray and neutron production and their transport are required to improve the precision of the measured chemical abundances. Therefore, we made the measurement of background gamma rays for the quantitative evaluation of the lunar surface material on December 11–12, 2008. Special spacecraft operations for the measurement were performed by controlling the spacecraft’s attitude so that the GRS pointed away from the Moon for much of each orbit. In these operations, the Ge detector viewed deep space for much of the time instead of always looking at the lunar nadir, as done during the regular observation. Energy spectra determined for both the regular observation and background operation are presented in Fig. 2. The background measurement showed that gamma rays from K, U, Ti, Al and Mg were detected from the spacecraft body and instrument itself at signiﬁcant magnitudes. In particular, the contribution of those gamma rays from Al is signiﬁcantly large, because most structure of the spacecraft and the mission payloads are made of Al. 3.3. Annealing of the germanium detector Radiation damage is induced in the Ge detector from the incidence of highenergy particles from space. The dominant source of radiation damage in the Ge detector mainly arises from protons in the galactic cosmic rays and energetic secondary particles made in the Moon and the spacecraft. Displacement eﬀects permanently result in radiation damage to the lattice structure. High energy particles, in particular, produce single defects and extended disordered regions resulting from collisions with Ge nuclei. As

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Count Rate [count/s/1.5 keV]

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Normal observation Background operation

0.01

400

800

1200

1600

2000

2400

2800

Energy [keV] Fig. 2. Energy spectrum of background gamma rays observed by special operation when the GRS looks at deep space (lower). Also shown is the energy spectrum in regular observation when the GRS looks down the lunar nadir (upper).

the trapping time becomes longer than the shaping time constant of ampliﬁer, the charges formed by the ionization process in Ge are partially lost. Therefore, the peaks of gamma-ray lines in an energy spectrum in a radiation-damaged detector are characterized by a broadening and tailing to the low energy region, and the energy resolution of such Ge detectors degrades. If a detector in space is kept colder than about 90 K, this damage is not clearly observed for several years. If the detector is once warmed and then cooled to an operational temperature, the damage is prominently observed in the spectra. However, radiation damage is annealed by heating the Ge detector to high temperatures. KAGUYA GRS started to cool the Ge detector on November 13, 2007, and the GRS was initially checked on November 16, 2007. Regular observations began on December 14, 2007. The energy spectrum even at the initial phase of observation showed a slightly long tail in the low energy part of each gamma-ray peak, which are caused by radiation damage induced in the Ge crystal from the incidence of high-energy cosmic-ray particles. The energy resolution at 1461 keV in the initial observation phase was about 6.5 keV in fwhm (full width at half maximum). The energy resolution

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gradually degraded with time after the launch. At the end of nominal mission (Nov. 2008), the energy resolution at 1461 keV was about 21 keV, which was seven times larger than that before the launch. Due to other operations of the KAGUYA spacecraft, cooling of the Ge detector and the gamma-ray observation had to be intermittently stopped. As a result of radiation dose absorbed and of the rise in temperature, the degradation of detector was clearly observed. We conducted an annealing operation of the Ge detector in December, 2008. The detector was kept at an intermediate temperature of 20◦ C for 24 h, then warmed up to 50◦ C and kept for 24 h, and then heated up to 85 ± 5◦ C for about 2 days. After annealing and cooling down the detector below 90 K again, the performance of the GRS was checked with HV = 2.5 kV. The energy spectrum after the annealing is shown together with that just before the annealing in Fig. 3. It is found that the low-energy tails of peaks after the annealing became much smaller. The energy resolutions were improved to approximately 6 keV, comparable to that at the initial phase of the nominal mission. This improved energy resolution yields better gammaray ﬂuxes and thus better elemental abundances because the correction for 0.08

24

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0.07

Mg 40

K

0.06

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0.04

After annealing 0.03

Before annealing 0.02 1300

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Energy [keV] Fig. 3. Energy spectra of gamma rays with K 1461 keV observed before (lower) and after (upper) the annealing of the Ge crystal.

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the continuum under a peak is reduced by the need for fewer channels of data and by reducing any overlap with adjacent peaks. 4. Global Mapping of Natural Radioactive Nuclides Gamma-ray energy spectra containing peaks from various chemical elements were obtained for constraining the elemental composition of the Moon by KAGUYA GRS observation. The unique identiﬁcation of peaks measured by the GRS is essential in the complex mixed gamma-ray ﬁeld in order to precisely derive elemental abundances. Clear peaks from the natural radioisotopes of K, Th and U are identiﬁed in spectra of gamma rays. These data delineate the global distributions of these key trace elements and the regions in which they and several other elements (called KREEP) are abundant in lunar materials.7 The global distribution of thorium is shown in Fig. 4, as a typical example. The abundances of the incompatible elements K, Th and U have considerable regional variations over the lunar surface. The western maria in the nearside is more abundant than that in the farside. Especially, over the Procellarum

Fig. 4. The global distribution of thorium in the lunar surface measured by GRS onboard KAGUYA (SELENE). This map is made by using data obtained from Dec. 2007 to Feb. 2008, and by smoothing average count rates in quasi-equal area pixels with 200 km × 200 km.

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KREEP terrain (PKT) their abundance is the highest. The South PoleAitken terrain (SPAT) is higher in these abundances than the surrounding regions, and the lowest was found in the farside feldspathic region. Figure 5 presents the intensity map of Th measured for the Imbrium basin. Some high-Th regions associated with craters near the rim of Imbrium are seen: Aristillus and Mairan and so on. Mountains of Jura, Archimedes and Carpathian are also abundant in Th. The wide region from the Carpathian Mountains to Mare Insularum, the North Cognitum, Fra Mauro, and the north Nubium, has so high in the abundance of Th that this region is identiﬁable as ejecta from the Imbrium impact. Relatively highTh regions also exist near the Aristarchus and highlands north of Imbrium basin. The GRS observation revealed the highest surface abundances of natural radioactive nuclides, which are quite localized around the Imbrium basin. This result conﬁrms that there is a special terrain enriched in K/Th/U on the Moon. The Imbrium impact spread a large amount of

Fig. 5. The intensity distribution of thorium measured for the Imbrium basin observed by the KAGUYA GRS. This map is made by using data obtained from Dec. 2007 to Feb. 2008, and by smoothing average count rates in quasi-equal area pixels with 200 km × 200 km. The shaded relief is produced based on the topographic data obtained by Laser Altimeter (LALT) onboard KAGUYA.8

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those materials over the Moon. During the period of KREEP volcanism, natural radioactive nuclides were distributed in the regions located around the Apennine Bench, Aristillus and near Sinus Iridum. And then mare basalt ﬁlled the Imbrium basin with less radioactive nuclides. Additionally, natural radioactive nuclides were excavated in various locations around the Imbrium basin.9

5. Summary The gamma ray spectrometer (GRS) was carried on the lunar polar orbiter, SELENE (KAGUYA). The GRS measured natural radioactive nuclides such as K, Th and U, and major elements such as O, Mg, Si, Ca, Ti and Fe in the lunar surface during the period from December 14, 2007 to May 29, 2009. The special operations for the GRS were conducted in December 2008 in order to measure background gamma rays emitted from the spacecraft material and the GRS instrument itself and to anneal the Ge crystal that had been degraded in performance by radiation damage. The background measurement of gamma rays was made for the estimation of absolute abundance of elements in the lunar surface. The comparison of both the energy spectra between the normal operation and background operation provided the backgrounds from material being located in and near the GRS. And the annealing of the Ge crystal greatly improved the energy resolution of gamma-ray peaks to the level of the initial phase of the nominal mission. These special actions provide us the high capability of identiﬁcation of elements and improved precision of abundance determinations. We also demonstrated the intensity variations of Th gamma rays measured by the GRS over the Moon, and particularly in the nearside PKT. After careful corrections of altitude variation in the orbit of SELENE (KAGUYA) spacecraft and background gamma rays in the energy band of peak area, the global maps of absolute concentration of radioactive nuclides, Th, U and K, will be presented elsewhere in the near future. Moreover, the abundance of major elements in the lunar surface will also be globally reported after simulations of cosmic-ray interactions and the production of gamma rays by cosmic-ray-produced particles to support the precise interpretation of observation data. The combination of GRS data with other precise data from other KAGUYA instruments such as LISM, LALT, VRAD/RSAT, and LRS will provide new insight about how the Moon, including its KREEP component.

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Acknowledgments We would like to thank the staﬀ of JAXA and NEC Toshiba-Space System Ltd. for generous supports during the whole period of the development and operation of SELENE. References 1. 2. 3. 4. 5. 6. 7. 8. 9.

M. J. Bielefeld et al., Proc. Lunar Planet. Sci. Conf. 7 (1976) 2661. W. C. Feldman et al., Nucl. Inst. Methods A422 (1999) 562. H. X. Sun and S. W. Dai, Acta Astronautica 57 (2005) 561. M. Kato et al., Adv. in Space Res. 42 (2008) 294. N. Hasebe et al., Earth Planets Space 60 (2008) 299. G. J. Taylor and L. M. V. Martel, Adv. in Space Res. 31 (2003) 2403. B. L. Jolliﬀ et al., J. Geophys. Res. 105(E2) (2000) 4197. H. Araki et al., Science 323 (2009) 897. D.J. Lawrence et al., Geophys. Res. Lett. 26 (1999) 2681.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

THE AMBIENT DOSE EQUIVALENT FROM LUNAR GAMMA-RAYS OBSERVED BY KAGUYA GAMMA-RAY SPECTROMETER Y. TAKEDA∗ , K. HAYATSU, S. KOBAYASHI, M. HAREYAMA and N. HASEBE Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan ∗ [email protected] S. KODAIRA National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba-shi 263-8555, Japan K. J. KIM Korea Institute of Geoscience and Mineral Resources, 30 Gajeongpdong, Yuseong-gu, Daejeon 305-350, Korea

The gamma-ray spectrometer (GRS) onboard the lunar polar explorer, SELENE (KAGUYA), globally measured gamma rays emitted from the lunar surface. Using the gamma-ray data observed by the GRS, global map of ambient dose equivalent due to lunar gamma rays for the first time are obtained for the energies from 200 keV to 10 MeV. The dose due to gamma rays on the lunar surface during the period of 2008 at solar minimum of solar activity ranges from 2.58 to 4.30 mSv/yr, depending on the regions of the Moon, which give higher than that due to gamma rays from natural radioactivity isotopes at the Earth. It is found that the dose is high in mare regions, especially the Procellarum KREEP Terrain, where natural radioactive isotopes such as U, Th and K and major elements such as Fe and Ti are abundant.

1. Introduction Exploration missions on lunar surfaces are currently being studied as an extension of human activity in Low Earth Orbit around the Earth. The ﬁrst long term human exploration mission will be the Moon because of a relatively easy access and communication. Study for the assessment of radiation environment in space is important for planning the future missions with astronauts working on the surface of the Moon, and there has been an increase in the study of radiation dose in recent years.1−3 69

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The radiation environments on the Moon is quite diﬀerent from that on the Earth’s surface in spite of the nearest astronomical objects from the Earth. Since the Moon has an extremely thin atmosphere, it does not protect the lunar surface from galactic cosmic rays (GCRs) and solar particle events (SPEs). Moreover, the Moon has almost no magnetosphere. As a result, GCRs and SPEs enter the lunar surface practically unobstructed. Therefore, the radiation environment on the Moon mainly consists of highly penetrative GCRs and SPEs. The impact of high energy protons and heavy ions in the GCRs and SPEs on the surface of the Moon produces a cascade of secondary particles due to fragmentation as primaries interact with lunar regolith. Some of these secondaries such as neutrons and gamma rays are directed upwards, and hence contribute to the dose deposited on a material located at the lunar surface, like a vehicle or an astronaut. The intensity of doses due to secondary particles and gammarays emitted natural radioactive isotopes is diﬀerent between each region because it depends on composition of lunar surface. At the same time, primaries enter the lunar surface isotropically and the intensity of doses due to primaries does not show regional diﬀerence. Therefore, the study of distribution of the secondary particles and gamma-rays emitted natural radioactive isotopes on the Moon is important for future exploration. Although the dose on the Moon is mainly contributed from high energy charged particles in the GCRs and SEPs, here we focus the dose due to gamma rays from the lunar surface. The high precision Gamma-Ray Spectrometer (GRS) on the Japanese lunar explorer SELENE (KAGUYA) globally measured gamma rays to determine the elemental composition of the lunar surface.4 Gamma-ray data were accumulated by the GRS from December 14, 2007 to December 16, 2008. During the period of observation, solar activity was so quiet that the eﬀect from SPEs was negligible small. The intensity map of gammaray spectra over the Moon was obtained. Using these gamma-ray data, we ﬁrstly derived the global map of ambient equivalent dose due to gamma rays on the Moon. The distribution of the gamma-ray dose over the Moon is presented and discussed in the paper.

2. KAGUYA GRS KAGUYA was operated in the circular polar orbit of the Moon at about 100 km Altitude. Her purpose is to observe the Moon globally with high accuracy to reveal the origin and evolution of the Moon.5

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Fig. 1. An energy spectrum of gamma rays obtained by the GRS. Live time is 9,626,220 sec.

The Gamma-Ray Spectrometer (GRS) on board KAGUYA observed lunar gamma rays. The GRS employed a Ge detector as a main detector and BGO and plastic scintillators as active shield detectors. The data used in this work were accumulated by the GRS during the period from Dec. 14, 2007 to Dec. 16, 2008. During the observation period, solar activity was very low. An energy spectrum of gamma rays obtained by the GRS is shown in Fig. 1. 3. Derivation Scheme of the Ambient Dose Equivalent In this work, it is assumed that the ambient dose equivalent on the lunar surface is proportional to a dose equivalent of the orbiting Ge detector. Based on the assumption the ambient dose equivalent is deﬁned as: HG = QDG ∝ Q E × f (E)dE ≡ HG (1) ∗ H (10) = C × Q E × f (E)dE. Dose equivalent of the GRS, HG , is proportional to the quality factor, Q, multiplied by total energy and the count rate whose product was deﬁned . Multiplying HG by the proportionality factor to an ambient dose as HG equivalent, C, gives ambient dose equivalent H ∗ (10). H ∗ (10) is deﬁned as a ambient dose equivalent at depth of 10 mm in the ICRU sphere with a diameter of 30 cm. The ICRU sphere is a phantom deﬁned by

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International Commission of Radiological Units and Measurements.3 C is constant because of the assumption that the ambient dose equivalent on the lunar surface is proportional to a dose equivalent of the orbiting Ge detector. Where DG is the absorbed dose of the GRS, E is a gamma-ray energy, and f (E) is the count rate of observation data, which is a function and C is of energy. Note that lower formula represents H ∗ (10) = CHG unknown. To determine C, HG derived from KAGUYA GRS observational data in the area where the composition of soil is known was compared with a calculated H ∗ (10) value in the following way. The ﬂuence of GCR-induced gamma rays on the lunar surface is calculated using Monte Carlo simulation library Geant4 release 8.0.p01. In the calculations, incident particles are GCR protons with solar mimimum activity in 2008.6 The targets are composed of materials with average composition of Apollo landing sites such as Apollo 11, 12, 14, and 16, and Lunar 16, 20, and 24.7 Using the calculated gamma-ray ﬂuence, we calculated ambient dose equivalent due to GCR-induced gamma rays on the Moon deﬁned as ∗ (2) H (10)[mSv/yr] = Cγ (E) × Φγ (E)dEγ where Cγ (E) is the conversion coeﬃcient provided by8 and Φγ (E) is gamma-ray ﬂuence.3 Note that Cγ (E) is diﬀerent from C in formula (1). By contrast ambient dose equivalent due to natural radioactive isotopes is easily calculated in comparison with concentration of Th of the Moon with the Earth which is approximately 0.5 mSv/yr.9 Figure 2 shows the plot of H ∗ (10) as a function of HG . From the regression line in Fig. 1, conversion coeﬃcient was determined. Brieﬂy C to H ∗ (10) is the is 5.4233 × 10−5 . The equation of conversion from HG following − 5.103. H ∗ (10) = 5.4233 × 10−5 × HG

(3)

HG in the whole area derived by using observational data from KAGUYA GRS is substituted for the Eq. (3) to make a global map of the ambient dose equivalent on the Moon.

4. Results and Discussion We derived the dose due to lunar gamma rays from KAGAYA GRS observational data and made the global dose map. The global map of the

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derived from Fig. 2. Comparison of ambient dose equivalent calculated with HG observational result. The horizontal axis is HG calculated by observed GRS data and the vertical axis is ambient dose equivalent calculated by Monte Carlo simulation and Th concentration ratio between the Earth and Moon. Apollo and Lunar soil data is from Ref. [7].

Table 1. The range of dose on the lunar surface shows from 2.58 ((lat : Lon) = (−32.5 ∼ −29.25 : −89.06 ∼ −85.26)) to 4.30 ((lat : Lon) = Max(32.5 ∼ 35.75 : 0 ∼ 3.91)) mSv/yr. Min [mSv/yr]

Max [mSv/yr]

2.58

4.30

ambient dose equivalent on the Moon is shown in Fig. 3. Consequently, the dose due to gamma rays on the lunar surface in 2008 (solar minimum) ranges from 2.58 to 4.30 mSv/yr (Table 1) and average dose is 2.96 mSv/yr. The value of the average doses due to gamma rays on the lunar surface, 2.96 mSv/yr, is higher than that on the Earth, about 0.5 mSv/yr.9 The reason for the diﬀerence between these values in spite of little diﬀerence of the concentration of radio active isotopes on the Earth and Moon is that gamma rays are produced from not only natural radioactive isotopes but major elements. Because of no existence of thick atmosphere around the Moon, GCRs interact with major elements on lunar surface and produce gamma rays. Hence, the doses due to gamma rays on the Moon are higher than that on the Earth. The doses show diﬀerent features in each region on the Moon. Figure 3 shows that the doses are high in maria and the in the Procellarum KREEP

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Fig. 3. The global map of the ambient dose equivalent due to lunar gamma rays. The doses are high in mare regions abundant in major elements such as Fe and Ti, and especially in the PKT, where natural radioactive isotopes such as U, Th, and K are abundant.

Terrane (PKT)10 is abundant in natural radioactive isotopes such as K, Th and U. The result that the doses are highest in PKT indicates that natural radioactive isotopes contribute largely to doses. Moreover the doses are high in maria. One of the reason is that Fe and Ti are abundant there. Both elements have larger cross sections of neutron production than other major elements, which generate more neutron-induced prompt gamma rays. The energy dependence of the dose is investigated. Figure 4 is a plot of average doses every 1 MeV on the lunar surface as a function of energy.

Fig. 4. Mean ambient dose equivalent [mSv/MeV/yr] on the lunar surface as a function of gamma-ray energy. Though the energy range of used data is from 0.2 to 10 MeV, the doses were corrected to the doses every 1 MeV in this figure. This figure shows that low energy gamma rays contribute to the doses largely.

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Figure 4 shows that doses in low energy are higher than that in high energy. Namely, low energy gamma rays contribute to the doses largely. The doses from 1 to 3 MeV account for 67% of the total doses. A continuum due to compton scattering contributes to doses larger than line gamma peaks. These results will be useful for a future manned exploration of the Moon. However, the doses due to neutrons produced by interaction of materials on the lunar surface with GCRs and SPEs are higher than those due to gamma rays. Therefore the dose map of neutrons is needed for the future. References 1. G. De Angelis, M. S. Clowdsley, J. E. Nealy, R. K. Tripathi and J. W. Wilson, Advances in Space Research 34 (2004) 1395–1403. 2. M. Gurtner, L. Desorgher, E. O. Fl¨ ukiger and M. R. Moser, Advances in Space Research 37 (2006) 1759–1763. 3. K. Hayatsu, M. Hareyama, S. Kobayashi, N. Yamashita, M. Miyajima, K. Sakurai and N. Hasebe, Bio. Sci. Space 22 (2008) 59–66. 4. N. Hasebe et al., Earth Planets Space 60 (2008) 299–312. 5. N. Hasebe et al., Advances in Space Research, 42 (2008) 323–330. 6. N. Yamashita, N. Hasebe, T. Miyachi, M. Kobayashi, O. Okudaira, S. Kobayashi, T. Ishizaki, K. Sakurai, R. C. Reedy, C. D’Uston, S. Maurice and O. Gasnault, Earth Planets Space 60 (2008) 313–319. 7. P. Lucey et al., Reviews in Mineralogy & Geochemistry 60 (2006) 83–219. 8. International Commission on Radiological Protection, ICRP Publication 74 (1997). 9. United Nations Scientiﬁc Committee on the Eﬀects of Atomic Radiation, United Nations, New York (2000). 10. B. L. Jolliﬀ, J. J. Gillis, L. A. Haskin, R. L. Korotev, M. A. Wieczorek et al., J.Geophys. Res. 105 (2000) 4197–4216.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

COMPUTATIONAL GEOLOGY FOR LUNAR DATA ANALYSIS FROM LISM ON KAGUYA∗ NORIAKI ASADA† , NARU HIRATA, HIROHIDE DEMURA, NAOTO HARADA, YUTO SHIBATA, SHOTA KIKUCHI and TOMOKI HODOKUMA Department of Computer Science and Engineering, The University of Aizu, Tsuruga, Ikki-machi, Aizu-Wakamatsu City, Fukushima Pref., 965-8580, Japan † [email protected] JUNICHI HARUYAMA, MAKIKO OHTAKE, YASUHIRO YOKOTA, TOMOKATSU MOROTA and CHIKATOSHI HONDA Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA), 3-1-1 Yoshino-dai, Sagamihara, Kanagawa 229-8515, Japan TSUNEO MATSUNAGA and YOSHIKO OGAWA Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan MASAYA TORII Fujitsu Limited, 9-3, Nakase 1-chome, Mihama-ku Chiba City, Chiba 261-8588, Japan TOKUHIRO NIMURA Department of Earth and Planetary Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan HIROSHI ARAKI and SEIICHI TAZAWA RISE Project Oﬃce, National Astronomical Observatory of Japan, 2-12 Hoshigaoka, Mizusawa, Oshu 023-0861, Japan

∗ This

work is supported by JSPS Grants-in-Aid for Scientiﬁc Research 19204045: H. Demura, 20540416: J. Haruyama and C. Honda, and 20 · 9211: T. Morota of the Japan Society for the Promotion of Science. 77

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The huge volume of Lunar Imager/Spectrometer (LISM) data (over 10 TBytes) returned from the moon requires computer processing. Previous automatic crater recognition algorithms to detect craters on photographs are strongly aﬀected by the solar elevation angle. On the other hand, automatic crater counting on a digital terrain model (DTM) can avoid the inﬂuence of the solar elevation angle. Crater chronology is expected to be developed through detailed analysis of data from the LISMs Terrain Camera (TC) aboard the KAGUYA lunar orbiter. The TC has a spatial resolution of 10 m/pixel. By using textural features of detailed topographic data obtained from the TC, as well as detailed spectral information from images acquired by the Multi-band Imager (MI), a more detailed mapping of the moon is possible. Reliable classiﬁcation for geological mapping may be obtained by using a k-means method, which classiﬁes the mineral composition and degree of space-weathering in addition to highland areas and mare.

1. Introduction The nominal observation phase began in December, after KAGUYA (SELENE) was launched on September 14, 2007, from Tanegashima Space Center, and the critical operation phase including the lunar polar-orbit insertion and the instrumental initial checkouts was completed. The Lunar Imager/Spectrometer (LISM) has three kinds of remote-sensing cameras, the Terrain Camera (TC), the Multi-band Imager (MI), and the Spectral Proﬁler (SP), together with other scientiﬁc observation equipment on KAGUYA. The TC consists of a pair of high-resolution stereo cameras for imaging the entire lunar surface with 10-m spatial resolution at a nominal altitude of 100 km.1 The MI is a multi-spectral imager comprised of ﬁve visible and near-infrared spectral bands from 415nm–1µm with 20-m spatial resolution and four near-infrared spectral bands from 1 µm to 1.55 µm with 62-m spatial resolution at nominal altitude. The SP is a line spectral proﬁler consisting of 296 spectral bands from 0.5–2.6 µm with a band resolution of 6–8 nm and a 500 m-wide footprint.2 The total amount of LISM data exceeds several tens of terabytes, over 90% of all KAGUYA data, and is too voluminous to handle without computer processing. An automatic crater recognition algorithm, mostly for crater chronology and automatic classiﬁcation of LISM data in geological mapping, has been recently developed and is introduced in this paper. Automated computations are absolutely necessary for both applications due to the huge volume of data obtained from KAGUYA.

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An automatic crater recognition algorithm from DTM is described in Chapter 2, and an automatic classiﬁcation scheme for geological mapping is described in Chapter 3.

2. Crater-Recognition Algorithm 2.1. Overview Automatic crater recognition is highly demanding. The size-frequency distribution, determined through crater counting, is a fundamental statistic used in the study of crater chronology. It can be used to determine the size dependency of crater topographic statistics such as crater depth, shape of the crater edge, existence of a central hill, and the shape of the crater bottom. These characteristics can be clearly determined if a statistically signiﬁcant number of craters are processed. Manual crater counting takes much too long, and the result is inﬂuenced by the personal skill of the operator. Therefore, a strong demand exists for automatic crater counting and recognition of geographical crater features. A technique for crater recognition should be robust in the presence of degrading factors such as unclear edge shapes, overlaying by other craters, and erosion by ejecta. Previous crater-recognition techniques used the Hough Transform,3 the fuzzy Hough Transform,4 the template-matching method5 or a learning algorithm.6 Typical crater-recognition rates were 70–80%. Scientists demand a higher recognition rate and more automated analysis software. Craters are usually recognized from photographs or digital terrain models (DTMs). The inﬂuence of the solar elevation and image contrast is very large when counting from photographs. These factors do not inﬂuence the analysis using DTMs. However, in addition to limitations imposed by the time needed to construct the DTM from the photographic image, an algorithm capable of clearly distinguishing the crater edge also becomes necessary. The main objective of the TC aboard KAGUYA is to construct a 3D map of the lunar surface, leading to the automatic construction of the DTM after each TC observation. Therefore, no additional eﬀort is required for the construction of the DTM. For the crater recognition step, we have adopted a General Hough Transform (GHT) approach. The objective of this research was to recognize craters over 10 pixels on the major axis using the DTM, and then to detect enough craters to be

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able to perform a statistically meaningful comparison against the crater-size distribution curve for crater chronology. Martian DTMs obtained by the Mars Orbiter Laser Altimeter (MOLA) were used as test data. The MOLA DTM currently has the highest spatial resolution available in the planetary science ﬁeld. Altitudes lying between +21,249 m and −8,508 m are stored as an 8-bit gray-scaled raster image on a simple cylindrical projection of the MOLA DTM data. The latitudinal resolution is 16 pixels/degree. 2.2. Edge detection Edge detection is one of the most important procedures in the recognition process. Edge detection consists of the following steps: 1. Edge extraction: Only the high-frequency component of the Haar wavelet transform is used in the inverse transform (Fig. 1a, 1b). It is very

(a)

(d)

(b)

(e)

(c)

(f)

Fig. 1. Edge extraction procedure for crater recognition algorithm. a. Original DTM (200 × 200 pixels) near Holden crater and surroundings. b. High-frequency component from Haar wavelet transform. c. Image after binarization. d. Image after a 3 × 3 median ﬁltering. e. Image after dilation process. f. Image after thinning process.

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sensitive to small and/or complex features, which turn out to be very important in crater recognition. Binarization: A threshold value is determined visually (Fig. 1c). This step only needs to be performed once. The image is then binarized. Median ﬁltering: The binarized image is ﬁltered by a 3 × 3 median ﬁlter (Fig. 1d) to eliminate noise and improve the recognition rate. Dilation: The median-ﬁltered image is dilated to connect nearby edges (Fig. 1e). Thinning: The Hilditch method7 is adopted in the thinning process (Fig. 1f). This plays a very important role in improving both the recognition rate and the calculation time, reducing the required resources.

Figures 1a to 1f present examples of edge extraction procedures. 2.3. Crater recognition The general Hough transform was adopted as a core algorithm8 for the recognition of circular or elliptical crater rims. GHT can even detect incomplete ellipses because of its high noise tolerance. The Hough transform identiﬁes straight lines calculated from edge points in the image using the position of the Hough parameter in Hough space. Recognition of ellipses using the Hough transform has been improved. The GHT procedures used in this research were as follows: 1. The tangent of each edge point on the crater rim is determined. The point with the most counts in Hough space is assumed to be a tangent in the image, where each Hough parameter is calculated for a straight line that passes through any two points on the crater rim. 2. The center of the crater is calculated to be at the center of an ellipse. A straight line is determined by connecting the intersection of two tangents and the mid-point of their contact points. This line passes through the center of the ellipse. The most likely intersection of lines for all combinations of tangents is determined as the ellipse center. 3. The diameter of the major and minor axis and the inclination of the major axis are calculated from the ellipse center and edge points pointing to the center. The crater parameter is determined as the point with the most counts among all projected points of calculated parameters in a new Hough space.

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(a)

(b)

(c) Fig. 2. Examples of crater recognition for the DTM image in Fig. 1. a. GHT crater recognition procedures (steps 1 to 3). b. Results after re-ﬁtting (step 4). c. Recognition results from MOLA DTM around Argyre basin (1000 × 500 pixels).

4. The minor axis diameter is improved, as it tends to be shorter using this method. The minor axis diameter is modiﬁed according to the best agreement between the edge extraction image and the new ellipse, where the center, major axis, and inclination of the major axis are ﬁtted as described above. Figures 2a to 2c present examples of crater recognition results. 2.4. Evaluation of this method A total of 101 craters with over 10 pixels on the major axis were detected by this algorithm (see Fig. 2c). A total of 114 craters with over 10 pixels (a total of 309 craters including smaller ones) were detected manually. Therefore, the detection rate of this algorithm was 89%. Figure 3 plots the cumulative size-frequency distribution (CSFD), which is commonly used in crater chronology. The results using automatic

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Fig. 3.

83

Cumulative size frequency distribution (CSFD) plot for the results of Fig. 2c.

recognition and manual counting agree well over all ranges. This indicates that the algorithm can be successfully employed in crater chronology. 3. Classification for Geological Mapping from Textural and Spectral Images 3.1. Overview Recognition of geological units on image data and the production of geological maps are fundamental parts of the remote sensing problem. A single geological unit can be deﬁned as a region with its own particular properties in terms of rocks (materials), topographical or geological structures, relative ages, and other geological features. In the 1960s and 1970s, researchers in lunar science used panchromatic photographs to make lunar geological maps,9 which were produced based on photo-geological interpretation of surface textures and topographic features. Recently, the range of remote sensing data has expanded greatly. Resolution and coverage of image data have increased, and multi-spectral images of the moon have been obtained through modern lunar missions.10 In addition, many techniques for automatic or semi-automatic image classiﬁcation have been developed. If these techniques are eﬀective for the recognition of geologic units in remote sensing data, automatic or semi-automatic data processing could become an important method for producing geological maps of the moon. The purpose of this research was to test these image classiﬁcation techniques with lunar high-resolution images and multi-spectral images

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obtained by the Terrain Camera (TC) and the Multi-band Imager (MI) onboard the KAGUYA lunar explorer. We especially focused on recognition of geologic units by combining textural and spectral features extracted from image data. 3.2. Characteristics of texture and spectra Texture is a small-scale pattern that reﬂects the surface undulation and reﬂectance of the object. It is aﬀected by illumination conditions, where the surface undulation controls the texture at low solar elevation, whereas reﬂectance governs texture at high solar elevation. Pixel variance can reveal textural features through statistical methods. Therefore, a ﬁltering process based on pixel variance was adopted in this research. Usually, diﬀerent materials have characteristic colors and reﬂection spectra. Therefore, diﬀerent materials can usually be distinguished using their spectral features. In this research, the spectral features were derived from multi-spectral image data. The band-ratio is a simple, widely utilized method to identify spectral features.11 Band-ratio images are proxies for the slope of the spectral continuum or for the depth of absorption bands. For the lunar case, 950 nm absorption features represent the contents of maﬁc minerals, and the 750 nm/415 nm ratio shows the degree of space weathering.12 Absorption band depths of appropriate wavelength may be more representative of material type. The k-means clustering algorithm, which is one of the most popular methods for unsupervised image classiﬁcation, was adopted to label pixels based on the textural and spectral features. 3.3. Classification procedures for geological mapping An experimental procedure for the semi-automatic recognition used in this work is as follows: 1. Preparation of high-resolution images (10 m/pixel) observed by the Terrain Camera (TC), as well as preparation of 9-band multi-spectral images (VIS: 20 m/pixel, NIR: 62 m/pixel) as observed by the Multiband Imager (MI). Images are co-located. 2. Positions of the TC and MI images are matched, pixel-by-pixel. 3. The variance image is derived using a ﬁltering process. Each pixel value is replaced by the variance in a square window with a constant area

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centered on the position of the pixel. Calculation is performed for the entire image area. 4. The band-ratio images and/or the absorption band depth images are derived for representative spectral features. In this paper, 750 nm/415 nm and 750 nm/900 nm images were used. 5. Textural and spectral feature maps are normalized in the interval [0, 1]. 6. A k-means clustering algorithm with appropriate k-number is applied for classiﬁcation. The textural feature map and spectral feature maps are used as input data. Figure 4 shows a 750 nm image of a highland area observed by the MI (before calibration) at 120◦ W, 37◦ S, which is about 1000 km south-west of the Orientale basin. The image covers an area of 20 km × 20 km. Ejecta material can be seen as bright rays with a diameter of around 1.4 km, appearing on space-weathered highland anorthosite topsoil. The degree of the space-weathering appears reduced due to the formation of other small craters at a later time. Figure 5a shows a variance map derived from Fig. 4 with a window size of 21 × 21 pixels, which corresponds to 420 × 420 m on the lunar surface. Bright pixels represent high-variance regions, which correspond

Fig. 4. An MI 750 nm band-image at 120◦ W, 37◦ S, about 1,000 km south-west of Orientale basin. Image coverage is 20 km × 20 km.

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(a)

(b)

(c)

Fig. 5. a. Variance image of Fig. 4, where variance window size is 21 × 21 pixels. b. 750 nm/415 nm band-ratio image of the site corresponding to Fig. 4. c. 750 nm/900 nm band-ratio image of site corresponding to b.

1 2 3 4 5 Fig. 6. Results of k-means classiﬁcation map with k = 5. Each color denotes a single category. The category-class color table is shown at the right-hand side of the ﬁgure.

to the existence of craters, and dark pixels indicate low-variance regions. Figures 5b and 5c show the 750 nm/415 nm and 750 nm/900 nm band-ratio images from the MI at the same site as shown in Fig. 4. Figure 6 shows the k-means clustering result of Figs. 5a, b, and c, where pixel values are normalized between 0 and 1 in each image. The k-number is 5, and each class, divided by diﬀering brightness, is shown in the color table in Fig. 6.

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3.4. Result of classification Figure 4 shows the highland test area. The image was captured by the MI before extensive calibration and was derived from the 750 nm band. Figure 5a shows the 21 × 21 pixel window variance image corresponding to Fig. 4. High-variance pixels appear as bright or white features, whereas low-variance pixels appear as dark or black features. Although it is better to use the TC image due to its good resolution, the MI 750 nm band image was used for this analysis, as the algorithm check was the principal objective of this paper. There are many bright patchy, square patterns in Fig. 5a, which are typical variance window patterns corresponding to small bright, spotty craters in the gray highland region. The degree of space-weathering can be seen in the 750 nm/415 nm band-ratio image11 shown in Fig. 5b, where the highly space-weathered area appears as a bright area, whereas a relatively fresh area appears as a dark region. Maﬁc minerals, such as pyroxene and olivine, have an absorption band around 950 nm, which appears as a bright area in Fig. 5c, whereas iron-poor minerals, such as plagioclase, give rise to relatively dark patterns. The results of the k-means clustering method with k = 5 is shown in Fig. 6, where each category-class is shown using the same gray color scale corresponding to the category-class table on the right-hand side of the ﬁgure. Category 1 includes ejecta materials corresponding to the largest-valued variance area in Fig. 5a and the dark area in Fig. 5b. Category 2 corresponds to the small-variance area in Fig. 5a and the dark region of Fig. 5c, which is classiﬁed as an area of strongly space-weathered Fe-poor minerals with small numbers of craters. Category 3 shows less space weathering, whereas category 4 reveals craters with a fresher surface. Category 5 includes crater boundaries, ejecta, and space-weathered topsoil. These results highlight the possibility of using the automatic classiﬁcation of areas based on diﬀerences in freshness, density of craters, and diﬀerences in mineral species.

4. Concluding Remarks The scientiﬁc results of the analyses presented will be published pending the acquisition of further LISM data. We are also developing software for the construction of a global lunar digital elevation model (DEM) and a KAGUYA GIS database system that will be able to visualize data on a lunar map.

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Results of this research are not only applicable to LISM on KAGUYA but can be applied to other planetary explorations and space activities. Many space exploration activities are scheduled in the near future. Observational data analysis is a rapidly expanding ﬁeld as observational equipment such as cameras and detectors, as well as satellite communication technology improves. The importance of automated data analysis, especially fundamental and systematic data analysis, is expected to increase. However, manual analysis and human intuition in the interpretation of data will continue to be necessary. In addition, the use of distributed computing in data analysis, which until recently had been considered diﬃcult, will become increasingly important. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

J. Haruyama et al., Earth Planets Space 60 (2008) 243. T. Matsunaga et al., Geophysical Research Letters 35 (2008) L23201. G. G. Michael, Planetary and Space Science 51 (2003) 563. Y. Sawabe, T. Matsunaga and S. Rokugawa, Advances in Space Research 37 (2006) 21. M. Masotti, S. Falsaperla, H. Langer, S. Spampinato and R. Campanini, Geophysical Research Letters 33 (2006) L20304. L. Bandeira, J. Saraiva and P. Pina, IEEE Trans. Geoscience and Remote Sensing 45 (2007) 4008. R. Honda, Y. IIjima and O. Konishi, Progress of Discovery Science LNAI 2281 (2002) 395. N. Matsumoto, H. Demura and N. Asada, Lunar and Planetary Science Conf. XXXVI 36 (2005) 1995. USGS, http://astrogeology.usgs.gov/Projects/PlanetaryMapping/ S. Nozette, P. Rustan, L. P. Pleasance, D. M. Horan, P. Regeon, E. M. Shoemaker et al., Science 266 (1994) 1835. C. M. Pieters, M. I. Staid, E. M. Fischer, S. Tompkins and G. He, Science 266 (1994) 1844. C. M. Pieters, L. A. Taylor, S. K. Noble, L. P. Keller, B. Hapke, R. V. Morris, C. C. Allen, D. S. Mckay and S. Wentworth, Meteoritics and Planetary Science 35 (2000) 1101.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

MODELING OF THE RADIATION ENVIRONMENT ON THE MOON∗† GIOVANNI DE ANGELIS CNESPS, Istituto Superiore di Sanita’ Rome I-00161, Italy [email protected] FRANCIS F. BADAVI Radiation Group, Christopher Newport University Newport News, VA 23606, USA JOHN M. CLEM Bartol Research Institute, University of Delaware Newark, DE 19716, USA STEVE R. BLATTNIG, MARTHA S. CLOWDSLEY, RAM K. TRIPATHI and JOHN W. WILSON Radiation Group, NASA Langley Research Center Hampton, VA 23681, USA

In view of manned missions to the Moon, for which radiation is one of the greatest challenges to be tackled, it is of fundamental importance to have available a tool, which allows the determination of the particle ﬂux and spectra at any time and at any point of the lunar surface. With this goal in mind, a new model of the Moon’s radiation environment due to Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE) has been developed. Primary particles reach the lunar surface, and are transported all throughout the subsurface layers, with backscattering patterns taken into account. The surface itself has been modeled as regolith and bedrock, with composition taken from the results of the instruments ﬂown on the Apollo missions. Subsurface environments like lava tubes have been considered in the analysis. Particle transport has been performed with both deterministic and Monte Carlo codes with an adaptation for planetary surface geometry. Results are given in terms of ﬂuxes, doses and LET, for most kinds of particles for various kinds of soil and rock chemical compositions.

∗ Work † Work

partially supported by the NASA Research Grant NCC-1-404. partially supported by the Research Grant I/033/06/0 of the Italian Space Agency

(ASI). 89

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1. Introduction Manned space activities have been until present time limited to the nearEarth environment, most of them to low Earth orbit (LEO) scenarios, with only some of the Apollo missions targeted to the Moon. In current times most human exploration and development of space (HEDS) activities are related to the development of the International Space Station (ISS), and therefore take place in the LEO environment. A natural extension of HEDS activities will be going beyond LEO, and reach the asteroids, Mars, Jupiter, Saturn, the Kuiper belt and the outskirts of the Solar System.1 Deep space human exploration activities have been recently boosted in the new US vision for space exploration in the 21st Century, a broad range of human and robotic missions to the Moon, Mars and beyond.2 A ﬁrst step in the Solar System exploration will be the return to the Moon, seen as an outpost on the way to Mars. Journeys to the Moon, as any other space journey outside the protective umbrella of the geomagnetic ﬁeld, will require higher levels of protection from the radiation environment found in the deep space.3 The radiation protection is now one of the two NASA highest concerns and priorities.4 Tools integrating diﬀerent radiation environments with shielding computation techniques especially tailored for deep space mission scenarios are instrumental in view of this exigency.5 So the radiation environment in space, on the surface of Moon and in the lunar regolith need to be known and evaluated for eﬀects on both astronauts and equipment in view of human presence in Moon (see discussions in Refs. [6–11]). The location of the next space outposts, after the LEO space station, will strongly aﬀect the evolution of every future deep space program.12 These outposts along routes to the further Solar System will have quite an important logistic function in the development of deep space mission scenarios.13 The Moon has been thought since long time being an ideal location for such outposts:14 a Moon Base will host scientiﬁc research activities15 and will oﬀer shelter to crews in case of emergencies.16 Precursor missions to manned deep space missions will be operations on the Moon, as well as the construction and operation of a Moon Base (see discussion in Ref. [10]). In view of these manned missions targeted to the Moon (for a review see e.g. Ref. [17]), for which as for Mars missions radiation exposure is one of the greatest problems and challenges to be tackled (Refs. [3, 18]), it is of fundamental importance to have available a tool which allows to know

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which are the particle ﬂux and spectra at any time at any point of the lunar surface, as well as above and below the lunar surface. With this goal in mind, a new model for the radiation environment to be found on the Moon due to Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE) has been developed. This radiation environment is based on the moon model by De Angelis et al.,8−11,19 a detailed description of the lunar regolith and rocks from both the physical and chemical point of view as from a single lunar location, namely the Oceanus Procellarum landing site of the Apollo 12 mission, with the same chemical composition adopted for the whole Moon for both surface and rock layers, chosen as an average of the Apollo 12 surface samples taken at the Oceanus Procellarum landing site. Radiation analysis work was performed with this radiation environment8−11,19−20 for some scenarios and review work in Ref. [21]. In this work the model shown in De Angelis et al.8−11,19 is shown in full and extended. These models have been, are and will be used as a planning tool for most ongoing and future Moon-targeted missions (e.g. LRO, CHANDRAYAAN-1, new NASA manned vehicles, etc.), as well as for the design and development of spacecraft payload instrumentation (e.g. instruments for LRO, the RADOM investigation for CHANDRAYAAN-1, etc.).

2. Particle Environments Models In space radiation analysis, all environments within which a mission is carried out are to be considered.5 The mission departure may take place either from ground-based launch facilities, or from orbital stations located in LEO orbits, and passing through suitable locations of the Earth-Moon dynamical system, like the L1 Lagrangian point.22 The inﬂuence of the terrestrial and circumterrestrial environments are of no importance in lunar missions, given that the Moon itself and the lunar trajectories are well outside of the trapped radiation belts of the Earth magnetosphere,23 so the building of the radiation dose is due to the eﬀects of Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE) through the spacecraft structure, as well as to the eﬀects of the Moon surface on the radiation ﬁelds. A mission scenario needs to be modeled in terms of environmental models, spacecraft trajectory and surface activities description, and dose calculations. The particle environmental models shown here have been already used in lunar radiation activities (e.g. Refs. [6–11, 18–20]). The models for both GCR and SPE adopted in the paper to build the lunar model have been

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provided as constraints, and were not a matter of choice for the paper authors. 2.1. Galactic cosmic rays (GCR) Galactic Cosmic Rays (GCR) originate outside our Solar System in ways not totally clear yet.24,25 They are composed of highly energetic, fully ionized nuclei of all charges from hydrogen to uranium, with a large decrease in the intensity of particles with charge Z higher than 28.26 From interstellar space the GCR enter the Solar System, where they come into contact with the particles of the solar wind, which transports the solar magnetic ﬁeld away from the Sun.27 The distribution of cosmic rays in the heliosphere depends on time, position and particle magnetic rigidity, and complies with the transport equation by Parker,28 a solution of the Fokker-Planck equation in which the inward diﬀusion of galactic cosmic rays is balanced by the solar wind outward convection, assuming a spherically symmetric heliosphere and an isotropic cosmic ray particles ﬂux. Processes included in the equation are the GCR convection by the solar wind, their drift in the inhomogeneous heliospheric ﬁeld, the anisotropic diﬀusion in the interplanetary magnetic ﬁeld irregularities, and the adiabatic energy losses caused by the divergence of these irregularities.29,30 The time-dependence due to solar activity of the variations of the solar wind velocity and diﬀusion coeﬃcient is taken into account with the statistical model developed by Wilson et al.31,32 relating the sunspot number to the cosmic ray induced neutron monitor count rate measured at the Deep River location, Ontario, Canada. The GCR cosmic ray ﬂux computations are performed in this work, as in previous work,32,33 with the simpliﬁed model by O’Neill.34 Studies of the solar modulation patterns performed by using data from Pioneer, Voyager, and IMP spacecraft show variability with solar cycle for some restricted energy ranges, but a good representation of the gross GCR behavior is given for all energies above 70 MeV.35 No rescaling for solar distance is needed for the spectra for GCR at 1 AU from the Sun for solar maximum and minimum since the heliocentric distance of the Moon and the Earth is the same. 2.2. Solar particle events The Sun has been known for long time as a proliﬁc source of energetic particles, with the ﬁrst detection of solar particles by Forbush36 as early as in 1946 leading to the name ‘solar cosmic rays’. Various short-term cosmic

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ray ﬂux increases have been observed shortly afterwards at the ground level in direct association with solar ﬂares,37−39 mostly as ground level ionization rate increases, and the largest event, that of 23 February 1956, was analyzed in detail through neutron monitor data.40,41 The analysis of the particle ﬂux of the 23 February 1956 solar particle event showed that only the solar magnetic ﬁeld was capable of accelerating protons in the amounts and to the energies detected in the event.42 This conclusion is still valid today whether or not the particles are produced within solar ﬂares or within coronal mass ejections, forming a bow shock transition region which the most recent opinions consider the most likely place where particle acceleration occurs, with the energy in both cases from the same magnetic ﬁeld, even if most solar particle events seem to be the result of ﬁrst-order diﬀusive shock acceleration.43−45 In order to take into account solar particle events in space mission radiation shielding analysis, three main issues are to be considered, namely ﬂuence, frequency distribution, expected ﬂux and energy spectra, and the largest likely event to be encountered during the mission.46 The greatest concern given by Solar Particle Events is due to our inability to predict their occurrence.47 Only few events of very large size can give appreciable consequences for deep space radiation shielding analysis,46 namely events with ﬂuence of protons with energy E > 10 MeV larger than 3 × 107 /cm2 . The rate of occurrence of such events is discussed in Ref. [48]. An average event could provide a neutron monitor count rate increase lower than a factor 1.5, whereas in the event of 23 February 1956, the largest yet observed, the neutron monitor count rates increased of 36 times above the background level. The second largest event ever observed was that of 29 September 1989, with a measured neutron monitor count rate 370 percent over background.49 No other events of such magnitude have ever been observed, apart from the 12 November 1960 and the August 1972 events,50 indeed having narrower energy spectra compared with the 1989 event, especially with respect to higher energies, the most relevant in this respect.51 From a model by Nymmik52 it comes out that the event of 29 September 1989 just for protons with energy E > 30 MeV had a ﬂuence of 1.4 × 109 /cm2 protons, so about 50 times larger than the threshold mentioned above. Due to the exceptionality of the 1956 event, and the comparability of other large events, and the more extended spectrum, compared to the other events, a worst-case strategy based on a multiple of the 29 September 1989 event seems to be quite suitable to the needs of radiation shielding analysis.53

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The radial dependence of the particle ﬂux of SPE is very poorly known, and seems to depend on the characteristics of the interplanetary magnetic ﬁeld through which these particles go,46 with events generated by the shock regions of a CME may decrease little between 1 AU to Mars orbit or even further, whereas the Gauss law (i.e. r−2 ) seems appropriate at large distances from the sun.7 The SPE particles are generally controlled all throughout the solar system by the ﬂux tubes of the solar wind Archimedes spiral,26 so for a well ﬁeld line connected event the particle ﬂux radial dependence46 should be as steep as r−3.3 . For the needs of a radiation shielding analysis, an event four times larger than the 29 September 1989 event31,53 which is likely to be exceeded only 1 percent of the time54 is used, with a simple inverse r (i.e. r−1 ) dependence for every spacecraft distance from the sun, to obtain an upper limit for the dose given by the event occurrence. For lunar missions, the same spectrum as for Earth-orbiting missions is assumed, since the heliocentric distance of the Moon and the Earth is the same. 3. Planetary Environmental Models 3.1. Planetary surface and subsurface environments A planetary target body, i.e. a planet or one of its satellites, needs to be modeled to assess the radiation dose a crew will intake during the surface activities. If the body is atmosphereless, it has to be modeled in position (astrometry), size, topography, and surface chemical composition, to get the atomic surface composition needed for transport computation, to evaluate the backscattering radiation component, especially neutrons. If the target body has an atmosphere, a proﬁle of the atmosphere in terms of density, temperature and composition vs. altitude (and time) should be provided, to compute how the primary particle ﬂuxes are modiﬁed by the interaction with the atmosphere. The knowledge of the target body topography is particularly important in the case an atmosphere is present, to know down to which surface altitude the eﬀects of the atmosphere have to be taken into account. In the Solar System bodies (see, e.g. Ref. [55]) two kinds of surface composition are prevalent, namely a silicatic rocky composition on the bodies of the Inner Solar System (i.e. Mercury, Venus, the Earth, the Moon, Mars and its satellites, asteroids), and a mostly icy (water ice, methane ice, ammonia ice) composition of the solid bodies of the Outer Solar System (satellites of Jupiter, Saturn, Uranus, Neptune, Pluto with his moon Charon, comets, the Kuiper Belt and all Trans-Neptunian

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objects). The giant planets of the Outer Solar System have a gaseous composition all along their body (Jupiter, Saturn, Uranus, Neptune), and seem not to have any solid surface56 on which any surface activity looks to be practicable. Interesting phenomena take place on the surface of bodies with locally mixed rock/ice composition, like in planets with seasonal or perennial volatile-generated polar caps, like e.g. the carbon dioxide ice and water ice caps on Mars,17 as well as at any interface, like atmospheresurface, space-surface, surface-subsurface, regolith-bedrock, etc.57 Neutron backscattering from silicatic surface is important particularly at the lower energies,58 whereas the interaction with ices produces far less neutrons.7 In free space, the particle environment is the same as shown above. At the surface, the particle environment undergoes two main modiﬁcations with respect to that found in free space: the primary particles are limited to come only from above the surface, so the solid angle of acceptance of primary particles is limited to 2π, and it is not the full 4π solid angle like in the free space case. In some cases, due to local topography features like valleys or craters, the solid angle might be even smaller than 2π.59 Moreover, the backscattering component, mostly neutrons, created by the interaction between the incoming particles and the nuclei composing the surface, is to be added to the particle ﬂux at the surface. For atmosphereless bodies this component is about 1% of the dose given by GCR alone,33 with little dependence on the composition of the surface materials. For target bodies with an atmosphere, a proﬁle of the atmosphere in terms of density, temperature and composition vs. altitude (and time) should be provided, to compute how the primary particle ﬂuxes are modiﬁed by atmospheric interactions. At the surface the modiﬁed particle ﬁelds interact with the nuclei composing the surface, whose physical conditions and chemical composition should be known with depth in order to evaluate the backscattered radiation. 3.2. The lunar physico-chemical model This lunar physico-chemical environmental model has been developed in successive phases.5,8−11,19 The Moon surface has been modeled as a 5 m regolith layer, followed by rock. The regolith density proﬁle has been obtained by combining data from groundbased radiophysical measurements and from in-situ analysis data from the Luna, Surveyor and Apollo missions,60 whereas for the rock layer a constant value of 3.3 g/cm3 has been used as typical of mare basalt rock.55 The analysis is shown in De

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Angelis et al.8,9 The same composition has been adopted for both surface and rock layers, and has been chosen as an average of the Apollo 12 surface samples61,62 taken at the Oceanus Procellarum landing site (see8−9,19 for the analysis). Two diﬀerent scenarios have been considered, namely a Lunar Night (Tsurface = 100 K) and a Lunar Day (Tsurface = 400 K) scenario, with temperature proﬁles for regolith and rock extrapolated from data from the Apollo 15 and Apollo 17 landing sites measurements.63−65 The primary eﬀect of the temperature variation is seen in the neutron spectrum near thermal energies, and is of no consequences to human protection (see Refs. [8, 9] for the analysis). The lunar subsurface environment has been described in Refs. [8, 9]. 4. Radiation Transport Computing Tools The computations for the evaluation of the lunar radiation environments has been performed in a two-fold way: deterministic and Monte Carlo techniques. As for the former, transport of positive charged particles, i.e. protons and heavier ions, have been performed with a current version of the NASA Langley Research Center (LaRC) heavy ion deterministic code HZETRN,66 which provides particle energy spectra at predeﬁned positions in the material layer of interest as well as the pertinent dosimetric quantities, with energy deposition from both primary and secondary particles, including nuclear target fragments, accounted for. The materials are modeled as a thickness ﬁle including distance of each material traversed in the order progressing from the outer boundary inward toward the target point. With the speciﬁed environment, i.e. the speciﬁed charged particle ﬂux boundary conditions, the transport code is used to generate dose vs. depth functions for each material under consideration over a range of thickness adequate for interpolation for the shielding analysis. Primary particles at planet distances at intermediate time between solar minimum and maximum epochs are obtained as discussed above, through the simpliﬁed model by O’Neill.34 The code allows also for the evaluation of doses as well as other radiation safety-related quantities. As for the Monte Carlo technique, all known particles, namely protons, neutrons, deuterons, alpha particles, heavy ions, electrons, photons, pions, muons, and other ones, have been transported with the three-dimensional Monte Carlo transport code FLUKA.67 The environment has been modeled in terms of combinatorial geometry as free space, surface, regolith and bedrock. The evaluation of the radiation safety-related quantities, used both in environmental

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assessments and in health-based procedures68,69 namely the Eﬀective Dose (E) and the Ambient Dose Equivalent (H∗ 10), has been performed with the conversion coeﬃcients by Pelliccioni70 from particle ﬂuence. The physical quantity Absorbed Dose (D) has been also obtained, by inversely using the ICRP6071 radiation-weighting factors wr . The computations for Monte Carlo transport techniques have been performed only for solar minimum cosmic ray conditions, in order to obtain an upper value for radiation ﬂuxes and doses, because to very time-consuming computations, i.e. 20 days CPU time on a dedicated ALPHA-DEC workstation, whereas on the same machine the deterministic techniques takes about 10 minutes to obtain very similar results: the two datasets for protons and neutron ﬂuxes diﬀer at most 5% and 8% from analogous datasets resulting from deterministic techniques. As for the initial conditions, in the Monte Carlo computation a primary spectrum of GCR (p, α, HZE) for Solar Minimum conditions modulated at 510 MV Heliocentric Potential, very close to 1977 solar minimum (with solar deceleration parameter 428 MV), fully explained in Ref. [72], has been adopted as background radiation, and a spectrum with particle ﬂuxes equivalent to four times the intensity of the 29 September 1989 event53 has been adopted for Solar Particle Events (p). All primary particles heavier than protons have been approximated as individual nucleons, e.g. He4 nuclei have been transported as 4 individual protons. In this latter analysis the radiation proﬁles given by the natural and induced radioactivity (α, β, γ) have been also taken into account. 5. Results Results have been obtained with both deterministic and Monte Carlo transport techniques. For sake of brevity it is impossible to show all available results for both GCR and SPE environments for both the computational techniques. Just few examples are shown here. As for deterministic techniques, the radiation environment at a location at the surface of the Moon is shown for GCR at solar 1977 solar minimum and 1990 solar maximum in Fig. 3 and regarding SPE in Fig. 4 for the solar particle event of September 29, 1989. The particles with ‘Z = 0’ in both ﬁgures are the albedo neutrons generated by the interaction of the primary particles with the lunar surface. Computations for GCR-induced backscattered neutrons shows that these particles are present at least up to a depth of 2.5 m in the regolith, whereas after 80 cm depth within regolith there are no backscattered neutrons due to SPE particles. For GCR

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Fig. 1. GCR particle environment during the 1977 solar minimum (full lines) and the 1990 solar maximum (dashed lines) on the lunar surface (results from deterministic technique).

and 1989 SPE results are shown for BFO dose equivalents respectively in Figs. 3 and 4. Results from the Monte Carlo technique are next shown. All known particles have been transported through the lunar subsurface layers. Fluences for protons, neutrons, pions along with results with depth for Eﬀective Dose (E) are shown in Figs. 5–8 for GCR. The Monte Carlo results show so similar to those obtained with the deterministic technique. Particles have been transported all along the layers, but after 7 m the ﬂuxes are greatly reduced. For SPE no backscattered neutrons are found after an average of about 80 cm depth, conﬁrming this way the results obtained with deterministic techniques. The lack of backscattered neutron also means that the regolith can work as a reasonably good shielding material for protection

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Fig. 2. The lunar surface environment during the September 1989 SPE (deterministic technique).

from SPE hazards, and that a greater regolith thickness is needed for protection of crewmembers and habitats from GCR hazards (see discussions in Refs. [6,8–11]).

6. Comparison with Modeling Results by Other Authors The model shown above cannot be accurately compared with any other model developed by other authors because there is no other time-dependent lunar regolith radiation model available.73 The only other results are those by Simonsen,74 in which a simplistic model for the surface is implemented with only a ﬁxed value for the density and a regolith 1m deep. Their surface values are in disagreement with recent lunar regolith models (see e.g.,75 and references therein). This model74 unfortunately has

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Fig. 3. Annual BFO dose equivalent due to GCR during the 1977 solar minimum (full lines) and the 1990 solar maximum (dashed lines)on the lunar surface (results from deterministic technique).

been widely used in lunar radiation analyses related to risk and doses evaluation.76−80 7. Comparison with Experimental Results Many studies have been devoted to the lunar radiation environment, from the observation from Explorer 35, Apollo, Clementine, Lunar Prospector, Geotail and WIND spacecraft.73 The existing data provide considerable insight into the lunar plasma and ﬁeld environment, crustal magnetic ﬁelds, lunar surface charging, lunar dust, lunar atmosphere (including remote detections), SPE events, and even astronaut dosimetry.81 There is surface neutron information from the Lunar Prospector,82 plus surface neutron models (discussed above). There is also relevant information on surface composition from Clementine, Lunar Prospector, and the archive of lunar samples (Ref. [73], and references therein). However, in spite

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Fig. 4. BFO dose equivalent on the lunar surface due to the September 1989 SPE (deterministic technique).

of the large amount of information available, there are still large gaps in understanding the lunar environment, because the information is not comprehensive enough. Moreover, there is no experimental validation of the existing radiation models, either in lunar orbit or on the lunar surface, as there was for the ISS-related LEO radiation environment.83 The ﬁrst measurements to validate the radiation environmental models will be those that the instrument RADOM will perform onboard the Chandrayaan-1 polar orbiter spacecraft that the Indian Space Agency ISRO will soon launch. Further measurements on both orbiters and landers will be needed in order to fully validate the radiation environmental models. 8. Conclusions A new model for the radiation environment to be found on the Moon (above, on and below the surface) due to Galactic Cosmic Rays (GCR), Solar Particle Events (SPE) and backscattering eﬀects has been developed

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Fig. 5. Proton diﬀerential ﬂux due to GCR in lunar regolith (results from Monte Carlo technique).

Fig. 6. Neutron diﬀerential ﬂux due to GCR in lunar regolith (results from Monte Carlo technique).

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Fig. 7. Pion diﬀerential ﬂux due to GCR in lunar regolith (results from Monte Carlo technique).

Fig. 8. Eﬀective dose due to GCR in lunar regolith (results from Monte Carlo technique).

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at the NASA Langley Research Center. A good agreement is shown between results from deterministic and Monte Carlo radiation transport techniques. The huge diﬀerences in the time and eﬀort involved in the deterministic and Monte Carlo approaches deeply favor the use of the deterministic approach in computations for scientiﬁc and technological space radiation analyses. This Moon Radiation Environment Model will be tested against the data from spacecraft instruments in the near future. Acknowledgments The authors are indebted with M. Caldora, K.Y. Fan, S.H. Husch, G.D. Qualls and W.A. Mickley for their invaluable help. This work has been performed under the ASI Grant I/033/06/0 and NASA Research Grant NCC-1-404. This work is dedicated to the so dear memory of Diana Bondanini. References 1. S. J. Hoﬀman and D. I. Kaplan, NASA SP-6107 (1997). 2. G. W. Bush, A Renewed Spirit of Discovery — The President’s Vision for U.S. Space Exploration, Washington (2004). 3. F. A. Cucinotta, W. Schimmerling, J. W. Wilson, L. E. Peterson, G. D. Badhwar, P. B. Saganti and J. F. Dicello, Radiat. Res. 156 (2001) 682. 4. S. O’Keefe, Administrator O’Keefe pitches his vision for NASA, http://www.spaceﬂightnow.com/news/n0203/27okeefe/(2002). 5. G. De Angelis, M. S. Clowdsley, J. E. Nealy, R. C. Singleterry, R. K. Tripathi and J. W. Wilson, in Proceedings of the Space Technology and Application International Forum (STAIF-2003) ‘Expanding the Frontiers of Science’, edited by M. El-Genk, AIP Conference Proceedings, New York (2003), pp. 972. 6. J. W. Wilson, J. Miller, A. Konradi and F. A. Cucinotta (Eds.), NASA CP3360 (1997). 7. J. W. Wilson, J. E. Nealy, G. De Angelis, M. S. Clowdsley and F. F. Badavi, in Proceedings of the Space Technology and Application International Forum (STAIF-2003) ‘Expanding the Frontiers of Science’, edited by M. El-Genk, AIP Conference Proceedings, New York, pp. 993 (2003). 8. G. De Angelis, J. W. Wilson, M. S. Clowdsley, J. E. Nealy, D. H. Humes and J. M. Clem, J. Rad. Res. 43 (2002) S41. 9. G. De Angelis, J. W. Wilson, M. S. Clowdsley, J. E. Nealy, D. H. Humes and J. M. Clem, Proc. Lunar Plan. Sci. Conf. XXXIII, Lunar and Planetary Institute, Houston TX (2002), pp. 1417. 10. G. De Angelis, F. F. Badavi, J. M. Clem. S. R. Blattnig. M. S. Clowdsley, J. E. Nealy, R. K. Tripathi and J. W. Wilson, Nucl.Phys. B 166 (2007) 184.

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11. G. De Angelis, F. F. Badavi, J. M. Clem, S. R. Blattnig, M. S. Clowdsley, J. E. Nealy, R. K. Tripathi and J. W. Wilson, Paper SAE-2005-01-2831, Society for Automotive Engineering (SAE) (2005), pp. 1. 12. G. R. Babb, H. P. Davis, P. G. Phillips and W. R. Stump, in Lunar Bases and Space Activities of the 21st Century, edited by W. W. Mendell, Lunar and Planetary Institute, Houston TX (1985), pp. 125. 13. P. W. Keaton, in Lunar Bases and Space Activities of the 21st Century, edited by W. W. Mendell, Lunar and Planetary Institute, Houston TX (1985), pp. 141. 14. R. D. Johnson and C. Holbrow (Eds.), NASA SP-413 (1977). 15. M. B. Duke, W. W. Mendell and P. W. Keaton, LALP 84-43, Los Alamos National Laboratories, Los Alamos NM (1984). 16. F. Horz, in Lunar Bases and Space Activities of the 21st Century, edited by W. W. Mendell, Lunar and Planetary Institute, Houston TX (1985), pp. 405. 17. M. B. Duke, S. J. Hoﬀman and K. Snook, NASA TP-2003-212053 (2003). 18. G. De Angelis, M. S. Clowdsley, R. C. Singleterry and J. W. Wilson, Adv. Space. Res. 34 (2004) 1328. 19. G. De Angelis, J. W. Wilson, R. K. Tripathi, M. S. Clowdsley and J. E. Nealy, IAC 2002 — Paper IAC-02-IAA.13.P.09 (2002). 20. M. S. Clowdsley, G. De Angelis, F. F. Badavi et al., in Proceedings of the Space Technology and Application International Forum (STAIF-2003) ‘Expanding the Frontiers of Science’, edited by M. El-Genk, AIP Conference Proceedings, New York, pp. 1034 (2003). 21. R. K. Tripathi, F. F. Badavi, J. W. Wilson and G. De Angelis, Adv. Space. Res. 37 (2006) 1749. 22. G. R. Woodcock, in Lunar Bases and Space Activities of the 21st Century, edited by W. W. Mendell, Lunar and Planetary Institute, Houston TX (1985), pp. 111. 23. J. G. Roederer, in Magnetospheric Physics, edited by D. J. Williams and G. D. Mead, American Geophysical Union, William Byrd Press, Richmond VA (1969), pp. 77. 24. D. L. Hall, M. L. Duldig and J. E. Humble, Space Sci. Rev. 17 (1996) 401. 25. W. Droege, in Cosmic Rays and Earth, edited by J. W. Bieber, E. Eroshenko, P. Evenson, E. O. Flueckiger and R. Kallenbach, Kluwer Academic Publisher, Dordrecht, The Netherlands (2000), pp. 121. 26. G. D. Badhwar, in Risk Evaluation of Cosmic-Ray Exposure in Long-Term Manned Space Mission, edited by K. Fujitaka, H. Majima, K. Ando, H. Yasuda, and M. Suzuki, pp. 17, Kodansha Scientiﬁc Ltd., Tokyo, Japan (1999). 27. G. D. Badhwar and P.M. O’Neill, Adv. Space Res. 17 (1996) 7. 28. E. N. Parker, Planet. Space Sci. 13 (1965) 9. 29. A. Belov, in Cosmic Rays and Earth, edited by J. W. Bieber, E. Eroshenko, P. Evenson, E. O. Flueckiger and R. Kallenbach, pp. 79, Kluwer Academic Publisher, Dordrecht, The Netherlands (2000). 30. V. K. Balasubrahmanyan, E. Boldt and R. Palmeira, J. Geophys. Res. 72 (1967) 27.

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54. M. A. Xapsos, J. L. Barth, E. G. Stassinopoulos, E. A. Burke and G. B. Gee, NASA/TP-1999-209763 (1999). 55. V. S. Safronov, Cosmochemistry of the Moon and Planets, Nauka Publishers, Moscow, USSR (1975). (In Russian) 56. J. S. Lewis, Physics and Chemistry of the Solar System, Academic Press, San Diego CA (1997). 57. G. De Angelis, J. E. Nealy, M. S. Clowdsley, R. K. Tripathi and J. W. Wilson, Adv. Space. Res. 34 (2004) 1395. 58. J. W. Wilson, M. H. Y. Kim, M. S. Clowdsley, J. H. Heinbockel, R. K. Tripathi, R. C. Singleterry, J. L. Shinn and R. Suggs, Mars Surface Ionizing Radiation Environment: Need For Validation, paper presented at the Workshop on ‘Mars 2001: Integrated Science in Preparation for Sample Return and Human Exploration’, Lunar and Planetary Institute, LPI Contribution No. 991, Houston, TX, October, 2–4 (1999). 59. L. C. Simonsen, J. E. Nealy, L. W. Townsend and J. W. Wilson, NASA TP-2979 (1990). 60. I. I. Cherkasov and V. V. Shvarev, Lunar Soil Science, Nauka Publishers, Moscow, USSR (1975). (In Russian) 61. Anonymous, Apollo 12 Preliminary Science Report, NASA SP-235 (1970). 62. Warner, J., Apollo 12 Lunar Sample Information, NASA TRR-353 (1970). 63. Anonymous, Apollo 15 Preliminary Science Report, NASA MSC SP-289 (1972). 64. Anonymous, Apollo 17 Preliminary Science Report, NASA JSC SP-330 (1972). 65. V. N. Zharkov, Internal Structure of Earth and Planets, Nauka Publishers, Moscow, USSR (1983). (In Russian) 66. J. W. Wilson, F. F. Badavi, F. A. Cucinotta, J. L. Shinn, G. D. Badhwar, R. Silberberg, C. H. Tsao, L. W. Townsend and R. K. Tripathi, NASA TP3495 (1995). 67. A. Fass` o, A. Ferrari, A. Ranft, P. R. Sala, G. R. Stevenson and J. M. Zazula, Nucl. Instr. Meth. Phys. Res. A 332 (1993) 459. 68. H. Yasuda and K. Fujitaka, J. Radiat. Res. 42 (2001) 57. 69. M. Kramer, J. Radiat. Res. 42 (2001) 39. 70. M. Pelliccioni, J. Nucl. Scie. Technol. Suppl. 1 (2000) 854. 71. ICRP, Publication N. 60, Annals of the ICRP 21 (1–3), Pergamon Press, Elmsford NY (1991). 72. J. M. Clem, G. De Angelis, P. Goldhagen and J. W. Wilson, Adv. Space Res. 32(1) (2003) 27. 73. NCR, Space Radiation Hazards and the Vision for Space Exploration: Report of a Workshop, The National Academy Press, Washington DC (2006). 74. L. C. Simonsen, in Shielding Strategies for Human Space Exploration, edited by J. W. Wilson, J. Miller, A. Konradi, and F. A. Cucinotta, pp. 43, NASA CP-3360, NASA Langley Research Center, Hampton VA, USA (1997). 75. P. Eckart, The Lunar Base Handbook, McGraw Hill, New York NY, USA (1999).

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76. F. A. Cucinotta, M. H. Y. Kim and L. Ren, Managing Lunar and Mars Mission Radiation Risk. Part I: Cancer Risk, Uncertainties, and Shielding Eﬀectiveness, NASA/TP-2005-213164, NASA Headquarters, Washington DC, USA (2005). 77. F. A. Cucinotta, M. H. Y. Kim and L. Ren, Managing Lunar and Mars Mission Radiation Risk. Part II: Non-Cancer Risk, Uncertainties, and Shielding Eﬀectiveness, NASA Headquarters, Washington DC, USA, in press (2008). 78. M. H. Y. Kim, A. Ponomarev, W. Atwell and F. A. Cucinotta, Space Radiation Risk Assessment for Future Lunar Missions, NASA/JSC-200716627, NASA JSC, Houston TX, USA (2007). 79. M. H. Y. Kim, M. J. Hayat, A. H. Feivelson and F. A. Cucinotta, Evaluation of Risks from the Lunar and Mars Radiation Environments, NASA/JSC2008-9783, NASA JSC, Houston TX, USA (2008). 80. M. H. Y. Kim, M. J. Hayat, H. N. Nounu, A. H. Feivelson and F. A. Cucinotta, Minimizing Astronauts’ Risk from Space Radiation during Future Lunar Missions, NASA/JSC-2007-29991, NASA JSC, Houston TX, USA (2007). 81. H. J. Schaefer, E. V. Benton, R. P. Henke and J. J. Sullivan, Radiat. Res. 49(2) (1972), 245. 82. W. C. Feldman, B. L. Barraclough, S. Maurice, R. C. Elphic, D. J. Lawrence, D. R. Thomsen and A. B. Binder, Science 281(5382) (1998) 1489. 83. J. E. Nealy, J. E., F. A. Cucinotta, J. W. Wilson, F. F. Badavi, Ts. P. Dachev, B. T. Tomov, S. A. Walker, G. De Angelis, S. R. Blattnig and W. Atwell, Adv. Space Res. 40 (2007) 1593.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

TELESCOPE OF EXTREME ULTRAVIOLET BOARDED ON KAGUYA: SCIENCE FROM THE MOON ICHIRO YOSHIKAWA∗ , GO MURAKAMI, FUKUHIRO EZAWA, KAZUO YOSHIOKA and YUKI OBANA Department of Earth and Planetary Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, 113-0033, Japan ∗ [email protected] MAKOTO TAGUCHI Department of Physics, Rikkyo University, 3-34 Nishiikebukuro, Toshima, Tokyo, 171-8501, Japan ATSUSHI YAMAZAKI, SHINGO KAMEDA and MASATO NAKAMURA Institute of Space and Astronautical Science, 3-1-1 Yoshinodai, Sagamihara, Kanagawa, 229-8510, Japan MASAYUKI KIKUCHI National Institute of Polar Research 9-10-1 Kaga, Itabashi, Tokyo, 173-8515, Japan MASATO KAGITANI and SHOICHI OKANO Planetary Plasma and Atmospheric Research Center, 6-3 Aramaki-aza-aoba, Aoba, Sendai, 980-8578, Japan KAZUO SHIOKAWA Solar-Terrestrial Environment Laboratory, Nagoya University, Furo-cho, Chikusa, Nagoya, 464-8601, Japan WATARU MIYAKE Department of Aeronautics and Astronautics, Tokai University, 1117 Kitakinme, Hiratsuka, Kanagawa, 259-1292, Japan [email protected]

We have succeeded in observations by the Telescope of Extreme Ultraviolet (TEX) aboard Japan’s lunar orbiter KAGUYA to characterize the evolution of the Earth’s plasmasphere. The view aﬀorded by the KAGUYA orbit encompasses the plasma distribution in a single exposure, enabling us to 109

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examine for the ﬁrst time the globally-averaged properties of the plasmasphere from the side (meridian) view. We focus on a study period that began with a likely moderate erosion event of plasma patches in a geomagnetically disturbed period, and follow reﬁlling of plasma from the upper ionosphere. The Earth’s plasmasphere grew up to saturated level at the rate of approximately 1,600 km per day to 4,800 km per day on the equatorial plane. From the “side view” of the Earth, a speciﬁc magnetic ﬂux tube with cold dense plasmas was seen and likely moved to outer magnetosphere, even while geomagnetic activity was low. From the moon, we are studying the terrestrial plasmas in the vicinity of the Earth. This is called “Geoscience from the Moon”.

1. Introduction The world ﬁrst’s plasmaspheric images were taken by a small EUV scanner boarded on Planet-B (Nozomi) spacecraft.1,2,3 It proved that plasmaspheric EUV emission is bright enough to be taken in snapshots, if new generation of optics is employed.4,5 Then, the knowledge from the Planet-B mission encourages us to build global images of the terrestrial plasma distribution, i.e. plasmasphere, polar wind, and plasma sheet.6−8 Later, the Imager for magnetopause-to-Aurora Global Exploration (IMAGE) mission took consecutive images of the evolution of the terrestrial plasmasphere from aerial view.9 At the stage also, we have gained our understanding of the plasmasphere. For example, Murakami et al. [2007] investigated the plasmaspheric response time to the solar wind electric ﬁeld which was measured by solar wind monitor (ACE satellite).10 The result is consistent with time scale derived from the ionospheric observations on the ground stations. They concluded that the electric ﬁeld penetrates from the magnetopause to the inner magnetosphere through the ionosphere. This study has become feasible by using global images of the plasmasphere. The technological development to visualize EUV radiations from the terrestrial plasmas is being in progress.11,12 Based on two rocket experiment heritages,13,14 we have built the second-generation extreme ultraviolet telescope for Japanese lunar mission (KAGUYA). The KAGUYA was launched by the H-IIA rocket in 2007 to be put into the orbit around the moon. In KAGUYA project, we carry out the scientiﬁc observations of the moon, at the moon, and from the moon. The Upper atmosphere and Plasma Imager (UPI) on KAGUYA takes 2-D visible and EUV images around the Earth. Two telescopes are boarded; one is Telescope for VISible light (UPI-TVIS), and the other is our Telescope for EXtreme ultraviolet light (UPI-TEX). The UPI-TVIS imager detects the four visible airglow

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emissions to take auroral images around both of Earth’s polar regions, and the UPI-TEX imager detects the resonance scattering emissions of oxygen ion (O II: 83.4 nm) and helium ion (He II: 30.4 nm) to take images of near-Earth plasmas.15 In this paper we report the ﬁrst light of the TEX instrument, i.e. the plasmasphere from the moon.

2. Observation Window Imaging of the near-Earth plasma requires global ‘snapshots’ with wide ﬁeld-of-view (FOV). KAGUYA provides us an ideal platform that commands a panoramic view of geospace. Our telescope of extreme ultraviolet is mounted on 2-axis gimbal system together with Telescope of Visible light (TVIS).15 Rotation around the azthumal axis cancels the drift and rotational motions of the satellite to keep the Earth in the center of the image. Elevation axis compensates the orbital inclination of the moon. The UPI-TEX instrument is a type of normal-incidence telescope with a split thin metal ﬁlter, which is made of Aluminum/Carbon and Indium, in order to detect the resonance scattering emissions of helium ions (He II: 30.4 nm) and oxygen ions (O II : 83.4 nm). The KAGUYA satellite orbits around the Moon with an orbital period of 2 hrs. Therefore, TEX has an observation window every 2 hr, but observation must satisfy geometrical conditions. Figure 1 displays geometry among the Earth, moon, and the satellite, and shows the observation conditions. Moon changes its position around the Earth due to the age. The vertical line across the moon indicates the orbit of KAGUYA. We can turn on the instrument in the conditions that (1) KAGUYA is in sight from the Earth. (2) KAGUYA is in umbra of moon to reduce stray light to UPI. (3) The umbra period is longer than 15 minutes, because UPI needs intermission to rewind along the azimuthal axis every orbit. It is noted that TVIS observation needs one more criterion, i.e. (4) less than half of Earth’s disk is sun-shined. Figure 2 shows moon age and beta angle (upper panel), the lunar longitude beneath KAGUYA satellite against Day-of-Year (DOY) (middle panel), and the umbra period during one orbit (lower panel). The beta is deﬁned by the angle between the orbital plane of KAGUYA and solar direction. It is noted that the moon faces the same surface to the Earth so that district between 71 to 290 degrees in lunar longitude is always in sight from the Earth. This criterion is described in the middle panel.

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Fig. 1. Geometry among the Earth, Moon, and the KAGUYA orbit. TEX starts to observe in the conditions that (1) KAGUYA is in sight from the Earth. (2) KAGUYA is in umbra of moon. (3) the umbra period is longer than 15 minutes. TVIS needs one additional condition that less than half of the Earth is sun-shined. The two telescopes are turned oﬀ, while apparent angular diﬀerence between the Earth and sun is less than 20 degree.

After the gimbal deployment in October 2007, we had primary function checks of the instrument and Earth-tracking system from the end of January to February. The ﬁrst light from the Earth came in March. 3. The First Light After the primary function checks of TEX instrument and gimbal system, we had the ﬁrst opportunity to turn on the instrument on 30 March 2008. Since the ﬁrst snapshot was taken on March 30, TEX observed the plasmasphere for 3 consecutive days (From March 30 to 1st April 2008). During this period the geomagnetic activity was exceptionally low. A geomagnetic storm (Dst < −40 nT) occurred on 26 March 2008. It was

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Fig. 2. Moon age and beta angle (upper panel), the lunar longitude beneath KAGUYA against Day-of-Year (DOY) (middle panel), and the umbra period during an orbit (lower panel). The ﬁrst light was available on 30 March.

Fig. 3. EUV polar arc viewed from the lunar orbit. The right side of the disk is the dayside and illuminated by the direct sun light. The black-while boundary is the terminator. The southern arc is identiﬁed around the south magnetic pole. Especially, the nightside arc is clearly found due to low background illumination (See the yellow arrow).

likely that the plasmasphere was contracted to lower L-shells. The following period was the best time to study plasmasphere reﬁlling. The ﬁrst snapshot of the Earth is shown in Fig. 3, which shows an EUV polar arc. The TEX instrument is not designed for the study of atmospheric

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glow, but some emissions do fall within its band-pass. Although a portion of this light may be due to emissions within the TEX band-pass at 30.4 nm, it seems likely that much of it due to emissions at longer wavelengths such as the O+ line at 53.9 nm. TEX has unexpectedly imaged the southern EUV polar arc with the intensity of 20 Rayleigh. Figure 4 shows a schematic drawing of geomagnetic ﬁeld lines from the perspective view of KAGUYA. We should note that a 2-dimensional view of the plasmasphere is not dipole-like, but the outer boundary is elliptic, because the brightness reﬂects the column density along the lineof-sight of the measurement. Figure 5 shows 3 consecutive observations of the plasmasphere. The observations were made with an Al/C ﬁlter and a readout area consisting of 128 pixels by 64 pixels. The Earth is located at the center of panel. The local time of the foot print of selected geomagnetic ﬁeld lines is indicated together with the L-shell value. The shadow of the Earth extends down to the left. A prominent feature seen in the panel is a pattern of plasma distribution in the duskside of the Earth (behind the Earth on the panel). We can see the duskside bulge, a main characteristics of the plasmasphere, in all panels. The plasmasphere contracted to the Lshell of 4 on the ﬁrst day (30 March 2008), but and expanded up to the L-shell of 4.5 on 31 March.

Fig. 4. View of the geomagnetic ﬁeld lines seen from KAGUYA. Each line indicates a dipole magnetic ﬁeld. The dipole magnetic ﬁeld lines are drawn extending from the ionosphere at every Local Time (LT).

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Fig. 5. Intensity of plasmaspheric He II emission measured from 30 March to April 1st, 2008. The contour lines of 3.5R (inner), 2.0R (middle), and 1.1R (outer) are indicated. The arrows point to an isolated magnetic ﬂux tube ﬁlled up to higher He+ density.

The solar EUV ﬂux is necessary for an accurate determination of the emission rate factor of He+ ions, which is required for the calculation of He+ ion column density along the line-of-sight. We estimate the solar EUV ﬂux using the ground-based observation of the F10.7 index. The F10.7 index is a measure of the noise level generated by the sun at the wavelength of 10.7 cm at the Earth orbit. Historically, this index has been used as an input to ionosphere models and a reference for the solar EUV ﬂux.16 The F10.7 index was 77.8 × 10−22 W m−2 Hz−1 on 1 April 2008, and we estimate the solar 30.4 nm ﬂux to be 7.6 × 109 photons cm−2 s−1 . Thus, the emission rate factor for He+ ions is estimated to be 1.8 × 10−5 sec−1 ion−1 , provided that the solar proﬁle at 30.4 nm is represented by a Gaussian function and the Doppler width is 0.0140 nm (FWHM). The intensity of the scattered

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emission is related to the He+ ion column density at 5.7 × 1010 He+ ions cm−2 per Rayleigh. The contour lines indicated as 1.1R in Fig. 5(a), (b), and (c) correspond to a He+ ion column density of 6.3 × 1010 He+ ions/cm2 . Beyond this boundary, the column density rapidly decreased. The calculated column length within the plasmasphere along the line-of-sight, by assuming the plasmaspheric outer shell at the L-shell of 4, is 1.2 × 109 cm.17 This leads to an average density of He+ ions of 50 cm−3 . This density is consistent with past in-situ measurements of the plasmapause.17 Beyond this line, which is indicated by the outer most contour line in all panels, the He+ density rapidly decreased to below 10 cm−3 . This region is considered to be located outside the separatrix between closed and open convection trajectories. There, the ﬂux tube corotating with the Earth lived in dayside for 12 hours, resulting in relatively low plasma density. We gazed up at the Earth’s plasmasphere from the southern hemisphere (20 degree oﬀ from the magnetic equator). Therefore, we can project the plasmasphere onto the magnetic equator on the assumption that the plasmapause is ﬁeld-aligned in the dipole magnetic ﬁeld, the point with the minimum L-shell along the line of sight is found, and then we can map this point onto the magnetic equatorial plane, like Murakami’s (2007) method. Figure 6 summaries the evolution of the outer edge of the plasmasphere (the plasmapause) projected on to the equatorial plane. The position of the plasmapause at 18–20 LT was highly variable even during quiet geomagnetic activity.3,19 This might be because even a small enhancement of convection electric ﬁeld induced by the solar wind caused a stagnation point to move inward and a part of the plasma originally in the corotational region, leaked to the outer magnetosphere, reported by Yoshikawa et al. (2002) and Matsui et al. (1999). Our observation also showed a similar event, although many reported the plasmaspheric evolution during times of high geomagnetic activities.20 On the other hand, the plasmapause at 20–22 LT moved constantly outward at the rate from 0.25 to 0.75 RE /day. The increase in density from 10 to 50 cm−3 d−121 is called “late-time reﬁlling”. According to simulation studies,21 Coulomb collision is eﬀective in “latetime reﬁlling”. In the near future, clear comparison between computer simulation and “side view” EUV image will be made to identify the process responsible for plasmasphere reﬁlling. The most interesting feature in the “side view” is an isolated magnetic ﬂux tube ﬁlled up to higher He+ density than its neighbors. Figure 5(d)

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Fig. 6. Evolution of the Earth’s plasmapause in the dusk side from 30 March to 1 April 2008. The plasmapause at 20-22 LT moved outward day by day. The plasmasphere was under evolution and reﬁlled with ionospheric plasmas. In the 18–20 LT sector, the location of the plasmapause varied with time.

shows a close-up image near L = 5.5 at 19.5 LT. Arrows in Fig. 5(c) and (d) point to the bright structure along the magnetic ﬁeld. It appeared near L = 5.5 at 19.5 LT. Because of the unfavorable viewing perspective, the next image was available 2-hour later, therefore we did not identify the brighter geomagnetic ﬂux tube. The brighter ﬂux tube was considered to move to the outer magnetosphere of the Earth.

4. Signal-to-Noise Ratio Based on In-flight Background Measurement Before the KAGUYA launch in 2007, Yoshikawa et al. (2008) estimated Signal-to-Noise Ratio (SNR) based on empirical assumptions. Here we have updated their result using data during the initial turn-on for the instrumental health check. The signal count rate n [cps] of the emission is calibrated as 0.014 cps/R at the bin of He II (30.4 nm) and 0.0036 cps/R at the bin of O II (83.4 nm), before the launch. As Yoshikawa et al. (2008) did, we have treated the detector behaves as an ideal photon counter so that signal corresponds to

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the number of photon events collected during an exposure period (texp ) and noise is the square root of signal. Instrumental background from MCPs in the detector unit (0.1–0.3 cps/ 2 cm ) is lower than outer sources such as cosmic rays and/or high energy particle bombardments in the magnetosphere.3 In the lunar orbit, we have measured the background count by 1.4 cps/cm2 (0.001367 cps/bin). It is lower than our previous mission (10.4 cps/cm2 ),3 also it includes some potential contamination from interstellar He I emission. But this proves the lunar orbit is the best platform for imagery of the Earth. Here we employ the same formula as presented by Yoshikawa et al. (2008). During the measurement, a detector pixel sees the EUV signal (NSignal ), measured in cps/bin and the background (NBackground: instrumental background plus contamination from the interstellar He I emission), measured in the same units. And the number of signal counts is the total observed counts minus the background. SNR can be written by the following equation NTotal = NSignal + NBackground NSignal = NTotal − NBackground 2 2 2 2 σSignal = σTotal + σBackground ≈ σSignal + 2 · σBackground ≈ NSignal + 2 · NBackground SNR =

NSignal σSignal

=√

(1)

NSignal NSignal +2·NBackground

Figure 7 shows the revised SNRs using NBackgrount measured in the lunar orbit. Expected intensity in each region is also indicated, which was discussed by Yoshikawa et al. (2008). We set “SNR = 2 or 3” as a norm. In comparison with the previous estimate by Yoshikawa et al. (2008), here we conclude that a shorter exposure is enough to achieve SNRs. For He II (30.4 nm) observation, the observation mode (2-minute exposure and 0.09 Re resolution) can identify the main body of the plasmasphere with a high reliability (SNR = 3). Also, identiﬁcations of plasmapause and reﬁlling region in the trough are feasible with a fairly high SNR. Imaging of the plasmasheet is the most challenging target, but we will be able to achieve the science goal against the low sky background of He I (10R). The 30minute exposure at O II (83.4 nm) with 0.5 Re resolution makes polar wind visible with SNR = 2. Imagery at O II (83.4 nm) was done, but is under evaluation.

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Fig. 7. Signal-to-Noise Ratios for He II (30.4 nm) and O II (83.4 nm) observations, based on in-ﬂight background measurement.

5. Summary The lunar orbit is an ideal platform to observe the terrestrial plasma environment. We report the ﬁrst light of the UPI-TEX instrument aboard KAGUYA satellite. The TEX instrument has imaged the terrestrial plasmasphare for 3 consecutive days from the side (meridian) view. One picture shows a speciﬁc magnetic ﬂux tube near L = 5.5 at 19.5 LT is brighter than other close-by tubes, but in the next it disappeared. The morphology to explain this event is not presented here, but to be discussed by using a number of EUV images.

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The position of the plasmapause at 18-20 LT was highly variable even during quiet geomagnetic activity, although the plasmapause at 20-22 LT moved constantly outward at the rate from 0.25 to 0.75 RE /day. The stagnation point might be located in 18-20 LT during the observation, and ﬂuctuated in response to the IMF polarity.

References 1. M. Nakamura, K. Yamashita, I. Yoshikawa, K. Shiomi, A. Yamazaki and S. Sasaki, Helium observation in the Martian ionosphere by an X-ray ultraviolet scanner on Mars orbiter NOZOMI, Earth Planets Space, 51 (1999) 61–70. 2. M. Nakamura, I. Yoshikawa, A. Yamazaki, K. Shiomi, Y. Takizawa, M. Hirahara, K. Yamashita, Y. Saito and W. Miyake, Terrestrial plasmaspheric imaging by an extreme ultraviolet scanner on Planet-B, Geophys. Res. Lett. 27 (2000) 141. 3. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa and M. Nakamura, Evolution of the outer plasmasphere during low geomagnetic activity observed by the EUV scanner onboard Planet-B, J. Geophys. Res. 105 (2000) 27777–27790. 4. I. Yoshikawa, A. Yamazaki, K. Yamashita, Y. Takizawa and M. Nakamura, Which is a signiﬁcant contributor for outside of the plasmapause, an ionospheric ﬁlling or a leakage of plasmaspheric materials?: Comparison of He II (304 ˚ A), J. Geophys. Res. 108 (2003) 1080, doi 10.1029/2002JA009578. 5. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa and M. Nakamura, Loss of plasmaspheric ions during a storm observed by the EUV scanner onboard Planet-B, J. Geophys. Res. 106 (2001) 18911–18918. 6. I. Yoshikawa, A. Yamazaki, K. Shiomi, M. Nakamura, K. Yamashita, Y. Saito, M. Hirahara, Y. Takizawa, W. Miyake and S. Matsuura, Development of a compact EUV photometer for imaging the planetary magnetosphere, J. Geophys. Res. 106 (2001) 26057–26074. 7. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa and M. Nakamura, Photometric measurement of cold helium ions in the magnetotail by an EUV scanner onboard Planet-B: Evidence of the existence of cold plasmas in the near-Earth plasma sheet, Geophys. Res. Lett. 27 (2000) 3567–3570. 8. A. Yamazaki, I. Yoshikawa, K. Shiomi, Y. Takizawa, W. Miyake and M. Nakamura, Latitudinal variation of the solar He I 58.4 nm irradiance from the optical observation of the interplanetary He I emission, J. Geophys. Res. 111 (2006) A06106. 9. J. L. Burch, S. B. Mende, D. G. Mitchell, T. E. Moore, C. J. Pollock, B. W. Reinisch, B. R. Sandel, S. A. Fuselier, D. L. Gallagher, J. L. Green, J. D. Perez and P. H. Reiﬀ, Views of earth’s magnetosphere with the IMAGE satellite, Science 291 (2001) 619–624.

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10. G. Murakami, M. Hirai and I. Yoshikawa, The plasmapause response to the southward turning of the IMF derived from sequential EUV images, J. Geophys. Res. 112 (2007) A06217, doi:10.1029/2006JA012174. 11. G. Murakami, K. Yoshioka and I. Yoshikawa: Development of Mg/SiC multilayer mirrors, Proceeding of SPIE 6317 (2006) 631714-1. 12. I. Yoshikawa, T. Murachi, H. Takenaka and S. Ichimaru, Multilayer coating for 30.4 nm, Review of Scientific Instruments 76 (2005) 066109–066109-2. 13. I. Yoshikawa, M. Nakamura, M. Hirahara, Y. Takizawa, K. Yamashita, H. Kunieda, T. Yamazaki, K. Misaki and A. Yamaguchi, Observation of He II emission from the plasmasphere by a newly developed EUV telescope on board sounding rocket S-520-19, J. Geophys. Res. 109 (1997) 19897–19902. 14. A. Yamazaki, S. Tashiro, Y. Nakasaka, I. Yoshikawa, W. Miyake and M. Nakamura, Sounding-rocket observation of O II 83.4-nm emission over the polar ionosphere, Geophys. Res. Lett. 29 (2002) 1–1. 15. I. Yoshikawa, A. Yamazaki, G. Murakami, K. Yoshioka, S. Kameda, F. Ezawa, T. Toyota, W. Miyake, M. Taguchi, M. Kikuchi and M. Nakamura, Telescope of extreme ultraviolet (TEX) onboard SELENE:science from the Moon, Earth Planets Space 60 (2008) 407–416. 16. D. G. Torr and M. R. Torr, Review of rate coeﬃcients of ionic reactions determined from measurements made by the Atmosphere Explorer satellites, Rev. Geophys. Space Phys. 16 (1978) 327–340. 17. D. L. Gallagher, M. L. Adrian, M. W. Liemohn, Origin and evolution of deep plasmaspheric notches, J. Geophys. Res. 110 (2005) A09201. 18. H. Matsui, T. Mukai, S. Ohtani, K. Hayashi, R. C. Elphic, M. F. Thomsen and H. Matsumoto, Cold dense plasma in the outer magnetosphere, J. Geophys. Res. 104 (1999) 25,077. 19. M. B. Moldwin, M. F. Thomsen, S. J. Bame, D. J. McComas and K. R. Moore, An examination of the structure and dynamics of the outer plasmasphere using multiple geosynchronous satellites, J. Geophys. Res. 99 (1994) 11,475. 20. R. C. Elphic, M. F. Thomsen and J. E. Borovsky, The fate of the outer plasmasphere, Geophys. Res. Lett. 24 (1997) 365–368. 21. G. R. Wilson, J. L. Horwitz and J. Lin, A semikinetic model for early stage plasmasphere reﬁlling. I — Eﬀects of Coulomb collisions, J. Geophys. Res. 97 (1992) 1109–1119.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

ASSESSMENT OF VLBI DATA FOR CHANG’E-1 PRECISION ORBIT DETERMINATION YAN JIANGUO∗,†,‡ , PING JINGSONG†,§ , LI FEI∗ and HUANG QIAN†,¶ ∗ State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430070, China † Shanghai

Astronomical Observatory, 80 Nandan Road, Shanghai 200030, China ‡ jgyan [email protected] § [email protected] ¶ [email protected]

In this paper we presented results assessing the role of space VLBI tracking data for precision orbit determination (POD) for Chang’E-1, China’s ﬁrst lunar exploration mission. The POD of the lunar orbit segment of Chang’E-1 was performed using S-band two-way Range and Range Rate (R&RR) data, together with VLBI delay and delay rate data. Description of the mission and its trajectory would be provided, followed by a discussion of the POD estimation procedure and models. The role of VLBI data in the POD of Chang’E-1 had been analyzed, and the orbit accuracy was given with diﬀerent orbit solution strategies. We concluded that the VLBI tracking data contributed signiﬁcantly to the Chang’E-1 POD, especially when there were maneuvers of reaction-wheel unloading and uploading between arcs. It was necessary to combine various types of tracking data in the orbit solution to satisfy scientiﬁc accuracy requirement of the POD.

1. Introduction On October 24, 2007, the Chang’E-1 spacecraft was launched from Xi’Chang in the Si Chuan province, China, onboard a Chang Zheng rocket. Chang’E-1 was the ﬁrst lunar exploration mission of China, which was designed to explore the Moon for an expected duration of two years. The scientiﬁc objectives of this mission were to determine the 3D surface image, analyze geochemical components of the lunar surface elements and distribution of diﬀerent material types, explore the characteristics of lunar soils, and study the Earth-Moon space environment (Sun, 2005). After three orbit transfer sequences, Chang’E-1 arrived at the Moon on October 123

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25, 2007 and was inserted into a highly elliptical near-polar orbit around the Moon with apolune altitude of 10,000 km and perilune altitude of 2,000 km. On October 25, 26 and 29 three aero-braking were implemented on Chang’E-1 to slow it down so that it would be inserted in a near-polar, near-circular orbit with an orbital height of 200 km around the Moon. The POD of Chang’E-1 presented in this paper was performed at the Shanghai Astronomical Observatory, and was conducted as a part of the investigation of the lunar gravity ﬁeld modeling using Chang’E-1’s tracking data. The data during satellite check out phase was investigated arising from condense observations of two-way R&RR, and VLBI delay and delay rate. First, a general description about the lunar orbit determination modeling was given including the use of two diﬀerent lunar gravity ﬁeld models, LP100J and LP150Q (Konopliv et al., 1998, 2001). Then, we provided a detailed analysis of the POD result on the orbital arcs from November 20, 2007 to November 29, primarily because there was only one mitigatory reaction-wheel unloading and uploading maneuver between every two consecutive orbital arcs, whereas during other periods, there were always more than one such maneuver, which might cause orbit determination accuracy to deteriorate. We conducted residual orbital analysis using various combinations of tracking data types for the Chang’E-1 precision orbit determination. The orbital overlap was chosen as a means of evaluating the relative accuracy of the orbit determination. These overlaps, produced by extrapolating the daily arcs in this period were analyzed and the orbital diﬀerences were presented. Two strategies were taken in the POD, based on two-way R&RR data, and two-way R&RR as well as VLBI delay and delay rate data. The results of diﬀerent strategies were presented, and the purpose of this work was to analyze the improvement of the Chang’E-1 POD speciﬁcally combining VLBI data. The GEODYNII software of NASA/GSFC, USA was used in this study for Chang’E-1 precision orbit determination analysis (Rowland et al., 1997). 2. Spacecraft Description and Tracking The Chang’E-1 spacecraft had a cubic shape, with a 2.00 m by 1.72 m base and a height of 2.2 m. The spacecraft had two solar array panels, attached to the opposite sides of the spacecraft bus (Fig. 1). The spacecraft carried eight science payloads: a CCD stereo camera, a lunar laser altimeter, a interferometer imaging spectrometer, a γ spectrometer, an X spectrometer, a microwave detector, a solar energetic particles detector, and a solar wind

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Fig. 1.

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The Chang’E-1 spacecraft.

ion detector. The lunar laser altimeter was used to get high-resolution lunar topography, and in particular, along with gravity ﬁeld modeling, had a high accuracy requirement on the orbit determination of Chang’E-1. Both S and X band radio links were used to obtain the tracking data. The S-band round signal was received and coherently transponded by a low gain antenna or by a high gain antenna of 0.6 m in diameter; where the X-band down-link VLBI beacon signal was transmitted by an X-band antenna. For the ground tracking stations, the Chang’E-1 mission was tracked at Qingdao (120:19◦E, 36:04◦ N) and Kashi (76.03◦ E N39.51◦) USB TT&C (United S-Band, Telemetry, Tracking & Command) stations by using twoway R&RR mode with 18 m antenna at the S-band (2.2 Ghz). Also, the spacecraft was simultaneously tracked by four VLBI stations in China at the X-band frequency (8.4 Ghz) with a maximum bandwidth of 16 MHz. The four VLBI stations are located at Shanghai (31.09◦ N, 121.19◦E), Beijing (40.55◦N, 116.97◦E), Kunming (102:42E, 25:03N) and Urumuqi (43.47◦N, 87.17◦ E), respectively. The VLBI delay measurement is obtained by correlating the telemetry or VLBI beacon signals from two stations using wide-band synthesizing method (Kikuchi, 2004). Besides the VLBI group delay, the VLBI delay rate is obtained by time variant of correlating phase. The delay and delay rate were independent or non-coherent someway. The expected accuracies are about 3 nanoseconds and 1 picosecond/second for the VLBI delay and delay

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rate observable, respectively (Kono, 2003). During the POD, the VLBI delay and delay rate data were transformed to range and range rate through multiplying them by the speed of light.

3. Orbit Determination Modeling and Estimated Parameters The POD of Chang’E-1 was performed using two-way S-band R&RR data and VLBI delay and delay rate data collected at domestic VLBI stations. The R&RR data were sampled at 1 second, where the delay and delay rate were sampled of 1 point per 5 seconds at all baselines. During the POD procedure, the range data were weighted with a standard deviation (σ) of 5 m, and the range rate data with a σ of 1 cm/s, while the delay plus delay rate data were weighted with a σ of 1 m and 0.01 cm/s respectively. There was a signiﬁcant systematic bias in Doppler data, so the sigma was set larger than actual observation accuracy. The GEODYNII software developed by GSFC/NASA, USA was adopted to process the Chang’E-1 tracking data. The GEODYNII could solve spacecraft initial orbit elements and other selected parameters based on the Bayesian least squares theory. The dynamic models used in orbit determination included lunar non-spherical gravitational perturbation, the solar radiation pressure, the Sun and Earth point-mass gravitation, and the relativity eﬀects. The maneuvers of reaction-wheel unloading and uploading were accommodated by estimating three-axis accelerations along the radial, along-track, and cross-track to the orbit directions at the time of the maneuvers. During the satellite check-out phase, since the unloading and uploading maneuvers were performed frequently, the tracking data arc length was limited to shorter than 10 hours. In order to assess the improvement in the Chang’E-1 POD by adding VLBI data, the daily orbital arcs from November 20 through 29 of 2007 were analyzed in this paper. In the Chang’E-1 POD, the Earth-ﬁxed coordinate system and the locations of the tracking stations were adopted to be consistent with the terrestrial reference frame labeled ITRF2000 recommended by International Earth Rotation Service. The Lunar-ﬁxed coordinate system was chosen to be consistent with the orientation parameters of JPL DE403 planetary ephemeris (Standish, 1995), so were the ephemeredes of the Sun, the Earth and other planets. The inertial coordinate system used for orbit integration was the lunar centered inertial coordinate system J2000.

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The parameters estimated in the POD of Chang’E-1 included initial orbital elements of Chang’E-1 and the three-axis accelerations. Pass dependent biases of two-way R&RR, VLBI delay and delay rate were estimated to account for any measurement modeling error, such as frequency oﬀset, and the imprecise modeling of the troposphere and ionosphere. The solar radiation pressure coeﬃcient was as adopted as a constant of 1.2. 4. Result The tracking data of most arcs in this paper included two-way R&RR and VLBI delay and delay rate data. In generally, the observation period of the two-way R&RR spanned over about 8 hours, and the VLBI delay and delay rate observation spanned over about 3 hours each day. The residuals of the four observation types were given from Fig. 2 to Fig. 5. The horizontal axis stands for date, or the arc number in November 2007, and the vertical axis stands for the magnitude of daily RMS of the residuals. The lunar gravity ﬁeld models of LP100J and LP150Q with full

Fig. 2.

Two-way Doppler residuals.

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Fig. 3.

Two-way range residuals.

Fig. 4.

Delay residuals.

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Fig. 5.

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Delay rate residuals.

orders and degrees were used in the Chang’E-1 POD and their results compared. Figure 2 to Fig. 5 clearly showed that there was no signiﬁcant diﬀerence between these two gravity ﬁeld models, mainly because of the orbit height of Chang’E-1 — at a height of 200 km it should be not sensitive to the high degree and order of the lunar gravity ﬁeld model. Alternatively, another possibility could be that the higher degree model was not providing extra information of the lunar gravitational potential for Chang’E-1. Figure 4 and Fig. 5 showed a trend of smaller residual magnitudes, mainly attributing to the more stable orbit, perturbed by less frequent reaction-wheel unloading and uploading maneuvers. For the POD of the short arc tracking, it was estimated that the R&RR together with VLBI data could improve the POD results by using R&RR data only. To assess the importance of VLBI data in the Chang’E-1 POD, the daily arc from November 20 through 29 of 2007 were adopted in the data processing, because the orbital arcs were separated very short by the frequent maneuvers of moderate reaction-wheel unloading and uploading. Usually, the maneuver between every two consecutive arcs of Chang’E-1 during this period was carried out when the spacecraft ﬂying on the

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farside of the moon, and there were nearly no reaction-wheel unloading and uploading maneuver during the USB R&RR and VLBI observation. Here the tracking data of November 27, 2007 were selected for illustration. Figure 6 to Fig. 9 showed the observation residual after the POD. In Figs. 6 and 7 the residuals of range and range rate were given, respectively, while in Figs. 8 and 9 the residuals of VLBI delay plus delay rate for the baseline Shanghai to Beijing were given respectively. In Figs. 7 and 9 there were periodic signatures with a period of about 1 hour, which was mainly caused by the Chang’E-1 slowly spinning movement that was diﬃcult to model in the POD. The overlap analysis was carried on by predicting the orbit of November 27, 2007 to 12 additional hours, which was then compared with the orbit determined by observation data of November 28. The POD errors were assessed by calculating the orbit diﬀerence at the start point of the comparison arc, and it was presented in the RTN coordinate frame (i.e. in the radial, transverse, and normal directions of the orbital plane). As for the other arcs, only the orbital diﬀerences at the start point between the predicted and solved orbit were given for simplicity. At the same time the RMS values of orbit diﬀerence in the RTN coordinate frame were given.

Fig. 6.

Range residual of orbit November 27, 2007.

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Fig. 7.

Fig. 8.

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Doppler residual of orbit November 27, 2007.

Delay residual of baseline Shanghai to Beijing of orbit November 27, 2007.

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Delay rate residual of baseline Shanghai to Beijing of orbit November 27, 2007.

Two strategies in the POD were used; one was to use two-way R&RR data, and the other was to use all the available tracking data. Figure 10 to Fig. 12 clearly showed that when the VLBI data were included, the orbit diﬀerence decreased signiﬁcantly. With VLBI data included, the transverse diﬀerence could be within several tens of meters, but could reach several hundred meters when only R&RR data were used. As to the normal diﬀerence, it would be worse by an order of magnitude when R&RR data were used. This conclusion could be further conﬁrmed in Table 1, which listed all statistical similar analyzing results for all arcs during the considering period. The transverse diﬀerence augmented with time was mainly caused by the maneuvers of reaction wheel unloading and uploading between these two successive days (arcs), where the direction of the maneuver was mainly along transverse. It showed secular perturbed eﬀects on the orbit. The orbit diﬀerence between the predicted orbit from November 27 and the estimated orbit on November 28 showed less discrepancy when the VLBI data was combined, indicating the orbit accuracy was improved. In Table 1 and Table 2 the statistics of orbital diﬀerences between the predicted orbit and the estimated orbit from the arcs between November

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Fig. 10.

Fig. 11.

Radial diﬀerence comparing the two strategies.

Transverse diﬀerence comparing the two strategies.

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Fig. 12.

Normal diﬀerence comparing the two strategies.

Table 1. Statistics of orbital overlapping diﬀerence for selected arcs and using various combination of tracking data. Arc date 20/21 21/22 22/23 23/24 24/25 25/26 26/27 27/28 28/29

Data type Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler

Radial (m) −5.48 12.85 5.33 12.55 10.03 12.23 13.97 11.43 12.09 14.76 3.45 50.04 1.39 3.9 10.83 10.07 1.64 1.28

Transverse (m) −54.04 2287.24 −87.22 −1403.74 −265.30 −352.11 477.26 450.21 36.70 149.16 −43.10 −43.90 −123.35 −196.44 −10.35 250.37 14.87 −446.26

Normal (m)

Position (m)

−14.21 475.06 −53.94 −491.68 −17.63 −127.04 10.29 29.26 14.38 223.49 −116.50 −63.48 −19.20 −121.72 4.02 42.97 −0.87 449.87

56.14 2336.08 102.69 1487.41 266.07 374.52 477.57 451.30 41.22 269.09 124.26 91.98 124.84 231.12 15.51 254.23 14.98 633.66

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Table 2. RMS of orbital overlapping diﬀerence for selected arcs and using various combination of tracking data. Arc date 20/21 21/22 22/23 23/24 24/25 25/26 26/27 27/28 28/29

Data type Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler Range + Doppler + VLBI Range + Doppler

Radial (m)

Transverse (m)

Normal (m)

8.920 3.606 22.252 19.364 3.530 3.696 3.714 6.249 6.146 9.904 50.421 55.074 7.545 6.120 4.382 2.967 0.880 2.166

28.312 273.565 99.666 156.875 114.503 104.996 156.883 155.941 18.723 32.155 114.465 127.560 78.499 61.707 107.623 90.132 10.024 7.354

16.319 515.121 112.136 413.145 13.351 90.009 8.720 19.684 13.292 334.610 447.329 644.588 9.459 364.677 15.511 288.501 5.753 127.649

20 and 29 using various combinations of tracking data were presented. It clearly showed that the diﬀerences decrease signiﬁcantly when VLBI delay and delay rate data were combined in the POD, especially in the normal direction of the orbital plane, which can also be veriﬁed in Table 2, the RMS value in normal clearly showed decrease when VLBI data were included. The orbit diﬀerence stated here was not an absolute means to judge the accuracy of POD, but it still could reﬂect the consistency between arcs. 5. Conclusion The tracking data of the check-out phase of Chang’E-1 were processed for precision orbit determination. Two gravity ﬁeld models, LP100J and LP150Q, were adopted for comparison in the POD. The result showed that there was no signiﬁcant diﬀerence in orbital residuals, this could be primarily caused by the insensitivity of Chang’E-1 to the high degree and order of lunar gravity ﬁeld, or the higher degree model was not providing extra information of the lunar gravitational potential for Chang’E-1. Further computations were performed to verify the importance of VLBI data in the Chang’E-1 POD. The arcs from November 20 through 29, 2007 were chosen to analyze the diﬀerences between the predicted orbit and the

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solved orbit, and results were presented clearly showing that the accuracy should be improved by more than an order of magnitude to most arcs if the VLBI delay and delay rate data were included. Acknowledgments This research is supported by grant of the National Natural Science Foundation of China (40674005), Teaching Foundation of Chinese Ministry of Education (200804861059), open foundation of State Key Laboratory in Information Engineering of Surveying, Mapping and Remote Sensing (WKL070201). We acknowledge NASA/GSFC, USA for the permission to use the GEODYNII/Solve software system. The precision orbit determination computation was conducted at the Shanghai Astronomical Observatory, Academia Sinica. We thank the Editor, Professor Yasumasa Kasaba, and the reviewers for their constructive comments, which have improved the paper. References 1. F. Kikuchi, Y. Kono, M. Yoshikawa et al., Earth Planets Space. 56 (2004) 1041. 2. Y. Kono, H. Hanada, J. Ping et al., Earth Planets Space 55 (2003) 581. 3. A. S. Konopliv, S. W. Asmar, E. Carranza et al., Icarus 150 (2001) 1. 4. A. S. Konopliv, A. B. Binder, A. Bkucinskas et al., Science 281 (1998) 1476. 5. D. D. Rowlands, J. A. Marshall, J. McCarthy et al., Contractor Report, Hughes STX Corp. Greenbelt, MD. 1–5 (1997). 6. E. M. Standish, JPL planetary and lunar ephemerides, DE405/LE405, JPLIOM 312. F-98–127, 1998. 7. H. X. Sun and S. Dai, Acta Astronautica 57(2–8) (2005) 561.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

CHANG’E-1 LASER ALTIMETRY DATA PROCESSING∗ QIAN HUANG† , JINGSONG PING‡ and JIANGUO YAN§ Shanghai Astronomical Observatory, Chinese Academy of Science, Nandan Road 80, Shanghai, China † [email protected] ‡ [email protected] § [email protected] JIANFENG CAO and GESHI TANG Beijing Aerospace Control Center, Beijing, 100094 RONG SHU Shanghai Institute of Technical Physics, CAS, Shanghai, 200083

Chang’E-1 is the ﬁrst lunar exploration mission of China. One of its most important scientiﬁc objectives is to determine the lunar 3D topographic maps. The Laser Altimeter Mission (LAM) is mainly used to obtain the distance between the satellite and its nadir point, which can assist to produce the lunar 3D maps and topographic models. About 3 million eﬀective ranging measurements obtained in two months by the LAM have been used to yield a 360th spherical harmonic expansion global topographic model of the Moon, namely the Chang’E-1 Lunar Topographic Model (CLTM-s01). This paper introduces the LAM mission; the precise orbit determination and attitude control of the satellite; the LAM data processing; and the ﬁrst results of CLTM-s01. The topographic ﬁeld has a vertical accuracy of ∼31 m and a spatial resolution of 0.25◦ (∼7 km) along the equator. This model shows the COF/COM oﬀset to be (−1.7766, −0.7299, 0.2370) km in the x, y, and z directions, respectively. Over some smooth maria regions of the nearside, the elevations of CLTM-s01 agree with the Clementine LIDAR measurements at a suﬃcient level (∼200 m). It turns out that two months’ measurements of LAM has given a good result of the lunar topography, and after 1yr normal mission of Chang’E-1, the spatial resolution should be better than 2km along the equatorial areas.

∗ This work is supported by National HST Project No. 2008AA12A209 and 2008AA12A210.

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1. Introduction The year of 2007 represented the beginning of a new era of lunar exploration. Not only were the Chinese Chang’E-1 and Japanese SELENE (Kaguya) missions successfully launched in this year, but these are closely followed by the Indian Chandrayaan-1 mission in October 2008 and the American Lunar Reconnaissance Orbiter (LRO) later in spring 2009. Chang’E-1 is the ﬁrst lunar exploration mission of China, aiming to obtain 3D images of the lunar surface, analyze the content of useful elements and types of materials, and explore the characteristics of lunar soil and the space environment between the earth and the Moon. The Chang’E-1 satellite was successfully launched on October 24th, 2007 from Xichang Satellite Launch Center, and was placed into a 2-hour circular lunar polar orbit on November 7th. One of the payloads of Chang’E-1, the Laser Altimeter (LAM), was used to measure the distance between the orbiter and the lunar surface, and we can obtain the lunar topographic models by combining the range measurements with precise orbits and attitudes data. This paper introduces the LAM system, its present status, the LAM data processing and its ﬁrst results of the lunar topographic model CLTM-s01. 2. The LAM System and its Present Status The LAM system consisted of two subsystems, namely the Altimeter Optical Head and the Altimeter Circuit Box. The Altimeter Optical Head comprised a laser transmitting system and an optical receiving system. The laser transmitter, contained a Q-switched Diode-pumped Nd:YAG source that produced laser every second at a wavelength of 1064 nm. The laser had a pulse-width of less than 7 ns, the pulse energy of 150 mJ, and a laser divergence of less than 0.5 mrad, which resulted in a surface spot size of 120 m when the satellite altitude was about 200 km. The optical receiver included a Cassegrain telescope, which had a telescope diameter of 140 mm and the focal length of 538 mm. The size of the Optical Head was 356 mm* 290 mm* 174.5 mm and the weight was 9.9 kg. The Altimeter Circuit Box was a control unit used to do the distance measuring and to supply the laser power. The size of it was 260 mm* 200 mm* 190 mm and the weight is 5.8 kg. Therefore the total weight of the Laser Altimeter System was 15.7 kg. Speciﬁcations of LAM are given in Table 1 (R. Shu, et al. 2008). The LAM was installed parallel to the Z axis of the orbiter, with an installation error of about 2 . The boresight of LAM was parallel to the CCD detecting system with a measuring accuracy of ±1 . Both the laser

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Chang’E-1 Laser Altimetry Data Processing Table 1.

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Chang’E-1 LAM instrument characteristics.

Characteristics Eﬀective distance range Footprint Wavelength Energy Width of Laser Pulse Repeat rate Receiver telescope diameter Telescope focal length Distance resolution Distance error Data rate Weight Power Life

Values 200 km ± 25 km 120 m @ 200 km 1064 nm 150 mJ <7 ns 1 Hz 140 mm 538 mm 0.96 m < ±5 m 384 bps 15.7 Kg 25 W 1 Year

transmitter and receiver telescope were installed facing the lunar surface. The LAM can work well when the orbit slope was less than 15◦ . The distance/ranging resolution of LAM was 0.96 m after the ground tests, and the ranging accuracy was in-ﬂight estimated to be less than ±5 m (R. Shu, et al. 2008). The along-track shot spacing was about 1.4 km when assuming a 100% laser ranging probability, and the minimum foot spacing along the equator should be about 7.5 km after two months’ measurements. Health check of the LAM was carried out during the in-orbit test phase from Nov. 5th to Nov 20th without laser ﬁring. The ﬁrst ranging experiment was carried out on Nov. 27th successfully. Since the LAM can obtain data on both ascending and descending arcs, more than 5 million range data were received and recorded normally during the ﬁrst forward ﬂying phase (2007/11/20∼2008/01/26). Because of many times large voltage instrument breaks and orbit controls, we lost about 171 passes altimetry data. From Jan. 27th the Chang’E-1 satellite was adjusted its attitude and stepped into the ﬁrst sideways ﬂying phase. The LAM worked normally in this phase until the ﬁrst lunar eclipse occurred on Feb. 21st. The Chang’E1 satellite began its second forward ﬂying phase after performing some attitude adjustments on May 1st, and the LAM switched on to work from May 15th. By now the LAM has been working normally and eﬃciently. Until July 1st, more than 7 million ranging data have been recorded and possibly that after 1 yr normal observation we would obtain more than 30 million laser points.

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3. Chang’E-1 LAM Data Processing The laser altimeter (LAM) transmits a beam of high-power narrow laser pulse to the lunar surface, and receives its returned signals by an optical telescope. By measuring the out and home time delay of the laser beam, we can calculate the distance between the satellite and the lunar surface. In order to determine a global topographic data set from the LAM ranging data, it was necessary to compute the precise spacecraft orbits and the attitudes which were subtracted from the range proﬁles to yield relative surface elevations. 3.1. Orbit determination and attitude control The precise orbit determination of Chang’E-1 was performed mainly by using two-way Uniﬁed S-band (USB) Doppler and Range data collected by Qingdao (120.19◦E, 36.04◦ N) and Kashi (76.03◦E N39.51◦) stations, and was assisted with VLBI delay and delay rate data collected by four VLBI stations, with 25 m at Shanghai and Urumuqi and 50 m at Beijing and Kunming (Huang, 2006). Generally, there would be 3 or 4 tracking circles per day, with all the data were sampled at 1 second rate. During the orbit determination, the range data was weighted with a sigma of 5 m, the Doppler data was weighted with a sigma of 1 cm/s, and the delay plus delay rate data were weighted at a sigma of 1 m and 0.01 cm/s separately. In general, the orbits were determined by arcs, including two days tracking data. The dynamic models used in orbit determination included lunar non-spherical gravitation by LP150Q, the solar radiation pressure, the Sun and Earth point-mass gravitation, the relativity eﬀects and Earth oblateness and Lunar tidal force. The maneuvers of reaction wheel unloading was accommodated by estimating three-axis accelerations, that is, the radial, along-track, and cross-track to the orbit at the time of the maneuvers. Our orbits were characterized in radial accuracy of 10 m (1sigma), and with along track 50∼100 m (1sigma) (J. G. Yan et al., 2008). Chang’E-1 is a three-axis stable satellite using a set of star sensors to measure the attitude. In the orbital coordinate system, the values and variations of all the three Euler angles are quite small. By analyzing the measured attitude data, the stability of each angle is better than 0.008◦ /s (3sigma), and the vertical error caused by attitude control is less than 1m (3sigma).

