Environmental Forensics: Principles & Applications

Library of Congress Cataloging-in-Publication Data Morrison, Robert D. Environmental forensics : principles and applica...

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Library of Congress Cataloging-in-Publication Data Morrison, Robert D. Environmental forensics : principles and applications / by Robert D. Morrison p. cm. Includes bibliographical references and index. ISBN 0-8493-2058-5 (alk. paper) 1. Environmental forensics. 2. Solvents — Environmental aspects. 3. Organochlorine compounds — Environmental aspects. 4. Petroleum chemicals — Environmental aspects. 5. Hydrocarbons — Environmental aspects. 6. Groundwater flow. I. Title. TD193.4.M67 1999 628.5—dc21

99-40624 CIP

This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. The consent of CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press LLC for such copying. Direct all inquiries to CRC Press LLC, 2000 Corporate Blvd., N.W., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks and are used for identification and explanation, without intent to infringe. © 2000 by CRC Press LLC No claim to original U.S. Government works International Standard Book Number 0-8493-2058-5 Library of Congress Card Number 99-40624 Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on acid-free paper

Preface Environmental forensics is the systematic examination of environmental information used in litigation. The purpose of this book is to provide a working reference for the practicing environmental attorney or environmental consultant. As a working reference, the topics and examples selected are common denominator issues encountered in environmental litigation; as such, this book is not intended to be a treatise on a particular subject but rather to present information that you will likely encounter. Whenever possible, expanded mathematical or chemical discussions were relegated to the Appendices. Chapters 1 and 2 provide a working overview of information about chlorinated solvents and petroleum hydrocarbons. The foundational information in Chapters 1 and 2 was selected to assist you in deciding which forensic tools described in Chapter 4 are applicable to your case. Recognize that the forensic tools described in Chapter 4 are rapidly evolving. Whenever possible, contact the proponents of these technologies directly to ascertain their current capabilities relative to your case. Chapters 3 and 5 provide information on how to identify biased environmental data and suggestions in regard to the applications and review of biased environmental data, as well as suggestions concerning the evaluation of contaminant transport models. Chapter 6 describes techniques for forensically evaluating settlement and trial exhibits and animations. The information in this book is intended to allow you to distinguish between evidence and opinions based on scientific methods vs. junk science. Regardless of your position on an allegation, everyone is well served if valid technical information and interpretations form the basis for an expert witness opinion. Best wishes for a successful and informed environmental career. Robert D. Morrison San Diego, CA

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The Author Robert Daniel Morrison has a B.S. in Geology, an M.S. in Environmental Studies, an M.S. in Environmental Engineering, and a Ph.D. in Soil Physics from the University of Wisconsin at Madison. Dr. Morrison has been working for 27 years in the environmental field on issues related to soil and groundwater contamination. He specializes in the forensic review and interpretation of scientific data used in support of litigation involving soil and groundwater contamination. Dr. Morrison has published articles and books on soil and groundwater contamination topics and has shared this information via lectures throughout the world. He is active in reviewing technical papers on forensics techniques and has served on the editorial boards of Ground Water and Groundwater Monitoring Review and Remediation and currently serves on the editorial board of The International Journal of Environmental Forensics. Dr. Morrison has worked as an expert witness and consultant for the U.S. Department of Justice, the Environmental Protection Agency (EPA), and numerous law firms on cases where environmental forensics were used to allocate responsibility. In the capacity as an expert witness and confidential consultant, Dr. Morrison has provided testimony in numerous cases, some with claims ranging from tens of thousands of dollars to as much as five billion dollars.

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Acknowledgments Scientists who directly assisted in the preparation of this book include Sherri Komelyan, Kathleen Calsbeck, Jamie Campos, Kevin Vaughn, and Christian Benitez of R. Morrison & Associates, Inc. Numerous colleagues and researchers provided assistance in the form of communication and information. Special thanks to Dr. Jim Bruya, of Friedman & Bruya in Seattle, WA; Dr. James Szecsody, of Battelle Northwest Laboratories in Hanford, WA; Dr. Blayne Hartman, of TEG in Solano Beach, CA; David Kaminski, of QED in Ann Arbor, MI; Kevin Beneteau, of Golder Associates, Calgary, Alberta, Canada; Dr. Barbara Sherwood Lollar, Department of Geology, University of Toronto, Canada; Dawn Zemo, of Geomatrix in San Francisco, CA; and Dr. Ramona Aravena, University of Waterloo, Waterloo, Ontario, Canada. Special thanks to the wonderful group at CRC Press, especially Becky McEldowney, who provided creative insight and inspiration, and Debrah Goldfarb. who provided marketing direction. Special thanks, too, to Sarah Nicely Fortener of Nicely Creative Services in Geneva, IL, for her wonderful editing of this book. Special acknowledgement to my wife, Donna, who tolerated my night stalking and the use of her computer during this effort.

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Contents Chapters 1 through 6 1

An Overview of the History, Chemistry, and Transport of Chlorinated Solvents 1.1 Introduction 1.2 Chronology and Use of Chlorinated Solvents 1.2.1 Trichloroethylene (TCE) 1.2.2 Tetrachloroethylene (PCE, or Perchloroethylene) 1.2.3 1,1,1-Trichloroethane (1,1,1-TCA, or Methylchloroform) 1.2.4 Methylene Chloride (Dichloromethane) 1.3 Chemistry and Properties of Chlorinated Solvents 1.3.1 Terminology and Classification 1.3.2 Chemical Structure and Properties 1.3.3 Henry’s Law Constant (KH) 1.3.4 Liquid Density 1.3.5 Solubility 1.3.6 Viscosity 1.3.7 Vapor Pressure and Density 1.3.8 Boiling Point and Latent Heat of Vaporization 1.3.9 Octanol/Water Partition Coefficient (Kow) 1.3.10 Hydrolysis 1.3.11 Sorption 1.3.12 Biodegradation 1.3.12.1 Anaerobic Degradation 1.3.12.2 Aerobic Degradation 1.4 Transport of Chlorinated Solvents through Soil 1.5 Impact of Cosolvency on Transport through Soil 1.6 Transport of Vapors in Soil 1.7 Transport through the Capillary Fringe 1.8 Transport in Groundwater 1.8.1 Darcy’s Law 1.8.2 Porosity (ne) 1.8.3 Permeability (k) and Hydraulic Conductivity (K) 1.8.4 Retardation 1.8.5 Dispersivity

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1.8.6 1.8.7 1.8.8 References

Free Phase Solvent Transport in Groundwater Transport in Fractures Transport in Fractured Porous Media

2

Chemistry and Transport of Petroleum Hydrocarbons 2.1 Introduction 2.2 Chemistry of Crude Oil 2.3 Chemistry of Refined Products 2.3.1 Gasoline 2.3.2 Diesel 2.4 Chemical Reactions in the Vadose Zone 2.4.1 Henry’s Law Constant (KH) 2.4.2 Liquid Density 2.4.3 Solubility 2.4.4 Viscosity 2.4.5 Vapor Pressure and Vapor Density 2.4.6 Sorption 2.4.7 Retardation 2.4.8 Biodegradation 2.5 Overview of Transport through the Unsaturated (Vadose) Zone 2.5.1 Transport through Soil 2.5.2 Cosolvation and Colloidal Transport 2.5.3 Residual Saturation 2.5.4 Vapor Phase Transport 2.6 Hydrocarbon Interactions at the Capillary Fringe 2.6.1 Hydrocarbon Solubilization from the Capillary Fringe into Groundwater 2.7 Transport in Groundwater 2.7.1 Rate of Transport 2.7.2 MTBE Transport in Groundwater 2.7.3 Length of a Petroleum Hydrocarbon Plume 2.7.4 Transport in Fractures References

3

Identification of Biased Environmental Data 3.1 Introduction 3.2 Geologic Characterization 3.2.1 Boring Log Terminology 3.3 Interpretation of Geologic Information 3.4 Soil Collection for Chemical Analyses 3.4.1 Soil Sampling Equipment 3.4.2 Subsampling and Sample Transfer 3.4.3 Soil Compositing

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3.5

Groundwater Characterization 3.5.1 Monitoring Well Location 3.5.2 Installation of Groundwater Monitoring Wells 3.5.3 Sampling Plan 3.5.4 Groundwater Purging 3.5.5 Groundwater Sampling 3.5.6 Sampling Equipment and Sequence 3.5.7 Equipment Decontamination 3.5.8 Sample Containers 3.5.9 Sample Filtration, Preservation, and Holding Times 3.5.10 Field Measurements 3.5.11 Field Quality Control Samples 3.6 Soil Vapor Surveys 3.6.1 Interpretation of Soil Vapor Data 3.7 Analytical Methods 3.7.1 Misidentification of Analytes 3.7.2 Laboratory Documentation 3.7.2.1 Chain of Custody 3.7.2.2 Document Control/Control Log 3.7.2.3 Signature List 3.7.2.4 Logbook Cover Sheet 3.7.2.5 Sample Kit Preparation Log 3.7.2.6 Field Logs 3.7.2.7 Sample Receipt Checklist and/or Log 3.7.2.8 Sample Preparation Logbook 3.7.2.9 Sample Analysis Log 3.7.2.10 Instrument Run Log 3.7.2.11 Instrument Maintenance Log 3.7.2.12 Certificates of Analysis 3.7.2.13 Laboratory Certification 3.7.3 Laboratory Quality Control Samples References 4

Forensic Techniques Used in Environmental Litigation 4.1 Introduction 4.2 Aerial Photography 4.3 Underground Storage Tank Corrosion Models 4.4 Inventory Reconciliation 4.5 Commercial Availability of a Chemical 4.6 Chemicals and Formulations Unique to a Manufacturing Process or Activity 4.6.1 Polychlorinated Biphenyls 4.7 Petroleum Refinery Throughput Analysis 4.8 Chemical Identification of Petroleum Hydrocarbons

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4.8.1 Analytical Strategy 4.8.2 Proprietary Additives: Petroleum Hydrocarbons 4.8.3 Anti-Knock Additives (Alkyl Leads) 4.8.4 Lead Scavengers 4.8.5 Oxygenates 4.8.6 Trace Inorganics 4.8.7 Petroleum Dyes 4.8.8 Octane Rating 4.9 Radioactive Isotope Dating 4.9.1 Dating Groundwater with Isotopes 4.9.2 Isotopic Analysis for Petroleum Hydrocarbons 4.9.3 Lead Isotope Analysis 4.9.4 Lead Isotope Analysis for Gasoline Fingerprinting 4.9.5 Isotope Analysis of Crude Oil and BTEX 4.9.6 Isotope Analysis of Gas Samples 4.9.7 Isotopic Analysis of Chlorinated Solvents 4.10 Chemical and Biological Degradation Models: Petroleum Hydrocarbons 4.10.1 Weathering and Biomarkers 4.10.2 Biodegradation Models 4.10.3 Pristane/Phytane Ratios 4.10.4 BTEX Ratios 4.10.5 Challenges to BTEX Ratio Methods 4.11 Chemical Degradation Models: Chlorinated Solvents 4.12 Rapid Optical Screening Tool™ Testing References 5

Contaminant Transport Modeling 5.1 Introduction 5.2 Liquid Transport through Pavement 5.3 Vapor Transport through Pavement 5.4 Contaminant Transport in Soil 5.4.1 Challenges to Contaminant Transport Models for Soil 5.4.2 Colloidal Transport 5.4.3 Preferential Pathways 5.4.4 Cosolvent Transport 5.5 Contaminant Transport in Groundwater 5.5.1 Types of Groundwater Models 5.5.2 Selection of Boundary Conditions, Grids, and Mass Loading Rates 5.5.3 Software Applicability 5.6 Application of Groundwater Modeling in Environmental Litigation 5.6.1 Confirmation Models

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5.6.2 5.6.3 5.6.4 5.6.5 5.6.6 References 6

Reverse Models Hydrogeologic Variables Contaminant Properties Challenges to Reverse Models Challenges to Phase-Separate Reverse Models

Forensic Review of Environmental Trial Exhibits 6.1 Introduction 6.2 Exaggerated Vertical and Horizontal Scales 6.3 Selective Data Presentation 6.4 Data Contouring 6.4.1 Manual Contouring 6.4.2 Computer Contouring 6.4.2.1 Inverse Distance Method 6.4.2.2 Kriging 6.4.2.3 Minimum Curvature Method 6.4.2.4 Sheppard’s Method 6.4.2.5 Polynomial Regression 6.4.3 Color-Coded Data References Appendices

A

Sample Calculation for the Transport of PCE Vapor through Concrete Pavement A.1 Introduction A.2 Sample Calculation References

B

Sample Calculation for the Transport of PCE Liquid through Concrete via Diffusion B.1 Introduction B.2 Sample Calculation References

C

Properties of Alcohol Oxygenates and Ether Oxygenates

D

Advective and Partitioning Transport Equations of Radon for Detecting Diesel in Groundwater D.1 Introduction D.2 Derivation D.3 Conclusions References

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E

Chemical and Commercial Synonyms for Selected Chlorinated Solvents and Aromatic Hydrocarbons References

F

Laboratory Terms and Definitions

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Chapters 1 through 6

1

An Overview of the History, Chemistry, and Transport of Chlorinated Solvents

PCE formulated by Faraday in 1821.

1.1 INTRODUCTION Chlorinated solvents are one of the most frequently encountered contaminants in environmental investigations (Siegrist, 1993). Trichloroethylene (TCE) and tetrachloroethylene (PCE), for example, were detected in 945 groundwater-supplied drinking systems in an Environmental Protection Agency survey of drinking wells in the United States. In September 1997, TCE and PCE were detected at 852 and 771, respectively, of the 1420 National Priority List (NPL) or Superfund sites in the United States (Butler and Hayes, 1999). As a result of the frequency of detection and toxicity of chlorinated solvents, millions and often billions of dollars are alleged in litigation associated with their investigation and remediation.

1.2 CHRONOLOGY AND USE OF CHLORINATED SOLVENTS The global production and use of chlorinated solvents began after World War II, with volumes gradually increasing through the 1950s and 1960s. In the early years of solvent use, the military was the primary consumer. From 1978 through 1988, the total production of chlorinated solvents in the United States declined modestly, by about 11%. After 1988, the decline was more substantial, amounting to about 45% between 1978 and 1985. The decrease in the demand of chlorinated solvents during 1978 to 1985 reflects the production ban on 1,1,1-trichloroethane (1,1,1-TCA, or TCA) and Freon-113 (1,1,2-trichloro-1,2,2-trifluoroethane). Another factor in this decrease was the increased regulations on TCA, tetrachloroethylene (PCE), and

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TABLE 1.1 Chlorinated Solvent Uses in the U.S. in 1988 Application

TCEa

PCEb

MCc

TCAd

Freon-113e

Total

Vapor degreasing Drycleaning Intermediate Cold cleaning Electronics Aerosols Paint stripping Adhesives Coatings Flexible foam Pharmaceuticals Textiles Food processing Pesticides Other Total demand Production

47.1 — 7.0 14.1 3.2 — — — — — — 1.0 — — — 72 82

18.1 120.0 80.0 6.7 1.3 3.0 — — 7.0 — — 2.0 — — 20.0 258 226

5.8 — — 17.2 16.9 20.0 50.0 5.0 — 23.2 14.4 — 4.2 1.0 49.3 207 229

106.0 — 22.5 17.0 40.8 40.8 — 26.0 17.2 — — 7.0 — 3.0 10.5 298 328

17.7 2.0 5.3 40.2 0.6 0.6 — — — — — 0.5 — — 7.5 78 78

194.7 122.0 114.6 90.2 78.6 64.4 50.0 31.0 24.2 23.2 14.4 10.5 4.2 4.0 87.3 913 943

a b c d e

TCE = trichloroethylene. PCE = tetrachloroethylene. MC = methylene chloride. TCA = 1,1,1-trichloroethane. Freon-113 = trichlorotrifluoroethane.

methylene chloride (MC). The total global capacity for chlorinated solvents in 1994 was about 1.7 million metric tons, with the U.S. accounting for about 36% of the total, followed by Western Europe and Japan at 40% and 23%, respectively. Table 1.1 summarizes the consumption of chlorinated solvent use in the U.S. in 1988 for various industries and applications (IRTA, 1994). The primary use of chlorinated solvents is vapor degreasing. In vapor degreasing, solvents are boiled (150 to 250∞F), thereby producing a heated vapor zone within the degreaser. A single-chamber vapor degreaser contains heating coils at the bottom to boil the liquid solvent, and cooling coils surround the top to contain the vapor (see Figure 1.1). Metal parts are lowered into the solvent vapor zone for cleaning, usually in a metal basket. The warm solvent condenses on the colder parts, dissolving the contaminants or oil into the solvent. In some instances, a spray wand is manually used to spray the solvent vapor on the parts in the basket. The vapor zone height is limited by the cooling coils that condense the solvents and return them to the liquid at the bottom of the degreaser. The mixture drains to a water/solvent separator, where the heavier solvent sinks to the bottom and the condensed water and dissolved solvent are disposed. While many vapor degreasers are more sophisticated, with vacuum

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FIGURE 1.1 Single-stage vapor degreaser.

systems, multiple chambers, attached distillation units for removing the soils from the solvent, ultrasonics, and mechanized basket trays, the general operating principle is the same. Cold cleaning is another degreasing technique. Cold cleaning is similar to vapor degreasing, except that the solvent is maintained at room temperature or is heated to a temperature below the solvent’s boiling point. Like vapor degreasing, metal parts are dipped into the liquid solvent, and the contaminants are dissolved and removed from the metal. Cold cleaning is less effective than vapor degreasing because the solvent is not boiled clean. The heated solvent used in vapor degreasing is also more effective in degreasing than the same solvent used at room temperature for the same purpose. The dominant cold cleaning solvent is 1,1,1-TCA. Equipment related to vapor degreasers includes distillation or evaporation stills used to recover solvents. The two types of stills are batch and continuous. In a batch still (also differential, Raleigh, or pot distillation), a fixed amount of spent solvent is placed inside a heated evaporation chamber from which the condensed vapor is withdrawn. Continuous, multistage distillation (also fractional distillation) is used when there is a need for a high degree of distillation purity, if the amount of spent solvent to be recovered is large, or when differences in solvent volatility are small. Continuous distillation is accomplished in a column equipped with trays or packing materials to facilitate contact between the liquid and vapor phases. Liquid is introduced continuously into the column at the top while the vapor moves upward, becoming more enriched with the more volatile compounds. The high boiling compounds thereby become concentrated in the liquid.

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TABLE 1.2 Solvent Compatibility with Distillation Stills Distillation Model/Manufacturer SD-15 Acra Electric; Schiller Park, IL LS-JR Finish Engineering; Erie, PA ER8; Westport, MA RS-20 Recyclene Products; San Francisco, CA

Boiling Range (∞F) N/A 100–320 <300 <400

Solvents Recycled TCE, 1,1,1-TCA, PCE Alcohols, aromatics, chlorinated solvents, aliphatics, ketones Chlorinated solvents Methylene chloride, acetone, methanol, 1,1,1-TCA, n-butyl-acetate, xylene, mineral spirits, isopropyl alcohol, Stoddard solvents

Knowledge of the vapor degreaser or solvent still manufacturer is useful in identifying what solvents are compatible with the equipment. Obtaining the original operating manual from the manufacturer will provide this information. Table 1.2 summarizes the boiling range and types of solvents that can be recycled for several distillation stills (California Department of Health Services, 1988). Chlorinated solvents are used in the electronics manufacturing industry, especially in the production of semiconductors. Applications include: • • • •

Semiconductor wafer fabrication and assembly Printed circuit board fabrication and assembly In situ generation of etchants Miscellaneous critical electronic applications

Chlorinated solvents used in the semiconductor industry include 1,1,2-trichloro1,2,2-trifluoroethane (Freon-113); 1,1,1-trichloroethane (TCA); methylene chloride (MC); trichloroethene (TCE); and tetrachloroethylene (PCE). Freon-113 and TCA applications include removal of flux from printed circuit boards after the various electronic components are soldered to the board. TCA is frequently combined with alcohol because alcohol is an effective flux remover. TCA and methylene chloride are also used in the photoresist process. In the early 1990s, all photoresist solutions were solvent, aqueous, or semi-aqueous solutions. In the photoresist process, dryfilm photoresist is applied to the copper substrate of the electronic board and the desired circuitry is imprinted by shining a high-intensity light through a photomask. If a negative photoresist is used, the areas of the film exposed to the light polymerize, whereas the unexposed areas do not. After the developer carries away the unpolymerized material, the photoresist is then developed with a solvent such as TCA, which is followed by the etching step. The remaining photoresist is then stripped, often with methylene chloride. Table 1.3 lists the composition of formulations

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TABLE 1.3 Compounds Associated with the Photoresist Process in Wafer Fabrication Proprietary Compound

Composition

Waycoat photoresist Microresist developer Photoresist developer I Photoresist developer II Negative photoresist Positive photoresist Ultrasonic degreaser Stripper 712D

85% xylene 95–100% Stoddard solvent 10–30% aromatic hydrocarbons; >60% aliphatic hydrocarbons Mixture of petroleum solvents 48% 2-ethoxyethylacetate; 5% n-butyl acetate; 5% xylene. 52% 2-ethoxyethylacetate; 6% n-butyl acetate; 6% xylene. Perfluoroisobutylene Dodecyl benzene sulfonic acid; 1,2,4-trichlorobenzene, phenols; pH = 2.4–2.6 63% methylene chloride and chlorobenzenes; 23% phenyl sulfonic acid; 14% phenols and derivatives. 75% chlorinated solvents; orthocresol, dodecylbenzosulfonic acid, PCE, and dichlorobenzene <25% phenol; <25% sulfonic acid; <25% aromatic solvents; <50% chlorobenzenes

Negative photoresist stripper J100 (Kodak) Microstrip Burmar

associated with the photoresist process (California Department of Health Services, 1988). Wafer fabrication is an integral process of semiconductor manufacturing. Potential contaminants associated with this process include xylene, n-butyl acetate, ammonium fluoride, hydrofluoric acid, sulfuric acid, arsenic, antimony, copper, zinc, phosphorus, boron, nitric acid, acetic acid, chromic acid, and phosphoric acid. Dopants used to change the electrical properties of the silicon wafer include antimony, arsenic, boron, and aluminum. In some cases, the chronological use of dopants provides a means of determining the earliest date that contaminants with these compounds were introduced into the environment. A diagram of a wafer fabrication process used since 1986 is shown in Figure 1.2. While the use and application of chlorinated solvents for semiconductor manufacturing has evolved with time, the manufacturing processes remains similar. The volume of solvents for different electronic applications in the U.S. for 1987 and 1989 is shown on Table 1.4 (California Department of Toxic Substance Control, 1991). As shown in Table 1.4, about 72,000 metric tons of chlorinated solvents were used in 1987. Freon-113 was widely used in 1987, followed by TCA and methylene chloride. The use of TCA and PCE during this time frame is believed to be associated with degreasing applications. Of the electronic board manufacturing activities, solvent use was highest for board assembly. In environmental litigation, the most commonly encountered solvents are TCE, PCE, 1,1,1-TCA, and methylene chloride. Information about the specific applications and historical production of these solvents is summarized in the following sections.

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FIGURE 1.2 Description of processes for semiconductor wafer fabrication, post-1986.

1.2.1 TRICHLOROETHYLENE (TCE) Trichloroethylene is used as a metal degreaser and has been available worldwide for about 50 years. Trichloroethylene was first prepared by Fisher in 1864 during experiments on the reduction of hexachloroethane with hydrogen (Hardie, 1964).

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TABLE 1.4 Use of Chlorinated Solvents in the Electronic Industry in the U.S. in 1987 and 1989 1987 (1989) Applications

Freon-113

Wafer fabrication Wafer assembly Developing photoresist Stripping photoresist Defluxing boards Critical cleaning In situ etchant generation

5.4 2.1 0.8 — 25.6 9.2 0.2

(4.9)

(23.0) (8.3) (0.2)

TCA

MC

TCE

PCE

0.3 (0.5) 1.1 (2.5) (3.2) — 6.6 (8.0) — 0.2 (0.2)

1.3 (0.9) 0.5 (0.8) — 13.8 (5.0) 0.7 (0.6) — —

2.2 (3.0) 0.3 (0.5) — — 0.5 (0.6) — —

0.5 (0.7) (0.3) — — 0.5 (0.6) — —

Note: Figures are in units of thousands of metric tons.

Trichloroethylene production began in Austria and the United Kingdom in 1908; Germany, in 1910; the U.S., 1925; and Japan, 1935. Trichloroethylene is manufactured by the catalytic oxidation of 1,1,2,2-tetrachloroethane (U.S. patent number 2,951,103) and the catalytic chlorination of acetylene (U.S. patent number 2,938,931). In the U.S., the Vietnam War accelerated the use of trichloroethylene for aircraft parts and engine maintenance and production, cleaning rocket hardware, and space applications and in the automotive industries. The demand for trichloroethylene in the U.S. peaked in 1968 at about 261,000 metric tons. In 1970, trichloroethylene accounted for 82% of all of the chlorinated solvents used in vapor degreasing; in 1976, its share had declined to 42%. By 1975, numerous federal, state, and local regulations in the U.S. existed that restricted the use of TCE due to its being a suspected carcinogen. In 1975, the National Cancer Institute reported to the National Institute of Occupational Safety and Health (NIOSH) that PCE and TCE were “suspect human carcinogens” and that exposure should be minimized. NIOSH recommended that TCA be handled with caution due to its chemical similarity to PCE and TCE. In 1976, the U.S. exported about 16 million kg, primarily to the Federal Republic of Germany (3.8 million kg), France (3.4 million kg), Mexico (2.1 million kg), and Brazil (2 million kg) (U.S. Department of Commerce, 1977). The demand for trichloroethylene in the U.S. in 1995 was about 128 million pounds, of which about 16.5 million pounds were imported and about 40 million pounds exported (Halogenated Solvents Industry Alliance, 1996). While trichloroethylene is an excellent vapor degreaser due to its ability to degrease faster and more thoroughly than alkaline cleaners, its suspected carcogenicity resulted in many users switching to TCA and PCE in the 1970s and 1980s. TCA gradually replaced TCE from 1963 through 1988; as the demand for trichloroethylene decreased, the use of TCA increased. In February of 1995, the International Agency for Research on Cancer (IARC) concluded that there was sufficient epidemiological and animal

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testing data to classify PCE and TCE as “probable human carcinogens”. The IARC did not classify 1,1,1-TCA as a human carcinogen. In 1996, the applications of TCE in the U.S. was about 55% for metal cleaning and degreasing, 41% as a chemical intermediate, and 4% for miscellaneous applications. Water-based products and compounds such as n-propyl bromide (EnviroChem) became more common as a replacement for TCE. In the U.S., trichloroethylene is produced by Dow Chemical Company and PPG Industries. Global consumption of trichloroethylene decreased from 224,000 metric tons in 1990 to 214,000 in 1993, but there is expected to be an increase in TCE consumption as a precursor for HFC-134a production. The annual trichloroethylene consumption in the U.S. and Japan from 1993 to 1998 was expected to increase about 16% and 6%, respectively. TCE consumption is expected to decrease in Western Europe by about 2% annually, as decreases in the use of TCE in metal degreasing will offset increases in HFC-134a precursor consumption. In Western Europe, trichloroethylene is produced by Elf Atochem (France), Dow Europe/Switzerland (Germany), EniChem (Spain), ICI Chemicals and Polymers (United Kingdom) and Solvay/Belgium (France and Italy). In Western Europe, according to the European Chlorinated Solvent Association (1998), TCE production from 1993 to 1997 was as follows: 1993 and 1994 (94,000 metric tons), 1995 (103,000 metric tons), 1996 (99,000 metric tons), and 1997 (92,000 metric tons). The increase in TCE production in 1995 and 1996 is due to the replacement of 1,1,1trichloroethane with TCE for vapor degreasing.

1.2.2 TETRACHLOROETHYLENE (PCE, OR PERCHLOROETHYLENE) Tetrachloroethylene was first formulated in 1821 (Izzo, 1992). Global demand of PCE decreased from 513,000 metric tons in 1990 to 338,000 metric tons in 1993. The use of PCE as a precursor in the production of chlorofluorocarbon-113 (CFC-113) ceased in 1996 due to its association with ozone depletion. In some countries, PCE consumption is expected to increase due to its use in manufacturing hydrochlorofluorocarbon-123 (HCFC-123) and hydrofluorocarbon-134a (HFC-134a). From 1993 to 1998, PCE consumption in the U.S. and Japan increased about 3% but decreased about 12% annually in Western Europe. Tetrachloroethylene has been the chlorinated solvent of choice in the drycleaning industry since the late 1930s. By the late 1940s or early 1950s, PCE replaced synthetic solvents such as carbon tetrachloride in the drycleaning industry. Prior to the 1960s, however, petroleum derivatives were still the dominant solvents in the drycleaning industry in the U.S., where the demand for PCE increased steadily from 1972 to 1981. PCE usage peaked in 1975 at about 348,000 metric tons. After 1975, a decline in demand continued until 1994, when the demand for tetrachloroethylene was about 113,000 metric tons. In the late 1980s, drycleaners consumed 56% of the PCE in the U.S. In 1990, PCE production in the U.S. was about 383 million pounds, of which 55 million pounds were exported. In 1990, about 72.1 million pounds were

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FIGURE 1.3 PCE demand by the drycleaning industry in the U.S. from 1985 to 1997.

imported into the U.S. (Halogenated Solvents Industry Alliance, 1994). In the U.S., PCE is produced by Dow Chemical USA, PPG Industries, and Vulcan Materials Company. Figure 1.3 summarizes PCE usage in the U.S. by drycleaners from 1985 to 1997 (Halogenated Solvents Industry Alliance, 1998a). In 1990, tetrachloroethylene use in the U.S. was 50% for drycleaning/textile processing, 25% as a chemical intermediate, and 15% in metal cleaning and degreasing, with miscellaneous uses accounting for about 10% (Halogenated Solvents Industry Alliance, 1998a). In 1992, there were approximately 34,000 drycleaning businesses in the U.S., with about 28,000 facilities using PCE. In 1992, the typical commercial drycleaner processed about 75,000 pounds of clothing annually, which represented about 90% of the industry. Approximately 25,000 of these commercial drycleaners used PCE (about 120,000 metric tons annually) (Wolf, 1992). The three categories of drycleaning machines that use tetrachloroethylene are • A transfer machine, in which the clothing is washed in one unit and physically transferred to a dryer for drying. Emissions from the washer and dryer can be uncontrolled or they can be routed to a control device. Approximately 30% of all drycleaning machines are transfer units. • A dry-to-dry vented unit, in which the clothing is washed and dried in the same cylinder. The PCE emitted from the unit can be uncontrolled or vented to a control device. Approximately 70% of the retail drycleaners in the U.S. have dry-to-dry units. • A dry-to-dry closed loop unit, in which the wash and dry cycles occur in the same unit. Tetrachloroethylene emissions are controlled within the unit with a refrigerated condenser.