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3.2. LAM data processing Since the Chang’E-1 takes polar orbits with a mean altitude of 200 km and the onboard LAM can detect the reﬂected signals day and night, near global laser ranging coverage can be obtained once in half a month. In the ﬁrst two months’ forward ﬂying phase, more than 5 million range measurements had been recorded. The spatial resolution along and across the orbit was about ∼1.4 km and ∼7.5 km, respectively. We had processed all the recorded ranging data from orbit 0243 to orbit 0878. During the ﬁrst forward ﬂying phase, the orbital maintenances were quite frequent and some orbital arcs had no ground-tracking information, forcing us to reject about 7 orbits ranging data. The returned laser pulse was substantially inﬂuenced by the characteristics of the laser spot. If the ﬁrst returned ranging was out of the hardware-based ranging threshold, the data management system will then record a fake value which was far bigger than the orbital altitude. This value is just to show that it was out of the detecting capability of the laser instrument. The ﬁrst step of LAM data processing was to delete those fake ranges. Generally, more than 7000 ranging points could be obtained in one single orbit, and the fake data deleting ratio was about 30%. Next was to do the systemic calibrations according to the instrument technical parameters. The ranging accuracy of the instrument was in-ﬂight estimated to be less than 5 m (3sigma). The topography proﬁles were generated by combining the processed ranging measurements with the precise orbit and attitude data, which were interpolated into the time of the laser pulse. We chose a sphere with radius of 1738km as a basis for converting the distances between the nadir and the Moon center to needed elevations. As the topographic proﬁles were pretty good, we just applied a simple ﬁltering method to reject the pseudoelevations in each orbit, with a deleting ratio of less than 1%. Finally, we got more than 3 million eﬀective elevation data and formed our ﬁrst global lunar topographic data set. Figures 1 and 2 are two examples of the topographic proﬁles by LAM. Figure 1 shows the elevation proﬁle of orbit 0249. From left sharpness to right smoothness, the proﬁle is coincident with the actual lunar topographic features well, showing the detailed shape of lunar surface from south to north. The maximum range diﬀerence between two sequential points in orbit 0249 is about 2.686 km, representing a maximum slope of ∼60◦ . Figure 2 depicts four sequential passes through the Moscoviense (149◦ E, 28◦ N) crater (Konopliv, et al., 2001). In Fig. 2 the longitude is from 152◦ E

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Fig. 1. The topographic proﬁle of orbit 0249 by LAM. Horizontal axis is UTC time with MJD form. The Height is referenced to a sphere with a radius of 1738 km and the origin as the center of mass.

to 149◦ E with the orbit number from 0253 to 0256. From south to north the average slope of the Moscoviense basin is about 2◦ . Figure 2 has clearly demonstrated that LAM can detect not only the general proﬁles but also the precise topographic features, such as the impact crater’s detailed outer ring and its central peak. 3.3. Lunar topographic model CLTM-s01 When assuming a 100% laser ranging probability, the along-track and across-track accuracy of two months’ observation are theoretically to be ∼1.4 km and ∼7.5 km respectively. The elevation data sets were assembled into a 0.25◦ × 0.25◦ grid in global corresponding to the resolution of equatorial regions and a 0.0625◦ × 0.0625◦ grid in the polar region reﬂecting its higher spatial resolution there. We did a 360th degree and order spherical harmonic expansion (half-wavelength resolution of ∼15 km) to the 0.25◦ × 0.25◦ gridded data and yielded a global topographic model of the Moon, namely the Chang’E-1 Lunar Topography Model s01 (CLTM-s01). The spherical harmonic expansion of lunar global topography H is deﬁned as: H(λ, ϕ) =

l N l=1 m=0

¯ ¯ ¯ Plm (sin ϕ)(Clm cos mλ + Slm sin mλ)

(1)

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Fig. 2. Topographic proﬁles of Moscoviense crater (149◦ E, 28◦ N) by LAM. Outer ring and central peak are clearly displayed. Horizontal axis is lunar latitude (One degree corresponds to 30.3 km). The Height is referenced to a sphere with a radius of 1738km and the origin as the center of mass.

Here the symbols ϕ and λ represent the selenocentric co-latitude and the east longitude of the observation point respectively. P¯lm are the normalized associated Legendre functions of degree l and order m. C¯lm and S¯lm are the normalized spherical harmonic coeﬃcients. Spherical harmonic coeﬃcients of the ﬁrst 4 degrees and orders are shown in Table 2. The map of CLTMs01 is shown in Fig. 3, with the nearside on the right and the farside on

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Table 2. Normalized coeﬃcients of the 4 × 4 CLTM-s01 lunar topographic model. Degree

Order

0 1 1 2 2 2 3 3 3 3 4 4 4 4 4

0 0 1 0 1 2 0 1 2 3 0 1 2 3 4

¯lm /m C −987.4 136.8 −1025.7 −667.7 −769.3 109.6 64.0 553.7 438.4 406.5 216.2 −226.1 −328.3 −199.2 −190.5

S¯lm /m — — −421.4 — −16.3 383.8 — 88.1 189.2 −5.2 — −48.0 −101.4 −286.3 110.8

Fig. 3. Topography of the Moon from the Chang’E-1 laser altimeter data. The map is a Mollweide projection with a center meridian of 270◦ E, and with nearside on the right and farside on the left. The interval of longitude and latitude are all at 30 deg.

the left. On the nearside there are many ﬂat maria regions with minus elevations, and on the farside there exists lots of impact craters. From Fig. 3, we can clearly recognize not only all the plateaus, maria regions, but also detailed features of numbers of craters. It is a reliable global topographic

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model of the Moon, which was produced only by laser altimetry data, with a vertical accuracy better than 31 m. Here we consider four error sources, with measured laser instrument error of less than 5 m (3sigma); the calculated orbit radial error of less than 30 m (3sigma); the observed spacecraft pointing error of less than 1 m; the footprint estimated error of less than 5 m when considering the laser altimeter in a critical tilt state of 15◦ . It has long been known that the Moon’s geometric center was displaced from its center of mass (W. M. Kaula et al., 1974). This new model CLTMs01 shows the COM/COF oﬀset to be (−1.777, −0.731, 0.237) km in the x, y and z directions, respectively. As a result of CLTM-s01, we know this displacement deviates from the Earth-Moon line, and on the farside of the Moon the COM/COF oﬀset is displaced approximately 22◦ toward the western limb. The highest and lowest places are all on the farside (M. T. Zuber et al., 1994, D. E. Smith et al., 1997). By the CLTM-s01 model, we found the deepest places were in the South Pole-Aitken Basin at (211.375◦E, 61.375◦S) with a depth of 9.227 km, and the highest topography of 9.840 km above the reference sphere at (201.375◦E, 5.375◦ N) north of the Korolev Crater (157◦ W, 4.5◦ S) (A. S. Konopliv et al. 2001). A fundamental characteristic of the lunar shape is that the topographic signatures of the nearside and farside are very diﬀerent (D. E. Smith et al., 1997). Figure 4 is a histogram of heights in 0.5-km-wide bins. Generally, the lunar topography is rich in −6 km to 4 km-scale structures. In contrast to the farside, the sharpness of the nearside histogram shows that the topographic relief of nearside is much smoother than the farside, which is a result of the wide maria regions. In the farside, there are much more plateaus and impact craters, and the highest and deepest region are all in that side. All of these demonstrate the obvious dichotomy of the Moon. The latest lunar global shape model made by laser altimetry data is the Goddard Lunar Topography Model 2 (GLTM2) (D. E. Smith et al., 1997), and the most complete Ground Control Point (GCP) network is the Uniﬁed Lunar Control Network 2005 (ULCN2005) (B. A. Archinal et al., 2006). GLTM2 is a 72nd degree and order spherical harmonic expanded global topography model, which was based on 72,548 Clementine LIDAR ranging data with coverage from 75◦ S to 75◦ N. The topographic ﬁeld has an absolute vertical accuracy of approximately 100m and a spatial resolution of 2.5◦ . Both the accuracy and resolution of CLTM-s01 are better than

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Fig. 4. Histogram of heights of all lunar topography (square black dot line), nearside topography (diamond black dot line), and the farside (up-triangle grey dot line).

GLTM2, as it has more than 3 million eﬀective global laser points, especially on the polar regions. The ULCN2005 is based on a combination of Clementine images and a previous network derived from Earth-based & Apollo photographs, and Mariner 10 & Galileo images. Mark Wieczorek has assembled these data into a 0.0625◦ ×0.0625◦ grid set and then expended it into a 359th spherical harmonic model UCLN359 (M. A. Wieczorek, 2006). A comparison between CLTM-s01 and ULCN359 shows that these two models agree with each other well within ∼200 m over the large maria regions, neglecting the quite big positional errors of ULCN2005 (B. A. Archinal, et al., 2006). Figure 5 shows the amplitude spectra of lunar topographic model CLTMs01 and ULCN359. The spectral power of CLTM-s01 is obviously higher at longer wavelength than ULCN359 owing mostly to more complete accurate sampling of the lunar surface. No single mission will observe the complete Moon in one or two years. Besides Chang’E-1, the Japanese lunar explorer KAGUYA (SELENE) has been orbiting the Moon for more than 1 year, and it has obtained more than 6.73 million points as of Mar. 31st. In this AOGS2008 Busan meeting, Araki

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3

10

Power Spectra of Spherical harmonic coefficients

CLTM-s01 ULCN359

2

10

1

10

0

10

-1

10

0

Fig. 5.

50

100

150

200 Degree

250

300

350

400

Lunar Topographic amplitude spectrum of CLTM-s01 and ULCN359.

and Ishihara represented their initial results by Kaguya-LALT Mission, showing their lunar global map with a resolution of 15 or 30 km in longitude (equatorial region) and 1.5 km in latitude (H. Araki et al. 2008; Y. Ishihara et al. 2008). 4. Summary More than 3 million range measurements from the Chang’E-1 Laser Altimeter have been used to produce an accurate global lunar topographic model CLTM-s01. This model is an actual global topographic model based only on altimetry data with a radial accuracy of approximately 31 m and an across resolution of 0.25◦ along the equator. The COF/COM oﬀset of CLTM-s01 is (−1.777, −0.731, 0.237) km, which is a little diﬀerent with (−1.74, −0.75, 0.27) km calculated by GLTM2 (Smith et al., 1997). Over the large maria regions, which we can neglect the positional errors to a certain extent, the CLTM-s01 altitudes agree with the Clementine lidar measurement within ∼200 m. Because of its large orbital altitude, Clementine LIDAR could not observe the polar regions, LAM has given a quite clear resolution of the polar regions. Chang’E-1 LAM shall continue to observe the whole lunar surface by the end of 2008 or later. After 1 yr

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normal observations, it should be much better than Clementine LIDAR with a spatial resolution about 2 km at the equator and better than 500 m at the polar regions. The key factor for altimeter data accuracy is the accuracy of the orbit. We intend to use all the usable tracking data to improve the gravity model, the result of which will be given later. We hope that we could combine the laser altimetry data of many missions to achieve higher resolution lunar topographic results. Acknowledgments We would like to express our special thanks to Gregory A. Neumann for his constructive reviews and suggestions. We are also grateful to the anonymous reviewers for their helpful reviews and comments. The topographic map was created using the Generic Mapping Tools of Wessel and Smith (1991). This work is assisted by National HST Project No. 2008AA12A209 and 2008AA12A210. References 1. H. Araki, S. Tazawa, H. Noda et al., Initial Results of the Lunar Laser Topography by KAGUYA-LALT Mission, AOGS2008 the 5th Annual Meeting, Busan (2008). 2. B. A. Archinal, M. R. Rosiek, R. L. Kirk et al., The Unified Lunar Control Network 2005, U.S. Geological Survey Open-File Report 2006-1367, Version 1.0 (2006). 3. Y. Huang, Orbit Determination of the First Chinese Lunar Exploration Spacecraft CE-1, Doctorial Thesis, Graduate University of Chinese Academy of Sciences (Shanghai Astronomical Observatory), in Chinese (2006). 4. Y. Ishihara, H. Araki, H. Noda et al., A Preliminary Lunar Topographic Model by KAGUYA/LALT, AOGS2008 the 5th Annual Meeting, Busan (2008). 5. W. M. Kaula, Theory of Satellite Geodesy, New York, Dover Publication (2000). 6. A. S. Konopliv, S. W. Asmar and D. N. Yuan, Recent Gravity Models as a Result of the Lunar Prospector mission, Icarus 150 (2001) 1–18. 7. J. S. Ping, K. Heki, K. Matsumoto et al. A Degree 180 Spherical Harmonic Model for the Lunar Topography, Advances in Space Research 31(11) (2003) 2377–2382. 8. D. E. Smith, M. T. Zuber, G. A. Neumann et al. Topography of the Moon from the Clementine Lidar, J. Geophys. Res. 102 (1997) 1591–1611. 9. R. Shu , J. Y. Wang, W. B. Chen et al. The Laser Altimeter in Chang’E-1 Lunar Exploration Satellite, AOGS2008 the 5th Annual Meeting, Busan (2008).

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10. M. A. Wieczorek, The Gravity and Topography of the Terrestrial Planets, Treatise on Geophysics 10 (2007) 165–206. 11. J. G. Yan, J. S. Ping and F. Li, Precise Orbit Determination of Smart-1 and Chang’E-1, AOGS2008 the 5th Annual Meeting, Busan (2008). 12. M. T. Zuber, D. E. Smith, F. G. Lemoine et al. The Shape and Internal Structure of the Moon from the Clementine Mission, Science 266 (1994) 1839–1843.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

THE SUB-KEV ATOM REFLECTING ANALYZER (SARA) EXPERIMENT ABOARD CHANDRAYAAN-1 MISSION: INSTRUMENT AND OBSERVATIONS ANIL BHARDWAJ∗ , M. B. DHANYA and R. SRIDHARAN Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum, 695022, Kerala, India ∗ Bhardwaj [email protected] MARTIN WIESER, STAS BARABASH, FUTAANA YOSHIFUMI ¨ and MATS HOLMSTROM Swedish Institute of Space Physics, Box 812, 98128, Kiruna, Sweden PETER WURZ and AUDREY SCHAUFELBERGER Physikalisches Institut, University of Bern, Sidlerstrasse 5, CH-3012, Bern, Switzerland ASAMURA KAZUSHI Institute of Space and Astronautical Science, 3-1-1 Yoshinodai, Sagamihara, Japan

SARA experiment aboard the ﬁrst Indian lunar mission Chandrayaan-1 had the objective to explore the solar wind–lunar interaction using energetic neutral atoms (ENA) from the lunar surface as diagnostic tool. SARA consisted of an ENA imaging mass analyzer CENA (Chandrayaan-1 Energetic Neutral Analyzer) and an ion mass analyser SWIM (Solar Wind Monitor), along with a digital processing unit (DPU) which commands and controls the sensors and provides the interface to the spacecraft. Both sensors have provided excellent observational data. CENA has observed ENAs from the lunar surface and found that ∼20% of the incident solar wind ions get backscattered as ENAs from the lunar surface. This is contrary to the previous assumptions of almost complete absorption of solar wind by the lunar surface. The observation is relevant for other airless bodies in the solar system.

1. Introduction The solar wind, which is a continuous ﬂow of plasma from the Sun, and consisting of ∼96% H+ , ∼4% He++ and <0.1% heavier ions,1,2 interacts 151

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with obstacles in its ﬂow such as planetary bodies or moons. For the Moon, the absence of a global magnetic ﬁeld and the presence of a surface-bound exosphere makes the solar wind to interact directly with the lunar surface. The impacting solar wind ions, on interaction with the lunar regolith, get mostly neutralized. Particles can get absorbed on the surface, thermalized or directly backscattered to space.3,4,5 As a part of this interaction, atoms can be ejected from the surface (a process known as sputtering) that have suﬃcient kinetic energy6,7 to be called energetic neutral atoms (ENAs). Observation of backscattered or sputtered ENAs from the lunar surface along with the monitoring of impacting solar wind ions provides understanding of the lunar–solar wind-surface interaction.8 Launch of Chandrayaan-1 on 22 October 2008 and its insertion into the lunar orbit on 8 November 2008 marked the beginning of a new era in the planetary exploration program of India. Chandrayaan-1 carried 11 experiments onboard — one among them was the Sub-keV Atom Reﬂecting Analyzer (SARA),6,9 which used a novel technique of ENA imaging to investigate the lunar–solar wind interaction from a 100 km polar orbit. Since the ENAs released from the lunar surface can have energy greater than the escape energy of Moon, once released, they travel along straight lines and can be observed at 100 km altitude. Around magnetic anomalies, mini-magnetospheres may form.10 In the presence of a mini-magnetosphere on the lunar surface, the direct entry of solar wind to that region will be obstructed, resulting in reduced ENA ﬂux from that region.7,11 Hence, magnetic anomalies present on the lunar surface can also be investigated with the SARA.

2. Instrumentation The SARA experiment has two sensors, Chandrayaan-1 Energetic Neutrals Analyser (CENA) for measuring ENAs, and Solar Wind Monitor (SWIM) for simultaneous measurement of plasma in the lunar environment. The two sensors are connected to the Digital Processing Unit (DPU) which commands and controls the sensors. The block diagram of SARA, which also shows the ﬂight models of CENA, SWIM and DPU, is shown in Fig. 1. The total weight of the SARA is 4.4 kg and consumes a power of 17.1 W. CENA measures ENAs in the energy range 0.01–3.3 keV. Its principle is based on the conversion of neutral atoms to positive ions via surface-interaction technique. Its main functional blocks are an ion deﬂection system, a conversion surface, an electrostatic wave system for

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Fig. 1. Block diagram of the SARA. The sensors CENA and SWIM, and the DPU are marked in the ﬁgure. CH-1 S/C refers to Chandrayaan-1 spacecraft.

Fig. 2. Cross-sectional 3D view of CENA with typical particle trajectory shown as solid line (taken from Ref. 9).

energy analysis, and a time-of-ﬂight (TOF) section. The energy analysis combined with the velocity measurement in the TOF section allows mass determination.12 The cross-sectional view of CENA is shown in Fig. 2. CENA has an electrostatic deﬂector near the entrance to deﬂect away charged particles entering the system. The deﬂector consists of two electrodes with one biased to +5 kV and the other at ground, which almost completely deﬂect away ions of energy <15 keV. Neutral particles,

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unaﬀected by the deﬂector, are incident at grazing incidence on a conversion surface that converts the neutral particles to positive ions. The conversion surface is a highly polished silicon wafer coated with MgO to provide high ionization eﬃciency.13 The ions then pass through a wave-type electrostatic energy analyzer. The analyzer uses four diﬀerent variable potentials applied to a system of electrodes to achieve energy analysis of the converted ions. The wave system also forms an optical labyrinth, eﬃciently blocking UV photons. Furthermore, the electrodes of the wave system are serrated and blackened to increase the UV suppression. This concept of the wave analyzer is similar to the one used in the MTOF sensor of the CELIAS instrument14 on SOHO, which provides a photon rejection factor of 2×10−8 (Refs. 6, 9). Before entering the TOF section, particles are post accelerated by a potential of 2.4 kV. In the TOF section, the converted ions fall on a start surface at 15◦ incidence and produce secondary electrons which propagate towards start MCP to produce a start pulse. The START surface is a highly polished mono-crystalline tungsten plate that provides specular particle reﬂection with low angular scattering. The surface material is also selected for high secondary electron yield and stable surface properties. The ions that are reﬂected from the start surface move mostly in form of neutral atoms toward the STOP MCP to produce the stop pulse. The diﬀerence in the timing of start and stop pulse gives the TOF. Since the distance the particle traverses between start surface and stop MCP is known from the instrument geometry, the velocity of the particle is calculated. As the energy of the ions from the energy analyzer is known with the information on post acceleration, the mass of the particle is deduced. The START MCP uses two sets of position sensitive anodes for the accurate determination of time-ofﬂight path length as well as to know the arrival direction of particles.6,9,12,15 Characteristics of CENA are summarized in Table 1. SWIM is an ion-mass analyzer; which is used for the observation of ions in the lunar vicinity in the energy range 0.01–15 keV/q. SWIM consists of an electrostatic deﬂector to scan the arrival direction of incident ions, an electrostatic energy analyzer and a time-of-ﬂight section.16 A schematic view of SWIM is shown in Fig. 3. The electrostatic deﬂector consists of two electrodes. By suitably varying the voltages applied on the two plates, sweeping of the arrival direction of ions is done thereby achieving a total azimuthal coverage of 180◦. Following the deﬂector, particles enter a cylindrical electrostatic analyzer with a deﬂection angle of 127◦ . Varying the voltages applied on one of its electrodes provides energy analysis of the ions. Additionally, at

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SARA Experiment Aboard Chandrayaan-1 Mission Table 1. Parameter Particle to measure Energy range Energy resolution Mass range (amu) Mass resolution Full ﬁeld-of-view Angular resolution (FWHM) G-factor/sector without eﬃciency Eﬃciency (%) Sensor mass

Fig. 3.

155

Characteristics of CENA and SWIM. CENA

SWIM

Neutrals 10 eV–3.3 keV 50% 1–56 H, O, Na/Mg/Si/Al-group, K/Ca-group, Fe-group 15◦ × 160◦ 9◦ × 25◦ (E > 50 eV)

Ions 10 eV/q–15 keV/q 7% 1–40 H+ , He++ , He+ , O++ , O+ , >20 amu 9◦ × 180◦ 4.5◦ × 22.5◦

10−2 cm2 sr eV/eV (at 3.3 keV) 0.2 cm2 sr eV/eV (at 25 eV) 0.01–1 1977 g

∼5 × 10−4 cm2 sr eV/eV (0.5–3 keV) for H+ 0.1–5 452 g

3D view of SWIM with typical particle trajectory (taken from Ref. 9).

the entrance of the energy analyzer, a UV-trap reduces sensitivity to UV photons. After exiting the energy analyzer, the ions are post accelerated by 400 V and enter the TOF section. The ions fall on start surface at grazing incidence and produce secondary electrons which are detected by

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start CCEM (Ceramic Channel Electron Multipliers) to produce start pulse. The ions gets reﬂected from the start surface mainly as neutral atoms and fall on the STOP surface producing secondary electrons which are collected by the STOP CCEM to produce stop pulse. The diﬀerence in timing of start and stop pulse gives the TOF from which the mass per charge of the ions are calculated in a similar way as described for CENA above. As in CENA, the start surface is made of mono-crystalline polished tungsten. The STOP surface, made of graphite coated by MgO, is optimized for high secondary electron yield and high UV absorption. Characteristics of SWIM are summarized in Table 1. CENA and SWIM are electrically interfaced with the spacecraft through the DPU (cf. Fig. 1). The DPU commands and controls the sensors. It powers the sensors, sets the sensor modes and telemetry modes, acquires data from the sensors, does the time-integration and binning, formats the data, and transfers the data to telemetry. The DPU is built around ADSP21060 DSP processor running at 32 MHz clock frequency and having 4 Mb on-chip memory for operational software. Data is transferred from DPU to spacecraft through MIL-STD-1553 bus. Along with the science data, DC-DC converter monitoring, current monitoring for the sensor units and other sensor health check data of the scientiﬁc instruments are digitized and transmitted to spacecraft telemetry through 1553 bus.6,9 SARA is mounted on the top deck of the 3-axis stabilized Chandrayaan1 spacecraft such that CENA is nadir viewing. SWIM is mounted at nearly 90◦ to CENA. The full ﬁeld of view (FOV) of CENA is 160◦ × 15◦ and that of SWIM is 180◦ × 9◦ . CENA has 7 and SWIM has 16 viewing directions. In this conﬁguration, due to the 180◦ ﬁeld of view of SWIM, a few viewing directions of SWIM will be looking at the lunar surface. The mounting geometry of SARA and the ﬁeld of view of the sensors along with the orbital motion of Chandrayaan-1 are as shown in Figs. 4(a) and 4(b).

3. First Observations and Results Because high voltages were used in SARA, suﬃcient outgassing time was required before the ﬁrst switch on. SARA was ﬁrst switched on two months after the launch and commissioning was completed by the end of January 2009. Regular operations of SARA began on 5 February 2009. An example of the ion data is shown in Fig. 5: Energy spectra of ions as measured by SWIM during its ﬁrst continuous observation on 25 January 2009 is shown. At this time, the Moon was upstream of the

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(b)

Fig. 4. (a) Mounting of CENA, SWIM and DPU on the top deck of the Chandrayaan-1 along with the FOV. (b) Field of view of CENA and SWIM at the poles and equator along with the orbit of Chandrayaan-1 for 6 February 2009. Day-night terminator is marked in the ﬁgure. CENA is nadir (Moon-facing) viewing and SWIM views at 90◦ to CENA.

Fig. 5. The energy spectra of solar wind ions observed by SWIM on 25 January 2009. The solid line represents the spectra of the impacting solar wind ions and the dotted line represents the spectra of the ions reﬂected from the lunar surface. The plot shows integrated counts for 36 minutes centered at 14:12 UT.

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Earth’s bowshock. SWIM measurements show that the solar wind has an energy of ∼500 eV/q on this day. The peak corresponding to that of He++ is seen around 1000 eV/q. The reﬂected solar wind ions show a broader energy spectrum which also peaks around 500 eV/q. Recently, Kaguya MAP/PACE has also observed reﬂected ions from lunar surface.17 Another example of SARA data is shown in Fig. 6, where energy spectra of impinging solar wind protons from SWIM observation are compared with energy spectra of reﬂected energetic neutral hydrogen atoms from CENA observation on 6 February 2009.18 . Data from three diﬀerent orbits are shown. The reﬂected neutral ﬂux varies accordingly with the intensity of the impinging solar wind ions. The spectra of reﬂected hydrogen ENAs are broader and have a distinct upper energy of ∼250 eV, after which the ﬂux falls oﬀ rapidly. The solar wind protons have peak energy around 500 eV. The observed energy of ENAs indicate that solar wind protons lose signiﬁcant amount of energy before getting backscattered as neutral hydrogen atoms. The fraction of

Fig. 6. Flux of reﬂected hydrogen ENAs observed by CENA (circles) and solar wind protons observed by SWIM (square) for 6 February 2009 [taken from Ref. 18]. The data is for 3 orbits which are indicated by the 3 lines each for backscattered hydrogen ENAs and solar wind protons. Solid lines represent the data for the orbit with dayside equator crossing at 05:22 UTC, dashed lines represent the orbit with dayside equator crossing at 07:20 UTC and the dotted lines represent the orbit with dayside equator crossing at 09:18 UTC. Error bars shown represent knowledge of the instrument geometric factor (1σ).

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reﬂected ENAs with respect to the ﬂux of incident solar wind protons is found to be around 20%.18

4. Discussion CENA observations show that Moon is a strong source of ENAs. About 20% of the incident solar wind ﬂux is found to be backscattered as ENAs from the lunar regolith. Most of these hydrogen ENAs have energy less than half of the impacting solar wind protons. Thus, SARA observations are in contrast with the earlier suggestions that only ∼1% of incident solar wind ions are backscattered from lunar surface as neutral atoms.4 The solar wind ions which are absorbed or implanted in the lunar regolith can get released to the lunar exosphere due to processes such as diﬀusion, solar wind sputtering and micrometeorite impact vaporization.19 The CENA observation of high hydrogen reﬂection rate from lunar surface calls for a re-look at hydrogen inventory of the lunar regolith. The signiﬁcant energy loss of the observed ENAs compared to impinging solar wind is due to elastic and inelastic processes during surface-plasma interactions, and possibly other processes such as retarding of solar wind ions by a positive surface potential. High hydrogen reﬂection is expected to occur on other regolith covered atmosphere-less bodies in the solar system, such as Mercury, asteroids, or Phobos. Recently, IBEX8 also observed backscattered hydrogen ENAs from the Moon albeit from a much larger distance and found an ENA albedo of ∼10%. The IBEX results are consistent with the ﬁndings of the SARA. The high hydrogen reﬂection may reduce the amount of solar wind hydrogen available for trapping in permanently shadowed areas near the poles.20,18 This may have implications for one of the proposed mechanisms for the formation of water and OH in lunar regolith by the implantation of solar wind hydrogen21; the presence of water on lunar surface has recently been unambiguously evidenced by Moon Mineralogy Mapper experiment on Chandrayaan-1,22 and conﬁrmed by observations made by Cassini VIMS23 and Deep Impact’s HRI-IR Spectrometer.24 In addition to the measurement of direct solar wind, SWIM has observed solar wind ions backscattered from the lunar surface.25 The reﬂected ions can be picked up by the solar wind convection electric ﬁeld and get accelerated and may return back to the lunar surface again or can be lost. These ions may signiﬁcantly contribute to the changes in the global plasma environment around the Moon.26

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Acknowledgments The eﬀorts at Space Physics Laboratory, Vikram Sarabhai Space Centre, were supported by Indian Space Research Organization (ISRO), while the eﬀorts at the Swedish Institute of Space Physics and University of Bern were supported in part by European Space Agency (ESA). References 1. D. E. Robbins, J. Geophys. Res. 75 (1970) 1178. 2. P. Wurz, Proceedings of the 11th European Solar Physics Meeting — The Dynamic Sun: Challenges for Theory and Observation, ESA SP–596 (2005). 3. R. R. Vondrak, Proceedings of the 2nd conference on Lunar Bases and Space Activities 1 (1992) 337. 4. D. H. Crider and R. R. Vondrak, Adv. Space. Res. 30 (2002) 1869. 5. F. L. Hinton and D. R. Taeusch, J. Geophys. Res. 69 (1964) 1341. 6. A. Bhardwaj, S. Barabash, Y. Futaana, Y. Kazama, K. Asamura, D. McCann, R. Sridharan, M. Holmstr¨ om, P. Wurz and R. Lundin, J. Earth Sys. Sci. 114 (2005) 749. 7. Y. Futaana, S. Barabash, M. Holmstr¨ om and A. Bhardwaj, Planet Space Sci. 54 (2006) 132. 8. D. J. McComas, F. Allegrini, P. Bochsler, P. Frisch, H. O. Funsten, M. Gruntman, P. H. Janzen, H. Kucharek, E. Mobius, D. B. Reisenfeld and N. A. Schwadron, Geophys. Res. Lett. 36 (2009) L12104. 9. S. Barabash, A. Bhardwaj, M. Wieser, R. Sridharan, T. Kurian, S. Varier, E. Vijayakumar, V. Abhirami, K. V. Raghavendra, S. V. Mohankumar, M. B. Dhanya, S. Thampi, K. Asamura, H. Andersson, Y. Futaana, M. Holmstr¨ om, R. Lundin, J. Svensson, S. Karlsson, R. D. Piazza and P. Wurz, Current Sci. 96 (2009) 526. 10. R. P. Lin et al., Lunar Surface Magnetic Fields and Their Interaction with the Solar Wind: Results from Lunar Prospector, Science 281 (1998) 1480. 11. M. Wieser, S. Barabash, Y. Futaana, M. Holmstr¨ om, A. Bhardwaj, R. Sridharan, M. B. Dhanya, A. Schaufelberger, P. Wurz and K. Asamura, Geophys. Res. Lett. Submitted (2009). 12. Y. Kazama, S. Barabash, A. Bhardwaj, K. Asamura, Y. Futaana, M. Holmstr¨ om, R. Lundin, R. Sridharan and P. Wurz, Adv. Space. Res. 37 (2006) 38. 13. M. Wieser, P. Wurz, K. Br¨ uning and W. Heiland, Nucl. Instr. Meth. B 192 (2002) 370. 14. D. Hovestadt, M. Hilchenbach, A. B¨ urgi, B. Klecker, P. Laeverenz, M. Scholer, H. Grunwaldt, W. I. Axford, S. Livi, E. Marsch, B. Wilken, H. P. Winterhoﬀ, F. M. Ipavich, P. Bedini, M. A. Coplan, A. B. Galvin, G. Gloeckler, P. Bochsler, H. Balsiger, J. Fischer, J. Geiss, R. Kallenbach, P. Wurz, K. U. Reiche, F. Gliem, D. L. Judge, H. S. Ogawa, K. C. Hsieh, E. M¨obius, M. A. Lee, G. G. Managadze, M. I. Verigin and M. Neugebauer, Solar Phys. 162 (1995) 441.

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15. Y. Kazama, S. Barabash, M. Wieser, K. Asamura and P. Wurz, Planet. Space Sci. 55 (2007) 1518. 16. D. McCann, S. Barabash, H. Nilsson and A. Bhardwaj, Planet Space Sci. 55 (2007) 1190. 17. Y. Saito, S. Yokota, T. Tanaka, K. Asamura, M. N. Nishino, M. Fujimoto, H. Tsunakawa, H. Shibuya, M. Matsushima, H. Shimizu, F. Takahashi, T. Mukai and T. Terasawa, Geophys. Res. Lett. 35 (2009) L24205. 18. M. Wieser, S. Barabash, Y. Futaana, M. Holmstr¨ om, A. Bhardwaj, R. Sridharan, M. B. Dhanya, P. Wurz, A. Schaufelberger and K. Asamura, Planet. Space Sci. 57 (2009) 2132. 19. P. Wurz, U. Rohner, J. A. Whitby, C. Kolb, H. Lammer, P. Dobnikar, J. A. Martin-Fernandez, Icarus 191 (2007) 486. 20. H. H. Schmitt, G. L. Kulcinski, J. F. Santarius, J. Ding, M. J. Malecki and M. J. Zalewski, Proceedings of Space 2000: the seventh International Conference and exposition of engineering, Construction, operations, and business in space, 653 (2000). 21. L. Starukhina and Y. Shkuratov, Icarus 147 (2000) 585. 22. C. M. Pieters, J. N. Goswami et al., Science 326 (2009) 568. 23. R. N. Clark, Science 326 (2009) 562. 24. J. M. Sunshine et al., Science 326 (2009) 565. 25. A. Bhardwaj, S. Barabash, M. B. Dhanya, M. Wieser, Y. Futaana, M. Holmstr¨ om, R. Sridharan, P. Wurz, A. Schaufelberger and K. Asamura, in Solar Wind Twelve: Proceedings of the twelfth Solar Wind Conference published by American Institute of Physics, in press (2009). 26. M. Holmstrom, M. Wieser, S. Barabash, Y. Futaana and A. Bhardwaj, J. Geophys. Res. in press (2009).

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

THE DOPPLER-SONNEMANN EFFECT (DSE) ON THE PHOTOCHEMISTRY ON MARS∗ M. GRYGALASHVYLY†,‡ , P. HARTOGH§ , G. R. SONNEMANN†,§,¶ and A. S. MEDVEDEV§ † Leibniz-Institute of Atmospheric Physics at the University Rostock in K¨ uhlungsborn, Schloss-Str.6, D-18225 Ostseebad K¨ uhlungsborn, Germany ‡ [email protected] ¶ [email protected] § Max-Planck-Institute for Solar System Research, Max-Planck-Str. 2, D-37191 Katlenburg-Lindau, Germany [email protected]

Based on a new coupled global 3D-model of the dynamics and chemistry of the Martian atmosphere termed MAOAM (Martian Atmosphere: Observations And Modeling) we investigate the inﬂuence of the zonal wind on the chemistry in the Martian atmosphere. This model was developed to investigate and interpret submillimetre observations of a number of important chemical species in the Martian atmosphere planned to measure by means of the Herschel Space Observatory in fall 2009 and summer 2010. The solar insolation periodically excites the chemistry of the atmosphere. The change of the period of 1 Martian day of the solar excitation for an air parcel moving with or against the rotation of Mars can be calculated by a modiﬁed Doppler formula. The calculation of the shift of the period resulting from the zonal wind using the advanced threedimensional GCM MAOAM proved that the eﬀect is essentially stronger on Mars than on Earth. The change of the period also entails a considerable change of the diurnal variation of the chemical active constituents if the characteristic chemical time ranges in the order of 1 day or the duration of sunset. We calculated the relative deviations of the concentrations of the individual constituents computed on the one hand with the full wind system and on the other hand for zero zonal wind. As the calculations made clear this so-called Doppler-Sonnemann eﬀect (DSE) has the broad implication on the Martian photochemistry as it inﬂuences the values and altitude of night time maximum of ozone and other chemically active minor constituents.

∗ This

work is supported by the German Research Community DFG, grant So 268/4-1. 163

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1. Introduction 1.1. Some historical remarks Sonnemann and Fichtelmann [1987] found that the photochemical system of the mesosphere represents a driven non-linear chemical oscillator. In this paper was shown that the photochemical system produces resonances if the period of an artiﬁcial day changes. In the joint paper Fichtelmann and Sonnemann [1992] showed that under idealized conditions this system is able to create subharmonic oscillations and chaos. The term photochemical Doppler eﬀect was ﬁrst introduced by Sonnemann et al. [1999]. The change of the period of the solar insolation if an air parcel zonally moves with or against the rotation of the Earth was discussed and the modiﬁed Doppler formula was derived. The term zonal wind eﬀect on the photochemistry (ZWEPC) was introduced in 2001 by Sonnemann. He used a highly idealized 1D-model with the zonal wind as control parameter to investigate the response of the photochemical system on the zonal wind in the Earth’s middle atmosphere. In this paper it was shown that the diurnal variations drastically changes in the upper mesosphere/mesopause region if the system approaches a resonance-like condition. This condition will be reached if the response of the chemical system to the external excitation by the solar insolation has phase shift π/2. An indication for resonance can be shift of the daytime maximum of ozone to the sunset. Later Sonnemann and Grygalashvyly [2003] examined the photochemical Doppler-Sonnemann eﬀect (DSE) on the basis of the 3D-model COMMA-IAP, and they found a pronounced impact of the zonal wind on the diurnal variation of the chemical active minor constituents above the lower mesosphere. In context with the interpretation of the so-called tertiary ozone maximum and the winter anomaly of the night-to-day ratio of ozone in the mesosphere the importance of the sunset period was examined. This period becomes important if the chemical system time as deﬁned by K¨orner and Sonnemann [2001] ranges in the order of the characteristic time of sunset. In Sonnemann et al. [2006] the DSE was applied to the Martian atmosphere. 1.2. The basic model description The GCM MAOAM (Mars Atmosphere and Observation And Modeling) is a part of a project in the frame of the research priority program “Mars and Terrestrial planets” of the German Research Foundation. It consists of a dynamical model which was coupled with a chemistry-transport model

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(CTM). The dynamic model was described in Medvedev and Klaassen [2000] and Hartogh et al. [2005] and the chemical transport model in Sonnemann et al. [2006]. For details we refer to these papers and quotations in they and repeat only in brief outlines the fundamentals of the model. The dynamic model is a ﬁnite diﬀerence (grid point) model basing on the primitive equations of the hydrodynamics in log-pressure coordinates. It comprises a set of physical parametrizations such as the radiative transfer calculations, the surface energy balance, and the subgrid scale dynamics. For the radiative transfer in the gaseous CO2 an optimized version of the exact non-LTE code of Kutepov et al. [1998] is used. In the near infrared bands the parametric formula of Forget et al. [1999] was employed. Using a scheme of Kuroda et al. [2005] the radiative eﬀect of dust in the whole spectrum between 0.1 and 200 µm was taken into account. The balance between the solar and thermal components of the net radiative, the sensible heat ﬂux, and the ﬂux into the soil determine the temperature evolution. The thermal albedo [Christensen 2001] and the distribution of the surface thermal inertia [Mellon et al. 2000] is based on the Thermal Emission Spectrometer (TES) measurements and the Martian topography is based on the Mars Orbiter Laser Altimeter (MOLA) proﬁles [Delacourt et al. 2003]. The vertical turbulent mixing parameterization for the free atmosphere basing on the Richardson number [Holtslag and Boville 1993] is used in the entire model region. In order to prevent super-adiabatic vertical temperature gradients the scheme was supplemented by an energy conserving convective adjustment scheme. Employing the spectral scheme of Medvedev and Klaasen [2000] coupled with orographic wave sources according to McFarlane [1987], the impact of non-resolved gravity waves on the wind and temperature ﬁeld was parameterized. The CTM consists of three separated codes employing the operator splitting method. The chemical code includes 22 constituents. It comprises 70 chemical and 24 photo-dissociation reactions and is based on a family concept [Shimazaki 1985]. The concentrations of the long-lived constituents such as CO2 , H2 , CO, O2 are determined by the initial conditions. The transport code considers advective and diﬀusive transport. The diﬀusion includes molecular and turbulent diﬀusion. The eddy diﬀusion proﬁle increases exponentially from ground up to 110 km from 105 to 108 cm2 s−1 . In order to reduce the numerical diﬀusion we use a transport scheme developed by Walcek [2000] and characterized by nearly zero numerical diﬀusion. The radiation code provides under the special conditions of the

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Martian orbit all relevant dissociation rates depending on height, solar zenith angle and season. 2. The Photochemical Doppler Eﬀect The chemistry of a rotating planet is periodically excited by solar radiation. Consequently, the chemically active species are marked by a certain diurnal variation. The odd oxygen-odd hydrogen system is a nonlinear driven chemical oscillator enforced by the periodic solar insolation [Sonnemann and Fichtelmann 1987]. Such systems are able to create resonances if the eigen frequency of the system corresponds with the frequency of the external forcing. The period of solar insolation of an air parcel moving along a parallel with or against the planet rotation shortens or prolongs according to the zonal wind direction and its velocity. The Doppler-Sonnemann eﬀect (DSE) describes the response of the chemical system of the planet atmosphere on the change of the period of solar insolation due to the inﬂuence of the zonal wind. The changed period of solar insolation of an air parcel for the case of non-zero zonal wind can be calculated by a modiﬁed Doppler formula: TDP =

Tplanet 1 + uzonal /uplanet

(1)

where uplanet = 2π(Rplanet + h) cos φ/Tplanet — rotation velocity of the planet at a certain altitude and latitude, R — radius of the planet (for Mars RMars ≈ 3394.5 km), h — altitude above the surface, φ — latitude and Tplanet — period of rotation (for Mars Tplanet ≈ 88775 s). The sensitivity to the zonal wind increases with increasing latitude according to cosφ. The radius of Mars is smaller than the radius of Earth but the zonal winds can be essentially stronger than in the mesospheric wind jet on Earth, thus DSE should be more signiﬁcant. Figure 1a shows the zonally averaged zonal wind on Mars according to calculations by the GCM MAOAM. The corresponding Doppler period displays Fig. 1b. Strongest deviations from a period of 24 Martian hours occur in the polar regions but also close to the equator. In case that the zonal wind blows into the direction of the planet rotation (west wind), the Doppler period shortens, otherwise it prolongs. One has to distinguish between that what happens in the moving air parcel and that what will be observed at a ﬁxed position. All ﬁgures shown use the last form of presentation.

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Fig. 1. a (left) and b (right): Zonally averaged zonal wind (1a) and the corresponding Doppler period (1b) for Ls = 270◦ (North Martian winter).

The solar radiation acts by the dissociation rates on the diﬀerent species (x). These dissociation rates are time-dependent, Jx = Jx(t). Over the daytime the dissociation rates alter relatively few whereas during sunset und sunrise the change dJX (t)/dt becomes large. But during night this quantity is zero. Normally, the photochemical system possesses an unequivocal solution which will be approached with a characteristic response time, but this solution depends for zero dissociation rates on the initial conditions and the kind of transition to the night-time conditions. The response time for a complex chemical system is usually not constant but it becomes larger when the system approaches its ﬁnal stage. For a very small characteristic system time τsys (τsys 1 day) the chemical system follows immediately the changing radiation conditions. For τsys 1 day (disregarding transports) the system is too inert to follow the changing conditions and it responses accordingly to the diurnally averaged dissociation rates.

3. Sunset Conditions In case the characteristic time of the sunset corresponds to the characteristic chemical system time the sunset conditions essentially determine the distribution of the odd oxygen-odd hydrogen (O, O3 )-(H, OH, HO2 ) system during night. A dissociation rate normalized to unity for the constituent x is deﬁned by the relation [Hartogh et al., 2004]: ∗ JX (χ, z) = JX (χ, z)/JX (0, z)

(2)

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with χ-solar zenith angle and z-altitude. The inequality is valid: ∗ ∗ (χ, z) ≤ JO (χ, z) JH∗ 2 O (χ, z) ≤ JO 2 3

(3)

The odd oxygen production becomes small for increasing solar zenith angle. However, the production of hydrogen radicals destroying odd oxygen decreases faster, thus odd oxygen could increase due to a reduced loss under the condition of maintained small production of odd oxygen. As the dissociation of ozone is almost undiluted until grazing incidence of radiation a permanent odd oxygen loss results from this fact so that the inequality [O]day + [O3 ]day > [O]night + [O3 ]night

(4)

is also valid although normally [O3 ]night > [O3 ]day . An eﬀective odd oxygen destroying catalytic cycle is given by H + O3 → OH + O2 OH + O → H + O2

(5)

net : O + O3 → 2O2 Although as mentioned above, according to (3), the dissociation rates of water vapor decreases faster with zenith angle than the dissociation rates of ozone, but the lifetime of the hydrogen radicals is long enough eﬀectively to act in the catalytic cycle. A second process of odd oxygen destruction is given by the Chapman reaction O + O3 → 2O2

(6)

The reaction rate is relatively small so that this process becomes relevant only for large ozone concentration. During sunset atomic oxygen is permanently produced by dissociation of ozone (without odd oxygen production, O3 is only converted into the odd oxygen constituent O) in the state O(1 D) which is able to oxidize water vapor and, consequently, additionally to form hydroxyl which acts in the catalytic cycle (3). H2 O + O(1 D) → 2OH

(7)

In order to get a nightly ozone level as high as possible the air parcel should traverse the sunset period as fast as possible. Meaning, the zonal wind should blow in direction of rotation of Mars that is for west wind condition (coming from west). However, a west wind also acts ambivalent. During

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daytime when odd oxygen is formed a west wind shortens the duration of odd oxygen formation. If the daytime is too short to reach the equilibrium then the west wind reduces the daytime level of odd oxygen. Hence the sunset starts from a lower level of the odd oxygen mixing ratio. This fact has to take into consideration if interpreting calculated results.

4. Results and Discussion The numerical experiment takes place in the following manner: the model runs with the full wind system until the day n, after that the zonal wind is switched of and the mixing ratios are registered after the ﬁrst day of zero wind (a hypothetical scenario in order to estimate the inﬂuence of zonal wind) calculations. In order to demonstrate the importance of the DSE in the Martian atmosphere we restrict the presentation in the paper to results for an areocentric longitude of Ls=270◦ and presented only few exemplary ﬁgures. To display the inﬂuence of the DSE on the chemical constituents we calculate the relative deviation R=

[X]U=0 − [X]U=0 · 100% [X]U=0

(8)

where [X]U=0 and [X]U=0 are the concentrations of the chemical constituents in cases of calculation without and with consideration of the zonal wind. The case R < 0 means that the concentration increases without zonal wind or in other words the zonal wind reduces the concentration of this constituent in the real atmosphere. For example, R = −100% means [X]U=0 = 2[X]U=0 . R > 0 means the concentration decreases without zonal wind or in other words the zonal wind enlarges the concentration. For example, R = 50% means [X]U=0 = [X]U=0 /2. Figure 2a–d show the diurnal variation of the relative deviation of ozone (a), atomic oxygen (b), hydroxyl (c) and atomic hydrogen (d) at 52.5◦ N for Ls = 270◦ . The relative deviation of ozone is positive for altitudes from 10 to 60 km with maximum of inﬂuence between 45 and 50 km. The relative deviation of atomic oxygen mirrors roughly the relative deviation of ozone. As OH also results from the reaction of atomic hydrogen with ozone this constituent reﬂects some typical features of the relative ozone deviation but it is also marked by a diﬀerent behavior particularly in the domain below 30 km.

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Fig. 2. a–d Diurnal variation of the relative deviation of ozone (a), atomic oxygen (b), hydroxyl (c) and atomic hydrogen (d) at 52.5◦ N for Ls = 270◦ .

Figure 3a–d show the diurnal variation of the relative deviation of ozone (a), atomic oxygen (b), hydroxyl (c) and atomic hydrogen (d) at 12.5◦ S for Ls = 270◦ . This latitude correspond to the region with Doppler period larger than one day, meaning that due to negative zonal wind the period of solar insolation is larger than 24 hours and particularly at this latitude it reaches a maximum with values of 40–44 hours at 45 km. The photochemical system of Martian atmosphere is highly nonlinear and the distributions of minor chemical constituents depend on balance between production and loss processes and transport. Thus, simple interpretation should be avoided and we can only point out the facts: a prolonged period of solar insolation due to a zonal wind against the rotation of the planet corresponds to a reduction of the concentration of the oddoxygen constituents and the opposite is valid for a zonal wind blowing

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Fig. 3. a–d Diurnal variation of the relative deviation of ozone (a), atomic oxygen (b), hydroxyl (c) and atomic hydrogen (d) at 12.5◦ S for Ls = 270◦ .

with the rotation of the planet. Partial explanation why the reduction of odd oxygen constituents correspond to negative zonal wind (TDP > 24 h) and vice versa was done in chapter 3, but additionally we should keep in mind that behavior of odd oxygen and odd hydrogen is determined by 4 inﬂuences: prolongation or shortening of night time period, period of sunset, period of daytime and, possibly, by eﬀect of resonance, which discussed below. The behavior of the chemical system diﬀers depending on the time of day. A prolongation of the time of sunset and of the night reduces the concentration of both odd families whereas their concentrations increase during daytime due to prolonged action of the net production by photolysis. Thus the response of the chemical system depends on local time, season, altitude and latitude and can be opposite for the same Doppler shift under diﬀering conditions. This is also clearly to recognize in the

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presented ﬁgures. Although the Doppler period varies only slightly with height but the response of the chemical system depends strongly on altitude due to changing system parameters such as the number density of the air or humidity. Analogically with other oscillators we can suppose that if eigen period of photochemical system of an air parcel will be equal to period of external forces (TDP ), one can expect like-resonance eﬀect. The DSE has a strong inﬂuence on the distribution of minor chemical constituents if the photochemical lifetime ranges in the order of the photochemical Doppler period TDP . A multi-component system can generally also possess more than one eigen frequency, meaning it can produce more than one maximum for varying frequency of the external excitation. The amplitude can also become a minimum with varying Doppler period [Sonnemann and Fichtelmann 1987]. In case that one species i of the family dominates all other constituents of the family the characteristic time becomes τf am = (Li )−1 . This is the case for atomic oxygen at and above its maximum around 50 to 60 km. In the domain below ozone dominates. Such likeresonance behavior was found for ozone night time maximum which placed between 30 and 50 km depending on season and latitude. For mean and equatorial latitude, this maximum tend to be near quasi-resonance line, where τOx = TDP , and maximum of absolute deviation is placed near this line. Thus we can make a conclusion that resonance eﬀect play role on formation and distribution of ozone night time maximum on Mars. We should notice that τOx is not a resonance frequency and real resonance frequency of photochemical system can be found just numerically but it should be larger than the largest individual characteristic time (τsys > τOx and τHx ). In Fig. 4 the red line stands for the place where the diurnal mean of the characteristic time of the odd oxygen family agrees with the diurnal mean Doppler period (the frequency of the external force). The blue line represents the same state of aﬀairs but for the odd hydrogen family. The ﬁgures display the diurnal variations of the absolute amounts and the absolute deviations due to the DSE for ozone and hydroxyl as representatives of both families for Ls = 270◦ and 7.5◦ S latitude. Obviously, the lines lie in the vicinity of the maxima of these constituents.

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Fig. 4. a–d Diurnal variation of ozone concentration (4a), absolute deviation of ozone (4b), hydroxyl concentration (4c), absolute deviation of hydroxyl (4d) at 7.5◦ S. The red and blue lines indicate where the Doppler period equals the characteristic time of the odd oxygen and odd hydrogen families.

5. Summary and Conclusion In order to understand the diurnal variation of the chemical active minor constituents in the Martian atmosphere one has to consider the impact of the zonal wind. The zonal wind changes the period of solar insolation of a zonally moving air parcel. The change of the period can be described by a modiﬁed Doppler formula. The response of the chemical system on the zonal wind depends on local time and is normally opposite between daytime and nighttime. The reason of this behavior follows from the fact that during daytime the photolysis forms the odd constituents of both families whereas during the night these constituents will be destroyed. The strong zonal winds and the small radius of Mars entail a pronounced eﬀect in

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regions where the characteristic chemical time corresponds to the Doppler period. Such resonance-like eﬀect possibly inﬂuence on values and altitude of night time maximum of ozone at mean and equatorial latitudes. The response of the chemical system depends on local time, season, altitude and latitude and can be opposite for the same Doppler shift. The high variability of the Martian wind also entails a high variability of the chemical active minor constituents for the same place and time. The sunset period becomes important if the characteristic chemical system time ranges in the order of the duration of sunset (few hours). The correct calculation of the distribution of the concentration of the chemical active constituents requires the use of sophisticated 3D-models of the dynamics and chemistry which considers correctly the impact of the zonal wind.

Acknowledgments This work was supported by the German Research Community DFG, grants HA 3261/1-2 and So 268/4-1.

References 1. P. R. Christensen, J. L. Bandﬁeld, V. E. Hamilton et al., Mars Global Surveyor Thermal Emission Spectrometer experiment: Investigation description and surface science results, J. Geophys. Res. 106 (2001) 23,823– 23,872, 10.1029/2000JE001370. 2. C. Delacourt, N. Gros, P. Allemand and D. Baratoux, Online Mars digital elevation model derived from MOLA proﬁles, EosTrans. AGU 84(52) (2003). 3. B. Fichtelmann and G. Sonnemann, Non-linear behaviour of the photochemistry of minor constituents in the mesosphere, Ann. Geophys. 10 (1992) 719–728. 4. F. Forget, F. Hourdin, R. Fournier et al., Improved general circulation models of the Martian atmosphere from the surface to above 80 km, J. Geophys. Res. 104 (1999) 24,155–24,175. 5. P. Hartogh, C. Jarchow, G. Sonnemann and M. Grygalashvyly, On the spatiotemporal behavior of ozone within the upper mesosphere/mesopause region under nearly polar night conditions, J. Geophys. Res. 109 (2004) D18303, doi:10.1029/2004JD004576. 6. P. Hartogh, A. S. Medvedev, T. Kuroda et al., Description and climatology of a new general circulation model of the Martian atmosphere, J. Geophys. Res. 110 (2005) E11008, doi:1029/2005 JE002498. 7. A. A. M. Holtslag and B. A. Boville, Local versus nonlocal boundary-layer diﬀusion in a global climate model, J. Climate 6 (1993) 1825–1842. 8. U. K¨ orner and G. Sonnemann, Global three-dimensional modeling of water vapor concentration of the mesosphere-mesopause region and implications

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with respect to the noctilucent cloud region, J. Geophys. Res. 106 (2001) 9639. A. Kutepov, O. Gusev and V. Ogibalov, Solution of the non-LTE problem for molecular gas in planetary atmospheres: Superiority of accelerated lambda iteration, J. Quant. Spectrosc. Radiat. Transf. 60 (1998) 199–220. T. Kuroda, N. Hashimoto, D. Sakai and M. Takahashi, Simulation of the Martian atmosphere using a CCSR/NIES AGCM, J. M. Soc. Jap. 83 (2005) 1. N. A. McFarlane, The eﬀect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposphere, J. Atmos. Sci. 44 (1987) 1775–1800. A. S. Medvedev and G. P. Klaassen, Parameterization of gravity wave momentum deposition based on a nonlinear theory of wave spectra, J. Atmos. Solar-Terr. Phys. 62 (2000) 1015–1033. M. T. Mellon, B. M. Jakosky, H. H. Kieﬀer and P. R. Christensen, High resolution thermal inertia mapping from the Mars Global Surveyor Thermal Emission Spectrometer, Icarus 148 (2000) 437–455. T. Shimazaki, Minor constituents in the middle atmosphere, D. Reidel Publishing Company, Dordrecht, Holland (1985). G. R. Sonnemann, A. M. Feigin, Y. I. Molkov, On the inﬂuence of diﬀusion upon the nonlinear behavior of the photochemistry of the mesopause region, J. Geophys. Res. 104 (1999) 30591–30603. G. R. Sonnemann, The photochemical eﬀects of dynamically induced variations in solar insolation, J. Atmos. Sol. Terr. Phys. 63 (2001) 781–797. G. Sonnemann and B. Fichtelmann, Enforced oscillations and resonances due to internal non-linear processes of photochemical systems in the atmosphere, Acta Geod. Geophys. Mont. Hung. 22 (1987) 301–311. G. Sonnemann, and M. Grygalashvyly, The zonal wind eﬀect on the photochemistry within the mesosphere/mesopause region, Adv. Space Res. 32(5) (2003) 719–724. G. R. Sonnemann, P. Hartogh, A. S. Medvedev, M. Grygalashvyly and U. Berger, A new coupled 3D-model of the dynamics and chemistry of the Martian atmosphere and some problems of the chemical modeling, 2nd International Workshop Mars Atmosphere Modeling and Observations, 5.1.6, February 27th–March 3rd, Granada, Spain (2006). C. J. Walcek, Minor ﬂux adjustment near mixing ratio extremes for simpliﬁed yet highly accurate monotonic calculation of tracer advection, J. Geophys. Res. 105 (2000) 9335–9348.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

A NEW COUPLED 3D-MODEL OF THE DYNAMICS AND CHEMISTRY OF THE MARTIAN ATMOSPHERE∗ G. R. SONNEMANN†,‡,§ , P. HARTOGH‡,¶ , M. GRYGALASHVYLY†,∗∗ and A. S. MEDVEDEV‡ † Leibniz-Institute of Atmospheric Physics at the University Rostock in K¨ uhlungsborn, Schloss-Str.6, D-18225 Ostseebad K¨ uhlungsborn, Germany ‡ Max-Planck-Institute for Solar System Research, Max-Planck-Str. 2, D-37191 Katlenburg-Lindau, Germany § [email protected] ¶ [email protected] ∗∗ [email protected]

We introduce a new coupled global 3D-model of the dynamics and chemistry of the Martian atmosphere termed MAOAM (Martian Atmosphere: Observations And Modeling). It is based on the COMMA-IAP (COlogne Model of the Middle Atmosphere of the Institute of Atmospheric Physics) model adjusted to Martian conditions. The model consists of two separately running parts. The dynamic part of the model calculates the wind and temperature ﬁelds used in the chemistry-transport model (CTM). The model does not yet operate interactively in the sense that the calculated chemical ﬁelds do not feed back to the dynamical model part. In the paper we describe the fundamentals of the model and present ﬁrst results. We compare these outcomes with available observations and discuss them in terms of dynamics and chemistry.

1. Introduction Much of our current knowledge of the global circulation and composition of the Martian atmosphere results from diﬀerent spacecraft missions, such as the Mariner spacecrafts or the Viking mission in the 60’s and 70’s. Particularly the long-term meteorological in situ measurements carried out by the two landers during the Viking mission and remote observations of the atmospheric thermal structure obtained by the IRIS instrument aboard Mariner 9 [Zurek et al., 1992] yielded a lot of results. The signiﬁcant progress in our current knowledge of the Martian atmosphere has been made with the help of recent measurements with the Thermal ∗ This

work is supported by etc. 177

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Emission Spectrometer (TES) onboard Mars Global Surveyor (MGS) [Smith et al., 2001; 2002; 2004], the Planetary Fourier Spectrometer (PFS) [Formisano et al., 2005] and the instrument SPICAM (Spectroscopy for the Investigation of the Characteristics of the Atmosphere of Mars) onboard Mars Express [Fedorova et al., 2006; Quemerais et al., 2006; Lebonnois et al., 2006]. Since that time the understanding of the global circulation grew thanks to the adaptation of general circulation models of the Earth’s atmosphere to the Martian atmosphere. These models were originally developed for weather forecasting, climate simulating, and modeling of the dynamical processes in the Earth’s atmosphere. In this way dynamical models were employed [e.g. Haberle et al., 1993; Hourdin et al., 1993; Collins et al., 1996; Wilson and Hamilton, 1996; Forget et al., 1999; Haberle et al., 2003, Takahashi et al., 2003; Moudden and McConnell, 2005; Kuroda et al., 2005; Hartogh et al., 2005]. The development of sophisticated three-dimensional models of both chemistry and the dynamics of the Martian atmosphere is of particular interest because a permanent lack of measurements of all atmospheric species exists. There have been diﬀerent model investigations of the chemistry in the past, but most of them were only one-dimensional [e.g. Atreya and Gu, 1994; Nair et al., 1994; Wong and Atreya, 2003]. Moreau et al. [1991] developed a coupled 2D-model and recently Lef`evre et al. [2004] presented the ﬁrst 3D-model with coupled gas-phase chemistry and applied this model to questions related to ozone chemistry on Mars. Meanwhile a second dynamic-chemical 3D-model has been published by Moudden and McConnell [2006a]. As the average wind components are larger on Mars than on Earth and its diameter is smaller, the dynamics inﬂuences the distribution of the chemical active species more strongly. This applies especially to those species and chemical families with characteristic chemical times ranging in the order of the characteristic transport times but also to long-lived constituents such as water vapor. On the other hand the inﬂuence of chemical constituents on the dynamics is smaller compared with that in the Earth atmosphere. Consequently, one needs 3D-models in order to model the composition of the Martian atmosphere correctly. Care has to be taken concerning the boundary conditions of these models. Also the knowledge of the atmospheric dust (absolute amount, spatial distribution, particle size distribution, etc.) is essential. In the domain of suﬃciently low temperatures, heterogeneous nucleation strongly determines the distribution of water vapor, the source

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gas of hydrogen radicals which inﬂuence considerably the chemical state of the Martian atmosphere. In this paper we introduce a new coupled global 3D-model of the dynamics and chemistry of the Martian atmosphere termed MAOAM (Martian Atmosphere: Observations And Modeling). It is based on the COMMA-IAP (COlogne Model of the Middle Atmosphere of the Institute of Atmospheric Physics in K¨ uhlungsborn) model — particularly designed to investigate the mesosphere/lower thermosphere of the Earth — adjusted now to Martian conditions. In the second section we give a brief introduction to the new model and mention its main characteristics. First results of model calculations are presented in section three, where we show that the model is able to compute reasonable ﬁelds of the chemically active minor constituents agreeing rather well with observations. In the fourth section we discuss the results and consider the inﬂuence of the zonal wind on the distribution of the minor constituents. In this section we also compare our results with observations and other model calculations. Finally, in section ﬁve, we brieﬂy summarize the main results and give a short prognosis of further developments. 2. Model Description 2.1. Chemistry-transport model In this model version, the chemistry and transport were driven by the simulated GCM wind and temperature ﬁelds. No feedback from chemistry to dynamics was taken into account. This is a possible approach as the main absorber, that is CO2 , is in principle not or only very little changed by the chemistry. The chemical heating rates are at most in the order of 1-2 K day−1. They could play a limited role in the domain of maximum ozone formation during the polar night. Higher horizontal resolution is essential in reproducing the dynamic ﬁelds. For the chemistry transport model we used the same latitudinal and vertical discretization; however, we reduced the number of longitudinal grid points from 64 to 16 and interpolated the output from the dynamic model into the grid of the chemistry-transport model (CTM). The CTM is composed of three parts — the chemical solver, the transport, and the radiation codes. It was originally developed to investigate the terrestrial middle atmosphere [see also Sonnemann et al., 2005, and quotations therein] and was now adjusted to the Martian atmosphere. The model has a variable horizontal and vertical resolution. The simulations to be presented here were performed on 16

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longitudinal, 36 latitudinal grid points and 118 vertical levels from the ground to approximately 120 km. The integration time step amounts to 100 s for all modules of the CTM. The chemistry module includes 22 constituents and the reaction scheme considers 70 chemical reactions and 24 photodissociation processes. Most of the reaction rates are taken from Sander et al. [2003] as also used in the models of other groups [e.g. Lef`evre et al., 2004; Krasnopolsky, 2006a]. The chemical code is based on a family concept introduced by Shimazaki [1985]. The processes of chemistry in the atmosphere are computed with the implicit backward Euler method. The long-lived constituents are solved separately by an implicit scheme. The short-lived constituents are included in chemical families, which are solved as fully implicit subsystems. For the members of a family the equations are solved simultaneously. For the three-body reactions, which are the reactions with a quadratic loss process, following Shimazaki [1985], the non-linear terms are linearized by Taylor expansion. The constituents are transported by advection and by the turbulent and molecular diﬀusion. In order to suppress or essentially reduce the numerical diﬀusion we used a transport code developed by Walcek and Aleksic [1998], marked by almost zero numerical diﬀusion. The eddy diﬀusion proﬁle increases exponentially from 105 cm2 s−1 at the ground to 108 cm2 s−1 at 110 km. For calculations of eddy and molecular diﬀusion we use the implicit Thomas algorithm as described in Morton and Mayers [1994]. In the simulations to be presented, the total visible depth of the airborne dust is assumed horizontally uniform and set to 0.2 in visible wavelengths. The vertical distribution of aerosol is prescribed as in equations (2) and (3) of Lewis and Read [2003]. A varying amount of dust would have a strong inﬂuence on the chemistry; however, reporting the corresponding sensitivity is beyond the scope of this paper. Water vapor has a strong inﬂuence on other chemical constituents as it is the source of the hydrogen radicals. The process of water vapor condensation on dust is very signiﬁcant for the water vapor distribution in the Martian atmosphere [Montmessin et al., 2004]. We parameterize the eﬀect of condensation according to the scheme described by Haberle and Jakosky [1990] and Nair [1994]. In this scheme it is assumed that the partial pressure of water vapor never exceeds the saturation pressure of water vapor; i.e. if the relative humidity in a cell of the model is larger than 100% then the excess water vapor is moved to the lowest cell. This process is repeated over the whole atmospheric column. Instead of the models mentioned above we use the

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latest result for the saturation pressure (Psat) given by Murphy and Koop [2005] valid for temperatures (T) larger than 110 K: Psat [Pa] = exp(9.550426 − 5723.265/T + 3.53068 ln(T) − 0.00728332T) (1) The lower boundary condition for water vapor relates to the water vapor column abundance measured by MGS/TES (MGS — Mars Global Surveyor; Smith et al., 2001, 2002, 2004) taking into calculation a constant density scale height. The process of condensation in the Martian atmosphere seems to be more complicated than on Earth, as it also includes nucleation of carbon dioxide and hydrogen peroxide (H2 O2 ). In the present version of the model we only consider the nucleation of water vapor. The initial distributions of long-lived species correspond to the latest results of measurements. The initial value of the mixing ratio of carbon monoxide was chosen to 8 · 10−4 ranging within the interval measured by Krasnopolsky [2003], who published values between 7 and 15 · 10−4. The initial value of the molecular oxygen mixing ratio used in the model amounts to 1.2 · 10−3 , which corresponds to values given by Trauger and Lunine [1983] who found a column density of 2.28 · 1020 cm−2 corresponding to a mixing ratio of 1 to 1.5 · 10−3 for uniformly mixed O2 . The molecular hydrogen mixing ratio employed is 17 ppmv according to results published by Krasnopolsky and Feldman [2001]. The latest results for an upper limit of nitric oxide predict a mixing ratio of 1.7 · 10−9 [Krasnopolsky, 2006b, 2006c]. We chose as initial condition a moderate mixing ratio of 0.6 · 10−9 . 2.2. Dynamical model The dynamical general circulation model was described in detail by Hartogh et al., [2005], Medvedev and Hartogh [2007]. Brieﬂy, it is a ﬁnite diﬀerence (grid point) model based on the primitive equations of the hydrodynamics in log-pressure coordinates. The horizontal resolution used in the simulations is 64 × 36 grid points in longitude and latitude. In the vertical, 118 log-pressure levels span the atmosphere from the surface to approximately 120 km. The model includes a comprehensive set of physical parameterizations: the radiative transfer calculations, the surface energy balance, and the subgrid scale dynamics. The radiative transfer in the gaseous CO2 15 µm band is calculated employing two radiation schemes. In the lower atmosphere, a local thermodynamic equilibrium (LTE) scheme of

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Nakajima et al., [2000] is used in the model. In the upper atmosphere, an optimized version of the exact non-LTE code of Kutepov et al., [1998] is applied. The cooling rates computed with both LTE and non-LTE schemes are smoothly merged between 60 and 70 km, where both algorithms give virtually identical values. The radiative eﬀects of the mineral dust in the entire spectrum from 0.1 to 200 µm are accounted for with the scheme of Kuroda et al., [2005]. The current version of the dust radiation scheme uses 19 representative wavelength bands: nine in the visible and ten in the infrared. The surface temperature evolution is determined from the balance between the solar and thermal components of the net radiative ﬂux, the sensible heat ﬂux, and the ﬂux into the soil. The distributions of the surface thermal inertia [Mellon et al., 2000] and thermal albedo [Christensen, 2001] are based on the Thermal Emission Spectrometer (TES) measurements. The topography is prescribed from the Mars Orbiter Laser Altimeter (MOLA) proﬁles [Delacourt et al., 2003]. The vertical turbulent mixing for the free atmosphere based on the Richardson number is modeled after Holtslag and Boville [1993] in the entire model domain. It is supplemented by the energy conserving convective adjustment scheme to prevent superadiabatic vertical temperature gradients. The impact of nonresolved gravity waves on the wind and temperature ﬁeld is parameterized using the spectral scheme [Medvedev and Klaassen, 2000], coupled with orographic wave sources [McFarlane, 1987].

3. Results Here we will conﬁne ourselves to typical relations for ozone and particularly consider results for Ls = 0◦ (northern Martian spring). The calculations are carried out under conditions of perpetual Ls. We show the results in pressure coordinates. In the ﬁgures the red dashed lines represent the socalled pseudo-altitudes, as commonly used [see e.g. Lef`evre et al., 2004], calculated accordingly to the formula z = −H ∗ ln(p/psurf ). The mean scale height we use amounts to H = 10.3 km and the surface pressure psurf = 6.1 mbar (the lowermost tick in the ﬁgures) actually varying between 5 and 8.5 mbar. The space between the individual lines generally amounts to 10 km. As an example for the dynamical ﬁelds Figs. 1a and 1b show the zonally averaged temperature for Ls = 0◦ and zonal wind in a heightlatitudinal cross-section. The chemically most important minor constituent in the Martian atmosphere is water vapor. It is the main source gas for

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Fig. 1. 1a (left) and 1b (right) Altitude-latitude cross-section of the temperature a) and the zonal wind b) for Ls = 0◦ .

Fig. 2. 2a (left) and 2b (right). Water vapor mixing ratios a) and ozone number density [cm−3 ] b) in an altitude-latitude cross-section at midnight for Ls = 0◦ .

the hydrogen radicals. Water vapor is subjected to the freeze drying that depends sensitively on the temperature. Figures 2a displays the calculated distribution of water vapor for Ls = 0◦ at midnight. One can recognize clear hygropauses approximately above 0.5 mbar. In high southern latitudes (beyond 60◦ S) in winter the atmosphere is dry. This feature was also observed during the Phobos mission [Rodin et al., 1996], which found a dry atmosphere above 20–25 km somewhat below the calculated hygropause. The summer hemisphere is more humid than the winter or spring hemisphere — a consequence of stronger evaporation of water vapor from the ice caps. The atmosphere above the hygropause is dry and the water vapor mixing ratios decrease to

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2 ppmv and lower. The cause is given by the relatively cold temperatures and the dust distribution used for the calculations entailing a freeze drying by heterogeneous formation of ice particles on the surface of dust. The diurnal variation of water vapor is small and mainly thermally and dynamically (not chemically) induced by tidal motion. The second key constituent in the Martian atmosphere is ozone. It is a relatively easily detectable species by means of the occultation technique [Blamont and Chasseﬁere, 1993; Korablev et al., 2001; Lebonnois et al., 2006]. In the domain below about 0.01 mbar ozone is the most abundant odd oxygen constituent, whereas above this altitude atomic oxygen dominates. Figs. 2b displays the ozone density at midnight in a height-latitude crosssection for Ls = 0◦ . Roughly between 0.1 and 0.01 an ozone layer occurs. Here, we will term it the secondary ozone layer. For Ls = 0◦ a maximum arises above the equator with maximum values of 9×109 cm−3 . This layer of enhanced ozone values extends to middle southern and northern latitudes. The primary ozone layer with values exceeding 1010 cm−3 occurs at the surface. A deep ozone minimum with values as small as <5 × 107 cm−3 is located below the secondary maximum. In high latitudes on both sides of the secondary ozone layer the concentrations are very small. During noon (not shown) the concentrations are essentially smaller than during the night (the maximum values are in the order of 109 cm−3 and below. Figures 3a to 3d exhibit four examples of the diurnal variation of the ozone mixing ratio at diﬀerent latitudes (67.5◦ S, 2.5◦ N, 22.5◦ N, and 42.5◦ N) for Ls = 0◦ . Strong diurnal variations are seen in the ﬁgures with highest values of ozone during the night. In low and equatorial latitudes the nighttime values are larger by an order of magnitude than those during daytime in the height of the secondary maximum. A daytime maximum occurs after noon between 0.5 and 0.2 mbar (clearly below the height of the nighttime maximum), resulting from the atomic oxygen formation by the photolysis of CO2 and O2 . In high latitudes the diﬀerence between day and nighttime ozone concentration is essentially smaller and the absolute values decline. The nighttime values are larger by one order in magnitude than those during daytime in the height of the secondary maximum. The reason for this behavior is that atomic oxygen forms ozone after sunset when the solar radiation, which dissociates ozone, becomes zero. Figures 4a to 4d depict the diurnal variations of ozone at 2.5◦ S for Ls = 0◦ , Ls = 90◦ , Ls = 180◦ , and Ls = 270◦ corresponding to all seasons. The results are in good agreement with calculations of Lef`evre et al. [2004], with exception of the result for Ls = 270◦ . We got a clear diurnal variation,

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Fig. 3. 3a to 3d Diurnal variation of the ozone mixing ratio at diﬀerent latitudes (67.5◦ S, 2.5◦ N, 22.5◦ N, and 42.5◦ N) for Ls = 0◦ .

whereas in Fig. 4 of Lef`evre et al., [2004] the secondary ozone layer also vanishes during the night. The odd hydrogen constituents H, OH, and HO2 are rather important for the chemistry as they are responsible for the odd oxygen destruction by some catalytic cycles. A chemically decisive and crucial constituent of them is hydroxyl, OH. On Mars it ensures the stability of the atmosphere, returning CO to CO2 in six catalytic cycles, as discussed in Sonnemann et al., [2006]. Of course, OH also impacts a large number of further chemical constituents and — in case of the Earth atmosphere — is often called the atmosphere detergent. Figure 5a and 5b display two examples of the diurnal variation of OH for Ls = 0◦ at 2.5◦ N and 67.5◦ N latitude. The daytime variation follows roughly the solar insolation although the daytime maximum shifts with increasing height to later hours (Fig. 5a). The ﬁgures also show the existence

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Fig. 4. 4a to 4d Diurnal variations of ozone at 2.5◦ S for Ls = 0◦ , Ls = 90◦ , Ls = 180◦ , and Ls = 270◦ .

Fig. 5. 5a (left) and 5b (right) Diurnal variation of the hydroxyl concentration [cm−3 ] for Ls = 0◦ at a) 2.5◦ N and b) 67.5◦ N in an altitude-local time cross-section.

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of a nighttime OH-layer in a height-local time cross-section with maximum values occurring approximately between 0.05 and 0.01 mbar. This layer corresponds to that in the Earth’s atmosphere and should be measurable by the Meinel-band airglow as it mainly results from the reaction of ozone with atomic hydrogen. During daytime the largest OH-concentrations occur below 0.1 mbar. The absolute maximum appears around 1 mbar.

4. Discussion The general behavior of the Martian atmosphere has some similarities to the middle atmosphere of the Earth; however, the diﬀerence is that the major constituent is CO2 instead of N2 and O2 . As far as measurements are available the calculations ﬁt the observations partly well, although disagreements also occur. For instance, the ozone measurements by Phobos 2 [Blamont and Chasseﬁere, 1993; Korablev et al., 2001] showed a mean maximum of the number density of about 109 cm−3 around 40–45 km for Ls = 0◦ –20◦ . The vertical distribution (20 to 70 km) of ozone on Mars was measured by SPICAM/Mars Express by means of the occultation technique during the night from Ls = 8◦ to Ls = 270◦ [Lebonnois et al., 2006]. According with this measurements the secondary ozone maximum occurs between 30-60 km altitude for the period Ls = 11◦ –130◦, reaching largest values of approximately 9×109 cm−3 during Ls = 40◦ –60◦ and fall below a detection threshold after Ls = 130◦ [Lebonnois et al., 2006]. The detection limit for ozone was given by approximately 108 cm−3 . The ozone concentrations calculated by the model agree quite good with those of the measurements for the period of ozone maximum. In our calculations the largest values at the secondary ozone maximum amount to about 9 × 109 cm−3 and occur between spring equinox and north summer solstice. Depending on latitude, local time, and season the maxima are located between 30 and 60 km. The concentrations decrease for high southern latitudes during this period. The concentrations at the secondary ozone maximum are smaller than those ones at the surface where the values exceed 1010 cm−3 . The secondary ozone maximum at the equator decreases after Ls = 90◦ to 100◦ . In contrast to the measurements the concentrations decrease only to values in the order of 108 to 109 cm−3 during Ls = 130◦– 360◦ , but they do not fall below the detection threshold of SPICAM/Mars Express. This discrepancy between measurement and model calculations of Lef`evre et al., [2004] was also stated in Lebonnois et al., [2006]. On the

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other hand, a strong maximum of ozone of about 1010 cm−3 at 37–39 km, 15◦ S and for Ls = 12◦ –13◦ has been observed by the Mars 5 satellite at the evening terminator [Krasnopolsky et al., 1975, 1977]. In this context it should be mentioned that the currently most sophisticated 1D-model of Krasnopolsky [2006a] calculates a nighttime ozone maximum with values of about 2 × 108 cm−3 at 50–60 km for Ls = 172◦ . The disagreement between model calculations and measurements for north winter season is a point for future investigations. The reason is not clear thus far and it may depend on the dynamic and thermal state of the Martian atmosphere not correctly considered by the models. In model calculations Lef`evre et al., [2004] also found a clear nighttime secondary ozone layer for Ls = 150◦ –180◦, but it is apparently missing for Ls = 270◦ –300◦, at least at the equator. Clancy and Nair [1996] suggest that the hygropause could rise around perihelion season. In this case hydrogen radicals resulting from water vapor would considerably reduce the ozone density. Obviously, the ozone concentration in the secondary ozone layer is quite variable. A reason for the strong variability of ozone could be given by the highly variable wind system and particularly by the zonal wind. Sonnemann [2001] introduced the photochemical Doppler eﬀect, consisting in the fact that the response of the chemical system depends on the zonal wind shortening or prolonging the period of solar insolation, depending on the direction of the wind with or against the rotation of the planet. The change of the period can be calculated by a modiﬁed Doppler formula. In the Earth mesosphere this is a very robust eﬀect. A winter westerly wind shortens the time of photodissociation and consequently the time of atomic oxygen formation during daytime. The opposite is true for a summery easterly wind system. A sensitive period is the time of sunset because during this time a variable share of atomic oxygen will be converted into ozone. This share is decisively inﬂuenced by the zonal wind speed. For solar zenith angles close to grazing incidence the atomic oxygen formation from the photodissociation of CO2 and O2 strongly decreases, but H2 O and particularly O3 are still eﬀectively subjected to the photolysis both reducing the odd oxygen concentration. Particularly the radiation (in the Hartley bands) dissociating ozone is almost unabsorbed at grazing incidence entailing the odd oxygen loss reactions O3 + hν → O + O2 O + O3 → 2O2 Net: 2O3 + hν → 3O2

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decreasing the ozone concentration during the sunset period. A shortening of this period by a zonal west wind relatively increases the ozone concentration. There are pronounced tidal waves in the Martian atmosphere with a strong semi-diurnal component, meaning the zonal wind velocity is accordingly modulated by the tidal winds. But the vertical wind, which is essentially stronger on Mars than on Earth, also is able to transport minor constituents, such as water vapor and chemical families, impacting the ozone layer. The inﬂuence of the dynamics on the chemistry is strongest if the characteristic times are of a comparable order. Below the secondary ozone layer a nighttime minimum occurs. The concentrations are below the detection limit. Such an ozone minimum corresponds to the pronounced ozone minimum around 80 km in the Earth atmosphere [e.g. Fussen et al., 2000, Hartogh et al., 2004]. 5. Summary and Outlook We present a newly developed 3D-model of the dynamics and chemistry of the Martian atmosphere. The wind ﬁelds (especially the zonal wind) have a considerable impact on the chemistry in the Martian atmosphere. The chemical scheme also includes a parameterization for deposition of water vapor near the surface. However, due to the lack of information about the dust distribution, a simple version has been chosen. We did not consider the deposition of considerable quantities of CO2 at the surface. This is still a drawback, also for the calculations in the CTM, as the three-body reactions and other parameters depend on the gas density. The comprehensive chemical code and the newly developed sophisticated transport scheme with extremely small numerical diﬀusion are the advantages of the model. First results obtained from our model exhibit fairly good agreement with observations. Particularly, the model well reproduces a spatio-temporal behavior of ozone during north spring to north summer seasons. However, diﬀerences to the ozone measurements by SPICAM/ME in height of the secondary maximum occurred during Ls = 130◦ –360◦. Not only our model but generally the GCMs calculate too large ozone concentrations during this season. The reason is still unclear or highly speculative. Each model run produces a huge quantity of data. We presented here only some results in order to show that the model produces reasonable data. Concerning our model, there is still a large number of open problems to be solved. Among other subjects the model has especially to be improved with regard to the microphysics taking into

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account such processes as condensation, sublimation, and transport of ice particles. Acknowledgments This work was supported by the German Research Community DFG, grants HA 3261/1-2 and So 268/4-1. References 1. S. K. Atreya and Z. G. Gu, Stability of the Martian atmosphere: Is heterogeneous catalysis essential? J. Geophys. Res. 99 (1994) E6, 13,133– 13,145. 2. S. K. Atreya and Z. G. Gu, Photochemistry and stability of the atmosphere of Mars, Adv. Space Res. 16(6) (1995) 57–68. 3. J. E. Blamont and E. Chasseﬁere, First detection of ozone in the middle atmosphere of Mars from solar occultation Measurements, Icarus 104 (1993) 324–336. 4. S. W. Bougher, R. G. Roble, E. C. Ridley and R. E. Dickinson, The Mars thermosphere. II. General circulation with coupled dynamics and composition, J. Geophys. Res. 95 (1990) 14,811–14,827. 5. P. R. Christensen, J. L. Bandﬁeld, V. E. Hamilton et al., Mars Global Surveyor Thermal Emission Spectrometer experiment: Investigation description and surface science results, J. Geophys. Res. 106 (2001) 23,823– 23,872, 10.1029/2000JE001370. 6. R. T. Clancy and H. Nair, Annual (perihelion-aphelion) cycle in the photochemical behavior of the global Mars atmosphere, J. Geophys. Res. 101(E5) (1996) 12,785–12,790. 7. M. Collins, S. R. Lewis, P. L. Read and F. Hourdin, Baroclinic wave transitions in the Martian atmosphere, Icarus 120 (1996) 344–357. 8. C. Delacourt, N. Gros, P. Allemand and D. Baratoux, Online Mars digital elevation model derived from MOLA proﬁles, Eos Trans. AGU 84(52) (2003). 9. A. Fedorova, O. Korablev, S. Perrier, J.-L. Bertaux, F. Lefevre and A. Rodin, Observation of O2 1.27 mm dayglow by SPICAM IR: Seasonal distribution for the ﬁrst Martian year of Mars Express, J. Geophys. Res. 111 (2006) E09S07, doi:10.1029/2006JE002694. 10. A. Fedorova, O. Korablev, J.-L. Bertaux, A. Rodin, A. Kiselev and S. Perrier, Mars water vapor abundance from SPICAM IR spectrometer: Seasonal and geographic distributions, J. Geophys. Res. 111 (2006) E09S08, doi:10.1029/2006JE002695. 11. F. Forget, F. Hourdin, R. Fournier, C. Hourdin, O. Talagrand, M. Collins, S. R. Lewis, P. L. Read. and J.-P. Huot, Improved general circulation models of the Martian atmosphere from the surface to above 80 km, J. Geophys. Res. 104 (1999) 24,155–24,175.

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59. A.-S. Wong and S. K. Atreya, Chemical markers of possible hot spots on Mars, J. Geophys. Res. 108(E4) (2003) 5026, doi:10.1029/2002JE002003. 60. R. W. Zurek, J. R. Barnes, R. M. Haberle, J. B. Pollack, J. E. Tillman and C. B. Leovy, Dynamics of the atmosphere of Mars. In: Mars, University of Arizona Press, Tuscon, AZ, pp. 835–933, 1992 (2001).

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

CHANGES IN MASS FLOW CAUSED BY CO2 CONDENSATION IN THE MARTIAN ATMOSPHERE K. OGOHARA∗ and T. SATOMURA Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University, Kyoto, 606-8502, Japan ∗ [email protected] www-clim.kugi.kyoto-u.ac.jp/ogohara/index.html

Impacts of mass deposition due to CO2 condensation on zonal mean circulation are examined by a Martian general circulation model (MGCM). It is shown that the atmospheric mass change in the polar region causes a vertically uniform increase in zonal wind, and an increase in northward wind concentrated near the surface at high latitudes. It is suggested that the enhancement of meridional wind near the surface is associated with Ekman transport in the boundary layer. It is shown that the Ekman mass transport is an important process of replenishing loss of atmospheric mass in the polar region.

1. Introduction The principal constituent of the Martian atmosphere, CO2 , condenses and sublimes. Over the winter season, in either hemisphere, about a third of the entire atmosphere condenses and deposits on the surface. Since such a large amount of the atmospheric mass is exchanged with the polar ice caps through the CO2 condensation-sublimation process, it is expected that the dynamics of the Martian polar atmosphere are strongly aﬀected by CO2 phase change. For example, it is possible that CO2 phase change has eﬀects on the occurrence and expansion of many local dust storms near the edges of the polar ice caps. The eﬀects of CO2 phase change on surrounding wind ﬁelds have been studied by Refs. [4, 11]. Reference [11] estimated the averaged meridional wind associated with the mass ﬂow forced by CO2 condensation. They considered the growing polar ice cap over the winter pole and supposed that the mass condensing onto the ice cap is continually replenished by a ﬂow into the cylindrical region above the cap, centered on the pole. 195

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They derived the meridional ﬂow of 0.2–0.5 m s−1 , assuming that the latent heat due to CO2 condensation is balanced with radiative cooling. However, they included neither the eﬀects of rotation of the planet nor the vertical distribution of the ﬂow. Therefore, it is uncertain whether the picture supposed by Ref. [11] is consistent with the real phenomena around the polar cap. On the other hand, Ref. [4] evaluated the eﬀects of CO2 phase change on wind ﬁelds by using their Martian general circulation model (MGCM). They concluded that there is a change of zonal wind only at the very lowest level over the cap. However, they mentioned only the changes in the meridional distribution of zonal mean zonal wind and did not investigate in detail the dynamics associated with the loss of the atmospheric mass due to CO2 condensation. Thus, the realistic pictures of eﬀects of atmospheric mass change on the atmosphere have not been studied in reality. In this study, we perform simulations with and without the mass change associated with CO2 condensation. By comparing the results, a new picture of the eﬀects of atmospheric mass change on the surrounding atmosphere will be suggested. 2. Model and Experiments Our MGCM is based on a model used by Ref. [9]. The horizontal resolution is approximately 5.6◦ longitude by 5.6◦ latitude (triangular truncation with wave number 21). The domain has 34 σ layers in the vertical direction and higher resolution is achieved only near the surface. The highest level is at σtop = 1.54 × 10−5, which corresponds to an altitude of about 90 km. Rayleigh friction is imposed near the upper boundary. The Rayleigh friction coeﬃcient is given by following equations, z − zR 0 , KR = KR 1 + tanh HR z = −H ln σ,

(1)

zR = −H ln σtop , 0 where KR , H, and HR are (1 day)−1 , 10 km, and 10 km, respectively. Martian topography is not considered because we are interested only in the responses of the atmosphere to the atmospheric mass change due to CO2 condensation. The shortwave and longwave radiation scheme used in this study is the same as that used by Ref. [9], except that atmospheric heating due to

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absorption of solar radiation in the near-IR bands (4.3, 2.7, and 2.0 µm) of CO2 is computed following equation (2) given by Ref. 3. The values of the surface albedo of the regolith and CO2 ice are 0.25 and 0.60, respectively, in all bands. The vertical proﬁle of dust mixing ratio is given in the same way as Ref. [9], which is based on a time-independent proﬁle described in Ref. [1]. The dust mixing ratio in this study provides the standard dust optical depth for clear atmospheric conditions, ∼0.25. The model consists of 21 subsurface layers. The subsurface layers are stretched from ∼0.9 cm at the top layer to ∼12 cm at the bottom layer in regolith regions and from ∼0.3 cm at the top layer to ∼4 cm at the bottom layer in the ice cap regions. Temperature in the ground is calculated using the thermal diﬀusion equation. The values of the thermal inertia of the regolith and CO2 ice are 200 J m−2 K−1 s−1/2 and 600 J m−2 K−1 s−1/2 , respectively.10 The eddy diﬀusion is evaluated by the level 2 scheme of Ref. [7]. The roughness length used in the scheme is independent of longitude and its latitudinal distibution is shown in Fig. 1. It is based on the distributions of roughness length given by Ref. [5]. A spin-up run was performed for one Mars year from the northern fall equinox. The one-year spin-up run started from an isothermal (220 K) condition with constant surface pressure (7 hPa) and no wind over the entire

Fig. 1.

A latitudinal distribution of roughness length z0 (m) used in this work.

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planet. During the spin-up run, the atmospheric temperature is adjusted to the condensation temperature of CO2 following a CO2 phase change scheme given by Ref. [2]. When snow falls on the surface, the mass of the snow is added to the mass of the polar cap. At the same time, the thermal inertia and the albedo of the surface are switched to those of CO2 ice. However, the surface pressure is not modiﬁed during the spin-up run even if the snow falls on the surface. After the spin-up run, a simulation called S1 is performed for the period between Ls = 180◦ and Ls = 270◦ at the same conditions as those used during the spin-up run. The other simulation called S2 is also performed at the same conditions and for the same period as those of S1 except that the surface pressure is modiﬁed based on the snow mass that falls on the surface. The seasonal variation of the northern ice cap mass and the seasonlatitude cross section of the zonal mean thickness of the northern ice cap in S2 from Ls = 180◦ to Ls = 270◦ are shown in Fig. 2a and 2b, respectively. They are roughly comparable with those observed by Refs. [6, 13].

3. Results Figure 3a and 3b show the latitude-height cross-sections of zonal mean zonal wind and meridional wind in the lower atmosphere, averaged over the period of the S1 and S2 simulations. In both simulations, the westerly wind in high latitudes is the lower part of the westerly jet. Strong northerly wind in low latitudes near the surface is the lower part of the Hadley cell. Strong southerly wind near the surface is also found in high latitudes, whose maximum velocity is 5–6 m s−1 . Figure 3c shows the diﬀerences between Fig. 3a and 3b. It is found that the zonal mean zonal wind increases uniformly in the vertical direction by approximately 3 m s−1 in S2. Considering the geostrophic relationship, it is consistent with the increase in the meridional gradient of the surface pressure shown in Fig. 3d due to CO2 condensation in the polar region in S2. There is also a large localized diﬀerence in zonal mean meridional wind near the surface in latitudes where the vertically uniform diﬀerence of zonal mean zonal wind exists. The magnitude of this diﬀerence of meridional wind near the surface is ∼0.8 m s−1 . The relationship between zonal mean zonal wind and meridional wind in Fig. 3 seems to be associated with the Ekman layer. Given the diﬀusion coeﬃcient of momentum of 10 m2 s−1, which nearly corresponds to the simulated value near the surface (not shown), the depth of Ekman layer around 60◦ N is ∼1.3 km, following the equation

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Fig. 2. The seasonal variations of the northern ice cap mass and its latitudinal extent. (a) The seasonal variation of the northern ice cap mass and (b) the season-latitude cross section of the zonal mean thickness (m) of the northern ice cap simulated in S2.

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Fig. 3. Simulated time-mean section of zonal mean zonal wind (shading), meridional wind (contours) in S1 (a) and S2 (b). Easterly wind is not shaded. Southerly (northerly) wind is indicated by solid (dashed) lines. Meridional wind contours are in intervals of 1 m s−1 . (c) Diﬀerences of zonal mean zonal wind (shading) and meridional wind (contours) between S1 and S2, which are deﬁned as results in S2 minus those in S1. Regions where the diﬀerences of zonal mean zonal wind are negative are not shaded. The contour interval is 0.2 m s−1 . (d) Latitudinal distributions of the surface pressure at Ls = 270◦ in S1 (dashed) and in S2 (dotted). A solid line indicates diﬀerences between S1 and S2, which are deﬁned as results in S2 minus those in S1.

given by Ref. [14], De = π

2Km , f

(2)

where De , f , and Km are the depth of the Ekman layer, the Coriolis parameter, and the diﬀusion coeﬃcient of momentum, respectively. Because the velocity of the westerly geostrophic wind above the Ekman layer is approximately 20 m s−1 as shown in Fig. 3a and 3b, the theoretical value of the maximum meridional velocity inside the Ekman layer is ∼6.5 m s−1 ,14 which agrees well with the simulated value. In addition, the spiral structure of horizontal wind characteristic of the Ekman layer is found (not shown). Therefore, it is reasonable that the strong southerly wind near the surface

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in high latitudes in Fig. 3a and 3b is seen as Ekman transport. Considering the relationship of the meridional wind in the Ekman layer with the upper zonal geostrophic wind, the increase in the southerly wind near the surface in high latitudes in S2 is quantitatively consistent with the enhancement of zonal mean zonal wind. Meridional distributions of the zonal mean meridional mass ﬂuxes are averaged over the period of the simulations in S1 and S2, and are shown in the left panels of Fig. 4a and 4b. The northerly wind area, which extends from the middle atmosphere in high latitudes to the lower atmosphere in low latitudes, consists of the lower and descending parts of the Hadley circulation and the descending branch of the Ferrel circulation. Localized meridional mass ﬂuxes in high latitudes in both simulations correspond to the strong southerly wind near the surface in Fig. 3a and 3b. Vertical proﬁles of the zonal mean meridional mass ﬂuxes in S1 and S2 averaged latitudinally from 52.6◦ N to 69.2◦ N are shown in the right panels of Fig. 4a and 4b. Figure 4c indicates the diﬀerences in zonal mean meridional mass ﬂuxes between S1 and S2. Zonal mean meridional mass ﬂux near the surface in high latitudes in S2 is larger than that in S1. It is also shown in Fig. 4c that the mean meridional circulation is weakened in S2. A vertical proﬁle of the diﬀerences of zonal mean meridional mass ﬂuxes averaged latitudinally from 52.6◦N to 69.2◦ N is also shown in Fig. 4c. The signiﬁcant increase of meridional mass ﬂux can be seen below 1 km altitude. There is also very slight increase (3 × 10−4–7 × 10−4 kg m−2 s−1 ) of meridional mass ﬂux in altitudes from 10 km to 20 km above the surface.

4. Discussion and Conclusion Figure 5 shows latitudinal distributions of the increase of the integrated meridional mass transport in S2. Considering that the northern ice cap exists at latitudes higher than 60◦ N, the atmospheric mass transported into the polar region associated with CO2 condensation in S2 over the period of the simulation is 2.0 × 1015 kg. During the period, 2.4 × 1015 kg of polar ice is formed, as shown in Fig. 2b. Thus, about 83% of the atmospheric mass lost due to CO2 condensation (i.e. the increment of the polar ice cap mass) is compensated by the northward mass ﬂux from the southern latitudes. Figure 5 also shows latitudinal distributions of the increase above and below σ = 0.9 of vertically, longitudinally, and temporally integrated meridional mass transport in S2. Half of the increment of the northward mass transport in mid- and high-latitudes is due to the increased northward

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Fig. 4. (left) Cross sections of zonally averaged meridional mass ﬂux and (right) vertical proﬁles of meridional mass ﬂux averaged latitudinally from 52.6◦ N to 69.2◦ N in (a) S1 and (b) S2. Meridional mass ﬂux contours are in intervals of 0.02 kg m−2 s−1 . (c) Diﬀerences of zonal mean meridional mass ﬂux between S1 and S2, which are deﬁned as results in S2 minus those in S1. The contour interval is 0.005 kg m−2 s−1 . Note that regions below σ = 0.8 are stretched vertically. Shaded regions express negative values.

mass ﬂux above the boundary layer. It corresponds to the slight but vertically wide decrease of the southward mass ﬂux in altitudes between 10 km and 20 km above the surface in S2 shown in Fig. 4, possibly associated with the descending branch of the weakened mean meridional circulation.

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Fig. 5. (solid line) Diﬀerences of meridional mass transport integrated vertically, longitudinally, and temporally between S1 and S2 over the period of the simulations, which are deﬁned as results in S2 minus those in S1. (dashed line) Same as the solid line, but integrated vertically below σ = 0.9. (dotted line) Same as the solid line, but integrated vertically above σ = 0.9.

The other half of the increment in the northward mass transport due to CO2 condensation results from the increase of the northward mass ﬂux below 1 km altitude in Fig. 5. This corresponds to the enhanced Ekman mass transport shown in Fig. 4c. Therefore, the enhancement of Ekman transport is one of the important processes for replenishing the atmospheric mass lost due to CO2 condensation, even if the Ekman layer is very shallow relative to the atmosphere. As described above, the eﬀects of CO2 condensation on the surrounding atmosphere is summarized as follows. (i) The surface pressure in the polar region drops due to CO2 condensation onto the surface. (ii) The westerly wind in high latitudes is enhanced uniformly in the vertical direction, corresponding to the increase of the meridional gradient of the surface pressure in high latitudes as reported by Ref. [4]. At the same time, the mean meridional circulation is weakened.

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(iii) The Ekman mass transport in the lower atmosphere is also enhanced, together with the westerly jet enhancement, and it compensates for the loss of the atmospheric mass in the polar region. Weakened mean meridional circulation results in a decrease in the southward mass transport in the descending branch. The third item is the new picture of the eﬀects of CO2 condensation on the surrounding atmosphere proposed in this study. Ref. [11] supposed that the mass condensing onto the ice cap is continually replenished by a ﬂow into the cylindrical region above the cap. Their supposition is consistent with our results. However, eﬀects of planetary rotation and the vertical distribution of mass ﬂow are important components for the northward mass transport. In this study, we did not determine exactly how the eﬀects of CO2 phase change on wind ﬁelds appear when topography is considered, because the meridional mass transport by topographic stationary waves is not included in either S1 or S2. In addition, the season of the simulation in this study is the northern fall and winter, when CO2 continues to condense. In future, we plan to study the season when CO2 continues to sublime. Acknowledgments GFD-DENNOU Library was used for drawing ﬁgures. The radiation portion of this work is based on that of the nonhydrostatic two-dimensional model for Mars, “deepconv”, which is available through the GFD Dennou Club web site (http://www.gfd-dennou.org/library/deepconv/nakajimaodaka 2000/index.htm.en). The open source policy of the GFD Dennou Club is greatly appreciated. References 1. B. J. Conrath, Thermal structure of the Martian atmosphere during the dissipation of the dust storm of 1971, Icarus 24 (1975) 36–46. 2. F. Forget, F. Hourdin and O. Talagrand, CO2 Snowfall on Mars: Simulation with a General Circulation Model, Icarus 131 (1998) 302–316. 3. F. Forget, F. Hourdin, R. Fournier, C. Hourdin and O. Talagrand, Improved general circulation models of the Martian atmosphere from the surface to above 80 km, J. Geophys. Res. 104(E10) (1999) 24155–24175. 4. R. M. Haberle, J. B. Pollack, J. R. Barnes, R. W. Zurek, C. B. Leovy, J. R. Murphy, H. Lee and J. Schaeﬀer, Mars atmospheric dynamics as simulated by the NASA/Ames general circulation model, 1, the zonal-mean circulation, J. Geophys. Res. 98 (1993) 3093–3124.

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5. N. G. Heavens, M. I. Richardson and A. D. Toigo, Two aerodynamic roughness maps derived from Mars Orbiter Laser Altimeter (MOLA) data and their eﬀects on boundary layer properties in a Mars general circulation model (GCM), J. Geophys. Res. 113 (2008) E02014, doi:10.1029/2007JE002991. 6. H. H. Kieﬀer and T. N. Titus, TES Mapping of Marsf North Seasonal Cap, Icarus 154 (2001) 162–180. 7. G. L. Mellor and T. Yamada, A hierarchy of turbulence closure models for planetary boundary layers, J. Atmos. Sci. 31 (1974) 1791–1806. 8. M. Odaka, K. Nakajima, M. Ishiwatari and Y.-Y. Hayashi, A numerical simulation of thermal convection in the Martian lower atmosphere with a two-dimensional anelastic model, Nagare Multimedia (in Japanese) 20 (2001) (http://www.nagare.or.jp/mm/2001/odaka/index ja.htm). 9. K. Ogohara and T. Satomura, Northward movement of Martian dust localized in the region of the Hellas Basin, Geophys. Res. Lett. 35 (2008) L13201, doi:10.1029/2008GL034546. 10. D. A. Paige, J. E. Bachman and K. D. Keegan, Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations 1. North polar region, J. Geophys. Res. 99(E12) (1994) 25,959–25,991. 11. P. L. Read and S. R. Lewis, The Martian Climate Revisited (Springer, 2003). 12. H. Savij¨ arvi, Radiative ﬂuxes on a dustfree Mars, Contr. Atmosph. Phys. 64 (1991) 103–112. 13. D. E. Smith, M. T. Zuber and G. A. Neumann, Seasonal Variations of Snow Depth on Mars, Science 294 (2001) 2141–2146. 14. R. B. Stull, An Introduction to Boundary Layer Meteorology (Kluwer Academic Publishers, 1997).

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

MODELING OF THE RADIATION ENVIRONMENT ON MARS∗,† GIOVANNI DE ANGELIS CNESPS, Istituto Superiore di Sanita’ Rome, I-00161, Italy [email protected] FRANCIS F. BADAVI Radiation Group, Christopher Newport University Newport News, VA 23606, USA STEVE R. BLATTNIG, MARTHA S. CLOWDSLEY, GARRY D. QUALLS, ROBERT C. SINGLETERRY JR., RAM K. TRIPATHI and JOHN W. WILSON Radiation Group, NASA Langley Research Center Hampton, VA 23681, USA

Results for the radiation environment to be found on the planet Mars due to Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE) has been obtained. Primary particle environments computed for Martian conditions are transported within the Mars atmosphere, modeled in a time-dependent way in terms of density, pressure, and temperature vs. altitude, down to the surface, with topography and backscattering patterns taken into account. The atmospheric chemical and isotopic composition has been modeled over results from the in-situ Viking Lander measurements for both major and minor components. The surface topography has been determined by using a model based on the data provided by the Mars Orbiter Laser Altimeter (MOLA) instrument on board the Mars Global Surveyor (MGS) spacecraft. The surface itself has been modeled in both the dry (‘regolith’) and volatile components. Mars regolith composition has been modeled based on the measurements obtained with orbiter and lander spacecraft from which an average composition has been derived. The volatile inventory properties, both in the regolith and in the seasonal and perennial polar caps, has been taken into account by modeling the deposition of volatiles and its variations with geography and time all throughout the Martian year. Results are given in terms of fluxes, doses and LET, for most kinds of particles, namely protons, neutrons, alpha particles, heavy ions, pions, and muons for various soil compositions. ∗ Work

partially supported by the NASA Research Grant NCC-1-404. partially supported by the Research Grant I/015/07/0 of the Italian Space Agency (ASI). † Work

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1. Introduction Manned space activities have been until present time limited to the nearEarth environment, most of them to low Earth orbit (LEO) scenarios, with only some of the Apollo missions targeted to the Moon. In current times most human exploration and development of space (HEDS) activities are related to the development of the International Space Station (ISS), and therefore take place in the LEO environment. A natural extension of HEDS activities will be going beyond LEO, and reach asteroids, Mars, Jupiter, Saturn, the Kuiper belt and the outskirts of the Solar System.1 Deep space human exploration activities have been recently boosted in the new US vision for space exploration in the 21st Century, a broad range of human and robotic missions to the Moon, Mars and beyond.2 The return to the Moon, seen as an outpost, will be only the ﬁrst step on the way to Mars. Journeys to Mars, as any other space journey outside the protective umbrella of the geomagnetic ﬁeld, will require higher levels of protection from the radiation environment found in the deep space.3 The radiation protection is now one of the two NASA highest concerns and priorities.4 Tools integrating diﬀerent radiation environments with shielding computation techniques especially tailored for deep space mission scenarios are instrumental in view of this exigency.5 In view of manned missions targeted to Mars (for a review see e.g. Ref. [1]), for which radiation exposure is one of the greatest problems and challenges to be tackled,3,6 it is of fundamental importance to have available a tool which allows to know which are the particle ﬂux and spectra at any time at any point of the Martian surface. With this goal in mind, a new model for the radiation environment due to Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE) to be found on the planet Mars has been developed. Galactic and solar primary particles rescaled for Mars conditions are transported within the Martian atmosphere, with temporal properties modeled with variable timescales, down to the surface, with altitude and backscattering patterns taken into account. The tool allows analysis for manned Mars landing missions (e.g. Ref. [1]), as well as planetary science studies, e.g. subsurface water and volatile inventory studies (e.g. Ref. [7]). This radiation environment is based on the Mars model by De Angelis et al.,6,8 with a detailed time-dependent description of the Martian surface with diﬀerent soil compositions including ices and volatiles. Radiation analysis work was performed with this environmental model.6,8−11 In this work the model from De Angelis et al.6,8 is extended: the older model allow computing a radiation environment only on the

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planet surface, whereas this model allow computing at any location within the atmosphere. Backscattered particles are transported from the surface through the atmosphere. The particle data and the techniques used to model the Mars environment have been presented in Refs. [9, 11], and will be only brieﬂy addressed in this paper. The models for both GCR and SPE adopted in this paper to build the Martian model have been provided as constraints, and were not a matter of choice for the paper authors. The emphasis of this paper is on results, in terms of ﬂuxes, doses and LET for most kinds of particles, i.e. protons, neutrons, alpha particles, heavy ions, pions, and muons for various soil compositions. The analysis for the pions and muons component is more extensively described in a companion paper.10 These models have been, are and will be used as a planning tool for most ongoing and future Mars-targeted missions (e.g. MSL, PHOBOS-GRUNT, NASA manned vehicles, etc.), as well as for design and development of spacecraft payload instrumentation (e.g. instruments for MSL, EXOMARS, LIULIN-F for PHOBOS-GRUNT, etc.). 2. Particle Environments Models 2.1. Galactic cosmic rays (GCR) Galactic Cosmic Rays (GCR) originate outside our Solar System in ways not totally clear yet.12,13 They are composed of highly energetic, fully ionized nuclei of all charges from hydrogen to uranium, with a large decrease in the intensity of particles with charge higher than 28.14 From interstellar space the GCR enter the Solar System, where they come into contact with the particles of the solar wind, which transports the solar magnetic ﬁeld away from the Sun.15 The distribution of cosmic rays in the heliosphere depends on time, position and particle magnetic rigidity, and complies with the transport equation by Parker,16 a solution of the Fokker-Planck equation in which the inward diﬀusion of galactic cosmic rays is balanced by the solar wind outward convection, assuming a spherically symmetric heliosphere and an isotropic cosmic ray particles ﬂux. Processes included in the equation are the GCR convection by the solar wind, their drift in the inhomogeneous heliospheric ﬁeld, the anisotropic diﬀusion in the interplanetary magnetic ﬁeld irregularities, and the adiabatic energy losses caused by the divergence of these irregularities.17,18 The time dependence due to solar activity of the variations of the solar wind velocity and diﬀusion coeﬃcient is taken into account with the statistical model developed by Wilson et al.19,20 relating the sunspot number to the cosmic ray induced

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neutron monitor count rate measured at the Deep River location, Ontario, Canada. The GCR cosmic ray density rescaling for distance is performed in this work, as in previous work,20,21 with the simpliﬁed model by O’Neill.22 Studies of solar modulation patterns performed by using data from Pioneer, Voyager, and IMP spacecraft show variability with solar cycle for some restricted energy ranges, but a good representation is given of the gross GCR behavior for all energies above 70 MeV.23 The ﬂux diﬀerence between 1 AU and the distance of Mars is at most a few percent,6,24 and it is computed to obtain the boundary conditions. 2.2. Solar particle events The Sun has been known for long time as a proliﬁc source of energetic particles, with the ﬁrst detection of solar particles by Forbush25 as early as in 1946 leading to the name ’solar cosmic rays’. Various short-term cosmic ray ﬂux increases have been observed shortly afterwards at the ground level in direct association with solar ﬂares,26−28 mostly as ground level ionization rate increases, and the largest event, that of 23 February 1956, was analyzed in detail through neutron monitor data.29,30 The analysis of the particle ﬂux of the 23 February 1956 solar particle event showed that only the solar magnetic ﬁeld was capable of accelerating protons in the amounts and to the energies detected in the event.31 This conclusion is still valid today whether or not the particles are produced within solar ﬂares or within coronal mass ejections, forming a bow shock transition region which the most recent opinions consider the most likely place where particle acceleration occurs, with the energy in both cases from the same magnetic ﬁeld, even if the best evidence is that solar particle events are the result of ﬁrst-order diﬀusive shock acceleration.32−34 In order to take into account solar particle events in space mission radiation shielding analysis, three main issues are to be considered, namely ﬂuence, frequency distribution, expected ﬂux and energy spectra, and the largest likely event to be encountered during the mission.35 The greatest concern given by Solar Particle Events is due to our inability to predict their occurrence.36 Only few events of very large size can give appreciable consequences for deep space radiation shielding analysis,35 namely events with ﬂuence of protons with energy E > 10 MeV larger than 3 × 107 /cm2 . The rate of occurrence of such events is discussed in Ref. [37]. An average event could provide a neutron monitor count rate increase lower than a factor 1.5, whereas in the event of 23 February 1956, the largest yet

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observed, the neutron monitor count rates increased of 36 times above the background level. The second largest event ever observed was that of 29 September 1989, with a measured neutron monitor count rate 370 percent over background.38 No other events of such magnitude have ever been observed, apart from the 12 November 1960 and the August 1972 events,39 indeed having narrower energy spectra compared with the 1989 event, especially with respect to higher energies, the most relevant in this respect.40 From a model by Nymmik41 it comes out that the event of 29 September 1989 just for protons with energy E > 30 MeV had a ﬂuence of 1.4 × 109 /cm2 protons, so about 50 times larger than the threshold mentioned above. Due to the exceptionality of the 1956 event, and the comparability of other large events, and the more extended spectrum, compared to the other events, a worst-case strategy based on a multiple of the 29 September 1989 event seems to be quite suitable to the needs of radiation analysis.42 The radial dependence of the particle ﬂux of SPE is very poorly known, and seems to depend on the characteristics of the interplanetary magnetic ﬁeld through which these particles go,35 with events generated by the shock regions of a CME may decrease little between 1 AU to Mars orbit or even further, whereas the Gauss law (i.e. r−2 ) seems appropriate at large distances from the sun.24 The SPE particles are generally controlled all throughout the solar system by the ﬂux tubes of the solar wind Archimedes spiral,35 so for a well ﬁeld line connected event the own particle ﬂux radial dependence35 should be as steep as r−3.3 . For the needs of a radiation shielding analysis, an event four times larger than the 29 September 1989 event42 which is likely to be exceeded only 1 percent of the time43 is used, with a simple inverse r (i.e. r−1 ) dependence for every spacecraft distance from the sun, to obtain an upper limit for the dose given by the event occurrence. 3. Planetary Environmental Models 3.1. Planetary surface and subsurface environments A planetary target body, i.e. a planet or one of its satellites, needs to be modeled to assess the radiation dose a crew will intake during the surface activities. If the body is atmosphereless, it has to be modeled in position (astrometry), size, topography, and surface chemical composition, to get the atomic surface composition needed for transport computation, to evaluate the backscattering radiation component, especially neutrons.

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If the target body has an atmosphere, a proﬁle of the atmosphere in terms of density, temperature and composition vs. altitude (and time) should be provided, to compute how the primary particle ﬂuxes are modiﬁed by the interaction with the atmosphere. The knowledge of the target body topography is particularly important in the case an atmosphere is present, to properly evaluate the thickness down to which the eﬀects of the atmosphere have to be taken into account. In the Solar System bodies (see, e.g. [44]) two kinds of surface composition are prevalent, namely a silicatic rocky composition on the bodies of the Inner Solar System (i.e. Mercury, Venus, the Earth, the Moon, Mars and its satellites, asteroids), and a mostly icy (water ice, methane ice, ammonia ice) composition of the solid bodies of the Outer Solar System (satellites of Jupiter, Saturn, Uranus, Neptune, Pluto with his moon Charon, comets, the Kuiper Belt and all Trans-Neptunian objects). The giant planets of the Outer Solar System have a gaseous composition all along their body (Jupiter, Saturn, Uranus, Neptune), and seem not to have any solid surface45 on which any surface activity looks to be practicable. Interesting phenomena take place on the surface of bodies with locally mixed rock/ice composition, like in planets with seasonal or perennial volatile-generated polar caps, like e.g. the carbon dioxide ice and water ice caps on Mars,6 as well as at any interface, like atmosphere-surface, space-surface, surface-subsurface, regolith-bedrock, etc.46 Neutron backscattering from silicatic surface is important particularly at the lower energies,47 whereas the interaction with ices produces far less neutrons.24 At the surface, the particle environment undergoes two main modiﬁcations with respect to that found in free space: the primary particles are limited to come only from above the surface, so the solid angle of acceptance of primary particles is limited to 2π, and it is not the full 4π solid angle like in the free space case. In some cases, due to local topography features like valleys or craters, the solid angle might be even smaller than 2π.48 Moreover, the backscattering component, mostly neutrons, created by the interaction between the incoming particles and the nuclei composing the surface, is to be added to the particle ﬂux at the surface. For atmosphereless bodies this component is about 1% of the dose given by GCR alone,21 with little dependence on the composition of the surface materials. For target bodies with an atmosphere, a proﬁle of the atmosphere in terms of density, temperature and composition vs. altitude (and time) should be provided, to compute how the primary particle ﬂuxes are modiﬁed by atmospheric interactions. At the surface the modiﬁed particle ﬁelds

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interact with the nuclei composing the surface, whose physical conditions and chemical composition should be known with depth in order to evaluate the backscattered radiation. 3.2. The mars physico-chemical model This Martian physico-chemical environmental model has been developed in successive phases.6,8−11 Mars is a planet with an atmosphere, so the modeling of the Martian radiation environment has to deal with both atmospheric and surface properties. The Martian atmosphere has been modeled by using the Mars Global Reference Atmospheric Model — version 2001 (‘Mars-GRAM 2001’,49), based on input data generated as output of the NASA Ames Mars General Circulation Model (MGCM) for the lower atmosphere, from the surface to 80 km altitude,50,51 the University of Arizona Mars Thermosphere General Circulation Model (MTGCM) for the higher atmosphere, from 80 km to 170 km altitude,52,53 and a modiﬁed Stewart-type thermospheric model, i.e. a latitude-longitude dependent parametric model also depending on solar activity,54 above 170 km altitude. This model can provide at any time a proﬁle of the Martian atmosphere in terms of density, pressure, and temperature vs. altitude, needed to compute the atmosphere thickness for the incoming particle ﬂux. The atmospheric chemical and isotopic composition has been modeled over results from the in-situ Viking Lander measurements for both major55 and minor56 components (composition given in Ref. [10]). The surface altitude, or better the atmospheric depth for incoming particles, to compute the atmospheric thickness proﬁle has been determined by using a model for the Martian topography based on the data provided by the Mars Orbiter Laser Altimeter (MOLA) instrument on board the Mars Global Surveyor (MGS) spacecraft.57 The MOLA topography is measured with respect to a zero elevation surface level known as the MOLA aeroid,58 which is deﬁned as the gravitational equipotential surface whose average value at the equator is equal to the mean planetary radius determined by MOLA data. Among the various data resolution available,59 in this work half-degree latitude-longitude resolution data for both MOLA aeroid surface and topography have been used (i.e. 30 km spatial resolution at the equator), but this value can be tuned in case of diﬀerent user needs. The atmospheric thickness for which the calculations have been performed ranges from 2∗ 10−5 g/cm2 (i.e. about +100 km altitude) up to 40 g/cm2 (i.e. about −10 km altitude). The Mars regolith composition

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has been modeled based on averages over the measurements obtained for Mars 560 and Phobos 261,62 with gamma-ray spectroscopy, and at the various landing sites Viking Landers 1 and 263,64 and Mars Pathﬁnder missions.65,66 From the averaging process an average composition has been obtained (composition given in Ref. [10]). This surface geochemical model got validated by the Mars Exploration Rovers: the geochemical and mineralogical data from Spirit and Opportunity67−71 show an impressive similarity with the data from this model, with soil compositional diﬀerences at most of a few percent, even 1% in some cases. In this ﬁrst project a value of 1.6 g/cm372 for the Mars soil density has been adopted. The composition, diﬀerent with respect to the regolith (e.g. CO2 ice, H2 O ice), of seasonal and perennial polar caps73 has been taken into account by modeling the deposition of the possible volatile inventory over the residual caps, along with its geographical variations all throughout the Martian year, for both the Mars North74,75 and South Pole,76,77 from results from imaging data of orbiter spacecraft. No such 3D Mars time dependent polar caps modeling was previously available for radiation analysis purposes. The importance of having a time-dependent soil composition model is shown below.

4. Radiation Transport Computing Tools The transport of positive charged particles, i.e. protons and heavier ions, have been performed with a current version of the NASA Langley Research Center (LaRC) heavy ion deterministic code HZETRN,78 which provides particle energy spectra at predeﬁned positions in the material layer of interest as well as the pertinent dosimetric quantities, with energy deposition from both primary and secondary particles, including nuclear target fragments, accounted for. The materials are modeled as a thickness ﬁle including distance of each material traversed in the order progressing from the outer boundary inward toward the target point. With the speciﬁed environment, i.e. the speciﬁed charged particle ﬂux boundary conditions, the transport code is used to generate dose vs. depth functions for each material under consideration over a range of thickness adequate for interpolation for the shielding analysis. Primary GCR particles at planet distances at intermediate time between solar minimum and maximum epochs are obtained with the model by Badhwar et al.22 The same transport code, HZETRN, is used for transport calculations of positive SPE particles.

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5. Results The radiation environment at a location at the surface of Mars is shown for GCR at solar 1977 solar minimum and 1990 solar maximum in Fig. 1 and regarding SPE in Fig. 2 for the solar particle event of September 29, 1989. Both results are shown for regolithic soil at the equator. The particles with ‘Z = 0’ in both ﬁgures are the albedo neutrons generated by the interaction of the primary particles with the surface,5 with a much higher energy tail than for atmosphereless bodies.5,79 The eﬀect of the atmosphere is quite evident on the particle transport, with a high energy tail component for neutrons generated by the atmospheric transport,80 absent on an atmosphereless body.79 Results have been obtained for various kinds of particles and for diﬀerent surface compositions: only the latitudes closer

Fig. 1. GCR particle environment during the 1977 solar minimum (full lines) and the 1990 solar maximum (dashed lines) on the Martian surface (results on regolithic soil at the equator).

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Fig. 2. The Martian surface environment during the September 1989 SPE (equatorial regolithic soil).

to the equator the soil is mostly silicatic regolith, whereas for northern and southern locations a suitable mix of ices of water and carbon dioxide needs to be used.6 For sake of brevity it is impossible to show all available results for both GCR and SPE environments and diﬀerent soils. As the most signiﬁcant examples, ﬂuences for protons, neutrons, and heavy ions due to 1989 SPE are shown in Fig. 3. The diﬀerent soil composition explains the much lower neutron production by the water ice than the silicatic regolith. As an example, a Mars high neutron radiation environment map,6 the tail created by atmospheric particle transport,5,79 due to GCR for 1977 Solar Minimum conditions is shown in Fig. 4, with a striking correspondence between neutron ﬂux and Mars topography, putting clearly into evidence the eﬀects of even this so tenuous atmosphere (a pressure of just few mbar at the surface at 0 km altitude) on particle transport. Dose and dose equivalents for diﬀerent ions are shown in Figs. 5 and 6.