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Most drycleaners (about 90%) remove soil, dust, hair, and lint from the solvent with cartridges of activated carbon. Distillation units are used to remove oils and fats from the solvent. After filtration through the activated carbon or tubular filters, the solvent is heated to between 190 and 250∞F. The PCE is condensed and recovered, and the remaining sludge can contain up to 50% PCE. Some drycleaners reclaim the PCE in the sludge in a muck cooker or a cooker/still combination. In Western Europe, tetrachloroethylene production declined about 4.8% between 1993 and 1997, from 84,000 tons in 1993 to 68,000 tons in 1997, due to the replacement of obsolete open drycleaning machines with closed systems. From 1988 to 1998, PCE use in the drycleaning industry in Western Europe declined by about two thirds due to replacement of older equipment with machines with refrigeration technology that reduced the volume required for operation (Halogenated Solvents Industry Alliance, 1998). In Western Europe, TCE is produced by Elf Atochem (France), Dow Europe/Switzerland (Germany), EniChem (Spain), ICI Chemicals and Polymers (United Kingdom), and Solvay/Belgium (France and Italy) (European Chlorinated Solvent Association, 1996).

1.2.3 1,1,1-TRICHLOROETHANE (1,1,1-TCA, OR METHYLCHLOROFORM) 1,1,1-Trichloroethane was created in 1840 by the reaction of chlorine with 1,1dichloroethane. TCA was first reported in the U.S. in 1946 (U.S. Tariff Commission, 1947). In the U.S., it is produced via the chlorination of vinyl chloride derived from 1,2-dichloroethane, via hydrochlorination of vinylidene chloride derived from 1,2-dichloroethane, or through the thermal chlorination of ethane. In Japan, 1,1,1TCA is produced by the chlorination of vinyl chloride. TCA production and consumption have decreased dramatically due to its ozone depletion potential in the upper atmosphere. Global consumption from 1990 to 1993 decreased from 665,000 to 349,000 metric tons. On a worldwide basis, production was reduced to 50% of its 1989 levels throughout 1994 and 1995. Since 1995, TCA in Europe has been used only as a precursor chemical. Except for its use as a precursor, worldwide production essentially ceased in 1996. TCA is the historical solvent of choice in cold cleaning. The demand for TCA increased substantially over about three decades (1967 to 1994) in the U.S. In the late 1960s, when the use of TCE came under scrutiny due to its identification as an animal carcinogen, TCA was often used as its replacement. The historical demand for TCA in the U.S. between 1967 and 1994 peaked in 1988 when about 298,000 metric tons were consumed. TCA usage declined in 1991 due to an amendment to the Montreal Protocol that called for a complete phase-out of TCA by 1996 due to its contribution to ozone depletion. In Western Europe, most manufacturers ceased production by the end of 1995 with the exception of its use as a chemical intermediate and for some permitted uses for virgin solvents. By 1994, the U.S. demand for TCA had decreased to about 159,000 metric tons.

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1.2.4 METHYLENE CHLORIDE (DICHLOROMETHANE) Methylene chloride was introduced as a replacement for more flammable solvents over 60 years ago. Total demand in the U.S. in 1996 was about 285 million pounds, of which about 20 million pounds were imported and about 130 million pounds exported (Halogenated Solvents Industry Alliance, 1998b). Globally, methylene chloride is produced by the following manufacturers: • • • • • • •

Aragonesas and Erkimia (Spain) Elf Atochem (France) Dow Chemical and Vulcan Materials (U.S.) Dow Europe/Switzerland (Germany) LIL Europe (Germany) ICI Chemical and Polymers (United Kingdom) Solvay/Belgium (France and Italy)

Methylene chloride consumption in Western Europe decreased from about 190,000 to 135,000 metric tons from 1985 to 1994 (European Chlorinated Solvent Association, 1997). Methylene chloride is the active ingredient in many paint removers, including commercial and furniture strippers and home paint removers. It is also used in aircraft maintenance due to its ability to penetrate, blister, and remove a variety of paint coatings. In the maintenance of military and commercial aircraft, a methylene chloride-based product is often specified for surface inspection for damage. Since the mid-1990s, methylene chloride has replaced 1,1,1-TCA in nonflammable adhesive formulations, including the fabrication of upholstery foam. TCA is currently the leading auxiliary blowing agent used to produce slabstock flexible polyurethane foams in the furniture and bedding industries. In the pharmaceutical industry, methylene chloride is used as a reaction and recrystallization solvent for extraction, as well as a carrier for pharmaceutical tablet coatings. In the chemical processing industry, it is used in the production of cellulose triacetate, which serves as a base for photographic film. The uses of methylene chloride in the U.S. in 1996 and Western Europe in 1994 as a percentage of the total consumption are shown on Table 1.5 (European Chlorinated Solvent Association, 1997).

1.3 CHEMISTRY AND PROPERTIES OF CHLORINATED SOLVENTS 1.3.1 TERMINOLOGY AND CLASSIFICATION Chlorinated solvents include a wide range of compounds. As such, a common terminology for describing these compounds is useful. Acronyms used in environmental reports to characterize chlorinated solvents and non-chlorinated compounds as a function of their specific density include the following terms (Lizette et al., 1997):

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TABLE 1.5 Use of Methylene Chloride in the U.S. and Western Europe Applications

United States (1996)

Western Europe (1994)

30 16 11 10 10 9 8 6

19.14 — 11.73 — 40.71 8.67 — 17.92

Paint stripping Adhesives Aerosols and coatings Foam manufacturing Pharmaceuticals Chemical processing Metal cleaning Miscellaneous Note: Figures are percent of total usage.

• NAPL (non-aqueous phase liquid) • DNAPL (dense non-aqueous phase liquid) • LNAPL (light non-aqueous phase liquid)

A NAPL is generally immiscible with water. The term “free phase liquid” is used to describe a NAPL or DNAPL/LNAPL mixture (U.S. EPA, 1992). A DNAPL describes a chemical with a fluid density greater than 1.01 g/cm3 and a vapor pressure less than 300 torr (a torr is equal to 1/760th of a standard atmosphere or about 1 mmHg). Examples of DNAPLs include acetic acid, phenol, dichloroethylene, carbon disulfide, naphthalene, polychlorinated biphenyls, ethylene dichloride, sulfuric acid, parathion, tetrachloroethylene, trichloroethylene, and methyl bromide. LNAPLs are compounds with a fluid density less than water (about 1.01 g/cm3) and include mineral spirits #10, hexane, gasoline, benzene, butyl acetate, turpentine, ether, crude oil, and diethyl sulfide. Another classification scheme is based on the degree of halogenation and whether the compound is volatile or semi-volatile. Classes of chlorinated hydrocarbons based on this scheme are summarized in Table 1.6. Properties of chlorinated solvents affecting their fate and transport through the subsurface include their chemical structure, their Henry’s Law constant, liquid density, water solubility, viscosity, vapor pressure and density, boiling point, latent heat of vaporization, and the octanol partition coefficient. Reactions that impact the movement and transformation of solvents in the subsurface and are interrelated with these chemical and physical properties include hydrolysis, sorption, and biodegradation.

1.3.2 CHEMICAL STRUCTURE AND PROPERTIES The major chlorinated solvents used in industry are TCE, PCE, 1,1,1-TCA, the Freons (primarily chlorofluorocarbon-113, or CFC-113), and methylene chloride. The chemical structures of these solvents are shown on Figure 1.4. Trichloroethylene (TCE) and perchloroethylene (PCE) have an ethylene or double-bonded carbon

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TABLE 1.6 Classification of Chlorinated Solvents Based on Degree of Halogenation and Volatility Halogenated Volatiles Chlorobenzene, 1,2-dichloropropane; 1,1-dichloroethylene; 1,2-dichloroethane; trans-1,2-dichloroethylene; cis-1,2-dichloroethylene; 1,1,1-trichloroethane; methylene chloride; 1,1,2-trichloroethane; trichloroethylene (TCE); chloroform; carbon tetrachloride; 1,1,2,2-tetrachloroethane; tetrachloroethylene (PCE); ethylene dibromide Halogenated Semi-Volatiles 1,1-dichlorobenzene; 1,2-dichlorobenzene; Aroclor-1242; Aroclor-1254; Aroclor-1260; chlordane; dieldrin; 2,3,4,6-tetrachlorophenol; pentachlorophenol Non-Halogenated Semi-Volatiles 2-methyl naphthalene; o-cresol; p-cresol; 2,3-dimethylphenol; m-cresol; phenol; naphthalene; benzo(a)anthracene; fluorene; acenaphthene; anthracene; dibenzo(a,h)anthracene; fluoranthene; pyrene; chrysene; 2,4-dinitrophenol Miscellaneous Coal tar, creosote

structure with three and four chlorines, respectively. Methylene chloride is a methylene chlorideane structure containing two chlorine atoms. Trichloroethane (TCA) and CFC-113 are ethane derivatives. 1,1,1-TCA has three chlorines, all on one carbon. CFC-113 is fully halogenated with three chlorines and three fluorine atoms. Freon is a chlorofluorocarbon because it contains a fluorine atom.

FIGURE 1.4 Chemical structure of PCE, TCE, TCA, Freon-113, and methylene chloride.

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TABLE 1.7 Henry’s Law Constant for Selected Chlorinated Solvents Henry’s Law Constant (atm-m3/mol)

Compound Trichloroethylene (TCE) Tetrachloroethylene (PCE) Carbon tetrachloride (PCM) Chloroform (TCM) Dichloromethane (DCM) 1,2-Dibromomethane (EDB) cis-1,2-Dichloroethylene (1,2-DCE) trans-1,2-Dichloroethylene (1,2-DCE) 1,1,1-Trichloroethane (TCA)

0.00937 0.0174 0.0298 0.00358 0.00212 0.000680 0.000374 0.000916 0.0167

1.3.3 HENRY’S LAW CONSTANT (KH) The Henry’s Law constant (KH) (also known as the air-water partition coefficient) is the ratio of the partial pressure of a compound in air to the concentration of that compound in water at a given temperature. The Henry’s Law constant is, therefore, a measure of the propensity of a compound to volatilize when moving through the soil. As the Henry’s Law value increases, the concentration of the contaminant in the soil vapor phase increases. Compounds with high Henry’s Law constants (PCE, Freon-11, Freon-113, and vinyl chloride) are more amenable to soil gas surveys and remediation via vapor extraction than compounds with low values. Values for Henry’s Law constants are usually expressed in units of moles per cubic meter for air to moles per cubic meter for water (atm-m3/mol). As a rule of thumb, compounds with a Henry’s Law constant greater than 10–3 atm-m3/mol and a molecular weight less than 200 g/mol are considered volatile (U.S. EPA, 1996). A compound with a Henry’s Law constant less than about 5 ¥ 10–5 atm-m3/mol is considered soluble and tends to remain in water (Olson and Davis, 1990). The Henry’s Law constants for TCE and PCE are 0.00937 and 0.0174 atm-m3/ mol, respectively, and Table 1.7 lists the Henry’s Law constants for selected chlorinated solvents (Montgomery, 1992; Pankow and Cherry, 1996). Values for Henry’s Law constants can also be expressed in dimensionless form as: KH¢ = KH/(RK) where KH¢ KH R K

= = = =

dimensionless Henry’s Law constant. Henry’s Law constant (atm-m3/mol). ideal gas constant (8.20575 ¥ 10–5 atm-m3/mol – K). temperature of water (degrees K).

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(Eq. 1.1)

TABLE 1.8 Chemical Formula and Liquid Density for Selected Chlorinated Solvents at 25∞C Chlorinated Solvent

Formula

Trichloroethylene (TCE) Tetrachloroethylene (PCE) 1,2-Dibromomethane (EDB)a cis-1,2-Dichloroethylene trans-1,2-Dichloroethylene 1,1,1-Trichloroethane (TCA) Chloroformb 1,2-Dichloropropane Dichloromethane (DCM)c 1,1-Dichloroethane Carbon tetrachloride (CT) Chloroethane 1,1,2,2-Tetrachloroethane 1,1,2-Trichloroethane Vinyl chloride (VC) Trichlorofluoromethane (Freon-11) Dichlorofluoromethane (Freon-12)

CHCl:CCl2 CCl2CCl2 BrCH2CH2Br CH2Cl2 CH2Cl2 C2H3Cl3 CHCl3 CH3CHClCH2Cl CHCl2F C2H4Cl2 CCl4 C2H5Cl C2H2Cl4 C2H3Cl3 C2H3Cl CCl3F CCl2F2

a b c d e

Liquid Density (g/cm3) 1.46 1.63 2.18 1.28 1.26 1.35 1.49 1.16 1.34 1.17 1.59d 0.90d 1.60 1.44 0.91d 1.49 1.35e

Also known as ethylene bromide and ethylene dibromide. Also known as trichloromethane. Also known as tetrachloromethane. At 20∞C. At 15∞C.

1.3.4 LIQUID DENSITY The density (also called specific gravity) of a substance is the ratio of its density relative to distilled water (a mass-to-volume ratio). The density of distilled water at standard temperature and pressure is about 1.0 g/mL. The density of a substance is dependent on the temperature at the time of measurement. Most chlorinated solvents have fluid densities greater than 1 g/cm3. Compounds with densities greater than 1.0 relative to water (e.g., perchloroethylene, trichloroethylene, polychlorinated biphenyls, bromoform) have a greater probability of “sinking” into the groundwater. Chlorinated solvents with fluid densities greater than water are transported vertically in the vadose zone due to gravity and capillary forces. Upon entering the groundwater, these DNAPLs are transported as a function of specific gravity and less by advection (the mass transport of groundwater) through groundwater. Liquids with densities less than 1.0 (methyl ethyl ketone, gasoline, diesel, Stoddard solvent, mineral oils) tend to “float” and spread along the capillary fringe. Table 1.8 lists selected chlorinated solvents, their formulas, and liquid densities (Montgomery, 1992; Pankow and Cherry, 1996; Ramamoorthy and Ramamoorthy, 1998).

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TABLE 1.9 Generic Categories of Solubility Generic Category

Solubility (mg/L)

Insoluble Slightly soluble Soluble Very soluble

Less than 1 1–100 100–10,000 Greater than 10,000

The density of a mixture of free phase chlorinated solvents varies as a result of the selective dissolution (i.e., effective diffusion coefficient) of individual solvents into soil or rock. Individual compounds of a DNAPL mixture such as a spent solvent migrating through a fractured clay will selectively dissolve with time into the clay. The dissolution of the chlorinated solvent into the clay results in a change in the composition and physical properties of the solvent, including liquid density (Parker et al., 1994a). In most cases, the specific density of the mixture increases as the higher density solvents persist longer in the immiscible phase.

1.3.5 SOLUBILITY The solubility of a compound is the saturated concentration of the compound in water at a known temperature and pressure. In general, the higher the water solubility, the more likely it is that the compound will be mobile in the subsurface while being less accumulative, bioaccumulative, volatile, and persistent. The lower the water solubility, the greater the probability that it will be immobilized via adsorption and will be more accumulative or bioaccumulative in organisms. The solubility of many chlorinated solvents is high. The terms “slightly soluble” or “very soluble” are used in environmental reports or by expert witnesses. These generic categories of solubility at room temperature (20 to 30∞C) are described in Table 1.9 (Kamrin, 1997). Calculated and literature solubilities of selected pure phase chlorinated solvents in water at 25∞C are shown in Table 1.10 (Huling and Weaver, 1991; Pankow and Cherry, 1996; Ramamoorthy and Ramamoorthy, 1998). The effective solubility of a multi-component solvent in water depends on the composition of the mixture and the respective breakdown products. A constituent’s solubility within this multi-component mixture may be orders of magnitude lower than the aqueous solubility of the pure chemical in water (Odencrantz et al., 1992). The concentration of a dissolved phase solvent at a threshold concentration is used as evidence of the presence of a DNAPL. In the 1980s, the rule of thumb was that, if a dissolved concentration of 10% of the saturation for the chlorinated solvent was detected, the presence of a DNAPL was inferred (Feenstra and Cherry, 1988). In the early 1990s, research indicated that concentrations 1% or more of a compound’s

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TABLE 1.10 Calculated and Literature Solubilities of Chlorinated Solvents Compound Trichloroethylene (TCE) Tetrachloroethylene (PCE) 1,2-Dibromomethane (EDB) cis-1,2-Dichloroethylene trans-1,2-Dichloroethylene 1,1,1-Trichloroethane (TCA) Chloroform (TCM) 1,2-Dichloropropane

Calculated Solubility (mg/L)a

Literature Solubility (mg/L)

1384.9 236.96 5017.5 6995.8 4389.1 1309.6 8513.5 2968.0

1100 200 4200 3500 6300 1300 8000 2800

a

Knowledge of the vapor pressure and Henry’s Law constant allows calculation of the solubility according to the following relationship: solubility (mg/L) = (vapor pressure [torr] ¥ molecular weight of the compound [g/mol])/(760 ¥ Henry’s Law constant) (Pankow and Cherry, 1996).

solubility constitute a high likelihood of the presence of a DNAPL (Cohen et al., 1993; U.S. EPA, 1992, 1993). The most recent convention is consistent with this “1% rule” (Newell and Ross, 1991; Pankow and Cherry, 1996).

1.3.6 VISCOSITY Viscosity is the property of a substance to offer internal resistance to flow. Kinematic viscosity is the absolute viscosity of the substance divided by its density. For example, the absolute viscosity of TCE is 0.57 cSt and its specific density is 1.46, so its kinematic viscosity is 0.39 cSt. A high-density liquid with a low viscosity has a low kinematic viscosity; such a fluid flows quickly through a porous medium vs. a liquid with a higher kinematic viscosity. Viscosity units encountered in environmental reports include the poise and stoke. The poise is a measure of absolute viscosity and is equal to gm/sec ¥ cm. Kinematic viscosity is expressed in stokes, which are equal to gm/sec ¥ cm ¥ density at a given temperature. A centipoise (cP) and centistoke (cSt) are each equal to 0.01 stoke. Fluid velocity through porous media is often approximated as a proportional inverse to the kinematic viscosity. In the vadose zone, TCE may move 2.5 times faster than water through the same soil (Dragun, 1988). A decrease in viscosity, therefore, increases the flow rate of a chlorinated solvent through a porous media. The kinematic viscosities of selected chlorinated solvents are summarized in Table 1.11 (Huling and Weaver, 1991; Montgomery, 1992).

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TABLE 1.11 Kinematic Viscosity of Selected Solvents Chemical

Trichloroethylene (TCE) Tetrachloroethylene (PCE) 1,2-Dibromomethane (EDB) cis-1,2-Dichloroethylene trans-1,2-Dichloroethylene 1,1,1-Trichloroethane (TCA) Chloroform (TCM) 1,2-Dichloropropane

Kinematic Viscosity (cSt) 0.39 0.54 0.79 0.38 0.32 0.62 0.38 0.75

1.3.7 VAPOR PRESSURE AND DENSITY Volatilization is the phase change of a compound from a liquid or solid to a gas. An example is the partition of TCE from a shallow or highly fluctuating groundwater into the soil vapor in the unsaturated zone. Volatilization is not a form of degradation. Factors affecting the volatility of a compound include: • • • • •

Vapor pressure Water solubility Soil moisture content Adsorption Wind speed, exposure to sunlight, air temperature, and turbulence (if the product is released at the ground surface) • Soil temperature • Depth below the land surface and time available for volatilization to occur

In general, compounds with vapor pressures exceeding 0.5 to 1 mmHg can exist in appreciable concentrations in the vapor phase near a free phase solvent. The vapor pressures and densities of selected chlorinated solvents are summarized in Table 1.12 (Montgomery1992: Pankow and Cherry, 1996; Ramamoorthy and Ramamoorthy, 1998).

1.3.8 BOILING POINT AND LATENT HEAT OF VAPORIZATION The boiling point of a chlorinated solvent is important due to its application in vapor degreasing. Table 1.13 lists the boiling point and latent heat of vaporization for several common chlorinated solvents (Montgomery, 1992: Ramamoorthy and Ramamoorthy, 1998). The boiling point of PCE is high, while methylene chloride and CFC-113 are low. The latent heat of vaporization is one measure of the energy necessary to maintain the solvent at its boiling point. The higher the latent heat of vaporization, the higher the energy needed to keep the solvent at its boiling point.

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TABLE 1.12 Vapor Pressure and Density of Selected Chlorinated Solvents Compound Tetrachloroethylene (PCE) Trichloroethylene (TCE) 1,1,1-Trichloroethane (TCA) Methylene chloride Freon-11 Freon-13

Vapor Pressure (mm at 20∞C)

Vapor Density (g/L)

14.0 57.8 90.0 348.9 687.0 270.0

6.86 5.37 5.45 3.47 5.61 7.66

1.3.9 OCTANOL/WATER PARTITION COEFFICIENT (KOW) The octanol partition coefficient (also called the partition coefficient) is the ratio of the equilibrium concentration of a chemical in octanol and water. Octanol/water partition coefficients are unitless. In general, compounds with values greater than 1000 are indicative of a low mobility in the subsurface, nonbiodegradability, and high sorbativity by soil (Ney, 1995). A low Kow value (<500) suggests a high water solubility, a high mobility, little to no bioaccumulation, and a susceptibility to degradation. The octanol/water partition coefficient is an estimate of the hydrophobicity or the partitioning tendency of a compound from water into organic media such as wax, lipids, humin, and humic acid. The Kow estimates the organic carbon-water partition coefficient (Koc) via the following relationship (Karickhoff, 1981): Koc = 0.41 Kow

(Eq. 1.2)

Koc (also known as the sorption or soil/sediment partition coefficient) is the ratio of the adsorbed chemical per unit weight of organic carbon to the aqueous solute concentration. This value is used in groundwater modeling to estimate the retardation of a compound transported in groundwater due to sorption.

TABLE 1.13 Boiling Point and Latent Heat of Vaporization Compound Tetrachloroethylene (PCE) Trichloroethylene (TCE) 1,1,1-Trichloroethane (TCA) Chlorofluorocarbon-113 (CFC-113) Methylene chloride (MC)

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Boiling Point (∞F)

Latent Heat of Vaporization (Btu/lb)

250 188 165 118 104

90 103 102 63 142

1.3.10 HYDROLYSIS Hydrolysis is the chemical breakdown of substances by water. The rate of breakdown depends upon the chemical structure of the contaminant, solubility, sunlight, pH, and oxidation-reduction (redox). Hydrolysis is generally assumed to be a first-order process (i.e., the time required to reach one-half [t1/2] of its original amount). An example of hydrolysis is the breakdown of TCA to acetic acid (McCarty, 1994). Hydrolysis rates vary over a few orders of magnitude, depending on the initial concentration or procedural differences in the measurement. Tetrachloromethane is reported to have a hydrolysis half-life of 7 years at a concentration of 7000 mg/L and 7000 years at a concentration of 1 mg/L (Mabey and Mill, 1978). The hydrolysis halflife of trichloromethane is reported to be 1.25 years and 3500 years at the same concentrations (Dilling et al., 1975). Hydrolysis rates in the presence of soil may be faster or slower than those reported in water, depending on the soil and compoundspecific effects of pH, redox, sorption, and surface catalyzed reactions.

1.3.11 SORPTION Sorption encompasses adsorption, absorption, ion exchange, ion exclusion, retardation, chemisorption, and dialysis. It is used to denote the uptake of a vapor or liquid into another material without reference to a specific mechanism (Chiou, 1989). Absorption (the penetration of substances into the bulk of a solid or liquid) and adsorption (the surface retention of solid, liquid, or gas molecules by a solid or liquid) are the most important. Sorption affects distribution of a contaminant between the solid and liquid phase and the relative retardation of the chemical. The higher the fraction of the chlorinated solvent sorbed, the less is available for transport deeper into the soil. The sorption capacity of a compound is described by its sorption coefficient. The sorption coefficient is the ratio of an adsorbed chemical per unit weight of organic carbon to its concentration. It implicitly assumes a reversible process where sorption and desorption occur at the same rate. The sorption coefficient is usually estimated via batch isotherm experiments. Several correlations are available for organic compounds that relate the distribution coefficient to the soil organic content as expressed by the octanol/water partition coefficient (Fetter, 1994).

1.3.12 BIODEGRADATION Biodegradation is the enzyme-catalyzed transformation of complex compounds (principally by bacteria, fungi, and yeast) into simpler substances. Bacteriological or reductive dechlorination is the principal process resulting in the degradation of chlorinated solvents in the subsurface (Gao et al., 1995). For most biodegradation pathways, the final degradation products are carbon dioxide and water. Figure 1.5 depicts reductive dechlorination degradation pathways for PCE, 1,1,1-TCA, and carbon tetrachloride. Soil contains both anaerobic and aerobic regions, many of

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FIGURE 1.5 Degradation pathways of PCE, 1,1,1-TCA, 1,2-DCA, and carbon tetrachloride. (Data from Vogel et al., 1987a,b; McCarty, 1993, 1994; Pankow and Cherry, 1996.)

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which are highly localized. These alternating regions of oxygen-rich and oxygendeficient sediments create unique and distinct degradation environments. A common classification scheme is the biological decay of chlorinated solvents as anaerobic or aerobic. 1.3.12.1 Anaerobic Degradation Anaerobic degradation occurs via dehalogenation. A chlorine atom is released during dehalogenation. Strong reducing conditions with low dissolved oxygen levels must exist in order for dehalogenation to proceed. Methanogenic (methane-producing) bacteria facilitate dehalogenation under anaerobic conditions. In anaerobic degradation, the rate of reductive dehalogenation decreases as more chlorines are removed. The process is examined via the loss of three chlorine atoms under anaerobic conditions as follows (Woodbury and Li, 1998): H+ + HC2Cl3 (TCE)

Æ H2C3Cl2 + Cl– Æ H+ + H2C3Cl2 Æ Æ (DCE) Æ (DCE)

H3C2Cl + Cl– Æ H+ + H3C2Cl Æ (vinyl chloride) Æ (vinyl chloride) Æ

H4C2 + Cl– (ethene)

Æ

DCE can exist as the three isomers 1,1-DCE, cis-DCE, and trans-1,2-DCE. Of these isomers, cis-1,2-DCE is produced in the greatest abundance, at a rate of about 30 times the concentration of trans-1,2-DCE. The decay rate from TCE to cis-1,2-DCE is also faster than from TCE to trans-1,2-DCE or 1,1-DCE. The decay rate from cis1,2-DCE to vinyl chloride (chloroethene), however, is slower than from trans-1,2DCE and 1,1-DCE to vinyl chloride. The eventual products of this dechlorination process beyond vinyl chloride are ethene, ethane, and carbon dioxide. Recent research indicates that under strongly reducing methanogenic conditions, methane is a significant degradation product of 1,1,1-TCA (Bradley et al., 1999). 1.3.12.2 Aerobic Degradation Aerobic degradation is believed to be initiated by enzymes called oxygenases (Tsien et al., 1989). These enzymes initiate degradation after producing a specific organic compound that serves as a carbon and energy source for the bacteria. Naturally occurring total organic carbon (TOC) can provide the carbon source. Research indicates that, unlike anaerobic environments, for aerobic degradation the more chlorinated the compound, the slower the degradation process. Subsurface environments conducive to aerobic degradation include highly transmissive aquifers, the presence of methane-oxidizing bacteria, and chlorinated compounds with a small number of chlorine atoms. The rate and ability of microbes to degrade chlorinated hydrocarbons is dependent on the ability of the subsurface environment to support a healthy community of microbes. The concentrations of nutrients and oxygen required to

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TABLE 1.14 Results of TCA and TCE Degradation in Anaerobic and Aerobic Environments Subsurface Environment Anaerobic

Aerobic

Aerobic

Week

TCA (mg/L)

TCE (mg/L)

0 4 8 95 0 2 4 14 0 2 4 14

570 420 580 73 600 440 540 430 600 580 620 650

540 260 340 54 650 440 480 260 540 540 600 500

sustain viable microbial communities are highly variable. Some generalizations concerning biodegradation are that biodegradation may not occur if the concentration of the compound is very low, although most chlorinated solvents can be degraded to some extent. An example of the effect of the subsurface environment on degradation is illustrated by a study of an aviation gasoline plume containing TCA and TCE. Soil samples spiked with TCE and TCA were analyzed over time to examine the anaerobic and aerobic degradation rates. Table 1.14 summarizes these results (Wilson et al., 1994). The presence of chlorinated solvents at high concentrations may inhibit the microbial degradation that may otherwise occur (Phelps et al., 1988). These types of complications, as well as the heterogeneity of the subsurface aerobic and anaerobic environments, introduce significant uncertainty in the use of degradation rates as indicators of the timing of a chlorinated solvent release (Alexander, 1985).

1.4 TRANSPORT OF CHLORINATED SOLVENTS THROUGH SOIL Chlorinated solvents can enter the subsurface as a dissolved phase, a non-aqueous phase liquid (NAPL), or a vapor. Non-aqueous phase liquids can exist as a separate phase within the subsurface and as a dissolved and/or vapor phase plume originating from the NAPL. Care must be exercised in extrapolating pure phase properties, such as fluid density, volatility, and viscosity, to a release that is a solvent mixture.

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As chlorinated solvents travel through soil, they are distributed in the unsaturated zone and capillary fringe as residual saturation. Dense non-aqueous phase liquid residual saturation values range from 2 to 40% of the soil pore space and are generally higher in poorly sorted soils. The residual saturation of PCE in a Selvilleta sand, for example, was reported to be 27% (Wilson et al., 1990). A vapor phase halo exists for some distance and concentration around this residual soil contamination. In the case of a solvent dissolved in water that is released at the ground surface, the dissolved phase spreads vertically and horizontally as a function of the soil suction gradient and gravity. This trend continues until the suction gradient in the upper portion of the contaminant plume becomes negligible. Gravity eventually constitutes the only remaining force to move the liquid vertically. If the liquid does not reach the capillary fringe, the fluid become immobilized as residual saturation around the soil grains until it is remobilized by infiltrating water or a fluctuating water table. The movement of a free phase liquid through soil is controlled primarily by capillarity due to the interfacial tensions present between different fluids (LNAPL/ DNAPL, LNAPL/water, DNAPL/air, etc.) and the size of the soil pore opening. The moisture content of the soil also influences the ability of the free phase liquid to move into the open pore space or displace the water occupying this space. In most cases, water coats the soil grains, thereby restricting the movement of the chlorinated solvent into the larger pore openings. The ability of a chlorinated solvent to enter the smaller openings between the soil grains is a function of the interfacial tensions between the chlorinated solvent and other liquids (air, water, another DNAPL/LNAPL). The energy or pressure required for entry into these smaller openings is known as the entry pressure, which is defined as the capillary pressure at which the free phase solvent becomes continuous at the macroscopic scale and is capable of flowing through the material. For most soils, the entry pressure corresponds to water saturation ranges from about 0.8 to 0.95 (Pankow and Cherry, 1996). The entry pressure is proportional to the interfacial tension between the free phase liquid and water and is inversely proportional to the opening between the soil grains. The entry of a free phase liquid into smaller openings between soil grains is dependent on the pore opening and interfacial tension(s) between the liquids. Free phase liquids tend to become immobilized or trapped within finer grained materials. Conversely, liquids introduced into the subsurface that reduce the interfacial tensions between the liquids (e.g., surfactants) enhance the movement of the free phase liquid into these smaller apertures. The primary forces driving free phase liquids through the vadose zone include (Kueper and McWhorter 1991, 1992): • • • • • •

Duration and volume of the release Density and viscosity of the fluid Pressures driving the liquid Intrinsic permeability of the soil Degree of free product saturation of the soil Presence of preferential pathways such as fractured rock or slickensides found in silt or clayey soils

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Highly permeable soil and free product saturation result in higher flow rates. A free phase liquid can also move laterally along the surface of sloping fine-grained stratigraphic units. Higher density and lower viscosity fluids also permit higher flow rates. Given that most chlorinated solvents are more dense than water and have viscosities lower than water, in a given geologic medium with high free product saturation most liquid chlorinated solvents migrate at rates comparable to or faster than water. Most solvent movement occurs when it is connected or continuous. In such cases, the free products in different pore openings form an immiscible phase continuum through the various pore throats. Once the solvent release at the surface ceases, the pressure forces driving the free phase liquid cease and the liquid in the pore openings becoming disconnected. This liquid then becomes residual free product attached to the soil particles as disconnected film or as wedges between soil particles. Once movement of the chlorinated solvent ceases and the free product exists as residual saturation or ganglia, high hydraulic gradients are required to remobilize the solvent.

1.5 IMPACT OF COSOLVENCY ON TRANSPORT THROUGH SOIL Cosolvency is another transport mechanism. Cosolvency (also referred to as cosolvation) is the enhancement of an otherwise low mobility compound by its preferential dissolution into an organic solvent. Examples include the remobilization of a hydrophobic compound such as DDT or PCB by a release of gasoline or oil into which DDT — 1,1¢-(dichloroethylidene)bis(4-chlorobenzene) — or PCBs (polychlorinated biphenyls) preferentially dissolve into the fuel and are transported to depth (Morrison and Newell, 1999). Cosolvation occurs when a mobile phase is formed from multiple solvents that are miscible (Kargbo, 1994). For soils, cosolvation is shown to increase the mobility of a compound significantly only at high cosolvent concentrations, usually greater than about 5% of the solution (Lane and Loehr, 1992; Nkedi-Kizza et al., 1987). Cosolvation is described by the theoretical solvophobic model, which assumes that sorption is the result of hydrophobic interactions (Rao et. al, 1985); the model is log-linear. Deviations in the adsorption coefficient (Kd) from water due to mixed solvents is estimated by the following equation (Nkedi-Kizza et al., 1985): ln (Kdm) = ln (Kdw) – (cs cf c)

(Eq. 1.3)

where Kdm Kdw c sc fc

= = = =

the partition coefficient from mixed solvents. the partition coefficient from water. an empirical constant. a number that, at a given concentration, is a function only of the solute and the solvents. = fraction of the cosolvent.

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1.6 TRANSPORT OF VAPORS IN SOIL Volatility is the tendency of a compound to be transported from the liquid to the vapor phase. Given that most chlorinated solvents are volatile, a vapor phase is often associated with a NAPL as it moves through the vadose zone. Vapor can partition into moisture in the vadose zone, thereby creating dissolved phase contamination of previously uncontaminated soil pore water and/or groundwater. The primary mechanism for vapor transport in the vadose zone is vapor diffusion (Thorstenson and Pollock, 1989). Generally, the more volatile the compound, the greater its diffusion rate. Transport also occurs via advection due to pressure and/or density gradients. Most chlorinated solvent vapors are denser than air, and large density gradients may exist near a residual source of chlorinated solvents (i.e., the vapor next to the free phase liquid may reach saturation). Density gradients can result in vapor velocities of meters per day. In some cases, density-induced advection is as significant as vapor diffusion. The volatility of a chlorinated solvent is described by its vapor pressure and its Henry’s Law constant. The greater the vapor pressure of a compound, the greater the diffusion rate. Vapor pressures increase with temperature for pure phase or multicomponent liquids. Henry’s Law constant is used to define both the amount of the compound in the vapor phase (assumes equilibrium) and the retardation of the compound according to (Cohen et al. 1993): Rd = (1 + nw) / [(naKH) + (rbKd)] / (naKH)

(Eq. 1.4)

where nw na KH rb Kd

= = = = =

water-filled porosity (dimensionless). air-filled porosity (dimensionless). Henry’s Law constant (dimensionless). soil bulk density. soil/liquid distribution coefficient.

The relative diffusive velocity of a chlorinated solvent in vapor can be estimated with Equation 1.4. For 1,1,1-TCA, TCE, and methylene chloride using Henry’s Law constants of 0.599, 0.379, and 0.084, respectively; a soil bulk density of 1.85 g/cm3; and an air and water porosity of 0.5, the relative diffusive velocities from highest to lowest are methylene chloride, 1,1,1-TCA, and TCE. Compounds with slower diffusive velocities such as TCE and PCE (relative to TCA or methylene chloride) are more useful in identifying soil source areas, while compounds with greater affinities for the gas phase are more useful as indicators of groundwater contamination. In field studies of trichloroethylene vapor transport in sand, vapor velocities were impacted by seasonal temperature variations. In some instances, vapors migrated several meters within several days of a release (Conant et al., 1996). In another study, TCE in a sandy soil emitted a vapor plume approximately 7 meters from the source

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TABLE 1.15 Chemical Formula and Vapor Density of Selected Chlorinated Solvents Chlorinated Solvent

Formula

1,1,2,2-Tetrachloroethane Tetrachloroethylene (PCE) Carbon tetrachloride (CT) Trichlorofluoromethane 1,1,1-Trichloroethane (TCA) 1,1,2-Trichloroethane Trichloroethylene (TCE) Dichlorofluoromethane (Freon-12) Chloroforma 1,1-Dichloroethane (1,1-DCA) cis-1,2-Dichloroethylene trans-1,2-Dichloroethylene 1,1-Dichloroethylene (1,1-DCE) Dichloromethane (DCM)b Vinyl chloride (VC)

C2H2Cl4 CCl2CCl2 CCl4 CCl3F C2H3Cl3 C2H3Cl3 CHCl:CCl2 CCl2F2 CHCl3 C2H4Cl2 CH2Cl2 CH2Cl2 C2H2Cl2 CHCl2F C2H3Cl

a b

Vapor Density (g/L) 6.86 6.78 6.29 5.61 5.45 5.45 5.37 4.94 4.88 4.04 3.96 3.96 3.96 3.47 2.55

Trichloromethane. Methylene chloride or Freon-30.

after 18 days (Hughes et al., 1992). A chlorinated solvent released from a degreaser at an elevated temperature, for example, can result in a significant volume of the solvent entering the vapor phase. For TCE, the vapor pressure is about double if the temperature is at 25 vs. 15∞Celsius. As vapors migrate through the soil, vapor partitioning into the aqueous and solid phases occurs which retards the distance and rate of vapor migration from the source. If the gas permeability of the soil allows the vapors to migrate vertically, these vapors will eventually reach the capillary fringe, where they can diffuse into the groundwater. Field studies have demonstrated that a solvent vapor source can contribute to groundwater contamination (Cherry and Smyth, 1996; Mendoza and Frind, 1990a,b,c). A rising water table can also provide the mechanism for these vapors to diffuse into the groundwater (Weeks et al., 1982). The vapor densities of selected chlorinated solvents are listed in Table 1.15 (Huling and Weaver, 1991; Montgomery, 1992). Chlorinated solvents can also volatilize from the water table into the overlying vadose zone. The vaporization rate of a solvent from groundwater is a function of its vapor pressure and chemistry. At the Picatinny Arsenal in Morris County, NJ, the flux of TCE from the water table was estimated to be about 0.1 mg/sec (Martin and Imbrigiotta, 1994).

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TABLE 1.16 Saturated Vapor Concentration of Selected Vapors Saturated Vapor Concentration Compound a

1,1,1-Trichloroethane (C2H3Cl3) Trichloroethylene (CHCl:CCl2) Perchloroethylene (CCl2CCl2) Dichloromethaneb (CH2Cl2) a b

(ppmv)

(mg/L)

132,000 77,000 19,000 460,000

730 420 130 1600

Methyl chloroform. Methylene chloride.

If a chlorinated solvent contains one compound, the equilibrium vapor concentration is equal to the vapor pressure of the pure compound. If the liquid is a mixture, Raoult’s Law can approximate it. Raoult’s Law is a relationship by which the equilibrium vapor pressure of each constituent is approximated as described by the following relationship: c = Xt (P o/RT)

(Eq. 1.5)

where c Xt Po R T

= = = = =

equilibrium vapor concentration of the constituent. mole fraction of the compound in the source liquid. pure compound vapor pressure of a particular constituent. universal gas constant. temperature (degrees Kelvin).

The vapor pressure and concentration for TCE as a single compound and as a component of a three-constituent mixture at 23∞C are 0.09 atm and 500 mg/L, and 0.25 atm and 138 mg/L, respectively. The presence of chlorinated solvents at concentrations of several percent of their saturated vapor pressure is indicative of the presence of a free phase liquid. The saturated vapor pressure of several chlorinated solvents at 20∞C in parts per million per volume (common soil gas units) and milligrams per liter are summarized in Table 1.16 (Feenstra, 1996). A soil gas concentration of 100 ppm by volume is commonly considered to be indicative of the presence of free phase liquid.

1.7 TRANSPORT THROUGH THE CAPILLARY FRINGE The capillary fringe is the portion of the subsurface located immediately above the groundwater table through which contaminants move to the underlying groundwater

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or through which vapors from contaminated groundwater volatilize and migrate into the vadose zone. The height of the capillary fringe is dependent on the soil texture; finer grained materials have a higher capillary fringe than coarse-grained sediments. A chlorinated solvent can enter the capillary fringe as a dissolved phase or as a DNAPL or DNAPL/LNAPL mixture. In the case of a dissolved phase, the contaminated water enters the capillary fringe and co-mingles with the underlying groundwater. For a DNAPL/NAPL mixture with a density less than water, vertical transport ceases and the mixture spreads horizontally along the capillary fringe. The DNAPL/NAPL usually accumulates as a mound on the groundwater surface and then spreads radially. The center of mass, however, moves downgradient with respect to the groundwater. A dense non-aqueous phase liquid entering the capillary fringe must displace water between the soil pores in order to continue its vertical migration into the groundwater. The radii between the soil pores in the capillary fringe can cause significant capillary pressures between the DNAPL and water which hinder further vertical movement. A misconception concerning DNAPL transport through the capillary fringe is that a DNAPL preferentially moves into the groundwater via the capillary fringe as a function of the greater specific density of the DNAPL relative to water. In many cases, this does occur, although the actual transport process is more complex. DNAPL transport through the capillary fringe is dependent on several factors, of which fluid density is only one. The height of a DNAPL required to penetrate the capillary fringe is described by Hobson’s equation as follows (Anderson, 1988; Berg, 1975): Zc = 2g cos q (1/rt – 1/rp) / Drg

(Eq. 1.6)

where Zc 2g cos q (1/rt – 1/rp) Dr g

= = = = = =

critical height of the DNAPL required to penetrate the capillary fringe. interfacial tension between the DNAPL and water. contact angle between the fluid boundary and the solid surface of the soil. radii of the throat and soil pore, respectively. difference in specific densities between the water and chlorinated solvent. acceleration due to gravity.

The practical application of this equation is that for soils with small pores such as silts and clay, a significant barrier to DNAPL migration through the capillary fringe exists. For a well-rounded and sorted sediment of diameter D with a rhombohedral packing, the pore and throat radii, rp and rt, can be estimated from the following relationships: rp = 0.212D rt = 0.077D As an example, assume a porous soil in a rhombohedral packing and a pore radius of 0.207D and throat radius of 0.077D, where D is the grain diameter. The critical

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TABLE 1.17 Critical Height of PCE To Penetrate the Capillary Fringe Porous Media Coarse sand Fine sand Silt Clay

Diameter (D) (mm) 1.0 0.1 0.01 0.001

Critical Height of PCE (Zc) (cm) 13 (5 in) 130 (4 ft) 1300 (43 ft) 13,000 (427 ft)

Note: Values used in the calculation of Zc were 0.62 g/cm3, g = 47.5 dyne/cm, and cos q = 1.

height of PCE necessary to overcome the capillary pressure for four different soil types is shown in Table 1.17 (Anderson, 1988; Morrison and McGowan, 1993). This approximation indicates that for a coarse sand, 13 cm (5 in) of DNAPL are required to accumulate above the capillary fringe until enough pressure is created to allow the PCE to move into the capillary fringe and underlying groundwater. A DNAPL can, therefore, be immobilized and accumulate within fine-grained sediments at the capillary fringe. A similar equation provides the entry pressure for a crack or fracture in a capillary barrier or rock (Kueper and McWhorter, 1991). The difference is that the pore/throat radius is replaced by the fracture aperture (Tuck et al., 1998). A DNAPL residing within the capillary fringe can volatilize and migrate by diffusion. Gaseous advection due to pressure or density gradients will affect this transport process. As these vapors migrate, they can partition into the aqueous and solid phases. These partitioning processes tend to retard the rate and distance of vapor migration. The vapors may eventually contaminate the groundwater by diffusion across the capillary fringe and water table at some distance from the DNAPL. Water infiltrating through the soil and contacting these vapors can result in the dissolution of the chlorinated solvent into the water which then enters the capillary fringe.

1.8 TRANSPORT IN GROUNDWATER Chlorinated solvent transport in groundwater occurs as a dissolved or dense nonaqueous phase liquid from which a dissolved phase “plume” originates. Once a solubilized chlorinated solvent and water mixture enters groundwater, the same advective (mass transport) dispersive and molecular diffusion processes used for estimating groundwater movement apply. In most cases, molecular diffusion (the transport of a chemical from a region of higher concentration to lower concentration) is not a significant process. An exception is in the transport of solvents through subsurface barrier systems; in these instances, transport is by molecular diffusion (Crooks and Quigley, 1984).

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1.8.1 DARCY’S LAW Darcy’s Law describes groundwater velocity. This law is named after the French engineer, Henry Darcy, who published a report in 1856 on the water supply for the city of Dijon, France. In the report, Darcy described a laboratory experiment he performed to analyze water flow through sand. Darcy concluded that the flow of a liquid through porous medium is in the direction of, and at a rate proportional to, the driving force acting on the liquid (the hydraulic gradient) and proportional to the ability of the conducting medium to transmit the liquid. Naturally occurring hydraulic gradients are typically on the order of 0.01; the units for hydraulic gradient are dimensionless. Darcy’s Law as expressed in terms of hydraulic head is Q = –KiA

(Eq. 1.7)

where Q –K i A

= = = =

discharge. saturated hydraulic conductivity. hydraulic gradient or slope. cross-sectional area.

Environmental reports usually describe the horizontal and vertical velocity of a contaminant in groundwater. Unlike the calculation of horizontal groundwater velocity, the vertical velocity is obtained by measuring the water levels in two monitoring wells or piezometers whose well screens are completed at different depths to obtain the vertical hydraulic gradient between the two wells. Soil porosity and saturated hydraulic conductivity are two parameters in Darcy’s Law that are key in estimating the average groundwater or contaminant velocity. These two input variables are briefly discussed.

1.8.2 POROSITY (nE) Porosity is an index (in percent) of the relative open space in a soil or a measure of the air between soil particles. Porosity is used to calculate the transport of liquid or vapor in the soil. It is usually expressed as the volume of pore space divided by the bulk volume multiplied by 100. It can be calculated if the particle density and dry bulk density of the soil are known. Soil porosity values range from 30 to 60% of the total soil volume. Porosity is measured directly in the field or laboratory. Laboratory methods include gas pycnometry and mercury intrusion. Coarse-textured soils tend to be less porous than fine-textured soil, although the mean size of individual pores is greater in the former than the latter. Porosity values are highly variable in clayey soils due to the swelling and shrinkage associated with changes in moisture content. The term “effective porosity” is often used interchangeably with the term “porosity” to describe this

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volume of interconnected pore space. The term “primary porosity” refers to the original openings in the soil or rock created when it was formed in its present state, while “secondary porosity” refers to features such as joints, faults, and openings along planes of bedding in consolidated rocks having a low primary porosity. Crystalline rocks such as granite have primary porosities ranging from 0 to 10%. Typical secondary porosity values range from 0.001 to 1.0%. Porosity is measured by laboratory drying experiments, laboratory drainage experiments, in situ unconfined multiple-well pumping tests, in situ single-well borehole-dilution test, in situ two-well tracer tests, and particle size analysis (Gorelick et al., 1993). Soil porosity can be estimated if the mean particle diameter for the soil is known. The mean particle diameter can be estimated from a grain size distribution chart. The empirical relationship is q = 0.261 – 0.0385 ln (d)

(Eq. 1.8)

where d is the mean particle diameter (cm).

1.8.3 PERMEABILITY (k) AND HYDRAULIC CONDUCTIVITY (K) Permeability and hydraulic conductivity describe the ability of a soil to transmit a fluid. The terms “permeability” (in older texts, coefficient of permeability) and “hydraulic conductivity” are often used interchangeably; however, they are not the same. Permeability refers to properties associated with the soil through which a fluid is migrating. These properties include the distribution of the grain sizes, the sphericity and roundness of the grains, and the nature of their packing. It is not a term that includes properties of the groundwater flowing through the media. The Water Resources Division of the U.S. Geological Survey defines hydraulic conductivity as (Lohman et al., 1979): A medium has a hydraulic conductivity of unit length per unit time if it will transmit in unit time a unit volume of groundwater at the prevailing viscosity through a crosssection of unit area, measured at right angles to the direction of flow, under a hydraulic gradient of unit change in head through unit length of flow.

Hydraulic conductivity (K) is a constant of proportionality in Darcy’s Law and is the building block for estimating contaminant transport in groundwater. Hydraulic conductivity has units of length per time. Common conversions for hydraulic conductivity are summarized in Table 1.18. When using the term “hydraulic conductivity”, the distinction between saturated hydraulic conductivity and unsaturated hydraulic conductivity should be made. Saturated hydraulic conductivity is the proportionality constant used in Darcy’s Law for saturated flow. Unsaturated hydraulic conductivity is used to express this constant for unsaturated flow (i.e., flow of liquids in the unsaturated zone). The difference in saturated and unsaturated hydraulic conductivity is that the value for unsaturated hydraulic conductivity varies with

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TABLE 1.18 Unit Conversions for Hydraulic Conductivity 1 1 1 1

gal/day/ft2 ft/day cm/sec m/day

= = = =

0.0408 m/day = 0.134 ft/day = 4.72 ¥ 10–5 cm/sec 0.305 m/day = 7.48 gal/day/ft2 = 3.53 ¥ 10–4 cm/sec 864 m/day = 2835 ft/day = 21,200 gal/day/ft2 24.5 gal/day/ft2 = 3.28 ft/day = 0.00115 cm/sec

Adapted from Fetter (1994).

the degree of moisture saturation. A lower soil moisture content results in a smaller unsaturated hydraulic conductivity value. Furthermore, the relationship between unsaturated hydraulic conductivity and the degree of saturation is nonlinear and exhibits hysteresis (i.e., non-repeating values). Hydraulic conductivity is described by the following equation: K = krwg/mw

(Eq. 1.9)

where k rw g mw

= = = =

intrinsic permeability (cm2). liquid density of water (1.0 g/cm3). gravity constant (980.7 cm/sec2). dynamic viscosity of water (0.801 millipoiseuille [mPl] = 0.801 centipose [cP]).

and k = K (mw/rwg)

(Eq. 1.10)

For water at 20∞C, the expression (mw/rwg) is equal to 1.02 ¥ 10–5 cm/sec. Intrinsic permeability is a function of the grain size distribution of the porous medium and generally decreases from sands to loam to silt to clayey soils. Intrinsic permeability is expressed in units of square centimeters (cm2) or Darcy (equal to about 10–8 cm2). To convert cm2 to Darcy, multiply the cm2 value by 108. Intrinsic permeability can range from about 10–15 to about 10–3 cm2. Hydraulic conductivity values for saturated zone soils are obtained by direct measurement from pumping well or slug tests. Hydraulic conductivity can be approximated if a soil grain distribution curve is available or from approximate functional relationships. Unsaturated hydraulic conductivity values can be determined with laboratory testing. If laboratory testing is performed for calculating the saturated or unsaturated hydraulic conductivity value of a soil and the wetting fluid used is water, recalculate the hydraulic conductivity value for estimating the hydraulic conductivity value for the contaminant of interest through the same soil. In the absence of site-specific measurements, hydraulic conductivity values can be derived using approximate functional relationships based on the grain-size distribution. One of the earliest equations was the Hazen formula (1893) which described

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2 , where d the saturated hydraulic conductivity (K) of a sample as K = Cd10 10 is the tenth percentile of the grain-size distribution and C is a coefficient that accounts for the nonuniformity in the grain-size distribution (Hazen, 1893; Pfleider and Moltyaner, 1993). Another relationship is the Kozeny-Carmen equation (Bear, 1979; Indelman et al., 1999):

K = (rg/m)(q3/(1 – q)2)(d2/180)

(Eq. 1.11)

where K r g m q d2

= = = = = =

saturated hydraulic conductivity (cm/sec). water density (kg/m3). acceleration due to gravity (m/sec2). viscosity of water (Newtons/sec/m2). porosity. mean particle diameter (cm).

The California Department of Water Resources uses a standard estimate for saturated hydraulic conductivity of soils based exclusively on grain size. Using this system, gravel, sand, and sandy clay hydraulic conductivity values are estimated to be about 270, 135, and 10 feet, respectively, per day. The rate of movement of a compound in groundwater is described by the term “advection”, which is the average linear groundwater velocity and is the dominant mechanism by which chemicals move in groundwater. It is described by Darcy’s Law. The horizontal stratification of sediments results in hydraulic conductivities that are usually greater in the horizontal direction than in the vertical direction. In sediments such as glacial till, the preferential flow of contaminants can occur within small lenses of materials that are more permeable than the majority of sediments in the aquifer. Since Darcy’s Law is an averaged value for transport in a homogeneous and isotropic media such as soil, contaminants are transported at greater rates within these preferential layers than what is estimated with Darcy’s Law. To estimate the average velocity of a particular contaminant, a variation of Darcy’s Law is employed and is described by the following expression: Vc = V/R

(Eq. 1.12)

where Vc = average velocity of a contaminant. V = average groundwater velocity. R = retardation coefficient.

1.8.4 RETARDATION While Darcy’s Law applies to the average linear velocity for groundwater, it is not contaminant specific. To examine the transport of an individual chemical,

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retardation must be considered. In an ideal case, soluble compounds with higher velocities are observed at the leading edge of a contaminant plume followed by those soluble components with decreasing velocities. The separation of the soluble components with distance from the source is explained by the retardation factor or retardation coefficient (R), which is the ratio of the concentration of a compound on a solid to the concentration of that compound in solution. Retardation values are strongly linked to the total organic carbon content of the media. The retardation values for TCE in soil with organic carbon percentages of 0.01 to 0.02, 0.001 to 0.01, and <0.001 are 4 to 13, 1.3 to 7, and 1 to 1.3, respectively (Olsen and Davis, 1990). Compounds that sorb strongly to organic carbon in soils characteristically have low solubilities; compounds with low tendencies to adsorb onto organic particles have high solubilities. Retardation is described as: R = 1 + (rb/q)Kd

(Eq. 1.13)

where rb = bulk density of the soil. q = porosity (at low soil porosity values, retardation increases, while retardation decreases as the soil porosity increases). Kd = distribution coefficient.

The variable bulk density in the retardation equation is the weight of a soil per unit volume. For most mineral soils, the bulk density ranges from about 1.0 to 1.54 Mg/ m3 (megagrams per cubic meter = grams per cubic centimeter). When the bulk density is greater than about 1.65 Mg/m3, the soil is compacted; values less than 1.0 indicate a high level of organic matter (Conklin, 1996). For a sandy aquifer, values for rb/q range from 4 to 6. Distribution coefficient (Kd) values are obtained from the literature, calculated from the measured organic carbon content in soil, or measured from laboratory batch sorption or column transport studies. The most common technique measures the soil organic content and obtains the soil/organic carbon partition coefficient (Koc) of the chemical from published tables. Kd is then estimated by the following relationship: Kd = (Koc)(foc)

(Eq. 1.14)

where Kd = distribution coefficient. Koc = soil/organic carbon partition coefficient. foc = organic carbon content of the soil.

Koc values for selected chlorinated solvents are listed in Table 1.19 (Mackay et al., 1993; Ramamoorthy and Ramamoorthy, 1998).

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TABLE 1.19 Soil/Organic Carbon Partition Coefficients for Selected Chlorinated Solvents Chemical Trichloroethylene (TCE) Tetrachloroethylene (PCE) 1,2-Dibromomethane cis-1,2-Dichloroethylene trans-1,2-Dichloroethylene 1,1,1-Trichloroethane (TCA) Chloroform (TCM) 1,2-Dichloropropane

Soil/Organic Carbon Partition Coefficient (mL/g) 126 364 92 86 59 152 44 51

Laboratory experiments indicate that values for retardation vary widely, depending on the chlorinated solvent and the soil. Given the uncertainties associated with calculating R, a compound with a value of less than 2 is considered to be moving at a rate similar to groundwater. Values for Kd vary over about 6 orders of magnitude, while bulk density divided by porosity (rb/q) values vary by a factor less than 10. Table 1.20 lists values of observed retardation coefficients for chlorinated solvents and other compounds in various sand and gravel aquifers (MacKay, 1990; Olsen and Davis, 1990). Predicted retardation values are generally two to five times lower than measured values (Ball and Roberts, 1991; Curtis et al., 1986; MacKay et al., 1986; Pankow and Cherry, 1996). Spatial variations in the composition and ratios of the degradation products of chlorinated solvents are frequently observed. The presence and distribution of the breakdown products are explained as a function of the redox potential of the aquifer, as well as the age of the release. A groundwater plume entering an area with low dissolved oxygen or an anaerobic environmental can display a unique chemical signature with more breakdown products than the aerobic portion of the groundwater plume. An example is the release of TCE into an aerobic aquifer in which the only breakdown product is cis-1,2-dichloroethylene. An anaerobic zone through which the aquifer passes results in the accelerated degradation of the TCE and cis-1,2dichloroethylene to 1,1-dichloroethylene and vinyl chloride, resulting in a distinctive chemical signature. This degradation sequence is used in the design of porous reactive walls as a remediation technology (Benner et al., 1997; Tratnyek et al., 1997). The geometry of a chlorinated solvent plume is dependent on whether the release is from a point or line source, the area of the release, and whether it is transient or steady state. A line source tends to create a large cross-sectional area through which the chlorinated hydrocarbons enter the groundwater. A point source usually creates a tear-shaped plume with the apex of the tear at the point source.