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Fig. 4. Map of high energy neutron integral flux on the Mars surface at 1977 Solar Minimum GCR.

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DOSE vs. A for 1
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Variability of neutron fluxes on Mars with the season due to surface composition.

The eﬀects of layer superposition due to seasonal polar caps modiﬁcations is evident in Fig. 7, where the neutron ﬂuxes in diﬀerent Mars regions are variable with the season due to surface composition changes. These doses are slightly higher than those from,81 obtained with a simpliﬁed model of the Martian atmosphere, with no time dependence and a ﬁxed atmosphere thickness. Other results, computed with the GEANT-4 Monte Carlo transport code,82−84 also these showing doses lower than those from this work, have had mostly astrobiological applications.

6. Conclusions An updated and extended model for the radiation environment to be found on Mars (above and on the surface) due to Galactic Cosmic Rays (GCR), Solar Particle Events (SPE) and backscattering eﬀects has been developed. Results for ﬂuxes, doses and dose equivalents have been given.

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J. D. Farmer, R. Gellert, A. Ghosh, S. Gorevan, T. Graﬀ, J. Grant, L. A. Haskin, K. E. Herkenhoﬀ, J. R. Johnson, B. L. Jolliﬀ, G. Klingelhoefer, A. T. Knudson, S. McLennan, K. A. Milam, J. E. Moersch, R. V. Morris, R. Rieder, S. W. Ruﬀ, P. A. de Souza Jr., S. W. Squyres, H. W¨anke, A. Wang, M. B. Wyatt, A. Yen and J. Zipfel, Science 305 (2004) 842. L. A. Soderblom, R. C. Anderson, R. E. Arvidson, J. F. Bell III, N. A. Cabrol, W. Calvin, P. R. Christensen, B. C. Clark, T. Economou, B. L. Ehlmann, W. H. Farrand, D. Fike, R. Gellert, T. D. Glotch, M. P. Golombek, R. Greeley, J. P. Grotzinger, K. E. Herkenhoﬀ, D. J. Jerolmack, J. R. Johnson, B. Jolliﬀ, G. Klingelh¨ ofer, A. H. Knoll, Z. A. Learner, R. Li, M. C. Malin, S. M. McLennan, H. Y. McSween, D. W. Ming, R. V. Morris, J. W. Rice Jr., L. Richter, R. Rieder, D. Rodionov, C. Schr¨ oder, F. P. Seelos IV, J. M. Soderblom, S. W. Squyres, R. Sullivan, W. A. Watters, C. M. Weitz, M. B. Wyatt, A. Yen and J. Zipfel, Science 306 (2004) 1723. R. Rieder, R. Gellert, R. C. Anderson, J. Br¨ uckner, B. C. Clark, G. Dreibus, T. Economou, G. Klingelh¨ ofer, G. W. Lugmair, D. W. Ming, S. W. Squyres, C. d’Uston, H. W¨ anke, A. Yen and J. Zipfel, Science 306 (2004) 1746. J. Br¨ uckner, G. Dreibus, G. W. Lugmair, R. Rieder, H. W¨anke and T. Economou, in Proceedings of 30th Lunar and Planetary Science Conference, pp. 1250 (abstract), Houston TX (1999). K. L. Tanaka and D. H. Scott, Geologic Map of the Polar Regions of Mars (scale 1:15000000), USGS Misc. Inv. Series Map I-1802-C (1987). R. Kahn, J. Geophys. Res. 88 (1983) 10189. P. R. Christensen and R. W. Zurek, J. Geophys. Res. 89 (1984) 4587. P. C. Thomas, J. Veverka and R. Campos-Marquetti, J. Geophys. Res. 84 (1979) 4621. P. B. James, K. M. Malolepszy and L. J. Martin, Icarus 71 (1987) 298. J. W. Wilson, F. F. Badavi, F. A. Cucinotta, J. L. Shinn, G. D. Badhwar, R. Silberberg, C. H. Tsao, L. W. Townsend and R. K. Tripathi, HZETRN: Description of a Free-Space Ion and Nucleon Transport and Shielding Computer Program, NASA TP-3495 (1995). G. De Angelis, F. F. Badavi, J. M. Clem, S. R. Blattnig, M. S. Clowdsley, J. E. Nealy, R. K. Tripathi and J. W. Wilson, Paper SAE-2005-01-2831, pp. 1, Society for Automotive Engineering (SAE) (2005). J. M. Clem, G. De Angelis, P. Goldhagen and J. W. Wilson, Adv. Space Res. 32(1) (2003) 27. P. K. Saganti, F. A. Cucinotta, J. W. Wilson, L. C. Simonsen and C. J. Zeitlin, Space Scie. Rev. 110 (2004) 143. L. Dartnell, L. Desorgher, J. M. Ward and A. J. Coates, Biogeosciences 4 (2007) 545. L. Dartnell, L. Desorgher, J. M. Ward and A. J. Coates, Geophys. Res. Letters 34 (2007) L02207. P. Morthekai, M. Jain, L. R. Dartnell, A. S. Murray, L. B´ øtter-Jensen and L. Desorgher, Nuclear Instruments Methods A 580 (2007) 667.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

ZONAL VARIABILITY OF NEUTRAL DENSITY, TEMPERATURE AND ION PRODUCTION RATES IN THE MARTIAN TROPOSPHERE VARUN SHEEL∗ and S. A. HAIDER Physical Research Laboratory, Ahmedabad, India ∗ [email protected] V. SINGH Universita’ degli Studi di Brescia, Italia W. C. MAGUIRE NASA Goddard Space Flight Centre, Greenbelt, Maryland, USA G. J. MOLINA-CUBEROS Dipartimento di Fisica, Universidad de Murcia, Murcia, Spain

The Mars Global Surveyor (MGS) has measured proﬁles of atmospheric density, temperature and pressure through the radio occultation experiment. We have analysed this data to study the longitudinal variation of neutral density, temperature and ion production rates in the lower atmosphere of Mars at high latitudes. We report here prominent longitudinal wave-like variations of temperature and neutral density in the troposphere of both hemispheres of Mars. A Fourier transform analysis shows that there seems to be a preferred mode, which can be described by wave harmonics up to wave number 2 and 3 for the northern and southern high latitudes respectively. This could be a manifestation of the diﬀerent seasons for the two hemispheres.

1. Introduction Zonal variations of atmospheric parameters have been observed in planetary atmospheres. For example on Mars, oscillations associated with planetaryscale waves and baroclinic instability processes have been conjectured in the upper atmosphere.1 On the other hand, wave-like longitudinal temperature variations have been observed in Jupiter’s upper troposphere.2 Ubiquitous

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thermal waves at equatorial latitudes of Jupiter were shown to exhibit a broad distribution of spatial power with wavenumbers 2–15. Deming et al.3 and Magalhaes et al.4,5 found a monochromatic power distribution as a function of spatial wave number, with a preferred mode of wavenumber ∼10. Later, Ficher et al.6 found in the jovian troposphere, a broader distribution having wave numbers from 1 to beyond 20. The Mars Global Surveyor (MGS) reached Mars in September 1997. Among the many experiments onboard, the radio occultation experiment has measured proﬁles of atmospheric density, temperature and pressure.7 The technique is based on the analysis of the radio signals received by MGS as it enters and exits the occultation by Mars. These measurements reveal that atmosphere/ionosphere varies with longitude like a wave over to Mars seasons (cf. [1, 8, 9]). In this paper we have analyzed data from the radio occultation experiment on board the MGS to study the structure of density and temperature proﬁles in the troposphere of Mars. For this we chose three speciﬁc altitudes namely, 1 km, 15 km and 30 km.The data for the northern hemisphere are taken during the period 24–31 December 1998 near solar longitude, Ls = 74 − 77 at high latitude range 64.7◦N to 67.3◦ N between solar zenith angle 78–81 degree. For the southern hemispheric data, the period is 02–15 March 1998 and solar zenith angles 90◦ –93◦ at latitudes 60◦ – 64◦ S. These measurements are distributed fairly well between longitudes 0◦ and 360◦ E. At the time of these measurements, Mars had summer season with moderate solar activity period (f10.7 = 132 − 181). The f10.7 index is a measure of the solar radio ﬂux in solar ﬂux units (1 sfu = 10−22 watt m−2 hertz), at a wavelength of 10.7 cm, near the peak of the observed solar radio emission. It is an important indicator of solar activity because it tends to follow the changes in the solar ultraviolet that inﬂuence the atmosphere. It represents a measure of diﬀuse, non-radiative heating of the coronal plasma trapped by magnetic ﬁelds over active regions, and is therefore an excellent indicator of overall solar activity levels. We have interpolated the available data at every 5◦ longitude to use it for our calculations. These datasets are made available by the MGS radio science team at NASA’s Planetary Data System (http:/pds-geophys.wustl.edu/pds/mgs/rs/). The energy loss model is used in the troposphere for the calculation of ion production rates due to impact of galactic cosmic rays at observed longitudes between altitudes 1 to 40 km. The characteristic of longitudinal distribution of density and temperature in the Martian ionosphere is assumed to be approximated as

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follows: y = p1 + p2 sin ψ + p3 cos ψ + p4 sin 2ψ + p5 cos 2ψ

(1)

where ψ is longitude and y is a function of ψ. The parameters p1 to p5 are calculated using this equation in the form of matrix as y = AP where A is coeﬃcient matrix and p is column matrix of parameter p1 to p5. This approach is similar to the approximation used by Bougher et al.8 and Haider et al.9 for studying longitudinal variations in thermosphere/ionosphere of Mars. We have employed the above equation for least square spectral ﬁtting to the MGS measurements and the ion production rates calculated by us, in the troposphere. The ﬁtting parameters p1 to p5 are diﬀerent for each curves. The calculations of ion production rates in the troposphere of Mars are described in Sec. 2. In Sec. 3 we discuss the method used to calculate the power spectra. Finally results are discussed in Sec. 4.

2. Energy Loss Model The high energy cosmic rays propagate through the atmosphere, producing nucleonic cascades. The impact of primary cosmic rays, mainly protons and α particle onto the atmospheric molecules produces protons, neutrons and pions. Fast secondary nucleons can gain enough energy to increase the production of particles by neutral collisions. Neutral pions quickly decay to gamma rays, and their contribution to the energy deposition is very important in the lower part of the atmosphere. At high altitude level the maximum ion production rates are due to protons. Charged pions decay to muons, which do not decay before reaching the ground, and hence the muon energy is mainly transferred to the surface. The ﬂux of incident cosmic rays is assumed to be same at diﬀerent longitudes. It is exponentially attenuated and can be calculated as given below: X0 X(t, θ) = h0

∞

exp[−(t2 /2R + t. cos θ)/h0 ].dt

(2)

t

where R is the radius of Mars equal to 3,390 km, X0 (=20 gm/cm2 ) is the total atmospheric thickness of Mars in the vertical direction, t is the distance along the slant path which makes angle θ to the vertical and h0 is the scale

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height equal to 11 km. For θ up to ∼80◦ one can use the approximation as: X(t, θ) =

X0 exp(−t. cos θ/h0 ) cos θ

(3)

The diﬀerential ﬂux of the particles generated by cosmic rays at depth X is given by O’Brien et al.10 as: Fj (X, E) = Bj

X −X/Λ S0 e λ E γ+1 (1 + uj )

uj = Bj =

1 0

Hmj cτj E nj (rj ).rj .drj

(4) (5) (6)

o where X is the depth of the atmosphere, E is the energy, ESγ+1 is the cosmic ray nucleon spectrum at the top of the atmosphere, Λ and λ are the attenuation and interaction mean free path of the nucleon respectively, mj and τj are the mass and life time of the particle j, H is the scale height of the atmosphere, nj (rj ) is the number of particles of type j, which receive a fraction rj of the incident nucleon energy in an interaction. In order to derive Eq. (3), it is assumed that interaction mean free paths of pions and kaons are equal to Λ. The value of S0 is taken to be 2.35 × 104 , if the ﬂux is measured in m−2 s−1 ster−1 GeV−1 . γ is equal to 1.67. The interaction and attenuation mean free path of nucleons are equal to 75 gm/cm2 and 120 gm/cm2 respectively. Following Haider et al.11 the formula for energy loss per cm path into the material media by a particle traveling with the velocity V and undergoing inelastic collisions is written as: dE 2πe4 m0 V 2 E 2 ergs/cm (7) −β = N Z ln 2 dh ion m0 V 2 I (1 − β 2 )

For simplicity, it is convenient to introduce m0 V 2 = β 2 m0 c2 and E+m0 c2 = 2 2 m0 c / 1 − β , thus obtaining from Eq. (7) dE m0 c2 = 4πr02 2 N Z dh ion β

12 E 1 2 E + m0 c2 MeV/cm (8) − β × ln β I m0 c2 2

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where E is the energy, I is ionization potential, h is the height, r0 is the classical electron radius with 4πro2 = 1.00 × 10−24 cm2 /electron; β 2 = (V /c)2 = 1 − [(E/m0 c2 ) + 1]−2 , m0 c2 = 0.51 MeV (rest energy of electron), N is the neutral density (in molucles/m3 ), Z is the atomic number and c is the velocity of light. Rodrigo et al.12 and Nair et al.13 have modeled the atmospheric constituents CO2 , N2 , Ar , O2 , CO, H2 O, H2 , O, O3 , NO, NO2 and HNO3 in the lower atmosphere of Mars. Molina et al.14 have used this model atmosphere to study nighttime lower ionosphere of Mars. We have derived neutral densities of these gases from measured total density by multiplying it by the mixing ratios of their gases. The mixing ratios of these gases are taken from Molina et al.14 The measured density proﬁles in the troposphere of Mars are discussed in Sec. 4. Using Eq. (8) the ion production rate at height h and solar zenith angle χ is given below: p(h, χ) =

1 Q

(dE/dh)F (χ, E, Ω)dΩdE E

(9)

Ω

where Q = 35 eV is the energy required for the formation of an electron ion pair, χ is taken as 80◦ and F is the total diﬀerential ﬂux of the galactic cosmic rays being expressed in cm−2 s−1 GeV−1 ster−1 at height h and Ω is the spatial angle. Since the cosmic rays penetrate isotropically into the atmosphere, Eq. (9) reduces as follows: 2π p(h, χ) = Q

(dE/dh)F (χ, E)dE

(10)

These calculations are made at 0 to 40 km and 0◦ to 360◦E.

3. Results and Discussions The longitudinal distribution of density and temperature in the Martian ionosphere is approximated using Eq. (1) (for wave number 2). For wave number 3, we will have 7 coeﬃcients. In Fig. 1 we represent the zonal distribution of total air densities at altitudes 1 km, 15 km, and 30 km at high northern latitude region (64.7◦ N–67.3◦N) and high southern latitude region (60◦ –64◦ S). In Fig. 2 we illustrate longitudinal distribution of temperature measured at same latitude regions, solar zenith angles and longitudes as in Fig. 1. The solid and dashed lines in Figs. 1 and 2 represent the best ﬁt values to the above equation and 0.95 conﬁdence limits respectively.

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Fig. 1. Longitudinal distribution of Density proﬁles measured by MGS at high latitudes northern and southern hemisphere for altitudes 1 km, 15 km and 30 km. Solid line indicates best ﬁt to the data and dashed line represent 0.95 conﬁdence limits. The error bar is also plotted in this ﬁgure.

It can be seen from Figs. 1 and 2 that for the northern hemisphere, the maximum temperature and density are measured at two longitudes ∼190◦E and 320◦E at 15 km and 30 km. At 1km, the peaks are at 130◦E and 330◦ E for the neutral density and 60◦ E and 200◦ E for the temperature. This suggests the possibilities of wave 2 oscillation in the Martian troposphere. It seems that wave pattern in the northern troposphere is not much diﬀerent from thermosphere at same location, time and day of the measurement. Thermosphere structure of Mars is also dominated by wave 2 to 3 harmonics.9,15 On the other hand, the southern high latitude troposphere (60◦ S–64◦ S) exhibits a wave 3 oscillation, where the density peaks at 60◦ E, 190◦ E and 300◦ E for all altitudes. The corresponding peaks are less pronounced for the southern latitude temperature variations at 1 km and 30 km, whereas the corresponding

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Fig. 2. Longitudinal distribution of temperature proﬁles measured by MGS at high latitudes northern and southern hemisphere for altitudes 1 km, 15 km and 30 km. Solid line indicates the best ﬁt to the data and the dashed lines represent 0.95 conﬁdence limits. The error bar is also plotted in this ﬁgure.

spectra shows a dominant wavenumber 3 at 1 km but no clear periodicity at other altitudes. In Fig. 3, we have plotted the longitudinal variabilty of production rates + + of three major ions (CO+ 2 , N2 and Ar ) near the surface (at altitude∼1 km), for sample northern latitude at 67.3◦ N. One can see a wave two structure just like for the density and temperature of the high latitude northern hemisphere. The ion production rates are required to calculate the ion densities,16 which is important because there are not many observations of ion densities on Mars. Hence theoretical calculations give an important insight. 4. Conclusions We report here longitudinal wave-like variations of temperature and neutral density in the troposphere of Mars. The data for temperatures and density

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Ionisation Rate (cm-3 s-1)

Ionisation Rate (cm-3 s-1)

Ionisation Rate (cm-3 s-1)

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CO2+

1.20e+1

1.13e+1

1.05e+1 0

50

100

150

200

250

300

350

150

200

250

300

350

200

250

300

350

2.20e-1 N2+

2.00e-1 1.80e-1 1.60e-1 0

50

1.75e-1

100

Ar+

1.68e-1 1.61e-1 1.54e-1 0

50

100

150 Longitude

(oE)

Fig. 3. Longitudinal distribution of ion production rates calculated using the Energy Loss model, for the northern hemisphere at solar zenith angle 80◦ .

proﬁles has been taken from the observation made by the Radio Science experiment on board the MGS. These datasets are used in the calculation of ion production rates which are calculated using the energy loss method taking the impact ionization source as galactic cosmic rays. The neutral density, temperature and ion production rates represent wave 2 and wave 3 oscillations in troposphere as a function of longitudes. This is consistent with a semi-diurnal wave frequency in the Martian atmosphere. There seems to be a preferred mode of wavenumber 2 and 3 for the northern and southern high latitudes respectively. This could be a manifestation of the diﬀerent seasons for the two hemispheres.

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Acknowledgments Authors are thankful to G. L. Tyler et al.,17 Stanford University Stanford, California, USA, for his encouragement and providing us radio science data. References 1. S. P. Seth, V. Brahmananda Rao, C. M. Esprito Santo, S. A. Haider and V. R. Choksi, Zonal variations of peak ionization rates in upper atmosphere of Mars at high latitude using Mars Global Surveyor accelerometer data, J. Geophys. Res. 111 (2006), doi: 10.1029/2006JA011753. 2. Deming et al., Observations and Analysis of Longitudinal Thermal Waves on Jupiter, Icarus 126 (1997) 301–312. 3. D. Deming et al. A search for p-mode oscillations of Jupiter: Serendipitous observations of non-acoustic thermal wave structure, Astrophys. J. 343 (1989) 456–467. 4. J. A. Magalhaes et al., Slowly moving thermal features on Jupiter, Nature 337 (1989) 444–447. 5. J. A. Magalhaes et al., Zonal motion and structure in Jupiter’s upper troposphere from Voyager Infrared and imaging observations, Icarus 88 (1990) 39–72. 6. B. M. Fisher, High Time-Resolution Infrared Imaging Observations of Jupiter, Ph.D. Thesis, University of California, San Diego (1994). 7. D. P. Hinson, G. L. Tyler, J. L. Hollingsworth and R. J. Wilson, Radio occultation measurements of forced atmospheric waves on Mars, J. Geophys. Res. 106 (2001) 1463. 8. S. W. Bougher, S. Engel, D. P. Hinson and J. M. Forbes, Mars Global Surveyor Radio Science electron density profiles: Neutral atmosphere implications, Geophys. Res. Lett. 28 (2001) 3091–3094. 9. S. A. Haider, S. P. Seth, V. R. Choksi and K. I. Oyama, Model of photoelectron impact ionization within the high latitude ionosphere at Mars: Comparison of calculated and measured electron density, Icarus 185 (2006) 102–112. 10. O’Brien, K. W. Friedberg, H. H. Sauer, and D. F. Smart, Atmospheric cosmic rays and solar energetic particles at aircraft altitudes, Environ. Int. 22(Suppl. 1) (1996) S9–S44. 11. S. A. Haider, V. Singh, V. R. Choksi, W. C. Maguire and M. I. − Verigin, Calculated densities of H3 O+ (H2 O)n , NO− 2 (H2 O)n , CO3 (H2 O)n , and electron in the nighttime ionosphere of Mars: Impact of solar wind electron and galactic cosmic rays, J. Geophys. Res. 112 (2007) A12309, doi:10.1029/2007JA012530. 12. R. Rodrigo, E. Gracia-Alvarez, M. J. Lopez-Gonzalez and J. J. Lopezmoreno, A non-steady one dimensional theoretical model of Mars’neutral atmospheric composition between 30 and 200 km, J. Geophys. Res. 95 (1990) 14975–14810. 13. H. Nair, M. Allen, A. D. Anbar, Y. L. Yung and R. T. clancy, A photochemical model of the Martian atmosphere, Icarus 111 (1994) 124–150.

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14. G. J. Molina-Cuberos, H. Lichtenegger and K. Schwingenschuh, Ion neutral chemistry model of the lower ionosphere of Mars, J. Geophys. Res. 107 (2002), doi: 10.1029/2000JE0014447. 15. R. J. Wilson, Evidence for non-migrating thermal tides in the Mars upper atmosphere from the Mars Global Surveyor accelerometer experiment, Geophys. Res. Lett. 29 (2002). 16. S. A. Haider, V. Sheel, V. Singh, W. C. Maguire and G. J. Molina-Cuberos, Model calculation of production rates, ion and electron densities in the evening troposphere of Mars at latitudes 67◦ N and 62◦ S: Seasonal variability, J. Geophys. Res. 113 (2008) A08320, doi:10.1029/2007JA012980. 17. G. L. Tyler, G. Balmino, D. P. Hinson, W. S. Sjogren, D. E. Smith, R. A. Simpson, S. W. Asmar, P. Priest and J. D. Twicken, Radio science observations with Mars Global Surveyor: Orbit insertion through one Mars year in mapping orbit, J. Geophys. Res. 106 (2001) 23327–23348.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

SCIENTIFIC AND TECHNICAL ASPECTS OF THE ESA MARSNEXT MISSION A. CHICARRO∗ , J. D. CARPENTER, R. FISACKERLY and A. SANTOVINCENZO ESA-ESTEC, Noordwijk, The Netherlands ∗ [email protected] D. BREUER DLR Institute of Planetary Research, Berlin, Germany E. CHASSEFIERE LMD/CNRS, Paris, France V. DEHANT Royal Observatory, Brussels, Belgium M. GRADY Open University, Milton Keynes, United Kingdom P. PINET Observatoire Midi-Pyr´ en´ ees, Toulouse, France A. P. ROSSI ISSI, Bern, Switzerland

MarsNEXT is a mission in Phase A study by the European Space Agency in the context of preparations for a future mission for Mars Sample Return (MSR). The MarsNEXT mission demonstrates key technologies for European involvement in MSR, which will be an international eﬀort, and also addresses unanswered questions on the interior, atmosphere and history of Mars. These science objectives are realized through a network of landers, which work in synergy with an orbiting spacecraft, a conﬁguration which is required in order to achieve a global understanding of Mars.

1. Introduction The MarsNEXT (Mars Next EXploration and Technology) mission is currently undergoing a Phase A study in the European Space Agency (ESA), following a call for ideas of new missions to prepare for a future 235

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Mars Sample Return mission. MarsNEXT will demonstrate the concepts of rendezvous with and capture of a sample-containing canister in Mars orbit and will establish the ﬁrst network of scientiﬁc stations on the surface of Mars, to study the interior, surface and atmosphere of the planet. With multiple stations, distributed across the surface of Mars it is uniquely capable of performing simultaneous seismological and meteorological measurements in order to infer the internal structure and geodesy of the planet, as well as the atmospheric circulation and weather patterns. In addition, MarsNEXT will investigate the morphology and geology of the landing sites, the chemical and mineralogical composition of the local Martian subsurface, and determine the physical properties of surface materials. Such measurements complement our understanding of Mars and contribute to preparations for future missions. The overall MarsNEXT mission scenario is illustrated in Fig. 1. A Mars Network Mission has never before been implemented, despite repeated recommendations by the International Mars Exploration Working Group (IMEWG) and endorsement by the worldwide scientiﬁc community

Fig. 1.

Illustration of the MarsNEXT mission scenario.

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on various occasions. The concept of a network of stations on Mars has been the subject of several previous mission studies including the joint ESA-NASA INTERMARSNET1 and the CNES-led NetLander.2 The Network Mission concept addresses key science goals on a given terrestrial planet (in this case, Mars) that can only be achieved by simultaneous measurements from a number of landers, which are spaced across the surface of the planet. The primary objectives of such a mission concern the planet’s internal geophysics and its meteorology. In addition, coordinated studies at a number of landing sites provide crucial information on the geology and geochemistry of the planet. A Mars Network Mission also allows for a signiﬁcant improvement to our understanding of the rotational parameters of the planet. This can be achieved by means of radio transmission between the various landers and a single orbiter. Studies on the rotational parameters of Mars are an important complement to seismological studies. Thus important science objectives at Mars cannot be achieved by any other means than a Mars Network science mission, such as MarsNEXT. 2. Science Goals and Instruments The MarsNEXT mission was conceived as a unique opportunity to address the key scientiﬁc questions of seismology, meteorology, rotational dynamics and those aspects of geology and geochemistry accessible only from distributed sites. MarsNEXT carries, on three landers, scientiﬁc payloads proposed by the Science Deﬁnition Team (SDT) and indicated here. All three landers will carry a seismometer and a meteorological package, as well as a few instruments dealing with subsurface chemistry and imaging. An orbiter will support the surface science by providing a communication relay with the landers and carrying out global observations of the atmosphere and surface. Orbiter investigations will be selected through an Announcement of Opportunity in the same manner as those for the landers. 2.1. Interior and dynamics Present knowledge on the internal structure of Mars has been determined by comparison with other terrestrial planets and by indirect measurements (e.g. Refs. [3, 4]). Crustal thickness, phase transitions, the core size, and the inner core size are highly uncertain. Neither do we understand the internal dynamics nor the thermal evolution. Knowledge of the internal dynamics places important constraints on volcanic history, atmosphere evolution and

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habitability. The primary goal of the MarsNEXT mission is to obtain a signiﬁcant improvement in understanding the Mars’ interior structure and dynamics which can only be provided by a network of geophysical stations at the Martian surface together with orbital instruments.5 MarsNEXT will deploy seismometers at three locations and will investigate the planet’s rotational dynamics using a radio science experiment. The seismometers provide seismic data and thus information on the internal structure, rotation parameters are obtained via radio science measurements and these in turn put constraints on the core’s dimension, state, and moments of inertia. Both the remanent and induced magnetic ﬁelds will be measured by magnetometers deployed at each station and in orbit. With the induced magnetic ﬁeld, measured by a magnetometer, information on the conductivity proﬁle of the upper mantle can be obtained. Investigations into the thermal state and properties of soils will be made using temperature sensors deployed by self-burrowing moles at each site, which will provide measurements to depths of up to 5 m. The near-surface temperature proﬁles provide the heat ﬂow, which gives an insight into the planet’s internal heat budget and dynamics. The combination of these data sets at three locations on the surface and in orbit provide important, and presently poorly deﬁned, boundary conditions for models of the interior structure, bulk composition, temperature, and dynamics of Mars. 2.2. Rotation The rotation of Mars is characterized by its precession, nutation, polar motion, and rotation rate variations. Nutations are heavily inﬂuenced by resonance due to the core, if the core is liquid, and amplitudes provide information on the state, dimension and moment of inertia of the core. Precession provides the global moment of inertia. These parameters are measured by MarsNEXT through a combination of radio links between the landers and the orbiter. By combining precession and nutation information, Mars’ interior structure can be inferred. Combination of seismic data with other data from MarsNEXT experiments will then be used to provide a complete geophysical characterisation of the planet’s core. From the rotation rate variations, measured by the Doppler shifts on the various radio links, seasonal exchange of CO2 between the atmosphere and the ice caps will also be deduced. This provides constraints on the

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global atmospheric behaviour and in particular on the seasonal cycles of the CO2 sublimation and condensation in the ice caps. Information on the properties of the ionosphere and its total electric content will also be derived from the Doppler shift on radio signals at diﬀerent frequency bands. 2.3. Atmosphere & escape 2.3.1. Global atmospheric system and planetary evolution An important characteristic of the Martian atmosphere is the vertical extent of most meteorological phenomena, which contrasts with the Earth, where the stratosphere conﬁnes the Hadley cells and most of the planetary waves to the troposphere. On Mars, however, stuctures extend to the thermosphere. Monitoring the global atmosphere from the surface up to thermospheric levels is thus of key importance since the physico-chemical states of the various layers are strongly interdependent. Escape ﬂuxes of the diﬀerent species at the top of the atmosphere are controlled by the composition of the thermosphere and surrounding exosphere, their vertical structures and the solar wind-atmosphere interactions. Over long time scales, outgassing plays also a major role in the history of volatiles and climate, and interior-atmosphere interactions are therefore of crucial importance in driving atmospheric evolution. The Mars’ surfaceatmosphere-Sun system must therefore be studied as a whole for an in-depth understanding of the Martian meteorology and climate. MarsNEXT combines in-situ measurements at the surface from a network of stations, remote sensing of the low and middle atmosphere from the orbiter, and in-situ measurements of the high atmosphere and solar wind interaction regions from the orbiter (near periapsis during the aerobraking phase). 2.3.2. Meteorology, physical chemistry and climate The combination of surface station and orbiter measurements will provide an unprecedented picture of the global atmospheric circulation, characterized by a dynamical regime similar to that of the Earth.6 The cycles of distribution and transport of volatiles, particularly H2 O and dust, will be characterised through the combination of surface (meteorological and opacity sensors) and orbital (microwave and IR spectrometer) measurements. Direct measurements of winds in the middle atmosphere by microwave spectroscopy, and in the thermosphere by in-situ measurements

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from the orbiter, will be combined with surface wind measurements for the ﬁrst time. H2 O2 and O3 are key species of the Martian atmospheric chemistry. As shown by coupled Global Circulation Models (GCM)–photochemical models, ozone is expected to be globally anti-correlated with water vapour, but with some signiﬁcant departures from this global picture, as shown by the measurements of the SPICAM instrument on Mars-Express.7 If the atmospheric electric ﬁeld and conductivity measurements from surface stations show that electrical discharges occur in the low atmosphere, then the expected chemical signature of electrical phenomena (formation of H radicals and subsequently H2 O2 ) will be evidenced through simultaneous measurements of hydrogen peroxide and dust. In the ﬁeld of climate studies, the mission will focus on the water cycle, which is still poorly understood. Water vapor and water ice also aﬀect the thermal structure of the atmosphere. Since the ﬁrst detection of water vapour, the Martian water cycle has been studied through both Earthbased telescopic observations and spacecraft measurements. MGS/TES water seasonal climatology measurements provided the largest temporal and meridional coverage,8 but its absolute water amount should be revised downwards by about 30% according to the MEX/PFS instrument.9 Several crucial questions remain unanswered: (i) How much do subsurface reservoirs contribute to the water cycle? This question is still a matter of considerable debate; (ii) What is the vertical distribution of water vapour and how does it vary spatially and temporally? Our current knowledge of climatology is based on column integrated abundance, whereas there is no systematic measurement of the vertical proﬁle, especially in conjunction with water ice, dust loading, and temperature vertical proﬁles. Another key link is the HDO cycle. Condensation processes induce isotopic fractionation, decreasing the D/H ratio in water vapour while increasing the D/H ratio in water ice. Within the global water seasonal cycle, this eﬀect induces strong temporal, vertical and meridional gradients in the HDO/H2 O ratio.10 Therefore, HDO can act as a powerful tracer indicating the spatial origin of any air mass and the strength of dynamical processes governing the geographical distribution of water, thus constraining the global water cycle. MarsNEXT will provide the ﬁrst 3-D mapping of H2 O, HDO, temperature and opacity (dust and ice), completed by surface measurements of relevant parameters (p, T, humidity, opacity, 222 Rn as a tracer of surface/atmosphere exchanges).

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2.3.3. Volatile history and climate evolution Understanding the evolution of Mars requires quantiﬁcation of escape and its relationship to solar activity and extrapolation to the past. The history of outgassing must also be reconstructed. Present outgassing will be determined using a suite of dedicated instruments on the orbiter, including electron, ion and neutral spectrometers. Recent measurements of the MEX/ASPERA-3 instrument during solar minimum11 indicate an escape rate hundred times smaller than that measured during solar maximum. As predicted by most of theoretical works,12 ion and neutral escape rates are strongly dependent on the solarUV intensity and solar forcing. Mars should have lost several tens of metres of water over geological time because of past solar conditions and because it was not shielded by a global magnetic ﬁeld. Therefore, the present Martian atmosphere is either the residual of the atmosphere which formed at that time or the residual of a period of sporadic outgassing which occurred few tens of million years ago or is constrained by a permanent equilibrium between present outgassing and loss into space. The loss mechanisms are strongly dependent on the exospheric and thermospheric composition, the temperature and the density. The diﬀerent escape mechanisms are associated with ejection rates and with diﬀerent composition, spatial and energy distributions and intensities. Therefore the only way to distinguish them is to measure the in-situ energy, density and composition of the escaping ﬂux as well as of the exosphere on long and short times scales. The escape package of Marx-NEXT will provide self-consistent measurements of these diﬀerent populations. Orbital measurements of the magnetic ﬁeld, together with electrons and ions, will provide a picture of solar-wind atmosphere interaction conﬁguration and resulting mini-magnetospheres, also required for a detailed description of escape. Little is known about present outgassing. The still debatable detection of methane in the Martian atmosphere from Mars-Express and Earthbased observations13−15 suggests that methane currently is being produced. An internal origin (volcanism or hydrothermalism) would indicate present outgassing processes. Although no typical volcanic gas, like SO2 has been detected on Mars, the existence of recent lava ﬂows (≈2 million years old) on Tharsis and Elysium16 shows that a residual volcanism is still episodically active. The lack of any isotopic fractionation of carbon and oxygen in Martian CO2 , as measured from the Viking landers,17 suggests that the present atmosphere of Mars is young, since it should have been fractionated

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by escape if it was old. Detecting volcanic trace gases in the atmosphere of Mars would be of great interest, because it would provide information about the present outgassing rate, and the possibility of a balance between escape and outgassing. The main potential volcanic/hydrothermal gases (SO2 , CH4 from orbit by microwave and IR spectroscopy, 222 Rn from surface stations by alpha-particle spectrometry) will be searched for and measured, if detected. 2.4. Geomorphology, geology & geochemistry Mars has had a complex geological history which has been divided into three epochs: Noachian (4.6 − ∼3.7 Gyr), Hesperian (∼3.7 − ∼3.0 Gyr) and Amazonian (∼3.0 — Present).18−20 Volcanism has been widespread from the earliest times and throughout the whole of Mars’ history,21 and local volcanic activity might have continued until very recently.16 Mars’ stable lithosphere and long-lived mantle plumes result in production of extremely large volcanoes (such as those on the Tharsis bulge). Sedimentary processes were mostly active during earlier periods on Mars.22 Nevertheless, glacial and periglacial processes might have been important in the late Amazonian and possibly in the very recent (present) geological past, in the circumpolar areas but also at tropical latitudes.23,24 Mars tectonics, both compressional25 and extensional stresses have been active throughout its history26 and a large part of its tectonic deformation is linked with extensive and long-lived volcanic activity, mainly related to Tharsis (e.g. [27]). The impact cratering history on Mars28 has been preserved, interacting with other endogenic or exogenic processes. Impact cratering might also play a role in determining the major planetary dichotomy on Mars: the presence of clearly distinct highlands in the southern hemisphere contrasting with the northern lowlands.29 Although most geological activity took place in the Noachian, decreasing in later times, volcanism and tectonics appear to be locally sensibly younger, e.g. in Thaumasia highlands [30] and they could still be active today (e.g. [16]), a fact that makes detection of geological and geophysical activity very important. All missions to Mars to date have concentrated on investigations of the atmosphere and the surface. There has been no detailed investigation of the three-dimensional structure of the planet. As a result, we do not know the relative dimensions of the core, mantle and crust, or their physical state, information that is essential if we are to understand Mars’ evolution, and how the major water reservoirs interact. The landing site of each

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of the MarsNEXT mission probes must be fully characterized in order to determine the type of rocks on which each probe has landed. This information is essential for correct interpretation of the geophysical data, as well as gaining a better understanding of the evolution of the Martian surface. For a full characterization of each landing site, two complementary suites of investigations are required, the ﬁrst to determine the geology and geomorphology of the site, and the second to ascertain the composition of the surface and subsurface, including measurement of the range and abundance of volatiles and volatile-bearing salts. 2.4.1. Geology and geomorphology of the landing site On MarsNEXT, the most obvious characteristics of each landing site (topography, features such as craters or rock outcrops, surface roughness, etc.) will be acquired by orbital and surface imagery. As well as giving the context to the geophysical measurements that are the main goal of MarsNEXT, there are speciﬁc scientiﬁc objectives that can be achieved. Reconstruction of the local stratigraphy will allow understanding of geological processes that formed the rock sequence of the landing site area and the relative time frame over which these processes operated. Identiﬁcation and characterisation of morphological features can indicate the presence of wind-related structures and deposits (dunes, crossbedded strata, etc.), so that current or historical atmospheric conditions (particularly wind regimes) may be resolvable. Imagery will also record distinguishable features of the surface layers and of the grains which they are made of. Such measurements are required to help in the interpretation of the physical properties of the Martian surface and subsurface (heat ﬂow, conductivity, etc.) obtained via subsurface measurements. A more detailed determination of the mineralogy and geochemistry of the rocks and soil at the various landing sites will require measurements not just from the surface, but also from the subsurface, in order to account for the eﬀects of weathering and alteration. Near to mid-infrared spectroscopy of the subsurface will help to identify the minerals present, and, indicate their mineral chemical composition. Infrared spectroscopy will also indicate the presence of water. One speciﬁc set of information that will be gained through the study of the geochemistry of the landing sites regards the eﬀects of water at and below the Martian surface. Identiﬁcation of liquid water on or near the Martian surface over an extended period of time has implications for the extent

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of erosion and weathering that has taken place, as well as aﬀecting the interpretation of heat ﬂow measurements. The presence of water is also a main determinant of the potential habitability of Mars. Key minerals for understanding the role of water in Mars’ evolution include primary maﬁc silicates and oxides, as well as secondary hydrated minerals (clays and sulfates).31 The presence of phyllosilicates in very ancient terrains suggests the existence of liquid water in the primitive environment of Mars. Results from remote spectroscopic observations (OMEGA on MEX and CRISM on MRO) indicate that there is an association between phyllosilicates, sulfates and iron oxides that has led to the development of a Martian chronology based on stratigraphy. Three periods of alteration have been recognized and given the names Phyllosian, Theiikian and Siderikian31 on the basis of the mineralogy of the sediments. Despite the concentration of CO2 in the Martian atmosphere, and identiﬁcation of carbonates in Martian meteorites, massive amounts of carbonates have not been detected on the surface of Mars. It is currently thought that ﬂuids might have been too acidic to allow precipitation of carbonates. On the basis of fundamental chemical and physical principles, it has been proposed32 that climate conditions which enable the existence of liquid water were maintained by appreciable atmospheric concentrations of volcanically-degassed SO2 and H2 S. The geochemistry resulting from the equilibrium of such an atmosphere with the hydrological cycle has been shown to inhibit the formation of carbonates. Thus the occurrence of layered sulfate-bearing sediments on Mars suggests the presence of water as a liquid phase during at least part of the Martian geological history. The determination of the mineralogy of these sulfate-bearing minerals will indicate the speciﬁc mechanisms (e.g. hydrothermal alteration of volcanic materials, brine/evaporite scenario in an aqueous environment, etc.) by which the sulfates were emplaced and the evolution of the Martian environment during geological time scales. Studies of volatiles are aimed at the identiﬁcation of any liquid water or ice in the subsurface of the landing site area, as well as the identiﬁcation of primary maﬁc minerals, secondary hydrated minerals (including phyllosilicates and sulfates) and iron oxides. If an instrumented mole were to be incorporated into the lander, it would be possible to acquire the vertical distribution of the soil mineralogy and geochemistry within the ﬁrst few metres of the regolith. These objectives present a high level of synergy with those to be addressed by the atmospheric chemistry experiments aimed at monitoring global and local distributions of key

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photochemical species and outgassed volcanic gases and key electrochemical species (e.g. H2 O2 ). Measurements, made with an instrumented mole, would deliver decisive information for testing alternative alteration reaction pathways.33 It is also pointed out that this in-situ geological/geochemical strategy is intimately related to the topics of ancient Mars climate evolution and conditions of habitability. 3. Mission Outline The MarsNEXT spacecraft consists of a Mars orbiter carrying three identical 120-kg class Network Science Probes. Each probe has a surface payload mass capability of 8.5 kg. The orbiter includes a 30 kg science payload in addition of the rendezvous and capture experiment. A possible design for a surface probe is shown in Fig. 2. The MarsNEXT spacecraft will be launched by a Soyuz 2.1b vehicle from the Guiana Space Centre (CSG). The nominal launch date is September 2015 with a back-up in September 2017. The baseline Earth-toMars transfer trajectory is a type T4 (i.e. based on more than 1.5 revolutions about the Sun) transfer requiring a 2.5-year cruise duration but with a minimum delta-V and low Mars arrival velocity. On its hyperbolic approach to Mars, the orbiter will sequentially deploy the probes. The mission design can support a Mars surface conﬁguration with one lander in an almost

Fig. 2.

A possible design for a MarsNEXT lander.

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antipodal location (i.e. about 130◦ apart) with respect to the other two. The ﬁrst probe release takes place as early as 28 days before entry; during this coasting phase the probes will be hibernated similarly to the scenario implemented during the Huygens mission. The entry will be ballistic and the descent phase will employ a single parachute and retrorockets to null vertical velocity above a given altitude over the Martian surface. In the last metres, the lander will perform a free fall and touch down cushioned by a non-vented bouncing airbag system. The nominal Mars surface mission duration is one Martian year (687 days). A latitude range between −15◦ and +30◦ is taken as reference for the mission, EDLS (Entry, Descent and Landing System) and lander designs. After the probes release, the orbiter performs a Mars Orbit Insertion (MOI) and a ﬁrst manoeuvre to reduce the apogee altitude. After that, an aerobraking sequence decreases further the apogee to about 500 km. A ﬁnal propulsive burn circularises the orbit. A possible design for the orbiter is shown in Fig. 3. The aerobraking phase will last for about 6 months. During aerobraking, the opportunity for magnetospheric science requiring lowaltitude measurements will be exploited (e.g. detailed mapping of the crustal magnetic anomalies). When the spacecraft reaches its ﬁnal Mars orbit, the MSR automatic rendezvous and capture demonstration is performed. In this demonstration, the orbiter will rehearse the rendezvous sequence between the MSR orbiter and the non-collaborative sample container. This phase will last for about two months. After the rendezvous demonstration the orbital science phase will start in synergy with the landers. Orbital science and relay with the

Fig. 3.

A possible design for a MarsNEXT orbiter.

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probes will take place in parallel until termination of the surface mission. The nominal mission lifetime of the orbiter in Mars orbit will be two Martian years.

4. Landing Site Selection The number and location of the MarsNEXT surface elements is strongly dependent on the science objectives of the mission and the measurement techniques required to meet those objectives. Previous authors have investigated probable landing sites for a Mars network (e.g. Refs. [33, 34]). Seismological measurements have the greatest dependence on the number of landers. A minimum of three surface stations is required to locate Martian quakes and determine their frequency and magnitude. The three landers should nominally be located around a seismically active region, a potential example being Tharsis. The addition of a fourth station in the opposing hemisphere of the planet would provide key data for deriving the state of the Martian core and the size of a possible inner core. For measurements on rotation, precession and nutation, sites on or near the equator are the best. For measurements of polar motion, a station at higher latitudes is needed. Landers distributed across the surface and supported by an orbiter allow the characterisation of large scale atmospheric phenomena, including, wave structures, Hadley cells and global dust storms. For measurements from the surface associated with geology, geochemistry and astrobiology it is desirable to have data from a number of new geological units across Mars not yet visited by other surface elements.

5. Concluding Remarks Network Science is crucial in order to achieve fundamental Mars scientiﬁc objectives, such as the study of the Mars’ interior, the planet’s rotation and atmospheric dynamics, fully complementary to ongoing Mars missions and Mars Sample Return. The MarsNEXT Mission represents a timely scientiﬁc opportunity, and oﬀers a chance for Europe to lead the ﬁeld of geophysical exploration, building on the heritage gained by Mars Express (radar sounding). In addition, a very strong interest exists in the scientiﬁc community worldwide (and especially in the USA, Japan, Russia & Canada) for this mission. The MarsNEXT Mission provides the global geological evolution context to interpret the astrobiological, geochemical and mineralogical ﬁndings from other missions.

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Acknowledgments The authors wish to acknowledge the work of the two industrial consortia involved in the MarsNEXT study, which are being led by EADS-Astrium (Toulouse, France) and Thales-Alenia Space (Turin, Italy); and the engineering team at ESA-ESTEC.

References 1. INTERMARSNET — Report of the Phase — A Study, Chicarro A. Editor, ESA SCI(96)2 (1996). 2. The Netlander Mission, CNES (1998–2003), http://smsc.cnes.fr/ NETLANDER/ 3. C. F. Yoder, A. S. Kosnopliv, D. N. Yuan, E. M. Standish and W. M. Folkner, Science 300 (2003) 299. 4. A. S. Konopliv, C. F. Yoder, E. M. Standish, D. Yuan and W. L. Sjogren, Icarus 182 (2006) 23. 5. O. Verhoeven, A. Rivoldini, P. Vacher, A. Mocquet, G. Choblet, M. Menvielle, V. Dehant, T. Van Hoolst, J. Sleewaegen, J.-P. Barriot and P. Lognonn´e, J. Geophys. Res. 110 (2005). 6. C. Leovy, Nature 412 (2001) 245. 7. S. Lebonnois, E. Qu´emerais, F. Montmessin, F. Lef`evre, S. Perrier, J. Bertaux, and F. Forget, J. Geophys. Res. 111 (2006) 9. 8. M. D. Smith, Icarus 167 (2004) 148. 9. F. Fouchet, E. Lellouch, N. I. Ignatiev, F. Forget, D. V. Titov, M. Tschimmel, F. Montmessin, V. Formisano, M. Giuranna, A. Maturilli and T. Encrenaz, Icarus 190 (2007) 32. 10. F. Montmessin, T. Fouchet and F. Forget, J. Geophys. Res. 110 (2005). 11. S. Barabash, A. Fedorov, R. Lundin and J.-A. Sauvaud, Science 315 (2007) 501. 12. E. Chasseﬁ`ere and F. Leblanc, PSS 52 (2004) 1039. 13. V. Formisano, S. Atreya, T. Encrenaz, N. Ignatiev and M. Giuranna, Science 306 (2004) 1758. 14. V. A. Krasnopolsky, J. P. Maillard and T. C. Owen, Icarus 172 (2004) 537. 15. M. J. Mumma, R. E. Novak, T. Hewagama, G. L. Villanueva, B. P. Bonev, M. A. DiSanti, M. D. Smith and N. Dello Russo, Bull. Am. Astron. Soc. 36 (2004) 1127. 16. G. Neukum, R. Jaumann, H. Hoﬀmann, E. Hauber, J. W. Head, A. T. Basilevsky, B. A. Ivanov, S. C. Werner, S. Van Gasselts, J. B. Murray and T. McCord, Nature 432 (2004) 971. 17. T. Owen, in Mars, edited by H. Kiefer et al., Univ. of Arizona Press, Tucson, Ariz., 818 (1992). 18. K. L. Tanaka, J. Geophys. Res. 91 (1986) 139. 19. K. L. Tanaka, D. H. Scott and R. Greeley, Global stratigraphy, in Mars, edited by H. Kiefer et al., Univ. of Arizona Press, Tucson, Ariz., 345 (1992).

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20. W. K. Hartmann and G. Neukum, Space Science Reviews 96 (2001) 165. 21. P. J. Mouginis-Mark, L. Wilson and M. T. Zuber, The physical volcanology of Mars, in Mars, edited by H. Kiefer et al., Univ. of Arizona Press, Tucson, Ariz., 424 (1992). 22. M. C. Malin and K. S. Edgett, Science 290 (2000) 192. 23. J. W. Head, G. Neukum, R. Jaumann, H. Hiesinger, E. Hauber, M. Carr, P. Masson, B. Foing, H. Hoﬀmann, M. Kreslavsky, S. Werner, S. Milkovich and S. van Gasselt, Co-Investigator Team, Nature 434 (2005) 34. 24. J. W. Head, The geology of Mars: New insights and outstanding questions, in The Geology of Mars: Evidence From Earth-Based Analogs, edited by M. G. Chapman, 1, Cambridge University Press, Cambridge (2007). 25. A. F. Chicarro, P. H. Schultz and P. Masson, Icarus 63 (1985) 153. 26. W. B. Banerdt, M. P. Golombek and K. L. Tanaka, Stress and tectonics on Mars, in Mars, edited by H. Kiefer et al., Univ. of Arizona Press, Tucson, Ariz., 249 (1992). 27. R. C. Anderson, J. M. Dohm, M. P. Golombek, A. F. C. Haldemann, B. J. Franklin, K. L. Tanaka, J. Lias and B. Peer, J. Geophys. Res. 106 (2001) 2056. 28. R. G. Strom, S. K. Croft and N. G. Barlow, The Martian impact cratering record, in Mars, edited by H. Kiefer et al., Univ. of Arizona Press, Tucson, Ariz., 383 (1992). 29. J. C. Andrews-Hanna, M. T. Zuber and W. B. Banerdt, Nature 453 (2008) 1212. 30. J. M. Dohm and K. L. Tanaka, Planetary and Space Science 47 (1999) 411. 31. J. P. Bibring, Y. Langevin, J. F. Mustard, F. Poulet, R. Arvidson, A. Gendrin, B. Gondet, N. Mangold, P. Pinet, F. Forget and the OMEGA team, Science 312 (2006) 400. 32. I. Halevy, M. T. Zuber and D. P. Schrag, Science 318 (2007) 1903. 33. G. Angelis and A. Chicarro, INTERMARSNET Mission — A Catalogue of Potential Landing Sites, ESA Contr. EP/SB/14.7/1900, ESA/ESTEC, Noordwijk, The Netherlands (1995). 34. G. Angelis and A. Chicarro, Planetary and Space Science 44(11) (1995) 1325–1346.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

STUDY ON THE O+ ION DISTRIBUTION AND ESCAPE IN MARTIAN ATMOSPHERE JIANKUI SHI∗ and ZHENXING LIU State Key Laboratory of Space Weather, CSSAR/CAS, Beijing 100190, China ∗ [email protected] KLAUS TORKAR and TIELONG ZHANG Space Research Institute, Austrian Academy of Sciences, Graz A-8042, Austria MALCOLM DUNLOP Rutherford Appleton Laboratory, UK

In this paper, we have considered the view that the Martian magnetic moment has been gradually decreasing from the past to the present, and have calculated the O+ ion ﬂux distribution along magnetic ﬁeld lines and the escaping ion ﬂux in the Martian tail with diﬀerent assumed Martian magnetic moments. The results show that the O+ ions ﬂux along magnetic ﬁeld lines decreases with increasing distance to Mars; that the ion ﬂux along the ﬁeld line decreases more rapidly if the magnetic moment is larger; and that the larger the magnetic moment, the smaller the ion ﬂux in the Martian tail becomes. The escaping ion ﬂux depends on the Z-coordinate in the Martian tail. With decreasing magnetic moment, the escaping ion ﬂux in the Martian tail is increasing. The results are signiﬁcant for studying the ion loss from Mars.

1. Introduction First reports of observations that Mars has magnetic ﬁeld, plasma and magnetopause appeared1 as early as in the 1960s. Thereafter, it was discovered that a bow-shock located close to Mars does permanently exist. There is a magnetic tail on the night side of Mars which is compressible, i.e. its lateral thickness decreases with increasing solar wind ram pressure. Other observations in the Martian atmosphere 2−5 showed the existence of a weak dipolar intrinsic magnetic moment. At higher altitudes the Martian magnetic ﬁeld is mainly an induced ﬁeld due to interaction of the solar wind with Mars.6,7 The early observations from spacecraft in situ also quantify 251

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the Martian dipole moment to within a range from about 2 × 1021 G · cm3 ,8 to about 8 × 1021 G · cm3 .1 Initial data from the spacecraft Mars Global Surveyor (MGS) point at an upper limit for the Martian moment of 2 × 1021 G cm3 ,5 but later the MGS/ER investigation reﬁned its estimate of the upper limit and showed that is about 10 times lower than the previous estimation.9 The observed weak surface magnetic ﬁelds on Mars seem to argue against a currently operating planetary dynamo. Glassmeier et al.10 pointed out that weak surface magnetic ﬁelds are also expected if a polarity of the Martian dipolar moment reversal occurs. This view implies that the Martian magnetic moment is gradually reducing from the past to the present.10 Nevertheless, Acuna et al.9 and Connerney et al.11 reported that MGS also measured crustal magnetic ﬁelds in the Mars. Unfortunately the Mars Express (MEX) spacecraft does not have a magnetometer on board to obtain magnetic ﬁeld data some author analyzed features of the crustal magnetic ﬁelds by other data from the instrument onboard the MEX. Soobiah et al.12 analyzed observations from the ASPERA-3 instrument on board the MEX near to crustal anomalies and found that the electrons near remanent magnetic ﬁelds either increase in ﬂux to form intensiﬁed signatures or signiﬁcantly reduce in ﬂux to form plasma voids. Franz et al.13 using data of the ASPERA-3 investigate eﬀect of the Martian crustal ﬁelds on electrons intruding from the magnetosheath and the shielding of precipitating electrons by the crustal ﬁelds. The analysis based on observations also shows that most of the Martian surface was covered by water in the past and the water has meanwhile disappeared. There are two views on the reasons for the water loss. One is that the water merged into rock in the Martian surface. The other is that the water ﬁrst vaporized into the atmosphere and ionized to O+ and H+ ions by solar radiation, and then moved out of the Martian atmosphere, i.e. the ions escaped. Since the O+ and H+ ions are charged particles and their movement is controlled by the magnetic ﬁeld, the ion escape will be inﬂuenced by the magnetic moment and its evolution. The early observations show that the Martian tail is composed of H+ and heavy ions which are basically of ionospheric origin.14,15 The Martian plasmasheet is mainly formed by O+ ions. The typical ﬂux of the O+ ions in the plasmasheet is about 2.5 × 107 cm−2 s−1 .16 Verigin et al.16 suggested that a polar wind mechanism could be responsible for the existence of O+ ions in the Martian magnetotail, similar to that reported by Lundin et al.17 in which thermal ions from the ionosphere are moving along the magnetic ﬁeld lines towards the plasmasheet. In the recent, Kallio et al.18 performed

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a numerical simulation to analyze the energy spectra of escaping planetary O+ and O+ 2 ions at Mars. The simulated time–energy spectrograms were generated along orbit no. 555 of MEX when its ASPERA-3 detected escaping planetary ions. The result show that O+ ions originating from the ionized hot oxygen corona are resulted in a high-energy (>1 keV) O+ ion population that exists very close to Mars. Using the data from the ASPERA-3, Carlsson et al.19 have examined 77 diﬀerent ion-beam events and the results showed that the most abundant ion species was found to +2 . Futaana et al.20 reported that the be O+ , followed by O+ 2 and CO ASPERA-3 detected intense ﬂuxes of neutral particles those are likely to be generated in the subsolar region of the Martian exosphere. According to early satellite observation that Mar has a weak intrinsic dipolar magnetic moment, Lammer21 and Haider22 studied the charged particles distributions along the magnetic ﬁeld lines in the Mars. Shi et al.23,24 also studied the ion distribution along the magnetic ﬁeld line in the Martian magnetosphere. However, the later satellite observation showed that the Mars has no intrinsic magnetic ﬁeld at present. In this paper, considering the reduction of the Martian magnetic moment from past to present, we study the O+ ion distribution along magnetic ﬁeld lines from the ionosphere to the Martian tail with the method as that shown in the references.23,24 We also study the ion escape ﬂux under diﬀerent assumed magnetic moments, which could correspond to the diﬀerent evolutionary stages of the Martian intrinsic moment from past to present. 2. Basic Method and Computational Formulation We suppose that there is an exobase S0 over the polar region of Mars. Above it, the guiding center approach is valid because collisions can be ignored. For the ions moving above the exobase S0 , quasi-neutrality holds everywhere, and both the ion gyro-radius and gyro-period are much smaller than the characteristic distance and the characteristic time of the ﬁeld changes, respectively. The ion velocity distribution function along the ﬁeld line can be taken as25,26 f (s, ull , u⊥ )  1 2 2   N C exp − 2 M (ull + u⊥ ) − E0 + Φ , (θ < θ , E > E ) 0 m m T =  0 (other) (1)

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where s is the coordinate along the ﬁeld line, N0 is the ion density at point which is located at the exobase S0 . M is the ion mass, ull and u⊥ are the ion velocities parallel and perpendicular to the ﬁeld line, respectively, Φ is the gravitational potential energy, θ = arctan(u⊥ /ull ) is the ion pitch angle, and E = 1/2M (u2ll + u2⊥ ) is the ion kinetic energy, and E0 is its initial value (at the point S0 ). T = T0 + E0 and T0 are ion temperatures. T0 , E0 and C are constants. θm is the maximum ion pitch angle, Em = E0 − Φ. Considering that θm is small, the Eq. (1) implies that only ions with suﬃcient energy parallel to the magnetic ﬁeld can move upward to the Martian tail. By integrating the ion velocity distribution function, we obtain the ion ﬂux j(s) along the ﬁeld line as ull f (s, ull , u⊥ )u⊥ dull du⊥ (2) j(s) = U

The integration region U is the area: θ < θm , E > Em on the phase space ull − u⊥ . Considering the magnetic ﬂux, the normalized ion ﬂux J(s) along the ﬁeld line (the ratio of the ion ﬂux at s over that at s0 ) can be written as B · U ull f (s, ull, u⊥ )u⊥ dull du⊥ J(s) = (3) B0 · U ull f (s0 , ull, u⊥ )u⊥ dull du⊥ Here B is the magnetic ﬁeld and B0 is its value at the Base S0 . 3. Results and Discussion Based on the view that the Martian magnetic moment is gradually decreasing, we assume that the Martian magnetic ﬁeld consists of an intrinsic dipole ﬁeld with changing moment and an induced ﬁeld.27 That is: T = m · (cos λ/r2 ) + B B  (0 ≤ λ < π/2)   BT ex BT = 0 (λ = π/2)   −BT ex (π/2 < λ ≤ π)

(4)

(5)

Here m is the Martian magnetic moment, λ is the co-latitude and ex is the unit vector along the x-axis. BT is constant and is mainly contributed by the IMF. The data suggest BT is about 10 nT, so we take BT = 10 nT into account in this study. Also, in this paper, we take the exobase S0 as 1.1RM (RM is the Martian radius), T0 = 2,000◦ K, and E0 = 2.5 eV. Then, we use the Eq. (3) to calculate the ion ﬂux distribution along the magnetic

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ﬁeld line with diﬀerent assumed magnetic moments. A coordinate system similar to GSM was taken for this study, but the origin is at the center of Mars instead of the Earth. Figure 1 shows the normalized O+ ion ﬂux distribution along the magnetic ﬁeld lines at diﬀerent co-latitudes for the assumed Martian magnetic moment of 2 × 1021 G cm3 . In Fig. 1, curves from left to right correspond to ﬁeld lines at co-latitudes 5◦ , 15◦ , 25◦ , 35◦ and 45◦ , respectively, and −X is the distance to the Martian center on the nightside. From the Fig. 1 we can deduce that the O+ ion ﬂux along the ﬁeld line decreases with distance from the planet at any co-latitude. When the co-latitude lies between 5◦ and 35◦ , larger the co-latitude result in a more rapid decrease of the O+ ion ﬂux along the ﬁeld line and a lower ﬂux in the Martian tail. Above 40◦ , the trend is reversed, and larger the colatitudes correlate with a slower decrease the O+ ion ﬂux with Martian distance, leading to a higher ﬂux in the Martian tail. These results introduce a dependence of the O+ ion ﬂux in the Martian tail on the coordinate Z. Figure 2 illustrates the normalized O+ ion ﬂux versus coordinate Z in the Martian tail when the coordinate X takes a ﬁxed value of −2.8RM . It 1.2

1.0

5 15 25 35 45

J(s)

0.8

0.6

0.4

0.2 0.0

1.0

2.0

3.0

−X / RM Fig. 1. The O+ ion ﬂux distribution along diﬀerent magnetic ﬁeld lines with assumed magnetic moment of 2 × 1021 G · cm3 .

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0.48

0.44

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0.28 0.40

0.60

0.80

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Z / RM Fig. 2. The O+ ion ﬂux versus coordinate Z in the Martian tail at X = −2.8RM and the assumed Martian moment of 2 × 1021 G · cm3 .

can be seen in the Fig. 2 that the O+ ion ﬂux in the Martian tail changes with the coordinate Z. When Z < 0.8RM , the O+ ion ﬂux decreases with increasing Z. At Z = 0.8RM , the normalized O+ ion ﬂux reaches a minimum of 0.32. When Z > 0.8RM , the O+ ion ﬂux increases with increasing Z. From a physics point of view it is perfectly reasonable that the O+ ion ﬂux decreases along the ﬁeld line. The O+ ions in the Martian atmosphere mainly originate from the ionosphere rather than from the solar wind. During the ions’ up-ﬂow from the Martian ionosphere, they are mainly controlled by the action of the magnetic ﬁeld and gravity. Thus, the ion density will be gradually decreasing with increasing distance from the planet. If the variation of the ion velocity is not too large, the ion ﬂux will decrease with increasing distance, too. On the other hand, the conﬁguration of the magnetic ﬁeld has an eﬀect on the ion distribution. From Eq. (1) we can see that only ions with large upward velocity can move outward to the Martian tail. Because of moving along the ﬁeld line, the ion will have an outward velocity in the Martian tail. According to the observation, the magnetic ﬁeld is controlled by the solar wind at a distance

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of 2.8RM in the Martian tail,6,7 thus the ions will be lost or escape from the Martian atmosphere. The ﬂux of escaping ions is just as the ion ﬂux that we have studied in this paper. Our study also shows that the ion ﬂux distribution depends on the assumed Martian magnetic moment. That is to say, the escaping ion ﬂux is diﬀerent in diﬀerent stages of evolution of the Martian moment. Figure 3 illustrates the O+ ion ﬂux distribution along the ﬁeld line at a co-latitude of 10◦ with assumed moments of 1 × 1021 G · cm3 , 2 × 1021 G · cm3 , 5 × 1021 G · cm3 , and 10 × 1021 G · cm3 , respectively. From Fig. 3 we can see for an assumed magnetic moment of about 1 × 1021 G · cm3 , that the normalized O+ ion ﬂux along the ﬁeld line decreases slowly and becomes about 0.55 at X = −2.8RM in the Martian Tail. The decrease is more pronounced for larger assumed moments, at X = −2.8RM , namely to 0.37 for 2 × 1021 G · cm3 , 0.15 for 5 × 1021 G · cm3 , and 0.045 for 10 × 1021 G · cm3 . This means that the Martian magnetic moment has a signiﬁcant inﬂuence on the ion ﬂux distribution along the ﬁeld lines. As mentioned above, the ion ﬂux at X = −2.8RM in the Martian tail is equivalent to the ion escaping ﬂux because the IMF is dominant at 1.2

J(s)

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m = 1.0E+21 m = 2.0E+21

0.4

m = 5.0E+21 m = 10.0E+21

0.0 0.0

1.0

2.0

3.0

X / RM O+

Fig. 3. The ion ﬂux distribution along the ﬁeld line at co-latitude 10◦ for diﬀerent assumed Martian magnetic moments.

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J(s)

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0.2

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8.0

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m / 1.0E+21

Fig. 4.

The ion escaping ﬂux versus assumed Martian magnetic moment.

this distance. Therefore, the Martian magnetic moment has a signiﬁcant inﬂuence on the escaping ion ﬂux in the Martian tail. Figure 4 shows the escaping O+ ion ﬂux versus the assumed Martian magnetic moment. The escaping O+ ion ﬂux is equivalent to the ion ﬂux along the ﬁeld line at co-latitude 10◦ and at X = −2.8Rm in the Martian tail. It can be seen from Fig. 4 that a decrease of the Martian magnetic moment from 10 × 1021 G · cm3 to 1 × 1021 G · cm3 , leads to an enhancement of the normalized escaping O+ ion ﬂux from 0.045 to 0.55 in the Martian tail. If we take the O+ ion ﬂux at S0 as 2 × 107 ions · cm−2 · s−1 ,22 then the escaping O+ ion ﬂux in the Martian tail will increase from 0.09 × 107 ions · cm−2 · s−1 to 1.1 × 107 ions · cm−2 · s−1 with the above mentioned decrease of the Martian moment from 10 × 1021 G · cm3 to 1 × 1021 G · cm3 , i.e. the normalized escaping ion ﬂux is reduced by more than one order of magnitude. This implies that the escaping ion ﬂux has been increasing from the past to the present, while the Martian moment was retreating. For the time scales in the changing magnetic moment of the Mars and consequently the time scales related to the change in ﬂux of escaping O+ ions, it is diﬃcult to estimate them because of the lack of the observation. But from the Fig. 4, we can get a correlation between the escaped ion ﬂux and the magnetic moment. We expect if we can deduce the time scales of the changing magnetic moment by analysis the structure of the rocks on

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the Mars, consequently we can know the time scales of the change in ﬂux of escaping O+ ions from the Mars. In this paper, we assume that the Martian magnetosphere was formed by a superposition of an intrinsic dipolar magnetic ﬁeld and an induced magnetic ﬁeld in Martian history. Thus, the ions are mainly moving along the ﬁeld lines and are controlled by the magnetic ﬁeld. The stronger the magnetic moment, the tighter the ﬁeld line is connected to Mars, the more ions are controlled in near-Mars space, and the smaller is the escaping ion ﬂux in the Martian tail. Therefore, it is reasonable to conclude that the escaping ion ﬂux increases with decreasing Martian magnetic moment. 4. Summary We have considered the view that the Martian magnetic moment has been gradually decreasing from the past to the present, and investigated the distribution of the ﬂux of the O+ ion originating from the Martian ionosphere along the ﬁeld line starting from the ion exobase and the escaping O+ ion ﬂux in the Martian tail. The results show that the O+ ion ﬂux along the ﬁeld lines in the Martian magnetosphere decreases with distance from Mars; and that the ﬂux of the ions along a ﬁeld line decreases more rapidly when the magnetic moment is larger. The smaller is the moment, the larger is the escaping ion ﬂux in the Martian tail. Thus, from the past to the present, the ion escape ﬂux in the Martian tail gradually becomes larger and larger. This study is signiﬁcant for us to understand ion escape from the Martian atmosphere, and it should be helpful for us to understand the water lost from the Mars. Acknowledgment This research was supported by National Natural Science Foundation of China grant under 40921063, Chinese Academy of Sciences grants KJCX2YW-T13-3, and the Specialized Research Fund for State Key Laboratories of China. References 1. J. J. O’Gallagher and J. A. Simpson, Science 149 (1965) 1233. 2. K. I. Gringauz, Adv. Space Res. 1 (1981) 5. 3. K. I. Gringauz, Planet Space Sci. 39 (1991) 73.

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4. C. T. Russell, Geophys. Res. Lett. 5 (1978a) 81. 5. M. H. Acuna et al., Science 279 (1998) 1676. 6. D. Mohlmann, W. Riedler, J. Rustenbuch et al., Planet Space Sci. 39 (1991) 83. 7. W. Riedler, K. Schwingenschuh, H. Lichtenegger et al., Planet Space Sci. 39 (1991) 75. 8. C. T. Russell, Geophys. Res. Lett. 5 (1978b) 81. 9. M. H. Acuna, J Connerney and P. Wasilewsky et al., J. Geophys. Res. 106(E10) (2001) 23,403–23,418. 10. K.-H. Glassmeier, G. Musmann, C. Vocks et al., Planet Space Sci. 48(12–14) (2000) 1153–1159. 11. J. E. P. Connerney et al., Geophys. Res. Lett. 28(21) (2001) 4015–4018. 12. Soobiah et al., Icarus 182(2) (2006) 396–405. 13. M. Fr¨ anz et al., Icarus 182(2) (2006) 406–412. 14. H. Rosenbauer et al., Nature 341 (1989) 612. 15. R. Lundin et al., Geophys. Res. Lett. 17 (1990) 873. 16. M. I. Verigin et al., Planet Space Sci. 39 (1991) 131. 17. R. Lundin et al., Nature 341 (1989) 609. 18. E. Karllio et al., Planet Space Sci. 56 1204–1213 (2008). 19. E. Carlsson et al., Icarus 182(2) (2006) 4320–328. 20. Futaana et al., Icarus 182(2) (2006) 413–423. 21. H. Lammer and S. J. Bauer, J. Geophys. Res. 97 (1992) 20925. 22. S. A. Haider, Adv. Space Res. 16(6) (1995) 49–55. 23. SHI Jian-kui et al., Chinese Astron. and Astrophys. 23 (1999) 377–383. 24. SHI Jiankui et al., Chinese Science Bulletin 42(22) (1997) 1898–1901 25. A. Eviater, A. M. Lencheek and S. F. Singer, Phys. Fluids 7 (1964) 1775–1779. 26. K. Schwingenschuh, T. L. Zhang, K. Torkar et al., Adv. Space Res. 29 (2002) 49–55. 27. J. G. Luhmann and L. H. Brace, Rev. Geophys. 29 (1991) 121.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

WIND VELOCITIES OF DIFFERENT SEASONS AND DUST OPACITIES ON MARS: COMPARISON BETWEEN MICROWAVE OBSERVATIONS AND SIMULATIONS BY GENERAL CIRCULATION MODELS TAKESHI KURODA∗ and PAUL HARTOGH Max Planck Institute for Solar System Research Max-Planck-Str. 2, Katlenburg-Lindau, D-37191, Germany ∗ [email protected]

Comparisons between the microwave observations of wind velocities in Martian middle atmosphere and the results simulated by two Martian general circulation models (MGCMs) have been done. One MGCM has a non-LTE CO2 radiation scheme, which well reproduces daily changes of zonal wind. Meanwhile, another MGCM with a LTE CO2 radiation scheme well reproduces the retrograde wind velocities especially at a higher opacity. Neither of the MGCMs can reproduce the retrograde wind velocity in lower dust case. Brief discussions for the discrepancies between the model and observation are provided.

1. Introduction Microwave observations of the Martian atmosphere are able to detect wind velocities directly from Doppler shifts detected on the rotational transitions of CO. Such measurements have been made from ground-based microwave telescopes such as the Institut de Radio-Astronomie Millimetrique (IRAM) 30 m,1,2 IRAM Plateau de Bure Interferometer (PdBI)3 and the James Clerk Maxwell Telescope (JCMT)4 , detecting the mesospheric (40–70 km height) wind velocities with the horizontal resolution of ∼300 km at highest from the 12 CO and 13 CO lines. According to the IRTM PbBI measurements, the observed typical retrograde (easterly) wind velocities near 50 km altitude in the oppositions between 1999 and 2005 were 70– 170 m s−1 , and clear latitudinal and longitudinal variances are seen.3 Comparisons between the measurements and the numerical results by Martian general circulation models (MGCMs) have also been made. LMD MGCM5 with the MY24 dust scenario (dust opacity of 0.1–0.5) tends to 261

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underestimate the retrograde wind velocities observed by IRTM PdBI and JCMT,3,4 as well as the longitudinal variances (observed velocity diﬀerences between morning- and evening-limbs) are also not well reproduced.3 Meanwhile, the MGCM with the dust opacity corresponding to the global dust storm in 2001 (∼4) shows longitudinal variances more comparable to the measurements,3 and the ‘warm’ simulation (with dust opacity of 0.7– 1.0 and maximux solar ﬂux) mostly reproduces, and even overestimates, the wind velocities detected from the IRAM 30 m measurements in 2001 and 2005.2 In this paper we present the comparisons of wind velocities among the IRTM PdBI measurements and the numerical results by two other MGCMs, the MAOAM-GCM6 and the CCSR/NIES/FRCGC MGCM.7 Note that the comparison between the JCMT wind measurements and the MAOAM-GCM simulations was already published.8 It is shown there that the retrograde wind velocity is comparable in morning-limb while the GCM underestimates in ∼100 m s−1 in evening-limb. The MGCMs used in this study are brieﬂy described in Sec. 2. The results of the simulations in comparison with the observations are presented in Sec. 3. Some discussions for the results are given in Sec. 4.

2. Description of the MGCMs A detailed description of the MAOAM-GCM is given in Ref. [6] with some updates,9 so we describe only a short summary of its characteristics here. It is a grid-point model from the surface to approximately 140 km, and has log-pressure coordinates in vertical. The resolution of the model is 64 grid points in longitude, 36 grid points in latitude, and 118 vertical layers with a step of about 1.2 km. The radiative CO2 scheme accounts for the non-LTE (breakdown of the Local Thermodynamic Equilibrium) above the altitude of 40 km, where the numerical results are used for the comparison with the observations in this paper. Note that the MAOAMGCM is the only MGCM at present which can well reproduce the winter polar warming at 50–60 km height as observed by Mars Climate Sounder.10 The other MGCM is the CCSR/NIES/FRCGC MGCM whose dynamical core is based on the terrestrial model developed in the Center for Climate System Research/National Institute of Environmental Studies/ Frontier Research Center for Global Change, Japan. It employs a spectral solver with T21 horizontal resolution (64 grid points in longitude and 32

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grid points in latitude), and the vertical resolution is 30 σ-levels with the top at about 80 km. A LTE radiative scheme of CO2 is adopted for all altitudes. More detailed description of the model is given in Ref. [7] with some updates.11 Both models include a dust radiative scheme. The dust opacity in the model calculations have been adapted to the dust opacity in the Martian atmosphere during the observations. CCSR/NIES/FRCGC MGCM has been extensively validated concerning the impacts of dust radiation on the atmospheric dynamics on Mars including the baroclinic planetary waves,12 semiannual oscillations in tropics,13 and the winter polar warmings during the solstitial global dust storm.14

3. Results To compare with the observed Doppler wind distributions shown in Ref. [3], we retrieved the respective Doppler wind plots from the MGCM results. Observations in Ref. [3] were targeted at the CO(1-0) rotational line at 115.271 GHz. The wind weighting function in the CO(1-0) line at limb has the peak altitude of ∼50 km (see Fig. 3 in Ref. [3]), so we used the simulated wind velocities at ∼50 km height for the comparisons. We calculated the zonal and meridional wind velocities for each local time, averaged in 3–4 sols of each longitude from the 2-hourly model output, as seen in Figs. 1a, 1b, 2a and 2b. Then we calculated the Doppler wind velocities in the manner as if they are viewed from Earth using the sub-Earth local time of the corresponding observations, as seen in Figs. 1c and 2c. Note that the sub-Earth latitudes of the respective Doppler wind plots are ﬁxed on the equator. Figures 1 and 2 show the simulated zonal and meridional wind velocities as functions of local time at ∼50 km, and the respective Doppler wind plot at the solar longitude Ls = 262◦ with dust opacity of 0.3 by the MAOAM-GCM and the CCSR/NIES/FRCGC MGCM, respectively, in order to compare with Fig. 4 in Ref. [3] (observed in September 2003). The MAOAM-GCM reproduces the day-to-night circulation in southern polar region as seen in observed Doppler winds, though the retrograde wind velocity in the tropics is much weaker. Meanwhile, CCSR/NIES/FRCGC MGCM reproduces the comparable retrograde wind velocity in tropics and prograde (westward) wind velocity in northern hemisphere, though the dayto-night circulation in the southern polar region is not reproduced. As seen in Fig. 1a the MAOAM-GCM produces a large change of zonal wind velocity

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Fig. 1. Latitude-local time cross-sections of zonally averaged (a) zonal and (b) meridional wind velocities at ∼50 km height and (c) respective Doppler wind plot (positive values denote the recessing wind velocites) calculated from (a) and (b) at Ls = 262◦ with dust opacity of 0.3 simulated by the MAOAM-GCM. Thick rectangles on (a) and (b) represent the part used for the calculation of (c) which was faced to the Earth at the corresponding observation in September 2003.3 N, S, E and W in (c) denote the North Pole, South Pole, morning limb (sky East, Martian West) and evening limb (sky West, Martian East), respectively.

as functions of local time in the southern hemisphere in summer, though it is not appeared in the CCSR/NIES/FRCGC MGCM (Fig. 2a). Figure 3 shows the respective Doppler wind plots at Ls = 143◦ with dust opacity of 0.1 by both MGCMs, for the comparison with Fig. 8a in Ref. [3] (observed in May 1999). In the observation, the retrograde

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Same as Fig. 1, except for simulated by the CCSR/NIES/FRCGC MGCM.

wind is seen from northern midlatitude to southern midlatitude. But in the MAOAM-GCM the numerical result is opposite to the observation: prograde wind is seen from the southern high latitude to northern midlatitude. In the CCSR/NIES/FRCGC MGCM very weak retrograde wind is seen above in tropics, and strong prograde wind is seen in southern hemisphere. Figure 4 shows the respective Doppler wind plots for the cases of higher dust opacity by the CCSR/NIES/FRCGC MGCM. The simulation at Ls = 317◦ with dust opacity of 0.5 for the comparison with Fig. 10a in Ref. [3] (observed in December 2003) is shown in Fig. 4a. The retrograde wind velocities in the southern hemisphere are comparable between observation

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Fig. 3. Respective Doppler wind plots at Ls = 143◦ with dust opacity of 0.1 simulated by (a) the MAOAM-GCM and (b) the CCSR/NIES/FRCGC MGCM. The values of contours and directions are the same as Figs. 1c and 2c.

Fig. 4. Respective Doppler wind plots simulated by the CCSR/NIES/FRCGC MGCM: (a) at Ls = 317◦ with dust opacity of 0.5 and (b) at Ls = 196◦ with dust opacity of 4.

and simulation. In the observations the retrograde wind is dominant also in the northern hemisphere, while in the simulations the prograde wind is dominant. The simulation at Ls = 196◦ with a dust opacity of 4 for the comparison with Fig. 12a in Ref. [3] (observed in July 2001) is shown in Fig. 4b. The wind features, prograde wind in the northern hemisphere, approaching wind in both morning and evening limbs and southward wind around the noon, are qualitatively consistent between the observations

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Fig. 5. Zonal wind velocities, where positive values denote the retrograde (easterly) winds, at the height of ∼50 km simulated by the CCSR/NIES/FRCGC MGCM. Solid, dashed and dashed-and-dotted lines denote the tropics (averaged in 20◦ S–20◦ N), northern midlatitudes (averaged in 20◦ N–50◦ N) and southern midlatitudes (averaged in 20◦ S–50◦ S), respectively. Thick and thin lines denote the morning (6 am) and evening (6 pm), respectively.

and simulations. This ﬁgure shows that the change of zonal wind velocity depending on local time is simulated with such high dust opacity. Figure 5 shows the annual changes of the zonal wind velocities simulated by the CCSR/NIES/FRCGC MGCM for morning (6 am) and evening (6 pm) in the tropics and midlatitudes of both hemispheres, for the comparison with Fig. 14 in Ref. [3]. The seasonal change of the dust opacity is along with the “TES2 dust scenario” (described in Ref. [7] in full details), a period with a “minor” dust storm during the southern spring with the increased up to ∼1 dust opacity and ∼0.2 in other seasons. The diﬀerences in simulated zonal wind velocities between morning and evening are less than ∼20 m s−1 in all seasons and latitudes. In most seasons the retrograde wind velocities are lower than the observations, especially in northern summer in the tropics and the southern hemisphere. But in southern spring with higher dust opacity the simulated retrograde wind velocities increase up to ∼ 150 m s−1 in the tropics and the southern hemisphere, which are comparable to the observations. 4. Discussions This paper showed the wind velocities at ∼50 km simulated by two MGCMs for comparison with ground-based microwave observations. There

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were large diﬀerences in the simulated results between MAOAM-GCM and CCSR/NIES/FRCGC MGCM. A possible reason is the diﬀerence of the CO2 radiative codes, though we cannot fully attribute to it. The MAOAM-GCM with a non-LTE CO2 radiative code well reproduced the daily change of zonal wind velocity as observed, while the CCSR/ NIES/FRCGC MGCM with a LTE code could not reproduce it. The non-LTE eﬀect weakens the radiative cooling, which results in the excitation of thermal tides. Figure 6 shows the zonally and daily averaged temperatures, and ∼50 km height temperatures as functions of local time, at Ls = 262◦ simulated by both MGCMs. The MAOAM-GCM simulates the zonal-mean ∼50 km temperature above the equator and North

Fig. 6. (upper panels) Zonally and daily averaged temperature at Ls = 262◦ with dust opacity of 0.3 simulated by (a) the MAOAM-GCM and (b) the CCSR/NIES/FRCGC MGCM. (lower panels) (c) and (d) are the same as (a) and (b), respectively, except for the latitude-local time cross-sections of temperature at ∼50 km height.

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Pole 10–20 K higher than the CCSR/NIES/FRCGC MGCM. Moreover, the temperature amplitude of semidiurnal tide above the equator is ∼10 K for the MAOAM-GCM, while less than 5 K for the CCSR/ NIES/FRCGC MGCM. The larger amplitude of semidiurnal tide provides the larger diﬀerences of wind velocities between morning and evening. Note that the LMD MGCM (with a LTE CO2 radiative code at this height) also did not reproduce such a daily change with low dust opacity.3 Simulations with diﬀerent dust opacities were done with the CCSR/NIES/FRCGC MGCM. It well reproduced the observed absolute values of the retrograde wind velocity, while the LMD MGCM mostly underestimated them,3 for higher (>0.3) dust opacities. As seen in Fig. 5 the retrograde wind velocity was rather sensitive to the dust opacity, and even the daily change of the velocity was reproduced in the global dust storm simulation (see Fig. 4b). Note that the LMD MGCM also reproduced the daily change of velocity in the global dust storm simulation (see Fig. 12b in Ref. [3]). The retrograde wind velocities in northern summer (with low dust opacity) are not well reproduced in MGCMs. The radiative eﬀects of water ice aﬀect the temperature ﬁelds above the equator in this season,15 therefore, an implementation of them might improve the wind velocity. Moreover, the eﬀects of the ion drag can be suspected to accelerate the retrograde wind, as we described in Ref. [8]. In addition to the improvements of the MGCMs, getting more data of wind velocities with higher time and spatial resolutions is indispensable to understand the dynamics of Martian middle atmosphere. Measurements by a sub-millimeter sounder onboard a Mars orbiter could possibly do it. Acknowledgments This work was partially supported by German Research Foundation (DFG), grant HA 3261/3, and the Research Fellowships of the Japan Society for the Promotion of Science (JSPS) for Young Scientists, Grant-in-Aid 20·1761. References 1. E. Lellouch, J. Rosenqvist, J. J. Goldstein, S. W. Bougher and G. Paubert, Astrophys. J. 383 (1991) 401. 2. T. Cavalie, F. Billebaud, T. Encrenaz, J. Brillet, F. Forget and E. Lellouch, Astron. Astrophys. 489 (2008) 795.

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3. R. Moreno, E. Lellouch, F. Forget, T. Encrenaz, S. Guilloteau and E. Millour, Icarus 201 (2009) 549. 4. R. T. Clancy, B. J. Sandor, G. H. Moriarty-Schieven and M. D. Smith, Second Workshop on Mars Atmosphere Modeling and Observations (2006) 134. 5. F. Forget, F. Hourdin, R. Fournier, C. Hourdine, O. Talagrand, M. Collins, S. R. Lewis, P. L. Read and J.-P. Huot, J. Geophys. Res. 104 (1999) 24155. 6. P. Hartogh, A. S. Medvedev, T. Kuroda, R. Saito, G. Villanueva, A. G. Feofilov, A. A. Kutepov and U. Berger, J. Geophys. Res. 110 (2005), doi:10.1029/2005JE002498. 7. T. Kuroda, N. Hashimoto, D. Sakai and M. Takahashi, J. Meteor. Soc. Japan 83 (2005) 1. 8. T. Kuroda and P. Hartogh, Advances in Geosciences Vol. 7: Planetary Science (PS) 13 (2007). 9. A. S. Medvedev and P. Hartogh, Icarus 186 (2007) 97. 10. D. J. McCleese et al., Nature Geoscience 1 (2008) 745. 11. T. Kuroda, PhD Thesis, University of Tokyo (2006). 12. T. Kuroda, A. S. Medvedev, P. Hartogh and M. Takahashi, Geophys. Res. Lett. 34 (2007), doi:10.1029/2006GL028816. 13. T. Kuroda, A. S. Medvedev, P. Hartogh and M. Takahashi, Geophys. Res. Lett. 35 (2008), doi:10.1029/2008GL036061. 14. T. Kuroda, A. S. Medvedev, P. Hartogh and M. Takahashi, J. Meteor. Soc. Japan 87 (2009) 913. 15. R. J. Wilson, S. R. Lewis, L. Montabone and M. D. Smith, Geophys. Res. Lett. 35 (2008), doi:10.1029/2007GL032405.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

RETRIEVAL SIMULATIONS OF THE VERTICAL PROFILES OF WATER VAPOUR AND OTHER CHEMICAL SPECIES IN THE MARTIAN ATMOSPHERE USING PACS G. PORTYANKINA∗ and N. THOMAS Physikalisches Institut, University of Bern, CH-3012, Bern, Switzerland ∗ [email protected] ∗ [email protected] www.space.unibe.ch P. HARTOGH† and H. SAGAWA‡ Max-Planck-Institut f¨ ur Sonnensystemforschung, Max-Planck-Straße, 2, D-37191 Katlenburg-Lindau, Germany † [email protected] ‡ [email protected] www.mps.mpg.de Water vapour, despite being a minor constituent in the Martian atmosphere with its precipitable amount of less than 70 pr. µm, attracts considerable attention in the scientiﬁc community because of its potential importance for past life on Mars. The partial pressure of water vapour is highly variable because of its seasonal condensation onto the polar caps and exchange with a subsurface reservoir. It is also known to drive photochemical processes: photolysis of water produces H, OH, HO2 and some other odd hydrogen compounds, which in turn destroy ozone. Consequently, the abundance of water vapour is anti-correlated with ozone abundance. The Herschel Space Observatory provides for the ﬁrst time the possibility to retrieve vertical water proﬁles in the Martian atmosphere. Herschel will contribute to this topic with its guaranteed-time key project called “Water and related chemistry in the solar system”. Observations of Mars by Heterodyne Instrument for the Far Infrared (HIFI) and Photodetector Array Camera and Spectrometer (PACS) onboard Herschel are planned in the frame of the programme. HIFI with its high spectral resolution enables accurate observations of vertically resolved H2 O and temperature proﬁles in the Martian atmosphere. Unlike HIFI, PACS is not capable of resolving the line-shape of molecular lines. However, our present study of PACS observations for the Martian atmosphere shows that the vertical sensitivity of the PACS observations can be improved by using multiple-line observations with diﬀerent line opacities. We have investigated the possibility of retrieving vertical proﬁles of temperature and molecular abundances of minor species including H2 O in 271

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1. Introduction: Martian Atmosphere and PACS The Herschel Space Observatory was launched on May 14, 2009. It is an ESA mission, intended to make high spatial resolution observations in the far infrared and sub-millimeter regime. The Photodetector Array Camera and Spectrometer (PACS) is one of the three science instruments of the Herschel Space Observatory. PACS provides capabilities for spectroscopy and imaging photometry in the /55–210/ µm range. In the middle of September 2009, PACS started the execution of its scientiﬁc observational programme. The guaranteed-time key project “Water and related chemistry in the Solar System”1 dedicates a substantial amount of observation time to Martian atmosphere studies with PACS. Section 2 provides a summary of these proposed PACS observations. Observations of the Martian atmosphere in the thermal infrared and sub-millimeter allow one to study the atmosphere’s vertical structure. Every layer of the atmosphere radiates and absorbs and the details of the emission spectrum depend on the molecules present in these layers in very distinctive ways. Near-nadir thermal emission can be used to measure temperature and constituent concentrations, as both of these quantities contribute to the thermal emission. We present the method used in the current work to retrieve atmospheric properties, such as vertical proﬁles of temperature and H2 O mixing ratio from PACS spectra, in the Sec. 3. The chemical composition of the Martian atmosphere can be determined spectroscopically by ground-based observations, observations from Earth orbit or by mission to Mars (either through remote sensing from orbit or by in situ analysis). While CO2 , O2 , CO, H2 O, H2 O2 , H2 , and O3 were discovered from ground-based or Earth orbiting observations, we owe our knowledge about the presence of the following species in the Martian atmosphere to space instruments: • N2 , Ar, Ne, Kr, and Xe — Viking’s mass spectrometer,2 • H and O — Mariner 6 and 7 ultraviolet spectrometers,3 • H2 S — Mariner 6 ad 7 infrared interferometer spectrometers.4 Photochemical models do predict the presence of several additional compounds, such as OH, HO2 , NO, etc.5, 6 For an overview of the Martian

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atmosphere composition and the chemical reactions that take place inside it see, for example, Krasnopolsky (2006)6 and Sonnemann et al. (2009)7 Herschel might contribute and extend the list of species that have been detected in the Martian atmosphere. We examined the possible detections of such minor species as O3 , O2 , H2 O2 , HCl, NO, SO2 , HF, and O with PACS. The results are reported in Sec. 4.1. According to the newest results from various instruments, such as High Resolution Imaging Science Experiment (HiRISE) on board the Mars Reconnaissance Orbiter mission, High Resolution Stereo Camera (HRSC) on board Mars Express and the Phoenix lander, the present day Mars has considerable quantities of water stored under the surface at mid-latitudes.8–10 Exchange of H2 O between this rather large reservoir, the polar caps and the atmosphere, i.e. its variations in atmospheric content of water vapour, has been the focus of numerous studies and debates for a long time.11, 12 Understanding this process is also critical for studies of the past Martian climate and the geological history of the Martian surface. The vertical distribution of water vapour in the atmosphere is a key aspect in these studies. Column-integrated amounts of water vapour were estimated by several authors using data from space missions such as Viking,2 MGS,13 Mars Express.14 Their temporal and spatial variations were also described. However, the observational data for vertical proﬁles of water vapour are very limited because the aforementioned instruments were limited in their capabilities. Our present knowledge of the H2 O vertical proﬁle comes from diverse models of the Martian atmosphere. The only observational sources are ground-based observations of the H2 O 22 GHz and HDO 226 GHz lines15, 16 and measurements of the vertical distributions of H2 O by solar infrared occultation observations by SPICAM experiment on Mars-Express.17 These observations show that the altitude of the minimum in the water vapour mixing ratio (so-called hygropause) varies between 10 km (aphelion) and 50 km (perihelion). However the sensitivity of ground-based observations is much smaller than similar observations that could be executed with Herschel. Potentially Herschel has the capability to conﬁrm or disprove this asymmetry of the mixing ratio. If it exists, this seasonal asymmetry strongly inﬂuences the water cycle. Due to its potential importance, a better observational characterization of this phenomenon is needed. It will be a strong constraint for models describing the general circulation of the Martian atmosphere.18, 19 In Sec. 4.3 we discuss retrievals of water vapour vertical proﬁles using PACS observations.

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The water vapour vertical proﬁle is sensitive to the temperature proﬁle, and theoretically it is possible to use CO lines in the atmospheric spectra to retrieve temperature information. In Sec. 4.2 we investigate the possibility to extract temperature proﬁles from PACS spectra. 2. Proposed PACS Observations for the Martian Atmosphere Herschel can only observe targets with Sun aspect angle between 60–120 degree. This constitutes a limitation in the Mars visibility window. Under the programme “Water and related chemistry in the solar system” a ﬁrst set of Herschel scientiﬁc observations of Mars have been planned at the beginning and the end of the ﬁrst two observational windows: (1) August-December 2009, solar longitude Ls = 323◦ –22◦ (2) March-July 2010, solar longitude Ls = 67◦ –116◦. PACS will be observing Mars for a total of 1.09 hours. The main advantage of PACS observations lies in the possibility of covering many spectral lines together with a precise measurement of the line depths. Hence, the range scan spectroscopy mode of PACS was chosen: it provides high signal to noise ratio (SNR) and covers the full PACS spectral range. Three high sampling density observations and one Nyquist sampling observation are proposed. These observational modes are described in detail in the PACS observer’s manual.1 We intend to study the seasonal variability of the Martian atmosphere, hence temporal coverage of the observations over the largest possible range of Ls is necessary. Mars’ apparent diameter for the proposed observational windows varies from 5 to 10 arcsec. As this is below the spatial resolution of Herschel, Mars will be treated as a point source. The other consequence of this fact is that observational times need to vary by a factor of 16 to achieve the requested SNR. After reduction and calibration the observational data will result in brightness temperature spectra for further scientiﬁc analysis. In this paper we calculated the expected PACS spectra for several chemical compounds using MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval) in order to evaluate if they are detectable. We also used calculated synthetic spectra for solving the inversion task 1 http://herschel.esac.esa.int/Docs/PACS/pdf/pacs

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of ﬁnding the vertical temperature proﬁle and water vapour distribution with the help of the inversion module of the same package, MOLIERE-5. 3. Description of the Techniques Used MOLIERE-5 is the general forward- and inversion model for planetary atmospheres for the millimeter- and sub-millimeter wavelength range. Being a modular application, the MOLIERE-5 forward model consists of modules describing spectroscopy, radiative transfer, and instrumental characteristics. Besides the “forward model”, MOLIERE-5 also provides a “retrieval model” for the retrieval of proﬁle information from radiometric measurements at millimeter and sub-millimeter wavelengths. The theoretical basis of the inverse method for atmospheric sounding is well described for example, by Rodgers et al. (1976).20 The physical and mathematical bases of MOLIERE are described in Urban et al. (2004).21 In our model, the atmosphere spans from 0–120.0 km with a vertical resolution of 1.5 km. Temperature and pressure proﬁles are based on Viking data. For the abundances of the chemical species, we refer to results of the general circulation model (GCM) calculations of Forget et al. (1999)18 and Sonnemann et al. (2009).7 We denote the speciﬁc intensity of radiation that reached the sensor at position sr at a frequency ν as Iν (sr ) and that is entering the atmosphere at the position se (at the direction of line-of-sight) as Iν (se ). MOLIERE numerically integrates the following expression for each atmospheric layer along the line-of-sight of the considered instrument (in our case PACS): sr αν (s)Bν (T )e−τ (s,sr ) ds. (1) Iν (sr ) = Iν (se )e−τ (se ,sr ) + se

The line-of-sight geometry for simulated PACS observations is calculated according to the Hershcel — Mars geometry during the PACS planned observational schedule. The ﬁrst term of the right hand side of Eq. 1 is the background radiation attenuated by the atmosphere. The second term is the absorption and emission within the atmosphere. αν (s) is a total absorption coeﬃcient that describes the spectroscopic properties of the media. This depends on temperature, pressure and abundance of chemical elements in the atmosphere and is given by the sum over the absorption coeﬃcients corresponding to the individual transitions plus a continuum term. Bν is the atmospheric source function, given in MOLIERE by the

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radiation of a black body, and τ (s1, s2) is the opacity or optical thickness between points s1 and s2. Spectroscopic data for molecular compounds that we assume are present in Martian atmosphere were taken from the HITRAN 2008 molecular spectroscopic database.22 The modelled intensity of radiation Iν (sr ) that reaches the sensor is then convolved with the antenna response and channel sensitivity of PACS to produce synthetic spectra. Instrument modeling was performed according to the PACS observer manual. We assume operating PACS in the full range scan mode by setting the synthetic spectrum’s frequency channels to a separation of half of the spectral resolution to investigate PACS’ lowest sampling density observations. Section 4.1 shows the result of forward calculations for several molecular compounds. For the results presented in Secs. 4.2 and 4.3 we used the inversion module of MOLIERE. First, we performed a forward calculation for CO and H2 O. The output of this forward model was then overlaid with random observational errors and used as input for the inversion module to retrieve temperature and H2 O vertical proﬁles. MOLIERE uses the linear least-squares method based on the Optimal Estimation Method (OEM, see e.g. Rodgers 197620 ) to combine statistical a priori knowledge of the variability of the searched parameters with the information provided by the measurement (in our case — synthetic PACS spectra). We calculate the forward model and the OEM inversion model iteratively using the Newton scheme combined with the Levenberg-Marquardt scheme, which allows us to solve non-linear inversions. The averaging kernel matrix is calculated in the same module and thus MOLIERE provides us with a means of error analysis. The averaging kernel matrix is a set of averaging functions for each atmospheric layer. Averaging functions show the sensitivity of the retrieved state to the true state for a particular layer, in other words we can assess the quality of a retrieval from the amplitudes of the averaging functions, and also estimate the eﬀective vertical resolution on the retrieved information from their broadening widths. 4. Results 4.1. Possibility of detection of minor species in the Martian atmosphere with PACS To check PACS’ capability in detecting minor species in the Martian atmosphere we selected several molecular compounds. H2 O2 , HCl and HF spectra are shown in Fig. 1. The left panel shows that in the range of

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PACS these compounds have distinctive spectral lines. However, the lines are narrow in part because of the small abundances of these species in the Martian atmosphere. After the spectrum is convolved with the PACS instrument model, these lines disappear (right panel of Fig. 1). The reason lies in the low spectral resolution of PACS. It does not allow one to resolve the core and wings of separate lines. Figure 2 illustrates this. The pressure broadened line width of HCl (5 → 4) transitions at 3.1 THz is expected to

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be less than 10 MHz, while PACS spectral resolution at 3.1 THz is ∼1 GHz. Therefore, despite the fact that the spectral lines in Fig. 2 are pronounced and deep enough to be detected with PACS’ S/N ratio, they are not likely detectable after smoothed by PACS’ spectral resolution. 4.2. Vertical temperature profile retrievals For temperature retrieval we can use CO spectral lines that lie inside PACS’ spectral range, in detail the rotational transitions of high J numbers (from 13 → 12 to 21 → 20). CO is believed to be well mixed vertically because of its large photochemical lifetimes (longer than 2 years), therefore the opacities of CO are often used for the temperature sounding of the Martian atmosphere. For this we have to construct a synthetic PACS spectrum of CO, that is shown in Fig. 3. Results of the inversion calculation using this synthetic spectrum are shown in Fig. 4. The true temperature proﬁle (black line on Fig. 4) is the proﬁle that was used as input to the forward module of MOLIERE to calculate the synthetic spectrum. The averaging functions for this case (right panel of Fig. 4) stay rather low. The closer these functions to 1 indicates the better sensitivity of the retrieval to the true state. One can see that averaging function from only one level (10 km) is closer to 1 than others, which means that only this layer eﬃciently contributes to the retrieval. This makes us conclude that the retrieval of complete temperature

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measurement spectrum (simulated PACS data) synthetic spectrum calculated with a priori state synthetic spectrum calculated with the retrieved state

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proﬁles from the low spectral resolution PACS data in the Nyquist scan mode is not satisfactory. 4.3. Water vapour vertical distribution retrievals The synthetic spectrum of H2 O in PACS’ range is shown in Fig. 5. Water vapour has many more lines in this spectral range than other species considered here (CO, HF and HCl) because of its more complex

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molecular rotational structure. Additionally, the spectral line intensities of a single water vapour molecule are generally stronger than those of other species. This allows a rather conﬁdent retrieval of the water vapour vertical distribution even under PACS’ spectral resolution. The result of H2 O retrieval and corresponding averaging functions are shown in Fig. 6. The expected vertical sensitivity of the water vapour retrieval using PACS data extends from the Martian surface up to approximately 30 km altitude. HIFI H2 O observations have the potential to sound the water vapour proﬁle

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up to 60–80 km.1 PACS’ sensitive altitude range cannot compete with the expected result of the HIFI measurements. However, we can point out one signiﬁcance of the PACS observations: the quality of the retrieval using PACS data relies on the SNR of the amplitude of the H2 O lines but not on the line shape. For HIFI data analysis, since the vertical information is retrieved from the line shape, even small deviations from the true line shape (due to any instrumental eﬀects) can lead to large errors in the determination of the vertical proﬁles. We consider the PACS data analysis to be less sensitive to such an issue. It should be noted here, that the retrieval of the water vapour vertical distribution uses temperature proﬁles of the atmosphere as a known input parameter. In the present work, temperature proﬁle was ﬁxed as identical to the one used in synthesyzing the measurement spectrum, i.e. we assumed the situation that the temperature proﬁle was determined independent of the PACS H2 O measurements. As we showed above, the temperature can not be satisfactorily retrieved from PACS data, so we have to use additional data. Temperature proﬁles from general circulation models are possible and practical candidates for this complementary information. Also the importance of coordinated observations with other instruments or facilities in order to get simultaneous data coverage should be noted.

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5. Conclusions We have calculated synthetic spectra of various minor species of the Martian atmosphere: HF, HCl, H2 O2 have been presented here, but also O, O2 , O3 , NO, SO2 have been considered. We have shown that the spectral lines of minor species in the atmosphere are too weak to be detected by PACS in its limited spectral resolution. Additionally, we solved the inverse problem of retrieving a vertical temperature proﬁle from CO spectral lines. PACS’ spectral range and/or

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spectral resolution of the proposed observation mode is not suﬃcient for a temperature proﬁle retrieval. This means that for water vapour retrievals we need external data input. The most straight forward idea is to use results of a general circulation model for the Martian atmosphere.19 However, some other instruments might provide the required data. For example a collaboration with Mars Climate Sounder — the instrument onboard Mars Reconnaissance Orbiter23 — is under discussion. For the October 2009 measurements, however, it appears that the safe mode of MRO will prevent simultaneous observations. We have shown that water vapour retrievals from PACS data are reliable especially in lower altitude levels (i.e. from surface up to 30 km) where at the present time, available data are scarce. This study shows that PACS will be useful in delivering important data sets of water vapour distribution in the Martian atmosphere.

Acknowledgments This work was supported by the Swiss National Science Foundation.

References 1. 2. 3. 4. 5. 6. 7. 8. 9.

10. 11. 12.

13. 14. 15. 16.

P. Hartogh et al., Planetary and Space Science 57 (2009) 1596. B. C. Clark et al., Science 193 (1976) 804. C. W. Hord, Icarus 16 (1972) 253. D. Horn et al., Icarus 16 (1972) 543. H. Nair et al., Icarus 111 (1994) 124. V. A. Krasnopolsky, Icarus 185 (2006) 153. G. R. Sonnemann et al., Advances in Geophysics (2009). S. Byrne et al., Science 325 (2009) 1674. W. J. Markiewicz et al., Sublimation of Exposed Snow Queen Surface Water Ice as Observed by the Phoenix Mars Lander, in Lunar and Planetary Institute Science Conference Abstracts, Lunar and Planetary Inst. Technical Report Vol. 40 (March 2009). J. B. Murray et al., Nature 434 (2005) 352. F. Forget et al., Science 311 (2006) 368. T. Fouchet et al., Martian water vapour: Mars Express PFS/LW observations and comparison with LMD/GCM simulations, in 37th COSPAR Scientific Assembly, COSPAR, Plenary Meeting Vol. 37 (2008). M. D. Smith, Journal of Geophysical Research (Planets) 107 (2002) 5115. A. Fedorova et al., Journal of Geophysical Research (Planets) 111 (2006) 9. T. Encrenaz et al., Annales Geophysicae 9 (1991) 797. R. T. Clancy et al., Icarus 122 (1996) 36.

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17. A. A. Fedorova et al., Icarus 200 (2009) 96. 18. F. Forget et al., Journal of Geophysical Research (Planets) 104 (1999) 24155. 19. P. Hartogh et al., Journal of Geophysical Research (Planets) 110 (2005) 11008. 20. C. D. Rodgers, Reviews of geophysics and space physics 14 (1976) 609. 21. J. Urban et al., Journal of quantitative spectroscopy and radiative transfer 83 (2004) 529. 22. L. Rothman et al., Journal of Quantitative Spectroscopy and Radiative Transfer 110 (2009) 533, HITRAN. 23. D. J. McCleese et al., Journal of Geophysical Research (Planets) 112 (2007) 5.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

NEAR-INFRARED LIGHTCURVES OF A VERY YOUNG ASTEROID, KARIN TAKASHI ITO∗ and FUMI YOSHIDA National Astronomical Observatory, Osawa, Mitaka, Tokyo 181–8588, Japan ∗ [email protected], [email protected]

(832) Karin, an S-type main belt asteroid, is the largest member of a very young asteroid family: the Karin family. This asteroid is likely a large fragment of a disruption event in the main asteroid belt about 5.8 million years ago. We carried out a near-infrared photometric observation of this asteroid in 2006 February near its opposition, and obtained its multicolor lightcurves over nearly the entire rotation phase. This asteroid has been reported to have surface color variation that may indicate the existence of both mature and fresh surfaces, perhaps caused by the disruption event that created the family. However, through our observation in near-infrared wavelength, this asteroid shows almost no surface color variation along its rotation phase. This result, together with the results of previous observations of this asteroid, might give us some insight into its spin axis orientation and hopefully its shape.

1. Introduction The Karin family, a small asteroid cluster in the large Koronis family, was recognized quite recently with the estimated age of only about 5.8 million years.1 This family consists of about 70 asteroids with sizes ranging from about 1.5 km to 20 km in diameter.2, 3 Most asteroid families are in general very old,4 and they have undergone signiﬁcant collisional and dynamical evolution since their formation, which likely masks the properties of the original collisions. However, the remarkably young Karin family asteroids possibly preserve some signatures of the original collisional event that formed the family. This extraordinary feature of the Karin family provides us with several signiﬁcant opportunities for the research of young asteroids such as detecting tumbling motion, obtaining distribution of rotation periods, and estimating the shapes of newly-created asteroid fragments. The Karin family is also quite interesting in its relation to the general diﬀerence of the reﬂectance spectrum of S-type asteroids from 285

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that of ordinary chondrites. Although S-type asteroids (like the Karin family members) are very common in the inner main belt, their reddened reﬂectance spectra are diﬀerent from those of ordinary chondrites, the most common meteorites. Though there is little observational conﬁrmation on the relation between asteroid age and the degree of surface alteration, space weathering have been thought responsible for the spectral mismatch.5 In particular, since (832) Karin is the largest fragment of a recent asteroid disruption, it is possible that this asteroid has both young and old surfaces together: a young surface that was exposed from the interior of the parent body by the family-forming disruption, and an old surface that used to be the parent body surface exposed to space radiation over a long time. Therefore, if the mixture of these two surfaces is detected by multicolor observation of this asteroid, it could have signiﬁcant implication for research on the evolution of asteroid surface spectra.6, 7 Driven by these motivations, we have begun a program since November 2002 to observe the lightcurves of all the Karin family members. The potential result derived from our observation could be a strong constraint on laboratory and numerical experiments of collisional fragmentation and space weathering. In this paper we report the result of our near-infrared multicolor observation of the largest member of this asteroid family, (832) Karin. Our largest purpose to publish this manuscript is to present nearinfrared lightcurves of this asteroid that were obtained near its opposition in the spring of 2006, which have not been on previous literature yet. Not only for conﬁrming whether or not this asteroid has in homogeneous color pattern on its surface, but the lightcurves of this asteroid we obtained will serve as an important constituent in future when we construct a detailed shape model of this asteroid that includes information about its spin axis direction, together with the lightcurves that we have already obtained in visible wavelengths from other observation opportunities in the past.8, 9 In Sec. 2 we describe the observing instrument and our observation method. Section 3 is devoted for describing the observation result. Section 4 goes to some discussions and interpretation of the results.

2. Observation Method We carried out simultaneous imaging observations of (832) Karin in the near-infrared bands J (1.25 µm), H (1.63 µm), and Ks (2.14 µm) from February 17 (UT) to 21 (UT), 2006, when the asteroid was close to its

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Table 1. Major parameters during our near-infrared multicolor observations of (832) Karin. From the left, UT date referring to the mid-time of each night, distances (AU) between the asteroid and the Sun (r) and the Earth (∆), observer-centered ecliptic longitude (λ) and latitude (β), and the solar phase angle (α) of this asteroid. The unit of angles is degree. Date (UT)

r

∆

λ

β

α

20060217.02 20060218.03 20060219.00 20060220.01 20060221.02

3.0666 3.0670 3.0673 3.0677 3.0681

2.1450 2.1391 2.1337 2.1283 2.1232

173.660 173.487 173.318 173.138 172.953

−1.433 −1.437 −1.441 −1.445 −1.448

7.979 7.629 7.289 6.931 6.569

opposition (the exact opposition was on March 10, 2006). See Table 1 for detail of the observation parameters. We used a near-infrared camera called SIRIUS equipped with the 1.4-m Infrared Survey Facility (IRSF) telescope at Sutherland, South Africa. The camera is equipped with three 1024 × 1024 pixel HgCdTe (HAWAII) arrays.10 Two dichroic mirrors enable simultaneous observations in the three bands.11 The image scale of the array is 0 .45/pixel, giving a ﬁeld of view of 7 .7 × 7 .7. We measured more than 300 independent data points of the asteroid for each of the J, H, and Ks bands with the exposure time of 15 seconds. Typical seeing was 1 .4 (FWHM) in the Ks band during our observation period. Two standard stars in the faint infrared standard star catalog12 were also observed (Persson 9,143 and 9,149) several times at each night for photometric calibration. We used the NOAO IRAF software package to reduce the data. We applied the standard procedures for near-infrared array image reduction, including dark current subtraction, sky subtraction, and ﬂatﬁelding.13 Lightcurves from the photometric data were constructed following one of the standard procedures.14 Principally this method is an iterative repetitions of frequency analysis and ﬁtting to Fourier series. We use Lomb’s spectral analysis method15 and the WindowCLEAN analysis16 for frequency analysis of the lightcurves, and ﬁt the data with a fourth-order Fourier series.17 Since we carry out relative photometry of an asteroid and nearby stars in the same frame, we have to be particularly careful when we combine the lightcurves of several observing runs. We combine the lightcurves of multiple observing runs based on the zero-level of each of the frames to obtain ﬁnal result.

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magnitude

14.2

J

14.4 14.6 14.8 15.0 13.8

H

magnitude

14.0 14.2 14.4 14.6 13.8

Ks

magnitude

14.0 14.2 14.4 14.6

0

0.2

0.4

0.6

0.8

1

rotation phase Fig. 1. J, H, Ks lightcurves of (832) Karin. The rotational period is 18.15 ± 0.05 hours. Solid lines are the best ﬁt curves for each of the data sets: fourth-order Fourier series.

3. Observation Results In Fig. 1 we showed the phased lightcurves of (832) Karin at J, H, and Ks bands after calibrating with the photometric standard stars, together with their best ﬁt sinusoids. In total there are 301 data points on each of the panels in Fig. 1. Through the period analysis, we determined the rotation period of this asteroid as 18.15 ± 0.05 hours for J, H, and Ks .

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This value is very close to what has been reported as the rotation period of this asteroid, 18.35 ± 0.02 hours through the lightcurve observation in the visible wavelengths..8, 9 The diﬀerence between these two period values is only about twelve minutes, and we do not think this is signiﬁcant, judging from the rather scattered lightcurve data shown in Fig. 1. The maximum peak-to-peak variation magnitudes of the lightcurves deduced from the best ﬁt curves shown in Fig. 1 are ∼0.57 for J, ∼0.56 for H, and ∼0.51 for Ks . The J band amplitude, ∼0.57, is greater than the lightcurve amplitude of this asteroid obtained by previous optical observations in R band.8, 9 This is not surprising because at this observation period in 2006 February we looked at the asteroid from a diﬀerent direction than at previous observation opportunities. Also, since our observation was performed in the near-infrared wavelengths, the lightcurve amplitude can be somewhat diﬀerent from that in the visible wavelength. As seen in Fig. 1, the lightcurve data that we obtained covers almost all of the rotational phase of this asteroid. Readers will notice that data points are sparser, as well as scattered, between the rotation phase 0.4 to 0.8 compared with other phase range. This is mainly because one of the observing nights, 2006 February 19 (UT), suﬀered from a relatively poor sky condition: barely photometric. We plotted the color diﬀerences of this asteroid such as J–H, J–Ks , and H–Ks as shown in Fig. 2. We calculated the errors of these values from the photometry errors of each of the J, H, and Ks images: For example, the √ error of J–H is δJ 2 + δH 2 where δH and δJ are the photometry errors of the H and J images (i.e. basically the square root of the counts that are calculated by IRAF packages). Looking at the three panels in Fig. 2, none of J–H, J–Ks , or H– Ks values shows signiﬁcant change throughout the asteroid’s rotation. Although there seems a small color change at phase ∼0.4 (such as relatively large J–Ks and H–Ks values), so far we cannot be quite sure if this feature is really signiﬁcant or not because this part of data is followed by the data points that are rather scattered (rotation phase 0.4–0.8). We need more observation data for this rotation phase in order to conﬁrm whether or not the apparent color variation really exits. To inspect the potential surface color variation of this asteroid in more detail, we calculated the wavelength dependence of the relative reﬂectance of this asteroid (Fig. 3). The relative reﬂectance in Fig. 3 is normalized at the wavelength of J band, 1.25 µm. Note that here we subtracted the solar values18 of J–H = 0.23, J–Ks = −0.29, and H–Ks = 0.06 from the

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290 0

J-H

0.1

magnitude

0.2 0.3 0.4 0.5 0.6 0.7 0

J - Ks

magnitude

0.1 0.2 0.3 0.4 0.5 0.6 0.7 -0.3

H - Ks

magnitude

-0.2 -0.1 0 0.1 0.2 0.3 0

0.2

0.4

0.6

0.8

1

rotation phase Fig. 2. Relative magnitude of J–H, J–Ks , and H–Ks calculated from the lightcurve data shown in Fig. 1.

asteroid’s data. Actually it is not so straightforward for us to tell whether the surface color of this asteroid is really “red” or not only from the data in this wavelength range from 1.25 µm to 2.14 µm: For S-type asteroids like (832) Karin in general, spectral diﬀerence between weathered (and hence red) surface and fresh (not red) surface typically appears in shorter wavelength range, such as ∼1 µm, which is not included in our current

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291

(a) phase: 0 - 0.125

(b) phase: 0.125 - 0.25

(c) phase: 0.25 - 0.375

(d) phase: 0.375 - 0.5

(e) phase: 0.5 - 0.625

(f) phase: 0.625 - 0.75

(g) phase: 0.75 - 0.875

(h) phase: 0.875 - 1.0

(i) entire phase average

1.1

relative reflectance

1.0 1.2

1.1

1.0 1.2

1.1

1.0 1.4

1.6

1.8

2.0

1.4

1.6

1.8

2.0

1.4

1.6

1.8

2.0

wavelength [µm] Fig. 3. Wavelength dependence of relative reﬂectance in J, H, and Ks band normalized at the J band wavelength, 1.25 µm, divided in each of the rotation phase ranges (the panels (a) to (h)). The panel (i) shows the average values of the relative reﬂectance of this asteroid over the entire rotation phase.

observation data. Nevertheless, it is clear that there seems no signiﬁcant diﬀerence in the relative reﬂectance of this asteroid at any part of the rotation phase, as is easily seen in Fig. 3.

4. Discussion Ever since (832) Karin was identiﬁed in 2002 as the largest member of an extremely young asteroid family, many observing attempts have been carried out to detect potential color variation on its surface. Several years ago two observation results were reported that claimed that this asteroid had a heterogeneous surface, some part being typically “red” i.e. very old and mature. This red surface was observed near the opposition in 2003 September through a near-infrared spectroscopy19 as well as through a multicolor photometry in visible wavelengths.8 At that opposition, heliocentric true longitude of Karin was ∼338◦ with respect to the ecliptic and mean equinox of ICRF/J2000.0 reference frame. Note that at that

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opposition Karin was relatively close to its perihelion (its argument of perihelion ω during this opposition was ∼325◦ ), so Karin was relatively brighter due to its smaller distance from the Earth. Recently, results of spectral observation in visible and near-infrared wavelengths were reported, claiming that there is no anomalous color change on the surface of this asteroid.20, 21 Both of these observations were carried out around the opposition in 2006 March, at nearly the same time as our observation that we have reported in this manuscript. At this opposition, heliocentric true longitude of Karin was ∼165◦ , and Karin was rather close its aphelion (argument of perihelion ω ∼ 153◦) and relatively dark. As we have described in this manuscript, we could not detect any signiﬁcant surface color diﬀerence on Karin’s surface at this opposition. In this term our result is consistent with what was presented in Refs. [20, 21]. We should also note that our own multicolor observation in visible wavelengths in 2004 September, a year after the opposition in 2003 September, did not detect the red surface on the asteroid.9 The key to solving this problem — whether this asteroid has a signiﬁcant surface color variation or not — lies in determining the spin axis direction and the shape of this asteroid. If Karin’s obliquity (i.e. the angle between its equator and its orbital plane) is so large that its spin axis is close to its orbital plane, it might account for the fact that this asteroid occasionally shows surface part with a diﬀerent color as it rotates, such as at the opposition in 2003 September (for example, see Fig. 3 in Ref. [9]). Having the lightcurves that we obtained this time, together with the lightcurves that we have obtained in previous observation opportunities, it is principally possible for us to determine the spin axis direction of this asteroid, as well as to construct its synthetic shape model.22 This kind of model, when established, will enable us to conﬁrm whether or not Karin really possesses a red, mature surface that was once reported but received with some skepticism. One thing that we might have to keep in mind when we discuss and compare surface colors and spectra of a certain object by various authors and literature is the eﬀect of backscattering that can cause opposition surge and variation of slope parameters. It is already known that apparent spectrum of the solar system objects can be quite diﬀerent when their solar phase angle is very large.23 Although we are not yet sure how serious this eﬀect could be when the solar phase angle is very small (such as when the object is around the opposition), inﬂuence of the backscattering eﬀect

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on color and spectrum of the solar system small bodies, as well as its dependence on wavelengths, must be explored in much more detail in future observations. (832) Karin will come to its opposition to the Earth about every 15 months. While we can obtain information of this asteroid around any oppositions, the opposition in 2013 September will be one of the best opportunities for us to get signiﬁcant information of the surface property of this asteroid, since at this opposition we will be able to observe this asteroid from nearly the same direction as we did in 2003 September when the property of red surface was once observed. Observation of this asteroid at this opportunity will deﬁnitely add something else to our current knowledge of this intriguing asteroid.

Acknowledgments The authors thank Motohide Tamura and Tomohiko Sekiguchi for our observing use at IRSF 1.4-m telescope with SIRIUS. We owe a lot to many people who helped us observe and analyze our asteroid data at IRSF, particularly to Jun Hashimoto, Akika Ishihara, Yasushi Nakajima, Ryo Kandori, and Tetsuya Nagata. Reviews by Takanori Sasaki and Shinsuke Abe suggested directions which bettered the quality of this paper a great deal. This study is supported by the Grant-in-Aid of the Ministry of Education of Japan (18540426 and 18540427, 2006–2008).

References 1. D. Nesvorn´ y, W. F. Bottke, L. Dones and H. F. Levison, Nature 417 (2002) 720. 2. P. Michel, W. Benz and D. C. Richardson, Nature 421 (2003) 608. 3. D. Nesvorn´ y and W. F. Bottke, Icarus 170 (2004) 324. 4. F. Marzari, P. Farinella and D. R. Davis, Icarus 142 (1999) 63. 5. S. Sasaki, K. Nakamura, Y. Hamabe, E. Kurahashi and T. Hiroi, Nature 410 (2001) 555. 6. C. R. Chapman, Meteoritics 32 (1996) 699. 7. B. E. Clark, B. Hapke, C. Pieters and D. Britt, in Asteroids III, Eds. W. F. Bottke, A. Cellino, P. Paolicchi and R. P. Binzel (Tucson: The University of Arizona Press, 2002), p. 585. 8. F. Yoshida, B. Dermawan, T. Ito, Y. Sawabe, M. Haji, R. Saito, M. Hirai, T. Nakamura, Y. Sato, T. Yanagisawa and R. Malhotra, Publ. Astron. Soc. Japan 56 (2004) 1105.

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9. T. Ito and F. Yoshida, Publ. Astron. Soc. Japan 59 (2007) 269. 10. N. Kusakabe, M. Tamura, Y. Nakajima, R. Kandori, A. Ishihara, T. Nagata, T. Nagayama, S. Nishiyama, D. Baba, S. Sato, K. Sugitani, E. L. Turner, L. Abe, H. Kimura and T. Yamamoto, Astrophys. J. 632 (2005) L139. 11. T. Nagayama, C. Nagashima, Y. Nakajima, T. Nagata, S. Sato, H. Nakaya, T. Yamamuro, K. Sugitani and M. Tamura, Proc. SPIE 4841 (2003) 459. 12. S. E. Persson, D. C. Murphy, W. Krzeminski, M. Roth and M. J. Rieke, Astron. J. 116 (1998) 2475. 13. Y. Nakajima, D. Kato, T. Nagata, M. Tamura, S. Sato, K. Sugitani, C. Nagashima, T. Nagayama, I. Iwata, Y. Ita, T. Tanabe, M. Kurita, H. Nakaya and D. Baba, Astron. J. 129 (2005) 776. 14. A. W. Harris and D. F. Lupishko, in Asteroids II, Eds. R. P. Binzel, T. Gehrels and M. S. Matthews (The University of Arizona Press, Tucson, 1989), p. 39. 15. N. R. Lomb, Astrophys. Space Sci. 39 (1976) 447. 16. D. H. Roberts, J. Lehar and J. W. Dreher, Astron. J. 93 (1987) 968. 17. B. Dermawan, T. Nakamura, H. Fukushima, H. Sato, F. Yoshida and Y. Sato, Publ. Astron. Soc. Japan 54 (2002) 635. 18. A. Delsanti, N. Peixinho, H. Boehnhardt, A. Barucci, F. Merlin, A. Doressoundiram and J. K. Davies, Astron. J. 131 (2006) 1851. 19. T. Sasaki, S. Sasaki, J. Watanabe, T. Sekiguchi, F. Yoshida, H. Kawakita, T. Fuse, N. Takato, B. Dermawan and T. Ito, Astrophys. J. 615 (2004) L161. 20. B. Chapman, C. R. Enke, W. J. Merline, P. Tamblyn, D. Nesvorn´ y, E. F. Young and C. Olkin, Icarus 191 (2007) 323. 21. P. Vernazza, A. Rossi, M. Birlan, M. Fulchignoni, A. Nedelcu and E. Dotto, Icarus 191 (2007) 330. 22. P. Magnussion, in Asteroids II, Eds. R. P. Binzel, T. Gehrels and M. S. Matthews (The University of Arizona Press, Tucson, 1989), p. 1180. 23. D. Domingue and F. Vilas, Meteor. Planet. Sci. 42 (2007) 1801.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

DEVELOPMENT OF A LIGHT-WEIGHT AND LARGE-AREA PARALLEL-PLATE IMPACT IONIZATION DETECTOR FOR IN SITU MEASUREMENT OF DUST/DEBRIS TAKAYUKI HIRAI Course of Marine Environmental Studies, Tokyo University of Marine Science and Technology 4-5-7, Konan, Minato-ku, Tokyo 108-8477, Japan [email protected] HIDEO OHASHI Department of Ocean Sciences, Tokyo University of Marine Science and Technology 4-5-7, Konan, Minato-ku, Tokyo 108-8477, Japan [email protected] SHO SASAKI RISE Project Oﬃce, National Astronomical Observatory of Japan 2-12, Hoshigaoka-chou, Mizusawa-ku, Oshu-shi, Iwate 023-0861, Japan [email protected] HIROMI SHIBATA Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University Yoshida-Honmachi, Sakyo-ku, Kyoto-shi, Kyoto 606-8501, Japan [email protected] KEN-ICHI NOGAMI Center of Medical Informatics, Dokkyo Medical University 880, Kita-Kobayashi, Mibu-Machi, Tochigi 321-0293, Japan [email protected] TAKEO IWAI Nuclear Professional School, School of Engineering, The University of Tokyo, 2-22, Shirakata-Shirane, Tokai-mura, Naka-gun, Ibaraki 319-1188, Japan [email protected]

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RALF SRAMA Max Planck Institute for Nuclear Physics Saupfercheckweg 1, Heidelberg 69117, Germany [email protected]

We have developed a light-weight and large-area impact-ionization dust/debris detector, which we call IID. This detector consists of a gold plated metal target and two grids. Ratio of mass/volume of this parallel-plate type of detectors is simply proportional to the target area. Therefore, we can fulﬁll the requirements, i.e. “eﬀective dust measurement with large aperture” and “light weighted to minimize the cost and payload” in future dust measurement in space. We can obtain information on mass and velocity of impacted particles by measuring the total charge and risetime of impact-generated plasma signals.

1. Introduction In the solar system, there exist a variety of dust particles with various velocity and mass distribution. For example, interplanetary dust particles from asteroids or comets should have relatively smaller velocity than interstellar dust particles from the extrasolar space. To clarify the inventory of natural dust particles in the space, in situ discrimination and distribution of those particles are important. Moreover, there exist small debris particles of artiﬁcial origin around the Earth. Since impacts of high speed debris particles are hazardous for spacecraft, investigation of debris particles is important for the space utilization, i.e. for the evaluation of the possible risk on the human activities in space. There are two types of detector for in situ measurement of dust/debris; 1) a counter to measure the physical parameters such as mass, velocity and incident direction of incident particles, as onboard GALILEO, NOZOMI, and 2) an analyzer to measure chemical composition of the dust, as onboard HELIOS, STARDUST, CASSINI, etc. In both cases high velocity dust particles are impacted on the metal target plate to form plasma cloud (impact ionization), then positive/negative ions from the cloud are collected and measured. Impact ionization type of detector prevails for in situ dust/debris measurement. For future dust measurement in space, some restrictions such as “eﬀective dust measurement with large aperture”, “light weight to minimize the cost and payload” are required. To fulﬁll these requirements, simpliﬁcation of the structure is necessary. Optimization of target shape, distance between target and grid, and applied voltage are crucial for the

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development. But some past detectors, such as MDC onboard NOZOMI, were box shaped with low symmetry to cause the undesirable impact position dependence of signals. CDA onboard CASSINI is another example of past detectors. Its hemispherical shape target cannot be enlarged while keeping the whole device small and light. Our objective of study is to determine the optimum shape and applied voltage condition based on the experiment for the impact ionization detector (IID). This paper reports the recent results of the 3rd and 4th IIDs, which are latest two of four detectors that we have developed.

2. Principle of Impact Ionization Detector Principle of impact ionization detector is shown in Fig. 1. This detector consists of a gold plated metal target, inner grid (grid1), outer grid (grid2), and sidewalls. Two grids are placed to measure velocity and charge of an incident particle and to study the plasma cloud behavior after impact. The two grids are grounded for easy handling, while the target is biased with high voltage (1 kV maximum). When a dust particle impacts target plate at the speed of more than few km/s, the impact generates plasma cloud. Near the impact site this plasma becomes very dense (>1012 ions/cm3 , 5TPa).1 By the electric ﬁeld negative ions and electrons are collected on the target, while positive ions head for grids. These target and grids signals are stored and analyzed.

Fig. 1.

The principle of impact ionization detector.

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Fig. 2.

The target signal.

Dust velocity v and mass m cannot be derived directly from the signal because the behavior of the produced plasma cloud is extremely complicated. In general, these values are obtained from calibration experiments. From the target signal indicated in Fig. 2, we can calculate risetime t and generated total charge Q. Since t and Q/m are functions of v, the following equations were empirically derived from the calibration experiments: t = cg v α ,

(1)

Q/m = cr v β

(2)

where cg , cr , α, and β are ﬁtting parameters.2−4 From the measured risetime t, we can obtain impacting dust particle velocity v from the v − t calibration curve. Then this vvalue is applied to the v−Q/m curve to obtain impacting dust particle mass m, while generated charge Q is already known. 3. Experiments Van de Graaﬀ accelerators at HIT (High Fluence Irradiation Facility, the University of Tokyo, Tokai-mura, Japan) and MPI-K (Max Planck Institute for Nuclear Physics, Heidelberg, Germany) are used for calibration experiments. Micron sized conductive particles are accelerated to a few to tens of km/s and are impacted onto metallic target. Projectiles are carbon and silver at HIT, and iron and latex at MPI-K. The particle velocity v is derived from the measurement of the ﬂight time of particles. The particle

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mass m can be obtained from the equation: mv 2 = qU 2

(3)

where m, v, and q are the mass, the velocity, and the charge of the accelerated particle, respectively, and U is the accelerating potential of the Van de Graaﬀ accelerator. We have developed IIDs shown in Fig. 3. The 1st IID have an aperture of 5 cm in diameter, single entrance grid, and Teﬂon sidewall. The 2nd IID have an aperture of 15 cm in diameter and two grids. Teﬂon sidewall is removed because some error signals result from Teﬂon sidewall were observed in the experiment of the 1st IID.5 The 3rd IID has an aperture of 30 cm in diameter with a total mass of 2 kg. And the 4th IID has an aperture of 20 cm square with total mass of 2 kg. Square type aperture was adapted to maximize the target area. The typical signals of the 4th IID are shown in Fig. 4. The horizontal axis is time and the vertical axis is signal voltage. Induced charges by the incoming dust particle are observed as signals on the grid prior to the impact time at the target. The applied target voltage, the incident position, the incident angle, and the projectile were changed in the calibration experiment to check the dependence on them. The experiment to study the impact angle dependence was performed with the 1st IID, but impact angle dependence was not observed.3 The distances between electrodes of the 3rd and 4th IID

Fig. 3.

The photographs of IIDs.

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Fig. 4. The typical impact signal of the 4th IID. Induced charges by the incoming dust particle are observed as signals on the grid prior to the impact time at the target. After the impact, negative ions and electrons are collected on the target, while positive ions head for grids.

are 20 mm (target-grid1) and 130 mm (grid1-grid2), which were selected because we obtained the largest number of data at these distances in the 2nd IID experiments. Therefore this determination has no scientiﬁc basis. We were unable to perform the experiments with various distances between electrodes due to machine time restriction. To determine these distances based on scientiﬁc evidence is one of our future tasks. 4. Results and Discussion 4.1. The 3rd IID Figure 5 represents the risetime t as a function of particle velocity v for iron, silver and carbon particles, and Fig. 6 shows v − t relation for iron particle dependent on the impact position. The charge to mass ratio Q/m as a function of v for these particles is also shown in Fig. 7 and the impact position dependence is shown in Fig. 8. From these ﬁgures it is clear that empirical formula (1) and (2) ﬁt experimental data well in general. In Figs. 5 and 7, ﬁtting parameters are as follows: Cg = 2.2 × 102 , α = −1.5, Cr = 2.4 × 10−4, β = 3.6.

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The eﬀect of incident particle material on v − t relationship for the 3rd IID.

Fig. 6.

The position dependence on v − t relationship for the 3rd IID.

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Fig. 7.

The eﬀect of incident particle material on v − Q/m relationship for the 3rd IID.

Fig. 8.

The position dependence on v − Q/m relationship for the 3rd IID.

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There exist little dependence on the incident particle materials (Fig. 5). It is indicated that the velocities of carbon and silver particles are limited in a narrow range compared to that of iron particles, for example the velocity of silver particle is less than 4 km/s. Which is because the range of particle mass at the experiments in HIT is narrower than that of iron particle mass in MPI-K — according to Eq. (3), the particle velocity is dependent on the particle mass. At high velocity (>10 km/s) the risetime is independent of impact velocity (<1 µs), which is observed at the past experiment to investigate impact on aluminum sidewall of detector.6 It might be suggested that considerable number of incident particles impact on the grid rather than hitting directly on the target. The dependence on impact position in v − t relation was not observed (Fig. 6). In v − Q/m there is little dependence of incident particle materials (Fig. 7), while the dependence on impact position was not observed (Fig. 8). 4.2. The 4th IID Figure 9 represents the risetime t as a function of particle velocity v for iron, silver, carbon and latex particles, and Fig. 10 shows v − t relation for iron particle dependent on the impact position. The charge to mass ratio Q/m as a function of v for these particles is also shown in Fig. 11 and the

Fig. 9.

The eﬀect of incident particle material on v − t relationship for the 4th IID.

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Fig. 10.

Fig. 11.

The position dependence on v − t relationship for the 4th IID.

The eﬀect of particle materials on v − Q/m relationship for the 4th IID.

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The position dependence on v − Q/m relationship for the 4th IID.

impact position dependence is shown in Fig. 12. In Figs. 9 and 11, ﬁtting parameters of equation (1) and (2) are as follows: Cg = 4.5 × 102, α = −2.1, Cr = 5.2 × 10−5, β = 4.0. Compared to the 3rd IID the data plots widely spread in Fig. 9. We assume that this results from the square shape of detector4 and/or the eﬀect of noise in the experiment. The same tendency as the result of 3rd IID exists at particles velocity of above 10 km/s. The dependence of impact position might be observed (Fig. 10). This dependence was not observed in the past experiments of cylindrical models of IID we developed. The behavior of plasma after impact diﬀers with the conﬁguration of electric ﬁeld applied to the detector. We will adopt computer simulation to understand these plasma behaviors. In v − Q/m relation the correlation shows little dependence of incident particle (Fig. 11) and there is little impact position dependence (Fig. 12).

5. Summary The performance of a new design (3rd and 4th model) of parallel-plate impact ionization detector was investigated with high speed particles. There

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is a good correlation between target signal risetime t, charge to mass ratio Q/m and impacting particle velocity v. From risetime t, dust impact velocity v can be estimated independent of incident particle materials and from v−Q/m relation, dust mass can be obtained. In the v−t relation there exists a little dependence on impact position in the square model 4th IID, while in the cylindrical model 3rd IID the dependence on impact position was not observed. We have demonstrated that parallel-plate conﬁguration has good features, such as light weight and high symmetry signal, as dust/debris impact ionization detector. Acknowledgments This research was supported by “Ground-based Research Program for Space Utilization” promoted by Japan Space Forum. We wish to thank dust group members of MPI-K for assistance in the experiments at MPI-K and valuable discussions. We also thank Takao Omata for operation of the Van de Graaﬀ accelerator at HIT. References 1. K. Yamakoshi, Extraterrestrial Dust: Laboratory Studies of Interplanetary Dust (Astrophysics and Space Science Library), Kluwer Academic Pub, 1995. 2. R. Srama, E. Gruen and the CASSINI-Dust-Science Team, Physics, Chemistry, and Dynamics of Interplanetary Dust, ASP Conference 104 (1996) 227–231. 3. E. Igenbergs et al., Mars Dust Counter, Earth Planets Space 50 (1998) 241–245. 4. E. Guen et al., Interplanetary Dust, Springer (2001), pp. 385–444. 5. S. Shoji, Development of an impact-ionization dust detector on board spacecrafts, Master’s thesis, Dept. Earth & Planet. Sci, The University of Tokyo (2003). 6. M. J. Willis, M. J. Burchell, M. J. Cole and J. A. M., Influence of impact ionisation detection methods on determination of dust particle flux in space, Planetary and Space Science 52(8) (2004) 711–725.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

APPLICATION OF PENETRATORS WITHIN THE SOLAR SYSTEM∗

ALAN SMITH† , ROBERT A. GOWEN, KERRIN REES and CRAIG THEOBALD Mullard Space Science Laboratory, University College London, Holmbury St Mary, RH5 6NT, UK † [email protected] PATRICK BROWN, WILLIAM T. PIKE, TOBY HOPF and SUNIL KUMAR Imperial College, London, UK PHILIP CHURCH QinetiQ Ltd., Fort Halstead, Sevenoaks, UK YANG GAO Surrey Space Centre, University of Surrey, UK ADRIAN JONES Department of Earth Sciences, University College London, London, UK KATHERINE H. JOY and IAN A. CRAWFORD Birkbeck College, University of London, London, UK SIMON SHERIDAN, AXEL HAGERMANN, SIMEON J. BARBER and ANDREW J. BALL Planetary and Space Sciences Research Institute, Open University, Milton Keynes, UK NIGEL WELLS QinetiQ Ltd., Cody Technology Park, Farnborough, UK

High impact velocity, instrumented space probes — Penetrators, have the potential to become an important part of the portfolio of planetary exploration technologies. The UK Penetrator Consortium is building upon existing heritage ∗ This

work is supported by the UK Science and Technology Facilities Council. 307

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in this area. Presented here is an overview of potential applications, a consideration of technology issues and a description of the highly successful full-scale trials undertaken at Pendine in May 2008.

1. Introduction While technically challenging the ability to deploy low mass, instrumented probes into the subsurface of planetary bodies would signiﬁcantly enhance our portfolio of robotic technologies. The class of penetrator considered here have an impact velocity of up to 400 ms−1 and undergo impact forces ∼5–50 kgee. A typical penetrator mission scenario involves: • Insertion into planetary orbit of a primary spacecraft which carries a number of descent modules (DMs) each with a penetrator delivery system (PDS) and penetrator. • Staged release of DMs. • De-orbit of each DM through use of a PDS motor. • Spin-up and re-orientation of the PDS/penetrator ready for impact. • Separation of the penetrator and PDS prior to impact. • Following impact the penetrator undertakes a programme of scientiﬁc measurements ∼few m below the surface and transmits its results back to Earth using the primary spacecraft as a communications link. • The mission ends when the penetrator power sub-system is fully depleted. To date there has been no successful deployment of a penetrator into a planetary surface. However, a great deal of heritage and experience exists. The Russian Mars96 mission1 included two high mass, low velocity penetrators. Although the mission failed before leaving Earth orbit, the penetrators had been proven in ground tests. Deep Space-2 (DS-2)2,3 included two low mass, high velocity penetrators but failed sometime after launch, probably on impact. The cancelled Japanese Lunar-A4,5 programme had planned to deploy two penetrators. While in development the programme had succeeded in demonstrating a lunar penetrator in fullscale trials and had gone a long way to develop associated technologies and mission concepts. Penetrator mission studies include: Polar Night6 — a study of permanently shaded craters; and LunarEx7 a multi-penetrator mission to establish a global geophysical network on the Moon, and

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explore the permanently shaded craters. LunarEx has gone on to become the proposed UK-led MoonLITE8,9 mission and would comprise a polar orbiting communications relay satellite and four penetrators. Lunar Glob remains in the Russian programme although its status and conﬁguration are unclear. At one time this mission envisaged the inclusion of a number of high speed penetrators including the possible use of the Lunar A penetrators. Penetrators are a peaceful application of a technology that has been very highly developed in a defense context. Survival of instrumented ‘shells’ following impacts at very high velocities is commonplace to parts of the defense industry. Given knowledge of the target material and its conﬁguration, detailed impact modelling can predict for a particular penetrator design the likely levels of impact stress and the depth of penetration. Penetrators and penetrometers have been the subject of two dedicated workshops10,11 and numerous international conference presentations. The UK Penetrator Consortium1 has begun a penetrator technology programme and we present here the results of the ﬁrst full-scale trials in May 2008 at the QinetiQ-operated impact test facilities, Pendine, South Wales, U.K. 2. Applications Penetrators have been proposed for the Moon,4−9 as a potential geophysical network on Mars,1,2,3 for the moons of the outer planets12 and asteroids. They are particularly well suited to a wide range of multi-point scientiﬁc measurements. This multiplicity provides both economies of scale and a natural redundancy. Proposed payload instruments include: accelerometers; seismometers; chemical sensors; thermal sensors; mass spectrometers; magnetometers; neutron, x-ray ﬂuorescence, gamma-ray, and alpha-proton spectrometers; microscopes; radiation monitors; beeping transmitters (see e.g.7 ), permittivity sensors and microphones. The deployment of seismometers within penetrators has some signiﬁcant advantages since the instruments are well coupled and emplaced below the planetary surface, away from diurnal thermal variations and, in the case of Mars and Titan, wind. A global network of seismometers can inform our understanding of the planetary interior including the core. Local 1 See

http://www.mssl.ucl.ac.uk/missions/Micro Penetrators.php

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studies of mantle thickness; layering and subsurface oceans are possible from few or even a single station. A measurement of the level of seismic activity as a function of orbital position provides important information about the general dynamics of the planet and, in the case of the Moon, potential hazards for manned occupation. A compact micromachined silicon seismometer with an appropriate performance for planetary investigations has already been demonstrated.14 Deployment below the surface has other advantages: radiation levels are reduced (important for Europa and Ganymede), and sampled material is less aﬀected by surface processes (e.g. micrometeroid gardening). A study of subsurface chemistry including volatiles could have profound importance both to detection of astrobiological materials and environments, and detection of signiﬁcant water deposits important for future manned lunar missions. Penetrators have the potential to access locations that are diﬃcult to reach using soft landers (e.g. lunar far side, permanently shaded craters). Interestingly, the thermal demands within the lunar permanently shaded craters may be similar to the icy moons of Jupiter or Saturn. See7 for a fuller science case for Lunar penetrators. If appropriately designed and delivered a penetrator has the potential to determine planetary heat ﬂow, a fundamental parameter in geophysics, through the measurement of temperature gradient and thermal conductivity. Such determinations have only been performed at two locations on the Moon (Apollo 15 and 17) and remain subject to interpretation and speculation.13

3. Technology While Mars-961 and DS-22,3 adopted a two-part design, more recent designs are generally monolithic. In a two-part design separation at impact can be an issue, the electrical continuity of the connection between stages is problematic and impact forces in the rear/surface part are very high. A two-part design has the potential advantage that it has access to sunlight (and so power) and communications from the penetrator do not have to pass through the regolith. The monolithic design comprises a single shell – necessary to protect the payload during impact, and a payload — the scientiﬁc instruments together with enabling sub-systems that provide power, telecoms etc. It will be necessary for penetrators to maintain communication with an orbiting spacecraft from more than 3 m below the surface.

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3.1. Shell The Shell must survive the impact with minimal deformation and to stop without serious deviation in direction or ablation. Potential materials include: Aluminium alloy: suitable for Lunar and Martian regoliths. A well understood material, easy to work and handle but not the lowest mass alternative. Steel: High mass but strong enough to be deployed into icy surfaces (where a good analogy is concrete). Titanium alloy: Low mass and strong but possibly subject to fracturing. CFRP: The ultimate choice of Lunar A. Low mass but more diﬃcult to model due to its non-isotropic properties. Its low thermal conductivity is an advantage for heat ﬂow measurements. 3.2. Penetrator bays, subsystems and payload For MoonLITE9 a modular design has been adopted involving an outer shell and internal bays. The bays are electrically linked with connectors. At the expense of some additional mass, this approach allows individual bays to be built and tested independently, and very rapid payload integration. The enabling sub-systems include: Telecommunications: transmission to a communications relay satellite. Table 1.

Technology challenges for planetary penetrator missions.

Technology

Descent Modules Power Thermal control Sample acquisition Descent Module release Penetrator release Payload instruments

Challenge Moon and Mars <8◦ impact angle; <3 km impact ellipse Long duration; alternatives to Li batteries Internal insulation; possible RHUs Impact hardening; access to material Separation Separation Impact hardening

Outer planet moons Penetrator shell and contents Additional impact hardening to >50 kgee Electronics Radiation hardening >1 MRad before impact Penetrator elements including batteries Survival during long cruise phase

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Power: at present Li based batteries with power density ∼300– 400 Watt.hrs/kg. Maintaining the battery temperature may require the use of Radioactive Heater Units for some applications. Data management and instrument control: a single system. Sample acquisition: Where possible remote observations are performed, otherwise drills or other technologies are required to bring samples into the body of the payload for analysis. Penetrator body apertures compromise its strength.

4. Pendine Trials In May 2008 a series of full scale trials were performed at the QinetiQ operated Pendine test range in South Wales, UK. The trials consisted of three penetrator impacts into compressed, dry sand. Details of each impact are given in Table 2. In fact, although a normal impact (0◦ angle) had been planned, the angle achieved was the worst case expected for a Lunar penetrator (taken from for Lunar-A). For impact angles >0◦ the lateral forces are very much increased. A penetrator is shown prior to impact in Fig. 1a and after impact in Fig. 1c. The internal bay structure is seen in Fig. 1b. The rear ﬂare was included for both aerodynamic reasons and to give stability during the penetration through the sand. It was noted that some of the light plastic packing material followed the penetrator into the sand after its release from the sled and was found largely undamaged immediately behind the penetrator body. This indicates that the penetrator body protects the region to its rear. Figure 1d shows a bay containing potted drill elements (see later). The payload for each trial together with a simple assessment of the payload element survival is given in Table 3. Described below are more details of the impact modelling, a consideration of the eﬀects of the Table 2.

Pendine trials firing details.

Item

Impact velocity m.s−1

Impact angle degrees

Firing #1 Firing #2 Firing #3 Nominal

311 310 309 300

8.4 6.8 8.0 0.0

Penetration m

Peak shock kgee

3.9 3.9 3.8

16 16 16

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(a)

(b)

(c)

(d)

Fig. 1. (a) Penetrator on sled prior to firing; (b) Penetrator internal bays; (c) Penetrator post firing; (d) Potted bay containing drill elements. Table 3.

Survival table for penetrator trials at pendine.

Item

Firing 1

Firing 2

Firing 3

Penetrator Shell Accelerometer Radiation Sensor Batteries

OK OK OK reduced capacity OK OK n/a

OK OK n/a n/a

OK OK n/a n/a

n/a

n/a n/a protected sensors OK OK (see text)

n/a n/a protected sensors OK OK (see text)

Open University

OK

OK

OK

MSSL

OK OK

OK OK

OK OK

MSSL MSSL

Drill components Magnetometer Micro seismometer components Mass spectrometer components Accelerometer, data logger and batteries Electrical harness Internal bay structure

Group responsible QinetiQ QinetiQ QinetiQ QinetiQ

Ltd Ltd Ltd Ltd

SSC IC IC

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impact on the target material, sample acquisition and magnetometer. Other elements have been described elsewhere.12,14 4.1. Impact modelling Impact simulations were performed using the DYNA3D hydrocode and advanced material models for the Al alloy.16,17 The initial set-up for the angled impact is shown in Fig. 2a and the penetrator path after 6.5 ms is shown in Fig. 2b. This shows that the penetrator survives the impact but clearly moves oﬀ line due to the asymmetric ﬂow ﬁeld. The penetration process illustrates that the interface pressure ahead of the penetrator in the sand is relatively low and peaks at about 250 MPa. This is below the yield strength of the aluminium alloy penetrator shell which explains why it exhibits little plastic deformation. A plot of the penetrator shows that the damage is conﬁned to the nose region due to erosion leading to striations and also the ﬂare at the rear, as shown in Fig. 2c. This is due to the socalled ‘tail slap’ where the tail impacts the side of the hole and occurs approximately 2ms after impact. The front compartment was tapered to accommodate a stress concentration revealed from the simulation. The simulation compared very well with the results of the test at Pendine (see Fig. 1c) and the penetration depth into the sand was about 3.7 m from the front face of the target, although the penetrator moved oﬀ the shotline due to the >0◦ impact angle.

(a)

(b)

(c)

(d)

Fig. 2. Left to right. (a) initial set-up of penetrator impacting target normally with an 8◦ attack angle; (b) penetrator path after 6.5 ms; (c) simulated penetrator after impact showing damage at nose and tail; (d) stress system in penetrator.

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Another consequence of the oblique nature of the impact is that the transient material loads exceeded the transient longitudinal loading and this was due almost entirely to the tail slap phenomenon, and the stress system is heavily triaxial as shown in Fig. 2d. This necessitates a structured series of small-scale impact trials, combined with simulations, to de-risk instruments and sub-systems before being subjected to full-scale trials. 4.2. Target materials Pendine Target Material: Firings were conducted under terrestrial atmosphere conditions into ∼100 tons of sand. The target sand was assessed for its engineering behaviour on site and sealed samples were retrieved for characterisation of their chemical, physical and mineralogical eﬀects in the laboratory. The unmodiﬁed target material is a relatively well-mixed coarse-sand with a range of grain sizes and shapes (Fig. 3a,c), composed mostly of rounded to subangular quartz with several percent of fragments of friable coal (anthracite), and both rounded and angular particles of crystalline rocks (metamorphic gneisses, concrete and sedimentary shales) and seashells. The median grain-size distribution, measured by sieving a 13 g sample, is 106–250 micron, but there is a signiﬁcant skewed distribution with ∼12% of particles >2 mm in diameter and a paucity (<1%) of ﬁnegrained particles <100 microns. Moisture contents of the sand are in the range 3.2–4 wt.% H2 O. Impact modification of target: Post-ﬁring, a few mm thick dark deposit was noted mantling the Penetrator body (see Fig. 3e). This modiﬁed target sand was darkened by comminuted coal particles binding with and coating other sand components (Figs. 3b,d). The boundary layer also contained microscopic man-made detritus in the form of distinctive plastic organic–carbon bearing particles derived from entrainment of the penetrator pre-launch support blocks, and native aluminium metallic and organic paint particles from abrasion of the penetrator exterior. The highenergy entrainment of these foreign particles within the boundary layer will require >5cm penetrator sampling to bridge an assumed comparable layer, to assure acquisition of pristine Lunar samples. Lunar considerations: Understanding the geotechnical properties of the lunar regolith is vital for constraining accurate theoretical impact models. Lunar regolith is a layer or mantling deposit, generated from continual meteoroid bombardment of bedrock lithological units. Compared with

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(e)

Fig. 3. (a) Optical microscope image of unmodified quartz sand; (b) Optical microscope image of region of modified sand after Penetrator impact showing black particulate coating; (c) Back scatter electron image of unmodified sand; (d) Back scatter electron image of modified sand showing particulate coating. Component labels: C = coal, Q = quartz, CC = calcium carbonate (shell). (e) dark contaminated-sand lining impression of penetrator (removed as in Fig. 1c).

target sand lunar regolith is (i) ﬁner grained with the median particle size 40–130 µm and an average of 70 µm22 ; (ii) not permeated by atmosphere; (iii) formed from a more limited range of rocks/minerals with little organic components18 ; (iv) more abrasive (angular grain shapes and glassy agglutinates); (v) much more compacted with depth19 (vi) completely dry, although some regions may contain minor trapped water ice20 ; and (vii) at hugely diﬀerent temperatures (∼250 K equatorial, to ∼40 K polar21 ).

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Conclusions for Lunar impact: While sand is a good 1st approximation to the lunar regolith material, with 1–3 m penetration expected (similar to Lunar-A23 ), future modeling should match the approach used to measure lunar regolith in-situ19 and address the observed increase in regolith compaction with depth.20 4.3. Sampling acquisition mechanism The design tested at Pendine is based on the screw-driven method and included a simulated micro-electrical motor and gearbox, drill string, and drill bit. The motor drives the drill which is propelled by a screw thread. The prototype used on the Pendine trial #1 ﬁring penetrator is made of aluminium alloy mounted to the base using double nuts and eight connectors (Fig. 4). There is no electrical connection during the impact trial. The micro-drill was packaged inside a Perspex acrylic cover and placed in the payload bay ﬁled with potting compound (Fig. 1d). The micro-drill itself survived the impact — i.e. all the integrated moving parts can function correctly. However, the nuts for the mounting were loosened and two of the eight mounting connectors which were machined using punch forming were distorted (see Fig. 4). 4.4. Magnetometer The magnetometer measures the local DC ﬁeld in the range 0–10 Hz and is comprised of a tri-axial arrangement of Anisotropic Magnetoresistive (AMR) sensors. Each sensor comprises four Permalloy elements deposited on Si substrate and conﬁgured as a Wheatstone bridge. The output bridge voltage varies in response to a change in resistance caused by an external magnetic ﬁeld. The sensor is operated in closed loop with conditioning electronics utilising pulsed current easy axis biasing to enhance the intrinsic sensitivity and minimise gain drift. The complete magnetometer is at a

Fig. 4. Left to right: SSC micro-drill before impact, post impact, installed in bay. OU mass spectrometer in un-potted bay.

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TRL4 breadboard model featuring a detectivity of 2nT. AMR sensors have been selected for this application because of their superior SNR performance at low frequencies compared to other magnetoresistive sensor families i.e. GMR, SDT24 etc. and because they can be packaged as conventional microchips and so are much smaller, lighter and more robust than ﬂuxgate sensors with similar SNR levels. For the impact trial only the sensors were included. Both plastic (Honeywell HMC1021) and high temperature ceramic (Honeywell HTMC1001D) packaged devices were ﬁtted to two orthogonal PCBs housed within a single penetrator bay with two MDM connectors on ﬂying leads. After assembly the entire compartment was ﬁlled with solid potting. The sensors were tested before and after ﬁring using magnetometer electronics and both types were found to have suﬀered no signiﬁcant change in performance. Micromachined seismometer suspensions were successfully protected from fracture by packing in a sublimant.15 Future trials will include the sensor control loop and data handling electronics (ideally powered during the ﬁring) with the sensor and electronics located in separate locations within the penetrator to minimise magnetic interference (the average lunar surface ﬁelds is in the range a few nT − 50 nT).25 The sensor control loop is similar to that of a ﬂuxgate magnetometer and can easily be implemented in radiation hardened mixed signal ASICs or FPGAs.26 4.5. Mass spectrometer The device tested at Pendine is a development of the “Ptolemy” mass spectrometer currently aboard the Rosetta mission to land on comet Churyumov-Gerasimenko in 2014.27 A Micro-Electro-Mechanical systems (MEMS) pressure sensor was also tested as a potential pre-analysis sample processing component. The mass spectrometer and pressure sensor were mounted to the base of the compartment with an M8 bolt. 1 mm diameter glass spheres were used in ﬁring #2 while in ﬁring #3 the bay was not potted. The mass spectrometers survived the in both impacts — i.e. the capacitance of the electrodes remained at the pre-impact values (20 pF) and there was no evidence of electrode deformation. There was no measurable change in the functionality of the ion source, the electron multiplier or the charge ampliﬁer. In both ﬁring the pressure sensor failed in its fully deﬂected state and in the un-potted compartment the mounting bolt sheared. The glass spheres showed no crushing damage.

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References 1. Y. A. Surkov and R. S. Kremnev, Planet. Sp. Sci. 46 (1998) 1689–1696. 2. S. Smrekar, D. Catling, R. Lorenz et al., J. Geophys. Res. 104(E11) (1999) 27013–27030. 3. S. Smrekar, R. D. Lorenz and M. Urquhart, in N. I. K¨ omle, G. Kargl, A. J. Ball and R. D. Lorenz, (eds) Penetrometry in the Solar System, Vienna, Austrian Academy of Sciences Press (2001), pp. 109–123. 4. H. Mizutani, A. Fujimura, M. Hayakawa et al., in N. I. K¨ omle, G. Kargl, A. J. Ball and R. D. Lorenz, (eds.) Penetrometry in the Solar System, Austrian Academy of Sciences Press (2001), pp. 125–136 . 5. H. Mizutani, A. Fujimura, S. Tanaka, H. Shiraishi and T. Hakjima, J. Earth Syst. Sci. 114(6) (2005) 763–768. 6. T. J. Mosher and P. Lucay, Polar night: a lunar volatile expedition, in: Proc. 5th IAA Int. Conf. on Low Cost Planetary Missions (2003). 7. A. Smith, I. A. Crawford, R. A. Gowen et al., Exp Astron 23 (2009) 711. 8. Y. Gao et al., Planet. Space Sci. 56(3–4) (2007) 368–377. 9. R. A. Gowen, A. Smith, B. W. Winter et al., An Update on MoonLITE, Proc. 59th IAC, Glasgow (2008). 10. N. I. K¨ omle, G. Kargl, A. J. Ball and R. D. Lorenz, (eds.) Penetrometry in the Solar System, Austrian Academy of Sciences Press (2001). 11. G. Kargl, N. I. K¨ omle, A. J. Ball and R. D. Lorenz, (eds.) Penetrometry in the Solar System II, Austrian Academy of Sciences Press (2009). 12. R. A. Gowen, A. Smith, B. Winter et al., Proc 59th IAC, Glagow (2008) 13. M. G. Langseth, S. Keihm, K. Peters, Lunar Planet. Sci. Conf. 7 (1976) 3143–3171. 14. W. T. Pike, I. M. Standley, W. J. Karl, S. Kumar, T. Semple, S. J. Vijendran and T. Hopf, Proc. Tranducers, Denver, M4F.003 (2009) 15. T. Hopf, S. Kumar, W. J. Karl and W. T. Pike, Adv. Sp. Res. in press (2009) 16. A. Butler, B. Goldthorpe and P. Church, Jnl. de Physique C8-471 (1994) 17. B. Goldthorpe, J Phys. IV 7(C3) (1997) 705–710 18. F. H¨ orz, R. Grieve, G. Heiken, P. Spudis and A. Binder, in Lunar Sourcebook (G. H. Heiken, D. T. Vaniman, and B. M. French, Eds.), Cambridge University Press (1991), pp. 1–120. 19. W. D. Carrier III, G. R. Olhoeft and W. Mendell in Lunar Sourcebook (G. H. Heiken, D. T. Vaniman, and B. M. French, eds.), Cambridge University Press (1991), pp. 476–594. 20. W. C. Feldman, S. Maurice, A. B. Binder, B. L. Barraclough, R. C. Elphic and D. J. Lawrence, Science 281(5382) (1998) 1496–1500. 21. D. Vaniman, R. Reedy, G. Heiken, G. Olhoeft and W. Mendell, in Lunar Sourcebook (G. H. Heiken, D. T. Vaniman and B. M. French, Eds.), Cambridge University Press (1991), pp. 27–60. 22. D. S. McKay, G. Heiken, A. Basu et al., The Lunar Regolith in Lunar Sourcebook (G. H. Heiken, D. T. Vaniman and B. M. French, Eds.), Cambridge University Press (1991). 23. R. Yamada et al., Planet. and Space Sci. 57 (2009) 751–763.

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24. N. A. Stutzke, S. E. Russek, D. P. Pappas and M. Tondra, J. Appl. Phys. 97 (2005) 10Q107. 25. R. P. Lin, D. L. Mitchell, D. W. Curtis et al., Science 281 (1998) 1480. 26. H. O’Brien, P. Brown, T. Beek et al., Meas. Sci. Tech. 18 (2007) 3645. 27. I. P. Wright et al., Sp. Sci. Rev. 128 (2007) 363.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

DUTY CYCLE WEIGHTING USING E-BEAM LITHOGRAPHY IN RACs FOR CHIRP TRANSFORM SPECTROMETERS XIANYI LI∗ and PAUL HARTOGH† MPS Katlenburg-Lindau, Germany ∗ [email protected] † [email protected] LEONHARD REINDL IMTEK Freiburg University, Freiburg, Germany [email protected] THOMAS WEIMANN PTB Braunschweig, Germany [email protected] VICTOR PLESSKY GVR Trade Neuchatel, Switzerland [email protected]

In this paper a new kind of amplitude weighting technique for reflective array compressors (RAC) is presented which uses duty cycle modulation for chirped grooves with constant depth. It can have almost the same weighting results as the conventional depth profile weighting3, 4 but the weighting is performed by varying the duty cycle of the grooves in the array, i.e. only changes in the layout design are required instead. This method is appropriate nowadays thanks to the availability of very high resolution e-beam lithography with resolution better than 2.5 nm. Then the groove depth can be kept uniform along the whole array and it will save a lot of etching time for fabrication. This method can be realized with standard commercial etching equipment and is more suitable for small series production with reasonable cost. In this work we designed a down chirp RAC filter with 400 MHz bandwidth, 10 µs dispersive delay and 1 GHz center freqeuency. The flat magnitude of above sample after duty cycle weighting is shown in Fig. 10, the magnitude ripple is limited in 2 dB in the whole 400 MHz bandwidth, the compressed pulse power envelope is shown in Fig. 11, its width is reduced to 2.319 ns, which is very close to theoretical value 2.213 ns. The weighting of the reflector structure resulted in 11.5% narrower compressed pulse compared to unweighted reflectors (2.632 ns).

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1. Introduction The Reﬂective Array Compressor (RAC)2 is one kind of Surface Acoustic Wave (SAW) dispersive delay line which is very often used in Chirp Transform Spectrometers (CTS) for real time Fourier analysis in heterodyne submillimeter wave observations of planetary atmospheres.1 For such kind of devices, the passband ﬂatness is very important as it will determine the compressed pulse width which is related to the frequency resolution of the CTS. In this work we designed a down chirp RAC ﬁlter with 400 MHz bandwidth, 10 µs dispersive delay and 1 GHz center freqeuency. The characteristic of the groove array part of the RAC shows that it will give a nonuniformity of 14 dB in magnitude from the low to the high frequency end for uniform chirp groove geometry. This is because for large bandwidth chirp ﬁlters, if we use constant groove depth and 50% uniform duty cycle, the single groove reﬂectivity will increase with the input frequency (as shown in Eq. (1)), the eﬀective number of grooves that reﬂecting in phase will also increase with input frequency, and further more due to SAW propagation and SAW transmission through grooves, large nonuniformity will be generated on the ﬁlter insertion loss. From the measurement results, the total insertion loss nonuniformity in the whole 400 MHz bandwidth can be 14 dB, which is shown in Fig. 1. The nonuniformity leads to a distortion of the compressed pulse (i.e. the autocorrelation function of the ﬁlter’s impulse response), which is shown in Fig. 2. The main lobe −3 dB width is τ3 dB ≈ 2.632 ns, which is much larger than the theoretical sinc function −3 dB main lobe width: τideal ≈ 0.885 ·

1 1 = 0.885 · = 2.213 ns B 400 MHz

(as the unweighted ﬁlter bandwidth is smaller than 400 MHz due to the nonuniformity). So if we use the unweighted RAC ﬁlter in CTS, it will cause the CTS to lose frequency resolutions, so this magnitude nonuniformity for RAC ﬁlter must be corrected. In the past special etching equipment was used3, 4 to perform the depth proﬁle etching along the groove array in order to realise amplitude weighting. But such technique is time consuming (etching performed on the single device basis), and the equipment is not available commercially. Both disadvantages prevent such devices to be produced in large volume therefore the cost is high. As the ion beam etched single groove reﬂectivity for Rayleigh wave oblique incident and 90 degrees

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Fig. 1. Measured RAC insertion attenuation using groove array with 25 nm constant depth and 50% uniform duty cycle.

reﬂection is ﬁrstly measured by J. Melngailis,10 and it can be derived using the following empirical formula:8 w h rg ≈ 2 · 0.51 sin π (1) λ λ here rg is the single groove amplitude reﬂectivity for Rayleigh wave; h is the groove depth, and λ is the Rayleigh wave wavelength; w is the groove ) duty cycle of the groove. width, and we call ( w λ From Eq. (1) we can see that the single groove reﬂectivity can also ) value while keeping the groove depth h be modiﬁed by varying the ( w λ constant. Then the weighting only need to change the layout design of RAC. But for doing so, the grooves will be narrower than 50% of the period, which will add diﬃculties to the lithography, especially when the groove width after weighting approaches the critical dimension(CD) for exposures. With modern very high resolution (2.5 nm) e-beam lithography technology, which has a critical dimension about 10 nm, it is already possible to control the groove width precisely, it brings a new kind of weighting method for designing RAC devices — duty cycle weighting. Using this weighting technique, the groove depth can be kept uniform along the whole array, so it will save a lot of etching time for fabrications

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Fig. 2. Comparison between compressed pulse from unweighted RAC (solid line) and sin(πBT ) (dashed line). The unweighted RAC compressed pulse standard Sinc function πBT −3 dB main lobe width is about 2.632 ns and the standard Sinc function −3 dB main lobe width is only about 2.213 ns.

compared to depth proﬁle etching. And also this method can be realized with standard commercial etching equipment and is more suitable for small series production with reasonable cost. 2. Loss Modelling of the RAC Device For doing the RAC device total insertion loss modulation, its loss mechanism must be very well understood. The total insertion loss IL(f ) for RACs can be considered being composed of several separate items:5 IL(f ) = R(f ) + IDT (f ) + P rop(f ) + T ran(f ) (dB)

(2)

Here all the loss items are frequency dependent in dB unit: R(f ) is the groove array reﬂection loss; IDT (f ) is the transducer transduction loss; P rop(f ) is the Rayleigh wave propagation loss on free surface (with air loading) and T ran(f ) is the loss due to transmissions through grooves in the ‘U’ shape SAW propagation path. In the following sections, the diﬀerent loss mechanisms are estimated for the designed RAC device.

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2.1. Reflection loss The total reﬂection loss of groove array can be calculated according to the well known stationary phase approximation (SPA),11 saying that the total reﬂectivity of the groove array is mainly contributed by the group of grooves which are reﬂecting the Rayleigh wave synchronuously: W 2 R(f ) = (rg (f ) · Nef f (f )) · Geom (3) La · tgα here rg (f ) is the frequency dependent groove reﬂectivity as deﬁned in Eq. (1), and Neﬀ (f ) is the eﬀective number of grooves that are reﬂecting in phase,7 B and T in the formula are chirp bandwidth and chirp delay time respectively: f ·T Neﬀ (f ) = √ 2 B·T

(4)

and frequency independent quantity Geom( LaW ) is the geometrical ·tgα factor which describes how the groove array reﬂectivity will depend on its geometry — the aperture W , it is only related to W . The factor Geom( LaW ·tgα ) is numerically calculated from the complete double summing impulse response model11 of reﬂective array (as shown in Fig. 3), when W < 1.75 · La , Geom( LaW ) almost linearly increases with the aperture ·tgα W , for W > 1.75 · La, Geom() is going to saturate, for the maximum eﬃciency normally we choose W = 2 · La , here Geom( LaW ·tgα ) ≈ 2.0, and La = Neﬀ (f ) · λ is the active length of the groove array at a speciﬁc frequency, which is the length of the group of grooves that are reﬂecting SAW in phase.6 2.2. Propagation loss The propagation loss of Rayleigh waves on YZ-LiNbO3 free surface was ﬁrstly measured by A. J. Slobidnik.9 The loss attribute in unit propagation time (dB/µs) is proportional to f 1.9 plus one linear term which is due to the air loading eﬀect(here f is in GHz unit): Att(f ) = 0.19f + 0.88f 1.9 (dB/µs)

(5)

For the down chirp ﬁlter, the propagation delay of the SAW at diﬀerent frequencies depends on the propagation length at that frequency. According to the linear chirp’s delay to frequency relationship, the RAC total

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Fig. 3.

The numerically calculated geometrical factor of the groove array.

propagation loss can be calculated as follows: Prop (f ) = −Att(f ) · [t1 + (f1 − f ) · T /B] (dB)

(6)

here t1 is the initial delay time of the practical device, and f1 = fc + B/2 is the high frequency end of the bandwidth. The loss decreases from 8 dB to 2 dB when frequency increase from 800 MHz to 1,200 MHz for the sample B = 400 MHz, T = 10 µs, fc = 1 GHz RAC ﬁlter. 2.3. Transmission loss As the SAW is propagating through the whole grating until it approaches the synchronously reﬂecting zone for a given frequency, the transmission for SAW going through the not in phase grooves in the path will also give contributions to the insertion loss, this part of loss could be estimated numerically using the following formula: nf −Neﬀ (f )/2

T ran(f ) ≈

2 [20 · lg(1 − rgn (f ))] (dB)

(7)

n=1

Here nf is the index number for the precisely in phase reﬂecting groove at frequency f ; and rgn (f ) is the reﬂectivity of the arbitrary groove indexed by

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n at frequency f . For the uniform structure, the transmission loss is quite high, for our designed sample, it is around 3 to 4 dB; but after the weighting as the reﬂectivity of the most grooves are reduced, the transmission loss become much smaller, only about 1 to 2 dB. 2.4. IDT transduction loss The IDT loss has been evaluated using experimental method, simple delay lines are fabricated, and the performance is measured using a vector network analyzer. The geometry of the interdigital transducer used ﬁrstly is the uniform Npair = 2.5 IDT centered at 1 GHz, then was changed to 8 electrodes IDT with one pair reverted structure.6 In order to realise 40% very wide −3 dB fractional bandwidth, the ﬁnger pair must be very small, Npair = 40%1−3dB = 2.5. And one extra pair with reverted polarization is added to supply a negative sidelobe in the time domain, which can give a more rectangular passband shape in frequency domain. The geometry of the PRT (pair reverted transducer) is shown in Fig. 4. The insertion attenuation comparison between the PRT and uniform IDT is shown in Fig. 5, we can see that the PRT have slightly ﬂatter passband shape under the same matching condition. 3. Duty Cycle Weighting The duty cycle weighted layout is calculated according to the following steps: (1) Evaluate the RAC insertion loss without any weighting technology. (2) Calculate the magnitude correction coeﬃcient according to formula (8) as shown in Fig. 6. (3) Modify the duty cycle proﬁle in the groove array according to formula Eq. (9).

Fig. 4.

The geometry of the one pair reverted transducer.

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IDT, W = 780 µm IDT, W = 780 µm, time gated PRT, W = 780 µm PRT, W = 780 µm, time gated

-20

Magnitude (dB)

-30

-40

-50

-60

-70 700

800

900

1000

1100

1200

1300

Frequency (MHz) Fig. 5. Transduction attenuation comparision between PRT(blue) and uniform IDT(red), the grey and green lines are their respective feedthrough time gated responses.

-10 -15

Mag(f)uw

Magnitude (dB)

-20

Mag(f)desired -25 -30

Mag(f)corr

-35 -40 -45 -50 700

800

900

1000

1100

1200

Frequency (MHz) Fig. 6.

Calculation of the magnitude correction factor.

1300

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Fig. 7.

329

Calculated groove array duty cycle profile.

(4) Evaluate the RAC insertion loss again with the weighting to verify the weighting results. M agcorr(f ) = M aguw (f ) − M agdesired(f )(dB) −M agcorr (f ) w 1 40 = · arcsin 10 λ local π

(8) (9)

The duty cycle proﬁle after weighting is shown in Fig. 7. From the reﬂection loss after weighting in Fig. 8, it is possible to see that the single groove reﬂectivity is small enough to keep R(f ) <= 0 dB in the whole passband, in this case the multiple reﬂections are controlled at a reasonably low level, so they cannot result in unacceptable magnitude and phase distortions.7 4. E-beam Lithography for Duty Cycle Weighting The exposure was done at PTB (Physikalisch Technische Bundesanstalt) using the VISTEC EBPG5000 + e-beam lithography machine, the applied electron accelaration voltage is 50 kv. Due to the proximity eﬀect of the back and forward scattering electrons, the duty cycle weighted grooves could not be exposed with uniform dose of e-beam. After several exposure tests

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Fig. 8.

Calculated groove array reflection loss after duty cycle weighting.

we have found that the required exposure dose of the e-beam is linearly dependent on the duty cycle of grooves but not on the period. An empirical exposure dose look up table was established for exposing the whole groove array. The whole layout was divided into 20 segments, the adjacent segment have 2.5% duty cycle variation and inside each segment grooves will be exposed with uniform e-beam dose, the updated layout was shown in Fig. 9. Each exposure dose is represented by one colour in the layout. 5. Discussion and Conclusions The measured RAC passband shape after the duty cycle weighting is shown in Fig. 10. The passband nonuniformity is less than 2 dB in the whole 400 MHz bandwidth. The compressed pulse was calculated by feeding the calculated matched up-chirp signal into the measured down-chirp ﬁlter, and the main lobe width τ−3 dB ≈ 2.319 ns is very close to the theoretical sinc function −3 dB main lobe width: τideal ≈ 0.885 ·

1 = 2.213 ns. 400 MHz

And if we compare to the compressed pulse from the one before weighting in Fig. 10, which has τ−3dB ≈ 2.632 ns, the compressed pulse width is

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Fig. 9. Layout of RAC for the groove duty cycle dependent e-beam exposure dose variation.

Fig. 10. Measured RAC magnitude after duty cycle weighting for 40 nm uniform depth groove array.

reduced by 11.5% (as shown in Fig. 11). This indicates that the frequency resolution of the Chirp Transform Spectrometer can be improved by 11.5% by using this weighted chirp ﬁlter compared to the unweighted chirp ﬁlter.

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Fig. 11. Comparison between the compressed pulse from weighted RAC filter (solid sin(πBt) (dashed line). The weighted line) and standard Sinc function with the form πBt RAC compressed pulse −3 dB main lobe width converged to about 2.319 ns and the standard Sinc function −3 dB main lobe width is about 2.213 ns.

Acknowledgment Xianyi Li thanks the Max Planck Solar System School for postgraduate scholarships, thanks Mr. Rudige Wendisch for all the Ar ion beam etching processes, and also thanks Mr. Peter Hinze for discussions of ﬁlter fabrication. References 1. Geronimo Luis Villanueva Sozzi, The high resolution spectrometer for SOFIAGREAT: Instrumentation, Atmospheric Modeling and Observations, PhD thesis, Max Planck Institute for Solar System Research, 2004. 2. R. C. Williamson and H. Smith, The use of surface-elastic-wave reflection gratings in large time-bandwidth pulse-compression filters, IEEE Transactions on Sonics and Ultrasonics, Vol. SU-20 (1973) 113-123. 3. J. Gong, Y. Zhang, X. Zhou and P. Hartogh, Wide Bandwidth SAW Chirp Filters with Improved Magnitude Response, 2006 Ultrasonics Symposium Proceedings. 4. H. I. Smith, R. C. Williamson and W. T. Brogan, Ion Beam Etching of Reflective Array Filters, IEEE Ultrasonics Symposium.

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5. O. W. Otto and H. M. Gerard, Nonsynchronous scattering loss in surface acoustic wave reflective array compression filters, J. Appl. Phys. 49 (1978) 3337–3340. 6. H. M. Gerard, O. W. Otto and R. D. Weglein, Development of a Broadband Reflective Array 10000:1 Pulse Compression Filter, 1974 Ultrasonics Symposium Proceedings, pp. 197–201. 7. S. M. Balashov, E. A. Garova and V. P. Plessky, Theory of Rayleigh-wave Bragg reflection in quasiperiodic structures, Physical Review B 42 (1990). 8. D. P. Morgan, Surface-Wave Devices for Signal Processing, Amsterdam, the Netherlands: Elsevier, 1985. 9. A. J. Slobidnik Jr., P. H. Carr and A. J. Buedreau, Microwave frequency acoustic surface wave loss mechanisms on lithium niobate, J. Appl. Phys. 41 (1970) 4380–4387. 10. J. Melngailis and R. C. M. Li, Measurement of impedance mismatch and stored energy for right-angle reflection of Rayleigh waves from grooves on Y cut LiNbO3 , 1975 Ultrasonics Symposium Proceedings, IEEE Cat. Vol. 75 CHO 994-4SU. 11. T. A. Martin, The IMCON Pulse Compression Filter and its Applications, IEEE Transactions on Microwave Theory and Techniques MTT21, April 1973, pp. 111–119.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

RETRIEVAL SIMULATIONS OF ATMOSPHERIC GASES FROM HERSCHEL OBSERVATIONS OF TITAN M. RENGEL∗ , H. SAGAWA† and P. HARTOGH‡ Max-Planck-Institut f¨ ur Sonnensystemforschung, Max-Planck-Straße 3, D-37191 Katlenburg-Lindau, Germany ∗ [email protected] † [email protected] ‡ [email protected] www.mps.mpg.de/homes/rengel/

The launch of the Herschel Space Observatory is scheduled for 2009 and Herschel is planned to be operational for 3.5 to 4 years. Among others, a guaranteed time key project called “Water and related chemistry in the Solar System” has successfully undergone a peer review process. This project dedicates a substantial amount of observation time for the atmospheres of the outer planets, of Enceladus, and of Titan, using all three Herschel instruments (Heterodyne Instrument for the Far Infrared (HIFI), Photodetector Array Camera and Spectrometer (PACS), and Spectral and Photometric Imaging REceiver (SPIRE)). In this paper we present calculations of the expected spectra in the Herschel wavelength range and investigate the possibility to retrieve vertical proﬁles of temperature and H2 O mixing ratio with the spectral resolution of HIFI, and temperature and H2 O, HCN, and CO mixing ratios with PACS in Titan’s atmosphere for the expected signal-to-noise ratios.

1. Introduction Titan, the largest moon of Saturn, is a body of considerable astrobiological interest in view of high organic abundances and potential subsurface liquid water. Titan is unique in the Solar System with its atmosphere: it is nitrogen (N2 )-dominated and contains many complex molecules in the form of hydrocarbons and nitriles.1–4 Methane (CH4 ) is the second most abundant substance detected in Titan’s atmosphere and one of the main greenhouse gases,5, 6 hydrogen cyanide (HCN) is the most abundant nitrile on Titan, and the carbon monoxide (CO) origin is not well understood (whether photochemical or primordial). The origin of Titan’s atmosphere is little understood and its chemistry is rather complicated. Furthermore, 335

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there is evidence of water in the upper atmosphere of Titan, implying the existence of external sources of water.7, 8 The main sources of external water (cometary impacts, and interplanetary dust particles) are not well constrained. The ESA’s fourth Cornerstone mission, the Herschel Space Observatory, will be a unique tool for detecting water, its isotopes, and chemically related species on Titan, among other solar-system objects. Furthermore, it will be the only space observatory to cover the spectral range from far-infrared to submillimetre wavelengths (approximately the 55–672 µm range), a region rich with numerous lines of trace gases. Herschel will carry a 3.5 m diameter telescope and three instruments: two cameras/medium resolution spectrometers (the Photodetector Array Camera and Spectrometer (PACS), and the Spectral and Photometric Imaging REceiver (SPIRE)) and a very high resolution heterodyne spectrometer (the Heterodyne Instrument for the Far Infrared (HIFI)). A guaranteed time key program, “Water and Related Chemistry in the Solar System”,1 is devoted to the study of the origin and evolution of water in Solar System objects. In the framework of the mentioned program one of the goals is performing line scan surveys with PACS (from 55 to 210 µm) to obtain the vertical proﬁles of important species. Tracing molecules such as CH4 , H2 O, HCN, and CO can help in determining the vertical structure of Titan’s atmosphere. This paper concentrates on the investigation of possible vertical proﬁle retrievals of temperature and mixing ratio of H2 O with HIFI, and temperature and mixing ratios of H2 O, HCN, and CO with PACS for the expected signal-to-noise ratios. In order to model the expected observed emission spectra, a forward model is required which accurately takes into account spectroscopy, atmospheric radiative transfer, and instrument characteristics. Furthermore, an inversion technique allows the retrieval of physical parameters such as the mixing ratio from the spectra. A detailed description of the general forward- and inversion model, and the basic physics and mathematics of the forward model are given in Rodgers (1976);9 Rodgers (1990);10 Urban et al. (2004),11 among others, and an example of the use and implementation of the retrieval technique and forward model, for the case of Venus, in Rengel et al. (2008).12 We present a description of the planned Herschel observations of Titan’s atmosphere, and of the methodology used to retrieve vertical proﬁles of 1 Also

known as “Herschel Solar System Observations” (HssO) project, URL: http:// www.mps.mpg.de/projects/herschel/HssO/index.htm.

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important species on Titan. Furthermore we report our resulting simulated observations and retrieved mixing ratios with HIFI and PACS. 2. Proposed Spectral Line Observations of Titan HssO will dedicate a substantial amount of observational time for the atmospheres of the outer planets, Titan, and Enceladus, using all three Herschel instruments (a total of ∼110 h). Within the framework of the HssO project, the proposed Titan observations consist mainly of a combination of: (i) low S/N (10 at 1 MHz spectral resolution) spectrally-resolved observations (repeated 3 times) of one or a few water lines with HIFI, including the 557 GHz line, with an observational time estimated of around 13 h, (ii) high S/N (100) full range spectra with SPIRE (194–672 µm), with proposed time of around 13 h, and (iii) dedicated, very high S/N (>100) observations of selected water lines for wavelengths in the range 55-210 µm, and very high S/N (100–300) fullrange spectra with PACS (which undoubtedly allow the detection of other species besides H2 O, including at least CH4 , HCN, CO, and their isotopes on Titan). Repeated (8 times at 8 day intervals over the 2010 window), high S/N, 3-band PACS photometric measurements will be acquired in search of a volcanic component. Titan cryovolcanism observations are planned in the May 10–July 22 2010 visibility window to minimize scattered emission from Saturn’s ring. The strongest 4512 GHz line will be observed 3 additional times during the mission to search for variability. The planned observational time is about ∼9 h. The vertical proﬁle of water vapor will be determined from (i) lineshape measurements with HIFI, (ii) multi-line observations with PACS. In the proposal, 7 lines are chosen to determine the vertical proﬁle of water on Titan with PACS, and they are at 2392, 2774, 3654, 3977, 4469, 4512, and 4600 GHz. These lines, which have diﬀerent strengths, show diﬀerential sensitivity, at a few percent levels, to the vertical distribution. 3. Retrieving Vertical Profiles of Species The feasibility of retrieving vertical proﬁles of the atmospheric constituents from HIFI and PACS observations of Titan was investigated here by performing forward- and inversion calculations. Our calculation package has been developed based on the general forward- and inversion models at the microwave wavelengths called MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval, version 5),11 and on AMATERAS (Advanced

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Model for Atmospheric TeraHertz Radiation Analysis and Simulation).13 In these models, the inversion calculation (e.g. retrieval of the molecular mixing ratios from the measurements) is solved by using the optimal estimation method which is fully described by Rodgers (1976; 1990).9, 10 The expected sensitivity of the measurements to the atmospheric species proﬁles and the quality of the retrieval are characterized here by the socalled weighting function Kx and averaging kernels A, respectively, as deﬁned by Rodgers (1990).10 Note that Kx used in this study is deﬁned by the partial derivative of the forward model-function F with respect to the unknown parameters x; under this deﬁnition, Kx can have negative values. Our atmospheric model is a multi-layered line-by-line model considering the spherical geometry of Titan’s atmosphere. It consisted of 180 layers that span the 0–900 km interval with a resolution of 5 km. Titan’s thermal and pressure proﬁles from the in-situ measurements of Huygens probe (Fulchignoni et al. 200514 ) are adopted for the opacity calculation of the CH4 , H2 O, HCN, and CO gases at each altitude level (Fig. 1, left). For CH4 , abundances are derived from Niemann et al. 200515 (altitude range between 0 and 140 km), and from Lara et al. (1996)16 (altitudes higher than 600 km); for the altitude range between 140 and 600 km, we assumed a constant mixing ratio of 0.014. For HCN, abundances are derived from Marten et al., 2002,17 and for CO from de Kok et al. 200718 (Fig. 1, right). The spectral resolution of Cassini/CIRS is not

Fig. 1. Left: Adopted Titan thermal and pressure proﬁles from Fulchignoni et al. (2005).14 Right: the atmospheric composition based on Lara et al. (1996),16 Marten et al. (2002),25 Niemann et al. (2005),15 and de Kok et al. (2007)18 for H2 O, HCN, CH4 and CO, respectively. H2 O and HCN are shown on a logarithmic scale.

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high enough to detect the H2 O emission lines, and then only the upper limit of 0.9 ppb at the lower stratosphere has been suggested from the CIRS measurements.18 We used the photochemical model of Lara et al. (1996)16 which covers the altitude range above 1000 km. N2 -broadening linewidths of the H2 O and HCN lines are taken from Gamache and Fischer 200319 and Yang et al. 2008,20 respectively. For CH4 and CO, the assumed N2 -broadening linewidths here are those of the HITRAN 2004 molecular spectroscopic database air broadening linewidth21 multiplied by a factor of 1.05 and 1.07, respectively. These factors are considered by extrapolating the ratio between N2 and the air-broadening widths at the infrared and millimeter wavelengths.17, 22 The collision induced absorption coeﬃcients of N2 , CH4 , and H2 mixtures, which dominate the millimeter and submillimeter continuum opacity of Titan atmosphere, are included by using the formulation of Courtin (1988)23 and Borysow and Tang (1993).24 The instrumental modeling for the simulated PACS observations was performed by following the description of the instrument paper26 and the observer’s manual of PACS.2 The spectral resolution range of PACS varies from 1 to 4 GHz (or 0.03 to 0.13 cm−1 ). Although a proposed S/N = 100 and 100–300 are listed for Titan observation with PACS, we have assumed a S/N of 50 for simulating the PACS observations in this study for exploring a normal case scenario. The 3.5 m-diameter primary reﬂector of Herschel yields a beam size of 13.3 and 4.4 (FWHM) at the frequencies of 1.6 and 4.8 THz, respectively, so that the Titan’s apparent diameter of 0.89 can be assumed as a point-like source object. The optimal estimation technique requires a priori proﬁle guesses of the parameters to be retrieved to regularize the ill posed inversion problems. The emission spectra of the atmospheric gases are dependent on both temperature structure and abundance of the molecules. Therefore it is frequently necessary to determine a temperature proﬁle before retrieving molecular abundances. For the temperature retrieval, we used the emission spectra of CH4 . CH4 is a good choice since it is expected to be uniformly mixed in the stratosphere15 and this allows us to assess the temperature proﬁle more accurately. Once the temperature proﬁle is determined, we retrieve the mixing ratio proﬁles of the atmospheric gases in consideration. We set vertically uniform a priori proﬁles of H2 O, HCN, and CO as constant mixing ratios of 1.0 × 10−9, 1.0 × 10−7, and 7.0 × 10−5 , respectively. For H2 O and HCN, their vertical distributions at the lower stratosphere (below 2 URL:

http://herschel.esac.esa.int/Docs/PACS/pdf/pacs om.pdf.

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∼100 km) were limited by saturation. We assumed moderate uncertainties on the a priori guesses of 10 K and 15 ppm for temperature and CO, respectively, and a factor of 10 for H2 O and HCN. The inversion grid is set to 20 and 40 km for the temperature and mixing ratio, respectively. The resultant error in the retrieval analysis can be divided into (i) the error due to the statistical measurement noises (so-called retrieval noise or measurement error), (ii) the error introduced by loss of information from the ﬁne structure (so-called smoothing error and often estimated by the covariance of the a priori guesses) and (iii) the error due to uncertainties in describing the forward model. In this study, we focused on the error components (i) and (ii) for the error analysis. 4. Results 4.1. Retrieval simulations with the spectral resolution of HIFI We started our investigation with the simulation of the emission of single lines of CH4 and H2 O at 1881.9 and 1669.9 GHz, respectively, with the spectral resolution of HIFI. Because of the very high spectral resolution of HIFI, only a line selection of CH4 and of H2 O as an example is considered. We adopted here a spectral resolution of 1 MHz and a total bandwidth of 2 GHz.27 Spectra with S/N = 50 are assumed for comparison with the simulations of the PACS observations. Figure 2 shows the normalizedweighting functions with respect to the temperature for the CH4 1881.9 GHz line for several frequency oﬀsets from the line center (left panel), and with respect to the H2 O mixing ratio for the H2 O 1669.9 GHz line (right panel). With 1 MHz spectral resolution, we can spectrally resolve the absorption line, and diﬀerent peak altitudes of the weighting function can be obtained at the line wings where opacity decreases to the continuum level. In Fig. 3 (upper panel) we present the simulated observation and ﬁtted spectrum of the CH4 1881.9 GHz line, retrieved temperature proﬁles (true, a priori, and retrieved) with its corresponding error proﬁles, and the averaging kernels. On the temperature error plots, it is shown that the error, at best, is less than 4 K at the altitude range of 40–100 km. Within this range, the total error is mostly contributed by the measurement error, which is determined by the signal to noise ratio of the measurements. The averaging kernels describe the transformation of the true proﬁle to the retrieved proﬁle; thus, it provides an eﬀective indication for understanding the quality of the retrieval and how the true state is smoothed by the remote

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Fig. 2. Normalized CH4 temperature (left) and H2 O mixing ratio (right) weighting functions as provided by the 1881.9 GHz CH4 and 1669.9 GHz H2 O lines, respectively, for various frequency oﬀsets from the line center (from 0 to 200 MHz oﬀset).

sensing system. The temperature retrieval has a sensitivity at the altitude region of 40–100 km with a vertical resolution reaching up to 30 km. The cutoﬀ of the sensitivity at the lowest altitude of 40 km is likely to occur, because the atmosphere becomes optically thick due to the N2 collision induced absorption. For the altitudes higher than 100 km, the information is certainly deducible up to 220 km, though the vertical resolution becomes poor. In Fig. 3 (lower panel) we present the simulated observation and ﬁtted spectrum of the H2 O 1669.9 GHz line, retrieved mixing ratio proﬁles calculated from 4 diﬀerent ﬁxed temperature proﬁles called (a)–(d) (see caption) with its corresponding error proﬁles, and the averaging kernels (given only for case (a) for simplicity). Comparison between diﬀerent mixing ratio results enables us to estimate the eﬀect of the uncertainty in the temperature proﬁle (particularly above 220 km) on the H2 O mixing ratio retrieval. To avoid introducing an oﬀset in the continuum level, the error components on temperature proﬁles (b)–(d) are added on the temperatures at altitudes higher than 60 km. The expected H2 O retrieval error in case (a) is 40–60% of the retrieved values at the most reliable altitudes (100–180 km), and a resolution of ∼50 km. From 180 to 420 km, the retrieved H2 O proﬁle seems to increase exponentially with altitude, which qualitatively agrees with the true proﬁle, although the averaging

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Fig. 3. Upper panel: simulated measurement (gray) and best-ﬁtted spectrum (black) for the CH4 1881.9 GHz line emission (left), retrieved proﬁles of temperature (center). Dotted lines and surrounding shaded areas correspond to the a priori proﬁles and their errors; the thin-solid lines are the true proﬁles; and the bold-solid lines are the retrieved proﬁles with error bars for the 1-σ level of the retrieval error. This latter one is the sum of the smoothing error (dotted line) and the statistical measurement error (dashed line). Lower panel: simulated measurement (gray) and best-ﬁtted spectrum (black) for the H2 O 1669.9 GHz line emission (left), retrieved proﬁles of H2 O considering 4 diﬀerent temperature proﬁles: by the temperature proﬁle which is retrieved from the CH4 1881.9 GHz line (proﬁle (a)), ±1-σ and +2-σ levels of the retrieval error of proﬁle (a) (b, c and d, respectively) (center). Right upper and lower panels: Averaging kernels, each curve corresponds to the averaging kernel for a certain retrieval altitude denoted by the tick on the curve. Gray bars on the right side indicate the altitude region where the retrieval is satisfactorily obtained.

kernels for those altitudes are vertically smeared. Resulting H2 O proﬁles considering cases (b) and (c) are ranged within 1-σ error from the one from case (a). Furthermore, the resulting H2 O proﬁle considering case (d) has larger ﬂuctuations than 1-σ error only at certain altitudes (example at 220 and 420 km). This indicates that a temperature proﬁle retrieved from the CH4 line with an uncertainty of around 10 K does not represent a critical error source in retrieving H2 O mixing ratios compared to retrieval errors due to the other eﬀects (e.g. a priori errors).

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Fig. 4. Synthesized spectrum of the Titan atmosphere with the spectral resolution of the PACS instrument (∆ν = 1–4 GHz). The symbols indicate the selection of the lines which we used in the retrieval analysis (Table 1).

4.2. Temperature and mixing ratio profiles of H2 O, HCN, and CO with PACS In Fig. 4 we show model calculations of the synthesized spectrum of Titan’s atmosphere (CH4 , H2 O, HCN and CO) with the PACS spectral resolutions (∆ν=1–4 GHz). The multiple-line scans with the chopping-nodding mode were employed as the setup of the observations in this study. Opposite to the case described in Sec. 4.1, where the spectral resolution mixing ratio retrieval is 1 MHz and the use of a single line produces a vertical range of the retrieval, PACS mixing ratio retrievals require the use of multiple-line observations with diﬀerent line opacities for each specie. This is because of the low spectral resolution of the PACS instrument, which prevents us from resolving the core and wing parts of the emission line. As indicated in Sec. 2, 7 lines are originally selected. We increase the number of lines from 7 to 10 to examine a better possibility in the retrieval output. Table 1 indicates the detailed frequencies (at the frequency region from 1.8 to 4.6 THz) of the diﬀerent lines of the species considered Table 1.

Frequencies of the lines of the species used to simulate the observations.

Specie CH4 H2 O HCN CO

Frequencies (GHz) 1882.0, 2774.0, 1681.6, 1611.8,

2194.7, 3013.2, 1769.8, 1726.6,

2505.6, 3331.5, 1858.0, 1841.3,

2816.0, 3654.6, 1946.2, 1956.0,

3127.4, 3807.3, 2034.3, 2070.6,

3436.8, 3977.0, 2122.3, 2185.1,

3740.5, 4166.9, 2210.4, 2299.6,

4046.0, 4468.6, 2298.3, 2413.9,

4350.5, 4665.5 4512.4, 4600.4 2386.2, 2474.0 2528.2

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here. Several transitions of HCN and CO on Titan are also expected to be detected with PACS in the frequency range lower than 2.5 THz. The retrieval simulations for PACS were performed following the same way as described in the previous section (ﬁrst, the temperature proﬁle is retrieved from multiple CH4 lines, second, the abundances are retrieved under the assumption of ﬁxed temperature proﬁles for cases (a)–(c)). Figure 5 shows (from the left to right column) the weighting functions with respect to the mixing ratios, retrieved mixing ratio proﬁles for the simulated observations with their corresponding error proﬁles, and the averaging kernels, except for CH4 plots (upper panels), which are corresponding to the retrievals with respect to the temperature. The weighting functions of multiple lines for each specie show diﬀerent sensing altitudes. The expected vertical sensitivity of the temperature retrieval from multiple CH4 lines extends from 20 to 240 km with a vertical resolution of 30 km, and an error of ∼2 K at its best, which is comparable to those of the ∆ν = 1 MHz observations (Fig. 3). The lower boundary of the altitude coverage slightly shifted downwards due to the decrease of the collision induced absorption opacity at higher frequency. The H2 O weighting functions are vertically smeared out as compared to those of HIFI, and the reliable altitude range for the retrieval is limited at the altitude of 140 ± 30 km. Although 1-σ level of the retrieval errors are very small (less than 10% of the retrieved value at 140 km) as compared to those of HIFI cases shown in Fig. 3, our H2 O retrievals from PACS measurements showed a larger dependence on the temperature proﬁle than the one on HIFI. The diﬀerence in the retrieved H2 O mixing ratio at 140 km altitude, for instance, between the cases (a) and (b), or (a) and (c) is ∼80% of the retrieved value of case (a), which is comparable to the retrieval errors estimated for the HIFI observations. A development of the data analysis strategy to reduce these errors on the mixing ratio retrievals contributed by the temperature uncertainty is required in future studies. One might point out that the retrieved H2 O proﬁle of case (b) matches to the true proﬁle in the upper altitudes around 500-600 km. This is just because the temperature proﬁle of (b) is close to the true proﬁle at these altitudes. Regarding HCN, if the temperature proﬁle (a) is used, the combination of the multiple-line observations provides sensitivity at wide altitude levels in the stratosphere and mesosphere: at 100–200 and 340–420 km, respectively, with a vertical resolution of 60–100 km. The expected error is 80–100% of the retrieved proﬁle. However, again, this result depends on how close

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Fig. 5. Retrieval simulations for the PACS observations. Left: CH4 weighting functions with respect to the temperature (upper panel) and H2 O, HCN, and CO weighting functions with respect to the mixing ratios. Each curve is plotted with an oﬀset of 0.1. Center: Temperature and error from CH4 lines (upper panel), and H2 O, HCN, and CO mixing ratios and errors. Right: averaging kernels. See the caption of Fig. 3 for more details. Note that the abscissa of the H2 O and HCN mixing ratio plots are on a logarithmic scale. Gray bars on the right side indicate the altitude region where the retrieval is satisfactorily obtained.

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346

the adopted temperature proﬁle is to the true temperature proﬁle; and the mesospheric information in case (b) can not be deduced, which has the temperature oﬀset of 15–20 K from the true values at the altitude region of 400–500 km. Finally, our CO calculations suggest that CO measurement with PACS has its sensitivity to the CO abundance at the limited altitude around 80 km, which is just above the altitude where the continuum emission comes from. The expected retrieval error is ∼10% of the retrieved proﬁle.

5. Conclusion • •

•

•

We have calculated the simulated spectra of CH4 and H2 O in Titan’s atmosphere with HIFI, and of H2 O, CO, HCN, and CH4 with PACS. We retrieved temperature proﬁles (from CH4 lines) and H2 O mixing ratios at 40–240 km, and 100–180 km, respectively, by using single lines for HIFI. Furthermore, by using a relevant combination of lines for PACS, we demonstrate the possibility of PACS to constrain the temperature and H2 O, HCN, and CO mixing ratios for a set of altitude levels: H2 O, CO and HCN at the stratosphere, and in addition, HCN at the mesosphere. Although with PACS’s low spectral resolution the information from the wing of each emission line is unresolved, the multiple-line simulated observation generates an almost as good a sensitivity to the vertical proﬁle of temperature as we can obtain with the high resolution spectroscopy of HIFI. By using a measured spectrum of uniformly mixed species (e.g. CH4 ), a retrieved temperature proﬁle successfully allows us to constrain mixing ratio proﬁles of atmosphere gases in Titan’s atmosphere.

These results in preparation for Herschel show our technique to be a promising tool for the analysis of Titan’s atmospheric data. Despite the success of the analysis presented here, some points need to be improved. As discussed in Sec. 4.2, uncertainties on the temperature proﬁle can induce a considerable error in the retrieved mixing ratio proﬁles from PACS observations if the temperature proﬁle is ﬁxed during the retrieval. One desirable alternative is to retrieve the temperature and mixing ratios simultaneously by using multiple lines. The accuracy of the retrievals themselves, which is limited for example by uncertainties in the a priori proﬁles, will be improved by the feedback of the future data and analysis

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of other emissions. Furthermore, the retrieval of gases for all Giant planets for PACS represents an in postmodum step of our work.

Acknowledgments We thank the two manuscript referees for their criticism and valuable suggestions for improvement of the initial submission. This research has made use of NASA’s Astrophysics Data System.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

DO GALILEAN SATELLITES OF JUPITER HAVE ISOCHEMICAL COMPOSITIONS?∗ V. A. KRONROD† and O. L. KUSKOV‡ V.I. Vernadsky Institute of Geochemistry and Analytical Chemistry, Russian Academy of Sciences, Kosygin Str. 19, 119991 Moscow, Russia † va [email protected] ‡ [email protected]

We have investigated a hypothesis of isochemical composition of Io and rockiron cores (without ice layer) of Europa and Ganymede. Models for the composition and structure of the Galilean satellites of Jupiter (Io, Europa, and Ganymede) were constructed using geophysical data provided by the Galileo mission on the mass, average density, and moment of inertia. The distribution of density, pressure, temperature, and gravity acceleration in the interiors of the satellites was determined. A simulation of the internal structure of the satellites showed the possibility of identical bulk compositions for water-free Io and the rock-iron cores of Europa and Ganymede. It has been shown that the geochemical parameters of the rock-iron constituent of the satellites are similar to the material of L/LL chondrites.

1. Introduction Kuskov and Kronrod1 hypothesized that Io, Europa, and Ganymede have structurally similar and chemically identical rock-iron cores (i.e. icy satellites without their outer ice–water shells) and diﬀer from one another only in the thickness and structure of the outer ice (water–ice) shell. In such a case, water-free Io (i.e. a satellite with an icy shell of zero thickness) can represent the material of the nonvolatile fraction of Jupiter’s disk. The estimates of the moment of inertia of Europa calculated on the basis of the hypothesis of the similarity of the rock-iron cores of the satellites coincided with experimental measurements,1,2 which provided indirect support for this hypothesis. An important argument in favor of ∗ This research was supported by Russian Academy of Sciences under Programs 9 and 18, and by RFBR grant 06-05-64308.

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the isochemical character of the rock-iron components of the Galilean satellites can be obtained from the construction of a model of the satellites with identical bulk composition of their rock-iron cores. This problem is addressed in detail in this paper. 2. Geophysical and Geochemical Similarity Assumptions Let us consider a model of the satellites consisting of a water–ice shell, the thickness of which varies from zero for Io to HIce for Europa and Ganymede, and a rock-iron (Fe–Si) core. Using the equations for the mass and moment of inertia of ice-free Io and water-ice-bearing Europa and Ganymede3 and the equations of state for water and high-pressure ices,4 the density (ρCor ) and normalized moment of inertia (ICor ) of the rock-iron cores of Europa and Ganymede can be determined as functions of the thickness of the outer shell (HIce )5 (Fig. 1). It can be seen that, at certain HIce values, the curves ρCor = ρCor (HIce ) E and ICor = ICor (HIce ) for Europa (HIce ∼ 107–115 km) and Ganymede G (HIce ∼ 870 km) pass close to the parameters of Io (IIo = 0.37824 ± 0.00022 and ρIo = 3.5275 ± 0.0029 g/cm3 ,3 ). This means that the average densities and moments of inertia of the rock-iron cores of Europa and Ganymede can be identical or similar to the parameters of ice-free Io. The question is whether this coincidence is accidental or related to the compositions and properties of materials composing the satellites. Let us derive the dependency of the moment of inertia of a rockiron core on its density, ICor = ICor (ρCor ). Varying the thickness of

0.36

0.35

0

40

80

3.2

120

Thickness of Europa’s ice shell, km

3.0 160

Moment of inertia of Io

0.38

3.6 Density of Io

3.4

0.36

0.34

0.32 600

700

800

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Density, g/cm 3

3.4

3.8

Shell thickness

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Density, g /cm 3

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Moment of inertia of Io

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Moment of inertia of rock-iron core

Density of Io

Shell thickness

Moment of inertia of rock-iron core

0.39

0.34

0.40

3.8

0.40

3.0

900

2.8 1000

Thickness of Ganymede’s ice shell, km

Fig. 1. Moment of inertia (dashed line) and average density (solid line) of the rock-iron cores of Europa and Ganymede as functions of the thickness of the ice shell, HIce .

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Moment of inertia of rock-iron core

Moment of inertia of rock-iron core

0.39 0.42 Ga nymede

0.40

0.38

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0.34 3.10

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3.50

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Average density of rock-iron core, g/cm3

Europa

0.38

0.37

0.36

0.35 3.00

3.20

3.40

3.60

Average density of rock-iron core, g/cm3

Fig. 2. Moments of inertia and average densities of the rock-iron cores of Europa and Ganymede at various values of the total moment of inertia of the satellites. The cross indicates the parameters of Io.3 Europa: the solid line corresponds to the experimental value of the moment of inertia of Europa, I = 0.346 [3]; the dashed line, I = 0.351; the dash–dot line, I = 0.341. Ganymede: the solid line corresponds to the experimental value of the moment of inertia of Ganymede, I = 0.3115 [3]; the dashed line, I = 0.3143; the dash–dot line, I = 0.3087. It can be seen that the solid lines pass near the point of Io.

the water–ice shell, we obtain a single curve, ICor = ICor (ρCor ), for the experimental values of moment and density of satellite (ISat , ρSat ) (Fig. 2). Therefore, the existence of a point in which the moment of inertia and density of Io3 coincide with those of the rock-iron cores of Europa and Ganymede is possible only under certain values of the moment of inertia and density of Europa and Ganymede. If the moments of inertia of Europa and Ganymede were diﬀerent from the measured values, the functions ICor = ICor (ρCor ) for these satellites would not pass near the point corresponding to the properties of Io, (Fig. 2). Thus, the relationships shown in Fig. 2 demonstrate that the coincidence of ICor and ρCor values for the three bodies is not accidental and must be related to the compositions and properties of the Fe–Si cores of the satellites. In such a case, the following similarity conditions must hold: E G ICor = ICor = IIo , G ρE Cor = ρCor = ρIo .

(1)

Similarity conditions (1) allow us to make important conclusions on the distribution of density in the interiors of the satellites. The analysis of Eqs.

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(1) provides the following possible law of density distribution in the interiors of the satellites: o G o o ρE Cor (r ) = ρCor (r ) = ρIo (r ),

ro = (r/RCor )

(2)

The moments of inertia and densities of the rock iron cores of the three satellites are equal, if the values of density in the Fe–Si cores are identical at a given value of the reduced radius ro . Let us consider a two-layer model for a satellite consisting of a central Fe–FeS core and silicate mantle with a constant density in each layer. Under a given Fe–FeS core density, only two variables must be determined from the system of equations for the mass and moment of inertia of the satellite: the density of the mantle and the radius of the Fe–FeS core. If the moments of inertia and densities of the rock-iron cores of the three satellites are equal, Eqs. (2) imply the identity of mantle densities (ρMan ) and dimensionless radii r0 at the core–mantle boundary: G Io ρE Man = ρMan = ρMan o G o Io (ro )E Cor = (r )Cor = (r ) ,

(3)

where ro = RFe–FeS /RCor , and RFe–FeS is the radius of the central Fe–FeS core. For the models of satellites with identical densities of Fe–FeS cores, Eqs. (3) imply the identity of the mass ratios of the Fe–FeS core to the whole rock-iron core (i.e. to the mass of silicate crust + mantle + Fe–FeS core): E E G G Io Io MFe –FeS /MCor = MFe–FeS /MCor = MFe–FeS /M

(4)

It was previously shown that the mantle density of Moon-sized satellites weakly changes with depth, because the eﬀects of pressure and temperature on the current values of density largely cancel out.6 Variations in the density of the core from the troilite composition to pure iron from 4.7 to 8.0 g/cm3 also exert a negligible inﬂuence on the distribution of density in the mantle of the satellites.7 Therefore, as a ﬁrst approximation, the density of the mantle of the satellites can be estimated from two-layer models. In such a case, the conditions of similarity Eqs. (1) are equivalent for satisfying conditions (3, 4). Kuskov and Kronrod7,8 showed that the composition of the silicate mantle could be estimated from density distribution. Therefore, given the equality of the average densities of the mantles of Io, Europa, and Ganymede, it can be supposed that the compositions of the silicate mantles

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of the three satellites are identical. The isochemical character of mantle materials yield the following geochemical similarity conditions: E (F etot /Si)G Cor = (F etot /Si)Cor = (F etot /Si)Io G E Io F eOSil = F eOSil = F eOSil

(F em /F etot )G Cor

=

(F em /F etot )E Cor

(5)

= (F em /F etot )Io

where (Fetot /Si)Cor is the mass ratio of total iron to silicon in the rock-iron core of the satellite; FeOSil is the mass concentration of FeO in the silicate crust and mantle, and (Fem /Fetot )Cor is the mass ratio of the abundance of metallic iron (Fem ) in the central Fe–FeS core to the bulk content of iron in the whole Fe–Si core of the satellite. Thus, we obtained geophysical (1-4) and geochemical (5) similarity conditions for the internal structures of Io and the Fe–Si cores of Europa and Ganymede. In fact, there is no exact coincidence of the moments of inertia and densities of the rock-iron cores of Europa and Ganymede and the parameters of Io (Figs. 1, 2). The observed discrepancies can be attributed to diﬀerences in the distribution of temperature and pressure in the interiors of the satellites. It is reasonable to expect that accounting for the eﬀects of compressibility and thermal expansion will provide more accurate parameters for the Fe–Si cores and the thicknesses of the water–ice shells of Europa and Ganymede. 3. Formulation of the Problem, Input Data, and Method of Solution Similar conditions (1) and (5) for the internal structures of Io and the Fe–Si cores of Europa and Ganymede imply identical chemical compositions of the rock-iron constituents of the three satellites. In order to test the isochemical hypothesis, we constructed models for the satellites compatible with the main geophysical (mass and moment of inertia) and geochemical constraints (composition of the mantle and metallic Fe–FeS) and minimizing the deviation of the solutions from the similarity conditions. The value of the observed moment of inertia factor has been calculated under the assumption that the satellites are in hydrostatic equilibrium, which may not be true for Ganymede.3 The spherical symmetry and thermal equilibrium was assumed for the satellites. The chemical compositions and physical properties of the satellites can be further constrained using the compositions of the silicate fraction of

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ordinary (H, L, and LL) and carbonaceous (CI, CM, and CV) chondrites. That is, the composition of the Fe–Si cores is constrained to lie between those of reduced Hchondrites and oxidized C chondrites. The chemical composition of the silicate fraction of the Fe–Si cores was determined in the course of the solution. The composition of chondrites was taken from9 and recalculated to the volatile-free Na2 O–TiO2 –CaO–FeO–MgO–Al2O3 – SiO2 –Fe–FeS system (NaTiCFMAS–Fe–FeS). The presence of metallic cores suggests that the interiors of the satellites were heated to high temperatures suﬃcient for the dehydration of water-bearing minerals. With this in mind, we assumed that the mantles of three satellites (Io, Europa, and Ganymede) consist of dehydrated silicates. The simulation of the chemical and mineral compositions of the mantles of these satellites was performed for the “dry” NaTiCFMAS-Fe–FeS system free of water and other volatiles. Equilibrium phase assemblages were calculated by Gibbs free energy minimization using the THERMOSEISM program package and database.8 The database includes the mutually consistent thermodynamic properties of minerals and their equations of state in the Mie–Gr¨ uneisen–Debye approximation. The errors in the density of phase associations were usually not higher than 1%. We assume that all metal and troilite present in the chondritic mantle migrate to form a core. Sulfur is one of the most important minor elements in the compositions of the metallic Fe–Ni–S cores of planetary bodies. Since iron is present in meteorites both as metal and as FeS, Kuskov and Kronrod7,8,10 considered various models of the composition of satellite cores, from pure iron to troilite. They showed that the suggestion that Io’s core consists of troilite (FeS) and has a mass of 18–20% is not consistent with any meteorite composition.7,10 The eutectic Fe–FeS composition also contains excess sulfur compared with chondrites. For this reason, we accepted a model of the satellites with a central Fe–10% S core containing 10 wt% S (Fe0.84 S0.16 ) with ρ = 5.7 g/cm3 at 50 kbar and 1500◦C.11 Models of Europa and Ganymede consist of an outer H2 O shell, a silicate crust, a mantle, and a Fe–10% S core.8,12 In our model, the thickness of the ice shell of Europa was taken to be 10 km, and it is underlain by the ocean extending to the boundary with the crust. Two models were considered for the composition of Ganymede’s outer shell8,12 : (1) polymorphous modiﬁcations of ice, and (2) a layer of ice-I (40–140 km thick) underlain by a liquid water layer. By analogy with other planetary bodies (e.g. the Earth and Moon), the appearance of a light crust is expected during the diﬀerentiation of

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the satellites. The density of Europa’s crust was taken to be 2.7 g/cm3 on the surface and 3.0 g/cm3 at the crust–mantle boundary with a linear dependency on the depth. Similar density distribution was accepted for Ganymede’s crust with a small correction for pressure due to the overlying ice shell. The thickness of the crust was a ﬁtted parameter calculated from relationships (1) and (5). The physical properties and phase state of the outer shells of Europa and Ganymede are controlled by phase equilibria in the H2 O system, including water, ice-I, and high-pressure ice modiﬁcations.4,13,14 The densities of H2 O phases were adopted from15 in accordance with the phase diagram of H2 O. Note that the thicknesses of the outer shells of Europa and Ganymede and their silicate crusts were determined from conditions (1) and (5). The distribution of temperature is assigned using the simpliﬁed thermal models of Jupiter’s satellites. It is assumed that uncertainties in the model of the temperature ﬁeld have a negligible inﬂuence on the main calculated parameter of the model, the distribution of density in the mantle.6 A surface temperature of T0 = 130 K was taken for the satellites.13 Conductive heat transfer and linear temperature variations were assumed for the ice cover from the surface to a depth of 10 km. Convective heat transfer14 and adiabatic temperature distribution was taken for the ocean and ice shell of Ganymede. The silicate crust of Europa and Ganymede is characterized by linear temperature variations. The temperature at the crust–mantle boundary (TCr−M ) was determined from conditions (1) and (5). Assuming an enrichment of radioactive elements in the material of the Galilean satellites, similar to meteoritic abundances, it is reasonable to suppose that heat transfer in the mantle of the rockiron cores of the satellites is similar to that operating in the Moon, i.e. via the conductive mechanism.3 It was previously shown6 that, within each zone of the lunar mantle, the density proﬁle is almost invariant with depth, i.e. the temperature proﬁle in the lunar mantle is such that the temperature- and pressure related variations in density tend to cancel each other. Based on such an analogy, a temperature proﬁles are constructed for the mantle of Europa (T E ) and Ganymede (T G ), providing the minimum density gradient with depth under the condition dρ/dH > 0 and then have been ﬁxed. The temperature proﬁle in the Fe–10% S cores is taken to be adiabatic. Based on the above assumptions, the temperature variations in the rock-iron cores of Europa and Ganymede were approximated by the

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following expressions: S + T S (Ho ), T S (Ho ) = TCr−M S S S Ho = (H − HCr )/(RCor − HCr ),

S = E, G,

(6)

where HCr is the thickness of the crust, TCr−M is the temperature at the crust–mantle boundary determined from the solution. Our model for Io consists of a thin solid crust, a partially molten asthenosphere, a solid mantle, and a Fe–10% S core.8,16 The thickness of the outer shell is determined by calculations, with the density of the solid crust, 1.5 km thick, taken as 2.15 g/cm3 . The density of the asthenosphere varies from 2.2 g/cm3 at the boundary with the solid crust to 3.25 g/cm3 at the boundary with the mantle.16 Based on a model of convective solidstate heat transfer, adiabatic temperature proﬁles were also assumed for the mantle and Fe–10% S core. The unknown parameter is the temperature at the mantle–asthenosphere boundary, which is calculated from conditions (1, 5). Models for the internal structure of the satellites are described by the system of the equations, including equations for the moment of inertia and mass, equations for the determination dependence of pressure and of gravity acceleration on radius in a hydrostatic equilibrium approximation and equation of state for the determination of the density of material in the ice shell, silicate mantle and rock-iron core. The goal of the numerical simulation was to determine using conditions (1, 5) the thickness of the water–ice shells, HIce ; the crust thickness, HCr ; the temperature at the upper boundary of the mantle, TCr−M and TA−M (crust–mantle boundary for Europa and Ganymede and the asthenosphere– mantle boundary for Io); the density of mantle and core material; and the sizes of the metallic Fe–10% S cores. The calculation procedure of the desired parameters can be divided into two stages. During the ﬁrst stage, the distribution of density in the mantle and Fe–10% S core, the radius of the Fe–10% S core, and all the parameters from similarity conditions (1, 5) were determined for the three satellites from the thickness of the water–ice shell (HIce ), the thickness of the silicate crust (HCr ) for Europa and Ganymede, the thickness of the crust + asthenosphere layer (HA−M ) for Io, and the temperature at the upper boundary of the mantle (TCr−M and TA−M ). Then, using the obtained values, the input parameters (HIce , HCr , TCr−M and TA−M ) were reﬁned, and the procedure was repeated until the similar conditions were satisﬁed to the desired

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accuracy. In order to solve the system of the equations at the ﬁrst step, we developed a rapidly converging iteration procedure accounting for the speciﬁc features of the simulated object. The distribution of density is constrained to be free of inversions with depth.5 4. The Internal Structure of the Satellites Under Isochemical Conditions The main result of our study is the possibility of constructing the satellite models satisfying the conditions of geochemical similarity of Io and the rockiron cores of Europa and Ganymede. The distribution of P , T , ρ, thicknesses of the water–ice shells and crust, and the geochemical constraints on the bulk compositions of the satellites were also determined (Tables 1 and 2). Table 1.

Physical parameters and internal structures of the Jupiter’s satellites.

Parameter I/M R2 ρ, g/cm3 RSat , km RCor , km RFe−10% S , km MFe−10% S /MSat , % MFe−10% S /MCor , % MCor /MSat MIce /MSat HIce , km (Fetot /Si)Cor PM −Cor , kbar P0 , kbar TM TM −Cor

Io

Europa

Ganymede

parameters3

Geophysical 0.37824 ± 0.00022 3.5275 ± 0.0029 1821.6 ± 0.5

0.346 ± 0.005 2.989 ± 0.046 1565 ± 8.0

Calculated parameters 1821.3 1445 737 576 10.91 9.52 10.91 10.25 1 0.929 0 0.071 0 120 1.00 0.97 58.5 36 79.7 49 1200 570 1304 1293

0.3115 ± 0.0028 1.942 ± 0.0048 2631.2 ± 1.7 1734 695 5.52 10.48 0.533 0.47 900 0.99 73 93.4 500 1310

Note: RSat , ρ, and I/M R2 are the radius, average density, and dimensionless moment of inertia of the satellite; RCor is the radius of the rock-iron core; RFe−10% S is the radius of the central core; MFe10% S /MSat is the ratio of the mass of the central Fe–10% S core to the total mass of the satellite; MFe−10% S /MCor is the ratio of the mass of the central Fe–10% S core to the mass of the rock-iron core; HIce is the thickness of the outer shell (water–ice for Europa and ice for Ganymede); MIce /MSat is the mass fraction of ice; (Fetot /Si)Cor is the mass ratio of total iron to silicon in the rock-iron core; PM −Cor is the pressure at the boundary between the mantle and Fe–10% S core; and P0 is the pressure in the center of the satellite. TM is the temperature at the upper boundary of the mantle, TM −Cor is the temperature at the mantle–core boundary.

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Table 2. Geochemical parameters of Jupiter’s satellites calculated from the conditions of the similarity of the internal structures of their rock-iron cores compared with the materials of ordinary chondrites. Parameter

Io

Hcrust , km 70 (Fetot /Si)Cor 1.00 (Fe/Si)Sil 0.534 (FeO)Sil , wt.% 16.1 9.82 Fem , wt.% Fem /Fetot 0.47 3.386 ρsil , g/cm3 ρCor , g/cm3 3.543

Europa

Ganymede

50 0.97 0.531 16.04 9.22 0.45 3.389 3.532

55 0.99 0.539 16.28 9.43 0.45 3.385 3.540

Average

LL

0.035 RCor 0.986 1.03 ± 0.04 0.534 0.714 16.14 19.66 9.49 6.33 ± 2.27 0.46 0.31 ± 0.1 3.387 3.431 3.538

L 1.18 ± 0.06 0.607 17.20 11.04 ± 1.46 0.49 ± 0.05 3.396

Note: Hcrust is the thickness of the silicate crust for Europa and Ganymede and the thickness of the crust + asthenosphere layer for Io; (Fetot /Si)Cor is the total iron to silicon mass ratio in chondrites and the rock-iron cores of the satellites; (FeO)Sil and (Fe/Si)Sil are the concentrations of FeO and Fe/Si mass ratio in the silicate fractions of the Fe-Si cores of the satellites and chondrites; Fem is the mass percent of metallic iron in the central Fe–10% S core relative to the total mass of the rock-iron core of the satellites and the abundance of metallic iron in chondrites calculated as Fem = Feom + Fem from FeS19 ; (Fem /Fetot ) is the mass fraction of metallic iron in chondrites19 and the central Fe–10% S cores relative to the total amount of iron in the satellites; ρSil and ρCor are the densities of the silicate fraction of the rock-iron cores of the satellites and chondrites, and the average density of the rock-iron cores recalculated to P = 20 kbar and T = 1000◦ C.

4.1. Io The thickness of the crust+asthenosphere system is ∼70 km. It is underlain by the silicate mantle and the Fe–10% S core with a radius of 737 km. The temperature varies from 1200◦C at the asthenosphere–mantle boundary to 1304◦ C at the mantle–core boundary. The density of the isochemical mantle increases monotonously from 3.392 g/cm3 at the upper boundary to 3.570 g/cm3 at the core–mantle boundary (Fig. 3). 4.2. Europa Europa has a water–ice shell with a thickness of 120 km (7 wt % H2 O of total mass), which is in agreement with our previous calculations.8,19 The thickness of the silicate crust is 50 km, and the radius of the Fe– 10% S core is 576 km. The temperature of the upper shells of Europa’s mantle is signiﬁcantly lower than that of Io. The temperature at the crust– mantle boundary is ∼570◦ C, and at the core–mantle boundary is ∼1293◦C. The density of the mantle is practically constant and ranges within 3.453– 3.463 g/cm3 .

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6

Density, g/cm3

To ,Ñ

1200

1000

800

5

4

600

400 0.0

0.2

0.4

0.6

0.8

(H-H0)/(RCor-H0)

1.0

3 0.0

0.2

0.4

0.6

0.8

1.0

(H-H0)/(RCor-H0)

Fig. 3. Distribution of temperature and density in the mantle and metallic Fe–10% S cores of Io (solid line), Europa (dash–dot line), and Ganymede (dashed line). H is the distance from the surface of the rock-iron core; H0 is the thickness of the silicate crust of Europa and Ganymede and the thickness of the crust + asthenosphere layer for Io, and RCor is the radius of the rock-iron core.

4.3. Ganymede Two models were considered for Ganymede. For the model without an ocean, the thickness of the ice shell is 900 km (47 wt % H2 O of total mass). For the model with an ocean, the conditions of similarity are satisﬁed only if its thickness is no more than 40–50 km, and the thickness of the ice-I cover is 130–140 km, which is in agreement with the data of.18 The total thickness of the water–ice shell of the satellite approaches to 900 km, which is consistent with the results of.8 The thickness of the silicate crust is 55 km. The radius of the Fe–10% S core is 695 km, which is 42 km smaller than the radius of Io’s core. The radius of the rockiron core of Ganymede is almost a twin of Io and diﬀers from the latter mainly in temperature distribution within the crust and mantle. The temperature proﬁle of the rock-iron core of Ganymede is very similar to that of Europa. Similar to Europa, the density is almost independent of depth. 4.4. Geochemical parameters The geochemical characteristics of Io and the rock iron cores of Europa and Ganymede are given in Table 2. The maximum diﬀerence from the average values (arithmetic mean) of geochemical parameters was obtained within

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1.5–2%. It can be concluded that the misﬁt in the similarity conditions given by Eq. (5) is not higher than 2%.

5. Discussion The physical and chemical parameters of the models of the composition and internal structure of the jovian satellites (Io, Europa and Ganymede) are investigated. Our study shows that equality of the moments of inertia and density of the Galilean satellites without ice layer is not casually. We have been formulated similarity conditions for Fe–Si cores and demonstrated that the coincidence of ICor and ρCor values for Io, Europa and Ganymede must result from the identical chemical composition of the Fe–Si cores of the satellites. The similarity conditions make it possible the estimates of the sizes of the satellites’ cores and the thicknesses of the ice–water shells of Europa (120 km) and Ganymede (900 km), as well as the distribution of density in the mantle and other geophysical and geochemical parameters for the three satellites (Tables 1 and 2). The ratios of the radii and masses of the Fe–S cores and rock-iron cores of Io, Ganymede, and Europa are identical: R(Fe–10% S-core)/RCor = 0.4 and M (Fe-10% S-core)/MCor = 10.55 wt%. The silicate fraction of the satellites contains about 16 wt% FeO and shows an Fe/Si mass ratio of 0.53. The total iron to silicon mass ratio is also identical in the three satellites: (Fetot /Si)Cor = 0.99. The main source of error in the solution is the uncertainty in core composition and the real distribution of temperature in the interiors of the satellites. An increase in the abundance of iron in the central Fe–S core results in a smaller and less massive core and a lower (Fetot /Si) value of the satellite.8 However, the maximum diﬀerence between the (Fetot /Si) values of Io’s core for pure Fe and Fe–FeS eutectic compositions is less than 10%. The variant used in this study is intermediate in iron content. Therefore, the error in the (Fetot /Si)Sat estimate must be lower than 5%. The main uncertainty in the distribution of temperature is related to the choice of the mass transfer mechanism in the mantle, either conductive or convective. In this study, the choice of a heat transfer mechanism was based not only on a priori information, but also on the results of numerical experiments. For instance, the conductive mechanism in the mantles of the three satellites, including Io, did not satisfy similarity conditions (5). After a series of preliminary calculations, we selected the conductive mechanism for the mantle of Europa and Ganymede and the convective mechanism for the mantle of Io.

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Taking into account the uncertainties in the problem formulation and numerical experiments, it can be concluded that the condition of identical bulk composition of the rock-iron cores is satisﬁed, if the material of the satellites is similar in composition to L/LL chondrites (Table 2). The (Fetot /Si)Cor ratio of the satellites is considerably lower than that of H ordinary chondrites (1.6) and CI (1.73), CM (1.6), and CV (1.48) carbonaceous chondrites. The element ratios and the masses of the Fe–10% S cores of the satellites (10.5 wt%) are in agreement with the bulk compositions and abundance of iron-sulﬁde phases in L chondrites (7.03 ± 0.95 wt % Fe and 5.76 ± 0.8 wt % FeS9 ). The abundance of metal in LL chondrites is signiﬁcantly lower (2.44 ± 1.6% Fe9 ), although the content of FeS (5.79 ± 0.1%) is similar to those of L chondrites and the Fe–S cores of the satellites. In contrast, CI, CM, and CV carbonaceous chondrites are essentially free of metallic iron; they are more oxidized than ordinary chondrites and contain 4–7 wt % FeS and negligible amounts of Fem . These results supplement our previous estimates of the L/LL chondritic composition of Io, Europa, and Ganymede.1,8,19 In contrast to the previous studies, this paper reports the determination of the bulk composition of the satellites satisfying the condition of their isochemical character; moreover, we attempted to demonstrate that the equality of the chemical compositions of Io, Europa, and Ganymede must result from the moment of inertia and density estimates for the satellites. Sohl et al.12 estimated the Fetot /Si ratio of the Galilean satellites. These authors obtained an increase in Fetot /Si with increasing distance from Jupiter: from 0.7–1.6 for Io and Europa to 2–5 for Ganymede. These estimates are not consistent with our models of the Galilean satellites. Both Europa and Ganymede have probably thick water layers and relatively small cores. The source of the magnetic ﬁeld of the Galilean satellites3 is still unknown and can be related to convective motions either in the partially molten core or in seawater. Such a dichotomy can be preliminarily accepted both for the induced ﬁeld of Europa and for the intrinsic ﬁeld of Ganymede. It was demonstrated17,20 that both the one-layer model of Callisto with constant ice concentration from its surface to the center and the two-layer model of the satellite diﬀerentiated into the ice shell and rock–iron core are not realistic. Hence the similarity condition for Callisto is unsuitable. By analogy we may allow L/LL chondritic composition of Callisto.17,20 Figure 4 illustrates the general trend of a decrease in the Fetot /Si ratio with increasing heliocentric distance from Mercury to the Jovian satellites.

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Mercury

Fe/Si, mass

8

6

Venus

4

Earth 2

0

Galilean satellites

Mars Moon 0

2

4

6

Heliocentric distance, AU Fig. 4. Simplified dependency of the Fetot /Si ratio in planets and satellites on their heliocentric distance according to6,21,22 and present paper.

The abundance of ice increases with increasing distance from Jupiter from 0 in ice-free Io to 7% in Europa, and to 47% in Ganymede and 49–55% in Callisto.8,17,20 Io, Europa, and Ganymede could be formed in the accretion disk of Jupiter from a material similar to L/LL chondrites under relatively low temperatures, not higher than the evaporation temperature of Fe and Fe–Mg silicates. 6. Conclusion We have investigated a hypothesis of isochemical composition of Io and rock-iron cores (without ice layer) of Europa and Ganymede. The models of the composition and internal structure of the jovian satellites were constructed using the geophysical constraints obtained by the Galileo mission on the mass, average density, and moment of inertia, geochemical data on the composition of meteorites, and thermodynamic data and equations of the state of water, high-pressure ices, and chondritic materials. The main conclusions are the following. 1. The results of modelling support the hypothesis that Galilean satellites can have identical compositions. 2. The coincidence of the moments of inertia and density for Io and rockiron cores of Europa and Ganymede is not accidental and must be related to the compositions and properties of the rock-iron cores of the satellites.

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3. The compositions of Io, Europa and Ganymede (silicate fraction and bulk) may be described by material approaching the L/LL type chondrites. 4. Rock-iron material forming the Galilean satellites may reﬂect the chemical composition of the solar nebula at the radial distance of Jupiter. References 1. O. L. Kuskov and V. A. Kronrod, Solar Syst. Res. 32 (1998) 42–50. 2. O. L. Kuskov and V. A. Kronrod, Geochem. Int. 35 (1997) 849–853. 3. G. Schubert, J. D. Anderson, T. Spohn and W. B. McKinnon in Jupiter: The Planet, Satellites and Magnetosphere. Ed. By F. Bagenal et al. Cambridge University Press (2004), pp. 281–306. 4. V. A. Kronrod and O. L. Kuskov, Geochem. Int. 41 (2003) 881–896. 5. V. A. Kronrod and O. L. Kuskov, Geochem. Int. 44 (2006) 529–546. 6. O. L. Kuskov and V. A. Kronrod, Phys. Earth Planet. Inter. 107 (1998) 285–306. 7. O. L. Kuskov and V. A. Kronrod, Solar Syst. Res. 35 (2001) 198–208. 8. O. L. Kuskov and V. A. Kronrod, Icarus. 151 (2001) 204–227. 9. E. Jarosewich, Meteoritics 25 (1990) 323–337. 10. O. L. Kuskov and V. A. Kronrod, Planet. Space Sci. 48 (2000) 717–726. 11. P. S. Balog, R. A. Secco, B. C. Rubie and D. J. Frost, J. Geophys. Res. 108 (2003) 2124. 12. F. Sohl, T. Spohn, D. Breuer and K. Nagel, Icarus 157 (2002) 104–119. 13. W. B. McKinnon, in Solar System Ices, Ed. by B. Schmitt et al. Kluwer, Dordrecht (1998), pp. 525–550. 14. F. Deschamps and C. Sotin, J. Geophys. Res. 106 (2001) 5107–5121. 15. M. J. Lupo and J. S. Lewis, Icarus 40 (1979) 157–170. 16. G. Leone and L. Wilson, J. Geophys. Res. 106 (2001) 32 983–32 995. 17. O. L. Kuskov and V. A. Kronrod, Icarus 177 (2005) 550–569. 18. T. Spohn and G. Schubert, Icarus 161 (2002) 456–467. 19. O. L. Kuskov and V. A. Kronrod, Geochem. Int. 41 (2003) 984–1001. 20. V. A. Kronrod and O. L. Kuskov, Geochem. Int. 43 (2005) 315–327. 21. A. E. Ringwood, Origin of the Earth and Moon, New York: Springer (1979), p. 295. 22. S. R. Taylor,Solar System Evolution: A New Perspective. Cambridge: Cambridge Univ. Press (2001), p. 460.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

INTERNAL STRUCTURE OF THE ICY SATELLITES OF JUPITER∗

O. L. KUSKOV† , V. A. KRONROD‡ and A. P. ZHIDIKOVA V.I. Vernadsky Institute of Geochemistry and Analytical Chemistry, Russian Academy of Sciences, Kosygin Str. 19, 119991 Moscow, Russia † [email protected] ‡ va [email protected]

Models of the internal structure of completely diﬀerentiated Europa and Ganymede, and partially diﬀerentiated Callisto have been constructed on the basis of Galileo gravity measurements, geochemical constraints on composition of ordinary and carbonaceous chondrites, and thermodynamic data on the equations of state of water, high-pressure ices, and meteoritic material. Geophysically and geochemically permissible thicknesses of outer water-ice shells of the icy satellites are determined. The allowed total thicknesses of an outer water-ice shell are in the range of 105–145 km for Europa, 780–940 km for Ganymede and 270–315 km for Callisto. The correspondence between the density and moment of inertia values for the rock-iron cores of Europa, Ganymede and Callisto shows that their bulk ice-free compositions may be, in general, similar and may be described by the isochemical composition close to a material of the L/LL type chondrites.

1. Introduction The Jovian system, which is regarded as a miniature model of the Solar system, includes four Galilean moons: Io, Europa, Ganymede, and Callisto and smaller satellites. The investigation of the outer parts of the Solar system was started by the spacecrafts of the Pioneer and Voyager series. The unique data obtained during Galileo ﬂybys gave rise to a number of intriguing discoveries and sensational reports on the tectonic, volcanic, and cryovolcanic activity of the Galilean satellites and possible existence of metallic cores and subsurface oceans which led to a revision and signiﬁcant addition of many early concepts on the internal structure and thermal ∗ This

research was supported by Russian Academy of Sciences under Programs 9 and 18, and by RFBR grant (06-05-64308). 365

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evolution of jovian moons.1−11 The characteristic feature of the icy satellites is the probable presence of liquid water beneath the outer ice crust, which gave rise to attractive hypothesis on the existence of extraterrestrial forms of primitive life. The thickness of these water layers could range from tens to hundreds of kilometers. There is only the limited number of quantitative studies of Europa’s, Ganymede’s and Callisto’s interior compositions. In the previous papers6,7 we have proposed an approach to the solution of the problem of modeling the constitution of the Galilean satellites which consists in estimating the chemical composition of the mantle, determining the radius of a core and assessing the internal density distribution from the geophysical observations (inverse modeling). The proposed approach integrates the geophysical (the mass and moment of inertia) and geochemical (composition of meteorites) constraints. Here, taking into account ordinary and carbonaceous chondrites as representatives of nebula matter and the more reliable estimates of moment-of-inertia factors (MOI), we also concentrate of assessing various geochemical parameters of the satellites. The phase diagram of H2 O and equations of state of high-pressure ices and meteoritic matter are taken into account. The general methodology is to combine the geophysical and geochemical constraints and thermodynamic approach, and to develop, on this joint basis, the self-consistent models of icy satellites, accounting for their composition and internal structure. 2. Formulation of the Problem 2.1. The model and geophysical constraints The problem of modeling the internal structure of a satellite is described by a system of equations specifying the conditions of thermodynamic and hydrostatic equilibrium, equations of state of phases, equations of heat transfer by heat conduction, and mass and moment conservation.6,7 The mass, average density and moment of inertia are used as input data (Table 1) for determination of (1) the thickness and phase state of an outer water-ice shell, (2) the density distribution with depth, and (3) the core sizes and masses. 2.2. Geochemical constraints Additional geochemical limits on mantle density (and indirectly on the temperature) are introduced from the density of the equilibrium phase

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Physical characteristics of the satellites.5−8

Satellite Europa Ganymede Callisto

ρ, kg m−3

I/MR2

RSat , km

2989 ± 46 1936 ± 22 1834.4 ± 3.4

0.346 ± 0.005 0.3105 ± 0.0028 0.3549 ± 0.0042

1565.0 2634.0 2410.3

assemblages (phase diagrams) calculated from the composition of silicate fraction of ordinary (H, L and LL) and carbonaceous (minus volatiles) chondrites. The mantle densities varied within the density continuum in the range of 3,320–3,670 kg m−3 , encompassing the possible density variations of mineral assemblages of the silicate fraction of chondrites at 0.2–4 GPa and 300–1,400◦C.6 2.3. Thermodynamic constraints The phase compositions and mantle densities are modeled within the system Na2 O-TiO2 -CaO-FeO-MgO-Al2O3 -SiO2 including the solid solution phases (olivine, spinel, ilmenite, garnet, orthopyroxene, and clinopyroxene). The equilibrium phase assemblages were calculated using the technique of free energy minimization; the equations of state of minerals were calculated in the Mie-Gr¨ uneisen-Debye approximation.6 The software package includes a series of computer codes for both forward and backward solutions. The former calculates the equilibrium phase assemblages, their physical properties, and moment-of-inertia factor for a planetary body of known composition, size, and mean density. The latter computes admissible density distributions, core radii, and compositional parameters of a planetary body with known geodetic characteristics. By applying suitable thermodynamic models for the equation of state of minerals and solid solutions and the technique of free energy minimization, the equilibrium phase assemblages and density proﬁles are derived entirely from an internally consistent model, with only thermodynamic data and bulk composition as input. 2.4. Model of a core The abundance of metallic iron is highly variable in diﬀerent kinds of chondrites. Since ordinary chondrites are the most metal-rich among chondrites and contain about 6 wt% FeS while carbonaceous chondrites contain a signiﬁcant amount of FeS and practically no iron in metal form, three-boundary models are considered for a satellite core: a Fe-10 wt%S core for ordinary chondrites, a eutectic Fe-FeS and an FeS core for ordinary

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and carbonaceous chondrites. The density of 5,700 kg m−3 is adopted for an Fe-10 wt%S alloy at 5 GPa and 1,500◦C; ρ = 4,700 and ρ = 5,150 kg m−3 are adopted for a central FeS core and for a eutectic Fe-FeS.6,7 2.5. Water-ice shell The phase state of the outer shell of the icy satellites depends on the thermal evolution, ice rheology, presence of volatiles and salts, and heat transfer mechanisms.1,4,11 Because the compositions and temperatures of the liquid phase of the satellites are poorly known and theoretical evaluations of salinity of oceanic water from Galileo magnetometer data are problematic, the physical properties and phase state of the outer shell were approximated by the single component (H2 O) multi-phase system water + high-pressure ices. The densities of liquid and high-pressure ices were calculated by the equations of state in accordance with the phase diagram of H2 O.10−12 3. Europa Geophysical and geochemical constraints are used to model the internal structure of Europa for three ﬁrst-order parameters (none of which is known): (1) the thickness of an outer water-ice shell; (2) the chemical composition (the ratio of total iron to silicon, Fetot /Si, and metallic iron content); (3) the core sizes and masses. Numerical solutions correspond to diﬀerentiated Europa models with the outer water-ice shell, chondritic mantle and central Fe-FeS core. The central pressure and pressure at the core-mantle boundary are found to be close to 5.6 GPa and 4.0 GPa for the Fe-10 wt%S core, and 4.8 GPa and 3.5 GPa, respectively, for the FeS core. The results show that Europa is diﬀerentiated into a water-ice shell, anhydrous mantle and iron-sulﬁde core.7 Both L/LL and CM chondrite compositions match the total mass and moment of inertia value of Europa and can be regarded either as the primary material of Europa (Cchondrites) or as a reasonable analogue for its anhydrous rock-iron core (ordinary chondrites). Within these models, the permissible thickness of Europa’s water-ice shell lies between 105 and 160 km (6.2–9.2% of total mass) for any model of diﬀerentiated or undiﬀerentiated chondritic mantle. The amounts of Fe and FeS, and the Fetot /Si ratio of Europa’s rockiron core are not consistent with the bulk compositions of the most oxidized CI chondrites and the most reduced H chondrites. It is likely that

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800 Chondritic models of Europa

700 Fe-FeS-core radius

600

500

400 180

H

L

LL

CM

Water-ice thickness

140 100 3.30

3.40

3.50

3.60

3.70

Mantle density, g cm-3 Fig. 1. The eﬀect of the mantle density on the thickness of an outer water-ice shell and core sizes for chondritic models of Europa’s diﬀerentiated (dashed lines) and undiﬀerentiated (solid lines) mantle. For the L/LL chondritic material, the allowed thickness of Europa’s H2 O layer ranges from 105 to 145 km. The highest mantle densities of CM chondrite phase assemblages lead to the largest Hshell values: 125–160 km.

Europa inherited a signiﬁcantly higher proportion of material close to the moderately oxidized L/LL type chondrites rather than to the C-chondrites. Core radii are estimated to be 470–640 km for the L/LL chondritic models with a central Fe-10 wt%S core (5–12.5% of the total mass). The allowed thickness of Europa’s H2 O layer (whether liquid or ice) ranges from 115 ± 10 km (6.8 ± 0.6%) for a diﬀerentiated L/LL-type chondritic mantle with a crust to 135 ± 10 km (7.9 ± 0.5%) for an undiﬀerentiated L/LL chondritic mantle (Fig. 1) in agreement with Schubert et al.11 The problem of the existence of the ocean in the past or present is of fundamental importance for geology of Europa and remains a subject of heated debate. Taking into account competitive factors — solid-state convection promoting freezing of the ocean and tidal heating maintaining the stability of the liquid phase — no deﬁnite conclusion can be obtained on the phase state of Europa’s outer shell.1−5,7,13 Based on the interpretation of Galileo magnetometer data, Zimmer et al.3 concluded that an electrically conductive liquid layer exists beneath the solid ice crust, whose surface bears evidence for the occurrence of resurfacing processes.