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TABLE 1.20 Retardation Values for Selected Chlorinated Solvents Site Location/Aquifer Material

Chlorinated Solvent

Palo Alto, CA/sand and gravel

Chloroform (CHCl3) Bromoform (CHBr3) 1,1,1-Trichloroethane (C2H3Cl3) Chlorobenzene (C6H5Cl) Perchloroethylene (CCl2CCl2) 1,4-Dioxane (C4H8O2) Tetrahydrofuran (C4H8O) 1,2-Dichlorobenzene (C6H4Cl2) Carbon tetrachloride (CCl4) Benzene (C6H6) Carbon tetrachloride (CCl4) Perchloroethylene (CCl2CCl2) Bromoform (CHBr3) 1,2-Dichlorobenzene (C6H4Cl2)

2.5–3.8 6 12 33 5 1.6 2.2 7.6 23 8.8 1.8–2.5 2.7–5.9 1.9–2.7 1.2–2.86

Trichloroethylene (CHCl:CCl2) Perchloroethylene (CCl2CCl2) Dichlorobenzene (C6H4Cl2) Trichloroethylene (CHCl:CCl2)

6–9 1.0 1.0–1.1 1–2

1,1,1-Trichloroethane (C2H3Cl3) Trichloroethylene (CHCl:CCl2) Trichloroethylene (CHCl:CCl2) Trichloroethylene (CHCl:CCl2)

1–2 0.1–3.2 0.01–0.7 0.02

R. Aare, Switzerland/sand and gravel Gloucester, Ontario/sand and gravel

Borden, Ontario/sand and gravel

Otis Air Force Base, MA/ sand and gravel

Rocky Mountain Arsenal, CO/ sand and gravel California site/sandy silt California site/fine sand California site/clay

Retardation Coefficient

1.8.5 DISPERSIVITY Dispersivity is the lateral spreading of a contaminant plume with distance in groundwater. Dispersivity is three dimensional (i.e., horizontal, vertical, and transverse) and is dependent on the aquifer characteristics and geometry of the contaminant source area. In a homogeneous, isotropic porous media, dispersivity occurs due to the following mechanisms: • • • •

Velocity variations within the space between soil grains Variations in travel path lengths Variations in velocity directions Molecular diffusion

Dispersivity values are obtained by fitting mathematical models to plume data or dye tracer tests performed in the field. Values for dispersivity increase with distance from the source, although a relatively stable value (macrodispersivity) should be obtained

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at some distance from the source. Dispersivity values are used in a longitudinal, transverse, and vertical direction relative to the center of mass of a contaminant plume. Longitudinal dispersivity values used with solute transport models range from 90 to 300 feet, while horizontal dispersivity values can be as much as 150 feet. There is little physical evidence for using such large numbers other than groundwater models are able to simulate contaminant concentrations which compare favorably with observed values in monitoring wells. In cases where no data exist, the U.S. Environmental Protection Agency recommends multiplying the length of the plume by 0.1 to estimate the horizontal dispersivity (Wilson et al., 1981). Other authors use probabilistic theory to estimate transverse and vertical dispersivity as 0.33 and 0.056 times the plume length, respectively (Gelhar and Axness, 1981; Salhotra et al., 1993). Field studies of dispersion for sand and gravel aquifers indicate that dispersion is weak in these types of aquifers (Freyberg, 1986). Similar observations are noted for aquifers where groundwater flow is relatively uniform with little divergence in flow direction (Feenstra et al., 1996).

1.8.6 FREE PHASE SOLVENT TRANSPORT IN GROUNDWATER A dissolved phase can originate from a free phase solvent that exists as a LNAPL or DNAPL in an aquifer. The rate at which the dissolved phase is created and the concentration are estimated from the partition coefficient, solubility data, and information on the chemical concentration of the chlorinated solvent (Dracos, 1987; McKay et al., 1991; Ptacek et al., 1987). The entry and distribution of a DNAPL into a granular media aquifer are affected by the density of the DNAPL and the distribution of horizontal zones of lower permeability materials. The difference in permeability between two zones does not have to be significant to alter the flow pattern of the DNAPL. Differences between a coarse sand to a finer sand, for example, may be sufficient to act as a barrier to vertical migration (Kueper et al., 1989). The entry pressure required for a DNAPL to penetrate a coarse and fine sand interface can be sufficient to cause the lateral movement of the DNAPL to a point where the entry pressure is lower and allows the DNAPL to resume its vertical migration. The randomness of DNAPL distribution in groundwater is due in part to variations in soil texture which change the entry pressure of a DNAPL. The accumulation of dense non-aqueous phase liquids in the saturated zone is considered to be greater than in the vadose zone (Schwill, 1988). For saturated soils, residual DNAPLs can occupy 2 to 15% of the total pore space. In the case where a DNAPL pool accumulates, the DNAPL can occupy 40 to 70% of the bulk pore space. The hydraulic conductivity in these areas is significantly reduced by the presence of the DNAPL. Whether a dense non-aqueous phase liquid is dispersed in the saturated zone as ganglia or as a pool has a significant impact on the volume of groundwater needed to “flush” the DNAPL until completed dissolution is achieved. If the dense non-

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aqueous phase liquid is dispersed in pools, the low permeability in the pool limits the groundwater flux through this zone. The time for remediation based on extraction of the dissolved phase contamination formed from the DNAPL pool is therefore increased. A multi-component DNAPL pool will exhibit the preferential dissolution of the more soluble components followed by those with smaller solubilities. A halo of chlorinated solvents leaving such a DNAPL pool will often exhibit changes in the detection and concentration of the individual solvents dissolving from the multicomponent DNAPL pool. The depth of DNAPL penetration in the saturated zone is dependent on the volume of DNAPL entering the aquifer and the various entry pressures created by changes in soil texture. At some point, these forces balance one another and vertical movement ceases. At sites with numerous layers and low-permeability zones, there is no means by which to predict the depth of DNAPL penetration. In such environments, DNAPL pools are more likely to accumulate at the interfaces of these soil layers, thereby providing an indication of where to sample to locate these DNAPL pools. For a DNAPL in groundwater, a dissolved plume is formed via contact by groundwater with the free phase liquid. The extent and geometry of the dissolved phase plume is dependent on the geometry of the DNAPL ganglia or pool. The composition of the dissolved phase plume is similarly dependent on the solubility and chemistry of the solvent. The ability to identify the distribution of a DNAPL will continue to be a daunting challenge, even at field-scale research sites (Broholm et al., 1999).

1.8.7 TRANSPORT IN FRACTURES Fractured media exist as fractured bedrock, in sandstone aquifers, clay layers, and in unconsolidated materials. DNAPLs entering these fractures will displace water. Given that the capillary entry pressure into most fractures is low (on the order of several centimeters of head), a DNAPL can flow into the fracture system until the fracture becomes saturated or the dense non-aqueous phase liquid is disconnected within the fracture system. The ability to be transported throughout a fracture system is primarily a function of the intersection and continuity of the fractures (De Marsily, 1985). Fracture aperture is a key parameter in determining the flow and transport characteristics of DNAPL in fractured media. Typically, fracture apertures are within 1 to 200 mm in width. Free phase solvents have the ability to enter fractures in these materials because of their high density, low water/solvent interfacial tension, and low viscosity. In natural fractures, there is usually a large distribution of fracture apertures even within a single fracture. The fracture aperture distribution is controlled by a number of factors, including the flaws and inclusions in the material and the history of mechanical, thermal, and chemical stresses on the soil or rock (Atkinson, 1989). In general, fracture density and apertures decrease with increasing depth. The ability

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to estimate the fracture aperture distribution is extremely unpredictable. Direct methods of detecting and measuring apertures include video imaging inside a well (Darilek, 1986; Palmer and Sparks, 1991) and geophysical techniques. Geophysical techniques include seismic reflection, electrical methods relying on the fact that water-filled fractures have a higher conductivity than unfractured rock and can mobilize ions in solution, and ground-penetrating radar. Indirect techniques for measuring the fracture aperture distribution include pumping and tracer injection tests. These are currently the most accurate means of assessing fracture apertures in the field. When a dense non-aqueous phase liquid enters a fracture, the pattern of DNAPL distribution within the fracture becomes non-uniform. Portions of the fracture system can be completely free of a dense non-aqueous phase liquid. A conceptual model should not assume that a DNAPL is uniformly distributed within a fracture network. Solvent transport through fractures and their distribution are a function of the orientation and connection of the fractures. Given that the sizes of the fracture or apertures vary, DNAPLs can accumulate in horizontal areas of larger openings as pools which then can become disconnected from other DNAPLs in the smaller sized fractures. The length of a stable DNAPL pool in a single fracture following a chlorinated solvent release is a function of the following variables (Kueper et al., 1992): • • • •

Size of the fracture aperture Fracture dip Interfacial tension between the DNAPL and fracture wall Contact angle of the DNAPL with the surface of the fracture wall

The probability that a dense non-aqueous phase liquid will accumulate in a vertical fracture is small, given the high capillary pressures that exist in vertical fractures. Fractured bedrock typically exhibits permeable zones separated vertically by less permeable zones in which vertical fractures are less frequent. In materials such as granite, the fracture pattern is usually less ordered and many of the fractures terminate without intersecting other fractures. These fractures then become reservoirs for DNAPL pools that can serve as long-term (on the order of decades to centuries) sources of groundwater contamination (Dawson et al., 1997). Equations describing the entry of a DNAPL into a fracture often reference whether the DNAPL or water is the wetting or non-wetting phase (Vold and Vold, 1983). These terms refer to the phenomenon by which, in the presence of a solid surface, one fluid preferentially “wets” the surface. In most cases, water is the assumed wetting fluid (Kueper et al., 1992). In order for a fluid to enter an aperture, the capillary pressure at the entrance to the fracture must exceed the entry pressure of the fracture. The entry pressure of a fracture is a function of the geometry of the opening that is exposed to the DNAPL. Once the entry pressure to the opening is exceeded, the DNAPL can flow into the opening. The entry pressure that is required decreases with increasing aperture

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diameter. The maximum depth that a DNAPL achieves in a fractured media is a function of the • • • •

Aperture size Number and type of fracture connections Physical properties of the DNAPL Height of the column of continuous DNAPL above the fractures at the front of the DNAPL zone

In some instances, DNAPLs in fracture rock environments have penetrated depths of hundreds of feet. In some cases, the depths are likely to be greater than 3000 feet (Pankow and Cherry, 1996). Current research is inconclusive as to whether or not DNAPL pooling on a clayey strata results in the desiccation of the clay mineral and the resultant development of vertical pathways for the DNAPL to travel through the clay. To date, the literature suggests that this scenario is unlikely.

1.8.8 TRANSPORT IN FRACTURED POROUS MEDIA The transport of dense non-aqueous phase liquids in fractured porous media, such as a fractured clay till or sedimentary rock, has been extensively studied (Ge, 1997; Hinsby et al., 1996). A current conceptual model is that as a DNAPL migrates through a fracture system, it is unaffected by diffusion, as the penetration is controlled primarily by fracture aperture and DNAPL properties (density, interfacial tension, and viscosity). Recent modeling indicates that for rough-walled fractures, the upward flow of groundwater can prevent the downward migration if a sufficient hydraulic gradient is present (Chown et al., 1997). Once the DNAPL is immobilized, contaminant diffusion into the porous matrix will commence. A distinction with DNAPL transport through fractured porous media is that a portion of the dense non-aqueous phase liquid and dissolved phase plume sorbs and dissolves into the porous media surrounding the fracture. The contaminant mass that has diffused into the solid matrix can diffuse back into water in the fracture, thereby resulting in a long-term source of contamination. In a study of free phase TCE in a fractured shale, it was estimated that the potential existed for 67% of the original DNAPL mass to have disappeared through matrix diffusion. This was estimated based on the 10-year period that the DNAPL could have been in contact with the porous bedrock (Frappa et al., 1996). Research indicates that the total mass of a dense non-aqueous phase liquid present in a fractured system is (Freeze and McWhorter, 1997): • • • •

Distributed in DNAPL in fractures Distributed in dissolved phase contamination in the water in the fractures Dissolved in the water in the porous bedrock or soil Sorbed on the solid material within the bedrock or soil

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In general, the loss of dense non-aqueous phase liquids by diffusion into the porous media is a function of the size of the aperture that the DNAPL occupies. The diffusion of a DNAPL into porous media in a small fracture results in the DNAPL disappearing within the aperture most rapidly. As the size of the aperture increases, the time for DNAPL disappearance within the fracture increases, assuming that the DNAPL is disconnected from an overlying DNAPL pool. The significance of DNAPL entry into a fractured subsurface environment is as follows: • The ability to intercept DNAPL fractures with a conventional boring program is low. • Pumping of liquid from below a DNAPL pool can result in the transport of the DNAPL to greater depths. • Matrix diffusion into porous material from a DNAPL-saturated aperture can result in a dissolved phase source for a significant period of time. • The transport and distribution of a DNAPL in a fracture system can occur rapidly compared to a granular aquifer. • The larger the volume of DNAPL released and the wider the fracture spacing, the greater the opportunity for DNAPL pools to develop and for the DNAPL to move a significant distance from the source. • The introduction of drilling fluids into a DNAPL-contaminated fractured system can result in pushing the DNAPL away from the borehole. • Drilling through a DNAPL pool can lead to borehole cross-contamination.

Given these issues, remediation of DNAPL contamination in a fracture system presents tremendous technical challenges.

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Broholm, K., Feenstra, S., and J. Cherry, 1999. Solvent release into a sandy aquifer. 1. Overview of source distribution and dissolution behavior, Environmental Science and Technology, 33(5):681–690. Butler, E. and K. Hayes, 1999. Kinetics of the transformation of trichloroethylene and tetrachloroethylene by iron sulfide, Environmental Science and Technology, 33(12), 2021–2027. California Department of Health Services, 1988. The Reduction of Solvent Wastes in the Electronics Industry, Final Report, Waste Reduction Grant Program, Grant No. 86T0110, California Toxic Substances Control Division, Alternative Technology and Policy Development Section, Sacramento, CA, p. 85. California Department of Toxic Substance Control (DTSC), 1991. Source Reduction of Chlorinated Solvents: Electronic Products Manufacture, Source Reduction Research Partnership, Metropolitan Water District of Southern California and the Environmental Defense Fund, 119 Electronic Electrical (ID#7229), Sacramento, CA, June, p. 32. Cherry, J. and D. Smyth, 1996. Non-Aqueous Phase Liquids in the Subsurface Environment: Assessment and Remediation, 1996 Annual Convention and Exposition, November 10– 14, American Society of Civil Engineers, Washington, D.C., p. 22. Chiou, C., 1989. Theoretical considerations of the partition uptake of nonionic organic compounds by soil organic matter, in Sawhney, B.L. and K. Brown, (Eds.), Reactions and Movement of Organic Chemicals in Soils, Soil Science Society of America Special Publication No. 22, Soil Science Society of America, Madison, WI, pp. 1–19. Chown, J., Kueper D., and D. McWhorter, 1997. The use of upward hydraulic gradients to arrest downward DNAPL migration in rock fractures, Ground Water, 35(3):483–491. Cohen, R., Mercer, J., and J. Matthews, 1993. DNAPL Site Evaluation, CRC Press, Boca Raton, FL, p. 48 (contract to Dynamic Corporation by EPA under Contact No. 68-C80058). Conant B., Gillham, R., and C. Mendoza, 1996. Vapor transport of trichloroethylene in the unsaturated zone: field and numerical modeling investigations, Water Resources Research, 32(1):9–22. Conklin, R., 1996. Bully for the sand’s physique, Soil and Groundwater Cleanup, November:31–33. Crooks, V. and R. Quigley, 1984. Saline leachate migration through clay: a comparative laboratory and field investigation, Canadian Geotechnical Journal, 21:349–362. Curtis, G., Roberts P., and M. Reinhard, 1986. A natural gradient experiment on solute transport in a sand aquifer. 4. Sorption of organic solutes and its influence on mobility, Water Resources Research, 22:2059–2067. Dawson, H. and P. Roberts, 1997. Influence of viscous, gravitational, and capillary forces on DNAPL saturation, Ground Water, 35(2):261–269. De Marsily, G., 1985. Flow and transport in fractured rocks: connectivity and scale effect, in Hydrology of Rocks of Low Permeability, Memoirs, Vol. XVII, Parts 1 and 2, International Association of Hydrogeologists (IAH), Tucson, AZ, pp. 267–277. Dilling, W., Tefertiller, N., and G. Kallos, 1975. Evaporation rates and reactivities of methylene chloride, chloroform, 1,1,1-trichloroethane, trichloroethylene, tetrachloroethylene, and other chlorinated compounds in dilute aqueous solutions, Environmental Science and Technology, 9:833–838. Dracos, T., 1987. Immiscible transport of hydrocarbons infiltrating in unconfined aquifers, in Vandermeulen, J.H. and S. Hrudey (Eds.), Oil in Freshwater: Chemistry, Biology, Countermeasure Technology, Pergamon Press, New York, pp. 161–175.

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Olson, R. and A. Davis, 1990. Predicting the fate and transport of organic compounds in groundwater, Hazardous Material Control, 3(3):39–64. Palmer, I. and D. Sparks, 1991. Measurement of induced fractures by downhole TV camera in Black Warrior Basin Coalbeds, Journal of Petroleum Technology, 43(3):270. Pankow, J. and J. Cherry, 1996. Dense Chlorinated Solvents and other DNAPLs in Groundwater, Waterloo Press, Guelph, Ontario, p. 522. Parker, B., Gillham, R., and J. Cherry, 1994. Diffusive disappearance of dense, immiscible phase organic liquids in fractured geologic media, Groundwater, 32(5):805–820. Pfleiderer, S. and G. Moltyaner, 1993. The use of velocity and conductivity data for the quantification of heterogeneity: a comparison, Water Resources Research, 29(12):4151– 4156. Phelps, T., Ringelberg, D., Hedrick, D., Davis, J., Fliermans, C., and D. White, 1988. Microbial biomass and activities with subsurface environments contamined with chlorinated hydrocarbons, Geomicrobiology Journal, 6, 157–170. Ptacek, C., Cherry, J., and R. Gillham, 1987. Mobility of dissolved petroleum-derived hydrocarbons in sand aquifers, in Vandermeulen, J.H. and S. Hrudey (Eds.), Oil in Freshwater: Chemistry, Biology, Countermeasure Technology, Pergamon Press, New York, pp. 195– 216. Ramamoorthy, S. and S. Ramamoorthy, 1998. Chlorinated Organic Compounds in the Environment: Regulatory and Monitoring Assessment, Lewis Publishers, Boca Raton, FL, p. 370. Rao, P., Hornsby, A., Kilcrase, D., and P. Nkedi-Kizza, 1985. Sorption and transport of hydrophobic organic chemicals in aqueous and mixed solvent systems: model development and preliminary evaluation, Journal of Environmental Quality, 14(3):376–383. Salhotra, A., Mineart, P., Hansen, S., and T. Allison, 1993. Multimed, the Multimedia Exposure Assessment Model for Evaluating the Land Disposal of Wastes — Model Theory, EPA 600/R-93/081, U.S. Environmental Protection Agency, Washington, D.C., p. 122. Schwill, F., 1988. Dense Chlorinated Solvents in Porous and Fractured Media-Model Experiments (J. Pankow, trans.), Lewis Publishers, Boca Raton, FL, p. 146. Siegrist, R., 1993. VOC measurement in soils: the nature and validity of the process, in National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art Research Needs, January 12–14, Las Vegas, NV, p. 10. Thorstenson, D. and D. Pollock, 1989. Gas transport in unsaturated porous media: the adequacy of Fick’s Law, Review of Geophysics, 27:61–78. Tratnyek, P., Johnson, T., Scherer, M., and G. Eykholt, 1997. Remediating ground water with zero-valent metals: chemical considerations in barrier design, Groundwater Monitoring Review, Fall:108–114. Tsien, H., Brusseau, G., Hanson, R., and L. Wackett, 1989. Biodegradation of trichloroethylene by methylosinus trichosporium OB3b, Applied Environmental Microbiology, 55(12):3155–3161. Tuck, D., Iversen, G., Pirkle, W., and C. Rulison, 1998. Time-dependent interfacial property effects on DNAPL flow and distribution, in Wickramanayake, G. and R. Hinchee (Eds.), Nonaqueous Phase Liquids: Remediation of Chlorinated and Recalcitrant Compounds, Battelle Press, Columbus, OH, pp. 73–78. U.S. Department of Commerce, 1977. United States Exports, Schedule B Commodity Groupings, Schedule B Commodity by Country, FT 410/Dec., U.S. Government Printing Office, Washington, D.C., pp. 2–85. U.S. EPA, 1996. Region 9 Preliminary Remediation Goals (PRGs) for 1996, U.S. Environmental Protection Agency, U.S. Government Printing Office, Washington, D.C., p. 22.

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U.S. EPA 1993. Evaluation of the Likelihood of DNAPL Presence at NPL Site, EPA/540/R93/073, Office of Emergency and Remedial Response, Hazardous Site Control Division, U.S. Environmental Protection Agency, Washington, D.C., p. 15. U.S. EPA, 1992. Estimating Potential for Occurrence of DNAPL at Superfund Sites, Publ. No. 9355.4-07FS, Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, U.S. Government Printing Office, Washington, D.C., pp. 9. U.S. Tariff Commission, 1947. Synthetic Organic Chemicals: United States Production and Sales, 1946, Rep. No. 159, Second Series, U.S. Government Printing Office, Washington, D.C., p. 141. Vogel, T. and P. McCarty, 1987. Abiotic and biotic transformations of 1,1,1-trichloroethane under methanogenic conditions, Environmental Science and Technology, 21:1208–1213. Vogel, T., Criddle, C., and P. McCarty, 1987. Transformation of halogenated aliphatic compounds, Environmental Science and Technology, 21(8):722–736. Vold, R. and M. Vold, 1983. Colloid and Interface Chemistry, Addison-Wesley, Reading, MA, p. 694. Weeks, E., Earp, D., and G. Thompson, 1982. Use of atmospheric fluorocarbons F-11 and F12 to determine the diffusion parameters of the unsaturated zone in the southern high plains of Texas, Water Resources Research, 18:1365–1378. Wilson, B., Wilson, J., Kampbell, D., Bledsoe, B., and J. Armstrong, 1994. Traverse City: geochemistry and intrinsic bioremediation of BTX compounds, in Symposium on Natural Attenuation of Ground Water, EPA/600/R-94/162, U.S. Environmental Protection Agency, Washington, D.C. Wilson, J., Conard, L., Mason, S., Peplinski, W., and W. Hagan, 1990. Laboratory Investigation of Residual Liquid Organics from Spills, Leaks and the Disposal of Hazardous Wastes in Groundwater, EPA/600/6-90/004, U.S. Environmental Protection Agency, Washington, D.C. Wilson, J., Enfield, T., Dunlop, W., Cosby, R., Foster, D., and L. Baskin, 1981. Transport and fate of selected organic pollutants in a sandy soil, Journal of Environmental Quality, 10:501–506. Wolf, K., 1992. Case study — pollution prevention in the dry cleaning industry: a small business challenge for the 1990s, Pollution Prevention Review, Summer:311–330. Woodbury, A. and H. Li, 1998. The Arnoldi-finite element method for solving transport of reacting solutes in reacting media, in Wickramanayake, G. and R. Hinchee (Eds.), Nonaqueous-Phase Liquids Remediation of Chlorinated and Recalcitrant Compounds, The First International Conference on Remediation of Chlorinated and Recalcitrant Compounds, May 18–21, Monterey, CA, Battelle Press, Columbus, OH, pp. 97–106.

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2

Chemistry and Transport of Petroleum Hydrocarbons

3800 B.C. First documented use of asphalt for caulking reed boats

2.1 INTRODUCTION An understanding of the chemistry and transport of petroleum hydrocarbons provides the foundation for forensically reviewing information dealing with petroleum hydrocarbon contamination. This chapter provides basic terminology and concepts associated with the transport and fate of crude oil and refined products in the subsurface.

2.2 CHEMISTRY OF CRUDE OIL There are over one million types of hydrocarbons in crude oil, ranging from light gases to heavy residues. No two crude oils are identical. Crude oil is defined by Philip (1998) as… …extremely complex mixtures of saturated and aromatic hydrocarbons, ranging from C1 to C100 or higher, plus a wide variety of compounds containing nitrogen, sulfur, and oxygen. In addition, there is also a fraction called the asphaltene fraction which is basically insoluble in n-pentane and contains a very complex matrix of high molecular weight polar compounds.

In most cases, 90 to 98% by weight of crude petroleum consists of hydrocarbons, while the remaining materials include sulfur, oxygen, nitrogen, and other organic compounds. Variations in crude oil composition occur due to the nature of the source of the organic material, the geologic and thermal history, chemical changes that occur during oil formation and migration, and chemical alteration due to biodegradation, oxidation, or selective dissolution. Despite wide variations in the chemistry of crude oil, the elemental compositions fall within a narrow range of elements, as shown on Table 2.1 (Neumann et al., 1981). Crude oils have normal paraffins (n-paraffins)

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TABLE 2.1 Elemental Composition of Crude Oil Element

Composition (%)

Carbon Hydrogen Sulfur Nitrogen Oxygen

84–87 11–14 0–3 0–1 0–2

ranging from C1 to C40. Although higher carbon numbers exist in crude oils, most crude oils fall within the C5 to C30 range (Schmidt, 1998). The predominant hydrocarbon classes that comprise crude oil are straight or branchedchain alkanes, cycloalkanes, and aromatics. Alkanes (paraffins) are saturated hydrocarbons. Linear or normal alkanes (n-alkanes) ranging from C1 to C40 have been identified in crude oil and usually comprise 15 to 20%. In general, the most abundant alkanes in crude oil are the low-molecular-weight normal alkanes (C5–10). Normal alkanes (n-alkanes) are linear chains of carbons linked by single covalent bonds. Isoalkanes are hydrocarbons containing branched carbon chains. The highest concentration of isoalkanes in crude oils is in the C6 to C8 range. Crude oil can contain 10 to 15% isoalkanes. Cycloalkanes are similar to alkanes except that cycloalkanes consist of rings of carbon atoms joined by single atomic bonds. Cycloalkanes are abundant in crude oils and can comprise up to 30 to 40% by weight. The most abundant cycloalkanes (also called naphthenes) are the single-ring cyclopentanes (C5H10) and cyclohexanes (C6H12). Steranes and triterpanes are complex cycloalkanes often used as markers to identify the source and age of crude oil (Hughes and Holba, 1988; Seifert and Moldowan, 1978; Stout et al., 1999). Aromatic hydrocarbons consist of rings of six carbon atoms that are unsaturated (i.e., they do not contain the maximum number of bonded hydrogen atoms). Aromatics include the BTEX (benzene, toluene, ethylbenzene, and total xylenes) and polynuclear aromatic compounds (PNAs). Aromatic hydrocarbons contain carbon atoms linked with double bonds, the simplest being benzene (C6H6). Each hydrogen atom on the aromatic ring can be replaced with an alkyl group (CH3) which results in compounds such as toluene with one alkyl group attached to the benzene ring. Benzene rings can be linked to other benzene rings to form compounds such as biphenyls or terphenyls. When two or more benzene rings are fused, polynuclear aromatic hydrocarbons (also known as polycyclic aromatic hydrocarbons, or PAHs) are formed (see Section 4.10 in Chapter 4). Polycyclic aromatic hydrocarbons are compounds that originate from crude oil and many pyrolysis processes. Polycyclic aromatic hydrocarbons are of concern because of their genotoxic properties. Naphthalene (C10H8) is a lower molecular weight example and is generally considered to be a polycyclic aromatic hydrocarbon, although it has only two aromatic rings. Other non-hydrocarbon components in crude oil include sulfur, oxygen, and nitrogen. ©2000 CRC Press LLC

Sulfur is typically the most abundant element and may be present in several forms, including elemental sulfur, hydrogen sulfide, mercaptanes, and thiophenes (i.e., hydrogen molecules with bonded sulfur atoms). The sulfur content in most crude oils varies from about 0.1–3% for some of the heavier oils to 5–6% for bitumen. Sulfur does not decompose during the distillation process. The majority of sulfur is, therefore, present predominately in the higher molecular weight fractions and becomes concentrated in the higher weight refined products. The analysis of the sulfur content of crude and refined products, such as diesel, can be used to provide evidence to distinguish between multiple sources. The sulfur content of a petroleum hydrocarbon is determined using standards such as American Society for Testing Materials (ASTM) D-124, D-1552, and D-4294. Oxygen reacts with hydrocarbons to form compounds such as phenols, cresols, and xylenols. Nitrogen can bond with hydrocarbon molecules in crude oil to form small concentrations of pyrrole, pyridine, and quinoline. Metals are present in crude oils, although usually in small amounts. Metals can occur as inorganic salts, metallic soaps, and organometallic compounds. In some instances, sodium arsenite and arsenic trioxide are added to oil pumping wells to inhibit corrosion (Rohrbach et al., 1953; Wellman et al., 1999). The presence of arsenic in crude oil may, therefore, provide a means for identifying the origin of the crude oil.

2.3 CHEMISTRY OF REFINED PRODUCTS The chemistry of a refined petroleum product is the result of the composition of the crude oil and the refining process. The term “refined products” refers to those petroleum hydrocarbons that are blended and to which additive packages are included. Examples of refined products include gasoline, aviation fuels, jet fuel, and the newer formulations of diesel fuels (Harvey, 1998). Major refinery processes that affect product chemistry are (Speight, 1991): • Separation of the crude oil into various fractions • Conversion of marketable portions of the crude oil • Finishing of the various product streams

Separation and removal of the various portions of crude oil have historically been accomplished via distillation. The three products created via distillation are naphtha, middle distillates, and residual hydrocarbons. Naphtha, with a boiling range of 90 to 190∞C, includes gasoline, which is further processed for octane improvement. The middle distillate fractions are separated into kerosene (light-end) and diesel range (heavy-end) products The light-end middle distillates (boiling ranges from 150 to 260∞C) include kerosene, mineral spirits, Stoddard solvent, jet fuels, and diesel No. 1. Stoddard solvent was used extensively in the first half of this century for degreasing but was replaced by chlorinated solvents such as trichloroethylene due to the potential fire hazards associated with Stoddard solvent (Stewart et al., 1991). Examples of heavy-end products are Bunker fuels, heavy fuel oils, and asphalt. Examples of chromatograms for mineral oil, Stoddard solvent, and kerosene are shown in Figure 2.1. ©2000 CRC Press LLC

FIGURE 2.1 Chromatograms of mineral oil, Stoddard solvent, and kerosene. (From Bruya, J., Chromatograms, Friedman and Bruya, Seattle, WA, 1999. With permission.)

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TABLE 2.2 Distillation Temperature and Carbon Range of Distilled Products Product Gasoline Naphtha Kerosene and jet fuels Diesel and fuel oils Heavy fuel oils Lubricating oils

Distillation Temperature (C∞)

Carbon Range

30–200 100–200 150–250 160–400 315–540 425–540

C5–C10/12 C8–C12 C11–C13 C13–C17 C19–C25 C20–C45

Heavy-end middle distillates with boiling ranges of 190 to 400∞C are processed to produce diesel fuel No. 2 and heating oils (Kaplan et al., 1995). Table 2.2 summarizes key distilled products, their distillation temperature range, and carbon range (Galperin, 1997; Schmidt, 1998). While the distillation temperature and American Petroleum Institute (API) gravity of hydrocarbons provide useful information in the refining process, they can provide corroborative evidence in distinguishing among multiple sources of fuel releases. API gravity is defined in Equation 2.1 as: API gravity = 141.5/P – 131.3

(Eq. 2.1)

where P is the specific gravity of the crude oil or refined product at 60∞F. Evidence used to distinguish among sources of diesel, gasoline + diesel + jet fuel, and gasoline at a refinery is shown in Figure 2.2 as a function of API gravity. The API gravity of each of the various fuels stored at the refinery were known, thereby providing a baseline for comparison. The use of the distillation temperature of a fuel to distinguish among multiple sources (degraded gasoline and a gasoline + diesel + jet fuel mixture) is shown on Figure 2.3. For the free product samples collected from the groundwater table shown in Figure 2.2, the initial boiling point (IBP) and final boiling point (FBP) of the fuels were known, thereby allowing correlation of the IBP and FBP of the samples to specific locations on the refinery. The evolution of crude oil refining over time has resulted in different products and blends of refined product. The unit process and the waste streams from these processing changes are helpful in age-dating a product and/or bracketing a time frame when certain refinery processes and their associated waste products were produced. Table 2.3 summarizes some of the key historical changes in petroleum refining (Gibbs, 1990; Harvey, 1998).

2.3.1 GASOLINE Gasoline is composed of low-boiling hydrocarbons in the C5 to C10–C12 range that are ignitable in an internal combustion engine. On a chromatograph, fresh gasoline

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FIGURE 2.2 Use of API gravity to distinguish between fuels.

exhibits an asymmetric distribution pattern from the CH1 (methylcyclohexane) to CH7 (a heptylcyclohexane) range, with the CH2 peak being the most abundant and the peaks CH2 to CH7 decreasing rapidly in intensity (Galperin, 1997). Gasoline has a boiling-point distribution from about 120 to 400∞F. As a result of the preferential partitioning of low-boiling-temperature compounds found in gasoline, the concentration of the BTEX components can be as high as 1 to 4% for benzene and 3 to 20% for toluene. Gasoline blending has changed, in part, to create fuels with different octane ratings. Examples of gasoline grades are summarized in Table 2.4 (Harvey, 1998). Gasoline blends often reflect the level of refining. A premium-grade gasoline, for example, is a

FIGURE 2.3 Use of initial (IBP) and final boiling point (FBP) temperatures to identify fuel types.

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TABLE 2.3 Chronology of Key Changes in Petroleum Refining in the U.S. Date

Key Refinery Process

1910 1913 1920 1923 1926 1928 1929 1936 1938 1940 1959 1970–74 1980 1990

Straight run (distilled) products produced; 65–75 octane rating Dubbs thermal cracking process introduced Coking introduced Lead introduced in gasoline to minimize backfiring Lead anti-knock additive introduced Lead scavengers ethylene dibromide and ethylene dichloride introduced Regular and premium gasoline sold Fluid catalytic cracking introduced Alkylation introduced Reforming introduced Hydrocracking introduced More olefins added to gasoline Lead regulations Advent of environmental regulations of sulfur, aromatics, and oxygenates

more tightly regulated blend than a mid-grade or regular gasoline. Chromatograms of gasoline grades and blends are shown in Figure 2.4 (Zemo et al., 1993). Changes in the octane ratings of different gasoline grades include a 65 to 75 octane rating in 1910, an average octane rating of 82 in 1946, and an average octane rating of 96 in 1968 (Gibbs, 1990). The significance of these different gasoline grades and octane ratings over time is that it is unlikely that forensic testing can identify a gasoline grade once it has entered the subsurface. Compounds used to provide higher octane ratings, however, can be identified on a chromatogram. Examples include isooctane, toluene, ethylbenzene, xylenes, and trimethylbenzene. For example, a premium-grade, 1994 gasoline tends to have a high percentage of iso-octane and aromatics. The greater the combined percentage of iso-octane and aromatic compounds, such as toluene, the higher the octane and fuel quality and, therefore, the more likely it is that the product was refined and blended.

TABLE 2.4 Grades of Gasoline Leaded Gasoline

Unleaded Gasoline

Super premium leaded Premium or supreme leaded “Super regular” leaded Regular leaded Economy leaded Regular low lead

Premium or supreme unleaded Mid-grade unleaded Regular unleaded

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FIGURE 2.4 Gasoline chromatograms. (From Zemo, D. and T. Graf, in Proc. of the 1993 Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Restoration, November 10–12, Houston, TX, Ground Water Management Book 17, National Ground Water Association, Dublin, OH, 1993, pp. 39–54. With permission.)

Refined gasoline contains olefins (alkenes and alkynes), while crude oils and virgin naphthas do not. As a result, olefins are useful for distinguishing between refined and crude oils. Olefins are products of the catalytic cracking process. Olefins are identified on chromatograms as a cluster of small peaks to the right of the C6 peak (Schmidt, 1998). Alkynes (acetylenes) are also not normally found in crude oil. Another indicator used to distinguish between refined and unrefined products is the

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FIGURE 2.5 Chromatograms for diesel fuels No. 1 and No. 2. (From Bruya, J., Chromatograms, Friedman and Bruya, Seattle, WA, 1999. With permission.)

presence of methylcyclohexane (MCH). Methylcyclohexane is abundant in unrefined gasoline range hydrocarbons and naphthas. In general, the greater the concentration of methylcyclohexane, the less the product has been refined, as well as the lower the octane rating of the gasoline.

2.3.2 DIESEL Diesel consists of hydrocarbons in the C11 to C18–27 range. Depending on the grade of diesel, it contains a high concentration of cycloalkanes and smaller amounts of aromatic compounds (i.e., BTEX). Diesel tends to have greater concentrations of polycyclic aromatic hydrocarbons than does gasoline. The changing formulation of diesel provides opportunities for dating a release. Prior to 1975, diesel was primarily straight chained, while post-1975 diesel was thermally cracked. This distinction can be determined analytically with only several milliliters of product, thereby providing a bracket of time when the product was available. Chromatograms of a diesel fuel No. 1 and No. 2 are shown in Figure 2.5.

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TABLE 2.5 Products, Synonyms, and Characteristics of Diesel and Jet Fuels Product and Synonym(s)

Composition and Characteristics

Diesel No. 1

Similar in composition to a blend of kerosene and diesel No. 2. Diesel No. 1 is manufactured in cold climates and is also sold in warm climates when a refinery desires to blend its kerosene with more expensive diesel No. 2. Diesel No. 1 exhibits an alkylcyclohexane pattern on a mass chromatograph in the range from CH1 to CH14, with a maximum at CH5.

Diesel No. 2

Automotive diesel. Straight-run or catalytically cracked petroleum distillate with a typical carbon range of C8–9 to C24–27 and a boiling range of approximately 163 to 382∞C. Includes straight-run kerosene, middle distillate, hydro-desulfurized middle distillate, and light catalytically and thermally cracked distillates. Formulated for use in atomizing-type burners. BTEX components can be present in small amounts. Using gas chromatography/mass spectrometry (GC/MS), diesel No. 2 shows a range of alkylcyclohexanes from CH1 to CH14, maximizing around the CH9 and CH10 peaks. Characterized by a smooth n-alkane distribution pattern.

Diesel No. 4

Railroad diesel. A straight-run or cracked petroleum distillate with a typical carbon range of C11 to C30. Used without preheating in commercial or industrial burners that can accommodate a higher viscosity diesel such as diesel No. 4.

Diesel No. 5

A fuel comprised primarily of straight-chained hydrocarbons. Diesel No. 5 is a residual fuel that often requires preheating for handling.

Bunker C (heating oil or diesel No. 6)

A residual fuel used in commercial and industrial heating. Bunker C requires preheating for storage and for burning. Sulfur is often found in higher concentrations than in other diesels, unless they are deliberately extracted. Bunker C is the primary fuel for steam-powered ships and for onshore power-generation plants and is primarily a mixture of diesel No. 1 and No. 2 and residual oil. Bunker C is a distillation residue of crude oil and contains biomarkers such as terpanes and steranes. Bunker C has a hydrocarbon range from C9 to about C36 and a boiling point range of about 340 to 1050∞F.

Kerosene (No. 1 fuel oil)

A straight-run distillate with hydrocarbons in the C9/10 to C16 range. A light-end middle distillate used in vaporizing-type burners where the fuel is ignited by contact with a heated surface or radiation. Consists primarily of paraffins with smaller amounts of naphthalene and aromatic hydrocarbons. The carbon distribution peaks around C12 to C13. It is similar in composition to JP-5 and JP-6 jet fuels.

Diesel is available in various grades. Diesel, kerosene, and the lighter distillates contain various amounts of the BTEX aromatics up to 1500 parts per million (ppm) (Dunlap and Beckmann, 1988). The composition and characteristics of diesels and middle distillate products are described in Table 2.5 (Havlicek, 1986; Kaplan et al., 1995; Kaplan and Galperin, 1996). A petroleum forensic laboratory to needed to distinguish between fuels that are similar. Figure 2.6 illustrates chromatograms for jet fuel No. 4 (JP-4) and jet fuel No. 5 (JP-5) to show the chromatographic similarity of these two fuels (Bruya, 1999).

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TABLE 2.5 (cont.) Products, Synonyms, and Characteristics of Diesel and Jet Fuels Product and Synonym(s)

Composition and Characteristics

Stoddard solvent

Used as a drycleaning solvent and paint thinner and in printing inks, certain adhesives, and some photocopy toners. It consists primarily of nonanes with smaller amounts of alkylbenzenes. Synonyms include mineral spirits, light petroleum naphtha, drycleaning safety solvent, petroleum solvent, varnoline, and spotting naphtha. Registered trade names include Texsolve S® and Varsol 1® (ATSDR, 1995). The boiling range is between 220 and 300∞F. Stoddard solvent exhibits an alkylcyclohexane pattern upon GC/MS in the CH2 to CH9 range, with the distribution maximizing at CH5.

Petroleum naphtha

Naphtha exhibits an alkylcyclohexane pattern in the CH1 to CH6 range that maximizes at CH3.

Jet fuels: JP-1

Military-grade distillate with a flash point of 95∞F.

JP-4 (Jet B)

Military-grade distillate with a flash point of –10∞F and a boiling range of 48 to 270∞C. Contains about 65% gasoline and 35% light distillates. Most of the volatile gasoline hydrocarbons are absent, and the iso-octane content is generally below 1%. On a chromatogram, it looks like a light-kerosene and/or gasoline blend with a considerable amount of aromatic compounds. Using GC/MS, it demonstrates a distribution pattern in the CH1 to CH9 range.

JP-5 (Jet A1)

A U.S. Navy distillate with a flash point of 95∞F and a boiling range of 150 to 290∞C. JP-5 has a low freezing point and high flash point for use by carrierbased aircraft for long-range flights. JP-5 has an alkane distribution pattern in the kerosene range with a maximum around C11. Using GC/MS, a distribution pattern in the kerosene range (CH1 to CH9) is discernible, with a noticeable difference in the maximum peak of distribution with CH5 for JP-5 and CH 4 for Jet A.

JP-6 (Jet A)

Military-grade distillate with a flash point of 100∞F. Preferred for short- and medium-range aircraft flights.

JP-8

A military aircraft fuel with a distribution pattern around C10 or C11. On a GC/MS, an asymmetric distribution pattern is observable in the CH1 to CH14 range.

2.4 CHEMICAL REACTIONS IN THE VADOSE ZONE The physical transport of crude oil and refined products through the subsurface is a function of product chemistry, the hydraulic conductivity (K) of the soil or rock, and the presence of a driving mechanism such as rainfall, ponded water, or leakage from an underground storage tank. An understanding of the relationship between a contaminant and the media through which it is transported is used to estimate the relative

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FIGURE 2.6 Chromatograms of JP-4 and JP-5. (From Bruya, J., Chromatograms, Friedman and Bruya, Seattle, WA, 1999. With permission.)

mobility and distribution of the contaminant. Contaminant properties impacting the mobility of a chemical through the unsaturated zone and saturated zones include its Henry’s Law constant, vapor pressure, density, solubility, and viscosity. If the petroleum hydrocarbon has a significant volatile component, vapor transport of the compound can be important. The chemical and physical interaction of petroleum hydrocarbons in the subsurface is important in understanding the mobility of the compound. Commonly encountered interactions include sorption, oxidation/reduction processes, chemical precipitation, ion exchange, hydrolysis, biological mediated reactions, and cosolvation.

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2.4.1 HENRY’S LAW CONSTANT (KH) The Henry’s Law constant (KH), also known as the air/water partition coefficient, is the ratio of the partial pressure of a compound in air to its concentration in water at a given temperature. The Henry’s Law constant is, therefore, a measure of the propensity of a compound to volatilize as it migrates through the soil (see Chapter 1, Section 1.3.3). As the Henry’s Law value increases, the amount of the contaminant in the soil vapor phase increases. Compounds with high Henry’s Law constants (e.g., butane, hexane, and benzene) are more amenable to soil gas surveys and remediation via vapor extraction than compounds with low values. For the lower alkanes (methane through hexane), the dimensionless Henry’s Law constant ranges from about 30 to 70 which means that, in equilibrium, 30 to 70 molecules of these alkanes are present in the soil vapor for every molecule that dissolves into the groundwater. For the BTEX constituents, the Henry’s Law constant is about 0.25, which means that one molecule of BTEX exists in the soil vapor for every four that dissolve into the water. As a result, a soil vapor survey is about 200 times more likely to detect the lower alkanes than BTEX compounds (Hartman, 1998).

2.4.2 LIQUID DENSITY The relative density (also called specific gravity) of a substance is defined as the ratio of the density of the substance to the density of distilled water (a mass-to-volume ratio). The density of distilled water at a standard temperature and pressure is 1.0 g/ mL. Specific density is a unitless measurement but is dependent on the temperature of the substance at the time of measurement. Light non-aqueous phase liquids (LNAPLs) have densities less than 1.0, while dense non-aqueous phase liquids (DNAPLs) have densities greater than 1.0. Most crude, residual, and used oils are LNAPLs with densities from about 0.6 to 1.0 g/mL. A contaminant’s density is important, especially when the contaminant enters the capillary fringe (that partially saturated area above the groundwater table). Liquids with densities greater than 1.0 (e.g., coal tar) have a greater probability of “sinking” into groundwater than do liquids with densities less than 1.0 (gasoline, diesel, Stoddard solvents, mineral oils), which tend to “float” on the water table. BTEX (benzene, toluene, ethylbenzene, and xylene) compounds are lighter than water, while polycyclic aromatic hydrocarbons (PAHs) such as anthracene, chrysene, fluorene, naphthalene, phenanthrene, and pyrene are heavier than water. The term PAH is synonymous with polynuclear aromatic hydrocarbons (PNAs). These chemicals are often classified as carcinogenic — benzo(a)pyrene, benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(g,h,i)perylene, chrysene, dibenzo(a,h)anthracene, and indeno(1,2,3-c,d)pyrene — and noncarcinogenic — naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, and pyrene. Hydrocarbons with a high specific gravity are transported vertically in the unsaturated zone due to gravity and capillary forces. If the volume of high-specificgravity hydrocarbons released is large, the hydrocarbons will be vertically transported

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TABLE 2.6 Density of Selected Light and Dense Hydrocarbons Density (g/cm3) Hydrocarbon Coal tar Bunker C (No. 6 fuel oil) No. 5 fuel oil Styrene No. 4 fuel oil Lube oil (gear oil) Lube oil (crankcase oil, new) Lube oil (crankcase oil, used) North Sea crude Benzene 10W40 engine oil Toluene Kerosene No. 2 fuel oil Light heating oil Marine diesel Diesel fuel Mineral spirits Soltrol Jet fuel JP-4 JP-5 JP-7 JP-8 JP-A JP-B Gasoline Naphtha (petroleum ether)

25∞C

15∞C

1.028 0.969 0.917 0.907 0.898 0.883 0.878 0.885 0.8–0.88 0.874 0.866 0.865 0.849 0.840 0.82–0.86 0.862 — 0.793 0.789 0.77–0.84 0.755 0.788 0.779 0.840 0.775 0.757 0.720 0.640

— 0.974 0.923 — 0.904 — — — — — — — 0.839 0 866 — — 0.827 — — — — 0.844 — — — — 0.729 —

through the soil and groundwater due to density. This phenomenon is known as density flow. Upon entering the groundwater, these hydrocarbons migrate as a function of specific gravity and less by advection (the mass transport of groundwater). Table 2.6 lists the densities of several light and dense hydrocarbons (API, 1989, 1994, 1995; Dragun, 1988).

2.4.3 SOLUBILITY The solubility of a compound is the saturated concentration of the compound in water at a known temperature and pressure. The more soluble the compound, the greater the fraction that dissolves into the soil pore water or groundwater. BTEX compounds

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TABLE 2.7 Highly Soluble Components of Gasoline Compound Benzene Toluene Ethylbenzene o-Xylene p-Xylene m-Xylene 2-Butene 2-Pentene Butane 1,2,4-Trimethylbenzene Pentane a

Percent in Gasoline by Weight 1.94 4.73 2.0 2.27 1.72 5.66 0.315a 0.435a 3.83 3.26 3.11

Average of cis- and trans-.

are so frequently encountered in groundwater in part due to their high solubility. Benzene, for example, was detected 23% of the time at 888 Superfund sites based on a total of 466 chemicals tested for, as of October 1986. Toluene and xylene were detected 27% and 13% of the time, respectively. Toluene was the second most frequently encountered contaminant, second only to trichloroethylene (TCE; 1100 mg/L at 20∞C) (Siegrist, 1993). Table 2.7 lists those highly soluble compounds in an API PS6 unleaded gasoline along with their estimated percent by weight (API, 1985, 1994). Compounds with high water solubilities tend to desorb from soils, are less likely to volatilize from water, and are susceptible to biodegradation. Compounds with low solubilities tend to sorb onto soils and volatilize more readily from water and are more likely to enter the groundwater. The water solubility of a compound varies with pH, the presence of inorganic salts, and the presence of organic carbon. Solubilities of pure phase compounds in water at three temperatures are summarized in Table 2.8 (Havlicek, 1986; Polak and Lu, 1973; Rossi and Thomas, 1981). BTEX solubility in water is dependent on the nature of the multi-component mixture, such as gasoline, diesel, or crude oil. The solubility of a constituent within a multi-component mixture may be orders of magnitude lower than the aqueous solubility of the pure chemical constituent in water (Odencrantz et al., 1992). The weight percent and mole fraction of the BTEX components as functions of the mixture are also important. Table 2.9 presents the calculated effective solubility of BTEX compounds in gasoline, diesel, and a California crude oil (API, 1985; Metcalf and Eddy, 1993).

2.4.4 VISCOSITY Viscosity is the property of a substance to offer internal resistance to flow. An ideal fluid is one that is devoid of viscosity. A similar but different term is “kinematic

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TABLE 2.8 Solubility of BTEX Compounds and MTBE Compound Benzene (C6H6) Toluene (C6H5CH3) Ethylbenzene (C6H5CH2CH3) m-Xylene (C6H4(CH3)2) o-Xylene (C6H4(CH3)2) p-Xylene (C6H4(CH3)2) MTBE ((CH3)3C(OCH3))

Solubility at 0∞C (ppm)

Solubility at 20∞C (ppm)

— 724 197 196 142 — —

1780 515 153 158 152 — —

Solubility at 25∞C (ppm) 1760 573 177 146–173 213 180–200 48,000

viscosity” which is the viscosity of the substance divided by its density. The viscosity of a liquid usually increases with decreasing temperature, though in some complex mixtures there is a discontinuity in the temperature/viscosity relationship. These discontinuities occur where there is a large change in viscosity over a very narrow temperature range. The simplest and most widely used determination of viscosity is American Society for Testing Materials (ASTM) Standard Method D-445 as described in Equation 2.2. m = p r4P/8Nl

(Eq. 2.2)

where m r P N l

= = = = =

quantity discharged in units of time. tube radius. pressure difference between the ends of a capillary tube. coefficient of viscosity. tube length.

TABLE 2.9 Effective Solubility of BTEX Components in Gasoline, Diesel, and Crude Oil Effective Solubility (ppm) Compounds

Gasoline

Diesel

California Crude Oil

Benzene Toluene o-Xylene m-Xylene p-Xylene Ethylbenzene

44.39 26.54 3.26 8.45 3.25 2.87

8.83 3.25 1.39 1.44 1.82 0.55

0.70 1.54 0.25 0.26 0.32 0.74

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TABLE 2.10 Kinematic Viscosity of Refined Products Product Gasoline Diesel Kerosene JP-4 No. 1 fuel oil No. 2 fuel oil No. 4 fuel oil No. 5 light fuel oil No. 5 heavy fuel oil No. 6 fuel oil a b

Kinematic Viscosity at 10∞C (cSt)a

Kinematic Viscosity at 100∞ C (cSt)a

0.61–0.85 2.7b 2.3b 1.1–1.8 2.2–4.2 3.0–8.0 30–100 130–400 500–1200 1500–30,000

<0.40 — — 0.47–0.64 0.7–1.0 0.85–1.3 2.5–4.8 5.5–8.0 9.0–13 15–50

One centistoke (cSt) = 1 ¥ 106 m2/sec. Measured at 15∞C.

While diesel and gasoline viscosities are similar, crude oil has a wide range of viscosities. For example, the viscosity of a Prudhoe Bay crude oil in Alaska is 73.5 Saybolt units, while a Kern River crude oil from Bakersfield, CA, is greater than 6000 Saybolt units. The viscosity of refined petroleum products varies from about 0.25 to more than 50,000 cPa at 15∞C. An approximate correlation between specific gravity and viscosity for refined products is described in Equation 2.3. hro = 8.28rro(9.5)

(Eq. 2.3)

where hro = ratio of the kinematic viscosity to water. rro = specific gravity of the refined produced.

As a basis of comparison, the kinematic viscosity for water at 20∞C is 0.01 cm2/sec, while benzene has a kinematic viscosity of 0.00721 cm2/sec. Pure benzene flows about 40% faster than water through identical porous media. The kinematic viscosity is called dynamic or intrinsic viscosity. Infiltration velocities are often approximated as a proportionality that is inverse to the kinematic viscosity. For example, a crude oil can migrate 3 to 35 times slower through soil than water (Dragun, 1988). The kinematic viscosity of a hydrocarbon is affected by temperature. For crude oil, this effect can be several orders of magnitude. Table 2.10 summarizes the kinematic viscosity of selected heavy fuel oils for two temperatures (API, 1989, 1994; Dragun, 1988). A decrease in viscosity increases the flow rate of a hydrocarbon through a porous media. During the natural weathering of petroleum products, viscosity tends to increase sharply.

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2.4.5 VAPOR PRESSURE AND VAPOR DENSITY Volatilization is the phase change of a compound from a liquid or solid to a gaseous phase; it is associated with the vapor pressure of the compound. In general, compounds with vapor pressures exceeding 0.5 to 1 millimeter of mercury (mmHg) can exist in appreciable concentrations as vapor near a free phase product. Hydrocarbons that volatilize quickly include butane, pentane, hexane, heptane, and octane. The aromatic BTEX and methyl ethyl benzenes and trimethylbenzenes also volatilize quickly but at a rate less than the butanes, pentanes, hexanes, heptanes, and octanes. The loss of BTEX compounds in a sequential order relative to vapor pressure is often observed in the analytical data at hydrocarbon-impacted sites. Vapor density is the density of a compound relative to air (e.g., 29 g/mol). Most petroleum hydrocarbons have densities 3 to 4 times greater than air. The vapor density is estimated by dividing the molecular weight of a compound by the molecular weight of air. The molecular weight of benzene is 78 g/mol; therefore, dividing 78 by 29 yields a vapor density for benzene of 2.5. The vapor density for gasoline is about 3.3. The significance of vapor density is that petroleum hydrocarbon vapors can migrate through porous soils in the unsaturated zone as a function of vapor density (Hartman, 1998).

2.4.6 SORPTION Sorption is the uptake of a vapor or liquid into another material without reference to a specific mechanism (Chiou, 1989). Sorption encompasses the processes of adsorption, absorption, ion exchange, ion exclusion, retardation, chemisorption, and dialysis. Of these processes, absorption (the penetration of substances into the bulk of a solid or liquid) and adsorption (the surface retention of a solid, liquid, or gas molecules by a solid or liquid) are the most important. This phenomenon results in a contaminant’s distribution between the solid and liquid phase and relative retardation of the chemical. The higher the fraction of the contaminant that is sorbed, the less is available for transport. The sorption capacity of a compound is described by the term “sorption coefficient”. The sorption coefficient is the ratio of an adsorbed chemical per unit weight of organic carbon to the concentration of the contaminant. It implicitly assumes a reversible process — that is, sorption and desorption occur at the same rate.

2.4.7 RETARDATION Retardation is the lowering of the average velocity of a contaminant mass relative to the average (advective) groundwater velocity. Compounds that sorb strongly to organic carbon material in soils characteristically have low solubilities; compounds with low tendencies to adsorb onto organic particles have high solubilities. The affinity of a compound to be sorbed by organic or mineral matter is called the retardation factor (R). The retardation factor or coefficient is the ratio of the

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concentration of a compound on a solid to the concentration of that compound in solution. Laboratory experiments indicate that values for retardation vary widely, depending on the type of soil and contaminant. Given the uncertainties associated with calculating R, compounds with values less than 2 can be considered to be moving at a rate similar to groundwater. Distribution coefficient values can be obtained from the literature, calculated from the measured organic carbon content in soil, or measured from laboratory batch sorption or column transport studies. The most common technique is to measure the organic content of the soil and obtain the soil/ organic carbon partition coefficient (Koc) of the chemical from published tables. Retardation directly impacts the rate at which a hydrocarbon or components of a hydrocarbon will move in the subsurface. For example, non-BTEX compounds that are relatively mobile in water (based on their retardation coefficients) include 1,2,4trimethylbenzene, naphthalene, 2-methylnaphthalene, cyclohexane, n-hexane, 2,3dimethylbutane, and 2,2-dimethylpentane. Compounds that are relatively less mobile in water values include benzo(a)anthracene, benzo(a)pyrene, 5-methylchrysene, 1methylphenanthrene, and dibenzothiophene.