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4. Ganymede

Ganymede's Fe-FeS core radius, km

As for Europa, a competing idea is that Ganymede may or may not possess salty liquid-water ocean. We do not consider here the mechanisms of the heat transport, rheological behaviour of ice, and the physical reasons for the existence of a liquid ocean. If the thermochemical evolution of Ganymede’s interior could not keep the temperature of the rock-iron core surface at the melting temperature of the high-pressure ice phases, the liquid ocean would be completely frozen. Two alternative density models of an outer shell are considered (Fig. 2). Model (A) — an outer shell is completely composed of the high-pressure ice phases (no water is present), resulting in a maximum in the density of an outer shell. Model (B) — in the three-layer model of an outer water-ice shell, we assume that below a shell of ice-I (30–120 km thick), a liquid layer of 230–140 km thick may exist, resulting in a minimum density of an outer shell. We adopted a “conductive” model12 where a mixed layer of water and high-pressure polymorphs of ice may coexist at depths between 260 km and an ice-rock interface. Our calculations show that the ice thickness of the outer shell in model (A) is about 880–940 km and in model (B) is 780–850 km. The content of H2 O in Ganymede’s icy envelope is 46–48% of the total mass. The amounts of Fe and FeS, and the Fetot /Si ratio of Ganymede’s diﬀerentiated rock-iron core (anhydrous silicate mantle

1000

A

800

600

400

B

200

0 700

800

900

1000

Thickness of water-ice shell, km

Fig. 2. The eﬀect of total thickness of an outer water-ice shell of Ganymede on radii of the eutectic Fe-FeS core. Model (A): total thickness of an outer solid ice shell is 880– 940 km, Rmax (Fe-FeS core) = 950 km. Model (B): total thickness of a water-ice shell is 780–850 km, Rmax (Fe-FeS core) = 780 km.

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+ Fe-FeS core) are consistent with the bulk compositions of the L and LL chondrites.6 5. Callisto 5.1. Water-ice shell We consider a six-layer model of Callisto consisting of an ice layer, a water ocean, a three-layer ice-rock mantle, and a rock-iron core. The major uncertainty in the internal structure of Callisto is related to the equation of state of rock-iron (Fe-Si) material, because its density can vary from low (hydrous silicates + Fe-FeS alloy) to high values (anhydrous silicates + Fe-FeS alloy). Taking into account the considerations from the previous section and the results from,6,7 we accept that the composition of the rock-iron material of Callisto is similar to the bulk composition of L/LL type chondritic material containing up to 10–15% of iron and iron sulﬁde. The calculated density of such a material is ρ◦ (298 K, 105 Pa) = 3,150– 3,620 kg m−3 . In agreement with conclusions,7,13 the distribution of temperature in Callisto can be calculated from the conditions of conductive transfer in an ice-I layer, and the temperature proﬁle in the stability ﬁelds of water and high-pressure ices goes along the adiabat. The maximum pressure (207 MPa, the melting point of ice-I at the minimum T = 251.1 K) of the existence of a water layer corresponds to a depth of ∼176 km. Heat ﬂow through the crust of such a thickness depends on the surface temperature: ∼2 mW m−2 at T = 130 K and 2.7 mW m−2 at T = 100 K.7 If the heat production in the Callisto interior exceeds a certain value corresponding to a heat ﬂow higher than 2.7 mW m−2 , the possibility of a liquid water layer beneath the ice crust is expected. The expected present-day surface heat ﬂows are estimated as 3.3–3.9 mW m−2 ,14 which suggest the probable occurrence of a liquid phase and the existence of the ocean. The thickness of the water layer under the solid ice crust can be estimated from the phase diagram of H2 O. The intersection of the adiabat with the liquidus line of ice-III or ice-V deﬁnes the pressure and temperature of the lower boundary of the water layer (Fig. 3). 5.2. A model for the interior structure of Callisto with an internal ocean It has been shown that a diﬀerentiated model (like Ganymede) or undiﬀerentiated (homogeneous) model of Callisto does not satisfy the

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Z, km 100

275

200

300

400

270

water

T, K

265

H(ice)=135 km

260

V I

255

H(ice)=150 km

III 250

0

0.1

0.2

0.3

0.4

0.5

0.6

P, GPa Fig. 3. Callisto, phase diagram of H2 O in the region ice-I-ice-III-ice-V-liquid. The dashed lines are adiabats in the convective oceanic zone at varying ice-I thickness. The dependency of pressure on depth for the entire water-ice shell of Callisto may be approximated by the equation P (MPa) = 1.1 Z + 6.75 × 10−4 Z2 (km).

moment of inertia constraint.7,8,11 In contrast to Ganymede, the surface of Callisto shows no evidence of extensive resurfacing. In accordance with the above results and constraints from Galileo magnetometer observations, we present here the calculations of the interior structure for a six-layer partially diﬀerentiated model of Callisto composed of the following shells7 : (1) an outer water-ice envelope; (2) an intermediate ice-rock mantle, which is subdivided into three reservoirs and composed of a mixture of highpressure ices and rock material (dry silicates and/or hydrous silicates + Fe-FeS alloy); and (3) a central rock-iron ice-free core made up of a mixture of rock material and iron-sulﬁde alloy. The results of calculations are illustrated in Fig. 4. The maximum thickness of Htot = 315 km corresponds to the minimum thickness of Hice−I = 135 km. The minimum thickness of Htot ∼ Hice−I ∼ 176 km corresponds to the existence of very thin liquid layer between the icy crust and ice-rock mantle. Figure 4 shows that Callisto may be partially diﬀerentiated into an outer ice-I layer, a water ocean, a rock-ice mantle (a mixture of

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Distance from the center, km

2500 ice-I water

2000 ice-rock mantle

1500

1

1000

500

rock-iron core 2

0

140

150

160

170

Ice-I thickness, km Fig. 4. A model of Callisto’s interior with an internal ocean. The allowed total (maximum) thickness of the outer water-ice shell is estimated as 270–315 km. The vertical line corresponds to the thickness of ice-I crust of 150 km. For the heat ﬂow values of 3.3– 3.7 mW m−2 , the thickness of ice-I crust is 135–150 km, and the permissible thickness of the underlying internal ocean is about 120–180 km. 1-maximum core radii: solid and dashed lines correspond to the density of the rock-iron core of 3,620 kg m−3 and 3,150 kg m−3 , respectively; 2-minimum core radii.

high-pressure ices and rock material), and a rock-iron core free of ice (mixture of anhydrous silicates and/or hydrous silicates + Fe-FeS alloy). Thus, Callisto cannot be a completely diﬀerentiated satellite like Ganymede. Anderson et al.8 also concluded that Callisto must only be partially diﬀerentiated, with the ice and rock incompletely separated. Assuming conductive heat transfer through the ice-I crust, heat ﬂows were estimated and the possibility of the existence of a water ocean in the process of the thermochemical diﬀerentiation of Callisto was examined. Calculations for the present-day heat ﬂows of 3.3–3.7 mW m−2 , which correspond to those expected from radiogenic heat sources,14 suggest that the water ocean is stable (not frozen up to the present) beneath the ice crust. The thickness of the ice-I crust is 135–150 km, and the thickness of the underlying internal ocean is about 120–180 km. The existence of a subsurface ocean in such bodies as Callisto and Titan could be explained by the presence of volatiles in the initial ocean.2,4 Nagel et al.15 also note that an ocean in Callisto at a depth of 100–200 km is diﬃcult to obtain if the ice is pure H2 O and if the ice–rock lithosphere is 100 km or more thick; a water ocean is more plausible for ice contaminated

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by ammonia, methane or salts, or for pure H2 O at a depth of 400–600 km. However pure H2 O ocean at depths of 400–600 km is not consistent with the maximum thickness of the outer water-ice shell of 270–315 km, satisfying the mass and moment of inertia constraints.7 The existence of the pure water ocean, which is discussed in the paper, should be considered as an end-member case. The above estimated heat ﬂows indicate that a pure water ocean may exist up to the present time. The presence of substances depressing the freezing temperature of water additionally strengthens this inference. The discovery of the induced magnetic ﬁeld of Callisto has been interpreted as evidence for a subsurface salty liquid-water ocean.3 According to our calculations, the ocean can exist within a relatively narrow range of heat ﬂow F∼2–3.7 mW m−2 at a surface temperature of 100–130 K. If F < 2 mW m−2 , the ocean will be completely frozen. In this case, the satellite can consist of three layers of diﬀerent compositions: icy lithosphere (ice I + high-pressure ices), ice-rock mantle, and rock-iron core free of ice. Calculations show that Callisto could be also represented as a two-layer body consisting either of the outer icy lithosphere with the maximum thickness of 320 km and internal ice-rock mantle (central rock-iron core is absent), or of outer ice-rock shell and central ice-free rockiron core with the maximum radius of ∼1,100 km for ρ◦Fe−Si = 3,620 kg m−3 and 1,300 km for ρ◦Fe−Si = 3,150 kg m−3 (icy lithosphere is absent). The volume between the rock-iron core and the icy lithosphere is occupied by the ice-rock mantle.

6. H2 O Content in the Galilean satellites Taking into account the H2 O content in hydrated silicates, the total amount of H2 O in Callisto is in the range from 49 to 55 wt%, which is diﬀerent from the cosmic mixture (∼60% ice, 40% rock by mass). The content of H2 O in Ganymede’s outer envelope was estimated as 46–48% of the total mass. Figure 5 shows an estimated amount of H2 O in the jovian satellites. It is also important to note that the simultaneous formation of Io (composed of anhydrous silicates and iron) and of the icy satellites with a huge amount of H2 O in diﬀerentiated Ganymede and partly diﬀerentiated Callisto cannot be explained by accretion of the material of C-type chondrites because of insuﬃcient water content in the latter. The bulk of the water ice in these outer moons is pure water ice that condensed directly from the protojovian nebula.

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375

H2O, wt%

60 Ganymede

Callisto

40

20 Io

Europa

0 5

10

15

20

25

30

Distance from Jupiter (in RJ) Fig. 5. Estimated amount of H2 O in the satellites. Io is an anhydrous satellite. Europa contains 6–8.5 wt% of water and ice. The content of H2 O in Ganymede and Callisto is between 46 and 55 wt%.

7. Conclusion (1) Models of the internal structure of completely diﬀerentiated Europa and Ganymede, and partially diﬀerentiated Callisto have been constructed on the basis of Galileo gravity measurements and magnetometer data, geochemical constraints on the composition of ordinary and carbonaceous chondrites, and thermodynamic data on the equations of state of water, high-pressure ices, and meteoritic material. Thickness and aggregate state of the water-ice shell, ice concentration in the ice-rock mantle, and total H2 O content in the satellites are determined. The allowed thicknesses of an outer water-ice shell are in the range of 105–145 km for Europa, 780–940 km for Ganymede and 270–315 km for Callisto. Some constraints are deduced on distribution of density in the mantle and maximum and minimum sizes of the central core. (2) We show that Callisto may be partially diﬀerentiated into an outer ice-I layer, a water ocean, a rock-ice mantle, and a rock-iron core (mixture of anhydrous silicates and/or hydrous silicates + Fe-FeS alloy). Assuming conductive heat transfer through the ice-I crust, heat ﬂows were estimated and the possibility of the existence of a water ocean in the process of the thermochemical diﬀerentiation of Callisto was examined. Calculations for the present-day heat ﬂows of 3.3–3.7 mW m−2 , which correspond to those expected from radiogenic heat sources, suggest that the water ocean is stable (not frozen up to the present) beneath the ice crust. The thickness of the ice-I crust is 135–150 km, and the thickness of the underlying internal

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ocean is about 120–180 km. The allowed total (maximum) thickness of the outer water-ice shell is estimated as 270–315 km. (3) The correspondence between the density and moment of inertia values for bulk ice-free Io, diﬀerentiated rock-iron cores (anhydrous silicate mantle + Fe-FeS core) of Europa and Ganymede, and partially diﬀerentiated rock-iron core (anhydrous silicates and/or hydrous silicates + Fe-FeS alloy) of Callisto shows that their bulk ice free compositions may be, in general, similar and may be described by the isochemical composition close to a material of the L/LL type chondrites.6,7,16 Therefore, planetesimals composed of these types of ordinary chondrites could be considered as analogues of building material for the rock-iron cores of the Galilean satellites. Similarity of the bulk ice-free compositions of the inner and outer satellites implies the absence of iron-silicon fractionation in the protojovian nebula. References 1. R. T. Pappalardo, M. J. S. Belton, H. H. Breneman et al., J. Geophys. Res. 104 (1999) 24015. 2. F. Sohl, T. Spohn, D. Breuer and K. Nagel, Icarus 157 (2002) 104. 3. C. Zimmer, K. K. Khurana and M. G. Kivelson, Icarus 147 (2000) 329. 4. T. Spohn and G. Schubert, Icarus 161 (2003) 456. 5. H. Hussmann, C. Sotin, J. I. Lunine, Interiors and Evolution of Icy Satellites, Treatise on Geophysics 10 (2007) 509–539. 6. O. L. Kuskov and V. A. Kronrod, Icarus 151 (2001) 204. 7. O. L. Kuskov and V. A. Kronrod, Icarus 177 (2005) 550. 8. J. D. Anderson, R. A. Jacobson, and T. P. McElrath et al., Icarus 153 (2001) 157. 9. A. J. R. Prentice, Earth Moon and Planets 87 (2001) 11. 10. V. A. Kronrod and O. L. Kuskov, Geochem. Int. 41 (2003) 881. 11. G. Schubert, J. D. Anderson, T. Spohn and W. B. McKinnon. In: F. Bagenal, T. Dowling and W. McKinnon (eds.), Jupiter: The Planet, Satellites and Magnetosphere, Cambridge University Press, (2004), pp. 281–306. 12. M. J. Lupo and J. S. Lewis, Icarus 40 (1979) 157. 13. J. Ruiz, Nature 412 (2001) 409. 14. S. Mueller and W. B. McKinnon, Icarus 76 (1998) 437. 15. K. Nagel, D. Breuer and T. Spohn, Icarus 169 (2004) 402–412. 16. V. A. Kronrod and O. L. Kuskov, Geochem. Int. 44 (2006) 529.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

JUPITER THERMOSPHERIC GENERAL CIRCULATION MODEL (JTGCM): GLOBAL THERMAL BALANCES AND THERMOSPHERIC WIND — A REVIEW∗ TARIQ MAJEED University of Michigan, 2455 Hayward St., Ann Arbor, Michigan, 48109-2143 USA and American University of Sharjah, P.O. Box 26666, Sharjah, UAE [email protected] J. HUNTER WAITE, JR. and G. RANDALL GLADSTONE Southwest Research Institute, 6220 Culebra Road, San Antonio, Texas 78238, USA STEPHEN W. BOUGHER University of Michigan, 2455 Hayward St., Ann Arbor, Michigan, 48109-2143 USA

A review of the three-dimensional Jupiter Thermospheric General Circulation Model (JTGCM) is presented with emphasis on model inputs, thermal and wind processes. The JTGCM has been fully “spun-up” and integrated for 86 Jupiter days with proper characterization of the Jovian upper atmosphere, embedded ionosphere, and auroral features, in order to examine underlying physical processes, including the feedback from energetics, neutral– ion dynamics, composition, and magnetospheric coupling from 20 µ bar to 1.1 × 10−4 nbar. We use the thermal and wind processes simulated within the JTGCM to interpret a growing multispectral database of temperatures and the Galileo probe measurements of the vertical temperature proﬁle near the Jovian equator. We ﬁnd that ion drag and joule heating in the JTGCM signiﬁcantly intensify the underlying global thermospheric circulation, thereby aﬀecting the distribution of neutral temperatures. Global simulations of Jovian thermospheric dynamics indicate strong neutral outﬂows from the auroral ovals with velocities up to 1.3 km/s, with subsequent convergence and downwelling at the Jovian equator. Such circulation is shown to be an important mechanism for transporting signiﬁcant amounts of auroral energy to the rest of the planet and for regulating the global heat budget in a manner consistent with temperature observations on Jupiter. The best ﬁt to the Galileo temperature proﬁle and ∗ This work is supported by NASA/STScI grant, NASA/Planetary Atmosphere grant and NSF grant.

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multispectral temperature data implies that the major energy source for maintaining the observed temperatures is dynamical heating induced by the low-latitude convergence of the high-latitude-driven thermospheric circulation. This dynamical heating is eﬃciently dissipated by hydrocarbon cooling through CH4 and C2 H2 infrared radiation at 7.8 µm and 12.6 µm, respectively.

1. Introduction Since its discovery in 1979,1 observations of the intense ultraviolet (UV) aurora at Jupiter from spacecraft,2,3,4,5 [and references therein] have demonstrated a strong electromagnetic interaction between the Jovian magnetosphere and ionosphere. Auroral activity at Jupiter deposits huge amounts of energy into its upper atmosphere.6 This energy ultimately derives from Jupiter’s rotational energy and plasma processes in the near corotating middle magnetosphere. The breakdown of corotation in the magnetodisk occurs at 20–30 Jupiter radii. This allows an upward ﬁeldaligned current generated by the transfer of Jupiter’s angular momentum to Iogenic plasma that is being driven radially outward in the magnetodisk.7,8 The region of maximum change in the departure of the magnetodisk from corotation is in fact the region of maximum plasma ﬂow in and out of the Jovian ionosphere through the magnetic ﬁeld lines that produce the main auroral oval.9,10,11 Charge particles accelerated downward in this process provide the ﬁeld-aligned currents associated with corotation breakdown, and produce ultraviolet emissions as well as ionization and heating of the ambient H2 atmosphere.12,13 This heating due to particle precipitation is a major driver of the thermospheric dynamics, since the globally-integrated solar heating of the Jovian thermosphere is approximately two orders of magnitude smaller than the globally-integrated auroral heating.14 The strong horizontal closure currents in the auroral ovals also produce joule heating in the ionosphere from ion–neutral collisions between the rotating ionosphere and the atmosphere. The atmospheric angular momentum in the thermosphere near the ionospheric peak where the joule heating takes place is supplied by the lower atmosphere, most likely through gravity wave propagation and dissipation,15 and is mediated by the thermospheric wind system. The key roles of time-varying energy deposition, infrared (IR) cooling, and wind transport dynamics in controlling the outer planets’ global thermospheric structures have been studied by three-dimensional Thermospheric General Circulation Models.16,14,17,18 Bougher et al.14 have described the main characteristics of the Jupiter Thermospheric

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General Circulation Model (JTGCM) in a comprehensive study of global thermospheric dynamics, energetics, and redistribution of thermospheric composition at Jupiter. Majeed et al.18 demonstrated that auroral heating at Jupiter, and subsequent dynamical transport processes can maintain a hot thermosphere in the equatorial region, as observed by the Galileo atmospheric entry probe.19 Furthermore, auroral heating in the JTGCM generates a mild thermospheric wind system consistent with that simulated by Achilleos et al.16 This allows meridional transport of heat from pole to equator with moderate magnitude upper atmospheric zonal jets resulting from action of the Coriolis force on the equatorward wind system [e.g. 14]. The ion drag forcing in the JTGCM has a profound eﬀect on the strength and structure of the upper atmospheric wind systems, especially in the southern hemisphere where the anti-corotational direction of the highlatitude zonal jets produces copious joule heating, which in turn strengthens the zonal jets due to increased meridional ﬂow in the equatorward direction, and leading to a feedback situation where the wind magnitudes and the thermal structure of the southern hemisphere are elevated with respect to the northern hemisphere.20 The purpose of this paper is to review the JTGCM inputs and the thermal processes responsible for maintaining the observed temperature proﬁle near the Jovian equator and the derived thermospheric temperatures from multispectral observations of Jupiter’s aurora. The review of the equatorial thermal and auroral processes is based on Bougher et al.14 and Majeed et al.18,20 While the strong neutral wind system developed within the JTGCM plays an important role in regulating the bulk of heating in the global thermosphere, this paper also brieﬂy discusses the processes responsible for generating horizontal winds.

2. Description of the JTGCM The JTGCM is a ﬁnite diﬀerence primitive equation model that solves for neutral temperatures, ion-neutral densities, and three component neutral winds over the globe. The governing equations found in Earthspeciﬁc’ Thermosphere General Circulation Models [cf., 21] and modiﬁed for Venus and Mars [see 22 and references therein] for neutrals, i.e. the thermodynamic equation, zonal and meridional momentum equations, the coupled continuity-diﬀusion equations (for H and He), the hydrostatic equation, and continuity equation (for vertical velocities) have been modiﬁed for Jupiter within the JTGCM. The major characteristics of the

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JTGCM and its objectives are described in detail by Bougher et al.14 Here, we brieﬂy review important points of the JTGCM that are related to this paper. The JTGCM uses a 5◦ –latitude by 5◦ –longitude grid with 39 vertical pressure layers in increments of 0.5 pressure scale heights. The model solves coupled governing equations self-consistently using the basic framework of the National Center for Atmospheric Research (NCAR) general circulation model [cf., 21]. Each of these governing equations is cast in log-pressure coordinates (Zp = ln(p0 /p)), with a speciﬁed reference pressure level corresponding approximately to the average homopause level. For the JTGCM code, this reference pressure is located at 4.5 µ bar (Zp = 0). Each Zp interval corresponds to one scale height (at the local temperature). 2.1. Parameterization of the JTGCM inputs 2.1.1. Input solar and particle heating The JTGCM uses solar EUV radiation as a source of equatorial heating, while the particle heating calculated by Grodent et al.13 (incident electron energy spectrum described by a combination of three Maxwellian distribution functions with a total particle energy ﬂux of 110 ergs cm−2 s−1 ) is used for the auroral region. An average solar EUV heating rate proﬁle estimated by Waite et al.12 is speciﬁed within the latitude band of ±50◦ latitude to investigate the relative importance of this heating mechanism on the Jovian equatorial thermosphere. Auroral heating by particle precipitation is speciﬁed symmetrically in λIII longitude along both the northern and southern polar ovals, which are currently described by the auroral morphology deduced from the analysis of HST/WFPC2 and HST/STIS acquired images (see Sec. 2.1.7). 2.1.2. Specification of the ionosphere The current version of the JTGCM uses particle precipitation ionization of H2 to determine the H+ 3 ion density, assuming chemical equilibrium and a loss of H+ from electron recombination and reaction with methane.14 3 Photoionization is not important for the auroral regions and therefore it has been ignored in the JTGCM. The H+ ion is prescribed within the JTGCM on the basis of a detailed 1-D proﬁle calculated oﬄine12 over the Jovian globe. The reason for inputting the H+ density proﬁle in this version of the JTGCM is to save run-time of this very complicated

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model. This assumption will not change the basic conclusion of the thermospheric dynamics and the Jovian thermal budget. The ionosphere is largely controlled by H+ production above an altitude of 1200 km and by H+ 3 below this altitude, regardless of the presence of winds and energetic particle precipitation.23,24 Current interpretation of the measured vertical ionospheric structure indicates that a combination of vertical plasma drift and enhanced populations of vibrationally excited H2 molecules with v ≥ 4 is required for interpreting the observations with 1-D models.25 Thus, a proper calculation of H+ densities requires a loss mechanism involving H2 vibrational levels. However, this key loss for H+ was not properly treated within the Waite et al. 1-D model, and likewise is ignored in the current JTGCM code. The proper calculation of these H2 vibrational levels in a future version of the JTGCM will allow us to simulate the upper ionosphere self-consistently with the Jovian thermal and dynamical structures on a global basis. 2.1.3. Specification of hydrocarbon cooling Our estimates of hydrocarbon cooling due to strong C2 H2 (12.6 µm) and CH4 (7.8 µm) radiation in the JTGCM are based on constraints provided by re-analyzing the Voyager 1 infrared Interferometer and Radiometer Spectrometer (IRIS) spectra.26 The total measured excess infrared auroral zone emission (averaged over the IRIS ﬁeld of view) in the hydrocarbon bands between 7 and 13 µm was found to be about 208 erg cm−2 s−1 over an area of about 2×1018 cm2 with a resulting power output of 4×1013 W. This large infrared output likely results from a large temperature enhancement in the upper stratosphere and lower thermosphere, in accord with strong auroral and joule heating that is conducted downward and made available for infrared radiation.14 Assuming that the hydrocarbon auroral emissions originate in optically thin layers, the JTGCM used the simple radiative transfer model of Drossart et al.26 to calculate the eﬀects of temperature and species abundances on the CH4 and C2 H2 infrared emissions. For these two molecules, the radiation is calculated for the fundamental transition that is predominant in the IR spectrum, for which optically thin conditions hold for pressure less than 20 µbar. The total emission intensity for CH4 and C2 H2 can be written as ICH4 = [CH4 (ν4 )] Aν4 hc σ(CH4 ) erg cm−3 s−1 ,

(1)

IC2 H2 = [C2 H2 (ν4 )] Aν5 hc σ(C2 H2 ) erg cm−3 s−1 ,

(2)

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where ICH4 and IC2 H2 are emission intensity, and hc σ(CH4 ) and hc σ(C2 H2 ) are the energies of radiative transitions 0.17 eV and 0.886 eV, respectively. The [CH4 (ν4 )] and [C2 H2 (ν4 )] are the densities of the excited molecules assuming Boltzman distribution [cf., 13]. The required vertical density proﬁles of the ground states of CH4 and C2 H2 are based on oﬄine tables generated from the model by Gladstone et al.27 Polynomial ﬁts are constructed that reproduce zonally averaged CH4 and C2 H2 density proﬁles up to 0.1 nanobars from Gladstone’s model. At lower pressures, hydrocarbon densities are negligibly small and resulting infrared cooling is minimal. H+ 3 cooling in the 3 to 4 µm fundamental band is also calculated making use of the photochemically derived H+ 3 densities within the JTGCM itself. Again, it is assumed that optically thin conditions prevail. A similar cooling rate formulation is used after the hydrocarbon scheme. Clearly, + H+ 3 cooling is expected to maximize where local H3 densities peak, in the auroral ionosphere. This implies that H+ 3 cooling serves to oﬀset auroral heating as electron precipitation also provides the source for H+ 3 densities. Recently, Yelle et al.28 re-evaluated radiative processes in Jupiter’s stratosphere between 0.1 bar and 10−6 bar based on constraints provided by the Galileo temperature proﬁle and composition proﬁles derived from various experiments. Heating and cooling rates were calculated based on realistic altitude proﬁles of C2 H2 , C2 H6 , and CH4 , which were in reasonably good agreement with predictions from photochemical models [e.g. 27]. Interestingly, Yelle et al.28 predicted that absorption of solar radiation in CH4 bands is the dominant heat source in the equatorial Jovian stratosphere. The 3.3 µm band is the primary heat source at pressures less than 4×10−6 bar, while the 2.3 µm band dominates the heat budget between 4 × 10−6 and 5 × 10−4 bar. Another important conclusion of Yelle et al.’s model is the dominance of C2 H6 cooling throughout the stratosphere with a minor contribution from C2 H2 , which is contrary to many earlier studies [e.g. 13]. Chemical heating resulting from the reaction chain initiated by the ionization of H2 plays an important role in maintaining the thermal structure in one-dimensional Jovian models.13 This source of thermospheric heating has also been neglected in the present JTGCM code because it is too complicated to include at this point. Future upgrades to the JTGCM code will incorporate the Yelle et al. model to improve the self-consistency of the energetic, dynamical, and chemical processes at lower thermospheric altitudes (>1 µbar).

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2.1.4. Specification of Jupiter’s magnetic field The present state-of-the-art in Jupiter magnetic ﬁeld mapping is described in detail by Connerney et al.29 who discussed the origins and limitations of the two primary magnetic ﬁeld models presently in use. The Voyager– Io–Pioneer 4 (VIP4) model has been improved over the O6 model by the use of Hubble Space Telescope (HST) and Infrared Telescope Facility (IRTF) images of the latitude track of the Io ﬂux tube. This yields a better agreement in the ﬁeld line mapping to the region of Io’s orbit. However, it may not improve the ﬁts for more distant regions in the outer magnetosphere (30–50 Rj limit of the ﬁeld model). The VIP4 magnetic ﬁeld model is used within the JTGCM formulations to specify the ion drag parameters and map the Jovian magnetosphere to the ionosphere. 2.1.5. Ion drag and joule heating formulations Ion-drag, which modiﬁes neutral wind speeds in the Jovian thermosphere, is produced by ion-neutral collisions in the Jovian auroral oval regions. Ions, magnetically connected to the subrotating regions of the magnetosphere, lose their momentum in collisions with neutrals and thus drive the neutrals to move in roughly the same direction. This drag is proportional to the product of the ion density and the relative drift between the neutral and ion species. Ion-drag is a dominant neutral momentum forcing process at auroral oval latitudes near the altitude of the ionospheric peak. In addition, Jupiter’s high latitudes map furthest into the Jovian magnetosphere, along magnetic ﬁeld lines (L ≥ 20); the corresponding ions are subject to corotation breakdown and thereby inﬂuence the corotating neutrals in unique ways. Ion-drag also depends on the ion– neutral collision frequency and on the local conﬁguration of the magnetic ﬁeld. At higher ionospheric altitudes where the ion gyro-frequency exceeds the ion–neutral collision frequency, ionization is constrained to move along ﬁeld lines, thereby dragging the neutrals. In addition, joule heating results from the frictional motion between ions and neutrals. Richmond et al.30 have shown that ion-drag can signiﬁcantly modify the neutral winds at Earth’s low and mid latitudes, thereby aﬀecting the distribution of neutral temperatures. The parameterization of ion-drag and joule heating in the JTGCM code is based on the formulation described by Roble and Ridley.31 The ion-drag parameters (tensors) for the 10◦ oﬀset Jovigraphic Jovimagnetic poles are

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described as follow: λxx = λ1 (1 − sin2 δ cos2 I),

(3)

λyy = λ1 (1 − cos2 δ cos2 I),

(4)

2

λxy = λ1 sin δ cos δ cos I + λ2 sin I,

(5)

λyx = λ1 sin δ cos δ cos2 I + λ2 sin I,

(6)

where δ is the magnetic declination angle and I is the magnetic dip angle. λ1 and λ2 are deﬁned as λ1 = σp B2 /ρ,

(7)

λ2 = σH B2 /ρ,

(8)

where σp and σH are the Pedersen and Hall electrical conductivity, respectively, B is the strength of the magnetic ﬁeld from the VIP4 model of Connerney et al.29 and ρ is the JTGCM density. The joule heating (per unit density) in the JTGCM is derived from the ion-drag parameters as QJ = λxx (ui − un )2 + λyy (vi − vn )2 + (λxy − λyx )(ui − un )(vi − vn ), (9) where ui and vi are the Jovigraphic zonal and meridional ion drift velocities; un and vn are the zonal and meridional neutral wind components determined at a given time step in the JTGCM. A convection electric ﬁeld is estimated and corresponding ion drifts are generated using an ionospheric convection model based on Voyager measurements of ion convection in the outer magnetosphere [cf., 32]. Subsequently, the VIP4 magnetic model is adapted to map this magnetospheric ion convection pattern to ionospheric altitudes at auroral oval latitudes. In this manner, anticorotational electrojet winds of nearly 3 km/s are prescribed around both main auroral ovals, driving the neutral winds to move in the same direction. Conversely, in non-auroral regions, ui and vi are zero (i.e. corotational); corresponding neutral winds are decelerated by iondrag forcing in those regions where the ion–neutral collision frequency remains high. These well-tested General Circulation Model formulations [cf., 31] provide a means to examine the general impact of iondrag and joule heating on the JTGCM neutral winds and thermal structure.

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2.1.6. Scaling of joule heating Recently, Bougher et al.14 demonstrated that a scaling scheme of ion drag and corresponding joule heating by adjusting the horizontal ion drift can be used to explore general characteristics of the global thermal structure and dynamics, which can then be used to explain multispectral observations of the Jovian thermosphere. They suggested a downward scaling of ion drift by 30% is needed for the JTGCM simulations to best describe the Jovian observations. This scaling likely reﬂects uncertainties in the (a) magnetosphere–ionosphere mapping that we have conducted using the VIP4 magnetic ﬁeld model29 and (b) derived high-latitude ion convection32 from Voyager observations of the middle magnetosphere of Jupiter. It is important to note that we used a diﬀerent scaling method than that adopted by Bougher et al.14 Rather than adjusting ion drifts, we follow Majeed et al.18,20 who used 15% of the total joule heating produced in the Jovian auroral ovals in order to reproduce the equatorial thermal structure observed by the Galileo probe. This is not too surprising since early versions of Earth’s TGCM allowed joule heating rates to vary as much as a factor of 20 from the global heating estimates based on derived timemean currents in the dynamo region.33 The global simulations from these models were utilized to interpret thermospheric temperatures and radar observations of neutral winds at low and midlatitudes.34 Joule heating in current models (e.g. TIEGCM) is induced by high-latitude plasma drifts associated with magnetospheric convection driven by a cross-tail potential that is highly variable, ranging from 20 kV to perhaps 200 kV depending on geomagnetic conditions.35 For the terrestrial thermosphere, this is an important parameter to account for in estimating diurnal neutral temperature distribution and thermospheric circulation. Thus, regardless of which method is to be used, the scaling down of the estimated joule heating is important for modifying the global thermospheric circulation on Jupiter to better agree with observations and is in accord with early versions of the terrestrial TCGM [cf., 34]. 2.1.7. Auroral morphology The auroral morphology in the JTGCM is described by the north and south polar ovals inferred from the analysis of the recently acquired Jovian ultraviolet images with the HST/STIS during the Cassini ﬂyby of Jupiter36 and HST/WFPC-2 images obtained between June 1996 and July 1997.37,38 Table 1 shows the coordinates of the main auroral ovals from the analysis

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386 Table 1.

Polar coordinates of the main auroral ovals [From 36].

λIII Main oval Main oval λIII Main oval Main oval Longitude North latitude South latitude Longitude North latitude South latitude 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0 160.0 170.0 180.0

88.22 88.33 88.40 88.41 88.40 88.33 88.21 88.05 87.81 87.42 86.85 85.97 84.55 82.13 63.00 57.43 56.06 56.88

−69.79 −69.27 −68.78 −68.36 −68.22 −68.51 −69.34 −70.69 −72.56 −74.74 −76.96 −78.98 −80.64 −81.92 −82.87 −83.56 −84.07 −84.40

190.0 200.0 210.0 220.0 230.0 240.0 250.0 260.0 270.0 280.0 290.0 300.0 310.0 320.0 330.0 340.0 350.0 360.0

58.94 61.37 64.10 67.05 70.45 73.76 76.58 78.93 80.83 82.38 83.66 84.73 85.64 86.45 87.02 87.51 87.81 88.04

−84.60 −84.68 −84.65 −84.52 −84.27 −83.87 −83.34 −82.62 −81.70 −80.58 −79.27 −77.82 −76.31 −74.85 −73.45 −72.23 −71.21 −70.49

of these images both for the northern and southern polar region. The input particle heating is speciﬁed symmetrically in λIII longitude along both polar ovals, with a vertical distribution (as a function of pressure) that is the same everywhere. The oval width is limited to the 5◦ latitude–longitude resolution of the JTGCM code, eﬀectively yielding a delta function for auroral forcing along the two ovals. This oval width in the JTGCM is coarser than that of Jupiter’s real oval; nevertheless, the integrated energy ﬂux is assumed to be the same. 2.1.8. Specification of the ionospheric electric field A simpliﬁed (magnetically) axisymmetric model of the ion convection observed by Voyager [cf., 32] is used to specify the ionospheric electric ﬁeld by mapping the magnetospheric convective motion into the ionosphere. The ion convection patterns in the magnetosphere are mapped with the VIP4 magnetic ﬁeld model29 to produce a reasonable mapping of the high-latitude ionospheric electric ﬁeld in the two Jovian hemispheres. Figure 1 illustrates the underlying single-cell plasma drift patterns both for the northern and southern hemispheres. These polar plots show that anticorotational ion ﬂow expected for an auroral electrojet prevails

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Fig. 1. Plasma drift vectors plotted on polar dials in the (a) north and (b) south. Vectors represent the magnitude and direction of the net horizontal ion winds. Latitude circles on these dials are spaced in 4◦ intervals ranging from 52–88◦ N (north oval) and 60◦ S to 88◦ S (south oval). Notice a single cell anticorotational plasma ﬂow pattern in each hemisphere, i.e. clockwise (north oval) and counterclockwise (south oval). The strongest vector ion wind arrows roughly coincide with the prescribed oval locations (as indicated by asterisks). This is in accord with the expected auroral electrojet in each hemisphere. Maximum zonal ion (ui ) winds approach ∼3.0 km/s; corresponding meridional (vi ) winds approach ∼1.5 km/s [From 14].

in both hemispheres. The length of the arrows signiﬁes relative ion wind speeds at the JTGCM grid points corresponding to the prescribed oval locations. The ion wind patterns are pronounced and well organized in both hemispheres; the northern hemisphere circulation cell extends over a wider range of Jovigraphic latitudes (57–90◦N) than in the southern hemisphere (65–90◦S). In both cells, zonal ion winds approach about 3 km/s, while meridional ion winds are weaker up to 1.5 km/s. Generally, the southern plasma drifts are slightly (20%) stronger than those in the northern hemisphere due to the mapping of VIP4 magnetic ﬁeld lines further outward into the Jovian magnetosphere. Such mapping results in a longer departure of the southern hemisphere plasma drifts from corotation than plasma drifts in the north. 2.2. Lower boundary conditions The lower boundary in the JTGCM is at 20 µbar, which takes into account hydrocarbon cooling due to C2 H2 (12.6 µm) and CH4 (7.8 µm) at the base of the thermosphere, below the homopause.26 This is important for proper

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cooling of the Jovian auroral atmosphere, where electron precipitation provides strong heating that is conducted downward and radiated away 39 via these strong infrared (IR) emissions. H+ 3 cooling from IR emissions is also included above the homopause. Our assumed boundary conditions are that the geopotential, zonal, and meridional winds are zero at the lower boundary (i.e. strict corotation). This is certainly a crude simpliﬁcation that neglects the strong stratospheric winds [e.g. 40] and upward propagating tides and gravity waves [e.g. 15, 41, 42, 43] that must be present in the Jovian lower atmosphere. Global average lower boundary conditions both for the temperature and neutral densities (H and He) are taken from Galileo19 and Voyager data.44 Speciﬁcally, an average global temperature, composed of observed equatorial and polar values near 250 km, is set to 190 K. The helium volume mixing ratio is set to 0.135 at 250 km (or 20 µbar), based upon Galileo probe observations.45 The atomic hydrogen volume mixing ratio is set to 4.23 × 10−8, in accord with Voyager data at the lower boundary. Photochemical equilibrium is assumed for the major + ions (H+ 2 and H3 ). 2.3. Upper boundary conditions Upper boundary conditions are speciﬁed at about 1.1×10−4 nbar in order to properly include high-altitude auroral heating processes13,46 and H+ 3 cooling in the near-IR.39 Corresponding boundary conditions for temperatures and neutral winds are identical to those employed in the terrestrial TIGCM; i.e. vertical gradients in temperatures and winds (zonal, meridional, and vertical) are set to zero at the top of the model. These conditions are in accord with weak energy sources at the highest altitudes; isothermal temperatures are also consistent with the emergence of the exosphere. For composition (H and He ), diﬀusive equilibrium is assumed at the top boundary [cf., 14]. Each of the JTGCM equations is time dependent, but is typically integrated toward steady-state conditions. The JTGCM simulations of the thermosphere/ionosphere are conducted for many Jovian rotations in order to achieve a steady-state solution in the modeled ﬁelds. Planetary TGCMs achieve steady-state solutions according to various timescales that vary as a function of altitude [e.g. 22]. For Jupiter’s thermosphere, a useful dynamical timescale can be deﬁned as the transport time for average meridional winds to redistribute auroral oval heating and atomic species to the Jovigraphic equator. Typical JTGCM zonally averaged meridional winds (125–300 m sec−1 )14 place this timescale at

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about 4–10 Earth days for pressures less than about 0.15 µbar. Equilibration requires that meridional pressure gradients are stabilized by both pole– to–equator and equator–to–pole wind ﬂows, for which the dynamical timescales should be multiplied by 2. This yields an eﬀective dynamical timescale of the order of 8–20 Earth days (or 20–50 Jovian rotations). Hence, JTGCM calculations can only achieve near-equilibrium solutions for the upper thermosphere when simulations run on the order of >50 Jovian rotations. Further discussion on the JTGCM computational scheme, numerical stability, ﬁltering and smoothing of prognostic ﬁelds is presented by Bougher et al.14 3. JTGCM Temperature and Wind Simulations Figure 2 shows the JTGCM-driven zonal average slices for temperature and horizontal wind distributions in the entire thermosphere from 20 µbar

Fig. 2. Zonal average slices over the entire JTGCM vertical domain (in log pressure coordinates). Fields include (a) temperature in 100 K intervals, (b) neutral zonal winds in 100 m/s intervals, (c) neutral meridional winds in 50 m/s interval, and (d) neutral vertical winds in 1.0 m/s intervals. Dashed lines indicate negative winds: zonal (westward), meridional (southward), and vertical (downward).

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to 1.1 × 104 nbar. This zonal view emphasizes latitudinal variations for the best-case scenario needed to explain measured temperature proﬁle near the Jovian equator.18 This scenario includes auroral forcing by particle heating and an additional forcing by 15% of the total joule heating produced in the auroral ovals. The model simulation was run for 86 Jovian rotations to achieve steady-state temperature and wind ﬁelds for pressures <1 µbar, while at higher pressures the JTGCM ﬁelds remain to be stabilized. The underlying global thermospheric circulation is greatly intensiﬁed when ion drag and joule heating processes are applied to an otherwise aurorally particle precipitation driven wind system.14 Note that joule heating signiﬁcantly modiﬁes the heat budget in both hemispheres, yielding warm exospheric temperatures of about 950–1200 K in both auroral oval regions (see Fig. 2a). Temperatures in the vicinity of 500–600 km, near the H+ 3 ion peak, are calculated to be 400 K (equatorial) to 700 K (polar). Note that a north–south asymmetry exists in the temperature distribution, which is consistent with that observed in the H+ 3 temperature map derived from spectral imaging of the Jovian atmosphere.47 The meridional temperature change aloft (above ∼700 km) approach 100–300 K; latitudinal temperature gradients below 600 km are even larger near the southern oval region (60–90◦S). These large gradients in the southern hemisphere give rise to a deep zonal jet centered at 70◦ S latitude, with wind speeds reaching 1.2 km/s (see Fig. 2b). This westward jet clearly dominates the zonal ﬂow, extends throughout most of the Jovian thermosphere (above the CH4 homopause), and is consistent with strong meridional (south to north) winds approaching 400 m/s (see Fig. 2c). Just above the homopause at high southern latitudes, the westward zonal ﬂow weakens dramatically, and is replaced by a strong poleward (Fig. 2c) and subsiding (Fig. 2d) ﬂow that yields considerable dynamical heating at pressures above the methane homopause (see Sec. 4.2). This dynamical heating is driven by unique neutral circulation that results directly from iondrag forcing poleward of the southern auroral oval. Further discussion of the impact of this dynamical heating on the distribution of the thermospheric temperature is given in Sec. 4. In the northern hemisphere, the westward zonal jet is centered at 60◦ N latitude, with wind speeds rising to −0.5 km/s (Fig. 2b); associated equatorward winds peak at −125 m/s (Fig. 2c). Corresponding vertical winds are strongly upward in the southern hemisphere (+5.0 m/s), downward at low latitudes (−1.0 m/s), and upward again near the northern pole (+5.0 m/s) (Fig. 2d). Clearly, a strong zonally averaged circulation

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results from the added joule heating, with upwelling/divergent winds at both poles, and convergent/downwelling ﬂow near the equator. Maximum neutral horizontal winds up to 1.3 km/s are obtained. These winds are nearly double those simulated with the model with no joule heating added.14 3.1. Wind processes The fastest winds on the nbar surface shown in Fig. 2 are blown in the strong outﬂow regions along the positions of auroral ovals in both hemispheres [see 14, 20 for wind vectors at diﬀerent pressure surfaces]. This outﬂow, characterized by wind speeds up to 1.3 km/s, is determined by various competing processes as described by governing zonal and meridional momentum equations [e.g. 21]. These processes will be discussed in detail elsewhere. Here, we brieﬂy describe how these processes can be used to reasonably explain strong Jupiter winds generated in the auroral ovals. Note that the most important processes in the momentum equations include terms associated with large pressure gradients, coriolis force, ion-drag process, and hydrodynamic advection. The zonal winds in the southern oval at the nbar levels are predominantly driven by the competition between large pressure gradients and hydrodynamic advection terms with minor contributions from the ion-drag process and coriolis terms. However, the ion-drag process alone competes with pressure gradients to drive zonal winds for pressures >0.01 µbar. The maximum zonal accelerations due to pressure gradients and coriolis terms occur at about 0.6 µbar with magnitudes of 0.2 and −0.15 m2 s−1 , respectively. The cause of meridional winds in the southern oval is found to be due to strong coriolis acceleration competing with corresponding acceleration due to large pressure gradients for pressures <1 µbar. The acceleration due to the ion-drag process becomes as important as coriolis acceleration for pressures >1 µbar, competing with corresponding acceleration due to pressure gradients to drive meridional winds. The magnitudes of the maximum accelerations due to pressure gradients and coriolis terms at 0.03 µbar are about 0.3 m2 s−1 and −0.35 m2 s−1 , respectively. The situation in the northern oval is quite diﬀerent than that in the southern oval. The magnitudes of the acceleration terms both for the zonal and meridional winds are smaller (up to a factor of 3) in the northern oval compared to those in the southern oval. Pressure gradients

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are primarily responsible for driving zonal winds in the northern oval for pressures <0.1 µbar with the peak magnitude of the acceleration of about 0.08 m2 s−1 . However, the competition between coriolis acceleration and ion-drag acceleration becomes the major source of zonal winds for pressures >0.1 µbar. The magnitudes of the maximum zonal accelerations at about 1 µbar due to coriolis and ion-drag terms are approximately 0.03 m2 s−1 and 0.015 m2 s−1 , respectively. The predominant source of meridional winds throughout the northern oval is due to coriolis acceleration with a peak value of about 0.1 m2 s−1 at around 0.02 µbar. 4. Interpretation of Multispectral Temperature Data with the JTGCM 4.1. Equatorial temperature Figure 3 shows the JTGCM temperature proﬁles in comparison with the temperature proﬁle measured by the Galileo probe near the Jovian equator, along with several temperature measurements from various sources. The results shown here are based on the recent work by Majeed et al.18 Curve B is the JTGCM ﬁt to the Galileo temperature proﬁle, Curve A is from the simulation that incorporates ion drag and moderate auroral heating caused by precipitated charged particle combined with solar EUV heating. This simulation, which ignored joule heating, ran for 86 Jovian rotations to achieve steady-state conditions at pressures below the 1 µbar level. The gradual cooling of the high-latitude auroral thermosphere has been seen in response to local pressure gradients that drive neutral winds (up to 1.3 km/s) away from the heated regions. These winds serve to reduce auroral temperatures in the exospheric region from 1000 K at the start of the simulation to around 600–700 K at the end of the simulation. Clearly, an exospheric temperature as high as 475 K (Curve B) is obtained at the entry location of the Galileo probe. This temperature is more than a factor of 2 larger than what would have resulted from a simulation relying only on solar inputs to heat the atmosphere.12 This diﬀerence in temperature suggests that energy has been transported from auroral regions to near the Jovian equator by a strong meridional ﬂow. However, the transported energy in this simulation is not suﬃcient to explain the measured characteristics of the Jovian thermal structure. Clearly, an additional heat source in the JTGCM is required to reproduce observations of multispectral temperatures and the observed temperature proﬁle by the Galileo ASI instrument. Curve C is a reasonable

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Fig. 3. JTGCM temperature proﬁles are shown in comparison with the equatorial temperature proﬁles measured in situ by the Galileo ASI probe (curve A). Remotely sensed temperature observations from various sources are also compared with the simulated temperatures. Curve B is from a simpliﬁed simulation (ion-drag, high-latitude auroral heating, and solar EUV heating, but no joule heating). Curve C is from a simulation that incorporates 15% of the total joule heating produced in the auroral ovals plus curve B conditions. Curve D is from a simulation that assumes 30% of the total joule heating plus curve C conditions. For the source of observations the reader is referred to.18

ﬁt to the Galileo temperature proﬁle from a simulation that assumes 15% of the total joule heating produced in auroral ovals in addition to charged particle heating and the equatorial EUV heating. The JTGCM temperatures in the nano-bar (1 nbar = 10−9 bar) region are also found to be in reasonably good agreement with those inferred from the analysis of Voyager UVS data and CFHT high-resolution H+ 3 emission spectra. However, the JTGCM temperatures between 1 and 10 bar appear to be slightly cooler than the measured temperatures. This suggests that meridional ﬂow of heat transport is still insuﬃcient to compete with radiative and adiabatic processes of cooling and thus the thermal budget at the entry location of the Galileo probe is dominated and controlled by

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the resulting net cooling from hydrocarbon (CH4 and C2 H2 ) radiation and upwelling winds. In the thermosphere between 1 and 0.01 µbar (1 µbar = 10−6 bar), the JTGCM (Curve C) predicts rapidly rising temperature as the meridional ﬂow of auroral winds carries auroral energy to lower latitudes. A similar rapid rise in temperature can be seen in the measured proﬁle with peak temperature gradient of 5 K/km at 0.3 µbar. At the Galileo probe location, the JTGCM predicts an integrated energy ﬂux of ∼1.35 ergs cm−2 s−1 [c.f., 18] for the region with pressures <1 µbar, for which the model has achieved steady-state conditions. This value is almost 30% larger than that used analytically by Yelle et al.52 to explain the measured temperature at 10 nbar51 and 0.3 µbar.50 The impact of excess joule heating on the heat transport processes, which control the thermospheric temperatures in the auroral14,20 and equatorial regions,18 has also been studied. This simulation has been run for 84 Jovian days to achieve equilibrium in temperatures and wind ﬁelds. Curve D in Fig. 3 shows an example of the equatorial temperature proﬁle from such a simulation that assumes twice the joule heating (30%) compared to the one that explains the Galileo temperature proﬁle. In this case, the exospheric temperature reaches up to 1880 K as a result of increased meridional transport of auroral heat to the entry location of the Galileo probe. Figure 4 shows the vertical proﬁles of thermal processes that best describe the thermal structure measured in situ by the Galileo probe and temperature data from various sources. The thermal balance between adiabatic heating, caused by compression of the neutral atmosphere, and cooling by thermal conduction (see Fig. 4a) plays an important role in maintaining an exospheric temperature of ∼890 K. Figure 4b shows that the Jovian wind system between 0.2 µbar and 1 nbar seems to play an active role in transporting energy from the oval regions to the equatorial region. While adiabatic and horizontal advection processes dominate the heat budget, the process of heat conduction combined with the H+ 3 cooling tends to cool down the atmosphere up to the pressure level of 0.2 µbar. The resulting net heating rate is overwhelmed by transport sources, yielding a rapid increase in equatorial temperatures from 0.2 to 0.01 µbar. The average timescale of heat transport and the corresponding timescale of cooling for pressure at <1 µbar is estimated to be nearly 2 × 106 s.18 Clearly, the magnitudes of heating and cooling timescales suggest that an estimated time of more than 70 Jupiter days is required for the Jovian winds to

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Fig. 4. Altitude proﬁles of heat balances for the JTGCM simulation representing curve C in Fig. 2 for three pressure regimes, (a) 10−9 to 10−12 bar, (b) 10−6 to 10−9 bar, and (c) 10−4 to 10−7 bar. Note that the heating and cooling rates are scaled in panel (b) and (c) by 10−2 and 10−3 , respectively [From 18]. Individual curves are delineated as follows: conduction (solid), adiabatic heating/cooling (dotted), hydrodynamic advection (dashed), IR cooling (dashed-dotted), solar EUV heating (3-dot dashed).

transport auroral heat to the equatorial region and to cool oﬀ the upper thermosphere. Note that dynamical sources of heat play an important role in our understanding of the bulk of the equatorial heat budget for the region where steady-state conditions prevail. However, as the pressure increases toward the lower boundary, the JTGCM ﬁelds begin to oscillate, causing a departure of the temperature ﬁeld from steady-state conditions. As shown in Fig. 4c, the dynamical heating in this region with strong thermospheric winds is eﬃciently dissipated by hydrocarbon cooling, caused by CH4 (7.8 µm) and C2 H2 (12.6 µm) radiation.14 4.2. Auroral oval temperatures Figure 5 shows the average JTGCM temperature proﬁles for the northern (dashed curve) and southern (solid curve) ovals from the simulation which incorporates ion drag terms and 15% of the total joule heating produced in

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Fig. 5. Average JTGCM temperature proﬁles both for southern and northern auroral ovals are shown in comparison with remotely sensed temperature observations from many sources [From 20].

the ovals, in addition to auroral heating caused by precipitated charged particles. These temperature proﬁles are used to interpret the existing auroral temperature data derived from various multispectral observations. The JTGCM temperatures at nanobar levels are found to be in reasonably good agreement with those inferred from the analysis of CFHT highresolution mapping of the H+ 3 emissions from both the northern (green triangle and diamond) and southern (blue asterisk) auroral regions.53 The temperatures derived from UKIRT47 near the H+ 3 peak from both the northern and southern intense H+ emissions (black asterisk and 3 square, respectively) are also in good agreement with those simulated by the JTGCM. Note that the thermospheric temperature for the southern auroral region observed with both CFHT and UKIRT is warmer than the northern auroral region, consistent with the JTGCM simulation. Figure 5 also shows the derived temperature near the homopause from HST-STIS (purple square) observation of intense H2 emissions characterizing the main northern auroral oval.54 This temperature is in excellent agreement with the JTGCM temperature. The temperatures derived from the analysis of the northern FUSE spectra (red diamond, triangle, and square) with many

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new H2 spectral features55 have shown reasonable agreement with the JTGCM temperature at 0.01 µbar. However, the JTGCM temperatures at around 1 µbar are found to be cooler than the FUSE temperatures. The cooler JTGCM temperatures are also predicted in comparison with IRFT (∼0.01 µbar)56 and GRHS (∼4 µbar)50 temperature observations for the northern oval. The vertical thermal structure of the Jovian stratosphere for pressure >2 µbar derived from ground-based occultation of HIP 936957 and Beta Scorpii58 by Jupiter’s northern and southern polar regions, respectively, are compared with those simulated by the JTGCM (see Fig. 5). The simulated temperature proﬁle in the north is in reasonably good agreement with those inferred from HIP 9369 occultation data (both ingress and egress; dark green curve) for pressure >3 µbar. However, in the south, the JTGCM temperatures between 2 µbar and 10 µbar are found to be considerably larger than those derived from Beta Scorpii occultation data (both ingress and egress; red proﬁle). For this simulation, IR cooling processes are still competing with dynamical terms of heat transport to increase hydrocarbon radiation. Thus, the thermal budget in the Jovian southern stratosphere appears to be dominated and controlled by the resulting net heating from hydrodynamic advection and adiabatic processes. The vertical proﬁles of the JTGCM thermal balances averaged over the entire oval that best describes the measured temperatures from multispectral observations of the Jovian aurora are shown in Figs. 6 and 7, for the southern and northern hemispheres, respectively. Clearly, the balance between auroral heating caused by precipitating charged particles and corresponding adiabatic cooling caused by neutral outﬂows (Fig. 6a) plays an important role in maintaining an exospheric temperature of about 1180 K in the southern oval, consistent with the CHFT temperature derived from 2 µm auroral emissions. In the northern oval, however, intense particle heating is primarily balanced with cooling generated by molecular conduction (see Fig. 7a) to maintain an exospheric temperature of about 980 K, consistent with those derived from CFHT observations of the Jovian northern aurora. In the southern thermosphere between 1 µbar and 1 nbar, joule heating and forcing by ion drag dominate the heat budget with a peak value of ∼ 3.7 × 107 eV cm−3 s−1 at 0.8 µbar (Fig. 6b). This huge amount of heat is largely balanced by cooling caused by horizontal advection, induced by meridional ﬂow with a maximum speed of ∼60 m/s. This thermal balance yielded a temperature of about 500 K at 0.8 µbar. A rapid increase in oval temperature is seen between 0.3 µbar and 0.02 µbar (see Fig. 6b) owing to

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Fig. 6. Average altitude proﬁles of heat balances are shown for the JTGCM simulation of the southern auroral oval. Three pressure regimes are shown (a) 10−9 to 10−12 bar, (b) 10−6 to 10−9 bar, and (c) 10−4 to 10−6 bar. Note that the heating and cooling rates are scaled in the three panels [from 20]. Individual curves are delineated as follows: conduction (solid), adiabatic heating/cooling (dotted), hydrodynamic advection (shortdashed), IR cooling (dashed-dotted), auroral heating (3-dot dashed), and Joule heating (long-dashed) [From 20].

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Same as Fig. 6, but for northern auroral oval [From 20].

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the net heating rate, predominantly controlled by the ion-drag process. In contrast, the impact of smaller ion-drag forcing and corresponding joule heating on the underlying northern thermosphere tends to provide the necessary cooling from horizontal advection induced by meridional ﬂow and IR cooling resulting from CH4 (7.8 µm) and C2 H2 (12.6 µm) radiation (see Fig. 7b). The Jovian thermosphere from the homopause (∼1 µbar) to the lower boundary of the JTGCM is the most complicated region. The competing processes responsible for controlling the thermal structure have not yet reached equilibrium. Downward motion is still causing atmospheric compression while meridional ﬂow is still transporting heat away from ovals. The net heating rate for the thermal structure in this region is determined by the competition between heat transport processes and radiative cooling processes. Figures 6c and 7c reveal that strong dynamical heating, mainly due to the horizontal advection process, with a minor contribution from adiabatic compression of neutral ﬂow, is in control of the net thermal budget of the lower thermosphere for both the northern and southern ovals, respectively. This strong dynamical heating in the JTGCM is regulated by an extremely large amount of cooling resulting from hydrocarbon radiation. The net impact of this thermal balance on the Jovian thermosphere can be seen from the distribution of neutral temperature, as shown in Fig. 5.

5. Conclusions We use our 3-D Jupiter Thermospheric General Circulation Model (JTGCM) to report input parameterizations and processes that drive the thermal structure and neutral wind system at Jupiter from 20 µbar to 1.1 × 10−4 nbar (or 250 km to 2100 km altitude). The JTGCM has been used to address global temperatures, three-component neutral winds, and neutral–ion species distributions in the Jovian thermosphere. The results of a case study from this JTGCM are presented that incorporate auroral heating due to particle precipitation, ion drag and joule heating rates. We ﬁnd that the best simulation, which can reasonably match available multispectral temperature data and the Galileo temperature proﬁle near the Jovian equator, requires 15% of the total joule heating produced in auroral ovals in addition to auroral heating by precipitating charge particles. The resulting strong neutral winds up to 1.3 km/s in the auroral ovals and underlying global thermospheric circulation play a signiﬁcant role in regulating the transport of energy outward from the auroral regions to the

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rest of the planet. Dynamical heating terms in fact are key to reproducing the observed temperatures near the Jovian equator and in the auroral zone. A north–south asymmetry exists in the JTGCM circulation and temperature distribution, which is related to hemispheric diﬀerences in the parameterized high-latitude ion convection pattern. Acknowledgements We are grateful to the National Center for Atmospheric Research (NCAR) for the use of the IBM/SP and SGI supercomputer resources necessary to develop and exercise the JTGCM thermospheric model and its postprocessor. In addition, special thanks go to Ben Foster of NCAR for his help preparing the JTGCM code to run on the IBM/SP computers. References 1. A. L. Broadfoot et al., Science 204 (1979) 979. 2. D. Grodent et al., J. Geophys. Res. 113, A01206, doi:10.1029/2007JA012601 (2008). 3. J. Gustin et al., J. Geophys. Res. 111, A09220, doi:10.1029/2006JA011730 (2006). 4. J. M. Ajello, W. Pryor, L. Esposito, I. Stewart, W. McClintock, J. Gustin, D. Grodent, G.-C. G´erard and J. T. Clarke, Icarus 178 (2005) 327. 5. R. P. Wayne et al., Icarus 178 (2005) 312. 6. J. Gustin, et al., Icaus 171 (2004) 336. 7. K. K. Khurana, J. Geophys. Res. 106 (2001) 25,999. 8. J. H. Waite, Jr. and D. Lummerzheim, Comparison of auroral processes: Earth and Jupiter, in Atmospheres in the Solar System: Comparative Aeronomy, Geophys. Monogr. Ser. Vol. 130, edited by M. Mendillo, A. F. Nagy and J. H. Waite, pp. 115–139, AGU, Washington, D. C. (2002). 9. T. W. Hill, J. Geophys. Res. 106 (2001) 8101. 10. S. W. H. Cowley and E. J. Bunce, Planet. Space Sci. 49 (2001) 1067. 11. S. W. H. Cowley, E. J. Bunce and J. D. Nichols, J. Geophys. Res. 108, doi:10.1029/2002JA009329 (2003). 12. J. H. Waite, Jr., T. E. Cravens, J. U. Kozyra, A. F. Nagy, S. K. Atreya and R. H. Chen, J. Geophys. Res. 88 (1983) 6143. 13. D. Grodent, J. H. Waite, Jr. and J-C. Gerard, J. Geophys. Res. 106 (2001) 12,933. 14. S. W. Bougher, J. H. Waite, T. Majeed and G. R. Gladstone, J. Geophys. Res. 110 (2005) E04008, doi:10.1029/2003JE002230. 15. L. A. Young, R. V. Yelle, R. Young, A. Sieﬀ and D. B. Kirk, Icarus 173 (2005) 185. 16. N. Achilleos, S. Miller, J. Tennyson, A. D. Aylward, I. Mueller-Wodarg and D. Rees, J. Geophys. Res. 103 (1998) 20,089.

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47. S. Miller, N. Achilleos, G. E. Ballester, H. A. Lam, J. Tennyson, T. R. Geballe and L. M. Trafton, Icarus 130 (1997) 57. 48. S. K. Atreya, T. M. Donahue and M. Festou, Astrophys. J. 247 (1981) L43. 49. W. B. Hubbard, V. Hammerle, C. C. Porco, G. H. Rieke and M. J. Rieke, Icarus 113 (1995) 103. 50. W. Liu and A. Dalgarno, Astrophys. J. 462 (1996) 502. 51. A. Marten, C. DeBergh, T. Owen, D. Gautier, J. P. Maillard, P. Drossart, B. L. Lutz and G. S. Orton, Planet. Space, Sci. 42 (1994) 391. 52. R. V. Yelle, L. A. Young, R. J. Vervack, R. Young, L. Pﬁster and B. R. Sandel, J. Geophys. Res. 101 (1996) 2149. 53. E. Raynaud et al., Icarus 171 (2004) 133. 54. J. Gustin, D. Grodent, J. C. Gerard and J. T. Clarke, Icarus 156 (2002) 91. 55. J. Gustin et al., Icarus 171 (2004) 336. 56. T. Stallard, S. Miller, G. Millward and R. D. Joseph, Icarus 154 (2001) 475. 57. E. Raynaud et al., Icarus 162 (2003) 344. 58. E. Raynaud, K. Matcheva, P. Drossart, F. Roques and B. Sicardy, Icarus 168 (2004) 324.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

THE SATURN HOT ATOMIC HYDROGEN PLUME: QUANTUM MECHANICAL INVESTIGATION OF H2 DISSOCIATION MECHANISMS XIANMING LIU∗,§ , D. E. SHEMANSKY†,¶ , P. V. JOHNSON∗, , C. P. MALONE‡ , H. MELIN† , J. A. YOUNG∗ and I. KANIK∗,∗∗ ∗ Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA † Planetary and Space Science Division, Space Environment Technologies, Pasadena, CA 91107, USA ‡ Department

of Physics, California State University, Fullerton, CA 92834, USA § [email protected] ¶ [email protected] [email protected] ∗∗ [email protected]

The Cassini/Huygens Mission to Saturn has provided new observations of thermospheric processes that emphasize the need for further work on the properties of weakly ionized hydrogen. The Cassini UVIS experiment has obtained high spatial resolution images of atomic and molecular hydrogen in the atmosphere and magnetosphere of Saturn. The images show atomic hydrogen ﬂowing out of the top of the sunlit thermosphere in a conﬁned, distinct plume in ballistic and escaping orbits, and reveal a continuous distribution of atomic hydrogen from the top of the Saturn atmosphere, measurable to at least 45 Saturn radii in the satellite orbital plane, and measurable to 30 Saturn radii latitudinally above and below the plane. Possible processes for the fast atomic hydrogen formation include the excitation of H2 singlet-ungerade states, doubly excited states by photons and electrons, the excitation of the singlet-gerade and triplet states by electrons, and chemical reactions involving the formation and dissociative recombination of H+ 3 . Based on the available laboratory measurements and quantum mechanical calculations, the various mechanisms for H2 → H production are examined here, especially those producing H atoms with suﬃcient energy to escape from Saturn. It is found that electron excitation of vibrationally excited H2 X 1 Σ+ g to the dissociative b3 Σ+ u state, as well as excitation to the doubly excited states and dissociative ionic states by solar photons and electrons, are mechanisms for the production of the observed hot hydrogen plume, and extended distribution in the magnetosphere.

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1. Introduction In 2005, virtual images of the Saturn system were obtained using the Cassini UVIS (Ultraviolet Imaging Spectrograph) experiment at a pixel resolution of 0.1 × 0.1 Saturn radii (RS ) in a unique geometry in which the rings were edge-on to the spacecraft, eliminating scattering or obscuration eﬀects. The image pixel content is composed of spectral vectors containing the accumulated exposure to the emission in a multiply scanned systemcentered matrix. The image data shows H Lyman-α (Ly-α) in ballistic and escaping trajectories sourced at the top of the thermosphere, mainly in the southern sunlit hemisphere.1, 2 Earlier low spatial resolution images were obtained by the Voyager UVS (Ultraviolet Spectrograph) experiment.3 Emission spectra of the H2 singlet-ungerade Rydberg series show strong deviation from local thermodynamic equilibrium (LTE) in the main source region and the X 1 Σ+ g state is found to be highly excited. Fig. 1 shows a contour plot of the H Ly-α image. The main feature in the image is

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Fig. 1. Cassini UVIS image of the Saturn system in a surface contour plot in H Ly-α emission showing the escape of atomic hydrogen in a non-uniform asymmetric distribution from the top of the Saturn atmosphere. Image accumulated 2005 DOY 74–86 at spacecraft-planet range of 24–44 RS . The image pixel size is 0.1 × 0.1 RS . The edge-on view of the rings is indicated; sub-spacecraft latitude is 0◦ . The 1 bar level and terminator (Sun on right side of image) is indicated by white dots. Range in the virtual image is indicated at the frame of the image in units of RS , where 0,0 is the position of the planet center. Contour lines of constant brightness are shown on the plot with Rayleigh brightness values given at selected locations. The locally conﬁned emission structure contains a foreground/background signal broadly distributed throughout the magnetosphere with magnitudes indicated near the north and south frames of the image. The core of the plume is at −13.5◦ planetocentric latitude. Subsolar latitude is −22.3◦ . Auroral emission is apparent at the poles extending over the terminator. Solar phase is 77◦ .

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a distinctive plume structure with a FWHM of 0.56 RS at the exobase sub-solar limb at ∼−13.5◦ planetocentric latitude constituting the core of the distributed outward ﬂow of HI from the sunlit hemisphere, with a counterpart on the anti-solar side peaking near the equator above the exobase limb. The structure of the image indicates that part of the out-ﬂowing population is sub-orbital and re-enters the thermosphere in ∼5 hour time scale. A larger and more broadly distributed component ﬁlls the magnetosphere to beyond 45 RS in the orbital plane and 20 RS FWHM latitudinally in an asymmetric distribution in local time.1–3 The phenomenon of escaping atomic hydrogen is unique to Saturn in two properties. First, the magnitude of the gravitational potential is small enough to accommodate the loss of the atomic dissociation products produced in the activated thermosphere. Secondly, Saturn is the only planet showing a remarkably conﬁned low latitude region in the sunlit atmosphere away from auroral inﬂuence from which a large fraction of out-ﬂowing hydrogen originates. The auroral zones are in fact not a signiﬁcant source of escaping atomic hydrogen and are not a measurable source on the magnitude scale of the low latitude outﬂow. It has also been found that the emission spectra of H2 singlet-ungerade states in the primary atomic hydrogen source region are highly non- LTE.1 The spectra in both extreme and far ultraviolet (EUV and FUV) regions collected along with the H Ly-α into the image mosaic show a distinctive H2 resonance property correlated with the location of the H Ly-α plume. Figure 2 shows an image of the H2 band resonance emission in the 1,220–1,370 ˚ A spectral region, corresponding to the same data set shown in Fig. 1. This ﬁgure shows the conﬁnement of H2 EUV/FUV band emission mainly to the southern hemisphere, with a ridge of emission roughly aligned with the atomic hydrogen plume and relatively strong emission crossing the terminator into the dark-side in the southern hemisphere. These properties infer electrodynamic electron impact excitation in the vicinity of the exobase. Emission in the H2 resonances shown in Fig. 2 show no detectable polar enhancement associated with the auroral zones, and in the north polar region the emission in these features is not detectable. Escaping hot atomic hydrogen is also not measurable above the foreground/background resident magnetospheric H Ly-α signal in the polar regions (Fig. 1). Heating at the poles by dissociation of H2 in auroral deposition in these observations must therefore be deeper and closer to the local heat sink. Contemporaneous published global model calculations4 assuming auroral deposition to be a major source of thermospheric heating show

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Fig. 2. Cassini UVIS image of Saturn in a surface contour plot in H2 band emission in the 1,220–1,370 ˚ A region from the same data set shown in Fig. 1. The 1 bar level and terminator (Sun on right side of image) is indicated by white dots. Range in the virtual image is indicated at the frame of the image in units of RS (Saturn radii), where 0,0 is the position of the planet’s center. Contour lines of constant brightness are shown on the plot. Rayleigh brightness values are indicated at selected locations on the image. The image shows a bright emission ridge roughly aligned with the plume feature in Fig. 1, and emission crossing the terminator in the southern hemisphere. Resonance emission is not strong in the auroral regions.

very hot polar thermosphere temperatures, but slow meridional transport leaves cold low latitude temperatures in the absence of additional processes. While the inferred approximate globally averaged energy deposition at the top of the thermosphere from the production of the hot atomic hydrogen can account for the measured atmospheric temperature,1 the mechanisms of the production of hydrogen atoms with suﬃcient kinetic energy to escape the gravitational potential are not fully delineated. The present paper explores mechanisms for the production of fast atomic hydrogen atoms responsible for the observed plume. The dominance of H2 in the atmosphere dictates that any plausible processes of hot HI atom production must involve H2 , which can be ro-vibrationally excited as inferred from observed H2 emission spectra of the singlet-ungerade states. The escape energy of a hydrogen atom at 2,000 km above the 1 bar level varies from 5.7 eV at the equator to 7.0 eV at the poles. The task of the present paper reduces to the examination of chemical reactions and excitation-dissociation processes of H2 and hydrogenic plasma products that produce HI with kinetic energy in the range up to and above 5.7 eV. The present work examines the kinetic energy distribution of HI produced

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from excitation into continuum levels of singlet-ungerade states, singletgerade states, triplet states, ionic states, and doubly excited states. 2. Method This section describes calculations of the photodissociation cross sections and discrete-continuum Franck-Condon factors. Both quantities are diﬀerential, and display the relative magnitude of dissociation in terms of the kinetic energy of the hydrogen atom product. Visual inspection of both quantities, in many cases, is suﬃcient to give a qualitative assessment of the importance of the process for energetic atom production. Both quantities are important for quantitative modeling of the hot hydrogen outﬂow on Saturn. Throughout the paper, we use indices i and j to denote levels of H2 X 1 Σ+ g and the excited electronic state, respectively. 2.1. Photodissociation cross section Under irradiation by photons with energy of Eph = hcν, the dissociation cross section for excitation from (vi , Ji ) to the continuum level (Ek , Jj ) is5 σ(vi , Ji ; Eph ) =

8π 3 ν Hji (Jj , Ji ) ρ(Ek )Υj,i (R) 3hc 2Ji + 1

(1)

Jj

where Υj,i (R) = |χEk ,Jj (R)|D(R)|χvi ,Ji (R)|2 , Hji (Jj , Ji ) and D(R) are the H¨onl-London factors and the electric dipole transition moment. χvi ,Ji (R) and χEk ,Jj (R) are the radial wave functions of initial level i and the continuum level j, respectively. ρ(Ek ) is the densityof-states normalization factor at energy Ek = hcνk above the dissociation limit of state j: δ(Ek − Ek ) ρ(Ek )

(2)

Ek = Eph + E(vi , Ji ) − Vj (R → ∞),

(3)

χEk ,Jj (R)|χEk ,Jj (R) =

where Vj (R → ∞) is the asymptotic potential energy of state j. It is convenient to convert internuclear distance, R, to a dimensionless quantity z = R/R0 where R0 is an arbitrarily selected scale length. Two A or 1 a0 (bohr).5, 6 In the present work, the convenient values for R0 are 1 ˚ amplitude of the continuum wave function is asymptotically normalized

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to unity: lim χEk ,Jj (z) = sin[kz + ηJj (Ek )],

z→∞

(4)

where ηJj (Ek ) is the phase shift and k = 2πR0 2µcνk /h, with µ being the reduced mass of H2 . The conversion and normalization give a density of states factor of ρ(Ek ) = 2R0 2µc/hνk (states per cm−1 ). The photodissociation cross section in equation (1) in units of Mb can be re-written as:6 2 4µEph Hji (Jj , Ji ) Υj,i (z), σ(vi , Ji ; Eph ) = 25.936 (5) mH Ek 2Ji + 1 Jj

where Eph and Ek are in hartree, D(z) is in au, R0 in bohr (a0 ), and mH is HI mass. 2.2. Franck-Condon factors The discrete-continuum Franck-Condon factor is the square of the overlap integral of χvi ,Ji (z) and the energy normalized continuum vibrational wave function. However, since the amplitude of χEk ,Jj (z) is asymptotically normalized to unity, an energy normalization factor, ρ(Ek ), must be applied. The diﬀerential Franck-Condon factor, in units of per hartree, is µ |χEk ,Jj (z)|χvi ,Ji (z)|2 (6) F CF (vi , Ji ; Ek , Jj ) = 19.289 mH Ek where Ek is in hartree and R0 in bohr. 2.3. Potential energy curves and transition moments The discrete and continuum nuclear wave functions, χvi ,Ji (R) and χEk ,Jj (R), are obtained by numerical solution of the Schr¨ odinger equation. For the X 1 Σ+ state, the Born-Oppenheimer (BO) potential g of Wolniewicz et al. ,7 along with adiabatic, relativistic and radiative corrections of Wolniewicz,8 is used. For the npσ 1 Σ+ u states, BO and adiabatic potentials calculated by Staszewska and Wolniewicz,9 and Wolniewicz and Staszewska10 are used. In addition, relativistic and radiative corrections, wherever available, are also applied.11 Similarly, BO and adiabatic potentials calculated by Wolniewicz and Staszewska12 along with appropriate relativistic and radiative corrections are used for the npπ 1 Πu states. Ab initio transition moments, D(R), calculated by Wolniewicz and Staszewska 10, 12 are utilized for the photodissociation cross

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1 1 + sections of the npσ 1 Σ+ u and npπ Πu −X Σg transitions. Finally, ab initio potentials and transition moments are not available for the high n Rydberg states. The approximate method via quantum defect theory outlined by Glass-Maujean et al.13 can be utilized to derive the estimated BO potentials and transition moments. 3 + 3 For the triplet states, adiabatic potentials of the a3 Σ+ g , b Σu , c Π u , 3 + 3 + 3 + 3 3 3 3 e3 Σ+ u , f Σu , g Σg , h Σg , i Πg , k Πu , r Πg and w Πg states and electronic transition moments between these states have been accurately calculated by Staszewska and Wolniewicz.14, 15 In addition, the nonadiabatic coupling of 16 the a3 Σ+ Results obtained g state has recently been treated by Wolniewicz. from these ab initio calculations are suﬃcient to evaluate the adiabatic transition probabilities of the triplet states and Franck-Condon factors between the X 1 Σ+ g state and the triplet states. For the singlet-gerade states, the EF 1 Σ+ g adiabatic potential of 1 + 1 + Orlikowski et al.,17 the GK 1 Σ+ g , P Σg and O Σg potentials of Wolniewicz ¯ 1 Σ+ and Dressler18 and Dressler and Wolniewicz,19 and the H H g potential 20 reﬁned by Wolniewicz are used. Ab initio potentials of other singletgerade states21 are also utilized. The discrete transition probabilities between singlet-gerade and singlet-ungerade states have been reported by Liu et al.22, 23 For the doubly excited states, the potential curves for the Q1 and Q2 series by S´anchez and Mart´ın24, 25 and the Q3 and Q4 series by Fern´ andez and Mart´ın26 are utilized to calculate Franck-Condon factors. Except for the lowest states of the Q1 and Q2 series calculated by Guberman27 and Borges and Bieloschowsky,28 electronic transition moments to the remaining doubly excited states are not available. The potential energy curves of H+ 2 calculated or tabulated by Hunter 29 30 et al. and Sharp are used to calculate Franck-Condon factors for dissociative ionization. The Flannery et al.31 transition moment is used to + 2 + calculate the photoionization cross section of the H2 X 1 Σ+ g to H2 X Σg transition.

3. Results 3.1. Excitation to singly excited states 3.1.1. Singlet-ungerade excitation Dissociation of H2 via singlet-ungerade Rydberg states can take place by either photon or electron excitation. Excitation of H2 to the continuum levels of the singlet-ungerade states results in direct dissociation that

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produces one hydrogen atom in the ground state and one in the excited state. Apart from direct dissociation, predissociation, arising from excitation to the ro-vibronic levels that are coupled to the continuum levels, also takes place. A number of theoretical calculations6, 32–34 have shown that photoexcitation to the continuum levels of singlet-ungerade states produces very few hydrogen atoms with kinetic energy greater than 3.5 eV. Figure 3 1 displays photodissociation cross sections of the B 1 Σ+ u and D Πu states 1 + from various (vi , Ji ) levels of the X Σg state as a function of the kinetic energy of outgoing hydrogen atom. 1 1 + The B 1 Σ+ u , C Πu and B Σu states are not predissociated by other singlet-ungerade states, though excitation to the H(1s) + H(2 ) continuum 1 + is signiﬁcant. Predissociation is possible for the other npσ 1 Σ+ u and npπ Πu states. A number of experimental and theoretical investigations by GlassMaujean and co-wokers have shown that the predissociation in the npσ 1 Σ+ u and npπ 1 Π+ u states is primarily caused by direct or indirect coupling to the 35–38 B 1 Σ+ The D1 Π+ u continuum. u levels above the H(1s) + H(2 ) limit are directly predissociated by the B 1 Σ+ u continuum. The predissociation (n > 4) takes place by homogeneous coupling with the B 1 Σ+ of npσu1 Σ+ u u continuum levels.36 The predissociation of npπu1 Π+ u (n > 3) takes place by 1 + 1 + 1 + either npπu1 Π+ u −D Πu homogeneous coupling followed by D Πu −B Σu 1 + 1 + Coriolis coupling or npπu Πu − npσu Σu Coriolis coupling followed by 1 + 1 − 1 − npσu1 Σ+ u −B Σu homogeneous coupling. The D Πu and npπu Πu states 1 + 1 + are not coupled to the B Σu or other npσu Σu states. They can only 1 − couple to a dissociating 1 Π− u state. Among the npπu Πu states below 1 − the H(1s) + H(n = 3) limit, C Πu is the only dissociative 1 Π− u state. 1 − Since npπu1 Π− states are only weakly coupled to the C Π state, their u u predissociation rates are negligibly small. The kinetic energy distribution of hydrogen atoms produced by predissociation of the singlet-ungerade states is similar to that from direct dissociation. Fig. 3 shows the photodissociation cross sections from various 1 + 1 vi levels of the X 1 Σ+ g state to the continuum levels of the B Σu and D Πu states as a function of the HI kinetic energy. From vi = 0, singlet-ungerade excitation can only generate hydrogen atoms with Ek < 1 eV. While more energetic hydrogen atoms can be produced from vi > 0 levels, very few hydrogen atoms with Ek > 3.5 eV are produced from H2 singlet-ungerade continuum levels. Electron excitation of H2 singlet-ungerade states above ∼20 eV is dominated by the dipole component.39 Electron impact excitation in

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1 Fig. 3. Photodissociation cross sections of the B 1 Σ+ u and D Πu state as a function of the kinetic energy of outgoing hydrogen atoms.6,33 Top panel: excitation from (vi = 1 + 0−7, Ji = 1) levels of the X 1 Σ+ g state to the B Σu continuum. Bottom panel: excitation 1 from (vi = 0 − 7, Ji = 0) levels of the X 1 Σ+ g state to the D Πu continuum. Note that in both cases very few, if any, hydrogen atoms with Ek > 3.5 eV are produced.

the high energy region is equivalent to photoexcitation. Electron impact dissociation cross sections of singlet-ungerade states is obtained from the corresponding photodissociation cross sections and the measured electron excitation functions.6 The kinetic energy distribution of hydrogen

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atoms produced by electron-impact is similar to photodissociation, shown in Fig. 3. 3.1.2. Singlet-gerade excitation Electron–electron exchange excitation of X 1 Σ+ g to singlet-gerade states is signiﬁcant in the low energy region.22, 23 In the asymptotic limit, the relative value of the electronic form factor is nearly independent of rovibrational quantum number and the Franck-Condon factor gives an accurate representation of relative diﬀerential cross sections with respect to kinetic energy of the outgoing HI from diﬀerent initial (vi , Ji ) levels. The discrete-continuum Franck-Condon factor thus represents the relative kinetic energy distribution of H atoms from various (vi , Ji ) levels of the X 1 Σ+ g state. 1 + ¯1 + Franck-Condon factors for X 1 Σ+ and X 1 Σ+ g −EF Σg g −H H Σg 22 discrete-continuum excitations are very small. The dissociation of H2 is thus dominated by the second member of the singlet-gerade series, the GK 1 Σ+ g state. Fig. 4 shows Franck-Condon factors to the continuum levels 1 + of the GK 1 Σ+ g state from several X Σg (vi , Ji ) levels. In general, more energetic atoms are more eﬃciently produced from higher initial vi levels. The continuum levels of higher singlet-gerade states such as J 1 ∆g , O1 Σ+ g,

Fig. 4. Franck-Condon factors from various vi levels of the X 1 Σ+ g state to the continuum levels of the GK 1 Σ+ g (Ek ) state. Note the negligible value for Ek > 3.5 eV.

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and P 1 Σ+ g all have small Franck-Condon overlap integrals with the vi = 0 1 + 1 level of the X 1 Σ+ g state, but are signiﬁcant for vi > 1. The X Σg −I Πg transition has a large discrete-continuum overlap integral for all vi . The excitation cross sections of the high lying states, however, are generally small.22, 40 The HI kinetic energy from these states is also mainly below 3.5 eV. We note, however, that production of <3.5 eV atoms at the exobase produce observed sub-orbital atoms shown in Fig. 1. Another mechanism of HI formation is via the continuum of the X 1 Σ+ g state. This primarily involves direct excitation of the singlet-ungerade states, followed by spontaneous decay to the continuum of the X 1 Σ+ g state. 1 + 1 + Excitation from low vi levels of X Σg gives the strongest B Σu −X 1 Σ+ g band system continuum emission. Continuum transitions of the B 1 Σ+ u, 1 1 + C 1 Π u , B 1 Σ+ u and D Πu −X Σg band systems have been investigated 41 by Stephens and Dalgarno, and Abgrall et al.,42 who found that these transitions produce hydrogen atoms with low kinetic energy. Nonadiabatic coupling among the singlet-gerade states leads to predissociation of some discrete levels.43, 44 Given that predissociation is ultimately caused by direct or indirect coupling with the continuum, the energy distribution of HI arising from predissociation should be similar to those of the continuum levels. 3.1.3. Triplet excitation Excitation to the triplet states by low energy electrons is a very important dissociation channel. Except for a few rotational levels of the c3 Π− u (0) state, excitations to all other triplet levels eventually end in dissociation or predissociation resulting in the production of fast H(1s) atoms. The lowest triplet state is the repulsive b3 Σ+ u . The next higher triplet state is a 3 Σ+ , the lowest triplet gerade state. Excitation of the a3 Σ+ g g state produces 3 + 3 + the so-called a Σg −b Σu continuum. Hydrogen molecules excited to other 3 + higher triplet states either cascade to b3 Σ+ u or a Σg and dissociate into 3 + fast H(1s) atoms via b Σu . Some rotational levels of c3 Πu (0) are lower in 3 + energy than counterparts of v = 0 of a3 Σ+ g . Spontaneous decay to a Σg is 3 + not possible for these levels. The c3 Π+ u state can be predissociated by b Σu 3 + 3 + 3 − via Σu − Πu coupling. These levels of c Πu (0) are metastable. The normalized kinetic energy distribution of H atoms from several 3 + ro-vibrational levels of the X 1 Σ+ g state excited to b Σu at asymptotic excitation energy is shown in the top panel of Fig. 5. Signiﬁcant populations of atoms with kinetic energy above 5 eV can be produced by excitation of

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Fig. 5. Top panel: relative H(1s) kinetic energy distribution from the X 1 Σ+ g (v, J) −b3 Σ+ u dissociative excitation at asymptotic energy as determined by Franck-Condon factors. Note that a signiﬁcant portion of H(1s) atoms with Ek > 5 eV can be produced via direct excitation from the vi ≥ 2 level of the X 1 Σ+ g state. Bottom panel: H2 3 + a3 Σ+ g −b Σu continuum transition probabilities as a function of the kinetic energy of 3 + 3 + outgoing hydrogen atom. In contrast to direct excitation to b3 Σ+ u , the a Σg −b Σu transition produces low energy atomic hydrogen with negligible HI formed with Ek > 3.5 eV.

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3 + H2 X 1 Σ+ g (vi ≥2). In contrast, the indirect excitation of b Σu by cascade from higher triplet states through a3 Σ+ g produces hydrogen atoms with moderate kinetic energy. The bottom panel of Fig. 5 shows the kinetic 3 + 45 The kinetic energy energy distribution produced via a3 Σ+ g −b Σu cascade. 3 + 3 + distribution of HI from somewhat less important g Σg and h3 Σ+ g −b Σu 3 + 3 + transitions is similar to that of a Σg −b Σu . The highest possible kinetic 3 + 3 + 3 + energy of HI formed from the a3 Σ+ g , g Σg and h Σg −b Σu transitions is limited to 5.1 eV.

3.2. Excitation to doubly excited and ionic states Doubly excited states of H2 can be viewed as a Rydberg series converging to the excited electronic states of H+ 2 (Fig. 6). The Q1, Q2, and Q3 series refer 2 2 + to Rydberg states converging to the 2pσu2 Σ+ u , 2pπu Πu , and 2sσg Σg ionic 1 + 2 states, respectively. The excitation from the X Σg (1sσg ) state to doubly excited states requires simultaneous change of two electron conﬁgurations and is forbidden within the independent electron model. Photoexcitation to the doubly excited states takes place through electron correlation. The cross section of doubly excited states is very small. Figure 6 shows the potential energy curves of Q1, Q2, Q3 and Q4 doubly excited states that can be accessed by photons from the X 1 Σ+ g state. Since most doubly excited H2 states autoionize to form HI and H+ , the total excitation cross sections to doubly excited states by electrons or photons can be estimated from the measured dissociative ionization cross section after the contributions 2 + of the H+ 2 ionic states are removed. X Σg is the only bound state of + + H2 . Excitation to the continuum levels of X 2 Σ+ g produce H(1s) and H + with low kinetic energy. All excited electronic states of H2 are repulsive and excitation to these states produce fast H(n ) and H+ . Figure 7 shows Franck-Condon factors for excitation from the vi = 0 and 1 levels of X 1 Σ+ g 2 + + to H+ 2pσ Σ as a function of the kinetic energy of outgoing H(1s) or H . u u 2 The upper horizontal axes indicate the required minimum energy of the excitation from the vi = 0 level to produce H(1s) or H+ with indictated kinetic energy Ek . It is clear that excitation to the dissociative ionic states can produce H(1s) atoms with suﬃcient kinetic energy to escape Saturn. Glass-Maujean and Schmoranzer46 have shown that the combined photoexcitation cross sections of the doubly excited states is only a few hundredths of a Mb, nearly two orders of magnitude smaller than the 1 + B 1 Σ+ u −X Σg photodissociation cross section shown in the top panel of Fig. 3.

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Fig. 6. Potential energy curves of the H+ 2 and H2 Q1, Q2, Q3, and Q4 states. Dashed colored lines refer to the 1 Σ+ u state while continuous colored lines denote states with 1 Π symmetry. Adapted from Aoto et al.47 u

Electron impact excitation of H2 X 1 Σ+ g to the doubly excited states takes place by interaction beyond electron correlation. Moreover, the doubly excited states accessed by electron impact are not limited to 1 + Σu or 1 Πu symmetry. Thus, the excitation to doubly excited states by electrons, relative to those of singly excited states, is more signiﬁcant than photoexcitation. Experimental measurement48 and model analysis49 have shown that the total excitation cross section of the excited ionic states and doubly excited states−depending on electron energy — can be 5–10% of the total singlet-ungerade excitation cross section.6, 13, 39 Electron impact excitation can be collectively signiﬁcant in the production of fast hydrogen atoms because all the doubly excited states and excited ionic states are repulsive.

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+ 2 + Fig. 7. Calculated Franck-Condon factors for the H2 X 1 Σ+ g (vi = 0, 1)−H2 2pσu Σu as a function of kinetic energy, Ek , of the outgoing H(1s) or H+ fragments. ∆E at the top of the horizontal axis refers to the minimum energy (i.e. threshold energy) required to produce the indicated Ek from the vi = 0 level. The corresponding threshold of the vi = 1 level is about 0.5 eV lower than that from vi = 0. The kinetic energy of the outgoing electron is assumed to be negligible. The solid line represents excitation from the vi = 0 level while the dotted line is excitation from vi = 1.

In addition to dissociation, autoionization rates of doubly excited H2 are signiﬁcant. The second member of the Q1 1 Σ+ u series, the Q1 1 + Σu (2) state, has been shown to dissociate to H(1s)+H(2s) and autoionize into H+ +H(1s) with 50% and 48% yields, respectively.46 Figure 8 shows the atomic kinetic energy distribution for dissociation and autoionization channels resulting from high energy electron impact excitation. In the case of autoionization, it is assumed that the kinetic energy of the outgoing electron is negligible and the energy is equally distributed between H+ and H. It can be seen that both channels are capable of producing energetic hydrogen atoms and the initial vibrational quantum number has a signiﬁcant eﬀect on the kinetic energy distribution. 4. Discussion In addition to the production of fast HI from dissociation of H2 , dissociative recombination of H+ 3 also forms fast hydrogen atoms. As discussed

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Fig. 8. Normalized relative kinetic energy distribution of atomic hydrogen from e + H2 1 + X 1 Σ+ g (vi = 0, 1)→Q1 2 Σu excitation at asymptotic energy. The solid line represents the dissociation channel, which produces H(1s)+H(2s), while the dotted line represents the autoionization channel, which forms H(1s)+H+ . Note that either channel is capable of producing energetic hydrogen atoms and the initial vibrational quantum number has a large eﬀect on the kinetic energy distribution. Each production channel has been separately normalized to unity. In the case of autoionization, it has been assumed that the kinetic energy of the electron product is negligible. + elsewhere,1 H+ 3 chemistry starts with the formation of H2 via charge + exchange of H with vibrationally excited H2 , which can be formed with electron excitation of ground state H2 . H+ 2 , produced via charge exchange or H2 ionization, reacts with H2 to form H+ 3 . Dissociative recombination with ambient electrons results in the production of fast hydrogen of H+ 3 atoms. These reactions can be summarized as: 1 + e + H2 X 1 Σ+ g (vi : Ji ) ↔ e + H2 X Σg (vj : Jj )

(7)

H + + H2 X (vj : Jj ) → H + H2+ X (v : J)

(8)

e/hν + H2 X(vi , Ji ) → H2+ X(v, J) + 2e/e H2+ X (v : J) + H2 X (v : J) → H3+ + H ea +

H3+

→ H +H +H

ea + H3+ → H2 X 1 Σ+ g (v : J) + H

(9) (10) (11) (12)

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where ea refers to ambient electrons. Note that reaction (8) is exothermic only for X 1 Σ+ g (v ≥4). The three-body channel (11), having a branchingratio of 0.64 ± 0.05,50 produces HI atoms with kinetic energy of ∼1.59 eV. Depending on the H2 X 1 Σ+ g vibrational quantum number, the two-body breakup reaction (12), with a branching-ratio of 0.36 ± 0.05, can produce HI with kinetic energy ranging from 3.15 to 6.15 eV. Both measurement51 and calculation53 show that the vibrational population distribution of H2 peaks near v = 5–6, which corresponds to the most probable HI kinetic energy of 4.4 eV to 4.5 eV. Preliminary analysis1 has shown that the energy deposition rate of H+ 3 dissociative recombination is not a signiﬁcant channel on Saturn, because of the small plasma mixing ratio. The possibility of a large number of H+ produced from excitation to the ionic states and doubly excited states was not considered in the analysis by Shemansky et al.1 Photoabsorption cross sections of doubly excited and ionic states are quite small. Electron impact excitation of ionic and doubly excited states is much more eﬃcient. If a suﬃcient population of electrons with energy greater than 28 eV is present, a signiﬁcant number of H+ will be produced, increasing the formation of H+ 2 by reaction (8), making reaction (12) signiﬁcant. The observed H2 singletungerade emission rate and overall energy deposition will constrain the number of electrons with Ek > 13 eV. Modeling of H2 emission and the hydrogen plume will provide a more deﬁnitive answer. Figure 9 compares the cross sections for formation of energetic HI from X 1 Σ+ g (0) by electron impact excitation. The solid trace represents the production cross section of energetic H(n ) and H+ by excitation to the excited ionic and doubly excited electronic states.49 The formation of H(1s)+H(n ) (n > 1) is a minor channel.52 The dissociative ionization cross section shown in the ﬁgure can therefore be taken as the total cross section of energetic HI from ionic and doubly excited states. The 3 + dot trace with ﬁlled circles is the X 1 Σ+ g (0)−b Σu cross section derived 54–57 from several measurements. Note that it has been reduced by a factor 3 + 20 in the ﬁgure. While the threshold of the the X 1 Σ+ g (0)−b Σu starts at ∼4.5 eV, only cross sections above 9 eV have been reliably measured. The b3 Σ+ u cross section peaks sharply near 15 eV, and declines rapidly with excitation energy, with the value at 60 eV being 16 times smaller than that at 15 eV. In contrast, the lowest threshold for double excitation is ∼28 eV. The cross section for H(n )+H+ does not peak until ∼90 eV. It also decreases more slowly than the b3 Σ+ u cross section, even though both are forbidden excitations. The peak cross section near 90 eV is about

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Fig. 9. Comparison of HI production cross sections by electron impact excitation of H2 1 + 3 + X 1 Σ+ g (0). The dotted line with circles denotes the cross section for the X Σg −b Σu 54−57 transition derived from various experimental measurements. Note that the b3 Σ+ u cross section has been reduced by a factor of 20. The solid line represents total dissociative ionization cross sections from excitation to the doubly excited states and excited ionic states, as determined from the diﬀerence between the measured total H+ cross section48 49 The * symbol and the inferred H+ cross section from continuum levels of X 2 Σ+ g . emphasizes that the cross section represents the formation of energetic H+ and H(n) (see Figs. 7 and 8). The dot-dash line with ﬁlled squares refers to the electron impact 6 dissociation cross section via the continuum levels of the B 1 Σ+ u state.

a factor of 28 lower than b3 Σ+ u excitation near 15 eV. For comparison, the dot-dash line with ﬁlled squares in Fig. 9 shows the HI production 6 cross section via the B 1 Σ+ u continuum, the largest component of singletungerade series. Figures 7 and 8 show that the production of HI or H+ with Ek > 5.5 eV does not require the presence of vibrationally excited H2 . The production of HI with Ek > 5 eV via b3 Σ+ u excitation practically cannot take place from the vi = 0 level, and requires signiﬁcant population at vi ≥ 2 levels. In the region where the intense HI plume was observed, the H2 emission spectra did show a signiﬁcant population in vibrationally excited levels.1 Several theoretical calculations58–60 have predicted signiﬁcant enhancement of the 3 + X 1 Σ+ g (vi )−b Σu cross section with larger vi . Figure 9 clearly shows the relative importance of the b3 Σ+ u channel and the ionic and doubly excited channels depends on the energy distribution of the primary electrons.

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The conﬁnement of the Saturn atomic hydrogen plume phenomenon to a relatively small region of the southern hemisphere, correlated spatially to the presence of enhanced non-LTE H2 EUV/FUV singlet-ungerade emission at the base of the source of escaping atoms is indicative of an unexplained electrodynamic extrasolar excitation process. It is not clear if the conﬁnement of the plume is the result of the altitude of a more generally spatially distributed region of excitation, electron temperature, latitudinal dependence of the escape energy or a combination of these physical factors.1 The image in Fig. 1 shows a bifurcated distribution of atomic hydrogen, one localized observationally to within approximately 4 RS of the center, and another constituting a background broadly distributed throughout the magnetosphere showing a longitudinal structure ﬁxed to local time with substantial mass loss from the system.1–3 The conﬁned distribution inside 4 RS of center is much shorter lived than the broad extended component, so that rates of atomic ﬂux from the top of the atmosphere are disproportionally represented in the observed steady state populations occupying the magnetosphere. The range of processes considered in this work are apparently needed to explain the observed distributions because the large production of atomic hydrogen from the excitation of the b3 Σ+ u state produces very little ﬂux at the escape energy. The higher energy ﬂux from the weaker doubly excited states may be necessary to explain the broader distribution of escaping and orbiting gas. The present exploration of the range of transitions in H2 that end in the conversion of the molecular binding energy and excitation of repulsive states into atmospheric heating and escape of the dissociation products shows that the more conﬁned considerations by Shemansky et al.1 underestimate the eﬃciency of heat deposition in giant planet atmospheres relative to the observed EUV/FUV Rydberg system and infrared emissions. This eﬃciency factor has not been accurately quantiﬁed to date, and detailed model calculations are needed so that the relationship between energy in the forcing process and heating from deposition can be accurately determined. The present work provides additional relevant physical rate processes for incorporation into these calculations.

Acknowledgments The analysis reported in this paper was carried out at Space Environment Technologies (SET) and Jet Propulsion Laboratory (JPL), California Institute of Technology. XL acknowledges the support of a NASA/JPL

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Senior Fellowship, administered by Oak Ridge Associated Universities through contract with NASA. DES acknowledges support by a Cassini UVIS contract with the University of Colorado. We acknowledge ﬁnancial support through NASA’s Outer Planets Research, Planetary Atmospheres Research and Cassini Data Analysis programs.

References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28.

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29. G. Hunter, A. W. Yau and H. O. Pritchard, At. Data Nucl. Data Tables 14 (1974) 11. 30. T. E. Sharp, At. Data 2 (1971) 119. 31. M. R. Flannery, H. Tai and D. L. Albritton, At. Data Nucl. Data Tables 20 (1977) 563. 32. A. C. Allison and A. Dalgarno, At. Data 5 (1969) 92. 33. M. Glass-Maujean, J. Phys. B 33 (1986) 342. 34. M. Glass-Maujean, S. Klumpp, L. Werner, A. Ehresmann and H. Schmoranzer, J. Phys. B 40 (2007) F19. 35. M. Glass-Maujean, Chem. Phys. Lett. 68 (1979) 320. 36. M. Glass-Maujean, J. Breton and P. M. Guyon, Phys. Rev. Lett. 40 (1978) 181. 37. M. Glass-Maujean, J. Breton and P. M. Guyon, Chem. Phys. Lett. 112 (1984) 25. 38. M. Glass-Maujean, J. Breton and P. M. Guyon, Z. Phys. D 5 (1987) 189. 39. X. Liu, D. E. Shemansky, S. M. Ahmed, G. K. James and J. M. Ajello, J. Geophys. Res. 103 (1998) 26739. 40. A. Aguilar, J. M. Ajello, R. S. Mangina, G. K. James, H. Abgrall and E. Roueﬀ, Astrophys. J. Suppl. Ser. 177 (2008) 388. 41. T. L. Stephens and A. Dalgarno, J. Quant. Spectrosc. Radiat. Transfer 12 (1972) 569. 42. H. Abgrall, E. Roueﬀ, X. Liu and D. E. Shemansky, Astrophys. J. 481 (1997) 557. 43. P. Quadrelli, K. Dressler and L. Woliewicz, J. Chem. Phys. 93 (1990) 4958. 44. K. Tsukiyama, J. Ishii and T. Kasuya, J. Chem. Phys. 97 (1990) 875. 45. X. Liu, P. V. Johnson, C. P. Malone, J. A. Young, I. Kanik and D. E. Shemansky, Astrophys. J. under review (2010) 46. M. Glass-Maujean and H. Schmoranzer, J. Phys. B 38 (2005) 1093. 47. T. Aoto, Y. Hikosaka, R. I. Hall, K. Ito, J. Fern´ andez and F. Mart´ın, Chem. Phys. Lett. 389 (2004) 145. 48. H. C. Straub, P. Renault, B. G. Lindsay, K. A. Smith and R. F. Stebbings, Phys. Rev. A 54 (1996) 2146. 49. X. Liu and D. E. Shemansky, Astrophys. J. 614, (2004) 1132. 50. B. J. McCall, A. J. Huneycutt, R. J. Saykally, N. Djuric, G. H. Dunn, J. Semaniak, O. Novotny, A. Al-Khalili, A. Ehlerding, F. Hellberg, S. Kalhori, ¨ A. Neau, R. D. Thomas, A. Paal, F. Osterdahl and M. Larsson, Phys. Rev. A 70 (2004) 052716. 51. D. Strasser, L. Lammich, S. Krohn, M. Lange, H. Kreckel, J. Levin, D. Schwalm, Z. Vager, R. Wester, A. Wolf and D. Zajfman1, Phys. Rev. Lett. 86 (2001) 779. 52. Y. M. Chung, E.-M. Lee, T. Masuoka and J. A. R. Samson, J. Chem. Phys. 99 (1993) 885. 53. V. Kokoouline, C. H. Greene and B. D. Esry, Nature 412 (2001) 891. 54. R. I. Hall and L. Andri´c, J. Phys. B 17 (1984) 3815. 55. H. Nishimura and A. Danjo, J. Phys. Soc. Jap. 55 (1986) 3031.

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56. M. A. Khakoo, S. Trajmar, R. McAdams and T. W. Shyn, Phys. Rev. A 35 (1987) 2832. 57. M. A. Khakoo and J. Segura, J. Phys. B 27 (1994) 2355. 58. D. T. Stibbe and J. Tennyson, New J. Phys. 1 (1998) 2.1. 59. C. S. Trevisan and J. Tennyson, J. Phys. B 34 (2001) 2935. 60. C. S. Trevisan and J. Tennyson, Plasma Phys. Control. Fusion 44 (2002) 1963.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

VUV ABSORPTION PROPERTIES OF GASEOUS AND SOLID C2 H2 : RELEVANCE TO OUTER PLANETARY ATMOSPHERES RESEARCH C. Y. ROBERT WU∗ , F. Z. CHEN and D. L. JUDGE Space Sciences Center and Department of Physics and Astronomy University of Southern California, Los Angeles, CA, 90089–1341 ∗ [email protected] B. M. CHENG National Synchrotron Radiation Research Center 101 Hsin-An Road, Hsinchu Science Park Hsinchu 30076, Taiwan [email protected]

High-resolution absorption cross-sections of gas phase C2 H2 and mediumresolution absorbance spectra of C2 H2 /Ar (=1/100) isolated matrix and thin ﬁlm C2 H2 ices at 10 K have been obtained. In the gas phase we have investigated the absorption proﬁle changes of two members of the ﬁrst Rydberg transition of C2 H2 at 295 and 150 K. The 147.84 nm band contour and the portion of the spectrum joining the 147.84 nm and the 151.93 nm bands show a strong temperature eﬀect. Pressure broadening coeﬃcients of several Rydberg transitions of C2 H2 at 295 K have been studied in the presence of H2 , N2 , and Ar at pressures as high as 1,000 Torr. In the isolated matrix and thin ﬁlm ice systems the absorption features of C2 H2 exhibit remarkable spectral broadenings and spectral shifts when compare with those of C2 H2 in the gas phase. In the thin ﬁlm C2 H2 ices the spectral broadening is very extensive so that only a broad peak is observed for all Rydberg transitions below 145 nm. The two known valence electron transitions show red shifts while the Rydberg transitions all display blue shifts with respect to that in the gas phase. The magnitude of the shifts in the Rydberg transitions is signiﬁcant, for example, a 14 nm and 6.7 nm blue shift have been observed for the member of 3Rv [nsσg ] Rydberg series of C2 H2 in the Ar isolated matrix and thin ﬁlm ices, respectively. The results presented in this work could have an important impact on modeling the C2 H2 abundances in the upper atmospheres of Jupiter, Saturn, Titan, Uranus, Neptune, and Pluto, and in understanding ice photochemistry in interstellar medium grains.

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1. Introduction The compositions of atmospheres and surfaces of planets may consist of various molecules, which can be in the gas, liquid (droplets), and solid (icy particles) phases.1−5 The compositions, temperature, pressure, and so on, vary as a function of altitude and latitude for a given planetary atmosphere. Therefore, the molecular properties such as absorption, emission, and reaction of molecules may be aﬀected by atmospheric conditions. In this work we are particularly concerned with the outer planets, which include Jupiter, Saturn, Uranus and Neptune. Thick molecular hydrogen atmospheres dominate these giant planets. The relevant atmospheric temperature is ∼260–1,000 K for Earth, ∼170–1,000 K for Jupiter, ∼140– 350 K for Saturn, ∼97–200 K for Titan, ∼50–100 K for Triton, ∼44–100 K for Pluto, and even lower for Uranus and Neptune. The giant planets have icy satellites, which can have an airless or tenuous atmosphere. Pluto and Charon3 are known to have solid surfaces, and a signiﬁcant portion of their mass is icy material such as frozen water, carbon dioxide, nitrogen, methane and carbon monoxide. Pluto3 has a tenuous atmosphere containing N2 and CH4 at an average temperature of 44 K. It is thus desirable to measure the molecular data under the planetary atmosphere conditions of interest. It is clear that an atmospheric model is only as good as the input laboratory data. We shall give examples to illustrate the need of obtaining molecular data at conditions beyond the typical room temperature laboratory settings. Regarding the potential eﬀects of atmospheric pressures we shall take Jupiter’s atmosphere as an example. In Jupiter’s atmosphere5 the abundances of the typical absorber C2 H2 vary from 0.2 cm-atms to 5 cm-atms in the presence of H2 . The partial pressure of H2 is in fact about 107 times that of C2 H2 . The electronic states of C2 H2 in the spectral region between 110 and 200 nm include valence electron and Rydberg states. Very diﬀerent pressure eﬀects are expected in the spectral features of transitions to the excited electronic states.6,7 This could have signiﬁcant impact on modeling the C2 H2 abundance in the upper atmospheres of Jupiter, Uranus, and Neptune. It is well known that high pressure in an absorbing system can cause line broadening, line shifts, and pressure-induced transitions.6−8 The pressure eﬀects vary in nature depending on the characteristics of the collision constituents. Temperature can signiﬁcantly aﬀect the physical and chemical properties of a given constituent, e.g. from solid to gas phases.9−11 In the gas phase the change of temperature of an absorbing system will aﬀect

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the rotational-vibrational population distributions, the Doppler linewidth (and hence the band proﬁle) of absorption10,12 and emission13 features, and spectral perturbation and predissociation eﬀects, which are J-dependent couplings. It is well documented that molecular cross-section values can vary signiﬁcantly as temperature changes.10,11,14−17 This is especially true for sharp features. In such cases high-resolution and low-temperature cross-section measurements are thus needed in order to provide spectral identiﬁcation and cross-section data for the accurate determination of abundances and temperature proﬁles of planetary atmospheres. In terms of requirements of laboratory data in atmospheric modeling we shall use the NASA Cassini-Huygens Mission as an example. The most recent Cassini UVIS experiment detected six species, CH4 , C2 H2 , C2 H4 , C2 H6 , C4 H2 , and HCN, of the atmosphere of Titan from a stellar occultation by Titan.18 The observations cover an unprecedented range of altitudes from 450 km to 1,600 km, allowing the ﬁrst determination of the mesopause in Titan. Our low-temperature absorption cross-sections10,15,16 of C2 H2 have been utilized to determine its temperature sensitive properties for diagnostic work on Saturn and Titan. A comparison of laboratory and atmospheric observational data19 looks very encouraging and we can apparently with more experimental work obtain direct temperature measurements at the mesopause on both bodies for the ﬁrst time. This will put deﬁnitive constraints on physical chemistry, radiative cooling, and atmospheric dynamics, a big advance in our investigation of both bodies. Most recently, Shemansky19 observed a very large decrease in the apparent absorption cross-section in the 149.0–151.0 nm region in the mesopause regions of both Saturn and Titan, implying very low temperatures (∼120 K or lower). To help resolve this important issue there is a need to measure the absorption cross section of C2 H2 at a temperature around 120 K. It is important to point out that the melting point of C2 H2 is 189 K.

2. Experimental Setup and Experimental Procedures For the gas phase measurements we have utilized the existing instrumentation and the true continuum synchrotron radiation source at the Synchrotron Radiation Center (SRC), University of Wisconsin-Madison, to provide the required VUV photon beam source. The experimental setup and experimental procedures have been previously described in detail.10,15,17 The 4-m Normal Incidence Monochromator (4-m NIM) beamline at SRC was employed in the measurements. A spectral resolution (FWHM, full

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width at the half maximum) of 0.007 nm was used in the measurements of sharp absorption features below 136 nm and above 180 nm while a 0.06 nm resolution was used to measure the diﬀuse Rydberg series in the 140–160 nm regions. It is to be noted that in a structured spectral region, the measured absorption cross-section at a cross-section peak decrease while the half width of the absorption feature increase as the instrumental bandwidth increases.10 In the present work, our spectral bandwidth is larger than the linewidths of absorption features of C2 H2 , especially in the spectral region below 140 nm and above 180 nm. Therefore, our measured cross section represents an “averaged” value over the bandwidth. For the measurements of the thin-ﬁlm ice and isolated matrix work we have utilized the facility available at the Astrophysics and Astrochemistry Laboratory, National Synchrotron Radiation Research Center (NSRRC), Hsinchu, Taiwan. The experimental setup and experimental procedures have been previously described in detail.9,20−22 A FWHM of 0.1 nm was employed in this investigation. The ice samples were obtained by gaseous deposition onto a LiF window, which was mounted on a cold ﬁnger of a cryostat and maintained at 10 K. The rate of deposition was regulated in a range of nano-mol s−1 and monitored with a ﬂow transducer. The duration of deposition depends on the thickness of the ice thin ﬁlm required. The gases were provided by the Matheson Co. and were used directly without further puriﬁcation except for C2 H2 . The stated grades of purity and contents of impurities in the commercially available gas cylinders are summarized in Table 1. The gaseous C2 H2 sample was used after Table 1.

Purity of the commercial gases used in the present study.

Impurity

C2 H2 99.6% min.

Ar 99.9999% min.

N2 99.9999% min.

H2 99.9999% min.

N2 O2 CO CO2 THC as CH4 H2 O PH3

Not analyzed Not analyzed Not analyzed Not analyzed Not analyzed Not analyzed < 15 ppm

< 1 ppm < 1 ppm < 0.1 ppm < 0.1 ppm < 0.1 ppm < 1 ppm —

— < 0.5 ppm < 0.1 ppm < 0.1 ppm < 0.1 ppm < 0.2 ppm —

< 0.5 ppm < 0.1 ppm < 0.1 ppm < 0.1 ppm < 0.1 ppm < 0.5 ppm —

Note: Gas cylinders with stated research grade purity were provided by the Matheson Gas Products Co. THC is the abbreviation for total hydrocarbons. According to the speciﬁcation provided by Matheson only the PH3 impurity was analyzed in the C2 H2 cylinder. None of the other common impurities were analyzed.

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the standard puriﬁcation procedures; namely, using the freeze-pump-thawpump-distill technique. This procedure has been very eﬀective in removing the acetone,15,23 which is commercially used as a chemical stabilizer in the C2 H2 sample cylinder. The pressure in the gas absorption cell was monitored with an MKS baratron capacitance manometer (for gas pressures from 10−4 Torr to 1 Torr) and a Datametrics barocell (from 2 × 10−2 Torr to 102 Torr). The known absorption features of CO and C2 H2 were used to provide the wavelength calibration to an accuracy of ±0.007 nm for the high-resolution measurements. For solid ices an accuracy of ±0.2 nm has been attained because of the broad nature of the absorption features and the onset of absorption threshold. The experimental errors in the absolute cross-section values are estimated to be ±10% of the given values, while the relative cross-section values are accurate to within ±4%. The temperature in the absorption cell is stable to within ±1 K for a given temperature in both the gas absorption cell and the cryostat system.

3. Results and Discussion A survey of the temperature-dependent absorption cross section of C2 H2 in the spectral region between 118 and 210 nm has recently been given.15 In Fig. 1 we display a panorama view of the C2 H2 absorption data at 150 K in a semi-log plot. At photon wavelengths longer than 155 nm the absorption features have been identiﬁed as valence electron transitions24−27 and in the photon wavelength region shorter than 155 nm as Rydberg series.15,28−31 The absorption spectrum in the 140–155 nm region exhibits sharp and relatively simple features, which have been assigned to the C 1 Πu − X 1 Σ+ g Rydberg transition8 with a linear geometry for both the excited and ground electronic states. The two peaks at 151.93 nm and 147.84 bands are the ﬁrst two bands of the v2 vibrational progressions, namely, the (v2 = 0, v2 = 0) 3R0 and (v2 = 1, v2 = 0) 3R1 bands of the C 1 Πu − X 1 Σ+ g Rydberg transitions, respectively. Several transitions are marked in Fig. 1 for easy reference. The cross-section values in the measured region vary from ∼ 3 × 10−16 cm2 in the 134 nm region to ∼5 × 10−16 cm2 in the 152 nm region and down to ∼5 × 10−21 cm2 in the 210 nm region, a change of about ﬁve orders of magnitude. In the following we shall discuss the results of the temperature and pressure eﬀects on the prominent Rydberg features of gaseous C2 H2 in the 150 nm region, and the absorbance spectra of isolated matrix

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Fig. 1. A panorama plot of the absolute photoabsorption cross-section data of C2 H2 at 150 K. The sharp features in the 118–138 nm and 180–210 nm regions were measured with a 0.007 nm resolution while the broad absorption features in the 138–180 nm region were obtained with a 0.06 nm resolution. The absorption features in the 180–210 nm region are mainly attributed to the A − X transition, which exhibits sharp subbands, not signal noise.15

C2 H2 /Ar = 1/100 and thin ﬁlm C2 H2 ices at 10 K in the spectral region between 107 nm and 240 nm. 3.1. Temperature eﬀects on the absorption properties of C2 H2 Gas We have previously investigated the temperature-dependent photoabsorption cross sections of C2 H2 in important spectral regions of atmospheric interest at relevant temperature conditions. In the present work we focus on the detailed band proﬁle changes at two temperatures. Figure 2 displays the cross-section data of C2 H2 in the 146–154 nm region. A spectral resolution (FWHM) of 0.007 nm was used in the present measurements. As can be seen in Fig. 2 the weak shoulder discernible on the short wavelength side of the 151.93 nm 3R0 band disappears as temperature drops to 150 K while the main peak increases in height. Although the band exhibits a distinctive change in shape, the absorption strength

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Fig. 2. The absolute photoabsorption cross-section data of C2 H2 at 295 K (blue curve) and 150 K (red curve) in the spectral region between 146 nm and 154 nm. A resolution of 0.007 nm was used in the measurements.

(i.e. the integrated area of cross-section values over the lineshape of the band) is constant to better than 0.5% as the temperature changes from 295 K to 150 K. The 147.84 nm 3R1 band displays a distinctive variation in band shape as well as the integrated cross-section area with temperature. At 150 K the main peak at 148 nm apparently resolved into a doublet-like feature. It is possible that this property may allow us to directly measure the temperatures of Saturn and Titan from the planetary data.19 The semicontinuum region between 149.0 and 151.0 nm are particularly important in this respect. A very large decrease in the apparent absorption crosssection in the 149.0–151.0 nm region is observed in the mesopause regions of both Saturn and Titan implying very low temperatures (∼120 K or lower). We are currently fabricating a windowless low-temperature absorption cell for the purpose of carrying out cross-section measurements of C2 H2 and other light hydrocarbons at temperatures lower than 140 K, the limit of our existing cooling system, a heavy duty commercial triple cascade Freon compressor system. A windowless absorption cell will be free from condensation of gases on the optical windows of the cell.

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3.2. Pressure-Broadening of C2 H2 by H2 , N2 , and Ar We have carried out a pressure-broadening study of the absorption features of C2 H2 at room temperature in the presence of H2 , N2 , and Ar to investigate the possible pressure eﬀects. The 4-m NIM Monochromator beamline at SRC was employed in the measurements. We have initially selected three spectral regions covering transitions leading to diﬀerent Rydberg states of C2 H2 . They are the 151.93 nm and 147.84 nm bands of the 3R0 [nsσg ] C 1 Πu — and 3R1 [nsσg ] C 1 Πu − X 1 Σ+ g transitions, respectively, the 139.24 nm band of the 3R0 [ndσg ]1 Σu − X 1 Σ+ g transition, transition. and the 133.71 nm band of the 3R0 [ndδg ]1 Πu − X 1 Σ+ g The pressure of C2 H2 in the absorption cell was typically ﬁlled to 0.5 mTorr for the 151.93 nm band, and to 8 mTorr for the other weaker bands in this work. The pressure of the broadening gas was varied from 50 Torr to 1,000 Torr (1.316 atmospheres or 1.333 bars). This gives a pressure ratio of, e.g. H2 /C2 H2 up to 2×106. The high-resolution absorption spectra at several selected pressures are shown in Fig. 3. We found that the absorption proﬁles of the above-mentioned Rydberg transitions exhibit mainly the pressure broadening eﬀects. There is no obvious pressure-induced spectral shifting observed under the present experimental

Fig. 3. Spectral scans of the 151.93 nm band of C2 H2 in the presence of H2 at various pressures. A resolution of 0.007 nm was used in the measurements.