2.4.8 BIODEGRADATION Biodegradation is the biological transformation of complex substances into simpler substances by bacteria, fungi, and yeasts. Hydrocarbon biodegradation is accomplished primarily by bacteria. Over 200 soil microbial species have been identified that can assimilate hydrocarbon substrates. Some of these microbes include Pseudomonas, Flavobacterium, Micrococcus, Mycobacterium, Nocardia, and Acinetobacter (Bowlen and Kosson, 1995; Manahan, 1984). For most biodegradation pathways, the final degradation products are carbon dioxide and water, a process called mineralization. It is possible that the final mineralization products are not achieved and that the degradation results in relatively stable aromatic hydrocarbons. While a multitude of degradation reactions can occur, common transformations occur stepwise from end carbons, producing alcohols, aldehydes, and fatty acids in sequence. The rate and ability of microbes to degrade hydrocarbons is dependent on the ability of the subsurface environment to support a healthy community of microbes. Conditions that influence the rates of hydrocarbon degradation include soil temperature, soil porosity, soil moisture content, the oxygen content of the particle spaces, the nutrient content, and fuel type (Kaplan et al., 1995). The concentrations of nutrients and oxygen required to sustain viable microbial communities are highly variable. In general, a 1:20 ratio of available inorganic nitrogen to the petroleum hydrocarbon and a 1:100 ratio of available phosphate to petroleum hydrocarbons are necessary to support biological degradation of petroleum hydrocarbons. Some generalizations concerning biodegradation are that biodegradation may not occur if the concentration of the compound is very low and that most organic

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compounds will degrade to some extent. Current research suggests that benzene is not degraded under denitrifying conditions and that toluene, xylene, and ethylbenzene degradation are slow (Kao and Borden, 1997). At the Eglin Air Force Base site, the preferential removal of toluene and ortho-xylene from the BTEX components closest to the spill was observed. Ethylbenzene and meta- and para-xylene degradation increased after the toluene and ortho-xylene were depleted (Wilson et al., 1994). It was also calculated that for the BTEX components within the groundwater approximately 1.0 mg of methane was produced for each 1.3 mg of BTEX destroyed. In general, if the concentration of petroleum hydrocarbons or heavy metal concentrations are in excess of 25,000 or 2500 ppm, respectively, then the environment is considered inhibitory or toxic to aerobic bacteria. Biodegradation commences as soon as the petroleum hydrocarbon is released into the subsurface, with the lower molecular weight alkanes degraded first, followed by the higher molecular weight compounds. The temperature of the surrounding soil or groundwater also impacts degradation rates. Some of the fastest bioattenuation rates of BTEX compounds observed by the Environmental Protection Agency’s Robert S. Kerr Environmental Research Laboratory in Ada, OK, have been in cases where groundwater temperatures are high (24 to 28∞C). Biodegradation rates are influenced by the molecular structure of the hydrocarbon. Straight-chained saturated hydrocarbons are degraded more readily than aromatics (BTEX compounds), which are subsequently degraded more readily than alicyclics and highly branched aliphatic hydrocarbons. As a result of these hydrocarbon degradation sequences, alicyclics and highly branched aliphatics accumulate in the soil, while the more biodegradable of the compounds in the original product are not present. In general, the weathering of gasoline, diesel, and Bunker C fuel proceeds in the following temporal sequence (Galperin, 1997): 1. 2. 3. 4. 5. 6. 7. 8. 9.

Abundant normal alkanes Light-end normal alkanes Middle-range normal alkanes, olefins, benzene, and toluene More than 90% removal of the alkanes Alkylcyclohexane and alkybenzenes Isorepnoids and C0-naphthalene reduction C1-naphthalenes, benziothiophene, alkylbenzothiophenes, and C2-naphthalenes Phenanthrenes, dibenzothiophenes, and other polynuclear aromatic hydrocarbons Tricyclic terpane enrichment, selective removal of regular steranes, reduction of C31–C35 homohopanes 10. Increased abundance of tricyclic terpanes, diasteranes, and aromatic steranes

The biodegradation of specific petroleum fractions in a fuel has been proposed as a means to age-date a hydrocarbon (Kaplan et al., 1995; Morrison, 1997; Raymond et al., 1976). The basis of this approach is reliance on the biodegradation half-life of hydrocarbon compounds in the soil or groundwater. The estimated half-life is the time required for one half of the compound to biodegrade. The rate of biodegradation is usually expressed in units of g/m2 day–1, g/m3 year–1, mg/day per bacterial cell, percent of oil removed after a known number of days or weeks, or g/m3 day–1. A

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TABLE 2.11 Biodegradation Half-Lives of BTEX and PAH Compounds Biodegradation Half-Life (hr)a Compound Benzene (C6H6) Toluene (C6H5CH3) Ethylbenzene (C6H5C2H5) o-, m-, p-Xylene (C6H4(CH3)2) Acenaphthene (C12H10) Anthracene (C14H10) Benzo(a)pyrene (C20H12) Chrysene (C18H12) Fluoranthene (C10H10) Fluorene (C13H10) Naphthalene (C10H8) Phenanthrene (C14H10) Pyrene (C16H10) a

Soil

Groundwater

120–384 96–528 72–240 168–672 299–2448 1200–11040 1368–12,720 8904–24,000 3360–10,560 768–1440 398–1152 384–4800 5040–45,600

240–17,280 168–672 144–5472 336–8640 590–4896 2400–22,080 2736–25,440 17,808–48,000 6720–21,120 1536–2880 24–6192 768–9600 10,080–91,200

Measured at 25∞C.

summary of the half-lives of selected BTEX and polynuclear aromatic hydrocarbon (PAH) compounds is provided in Table 2.11 (API, 1985; Howard et al., 1991).

2.5 OVERVIEW OF TRANSPORT THROUGH THE UNSATURATED (VADOSE) ZONE The unsaturated zone is that portion of the subsurface situated between the ground surface and first water-bearing formation. Surface releases of hydrocarbons usually transit this zone prior to entering the groundwater. Physical parameters used to describe soils and used in petroleum transport calculations include porosity, permeability, hydraulic conductivity, and gas permeability. The transport of petroleum hydrocarbons through soil can change the hydraulic conductivity of the native soil, if the hydrocarbons are the primary wetting fluid (as opposed to water). This can occur with a massive release in which the hydrocarbons displace the water between the soil grains. It is a physical process and is reversible; if water subsequently displaces the petroleum hydrocarbons, the hydraulic conductivity will significantly decrease. These changes usually occur due to the permeation by nonpolar organics with clay. Typically, these changes are related to the following mechanisms: dehydration, swelling, flocculation, and macroscopic cracking (Anderson et al., 1985; Daniel et al., 1986). Unsaturated hydraulic conductivity values for the vadose zone are obtained in the field or laboratory by measuring the hydraulic conductivity of a soil under saturated

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conditions and then allowing the water to drain from the soil. The resulting graph that plots the percent moisture vs. soil suction is called a soil moisture characteristic curve. A dry soil exhibits greater soil suction than a wet soil. A soil characteristic curve enables calculation of the hydraulic conductivity as a function of soil moisture content.

2.5.1 TRANSPORT THROUGH SOIL The fundamental principles governing advective (mass) transport of water in soil generally apply to those for hydrocarbon transport (i.e., gravity and capillarity). Hydrocarbons move through the soil under a three-phase flow condition, displacing air and water. Variations in soil permeability result in a deviation from the gravitationally dominated vertical flow; as the hydrocarbon encounters layers of slightly less permeable materials or materials with smaller pores, it will tend to flow mostly in the horizontal direction until it encounters a path of less resistance. This conceptual model is more complex, however, because other transport and transformation processes occur. If a large volume of gasoline or diesel is released at or near the surface, it initially tends to infiltrate vertically through the soil. If the volume of release is sufficient to overcome the residual soil-retention capacity, the migration of the hydrocarbon will continue until the fluid reaches the capillary fringe, where it accumulates (Bossert and Bartha, 1984). As the hydrocarbon is transported through the soil, it may encounter less permeable soils that create a boundary condition; this may result in lateral spreading until a more permeable horizon is encountered for the hydrocarbon to move vertically. On a soil particle scale, petroleum hydrocarbon distribution in soil is dependent on the pore size between the soil grains and the pore pressures of the air, water, and hydrocarbons occupying these pore spaces. If the hydrocarbon completely saturates the soil and displaces water in the soil, maximum lateral and vertical spreading will occur. Gasoline components will also preferentially dissolve from the bulk hydrocarbon and migrate at different velocities through the soil (as well as the groundwater). This phenomenon is called chromatographic separation, which is often observed in the separation of more mobile compounds such as methyl-tertiary-butyl-ether (MTBE) moving ahead of the center of mass of a hydrocarbon in groundwater.

2.5.2 COSOLVATION AND COLLOIDAL TRANSPORT Cosolvation (also referred to as cosolvency) is the enhancement of an otherwise low mobility compound by its preferential dissolution into an organic solvent. Cosolvation occurs when a mobile phase is formed from multiple solvents that are miscible in each other (Kargbo, 1994). The addition of a cosolvent decreases the retardation and sorption coefficient of hydrophobic organic compounds such as polycyclic aromatic hydrocarbon compounds. For soils, cosolvation is shown to increase mobility significantly only at high cosolvent concentrations, usually greater than about 5% of the solution (Nkedi-Kizza et al., 1987). Cosolvation has been demonstrated to enhance the solubilization of sparingly soluble compounds in the pharmaceutical literature and in soil research (Lane and Loehr, 1992).

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TABLE 2.12 Residual Saturation (mg/kg) of Refined Products in Soil Soil Type Coarse gravel Gravel to coarse sand Coarse to medium sand Medium to fine sand Fine sand to silt

Gasoline

No. 2 Fuel Oil

Lube Oil

No. 6 Fuel Oil

— — — 2000 —

800 1600 2800 4800 8000

1600 3200 5600 9600 16,000

— — — 60,000 —

Another example illustrating cosolvation is the detection of the polynuclear aromatic (PNA) naphthalene and a solvent, such as methanol, at depth. The solubility of naphthalene in various solvents is as follows: 30 mg/L in water, 77 g/L in ethanol and methanol, 285 g/L in benzene and toluene, and 500 mg/L in chloroform and carbon tetrachloride. The presence of methanol and naphthalene at depth would, therefore, suggest the preferential transport of naphthalene to depth via cosolvation with methanol. Another example is the release of oxygenated fuels into soil containing PAHs. The theoretical sorption of a PAH coefficient decreases exponentially as the fraction of the organic solvent increases (Chen et al., 1977); therefore, the presence of an oxygenate such as MTBE in the fuel can enhance the transport of PAHs, as well as benzene, toluene, ethylbenzene, and xylene present in the soil due to cosolvency effects.

2.5.3 RESIDUAL SATURATION Residual saturation is defined as the fraction of total soil space filled with a liquid due to capillary forces. As hydrocarbons migrate through soil, a small amount of the total hydrocarbon mass remains attached to these soil particles via sorption. The hydrocarbon retained by the soil particles is known as residual or immobile saturation. The percentage of residual saturation remaining in a soil is dependent on soil moisture content, soil porosity, and soil texture. The residual saturation for light oil and gasoline is about 1% of the total soil porosity; for diesel and light fuel oil, 15%; and for lubricating and heavy fuel oil, about 2%. Residual saturation estimates are routinely used to estimate the volume of recoverable hydrocarbon in the soil. Residual saturation values are measured directly by collecting a representative soil sample and saturating it with the petroleum hydrocarbon of concern, followed by allowing the soil to drain for several days and then measuring the volume of hydrocarbon retained by the soil. The viscosity of a fuel affects its residual saturation. As the viscosity decreases, the residual saturation concentration decreases (Hoag and Marley, 1986). Theoretical studies suggest that the residual saturation increases proportionally to the fourth root of the product’s viscosity. Table 2.12 lists the residual saturation of petroleum products in soils (Dragun, 1988). Residual saturation is significant because it remains as a source of contamination via water infiltrating through the soil column coming

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into contact with the residual hydrocarbons. Seasonal changes in groundwater level can resolubilize residual hydrocarbons into the groundwater, a fact that is reflected in downgradient monitoring wells as a seasonal trend of high and low concentrations of BTEX concentrations coinciding with the fluctuating water table. Residual saturation contamination of soils by hydrocarbons can occur in soil downgradient of a spill that may be on an adjacent property. This situation occurs when free product on the water table comes into contact with otherwise clean soils above it due to a rising water table. When the groundwater drops, the previously clean soil contains a certain percentage of residual saturation. Previously uncontaminated soils now become a source for further contamination. This phenomenon is important to consider when examining soil gas survey data as indicators of the source of contamination, especially with shallow groundwater. Soils with residual hydrocarbon downgradient of the original spill may volatilize, resulting in the appearance of a release and/or masking of the original source of the contamination.

2.5.4 VAPOR PHASE TRANSPORT The volatile component of hydrocarbons (BTEX compounds) often partition into their gaseous state and are present in the subsurface along with the liquid phase hydrocarbons. The term “volatile hydrocarbons” refers to those compounds with vapor pressures greater than 1 mmHg or 0.001 atm. The transport of these gases is about 100 times faster in soils than in the groundwater and is described in Equation 2.4 by a general form of Darcy’s Law as: v = –k/m(—P + rg)

(Eq. 2.4)

where v = velocity of laminar air flow through the soil. k = intrinsic permeability. m = viscosity. P = pressure head difference. r = fluid density. g = acceleration due to gravity.

The transport of gas occurs due to several transport mechanisms, including diffusion, convection, and gravity-driven flow; the effective porosity of the soil and the contaminant’s vapor density are also important. Other factors include air temperature and, for near-surface soil, barometric pressure. In general, molecular diffusion is the dominant transport for the gas phase. The driving force of convective flow is the gradient of the total gas pressure which results in the movement of air mass from an area of higher pressure to an area of lower pressure. In the case of diffusion, the driving force is the partial pressure gradient of each gaseous component in a gas mixture. It is believed that in most cases diffusion is the dominant transport mechanism.

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TABLE 2.13 Vapor Densities of Gases Relative to Air Gases Lighter than Air

Gases Heavier than Air

Hydrogen Ammonia Acetylene Methane N-gas Ethylene Helium

Gasoline Chlorine Alcohol Acetone Ethylene dibromide Propane

Gravity-driven flow is the tendency of the vapor to move within the vadose zone as a function of density. The presence of relatively high concentrations of volatile compounds detected at the bottom of coarse-grained sediments is an example of this transport mechanism. The importance of effective porosity for liquids is identical to that for gas; open space in the soil must be available for the gas to migrate. In sandy soils, as much as 25% of the volume is air; in loamy soils, it is generally between 15 and 20%; and in clayey soils, the volume of air space is usually below 10% of the total volume. As vapor density increases, the potential for the gas to move vertically through the soil column increases. Vapors move through the soil as a function of the concentration gradient of the contaminant via diffusion as described by Fick’s Law. The movement is therefore away from areas of high concentration to areas of low concentration. Another mechanism is temperature; a temperature gradient in the soil creates a driving force with volatile compounds moving from areas of high to low soil temperature. Pressure fluctuations due to barometric pressure changes and wind across the soil surface can also impact the movement and dispersion of soil gas in shallow soils (Rolston, 1986). The vapor density of a substance is the mass of vapor per unit volume. Gases that are heavier and lighter than air are listed in Table 2.13. A related characteristic is vapor pressure, which is the pressure exerted by the gas of a substance in equilibrium conditions. Vapor pressure provides a qualitative rate at which a compound volatilizes from soil. Table 2.14 is a list of vapor densities and pressures for commonly encountered hydrocarbons (API, 1994; Luhrs and Stewart, 1992). Soil gas surveys using this property to locate sources of soil and groundwater contamination commonly report the results as parts per billion per volume (ppbv). A useful conversion is that 250 ppbv is equal to about 1 mg/L in the vapor phase. While organic contaminants are absorbed onto organic matter, research has shown that volatile organic compounds in a gas phase can also sorb onto dry soils. Mineral matter in dry soils, for example, can adsorb TCE from the vapor phase (Peterson et al., 1988). Research comparing the uptake of volatile compounds onto wet vs. dry soil shows that vapor uptake on dry soils is greater than for wet soils. These findings also indicate that vapor uptake is suppressed by the presence of water

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TABLE 2.14 Vapor Densities and Pressures for BTEX and MTBE Compound

Vapor Density (g/L)

Vapor Pressure (mmHg)

Temperature (∞C)

Benzene Toluene Ethylbenzene o-Xylene m-Xylene p-Xylene MTBE

3.19 3.77 4.34 4.34 4.34 4.34 —

76 22 12 6.6 8.3 8.8 245

20 20 30 25 25 25 25

(Chiou and Shoup, 1985; Ong and Lion, 1991a,b; Poe et al., 1988; Rhue et al., 1988). In general, soils with a high clay content and large surface area adsorb a greater amount of a chemical. Once volatilized, the vapor is transported through the soil by advection and diffusion. The vapor will move primarily in the horizontal direction, controlled by the slope of the water table and by geologic media (i.e., gas permeability of the media) and temperature gradients. Given that residual hydrocarbons can release volatiles for long periods of time depending on their initial molecular arrangement, soil temperature, moisture content, and biodegradation, a long-term soil vapor source is often present. Products of hydrocarbon degradation are used to identify the location of soil or groundwater contamination using concentrations of gases, such as carbon dioxide or methane, as indicators of microbial activity. Elevated concentrations of methane gas, for example, have been shown to demonstrate that hydrocarbons are reduced by a wide range of anaerobic processes that can produce vapor phase products (Barcelona et al., 1996).

2.6 HYDROCARBON INTERACTIONS AT THE CAPILLARY FRINGE Vertical migration ceases when a hydrocarbon encounters water-saturated pores (i.e., the capillary zone or perched layer), because most petroleum hydrocarbons and refined products are less dense than water. As the volume of floating product increases, saturation at the capillary fringe becomes sufficient for lateral spreading to occur. A mound above the water table will occur along with a corresponding depression in the water table. The amount of collapse depends on the hydrocarbon density. As the specific gravities of gasoline and light hydrocarbons are approximately 0.7 to 0.8,

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about 70 to 80% of the hydrocarbons will reside below the depth of the original water table. Spreading occurs along the groundwater surface as a result of the natural groundwater gradient. This hydrocarbon lens will spread laterally until equilibrium is achieved between the lens thickness and the capillary pressure. The balance of forces results in a thick layer in fine-grained sediments and a thinner layer in coarse sediments (Ryan and Dhir, 1993). The center of the hydrocarbon mass will move downgradient with respect to groundwater. The velocity of the floating product can be estimated via Equation 2.5 (ES&T, 1996; Parker and Leonard, 1990): nN = (fNrroKh/hrofe)—Zaw

(Eq. 2.5)

where nN fN rro Kh hro fe —Zaw

= = = = = = =

velocity of the leading edge of the gasoline on the water table. mobility factor defined as oil mobility divided by the free oil specific volume. specific gravity of the gasoline. horizontal saturated hydraulic conductivity to water. the gasoline-to-water viscosity ratio. effective or “drainable” soil porosity. the air/water table gradient (same as the water table gradient, which may underestimate the gasoline velocity if the travel distance is large and/or the product thickness is low).

A phenomenon known as thin film spreading occurs within the capillary fringe and groundwater interface. This hydrocarbon film will be one to two soil pore diameters thick. This layer spreads laterally along the interface of the capillary fringe and upper two pore volumes. The hydrocarbon will initially spread over a larger area than the bulk of the hydrocarbons in contact with the capillary fringe. Solubilization of hydrocarbon components from this thin film also occurs; compounds with low oil/ water partition coefficients will tend to diffuse outward and transfer into the aqueous phase, leaving the heavier weight hydrocarbons. The hydrocarbon residing in the capillary fringe will volatilize into the soil air (Gierke et al., 1990; Miller et al., 1990; Powers et al., 1991; Wilkins et al., 1995). Volatile components within the LNAPL will evaporate and diffuse upward, while the higher molecular weight compounds will remain in the LNAPL pool. The rate of vapor loss from a LNAPL pool residing at the capillary fringe is described by Fick’s Law of diffusion (see Section 2.5.4) or can be measured directly. For the latter case, a soil gas survey above the LNAPL can be used to extrapolate the initial slope of the concentration vs. height to zero concentration to estimate the effective diffusion length. When direct measurements are unavailable, the one-dimensional conservative mass transfer (kaa) due to diffusion described by Fick’s Law is described by Equation 2.6.

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kaa = Daaof4/3S10/3 a Ha/La

(Eq. 2.6)

where Daao = diffusion coefficient in free air for species a. f4/3 = soil porosity. = the fraction of pore volume with air (90% or less for coarse-sand soils to 10% S10/3 a or greater for fine-textured soils). Ha = Henry’s Law constant. = effective diffusion coefficient. La

Upon entering the capillary fringe, sufficient hydraulic pressure can exist to cause the hydrocarbon to move hydraulically upgradient. This upgradient distance is minimal, however, when compared to the downgradient distance. As the hydrocarbon lens moves laterally, water in the capillary fringe impedes its movement. In the upper section of the capillary fringe where small amounts of water are present, the hydrocarbons tend to migrate laterally. In the lower section of the capillary fringe where relatively large amounts of water are present, the bulk hydrocarbons will also migrate laterally but at negligible rates as compared to hydrocarbons in the upper portions of the capillary fringe.

2.6.1 HYDROCARBON SOLUBILIZATION FROM THE CAPILLARY FRINGE INTO GROUNDWATER The solubilization of compounds from a free phase product residing at the capillary fringe into groundwater results in dissolved components that are compositionally different than the non-aqueous phase hydrocarbon. For non-oxygenated gasoline, the most soluble components are benzene, toluene, xylene, and ethylbenzene. Benzene concentrations in groundwater, for example, are enriched up to ten times more than their concentration in gasoline. While some unleaded gasoline contains 49% of the aromatic compounds, water in contact with this gasoline has been found to contain 95% of these compounds after 30 minutes of mixing (Coleman et al., 1984). For crude oils, solubility is partially dependent on the API gravity of the crude oil. Crude oil with a high API is light (less dense than water), while a low API crude is heavy. The solubility of the crude oil in contact with groundwater increases with higher API gravities because high-API crude oils tend to be rich in low-molecular-weight compounds with high solubilities. Numerous expressions are available to estimate the rate of dissolution of compounds into the groundwater and they may be represented as from water washing through the free phase hydrocarbon and into the groundwater and via solubilization by groundwater in contact with the NAPL. An example of the latter approach is described in Equation 2.7 (Pfannkuch, 1984): Ssa = kov(Csa – Cma)

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(Eq. 2.7)

where ko

= a dimensionless NAPL mass transfer coefficient defined as ko = Av/L, where Av is the vertical dispersivity of the aquifer and L is the effective aquifer thickness. v = groundwater velocity. Csa = the dissolved concentration in equilibrium with the NAPL in the groundwater. Cma = actual concentration in the groundwater in the mobile region.

Equation 2.7 requires that the initial mass fraction of the various compounds of interest be known or approximated. A useful application of this information is to estimate the concentration of the BTEX components under the NAPL as additional data points for creating an iso-contour map for dissolved contaminants. It is not uncommon for groundwater under a gasoline or diesel layer not to be sampled and tested.

2.7 TRANSPORT IN GROUNDWATER Petroleum hydrocarbons entering groundwater are transported as free and dissolved phases. The free phase components are normally thickest at the point at which the hydrocarbon enters the groundwater. The rate of dissolution from the free phase can be estimated from estimating the partition coefficient from solubility data and from information on the chemical concentration of the compound. Most hydrocarbon fractions are immiscible with water. Some components in hydrocarbons, however, are soluble (i.e., benzene, toluene, ethylbenzene, and total xylenes) as well as additives such as MTBE. This property provides a useful means for characterizing hydrocarbons and understanding whether BTEX concentrations represent near-saturation conditions. Once the soluble fraction of the hydrocarbon has entered the groundwater, its movement is controlled by the same advective and dispersive processes used for estimating the mass transport of groundwater.

2.7.1 RATE OF TRANSPORT Advection describes the mass movement of a chemical in groundwater and is the dominant mechanism by which chemicals move in groundwater. The primary input variable affecting advective transport is hydraulic conductivity. The use of hydraulic conductivity in one form of Darcy’s Law is described by Equation 2.8: v = [K (h1 – h1)/l]/ne where v K (h1 – h1)/l] ne

= = = =

groundwater velocity (units of length over time). hydraulic conductivity (gal/day/ft2, m or cm/sec). groundwater gradient (dimensionless). effective porosity (percentage).

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(Eq. 2.8)

TABLE 2.15 Saturated Hydraulic Conductivity Values for Soils Soil Texture Gravel Sand Silty sand Silt Glacial till Clay

Hydraulic Conductivity (cm/sec) 102–10–1 1–10–4 –1 10 –10–5 10–3–10–7 10–4–10–12 10–7–10–11

Hydraulic conductivity is a function of the porous medium through which the fluid is moving and of the fluid. Table 2.15 lists ranges of hydraulic conductivity for several soils (Driscoll, 1986; Freeze and Cherry, 1979). The horizontal stratification of sediments results in hydraulic conductivity values that are usually greater horizontally than vertically. In sediments such as till, preferential flow of contaminants occurs within small lenses of materials that are more permeable than the majority of sediments in the aquifer. Since Darcy’s Law is an averaged value for transport, contaminants can be transported at greater rates within these preferential layers than what is estimated with Darcy’s Law. While Darcy’s Law applies to the averaged linear velocity of groundwater, it is not contaminant specific. To examine the transport of an individual chemical, retardation must be considered. In an ideal case, soluble components with higher velocities precede components with decreased velocities at the leading edge of a contaminant plume. The apparent velocity of BTEX components is affected by the retardation of the specific compound within the aquifer. For example, the retardation of benzene within a sand and gravel aquifer at a site in Glouchester, Ontario, was 8.8; this means that if groundwater flow is 8 feet per day and the benzene retardation coefficient is 8.8, then the rate of benzene transport is about 0.9 feet per day (MacKay, 1990).

2.7.2 MTBE TRANSPORT IN GROUNDWATER Methyl-tertiary-butyl-ether (MTBE) is an oxygenate added to gasoline to increase both the octane ratio of gasoline and combustion efficiency. MTBE lowers the atmospheric ozone and carbon monoxide concentrations as required by the Clean Air Act. In 1992, the U.S. Environmental Protection Agency (EPA) mandated that oxygenated compounds such as MTBE containing at least 2.7% oxygen by weight should be added to gasoline. This additive has gained considerable attention in recent years due to its being a primary contaminant of concern with gasoline releases. Analytical methods used to test for MTBE are EPA Methods 8020 and 8240/8260.

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For drinking waters, EPA Method 524 is used. Another method is a modified ASTM Method D4815, which tests samples for methanol, ethanol, ethyl-tertiary-butyl-ether (ETBE), and tertiary-methyl-ether (TAME), as well as MTBE. The separation of MTBE ((CH3)3C(OCH3)) from the gasoline plume is often detected along the downgradient edge, followed in time by detection of the BTEX components (Squillace et al.,1996). MTBE can comprise as much as 11% by volume of gasoline and is more soluble than benzene; as a result, it tends to be more mobile than the other soluble gasoline components. A breakdown product of MTBE, tertbutanol (TBA; tert-butyl alcohol or 2-methyl-2-propanol), is possible, although additional confirmation research is required (Barker et al., 1996). Tert-butyl alcohol is a significant degradation product, as it has been identified as a carcinogen in laboratory animals (Cirvello et al., 1995). One field study measured a 14% loss of MTBE after 476 days of monitoring, while another investigation reported aerobic biodegradation of MTBE based on MTBE losses and oxygen consumption (Horan and Brown, 1995). In general, MTBE does not readily degrade in the subsurface, and the primary attenuation mechanism is dispersion. MTBE can decrease the retardation of the BTEX components, as they are more soluble in ether than in water. As a result, when MTBE is present in a contaminant plume, the BTEX components are often found in higher concentrations (Garrett et al., 1986). The physical and chemical characteristics of MTBE are significantly different than other compounds found in gasoline. MTBE has a low affinity for organic carbon; as a result, retardation due to the presence of soil organic matter is minimal. Testing of the retardation of MTBE in the Borden aquifer in Canada resulted in a retardation factor of 1.0. The solubility of MTBE (43,000 mg/L) is about 25 times greater than for benzene (1780 mg/L). The biodegradability of MTBE relative to aromatic compounds (BTEX) is substantially lower. MTBE will also preferentially leach from gasoline because it has a high affinity for water, which is why MTBE is found at the leading edge of a gasoline plume, followed by benzene (assuming a single spill and chromatographic separation of the components in the groundwater). The ratio of the MTBE plume in groundwater relative to benzene depends on the concentrations used to define the leading edge of the gasoline plume and the contaminant residency (Rempel and Escalante, 1996). A review of 32 sites found the MTBE to benzene plume-length relationship to be 1.5 to 2.0 after a few years of contaminant residency (Davidson, 1995). Another factor in MTBE dissolution from gasoline is due to the natural attenuation of the BTEX components relative to MTBE. In groundwater, research has found that toluene had the highest attenuation rate, followed by xylene, benzene, and ethylbenzene. While attenuation rates for xylene, benzene, and ethylbenzene are not significant, toluene is significantly greater (Borden et al., 1995; Buscheck et al., 1996). The vertical distribution of MTBE in a gasoline plume usually results in the MTBE being present at a greater depth than the gasoline. The longer distance of the MTBE plume relative to the gasoline plume allows the MTBE to be distributed vertically over a greater distance. The longer MTBE plume can also be driven deeper into the aquifer due to infiltration events.

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The shape of a MTBE hydrocarbon plume also depends on whether the release originates from a point or line source and if it is transient vs. steady state. For underground storage tanks, it is estimated that 65% of all releases originate from the product lines, 25% are from the tanks, and the remaining sources are from causes such as overfilling or spillage. Releases from each of these types of sources will therefore result in a different type of plume geometry in the subsurface. A line source creates a large area into which the hydrocarbons are entering the groundwater, while a point source release creates more of a tear-shaped plume with the apex of the tear at the point source. The temporal nature of the release will also impact the geometry of the contaminant plume. A transient release creates a “pulse” or discrete mass of contaminant that flows advectively with the groundwater; a steady-state release tends to create a more continuous plume. Dispersivity also affects the geometry of an MTBE plume. Dispersivity is the three-dimensional spreading of a contaminant plume in groundwater; it is primarily dependent on the aquifer characteristics and the geometry of the contaminant source area. Dispersivity values are obtained by fitting mathematical models to plume data or from measured values obtained from dye tracer tests performed in the field. Values for dispersivity increase with distance from the source, although a relatively stable value (macro-dispersivity) should be obtained at some distance from the source. Dispersivity values are used in a longitudinal, transverse, and vertical direction relative to the center of mass of a contaminant plume. In general, the horizontal dispersivity is about ten times greater than the vertical transverse dispersivity (Davis, 1986). (See Chapter 1, Section 1.8.5, for further details.)