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conditions, e.g. resolution and pressure. The broadening in line widths and decreases in peak heights of the absorption features result from the long-range interaction potentials between the collision partners.32,33 It is interesting to mention that the spectral position of the impurity of CO in the H2 bottle serves as a good spectral calibration and also an indication of a good repeatability of the wavelength scanning of the monochromator system. The low temperature cross-section data15 of C2 H2 at 150 K is also shown for comparison. In Fig. 3 we show the spectral scans of the 151.93 nm band from 150.3 nm to 153.3 nm in 5,000 steps (i.e. 0.0006 nm/step, 10 steps equal the speciﬁed resolution). The pressure of C2 H2 in the absorption cell is 0.5 mTorr. For clarity only the data measured in the presence of H2 at 0 Torr, 650 Torr, and 847 Torr are displayed in Fig. 3. The linewidth (FWHM) of this absorption band is 0.278±0.006 nm. There is no rotational structure because of a strong predissociation eﬀect.8,15 As the pressure of H2 in the absorption cell increases the peak height clearly decreases as shown and hence the lineshape of the absorption feature becomes broadened. The FWHM of the absorption increases accordingly, a consequent change of the absorption cross-section values over the band proﬁle although the integrated area of absorption remains unchanged. The measured linewidths of the 151.93 nm band and the 147.84 nm band of the Rydberg transitions of C2 H2 in the presence of H2 and N2 are shown in Fig. 4. A linear and a second-order polynomial function were used to ﬁt the measured linewidth data. As one can see from Fig. 4 the data can be fairly well ﬁt by a linear function of pressure. However, the linewidth data of the 151.93 nm band, i.e. panel c, appear to deviate from a linear ﬁt at a N2 pressure greater than about 600 Torr. This indicates that a second order pressure eﬀect becomes important at pressures higher than 600 Torr. However, the pressure broadening coeﬃcients are determined from data points which exhibit linear dependence of N2 pressure. The broadening coeﬃcients (FWHM) are 2.1 × 10−5 nm/Torr and 1.02 × 10−4 nm/Torr for the respective 151.93 nm and 147.84 nm bands at H2 pressures up to 1000 Torr at room temperature conditions. The corresponding broadening coeﬃcients by N2 are 1.80 × 10−5 nm/Torr and 5.70 × 10−5 nm/Torr for pressure up to 600 Torr. The results show that the rates of pressure broadening depend on the nature of electronic transition and the identity of collision partner. For example, the broadening rate for the 3R1 147.84 nm band is a factor of 4.86 and 3.16 larger than that of the 3R0 151.93 nm band in the presence

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Fig. 4. The measured linewidth (FWHM) of two C2 H2 absorption bands as a function of the pressure of H2 and N2 . The widths of the 151.93 nm and 147.84 bands of the C2 H2 in the presence of the H2 are shown in panels a and b and of the N2 in panels c and d, respectively.

of H2 and N2 , respectively. The results support the fact that the pressure eﬀect is proportional to the quantum number of Rydberg transition. The broadening rate for the 147.84 nm and the 151.93 nm band in the presence H2 gas is a factor of 1.8 and 1.17 larger than that in the presence of N2 gas. We thus conclude that pressure broadening induced by H2 is more eﬃcient than by N2 . This is possible because of the additivity of H2 to C2 H2 to form C2 H4 . 3.3. Isolated matrix and solid thin ﬁlm of C2 H2 ices We have measured the absorption spectra of C2 H2 in an isolated matrix21,22 and in a thin ﬁlm of C2 H2 ice at 10 K. The isolated matrix was a very diluted C2 H2 in Ar with a composition ratio of C2 H2 /Ar = 1/100. Under such conditions a C2 H2 molecule is isolated by Ar atoms, and is completely separated from other C2 H2 molecules. The thin ﬁlm C2 H2 ice sample was

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Fig. 5. The absorbance of an isolated matrix of C2 H2 /Ar = 1/100 coated on a LiF window at a temperature of 10 K in the spectral region between 107 nm and 245 nm. A resolution of 0.1 nm was used in the measurement.

prepared by slow deposition of C2 H2 vapor onto a LiF optical window cooled to 10 K. The absorbance spectra of both samples in the spectral region between 107 nm and 240 nm are plotted in Figs. 5 and 6, respectively. Due to the broad nature of absorption features in the condensed phase a resolution of 0.1 nm was used in the measurements. The absorption features in the wavelength region longer than 155 nm are enlarged and shown in the insets. The electronic transitions in this spectral region6−8,14 are known to belong to the weak valence electron B−X and A − X transitions (see Fig. 1). The measured spectral positions of the C2 H2 /Ar isolated matrix and the C2 H2 thin ﬁlm ice are listed in Table 2, along with those34,35 previously reported. The measured spectral positions of pure C2 H2 in gas phase14,15 are also listed in Table 2 as references for the calculation of spectral shifts. The B − X transition still exhibits the vibrational progressions, like those in the gas phase. Their spectral positions are clearly red-shifted toward the long wavelength end, as expected for a valence electron

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Fig. 6. The absorbance of a thin ﬁlm C2 H2 coated on LiF window at a temperature of 10 K in the spectral region between 107 nm and 245 nm. A resolution of 0.1 nm was used in the measurement.

excitation.6,7 As tabulated in Table 2 the average red-shift for the C2 H2 /Ar isolated matrix and thin ﬁlm C2 H2 ices is 0.27 nm and 3.47 nm, respectively. The interaction between C2 H2 molecules in the ice is stronger than that between C2 H2 and Ar atoms because the rare gases are known to be quite inert in chemical bonding. The weak, sharp A−X transition of C2 H2 is completely smeared out in both the isolated Ar matrix (longer than 185 nm) and in a thin ﬁlm sample (longer than 190 nm). The same result has also been observed in various rare gas matrices.6 Robin6 has proposed a possible explanation that the A − X band systems at 188 nm and longer is a valence 1πu − 3σg∗ transition, which is strongly mixed with the 1πu − 3s Rydberg conﬁguration and so assume considerable Rydberg character. While this is a viable proposal we feel that we fail to see the A − X band structure is because of its sharp absorption features and its extremely small absorption cross-sections (see Fig. 1). The onsets of the absorption threshold for the isolated matrix and thin ﬁlm ices have been determined to be at 212 nm and 225 nm, respectively. The enlarged spectrum for the thin ﬁlm C2 H2 ice is shown in the left inset in

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Table 2. The measured spectral positions (nm) of C2 H2 absorption features in the gas phase, isolated matrix, and thin ﬁlm ice. The spectral shifts (nm), ∆ (I-G) for the isolated matrix data and ∆ (S-G) for the solid ice, of the given band systems with respect to that of the gas phase are also listed. Band system

4R1 4R0

3R2 , 3R2 3R1 , 3R1

G (gas)

I (isolated matrix)

S (solid ice)

∆ (I-G)

∆ (S-G)

121.87 124.72

119.04 121.73 122.0a 124.63 124.5a 126.83 127.0a 129.62 129.5a — — 130.1a 134.42 134.5a 134.4b 137.82 138.0a 137.5b 157.63 159.53 161.33 163.23 165.13 166.94 169.04 171.05 173.75 175.66 177.66 180.27 182.58 185.09

— —

−2.83 −2.99 −2.72a −3.32 −3.45a −4.07 −3.9a −4.47 −4.59a — — −13.78a −13.45 −13.37a −13.47b −14.12 −13.94a −14.44b +0.14 +0.49 +0.48 +0.32 +0.27 +0.24 +0.31 +0.27 +0.31 +0.05 +0.09 +0.15 +0.29 +0.31

— —

127.95 130.90

3R0 , 3R0

134.09

3R3 3R2

140.31 143.88

3R1

147.87

3R0

151.94

B(13,0) B(12,0) B(11,0) B(10,0) B(9,0) B(8,0) B(7,0) B(6,0) B(5,0) B(4,0) B(3,0) B(2,0) B(1,0) B(0,0)

157.49 159.04 160.85 162.91 164.86 166.70 168.73 170.78 173.44 175.61 177.57 180.08 182.29 184.78

— — — — — 134.82

145.22

— 160.63 162.43 166.24 168.44 170.44 172.45 174.65 176.86 179.27 181.48 184.09 186.69 189.11

— — — — — −13.05 −6.72

— +1.60 +1.58 +3.33 +3.58 +3.74 +3.72 +3.87 +3.42 +3.66 +3.91 +4.01 +4.40 +4.33

Note: The vibrational quantum numbers indicated in the Table refer to the v3 mode for the A and B states, and the v2 mode for the Rydberg states. a: Gedanken et al. [Ref. 34] and b: Pysh et al. [Ref. 35].

Fig. 6. However, the absorption onset may slightly depend on the thickness of the ice and the composition ratio of the constituents in the isolated matrix. In contrast to the valence electron transitions, the nRv [nsσg ] C 1 Πu −, the nRv [ndδg ] 1 Πu −, and the nRv [ndσg ]1 Σu −X 1 Σ+ g Rydberg transitions

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below 155 nm region show blue-shifts with respect to those of the gas phase C2 H2 molecule. In Fig. 5 the spectrum of C2 H2 /Ar isolated matrix shows two clear Rydberg members of the 3Rv series, three members of the 3Rv + 3Rv series, and two of the 4Rv series. The spacing between the 3R0 and 3R1 peaks is 3.40 nm as compared to 4.07 nm in the gas spectrum, reﬂecting a vibrational perturbation induced by the Ar matrix. The measured spectral shifts (nm), ∆ (I-G), of given band systems with respect to the corresponding feature in the gas phase are tabulated in Table 2. Huge blue shifts, namely, 14.1 nm and 13.4 nm, have been observed for the 3R0 and 3R1 Rydberg series, respectively. The magnitudes of shifts are in excellent agreement with the previous reported values, which are also summarized in Table 2. The trend of the magnitudes of blue shifts decreases at higher Rydberg transitions. In the gas phase it is expected that the magnitudes of spectral shifts and broadenings of Rydberg transitions should increase with increasing n, the principal quantum number. This is because the Rydberg electron orbital proportionally increases with n2 , and hence subject to larger perturbation by collisional partners. It is interesting to demonstrate that the trend of spectral shifts is so diﬀerent in the isolated matrix and in thin ﬁlm (crystalline) in comparison to that in the gas phase, as discussed in the previous section and in literature.6,7 The most striking eﬀect is the seemingly featureless spectrum in the thin ﬁlm C2 H2 ices as can be seen in Fig. 6. The broad blue-shaded feature peaks at 145.22 nm with one apparent shoulder on each side. The 134.8 nm shoulder can be attributed to 3R1 — X transition. However, the 149.0 nm shoulder does not correspond to any expected feature, because the 3R0 — X transition is the ﬁrst Rydberg feature of C2 H2 (see Fig. 1 for the gas phase spectrum). The origin of the shoulder at 149.0 nm may be due to excited clustered C2 H2 molecules and/or excited state of the matrix,6,7,34 and further study is warranted. The diﬀerent behaviors of spectral shifts and broadenings of Rydberg transitions between gas, isolated matrix, and solid ice are theoretically interesting, and may also have important astronomical implications as well.

4. Concluding Remarks The data on pressure-induced line broadening may provide the necessary information required for a better modeling of the atmospheres of giant planets in our solar system, including Titan, and a better understanding

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of the nature of the long-range interaction potentials of the C2 H2 -H2 and C2 H2 -N2 collision complexes.32,33 As the pressure increases further, third body collision processes become important and may eventually lead to the formation of stable C2 H2 -H2 and C2 H2 -N2 “dimmer-like” complexes. New pressure-induced transitions may consequently become observable.6,7 At high pressure the collision processes can go from long-range collisions to the short-range ones, as collision complexes of dimers, clusters, and chemical reactions may come into being. The eﬀects of temperature on the collisional chemical reactions apparently need further attention in the future. Spectral shifts and broadenings in the C2 H2 /Ar isolated matrix and the thin ﬁlm C2 H2 ices are quite remarkable. In terms of astronomical implications interstellar medium and icy grain surfaces adsorbed with C2 H2 will be subjected to exposure of photons at wavelengths longer than that by gaseous C2 H2 molecule (see Table 2). However, in terms of VUV photolysis the thresholds of dissociation and ionization processes of condensed C2 H2 ice systems will take place at higher energy because of the blue shifts. To quantitatively evaluate the photo-induced processes in condensed C2 H2 ices it is important to measure their absolute absorbance (cross-sections) in the VUV region. Our existing gas phase absorption cross-section measurement facility only permits measurements, at the best, to 140 K. We are now working on a new facility to extend our capability to a temperature lower than 120 K. With it we can investigate the absorption proﬁles of gaseous C2 H2 in the 151.93 nm and 147.84 nm bands of the 3R0 and 3R1 of the C 1 Πu − X 1 Σ+ g transition, which will allow us to obtain data required for the determination and interpretation of the temperatures in the mesopause regions of both Saturn and Titan. It is important to further examine the pressure eﬀects at a realistic atmospheric temperature condition, appropriate to the giant planets.

Acknowledgment We are indebted to D. Shemansky for suggesting the thin ice measurements and for stimulating discussions. We are grateful for the support of the staﬀ of the Synchrotron Radiation Center, University of Wisconsin-Madison, for the gas phase work, and the support of the National Synchrotron Radiation Research Center, Hsinchu, Taiwan for the solid phase measurements. This research is based on work supported by the NASA Planetary Atmospheres Program under Grant No. NNG06GG72G (Wu) and the Astrophysics

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and Astrochemistry Program of the NSRRC (Cheng). The Synchrotron Radiation Center, University of Wisconsin-Madison, is supported by the National Science Foundation under Award No. DMR-0537588.

References 1. M. S. Matthews, S. K. Atreya and J. B. Pollack, Eds., Origin and Evolution of Planetary and Satellite Atmospheres, University of Arizona Press, Tucson, Arizona, 1989. 2. M. A. Barucci, H. Boehnhardt, D. P. Cruikshank and A. Morbidelli, Eds., The Solar System Beyond Neptune, University of Arizona Press, Tucson, Arizona, 2008. 3. S. A. Stern and D. J. Tholen, Eds., Pluto and Charon, University of Arizona Press, Tucson, Arizona, 1998. 4. M. S. Matthews, J. T. Bergstralh and E. D. Miner, Uranus, University of Arizona Press, Tucson, Arizona, 1991. 5. T. Gehrels, Ed., Jupiter, University of Arizona Press, Tucson, Arizona, 1976. 6. M. Robin, Higher Excited States of Polyatomic Molecules, Vol. II, Academic Press, New York and London, 1975. 7. M. Robin, Higher Excited States of Polyatomic Molecules, Vol. III, Academic Press, New York and London, 1985. 8. G. Herzberg, Molecular Spectra and Molecular Structures, Vol. III, Van Nostrand Reinhold, New York, 1966. 9. H.-C. Lu, H.-K. Chen, B.-M. Chng, Y.-P. Kuo and J. F. Ogilvie, J. Phys. B 38 (2005) 3693. 10. C. Y. R. Wu, T. S. Chien, G. S. Liu, D. L. Judge and J. J. Caldwell, J. Chem. Phys. 91 (1989) 272, and references therein. 11. C. Y. Chung, E. P. Chew, B.-M. Cheng, M. Bahou and Y.-P. Lee, Nucl. Instr. Meth. Phys. Res. A 467–8 (2001) 1572. 12. K. P. Huber and Ch. Jungen, J. Chem. Phys. 92 (1990) 850. 13. C. Y. R. Wu, H.-S. Fung, K.-Y. Chang, T. S. Singh, X.-L. Mu, J. B. Nee, S.-Y. Chiang and D. L. Judge, J. Chem. Phys. 127 (2007) 084314. 14. C. Y. R.Wu, , F. Z. Chen and D. L. Judge, J. Geophys. Res. 109 (E7) (2004) E07S15. 15. C. Y. R. Wu, F. Z. Chen and D. L. Judge, J. Geophys. Res. 106 (2001) 7629. 16. T. J. Xia, T. S. Chien, C. Y. R. Wu and D. L. Judge, J. Quant. Spectrosc. Relat. Transf. 45 (1991) 77. 17. F. Z. Chen and C.Y. R. Wu, J. Quant. Spectrosc. Rediat. Transf. 85 (2004) 195. 18. D. E. Shemansky, A. I. F. Stewardt, R. A. West, L. W. Espoito, J. T. Hallett and X. Liu, Science 308 (2005) 978. 19. D. E. Shemansky, (private communication, 2008). 20. Y. P. Kuo, H. C. Lu, Y. J. Wu, B. M. Cheng and J. F. Ogilvie, Chem. Phys. Lett. 447 (2007) 168.

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21. Y. J. Wu, M. Y. Lin, B. M. Cheng, H. F. Chen and Y. P. Lee, J. Chem. Phys. 128 (2008) 204509. 22. Y. J. Wu and B. M. Cheng, Chem. Phys. Lett. 461 (2008) 53. 23. Y. Benilan, D. Andrieux and P. Bruston, Geophys. Res. Lett. 22 (1995) 897. 24. M. Herman and R. Colin, J. Mol. Spectrosc. 85 (1981) 449. 25. M. Herman and R. Colin, Phys. Scr. 25 (1982) 275. 26. P. D. Foo and K. K. Innes, Chem. Phys. Lett. 22 (1973) 439. 27. K. K. Innes, J. Chem. Phys. 22 (1954) 863. 28. M. Jungen, Chem. Phys. 2 (1973) 367. 29. J. M. Lundberg, D. M. Jonas, B. Rajaram, Y. Chen and R. W. Field, J. Chem. Phys. 97 (1992) 7180. 30. M. N. R. Ashfold, B. Tutcher, B. Yang, Z. K. Jin and S. L. Anderson, J. Chem. Phys. 87 (1987) 5105. 31. M. Suto and L. C. Lee, J. Chem. Phys. 80 (1984) 4824. 32. C. Y. R. Wu and W. C. Stwalley, Phys. Rev. A 24 (1981) 1117. 33. C. Y. R. Wu and W. C. Stwalley, Phys. Rev. A 18 (1978) 1066. 34. A. Gedanken, B. Raz and J. Jortner, J. Chem. Phys. 58 (1973) 1178. 35. E. S. Pysh, S. A. Rice and J. Jortner, J. Chem. Phys. 43 (1965) 2997.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

EXCITED STATES OF N2 FOR PLANETARY AIRGLOW: A LABORATORY STUDY JAN B. NEE Department of Physics, National Central University, No. 300, Jhongda Road, Jhongli City, Taoyuan County, Taiwan, ROC 32001 [email protected] H. S. FUNG National Synchrotron Radiation Research Center, Hsingchu, Taiwan 350

Excited states of N2 in the VUV region are studied in the laboratory by using the absorption and ﬂuorescence measurements in the wavelengths of 90– 145 nm. The forbidden absorption of the Tanaka bands can produce the UV ﬂuorescence of the 2nd positive band (2PB): C3 Πu –B3 Πg at the wavelengths at 300–400 nm. The (1,0) band of Tanaka system at 109.9 nm is coincident with NI line at the same wavelength. In the 90–100 nm wavelength region, excited states of b1 Π, b1 Σ, c1 Π, and c1 Σ are dominant in the absorption spectrum, and predissociation of these states are observed. Most of these resonance states can be sources of N atoms in the upper atmosphere.

1. Introduction Prominent emissions of nitrogen produced in the planetary airglow have motivated extensive research for understanding the excitation mechanisms. Although N2 absorbs very little visible or UV radiation, emissions from excited states of N2 are observed throughout the whole wavelength region. The information of the spectroscopic data for nitrogen has been reviewed in Lofthus and Krupenie.1 Many prominent emissions of nitrogen are produced by the inter-state transitions such as the 2PB band of the C3 Πu –B3 Πg transition and the 1st positive band (1PB) of the B3 Πg –A3 Σ+ u transition commonly also observed in Earth’s upper atmosphere produced by electron impact excitation of N2 .2,3 In the wavelength region between 100 and 200 nm, there are several well known forbidden transitions of N2 including C3 Πu –X1 Σ+ g (Tanaka system), 445

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1 − 1 + a1 Πg –X1 Σ+ g (Lyman-Birge-Hopﬁeld system or LBH system), a Σg –X Σg 1 + (Ogawa-Tanaka-Wilkinson-Mulliken System), B3 Σ− u ← X Σg (Ogawa4−9 Tanaka-Wilkinson System) which have been studied and reviewed in Lofthus and Krupenie.1 Laboratory studies of photoabsorption and ﬂuorescence spectra can be useful for understanding the airglow emissions observed in the upper atmospheres of the Earth2,3 and outer planets.10−13 UVS spectrometer of Voyager launched in 1980 to Titan observed two strong bands at 95.8 and 12,13 in the 98.1 nm assigned as the (0,0) and (0,1) bands of c4 1 Σ+ u state of N2 airglow spectrum. In addition, emission peaks in 100–150 nm wavelengths including LBH system in 135 nm wavelength region were assigned along with atomic nitrogen emissions. However, the resolution of UVS was about 3 nm, therefore assignments were not deﬁnite. The recent ﬂight of CASSINI mission has its spectrometers with improved resolution (∼0.5 nm) to allow more speciﬁc identiﬁcation of the excited states.10,11 The principal source of the excitation of VUV airglow of nitrogen was considered to be electron impact excitation. Photon excitation in the dayside of the atmosphere is limited by the optical thickness condition in the atmosphere since N2 is the dominant gas. Broadfoot, Strobel, Shemansky, and others12−15 have reported the precipitation of magnetospheric electrons in Titan’s sunlit hemisphere and estimated the power dissipation for the production of atomic and molecular nitrogen emissions. Identiﬁcation of the 95.8 nm line was later considered to be related with other sources by Stevens17 who used a multiple scattering model to calculate the radiative transfer of c4 emissions. His results showed that the emission at 95.8 nm observed by Voyager should be produced by NI emissions at 95.32 and 96.45 nm. NI emissions can be produced by photodissociation of N2 by VUV radiation in the optical thin region, and solar scattering in 145– 200 nm has been considered by Wilson and Atreya18 at upper region of the Titan. These studies showed the importance to understand the absorption and photodissociation of N2 . In the wavelength range of 90–150 nm, the absorption spectrum is mainly contributed by several metastable states which has been well studied in the laboratory.1,4−9 However, the production of UV or visible ﬂuorescence by photon impact is worth further studies in view of recent planetary explorations.

2. Experimental Experiments of absorption spectrum of N2 were performed at the National Synchrotron Radiation Research Center (NSRRC) with the

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1-m Seya beamline (1m-SNM, BL04B) which has been installed with diﬀerent gratings. By using the grating of 1,200 grooves/mm, we measured absorption spectra in diﬀerent wavelength regions. For the spectral region between 80 and 100 nm (EUV) an instrumental resolution of 0.06 nm (75 µm slit width) was used, and the in 105–150 nm (VUV) wavelength region a resolution of 0.12 nm was used. The EUV experiments required windowless condition, but the VUV experiments were carried out with a lithium ﬂuoride (LiF) window to isolate high pressure conditions employed here in order to measure the weak absorption spectrum. The gas cell had pressures ranged from a few mTorr, for EUV experiments, to 0.1–100 Torr, in VUV experiments. The gas cell was connected to the monochromator through a two-stage diﬀerential pumping system (DPS) which consists of two turbo pumps (Seiko STP451 and Alcatel Drytel 100). This DPS was connected to the beam line acting as a buﬀer to pump down the residual gases ﬂowing into the monochromator in the EUV experiments. The monochromator requires a vacuum of 10−7 Torr or better; but between the beam line and the monochromator, a vacuum of 10−8 to 10−9 Torr is needed. Similar experiments have been reported in previous publications.19−20 The ﬂuorescence signals were measured by two photomultiplier tubes (PMT’s). The ﬁrst one is a solar blind PMT (Hamamatsu R1460) sensitive to wavelengths in 115–320 nm and the second PMT is sensitive in UVvisible wavelengths in 180–650 nm (EMI 9789QB). The transmitted VUV photon ﬂux was measured by a third PMT (Hamamatsu R268) which was installed with a front window coated by sodium salicylate to convert VUV radiation into UV wavelengths observable by the PMT. The N2 gas has a stated purity of 99.995% minimum and was used without further puriﬁcation.

3. Results and Discussion 3.1. The absorption and fluorescence excitation of Tanaka and LBH system Figure 1 shows the absorption spectrum which consists of vibrational bands 1 1 + of the C3 Πu –X1 Σ+ g (Tanaka) and the a Πg –X Σg (LBH) systems. The absorption cross sections were derived by using the Lambert–Beer’s law through an absorption tube of a length 141 cm. By varying the pressure over the range between 0.8 to 90 Torr, we found the absorption cross sections are in the order of 10−20 cm2 .

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Absorption cross section (10

-20

2

cm )

5.0

LBH

4.5 4.0

Tanaka (10,0)

3.5

(0,0)

(5,0)

(0,0)

3.0 2.5 2.0 1.5 1.0 0.5 0.0 110

120

130

140

150

Wavelength (nm) Fig. 1. The absorption spectrum of N2 in 105–150 nm wavelength regions measured at 8 Torr. Vibrational levels of LBH and Tanaka system are assigned.

The cross sections for these sharp bands vary with pressure, but appear to level oﬀ at a low pressure conditions. Absorption cross sections reported here represent an average over the band spectral width. The uncertainty of the cross sections is estimated to be about ±25%. Errors mainly result from ﬂuctuation in light intensity and pressure measurements. We also measured 1 + 3 − minor absorptions caused by forbidden bands of a1 Σ− g –X Σg and B Σu ← 1 + X Σg of N2 with cross sections much smaller. Fluorescence signals are detected at the Tanaka bands but not at the LBH bands owing to small probability of transition and quenching of the a1 Πg state at high pressure conditions (few Torrs) employed here. As shown in Fig. 2, the ﬂuorescence excitation spectrum (FES) shows strong signals produced at peaks 112.4, 109.9, 107.6, 105.1 nm for (0,0), (1,0), (2,0), and (3,0) bands. The ﬂuorescence detected at these bands is in UV wavelengths in 300-400 nm caused by the 2PB of C3 Πu –B3 Πg transition. The C3 Πu state is populated by the absorption process and followed by the radiative transition to the lower B3 Πg state. This mechanism was conﬁrmed by measuring the UV ﬂuorescence using band pass ﬁlters in the 300–400 nm wavelength region. For reference, a spectrum of C3 Πu –B3 Πg transition at 300–400 nm produced by discharging N2 is shown in Fig. 3. The 2PB of nitrogen is a prominent dayglow of the Earth’s thermosphere, the source of this airglow emission being electron impact

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4000

v'=0 3

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Intensity (count/s)

3000

2000

1000

0 104

106

108

110

112

114

Wavelength (nm)

Fig. 2. The ﬂuorescence excitation spectrum in 104–114 nm wavelength region (resolution 0.5 nm) where bands of Tanaka system are assigned.

1 3

ν'=0

3

C Π u-B Π g

Intensity (a.u.) 0

1

0

ν'=3 1

0 ν'=4 1

2

2

2

2

1

0

ν'=2

1

0

ν'=1

3

(0,1)

3

3

4

(0,0)

(1,0)

280

290

300

310

320

330

340

350

360

Wavelength (nm) Fig. 3. The 2PB ﬂuorescence spectrum of N2 C3 Πu (v ) − B3 Πg (v ) transition in 280– 360 nm produced in the laboratory by electron excitation in the discharge. Various (v ,v ) bands are assigned in the spectrum.

excitation processes.2,3 However, our laboratory experiment shows that direct photoabsorption in the Tanaka system can generate the 2PB emission. Although the absorption process C ← X is forbidden, the production of 2PB ﬂuorescence is eﬃcient for the strongly allowed C → B

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emission. Absorption of the Tanaka band is particularly interesting at 109.9 nm for its match with lines of N I at 109.7–110.0 nm of 2 DJ −2 FJ transitions (NIST list seven lines in this multiplet for various J and J values between 1/2 and 7/2 producing emissions at 109.7237, 109.8095, 109.8260, 110.0360, 110.0465, 110.1291 nm). Since these NI emissions also exist in the dayglow spectrum,21 a resonant production of 2PB airglow by these N I atomic emissions would be feasible. The production 2PB airglow at 109.9 nm can be also made by solar radiation at the same wavelength. The 2PB ﬂuorescence can be eﬃciently produced at the (1,0) Tanaka band at 109.9 nm because of the strong C → B transition with unity quantum yield. Non-predissociative of low vibrational levels of N2 (C) with v < 4 has been reported.1 3.2. Excited states in 90–100 nm wavelength region To understand the EUV emissions of Titan airglow, the absorption and ﬂuorescence excitation spectra for 90–100 nm are studied as shown in Fig. 4. The absorption spectrum in 90–100 nm in the upper panel consists of many valence and Rydberg states with large cross sections especially for 1 1 + 1 1 + bands of b1 Πu , b1 Σ+ u , c Πu , c Σu , o Πg , and o Σg states. The strongest 1 absorption bands are caused by b Πu (v = 0 − 10), c41 Σu (v = 0 − 2),

Absorbance(a.u.)

8 6 4

1

bΠ 0 Ab sorption

c 3 (0 )

10 b'(8) c 3 '(2)

c 4 '(0)

c 3 '(1) O( 0)

2 0 90

91

92

94

95

c 4 '( 1 )

c 4 '( 2 )

c 4 '(3 )

Intensity(a.u.)

93

96

97

98

c 4 '(0 )

99

100

Fl uor es ce nce 1

2

b' Σ

10

b( 1) c 3 '(2)

b( 6)

0 90

91

92

93

94

95

96

97

98

99

100

wavelength (nm) Fig. 4. The absorption and ﬂuorescence excitation spectra for 90–100 nm. The assignments of the excited states are referenced in both diagrams.

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and b1 Σu (v = 8), and the strongest ﬂuorescence can be produced by c4 (0) and b(1, 5 − 8) bands (reference to assignments in the absorption spectrum). Excited states of c41 Σ+ u has large cross sections at the (0,0) and (1,0) bands as shown in the absorption spectrum. In the lower panel of Fig. 4, we ﬁnd bands of b1 Πu that produce weak ﬂuorescence except the b(1) band at 98.6 nm, indicating b1 Πu is strongly predissociative. More detailed discussions can be found elsewhere.20 Cassini UVIS observed emissions at 90.9, 91.5, 92.8, 94.4, 95.3, 96.5, 98.0, 98.7, 100.7, 102.6 nm.9 Emissions at 92.8, 96.5, 98.0, and 98.7 can be seen in the FES in Fig. 4 by the states b1 Πu (v = 9, 4, and 1) or alternatively by b1 Σ+ u (v = 0) at 96.5 nm. Emissions of the Titan airglow spectrum are produced by transitions between higher vibrational levels such as c4 (4,3), c4 (3,2), b (9,2), c4 (6,5), b (16,4) bands for 94.4 nm.10,11 4. Conclusion We have studied the absorption and ﬂuorescence excitation spectra of N2 in 90–145 nm wavelength region. In the region of 100–145 nm, the Tanaka system and LBH system are dominating the absorption spectrum and produces strong C3 Πu –B3 Πg (2PB) transition in 300–400 nm wavelengths. The production of airglow at 109.9 nm at the Tanaka (1,0) band is particularly interesting for its match with NI lines at the same wavelength. In the 90–100 nm wavelength region, a complex system of absorption and ﬂuorescence are observed. All these states are predissociative for sources of N atoms in the atmosphere. Acknowledgments This research is supported by the National Science Council of ROC. We thank Drs. S. Y. Chiang and B. M. Chen of NSRRC for helps during the experiment. References 1. 2. 3. 4. 5. 6.

A. Lofthus and P. H. Krupenie, J. Phys. Chem. Ref. Data 6 (1977) 103. D. C. Cartwright, J. Geophys. Res. 83 (1978) 517. R. R. Meier, Space Science Rev. 58 (1991) 1. Y. Tanaka., M. Ogawa and A. S. Jursa, J. Chem. Phys. 40 (1964) 3690. S.G. Tilford, J. T. Vanderslice and P. G. Wilkinson, Ap. J. 142 (1965) 1203. S. G. Tilford, P. G. Wilkinson and J. T. Vanderslice, Ap. J. 141 (1965) 427.

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7. 8. 9. 10.

P. G. Wilkinson, Ap. J. 126 (1957) 1. S. G. Tilford and P. G. Wilkinson, J. Mol. Spectrosc. 12 (1964) 231. J. T. Vanderslice, S. G. Tilford and P. G. Wilkinson, Ap. J. 141 (1965) 395. J. M. Ajello, J. Gustin, I. Stewart, K. Larsen, L. Esposito, W. Pryor, W. McClintock, M. H. Stevens, C. P. Malone and D. Dziczek, Geophys. Res. Lett. 35 (2008) L06102, doi:10.1029/2007GL032315. J. M. Ajello, M. H. Stevens, I. Stewart, K. Larsen, L. Esposito, J. Colwell, W. McClintock, G. Holsclaw, J. Gustin and W. Pryor, Geophys. Res. Lett. 34 (2007) L24204, doi:10.1029/2007GL031555. A. L. Broadfoot, B. R. Sandel, D. E. Shemansky, J. B. Holberg, G. R. Smith, D. F. Strobel, J. C. McConnell, S. Kumar, D. M. Hunten, S. K. Atreya, T. M. Donahue, H. W. Moos, J. L. Bertaux, J. E. Blamont, R. B. Pomphrey and S. Linick, Science 212 (1981) 206. A. L. Broadfoot, S. K. Atreya, J. L. Bertaux, J. E. Blamont, A. J. Dessler, T. M. Donahue, W. T. Forrester, D. T. Hall, F. Herbert, J. B. Holberg, D. M. Hunten, V. A. Krasnopolsky, S. Linick, J. I. Lunine, J. C. Mcconnell, H. W. Moos, B. R. Sandel, N. M. Schneider, D. E. Shemansky, G. R. Smith, D. F. Strobel and R. V. Yelle, Science 246 (1989) 1459. D. F. Strobel, M. E. Summers and X. Zhu, Icarus 100 (1992) 512. D. F. Strobel, R. R. Meier, M. E. Summers and D. J. Strickland, Geophys. Res. Lett. 18 (1991) 689. D. F. Strobel and D. E. Shemansky, J. Geophys. Res. 87 (1982) 1361. M. H. Stevens, J. Geophys. Res. 106 (2001) 3685. E. H. Wilson and S. K. Atreya, J. Geophys. Res. 109 (2004) E06002, doi:10.1029/2003JE002181. J. B. Nee, Chem. Phys. 315 (2005) 81. C. Y. Wu, Hok-Sum Fung, Kuang-Yu Chang, Thounaojam S. Singh, Xiao-lan Mu, Jan B. Nee, Su-Yu Chiang and D. L. Judge, J. Chem. Phys. 127 (2007) 084314. P. D. Feldman, D. Sahnow, J. Kruk, E. Murphy and H. Moos, J. Geophys. Res. 106 (2001) 8119.

11.

12.

13.

14. 15. 16. 17. 18. 19. 20.

21.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

VACUUM-ULTRAVIOLET ABSORPTION SPECTRA OF SMALL MOLECULES IN THE SOLID PHASE H.-C. LU, H.-K. CHEN, Y.-J. WU and B.-M. CHENG∗ National Synchrotron Radiation Research Center, 101 Hsin-Ann Road, Hsinchu Science Park, Hsinchu 30076, Taiwan ∗ [email protected] J. F. OGILVIE Escuela de Quimica, Universidad de Costa Rica, Ciudad Universitaria Rodrigo Facio, San Pedro de Montes de Oca, San Jose 2060, Costa Rica [email protected]

A synchrotron that provides intense and energetic radiation with a continuous span enables quantitative measurements of both wave length or wavenumber and intensity in the vacuum-ultraviolet region for compounds of astrophysical interest. We present absorption spectra of CO, CO2 , H3 COH, N2 O, O2 and NO in solid phases at 10 K to show the quality of spectra that is achievable with a cryogenic refrigerator coupled to a beam line of the Taiwan synchrotron producing radiation in a region of wavelength greater than 105 nm, limited by the transmission of LiF windows on cells. The astrophysical implications of our measurements are briefly discussed.

1. Introduction Despite the much enhanced experimental diﬃculty of measurements in the vacuum-ultraviolet region at a wave length less than 200 nm, early absorption spectra of gaseous samples provided information, even if largely qualitative, about electronic transitions of simple molecules, analogous to the results of more thorough analysis of spectra practicable in the visible and near-ultraviolet regions. Little information is, however, available about the spectra of these compounds in condensed phases, and even those reported spectra suﬀer from the challenging experimental conditions of those experiments. A synchrotron is an electron accelerator that provides intense and energetic radiation with a continuous span from the far infrared into the xray region. With such a source of light we have 453

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undertaken quantitative measurements of both wave length and intensity for compounds of astrophysical interest, comprising small molecules that exist as gases or vapours at temperature 300 K. To demonstrate the quality of spectra that is achievable with a cryogenic refrigerator coupled to a beam line of the Taiwan Light Source (TLS), we present here spectra of CO, CO2 , NO, N2 O, O2 and H3 COH in solid phases at 10 K, with other phases for comparison. These compounds are among the more abundant species of molecular matter discovered through astrophysical observations. 2. Experiments For these spectral measurements of samples in solid phases at 10 K, we employ a refrigerator system that operates with a Stirling cycle in two stages to attain that temperature.1−3 As depicted in Fig. 1, this refrigerator is connected to a beam line of the TLS so that beam of radiation is dispersed

Fig. 1. Apparatus employed for measurements of absorption spectra for a sample in a condensed or gaseous phase.

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with a diﬀraction grating; by this means we vary the wave length of light incident on a sample that is condensed from the gaseous phase onto a cooled LiF window. Part of the beam before the cryostat is directed to a detector so that we record a ratio of the intensity of light transmitted through the sample to the intensity of the light in the reference beam. From that transmission spectrum of a sample we subtract the spectrum of the background with no sample. This net signal hence becomes available for analysis of the spectral features, which we undertake as follows. For gaseous samples the cryostat is simply replaced with a cell to contain the sample between LiF windows. For our experiments the radiation is limited to a region of wavelength greater than 105 nm by the transmission of LiF windows on our cells. Our quantitative analysis of spectra of condensed or gaseous samples proceeds as follows. After conversion of wave length to wavenumber, the net absorbance is divided by wavenumber at each point to eliminate the frequency factor in absorption spectra, analysis of the intensity of these spectra shows that the reduced proﬁles are satisfactorily described with a sum of gaussian contributions, with central wavenumber, width, stature (net absorbance after subtraction of background) and integrated area as ﬁtting parameters. Under these conditions we locate and deﬁne both signiﬁcant electronic transitions and their vibrational substructure, even when the widths of individual contributions are comparable with the diﬀerences between adjacent features.

3. Results and Discussion The widths of these electronic and vibrational features evident in the accompanying plots of absorption spectra of the selected molecular samples make diﬃcult their assignment to transitions between particular electronic and vibrational states of molecules in condensed phases, but comparisons with spectra in the gaseous phase, which generally have narrower structure, and with the results of calculations of molecular electronic structure enable at least tentative assignments in most cases. A complicating characteristic of spectra of solid compounds is that the proximity of molecules and the expanded electronic volumes typical of excited electronic states generate strong intermolecular interactions that are absent from gaseous conditions and that calculations on single molecules fail to take into account. For most small molecular species that we have investigated, extensive delocalization in excited electronic states and excitonic phenomena appear

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2.5 1

A Π

2.0 1.5 1.0

10

5

0

1

E Π 1 + C Σ

A Π

1 +

B Σ

0.5

(c)

0.0

absorbance

2.5 2.0

90000

85000

80000

75000

10

5

1

E Π 1 +

1.5

70000

C Σ

65000 1

0A Π

1 +

B Σ

1.0 0.5

(b)

0.0 90000 2.0 1.5 1.0

85000 80000

70000

65000 60000

1

A Π 5

10

1 +

0

B Σ

0.5 0.0 95000

75000

1

E Π 1 + C Σ

(a) 90000

85000

80000

75000

70000

65000

-1

wavenumber /cm

Fig. 2. VUV absorption spectra of CO (a) as a gas at 300 K, resolution 0.02 nm; (b) as a pure solid at 10 K, resolution 0.03 nm; (c) dispersed in solid Ar (1/250) at 10 K, resolution 0.03 nm.

to be unimportant despite the broadening phenomenon, but Rydberg transitions seem to be generally absent from spectra of solid samples.4 As an example of this phenomenon, we show in Fig. 2 a comparison of spectra of carbon oxide as a gaseous sample, as a pure solid and dispersed in solid argon.1 Under our conditions of measurements, the absorption spectrum of this gaseous sample in Fig. 2a shows not only well deﬁned vibrational structure in several progressions that indicate separate upper electronic states but even rotational structure (not visible on the compressed scale of this plot) as either separate rotational lines or incompletely resolved branches. Because rotational motion is strongly inhibited in a pure condensed sample other than dihydrogen H2 and its isotopic variants, we hereafter ignore this aspect of the spectra. These spectra show that for the ﬁrst vibrational progression, assigned to an

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electronic transition A ← X, a similar structure is readily discernible under all three conditions of samples, but for only that ﬁrst electronic transition does the vibrational structure persist in the spectra of our condensed samples. A vestigial second vibrational progression within the region of the ﬁrst electronic transition is also deduced on ﬁtting the spectra. Relative to the spectrum of pure solid CO in Fig. 2b, the spectrum of CO dispersed in solid argon in Fig. 2c at a molar ratio 1:250 exhibits, however, narrower lines for that progression and narrower features ascribed to overlapping electronic transitions at greater wavenumbers. The diﬀerences between the spectra of pure solid CO and of CO dispersed in Ar reﬂect the extent of isolation of intrinsic molecular properties in the latter condition because the perturbation of a CO molecular species by about twelve atomic Ar entities surrounding it as nearest neighbours is small at energies less than that of the onset of appreciable absorption by solid argon. This isolation that is eﬀective to some extent hence prevents CO molecules from interacting with each other, or, more explicitly, a CO molecule excited to an upper electronic state from interacting with neighbouring CO molecules still in their electronic ground states such that that energy of excitation becomes transferable from one molecular centre to another. An alternative point of view is that a photon is absorbed not at all by one particular molecule, but rather by the collective assembly of molecules; although that point of view might be preferable for the more highly excited electronic states that show a loss of all discernible vibrational structure, the residual vibrational structure in the ﬁrst electronic transition might warrant the former point of view, namely an absorption event occurring primarily in a particular molecule that is, however, perturbed, and interacting to some extent, with its environment. The energy of excitation arising from an absorption of a photon invariably increases the eﬀective volume of a molecule, because that energy causes an altered distribution of electronic density, corresponding to a decrease thereof near the atomic nuclei and an increase at greater distances from nuclei. For a molecule in a gaseous sample under rareﬁed conditions such as for Fig. 1a, such an expansion of electronic density has a negligible eﬀect on other molecules, but in a condensed sample such expansion evidently increases the interaction between neighbouring molecular centres. This eﬀect might increase or decrease the wavenumber of maximum intensity associated with a particular transition, depending on the nature of the interaction. For an absorbing molecule surrounded by other and less polarizable species, an increased wavenumber is commonly

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observed, but with like molecules a phenomenon akin to resonance might decrease not only the wavenumber of maximum absorption but especially the onset of absorption, so to extend the absorption to the near-ultraviolet region. The spectrum of pure solid carbon dioxide in Fig. 3 contains four distinct regions of features — broad and weak lines with maxima near 54,300 and 70,000 cm−1 , a region of resolvable ﬁne structure centred about 79,000 cm−1 and, beyond 84,000 cm−1 , a much more intense block of absorption of which the shape is atypical of separate electronic or vibrational transitions;3 the latter region is satisfactorily ﬁtted with three overlapping lines, consistent with the shape of the curve at the top of the block, with the most intense component extending beyond the range of measurement. The ratio of statures of most intense and least intense ﬁtted components, at either end of the measured spectrum, attains 1,000. Between 75,800 and 83,750 cm−1 , as shown in the inset to Fig. 3, the absorption proﬁle is adequately ﬁtted with 14 lines in a sequence, with mean interval (611 ± 42) cm−1 comparable with their ﬁtted widths, of mean (710 ± 190) cm−1 . The fact that these widths are comparable with the separations between adjacent members of a vibrational progression in CO2 obscures this progression to a much greater extent than for the ﬁrst 2.0

0.15

absorbance

1.5 0.10

1.0 0.05

0.5

0.00 84000

82000

80000

78000

76000

74000

0.0 90000

80000

70000

60000

wavenumber / cm

50000

-1

Fig. 3. Absorption spectrum of solid CO2 at 10 K, resolution 0.2 nm; inset resolution 0.1 nm.

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progression in CO, shown in Fig. 2b; the separations, unlike the widths, are there much larger, reﬂecting the attribution of that progression in CO to a stretching vibrational mode but in CO2 to an angular deformation. For CO2 even in the gaseous phase, vibrational structure is diﬀuse at best, unlike the progressions discernible in multiple electronically excited states in the spectrum of CO in Fig. 2a. For pure solid methanol the absorption spectrum2 in Fig. 4a is entirely diﬀuse, exhibiting no individual feature that is separately resolvable or distinct from adjacent features; three components of that total absorption are deducible on ﬁtting with lines of gaussian shape, but those deduced individual properties are by no means unambiguous. In contrast, for methanol dispersed in solid krypton according to the spectrum in Fig. 4b, the modulation of the absorption proﬁle hints at underlying vibrational structures that are totally obscured in the spectrum of the pure solid. 3.0 (b) 2.5

1.5

5

absorbance / wavenumber / 10 cm

2.0

1.0 0.5 0.0 75000 70000 65000 60000 55000 50000 2.0

(a)

1.5 1.0 0.5 0.0 90000

80000

70000

60000

wavenumber / cm

50000

-1

Fig. 4. VUV absorption spectra of (a) pure solid H3 COH, resolution 0.25 nm; (b) H3 COH/Kr=1/250, resolution 0.2 nm, both samples at 10 K.

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The presence here of vacuum-ultraviolet spectra of CO, CO2 and H3 COH enables us to make further comparisons related to the size or number of constituent atomic centres of the molecules and the nature of the vibrations. For an isolated or free diatomic molecule, only a vibration described as a bond-stretching mode is possible; for CO the progressions in spectra of either gaseous or condensed samples accordingly show the corresponding intervals of wavenumber. For a free triatomic molecule, both bond-stretching modes and an angular deformation constitute the possible vibrational degrees of freedom; in the spectrum of solid CO2 in Fig. 3, only progressions associated with that angular deformation are discernible. For a polyatomic molecule such as methanol with a topology containing four atomic centres H-C-O-H bound in a non-linear sequence, also a torsional vibrational mode is possible;5 the spectrum of a gaseous sample exhibits much eﬀect of this torsional mode, but its small wavenumber relative to widths of lines in the solid phase or even for methanol dispersed in solid argon or krypton precludes identiﬁcation of such vibrational structure with even the most advanced ﬁtting procedures practicable at present. The spectrum of solid dinitrogen oxide in Fig. 5 exhibits only four distinct features,3 but the ﬁt of the total proﬁle near 65,000 cm−1 and 79,000 cm−1 seems to require further contributions centred near those locations. The ﬁrst weak and broad line, with maximum near 55,500 cm−1 , is practically separate from other features, with the other 2.5

absorbance

2.0

1.5

1.0

0.5

0.0 90000

80000

70000

60000

50000

40000

-1

wavenumber / cm Fig. 5.

VUV absorption spectrum of pure solid N2 O at 10 K, resolution 0.2 nm.

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ﬁve overlapping lines on either side of the prominent maximum near 77,500 cm−1 . Close scrutiny of the residual between the total absorption divided by wavenumber and the sum of those six features indicates the presence of two additional series of weak lines, superimposed on much broader and stronger lines. To ﬁt quantitatively these weak lines in the presence of much more intense and broad features proved impracticable because their statures are at most twice the amplitude of noise, but their widths seem smaller than the separations between adjacent lines. Eight features in the ﬁrst progression, beginning at 53,688 cm−1 have a mean separation (1,050±71) cm−1 between adjacent features, whereas six features in a second progression, beginning at 64,949 cm−1 , have a mean separation (674 ± 79) cm−1 . The spectrum of pure solid dioxygen in Fig. 6 contains apparently two broad lines, with maxima near 60,000 and 72,000 cm−1 ,3 and a hint of a further absorption feature beyond the range of spectral measurement. Fitting the total proﬁle of absorption with three gaussian contributions centred at 56,700, 62,400 and 72,700 cm−1 , rather than two, yields a signiﬁcantly improved ﬁt, but there is otherwise no evident requirement for the middle broad line. The curve of pure solid nitrogen oxide in Fig. 7 contains three readily recognizable features, all broad lines.3 The most prominent feature occurs before the vacuum ultraviolet region, with a maximum near 48,000 cm−1 ;

2.0

absorbance

1.5

1.0

0.5

0.0 90000

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another feature with maximum near 67,000 cm−1 is much broader but weaker, and a third continuum extends beyond the limit of measurements as restricted by the LiF windows. Four weak features are barely discernible as a weak modulation of the proﬁle of the subsidiary maximum near 67,000 cm−1 , with centres near wavenumbers/cm−1 65,600, 66,800, 68,100 and 69,300 with uncertainties 200 cm−1 , so with an interval approximately 1,200 cm−1 . The spectrum of solid N2 O in Fig. 5 hence manifests a signiﬁcant resemblance to that of solid CO2 in Fig. 3, whereas the spectra of solid NO and of solid O2 in Figs. 6 and 7 exhibit almost no discernible vibrational structure, in contrast with the spectrum of solid CO in Fig. 2b. Even for the latter three diatomic species their spectra diﬀer remarkably, but the trend to decreased vibrational structure in these cases bodes poorly for the possibility of discovering vibrational structure in larger molecules containing these moieties. 4. Conclusion Our survey of spectra in the vacuum-ultraviolet region of selected small molecular species in their pure solid phases, with spectra of gaseous samples or dispersions in solid Ar and Kr for comparison in some cases, indicates a poor prognosis for the prospective identiﬁcation of these compounds through the measurement of ultraviolet spectra — necessarily in reﬂectance,

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because an alternative absorption mode is impracticable — from the frozen surfaces of astronomical objects such as the farther planets and planetoids. These surfaces would inevitably contain mixtures of compounds, from which broad spectral lines of species such as CO2 , H3 COH, N2 O, O2 , and NO would be distinguishable with only the utmost diﬃculty. A further complication in the case of such a mixture is that the characteristics of spectral lines of each particular compound would undoubtedly be modiﬁed to a greater or lesser extent by the presence of the multiple components of that mixture. For only CO is there a reasonable prospect that its presence might be detected in such an environment by means of vacuum-ultraviolet spectra, even in the presence of its admixture with other compounds. For these discussed molecular species there is little or no absorption in spectra at wave lengths greater than 200 nm, with the prominent exception of NO. In such cases infrared spectra of these surfaces in reﬂectance might yield more conclusive evidence of the nature of these solid materials. With further data ﬁtted from spectra presented here, we discuss elsewhere3 also the spectra of solid H2 O (water ice) and solid ammonia, which like most solid compounds discussed above, show only highly diﬀuse absorption spectra in the vacuumultraviolet region. Acknowledgment National Science Council of Taiwan (grant No. 96-2113-M-213-006-MY3) provided support for this project. References 1. H.-C. Lu, H.-K. Chen, B.-M. Cheng, Y.-P. Kuo and J. F. Ogilvie, J. Phys. At. Mol. Opt. Phys. B 38 (2005) 3693. 2. Y.-P. Kuo, H.-C. Lu, Y.-J. Wu, B.-M. Cheng and J. F. Ogilvie, Chem. Phys. Lett. 447 (2007) 68. 3. H.-C. Lu, H.-K. Chen, B.-M. Cheng, and J. F. Ogilvie, Spectrochim. Acta Mol. Spectr. A71 (2009) 1485. 4. M. B. Robin and N. A. Keubler, J. Elec. Spectrosc. Related Phenom. 1 (1972) 13. 5. B.-M. Cheng, M. Bahou, W.-C. Chen, C.-H. Hui, Y.-P. Lee and L. C. Lee, J. Chem. Phys. 117 (2002) 1633.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

PHOTOABSORPTION SPECTRA OF SOME ORGANIC MOLECULES FOR PLANETARY INTERESTS JAN. B. NEE Department of Physics, National Central University, Chung-Li, Taiwan 32054 [email protected]

We have measured absorption spectra of several small organic molecules including ethylene, allene, propyne, acetone, and four simplest alcohols. Their absorption cross sections in 105–200 nm wavelengths are discussed and compared with previous works. The ethylene and allene show similar spectra resulting from of CC double bond excitations. For propyne and acetone, complicate structures are caused by many Rydberg states existed in the 10 eV energy region. For methanol, ethanol and propanols (1 and 2), their absorption spectra are divided into three continuous bands, with methane having Rydberg structures in the second band. Their long wavelength end can be fitted by Gaussian curves.

1. Introduction Many organic molecules exist in the outer planets including Jupiter, Saturn, their satellites such as Titan.1−4 They are also found in the comets.4 It is interesting to study the photochemical processes of organic molecules in these atmospheres. Methane, which is the simplest organic compounds, has been found in several planetary atmospheres. Photodissociation or electron impact dissociation of methane is source of free radicals CH, CH2 , and CH3 which are precursors of complex carbons. In general, photochemistry of hydrocarbon molecules is important in determining the composition and structures of the atmospheres of outer planets, their satellites, and comets. The hydrocarbon photochemistry involved not only methane and alkanes, but also compounds of double and triple bonds of carbon molecules, which can be produced by secondary products of methane. For example, ethylene can be produced by the reaction: CH2 + CH3 → C2 H4 + H

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Similar reactions will lead to the productions of C2 H2 , C3 H4 , C2 H6 , C3 H8 , etc. which have been studied by several planetary models1−3 and observed by Cassini mission.5 Isomers of carbon compounds with double or triple bonds are also important constituents. For example, there are three forms of C3 H4 : methyl-acetylene (CH3 C2 H), allene (CH2 CCH2 ), and a ring formed cyclicpropene. They may be produced by insertion a CH into a C2 compounds. Except for cyclipropene, the other two compounds have been studied as atmospheric compositions.1−3 To understand the photochemistry of organic compounds for the outer planets, an extensive laboratory data is needed. The modeling works usually involve hundreds of reactions. Currently, there is lacking of data for many hydrocarbon molecules, including simple compounds whose data are sometimes incomplete or even unavailable in several wavelength regions as indicated in some papers.3,4 A lot of earlier photoabsorption measurements were made with photographic method, or deduced from electron energy loss techniques, or in limited wavelength regions by using resonance lines produced in discharge lamps. These data are valuable for understanding the electronic structures of the excited states. But absolute cross sections in extended wavelength regions and temperature dependent studies are needed especially for planetary study purposes. In this paper, we would like to report the absorption spectra for several simple organic molecules including ethylene, allene, methyacetylene, acetone, and four types of alcohols (methanol, ethanol, and two forms of propanol). We will compare our results with recently available references. A complete review of the literatures is beyond the scope of this paper due to limited space. We will limit our studies to absorption cross sections and without detailed discussions on their spectroscopic information (such as assignments of excited states) in general. Excited states involved in the short wavelength region as studied here are mostly Rydberg states. Their assignment and interactions are extremently interesting. However, such studies are elaborate and lengthy, which are not generally interested for aeronomy studies.

2. Experimental The experiments are carried out either in the laboratory of the National Central University (NCU) or at the National Synchrotron Radiation Research Center (NSRRC) at Hshinchu, Taiwan as described in previous publications.6−7 The experimental results presented here have been

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carried out over many years of works; therefore, experimental conditions are diﬀerent. The experiments measured at NCU were carried out by using 0.5 meter and 3 meter monochromators with light sources of a tungsten lamp, deuterium lamp, or a H2 discharge lamp. Absorption cells of diﬀerent path lengths ranging from 0.3–2.0 meters have been employed. For measuring absorption spectra at wavelength in 60–165 nm, the experiments were carried out using the synchrotron radiation at the NSRRC. The continuous radiation is dispersed by various monochromators for experimental use. There are several monochromator systems at diﬀerent beam lines suitable for photoabsorption studies. The 1-m Seya type monochromator has been used by us more often than other systems. For large absorption cross section, a short path of about 35 cm was employed with the absolute length of the absorption path calibrated by using absorption cross sections of the Schumann-Runge continuum of oxygen. Both the laboratory and synchrotron radiation experiments were overlapped in some wavelength region (usually in 160 nm region) to compare. The experiments were usually measured with resolutions 0.03–0.1 nm. However, some results were smoothed to 0.1 nm intervals such that results may be more easily used although resolution is reduced. The pressures of the gases were measured by a few calibrated pressure transducers (MKS Baratron). All chemicals were purchased from the best grade available commercially (such as optic grade for alcohols). The absorption cross sections are determined by using the Lambert Beer’s law with uncertainty mainly resulting from ﬂuctuations of light intensity and pressure measurements. The average error for each experiment is diﬀerent but generally about ±10%. There may be systematic error depending on the condition. However, we often calibrate our system by absorption spectrum of O2 in the Schumann-Runge continuum to check the accuracy. 3. Results and Discussion 3.1. C2 H4 The absorption spectrum of ethylene in the wavelength range 105–190 nm is shown in Fig. 1. The spectrum consists of several broad bands at 185–140, 140–130, 130–110 and 110–105 nm. Such groups of absorption bands have been observed in many hydrocarbon molecules such as C3 H4 and alcohols. The absorption spectrum start with peaks of Rydberg states in 160–175 nm wavelength region as shown in Fig. 1. Several doublet peaks

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at 160–175 nm have been assigned to the C=C stretching (υ2 = 1,380 ∼ 1,180 cm−1 ) and C=C torsion (υ4 ∼ 454 cm−1 ).9 These vibrational energies are in good agreement with those reported by McDiarmid9 (viz υ2 = 1,374 cm−1 and υ4 = 461 cm−1 ). A few bands at 140 nm are Rydberg states converging to the ionization threshold at 118 nm. The absorption spectra have been reported by a few authors with emphasize on the spectroscopy of the excited states.8−10 Absolute cross sections have been reported by the early references of Watanabe and Zelikopf 8 for wavelength region 106.5–200 nm and by Wu et al. 10 for 118–192 nm with temperature dependence. Our cross sections are higher by about 2% than those of Watanabe and Zelikopf 8 but smaller by about 17% than those of Wu et al.10 As a simple and symmetric organic molecule, ethylene has been studied extensively for understanding the spectroscopy of the excited state, as discussed in Robin.12 The research has been continuously published by many scientists at present time for understanding its electronic structure.13 3.2. C3 H4 3.2.1. Allene The absorption spectrum of allene in the wavelength region of 105–200 nm is shown in Fig. 2. The absorption spectrum of allene has been reported previously by several authors.14−17 Compared with the most recent

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studies,16 our cross sections are about 22% higher in the ﬁrst band at 170 nm, 25–40% higher in the second band at 140 nm, and 8–18% higher at 120–130 nm. Early data14 showed cross sections smaller by about 40% in some region compared with cross sections of Chen et al.16 Our higher cross sections compared with past references may cause by resolution, since our data was measured at 0.05 nm resolution. Although a smoothing to 0.1 nm interval has been made later. There could also be just experimental errors. It is interesting to compare the absorption spectrum of C3 H4 with that of C2 H4 . We ﬁnd a kind of similarity between absorption spectra of both molecules. There are three groups of absorption bands in 110–180 nm for allene, similar structures are found for ethylene. Further more, the absorption cross sections of C3 H4 are about twice as large as compared with those of C2 H4 . For example, allene has a maximum cross section of about 120 Mb (10−18 cm2 ) for the ﬁrst band at 170 nm, and ethylene’s ﬁrst band has a maximum cross section of about 60 Mb. The other bands have similar ratio although ﬁne diﬀerences do exist. The similarity in the absorption spectra and their relative magnitude of cross sections between allene and ethylene can be understood in terms of the electronic structures of both molecules. There are two double bonds (π bonds) in C3 H4 instead of a single one in C2 H4 . The two π bonds in C3 H4 are known to be perpendicular to each other with little interaction. As a result, the intensity of electronic transitions is twice as large for allene compared with those of ethylene.

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By examining the spectra in scrutiny, we found diﬀerences do exist between C2 H4 and C3 H4 . For example, ethylene shows more structures in the ﬁrst band at 170 nm while allene has more structures in the middle band at 150 nm. The doublet structures at 175–160 nm for ethylene are not appeared in allene. This is probably partially caused by broadening of bands for C3 H4 since it is a larger molecule. It will be interesting to study the interaction of two pi bonds to see any eﬀects. 3.2.2. Methylacetylene (Propyne) The absorption spectrum of propyne, CH3 C2 H, is shown in Fig. 3. With a combination of triple and a single CC bond, propyne has an absorption spectrum diﬀerent from that of allene. At energies higher than about 8 eV, many peaks of Rydberg states converging to the ionization threshold at 119.6 nm exist as discussed in Robin.12 The absorption cross sections have been reported by a few authors recently.16,18 Fahr and Nayak18 reported the absorption spectrum for the long wavelength continuum in 160–200 nm. Temperature dependent data have been published by Chen et al.,16 who have also discussed the causes of the discrepancies between their results and data of Ref. [18] and earlier ones. Our data agrees within 5% with that of Ref. [16]. Studies of excited states including their assignment has been reported by Ho et al.19

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3.3. Acetone The absorption spectrum of acetone in 104–200 nm is shown in Fig. 4. The absorption spectrum in 112–310 nm has been reported recently.20 There are two regions of interests: in the 185–200 nm region, there are three strong absorption bands corresponding to the Rydberg state transition no → 3s (at 195 nm),12,20 and in 105–170 nm, structured continuum of higher Rydberg states (ns, np, and nd) exist. The ﬁrst band at 195 nm have been investigated earlier,21−23 with the absorption cross sections agreeable with us within about 10%. In the short wavelength region, our cross section is also consistent with the recent report20 within about 10%. Acetone is a potential source for odd hydrogen and aﬀects NOx chemistry in the atmosphere. The HOx produced from acetone may lead to CH2 O formation in the lower atmosphere of Earth.24 Their planetary signiﬁcance has been rarely studied. 3.4. Alcohols: CH3 OH, C2 H5 OH, 1-C3 H7 OH, and 2-C3 H7 OH The absorption spectra for four types of alcohol molecules CH3 OH, C2 H5 OH, 1-C3 H7 OH, and 2-C3 H7 OH (isopropanol) in the wavelength region 105–210 nm are shown in Fig. 5. The absorption spectra of all four molecules are similar and may be divided into three regions of continua at

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Fig. 5. Absorption spectra of methanol, ethanol, 1-propanol, 2-propanal in wavelength regin 105–210 nm. Resolutions are 0.1 nm.

wavelengths 165 ∼ 210 nm (1st continuum), 140–165 nm (2nd continuum), and 105–140 nm (3rd continuum). The continuous absorption in the ﬁrst region can be ﬁtted by Gaussian functions with excellent correlation coeﬃcients when compared with experimental data.The details are not discussed here due to limited space. In the 2nd region between 140– 165 nm, only methanol has structured bands, while ethanol and two types of propanols have structureless continua. The absorption cross sections for the 3rd part in 105–140 nm are continuous for all species with cross sections rising at higher energy regions for all molecules. The absorption cross sections in 105–210 nm have been reported by various authors.25−29 However, these early data are limited in wavelength regions. For example, Harrison et al.25 reported the absorption spectra of four types of alcohols in the wavelength region 200–154 nm (50,000– 65,000 cm-1). Salahub and Sandorfy26 extended the spectrum to about 117 nm (85,000 cm-1). Nee et al. reported absorption spectrum for methanol for 105–198 nm.27 Vinogradov and Vilesov29 reported the absorption and photodissociation of all alcohols in the wavelength region 90–150 nm. Compared with early references,25,26 our current spectra are more complete by extending into wavelength at about 210 nm. Our current cross sections

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are consistent with past results within ±5% at the peaks of the 180 nm continuum. At short wavelength region at 125 nm, our cross sections are within about ±10% compared with those of Ref. [26]. Photodissociation of alcohols in 105–210 nm wavelengths should be important for producing radicals such as CH3 and OH.30−32 The abundances of simple alcohols in planetary, comets, and interstellar medium has been reported.1−4 4. Conclusion Absoprtion spectra of several organic molecules are reported in wavelength region 105–200 nm with results compared with previous references. For ethylene, allene, and four alcohols, the spectra are divided into three broad regions. The double bond ethylene and allene show interesting similarity between their spectra and e cross sections. The absorption spectra for propyne and acetone consist of excitations of various Rydberg states. Four simplest alcohols, from methanol to propanol, have similar absorption spectra, which can be divided into three continua in the wavelengths 185–210 nm, 140–165 nm, and 105–140 nm. The ﬁrst region can be ﬁtted excellently by Gaussian functions. The cross section of all but allene show deviation of less than about 20%. Acknowledgments This research is supported by the National Science Council of ROC with project number NSC02-2008 M-008-046. We wish to thank staﬀs of SRRC for technical support at the Seya beam line. References 1. Y. L. Yung and W. B. DeMore, Photochemistry of Planetary Atmospheres, Oxford University Press, New York, (1999). 2. J. I. Moses, T. Fouchet, R. V. Yelle, A. J. Friedson, G. S. Orton, B. B´ezard, P. Drossart, G. R. Gladstone, T. Kostiuk and T. A. Livengood, The stratosphere of Jupiter, in Jupiter: Planet, Satellites and Magnetosphere, eds. by F. Bagenal, T. E. Dowling, W. B. McKinnon, Cambridge Univ. Press, New York, 2004, pp. 129–157. 3. G. R. Gladstone, M. Allen and Y. L. Yung, Icarus 119 (1996) 1. 4. J. Crovisier, J. Geophys. Res. 99 (1994) 3777–3781. 5. D. E. Shemansky and X. Liu, J. Geophys. Res. 110 (2005) A07307. 6. P. C. Lee and J. B. Nee, J. Chem. Phys. 112 (2000) 1763. 7. J. B. Nee and H. S. Fung, Adv. Geosciences, to be publish, (2008).

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8. 9. 10. 11.

M. Zelikoﬀ and K. Watanabe, J. Opt. Soc. Am. 43 (1953) 756. R. McDiarmid, J. Phys. Chem. 84 (1980) 64. G. Cooper, T. N. Olney and C. E. Brion, Chem. Phys. 194 (1995) 175. C. Y. R. Wu, F. Z. Chen and D. L. Judge, Temperature-dependent photoabsorption cross sections in the VUV-UV region: Ethylene, J. Geophys. Res. 109 (2004) E07S15, doi:10.1029/2003JE002180.12 M.B. Robin Higher Excited States of Polyatomic Molecules, Vol. III Academic Press, New York, (1985). A. Hazra, H. H. Chang and M. Nooijen, J. Chem. Phys. 121 (2004) 2125. J. W. Rabalais, J. M. McDonald, V. Scherr and S. P. McGlynn, Chem. Rev. 71 (1971) 73. M.P. Holland and D. A. Shaw, Chem. Phys. 243 (1999) 333. F. Z. Chen, D. L. Judge and C. Y. R. Wu, Chem. Phys. 260 (2000) 215. M. H. Palmer, J. Molec. Spectrosc. 237 (2006) 123. A. Fahr and A. Nayak, Chem. Phys. 203 (1996) 351. G. H. Ho, Ming S. Lin, Yuan L. Wang and Ten W. Chang, J. Chem. Phys. 109 (1998) 5868. M. Nobre, A. Fernandes, F. Ferreira da Silva, R. Antunes, D. Almeida, V. Kokhan, S. V. Hoﬀmann, N. J. Mason, S. Edenc and P. Lima˜ o-Vieira, Phys. Chem. Chem. Phys. 10 (2008) 550. T. S. Lake and A. J. Harrison, J. Chem. Phys. (1959) 30361. Ito, Y. Nogata, S. Matsuzaki and A. Kuboyama, Bull Chem. Society Japan 42 (1969) 2453. H. Ogata, J. Kitayama, M. Koto, S. Kojima, Y. Nihei and H. Kamada, Bull. Chem. Soc. Japan 47 (1974) 958. S. A. McKeen, T. Gierczak, J. B. Burkholder, P. O. Wennberg, T. F. Hanisco, E. R. Keim, R. S. Gao, S. C. Liu, A. R. Ravishankara and D. W. Fahey, Geophys. Res. Lett. 24 (1997) 3177. A. J. Harrison, B. J. Cederholm and M. A. Terwilliger, J. Chem. Phys. 30 (1959) 355. D. R. Salahub and C. Sandorfy, Chem. Phys. Lett. 8 (1971) 71. J. B. Nee, M. Suto and L. C. Lee, Chem. Phys. 98 (1985) 147. J. C. Person and P. P. Nicole, J. Chem. Phys. 55 (1971) 3390. I. P. Vinogradov and F. I. Vilesov, Khim. Vys. Energ. 11 (1977) 17. S. Satyapal, J. Park and R. Bersohn, J. Chem. Phys. 91 (1989) 6873. S. Harich, J. J. Lin, Y. T. Lee and X. M. Yang, J. Chem. Phys. 111 (1999) 5. J. C. Han, M. Suto and L. C. Lee, J. Quant. Spect. Rad. Transf. 42 (1989) 557.

12. 13. 14. 15. 16. 17. 18. 19. 20.

21. 22. 23. 24.

25. 26. 27. 28. 29. 30. 31. 32.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

C2 H2 ABSORPTION CROSS-SECTION MEASUREMENTS AT EXTREME LOW TEMPERATURE — A WINDOWLESS TECHNIQUE∗ J. I. LO, Y. C. LIN and T. S. YIH, National Central University, Jhongli, Taiwan C. Y. R. WU† and D. L. JUDGE University of Southern California, Los Angeles, California, USA † [email protected] H. S. FUNG National Synchrotron Radiation Research Center, Hsinchu, Taiwan

A new windowless absorption cell technique for gas phase cross-section measurements has been implemented and preliminary results of C2 H2 in the spectral region between 146 and 154 nm have been obtained with a resolution of 0.01 nm and at temperatures of 296, 151, 139, and 130 K. The detailed calibration procedures for the eﬀective path length of the windowless cell are described, and the absolute cross-section values determined are reported. The cross-section data at 296 and 151 K obtained from the present windowless absorption cell technique agree very well with the corresponding data previously obtained using a closed absorption cell. Under the molecular ﬂoe conditions the eﬀective path length at 150 K is found to be the same as that at 296 K. If we assume the sticking coeﬃcient of C2 H2 at 296 K is Sc296 K = 0, we obtain a sticking coeﬃcient value of Sc150 K = 0.32 ± 0.02 at 150 K. The data obtained will provide low-temperature absorption cross-sections of the solar system molecules, and thus determine temperature sensitive properties for diagnostic work on the atmospheres of outer planets, putting deﬁnitive constraints on the physical chemistry, radiative cooling, and atmospheric dynamics of Saturn and Titan.

1. Introduction CH4 , C2 H2 , and other light hydrocarbons have been observed in the atmospheres of Jupiter,1−4 Saturn,2,5 Uranus,6,7 Neptune,8,9 Titan,10,11 ∗ This

work is supported by the NASA Planetary Atmospheres Program under Grant No. NNG06GG72G. 475

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and Triton.12,13 CH4 has also recently been detected in the atmosphere of Mars14,15 Since we are particularly concerned with the outer planets, it may be interesting to mention that the relevant atmospheric temperature is ∼170–1,000 K for Jupiter, ∼140–350 K for Saturn, ∼97–200 K for Titan, ∼50–100 K for Triton, ∼44–100 K for Pluto, and even lower for Uranus and Neptune. It is well documented that molecular cross-section values can vary signiﬁcantly in certain spectral regions as temperature changes.16−19 Therefore temperature dependent cross-sections are required to provide important data for modeling the atmospheres of a broad range of planets and satellites throughout the solar system. Recently the Cassini UVIS experiment detected six species, CH4 , C2 H2 , C2 H4 , C2 H6 , C4 H2 , and HCN, of the atmosphere of Titan from stellar occultations by Titan.20 The observations cover an unprecedented range of altitudes from 450 km to 1,600 km, allowing the ﬁrst determination of the mesopause. The properties of C2 H2 in particular allow the determination of temperature in occultation measurements providing an important limit on determination of atmospheric structure. Furthermore, a very large decrease in the apparent absorption cross-section of C2 H2 in the 149.0–151.0 nm region is observed in the mesopause regions of both Saturn and Titan21 implying very low temperatures (∼120 K or lower). With cross-section data at temperatures lower than 140 K it will be possible to analyze observational measurements at the mesopause on both Saturn and Titan for the ﬁrst time. This will in turn put deﬁnitive constraints on the physical chemistry, radiative cooling, and atmospheric dynamics, a signiﬁcant advance in our understanding of these atmospheres. The temperature dependent cross-section data of CH4 and C2 H2 have recently been reviewed.17,19 In brief, the low temperature absorption crosssections of C2 H2 have been measured at 195 K, 173 K, 155 K, and 145 K, while those for CH4 have only been measured at 200 K and 150 K. It is important to model the atmospheres of Titan and the other outer solar system bodies with the cross-sections of these hydrocarbons measured at the appropriate temperature. It is our goal to measure cross-sections of C2 H2 to a temperature as low as 110 K using the new windowless cell setup. In this preliminary study we have demonstrated that we can measure the cross-section of C2 H2 at 130 K using a 10 cm cell. We also found that the C2 H2 gas pressure in the windowless cell is about 6 mTorr at 110 K.22 If a 30 cm long cell is used we will have a column density of ∼180 cm· mTorr, which will allow accurate cross-section measurements with values as small as 1 × 10−19 cm2 . In other words, it will be possible to carry out

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C2 H2 cross-section measurements at 110 K in the VUV region. This work is scheduled for the near future.

2. Experimental Setup and Experimental Procedures An experimental facility with closed absorption cells has been previously used in our cross-section measurements to a temperature as low as 145 K16−19 by using the industrial grade Triple-Cascade Refrigeration System (Model P-200, Polycold Systems Inc.). To extend this capability a liquid nitrogen dewar and a heating unit was utilized as a temperature adjustable cooling system. The lowest temperature will be 77 K, liquid nitrogen temperature. Thus, the new windowless absorption cell apparatus will allow us to carry out measurements at temperatures lower than 140 K. In the following a brief description of the setup, experimental procedures, and the preliminary results is provided. The experimental arrangement is composed of four parts: a continuum synchrotron radiation source and a vacuum monochromator, a windowless photoabsorption cell, a detection system, and a data acquisition system. A schematic diagram of the experimental chamber is shown in Fig. 1. Two solar-blind PMT (Hamamatsu R1460) detectors were used to monitor the incident and transmitted synchrotron radiation (SR) light intensities, respectively. A PC based data acquisition system is employed to acquire and process the incident and transmitted photon ﬂux data, the gas pressure and the temperature of the windowless absorption cell as a function of the incident photon wavelength.16−19 In the windowless apparatus a 510 liter/s turbomolecular pump was used to provide a base pressure of 1 × 10−9 Torr. The typical operating pressure in the chamber is normally less than 5×10−5 Torr with a maximum sample gas pressure of ∼100 mTorr in the windowless absorption cell operation. The dimensions of the cell are 10 cm in length and 4 cm in inside diameter. At each end of the windowless cell is an open oriﬁce with a dimension of 2 cm in length and 0.2 cm in diameter. The combinations of the oriﬁce size and the gas pressure used in the measurements result well within molecular ﬂow conditions. The large inside diameter and thick wall (1.2 cm) of the cell body provides a large volume and a heavy heat sink so that accurate pressure reading and stability of temperature can be achieved. Two low-temperature sensors (a LakeShore silicon diode and a thermocouple, marked as number #2 and #3 in Fig. 1) are attached to the bottom of the cell body. The temperature of the windowless absorption

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Fig. 1. A schematic diagram of the new experimental chamber system. The dimensions of the windowless absorption cell are 10 cm in length and 4 cm in inside diameter, with a long oriﬁce (2 cm long and 0.2 cm inside diameter) on each end of the cell. The lowest temperature at which it can be operated is about 77 K. In the diagram the number #1 indicates the port connecting to an ultrahigh speed turbomolecular pump station; #2 and #3 indicate the temperature sensors (a silicon diode and a thermocouple); #4 a LiF beam splitter; and #5 is a connection to pressure gauges (a 0.1-Torr and a 2-Torr head MKS capacitance manometer). The gas enters the cell body after a long winding cooling path.

cell is stable to within ±1 K for a given temperature over a period of a typical experimental run, i.e. 16 hours. The gas is controlled by a precision ﬂow meter and gets into the cell body after a long winding cooling path, which is machined on the space block between the liquid nitrogen dewar and the windowless cell body. The gas pressure inside the windowless cell is monitored by temperature-stabilized pressure gauges (a 0.1-Torr and a 2-Torr head MKS capacitance manometer). The pressure reading has an accuracy of 10% for a given pressure in the range between 1 mTorr and 100 mTorr. The 6-m Cylindrical Grating Monochromator High-Resolution Spectroscopy Undulator Beamline available at the National Synchrotron Radiation Research Center (NSRRC), Taiwan, was utilized in this preliminary study. Calibration of the High-Resolution Spectroscopy Monochromator wavelengths has been established by comparison with the spectral positions of the atomic absorption lines of the rare gases and Mg vapor.23 We have routinely made use of the known sharp absorption features

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of CO in our in-situ wavelength calibration.24,25 In the present work a resolution (fwhm) of 0.01 nm was found suﬃcient to resolve the 3R0 and 3R1 Rydberg series of C2 H2 in the 146–154 nm region. The uncertainty in wavelength determination is ±0.02 nm. The C2 H2 gas was supplied by Matheson Gas Products, Inc. In purifying the C2 H2 sample the standard freeze-pump-thaw-pump-distill technique has been found to be very eﬀective in removing acetone,16,19,26,27 which is commercially used as a chemical stabilizer in the C2 H2 sample cylinder.

3. Data Analysis and Results The advantage of using a windowless cell is that it is free from gas condensation occurring on the optical windows, which often takes place in a closed absorption cell system at temperatures lower than the melting point of the gas of interest. However, in a windowless cell it is necessary to accurately determine the eﬀective path length (or the column density) in order to make accurate cross-section measurements. The following text describes the procedures of path length calibration, data reduction and analysis, the determination of C2 H2 cross-section values, the deduction of C2 H2 sticking coeﬃcient at 150 K, and discussion. 3.1. Procedures for data reduction and analysis The NSRRC facility has been operated in TOP-UP Operation, in which electron current in the storage ring is maintained at a constant level of 300 mA by injecting a few electrons per minute. The mode of operation gives a constant current in the storage ring to better than 0.5%, and hence a constant photon radiance to better than 99% stability. A LiF window installed in the beamline eﬀectively eliminates high order SR radiation for wavelengths shorter than 106 nm. However, stray light has to be corrected through data reduction. Therefore, a non-standard notation is required to clearly explain the step by step outline of the data acquisition and reduction procedures, which have been developed over the past three decades of experience as a synchrotron radiation (SR) user. The methods used are described below. For a given absorption cell temperature, T (K), and path length of the cell, d cm, the raw data obtained from the automatic data acquisition system are for a given sample at various pressure conditions. A split-beam

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technique has been employed in the present work.28 As shown in Fig. 1 the intensity of the photon beam transmitted through the absorption cell (IT 0 , monitored by PMT 2) is readily corrected for variation in the incident photon intensity (IBS , the reﬂected light intensity from the beam splitter as monitored by PMT 1). This gives a measure of the light intensity ratio IT 0 /IBS , which eﬀectively eliminates small ﬂuctuation in the SR photon beam. The ratio of the incident light intensity to the transmitted light intensity, IT 0 /IBS , measured at a given wavelength and gas pressure, is given by R = (IT 0 /IBS )/(IT 0 /IBS ).

(1)

The values of Ln(R) obtained for the diﬀerent gas pressures can be used to obtain the cross-sections. For a given spectral region of interest, at least six spectra, each corresponding to a diﬀerent gas pressure, are normally obtained from which the cross-section data can be determined. To make sure that the measured raw data are free from the eﬀects of saturation due to high column density we reject those data sets in our data reduction which deviate from the linear behavior as a function of pressure. A slope, S (in units of mTorr−1 ), is determined from the least-square-ﬁt of Ln(R) vs gas pressure P (in units of mTorr). This procedure allows us to eliminate the low level stray light in the SR light source. Under the present experimental setup and for a given temperature (T = nRT /P V ), the relationship between the absorption cross-section, σ (in units of cm2 ), and the determined slope is given below:16,19 σ = 1.02 × 10−16∗ T (K)∗ S/d.

(2)

3.2. Determination of the eﬀective path length Regarding the determination of the eﬀective path length, d, using a windowless absorption cell we have adopted a calibration procedure developed in our previous investigations of high-temperature ultrahighresolution (0.0003 nm) absorption cross-section measurements of N2 and O2 .29−31 In the present work we selected four major peaks of C2 H2 at 147.8, 148.2, 149.8, and 151.9 nm, where the absorption cross-sections have been measured using a closed cell technique at 150 K19 and 295 K.19,32 We ﬁrst used 10 cm (the length of the windowless cell body) as the path length in our cross-section determination. By normalizing the deduced values to the reported values of C2 H2 at the four wavelengths we obtained an eﬀective

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11.8

11.6 146

147

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150

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Photon Wavelength (nm) Fig. 2. The calibration results of the eﬀective path length of the windowless absorption obtained by normalizing the cross-sections to those obtained with a closed window cell. The eﬀective path length is determined to be 11.83 (±0.05) cm under the present experimental conditions.

path length. In Fig. 2 we display the eﬀective path lengths obtained for the four diﬀerent wavelengths and two temperatures. From a linear ﬁt we obtained a calibrated eﬀective path length d = 11.83 (±0.08) cm. The eﬀective path length appears to be insensitive to gas temperature at 151 and 296 K, with the C2 H2 pressures operating in the range between 3 mTorr and 80 mTorr. This is understandable because the conditions at which the data obtained were well within the molecular ﬂow regime. 3.3. Determination of cross-section values at low temperatures The calibrated eﬀective path length 11.83 cm is subsequently used in the cross-section determination for the C2 H2 at gas temperatures of 139 and 130 K. The results are shown in Fig. 3 along with those measured at 296 and 151 K. The two major peaks are members of the ﬁrst two Rydberg series of C2 H2 , R0 at 151.93 nm and R1 at 147.79 nm.19 The shoulder of the R0 band at 151.32 nm appears to be a hot band, which quickly vanishes as the temperature decreases. This shoulder does not ﬁt with any known absorption features of acetone,16,19,26,27 which is commercially used as a chemical stabilizer in the C2 H2 sample cylinder. The proﬁles of the P - and

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296K 151K 139K 130K

80 70 60 50 40 30 20 10 0 146

147

148

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150

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152

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Photon Wavelength (nm) Fig. 3. The cross-sections of C2 H2 in the spectral region between 145 and 154 nm measured at 296 K, 151 K, 139 K, and 130 K using the windowless absorption cell.

R-branches of the R1 band at low temperatures clearly show the changes of rotational and vibrational population distributions in the ground electronic state of C2 H2 . The band shapes of the R0 and R1 , as well as the very much weaker features in between the two bands, all become sharper (narrower) with the decrease of temperature. Furthermore, we note that the crosssection values in between the two bands show a better S/N ratio than do the previously reported values.19 The present results at 296 K and 151 K agree very well with our previously reported data at 295 K and 150 K using a closed absorption cell with LiF windows.16,19 3.4. Deduction of C2 H2 sticking coeﬃcient at 150 K Finally, we would like to brieﬂy discuss why eﬀective path length does not seem to change much from 296 to 150 K in the case of C2 H2 . For an ideal gas system and when the pressure is very low so that molecular ﬂow conditions prevail inside an oriﬁce tube (with a dimension of L cm in length and D cm in diameter) the conductance is given by the well known equation:35,36 C = 3.81(T /M )1/2 (D 3 /L).

(3)

Here C is in units of liter/sec, which is equivalent to pumping speed through the tube. For a given T and a molecule with mass M the conductance

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is independent of the pressure under molecular ﬂow conditions, as is the eﬀective path length for gaseous molecules to pass through the oriﬁce tube. According to Eq. (3) the conductance decreases proportionally to the decreases of the square root of temperature, provided that the ideal gas law is valid. However, as temperature decreases there are interactions occurring between the gas and surfaces (or substrate in surface physics). The surface interactions can range from simple physical adsorption to complicated chemical reactions. The principle of a cryo-pump is based on surface adsorptions at low temperatures because the sticking coeﬃcient, ScT , increases as temperature decreases. As a result, the conductance can be aﬀected by temperature and the nature of the gas and the substrate of interest. In the present work only the temperature is relevant to our consideration. For C2 H2 , and condensable gases in general, the sticking coeﬃcient is expected to increase as temperature decreases. Therefore the eﬀective conductance will obviously increase because of increasing sticking coeﬃcient. In a cryo-pumping system37 the cryo-pumping speed is proportional to [2ScT /(2 − ScT )] or [ScT /(1 − ScT )], respectively, depending on whether the cryo-tube is perpendicular to or directed toward the gas stream. In other words the additional conductance contributed by the cooling and sticking eﬀect can be described37 as: CT ≈ (T /M )1/2 [2ScT /(2 − ScT )].

(4a)

CT ≈ (T /M )1/2 [ScT /(1 − ScT )].

(4b)

When there is no sticking eﬀect, namely, ScT = 0, the additional conductance in Eq. (4) is equal to zero because there is simply no cryopuming eﬀect. The maximum cryo-pumping speed, and hence the maximum conductance, is achieved when every molecule impinging on the cryosurfaces sticks to it, i.e. ScT = 1. From the result shown in Fig. 2 the calibrated eﬀective path length is roughly constant between 296 K and 150 K. This suggests that the conductance of our open windowless oriﬁce is roughly the same at both temperatures because the T 1/2 decrease is compensated for by the increasing sticking coeﬃcient, ScT . In the present experimental setup the directions of the molecular ﬂow and the windowless cell fall between the above-mentioned two extreme cases described by Eqs. (4a) and (4b). Therefore the additional contributions to the conductance from eﬀects of temperature and sticking coeﬃcients will be a combination of these cases.

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It is safe to assume that C2 H2 does not stick to the stainless steel surfaces of the windowless cell at 296 K, i.e. Sc296 K = 0. Thus, we can deduce the sticking coeﬃcient for C2 H2 at 150 K according to Eq. (4), which yields a sticking coeﬃcient for C2 H2 at 150 K of Sc150 K = 0.34 and 0.29 for the case described by Eqs. (4a) and (4b), respectively. The design of the windowless cell falls between these two extremes. Thus, it may be reasonable to suggest a sticking coeﬃcient of Sc150 K = 0.34 ± 0.02 for C2 H2 at 150 K. No other sticking coeﬃcient values for C2 H2 are available in the literature for comparison. It may be warranted to carry out direct sticking coeﬃcient measurements of C2 H2 and CH4 in the future. 4. Concluding Remarks We have successfully demonstrated that a windowless absorption cell is suitable for cross-section measurements in C2 H2 at low temperatures. The procedures used to determine the eﬀective path length of an open cell appear to be valid for a windowless absorption cell operating in molecular ﬂow regime at 296 and 151 K. We have extended the procedures to data reduction at 139 and 130 K. It is to be noted that the peak cross-section value19,32 of the 3R0 band is extremely large, 428 × 10−18 cm2 . The absorption in the vicinity of the intense peak obviously reaches saturation with a few mTorr gas pressures in the 10 cm long windowless cell. We will fabricate a 2 cm path length cell to make accurate measurement for the intense 3R0 peak. In contrast to the intense peak, to make accurate measurements for absorption cross-section values as small as 1 × 10−19 cm2 for C2 H2 we need a cell with 30 cm path length to provide suﬃcient column density of ∼180 cm · mTorr. With three diﬀerent path length windowless absorption cells we can carry out crosssection measurements over the spectral range from 120–190 nm for C2 H2 and 120–160 nm for CH4 at temperatures as low as 110 K. In Sec. 3.1 we found that the eﬀective path length is insensitive to gas temperature at 151 and 296 K provided that the C2 H2 pressure is operated well within the molecular ﬂow regime. We then made use of the same eﬀectice path length to the determination of cross-sections at 139 and 130 K. We plan to further test the validity in the case of CH4 . This is possible because the melting point for CH4 is 90.5 K, and its pressure at 111.5 K is about one atmosphere, namely, 760 Torr.33,34 Therefore, we will be able to measure CH4 cross-section values to temperatures at 110 K, and lower. Using a 30 cm long windowless cell cross-section values as small as

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1.4 × 10−23 cm2 at 110 K are expected to be measurable. This study will allow us to support or repudiate the assertion that the eﬀective absorption path length is relatively independent of temperature under the present operating pressure conditions. We will carry out this study in the near future.

Acknowledgments We are indebted to D. Shemansky for stimulating discussions. We are grateful for the support of the staﬀ of the National Synchrotron Radiation Research Center, Hsinchu, Taiwan. This research is based on work supported by the NASA Planetary Atmospheres Program under Grant No. NNG06GG72G (Wu).

References 1. C. A. Nixon and 14 coauthors, Icarus 188 (2007) 47. 2. P. V. Sada, D. E. Jennings, B. E. Hesman, G. L. Bjoraker, P. N. Romani, R. J. Boyle, M. Edwards and G. H. McCabe, Observations of Hydrocarbons in the Stratospheres of Jupiter and Saturn Using Celeste, American Geophysical Union Fall Meeting 2007, abstract #P23A–05. 3. J. I. Moses, T. Fouchet, R. V. Yelle, A. J. Friedson, G. S. Orton, B. B´ezard, P. Drossart, G. R. Gladstone, T. Kostiuk and T. A. Livengood, The stratosphere of Jupiter. In: F. Bagenal, W. B. Dowling, T. E. McKinnon, T. E. (Eds.), Jupiter: The Planet, Satellites and Magnetosphere. (Cambridge Univ. Press, Cambridge, 2004), Chapter 7, pp. 129–158. 4. G. R. Gladstone, M. Allen and Y. L. Yung, Icarus 119 (1996) 1–52. 5. C. Howett, P. Irwin, P. Yanamandra-Fisher, P. Parrish, G. Orton, L. Fletcher and N. Teanby, CIRS Team, Variations in the Abundance of Acetylene and Ethane in the Atmosphere of Saturn, as Deduced from Cassini/CIRS and IRTF/MIRI Measurements, American Astronomical Society, DPS meeting #38, #39.07; Bull. Amer. Astron. Soc. 38 (2006) 555. 6. M. Burgdorf, G. Orton, J. van Cleve, V. Meadows and J. Houck, Icarus 184 (2006) 634. 7. S. K. Atreya, B. R. Sandel and P. N. Romani, Photochemistry and vertical mixing. In: J.T. Bergstralh, E. D. Miner, M. S. Mathews (Eds.), Uranus, (University of Arizona Press, Tucson, 1991), pp. 110–146. 8. V. S. Meadows, G. Orton, M. Line, M.-C. Liang, Y. L. Yung, J. Van Cleve and M. Burgdorf, Icarus 197 (2008) 585. 9. J. Caldwell, I. Dashevaky, C. Y. R. Wu and D. L. Judge, UV Absorption Coeﬃcients of NH3, C2 H2 , and CO Applied to Hubble Space Telescope Observations of Jupiter, Neptune, and Uranus, in NASA Lab Space Sci. Workshop, Cambridge, Mass, April 1–3, 1998, pp. 117–120.

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10. 11. 12. 13.

A. Coustenis and 25 coauthors, Icarus 189 (2007) 35. H. G. Roe, I. de Pater and C. P. McKay, Icarus 169 (2004) 440. F. Herbert and B. R. Sandel, J. Geophys. Res. 96 (1991) 19241. D. F. Strobel, M. E. Summers, F. Herbert and B. R. Sandel, Geophys. Res. Lett. 17 (1990) 1729. V. A. Krasnopolskya, J. P. Maillard and T. C. Owen, Icarus 172 (2004) 537. M. J. Mumma, R. E. Novak, M. A. DiSanti and B. P. Bonev, A Sensitive Search for Methane on Mars (abstract only). American Astronomical Society, 2003, DPS meeting #35, paper #14.18. C. Y. R. Wu, T. S. Chien, G. S. Liu, D. L. Judge and J. J. Caldwell, J. Chem. Phys. 91 (1989) 272. F. Z. Chen and C. Y. R. Wu, J. Quant. Spectrosc. Rediat. Transf. 85 (2004) 195. C. Y. R. Wu, F. Z. Chen and D. L. Judge, J. Geophys. Res. — Planets 109(E7) (2004) E07S15. C. Y. R. Wu, F. Z. Chen and D. L. Judge, J. Geophys. Res. 106 (2001) 7629. D. E. Shemansky, A. I. F. Stewardt, R. A. West, L. W. Espoito, J. T. Hallett and X. Liu, Science 308 (2005) 978. D. E. Shemansky, (private communication, 2008). J.-I. Luo, Y.-C. Lin, C. Y. R. Wu, H.-S. Fung, T.-S. Yih and D. L. Judge, Performance of a New Windowless Low-Temperature Absorption Apparatus, The Asia Oceanic Geophysics Society (AOGS2009) Sixth Annual Meeting, Singapore, August 11–15, 2009, paper PS12–A020. H. S. Fung, SRRC Newsletter, 53 (2003) 24. C. Y. R. Wu, F. Z. Chen, D. L. Judge and B.-M. Cheng, VUV Absorption Properties of Gaseous and Solid C2 H2 : Relevance to Outer Planetary Atmospheres Research, Advances in Geosciences, 23 (in press, 2009). H. P. White, X. M. Hua, J. Caldwell, F. Z. Chen, D. L. Judge and C. Y. R. Wu, J. Geophys. Res. 98 (1991) 5491. M. Nobre, A. Ferrandes, F. Ferreire da Silva, R. Antunes, D. Almeida, V. Kokhan, S. V. Hoﬀmann, V. J. Mason, S. Eden and P. Limao-Vieira, Phys. Chem. Chem. Phys. 10 (2008) 550. Y. Benilan, D. Andrieux and P. Bruston, Geophys. Res. Lett. 22 (1995) 897. T. J. Xia, T. S. Chien, C. Y. R. Wu and D. L. Judge, J. Quant. Spectrosc. Relat. Transf. 45 (1991) 77. C. Y. R. Wu, D. L. Judge and T. Matsui, J. Geophys. Res. 111 (2006) A05301. C. Y. R. Wu, D. L. Judge and T. Matusi, J. Electron Spectrosc. Relat. Phenom. 144–147 (2005) 123. C. Y. R. Wu, T. Hung, D. L. Judge and T. Matsui, J. Geophys. Res. 105 (2000) 5329. M. Suto and L. C. Lee, J. Chem. Phys. 80 (1984) 4824. D. R. Lide, Editor, CRC Handbook of Chemistry and Physics, 90th Edition (2009–2010). S. Ohe, Distillation, Vapor Pressures, Gas-Liquid Equilibrium, Computer Aided Data Book, 2nd edition, (Tokyo University, 1999). http://www.sohe.com/index.html

14. 15.

16. 17. 18. 19. 20. 21. 22.

23. 24.

25. 26.

27. 28. 29. 30. 31. 32. 33. 34.

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35. J. F. O’Hanlon, A User’s Guide to Vacuum Technology, 2nd edition (Pergamon Press, New York, 1989). 36. M. Meier and A. von Keudell, J. Chem. Phys. 116 (2002) 5125. 37. A. Roth, Vacuum Technology, (North-Holland Pub., Amsterdam, New York, 1976), p. 249.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

VACUUM ULTRAVIOLET PHOTODISSOCIATION OF ETHENE ISOLATED IN SOLID NEON YU-JONG WU, MENG-YEH LIN, SHENG-CHUAN HSU, HSIAO-CHI LU, HONG-KAI CHEN and BING-MING CHENG∗ National Synchrotron Radiation Research Center, 101 Hsin-Ann Road, Hsinchu Science Park, Hsinchu 30076, Taiwan ∗ [email protected]

Vacuum ultraviolet radiation dispersed from a synchrotron onto a Ne matrix sample near 3.0 K containing ethene (C2 H4 ) yielded photoproducts of which C2 H, C2 H2 , C2 H3 , C4 , C4 H and C4 H2 were identiﬁed from their characteristic infrared absorption spectra. The eﬃciency of photolysis of ethene and the nature of the photoproducts depend on the selected wavelength.

1. Introduction Photochemical and photophysical processes of interstellar molecules that play important roles in astro-environments have received substantial attention in recent years. Photolysis of molecules in atmospheres of planets and comets and in interstellar clouds generates both free radicals and molecular ions. Astronomers have tried to emulate chemical syntheses of these transient species in a laboratory, but these species have an extremely transitory existence under typical conditions and are thus diﬃcult to prepare in suﬃcient quantity to enable detection. The matrix isolation technique has become recognized as an excellent method to store and to accumulate transient species, and has been successful in research on exotic species. To investigate infrared spectra of transient species, we have established a matrix-isolation end station coupled to a beam line for vacuum ultraviolet (VUV) radiation from an undulator in Taiwan’s light source. Taking advantage of matrix isolation and the unique properties of synchrotron radiation, we are exploring the spectroscopy of transient species with exciting prospects.1,2 We investigate also the photochemical and photophysical processes of interstellar molecules in solid phases and

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mixed-ice analogues with the same experimental scheme. To demonstrate the capability of photolysis of solid interstellar molecular matter with VUV radiation using this new end station, we report here our work on the photodissociation of ethene dispersed in solid neon. Methane and ethane are trace species ubiquitous in the stratospheres of the outer planets. Upon absorption of solar UV radiation, primarily at the Lyman α line (121.6 nm), methane undergoes photochemical reactions that yield acetylene, ethene, ethane and other hydrocarbons. In the conversion of methane to ethane in the giant planets, the major reaction pathways involve the photochemical reaction of ethene. For this reason the photodissociation of ethene with VUV has received considerable attention for several decades. Some previous investigators used a Kr resonance lamp at 123.6 nm for photolysis of partially deuterated ethane, and identiﬁed photoproducts that include mainly hydrogen, acetylene, ethane and butane.3 Further work performed with a molecular-beam apparatus revealed the distribution of kinetic energy and branching ratios in the photolysis of ethene and its isotopic variants at 193 nm.4,5 Investigating the dynamics of photodissociation of C2 H4 at 157 nm, Lin et al. reported that elimination of H and H2 are equally important channels of reaction;6 isotopic and site eﬀects on the branching ratios of distinct H2 -elimination channels have also been observed. Previous workers who focused mainly on the photodissociative dynamics of ethene in the gaseous phase reported that an exposure of ethene to energetic photons opens four dissociation channels: C2 H4 + hv → HC ≡ CH + H2 ,

(1)

→ H2 C = C: + H2 ,

(2)

→ H2 C = CH + H,

(3)

→ HC ≡ CH + 2H.

(4)

The former two channels eﬀect elimination of molecular hydrogen, in one case accompanied by formation of a stable molecule, acetylene; the alternative case generates a diradical, vinylidene. The height of the barrier for isomerization from vinylidene to acetylene is ∼6 kJ mol−1 .7 The latter two channels eﬀect elimination of atomic hydrogen and produce vinyl radical in one case and acetylene in the other. As mentioned above, the preceding research provides valuable information to aid our understanding of the photodissociation of ethene in the gaseous phase, but our knowledge about photolysis of ethene in a

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condensed phase is limited. In this work, our objective was to investigate the photochemical process, eﬃciency of photodissociation, and yields of products formed upon irradiation of ethene in solid Ne with VUV photons of varied energy. 2. Experiments The experimental setup is similar to that described elsewhere.1,2 A CsI window cooled to ∼3.0 K serves as a cold substrate for a solid sample. A closed-cycle cryogenic system (Janis RDK-415) employed to cool the target is mounted on a rotatable sealed plate; the cold CsI window is thereby readily rotated to face a jet for sample deposition, or radiation from the synchrotron, or a port for infrared detection. The cryo-chamber is evacuated with a turbomolecular pump backed in turn by a scroll pump; the pressure is typically less than 1 × 10−8 Torr. A gaseous mixture of C2 H4 (0.030 mol) and Ne (1,000-fold excess) was typically deposited over 1 h before exposure to VUV radiation. Tunable VUV light for photolysis of solid samples emanated from the U9 undulator at the National Synchrotron Radiation Research Center in Taiwan to provide pseudo-continuous VUV light with a ﬂux ∼1016 photons s−1 (2% bandwidth). The higher harmonics generated by the undulator are suppressed with a ﬁlter of absorbing gas — noble gas Ne or Ar or Kr, depending on the desired photon energy. When the desired photon energy is less than 11.8 eV (corresponding to 105 nm), a LiF window installed downstream from the beamline serves also to suppress the photons in higher harmonics. We selected wavelengths 170, 157 and 120 nm of VUV light for photolysis of our solid samples of ethene dispersed in neon. Infrared absorption spectra were recorded at various stages of experiments with an interferometric infrared spectrometer (FTIR, Bomem, DA8) equipped with a KBr beamsplitter and a Hg/Cd/Te detector (cooled to 77 K) to cover the spectral range 500–5,000 cm−1 . 400 scans with a resolution 0.5 cm−1 were typically recorded at each stage of the experiment. C2 H4 (99.0 %, Matheson Gases) and Ne (99.999 %, Scott Specialty Gases) were used without further puriﬁcation. 3. Results and Discussion 3.1. Experimental observations Before photolysis of a sample, we recorded the absorption spectra of ethene as a reference for selection of wavelength. The absorption curve, as cross section, of gaseous ethene at 298 K and the absorption spectrum of solid

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Fig. 1. (A) Absorption cross section of the gaseous C2 H4 at 298 K; and (B) absorption spectrum of the solid C2 H4 at 10 K in the wavelength range 105–185 nm.

ethene at 10 K in the wavelength range 105–185 nm are shown in Fig. 1. As indicated in Fig. 1(A), the absorption spectrum of gaseous ethene in the VUV region is complicated because of series of Rydberg transitions. The ﬁrst band that appears in the region 150–180 nm is assigned to a 3 s Rydberg transition, with maximum cross section 58 Mb at 170 nm (1 Mb = 10−18 cm2 ). The second band occurs in a region 130–140 nm and is assigned to 3d and 4d Rydberg transitions. The third band spanning from 130 nm to 118 nm is attributed to overlapping transitions to 4d, 5d, 5s and 6s Rydberg states.8 In contrast to these spectra of a gaseous sample, the absorption spectrum of solid ethene at 10 K is amalgamated into two broad bands with maxima about 125 and 172 nm and a shoulder near 150 nm in the same wavelength region. Considering these absorption spectra of ethene and the wavelengths for photolysis used in previous experiments on molecular beams, we tuned the synchrotron radiation to 170, 157 and 120 nm as wavelengths for photolysis of our solid samples. The ratios of depletion of ethene (in 1,000 Ne) versus duration of irradiation at a selected wavelength are plotted in Fig. 2. 3.1.1. Irradiation of C2 H4 /Ne=1/1000 at 170 nm We recorded an infrared absorption spectrum of the sample before and after photolysis. To facilitate visualization of the changes due to photolysis, we

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80 170 nm 157 nm 120 nm

70

Depletion ratio %

60 50 40 30 20 10 0 0

10

20

30

40

50

60

Irradiation time / min-1 Fig. 2. Temporal proﬁles of depletion ratios for C2 H4 /Ne=1/1,000 irradiated with various photon wavelengths.

subtracted the spectrum recorded at each stage of irradiation from that recorded before irradiation to produce diﬀerence spectra, in which lines pointing upward indicate production and those pointing downward indicate destruction. The diﬀerence spectra for C2 H4 /Ne (1/1,000) irradiated at various wavelengths are depicted in Fig. 3. The result of photolysis, at 170 nm for 30 min, in the diﬀerence spectrum is presented in Fig. 3(A); after irradiation, intensities of lines due to C2 H4 decreased by ∼30%, as indicated in Fig. 2. The photoproduct acetylene (C2 H2 ) generated is characterized by intense lines at 732.0, 1,330.4, 1,958.9, 3,283.9 and 3,296.8 cm−1 , corresponding to vibrational modes ν5 , ν4 + ν5 , ν2 , ν3 , and ν3 + ν4 + ν5 , respectively, of acetylene in solid neon. A weak line that appeared at 895.3 cm−1 is assigned as mode ν8 of C2 H3 following a previous report.9 We found also a line at 1,835.8 cm−1 assigned as ν3 mode of C2 H.10 3.1.2. Irradiation of C2 H4 /Ne=1/1000 at 157 nm The diﬀerence spectrum of the target sample after irradiation at 157 nm for 30 min is shown in Fig. 3(B). After photolysis, intensities of absorption lines due to C2 H4 decreased by ∼45%. Intense lines attributed to C2 H2 and to C2 H in its ν3 mode at 1,835.8 cm−1 were also observed. New infrared absorption features at 2,064.3, 3,333.1 and 628.6 cm−1 appeared; the ﬁrst

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Fig. 3. Diﬀerence infrared absorption spectra of C2 H4 /Ne=1/1,000 upon irradiation at (A) 170 nm, (B) 157 nm, and (C) 120 nm for 30 minutes.

of these corresponds to the ν3 mode of C4 H, and the latter two features conform to the ν4 and ν8 modes of C4 H2 .10 A signal near 1,546 cm−1 with intensity just above the noise level might be ascribed to the ν3 mode of C4 ,10 but we found no line at 895 cm−1 corresponding to the ν8 mode of C2 H3 . 3.1.3. Irradiation of C2 H4 /Ne=1/1000 with 120 nm Figure 3(C) shows a diﬀerence spectrum recorded after irradiation of C2 H4 /Ne (1/1,000) at 120 nm for 30 min, which caused intensities of lines for C2 H4 to decrease by ∼65%. Among the photoproducts, we identiﬁed C2 H2 by its strong lines, and C2 H3 through its features at 3,141.0 (ν1 ), 2,953.6 (ν2 ), 2,911.5 (ν3 ), 1,357.4 (ν5 ), 677.1 (ν7 ), 895.3 (ν8 ) and 857.0 (ν9 ) cm−1 ; details of assignments for C2 H3 can be found in our separate paper.1 Photoproducts C2 H (1,835.6 cm−1 , ν3 ), C4 (1,546.8 cm−1 , ν3 ), C4 H (2,064.3 cm−1 , ν3 ), and C4 H2 (3,333.1 cm−1 , ν4 and 628.6 cm−1 , ν8 ) were also identiﬁed. 3.2. Photoproducts in relation to photolysis wavelength The energies of photons at our selected photolysis wavelengths 170, 157 and 120 nm correspond to energies 703, 761.5, and 996 kJ mol−1 , respectively; these energies are great enough to cause scission of not only the C–H

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Table 1. Observed species and their vibrational wavenumbers after irradiation of ethene matrix samples at selected photolysis wavelengths. Photolysis wavelength/nm Species C2 H2 C2 H C2 H3 C4 C4 H C4 H2

Vibrational wavenumber/cm−1 1958.9 (ν2 ), 3283.9 (ν3 ), 732.0 (ν5 ), 1330.4 (ν4 + ν5 ), 3296.8 (ν3 + ν4 + ν5 ) 1835.8 (ν3 ) 3141.0 (ν1 ), 2953.6 (ν2 ), 2911.5 (ν3 ), 1357.4 (ν5 ), 677.1 (ν7 ), 895.3 (ν8 ), 857.0 (ν9 ) 1546.8 (ν3 ) 2064.3 (ν3 ) 3333.1 (ν4 ), 628.6 (ν8 )

170a

157a

120a

Y

Y

Y

Y Y

Y N

Y Y

N N N

Y Y Y

Y Y Y

a Y denotes a species observed upon irradiation with ethene at this wavelength, N not observed.

bond but even the C–C bond of ethene. As demonstrated in Fig. 2, the extent of depletion per unit time of ethene in solid Ne depended on the irradiation energy: the greater was the energy, the more rapidly ethene was photodissociated. Table 1 lists the photoproducts and their infrared vibrational wavenumbers observed after irradiation of ethene in solid Ne at selected photolysis wavelengths. The nature of the generated photoproducts was also related to the irradiation energy. Upon irradiation at 170 nm (7.29 eV), the species C2 H2 , C2 H, and C2 H3 were produced; with irradiation at 120 nm (10.33 eV), three further species C4 , C4 H and C4 H2 were generated. Among these photoproducts, C2 H2 and radical C2 H3 might be primary species formed directly from ethene by VUV light, whereas secondary photodissociation of C2 H2 might generate C2 H radicals. Vinyl (C2 H3 ) radicals were produced on direct dissociation of a C–H bond of ethene at photolysis wavelengths 170 and 120 nm, but photolysis of C2 H4 at 120 nm yielded a larger proportion of vinyl radicals. We performed time-dependent density-functional calculation11 with B3LYP/PBS to estimate the adiabatic vertical excitation energies and corresponding oscillator strengths of vinyl; the results indicate that excitation of vinyl at 120 nm shows the smallest oscillator strength among excitations at these three wavelengths. Perhaps for this reason we observed greater signals pertaining to vibrational modes of vinyl upon irradiation of ethene at 120 nm. Three species containing four carbon atoms — C4 , C4 H, and C4 H2 — were obtained in the experiment with photolysis at 157 and 120 nm. These C4 -species might be generated on either photolysis of ethene

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dimers or recombination of ethynyl (C2 H) radicals to form C4 H2 ﬁrst; further photo-induced reaction of C4 H2 then produced C4 H and C4 . As shown in Fig. 1(B), the absorption spectrum of ethene in the pure solid phase shows an intense feature near wavelength 120 nm and a shoulder at 157 nm; photodissociation of ethene at these wavelengths was hence eﬃcient. We expect that the photofragments generated on photolysis at 157 and 120 nm have increased nascent energy, and thus a corresponding propensity to undergo further reaction. To unravel further details of the mechanism requires additional experiments, preferably with further selected wavelengths of radiation for photolysis. 4. Conclusion After irradiating samples of C2 H4 in solid Ne at a ratio 1/1,000 near 3 K with VUV light from a synchrotron, we identiﬁed the photoproducts from their characteristic infrared absorption spectra. Photolysis of C2 H4 in a Ne matrix yielded photoproducts including C2 H, C2 H2 , C2 H3 , C4 , C4 H, and C4 H2 . The eﬃciency of depletion of parent molecules and the detected photoproducts show a dependence on the wavelength of photolysis. The experimental results show that, upon irradiation at 120 nm, we produced much C2 H3 , but we observed also C4 -species in a dilute ethene matrix sample on photolysis at 120 and 157 nm. Acknowledgments National Science Council of Taiwan (grant No. 96-2113-M-213-006-MY3) provided support for this project. References 1. Y.-J. Wu, M.-Y. Lin, B.-M. Cheng, H.-F. Chen and Y.-P. Lee, J. Chem. Phys. 128 (2008) 204509. 2. Y.-J. Wu and B.-M. Cheng, Chem. Phys. Lett. (in press). 3. H. Okabe and J. R. McNesby, J. Chem. Phys. 36 (1962) 601. 4. B. A. Balko, J. Chang and Y. T. Lee, J. Chem. Phys. 97 (1992) 935. 5. E. F. Cromwell, A. Stolow, M. J. J. Vrakking and Y. T. Lee, J. Chem. Phys. 97 (1992) 4029. 6. J. J. Lin, C. C. Wang, Y. T. Lee and X. Yang, J. Chem. Phys. 113 (2000) 9668. 7. A. H. H. Chang, A. M. Mebel, X. Yang, S. H. Lin and Y. T. Lee, J. Chem. Phys. 109 (1998) 2748.

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8. R. McDiarmid, J. Phys. Chem. 84 (1980) 64. 9. M. E. Jacox and W. B. Olson, J. Chem. Phys. 86 (1987) 3134. 10. D. Forney, M. E. Jacox and W. E. Thompson, J. Mol. Spectrosc. 170 (1995) 178. 11. M. J. Frisch, G. W. Trucks, H. B. Schlegel et al., Gaussian 03, Revision A7, Gaussian Inc., Pittsburgh, PA, USA, 2003.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

IRREVERSIBLE THERMODYNAMICS OF A GAS-LIQUID INTERFACE∗ DANIEL M. PACKWOOD and LEON F. PHILLIPS† Chemistry Department, University of Canterbury, Christchurch, New Zealand † [email protected]

Onsager’s irreversible thermodynamics is summarised as it applies to a gas-liquid interface. Recent experimental measurements of the Onsager heat of transport at interfaces are described and discussed.

1. Introduction Transport of matter through a gas-liquid interface is an essential step in many planetary processes. On Earth, exchange between atmosphere and ocean via the air-sea interface plays an important role in the cycling of climate- and health-related gases. In particular, absorption of carbon dioxide by the ocean tends to slow the rate of anthropogenic global warming and also contributes to the rate of decrease of pH in the oceans. In the atmosphere, an aerosol droplet rapidly acquires the temperature of the surrounding air but, for a large body of water such as a lake or an ocean, the temperature diﬀerence across the gas-liquid interface is likely to be substantial and long-lived, and can play a signiﬁcant role in deciding the magnitude and even the direction of the gas ﬂux through the dividing surface. This possibility exists because the heat and matter ﬂuxes through the interface are coupled via the heat of solution or condensation, in accordance with Onsager’s irreversible thermodynamics.1 It is very common in ﬁeld studies of air-sea exchange to assume that the gas ﬂux J through the interface is simply proportional to the partial pressure diﬀerence between the gas above the surface and that in the bulk ∗ This

work was supported by the Marsden Fund (administered by the Royal Society of New Zealand) and by the United States National Science Foundation EMSI grant CHE-0431512. DMP is grateful for the award of a Top-Achiever Doctoral Scholarship. 499

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liquid, that is J = kw (ps − pb )

(1)

where ps is the partial pressure of gas at some ﬁxed height above the surface, pb is the partial pressure of the gas in equilibrium with a sample of water drawn from a depth below the mixed layer, and kw is a quantity, known as the transfer velocity or piston velocity, that is assumed to depend mainly on wind-speed and to scale in proportion to the Schmidt number (kinematic viscosity/diﬀusivity) of the gas being transferred.2 In practice, the values of kw obtained by using Eq. (1) are widely scattered when plotted against wind-speed, so it is clear that some contributing factors, such as the temperature diﬀerence across the interface, are being neglected. For this reason, we prefer the eddy-correlation method for measuring the ﬂux of a gas such as CO2 through the air-sea interface, despite the diﬃculty of applying the method on the mobile platform provided by a ship.3 The work described in this paper directly measures the relative importance of a temperature gradient and a pressure gradient in driving a ﬂux of gas through a gas-liquid interface. The problem is handled thermodynamically, by treating the gas-liquid interface as a steady-state system and using a gas ﬂux equation that involves both a temperature gradient and a partial pressure gradient. A key feature of this equation is that it contains a coeﬃcient that gives the relative importance of the two gradients. The problem then becomes one of setting up a system in the laboratory for measuring the coeﬃcients over a range of conditions. For the range of systems investigated so far, it is found without exception that it is the fractional temperature gradient, rather than the fractional pressure gradient, that makes the greater contribution to the ﬂux of gas through a gas-liquid interface. 2. Linear Irreversible Thermodynamics and the Gas-Flux Problem The basic equations of irreversible thermodynamics apply generally for any number of coupled ﬂuxes in a system, which is assumed to be not far from equilibrium, so that each of the ﬂuxes can be written as a linear function of the various thermodynamic driving forces Xi in the system. The rigour of the requirement that the system should be close to equilibrium depends on the nature of the ﬂuxes and driving forces. For the kind of system we are considering here, namely coupled ﬂuxes of heat and matter through the

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membrane created by surface tension, the equations remain valid for quite large departures from thermodynamic equilibrium. For heat ﬂux J1 (units: J s−1 m−2 ) and matter ﬂux J2 (units: mol s−1 m−2 ) the linear equations are J1 = L11 X1 + L12 X2 J2 = L21 X1 + L22 X2

(2)

where the coeﬃcients Lij are ﬁxed by the system, X1 is the thermodynamic driving force for the heat ﬂux, and X2 is the thermodynamic driving force for the matter ﬂux. The coeﬃcient L11 can be determined by requiring the ﬁrst equation to reduce to Fourier’s law of heat conduction when the driving force X2 is zero, and the other diagonal coeﬃcient L22 can be determined by requiring the second equation to reduce to Fick’s law of diﬀusion when the driving force X1 is zero and the force X2 is small enough for Fick’s law to apply. As we would expect, X1 is related to a temperature gradient and X2 to a pressure or concentration gradient. The deﬁnitive feature of (2), which is missing from (1), is that both ﬂuxes depend on both driving forces. For the oﬀ-diagonal coeﬃcients, Onsager showed that L12 = L21

(3)

which expresses a symmetry in the coupling of the heat force to the matter ﬂux and of the matter force to the heat ﬂux. The Onsager heat of transport Q∗ is most simply introduced by making the substitution L12 X2 = Q∗ J2

(4)

in (2), which shows that Q∗ is simply the contribution to the heat ﬂux from a unit ﬂux of matter. The forces X1 and X2 are obtained from the expression T dS = J1 X1 + J2 X2 δ dt

(5)

where T is the ﬁxed temperature at the reference end of the temperature gradient and δ is the width of the region of interest, which in our case comprises the surface itself plus a thin layer of gas immediately above the liquid surface. The quantity (dS/dt)/δ is the rate of entropy production, per unit volume of the interface, by the irreversible processes that are the ﬂuxes J1 and J2 . Multiplying this by T produces a quantity known as the ’dissipation’, with dimensions energy/time. Onsager’s original derivation of Eq. (3), outlined in reference 1, was based on considerations of microscopic reversibility for a system close to equilibrium. A simpler derivation is based

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on Prigogine’s principle4 that in a stationary state with one of the ﬂuxes, say J2 , equal to zero, the rate of entropy production is a minimum with respect to variations in the force X2 . In the equilibrium state, of course, the rate of entropy production and the ﬂuxes are all zero. From the limiting cases of (5) when one of the forces is zero, one obtains3 X1 = −grad(T )/T

(6)

X2 = −T grad(µ/T ) = −RT grad(p)/p = −RT grad(c)/c

(7)

and

where µ is the chemical potential, p is the partial pressure and c is the concentration of the species being transferred, and the gradients are at right angles to the interface. Using these results, Denbigh and Raumann5 obtained the gas-ﬂux equation L22 RT Q∗ ∆T ∆p J2 = − + (8) δ RT T p where the gradients of temperature and pressure are ∆T /δ and ∆p/δ, respectively. An important feature of this equation is the presence of the factor Q∗ /RT whose magnitude directly weights the relative contributions of the temperature gradient and the partial pressure gradient in deciding the magnitude and direction of the gas ﬂux J2 . For the special case of a stationary state with J2 = 0, Denbigh and Rauman wrote T ∆p Q∗ =− RT p ∆T

(9)

and they subsequently used this expression to determine Q∗ for the transfer of a variety of gases through natural rubber membranes.6 For these systems, Q∗ was rather small, of the order of 1–2 kJ mol−1 , a result which for many years generated a lack of interest in such quantities on the part of physical chemists. However, when the transfer takes place across a phase interface, Q∗ can be a major fraction of the enthalpy of condensation or solution, so that the weighting factor Q∗ /RT in Eq. (8) is likely to be signiﬁcantly greater than unity. 3. Measuring the Onsager Heat of Transport A cross-section of our present cylindrical, 15-cm diameter, stainless-steel apparatus for measuring the heat of transport Q∗ is shown in Fig. 1. This

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Fig. 1. Cross-section of the cylindrical, stainless steel cell used to measure Q∗ for a sparingly-soluble, infrared-absorber. Channels for circulating anti-freeze not shown.

version uses a high-resolution infrared diode laser to scan across a single rotational line of nitrous oxide above a water surface, and the purpose of tilting the infrared windows is to avoid etalon eﬀects that would be produced by parallel windows. Previous versions of the apparatus used MKS Baratron pressure gauges to monitor the pressure of gas above the liquid, but that method does not work when the partial pressure of the gas of interest is much less than the liquid’s vapour pressure, hence the use of infrared absorption. The temperatures of the upper and lower sections of the apparatus are measured with PT100 platinum-resistance thermometers and are regulated to within 0.01◦C by balancing the cooling eﬀect of a ﬂow of antifreeze liquid from a Julabo circulating bath against the output from two banks of computer-controlled cartridge heaters. In previous versions of the apparatus the depth of liquid was only 3 mm but, for N2 O and CO2 over water, the gas solubility is so low that the liquid depth must be increased to 30 mm in order to ensure that the concentration

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of dissolved gas remains essentially constant when the partial pressure in the 5 mm vapour gap changes. To ensure a uniform liquid composition it is necessary to incorporate a magnetically-driven stirrer and to wait 24 hours or more for each new partial pressure to stabilize after the temperature diﬀerence ∆T has been altered. To measure the heat of transport for a particular gas-liquid system, the temperature of the liquid is set to T , and that of the top plate to a temperature T + ∆T , and the partial pressure of the gas is measured at intervals until the system has reached a stationary state. Then the process is repeated a number of times with diﬀerent values of ∆T . For N2 O the pressure measurement is replaced by a series of scans over the R27 line (pressure-broadened width 0.057 cm−1 FWHM) of the 2,200 cm−1 absorption band, using an infrared diode laser with a nominal bandwidth of 0.0007 cm−1 , and ∆p/p in Eq. (9) is replaced by ∆A/A, where A is the area under the absorption line when plotted as Ln(I0 /I) versus laser current. 4. Representative Results Figure 2 shows a typical plot of ∆P versus ∆T for water vapour over liquid water, as obtained by working downwards from large to small values of ∆T .7

Fig. 2.

Plot of pressure versus ∆T for water vapour over water at 0◦ C.

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An interesting feature of this plot is that two linear regions are present. This is a common occurrence, the change in slope, or ‘knee’, coinciding with the onset of cool-to-warm distillation8 that results in condensation of liquid on the upper plate. Cool-to-warm distillation occurs because the ﬁlm of adsorbed liquid on the upper plate experiences a negative temperature gradient that lowers its eﬀective vapour pressure, while the liquid below experiences a positive temperature gradient that increases its eﬀective vapour pressure until it exceeds that of the liquid on the upper plate. The necessary condition for distillation against the temperature gradient is that Q∗ is more than half of the latent heat of condensation. The wet surface that exists below the knee in the plot has a thermal accommodation coeﬃcient close to 1, so the whole of ∆T is applied to the temperature gradient and Q∗ can be obtained from the slope of the plot in this region. Above the knee, the dry stainless-steel surface of the top plate has a thermal accommodation coeﬃcient much smaller than 1, so a large ‘temperature jump’ occurs at this surface, and this temperature jump subtracts from the applied temperature diﬀerence ∆T , with the result that ∆p is smaller than it should be. From plots such as that in Fig. 2 it is possible to obtain values of the temperature jump, and hence of the thermal accommodation coeﬃcient,9 and the variation of the measured thermal accommodation coeﬃcient with the partial pressure of the vapour has been modelled successfully using the BET theory of multi-layer adsorption.10 For ammonia over water11 it was found that exposure of the cell to ammonia at a pressure near one atmosphere resulted in conditioning of the upper-plate surface so that the knee was absent and ∆p versus ∆T plots were linear up to values of ∆T of 15◦ C or more. This conditioning is potentially very helpful for systems where Q∗ is small, because it has the eﬀect of greatly extending the range of ∆T over which the plot of ∆p versus ∆T is linear. An interesting result from the ammonia experiments was that Q∗ was found to be constant at total pressures from about 20 Torr to over 900 Torr. This behaviour is not predicted by our current model for the origin of Q∗ , which postulates that the vapour pressure increases with increasing ∆T because of the eﬀect of the temperature gradient on the height of a free energy barrier located in the capillary-wave zone at the liquid surface, and in which the temperature diﬀerence across the Knudsen zone close to the liquid surface plays a major role. The model works well at pressures such that the distance of the top plate from the liquid surface is a small number of mean-free-paths. For example, −Q∗ at the liquid-vapour interface of n-heptanol has been observed to approach the latent heat of

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Fig. 3. (a) Scan across the R27 absorption line on a non-storage oscilloscope, with a rotary chopper in the beam, to establish the peak-to-baseline voltage diﬀerence. (b) Trace downloaded from a storage oscilloscope, with added markers. (c) Polynomial ﬁt to trace between the outer pairs of markers, to establish the I0 voltage across the absorption line. (2) Resulting plot of Log(I0 /I) versus diode current.

vaporisation as the pressure is lowered, in line with predictions. However, the model does not predict the existence of the high-pressure regime of constant Q∗ and some modiﬁcation will be required to treat this. Figures 3a–d and 4 give preliminary results from our experiments with N2 O and water in the apparatus in Fig. 1, after conditioning of the surface of the top plate with ammonia. Figure 3a is a photograph of a scan over part of a single diode laser mode, showing the R27 absorption line in the 2,200 cm−1 band of N2 O as obtained with an ordinary analog oscilloscope with the laser beam interrupted asynchronously with a rotary chopper. Figure 3b shows the scan without the chopper as downloaded from a Fluke digital storage oscilloscope averaging 4,096 sweeps across the mode, with markers added by computer. The baseline level for this plot was established

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Fig. 4. Area of the absorption line of Fig. 3d as a function of the temperature diﬀerence across the vapour gap.

by measuring the signal maximum-to-baseline distance in Fig. 3a. Figure 3c shows the result of ﬁtting the laser mode between pairs of markers on either side of the absorption line to a polynomial, in order to obtain I0 values, and Fig. 3d shows the resulting plot of Ln(I0 /I) as a function of time during the sweep across the mode. Figure 4 shows a plot of the area under the Ln(I0 /I) plot as a function of ∆T , from which we obtain a tentative value of 3.4 kJ mol−1 for −Q∗ . This value is quite low in comparison with the values we have obtained for other systems, yet −Q∗ /RT is still signiﬁcantly greater than 1. [Note added in proof: our ﬁnal value13 of Q∗ for this system is −6.6±0.85 kJ mol−1]. Similar experiments with CO2 will be more diﬃcult because of the possibility of compound formation, the need to control the pH of the water, and the likelihood of spectroscopic interference from the CO2 in air. Table 1 gives the results of Q∗ measurements for all of the systems that we have studied so far and for which the results are considered reliable. The value of Q∗ is always negative and is usually a large fraction of the heat of solution or condensation. The results for water vapour over ice are consistent with the existence of a quasi-liquid layer on the ice surface, as originally deduced by Michael Faraday12; the results for old and new ice imply that the usual form of ice is the product of surface reconstruction of a less stable form that is produced by rapid freezing.

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Table 1. Summary of published results of Q∗ measurements at the liquid-vapour interface for some one-component and two-component systems. Units of Q∗ are kJ/mol. System Aniline n-heptanol H2 O/H2 SO4 H2 O/glycerol H2 O H2 O/new ice H2 O/old ice n-octane NH3 /H2 O N2 O/H2 O

−Q∗

T /K

Q∗ /RT

15 to 40 36 to 57 ∼10 5 to 17 24.3 ∼15 28 32 7.7 6.6

268 266 244 238 275 269 267 276 283 282

7–18 16–26 ∼5 2.5–9 10.6 7 13 14 3.3 2.9

Comments Cool-to-warm distillation −Q∗ ∼ ∆Hvap at low p Compound formation No compound formation Thermal accommodation Surface reconstruction Quasi-liquid layer Consistent with theory Q∗ at high p, conditioning Infrared measurement13

5. Conclusions All of the experimental results show that −Q∗ /RT is greater than 1, so that the gas ﬂux through the interface given by Eq. (8) is more dependent on the fractional temperature gradient than on the fractional partial pressure gradient. Thus there is no guarantee that even the direction of the gas ﬂux can be predicted from the sign of the partial pressure diﬀerence that appears in Eq. (1). It might be argued that laboratory results obtained with a static liquid surface do not necessarily apply to the turbulent wave ﬁeld at the surface of the ocean. This is true only to the extent that the relevant pressure and temperature gradients in a wave ﬁeld are diﬃcult to determine. There is no doubt that Eq. (8) will continue to apply locally at such a surface. References 1. K. G. Denbigh, The Thermodynamics of the Steady State, Methuen, London, 1951. 2. R. Wanninkhof, W. E. Asher, D. T. Ho, C. Sweeney and W. R. McGillis. Ann. Rev. Marine. Sci. 1 (2009) 213. 3. B-J. Tsuang, C-Y. Tu, Y-Y. Lan, Y-L. Chen, T-Y. Wu, S-W. Chen and Y-D. Chen, Asia Oceanic Geosciences Society, 6th Annual Meeting, paper OS14A002, Singapore, 2009. 4. I. Prigogine, Etude Thermodynamique des Phenomenes Irreversibles, Desoer, Liege, 1947. 5. K. G. Denbigh and G. Raumann, Proc. Roy. Soc. (London) A210 (1952) 377. 6. K. G. Denbigh and G. Raumann, Proc. Roy. Soc. (London) A210 (1952) 518 7. C. J. Pursell and L. F. Phillips, Phys. Chem. Chem. Phys. 8 (2006) 4694. 8. C. T. Mills and L. F. Phillips, Chem. Phys. Lett. 372 (2003) 615.

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9. S. K. Loyalka, C. E. Siewert and J. R. Thomas, Jr., Phys. Fluids 21 (1978) 854. 10. G. A. Biggs and L. F. Phillips, Chem. Phys. Lett. 452 (2008) 84. 11. R. B. Currie and L. F. Phillips, J. Non-Eqm. Thermod. (in press). 12. V. Petrenko and R. Whitworth, Physics of Ice, Oxford University Press, London, 1999. 13. D. M. Packwood and L. F. Phillips, Chem. Phys. Lett. (in press).

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

LABORATORY MODELS FOR ICES IN COMET NUCLEI ´ ´ MATE ´ RAFAEL ESCRIBANO, OSCAR GALVEZ, BELEN and V´ICTOR J. HERRERO Instituto de Estructura de la Materia, CSIC Serrano 123, 28006 Madrid, Spain [email protected]

Ices grown in the laboratory may constitute an appropriate means to simulate the frozen components of comet nuclei and other astrophysical objects. Spectroscopic and thermal desorption are usually chosen as tools for that study. The interaction of carbon dioxide with host ices of amorphous water and amorphous methanol is studied in this chapter in a range of temperatures, from 85 K to above 130 K, using infrared spectroscopy and mass spectrometry. Samples are prepared by deposition on a plate inside a cold chamber, of the gases admitted simultaneously or sequentially, after the host ice has been formed. Two slightly diﬀerent structures of CO2 are found, displaying diverse spectroscopic characteristics. The speciﬁc surface area for adsorption and the desorption energy of sequential samples are evaluated. Amorphous water ice is more porous than methanol ice and allows larger amounts of CO2 to penetrate inside the bulk.

1. Introduction Comet nuclei have often been referred to as dirty iceballs, icy dirtballs, or even mudballs!.1 The present understanding of these systems, which is far from deﬁnitive, is that in general they are comprised basically of an outer crust of refractory material, covering an icy mantle, and an inner core of mainly silicate composition. In their path along the solar system, comets leave a dust expanse of freshly emitted particles, the tail, and a long-term track of particles in the mm-cm range, the trail. With an average mass loss of ∼23 Kg/s,2 comets supply to our solar system an important amount of dust, originated from their crust, and it is therefore this constituent that has been more largely studied, both by remote observations and from samples transported to Earth laboratories (see, for example, the Stardust webpage3 ). On the other hand, the icy composition of the nuclei can only be investigated by spectroscopic techniques using detecting devices at a 511

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distant location. There is a great need of observational data, which will make the results of the AKARI and WISE missions4 particularly welcome. Models for the ice component of comet nuclei can however be prepared in the laboratory. It is known that the main constituents are5 solid phases of water, the most abundant by far, carbon monoxide, carbon dioxide, methane, methanol and others. With appropriate cryostats, ices can be generated of single components or mixtures of these substances, and their physical properties can be studied, usually by infrared spectroscopy and thermal desorption techniques. The present contribution describes the research carried out and underway in this area by our group in Madrid, with references to related results attained by other teams. In the next section, typical laboratory facilities and the experimental methodology will be described. Next, a brief summary will be given of the theoretical background required to comprehend the spectroscopic and thermodynamic measurements. Recent results on ices of mixtures of carbon dioxide and water, and an advance of the impending outcome on carbon dioxide/methanol systems will then be presented, with the conclusions of this research outlined in a ﬁnal section. 2. Laboratory Set-up The basic system for the study of ice systems of astrophysical interest is schematically depicted in Fig. 1, where a top view of a typical chamber is

Fig. 1.

Schematics of deposition chamber for the study of astrophysical ices.

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shown. Ices are grown by condensation of vapours on a plate in contact with a cryostat. The temperature of the plate can be monitored within values which depend on the type of cryostat, reaching a few K for He-cooled systems or ∼85 K for liquid N2 refrigerants. The gas content in the chamber is controlled by mass spectrometry, and the solids deposited are studied by infrared spectroscopy, either in a transmission or a reﬂection-adsorption (RAIR) set-up. Besides the standard components described, the chamber may contain a microbalance adjoining the deposition plate and several inlets for admission of radiation of diﬀerent sources, either for optical control or to induce chemical reactions in the solid via high energy irradiation or electron bombardment.6−8 Both the composition of the ice and the manner in which it was created are important, from the astrophysical point of view, since the formation history of ices and grains is still under debate. In the laboratory, this point is addressed by using diﬀerent deposition systems, which in practice can be assembled in two categories: the vapours can be admitted simultaneously or sequentially, and the solid formed displays in either case diﬀerent characteristics, which depend also on its porosity and adsorption surface. The temperature at which the deposition takes place is another factor to consider, and phase changes can be induced in the samples, simulating heating processes that comet nuclei, for instance, are known to bear in their perihelion.

3. Theoretical Background Infrared spectroscopy is a powerful tool to investigate the structure of the ice. In molecular ices, the main vibrational bands of the molecules in the gas phase normally constitute the stronger spectral features, but their characteristics may vary depending on the symmetry and environment of the molecular unit in the solid. Besides, new features are sometimes visible in the overtone region of the fundamentals. Moreover, spectral bands of ices containing multiple components can be shifted or broadened with respect to the corresponding ones in the pure constituents. Examples will be presented below for the system CO2 /H2 O. The optical properties of a ﬁlm or solid are gathered in its refraction index n = n + ik, which can be determined experimentally from its vibrational spectra using the KramersKronig relationships,9,10 or predicted from theoretical calculations if the n∞ is known.11 The knowledge of the refraction index measured in the laboratory plays a key role in the interpretation of observed spectra.

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The adsorption of gas phase molecules on previously formed solids can be studied from a thermodynamic point of view, providing relevant information for astrophysical systems. The relative amount of adsorbate can be estimated from the intensity of appropriate bands in the infrared spectrum. The adsorption results can be treated in a similar way to standard adsorption isotherm experiments, by means of the Brunauer, Emmet and Teller (BET) isotherm model:12 pgas 1 c − 1 pgas = + υ(p0gas − pgas ) υm c υm c p0gas

(1)

where pgas is the partial pressure of the adsorbate in the gas phase, p0gas its saturation value, v is the amount of gas adsorbed per unit mass of substrate ice, and vm the amount adsorbed per unit mass for monolayer coverage. v and vm can be expressed in terms of the corresponding molecular ratio (ngas /nadsorbent). The amount of gas adsorbed per unit mass of substrate is determined from the integrated absorbance of an infrared band as detailed in the Experimental Section of Ref. [24], and the values of c and vm are deduced from the slope and intersect of a graphical representation of Eq. (1), as shown in the right panel of Fig. 4 below. The BET constant c is approximately equal to exp(E1 − EL )/kT , where E1 and EL are the heat of adsorption of the ﬁrst layer and the heat of condensation, respectively. The speciﬁc surface area (SSA) for adsorption can then be derived from vm by assuming an eﬀective value for the area of the adsorbed molecules. These magnitudes, the speciﬁc surface area and the desorption energy, enclose key information on the adsorption process. Desorption energies can also be estimated from TPD experiments,13 but in certain set-ups it may be diﬃcult to diﬀerentiate between the gas desorbed from the sample plate and that which had been adhered to the cold surfaces in the cryostat, thus inducing large uncertainties in the results. 4. Recent Results 4.1. Ices of carbon dioxide and water This system is one of the most thoroughly studied in this ﬁeld, both because of its comparatively larger simplicity with respect to other ice mixtures, and because CO2 is the most abundant species detected in astrophysical ices, after H2 O. Among other previous publications, we may refer to the works of Sandford and Allamandola,14 who carried out a comprehensive study of the infrared spectra of CO2 /H2 O matrices as function of their composition and

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temperature; Kumi et al.15 who recorded IR spectra of ﬁlms of variable thickness obtained by sequential addition of the components; Collings et al.13 who studied the thermal desorption of a number of individual molecules, comprising CO2 , CH3 OH, CH4 , NH3 and of course, H2 O; and many others (see for instance Strazzulla et al.16 Ehrenfreund et al.17 ¨ Bernstein et al.18 Malyk et al.19 Oberg et al.20 ); and also to the recent paper by Chaban et al.21 who presented theoretical calculations of clusters of CO2 and up to n water molecules, at a high level of the theory. In our Molecular Physics of Atmospheric and Astrophysical Systems (MPAAS) laboratory in Madrid, we have carried out several investigations on this subject using the techniques described above, namely infrared spectroscopy and thermal desorption.22−24 Although we have covered a range of temperatures and several deposition techniques, we can present our results in a broad arrangement in terms of, ﬁrst, the colder experiments, where the gases were deposited at 80–90 K, and second, the study of warmed-up samples, above 105 K; and within these temperature ranges, we can diﬀerentiate between those obtained using sequential or simultaneous deposition techniques. In all cases, the base pressure of the chamber was ∼10−7 mbar and the gas pressure during deposition of the order of ∼10−5 mbar. The deposition rate in diﬀerent experiments varied between 0.2 and 0.6 nm s−1 , and as far as we could detect, no changes in the porosity of the ice were evident in this range of values. The samples studied normally contain a higher proportion of water than of carbon dioxide, and the spectroscopic diﬀerences can be better appreciated on the vibrational bands of the latter. In particular, the asymmetric C–O stretching ν3 band, at ∼2,340 cm−1 , being the strongest CO2 spectral feature, contains the more substantial information. Other sources of data, which can be used to supplement that information, are the weaker ν2 bending, at ∼650 cm−1 , the even weaker combination bands, in the 3,600 cm−1 region, and, also very important, the same bands for the 13 CO2 isotopomer, which can be easily detected in natural abundance samples. Figure 2 displays transmission IR spectra of the ν3 region of CO2 , for a sequentially deposited sample (above) and for a simultaneously deposited mixture (below), both at the deposition temperature (80 K) and after heating for a couple of minutes at 105 K. In the sequential experiment the thickness of the water sample was 660 nm, and that of the added carbon dioxide, ∼45 nm, and in the simultaneous deposition experiment the H2 O:CO2 ratio was 15:1. These values are typical of the experiments

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0.4 0.3

Sequential

-0.03

2344 cm-1

Sequential 80 K 105 K

80 K 105 K

-0.04

2282 cm-1

0.2

0.0

0.5 0.4 0.3

-0.05

2341 cm-1

Simultaneous

80 K 105 K

2343 cm-1

Absorbance

Absorbance

0.1

-0.06

-0.02

Simultaneous 2275 cm-1 80 K 105 K

2340 cm-1

-0.03

0.2 -0.04

0.1 0.0 2420 2400 2380 2360 2340 2320 2300

Wavenumber (cm-1)

2290

2285

2280

2275

2270

Wavenumber (cm-1)

Fig. 2. Transmission IR spectra of sequentially and simultaneously deposited CO2 /H2 O mixtures, top and bottom respectively. Spectral regions represented correspond to the ν3 band of 12 CO2 and 13 CO2 , left and right respectively. The spectra were recorded at 80 K (black trace) and 105 K (grey trace).

performed in our laboratory. The left-hand panels of Fig. 2 correspond to the 12 CO2 bands, and those on the right to the 13 CO2 species. The sequential sample is formed by admitting CO2 vapor in the chamber, where an amorphous water solid (ASW) had been previously deposited. These spectra reveal the existence of two apparent varieties of solid CO2 , characterized by shifted band peaks for the ν3 vibration, and also by diﬀerent temperature and deposition dependences. One of the varieties has a peak frequency at 2,344 cm−1 , that is, the same value as for the pure CO2 crystal, and is the main species in sequentially deposited samples at 80 K. It is also present in the co-deposited sample at that temperature. For clarity, we may refer to this specimen as normal CO2 , or CO2 -norm. After heating the samples, the band peak is shifted to lower frequencies, by ∼3 cm−1 for the 12 C isotopomer and ∼7 cm−1 for the 13 C species. This other variety is the dominant one in simultaneously deposited mixtures, but

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Fig. 3. RAIR spectra of a simultaneously deposited CO2 /H2 O mixture in the regions of the combination bands ν1 + ν3 and 2ν2 + ν3 (left) and of the ν2 fundamental (right). Incident light with P polarization was used. Spectra were recorded at 87 K (black) and 105 K (gray).

also appears in sequential samples at 105 K. Its structure must correspond to some kind of distorted CO2 , and hence can be termed CO2 -dist. The spectra recorded in a reﬂection-absorption set-up23 contribute to enlighten the problem. The CO2 -norm structure has the typical characteristics of a polycrystalline solid, whereas CO2 -dist seems to correspond to very small ensembles of molecules without any slab or layered structure. A good example is provided in Fig. 3, where the region of the combination bands at ∼3,600 cm−1 is shown on the left, and that of the ν2 band, on the right. At the lower temperature, characteristic features of the solid appear (sharp peaks in the overtone region, two split components for the otherwise degenerate band ν2 ), whereas the shape of the bands remaining at 105 K is more typical of non-crystalline structures (weak and broad bands). We can put forward the following interpretation for the two CO2 varieties. In sequential samples, where ASW is ﬁrst built, the porous structure of the substrate allows CO2 molecules to ﬁll the available pores at the surface and in the interior, forming amorphous or small polycrystalline domains with fairly standard icy characteristics (CO2 -norm). Small polycrystals adsorbed at the surface would have the same structure. In co-deposited samples, CO2 and water molecules arrive simultaneously to the cold plate, and a diﬀerent arrangement is favored in which a large proportion of carbon dioxide molecules do not succeed in creating ice structures, being surrounded by water molecules with which they have a stronger interaction (CO2 -dist). These structures are placed in the

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- pCO2) (cm-3 STP g)

inner part of the ice and remain trapped if the sample is heated up to the temperature of the ﬁrst water phase change. When sequentially deposited samples created at low temperature are warmed, the CO2 -norm microcrystals at the surface or in surface pores are the ﬁrst to sublimate; the reshuﬄe of the amorphous water upon heating may induce the smaller CO2 fraction in the interior to be trapped in a similar arrangement to that of CO2 -dist. This hypothesis seems to explain all the experimental ﬁndings described above. Sequential experiments carried out on crystalline ice, formed by annealing of the amorphous phase, indicate that CO2 -norm is only formed, probably retained at the water ice surface because of the lack of pores, and sublimates completely at 105 K leaving no trace of carbon dioxide in the samples. Using the spectral features as an evidence of the sticking or releasing of CO2 in sequential samples as a function of CO2 partial pressure and temperature, it is possible to evaluate thermodynamic magnitudes like adsorption activation energy, net heat of adsorption and speciﬁc surface area (SSA), as described in Section 3 above. These results are represented in Fig. 4 and collected in Table 1. A comparison with previous determinations indicates that the SSA values have a marked dependence to decrease for

0.015

CO2

0.010

/ v*(p0

ASW: 02 nm/s,L=200 nm. 0.2 nm/s,L=370 nm 0.6 nm/s,L=200 nm

0.005

p

0.000

CO2

nCO2 / nH2O

0.020

0

1

2

3

4

pCO2 (x10-5 mbar)

120 100 80 60 40 20 0 0.0

0.2

5

pCO2 /

0.4

0.6

p0

CO2

Fig. 4. Left: Concentration ratio CO2 /H2 O vs partial pressure of CO2 in a sequentially deposited sample. The water host was grown at the indicated rates up to the speciﬁed thickness values, without signiﬁcant relative variation in the concentration ratio. Right: Typical BET representation from the values of the left panel in the indicated pressure range, with a linear ﬁt (solid line).

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Table 1. Thermodynamic properties derived from spectral data on CO2 /H2 O and CO2 /CH3 OH mixtures. c

vm

SSAa (m2 g−1 )

(E1 -EL )/k (K)

CO2 /H2 O CO2 /CH3 OH

7.06 12.2

0.0074 0.002

39 6.5

186 213

CO2 /H2 O CO2 /CH3 OH

T-ice (K) 90 90

P CO2 (mbar) 7.0 × 10−6 4.6 × 10−5

Eact (kJ mol−1 )b 20.8 19.4

Sample

a Calculated

assuming a mean molecular area of CO2 of 15.5 ˚ A2 .14 assuming a value of 2.9 × 10−12 s−1 for the frequency of the CO2 oscillation at the surface.14 b Calculated

higher temperatures of the experiment. Our estimation agrees well with those of Refs. [25–27] (SSA between 38 and 52 m2 g−1 ), obtained within a close temperature range. 4.2. Ices of carbon dioxide and methanol This section describes the latest results of research on samples containing CO2 and CH3 OH. These are two of the most abundant frozen gaseous components in the core of comets and some astrophysical objects, as mentioned above. The aims of this investigation are not only to gather spectroscopic and thermodynamic data on this system, but also to compare these results with those available for the CO2 /H2 O species. Previous publications on this system were prompted by the data collected by ISO,17,28−30 and others deal with some speciﬁc subjects of this species.18,21 The methodology employed is similar to that described above. Our samples are prepared at 85 K and later warmed to monitor desorption and sublimation processes by means of IR spectroscopy and mass spectrometry. Sequential or simultaneous deposition is utilized for the preparation of the samples, which have a variable composition. In sequential samples, methanol is ﬁrst admitted into the chamber, and once the ice is formed, carbon dioxide is introduced. Spectral features of CO2 are speciﬁcally searched as indicators of the state and progress of the processes. When a CO2 /CH3 OH sample is heated in a temperature programmed desorption (TPD) experiment, most CO2 sublimates from all cold surfaces within the cryostat at 105 K, but a fraction remains within the ice until higher temperatures are reached. This last part of the experiment is depicted in Fig. 5 for sequentially and simultaneously grown samples (above and below, respectively), prepared with a similar CO2 /CH3 OH

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Fig. 5. Temperature programmed desorption of CO2 /CH3 OH samples grown sequentially (above) and simultaneously (below). Black trace: CO2 ; grey trace: CH3 OH.

concentration. Methanol sublimates at ∼165 K, but it undergoes a phase change at ∼120 K.31 At that temperature, the small fraction that remained in sequential samples (note the intensity scaling factor) after the initial heating evaporates, as does a large part of the CO2 contained in codeposited samples, in a so-called volcano desorption.32 However, for the latter type, a portion is still held trapped and is only released at the onset of methanol sublimation. This behavior will be discussed below along with the spectroscopic ﬁndings. Figure 6 presents an overall view of the transmission spectra of amorphous pure methanol and of a co-deposited CO2 /CH3 OH mixture at 85 K. The eﬀect of temperature rising is depicted in Figs. 7 and 8 for sequential and simultaneous samples, respectively, focused on speciﬁc spectral regions of the CO2 spectrum. Figure 7 indicates very clearly various facts. First, when heating a sequential sample from 85 to 105 K, most of the CO2 sublimates; second, the fraction that remains has a slightly diﬀerent structure than the original one, the ν3 band being red-shifted by ∼4 cm−1 ; and ﬁnally, further heating

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Fig. 6. Transmission IR spectra of amorphous methanol (below) and of a simultaneously deposited CO2 /CH3 OH sample (above, oﬀset), recorded at 85 K.

Fig. 7. Transmission IR spectra of a sequentially deposited CO2 /CH3 OH sample, in the region of the ν3 band of CO2 . The spectra were recorded at the speciﬁed temperatures, showing the shift in the band maximum at 105 K and the complete loss of CO2 at 130 K.

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Fig. 8. Transmission IR spectra of a simultaneously deposited CO2 /CH3 OH sample in the spectral regions of: (a) ν3 12 CO2 ; (b) ν313 CO2 ; (c) ν2 ; (d) ν1 + ν3 and 2ν2 + ν3 . Spectra recorded at 85 K (black trace) and 130 K (light grey trace). The spectrum of pure CO2 recorded at 85 K (grey trace) is added for reference. All spectra are oﬀset for clarity.

to 130 K releases all CO2 from the sample. Figure 8 reveals more complex processes. The sample was formed by co-deposition of a concentrated mixture, with p(CO2 )/p(CH3 OH) = 0.68, yielding 63% CO2 concentration in the ice. The spectra did not change signiﬁcantly between 85 and 105 K, and therefore only the traces at 85 and 130 K are displayed, focused on the ν3 band of 12 CO2 , the same band for 13 CO2 , the ν2 band, and the

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combination band region, from top to bottom respectively. To these we have added a spectrum of pure CO2 for comparison in all four windows. Besides the main CO2 component, the co-deposited sample at 85 K contains one more CO2 species, characterized by a shoulder in panel (a) and separate broad bands in panels (b) to (d), always at red-shifted frequencies to those of the main component. Contrarily to sequential samples, no CO2 is released on heating to 105 K. Warming the sample at 130 K, when the methanol phase change has taken place, a large part of CO2 sublimates, and the fraction that remains is the main component existing at 85 K, whose vibrations are in fact coincident with those of pure CO2 . Matching the nomenclature employed above, we may call the corresponding CO2 species CO2 -norm and CO2 -dist, to represent those that are more similar to pure CO2 or bearing some slightly distorted structure, respectively. The spectroscopic and thermal data together seem to hint to the following interpretation. When CO2 is added in a sequential experiment the gaseous molecules become adsorbed at the surface and ﬁll the pores available. The carbon dioxide structure that is formed is that of CO2 -norm in either case. Warming the sample to 105 K induces sublimation of the largest part of CO2 , probably that which was kept at the surface or in surface pores. The fraction that remains is aﬀected by stronger interaction with methanol molecules, yielding CO2 -dist. This interaction is however not strong enough to prevent CO2 from escaping after further heating to 130 K. In co-deposited samples, CO2 ensembles grow together with methanol ice, and both CO2 -norm and CO2 -dist are formed, probably within the inner structure of the methanol ice. Thus, warming to 105 K does not aﬀect much this whole structure. When methanol changes phase at 120 K, important structural changes take place in the solid, aﬀecting mainly the CO2 that was in more intimate interaction with methanol, CO2 -dist, which is released during this process, whereas a fraction of CO2 -norm is still kept in the bulk. From the spectroscopic data, a study can be performed on the thermodynamic properties of the ice samples, similar to the one carried out for the CO2 /H2 O system. The numerical results of this investigation are included in Table 1, thus facilitating a comparison between both species. The desorption energies found are similar, ∼20 kJ mol−1. The strength of the adsorption interaction must therefore have comparable characteristics between CO2 and methanol or water ice. However, the speciﬁc surface area of the amorphous methanol ice is much smaller than that of ASW, indicating a much less porous surface of the former, and a greater impediment for CO2 molecules to reach inner cavities in methanol.

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Carbon dioxide sticks on crystalline methanol ice at 85 K, but is completely sublimated at 105 K, in parallel to the observations for crystalline water ice. This research on the carbon dioxide/methanol system is still underway at MPAAS, and more complete results should be available in the near future. 5. Conclusions Water, carbon dioxide and methanol constitute three of the most abundant species in frozen matter of the solar system and some astrophysical objects. The present investigation describes typical experimental facilities to study icy mixtures of these species in the laboratory, and reports new results on the spectroscopic and thermodynamic properties of binary systems, CO2 /H2 O and CO2 /CH3 OH. In the range of temperatures and pressures employed at the Molecular Physics laboratory MPAAS in Madrid, CO2 adopts two slightly diﬀerent conﬁgurations both in ice mixtures with water and methanol: one which resembles pure CO2 , with analogous vibrational characteristics, labeled CO2 -norm; and another one whose spectral features are not reminiscent of the solid and are displaced to lower frequencies than those of CO2 -norm, indicating some distortion in the CO2 structure and a stronger interaction with the host species, labeled CO2 -dist. The process of formation of these structures depends on the way that the samples are prepared, either by sequential or simultaneous deposition of the gases onto a cold substrate, and their response to warming is also diﬀerent. If a phase change of the host takes place during the warming of the sample, a reshuﬄing of the CO2 is produced, inducing the release of part of the trapped carbon dioxide. The adsorption of CO2 on water or methanol ices has similar strength, but the speciﬁc surface for adsorption in water is much larger than in methanol, as corresponds to a more porous structure in amorphous water ice. Acknowledgments This research has been carried out with funding from the CSIC PIF Program, ref. 200530F0050, and the Spanish Ministry of Education, Project FIS2007-61686. O.G. acknowledges ﬁnancial support from the same Ministry, “Juan de la Cierva” program.

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References 1. M. V. Sykes, AOGS 5th Annual Meeting, Contribution PS03–A051, Busan (Korea) 2008. 2. M. Ishiguro, AOGS 5th Annual Meeting, Contribution PS03–A018, Busan (Korea) 2008. 3. Stardust NASA mission, http://stardust.jpl.nasa.gov/home/index.html 4. AKARI mission: http://www.ir.isas.jaxa.jp/AKARI/Outreach/index e.html; WISE mission: http://wise.ssl.berkeley.edu/mission.html 5. D. Bockel´ee-Morvan, J. Crovisier, M. J. Mumma and H. A. Weaver, in Comets II, The University of Arizona Press, 2005. 6. P. Ehrenfreund, L. d’Hendecourt, S. B. Charnley, R. Ruiterkamp, J. Geophys. Res. 106 (2001) 33291. 7. H. J. Fraser, M. P. Collings and M. R. S. McCoustra, Rev. Sci. Instrum. 73 (2002) 2161. 8. G. M. Mu˜ noz Caro, G. Matrajt, E. Dartois, M. Nuevo, L. d’Hendecourt, D. Deboﬄe, G. Montagnac, N. Chauvin, C. Boukari and D. Le Du, Astron. Astrophys. 459 (2006) 147. 9. O. B. Toon, M. A. Tolbert, B. G. Koehler and A. M. Middlebrook, J. Geophys. Res. 99 (1994) 25631. 10. T. Buﬀeteau and B. Desbat, Appl. Spectrosc. 43 (1989) 1027. 11. D. Fern´ andez-Torre, R. Escribano, V. J. Herrero, B. Mat´e, M. A. Moreno and I. K. Ortega, J. Phys. Chem. B 109 (2005) 18010. 12. S. Brunauer, P. H. Emmett and E. Teller, J. Am. Chem. Soc. 60 (1938) 309. 13. M. P. Collings, M. A. Anderson, R. Chen, J. W. Dever, S. Viti, D. A. Williams and M. R. S. McCoustra, Mon. Not. R. Astron. Soc. 354 (2004) 1133. 14. S. A. Sandford and L. J. Allamandola, Astrophys. J. 355 (1990) 357. 15. G. Kumi, S. Malyk, S. Hawkings, H. Reisler and C. Wittig, J. Phys. Chem. A 110 (2006) 2097. 16. G. Strazzulla, B. Nisini, G. Leto, M. E. Palombo and P. Saraceno, Astron. Astrophys. 334 (1998) 1056. 17. P. Ehrenfreund, O. Kerkhof, W. A. Schutte, A. C. A. Boogert, P. A. Gerakines, E. Dartois, L. d’Hendecourt, A. G. G. M. Tielens, E. F. van Dishoeck and D. C. B. Whittet, Astron. Astrophys. 350 (1999) 240. 18. M. P. Bernstein, D. P. Cruikshank and S. A. Sandford, Icarus 179 (2005) 527. 19. S. Malyk, G. Kumi, H. Reisler and C. Wittig, J. Phys. Chem. A 111 (2007) 13365. ¨ 20. K. I. Oberg, H. J. Fraser, A. C. A. Boogert, S. E. Bisschop, G. W. Fuchs, E. F. van Dishoeck and H. Linnartz, Astron. Astrophys 462 (2007) 1187. 21. G. M. Chaban, M. Bernstein and D. P. Cruikshank, Icarus 187 (2007) 592. 22. O. G´ alvez, I. K. Ortega, B. Mat´e, M. A. Moreno, B. Mart´ın-Llorente, V. J. Herrero, R. Escribano and P. J. Guti´errez, Astron. Astrophys. 472 (2007) 691. 23. B. Mat´e, O. G´ alvez, B. Mart´ın-Llorente, M. A. Moreno, V. J. Herrero, R. Escribano and E. Artacho, J. Phys. Chem. A 112 (2008) 457. 24. O. G´ alvez, B. Mat´e, V. J. Herrero and R. Escribano, Icarus 197 (2008) 599. 25. E. Mayer and R. Pletzer, Nature 319 (1986) 298.

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26. A. Bar.Nun, G. Notesco and T. Owen, Icarus 190 (2007) 655. 27. C. S. Boxe, B. R. Bodsgrad, W. Smythe and M. T. Leu, J. Colloid and Interface Science 309 (2007) 412. 28. P. Ehrenfreund, E. Dartois, K. Demyk and L. d’Hendecourt, Astron. Astrophys. 339 (1998) L17. 29. E. Dartois, K. Demyk, L. d’Hendecourt and P. Ehrenfreund, Astron. Astrophys. 351 (1999) 1066. 30. O. Kerkhof, W. A. Schutte and P. Ehrenfreund, Astron. Astrophys. 346 (1999) 990. 31. A. B. Dempster and G. Zerbi, J. Chem. Phys. 54 (1971) 3600. 32. R. S. Smith, C. Huang, E. J. L. Wong and B. D. Kay, Phys. Rev. Lett. 78 (1997) 909.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

STUDIES IN THE LABORATORY ON THE STRUCTURE OF CO2 ICE. ASTROPHYSICAL IMPLICATIONS R. LUNA Department of Applied Physics, Escuela Polit´ ecnica Superior de Alcoy Universidad Polit´ ecnica de Valencia, Alcoy, 03801 Alicante, Spain [email protected] www.upv.es

The aim of this paper is to describe a set of experiments carried out in our laboratory to obtain several parameters that are relevant to improve the understanding of the structure of CO2 ice and the implications derived from them. Density, refractive index, desorption temperature of pure ices and retention capacity of CO2 are presented as a ﬁrst approximation to the CO2 ice structure at relevant temperatures for astrophysics.

1. Introduction Ices are ubiquitous in the Universe. Despite the fact that water ice is the most common molecule in solid phase, other common molecules such as CO, CO2 , CH4 , N2 are also quantitatively relevant, and in some scenarios they could even be the dominant molecule. Nowadays, there are many aspects of these ices studied in detail, such as their spectra in the MIR region (1.5–25 micron) or their evolution with ion or photon irradiation. Despite these studies, there are many intriguing questions partially explored or still completely unexplored. One of these questions is the eﬀect of the structure of these ices on their physical or chemical properties. The main objectives of our experimental research group are: (i) to study the physical characteristics of pure and mixture of ices as density, refractive index at several wavelengths, desorption temperature, energy of sublimation, etc. (ii) to investigate the structural changes after annealing and/or UV irradiation to apply our results to astrophysical environments. Our setup is currently suitable to perform measurements at the same time by using diﬀerent techniques, physical and spectroscopic studies. 527

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The ﬁrst one includes double laser interferometry (DLI); quartz crystal microbalance QCMB; quadrupole mass spectrometry (QMS) combining these techniques, parameters as density, refractive index, temperature and energies of desorption can be derived. The second one includes, ultraviolet and mass spectroscopy. Additionally, we are now coupling IR spectroscopy to perform it simultaneously with the rest of the techniques above quoted. In this paper, we show the techniques that we are able to use with our experimental setup and our most recent results about studies of pure CO2 , N2 , CH4 ices and mixtures of CO2 ice with the other two molecules, being CO2 the major component, for this reason we have divided the paper as follows: In Sec. 2 we brieﬂy describe our experimental setup, in Sec. 3 we present the type of experiments that we can perform and the parameters that we can obtain during ice deposition, in Sec. 4 we show the experiments carried out and the parameters obtained during desorption and ﬁnally, in Sec. 5 we present our conclusions.

2. Experimental Setup The basic components of our experimental conﬁguration to carry out these experiments (Fig. 1) are a high vacuum (HV) and low temperature system, a QCMB, a DLI system and a QMS. The main component is a high vacuum chamber (P ≤ 10−7 mbar) whose pressure conditions are obtained with a rotatory pump (∼10−3 mbar) backing a turbo pump (∼10−7 mbar). The ﬁrst stage of a closed-cycle He cryostat (40 K) thermally connected to a shield protector acts as a cryopump providing a pressure in the chamber below 10−7 mbar measured with an ITR IoniVac transmiter (5% in accuracy). The second stage of the cryostat is named cold finger and it is able to achieve 10 K. Below it, is located the sample holder bearing a QCMB (gold plated surface) in thermal contact with the cold ﬁnger. The temperature in the sample (QCMB) is operated by the Intelligent Temperature Controller ITC 503S (Oxford Instruments) using the feedback from a silicon diode sensor (Scientiﬁc Instruments), located just behind the microbalance, that lets the temperature vary between 10 and 300 K with three signiﬁcative numbers. Another sensor is located at the end of the cryostat second stage, on the edge of the sample holder, in order to monitor the behaviour of the system.

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Experimental setup.

Gases or mixtures under study are prepared in a prechamber in a proportion estimated from their partial pressures measured with a Ceravac CTR 90 (Leybold Vacuum) whose accuracy is 0.2%, provided with a ceramic sensor not inﬂuenced by the gas type. The gas transfer from the prechamber to the deposition vacuum chamber is controlled by a needle valve (Leybold D50968) which regulates the gas ﬂow. During deposition, the QMS (AccuQuad RGA 100 with a resolution of ∼0.5 amu) allows us to verify the composition of gases in the chamber. The following chemicals have been used: CH4 − 99.9995 (Praxair), CO2 − 99.998 (Praxair), and N2 − 99.999 (Air Products). Once the temperature of deposition is ﬁxed, a needle valve from the prechamber is opened and the gases ﬁll the chamber keeping the pumping system on. Molecules replenish the chamber randomly and deposit onto the QCMB (background deposition). The amount of deposit is enough to make contamination negligible and insuﬃcient to saturate the mass spectrometer (saturates at 10−4 mbar) during desorption. In all cases the rate of ice deposition is around 1.0 micrometer per hour, measured using double laser (He-Ne) interferometry1 and the QCMB frequency variation.

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3. Parameters Obtained by Means of Using Experiments of Deposition A part of our experiments are devoted to calculate the following physical parameters from deposition of ices: density, refractive index and porosity for pure and mixture of ices. The properties of these ices, under laboratory conditions as similar as possible to the astrophysical ones, help us to understand the behavior of the ices in environments related to astrophysics. 3.1. Density and refractive index In this section we describe the procedure for extracting the refractive index and density of the deposited ice or mixture of ices. The density of a sample is obtained by growing an ice ﬁlm onto a QCMB of known area, where the mass deposited on it (Fig. 2 straight line) is derived from the variation of its frequency (Sauerbrey equation). Taking into consideration that the QCMB is also temperature sensitive, in all the experiments the temperature during deposition is maintained constant. In these conditions the variation of 1 Hz is equivalent to 15.4 ng cm−2 .

Fig. 2. The straight line represents the variation of the QCMB frequency for a typical experiment of CO2 deposition. The curves represent the interference patterns obtained during the same experiment with the DLI system.

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Film thickness can be derived from one interference pattern if the real part of the refractive index (n) is known. Most ices have unknown refractive index at the temperatures of interest. Then, for each particular ice its refractive index must be determined. It is calculated from the interference pattern of two polarized He-Ne lasers (Fig. 2), this system allows us to determine the real part of the refractive index of transparent non conductors. We recall this method as a “double laser interferometry” and is based on the Bragg refraction equation1 where the change in thickness between two adjacent peaks, ∆τ , is given by ∆τ = ∆qλ/2n(1 − sin2 βi /n2 )(1/2)

(1)

where ∆q = 1, taking q the numbers 0, 1, 2, 3, . . . or 1/2, 3/2, 5/2, 7/2, . . . depending on whether they correspond to the ﬁrst, second, third . . . maximum or minimum of the interferogram then, in any case, between adjacent maximums or minimums ∆q = 1, n is the refractive index, λ is the wavelength of the incident light and βi is the incidence angle of the light. There are two unknown parameters in this equation, the thickness (∆τ ) and the refractive index (n). As we have two interferometric patterns corresponding to two diﬀerent angle of incidence, we solve a two equation system obtaining both unknown parameters. With them and knowing the mass deposited · cm−2 (from the QCMB), the density is directly obtained. One relevant point during our experiments is that we are able to control the deposition and warming up at a constant rate and this way we can ensure the obtention of accurate results. As an example, Fig. 2 shows a constant rate of deposition (which is deduced from the constant slope of the straight line) obtained during a typical experiment of CO2 deposition. For more details about our experimental setup and the control of the constant rate of deposition and warming up procedures you can see Luna et al., 2008 (in these proceedings).2 We have obtained the density and the real part of the refractive index (at λ = 632.8 nm) for CH4 , N2 , and CO2 at diﬀerent temperatures of deposition from 10 K up to near the desorption temperature of every molecule.3 For each molecule every point is obtained as many times (experiments) as necessary in order to check the reproducibility of the results. Figure 3 represents the results obtained for density (upper panel) and refractive index (lower panel) in the case of CO2 ice. Every point represents

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Fig. 3. Density and refractive index of CO2 ice obtained for diﬀerent temperatures of deposition.

an independent experiment where the sample holder is cooled to the desired temperature and then the ice was deposited. We can distinguish three diﬀerent parts, up to 15 K we can observe a constancy in both parameters. From 15 to 50 K an increase in the value of both parameters occurs. And ﬁnally in the range from 50 K to the desorption temperature both values are constant again. Taking into consideration the whole range of temperatures carbon dioxide has a large variation in density and in index. The ﬁrst varies around a 50% meanwhile the index changes around a 15%. Our results compare well with those of other authors (for example the refractive index of CO2 at 77 K,4, 5 or that for the refractive index and density for CH4 , and N2 at 20 K6 despite the fact that diﬀerent authors use diﬀerent methods. In the case of CH4 and N2 we found no signiﬁcative variations with the temperature of deposition. Both molecules have a constant value for the refractive index and density at all temperatures studied, (refractive index) n = 1.30 and (density) d = 0.47 g cm−3 for methane, meanwhile nitrogen presents a lower value than that of methane for the refractive index 1.21 and its density is 0.94 g cm−3 .

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Our results reveal a diﬀerent behavior of methane and nitrogen, where no variations are observed for any temperature studied (within the error bars), and carbon dioxide, where variations represent an increase of around 50% in density. It is deduced that the arrangement between molecules does not depend on the growth temperature for the ﬁrst two molecules but it does for the last one. This procedure to measure the density and refractive index is revealed as a powerful method since it is possible even to obtain these parameters for mixture of gases. In fact, we are performing the same kind of experiments for the mixture of ices CO2 :CH4 and CO2 :N2 (at diﬀerent proportions), obtaining preliminary results of density and refractive index roughly proportional to the fraction present of every molecule. 3.2. Porosity The study of the porosity of a speciﬁc ice could reveal the ability to trap other molecules in its structure at temperatures higher than their characteristic temperature of desorption. This fact could propitiate chemical interactions in some astrophysical scenarios where these molecules are present. As an example we show the results of the study of CO2 porosity with the temperature of deposition (Fig. 4). We have calculated the porosity by

Fig. 4.

Porosity of CO2 as a function of the temperature of deposition.

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the Lorentz-Lorez equation: p = 1 − ρρai , (where ρa is the density obtained at certain temperature of deposition and ρi is the intrinsic density), being ρi = 1.55 g cm−3 .3 4. Experiments of Desorption of Simple Molecules Once the parameters obtained during deposition are described, let us to show how to obtain other physical parameters of ices (characteristic desorption temperature, desorption energy . . .) from desorption experiments at a constant rate of warming up. Once deposited, the substrate is heated at constant rate of 1 K min−1 , with the vacuum system working continuously. The desorbed molecules during warming up were monitored with the QMS, and the mass released were measured with the QCMB from its variation in frequency, once the variation due to the increase of temperature is corrected. 4.1. Desorption temperature This is a set of experiments devoted to characterize pure ices in order to perform further experiments involving mixture of ices. The results obtained here are necessaries to study interactions between molecules when mixtures are studied by means of TPD experiments. We have used two techniques to establish the desorption temperature of the gases under study: QCMB (Fig. 5) and QMS (Fig. 6). Figure 5 plots frequency signal versus temperature. The Y axis covers the total variation of frequency due to the variation between the temperature of deposition and 90 K. From these variations can be inferred that the amount of mass deposited for each molecule is diﬀerent. This is due to the fact that we deposit roughly

Fig. 5.

QCMB signal during a warming up of N2 , CH4 and CO2 .

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Fig. 6.

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QMS signal during a warming up of N2 , CH4 and CO2 .

the same thickness for every ice, but each molecule has its own density, obtaining diﬀerent amount of mass deposited. In the ﬁrst technique we have taken as desorption temperature the point in the plot where the slope changes abruptly. In the second technique we have taken the extrapolation of the leading edge of the desorption (when two peaks appear, we have taken the ﬁrst one because it corresponds to the sample holder) to the base line as proposed by Notesco et al.7 The results are shown in Table 1. Plots show that pure gases only desorb at a characteristic temperature related to the pressure in our experimental setup. Both methods lead to similar results taken into account our experimental error (±1 K). The desorption temperatures of pure gases obtained here are in agreement with those given by other authors.8 These temperatures cannot be considered strictly as sublimation temperatures because the sublimation occurs in an equilibrium situation. Here we force the system to increase the temperature at a rate of 1 K min−1 , forcing the system to the non equilibrium. In general, the temperature of sublimation depends on the pressure following the Clausius-Clapeyron equation. The less the pressure, the lower the temperature of sublimation is. As a reference, the temperature Table 1. Desorption temperature for CO2 , CH4 and N2 determined by two diﬀerent procedures. Gas

T (K) QMS

T (K) QCMB

CO2 CH4 N2

90 42 25

91 39 23

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of sublimation of water ice is around 180 K under our experimental conditions. 4.2. Desorption energy The method generally used to determine the desorption energy uses an special experimental setup (that generally includes a Knudsen eﬀusion cell) avoiding the possibility of determining other physical parameters simultaneously. The method presented here to obtain the desorption energy of ices allows us to simultaneously perform various techniques and to obtain diﬀerent parameters at the same time, guaranteing that all the results correspond to the same experimental conditions. The procedure to obtain the desorption temperature (removing the inﬂuence of contaminants, removing the eﬀect of the temperature and obtaining the derivative of the remaining signal) is based on the graphs obtained with the QCMB during the experiments of desorption. From them, it is possible to derive the desorption energy of pure ices, because the process involves a zeroth-order desorption as can be seen from the proﬁle of the desorption rate of CO2 during the experiment (Fig. 7). This shape ﬁts a Polanyi-Wigner equation as can be seen from the abrupt fall on the right side of the peak. Table 2 reports some of the values obtained in our laboratory.9 This energy can be used to determine the eﬀects of temperature variations on objects related to astrophysical scenarios where,

Fig. 7. Desorption rate during a warming up experiment for CO2 (left panel). The proﬁle of the plot obtained is typical for a zeroth-order desorption as can be seen in right panel.

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Table 2. Desorption energy obtained for CO2 and CH4 . Molecule CO2 CH4

Edes (kJ mol−1 ) 29.3 ± 0.2 8.5 ± 0.3

for example, these molecules are segregated from H2 O and CO2 after a thermal history.10 4.3. Retention capacity Taking into consideration that CO2 is the most abundant ice in the universe after water, it is interesting to determine whether carbon dioxide could complement eﬃciently the capacity of water ice to retain other molecules (CH4 , N2 . . . ). To study the retention capacity of CO2 we have performed the desorption of mixtures of CO2 :CH4 and CO2 :N2 in a proportion 95:5 in both cases. As the QCMB does not allow us to discriminate between molecules, it is necessary to monitor the sublimation of mixtures by using the QMS technique. The interactions between carbon dioxide and the hostage molecule are revealed when results are compared with the QMS signal for pure molecules. In both cases, during the desorption of the mixture of gases (Fig. 8), several processes occur in light of our graphs.11 There are some noteworthy points: (i) the ﬁrst release of molecules does not occur at their characteristic sublimation point but at higher temperatures (in the case of nitrogen, more than 20 K shift); (ii) molecules are retained up to the sublimation of the CO2 , whose characteristic temperature of sublimation is not aﬀected by the presence of other molecules, in the proportion studied; (iii) diﬀerent sublimation processes are involved between the two previous cases. To explain this CO2 ice matrix behavior, in the literature an amorphous CO2 structure is generally accepted. Some authors argue that no crystals exist in the whole ﬁlm when it is grown at temperatures below 30 K12 but others suggest that this amorphous structure arises from a compilation of small crystallites randomly oriented.13 Looking at both models, the three zones of desorption could correspond to crystallization/compacting (around 50 K), ﬁnal compacting (around 75 K) and sublimation (around 90 K).

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Fig. 8. Upper panel: Desorption experiment for a mixture of CO2 :CH4 (95:5). Lower panel: Desorption experiment for a mixture of CO2 :N2 (95:5). In both cases a warming up at constant rate (1 K min−1 ) was used.

The results obtained in our experiments can be applied to whatever astrophysical scenario where these ices are present, taking into account the shift in temperature due to their particular atmospheric pressure. 5. Conclusions From the results shown in this work we can conclude that our experimental setup permits to obtain a constant rate of deposition and desorption. This

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is crucial to performing experiments to obtain relevant parameters in the study of the structure of ices. Additionally, the pumping speed of our system is appropriate to study desorption processes of ices of simple molecules or mixtures by means of QMS. The signals obtained by means the QCMB or the QMS techniques can be used to determine the parameters related to desorption processes. We can state that the QMS under our experimental conditions can be used to study the structure of ices from the desorption of other gases present as minor components in the mixture. The density and the real part of the refractive index remain constant within the temperature range from 10 K to sublimation temperature in the case of nitrogen and methane. This is not the case for carbon dioxide because its density increases by ﬁfty per cent from 10 K to 50 K and the real part of the refractive index increases by ﬁfteen per cent. In the case of nitrogen and methane, the structure is the same for any temperature of deposition in the light of our experiments. But it is possible to conclude that a more compact structure is formed for CO2 at 50 K or higher than that obtained for lower temperatures. It is possible that this result reﬂects a modiﬁcation of the structure, such as a crystallization process. Our results establish that the possibility exists that if there are trapped volatile molecules in its structure, part of them remain in it to the sublimation of CO2 . It has been observed in the laboratory that CO2 retains eﬃciently CH4 and N2 at higher temperatures than their characteristic temperature of sublimation, at three diﬀerent temperatures at around 50, 75, and 90 K. Corresponding to crystallization/compacting, ﬁnal compacting and sublimation. 6. Acknowledgments This research has been founded by Universidad Polit´ecnica de Valencia PAID-04-08 and Ministerio de Ciencia y Tecnolog´ıa, projects AYA 20012385, AYA 2004-0532, AYA 2007-65899 and FEDER funds. The author thanks Carlos Mill´ an and Miguel A. Satorre for their fruitfully comments, discussions and revision of the text. References ´ Satorre and J. Cant´ 1. M. Domingo, Mill´ an, M. A. o, Proceeding of SPIE 6616 (2007) 66164A. ´ Satorre, C. Mill´ 2. R. Luna, M. A. an and J. Cant´ o, AOGS (2008). ´ Satorre, M. Domingo, C. Mill´ 3. M. A. an, R. Luna, R. Vilaplana and C. Santonja, PSS 56 (2008) 1748.

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4. K. E. Tempelmeyer and D. W. Mills Jr., J. Appl. Phys. 39 (1968) 2968. 5. S. G. Warren, Appl. Opt. 25 (1986) 2650. 6. J. A. Roux, B. E. Wood, A. M. Smith and R. R. Plyler, Arnold Air Force Station, TN. (1980). 7. G. Notesco and A. Bar-Nun, Icarus 126 (1997) 336. 8. T. Yamamoto, N. Nakagawa and Y. Fukui Astron. Astrophys. 122 (1983) 171. 9. C. Mill´ an, in preparation, (2008). ´ Satorre, R. Luna, C. Mill´ 10. M. A. an, C. Santonja and J. Cant´ o, PSS (in press), doi: 10.1016/j.pss.2008.05.017. ´ Satorre, ApSS 314 (2008) 113. 11. R. Luna, C. Mill´ an, M. Domingo and M. A. 12. S. A. Sandford and L. J. Allamandola, The Astrophysical Journal 355 (1990) 357. 13. W. Schulze and H. Abe, Chemical Physics 52 (1980) 381.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

THE INTERSTELLAR ASTROCHEMISTRY CHAMBER (ISAC) ˜ ´ MART´IN-GAGO, C. ROGERO, G. M. MUNOZ CARO∗ , J. A. ´ A. JIMENEZ-ESCOBAR and J. M. SOBRADO Centro de Astrobiolog´ıa, CSIC-INTA Ctra. de Ajalvir, km 4, Torrej´ on de Ardoz, 28850 Madrid, Spain ∗ [email protected] www.cab.inta.es C. ATIENZA Tecnovac S.L., 28760 Tres Cantos, Madrid, Spain [email protected] S. PUERTAS Maques S.L., C/ Fresadores 8, Pol´ıgono Industrial Alcamar, 28816 Camarma de Esteruelas, Madrid, Spain [email protected]

The Interstellar Astrochemistry Chamber (ISAC) is mainly designed for the study of solids (ice mantles, organics, and silicates) in interstellar and circumstellar environments: characterization of their physico-chemical properties and their evolution due to vacuum-UV and/or cosmic ray irradiation, and thermal processing. ISAC is an ultra high vacuum chamber, with base pressure down to P = 2.510−11 mbar, where an ice layer made by deposition of a gas mixture onto a cold ﬁnger at 10 K, achieved by means of a closed-cycle helium cryostat, can be irradiated with UV photons. We intend to incorporate also an ionic source for the simulation of cosmic ray processing. Samples can be heated in a controlled way from 10 K to room temperature. The evolution of the solid sample is monitored by in situ transmittance FTIR and Raman spectroscopy, while the volatile species are monitored by QMS. Gas mixtures typically contain H2 O and CH3 OH vapors, mixed with gases like CO, CO2 and NH3 . The gas line works dinamically, and allows the deposition of gas mixtures with the desired composition, that is monitored in real time by a QMS. A prechamber is used to introduce and extract the samples preserving the ultra high vacuum in the main chamber. Some experiments for the calibration of ISAC are presented.

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1. Introduction Mineral and carbonaceous grains, present in the atmospheres of giant stars, are ejected into the interstellar medium (ISM). Dust grains in the diﬀuse ISM (hydrogen number density lower than 103 cm−3 ) have typical sizes of tenths of micron with individual masses of the order of 10−14 − 10−12 grams. They experience a UV photon ﬁeld of ≈8 107 UV photons cm−2 s−1 with photon energy Eph ≥ 6 eV1 and cosmic ray irradiation, mainly due to protons of MeV energies and electrons, and partly also to heavier ions.2 As a result of such irradiation the typical temperature of dust in the diﬀuse medium is around 100 K. The main components of dust observed in the diﬀuse ISM, as inferred from infrared observations, are highly amorphous silicates (responsible for the 10 and 18 µm absorption bands) and a form of hydrogenated amorphous carbon (responsible for the 3.4 µm feature). Dense molecular clouds in the ISM (typical densities of 104 cm−3 ) have temperatures as low as 10 K in the interior due to shielding from UV irradiation. Here dust particles like those present in the diﬀuse medium accrete ice mantles, with estimated thicknesses of hundreths of micron, composed mainly of H2 O, and other species like CO, CH3 OH, CO2 , and NH3 .3 Icy dust particles in dense clouds are submitted to energetic processing, mainly by the cosmic-ray induced UV ﬁeld, and partly by direct energy input by cosmic-ray particles of 1–1,000 MeV energies. The energy deposition increases as the energy of the particle decreases and therefore 1 MeV protons are the most relevant.2 Young stars are born in dense clouds, the envelopes around stars contain icy grain mantles similar in composition to those present in dense clouds.4, 5 Such circumstellar ices will be exposed to irradiation from the central star and the surrounding diﬀuse ISM, providing a new scenario for energetic ice processing.6 These envelopes often give rise to disks, which in term can lead to planetary systems. The evolution of the solar nebula led to the formation of planets, comets, and asteroids. The ﬁrst laboratory dedicated to the simulation of energetic processing of interstellar dust was founded in the Leiden Observatory by J. Mayo Greenberg and Lou J. Allamandola in the mid-seventies. The experimental system in Leiden was adapted by L. Allamandola in NASA-Ames, and later by L. d’Hendecourt at the IAS in Orsay. The typical experimental system consists of a high vacuum chamber with a pressure of the order of 10−7 mbar, where an ice layer is formed at 10 K, which can be irradiated with vacuum UV light (groups at NASA-Ames, IAS in Orsay, CIA in Alcoy, University of Virginia, Hokkaido University, etc.), vacuum/extreme

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UV light using synchrotron radiation sources (University of Southern California, National Central University in Taiwan), or ions (groups at NASA Goddard Space Flight Center, Osservatorio di Astroﬁsica di Catania, Osservatorio Astronomico di Capodimonte in Naples, etc.). In recent years, some experiments were performed combining both photons and ions (NASA Goddard Space Flight Center and Osservatorio di Astroﬁsica di Catania). In situ analysis of ice is generally performed by Fourier Transform Infrared (FTIR) spectroscopy, but the Osservatorio di Astroﬁsica di Catania team has successfully used a Raman spectrometer. Some laboratories are now using ultra-high-vacuum (UHV) systems for ice UV-irradiation experiments, e.g. the Sackler laboratory from Leiden Observatory. In the last years, three laboratories dedicated to study astrophysical ices were established in Spain. These are the CIA in Alcoy (Politechnical University of Valencia), the group at the IEM (CSIC) in Madrid, and the group at CAB (CSIC-INTA) in Torrej´ on de Ardoz (Madrid). The Interstellar Astrochemistry Chamber (ISAC), located at CAB, is mainly designed for the study of solids (ice mantles, organics, and silicates) in interstellar and circumstellar environments: characterization of their physico-chemical properties and their evolution due to vacuum-UV and/or cosmic ray irradiation, and thermal processing. The density on the surface of the Earth at see level is about 3 1019 molecules cm−3 , corresponding to 1 bar. Thus, at room temperature, a rough estimate of the pressure in the dense interstellar medium, with densities of 103 − 106 particles cm−3 , is between 10−14 and 10−10 mbar. This paper describes the ISAC setup and the experimental protocol. It reports some data obtained during the calibration of the system. ISAC is essencially an UHV chamber, with pressure typically in the range P = 2.5−4.0 10−11 mbar, where an ice layer made by deposition of a gas mixture onto a cold ﬁnger at 10 K, achieved by means of a closed-cycle helium cryostat, can be UV irradiated. Samples can be heated from 10 K to room temperature. The evolution of the solid sample is monitored by in situ transmittance FTIR and Raman spectroscopy, while the volatile species are monitored by quadrupole mass spectroscopy (QMS). Gas mixtures typically contain H2 O and CH3 OH vapors, mixed with gases like CO, CO2 , and CH4 . The gas line works dinamically, and allows the deposition of gas mixtures with the desired composition, that is monitored in real time by QMS. There is a second deposition tube for co-deposition of corrosive gases, like NH3 . A prechamber is used to extract the samples preserving the UHV in the main chamber.

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Probably the outstanding characteristics of ISAC, compared to other systems, are the excellent UHV conditions with pressures down to 2.5 10−11 mbar after baking the system, the prechamber for the extraction of samples with no need to break the UHV of the main chamber, and the novel design of the gas line system for the preparation of complex gas mixtures with unprecedented accuracy in the composition. In addition to FTIR spectroscopy, we plan to perform Raman spectroscopy in the near future, and to incorporate an ion source for simultaneous irradiation of the ice with photons and ions. 2. Technical Description of ISAC A cartoon image of ISAC is shown on Fig. 1. The setup has a vertical conﬁguration, consisting of two chambers: the main chamber, where gas deposition onto a substrate located at the tip of a cryostat (cold ﬁnger),

Fig. 1.

Schematic cartoon of the ISAC experimental setup.

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and irradiation of the formed ice layer takes place, and a prechamber separated by a valve from the main chamber. The prechamber allows the introduction and extraction of samples with no need to break the vacuum in the main chamber. The main chamber has two levels. The sample holder with the substrate, usually an infrared transparent window, placed at the cold ﬁnger, is at the upper level, where it is intersected by the beam of the FTIR spectrometer and irradiated by the UV lamp (an ion source and a UV-spectrophotometer will be implemented in the future). There is also a QMS at the upper level for monitoring of the volatiles. An schematic view of the upper level is shown on Fig. 2, with the sample holder at the deposition position. Rotation of the sample holder by 90◦ is required for FTIR spectrometry of the sample. The lower level is where the pumps

Fig. 2. Schematic representation of the upper level of the main chamber of the ISAC experimental setup, where gas deposition onto the cold substrate forms an ice layer that is UV irradiated. FTIR and QMS techniques allow in situ monitoring of the solid and gas phases.

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are located, as well as the two gas deposition tubes, the pressuremeters and the Raman spectrometer. As mentioned above, the base pressure at room temperature in the main chamber is 2.5–4 10−11 mbar, thanks to the combination of a series of UHV pumps. The samples can be cooled down to 10 K and warmed up to room temperature thanks to a closed-cycle helium cryostat and a tunable heater, that in combination with the QMS of the main chamber, allows temperature programmed desorption (TPD) experiments on ices. A gas line monitored by a second QMS is attached to the main chamber for controlled deposition through the deposition tubes. The gas line consists of a novel design that allows the preparation of gas mixtures containing up to 5 diﬀerent species. The ISAC setup components are described in more detail below. • Prechamber for sample introduction: A small chamber is on top of the main chamber separated by a hydraulic VAT valve. The samples are introduced and extracted from the system via the prechamber. This is done by vertical traslational movement of the cold ﬁnger, where the sample holder is located. The prechamber is practical because it makes the work easier and it shortens the time between experiments from three to one day, thus enhancing the durability of the vacuum components and optimising the system performance. It consists of: — Fast entry lock. — Pumping system: Independent from that of the main chamber, which reaches a pressure of about 10−9 mbar. It supports the pumping system of the main chamber when the valve connecting the two chambers is open. It consists of a turbomolecular pump (abbreviated TMP) backed up by a rotary pump, and a titanium sublimation pump (TSP). — Cold ﬁnger with sample holder connected to a closed-cycle-Hecryostat by a gold ring. The sample holder is mounted on a tube that can be rotated by 360◦ and moved traslationally to place samples in the main chamber. The temperature range is between 10 K and 400 K at the sample position. • Main chamber: Where ice deposition and irradiation takes place. The interior of the chamber is covered by Mu-metal in order to isolate it from external magnetic ﬁelds. The UV lamp is positioned in front of the deposition substrate so that the sample is irradiated homogeneously. A cylindrical quartz tube of 10 mm diameter, placed between the lamp and

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the sample holder, acts as an optical guide to maximize the ﬂux, given in UV photons cm−2 s−1, at the sample position. A UV spectrophotometer will be mounted on the opposite side of the main chamber to allow in situ monitoring of the UV ﬂux. A Bayer-Alpert pressuremeter measures pressures in the 10−11 mbar range. The characteristics of the deposition or main chamber are: — Pumping system: The combination of a series of UHV pumps is aimed to obtain a base pressure down to ∼2 10−11 mbar. It consists of: ∗ TMP of 550 l/s with connection ﬂange DN 160CF and integrated controller. Pumping capacity of H2 :450 l/s, He:520 l/s, N2 :510 l/s, Ar:500 l/s. The pump is backed up by a second TMP and a rotary pump. ∗ TSP. ∗ Non-Evaporable Ion Getter (IGP) pump. — Vacuum UV lamp: The UV source is a microwave stimulated hydrogen ﬂow discharge lamp (output 1.5 1015 photons s−1 , Ephoton = 7.3 − 10.5 eV), purchased from Opthos, which is separated from the vacuum chamber by a MgF2 window. Using the x-y manipulator, the sample holder can be positioned in close contact to the quartz tube acting as an optical guide. That way, the circular spot size of the UV ﬂux at the sample position has a diameter slightly larger than the 10 mm diameter of the quartz tube, which corresponds roughly to the size of the 13 mm diameter infrared transparent window where ice deposition takes place. The UV lamp requires a simple circuit where hydrogen circulates from a hydrogen bottle to the lamp and it is pumped by a roughing pump. A microwave generator with a 100 W power is responsible for the excitation of the hydrogen. The Evenson cavity of the lamp is refrigerated with air. The UV photon spectrum of this hydrogen-lamp resembles that of the diﬀuse interstellar UV ﬁeld.6, 7 — Analytical techniques: Provide the in situ characterization of the samples during the deposition/irradiation and warmup. Fouriertransform infrared (FTIR) spectroscopy provides the ice composition and aids the characterization of the more refractory products observed at room temperature. Due to the diﬀerent selection and excitation rules, Raman spectroscopy allows the detection, general characterization and determination of the structure of organic matter,

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even at cryogenic temperatures. The quadrupole mass spectrometer (QMS) provides the in situ detection of volatiles produced during warmup of the ice and serves to control the gas deposition. An UV spectroradiometer will be installed to monitor the UV ﬂux of the lamp. ∗ FTIR spectrometry: It is done in transmitance, using a Vertex 70 Bruker spectrometer, equipped with a DTGS detector working in the 7,500 to 370 cm−1 (∼1.3 to 27 µm) spectral range. The main vibrational molecular modes are commonly observed in that range. The infrared beam goes across the main chamber through two ZnSe windows. ∗ Raman spectrometry: A HORIBA Jobin Yvon iHR550 spectrometer will be used. The laser wavelength is 532 nm (green). The laser makes an angle of 45◦ with the deposition window. ∗ Quadrupole mass spectrometry (QMS): Pfeiﬀer Prisma with mass spectral range from 1 to 100 amu. Serves for the detection of molecules ejected from the ice surface into the gas phase and to measure the residual gas composition. It is also used to monitor the deposition. — Gas line: For the preparation of gas mixtures for deposition. A mixture of a maximum of 5 components can be prepared in the gas line. The design of a gas line for the preparation of a complex gas mixture under controlled conditions, containing H2 O and CH3 OH vapor and three gas components, commonly CO, CO2 , and CH4 , was an important challenge. This was accomplished using electrical valves to control the entrance of the individual components and working dinamically at a total pressure below 1 mbar, thus ensuring laminar ﬂow conditions. The electrical valves are activated according to the partial pressures measured by a QMS, that is connected to the gas line. Either CH3 OH or H2 O are deposited manually into the gas line, and the other components are deposited proportionally to the amount of CH3 OH/H2 O in the gas line. The QMS monitors the composition of the gas mixture at any time. When the desired composition of the gas mixture is obtained, the deposition tube is opened through a needle valve and the gas enters the main system, accreting onto the substrate window at 10 K and forming an ice layer. In addition, there is a second deposition tube for the deposition of corrosive gases, like NH3 , into the main chamber.

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3. Experimental Protocol The experimental protocol that is described below corresponds to a deposition/irradiation experiment for the simulation of icy grain mantle processing in the interstellar/circumstellar medium. It comprises the following steps: • In the prechamber compartment, while the valve between the prechamber and the main chamber is closed, an infrared transparent window (CsI or KBr) is ﬁxed on the tip of the cryostat. The infrared window serves as the substrate for the deposition. Afterwards, the fast entry lock is closed and the prechamber is evacuated. • Once the vacuum in the prechamber is of the order of 10−9 mbar, the valve connecting the prechamber to the main chamber is opened. The base pressure in the main chamber should be below 4 10−11 mbar and the cryostat is moved downwards so that the substrate is on the deposition/irradiation position. • A gas mixture for deposition is prepared in the gas line. Predeposition is started, with the substrate at room temperature, to calibrate the ﬂow of the deposition and set the valve positions that correspond to the desired gas ﬂow. The Langmuir relation provides an approximation of the number of monolayers of ice deposited as a function of the pressure of the gas and the deposition time, assuming a sticking coeﬃcient equal to unity, which is valid for cryogenic temperatures around 10 K. One Langmuir (1 L) corresponds to the deposition of one monolayer, and it is given by 1 L = 10−6 Torr s. • The cryostat is turned on and the temperature reaches ≈10 K. The valve connecting the gas line with the main chamber is opened, at the position determined during the predeposition, to start the deposition. During the deposition the ice layer can be irradiated with photons and/or ions. At diﬀerent intervals, the cryostat can be rotated 90◦ to perform transmittance FTIR spectroscopy, to monitor the ice evolution. Raman spectroscopy can be done at the deposition/irradiation position of the sample. QMS monitors the gas phase molecules during the deposition and irradiation. • Once the deposition/irradiation is completed, the warmup can be started following a linear heating ramp of 1 K min−1 or lower. QMS is used for the detection of volatiles during warmup, while FTIR and Raman spectroscopy are employed to monitor changes in the ice composition and structure.

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• At room temperature, the cryostat is pulled up, the substrate with the refractory organic residue is now in the prechamber, which is isolated from the main chamber closing the VAT valve, so that the sample can be extracted from the setup without breaking the vacuum in the main chamber. The organic residue, obtained from irradiation and warmup of the interstellar/circumstellar ice analog, can be analyzed ex situ by other techniques.

4. Calibration Experiments Figure 3 shows the mass spectrum of the residual gas in the main chamber of ISAC, measured at a pressure of 3.6 10−11 mbar. Under those UHV conditions the dominant gas component is H2 , see ﬁgure caption. A simple test can be carried out to observe the pumping eﬃciencies of the pumps. Figure 4 illustrates the role played by the diﬀerent pumping systems in the 10−11 mbar total gas pressure range. The partial pressures of H2 , H2 O,

Fig. 3. Residual gas analysis in the main chamber where the deposition and irradiation of ice layers is performed. The total gas pressure measured by a Bayer-Alpert gauge was 3.6 10−11 mbar. The intensity scale on this plot corresponds approximately to pressure in mbar units. The most abundant species are H2 (m/z = 2), H2 O (m/z = 18), CO/N2 (m/z = 28), CH3 OH (m/z = 31), and CO2 (m/z = 44). The level of organic contaminants, toluene or xylene at m/z = 91 and 92, is below 10−13 mbar.

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Fig. 4. The evolution of the partial gas pressures is coupled to the operation of the diﬀerent pumping systems as follows: (i) the valve connecting the IGP to the main chamber is closed after 175 s, (ii) in addition the TSP valve is closed after 315 s, (iii) the TSP valve is opened after 575 s, (iv) the IGP valve is opened after 705 s, (v) the TMP valve is closed after 895 s, (vi) the TMP valve is opened after 1,067 s.

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and CO increase signiﬁcantly when the valve connecting the IGP to the main chamber is closed, and rapidly reach their initial values when the valve is opened again, showing that those gas components are continuously pumped by the IGP. Only H2 is clearly pumped continuously by the TSP, albeit less eﬃciently than the IGP. H2 , CO, Ar, and CH4 gas molecules are pumped continuously by the TMP. Except for eventual jumps during valve opening/closing, likely due to retained pockets of gas, the partial pressures of CH3 OH, O2 , and CO2 do not vary much, indicating that those species have reached their minimum partial pressure values. So far, we have only performed a few test experiments for calibration, that serve to check the performance of ISAC by comparison to previous results published in the literature. The preliminary data presented below corresponds to the deposition and sublimation of CO ice. The relative concentrations of the gas components in the gas line are monitored continuously, and were found to be very stable even for long duration experiments, i.e. longer than one day. Figure 5 shows the concentration of gases in the gas line during the deposition. CO, the selected gas for the deposition in this experiment, has a concentration around 99%, compared to the residual gases that remain in the gas line. Residual H2 O is below 1% concentration, while the CO2 and CH3 OH remaining in the gas line from the previous experiment are below 0.1% concentration. The QMS located at the main chamber measures the increase in the partial pressure of CO when deposition is started. This is illustrated in

Fig. 5. Relative abundances of CO and the residual gas species present in the gas line during the CO deposition experiment. The y-scale is logarithmic.

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Fig. 6. Partial pressure of CO during deposition. The ion current in A, represented on the y-scale, corresponds roughly to the partial pressure in mbar. The most abundant residual components remaining in the chamber have m/z = 2, 18, 44, and 32, and correspond to H2 , H2 O, CO2 , and CH3 OH/O2 .

Fig. 6. CO is detected for m/z = 28. It is found that m/z = 2, 18, and 44, corresponding to H2 , H2 O, and CO2 , also increase during the deposition of CO, but their partial pressures are very low compared to that of the deposited CO. Once deposition was completed, warmup was started increasing the temperature slowly at 1 K min−1 . The QMS detected an increase of CO in the gas phase, reaching a maximum at 28 K, corresponding to the desorption temperature of CO under UHV conditions. This temperature value for the desorption of pure CO ice is in good agreement with the values previously reported.8 This is shown in Fig. 7, see ﬁgure caption. As CO desorbs a slight increase in the partial pressure of H2 is also observed. H2 is not expected to accrete on the substrate at 7 K, the substrate temperature during deposition, but can be trapped in the micropores of CO ice. As an example, the trapping of CO at 10 K in amorphous H2 O ice has been reported.9 Figure 8 presents four infrared spectra corresponding to the stretching mode of CO ice at diﬀerent temperatures during warmup. Each spectrum corresponds to 128 scans at resolution 2 cm−1 .

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Fig. 7. CO ice desorption during warmup. The main residual gas components are also shown: H2 , H2 O, CH3 OH/O2 , and CO2 . The current intensity y-scale in A, corresponds roughly to partial pressure in mbar.

Fig. 8.

Infrared spectrum of CO ice at four diﬀerent temperatures during warmup.

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5. Conclusions The ﬁrst calibration experiments performed with ISAC indicate that this UHV setup is performing as expected. All components (pumping systems, cryostat, detectors, deposition system, . . .) are functioning optimally, and the base pressure in the main chamber can be down to 2.5 10−11 mbar. The QMS was connected to the temperature controller to collect the temperature values during warmup, required to perform temperature programmed desorption (TPD) experiments, see Fig. 7. The system for the preparation of complex gas mixtures, containing H2 O and CH3 OH vapors, and gas components like CO, CO2 , CH4 , etc. is probably unique compared to other setups dedicated to astrochemistry. The gas line design that incorporates electrical valves and a QMS monitoring the gas composition, and laminar ﬂow conditions at pressure below 1 mbar, allow the preparation of complex ice mixtures with practically no change in their composition, even for long depositions of the order of one day. This is important for the accuracy and reproducibility of the experiments aiming at the simulation of ice mantle processing in astrophysical environments. The common deposition of gas mixtures under static conditions, typically using a bulb containing a gas mixture with a total pressure of several mbars, does not guarantee the deposition of complex gas mixtures with constant composition, and often the composition of the deposited ice diﬀers from the one expected. At this stage, ISAC is ready for experimentation aimed to produce relevant scientiﬁc results in the ﬁelds of laboratory astrophysics and astrochemistry. Acknowledgments We are grateful to the former director of CAB, Prof. Juan P´erez Mercader, for his support on this proyect. G.M.M.C. was ﬁnanced by a Ram´ on y Cajal research contract from the MCYT in Spain. References 1. J. S. Mathis, P. Mezger and N. Panagia, A&A 128 (1983) 212. 2. C. J. Shen, J. M. Greenberg, W. A. Schutte and E. F. van Dishoeck, A&A 415 (2004) 203. 3. E. L. Gibb, D. C. B. Whittet and J. E. Chiar, ApJ 558 (2001) 702. 4. W. F. Thi, K. M. Pontoppidan, E. F. van Dishoeck, E. Dartois and L. d’Hendecourt, A&A 394 (2002) L27.

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5. K. M. Pontoppidan, C. P. Dullemond, E. F. van Dishoeck, G. A. Blake, A. C. A. Boogert, N. J. Evans II, J. E. Kessler-Silacci and F. Lahuis, ApJ 622 (2005) 463. 6. G. M. Mu˜ noz Caro and W. A. Schutte, A&A 412 (2003) 121. 7. P. Jenniskens, G. A. Baratta, A. Kouchi, M. S. de Groot, J. M. Greenberg and G. Strazzulla, A&A 273 (1993) 583. 8. K. Acharyya, G. W. Fuchs, H. J. Fraser, E. F. van Dishoeck and H. Linnartz, A&A 466 (2007) 1005. 9. B. Rowland, M. Fisher and J. P. Devlin, J. Chem. Phys. 95 (1991) 1378.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

RELIABILITY OF MASS SPECTROSCOPY UNDER HV CONDITIONS TO STUDY RETAINING MECHANISMS OF ICES ´ SATORRE, C. MILLAN ´ and J. CANTO ´ R. LUNA∗ , M. A. Department of Applied Physics, Escuela Polit´ ecnica Superior de Alcoy Universidad Polit´ ecnica de Valencia, Alcoy, 03801 Alicante, Spain ∗ [email protected] www.upv.es

This article explains how mass spectroscopy under HV conditions with an appropriate pumping speed can be used in Temperature Programmed Desorption experiments in a small vacuum chamber. A quartz crystal microbalance and an interferometric system are used to check and demonstrate this.

1. Introduction One of the aims of astrophysics and astrochemistry is to understand the behaviour and implications of the presence of ices such as CO2 , N2 , CH4 , etc., in environments of astrophysical interest. One relevant characteristic of a particular ice is its structure and interaction with other relevant molecules. There are many ways to carry out research on this area. One of the most used techniques is temperature programmed desorption (TPD), usually based on mass spectroscopy under ultra high vacuum (UHV) conditions. The goal of this contribution is to show how, using two very sensitive techniques such as a quartz crystal microbalance (QCMB) and double laser interferometry (DLI) in combination with a quadrupole mass spectrometer (QMS) in a small chamber under high vacuum (HV) conditions, it is possible to obtain results with a sensitivity close to that of TPD experiments performed with larger chambers under UHV conditions. With all these techniques working together, it is possible to determine several parameters of ice analogues such as density, refractive index, porosity, energy of sublimation, etc. 557

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To ensure reliable results, during these experiments, it is necessary to mantain accurate control in three crucial parameters: the negligible presence of contaminants, the constant rate of deposition of the ice ﬁlm and the constant rate of warming up. 2. Experimental Setup The basic components of our experimental conﬁguration (Fig. 1) are: a HV and low temperature system; a QCMB; a system of DLI and a QMS. The main component is a high vacuum chamber (volume ∼2 L) whose pressure conditions (P < 10−7 mbar) are obtained with a rotary pump (∼10−3 mbar) backing a turbo pump (∼10−7 mbar).

Fig. 1.

Experimental setup.

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The second stage of the cryostat is named cold finger and is able to achieve 10 K. Below the cold ﬁnger, is located the sample holder bearing a QCMB (gold plated surface) in thermal contact with it. The QCMB (whose characteristic resonant frequency is 5 MHz) is surrounded by a heat shield cooled to ∼40 K to reduce the radiative heat transfer from the surrounding room temperature chamber walls, providing additional pumping. The ﬁnal pressure, below 10−7 mbar, is measured with a hot cathode-pirani gauge transmitter. The QCMB temperature is controlled by the Intelligent Temperature Controller ITC 503S connected to a resistor located at the end of the second stage, using the feedback from a silicon diode sensor, located just behind the balance. This setup allows the temperature to vary between 10 and 300 K. Another sensor is located at the end of the cryostat second stage, on the edge of the sample holder so that we can control the gradient of temperatures in our system. In the DLI system,1 the signal of the two lasers (He-Ne, 632.8 nm, with angles of incidence: 73◦ and 12◦ ), reﬂects on the sample, and then is collected by two photometers (BPW21). The whole interferometric system, including appropriate software has been developed by ourselves and is used to obtain the refractive index of the ice (pure or mixture) deposited.

3. Parameters to Control Pure gas for an experiment is prepared in a prechamber at a pressure measured with a ceramic sensor not inﬂuenced by the gas type. Additionally, if necessary, our system allows us to perform experiments with a mixture of gases. In this case, the relative proportions in the prechamber are estimated from the partial pressures of the mixed gases (Dalton’s law). The experiments have been carried out using the following chemicals: CH4 − 99.9995 (Praxair), CO2 − 99.998 (Praxair), and N2 − 99.999 (Air Products). In all cases the overall pressure in the prechamber was ﬁxed at 90 mbar after isolating and cleaning it with a rotary pump. In order to obtain a desired temperature of deposition and to reduce contamination, the procedure to cool down the cold ﬁnger is as follows: the cryostat is connected and, when the temperature in the sample holder is 15 K, the resistor is turned on at a voltage high enough to achieve 200 K in the cold ﬁnger. This temperature is above the deposition temperature of undesired gases, mainly H2 O, N2 , and CO2 . After 5 min at 200 K, the current through the resistor is turned oﬀ. This procedure allows us to

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Fig. 2. Procedure to obtain the rate of contamination. Left panel: plot from a real experiment with contamination. Right panel: plot after removing contamination.

get 5 · 10−8 mbar, which is the working base pressure. The deposition temperature (15 K in the coldest case) is achieved again quickly enough to reduce contamination. This procedure allows us to ensure that only a negligible amount of contaminants remain in the chamber. Figure 2 shows the procedure to calculate the amount of undesired molecules during the experiment. The left panel represents the QCMB signal during a real experiment: cooling down, deposition of ice and warming up. In this case, a gap is present in the signal when 90 K is reached during desorption (upper right corner of left panel) corresponding to the amount of contaminants (water) that have been deposited into the QCMB during the period covering 90 K when the temperature was decreasing and 90 K when the temperature was increasing. The right panel represents the QCMB signal after removing the signal due to contaminants. We can see how after desorption (at 90 K) both signals (cooling down and warming up) match. From this removed gap we roughly obtain a rate of deposition of contaminants of 0.5 ng s−1 . To control the deposition of the gas coming from the prechamber to the vacuum chamber we use a needle valve (Leybold D50968) which regulates the gas ﬂow. During deposition, the QMS (AccuQuad RGA 100 with a resolution of ∼0.5 amu) allows us to verify the composition of gases in the chamber. In Fig. 3 we can see a typical experiment of deposition registered with the QCMB. The constancy of the deposition rate can be inferred from the constant variation of the signal with time. The controller ITC 503S regulates the warming up rate with the required accuracy to obtain desorption experiments with warming up rates from 0.50 up to 5.0 K min−1 .

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Frequency vs. time in a deposition experiment for CO2 .

As can be inferred from the preceding paragraphs our procedure fulﬁls the following experimental conditions to perform TPD experiments:2 (i) amount of contaminants negligible with respect to the amount of ice deposited, (ii) a constant rate of deposition as can be inferred from the regression coeﬃcients obtained for the linear ﬁt of the deposition in a typical experiment for CO2 (Fig. 3) and (iii) a ﬁxed rate of warming up during desorption as can be deduced from the linear ﬁt of the plot in Fig. 4. These facts ensure that our experimental procedure allows us to obtain accurate results. 4. Deposition During deposition (Fig. 5) the real part of the refractive index and the density3 can be calculated by means of our “double laser interferometry” system (for a detailed procedure of this method the reader is referred to Domingo et al., 2007) and the QCMB. As a brief summary: The thickness of the sample can be determined by the QCMB if its density is known, but for most of the ices deposited its density at low temperature is still unknown. The density could be determined by using the QCMB signal (Hz s−1 cm−2 /ng s−1 cm−2 ) and the thickness of the sample. In principle,

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Fig. 4.

Warming up during a desorption experiment for CO2 .

using one laser beam, it is possible to determine the thickness if n (refractive index) is known, but once again this is unknown for ices at low temperature. However, using simultaneously two laser beams at two diﬀerent angles of incidence (DLI) we obtain the refractive index and then the thickness and density are determined. The reliability of this method is based on the constancy of the deposition rate. Once the temperature is ﬁxed, the needle valve is opened and the gas ﬁlls the chamber for around 5 minutes, which is the time of deposition used only in these experiments performed to demonstrate the validity of our procedure. In Fig. 5, the start and ﬁnish point of deposition for the laser signal (vertical lines in upper panel) have been obtained manually by blocking the laser beam. In the other two panels (intermediate and bottom) these two points are clearly identiﬁed for the QCMB and QMS. For TPD experiments we can use times of deposition around 30 s (six times lower than that used in the experiments presented here) in order to better prevent contaminants. The pumping system is kept on during deposition, allowing molecules to replenish the chamber randomly and deposit onto the QCMB (background deposition).

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Deposition experiment for N2 .

The amount of deposit is enough to assume that the deposition of contaminants, called “continuum”, is negligible but the pressure of the gas ﬂow during deposition is low enough to not exceed the saturation pressure of the mass spectrometer (10−4 mbar). It is worth remarking that after 5,100 s the laser signal reaches a constant value (the valve that regulates the entrance from the prechamber is turned oﬀ, Fig. 4, upper panel), the frequency signal immediately reaches

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a constant value in the case of the QCMB (intermediate panel), or it drops abruptly to the base signal in the case of QMS (lower panel) as occurs in TPD experiments under UHV conditions. The match obtained among the three techniques ensures the accuracy of the measurements of the mass spectrometer because it responds simultaneously with the signal variation of both: the laser and the QCMB.

5. TPD Experiments After deposition, the system is ready to perform a desorption experiment. The accuracy of this procedure depends on the rate (and constancy) of warming up, the minor rate of warming up the major eﬃciency of the pumping system. Although our ITC 503S can be programmed to perform warming up at a rate of 0.5 K min−1 and other research groups use gradients of 5 K min−1 , we usually heat the sample at 1 K min−1 since we can compare directly with most data present in the literature. During desorption, once again, a match in the signal of the three techniques is obtained (Fig. 6). This experimental fact conﬁrms the capability of the QMS to monitor accurately the desorption of molecules from the sample holder because of the simultaneity with the laser and the QCMB signals. It is worth commenting that we have this match despite the laser and QCMB signal being produced due to variations of the number of molecules on the surface of the QCMB in thermal contact with the sample holder and the QMS represents the molecules coming from all the vacuum chamber. The sample holder is at a certain temperature and is covered by the ice ﬁlm. When the temperature rises, the sublimation is produced, not only on the QCMB but on the sample holder too. The possibility exists that ice sublimes from the QCMB and not from the sample holder and vice versa. But as all the signals coincide at the start and end, it means that ice sublimes from the sample holder essentially at the same time from the QCMB or the rest of it. Taking into account that the QMS reﬂects the composition of the gas in the chamber, and from the match of the signals of QMS and QCMB (located in the sample holder) we can state that the latter also reﬂects this composition. Therefore we can state that the QCMB signal is representative of the chamber. We should also highlight the fact that the laser signal loses its symmetry (Fig. 6 upper panel) with respect to the deposition experiment (Fig. 5

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Left panel: Sublimation experiment for N2 . Right panel: Warming rate.

upper panel) due to an increasing rate of desorption, as we get close to the temperature of sublimation. Another important point to note is the high pressure of N2 after 6,600 s. This signal comes from the sample holder on which the QCMB is located, and this is the reason for not appearing in the frequency signal nor in the laser signal. Additionally, we have performed experiments to determine the temperature of the shield and to check whether N2 is accreted there and we found that no N2 was deposited on the radiation shield except that retained in water or CO2 . In principle, the heat shield is at a temperature (50 K) much higher than the sublimation one of N2 (under our experimental conditions), so we do not expect N2 to desorb from this shield during desorption experiments. Once the validity of the results obtained with the QMS in our system is demonstrated, it is possible to perform diﬀerent experiments to determine the temperature and energy of sublimation of simple molecules or mixtures.

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Fig. 7.

Desorption experiment of a mixture of CO2 and CH4 (95:5).

6. Conclusions From the results shown in this work we can conclude that our experimental setup allows us to obtain a constant rate of deposition and desorption. This is crucial to performing experiments to obtain relevant parameters of the ice structure. Additionally, the pumping speed of our system is appropriate to study desorption processes of ices of simple molecules or mixtures by means of QMS. The signals obtained from the QCMB or QMS techniques can be used to determine the parameters related to desorption processes. We can state that the QMS under our experimental conditions can be used to study the structure of ices from the desorption of other gases present as minor components in the mixture. In Fig. 7 we can see a desorption experiment of a mixture of CO2 and CH4 (95:5) ices, where CH4 is retained until temperatures higher than its characteristic desorption one implying a retaining mechanism related to the CO2 ice structure.4, 5 Acknowledgments This research has been founded by Universidad Polit´ecnica de Valencia PAID-04-08 and Ministerio de Ciencia y Tecnolog´ıa, projects AYA 20012385, AYA 2004-0532, AYA 2007-65899 and FEDER funds.

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References ´ Satorre and J. Cant´ 1. M. Domingo, Mill´ an, M. A. o, Proceeding of SPIE 6616 (2007) 66164A. 2. M. P. Collings, M. A. Anderson, R. Chen, J. W. Dever, S. Viti, D. A. Williams and M. R. S. McCoustra, Mon. Not. R. Astron. Soc. 354 (2004) 1133. ´ Satorre, M. Domingo, C. Mill´ 3. M. A. an, R. Luna, R. Vilaplana and C. Santonja, PSS 56 (2008) 1748. ´ Satorre, ApSS 314 (2008) 113. 4. R. Luna, C. Mill´ an, M. Domingo and M. A. ´ Satorre, R. Luna, C. Mill´ 5. M. A. an, C. Santonja and J. Cant´ o, PSS (in press), doi: 10.1016/j.pss.2008.05.017.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

A NEW, HIGH-PERFORMANCE, HETERODYNE SPECTROMETER FOR GROUND-BASED REMOTE SENSING OF MESOSPHERIC WATER VAPOUR K. HALLGREN∗ , P. HARTOGH† and C. JARCHOW Max-Planck-Institut f¨ ur Sonnensystemforschung Katlenburg-Lindau, 37191, Germany ∗ [email protected] † [email protected] www.mps.mpg.de

We present a new, high time-resolution, heterodyne spectrometer operating at 22.235 GHz for the detection of short timescale mesospheric water vapour variations. The instrument observes the water vapour spectrum in both vertical and horizontal polarisation and averages these in order to get an optimum signal-to-noise ratio. The diﬀerent polarisations have separate, but identical, signal chains consisting of a 22 GHz cooled HEMT ampliﬁer, a second warm 22 GHz HEMT ampliﬁer, an IF stage and a Chirp Transform Spectrometer (CTS) backend. Continuous calibration of the signal with two internal loads, a wobbling optical table to reduce standing waves in the optical path and the low receiver temperature ensures a time resolution of an order of magnitude better than what has been achieved by earlier instruments.

1. Introduction Today several tools for studying and measuring the middle atmosphere exist. During the last few decades millimeter remote sensing has developed into a powerful tool for aeronomy and meteorology. Active (e.g. radars) as well as passive (e.g. radiometers) techniques have proved to be valuable and complement each other well. A number of atmospheric gases (such as ozone, carbon monoxide and water vapour) have successfully been detected and measured with passive methods.1–4 Intercomparison campaigns between ground-based and satellite measurements have been carried out and indicate good agreement between the diﬀerent platforms.5, 6 The vertical distribution of the detected species can be inferred from the measured line shapes. The line shape is determined by molecular 569

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parameters, the number of molecules along the line of sight, broadening of the line by collisions and the velocity distribution of the molecules (Doppler broadening). There exists a threshold altitude where the Doppler broadening exceeds the collisional broadening. Since the vertical distribution is derived from the pressure-broadened line shape7 this altitude also marks the upper limit of the vertical proﬁle that can be retrieved. When observing water vapour at 22.235 GHz this transition occurs between 80– 85 km.8 The water vapour mixing ratio decreases from the lower troposphere to the mesosphere by 4 orders of magnitude. Water enters the middle atmosphere through the tropical tropopause. Its temperature determines the “background” water vapour volume mixing ratio.9 A second source of middle atmospheric water vapour is methane, which is oxidised by the hydroxyl radical. This creates an increase of water with increasing altitude in the middle atmosphere, peaking at approximately 60 km. Higher up in the atmosphere Lyman-α radiation will dissociate the water molecules with a decrease in water vapour mixing ratio as result. The distribution of water vapour in the middle atmosphere is therefore a balance between the primary source and sink above 60 km, transport and photodissociation. The rate of photo-dissociation is fairly well understood10 hence measurements of water vapour distribution above 60 km can be used to constrain the timescales of middle atmosphere transport. In the upper mesosphere water vapour is expected to show a diurnal or semidiurnal variation, which is essentially determined by atmospheric tidal waves. These global scale waves are thermally driven by the periodic absorption of solar radiation throughout the atmosphere, primarily the absorption of infrared radiation by water and water vapour in the troposphere and ultraviolet radiation by stratospheric ozone. Large-scale latent heat release by convective systems and non-linear interactions between global-scale waves are also important excitation sources of atmospheric tidal waves.11–13 The transport of water vapour changes its locally determined vertical proﬁle. The diurnal and semidiurnal tides should therefore be found in the water vapour distribution. Apart from being a good tracer in the middle atmosphere for the above mentioned tides, mesospheric water vapour plays an important role in the many processes speciﬁc for the polar mesosphere, such as Noctilucent Clouds (NLC) and Polar Mesospheric Summer Echoes (PMSE).14 References [15, 16] point to the need for observational data of

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high temporal resolution to fully understand and interpret these processes and their governing dynamics. There is clearly a need for reliable continuous observations of mesospheric water vapour. We will here present an instrument which aims to provide such observations. The new instrument, which is based on the spectrometer reported in Ref. [17], is capable of resolving timescales of a few hours. This improved temporal resolution will allow to measure some of the above mentioned processes for the ﬁrst time. In the next section we will describe the hardware, from the heterodyne frontend to the spectrometer backend. Later we will discuss calibration and retrieval processes and in the last section a short outlook will be presented.

2. Instrument Overview The instrument consists of a cooled heterodyne receiver frontend and a spectrometer backend. The receiver frontend consists of a corrugated horn antenna, an orthomode transducer (OMT) that splits the incoming signal into vertical and horizontal polarisation, two InP HEMT ampliﬁers followed by a single sideband ﬁlter and an IF-preprocessing unit that downconverts the 22 GHz signal to 1,350 MHz. The horn antenna, the OMT and the HEMT ampliﬁers are mounted into an aluminium dewar and cooled to a temperature of approximately 10 K. The receiver temperature of the system has been greatly improved, reaching 25 K for both polarisations (single side-band, SSB), compared to 110 K of the former heterodyne system. The dewar also contains the cold (45 K) and hot (115 K) load. The optical table, dewar and IF-preprocessing unit are mounted on a aluminium baseplate which is integrated into an aluminium rack. The Chirp Transform Spectrometers and the process-control computer are mounted into another 19 rack. A three level control- and redundancy-routine is applied to ensure smooth operation of the instrument without human interference. If any system parameter is out of predeﬁned values or a control process stops to acknowledge control signals an email is sent to operating personnel. The increase in sensitivity of the new system compared to the old one is based on 3 improvements: (1) Cooling of the antenna horn, (2) higher sensitivity of the HEMT ampliﬁers and (3) detection of two rather than one polarisation. The horn antenna cooling is responsible for the largest improvement.

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2.1. Instrument dewar On the frontside of the dewar there are three PTFE windows, one for each load and one for the antenna. PTFE was chosen because of its high transparency in the 22 GHz frequency range. The window thickness has been tuned (by milling) to optimum transmission at 22 GHz. Behind R which serves to reduce each window there are 3 infrared ﬁlters (Zytex) the impact of incoming room-temperature radiation on the loads and the antenna. The loads are encapsulated in metal cylinders to further block heat radiation from the dewar walls. For the absolute calibration of the atmospheric ﬂux, two calibration loads (hot and cold, both microwave black bodies) are required. In order to switch the beam between the atmosphere and the loads an optical table is used. Three separate parabolic mirrors (two ﬁxed and one rotating) are mounted on this table. The rotating mirror alternately reﬂects the radiation from the atmosphere and the two calibration loads via the ﬁxed mirrors into the receiver frontend. The rotation of the mirror is controlled by a processcontrol and house-keeping computer. In order to reduce standing waves in the receiver we have chosen to use a pathlength modulator18 realised by mounting the whole optical complex on a movable table. The table itself is moved back and forth by a computercontrolled stepper-motor with an accuracy of 1 µm. The wobbling amplitude accuracy requirement is 50 µm. The movement is synchronised with the chopper-controller, i.e. one measurement of the atmosphere will take place at the same time as the table moves forward. Consequently during load measurements the table will move the same distance backwards and end up at the initial position, ready for a new atmospheric measurement. The intention of the movement is to remove any standing waves in the optical path that might interfere with the measurements. The movement has a geometrical distance of a multiple of the center frequency wavelength. A movement of distance d will result in a path-length diﬀerence of 2d due to the optical setup. This method reduces the inference of standing waves in the baseline by one or two orders of magnitude. Behind the window opposite to the rotating mirror a cooled corrugated horn antenna is mounted. The incoming signal is directly split into a horizontal and vertical part by means of an OMT, mounted directly on the antenna. As mentioned above, in series with the OMT are two HEMT ampliﬁers mounted. The HEMT ampliﬁers have a noise temperature of 12 to 15 K (compared to 30 K of the former water vapour spectrometer) when cooled. The received signal, ampliﬁed by 40 dB leaves the dewar

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Atmosphere Coolant (He)

HEMT

Horn

Chopper

antenna

Amplifier

Hot/Cold

load

Wobble mechanism

Dewar LO

Filter

Filter

Amplifier

CTS

Mixer IFstage Fig. 1. A schematic overview of the instrument. The main mirror rotates to switch the beam between the loads and the atmosphere. In the dewar the signal is split into two identical chains (only one is shown for readability) which amplify, downconvert and ﬁlter it before ﬁnally being analysed in the CTS.

via two stainless steel semi-rigid cables. This is the output of the cooled dewar and at the same time the input to the IF-preprocessing box. Here, at room temperature and in two identical processing chains, the 22 GHz signal is ampliﬁed again by booster ampliﬁers before it gets downconverted to 1,350 MHz, the input frequency of the Chirp Transform Spectrometers. 2.2. CTS The backend of the system consists of two narrow-band chirp transform spectrometers (CTS), one for each polarisation. They both have a bandwidth of 40 MHz, a spectral resolution of 14 kHz and the data is evenly binned into 4,096 channels of 9.8 kHz (oversampled by 40%). The center frequency of the CTS is 1,350 MHz.

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Control-signals and data transfer between the CTS and process-control computer are sent over Ethernet and directly handled on each side by socket layers. The principle of the CTS and its applications to water vapour observations has been described before.19, 20 In the present instrument, improvements from developments for the SOFIA GREAT project have been incorporated.21, 22 2.3. House-keeping and redundancy An ordinary desktop PC running a Linux kernel is used for processcontrol and house-keeping purposes. It is patched with an Real-Time Application Interface (RTAI) to achieve deterministic behavior. The RTAI layer provides latencies of the system of approximately 15 µs, much faster than the time needed to rotate the mirrors (≈200 ms) which assures that the process control of the system can be assumed to be instantaneous. The computer controls the wobbler and chopper via parallel port interfaces and the timing of the CTS measurements. To ensure system stability in the case of harddrive failure a soft RAID mirroring array is administered. The array has enough storage space to save data of more than 50 days of continuous autonomous measurements. The system can run indeﬁnitely if there is an Internet connection to upload the data to a long term data storage. Raw data from the CTS is sent over Ethernet to the computer where it is stored. To allow instantaneous viewing and spectrum control a buﬀer with calibrated data is also maintained. For maximum analysis ﬂexibility the data is saved in raw format, together with system performance parameters, calibration temperatures and room temperatures. This adds up to almost 500 MBytes every 24 hours. A three level approach controls the instrument operation: (1) instrument parameter check (e.g. dewar pressure and temperature of the ampliﬁers), (2) software control and (3) network availability. During the logging process of the above mentioned parameters all values are compared to a predeﬁned “normal operations” condition table and if any value is outside the expected interval a warning message is sent. The control software bundle consists of more than 10 diﬀerent, simultaneously running, applications. Every hour a process acknowledge test is performed. If a process fail to answer it is assumed to malfunction and a detailed warning message is sent. Due to the fact that everything is controlled over Ethernet the outermost layer of control is an external network check. If the process

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control computer itself does not answer a regular network ping a computer or network problem is assumed, which has to be controlled. All the above mentioned levels of continuous control, redundancy and a robust front- and back-end gives a reliable, almost completely autonomous, system for high time resolution measurements of the middle atmosphere water vapour. 3. Calibration and Retrieval Method For calibration purposes a linear relationship according to the Rayleigh– Jeans law between antenna temperature and output power within a well deﬁned range is assumed.8 Two loads at well-known temperatures are used in a hot–cold load, interleaved, calibration scheme. The cold load is kept at ≈45 K, whereas the hot load is kept at ≈115 K. By keeping the load temperatures close to the expected atmospheric temperature range second order non-linearities can be minimized23 and the eﬃcient noise temperature is kept at low level.24 During normal operating mode, every second spectrum is taken from a load, hot and cold alternatively, the other from the atmosphere. Each atmospheric spectrum is then calibrated against both the hot and cold load spectrum. In this way each load spectrum is used twice, once for the preceding atmospheric spectrum and once for the following, see Fig. 2. Such a routine results in a duty cycle of 50%.24 Due to mounting limitations of the temperature sensors and the loads not being perfect blackbodies there exist a small oﬀset between the measured temperature and the radiometric temperature. This oﬀset has been accurately measured and is included in the calibration process to minimize calibration errors. Assuming the oﬀset being constant within a range of a few Kelvin the loads are expected to linearly follow the logged load temperature to a high degree. Load temperature stability is of importance for high reliability of long term continuous measurements. First measurement

Cold

Sky

Hot

Third measurement

Sky

Cold

Sky

Hot

Second measurement

Fig. 2.

The interleaved calibration technique where each load element is used twice.

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As the two backends are measuring information from uncorrelated sources, vertical and horizontal polarisation, we can average these spectra to decrease the noise of our signal. Each spectrum has a calculated variance, which is a measure of how noisy it is. This variance is normalised and used as a weight for optimal use of the diﬀerent signals. The new variance, and hence the noise of the new signal can be described as 1 1 1 = + Sn S1 S2

(1)

If S1 ≈ S2 this results in Sn =

S1 2

(2)

which is equivalent of dividing the time needed to reach a certain SNR by two, in other words the time–resolution is doubled. In summary, measuring both polarisations (vertical and horizontal) allows us to reduce the eﬀective system receiver temperature from 25 K to 18 K (a factor of square root of 2). This corresponds to an overall increase in sensitivity of a factor of 6 compared to the former system (SSB noise temperature of 110 K), and an increase in the time resolution of 36 (according to the radiometer formula). Assuming an optical thin case, information contained in a retrieved spectrum can be thought as of two diﬀerent kinds. The line amplitude as a measure of the amount of water vapour observed, whereas the line width contains the altitude distribution. Exact spectral line parameters are taken from the JPL catalog.25 The vertical water vapour proﬁle is retrieved by using the optimal estimation method (OEM).7 An a priori proﬁle is needed for the OEM and here a piecewise linear proﬁle with Gaussian smoothing is used. Required temperature and pressure data for the retrieval process are taken from measured values provided by the National Center for Environmental Protection (NCEP). 4. Initial Results and Outlook A ﬁrst hand inspection of retrieved data shows that the improved design is as good as expected. The new system has the ability to resolve atmospheric water vapour dynamics on shorter timescale than ever before observed by ground-based heterodyne spectrometry. An integration time on the order of a few hours is needed to resolve the short time-scale dynamics of water vapour up to approximately 80 km altitude. This is

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more than an order of magnitude better time resolution than earlier instruments.3, 17 Since spring 2008 the instrument runs at ALOMAR Observatory ◦ (69 N, 16◦ E, elev. 380 m). Data intercomparison between the above described system and an older, similar, instrument, running at ALOMAR since 1996,3 is planned. Analysis of this summer’s data is underway and seems promising for a ﬁrst time observation of diurnal atmospheric tides in the mesospheric water vapour by a ground-based heterodyne spectrometer.

Acknowledgments The ﬁrst author is a graduate student at the International Max Planck Research School at Max Planck Institute for Solar System Research and wish to thank the Max Planck Society for this opportunity. We would also like to thank Sandy Weinreb, Caltech Pasadena, for providing the HEMT ampliﬁers.

References 1. P. Hartogh, G. K. Hartmann and P. Zimmerman, Simultaneous water vapour and ozone measurements with millimeterwaves in the stratosphere and mesosphere, in IEEE Catalog Number 91CH2971-0, 1991. 2. P. Hartogh, C. Jarchow, G. R. Sonnemann and M. Grygalashvyly, Journal of Geophysical Research (Atmospheres) 109 (2004) 18303. 3. C. Seele and P. Hartogh, Geophysical Research Letters 26 (1999) 1517. 4. C. Seele and P. Hartogh, Geophysical Research Letters 26 (2000) 3309. 5. G. E. Nedoluha, R. M. Gomez, B. C. Hicks, R. M. Bevilacqua, J. M. Russell, B. J. Connor and A. Lambert, Journal of Geophysical Research (Atmospheres) 112 (2007) 24. 6. D. G. Feist, C. P. Aellig, P. M. Solomon, J. W. Barrett, S. Zoonematkermani, P. Hartogh, C. Jarchow and J. W. Waters, Journal of Geophysical Research 105 (2000) 9053. 7. C. D. Rodgers, Reviews of Geophysics and Space Physics 14 (1976) 609. 8. M. A. Janssen (ed.), Atmospheric Remote Sensing by Microwave Radiometry (Wiley, 1993). 9. J. R. Holton, P. H. Haynes, M. E. McIntyre, A. R. Douglass, R. B. Rood and L. Pﬁster, Reviews of Geophysics 33 (1995) 403. 10. G. Brasseur and S. Solomon, Aeronomy of the Middle Atmosphere (D. Reidel Publishing Company, 1998). 11. S. Chapman and R. Lindzen, Atmospheric Tides. Thermal and gravitational (Dordrecht: Reidel, 1970).

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12. M. E. Hagan and J. M. Forbes, Journal of Geophysical Research (Atmospheres) 107 (2002) 4754. 13. M. E. Hagan and J. M. Forbes, Journal of Geophysical Research (Space Physics) 108 (2003) 1062. 14. U. von Zahn, G. Baumgarten, U. Berger, J. Fiedler and P. Hartogh, Atmospheric Chemistry & Physics 4 (2004) 2449. 15. U. von Zahn and U. Berger, Journal of Geophysical Research 108 (2003). 16. M. Gerding, J. H¨ oﬀner, M. Rauthe, W. Singer, M. Zecha and F.-J. L¨ ubken, Journal of Geophysical Research (Atmospheres) 112 (2007) 12111. 17. P. Hartogh and C. Jarchow, Groundbased detection of middle atmospheric water vapor, in Proc. SPIE, Global Process Monitoring and Remote Sensing of the Ocean and Sea Ice, eds. D. W. Deering and P. Gudmandsen, Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Vol. 2586, December 1995. 18. J. J. Gustincic, A quasi optical receiver system, in IEEE Conference Proceeding on MTT, 1977. 19. P. Hartogh, Present and future chirp transform spectrometers for microwave remote sensing, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, ed. H. Fujisada, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 3221, December 1997. 20. P. Hartogh, High-resolution chirp transform spectrometer for middle atmospheric microwave sounding, in Proc. SPIE, Satellite Remote Sensing of Clouds and the Atmosphere II , ed. J. D. Haigh, Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference, Vol. 3220, December 1997. 21. G. Villanueva and P. Hartogh, Experimental Astronomy 18 (2004) 77. 22. G. Villanueva, P. Hartogh and L. Reindl, Microwave Theory and Techniques, IEEE Transactions on 54 (2006) 1415. 23. L. Paganini, Power spectral density accuracy in chirp transform spectrometers, PhD thesis, Albert-Ludwigs-Universit¨ at, (Freiburg im Breisgau, 2008). 24. C. Jarchow, Bestimmung atmosph¨ arischer wasserdampf– und ozonproﬁle mittels bodengebundener millimeterwellen–fernerkundung, PhD thesis, Universit¨ at, (Bremen, 1998). 25. R. L. Poynter and H. M. Pickett, Applied Optics 24 (1985) 2235.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

EXTREME ULTRAVIOLET SPECTROSCOPE FOR EXOSPHERIC DYNAMICS EXPLORE (EXCEED) ICHIRO YOSHIKAWA∗ , KAZUO YOSHIOKA and GO MURAKAMI Department of Earth and Planetary Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, 113-0033, Japan ∗ [email protected] ATSUSHI YAMAZAKI and SHINGO KAMEDA Institute of Space and Astronautical Science, 3-1-1 Yoshinodai, Sagamihara, Kanagawa, 229-8510, Japan MUNETAKA UENO Department of Earth Science and Astronomy, Graduate School of Arts and Sciences, University of Tokyo, Komaba 3-8-1, Meguro-ku, Tokyo, 153-8902, Japan NAOKI TERADA National institute of information and Communications technology, 4-2-1, Nukui, Koganei, Tokyo, 184-8795, Japan FUMINORI TSUCHIYA, MASATO KAGITANI and YASUMASA KASABA Planetary Plasma and Atmospheric Research Center, 6-3 Aramaki-aza-aoba, Aoba, Sendai, 980-8578, Japan

An earth-orbiting Extreme Ultraviolet spectroscopic mission, EXtreme ultraviolet spectrosCope for ExosphEric Dynamics explore (EXCEED) that will be launched in 2012 is now under development. The EXCEED mission will carry out observations of Extreme Ultraviolet (EUV) emissions from tenuous plasmas around the planets. It is essential for planetary EUV spectroscopy to avoid the Earth’s atmospheric absorption, therefore it should be mandatory to observe above the Earth’s atmosphere. In this paper, we will introduce the general mission overview, the instrument, and the scientiﬁc targets.

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1. Introduction Japanese intensive exploration of space began with the launch of the ﬁrst earth-orbiting spacecraft, OHSUMI. It weighted only 24 kilograms, and today this spacecraft might be classiﬁed as a micro-satellite. After the success, the Institute of Space and Astronautical Science (ISAS) has built and launched more than 25 satellites for science and/or engineering purposes. Traditionally, many scientists in Japan carried out sounding rocket experiments as an access-to-space and “hands-on” training ground for young generations. They were developed quickly at low prices, and provided frequent opportunities for space experiments. In the 90s, a solid propulsion rocket (M-V) developed by ISAS was ready to launch, and has been used as one of the powerful vehicles at the expense of frequent opportunities. On the other hand, a series of small scientiﬁc satellites, which ISAS has recently started to develop, based on the concept ‘cheaper and faster realization of unique space experiments’ as a complementary program of mainstream scientiﬁc satellites. ISAS has released a plan to launch some small satellites for 5 years (Fukuda et al., 2008). The satellites will weigh approximately 300–400 kg. They are responsible for greatly reducing the time needed to obtain science and technology results. The shorter development times for smaller missions can reduce overall costs. Therefore, ISAS has built standard bus architecture, where the bus and payloads are clearly separated in a modular manner. At present, ﬁfteen working groups for small scientiﬁc satellites are constituted under the Steering Committees of Space Science and Space Engineering in ISAS. Our EXCEED mission (EXtreme ultraviolet speCtroscope for ExosphEric Dynamics) was one of the proposals, which were submitted to this new framework, and has been oﬃcially selected as the ﬁrst program. It will be launched in early 2012. In this paper we present the general description of the EXCEED mission. 2. Science Objectives One of the major objectives in the EXCEED mission is to measure plasma escape rates from the terrestrial planets. The amount of terrestrial atmosphere escaping to space still remains as one of the unresolved problems (Shizgal and Arkos, 1996). There were in-situ observations by orbiters, but our knowledge has still been limited. They measured physical parameters such as velocity and temperature along the orbits, but

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global aspects such as total amount of outward-ﬂow plasma are diﬃcult to deduce. EXCEED carries out imaging observations of the planetary plasmas. The observation will enhance our knowledge on characteristics of outward-ﬂowing plasmas, e.g. composition, rate, and dependence on solar activity. The Io plasma torus in the inner magnetosphere of Jupiter is other target of the EXCEED mission. The Io plasma torus is the main source of plasmas for the Jovian magnetosphere, and it characterizes shape and dynamics of the rapidly rotating magnetosphere. Major ion species, sulfur and oxygen ions, have a lot of EUV emission lines from 65 nm to 145 nm, and they radiates the energies outward (Delamere and Bagenal, 2003; Steﬄe et al., 2004). The EUV imaging enables us to know spatial distribution of the ions, and to deduce electron temperature in the inner Jovian magnetosphere.

3. Mission Scenario The ﬁrst small satellite of ISAS, EXCEED, will be launched by the new solid propulsion rocket, and employs a new standard bus module developed by ISAS for this category. Our EUV spectrometer is a single instrument boarded on the satellite. The target mass of the spacecraft is 350 kg. The satellite will be inserted into 800 km × 1,200 km orbit with the orbital inclination of 31 degree. The mission life is designed as 1–2 years. The nominal pointing accuracy of the satellite is around 1’. A target ﬁnding camera identiﬁes the planet, and feeds the oﬀset back to an attitude control system so that we can drop the target image into the slit. A mission data processor samples and averages spectrographs every 5 minute.

4. Instrumental Overview We list the major design parameters of this instrument in Table 1. Figure 1 shows the preliminary optical layout. The EXCEED instrument employs a middle-size oﬀ-axis parabolic mirror. The diameter is 20 cm. The surface material is made of silicon carbide manufactured by chemically vapor deposited process (CVD-SiC). Although multi-layered coating mirrors achieve high reﬂectivity in the EUV range (Yoshikawa et al., 2003, 2004, 2005; Murakami et al., 2006), those have not been preferred. This is because no-multilayered coating mirrors can cover the wide spectral range required for the EXCEED instrument. The oﬀ-axis of the entrance mirror is 5 degree,

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582 Table 1. Wavelength bands Slit width Field-of-view Spectral resolution Spatial resolution Primary mirror Grating Detector ∗ Observations

∗∗ Observation

Speciﬁcations of EXCEED spectrometer. 65–145 nm (1) 78 um (Planet mode)∗ (2) 233 um (Jupiter mode)∗∗ (1) 120 arcsec (2) 400 arcsec (1) 0.1–1 nm (FWHM) (2) 0.3–1 nm (FWHM) (1) 10 arcsec (2) 30 arcsec 20 cm diameter; polished CVD-SiC surface; F = 8 Laminar type with 1,800 lines/mm on CVD-SiC plate MCP with photocathode (CsI) and RAE

for Mercury, Venus, and Mars. for Jupiter and Io.

Fig. 1. Optical layout of the EXCEED spectrometer. The surface of entrance mirror is made of SiC, and it is manufactured by chemically vapor deposition (CVD) technique. The focal length is 160 cm. The spectrometer part consists of the slit, grating, and detector (MCP).

the focal length is 160 cm. The reﬂectivity in the EUV spectral range is calculated, and shown in Fig. 2 with dashed curve. The entrance mirror focuses the incident ﬂux onto a slit. We have two operation modes to satisfy science requirements. One is named as “Planet Mode” which observes the outward-ﬂowing plasmas from the terrestrial planets. The other is named as “Jupiter Mode” which observes the Io plasma torus around the Jupiter. For Planet Mode, the

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Fig. 2. The eﬃciencies of optical components. The bold line indicates an overall sensitivity.

slit width is 78 µm and for Jupiter Mode the width is 233 µm. The widths of these slits are deﬁned depending on the required spectral and spatial resolution. Behind the slit, a laminar-type grating disperses the incident ﬂux onto focal plane. The grating surface is also made of CVD-SiC, achieving a high reﬂectivity in the EUV. The calculated diﬀraction eﬃciency is shown in Fig. 2 with dotted curve. We place the detector surface on the focal plane. The microchannel plates (MCPs) with V-Z stack are used with a photocathode of CsI. A resistive anode encoder (RAE) for position analysis is employed. The overall assembly is commonly used for EUV observations (Yoshikawa et al., 2001a, 2007; Yoshioka et al., 2007). The CsI-coated MCPs have 1.5 to 50 times higher quantum detection eﬃciencies (QDEs) in the EUV spectral range, compared with the bared one (Tremsin and Siegmund, 1999, 2000, 2001; Taguchi et al., 2001; Yoshikawa et al., 2001b; Yoshioka et al., 2007). The overall detector is vacuumed during the ground-based operations. The entrance cover will be unlocked and released by activating the paraﬃn-actuator just after the launch. Optical alignment and sensitivity are insensitive to thermal condition along the orbit.