2.7.3 LENGTH OF A PETROLEUM HYDROCARBON PLUME Recent examination of hydrocarbon plumes has resulted in the finding that plumes rarely exceed 260 feet in length (Rice et al., 1995). These observations, in turn, provide evidence for consideration and/or adoption of natural attenuation strategies (see ASTM Standard Guide for Remediation by Natural Attenuation at Petroleum Release Sites, ASTM, 1996). Lawrence Livermore National Laboratory conducted a study of hydrocarbon plumes in groundwater for the California State Water Resources Control Board to support revision of the Leaking Underground Fuel Tank corrective action process; hydrocarbon plume lengths in groundwater were summarized in this study. These results are similar to the findings of a study by Chevron of 119 sites in California. The results of both studies are summarized in Table 2.16 (Buschek et al., 1996; Rice et al., 1996). These studies also classified hydrocarbon plumes in terms of the change in plume geometry for benzene. The plumes were described as “shrinking”, “no significant trend”, and “increasing”. Table 2.17 lists the result of this classification in percentage of the total sites (Buschek et al., 1996). A recent examination of the Lawrence Livermore data indicated that benzene plume lengths defined by the 1-ppm concentration contour were less than 200 ft for 90% of the 1092 sites and less than 75 ft for 70% of the leaking underground storage tanks sites (McNab and Dooher, 1999).

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TABLE 2.16 Length of Hydrocarbon Plumes in Groundwater Plume Length (L)

Lawrence Livermore (% of 271 sites)

Chevron (% of 62 sites)

50 40 10

47 40 13

L < 100 ft 100 ft < L < 260 ft L > 260 ft

Analytical solutions for groundwater transport and attenuation of hydrocarbons used to estimate the length of hydrocarbon plumes are similar in the Lawrence Livermore and Chevron findings (Domenico, 1987). Similarities between modeled and observed plume lengths include the finding that BTEX plumes may be relatively short (< 300 ft). Longer plumes might be expected when groundwater velocity is high (> 0.1 ft/day) and when attenuation rates are relatively low. Modeling results of hydrocarbon plumes also suggest that BTEX plumes may reach stable or steady-state conditions within 3 to 7 years (McCallister, 1996). These correlations suggest that, in cases where monitoring data are available to verify plume attenuation rates and groundwater velocities are known, groundwater modeling may be used to estimate plume lengths reliably. This information can assist in identifying optimum locations for additional monitoring wells.

2.7.4 TRANSPORT IN FRACTURES Fractures such as joints, faults, or bedding plane separations can occur in a variety of geologic media. The release of hydrocarbons into a fracture system is significant in that the velocities can be greater than for an unconsolidated media, and the distribution of the hydrocarbons within the fracture system becomes difficult to define.

TABLE 2.17 Changes in Hydrocarbon Plume Geometry Change in Plume Geometry

Lawrence Livermore (% of 271 sites)

Chevron (% of 62 sites)

59 33 8

51 40 9a

Shrinking No significant trend Increasing a

Insufficient data for 10 or 11 sites.

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The flow of hydrocarbons that have entered a fracture network is controlled by a number of factors, including the fracture aperture (i.e., the distance between the fracture walls), fracture density (i.e., spacing between the fractures), and fracture length and orientation. While fracture spacing, length, and orientation control the degree of interconnection of the fracture network and can be mapped, fracture aperture is usually not measurable in the field. The inability to measure fracture apertures is primarily due to their size (10 to 100 mm) and the interferences caused from drilling or excavation stress relief. As a result, aperture values are usually estimated using the “cubic law” (Snow, 1969), which is based on the relationship between hydraulic gradient and the discharge for a viscous fluid flowing between two parallel smooth surfaces. In reality, apertures can vary greatly in size and wall roughness, but these are not easily measured. The transport of a dissolved phase hydrocarbon in a fractured porous medium occurs by advection through the fractures, advection into the fracture wall matrix, and diffusion into the fracture walls (assuming that the material is porous). In most cases, advection into the wall is negligible; diffusion controls solute transport from rapidly moving liquid through the fractures into the relatively immobile pore water of the wall matrix. The process of matrix diffusion can theoretically retard the overall migration of a hydrocarbon by several orders of magnitude relative to transport within the fracture system. For example, modeling simulations showed that in a scenario which included matrix diffusion, chloride migrating through a 25-mm aperture fracture in a glacial clay would take about 50 years to reach the underlying aquifer present at a depth of 10 m (Sudicky and McLaren, 1992). For the same modeling scenario but with no matrix diffusion, the solute would reach the aquifer within about half a day. For non-aqueous phase liquids (NAPLs) moving vertically through a fracture system, the transport will be rapid after the release; diffusion will have little impact, as the aperture size and hydrocarbon properties (density, interfacial tension, and viscosity) will impact the rate of flow (Kueper and McWhorter, 1991). Once the hydrocarbon becomes immobilized within the fracture system, diffusion into the porous matrix will occur. The diffusion of the hydrocarbon into the porous matrix significantly complicates the remediation of the hydrocarbons present within the porous media.

REFERENCES API, 1995. Petroleum Contaminated Low Permeability Soil: Hydrocarbon Distribution Processes, Exposure Pathways and In Situ Remediation Technologies, API No. 4361, American Petroleum Institute, Washington, D.C., pp. A1–A34. API, 1994. Transport and Fate of Non-BTEX Petroleum, API No. 4593, American Petroleum Institute, Washington, D.C., p. 85. API, 1989. A Guide to the Assessment and Remediation of Underground Petroleum Releases, 2nd ed., API No. 1628, American Petroleum Institute, Washington, D.C., p. 81.

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API, 1985. Literature Survey: Hydrocarbon Solubilities and Attenuation Mechanisms, API No. 4414, American Petroleum Institute, Washington, D.C., p. 101. ASTM, 1996. Standard Guide for Remediation by Natural Attenuation at Petroleum Release Sites (draft), American Society for Testing Materials, Philadelphia, PA, p. 16. ATSDR, 1995. Toxicological Profile for Stoddard Solvent, Agency for Toxic Substances and Disease Registry, Public Health Service, U.S. Department of Health and Human Services, Atlanta, GA, p. 3. Barcelona, M. and R. Morrison, 1988. Sample collection, handling and storage: water, soils, and aquifer solids, in Proc. of Groundwater Quality Methodology Workshop, November 13, Cooperative States Research Service, Arlington, VA, p. 13. Barcelona, M., Fang, J., and C. West, 1996. Monitoring in situ bioremediation of fuel hydrocarbons: the use of chemical and biochemical markers, in 1996 Proc. of the Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Remediation Conference, November 13–15, National Ground Water Association, Houston, TX, pp. 511–523. Barker, J., Schirmer, M., and C. Hubbard, 1996. The longer term fate of MTBE in the Borden aquifer, in Proc. of the 1996 Petroleum Hydrocarbons and Organic Chemicals in Groundwater: Prevention, Detection, and Remediation Conference, November 13–15, National Ground Water Association, Houston, TX, pp. 5–14. Borden, R., Gomez, A., and M. Becker, 1995. Geochemical indicators of intrinsic bioremediation, Ground Water, 33(2):180–189. Bruya, J., 1999. Chromatograms, Friedman and Bruya, Seattle, WA. Buschek, T., Wickland, D., and D. Kuehne, 1996. Multiple lines of evidence to demonstrate natural attenuation of petroleum hydrocarbons, in Proc. of the 1996 Petroleum Hydrocarbons and Organic Chemicals in Groundwater: Prevention, Detection, and Remediation Conference, November 13–15, National Ground Water Association, Houston, TX, pp. 445–459. California Environmental Protection Agency, 1996. Draft Policy for Cleanup of Petroleum Discharge: October 29 letter from Harry Schueller to Regional Water Quality Control Board Executive Officers, State Water Resources Control Board Resolution No. 1021b, p. 4. Chen, C., Rao, S., and J. Delfino, 1977. Cosolvent Effects on the Dissolution of Polynuclear Aromatic Hydrocarbons Due to Spills of Oxygenated Fuel in the Subsurface Environment, presented at the 213th Annual Meeting of the American Chemical Society, Division of Environmental Chemistry, April 13–17, San Francisco, CA, Preprints of Extended Abstracts, 37(1):387–389. Chiou, C., 1989. Theoretical considerations of the partition uptake of nonionic organic compounds by soil organic matter, in Sawhney, B.L. and K. Brown, (Eds.), Reactions and Movement of Organic Chemicals in Soils, Soil Science Society of America, Madison, WI, pp. 1–19. Chiou, C. and T. Shoup, 1985. Soil sorption of organic vapors and effects of humidity on sorptive mechanism and capacity, Environmental Science and Technology, 19:1196–1200. Cirvellol, J., Radovsky, A., Heath, J., Farnell, D., and C. Lindamood, 1995. Toxicity and carcinogenicity of t-butyl alcohol in rats and mice following chronic exposure in drinking water, Toxicology and Industrial Health, 11(2):151–166. Coleman, W., Munch, J., Stricher, R., Ringhand, H., and F. Kopfler, 1984. The identification and measurement of components in gasoline, kerosene, and No. 2 fuel oil that partition into the aqueous phase after mixing, Archives of Environmental Contamination and Toxicology, 13:171–178.

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Corey, A., 1986. Air permeability, in Klute, A. (Ed.), Methods of Soil Analysis. Part I. Physical and Mineralogical Methods, 2nd ed., American Society of Agronomy, Madison, WI, pp. 1121–1136. Daniel, D., Anderson, D., and S. Boynton, 1986. Fixed wall versus flexible wall permeaters, in Hydraulic Barriers in Soils and Rocks, ASTM STP 874, American Society for Testing Materials, Philadelphia, PA, pp. 107–126. Danielson, R., and P. Sutherland, 1986. Porosity, in Klute, A. (Ed.), Methods of Soil Analysis. Part I. Physical and Mineralogical Methods, 2nd ed., American Society of Agronomy, Madison, WI, p. 443–461. Davidson, J., 1995. Fate and transport of MTBE: the latest data, in 1995 Proc. of the Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Remediation Conference, National Ground Water Association, Dublin, OH, pp. 285–301. Davis, A., 1986. Deterministic modeling of dispersion in heterogeneous permeable media, Ground Water, 24(5):609–615. Domenico, P., 1987. An analytical model for multidimensional transport of a decaying contaminant species, Journal of Hydrology, 91:49–58. Dragun, J., 1988. The Soil Chemistry of Hazardous Materials, Hazardous Materials Control Research Institute, Silver Springs, MD, p. 458. Driscoll, F., 1986. Groundwater and Wells, Johnson Division, St. Paul, MN, p. 1089. Dunlap, L. and D. Beckmann, 1988. Soluble hydrocarbon analysis from kerosene/diesel type hydrocarbons, in Proc. of the Association of Ground Water Scientists and Engineers and the American Petroleum Institute (API) Conference on Petroleum Hydrocarbons and Organic Chemicals in Ground Water, National Ground Water Association, Houston, TX, pp. 37–45. ES&T, 1996. ARMOS User Guide: A Real Multiphase Organic Simulator for Free Phase Hydrocarbons Migration and Recovery, Environmental Systems & Technologies, 2608 Sheffield Drive, Blacksburg, VA. Feenstra, S., Cherry, J., and B. Parker, 1996. Conceptual models for the behavior of dense nonaqueous phase liquids (DNAPLs) in the subsurface, in Pankow, J. and J. Cherry (Eds.), Dense Chlorinated Solvents and other DNAPLs in Groundwater, Waterloo Press, Guelph, Ontario, pp. 53–128. Freeze, A., and J. Cherry, 1979. Groundwater, Prentice-Hall, Englewood Cliffs, NJ, p. 604. Freyberg, D., 1986. A natural gradient experiment on solute transport in a sand aquifer. 1. Spatial moments and the advection and dispersion of nonreactive tracers, Water Resources Research, 22(13):2031–2046. Galperin, Y., 1997. Application of Forensic Geochemical Methods for Hydrocarbon Fuels Fingerprinting and Age Dating. Section 2. Hydrocarbon Pattern Recognition and Dating, University of Wisconsin College of Engineering, Madison, WI, p. 41. Garrett, P., Moreau, M., and J. Lowry, 1986. Methyl tertiary butyl ether as a ground water contaminant, in Proc. of the Petroleum Hydrocarbons and Organic Chemicals in Ground Water Conference, National Water Well Association and American Petroleum Institute, Washington, D.C., pp. 227–238. Gibbs, L., 1990. Gasoline Additives: When and Why?, Technical Paper 902104, Society of Automotive Engineers, Warrendale, PA, p. 24. Gierke, J., Hutzler, N., and J. Crittenden. 1990. Modeling the movement of volatile organic chemicals in unsaturated soils, Water Resources Research, 26(7):1529–1547. Hartman, B., 1998. Applications and interpretations of soil vapor data, in Petroleum Hydrocarbons: Legal and Technical Considerations, Argent Communications Group, Foresthill, CA, p. 81–110.

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Manahan, S., 1984. Environmental Chemistry, 4th ed., PWS Publishers, Boston, MA, p. 612 McAllister, P., 1996. Application of screening model approaches for evaluation of BTEX natural attenuation in groundwater, in 1996 Proc. of the Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Remediation Conference, National Ground Water Association, Dublin, OH, pp. 481–494. McNab, W. and B. Dooher, 1999. Discussion of papers, Ground Water, 37(2):167–168. Metcalf and Eddy, Inc., 1993. Chemical and Physical Characteristics of Crude Oil, Gasoline, and Diesel Fuel: A Comparative Study, Western States Petroleum Association, Glendale, CA, p. 33. Miller, C., Poirier-McNeil, M., and A. Mayer, 1990. Dissolution of trapped non-aqueous phase liquids; mass transfer characteristics, Water Resources Research, 26(11):2783–2796. Morrison, R., 1997. Forensic techniques for establishing the origin and timing of a contaminant release, Environmental Claims Journal, 9(2):105–122. Neilsen, J. and S. Hansen, 1992. Fate and Transport of Creosote Compounds in a Sand Aquifer at CFB Borden, Ontario, Canada, Master’s thesis, Technical University of Denmark, Lyngby. Neuman, S. and G. Chen, 1996. On instability during immiscible displacement in fractures and porous media, Water Resources Research, 32(6):1891–1894. Neumann, H., Paczynska-Lahme, B., and D. Severin, 1981. Composition and Properties of Petroleum, Halstead Press, New York, p. 561. Nkedi-Kizza, P., Rao, S., and A. Hornsby, 1987. Influence of organic cosolvents on leaching of hydrophobic organic chemicals in soils, Environmental Science and Technology, 21:1107–1111. Odencrantz., J., Farr., J., and C. Robinson, 1992. Transport model parameter sensitivity for soil clean-up level determinations using SESOIL and AT123D in the context of the California leaking underground fuel tank field manual, Journal of Soil Contamination, 1(2):159– 182. Ong., S. and L. Lion, 1991a. Mechanisms for trichloroethylene vapor sorption onto soil minerals, Journal of Environmental Quality, 20:180–188. Ong., S. and L. Lion, 1991b. Trichloroethylene vapor sorption onto soil minerals, Soil Science Society of America Journal, 55:1559–1568. Parker, J. and R. Lenhard, 1990. Vertical integration of three phase flow equations for analysis of light hydrocarbon plume movement, Transport in Porous Media, 23:2187–2196. Perry, R. and C. Chilton, 1973. Chemical Engineers’ Handbook, 3rd ed., McGraw-Hill, New York. Peterson, J. et al., 1988. Influence of vapor phase sorption and diffusion on the fate of trichloroethylene in an unsaturated aquifer system, Environmental Science and Technology, 22:571–578. Pfannukuch, H., 1984. Determination of the contaminant source strength from mass exchange processes at the petroleum/ground water interface in shallow aquifer aquifers, in Proc. of the NWWA/API Conference on Petroleum Hydrocarbons and Organic Chemicals in Ground Water Prevention, Detection, and Restoration, Session II, November 5–7, National Water Well Association, Dublin, OH, p. 111–130. Philip, P., 1988. Forensic geochemistry: who was responsible for the spill?, in Proc. of Environmental Forensics: Determining Liability through Applied Science Conference, September 24–25, International Business Communications (IBC), Southborough, MA. Poe, S., Valasaraj, K., Thibodeaux, L., and C. Springer, 1988. Equilibrium vapor phase adsorption of volatile organic chemicals on dry soils, Journal of Hazardous Matter, 19:17–32.

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Polak, J. and B. Lu, 1973. Mutual solubilities of hydrocarbon and water at 0 and 25∞C, Canadian Journal of Chemistry, 51:4018–4023. Powers, S., Loureiro, C., Abriola, L., and W. Weber, 1991. Theoretical study of the significance of nonequilibrium dissolution of nonaqueous phase liquids in subsurface systems, Water Resources Research, 27(5):363–377. Raymond, R., Hudson, J., and V. Jaminson, 1976. Oil degradation in soil, Applied and Environmental Microbiology, 31(4):522–535. Rempel, R. and F. Escalante, 1996. Comparison of Dissolved MTBE vs. Benzene Plumes at Seven Unocal Sites in California, abstract from Association for the Environmental Health of Soils Annual Conference, October 1996, University of Massachusetts, Amherst. Rhue, R., Rao, P., and R. Smith, 1988. Vapor phase adsorption of alkylbenzenes and water on soils and clays, Chemosphere, 17:727–741. Rice, D., Grose, R., Michaelson, J., Dooher, B., MacQueen, D., Cullen, S., Kastenberg, W., Everett, K., and M. Marino, 1995. California Leaking Underground Fuel Tank (LUFT) Historical Case Analysis, UCRL-AR-122207, Environmental Protection Department, Lawrence Livermore National Laboratory, Berkeley, CA; submitted to the California State Water Resources Control Board. Rohrbach, G. et al., 1953. Corrosion inhibitors for oil wells, U.S. Patents 2,635,996–2,636,000, April 21. Rolston, D., 1986. Gas flux, in Klute, A. (Ed.), Methods of Soil Analysis. Part I. Physical and Mineralogical Methods, 2nd ed., American Society of Agronomy, Madison, WI, pp. 1103–119. Rossi, S. and W. Thomas, 1981. Solubility behavior of three aromatic hydrocarbons in distilled water and natural seawater, Environmental Science and Technology, 15:715–716. Ryan, R. and V. Dhir, 1993. The effect of soil-particle size on hydrocarbon entrapment near a dynamic water table, Journal of Soil Contamination, 2(1):59–92. Salhotra, A., Mineart, P., Hansen, S., and T. Allison, 1993. Multimed, the Multimedia Exposure Assessment Model for Evaluating the Land Disposal of Wastes: Model Theory, EPA 600/R-93/081, U.S. Environmental Protection Agency, Washington, D.C., p. 122. Schmidt, G., 1998. The effect of petroleum weathering on pattern recognition and dating, in Proc. of Environmental Forensics: Determining Liability through Applied Science Conference, September 24–25, International Business Communications (IBC), Southborough, MA, p. 11. Seifert, W. and J. Moldowan, 1978. Application of steranes, triterpanes and monoaromatics to the maturation, migration and source of crude oils, Geochimica et Cosmochimica Acta, 42:77–95. Sellers, K. and C. Fan, 1991. Soil vapor extraction: air permeability testing and estimation methods, in Proc. of the 17th RREL Hazardous Waste Research Symposium, EPA/600/ 991/002, U.S. Environmental Agency, Washington, D.C. Siegrist, R., 1993. VOC measurement in soils: the nature and validity of the process, in National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art Research Needs, American Petroleum Institute and the University of Wisconsin at Madison Extension Engineering Program, January 12–14, U.S. Environmental Protection Agency, Washington, D.C., p. 9. Snow, D., 1969. Anisotropic permeability of fractured media, Water Resources Research, 29:716–728. Squillace, P., Zogorski, J., Wilber, W., and C. Price, 1996. Preliminary assessment of the occurrences and possible sources of MTBE in groundwater in the United States, 1993– 1994, Environmental Science and Technology, 30:1721–1730.

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Stout, S. et al., 1999. Biomarkers — underutilized components in the forensic toolkit, Soil and Groundwater Cleanup, June/July, 58–59. Sudicky, E. and R. McLaren, 1992. The Laplace transform Galerkin techniques for large scale simulation of mass transport in discretely fractured porous formations, Water Resources Research, 28(2):499–514. Tanner, C. and R. Wengel, 1957. An air permeameter for field and laboratory use, Soil Science Society of America Proceedings, 21(6):663–664. U.S. Environmental Protection Agency, 1986. Hazardous waste management system: land disposal restrictions, Federal Register, 15(9):1649. U.S. Geological Survey, 1979. Ground-water hydraulics, Geological Survey Professional Paper, 708:70. Wellman, D., Reid, D., and A. Ulery, 1999. Elevated soil arsenic levels at a former crude oil storage facility: assessment, remediation, and possible sources, Journal of Soil Contamination, 8(3), 329–341. Wilkins, M., Abriola, L., and K. Pennell, 1995. An experimental investigation of rate-limited nonaqueous phase liquid volatilization in unsaturated porous media: steady state mass transfer, Water Resources Research, 31(9):2159–2172. Wilson, J., Pfeffer, F., Weaver, J., Kampbell, D., Wiedemeier, T., Hansen, J., and R. Miller, 1994. Intrinsic bioremediation of JP-4 jet fuel, in Symposium on Natural Attenuation of Ground Water, EPA/600R-94/162, U.S. Environmental Protection Agency, Washington, D.C., pp. 60–67. Wilson, J., Enfield, T., Dunlop, W., Cosby, R., Foster, D., and L. Baskin, 1981. Transport and fate of selected organic pollutants in a sandy soil, Journal of Environmental Quality, 10:501–506. Zemo, D. and T. Graf, 1993. The importance and benefit of fingerprint characterization in site investigation and remediation focusing on petroleum hydrocarbons, in 1993 Proc. of the Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Restoration, November 10–12, National Ground Water Association, Dublin, OH, p. 39–54.

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3

Identification of Biased Environmental Data

Coincidence, error, studied ignorance, or junk science?

3.1 INTRODUCTION An expert opinion is worth no more than the factual data upon which it is based. The critical review of environmental data is therefore essential for judging the reliability of the factual information. Environmental data relied upon to form an opinion should be of a sufficient known quality to withstand the scientific and legal challenges relative to the purpose of the data collection. In most instances, only a small percentage (about 10 to 15%) of the data in an environmental investigation contains elements susceptible to bias. These elements are usually associated with the geologic investigation and sample collection, analytical testing, and interpretation of the horizontal and vertical extent of soil and groundwater contamination. An important task in the forensic review of environmental data is the determination of whether a pattern of bias (systematic error) exists. This bias can be due to factually incorrect information, errors, or intentional manipulation. Figure 3.1 illustrates bias and data variability (random error) based on a sample population whose true concentration is about 20 parts per million (ppm). As depicted in Figure 3.1, data can be biased negatively or positively. Three specific types of biases and/or errors are defined as follows: 1. Positive bias: In a data sufficiency context, a positive bias arises when a test incorrectly indicates contamination or an increase in contamination when there is none. 2. Negative bias: In a data sufficiency context, a negative bias occurs when monitoring fails to detect contamination or an increase in the concentration of a hazardous material. 3. Erratic data: Erratic data are anomalous values which make it statistically impossible to develop meaningful trends and/or correlations.

These biases result from investigative, sampling, analytical, and statistical errors. Ultimately, expert witness opinions based on incorrect information can result.

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FIGURE 3.1 Graphical representation of sample bias and variability. (From Mishalanie, E., in Proc. of the National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, August 27–28, College of Engineering and Engineering Professional Development, University of Wisconsin, Madison, 1998, p. 27. With permission.)

3.2

GEOLOGIC CHARACTERIZATION

The geologic characterization component of a site investigation provides insight regarding contaminant distribution and transport. Components of a geologic investigation usually include: • Drilling and logging of the boreholes and/or trenches • Soil retrieval for textural classification and/or physical testing • Soil sampling for chemical analysis

The first step is to acquire and review the original field borings and/or trench logs. Compare the information on the field logs and final logs in the report for consistency. If geologic cross-sections or fence diagrams are included in the report, examine them for consistency with the field log/trench descriptions. When reviewing boring logs, examine their placement relative to historical information, especially areas of known or suspected contamination. This review often provides insight as to whether additional borings and/or sampling are necessary. Given that site access agreements among multiple parties are usually required in order to perform additional sampling, the sooner the data sufficiency of the

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TABLE 3.1 Soil Classification Schemes Particle Size Classification

Classification Scheme Used

Very fine sand to silt Very fine sand to coarse silt Fine sand Fine sand to fines (silt and clay) Fine sand to fines (silt and clay) Fine sand to silt

U.S. Department of Agriculture Canada Soil Survey Committee International Soil Science Society American Society of Testing Materials German Standards British Standards Institute

geologic information is identified, the sooner the site access agreements and sampling can proceed. The sufficiency of existing geologic information can be determined via the following steps: • Ascertain whether the drilling method employed allows an accurate description of the subsurface. • Determine whether the number of soil borings are sufficient to characterize the geologic environment relative to litigation allegations. • Decide whether the borings are sufficiently deep to characterize the geology of interest. • Decide whether the borings are spatially located so as not to preclude developing useful information for geologic characterization.

The drilling technology impacts the geologist’s ability to describe the soil and/or geologic setting. Reliance solely on mixed drill cuttings from air or mud rotary drilling, for example, precludes the ability to provide detailed descriptions of stratigraphic changes. Continuous hollow stem augering and/or most push technologies that retrieve an in situ soil sample provide this level of detail.

3.2.1 BORING LOG TERMINOLOGY Soil descriptions on a boring log are based on visual observations of drill cuttings or from physical testing (e.g., sieve analysis and hydrometer tests). The review of soil textural descriptions requires that a uniform soil classification scheme be used or that different classifications are standardized (ASTM, 1993). The use of multiple soil classification schemes is not uncommon where numerous environmental consultants have performed geologic investigations at the site. An illustration of the importance of a common classification scheme is a soil described as a silt based on the results of a grain size analysis. The particle size of the soil lies between 0.1 and 0.02 mm. Based on these grain size results, multiple particle size classifications are possible, as shown in Table 3.1 (Gee et al., 1986; Hillel, 1982; Wilson et al., 1998). According to the International Soil Science Society classification, the soil is a fine sand. Other schemes classify the soil as ranging from

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FIGURE 3.2 Unified Soil Classification System, grain size chart, and well construction symbols used on boring logs.

a silt to a fine sand. All are correct for their respective classification schemes. Without adjusting these interpretations to a common standard, however, subsequent geologic interpretations and associated diagrams can perpetuate this nonstandardized bias. In the United States, the Unified Soil Classification System developed by the Corps of Engineers (U.S. Corps of Engineers, 1960) is the most commonly used system (Figure 3.2).

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Soil color is usually recorded on a boring log. If a standardized color scheme is not used, the correlation value of this information should be considered qualitative. The most common color standard is the Munsell Soil Color Chart, which contains 196 different standard color chips (Kollmorgen Corp., 1975). The Munsell system is arranged by the following characteristics: • Hue is the color of the soil relative to red, yellow, green, blue, and purple. • Value indicates the lightness of the soil (0 for black and 10 for absolute white). • Chroma is the strength of the color (0, for neutral grays, to 20). For absolute achromatic colors (pure grays, white, and black) with zero chroma and no hue, the letter N (neutral) is used in place of the hue designation.

A notation such as 5YR 5/6 on a boring log indicates use of the Munsell system. In “5YR”, 5 is the middle of the color value between yellow and red color hue (YR). The notation “5/6” is the chroma value between 5 and 6. Boring logs often contain soil terminology used by non-geologists (drillers or soil scientists). A driller’s log may qualitatively describe a soil as light or heavy. A sandy soil that is loose and well aerated is called light, while a clayey soil that tends to absorb and retain fluid when wet is termed heavy. If there is doubt about the meaning of such terms, ask the author of the boring log. When soil samples are collected at random depth intervals, ascertain whether there is an attempt to avoid collecting soil samples with a higher or lower probability of detecting contamination. An example is the consistent sampling of coarse sands and the avoidance of sample collection in finer grained materials (silty or clayey soils) through which a contaminant with a high sorption capacity has infiltrated. Conversely, soil samples collected at the interface of coarse, overlying, fine-grained sediments (i.e., a sand overlying a clay) can result in an overestimation of the concentration, volume, and (by extension) remediation costs for the contaminated soil. An extension of this manipulation is the use of small sample volumes for chemical analysis which biases the chemical results due to the soil particle size not being representative. This technique assumes that the association of a chemical in the soil is uniquely associated with a particular particle size. A proposed approach to quantify this potential particle size bias is to examine the sample size required for analysis relative to the particle size distribution of the soil sample. This method identifies the potential bias due to the grain size distribution between soil samples collected from similar soil textures. Ramsey (1996) defines this potential bias due to the particle size representativeness as: S = (22.5d3/ms)1/2

(Eq. 3.1)

where S = sample mass. 22.5 = sampling constant, which is an approximation and is applicable to many, but not all, hazardous waste materials. = maximum particle diameter. d3 ms = sample mass in grams.

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FIGURE 3.3 Boring log with organic vapor analysis measurements.