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Fig. 3. Schematics of the EUV detector. Microchannel plates (MCPs) are installed inside, and are kept vacuumed. After the launch, the paraﬀﬁn actuator unlocks MgF2 door. Position analysis electrical board and high voltage power supply are installed behind.

5. Contamination from the Terrestrial Airglow We need to pick up a small signal to archive the scientiﬁc goal. The contamination by the Earth’s airglow emissions such as O II (83.4 nm) and H I (121.6 nm) is quite serious. On the other hand, if the satellite was launched up to a few thousands kilometers, the Earth’s radiation belt would hinder our observation seriously. The intensity of geocorona depends on the solar activity. The operation window of the EXCEED is planned from 2012 to 2013. It corresponds to the solar maximum period. In the following, we assume the maximum intensity of the geocorona. In the spectral range of our spectrometer, the most serious contamination source is oxygen ions, which emit at 83.4 nm, in the Earth’s ionosphere. There are three potential source processes of excitation leading to 83.4 nm emission (Meier, 1991). The dominant process below 800 km is a photo-ionization of neutral O leading to excited O+ . During the period of the solar maximum, the corresponding emission rate factor, so-called g-factor, is 2.2 × 10−8 sec−1 . An ionization of O by an electron impact is

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Fig. 4. The column density proﬁles of oxygen atom and ion during the period of solar maximum, based on MSIS-90 and IRI models. The local time is 20 hour.

the second contamination process with g-factor being 2.0 × 10−9 sec−1. The brightest contamination above the altitude of 800 km is a solar resonant scattering by ionized oxygen. The corresponding g-factor is 1.5×10−6 sec−1 . Figure 4 shows the column density proﬁle of the neutral oxygen and ionized one in the dayside. We used the MSIS-90 (Mass-SpectrometerIncoherent Scatter) and IRI (International Reference Ionosphere 2007) models to obtain the height proﬁle (Hedin, 1991; Bilitza, 2001) and calculated the column density along line-of-sight. Figure 5 shows the

Fig. 5.

The brightness of geocoronal emission at 83.4 nm versus the altitude.

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intensity proﬁles versus the altitude. Each brightness of the contaminations as cited above is shown.

6. Estimate of Signal-to-Noise Ratio We estimate signal-to-noise ratio (SNR) in order to determine the orbital altitude of spacecraft. Potential noise sources for our observation are (1) geocorona emission, (2) energetic electron in the radiation belt, and (3) detector (MCP) internal noise. We assumed the calculated reﬂectivity, diﬀraction eﬃciency, and quantum detection eﬃciency shown in Fig. 2. We assume that the intensity of O II (83.4 nm) from the Venus ionosphere is 3.5 Rayleigh and that the outward-ﬂowing oxygen ions forming the ionospheric tail (e.g. 1 Venus radii from the Venus surface) have the intensity by 0.0033 Rayleigh (Yamazaki et al., 2003, 2004). To avoid the Earth’s dayside ionospheric O II contamination, at the Earth’s morning/evening sector we plan to observe Venus O II emission during the period of the western/eastern greatest elongations. We use the simple formula to estimate SNR. (Signal counts) S √ = N (Counts from the Geocorona) + (counts from energetic electrons) + (MCP internal noise counts)

(1) We constructed a mass model in GEANT4 code, which included all the components of the instrument such as a shielding box, MCPs, grating, supporting staﬀ, and so on. We simulated the propagation and attenuation of the energetic electrons from the outside the instrument to MCPs (Tanaka et al., 2007). Our model indicates that the energetic electrons drop noise counts as 1.5 cm−2 sec−1 on the MCP. We also take into account the geocoronal emission as discussed in Section 5. For the MCP internal noise, we used the value of 0.3 cm−2 sec−1 . The value is based on our instrumental development heritage (Yoshikawa et al., 2000a, 2000b, 2007, 2008, in press; Chasseﬁere et al., in press). Figure 6 shows SNR versus altitude. The result of our calculation indicates that the 3,600-second exposure is enough to achieve the suﬃcient SNR for the Venus ionosphere, but 100,000-second exposure is necessary for the tail. Also, we conclude that observations at the altitude of 1,000 to 1,200 km can detect the EUV lights emitted from the targets.

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Fig. 6. Signal-to-Noise Ratio for Venus O II measurements versus orbital altitude of the satellite. (Upper) observation for Venus ionosphere (Lower) observation for the outwardﬂowing oxygen ions toward the Venus ionospheric tail.

Figure 7 summarizes our calculation. The y-axis represents count rate, and the x-axis denotes the spatial resolution (spatial binning) for the observation. Red-, black-, and blue-tinged colors represent calculations for the cases that we observe Mercury, Venus, and Mars, respectively. The green line indicates Io. The dotted line shows the exposure time, where we can achieve SNR at 1. We can identify the EUV signal from Io with a 20” spatial resolution within 1,000 seconds (approximately 20-minute) exposure. Plasma outﬂows from Venus and Mercury are feasible to image within 10 k–100 k seconds, if we decrease the spatial resolution to planetary apparent diameters. However, plasma outﬂow from Mars is diﬃcult to

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Fig. 7. Counts rate versus spatial resolution. Red-, black-, and blue-tinged colors represent calculations of Mercury, Venus, and Mars, respectively. The green line indicates calculation of Io. The dotted line shows the exposure time, where we can achieve SNR at 1.

identify, even if we sacriﬁce the spatial resolution down to Martian apparent diameter. This is because we need much longer integration time, e.g. 6–9 M seconds (approximately 2–3 months), compared with the observational window for Mars. 7. Summary The EXCEED mission is under development in the new framework of ISAS small satellites. It will be launched in 2012. We have completed the primary optical layout and the detector design. We concluded that (1) an altitude of 1,000 to 1,200 km is relatively good platform and that (2) an exposure for several mega seconds is necessary to identify and image EUV emissions from the Martian plasma outﬂow. Acknowledgments The authors are grateful to Dr. Yasuyuki Tanaka of Tokyo institute of Technology who has assisted us in preparing Geant4 simulations.

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References 1. D. Bilitza, International Reference Ionosphere 2000, Radio Science 36 (2001) 261–275. 2. P. A. Delamere and F. Bagenal, Modeling variability of plasma conditions in the Io torus, Journal of Geophysical Research 108(A7) (2003) 1276. 3. E. Chasseﬁre, J.-L. Maria, J.-P. Goutail, E. Qu merais, F. Leblanc, S. Okano, I. Yoshikawa, O. Korablev, V. Gnedykh, G. Naletto, P. Nicolosi, M.-G. Pelizzo, J.-J. Correia, S. Gallet, C. Hourtoule, P.-O. Mine, C. Montaron, N. Rouanet, J.-B. Rigal, G. Muramaki, K. Yoshioka, O. Kozlov, V. Kottsov, P. Moisseev, N. Semena, J.-L. Bertaux, M.-Th. Capria, J. Clarke, G. Cremonese, D. Delcourt, A. Doressoundiram, S. Erard, R. Gladstone, M. Grande, D. Hunten, W. Ip, V. Izmodenov, A. Jambon, R. Johnson, E. Kallio, R. Killen, R. Lallement, J. Luhmann, M. Mendillo, A. Milillo, H. Palme, A. Potter, S. Sasaki, D. Slater, A. Sprague, A. Stern and N. Yan, PHEBUS: A double ultraviolet spectrometer to observe Mercury’s exosphere, Planetary and Space Science, 2008 (in press). 4. S. Fukuda, S. Sawai, S. Sakai, H. Saito, T. Nakagawa, T. Tohma, J. Takahashi and K. Kitade, Flexible standard bus for ISAS/JAXA small scientiﬁc satellite series, 26th International Symposium on Space Technology and Science (ISTS), Hamamatsu, Japan, 2008-f-17, 2008. 5. A. E. Hedin, Extension of the MSIS Thermospheric Model into the Middle and Lower Atmosphere, J. Geophys. Res. 96 (1991) 1159. 6. R. R. Meier, Ultraviolet spectroscopy and remote sensing of the upper atmosphere, Space science Reviews 58 (1991) 1–185. 7. G. Murakami, K. Yoshioka and I. Yoshikawa, Development of Mg/SiC multilayer mirrors, Proceedings of SPIE 6317 (2006) 631714-1-8. 8. B. D. Shizgal and G. G. Arkos, Nonthermal escape of the atmospheres of Venus, Earth and Mars, Rev. Geophys. 34 (1996) 483–505. 9. A. J. Steﬄe, F. Bagenal, A. Ian F. Stewart, Cassini UVIS observation of the Io plasma torus. II. Radial variations, Icarus 172 (2004) 91–103. 10. Taguchi M., H. Fukunishi, H. Watanabe et al., Ultraviolet imaging spectrometer (UVS) experiment on board the NOZOMI spacecraft: instrumentation and initial results, Earth Planets Space 52 (2001) 49–60. 11. Y. Tanaka, I. Yoshikawa, K. Yoshioka, et al., Gamma-ray detection eﬃciency of the microchannel plate installed as an ion detector in the low energy particle instrument onboard the GEOTAIL satellite, Review of Scientific Instruments 78 (2007) 034501-1-034501-4. 12. A. S. Tremsin and O. H. W. Siegmund, The dependence of quantum eﬃciency of alkali halide photocathodes on the radiation incidence angle, Proceeding of SPIE, EUV, X-Ray and Gamma-Ray Instrumentation for Astronomy VI, 3765 (1999) 441–451. 13. A. S. Tremsin and O. H. W. Siegmund, The stability of quantum eﬃciency and visible light rejection of alkali halide photocathodes, Proceeding of SPIE 4013 (2000) 411–420.

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14. A. S. Tremsin and O. H. W. Siegmund, UV radiation resistance and solar blindness of CsI and KBr photocathodes, IEEE Trans. Nuclear Science 48 (2001) 421–425. 15. A. Yamazaki, I. Yoshikawa, Y. Takizawa, et al., Feasibility study of the O II 83.4 nm imaging of ionosphere and magnetosphere, Advances in Space Research 32 (2003) 441–446. 16. A. Yamazaki, I. Yoshikawa, N. Terada, M. Nakamura, EUV imaging of near — Venus space, Advances in Space Research 33(11), (2004) 1932–1937. 17. I. Yoshikawa, M. Nakamura, M. Hirahara, Y. Takizawa, K. Yamashita, H. Kunieda, T. Yamazaki, K. Misaki and A. Yamaguchi, Observation of He II emission from the plasmasphere by a newly developed EUV telescope on board sounding rocket S-520-19, J. Geophys. Res. 109 (1997) 19897–19902. 18. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa, and M. Nakamura, Photometric measurement of cold helium ions in the magnetotail by an EUV scanner onboard Planet-B: Evidence of the existence of cold plasmas in the near-Earth plasma sheet, Geophys. Res. Lett. 27(2000), (2000a) 3567–3570. 19. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa, and M. Nakamura, Evolution of the outer plasmasphere during low geomagnetic activity observed by the EUV scanner onboard Planet-B, J. Geophys. Res. 105 (2000b) 27777–27790. 20. I. Yoshikawa, A. Yamazaki, K. Shiomi, K. Yamashita, Y. Takizawa and M. Nakamura, Loss of plasmaspheric ions during a storm observed by the EUV scanner onboard Planet-B, J. Geophys. Res. 106 (2001a) 18911–18918. 21. I. Yoshikawa, A. Yamazaki, K. Shiomi, et al., Development of a compact EUV photometer for imaging the planetary magnetosphere, Journal of Geophysical Research 106 (2001b) 26057–26074. 22. I. Yoshikawa, A. Yamazaki, K. Yamashita, Y. Takizawa and M. Nakamura, Which is a signiﬁcant contributor for outside of the plasmapause, an ionospheric ﬁlling or a leakage of plasmaspheric materials?: Comparison of He II (304 ˚ A), J. Geophys. Res. 108 (2003) 1080, doi 10.1029/2002JA009578. 23. I. Yoshikawa, A. Yamazaki, T. Murachi et al., Development of an Extreme Ultraviolet Imaging Spectrometer for the BepiColombo Mission, Advance in Space Research 33(12) (2004) 2195–2199. 24. I. Yoshikawa, T. Murachi, H. Takenaka et al., Multilayer coating for 30.4 nm, Review of Scientific Instruments 76 (2005) 1. 25. I. Yoshikawa, S. Kameda, K. Matsuura, K. Hikosaka, G. Murakami, K. Yoshioka, H. Nozawa, D. Rees, S. Okano, H. Misawa, A. Yamazaki and O. Korablev, Observation of Mercury’s sodium exosphere by MSASI in the BepiColombo mission, Planetary and Space Science 55 (2007) 1622–1633. 26. I. Yoshikawa, A. Yamazaki, G. Murakami et al., Telescope of extreme ultraviolet (TEX) onboard SELENE: science from the Moon, Earth Planets Space 60 (2008) 407–416. 27. I. Yoshikawa, O. Korablev, S. Kameda, D. Rees, H. Nozawa, S. Okano, V. Gnedykh, V. Kottsov, K. Yoshioka, G. Murakami, F. Ezawa and

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G. Cremonese, The Mercury Sodium Atmospheric Spectral Imager for the MMO Spacecraft of Bepi-Colombo, Planetary and Space Science (in press). 28. K. Yoshioka, K. Hikosaka, G. Murakami, et al., Development of the EUV detector for the BepiColombo mission, Advances in Space Research 41(9) (2007) 1392–1396.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

COMMON ERRORS IN THE CALCULATION OF AIRCREW DOSES FROM COSMIC RAYS KERAN O’BRIEN Department of Physics and Astronomy, Northern Arizona University, PO Box 6010 Flagstaﬀ, Arizona 86011-6010,USA [email protected] ERNST FELSBERGER Aircrew Dosimetry, IASON GmbH, Feldkirchner Strasse 4, A-8054 Graz-Seiersberg Graz, (Styria), Austria PETER KINDL Arbeitsgruppe Strahlenphysik, Institut f¨ ur Materialphysik, Petersgasse 16/4, A-8010 Graz, (Styria), Austria

Radiation doses to air crew are calculated using ﬂight codes. Flight codes integrate dose rates over the aircraft ﬂight path, which were calculated by transport codes or obtained by measurements from take oﬀ at a speciﬁc airport to landing at another. The dose rates are stored in various ways, such as by latitude and longitude, or in terms of the geomagnetic vertical cutoﬀ. The transport codes are generally quite satisfactory, but the treatment of the boundary conditions is frequently incorrect. Both the treatment of solar modulation and of the eﬀect of the geomagnetic ﬁeld are often defective, leading to the systematic overestimate of the crew doses.

1. Introduction To calculate cosmic-ray intensities in the Earth’s atmosphere starting with a given local interstellar cosmic-ray spectrum (LIS), the boundary conditions of the ﬂux at the top of the Earth’s atmosphere must be calculated. These boundary conditions depend on solar modulation through the heliosphere and the eﬀect of the geomagnetic ﬁeld. To determine the radiation doses to aircrews on a given ﬂight trajectory, these ﬂuxes must be then used to calculate doses (eﬀective or ambient) and combined in a ﬂight code. Those steps are frequently treated incorrectly. There are two approximations to the Parker transport equation that are widely 593

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used, the convective-diﬀusion equation and the force-ﬁeld, or heliocentric approximation.1 The convective-diﬀusion equation is inaccurate in the inner heliosphere, whereas the heliocentric equation is quite accurate out to about 20 AU. In the cases at hand, the time-dependent solution to the convectivediﬀusion equation is seriously in error. The heliocentric approximation, while quite accurate at 1 AU has also been incorrectly calculated in at least one case. In this paper we shall attempt to indicate what these errors are in the hope that they may be avoided in the future. 2. The Heliosphere The heliosphere is a roughly spherical bubble created by the pressure of the solar wind against the pressure of the interstellar medium. It terminates in the solar wind transition shock at a distance of roughly 100 AU from the sun. The transport of galactic cosmic rays through this medium is described by Parker’s equation.1 A useful and accurate approximation to this transport equation at 1 AU, or Earth orbit, is the force-ﬁeld or heliocentric potential approximation due to Gleeson and Axford.2 A competing model, the convective-diﬀusion model has been used at 1 AU, but is extremely inaccurate below 400 MeV at that distance as extensively discussed by Caballero-Lopez and Moraal3 extensively. A widely used convective-diﬀusion equation is the deceleration potential of Badwhar and O’Neill.4 They argue that the cosmic ray ﬂux below a rigidity of 3 GV arrives 93 days after the ﬂux above that rigidity (cf. Fig. 1).

Fig. 1.

Cosmic-ray particle arrival time according to deceleration potential theory.

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Arrival time of cosmic rays to Earth orbit.

This assumption has been used in combination with the Climax Neutron monitor that has a vertical cutoﬀ of 3 GV to predict solar modulation and hence radiation doses 3 months ahead. I has also been assumed that the essentially all the cosmic-ray dose rate is due to particles below 3 GV. It has, however, been shown that the arrival time relative to 3 GV (about 4 GeV per nucleon) at 10 MeV is on the order of hours, not months.5,6 Figure 2 shows the calculated arrival time using the code ATROPOS at solar maximum (the arrival time is less at solar maximum than at solar minimum because the particles start at higher energies).7 Because monthly-averaged solar modulation generally changes slowly from month to month, the error resulting from this assumption is usually small, especially during the quiet times near solar minimum. During solar maximum, the variation may be considerably larger. This assumption also gives only the monthly-averaged convention-diﬀusion calculation of the potential. The additional error associated with that assumption will be discussed later in this paper. 3. The Geomagnetic Field In order to create a ﬂight code from a data base consisting of extensive calculations of dose rates at some location over the surface of the earth, it

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Fig. 3.

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Two-dimensional geomagnetic cutoﬀ distribution near the magnetic equator.

is necessary to index them in some way. The approach used by the authors of EPCARD is to calculate and index these data using the vertical cutoﬀ alone.8 In Fig. 3, one can see in the “wings” of the two-dimensional cutoﬀ distribution, calculated near the magnetic equator; a sizeable “East-West eﬀect. The vertical cutoﬀ is the line at the bottom left of the ﬁgure at a zenith angle of zero degrees. While the geomagnetic cutoﬀ at an azimuth of 180◦ and a zenith angle of 90◦ is somewhat less than the vertical cutoﬀ, it is clear that the consequence of the East-West eﬀect is to increase the overall eﬀective cutoﬀ, meaning that the use of the vertical cutoﬀ alone will overestimate the cosmic-ray ﬂux and the radiation dose. See also Lin, et al.,9 Clem, et al.,10 De Angelis, et al.11 This could be, and has been interpreted, incorrectly, as an aircraft structural eﬀect instead of an incorrect treatment of the geomagnetic ﬁeld.12 The magnitude of this overestimate is shown in Fig. 4 for a ﬂight level of 35,000 feet at solar minimum. 4. In the Atmosphere While the CARI code [13] calculates the eﬀective dose rate correctly at a given altitude, latitude and longitude for the correct heliocentric potential, the calculations for potentials give wrong values resulting in an overestimate for the dose to aircrew. The size of this error as a function of time for the last four years is shown in Fig. 5.

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90 75 1 60 5 1 45 10 5 15 30 10 20 15 15 20 25 0 20 -15 -30 15 10 -45 5 -60 1 -75 -90 -180 -150 -120 -90 -60 -30 0 30 60 90 120 150 180 Longitude / Degree

Fig. 4. World map of the percentage eﬀective dose overestimate using the vertical geomagnetic cutoﬀ alone, at 35,000 feet and solar minimum.

Fig. 5. The relative percentage error in the heliocentric potential calculated by the Aerospace Medical Research Team of the Federal Aviation Administration.

While the FAA will provide users of their system with hourly potentials, the data available on the web are monthly averages. The deceleration potential supplies only incorrect monthly averages. During this long solar minimum, the hour-by-hour variation is comparatively small. However, during solar maximum, the hour-by hour variation can be considerable. The mean heliocentric potential for the month of September 1982, for instance, based on the Apatity monitor14,15 is 1,209 MV. However, for the

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4-hour period beginning September 21, 1982 at 1,600 hours, the heliocentric potential is 1,554 MV, and for the 4-hour period beginning September 4, at 0800 hours it is 1,076 MV. The diﬀerences from the mean are 29% and 10% respectively.

5. Conclusions Flight codes that use only the vertical cutoﬀ to account for the eﬀect of the geomagnetic ﬁeld on incident cosmic rays, will overestimate the eﬀective does to aircrew, as will the CARI code because of its poor representation of the heliocentric potential. Such systematic overestimates may have an economic impact on the airlines using them as it may appear that air crew members have reached their exposure limit, where, in fact, they may not. Overestimates of the dose rate based on these codes compared to accurate measurements may be ascribed to aircraft structural eﬀects instead of the use of incorrect “boundary conditions”. The use of a monthly-averaged heliocentric potential may expose a crew to radiation intensity signiﬁcantly diﬀerent from the calculated value. Finally, the use of the deceleration potential may expose a crew to radiation from the wrong month. Although the month-to-month variation is usually small,5 it can vary considerably at higher at higher solar activity levels.

References 1. E. N. Parker, Planet. Space Sci. 13 (1965) 9. 2. L. J. Gleeson and W. I. Axford, Can. J. Phys. 46 (1968) S937. 3. R. A. Caballero-Lopez and H. Moraal, Journ. of Geophys. Res. 109 (2004), A01101, doi:10.1029/2003JA010098. 4. D. Badwhar, Radiat. Res. 138 (1997) S3. 5. K. O’Brien, Radiat. Prot. Dos. 109 (2004) 357. 6. K. O’Brien, Cosmic Rays in the Solar System. Eighth International Symposium on the Natural Radiation Environment (NRE VIII), AIP Conference Series, J.P. McLaughlin, S.E. Simopoulos, and F. Steinh¨ ausler, Eds., (in press). 7. K. O’Brien, From Earth to Mars, Radiation Intensities in Interplanetary Space, Advances in Geosciences, 8: Planetary Science, Ed., Anil Bhardwaj, World Scientific Publ. Comp., Singapore (in press). 8. German Research Center for Environmental Health, EPCARD, http:// www/helmholtz-muenchen.de/en/epcard-portal/epcard-home/index.html (2008). 9. Z. Lin, J. Bieber and E. Evenson, J. Geophys. Res. 100 (1995) 23543–23549.

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10. J. M. Clem, J. W. Bieber and P. Evenson, J. Geophys. Res. 102 (1997) 26919–26926. 11. G. De Angelis, J. M. Clem, P. Goldhagen and J. W. Wilson, Adv. Space Res. 32(1) (2003) 17–26. 12. A. Ferrari, M. Pelliccioni and R. Villari, Radiat. Prot. Dosimetry 108 (2004) 91. 13. K. O’Brien, D. F. Smart, M. A. Shea, E. Felsberger, U. Schrewe, W. Friedberg and K. Copeland, Adv. Space Res. 31 (2003) 835. 14. Apatity Neutron Monitor: http://pgia.ru/CosmicRay/ (2008). 15. K. O’Brien, and Gail de P. Burke, J. Geophys. Res. 78 (1973) 3013.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

MULTI-FREQUENCY TOTAL FLUX MEASUREMENTS OF JUPITER’S SYNCHROTRON RADIATION IN 2007 F. TSUCHIYA∗ , H. MISAWA† , K. IMAI‡ , and A. MORIOKA§ Graduate school of Science, Tohoku University, Sendai, Miyagi 980-8578, Japan ∗ [email protected] † [email protected] ‡ [email protected] § [email protected] T. KONDO National Institute of Information and Communications Technology, Kashima, Ibaraki 314-0012, Japan Ajou University, Suwon 443-749, Korea [email protected]

Total ﬂux densities of Jupiter’s synchrotron radiation (JSR) were regularly observed at frequencies of 325 and 785 MHz with the Iitate Planetary Radio Telescope (IPRT) from May to July 2007 and at 2.3 GHz with the 34-m radio telescope at the National Institute of Information and Communications Technology (NICT) in June. These observations were made as part of a simultaneous spectrum and interferometer observation campaign. This paper describes the results of the absolute total ﬂux measurements made by the single dish telescopes. Since the frequency range below 1 GHz is not often used for JSR observations, except for campaign-based observations, regular observation in this low frequency range is expected to provide new information on the dynamic behavior of Jupiter’s radiation belt. The receiver system of IPRT has a function to measure the on-site gain and noise temperature of the receiver, and it can compensate for instrumental ﬂuctuations. Besides the observation of JSR itself, the galactic background ﬂux just behind Jupiter was also observed in order to obtain the absolute ﬂux density of JSR. The JSR observations have a short-term variation with a time scale of a few days and amplitude of ±20–30%. The variation does not coincide with the solar F10.7 ﬂux. This implies that an enhanced radial diﬀusion, which is driven by the neutral wind in the upper atmosphere, is not responsible for the time variation in JSR. Some enhancements in JSR suggest the time response to changes in solar wind activity. The characteristics of the short-term variation in the low-frequency range would imply that various mechanisms contribute to it.

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1. Introduction Jupiter’s synchrotron radiation (JSR) is emitted from relativistic electrons trapped in Jupiter’s inner radiation belt. The observation of JSR is therefore a useful tool for investigating the behavior of relativistic electrons in the radiation belt. A number of observations of JSR have been made since its discovery,1 and the averaged spatial distribution of the emission source2–4 and the radio spectra5, 6 have been revealed. The time variations of JSR are still poorly understood, except for the long-term variation associated with solar activity.7–12 The early reports do mention short-term variations in JSR.13, 14 However, it was later concluded that these were not natural variations and were due to the background confusion eﬀect or instrumental instability.5, 15 Since the 1990’s, monitoring of JSR following the impact of the Shoemaker-Levy 9 comets with Jupiter enabled a search for the shortterm variations, and some eﬀorts at making continuous observations showed evidence of them.9, 16–21 Miyoshi et al.19 carried out a careful measurement of the absolute ﬂux of JSR at 2.3 GHz that took into account errors such as the background confusion eﬀect and instrumental instability. They found a variation in JSR on a time scale of a few days and attributed it to enhanced radial diﬀusion in the radiation belt. JSR has mainly been observed in the frequency range above 1 GHz, and only a few regular observations have been done below 1 GHz.20, 22 Some of the previous observations imply that observations of JSR at low frequencies might reveal the dynamics of the radiation belt. In-situ observations of radiation-belt particles by the Pioneer 10 and 11 spacecraft showed that the electron ﬂuxes with lower energy were more variable than those with higher energy.23 Comparisons of the full spectra of JSR obtained in two separate periods show a large change in radio ﬂux in the lower frequency range but only a small change in the higher frequency range.6 de Pater24 reported an unexpected increase in total ﬂux density at 330 MHz and a subsequent drop the next day, which were not detected at the higher frequency of 2 GHz. Nomura et al.25 found an unusual enhancement at 327 MHz. It is expected that the time variability of the radio spectrum has important information on the physical process in the radiation belt.26 Theoretical studies proposed that the radial diﬀusion process in Jupiter’s radiation belt has a weak energy dependence,27 while the dominant loss processes, such as the sweeping eﬀect of rings and satellites, the synchrotron radiation eﬀect, and pitch angle scattering, have strong energy dependences.6, 26, 28, 29 However, these energy dependences have not been suﬃciently conﬁrmed by the observations of time variability in JSR.

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The Iitate Planetary Radio Telescope (IPRT), which measures meter to decimeter radio waves, was developed at the Iitate observatory of Tohoku University (Iitate village, Fukushima prefecture, Japan; 37◦ 42 N, 140◦ 41 E),30 and the observation system for 325 and 785 MHz was installed in 2002 and 2006, respectively.31–34 To investigate the dynamic behavior of JSR in the low-frequency range, we made continuous spectrum observations at 325 and 785 MHz with IPRT from May to July 2007, as well as total ﬂux observations at 2.3 GHz with the 34-m radio telescope at the National Institute of Information and Communications Technology (NICT) in June. These total ﬂux observations were made as part of a simultaneous spectrum and interferometer observation campaign, and the interferometer observations were made at 610 and 235 MHz with the Giant Metrewave Radio Telescope (GMRT) in India.35, 36 In this paper, we describe the results of the total ﬂux observations made by the two radio telescopes. Secs. 2 and 3 describe the instrumentation of IPRT and methods to extract the absolute ﬂux of JSR from the data. Brief descriptions of the 34-m telescope at NICT and the JSR observations can be found in Miyoshi et al.19 and Misawa et al.37 The results of the observations are described in Sec. 4.

2. Observation System IPRT is a low-frequency radio telescope dedicated to observing planetary radio emissions, particularly synchrotron radiation from Jupiter’s radiation belt. IPRT therefore is advantageous for investigating the dynamic behavior of Jupiter’s radiation belt. The antenna is an oﬀset parabola whose physical aperture area and eﬃciency are 1,023 m2 and 65%,32 respectively, and it is composed of two separate rectangular parabolic sections as shown in Fig. 1. Received signals from the two sections are synthesized by using the phased-array technique.38 The primary observation frequency is 325 MHz, which is authorized as a radio astronomical observation band. The other observation frequency (785 MHz) was chosen after a survey of radio interference at the Iitate observatory.34 The primary feed antenna, which converts the radio wave into an electric signal, is located at the focus and consists of crossed half-wave dipoles with a plane reﬂector for 325 MHz to make total ﬂux and polarization measurements. The feed antenna for 785 MHz consists of only a horizontal half-wave dipole with a the plane reﬂector. The receiver system is composed of front-end and back-end receivers installed in temperature-stabilized boxes. Low noise ampliﬁers (LNA)

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Fig. 1.

Photograph of Iitate Planetary Radio Telescope (IPRT).

are used as the 1st stage signal ampliﬁers of the front-end receiver, and their noise temperatures are typically 80 and 50 K for 325 and 785 MHz, respectively. Standard noise sources (346B, Agilent Technology Inc.) are installed in the front-end receiver in order to measure the on-site gain and noise temperature with the Y-factor method.39 The minimum detection sensitivity of IPRT is ∼0.1 Jy (1 Jy = 10−26 W m2 Hz−1 ) at both frequencies, given a receiver band width of 10 MHz and an integration time of 10 seconds. Measurements taken since the 1960’s indicate that the total ﬂux density of JSR varies between 3 and 6 Jy.9, 40 The amplitude of natural variations on time scales of weeks to months is reported to be >10%.9, 16–19 Therefore, the sensitivity of 0.1 Jy is suitable for detecting the natural variation in JSR. 3. Observations and Analysis Jupiter and standard ﬂux calibrators were observed with the drift scan method. During such an observation, the direction of the radio telescope is pointed such that the target radio source passes through the center of

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the drift scan. Considering the beam width of IPRT (∼1.6 and 0.6 degrees at 325 and 785 MHz, respectively) and celestial motion of the radio source, it takes 30 minutes at 325 MHz and 15 minutes at 785 MHz to measure a complete drift curve of the target radio source and the background radio ﬂux behind the target. The signal power output from the back-end receivers is measured by power meters every 0.5 second and averaged over 10 seconds. Power output from the receiver during a drift scan of Jupiter, PJSR , is PJSR = kB G∆f (TJ + TRX + Tsky ),

(1)

where TJ and Tsky are antenna temperatures of Jupiter and the background components, respectively, kB is the Boltzmann constant, G system gain, TRX noise temperature, and ∆f the bandwidth of the receiver. A few weeks before or after the JSR observations, the same celestial position was measured by using the same method in order to obtain the galactic background ﬂux behind Jupiter. The output from the receiver, PBKG , is + Tsky ), PBKG = kB G ∆f (TRX

(2)

where G and TRX indicate the gain and noise temperature during the observation, respectively. The antenna temperature of JSR can be obtained by calibrating the gain and noise temperature and subtracting Eq. (2) from Eq. (1). To compensate for instrumental ﬂuctuations, the gains and noise temperatures were measured every 3 minutes during the drift scan. Because the antenna temperature of Jupiter measured by IPRT (∼1 K) is smaller than that of the galactic background component at 325 MHz (tens to hundreds of Kelvin), it is quite important to evaluate the precise background ﬂux to obtain the correct absolute ﬂux density of JSR in the low-frequency range. The antenna temperatures of the background ﬂux at the same celestial position as Jupiter were observed several times and averaged to make a precise evaluation. Examples of the drift scan observation and the subtraction analysis at 325 MHz are shown in Fig. 2. Because the antenna temperature of Jupiter after subtraction should represent the beam pattern of the radio telescope, the subtracted curve is ﬁtted to a Gaussian curve by using a non-linear least squares method, and from this, one obtains the antenna temperature of Jupiter and the standard deviation of the residual values between the measured and ﬁtted curves. If side lobes of the antenna beam pattern are found in the subtracted curve, we determine a baseline by using values at two null points between the main beam and the ﬁrst side lobe. The standard deviation includes errors caused

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Fig. 2. Example of the subtraction analysis of the galactic background component at 325 MHz. (a) Antenna temperature during a drift scan of Jupiter observed on May 25, 2007 (red) and averaged antenna temperature of the background component (blue). (b) Antenna temperature of Jupiter after the subtraction analysis. Red triangles and error bars indicate average values of the antenna temperature and their standard deviation for 10 seconds, respectively.

by small instrumental ﬂuctuations in the gain and noise temperature and was added to the uncertainty of the ﬂux density of JSR. A primary or secondary ﬂux calibrator (3C348 and 3C353)41 was also measured every few JSR observations in order to calibrate the absolute ﬂux density of JSR. The ﬂux densities were corrected at the distance of 4.04 AU from Jupiter. Because of the tilt of Jupiter’s magnetic axis (∼10 degrees with respect to the spin axis) and the anisotropic directivity of JSR, the total ﬂux shows a ten-hour modulation with ∼ ±10% amplitude as Jupiter rotates, which is referred to as the beaming curve. Due to the elevation limit of IPRT (22◦ ) and low declination of Jupiter in 2007 (∼ −22◦ ), the number of drift scans at each frequency was at most 4–5 times during each ∼4-hour observation in a day. To investigate the short-term variations in JSR, the beaming curve is sometimes compensated by using a reference beaming curve.16, 17, 20, 42 In this study, we used the empirical beaming curve for the case of DE = −2.9◦ , which was obtained from an observation at 2.3 GHz.40 It is reported that the beaming curve measured at 333 MHz is similar to the one measured at 2.3 GHz.43 After the correction, the observed ﬂux densities were averaged over one day.

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The receiver system for 785 MHz measured only the horizontal linear polarized component, as described in Sec. 2. Because JSR is known to have a linearly polarized component of 20–25%,5 observation with a linear dipole would cause an apparent variation in JSR depending on the angle between the dipole element and the direction of linear polarization. Hence, an uncertainty of 25% was added to the observed ﬂux density at 785 MHz. 4. Results and Discussion The result of the total ﬂux observation is shown in Fig. 3. Panels (a) and (b) in the ﬁgure show the total ﬂux densities of JSR observed by IPRT at 325

Fig. 3. Variations in ﬂux density of JSR at (a) 325 MHz, (b) 785 MHz, and (c) 2.3 GHz during the period between 5 May (DOY 130) and 8 July (DOY 190) 2007. Shaded portions indicate periods when increases in the ﬂux density of JSR occurred. (d) Solar F10.7 ﬂux which is used as an index of the solar UV/EUV ﬂux. The time axis is shifted to take account of the diﬀerence in heliocentric longitude between the Earth and Jupiter (see text for an explanation). (e) Dynamic pressure of the solar wind extrapolated at Jupiter using a 1-D MHD simulation of the solar wind.

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and 785 MHz, respectively. The ﬂux densities at both frequencies showed similar short-term variations around DOY 145 and between DOY 152 and 170, although not all of the time variations were synchronized with each other. The ﬂux density at 2.3 GHz (Fig. 3 (c)) also tended to have a small increase and subsequent decrease during the period between DOY 157 and 162. The amplitudes of the variations at 325 and 785 MHz were ±20–30%, which are larger than those at 2.3 GHz. The variations in JSR which are independent of the observed frequency imply that the short-term variations are caused by energy-independent processes in the radiation belt. One of the possible explanations is enhancement of radial diﬀusion driven by the neutral wind in the upper atmosphere. The radial diﬀusion process is driven by the perturbations of magnetic and/or electric ﬁelds. In Jupiter’s inner magnetosphere, ﬂuctuating electric ﬁelds are thought to be generated in the ionosphere through a dynamo process induced by the atmospheric neutral wind. Brice and McDonough27 proposed that this process dominates the radial diﬀusion in Jupiter’s radiation belt and has a weak energy dependence. It is predicted that the neutral wind may be induced by solar UV/EUV heating.27 If more trapped electrons move inward as a result of enhanced radial diﬀusion and are accelerated adiabatically, the ﬂux density of JSR should increase. This idea is supported by previous observations made at 2.3 GHz12, 19 in which the ﬂux density of JSR increased immediately after an increase in solar F10.7 ﬂux (The solar F10.7 ﬂux has been used as an index of the solar UV/EUV ﬂux). Fig. 3 (d) shows the solar F10.7 ﬂux during the observation period. To predict the solar F10.7 ﬂux at the position of Jupiter, the time axis of F10.7 is shifted to take account of the diﬀerence in heliocentric longitude between the Earth and Jupiter under the assumption that the enhanced F10.7 ﬂux was emitted with some directivity from a long-lived compact active region corotating with the sun.19 The ﬂux increases starting from DOY 146 and 156 were preceded by those of F10.7 by several days. On the basis of the large time delay, we may conclude at this stage that ﬂux variations in JSR during our observations can not be explained by the enhanced radial diﬀusion scenario. Another possible interpretation comes from comparisons of the ﬂux variation o JSR and the dynamic pressure of the solar wind. The dynamic pressure of the solar wind shown in Fig. 3(e) was extrapolated from the solar wind observation made by the ACE spacecraft at 1 AU from the sun by using a 1-D MHD model.44 Tao et al.44 compared the solar

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wind proﬁle at Jupiter’s orbit from the MHD simulation with actual data measured by the Ulysses spacecraft and found that pressure pulses with large amplitudes of >0.25 nPa were reasonably well predicted. The prediction error of the MHD simulation was at most 2 days when the separation of the heliocentric longitude between the Earth and Ulysses was less than 50◦ . During the period shown in Fig. 3, the longitude diﬀerence between the Earth and Jupiter was less than 30◦ . The shaded regions in Figs. 3(a) and (b) show the periods when the ﬂux increases were observed. The ﬂux increases starting from DOY 146, 156, and 172 seem to coincide with abrupt increases in the dynamic pressure of the solar wind within the prediction error of 2 days. If this relation is real, it suggests to us the interesting possibility that the solar wind inﬂuence was responsible for short-term variations in JSR on time scales of a few days to a week. However, it is still not known whether the inner part of the Jupiter’s radiation belt can respond to changes in the solar wind activity in such a short time period. The observations of JSR at IPRT indicate that the short-term variations in the low frequency range are controversial and that various mechanisms contribute to their generation. Further continuous observations of JSR are needed to elucidate the behavior of the short-term variation at low frequencies. A series of interferometer observations which was made simultaneously with GMRT is intended to reveal the spatial distribution and time variation of JSR, and they may provide key information on the cause of the short-term variation. Comparisons of the total ﬂux observation presented in this paper and the interferometer observations are now underway.

5. Summary We made observations of JSR with IPRT (325 and 785 MHz) between May and July 2007 and at NICT (2.3 GHz) during June 2007, as part of the simultaneous spectrum and interferometer observation campaign. We found that the total ﬂux densities of JSR show a short-term variation with a time scale of a few days and not all of the time variations observed at 325 and 785 MHz were synchronized with each other. The amplitude of the variations of JSR was larger than those of the previous observations made at a few GHz. The characteristics of the short-term variation in the lowfrequency range seem to be complex and imply that various mechanisms contribute to the short-term variation.

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Acknowledgments We are grateful to C. Tao for providing solar wind dynamic pressure data. The solar F10.7 ﬂux data was provided by the National Oceanic and Atmospheric Administration of the United States. Heliocentric position data for the Earth and Jupiter were provided by the JPL HORIZONS on-line solar system data and ephemeris computation service.

References 1. R. M. Sloanaker, Astron. J. 64 (1959) 346. 2. I. de Pater, M. Schulz and S. H. Brecht, J. Geophys. Res. 102 (1997) 22043. 3. R. J. Sault, T. Oosterloo, G. A. Dulk and Y. Leblanc, Astron. Astrophys. 324 (1997) 1190. 4. S. J. Bolton, S. M. Levin, S. L. Gulkis, M. J. Klein, R. J. Sault, B. Bhattacharya, R. M. Thorne, G. A. Dulk and Y. Leblanc, Geophys. Res. Lett. 28 (2001) 907. 5. T. D. Carr, M. D. Desch and J. K. Alexander, in Physics of the Jovian Magnetosphere, (Cambridge University Press, New York, 1983). 6. I. de Pater, B. J. Butler, D. A. Green, R. Strom, R. Millan, M. J. Klein, M. K. Bird, O. Funke, J. Neidh¨ ofer, R. Maddalena, R. J. Sault, M. Kesteven, D. P. Smits and R. Hunstead, Icarus 163 (2003) 434. 7. S. J. Bolton, S. Gulkis, M. J. Klein, I. de Pater and T. J. Thompson, J. Geophys. Res. 94 (1989) 121. 8. I. de Pater, J. Geophys. Res. 99 (1994) 2271. 9. S. J. Bolton, M. Janssen, R. Thorne, S. Levin, M. Klein, S. Gulkis, T. Bastian, R. Sault, C. Elachi, M. Hofstadter, A. Bunker, G. Dulk, E. Gudim, G. Hamilton, W. T. K. Johnson, Y. Leblanc, O. Liepack, R. McLeod, J. Roller, L. Roth and R. West, Nature 415 (2002) 987. 10. D. E. Dunn, I. de Pater and R. J. Sault, Icarus 165 (2003) 121. 11. A. Sicard and S. Bourdarie, J. Geophys. Res. 109 (2004) A02216. 12. D. Santos-Costa, S. J. Bolton, R. M. Thorne, Y. Miyoshi and S. M. Levin, J. Geophys. Res. 113 (2008) A01204. 13. E. Gerard, Astron. Astrophys. 8 (1970) 181. 14. E. Gerard, Radio Sci. 5 (1970) 513. 15. M. J. Klein, S. Gulkis and C. T. Stelzried, Astrophys. J. 176 (1972) L85. 16. P. H. M. Galopeau, E. Gerard and A. Lecacheux, ICARUS 121 (1996) 469. 17. P. H. M. Galopeau, E. Gerard and A. Lecacheux, Planet. Space Sci. 45 (1997) 1197. 18. M. Klein, S. Gulkis and S. J. Bolton, in Planetary Radio Emission IV, (Austrian Academy Sci., Wien, 1997). 19. Y. Miyoshi, H. Misawa, A. Morioka, T. Kondo, Y. Koyama and J. Nakajima, Geophys. Res. Lett. 26 (1999) 9. 20. H. Misawa and A. Morioka, Adv. Space Res. 26 (2000) 1537. 21. P. H. M. Galopeau and E. Gerard, Planet. Space Sci. 49 (2001) 1379.

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22. S. Nomura, Doctor thesis, (Tohoku University, Sendai, 2007). 23. A. W. Schardt and C. K. Goertz, in Physics of the Jovian Magnetosphere, (Cambridge University Press, New York, 1983). 24. I. de Pater, in Perspectives on Radio Astronomy: Science with Large Antenna Arrays, (M. P., ASTRON, Dwingeloo, 1999). 25. S. Nomura, H. Misawa, F. Tsuchiya and A. Morioka, in Abstract of Magnetospheres of the Outer Planets Meeting, (San Antonio, 2007). 26. S. J. Bolton, R. M. Thorne, S. Bourdarie, I. de Pater and B. Mauk, in Jupiter The Planet, Satellites and Magnetosphere, (Cambridge University Press, New York, 2004). 27. N. M. Brice and T. R. McDonough, Icarus 18 (1973) 206. 28. D. Santos-Costa and S. A. Bourdarie, Planet. Space Sci. 49 (2001) 303. 29. D. Santos-Costa and S. J. Bolton, Planet. Space Sci. 56 (2008) 326. 30. H. Misawa, A. Morioka, F. Tsuchiya, Y. Miyoshi, T. Watanabe, R. Kudo and T. Kondo, Proc. of the 34th ISAS Lunar and Planet. Symp. 175 (2001). 31. F. Tsuchiya, H. Misawa, Y. Miyoshi, T. Watanabe, R. Kudo, A. Morioka and T. Kondo, Proc. 35th ISAS Lunar and Planet. Symp. 211 (2002). 32. H. Misawa, R. Kudo, F. Tsuchiya, A. Morioka and T. Kondo, Proc. 3rd CRL TDC Symp. 57 (2003). 33. F. Tsuchiya, H. Misawa, R. Kudo, Y. Miyoshi, T. Watanabe, A. Morioka and T. Kondo, Proc. 36th ISAS Lunar Planet. Symp. 222 (2003). 34. K. Imai, H. Misawa, F. Tsuchiya, A. Morioka, T. Watanabe and R. Kudo, Proc. 39th ISAS Lunar and Planet. Symp. (2006). 35. H. Misawa, K. Imai, A. Bhardwaj, F. Tsuchiya, A. Morioka and T. Kondo, in Abstract of the fifth meeting of the Asia Oceania Geosciences Society, (Busan, 2008). 36. K. Imai, H. Misawa, A. Bhardwaj, F. Tsuchiya, A. Dio, T. Kondo and A. Morioka, in Abstract of 37th COSPAR Scientific Assembly, (Montreal, 2008). 37. H. Misawa, A. Morioka, F. Tsuchiya, Y. Miyoshi and T. Kondo, Proc. 35th ISAS Lunar and Planet. Symp. 207 (2002). 38. T. Watanabe, H. Misawa, T. Tsuchiya, Y. Miyoshi, T. Abe and A. Morioka, Tohoku Geophys. J. 37 (2005) 1. 39. Agilent Technology Inc., Application Note 57–2 (2004). 40. M. J. Klein, S. Gulkis and S. J. Bolton, in Time Variable Phenomena in the Jovian System, (NASA Spac, Publ., SP-494, 1989). 41. J. W. M. Baars, R. Genzel, I. I. K. Pauliny-Toth and A. Witzel, Astron. Astrophys. 61 (1977) 99. 42. G. A. Dulk, Y. Leblanc and R. W. Hunstead, Geophys. Res. Lett. 22 (1995) 1789. 43. I. de Pater, Astron. J. 102 (1991) 795. 44. C. Tao, R. Kataoka, H, Fukunishi, Y. Takahashi and T. Yokoyama, J. Geophys. Res. 110 (2005) A11208.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

STUDIES OF THE INTERIOR STRUCTURE OF PLANETARY BODIES BY LASER ALTIMETRY C. KOCH∗ , R. KALLENBACH† , U. R. CHRISTENSEN and M. HILCHENBACH Max Planck Institute for Solar System Research, D-37191 Katlenburg-Lindau, Germany ∗ [email protected] † [email protected] www.mps.mpg.de

Laser altimetry is a powerful tool to map planetary surfaces. In addition to the static topography, time-dependent variations such as libration and tidal elevation can be extracted from laser altimeter data in order to investigate the internal structure of the planetary body. In the frame of the BepiColombo Laser Altimeter (BELA) project, we have carried out numerical simulations in order to estimate the uncertainty of the tidal and forced libration amplitudes of Mercury’s surface to be extracted from topography data. The simulation results demonstrate that it seems feasible to test current models on the state and the size of Mercury’s core with suﬃcient precision. Laser altimeters will also be applied during future missions to the satellites of the giant planets Jupiter and/or Saturn. Particularly interesting is the question on the existence and nature of subsurface oceans of these satellites. The measurement precision and scientiﬁc return achievable with a new generation of altimeter applying miniaturized diode laser-pumped solid-state lasers pulsed with kHz repetition rate and a single photon counting technique are explored.

1. Introduction Geodetic observations of the gravity ﬁeld, the rotational state, and the tides of terrestrial planetary bodies from orbiting spacecraft put constraints on the deep interior structure of these bodies.1 The low-degree gravity ﬁeld of a terrestrial planet gives information on the diﬀerences of the principal moments of inertia, and consequently on the interior mass distribution. Determination of the amplitude of forced libration and of the moment of inertia factor reveals whether the mantle can slip with respect to the core. This indicates whether the core is liquid or at least partly liquid.2 Timedependent tidal elevations or mass displacements caused by the gravitation 613

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of the Sun or another planet depend on the material properties deeply inside the planetary body. Therefore, the tidal Love number k2 , characterizing the additional gravitational potential due to displaced mass relative to the tide generating potential, provides information on the state of material inside a planetary body. Similarly, the tidal Love number h2 , representing the vertical displacement of the planetary surface relative to the height of the tidally unperturbed geoid, is key to study the planetary interior. During future planetary missions, all geodetic observations have to be analysed together in order to establish a clear understanding of the planetary interior. In particular, determination of the tidal Love number h2 provides information on the planetary interior which cannot be retrieved from the tidal Love number k2 and the principal moments of inertia alone. In the case of Mercury, both Love numbers, k2 and h2 , need to be known in order to derive estimates on the core radius, its stage of thermal evolution, and on the initial sulphur content of the planet.3 In the case of the icy satellites of the giant planets, a large Love number h2 is the key indicator for a subsurface ocean. The thickness of an ice shell above a subsurface ocean can be derived from the ratio h2 /k2 .4 Laser altimetry applied to any of these planetary bodies requires precise determination of the spacecraft orbit and the tidally perturbed planetary reference surface by radio doppler tracking5 at ﬁrst, which in turn leads to the determination of the Love number k2 . The upcoming studies on the interior structure of Mercury are motivated by the observation of the weak global magnetic ﬁeld during the three ﬂybys by Mariner 10 in 1974/75. This magnetic ﬁeld could be generated by a dynamo process which requires at least a partly liquid core. Mercury is the terrestrial planet with the highest uncompressed density suggesting a high metal-to-silicate ratio of about 0.6.6 Thermal evolution models7–9 suggest that Mercury is diﬀerentiated into a solid pure iron core with a radius of approximately 0.75 times the planetary radius and a liquid outer core consisting of an iron-sulphur eutectic. From ground-based radar interferometry, Margot et al. (2007) have already found evidence for Mercury’s core being partly liquid.10 They have determined the amplitude of the 88-day forced libration Φlib due to solar torques on Mercury’s aspherical mass distribution. From the value Φlib = (35.8 ± 2.0) arcsec and from moments of inertia derived from Mariner 10 observations,11 Margot et al. (2007) conclude that Mercury’s solid mantle slips at the core-mantle boundary, which suggests that Mercury has a liquid outer core.10 From precise values for the Love numbers h2 and k2 , the radius of the core as well as the initial sulphur content and the thermal evolution stage of Mercury could be inferred.

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The envisaged studies of the icy satellites of Jupiter and Saturn are motivated by the search for extraterrestrial life. Moore and Schubert,12 Tobie et al.,13 Sohl et al.14 (2003), Hurford et al.15 (2007), Mitri et al.,16 and Rappaport et al.17 (2008) predict the existence of subsurface water oceans which may host life. Hussmann et al.18 (2006) provide a more complete analysis under which conditions globe-encircling liquid reservoirs could also have survived to the present day on mid-sized icy satellites and large Kuiper belt objects. The ﬁrst step to get insight into these planetary bodies is the determination of the gravity coeﬃcients, Love numbers, and libration amplitudes by geodetic observations. At present, no information is available on the tidal Love number h2 of the diﬀerent terrestrial planetary bodies except for the Earth, where h2 = 0.617 ± 0.007 has been determined from data sets of the global Very Large Baseline Interferometer (VLBI) system.19 However, the values of the parameter k2 have been determined for Venus and for Mars from radio doppler tracking of the Magellan and Pioneer Venus Orbiters and of the Mars Global Surveyor spacecraft, respectively. Yoder et al. (2003)20 concluded from the value k2 = 0.153 ± 0.017 and from the planet’s polar moment of inertia factor that the core of Mars has a radius of 1,680±160 km and that it is not completely solid. For Venus, Konopliv and Yoder (1996)21 concluded from the value k2 = 0.295 ± 0.066 that its core is liquid. Further determination of key tidal parameters would provide the most reliable constraints on Venus’ deep interior since a determination of the axial moment of inertia from the planet’s precession rate is very diﬃcult. This is because Venus rotates very slowly and its rotation axis is aligned almost perpendicular to the orbital plane. In this article, we report on the prospects of determining the tidal Love number h2 and the amplitude Φlib of forced libration of planetary bodies by laser altimetry from orbiting spacecraft. In the frame of the upcoming BepiColombo mission to Mercury we build laser ﬂight hardware as part of the BepiColombo Laser Altimeter BELA.22 The measurement of Mercury’s tidal Love number h2 is one of the most interesting science objectives to be achieved with the BELA instrument, and the measurement of Mercury’s forced libration amplitude is envisaged to complement the measurement by Margot et al.10 (2007). In the frame of missions to the giant planets proposed as part of ESA’s Cosmic Vision Programme,23, 24 it has been proposed to apply laser altimetry to measure the tidal Love numbers h2 of icy satellites such as Europa, Ganymede, or Enceladus. For all these planetary bodies, the tidal elevation of the solid surface is rather large, if there is a liquid layer in the

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interior, while the tidal elevation is very small, if the interior is entirely solid. It will also be of great interest to measure the libration amplitudes of these icy satellites,25 which also should be feasible with high precision by using extraction techniques of laser altimetry data by Koch et al.26 (2008). In the following, we present two techniques to study the interior of planetary bodies by retrieving time-dependent topography data from laser alti-meter data records: • The simultaneous extraction of the static topography expressed in form of a spherical harmonic expansion and the time-dependent libration and tidal elevation from laser altimeter data records densely covering the planetary surface. • The extraction of the tidal Love number h2 from observations at crossing points of the spacecraft ground tracks on the planetary surface. If the spacecraft passes these points at times of diﬀerent tidal phase angles, the tidal amplitude can be calculated from the diﬀerence of the topographic measurements at these points. The ﬁrst technique has been tested extensively in simulations by Koch et al.26 (2008) for the case of the BepiColombo mission to Mercury carrying the BELA laser alti-meter on board the Mercury Planetary Orbiter MPO. Such simulations have not been carried out in detail for the cases of the icy satellites of Jupiter and Saturn, but the technique is expected to work equally well if the spacecraft ground-tracks cover the planetary surface densely. The second technique is ﬁrst applied to the case of Mercury as well, and then we explore the potential of this technique for studies of the icy satellites of the giant planets. The measurement precision achievable with laser altimetry is also discussed in the context of alternative and complementary methods. 2. Simultaneous Extraction of Static and Time-Dependent Topography of Mercury from Synthetic BELA Data Two space missions will explore Mercury in the next two decades, with elucidating Mercury’s internal structure as one of their primary goals. NASA’s MESSENGER mission has executed its ﬁrst ﬂyby and will enter a highly elliptical orbit in 2011.6 The BepiColombo mission of the European and Japanese Space agencies (ESA and JAXA, respectively) will be launched in 2013, to reach Mercury in 2019 and put two spacecraft into

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orbit.27 ESA’s Mercury Planetary Orbiter (MPO), one of the two orbiters of BepiColombo, is particularly well suited for mapping the global topography because it will have an only moderately elliptical near-polar orbit with 400 km and 1,500 km minimum and maximum altitudes above Mercury’s surface, respectively. During its pass from the Southern to the Northern polar regions, MPO will remain at altitudes below 1,000 km at which operation of BELA22 is feasible. MPO’s short orbital period of 2.33 hrs results in a fairly small mean longitudinal separation of laser ground tracks of order 6 km within the nominal mission duration of one Earth year or four Mercury years, respectively. For Mercury, the tidal Love numbers h2 and k2 have been predicted by van Hoolst and Jacobs3 (2003) to be 0.7 and 0.4, respectively, if the core is partly liquid. The Love number h2 ≈ 0.7 corresponds to a tidal amplitude of about 1.5 meters at Mercury’s equator. Further information about Mercury’s interior can be retrieved from the libration amplitude caused by the torque of the solar gravitation on the non-spherical mass distribution of the planet. The libration amplitude, in combination with low-order coeﬃcients of the gravity potential derived from radio doppler tracking5 and the obliquity of the rotation axis, allows to constrain the ratio of the moment of inertia of the solid mantle alone to that of the entire planet, provided the mantle is mechanically decoupled from the core.2, 28 With the aim to model the potential science return from the BepiColombo mission to Mercury, Koch et al. (2008)26 have simulated the simultaneous extraction of the static long-wavelength topography, the tidal Love number h2 , and the libration amplitude Φlib from synthetic data of BELA. With this technique, the static topography has been retrieved in form of a spherical harmonic expansion up to order 64 with typical uncertainties of a few centimeters in its expansion coeﬃcients (Fig. 1, upper panel). The tidal Love number (Fig. 1, center) and the libration amplitude (Fig. 1, lower panel) have been retrieved with a precision of a few percent. In these simulations, the synthetic Hermean topography has been approximated by a spherical harmonic expansion with degree power Vl =

A2 , l2

A ≈ 2000 m;

(1)

see Fig. 1, upper panel, for the adjacent degree amplitude. The degree power l 2 2 is deﬁned as Vl = m=0 (Clm +Slm ), where Clm and Slm are the coeﬃcients of a spherical harmonic expansion. The harmonic degree is l, while the index m numbers the trigonometric functions describing the azimuthal variation

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0.1 0.08 0.06 ∆ h2

0.04

0.02

0.01 20

30

40 linv

50

60 70

6.0

∆Φlib [arcsec]

5.0 4.0 3.0

2.0 20

30

40 linv

50

60 70

Fig. 1. Upper panel: Spherical harmonic degree amplitude of the simulated static input topography of Mercury (·) and degree error after extraction from simulated BELA measurements assuming uniform surface coverage (∗). Center panel: Errors of the Love number (h2,input = 0.7) vs. maximum harmonic degree of inversion for a resonant spacecraft orbit (∆) i.e. 910 orbital periods of MPO corresponding to exactly one Mercury year and a non-resonant orbit, i.e. 909.234 orbits corresponding to one Mercury year, for the case of BELA measurements from all spacecraft altitudes () and for the case that measurements are only possible at altitudes below 1,000 km (♦). Lower panel: The same for the libration amplitude (Φlib,input = 40 arcsec). The lines represent linear regressions.

of the spherical harmonic basis functions. For the lower harmonic degrees, the topography expansion of Eq. (1) resembles the lunar topography.29, 30 Details of the technique and the error analysis can be found in Koch et al. (2008).26 The simulations had been based on the assumption that the measurement uncertainty is of purely statistical nature with a Gaussian distribution. So far, no systematic bias in the spacecraft orbital data, or insolation eﬀects on the laser altimeter, such as thermoelastic bending, have been included in the simulations. Great care is taken in the hardware development to reduce such systematic errors. The inﬂuence of various

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parameters such as instrument temperature or spacecraft pointing has been modelled but not published yet as part of the BELA laser hardware project. 3. Tidal Elevation Measurement at Orbit Crossing Points The simultaneous extraction of the static topography, the tidal Love number h2 , and the amplitude of forced libration Φlib from laser altimeter data records is not possible for missions where the planetary surface is not fully covered by spacecraft ground tracks. However, during such missions the orbit crossing point technique for extracting the tidal Love number h2 (the second technique mentioned in Section 1) is still applicable. It may be used to evaluate data of the MESSENGER laser altimeter or of laser altimeters on board spacecraft not orbiting but only repeatedly ﬂying by the icy satellites of the giant planets such as Ganymede, Callisto, Titan, or Enceladus.23, 24 As an example, we evaluate topographic diﬀerence measurements at BepiColombo’s MPO orbit crossing points. These are concentrated in the polar regions of Mercury, where the Sun excites a tidal amplitude of order 60 cm because of Mercury’s eccentric orbit (e = 0.20563), provided that Mercury’s core is partly liquid. The precision to which this amplitude can be measured depends on three main error sources: • The measurement of the topographic height at the laser footprint has an experimental uncertainty ∆Tmeas. • The topographic height at an orbit crossing point has to be estimated from an interpolation between the neighboring laser footprints spaced by intervals L ≈ 300 m. The interpolation uncertainty ∆Tint only includes scales k ≤ kB = π/L i.e. all spatial frequencies below the Nyquist limit. • In addition, there is an uncertainty ∆TSST related to the unknown smallscale topography (SST) at spatial frequencies above the Nyquist limit kB . The ﬁrst uncertainty is of order ∆Tmeas ≈ 1 m and mainly depends on the timing resolution of the BELA instrument and on the typical slopes on Mercury. Gardner et al.31 (1992) has shown that the inﬂuence of pointing jitter can be neglected in the analysis of laser shots. The spacecraft position will be determined with tens of cm precision from post-processing of radio doppler tracking data.5 The remaining range uncertainty after correction for the measured oﬀ-nadir angles of the MPO spacecraft can also be neglected. The two other uncertainties mentioned above are functions of the distance ∆Li/j between the crossing point and the next laser footprints

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on the crossing ground tracks numbered i and j and need to be evaluated in more detail. We begin with the discussion of the small-scale topography. 3.1. Uncertainty due to small-scale topography The small-scale topography of Mercury has not been analyzed quantitatively yet. Mercury is geologically old, and erosion is weak due to the lack of a signiﬁcant atmosphere. The surface of Mercury may be similar to the surfaces of the Moon or the rough surfaces of the Southern Highlands of Mars. In the simulations by Koch et al. (2008),26 the Hermean topography has been approximated by a degree power (Eq. 1) that agrees with that of the lunar topography at low spherical harmonic degrees. Figure 2 shows a comparison of the power spectral density of the lunar topography with that of two types of Martian topographies. For the latter, Aharonson et al. (2001)32 have determined the power spectral densities from data of the MOLA laser altimeter on board the Mars Global Surveyor spacecraft. The Southern Highlands (Fig. 2, region A), are geologically old and thus heavily cratered, while the Northern Lowlands (Fig. 2, region B), which resemble an ocean ﬂoor dominated by geological features from sedimentation, are much smoother. We see from Fig. 2 that the topographic power spectral density at large scales of the Southern Highlands of Mars is a factor of 2–3 below the lunar power spectral density. Kreslavsky et al. (2008)33 found from studies of the surface roughness of the Moon, Mercury, Mars, and Venus that the surface of Mercury is about as rough as the Southern Highlands of Mars but not as rough as the surface of the Moon. The roll-over from a power law with exponent −2 to a steeper power law at a scale of about 3 km (Fig. 2) is similar for the Moon, Mercury, and the Southern Highlands of Mars. We therefore can approach the power spectral density at scales smaller than 3 km on Mercury with the power law that describes the topography of the Southern Highlands of Mars: PSST (k) = P0 k −β ;

P0 ≈ 10−4 m3−β ,

(2)

where β ≈ 3.4, and k is 2π/λ with λ the scale size. The uncertainty for a topography measurement at a crossing point introduced by the small-scale topography TSST (x) depends on the distances ∆Li and ∆Lj from a crossing point to the next measurement locations belonging to the crossing spacecraft tracks i and j. If L is the distance

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Fig. 2. Power spectral density of the topography of two types of regions on the Martian surface.32 The geologically old Southern Highlands (Region A) have a much larger power spectral density than the Northern Lowlands (Region B) which are dominated by sedimentation. At large scales, the power spectral density of the Martian Southern Highlands has the same spectral index as the lunar topography, but the power spectral density of the large-scale lunar topography is still somewhat larger. The lunar large-scale topography can be described by the degree power Vl (Eq. 1) of a spherical harmonic expansion, where l is the harmonic degree. This degree power has been used in the simulations by Koch et al. (2008),26 see Fig. 1, upper panel.

between two consecutive laser shots of BELA, the uncertainty in the determination of the topographic height at the crossing point derived from one spacecraft track is (see Appendix A) CB (β)RB,0 (L − ∆L)2 (3) ∆TSST ≤ (kB ∆L) 2 ∆L2 + (L − ∆L) with CB (β) =

β , β−3

RB,0 =

1−β P0 kB , π β−1

kB =

π , L

(4)

where β is assumed to be larger than 3. For β = 3.4 and P0 given above, this yields approximately ∆TSST < 5 m.

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3.2. Interpolation uncertainty The uncertainty of a Polynomial interpolation of the large-scale topography (k ≤ kB ) at an orbit crossing point is estimated by standard methods:34 (n+1)

TLST (¯ x) − Q0 1 ··· n (¯ x) =

ω(¯ x) · TLST (ξ) , (n + 1)!

(5)

x) is a polynom of degree n interpolating n + 1 topographic where Q0 1 ··· n (¯ measurements on one ground track next to the orbit crossing point and ω(¯ x) a standard remainder term. The large-scale topography TLST only includes scales k ≤ kB = π/L i.e. all spatial frequencies below the Nyquist limit. The uncertainties which result from using the power spectral density derived from the Southern Highlands of Mars are listed in Appendix B for degrees n = 1, n = 2, and n = 3. 3.3. Uncertainty in the measured tidal Love number Figure 3 shows the diﬀerent contributions to the measurement uncertainty at a single orbit crossing point. We ﬁnd that the uncertainty is dominated by

Fig. 3. Contributions to the measurement uncertainty vs. the distance of the crossing point to the closest observation ∆L: positioning uncertainty (dotted line), range uncertainty (dashed line), uncertainty related to the small-scale topography (SST, ×), and interpolation error () for the linear case (n = 1, dashed line), for a quadratic expression (n = 2, dashed-dotted line), and for a cubic expression (n = 3, solid line).

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the small-scale topography and the interpolation uncertainty, if we assume the laser shot repetition rate and instrumental uncertainties of BELA. Only when the crossing point is very close to a measurement point, the positioning and range uncertainty play a role. The tidal Love number can be calculated from an average of all topographic diﬀerence measurements at all possible orbit crossing points. For each crossing point, we assume the typical uncertainty given in the previous subsections. To estimate the mean uncertainty, we need to know the eﬀective number N of orbit crossing points during the mission time of BepiColombo. The mission nominally lasts I = 4 Mercury years. Approximately J = 910 satellite tracks map the surface within one Mercury year. However, only the tracks close to Mercury’s peri — and apohelion are used because the diﬀerence in the tidal elevation is largest there. This reduces the number of orbits to roughly J = 455. Each of these orbit tracks crosses each other so that the number of crossing points is N ≈ IJ 2 . We assume the worst case, a range uncertainty of 1 m, and the maximum distance ∆L1/2 = 150 m from the crossing points to the measurement points. For the quadratic interpolation the uncertainty is 8.2 m. This number includes all uncertainties that contribute to a single measurement at a crossing point (Fig. 3) and also takes into account that two measurements from two diﬀerent tracks are necessary to derive a topographic diﬀerence measurement. The resulting uncertainties of the averaged diﬀerence measurements at all orbit crossing points i.e. of the measurement of the tidal amplitude Atide adds up to 9 mm after the nominal mission time of 4 Mercury years. If we take a conservative estimate of 30 cm for the tidal amplitude at Mercury’s poles, we arrive at a relative uncertainty of 3%. After an extended mission time of 8 Mercury years, the precision of the measurement could become better than 2%. Note, that orbit crossing points, where the diﬀerence of the tidal elevation is close to zero, can be used for range calibration.

4. Prospects for Missions in the Frame of ESA’s Cosmic Vision Programme A precision of 3% in the determination of the tidal Love number h2 is suﬃcient to test models on the interior structure of Mercury.3 In the case of BELA data, the precision is mainly limited due to uncertainties in the small-scale topography. These uncertainties could be substantially reduced if the spacing of laser shots L could be reduced. This spacing is given

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by the repetition rate of the laser which is 10 Hz for BELA. For future planetary missions, laser alti-meters with a single-photon detection scheme are developed.35 Rather than measuring the time of ﬂight between the laser shot and typically 1,000 photons reﬂected oﬀ the planetary surface, only one returned photon per shot will trigger the time-of-ﬂight measurement. This has several advantages: • With the same power resources the laser pulse energy can be reduced by a factor of 1,000, while the laser shot repetition rate can be increased by a factor of 1,000. • Rather than converting the analog photo-current signal of the Avalanche Photodiode (APD) to a digital signal in time, a discriminator technique can be applied which is much less power-consuming. • The time and thus the range resolution can be improved because the lasers with lower pulse energy can be realized with shorter pulses e.g. 300 ps instead of 3 ns. Future missions may have more restrictions regarding resources in power and mass, so that rather a diode-pumped microchip Nd:YAG laser will be applied at even lower mean power. A typical re-scaling of the BELA instrument parameters to design a laser altimeter to be applied on missions in the frame of the Cosmic Vision Programme is shown in Table 1. The measurement precision of such a re-scaled laser altimeter is not exactly evaluated yet, but it is apparent that the inﬂuence of small-scale topography and interpolation errors is reduced by about the same factor as the increase in the repetition rate. Table 1. Parameters for the presently implemented BepiColombo laser altimeter (BELA) and for future laser altimeters employing microchip lasers and single-photon detection.

Pulse energy [mJ] Repetition rate [kHz] Pulse width [ns] Range resolution [ns] Power [W] Mass [kg] a Proposed

BELA22

Cosmic visiona

50 0.01 3 0.5 40 11

0.01 10 0.3 0.05b 7 <5c

by the BELA team. shot without averaging measurements. c Including shielding for 1 MRad radiation. b Single

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The measurement precision will then ultimately be determined by the positioning and range uncertainty. Shorter pulses of the laser should allow for a reduction of the range uncertainty to the cm-level. It will be a big challenge to determine the position of the spacecraft with such high accuracy. It may be feasible to determine spacecraft positions with the global Very Large Baseline Interferometer system of radio antennas. Alternatively, altitude calibrations may be possible at orbit crossing points themselves. Preliminarily, the precision of a single measurement can be expected to be of order 0.05 m. After averaging all measurements from all crossing points, much larger precision should be attainable if the spacecraft orbit is well chosen for this purpose. Typically, 100 orbit crossing points would be necessary to achieve a measurement precision of about 1 cm. Ultimately, the preferred mission scenario includes a dense coverage of the planetary surface so that the technique described in Koch et al. (2008)26 can be applied. Likely targets of missions in the frame of ESA’s Cosmic Vision Programme are the satellites of the giant planets, such as Europa or Ganymede in the Jovian system and Titan and Enceladus in the Kronian system. In the Jovian system, Io, Europa, and Ganymede are locked into the well-known Laplace resonance, and tides are caused by Jupiter’s gravity on the icy surfaces of Europa or Ganymede. These two satellites may be visited in the frame of the mission originally proposed by Blanc et al. (2005).23 The scientiﬁc return of the measurement of the tidal elevation on the satellites of Jupiter has been modelled extensively by Wu et al. (2001),4 Moore and Schubert (2003),12 and Tobie et al. (2003).13 The prime goal is to ﬁnd out whether the icy satellites have a subsurface ocean and how deep these oceans are. Predicted typical tidal elevations on the icy surfaces of the Jovian satellites are listed in Table 2 for the two cases “ocean” and “no ocean”. It will also be important for scientiﬁc purpose but also for future missions to know how thick are the ice crusts covering the oceans. For the Table 2. Tidal elevation amplitudes of the icy satellites of Jupiter12, 13 and of Saturn.14–18

Europa Ganymede Callisto Titan Enceladus

No ocean

Ocean

0.1 m 0.5 m 0.3 m 1.0 m 0.01 m

30 m 7m 5m 15 m 5m

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case of Europa, Wu et al. (2001)4 have estimated that a measurement of the two tidal Love numbers h2 and k2 from a combination of altimetry and spacecraft position tracking with permil precision would be required to resolve the ice shell thickness to about 1 km. For Europa, the requirement for permil precision in the measurement of the tidal amplitude would correspond to an instrumental resolution of 3 cm, or equivalently to a timing resolution of 100 ps for a single laser shot. Assuming Gaussian distribution of the timing uncertainty one would need to average 10 measurements with a timing resolution of 0.3 ns. Table 2 also lists theoretical predictions for the tidal amplitudes of Titan and Enceladus14–18 which may be visited by a mission proposed by Coustenis et al. (2008)24 in the frame of ESA’s Cosmic Vision Programme. 5. Conclusions In the case of Mercury, the achievable precision for retrieval of the tidal Love number h2 has been estimated for two techniques. When the tidal Love number h2 is retrieved simultaneously with the spherical harmonic coeﬃcients of the static topography, an uncertainty of less than 10% at the 2σ-level can be expected, provided that BELA continuously takes data during the nominal mission duration of approximately four Mercury years. This is valid even in the case that data can only be taken at spacecraft altitudes of less than 1,000 km above the planetary surface. If Mercury’s core is partly liquid, this will allow to determine the core radius within 75 km according to the results by van Hoolst and Jacobs (2003).3 The static topography coeﬃcients are extracted simultaneously with errors at the centimeter level for a harmonic inversion degree up to 64. Higher precision in the tidal Love number h2 will require larger computational eﬀort. With the crossing-point technique, a precision of about 6% at the 2σ-level in the parameter h2 can probably be achieved during the nominal mission time of BepiColombo. For the extraction of the tidal Love number h2 , laser altimetry is presumably the most precise method because measurements can cover the planetary surface very densely, and each topographic measurement i.e. each laser shot is restricted to a very small area with little variation of the static topography. The spot size of a laser beam on the planetary surface is much smaller than that of any radar instrument, for instance. Topographic measurements with meter-precision using stereo cameras have already been carried out on the Martian surface.36 However, laser altimetry can ultimately be more precise than mapping with cameras.

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With respect to future missions to the icy satellites of the giant planets, it is expected that the measurement precision can substantially be improved by a higher repetition rate of the laser shots. This is particularly valid, if the spacecraft orbits allow for coverage of the planetary surfaces as dense as in the case of the BepiColombo mission carrying BELA. The orbit crossing technique described in Section 3 still promises a high science return from laser altimetry if the spacecraft will not orbit the icy satellite but only ﬂy by several times. However, it is then particularly important that the spacecraft position is tracked with very high precision by a radio science experiment or by the global VLBI system. An alternative method to determine tidal amplitudes of planetary surfaces has been discussed in the frame of the Cosmic Vision proposal23 for a mission to Europa and Ganymede. The position of a mark deposited on the planetary surface may continuously be tracked from an orbiting spacecraft which in turn is tracked by the global VLBI network. The uncertainty of such measurements may be as low as 10 centimeters. However, the precision of laser altimetry can in principle be better than this. Furthermore, laser altimetry maps the full planetary surface and, therefore, misinterpretations of local time-dependent topography changes at the location of any particular mark can be ruled out with higher conﬁdence. Positioning of a superconducting gravimeter37 on the surfaces of Europa and Ganymede bares the same risk, and the installation of a full network of such gravimeters on any of the icy satellites seems rather demanding. The uncertainty in the determination of the libration amplitude Φlib of Mercury from synthetic BELA data is 5 arcsec (12%), which is more than but still comparable to the measurement precision achieved with ground-based radar inferometry.10 In order to achieve higher precision with laser altimetry, the maximum degree of inversion in the analysis of topographic data must be increased much above linv = 64 which implies larger computational eﬀort. It remains unclear whether a more precise determination is possible in course of the BepiColombo mission without support from stereo-photo-grammetry with the SYMBIOSYS camera.38 However, the technique of retrieving libration amplitudes by laser altimetry could be very useful in the frame of missions to the icy satellites of Jupiter or Saturn, where resources may be too limited to include a stereo camera into the payload. Comstock and Bills (2003)25 have calculated the expected amplitudes for a number of planetary bodies which could be tested by laser altimetry. Laser technology will not give a principal limitation for the scientiﬁc return of future missions applying laser altimetry to study the interior

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structure of terrestrial planets or the icy satellites of the giant planets. It will be challenging, however, to develop radiation-hard instrumentation that will survive the hostile environment in magnetospheres of the giant planets. Laser devices of the BepiColombo mission are tested for radiation doses of up to 60 kRad. The higher this level can be pushed, the longer will a laser altimeter operate to map Europa, Callisto, or Ganymede. In the environment of Europa, the dose of 1 MRad typically corresponds to a mission duration of approximately 1 month depending on how much mass is available for shielding and how well the geometry of the scientiﬁc payload can be optimized to share the shielding material. The feasibility of a mission into the radiation environment of the magnetospheres is explored in the frame of a technology preparation study of ESA. Particular care has to be taken about background in the single photon detection electronics caused by particle radiation. Overall, laser altimetry oﬀers a wide range for applications in future planetary missions. The most intriguing application may be the determination of the Love number h2 of planetary bodies, which gives insight into the interior structure of these bodies which cannot be gained by other means. Scientiﬁcally, the laser altimeters have received high priority to be included on spacecraft orbiting the icy satellites of Jupiter or Saturn in order to ﬁnd out how these icy satellites have formed and evolved, and whether they host life. Appendix A. Uncertainty due to small-scale topography In order to derive Eq. (3), we make use of the autocorrelation function RSST of the topography and the Wiener-Khinchine theorem: |TSST (x) − TSST (x + ∆L)|2 = 2[RSST (0) − RSST (∆L)], −β+1 1 ∞ P0 kB RSST (∆L) = PSST (k) cos(k∆L)dk = π kB π β−1 kB ∆L sin(kB ∆L) × cos(kB ∆L) + 2−β ∞ dk ∆L2 cos(k∆L) . + 2 − β kB k β−2 Taking into account the two measurements on one trajectory next to the crossing point leads to the estimate of Eq. (3).

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Appendix B. Remainder terms of polynomial interpolation Evaluating the remainder terms ω(¯ x) for degrees n = 1, n = 2, and n = 3 in Eq. (5) using the power spectral density of the Southern Highlands of Mars gives the following expressions for the interpolation uncertainty: 5−β P0 k B L∆L − ∆L2 n=1 , = ∆Tint 2π(5 − β) 2 7−β L2 ∆L − ∆L3 P0 k B n=2 , ∆Tint = 2π(7 − β) 6 9−β P0 k B 2L3 ∆L − L2 ∆L2 − 2L∆L3 − ∆L4 n=3 ∆Tint = . 2π(9 − β) 24 Acknowledgments This work is supported by the German Aerospace Agency DLR. References 1. T. Van Hoolst, F. Sohl, I. Holin, O. Verhoeven, V. Dehant and T. Spohn, Space Sci. Rev. 132 (2006) 203. 2. S. Peale, Icarus 17 (1972) 168. 3. T. Van Hoolst and C. Jacobs, J. Geophys. Res. 108 (2003) doi:10.1029/ 2003JE002126. 4. X. Wu, Y. Bar-Sever, W. Folkner, J. Williams and J. Zumberge, Geophys. Res. Lett. 28 (2001) 2245. 5. A. Milani, A. Rossi, D. Vokrouhlicky, D. Villani and C. Bonanno, Icarus 49 (2001) 1579. 6. S. Solomon, R. McNutt, R. Gold and D. Domingue, Space Sci. Rev. 131 (2007) 3. 7. G. Schubert, M. Ross, D. Stevenson and T. Spohn, Mercury’s thermal history and the generation of its magnetic field, in Mercury, eds. F. Vilas, C. Chapman and M. Matthews (Univ. Arizona Press, Tucson, 1988), pp. 429–460. 8. T. Spohn, F. Sohl, K. Wieczerkowski and V. Conzelmann, Planet. Space Sci. 49 (2001) 1561. 9. S. Hauck, A. Dombard, R. Phillips and S. Solomon, Earth Planet. Sci. Lett. 222 (2004) 713. 10. J. Margot, S. Peale, R. Jurgens, M. Slade and I. Holin, Science 316 (2007) 710. 11. J. Anderson, G. Colombo, P. Esposito, E. Lau and G. Trager, Icarus 71 (1987) 337. 12. W. Moore and G. Schubert, Icarus 166 (2003) 223.

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13. G. Tobie, G. Choblet and C. Sotin, J. Geophys. Res. 108 (2003) doi:10.1029/ 2003JE002099. 14. F. Sohl, H. Hussmann, B. Schwentker, T. Spohn and R. Lorenz, J. Geophys. Res. 108 (2003) 4. 15. T. Hurford, P. Helfenstein, G. Hoppa, R. Greenberg and B. Bills, Nature 447 (2007) 292. 16. G. Mitri, A. Showman, J. Lunine and R. Lopes, Icarus 196 (2008) 216. 17. N. Rappaport, L. Iess, J. Wahr, J. Lunine, J. Armstrong, S. Asmar, P. Tor-tora, M. Di Benedetto and P. Racioppa, Icarus 194 (2008) 711. 18. H. Hussmann, F. Sohl and T. Spohn, Icarus 185 (2006) 258. 19. J. Mitrovica, J. Davis, P. Mathews and I. Shapiro, Geophys. Res. Lett. 21 705 (1994). 20. C. Yoder, A. Konopliv, D. Yuan, E. Standish and W. Folkner, Science 300 (2003) 299. 21. A. Konopliv and C. Yoder, Geophys. Res. Lett. 23 (1996) 1857. 22. N. Thomas, T. Spohn and et al., Planet. Space Sci. 55 (2007) 1398. 23. M. Blanc, D. Moura, S. Atreya, M. Barthelemy, A. Barucci, B. Bezard, D. Bockelee-Morvan, S. Bolton, R. Brown, L. Colangeli, A. Coradini, A. Doressoundiram, P. Drossart, M. Festou, M. Fulchignoni, D. Gautier, Z. Guillot, R. Kallenbach, N. Krupp, P. Lamy, J.-P. Lebreton, A. Leger, D. Matson, A. Morbidelli, T. Owen, R. Prange, C. Sotin, D. Strobel, N. Thomas, P. Zarka, Y. Alibert, N. Andre, I. Baraﬀe, R. Beebe, W. Benz, G. Chanteur, M. Dougherty, E. Flamini, M. Galand, T. Gombosi, T. Krim-igis, W. Kurth, Y. Langevin, P. Louarn, J. Lunine, F. Raulin, R. Srama, H. Waite, O. Witasse and J. Zarnecki, Tracing the origins of the Solar System, in Trends in Space Science and Cosmic Vision 2020, eds. A. G. F. Fa-vata, J. Sanz-Forcada and B. Battrick, ESA SP, Vol. 588 (European Space Agency, 2005), pp. 213–224. 24. A. Coustenis, S. Atreya, T. Balint, R. Brown, M. Dougherty, F. Ferri, M. Fulchignoni, D. Gautier, R. Gowen and C. Griﬃth, Experimental As tronomy (2008) doi:10.1007/s10686 . 25. R. Comstock and B. Bills, J. Geophys. Res. 108 (2003) CiteID 5100, doi:10.1029/2003JE002100. 26. C. Koch, U. Christensen and R. Kallenbach, Planet. Space Sci. 56 (2008) 1226. 27. C. Erd, R. den Hartogh, A. Jeanes, A. Owens, P. Pablos, N. Rando, S. Kraft, M. Collon, J. Montella, J. Harris, E. Buis and M. Beijersbergen, BepiColombo Payload Study Document (ESA/ESTEC, Noordwijk, The Netherlands, 2004). 28. S. Peale, R. Phillips, S. Solomon, D. Smith and M. Zuber, Meteor. Planet. Sci. 37 (2002) 1269. 29. A. McEwen and M. Robinson, Adv. Space Res. 19 (1997) 1523. 30. R. Rummel, Earth, Moon, and Planets 94 (2005) 103. 31. C. Gardner, IEEE Trans. Geosci. Remote Sensing 30 (1992) 1053. 32. O. Aharonson, M. Zuber and D. Rothmann, J. Geophys. Res. 106 (2001) 23723.

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33. M. Kreslavsky, J. Head and J. Harmon, Large-scale topographic roughness of terrestrial planets: A comparison, in 39th Annual Lunar and Planetary Science Conference, March 2008, League City, Texas. 34. R. Freund and R. Hoppe, Stoer/Burlish: Numerische Mathematik 1 (Springer Verlag, Heidelberg, 2007). 35. J. Blazej, I. Prochazka, K. Hamal, M. Fedyszynova, F. Yang, P. Huang, H. Michaelis and U. Schreiber, J. Optics A 9 (2007) S98. 36. R. Kirk, E. Howington-Kraus, M. Rosiek, J. Anderson, B. Archinal, K. Becker, D. Cook, D. Galuszka, P. Geissler, T. Hare, I. Holmberg, L. Keszthelyi, B. Redding, W. Delamere, D. Gallagher, J. Chapel, E. Eliason, R. King and A. McEwen, J. Geophys. Res. 113 (2008) p. CiteID E00A24. 37. J. Neumeyer, F. Barthelmes, O. Dierks, F. Flechtner, M. Harnisch, G. Harnisch, J. Hinderer, Y. Imanishi, C. Kroner, B. Meurers, S. Petrovic, C. Reigber, R. Schmidt, P. Schwintzer, H.-P. Sun and H. Virtanen, J. Geodesy 79 (2006) 573. 38. V. Da Deppo and N. Giampiero, Proc. SPIE (2006) 626527.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientific Publishing Company

REGIONAL CENTRES FOR SPACE SCIENCE AND TECHNOLOGY EDUCATION AFFILIATED TO THE UNITED NATIONS A. J. A. AQUINO and H. J. HAUBOLD United Nations Oﬃce for Outer Space Aﬀairs, Vienna International Centre, Vienna, A-1400 Vienna, Austria [email protected]

Based on resolutions of the United Nations General Assembly, Regional Centres for space science and technology education were established in India, Morocco, Nigeria, Brazil and Mexico. Simultaneously, education curricula were developed for the core disciplines of remote sensing, satellite communications, satellite meteorology, and space and atmospheric science. This paper provides a brief report on the status of the operation of the Regional Centres and draws attention to their educational activities.

1. Background The United Nations General Assembly, in its resolutions 45/72 of 11 December 1990 and 50/27 of 6 December 1995, endorsed the recommendation of the Committee on the Peaceful Uses of Outer Space (COPOUS) that Regional Centres for space science and technology education should be established on the basis of aﬃliation to the United Nations, in developing countries. Under the auspices of the United Nations, through its Oﬃce for Outer Space Aﬀairs (UN-OOSA), four Regional Centres were established on the basis of regions that correspond to the United Nations Economic Commissions: Asia and Paciﬁc (India), Latin America and the Caribbean (Brazil and Mexico) and Africa (Morocco, Nigeria). All of these Regional Centres are aﬃliated to the United Nations through UN-OOSA. A ﬁfth Centre in Western Asia (Jordan) will be established in the future. These Regional Centres use existing facilities and expertise already available in education and other research institutions in their respective regions (http://www.unoosa.org/oosa/en/SAP/centres/index.html). 633

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The overall policy-making body of each Centre is its Governing Board (GB) and consists of member States (within the regions of Latin America and the Caribbean, Africa, and Asia and the Paciﬁc, as shown in the following ﬁgure, where the Centre is located), that have agreed, through their endorsement of the Centre’s agreement, to the goals and objectives of the Centre.

The United Nations Programme on Space Applications, with the support of prominent educators, has developed standard education curricula, which were adopted by the Regional Centres for teaching each of the four core disciplines. These four education curricula, as shown in the following ﬁgures, are being revised, updated, and upgraded in United Nations expert meetings on the Regional Centres on a regular basis and published by the United Nations. The overall goal of the Regional Centres is to develop, through in-depth education, an indigenous capability for research and applications in the core disciplines of Remote Sensing and Geographical Information Systems, Satellite Communications, Satellite Meteorology and Global Climate, and Space and Atmospheric Sciences. Education curricula have been developed for the four core disciplines. Two further model curricula are currently being

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developed under the auspices of the United Nations in the area of global navigation satellite systems (GNSS) and space law. These disciplines would be included into the education programme of the Regional Centres once the work is concluded. Detailed information on the Regional Centres, including shortterm and long-term educational activities, membership in Governing Boards and Advisory Boards, statistics of participation of scholars from diﬀerent nations in educational programmes, annual reports on the activities of the Regional Centres, public outreach activities, contact information, cooperation of the Regional Centres with governmental and non-governmental entities as well as international, regional, and national organizations is available on the websites of all Regional centres as given below. Such websites are updated on a regular basis. Regional Centres report their achievements, through printed reports and oral presentations, to the United Nations Committee on the Peaceful Uses of Outer Space on an annual basis.

2. Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP) The Centre for Space Science and Technology Education in Asia and the Paciﬁc (CSSTEAP), which was established in 1995, pioneered the United Nations initiative to create space educational Regional Centres in developing countries. The Centre is headquartered in Dehradun, India, and its programmes are implemented by staﬀ of the Department of Space (DOS) at campuses in Dehradun and Ahmedabad (http://www.cssteap.org). The Centre has access to the facilities, infrastructure and expertise of the Indian Institute of Remote Sensing (IIRS) in Dehradun, the Space Applications Centre and the Physical Research Laboratory (PRL), both at Ahmedabad. Its Governing Board comprises 14 members from 14 countries in the Asia

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and Paciﬁc region and two observers. To date, CSSTEAP has conducted 26 long-term postgraduate courses and 18 short-term programmes in the core disciplines. These programmes have beneﬁted 46 countries and 973 scholars in the Asia and Paciﬁc region and beyond. Since 1999, CSSTEAP has achieved the status of an institution of excellence and celebrated the tenth anniversary of its establishment in 2005. In 1998, CSSTEAP signed a Memorandum of Understanding with Andhra University, Visakhapatnam, India, under which the University can award the Masters of Technology degree to those scholars who have completed the nine-month post-graduate programme at the Regional centre together with a one-year research or application project implementation in the home country of the scholar.

3. African Centre for Space Science and Technology — in French Language (CRASTE-LF) The African Centre for Space Science and Technology — in French Language (CRASTE-LF) was established in Morocco in 1998. It is based at the Mohammadia School of Engineers at the University Mohammed V Agdal in Rabat (http://www.enssup.gov.ma/craste). Important national institutions such as the Royal Centre of Space Remote Sensing (CRTS), Scientiﬁc Institute (IS), Agronomic Institute and Veterinary Hassan II (IAV), National Institute of Telecommunications (INPT) and Directorate of National Meteorology (DMN), actively support the educational programmes oﬀered by the Centre. The Governing Board of CRASTE-LF is composed of 16 members from 13 countries in the region and one observer. The Centre has already carried out nine long-term postgraduate courses and 12 short-term programmes. The long-term programmes were attended by 129 scholars from 16 countries in the region.

4. African Regional Centre for Space Science and Technology Education — in English Language (ARCSSTE-E) The African Regional Centre for Space Science and Technology Education — English (ARCSSTE-E) was inaugurated in Nigeria in 1998. It operates under the auspices of the National Space Research and Development Agency (NASRDA) and is located at Obafemi Awolowo University (OAU) campus, Ile-Ife (http://www.arcsstee.org). The Centre’s facilities are mainly provided by departments from OAU and the Regional Centre for Training in Aerospace Surveys (RECTAS), which is also located

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on the OAU campus. ARCSSTE-E has already oﬀered 12 postgraduate courses and eight short-term programmes. About 51scholars from 13 countries in the region attended the long-term courses.

5. Regional Centre for Space Science and Technology Education for Latin America and the Caribbean — Brazil and Mexico campuses (CRECTEALC) The Regional Centre for Space Science and Technology Education for Latin America and the Caribbean — Brazil and Mexico campuses (CRECTEALC) was established in 1997 after Brazil and Mexico signed an agreement recognizing the Centre with a campus located in each country (http://www.crectealc.org). The campus in Brazil beneﬁts from the facilities made available to it by the National Institute for Space Research (INPE), a renowned Brazilian research institution in space science and technology. Similar high quality facilities are found at the campus in Mexico that is supported by the National Institute of Astronomy, Optics and Electronics. The Governing Board of CRECTEALC is chaired alternatively by Mexico and Brazil. The Campus Brazil has already conducted ﬁve postgraduate courses and four short-term programmes. These postgraduate courses have beneﬁted 44 scholars from 12 countries in the region. The Campus Mexico also carried out four nine-month postgraduate courses in RS & GIS and two courses in Satellite Communications. These courses have beneﬁted 24 participants from ﬁve countries in the region (Colombia, Ecuador, Peru, Haiti and Mexico).

6. Future Development Two further model curricula are currently being developed under the auspices of the United Nations in the area of global navigation satellite systems and space law. These disciplines would be included into the education programme of the Regional Centres once the work is concluded. In the recently established International Committee on Global Navigation Satellite Systems (ICG, http://www.icgsecretariat.org), negotiations with the Regional Centres are on-going, to use the Regional Centres as ICG Information Centres for training and information dissemination on global applications of GNSS and their beneﬁts for humanity.

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References 1. N. W. Dias, Developing remote sensing and GIS hands-on modules to support UN-aﬃliated education programmes, Space Policy 20 (2004) 55–58. 2. H. J. Haubold, Education curricula of the UN-aﬃliated Regional Centres for Space Science and Technology Education, Space Policy 19 (2003) 67–69. 3. H. J. Haubold, Education curricula in space science and technology education: the approach of the UN-aﬃliated Regional Centres, Space Policy 19 (2003) 215–219. 4. International Institute for Geo-Information Science and Earth Observation (ITC): Report of the Executive Seminar on Recognition of Cross-Border Capacity Building in Earth Observation, ITC Enschede 2007. 5. K. R. Lang, An education curriculum for space science in developing countries, Space Policy 20 (2004) 297–302. 6. J. Newport, Amateur satellites: A neglected vehicle for satellite communication education, Space Policy 21 (2005) 101–104. 7. United Nations: Capacity building in space science and technology: Regional Centres for Space Science and Technology Education, Aﬃliated to the United Nations, UN document ST/SPACE/41 New York 2008.

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Advances in Geosciences Vol. 19: Planetary Science (2008) Ed. Anil Bhardwaj c World Scientiﬁc Publishing Company

ASIA-PACIFIC REGION WATER BOOSTED ROCKET EVENTS K.-I. OYAMA Institute of Space Science, National Central University, Taiwan [email protected] A. HIDAYAT and E. SOFYAN National Institute of Aeronautics and Space of Indonesia, Indonesia H. S. S. SINHA Physical Research Laboratories, India, Science & Technology Center, Indonesia K. HERUDI

T. KUBOTA Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, Japan S. SUKKARIEH University of Sydney, Australia J. L. ARBAN Department of Science and Technology, Philippine D. M. CHUNG Space Technology Application Center, Vietnam I. MEDAGANGODA Arthur C.Clark Center for Modern Technologies, SriLanka Z. B. MOHD National Space Agency of Malaysia, Malaysia

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S. PITAN Geo-informatics and Space Technology Development Agency, Thailand C. CHIN Ministry of Land Management, Urban Planning and Construction, Cambodia F. R. SARKAR Bangladesh Astronomical Society, Bangladesh

Space Education and Awareness Working Group, which is one of four working groups of Asia- Paciﬁc Regional Space Agency Forum, had organized water boosted rocket competition in Japan in 2005, in Indonesia in 2006, and in 2007 in India. One junior high school student (12–15 years old) and one leader from 9 and 13 Asian/Paciﬁc countries attended the 1st, 2nd, and 3rd water rocket events, respectively. The 4th event is planned in Vietnam, in December 2008. The manuscript introduces the structure and activities of Space Education and Awareness Working Group, which is working under Asia-Paciﬁc Regional Space Agency Forum sponsored by Ministry of Education, Culture, Sports, and Technology of Japan; and application of water-boosted rocket to other ﬁeld is described. Details of the water boosted rocket events, such as the purpose, competition rules, and the schedules are provided. Finally we discuss the issues to be taken into account for the future event.

1. Introduction Asian-Paciﬁc Regional Space Agency Forum (APRSAF) was established in 1993 in response to the declaration adopted at the Asia Paciﬁc International Space Year Conference (APIC) held in 1992 to enhance the development of each country’s Space Education program and to exchange views on future cooperation in space activities in the region. APRSAF has held thirteen annual meetings so far, convened jointly by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan and the Japan Aerospace Exploration Agency (JAXA). At the initial stage the forum was held in Japan and later the forum was co-hosted by the Asian countries, viz., Mongolia (7th, 1999), Korea (9th, 2003), Thailand (10th, 2004), Australia (11th, 2004), Japan (12th, 2005), Indonesia (13th, 2006), and India (14th, 2007). The forum consists of 4 working groups, namely Earth Observation, Communication satellite Application, Space Education and Awareness (SEA, http://www.aprsaf.org/text/ap13-info1.html#SEAWG), and International Space Station. These groups exchanged information,

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generate recommendations and discuss action items for the year in each of the sessions, which are held after the plenary meeting of APRSAF. The SEA WG members discussed on the eﬀective running of the working group, especially during the 9th APRSAF in Korea. Almost all SEA WG members felt that the meeting was not very productive, although it was informative. Such meeting should have speciﬁc action items and it should be ensured that these are carried out sincerely. However, the WG deliberations so far have not been on these lines. At the 10th APRSAF in Thailand, the SEA WG members expressed again that items discussed in the SEA WG meeting should be sincerely pursued. At the 11th meeting again, this opinion that the action items discussed in previous meetings should be completed was repeated by most of the SEA WG members. This paper describes the SEA WG, and Water Boosted Rocket Events, which was conducted in Japan, Indonesia, and India in 2005, 2006, and 2007 respectively, which highlight one completed action item suggested by the SEA WG under the umbrella of APRSAF. 2. Space Education Awareness Working Group (SEA WG) 2.1. Structure of SEA WG The objective of the SEA WG is to contribute towards the peaceful harmony of the Asian countries through the development and utilization of space. To be more speciﬁc, the SEA WG aims to trigger the interest of the young generation through space and to increase public awareness of the importance of space development. The SEA WG consists of one representative from each of the Asia-Paciﬁc countries. The SEA WG representatives who are routinely attending WG meetings of APRSAF are Australia, Cambodia, Indonesia, India, Republic of Korea, Malaysia, Nepal, Philippine, Sri Lanka, Thailand, Vietnam and the United Nations. Two Co-chairmen usually chair the session meeting, which is held on the occasion of plenary meeting of APRASF. One of these Co-Chairmen is basically from Japan and another one is from the co-host country where APRSAF is held. Co-chairman of Japan has a long-term involvement until he resigns, while term of Co-chairman of co-host country is one year starting right before APRSAF and ending before next APRSAF. The SEA WG requests a Co-chairman from the co-host country to report the summary of the discussion, action items, and recommendations of the session. The functions of SEA WG are: (a) the SEA WG takes speciﬁc actions for the

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items, which are agreed in the SEA WG, and therefore (b) representative from each country has the full responsibility for the Space Education Awareness activities that are conducted under the umbrella of APRSAF. The roles of the SEA WG members are; (i) to serve as a single contact point of each country, (ii) to organize local space education activities, (iii) to collect information on his (her) country’s activities. Representative from individual countries are requested to inform to the Co-Chairman of Japan in case the SEA WG member is replaced. It goes without saying that the success of the SEA WG activities totally depends on the WG members, who should be aware of his or her role and the associated major responsibility. 2.2. Items to be awared among SEA WG The mission of the SEA WG is to explore the ways and means of strengthening the level of education and awareness of the government, public and those responsible for the basic and higher education within the Asia-Paciﬁc Region to achieve a common goal in Space Education and Awareness with the available resources and technologies among the member countries and to share the beneﬁts of space through the process of collaboration and education. However, it is important to know the fact that the levels of education and awareness in the countries within the region diﬀer signiﬁcantly. This occurs at the public, primary, secondary and tertiary levels. Hence formulating grand visions of collaboration on education and awareness projects is a diﬃcult concept to accept and promote. One must recognize that for such large-scale education projects to succeed there are still some fundamental goals, which need to be achieved ﬁrst. If we are truly looking at the region with the aim of promoting Space to the public, we must consider the following: (1) the educational material available in some of the less developed countries is scarce, if any at all, (2) The level of IT support (access to the Internet) is also low or nonexistent, in some of the countries or regions within the country. (3) The level of educational training (how and what to teach) varies and in some cases there is no formal level of training educators. The SEA WG is trying to take speciﬁc aﬀordable actions under the common awareness described above. After the action items are accepted each year, the working group members have heavy responsibilities to conduct space education activities in each country. This means that the SEA WG members are at the position to be able to organize

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activities in each country. The occupations of the SEA WG members are government employees, university professor and scientists of reputed laboratories/institutes. The persons who had discharged duties of SEA WG members, up to 2006, are Prof. K.-I. Oyama (Co-Chair, Japan), Mr. C. Chin (Cambodia), Dr. D. M. Chung (Vietnam), Mr. A. Hidayat (Indonesia), Prof. H. S. S. Sinha (India), Dr. J. E. Arban (Philippine), Dr. S. Pitan (Thailand), Dr. J. Lee (Republic of Korea), Mr. N. I. Medagangola (Sri Lanka), Mr. K. Adhikary, and Dr. S. Sukkarie (Australia). United Nations Educational, Scientiﬁc and Cultural Organization (UNESCO) attended as an observer until 2006, and the SEA WG agreed UNESCO as an oﬃcial SEA WG member at 13th APRSAF in Indonesia. A member from UNESCO is currently Ms. S. L. Berenguer. As of 21 November 2007, the SEA WG member is composed of the members from following 16 countries and 3 international entities. Those are; Australia, Bangladesh, Cambodia, India, Indonesia, Japan, Kazakhstan, Malaysia, Myanmar, Nepal, Pakistan, Philippine, Republic of Korea, Sri Lanka, Thailand, Vietnam, Asian Institute of Technology, UNESCO, and United Nations Oﬃce for Outer Space Aﬀairs (UNOOSA)

3. Water Boosted Rocket Event One of the action items, agreed upon during the discussions of the SEA WG meeting at APRSAF-11, is to conduct the APRSAF Water Boosted Rocket Event for the children between 12–15 years old. One student and the curator from each country get his/or her travel support from JAXA. The student and curator were expected to be chosen through a national competition. When the country is not ready for the national event in that year, the SEA WG member is responsible for the selection of the student and curator under a condition that national competition should be held by the next APRSAF even on a small scale. Another condition is that the students and curator who are selected teach the water boosted rocket to other children after they return to their country. The SEA WG member should take care of their VISA issues, and their safe travel to and from the airport inside their countries. Once they arrive at the country where Water Boosted Rocket Event (host country) is held, all responsibilities lies with the SEA WG member of host country. We deﬁne this as one of the responsibilities of the SEA WG member. Those who are not selected can attend the event by their own expense, but they are equally treated during the event.

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3.1. Various applications of the water boosted rockets Water boosted rocket usually uses two PET bottles of the volume of 1.5–2 litters. One bottle will be used for the rocket body, and the other to make the nosecone. While it is usually advisable to use 1.5 litters round (cylinder) bottles, smaller 0.5 litter bottles can also be used. The PET bottles must be for carbonated drinks, as these can withstand higher pressure than bottles used for non-carbonated drinks. When launching your rocket, about one third of the volume can be ﬁlled with water and pressurized up to about 4 Kg/cm2 (this number is recommended from the safety reason) through a throat of the pet bottle, which acts as a nozzle of the rocket. At the bottom of the cylindrical pet bottle, nose cone (which can be made by using hard paper) is attached. Near the bottom of the bottle, 4 ﬁns, which are equi-spaced, are ﬁxed by adhesive tape around the cylinder (http://edu.jaxa.jp/Water Rockets Educator’s manual, Japan Aerospace Exploration Agency, or DVD is available upon request). When the nozzle is opened, the PET bottle ﬂies according to the law of action-reaction (Newton’s third law of motion). It is ensured that the water rockets should be easy to make so that elementary school children can enjoy making these. The event can be designed by competing for the maximum distance from the launcher, maximum altitude of the rocket, and by aiming at the designated target area, depending on the area of the ﬁeld where the competition is conducted. In order to have a maximum distance or maximum altitude, we need to optimize the amount of the water and the pressure inside by using computer. Therefore even university professor can use the water boosted rocket as one of the teaching materials (Tomita and Watanabe, 2004). The drag of the nose cone, F , can be estimated by the following equation: F = 1/2AρV 2 Where, V is the speed of the rocket, A is the cross section along the moving direction and ρ is the atmospheric density. Another application of the water-boosted rocket to the higher-level education is that students can put digital memory chip(s), accelerometer and/ or magnetometer, with a small battery on the water-boosted rocket. After the touch down of the rocket, these data can be retrieved. Recent technology makes sensors of the magnetometer (magneto resistance magnetometer) and the accelerometer accommodated in the small rocket.

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Next advanced course is to put a small telemeter on the rocket with an accelerometer, and a magnetometer. The telemetry signal is received on the ground. Since the attitude of the rocket can be roughly calculated from magnetometer data, students can investigate on the stability of the rocket. As this system is very similar to the launch of real rocket operation, the student can get systematic information on the rocket launching such as transmitting, receiving, and discriminating of the signals transmitted from the rocket, and data analysis. In terms of demonstrating the practical use of water boosted rocket, a possibility exists to trigger the lightning with a tether- attached rocket, if it can go up to about 200–300 meters. This issue might be worth pursuing by making large rocket as well as by using second stage rocket. The bridging over the river can be done by water-boosted rocket, which can ﬁrst deliver a tether of small diameter. As such, the water-boosted rocket can be used to transform the elementary school education, including higher-level educations into the real application. The information on all these aspects is available on several Internet web pages listed in the reference. 3.2. First water boosted rocket event in Japan The event had two major targets for education. Those are: (1) To stimulate the curiosity of young generation through space related activities, and (2) To open eyes of young generation towards outside world by interacting with people from various countries of diﬀerent cultures. The program also tries to touch environmental issues by lectures, which are given during the event on the deforestation, global warming, ozone depletion of our planet earth, and others. Finally, the program provides an excellent opportunity to ask support from taxpayers and to inform them about the importance of space activities. Immediately after APRSAF-11 in Australia, We started preparations to hold the exciting event on the occasion of the APRSAF-12 meeting, which was planned to be held in Kitakyushu, Japan on October 11–13, 2005. We planned to hold the water boosted rocket event right after the APRSAF-12 meeting on October 14–16, to enable the SEA WG member to attend the event. After ﬁxing the date of the water rocket event, we asked the foreign aﬀair oﬃce of the Kitakyuushu city to ﬁnd the facility for the attendants’ stay, and the site for the water boosted rocket event and we also asked to provide the necessary transport facilities. We

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asked Prof. Aso of Kyushu University to organize events in Kyushu area, which consists of 7 prefectures, and also to provide volunteers from Japan Young Astronautics Club from Fukuoka and Kitakyushu. In parallel with national activities, the Co-Chair (Prof. Oyama) sent a message to request that WG members of each country to prepare for this competition. It turned out that 9 countries from outside Japan sent one student and one curator each. Those are Australia, India, Indonesia, Japan, Korea, Malaysia, Sri Lanka, Thailand, and Vietnam. In addition to these, Thailand sent two curators and 6 students by their own support. One student of junior high school and one curator from each prefecture of Kyushu District were also supported by JAXA. All the above mentioned were the participants to the international event. Prior to the international event, national events were organized for the student from Kyushu area. About 50 local participants attended this national event. The schedule of the events is given below. 3.2.1. Schedule for 1st water boosted rocket in Japan On the 14th, 2005 (Friday), JAXA volunteers who were easily identiﬁable by their specially prepared T-shirts and blue JAXA armbands received all the international participants at the Fukuoka International Airport. These participants were then taken to their place of stay, Genkai Seinen no Ie (Lodge for young people), by bus via Kokura city. Students and curators from 9 countries gathered in one place. After they settled to stay, we had an orientation, which included giving rules and advices during the stay at the lodge, and explaining the whole schedule. Figure 1 shows the orientation before the reception dinner. We prepared vegetarian and non-vegetarian foods. After the dinner was over, Mr. Takemae gave a brief lecture on the principle of the rocket ﬂight, competition including rules as Fig. 2 shows. Mr. Kataoka showed the video where he tried to push up one person on the seat, which is boosted by many PET-bottles assembled. The video attracted the minds of all participants. On the 15th October 2005 (Saturday), the activities started from breakfast at 7:30, and they moved to Kitakyushu Conference Center. After the opening ceremony, the participants started fabrication of the water — boosted rocket in one of the rooms at the Kitakyushu Conference Center, and after launch they moved to a baseball ground by bus where competition was held. Before the competition started, the competitors were given three trial launches.

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Fig. 2.

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Orientation at canteen of Genkai–Seinen-no Ie.

Lecture by Mr.Takemae on how rocket ﬂies.

At 13:00 international competition started and then from 14:30, competition for the local participants from Fukuoka prefecture was conducted. Participants who obtained good score were awarded by JAXA. After the event was over, we moved to Kitakyushu Conference Center for a reception. Reception is one of the main events because participants have

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chances to get acquainted with each other. It is amazing that they had no diﬃculty to become friends some time after the reception. On the 6th October 2005 (Sunday), they moved to Fukuoka city by bus to visit the 56th International Astronautical Congress and took Space Exhibition Tour. On the 7th October 2005 (Monday), all participants from outside Japan left for their countries. 3.2.2. Lessons learned from the 1st event The ﬁrst step to organize students of Asia-Paciﬁc regions for Space Education has been cleared by SEA WG of APRSAF. We can raise two fundamental factors, which generated the successful result. First the SEA WG assigned one single person in individual countries, so that he or she was responsible for the activities in his or her countries. Secondly JAXA supported ﬁnancially. However we were not satisﬁed with this successful event, which can only be the ﬁrst step. The ﬁrst lesson, which we learned from the ﬁrst APRSAF Water Boosted Rocket Event, was that we should improve the system for the eﬀective information exchange among students as well as curators of diﬀerent countries and secondly we should have time to give lectures on the importance of space use for human beings and our solar system and universe. These lessons were fed back to the second water boosted rocket event in Indonesia.

Fig. 3.

Instructional class to fabricate water boosted rocket at Kita Kyushu, Japan.

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Fig. 4.

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1st Water Booted Rocket Event at Kita Kyushu Japan.

3.3. Second water boosted rocket in Indonesia National Institute of Aeronautics and Space of Indonesia (LAPAN) hosted the second water boosted rocket event during 7–9 December 2006 right after 13th APRSAF was over. The person in charge was Dr E. Sofyan, LAPAN. The venue was Taman Mini Indonesia Indah (TMII), Science & Technology Center (PPIPTEK), which is located outside of Jakarta city. 13 countries (Australia, China, Cambodia, India, Indonesia, Japan, Malaysia, Korea, Philippine, Sri Lanka, Singapore, Thailand, and Vietnam) sent one student and one curator. The lessons learnt from the 1st rocket event were fed back to the event. The major diﬀerence between the second and the ﬁrst event was that the second event provided special lectures to the participants on the importance of space and environment. On the 7th December 2006 (Thursday), all the international participants were received at the Jakarta International Airport by LAPAN volunteers and were taken to their place of stay, Taman Mini Indonesia Indah (TMII), by bus. Registration and welcome reception were held at Science & Technology Center (PIPTEK). On the 8th December 2006 (Friday), the activities for the days were Space School (Lectures on the latest space activities), Technical tour around PPIPTEK, Lunch, Cultural tour (Indonesia in Miniature), Dinner, and Watching IMAX theatre. The activities were followed by a Leaders’

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Fig. 5. Leaders meeting: Leaders from diﬀerent countries explained their own home — made launchers.

meeting, which provided a chance to exchange of opinions among the SEA WG members & leaders. It was impressive that participants presented their own several ideas especially on the releasing of the nozzle of a pet bottle, and hot discussion was continued. On the 9th December 2006 (Saturday), main event for this day was launching competition followed by International Water Rocket Workshop, and fabrication of the water boosted rockets. The competition was conducted by aiming the targeted area, which was the same as for the 1st rocket events in Japan. The details are below. 1. All contestants do not need to bring anything for the competition. All materials to make and launch water rockets, including nozzles and launchers, was be provided by the organizer. 2. Each contestant should make 3 rockets to launch at PPIPTEK. Whereas the launch will be conducted at the launch site 5 minutes away from PPIPTEK. 3. Each contestant was encouraged to be creative in designing a nose and ﬁns of the rocket. 4. The organizer provided 1.5 liter PET bottles to make rockets.

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5. The contestant was expected to adjust the volume of the water and its pressure. 6. Each contestant was given opportunities to conduct 3 launches (see map). 7. 100 points, or the maximum points, were given if the rocket hits the target point (57.5 m from the launcher) or the impact point is within the range of ±1.5 m from the target point. Fewer points were given if the impact point was farther away from the target point as indicated below: Zone I: Zone II: Zone III: Zone IV:

56.0–59.0 m: 100 points 53.5–56.0 m and 59.0–61.5 m: 80 points 50.0–53.5 m and 61.5–65.0 m: 60 points 45.0–50.0 m and 65.0–70.0 m: 40 points 70m 57.5m 45.0m

Launcher Point

IV

III

II

I I

II

III

IV

8. If the impact point is exactly on the zone marker, i.e. the line between two zones, the points accorded to the zone closer to the launcher will be awarded. 9. If the impact point is outside the dedicated zone, i.e. Zones I, II, III and IV, no point will be awarded. 10. The contestant who scores the highest points in total after three launches will be declared the winner of the Competition. Award Ceremony and Friendship Gathering followed the completion. On the 10th December 2006 (Sunday), participants left TMII in the morning by buses for the international airport with wonderful memory.

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Fig. 6. At the PPIPTEK launch site the rockets were launched from one island (Sulawesi, around center at right ﬁgure) to other Ireland (Kalimantan left side at right ﬁgure), which was uniquely facilitated in the artiﬁcial lake, which is supposed to be the sea surrounding Indonesia (APRSAF home page).

Fig. 7.

Participants, Guests invited, and public watchers.

3.4. 3rd water boosted rocket event in India 3rd water boosted rocket event was successfully conducted during 23– 25 November 2007 at National Aerospace Laboratories Central School, Bangalore, India right after APRSAF 14th. The event was co hosted by Indian Space Research Organisation, and Ministry of Education, Culture, Sports, Science and Technology of Japan, and Japan Aerospace Exploration Agency (JAXA). 24 students from 11 countries (Bangladesh, Cambodia, India, Indonesia, Japan, Malaysia, Philippine, Thailand, Sri Lanka, Singapore and Vietnam) attended. The event enjoyed good media

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Fig. 8. Rocket launch for opening ceremony was ignited by Vice Minister of Science and Education.

Fig. 9.

Preparations underway for the water rocket event at Bangalore, India.

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Fig. 10.

Water rocket approaching its apogee at Bangalore.

coverage and received sponsorship by Coca Cola in Bangalore. The schedule of the event is shown below. On the 22nd November 2007 (Thursday), the participants arrived at Bangalore airport and were transported to the lodging place. In the morning of the 23rd November 2007 (Friday), participants arrived at event place, and in the afternoon, followed by the orientation for the participants, lectures on the latest space activities and theory of water rocket were provided to the participants. In the evening welcome reception was hosted by ISRO. It is a good idea to have a reception at ﬁrst night, so that at least children have chance to talk with foreign students. In the morning of 24th November 24, 2007 (Saturday), the water rocket launch competition issues such as schedule, rules of the competition were informed to the participants. Making of water rockets was completed in the morning. In the afternoon, launch competition was conducted. The diﬀerences of the competition rules from the second rocket event in Indonesia are followings. The diameter of the pet bottle was 2 litters instead of 1.5 litters. Competitors made two rockets instead of 3 rockets, which we made in Indonesia. The competitors are given two launch chances. Whilst in Indonesia, we had 3 launches. The competition was followed by Prize award ceremony.

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On the 25th November 2007 (Sunday), all participants from foreign countries left for their countries.

4. Concluding Remarks Children who participated in the water boosted rocket events were ﬁrst exposed to an international atmosphere, which surely expanded their sight. At the same time, they are encouraged to learn English as a way of communication. They also learned on the importance of space activities, which directly related to daily and future life of human beings. They were also taught through space related lectures on their planet earth to be saved from various environment destructions. These two issues, awareness of the importance of space activities and environmental problems will be conveyed to their family, and friends in his /her countries. Thus we conclude that the SEA WG was able to conduct very successfully three water boosted rocket events. Especially the second water boosted rocket event, which was held in Indonesia, was much better organized than the ﬁrst one held in Japan. It is hoped that the number of participating countries increases for future events. Although the main purpose of the event is not to increase the number of the participant’s countries, the eﬀort should be continued to increase the number of the countries, which are keen for space education because one of the main objectives is to contribute the peace of the world by trusting each other. This ﬁnal goal is only possible through education. It is further expected that the event, which is now conﬁned to Asian/Paciﬁc region, will be extended to whole world. However, as the number of countries increases, the necessary funding amount also increases and it may not be possible for JAXA to keep the present funding policy, i.e. to pay travel fare of one student and one curator from individual developing countries. If these activities have to really extend to more countries, it is essential to make eﬀorts to ﬁnd sponsoring/supporting organizations, such as private companies, well-established voluntary associations, and private foundations if the each country cannot support the people from his own countries. It is quite clear that without this eﬀort the domain of this event cannot be expanded. At the same time space agencies of all countries should try to support the travel of participants from their own country. The SEA WG members of each country should take continuous actions toward his/her government. The role of the SEA WG representative becomes more and more important.

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Acknowledgments Individuals and organizations that contributed towards the successful ﬁrst water boosted rocket event, which was held in Japan, are; Prof. Aso (Kyushu University), Prof. S. Matsumoto (Leader of YAC Kitakyushu Branch, Waseca University), Mr. Takemae (Launch conductor), Mr. T. Kataoka (Launch conductor). Mr. Y. Kamakura and K. Tanaka (Leader, Fukuoka Branch) and Kitakyushu Branch of Young Astronaut Club, Keirinkan Co Ltd. Ms M. Onuki worked as a secretary to Water boosted Rocket Event. Kitakyushu city took all necessary actions, which were needed for water boosted rocket event, such as ﬁnding lodge, event ﬁeld, transportation, etc. Prof Y. Matogawa always helped one of the authors (K.-I. Oyama). The second water boosted Rocket in Indonesia was co hosted by LAPAN. Ms. Akiba, who was the secretary in Japan, supervised all event processes with the consultation and coordination with Dr. E. Sofyan of LAPAN. The third water boosted rocket event was taken care of by Mr. B. R. Guruprasad of the Indian Space Research Organization (ISRO). Finally we would like to express our sincere thanks to Japan Space Exploration Agency (JAXA), Ministry of Education, Sport, culture, and Technology in Japan for the funding, Ministry of Science, Indonesia, LAPAN for the second water boosted rocket event and to ISRO for the 3rd water boosted rocket event. Without their understanding to space education and ﬁnancial support, this grand project, which covers many Asian/Paciﬁc countries, could not have been possible. One of the authors (K.-I. Oyama) should not forget to mention Ms T. Chiku, Space Education Center, JAXA for her continuous and dedicated work as a secretary of SEA WG since the 13th APRSAF. The manuscript was completed while one of the authors (K.-I. Oyama) is a visiting professor of the Institute of Space Science, National Central University, Taiwan after he has retired from the Institute of Space and Astronautical Science, JAXA. He expresses his sincere thanks to National Central University for the support.

References 1. Tomita, N., and R. Watanabe, and A. Nebylov, Hand-on Education System Using water Rocket, IAC-04-IAF-P.1.05, 2004. 2. Prusa, J. M., Hydrodynamics of a water rocket, SAM (Society for Industrial Applied Mathematics) Review 42, 4,719–726, 2000.

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3. http://www.aprsaf.org/text/ap13-info1.html#SEAWG. 4. http://edu.jaxa.jp/ Water Rockets, Educator’s manual, Japan Aerospace Exploration Agency. 5. DVD: Water Rockets-For Educators-, Space Education Center, Japan Aerospace Exploration Agency. 6. http://en.wikipedia.org/wiki/Water rocket. 7. www.npl.co.uk/waterrockets, A guide to building and understanding the physics of water rockets. 8. http://exploration.grc.nasa.gov/education/rocket/rkbot.html, water rocket by NASA. 9. http://www.instad.asn.au,INSTAD,Water Rocket Design Project. 10. http://www. SeedsLearn.com, Simple Science Design Drag Tests for Water Rockets. 11. http://members.aol.com/hayhurs11/h2orocket.htm Genesis Education Investigation Water Rockets.

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