In most cases, the larger the sample volume, the smaller the potential particle size bias. If a soil sample is homogenized or sieved by the laboratory and a particular particle size fraction is selected for extraction, a similar chemical bias can be introduced. Examination of laboratory documentation will provide this information. If a contaminant is migrating through the soil via unsaturated flow, it can preferentially circumvent a coarse-grained layer. As a result, systematic sampling of these coarse-grained sediments underestimates the extent of contamination. Conversely, sampling consistently at the interface of a coarse and fine-grained sediment through which a contaminant has traveled in an unsaturated state provides the greatest opportunity of detecting a contaminant. Plate 3.1* illustrates a field experiment where dye moving through a medium-grained glacial sand in an unsaturated state preferentially migrates around the coarse-grained sediment. * Plate 3.1 appears behind page 242.

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FIGURE 3.4 Boring log with field measurements (OVA and HNu™).

Soil lithology descriptions, field measurements, and sampling locations recorded on a boring log can provide insight regarding the intentional manipulation of sampling locations for the purpose of biasing the chemical results. Figure 3.3 is a portion of a boring log containing field organic vapor analysis (OVA) and HNu™ measurements. The presence of a distinct layer of contamination between 45 and 50 ft is suggested by the HNu™ readings of 200 ppm; if samples were not collected for chemical testing between this interval, this could suggest intentional biasing. This type of analysis is also useful for targeting subsequent evidentiary sampling. Figure 3.4 is a field boring log example that illustrates the presence of a volatile compound at about 5 ft (OVA = 1000 ppm) that was not sampled. Samples in Figure 3.4 with non-detect and near OVA and HNu™ detection levels at 10 and 20 feet, however, were sampled. In this instance, the decision not to sample at 5 feet precludes the confirmation of a potential surface release indicated by the OVA reading of 1000 ppm.

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FIGURE 3.5 Boring log with PID, FID, and IR readings.

Field measurements used to screen soil sampling locations are qualitative and sensitive to the compound detected and instrument calibration, but do not rely on field measurements beyond this qualitative, field-screening purpose. Figure 3.5 is a field log in which photoionization (PID), flame ionization (FID), and infrared (IR) detectors were used. Values for the three instruments for the same soil ranged from 0 to 841 ppm.

3.3 INTERPRETATION OF GEOLOGIC INFORMATION Information on a boring log is used to create geologic cross-sections or fence diagrams. Significant latitude is available in the extrapolation of boring log descriptions

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to create these diagrams. These interpretations are important when low permeability horizons, relative to vapor or liquid contaminant transport, are incorporated in the geologic cross-sections or fence diagrams. Geologic diagrams are created via manual interpretation (Figure 3.6) or interpolation by computer software. Areas of inquiry (A through D) on Figure 3.6 are framed and labeled. If the purpose of the cross-section is to represent the presence of a continuous layer of clayey soils that retards contaminant transport, potential areas for differing interpretation are possible as described in the following text. A. A contact between artificial fill (speckled fill) and a silt and clay (white space) is present midpoint between Boring 1 and MW-1. This interpretation extends the silt/ clay layer into an area where no data are available but which may be a logical assumption. B. The contact between the silty and clayey sand (dotted fill) and the silts and clays (white space) is interpreted to occur at a point that is not midpoint between MW1 and MW-B1. This interpretation is inconsistent with the midpoint methodology used in A. C. The extent of the silty and clayey sand (dotted fill) is interpreted to extend halfway between Boring 2 and VE-2 in one direction but only a short distance in the opposite direction between Boring 2 and VE-5. This interpretation creates a significant horizon of predominately silt and clays between C and D. Another interpretation is to create a contact between framed areas C and D. This alternative interpretation creates a thin layer of silt and clays that are less of an impediment to the vertical transport of contaminants. This interpretation is also inconsistent with examples A and B, where the soil contact between two wells is interpreted as the midway point. Furthermore, there is no boring located between Boring 2 and VE-4 to indicate the presence of a clay layer. D. The contact between the gravels at the bottom of VE-5 is extended toward Boring 2, where it is not encountered. This is inconsistent with the method used in A and B. E. The geologic interpretation between Boring 2 and VE-4 deviates from the pattern observed in frames A to C in that the contact between the silty and clayey sands in Boring 2 and gravels in VE-4 is not interpreted as occurring midpoint. The silty and clayey soils in VE-4 are portrayed as extending just short of Boring 2, although there are no intervening data to confirm this interpretation.

Examine the horizontal and vertical scales used in cross-sections. In Figure 3.6, the vertical scale is 0.4¥ of the horizontal scale. If the scale is not 1:1, the viewer’s perception may be significantly skewed. The preparation of an alternate geologic cross-section that is scaled and presented as a rebuttal exhibit may be appropriate. A variation to the Figure 3.6 manual interpretation of the geologic data is assignment of numerical values that represent different soil properties. Computer software then spatially extrapolates between these values. Computer interpretations and their portrayal in cross-sections, isopach maps, or fence diagrams can produce highly erroneous interpretations. When reviewing a computer-generated geologic diagram employing this technique, you will need to:

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FIGURE 3.6 Example of manually created geologic cross-section. ©2000 CRC Press LLC

• Obtain a copy of the tables and/or spreadsheets used to assign numerical values to different soil and geologic materials. • Evaluate whether a consistent numerical value is used for identical soil and/or geologic descriptions. • Determine how the computer software deals with and assigns geologic descriptions to two numbers (e.g., rounded up or down). • Identify whether multiple measurements of a geologic or soil property are statistically manipulated to skew the interpolation and resulting graphical portrayal of this property; for example, combining measurements over some vertical distance and taking the average or arithmetric log of the data can mask the presence of a geologic or soil property of interest.

3.4 SOIL COLLECTION FOR CHEMICAL ANALYSES Significant opportunity exists for introducing bias during the collection of soil samples. Sampling procedures susceptible to chemical bias (especially volatile organics) include the following: • • • •

Improper selection of sampling equipment relative to the analyses to be performed Subsampling and sample transfer Sample compositing Extended holding times

3.4.1 SOIL SAMPLING EQUIPMENT A variety of soil sampling equipment is available with different levels of potential chemical bias (ASTM, 1997a,b). Split-spoon sampling is probably the most commonly used method. Split-spoon barrel samplers are not recommended if there is poor sample recovery (e.g., the metal or brass rings are not completely filled with soil) due to the potential loss of compounds by volatilization into the headspace of the partially filled brass tubes. Confirmation that the brass tubes are decontaminated prior to use is required. Pre-cleaned rings or tubes can be purchased with decontamination certification. Recycled tubes can be cleaned at a laboratory with the requisite number of rinsate samples and testing. In the field, the sampling barrel is attached to the drive rod of the drill rig and is driven into the soil with soil filling the sampling barrel. The barrel is then retrieved at the surface and broken open, and the soil in the brass or steel rings is sealed or transferred into another container. The exposed end of the soil in each ring should be quickly covered and sealed in the field using an inert film, such as TEFfluorocarbon sheets that are then covered with plastic or threaded metal caps. The use of electrical tape for sealing the plastic end caps on the brass rings is discouraged (see Figure 3.7). Permeation of toluene from the adhesives in these tapes through the plastic end caps can occur, resulting in a false bias. In order to confirm the origin of the toluene from the adhesive, it is the author’s experience that subsequent samples from the same location are required but without the tape used in the initial sampling.

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FIGURE 3.7 Improper use of electrical tape to seal brass tubes containing soil samples.

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FIGURE 3.8 Example of subsampling of soils in the field.

3.4.2 SUBSAMPLING AND SAMPLE TRANSFER Subsampling is the process of “repackaging” a sample into another container. Volatile organic compound losses occur primarily during the soil transfer from a splitspoon sampler into a 40-mL glass vial, an 8-oz glass jar, or plastic bag, through volatilization. The amount lost is dependent on the vapor pressure of the compound, the amount of headspace in the sample container, the ambient temperature, and the amount of sample disturbance (Hewitt et al., 1992). Figure 3.8 illustrates soil subsampling from one partially filled brass ring into a second ring so that no headspace is present. If the subsampled soil in the second brass ring is tested for volatile organic compounds, losses can be as much as 100% of the actual value (Siegrist, 1993). Figure 3.9 summarizes data from soil samples contaminated with TCE collected with different subsampling procedures and/or containers (Siegrist and Jenssen, 1990). The primary mechanism for loss was due to volatilization during collection, sample storage, and handling. The initial concentration of the spiked soil sample was 4.7 ppm. The soil sampling location coupled with an understanding regarding volatile losses that occur during soil subsampling can be used to manipulate test results. Consider excavated soil from an underground gasoline tank removal that is stockpiled for several days. The ultimate disposal decision for this soil by the regulatory authority is predicated on the sample results from the stockpile detecting compounds below a specific action level (Plate 3.2*). BTEX results from a soil sample collected from the crust of the pile has a higher probability of a lower concentration than a sample collected from within the interior of the soil pile. A decision based on the former location can result in the non-detect BTEX results. The stockpiled soil is then approved for placement into the excavation. At some future time (e.g., a Phase II * Plate 3.2 appears behind page 242.

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FIGURE 3.9 Loss of TCE from different sampling containers. (Adapted from Siegrist, S. and P. Jenssen, Environmental Science and Technology, 24(9), 1387–1392, 1990.)

property transfer), soil in the former tank excavation is sampled, the samples are above a regulatory action limit, and remediation is required. This is a common scenario, especially with aboveground ex situ remediation, that can be avoided by the selection of appropriate sampling locations and an adequate number of confirmation samples. When designing a soil sampling program for volatile organic compound analysis, minimize the number (if any) of subsampling and/or sample transfer steps. Current soil sampling procedures specify that samples analyzed for volatile organic compounds should be shipped to the laboratory in containers filled to capacity (i.e., no headspace) and stored at 4∞C for no more than 14 days. An option for improving sample integrity is to use glass jars containing methanol. Given that volatile compounds are more soluble in methanol than water, the longer contact time between the methanol and soil results in excellent extraction efficiency. In addition, extraction of the volatile compounds from the soil is performed with a larger subsample than used in some methods (e.g., 100 g vs. 5 g, or, if placed directly into the purge vessel, 1 g for gas chromatography/mass spectrometry [GC/MS] analysis). Thus, a more representative determination of the volatile compounds present results. The methanol container is usually a wide-mouth, 8-oz jar with TFE-fluorocarbon-lined lids. Analytical-grade methanol (100 mL) is added to the jar, into which the soil is placed to a predetermined level followed by immediate sealing of the jar. Michigan, New Mexico, Massachusetts, and Wisconsin currently require this procedure for soils analyzed for volatile organic compounds. Considerations in using this technique include investigating whether sample shipment by a commercial carrier is restricted. Coordination with the laboratory is also required if the laboratory prepares the methanol-filled containers prior to sampling.

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When reviewing test results obtained from soil samples using this technique, be aware that methanol has a high affinity for many organic compounds. Once a methanol bottle used to prepare the 8-oz jars is opened, organic compounds can be rapidly adsorbed into the methanol, thereby resulting in cross-contamination. Laboratories also purchase methanol with contaminant levels exceeding method detection limits (Hartman, 1998a). Testing the methanol using the same method selected for the soil samples prior to filling the jars allows quantification of this potential bias. A potential reduction in analytical sensitivity may also occur if a gas chromatograph/ Hall detector is used.

3.4.3 SOIL COMPOSITING Composite samples consist of multiple samples collected at various sampling locations and/or points in time. The constituent information for the individual samples is lost, although it may be indirectly observed through the composite measurement. Composite sampling reduces concentration variability, thereby narrowing the confidence interval of the population as contrasted with grab samples that maximize concentration variability. When analyzed, composite samples produce a global average value. Compositing can result in loss of information via sample dilution, especially at near-detection levels, as well as the possibility of adverse physical, chemical, and biological interactions resulting from the mixing process (Lancaster et al., 1988). Samples analyzed for volatile organic compounds should not be composited (ASTM, 1997d). Compositing can mask information otherwise useful for dating a contaminant release. Figure 3.10 illustrates this concept; discrete samples collected from borehole SB2 allow the correction of historical water levels to a known release date to confirm the release of diesel into the groundwater after 1982. Composite sampling would not provide the depth of discrete information necessary for this interpretation. Compositing, however, has value as a field screening technique for rapidly identifying whether contamination is detectable or providing a precise estimate of the mean concentration of a waste analyte in soil or groundwater. Composite sampling is routinely encountered in soil confirmation sampling. This application has merit due to the expected contiguous and non-randomness of the contamination, along with the assumed quantity of non-detects associated with the testing. In general, individual samples selected for compositing should be of a similar mass, although proportional sampling may be appropriate. An example of proportional sampling is the collection of soil cores from contaminated soil overlying an impermeable zone (ASTM, 1997c). Soil cores of different length can provide an averaged contaminant concentration value of the overlying soil, regardless of core length. The collection time for a single composite sample should not exceed 24 hr. If longer sampling periods are necessary, the collection of a series of composite samples is recommended (ASTM, 1996). If composite samples are collected without the opportunity to resample, a novel application using the inverse theory technique

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FIGURE 3.10 Use of discrete soil sample results and historical groundwater level data to confirm the release of diesel into the groundwater after 1992.

of linear regularization may provide concentration estimates at the individual sample level (Lancaster and McNulty, 1998). The use of field screening technologies rather than composite sampling can provide a cost-efficient option to compositing. X-ray fluorescence, for example, can quickly screen a soil sample for a particular element or target compound, thereby providing the basis to identify a discrete number of samples for testing (see Table 3.10). This approach is conducive to evidentiary sampling, because a large number of samples can be tested in the field in a short period of time.

3.5 GROUNDWATER CHARACTERIZATION The hydraulic properties of an aquifer are commonly estimated or measured as part of a groundwater characterization investigation. The determination of how these properties are measured and their reliability is one factor in evaluating contaminant transport and risk assessment models. Hydraulic properties and their definitions include: • Hydraulic conductivity: The rate of flow of water in gallons per day through a cross-section of 1 ft2 under a unit hydraulic gradient at a prevailing temperature.

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• Hydraulic gradient: The rate of change in total head per unit of distance of flow in a given direction. • Permeability: The property or capacity of a porous rock, sediment, or soil to transmit a fluid. • Porosity: The percentage of the bulk volume of a rock or soil occupied by interstices, whether isolated or connected. • Transmissivity: The rate at which liquid is transmitted through a unit width of an aquifer under a unit hydraulic gradient.

The accuracy and representativeness of these values are in part dependent on whether they are measured in the field or laboratory. Three methods used to measure the saturated hydraulic conductivity of an aquifer (listed from least to most representative method) are laboratory permeater tests, slug tests (field), and pump tests (field). Groundwater velocity is a key input parameter used for advective and for contaminant transport models. Sources of error in acquiring this information include the following: 1. Installing a well (to measure groundwater levels) near activities that disrupt the aquifer, such as municipal or irrigation wells that are periodically pumped and/or spreading basins used for groundwater recharge 2. Surface water bodies (e.g., streams, lakes, or reservoirs) with highly fluctuating flows located near a monitoring well 3. Tidal cycles that affect groundwater levels 4. Leaking sewers, water mains, and/or ornamental irrigation that affect localized hydraulic gradients 5. Inaccurate surveying of monitoring wells

In order to determine groundwater velocity, monitoring wells are surveyed on the horizontal and vertical axis. Wells should be surveyed to a vertical accuracy of 0.01 ft. The water level depth in each well is adjusted to provide a standardized reference point (usually mean sea level, MSL) which is used to create a groundwater contour map. If the original vertical survey for a well is incorrect, subsequent measurements can perpetuate this error, resulting in incorrect interpretations regarding groundwater direction and velocity. Incorrect water level measurements can occur as a function of the measuring point or the equipment. The measuring point refers to the location at the ground surface or well casing from which the depth is measured; the surface measuring point must be consistent. In some cases, a well casing can settle over time, resulting in a biased measurement; if this is suspected, re-survey the well. Differences in water level measurements can also occur as a function of the equipment (e.g., steel tape vs. a pressure transducer) (Rosenberry, 1990). There is sufficient error in the two techniques to produce misleading information about the direction of groundwater flow, especially for small groundwater gradients (@ 0.001). Knowing what equipment was historically used for measuring the depth to groundwater in a monitoring well and the consistency of the measurement technique may explain apparent anomalies in groundwater flow patterns.

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Another potential source of error in identifying the direction and velocity of groundwater is combining groundwater level measurements from wells screened in discrete aquifers, especially for unconfined and confined aquifers. Using regional maps (e.g., 1 in. = 24,000 ft) to determine groundwater flow and direction rather than installing on-site wells can also result in erroneous determinations of groundwater direction and velocity. Do not accept reported groundwater direction or velocity a priori without reviewing the actual measurements. This requires plotting groundwater level measurements and creating a groundwater contour map. The groundwater direction obtained from the graphing should be compared to the general direction of reported groundwater flow in the environmental report.

3.5.1 MONITORING WELL LOCATION Given a sufficient understanding of the hydrogeological environment and the origin and physiochemical characteristics of the chemicals released into the subsurface, monitoring wells can be designed to collect samples for the following purposes: • Provide representative (i.e., the degree to which sample data are characteristic of a population, variations at a point, or an environmental condition) samples. • Avoid detecting contaminants. • Underestimate contamination. • Overestimate contamination. • Generate anomalous data.

The location of a monitoring well and well screen interval has a profound impact on the chemistry of groundwater samples collected from the well. Monitoring well design features indicative of manipulation are summarized in Table 3.2. Other sources of potential bias include well construction materials, grouting materials, design of security covers, and drilling methods (Powell, 1997). If monitoring wells are constructed from different materials, this might indicate an attempt to manipulate the chemical data through well construction materials. It can also indicate several generations of consultants working at the site with different preferences for well construction material. Elevating sample pH through improper grouting procedures or the use of grouting materials containing potential contaminants can impact sample chemistry. Cement grout (CaCO3) can raise the pH of the surrounding soil several pH units. Elevated pH values in the vicinity of the well screen may cause precipitation of otherwise soluble metals as they enter a halo of higher pH groundwater. If this phenomenon is suspected: (1) examine whether the pH values are high relative to other wells in the area, and (2) excessively purge the well prior to sampling (e.g., 10 to 20 casing volumes) and measure the pH to observe if it suddenly drops several pH units. If pH values decrease abruptly, this may suggest that the grout material has impacted groundwater pH in the immediate vicinity of the well.

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TABLE 3.2 Effect of Well Location on Sample Chemistry Impact on Sample Chemistry

Design/Location Characteristics

Contaminants non-detected

Wells installed cross-gradient and/or upgradient of source areas; wells with long screens (>20 ft) and contaminants present at low concentrations

Contaminants underestimated

Long screens (>20 ft); wells screened across geologic units with a low probability of transporting contaminants

Contaminants overestimated

Short screens located to intersect zones with a high probability of contamination (i.e., LNAPLs at the water table); wells screened across high- and low-contaminated zones that result in an averaged concentration that is higher than the actual concentration in the groundwater

Anomalous data

Well located next to a surface water body whose chemistry is dissimilar to the groundwater chemistry and whose presence impacts the sample chemistry in a transient and unpredictable manner; well located in an area of changing groundwater direction that results in varied chemistry depending on the direction of groundwater flow.

Well construction can also impact sample chemistry. Poorly constructed security covers or valve boxes that allow contaminated surface seepage into the well can produce anomalous chemical results (see Plate 3.3*). It is the author’s experience that street runoff containing soluble lead and high total petroleum hydrocarbon concentrations draining into a well via a cracked security cover can result in detection of these contaminants in groundwater samples above regulatory action limits. Whenever possible, arrange a site visit to identify the existence of these types of biases prior to examining the groundwater chemical results. Another area of inquiry for wells drilled through multiple aquifers is whether the consultant drilled through a confining layer, thereby introducing contamination into a deeper, previously uncontaminated aquifer. This situation is often identified on a boring log that indicates that the borehole was over-drilled with the lower portion of the hole backfilled with grout to seal off the penetration of the confining layer. A variation to this scenario is if the well screen intersects multiple aquifers in which only the upper horizon is contaminated. Contaminants from the upper, contaminated zone enter the lower, previously uncontaminated zone. A reverse situation is shown in Figure 3.11, where contamination from a lower aquifer is allowed to mix within the well casing during pumping. Contaminants then flow into the shallower zones when the pump is not operating. The result is the contamination of a previously uncontaminated shallow water-bearing zone. * Plate 3.3 appears behind page 242.

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FIGURE 3.11 Cross-contamination of a shallow aquifer by a multiple-screened pumping well.

3.5.2 INSTALLATION OF GROUNDWATER MONITORING WELLS Contaminant distribution in groundwater is defined by the horizontal placement of the monitoring well as well as the screen length and interval. While federal and state guidelines exist, the consultant or driller usually designs the well. As a result, multiple well construction designs may be present which impact the chemical interpretation of samples collected from the network. If well construction is suspected of biasing sample chemistry in some manner, the first step is to review the placement of the well screen. The location of the well screen determines the vertical horizon from which a sample is collected, unless discrete vertical depth sampling is performed. Questions to be answered during this analysis include:

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FIGURE 3.12 Hydrograph indicating the presence of two aquifers.

• Are the wells screened in similar water-bearing zones? • Does the well screen length bias sample chemistry? • Is the well screen providing a pathway for contaminant transport from areas of high to low contamination or from contaminated to non-contaminated zones?

The first step in answering these questions is to construct a hydrograph. A hydrograph plots time on the horizontal axis and the water level measurement for each well on the vertical axis. If sufficient information is available, the water level in each well for a point in time is plotted and the data connected. If the wells intersect the same water-bearing zone (i.e., if they are hydraulically connected), the lines for the various wells will follow a similar pattern over time. If the wells do not follow the same general pattern, this may be evidence of multiple saturated zones that are monitored by the well network. Separate water level contour maps should be created for each aquifer indicated by the hydrograph. Figure 3.12 is an example of a hydrograph showing two distinct aquifers. Another technique is to sketch all of the monitoring wells on a single sheet of paper, adjusting for the surface elevation for each well, with the vertical axis representing well depth. Mark the screen interval on each well along with the water level. This sketch provides insight regarding the consistency of the well screens between wells and patterns between well screen length and water levels. Another area of inquiry is whether the screen interval biases sample chemistry. If the predominant contaminant of interest is a light non-aqueous phase liquid (LNAPL) and the well screen does not intersect the water table, the LNAPL will not be detected. Other examples of high contaminant concentrations near the water table that decrease sharply with depth include toluene, xylene, xylidine, dissolved oxygen, and manganese concentration profiles (Kaplan et al., 1991) and BTEX concentrations (Gibs et al., 1993; Martin-Hayden et al., 1991). An example of the latter is the sampling for BTEX components at the water table with a short screen (<5 to 10 ft) well vs. a longer screened (>20 ft) well. If this inquiry reveals potential patterns

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between compound concentration depth profiles and screen length, examine the screen length as a function of proximity to the contaminant source (if known). If monitoring wells closest to the source area have long screens (possible sample dilution) and those farthest from the source are short screened, a pattern of sample chemistry manipulation and contaminant plume geometry via well screen length and proximity to the source may become apparent (Martin-Hayden and Robbins, 1997). The interpretation of the vertical distribution of a contaminant is especially sensitive to well screen length, interval, and placement (Robbins and Martin-Hayden, 1991). Detailed studies of vertical spatial and temporal gradients indicate that transport of contaminants is often limited; therefore, concentration profiles can be highly variable with depth (Barcelona et al., 1989; Garabedian et al. 1987; Gibs et al., 1993; Sudicky et al., 1983). The ability of the monitoring well to provide this resolution is, then, spatially dependent, primarily on the monitoring well screen design. An example of the impact of well screen length on source identification is shown in Figure 3.13. The plan view in the upper panel of Figure 3.13 plots TCE concentrations from groundwater samples. During the first round of sampling, all of the wells, except the demonstration well, were sampled (the demonstration well was installed after the first round of sampling). The interpretation of the data indicated a source in the vicinity of the 1650 ppb of TCE given the upgradient well value of 120 ppb. TCE concentrations relied upon for this conclusion were the 120 ppb from the upgradient well, the 1650 ppb from the well near the source, and the downgradient well with 1500 ppb. The source and downgradient wells were short screened (10 ft) and completed in a silty sand. The upgradient well (120 ppb) was completed with a 20-foot screen that intersected the silty sand and a highly permeable sand and gravel layer. Concern about the longer screened, upgradient well diluting the TCE concentration via the uncontaminated sand and gravel layer resulted in installation of a demonstration well screened in a manner identical to the source and downgradient wells upgradient of these three wells. Sampling of the demonstration well shown in the cross-section on the lower panel of Figure 3.13 resulted in a TCE value of 1600 ppb. This information is consistent with a revised interpretation that TCE migrated onto the property from an upgradient source. Ideally, monitoring wells are all short screened (approximately 5 to 10 ft) and located at appropriate depths relative to the goal of the monitoring program. In most cases, however, monitoring wells are constructed with different screen lengths and may not be ideally located. While the potential bias associated with different monitoring well construction can be identified, quantification of this bias cannot be assessed. The qualitative impact of different well construction designs in addition to an evaluation of groundwater purging and sampling techniques should be examined in total and a judgment made concerning the reliability of the chemical data.

3.5.3 SAMPLING PLAN Environmental reports often include soil and groundwater sampling plans. Review the sampling plan and compare it with the field notes describing the actual field

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FIGURE 3.13 Impact of well screen length on source identification.

practice. This review can identify whether significant deviations from the sampling plan occurred. A recommended step in performing this review is to compare the following components of the sampling plan with what transpired during its implementation: • Could purging, sampling, and handling procedures for compounds susceptible to volatilization, precipitation, or other forms of known chemical transformation result in chemical transformations? • Was sample filtration and/or preservation properly implemented? • Were sufficient field blanks, travel blanks, duplicate samples, and/or equipment rinsate blanks incorporated into the sampling protocol to allow for the discrimination of potential sampling introduced bias? • Were expedited storage and transportation of samples to the laboratory implemented as specified in the sampling plan?

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3.5.4 GROUNDWATER PURGING A review of groundwater purging procedures is useful, as inconsistent purging practices can result in different interpretations concerning the identification of zones of low concentration, differences in the direction of contaminant flow, contaminant plume geometry, and the identification of intermittent or multiple sources of groundwater contamination (Martin-Hayden and Robbins, 1997). A lively discussion in the environmental consulting industry during the past several years has occurred regarding the merits of purging two to five casing volumes of groundwater prior to sampling or whether “micropurging” a smaller volume of water is adequate. Micropurging and sampling can provide representative chemical results while minimizing issues regarding disposal of purge waters and/or sample oxygenation. A routine purging practice is to pump 5 to 10 times the volume of standing water in the well to remove the stored water in the well casing (ASTM, 1992). For most wells, three to five well volumes are purged, or until pH, conductivity, and water temperature values stabilize. Stable sample chemistry is considered to occur if field values of temperature, specific conductance, oxygen, pH, and turbidity are within ±10% in purge water pumped over at least two successive well volumes. If a monitoring well slowly recharges, sufficient time should elapse so that at least 95% of the purged water comes from the aquifer; wells should also be sampled within 6 hr of purging (Csuros, 1994). At no times should a well be purged to dryness if the recharge rate causes the formation water to cascade down the interior of the well screen. For a well whose screen intersects a low-permeability formation, desaturating the well during purging can also result in weighting the average contaminant concentrations near the bottom of the well and therefore underestimating the concentration and size of the contaminant plume (Martin-Hayden et al., 1991). Micropurging or low-flow sampling is generally considered to be between about 100 to 200 mL per minute (Puls et al., 1990). Higher rates are acceptable (i.e., 1 L per minute) for more transmissive formations (Powell 1993). Research indicates that a representative groundwater sample for volatile organic sampling is achievable via micropurging without pumping 2 to 5 well casing volumes (Kearl et al., 1994; Powell et al., 1997; Puls et al., 1995). The U.S. Environmental Protection Agency advocates micropurging coupled with turbidity, pH, redox potential, and dissolved oxygen measurements using downhole meters or flow-through cells until stability is achieved. These measurements are considered stabilized when the values are within approximately 10% over at least two measurement events. Stabilization can also occur prior to the removal of one well casing volume or may require excessive purging (Barcelona et al., 1994; Robin et al., 1987). Research indicates that for fully hydrogeologically characterized sites with long-term monitoring data, micropurging and the measurement of water quality parameters such as pH, turbidity, and total conductance may not be necessary. Groundwater sampling for uranium at the Fernald facility in southwestern Ohio, for example, indicated that representative samples were collected with micropurging sampling without water quality parameter measurements (Shanklin et al., 1995).

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In a California study involving trace metal contamination, low-flow purging and sampling in addition to rigorous adherence to sampling and handling procedures were examined. When low-flow and trace metal clean techniques were employed, resultant trace element concentrations were notably lower than for values obtained with conventional methods. The trace element concentrations from groundwater wells were 2 to 1000 times lower than those previously reported by consultants using conventional sampling techniques at the same wells. While the consultant reported that cadmium and chromium concentrations exceeded the California maximum contaminant levels (MCLs), these levels appeared to be artifacts of inappropriate, albeit standard, sampling techniques (Creasey, 1996). The use of micropurging can bias sample chemistry due to the small capture zone associated with low purging rates. Consider a monitoring well with phase-separate TCE in the groundwater that is 25 feet down-gradient from the well. Historical TCE concentrations in groundwater from this well are consistently in the parts-per-million range. Purging rates of 5 gallons per minute and greater were used. Subsequent sample results collected via micropurging (100 mL/min) are non-detect because the purging and sampling capture zone does not extend to the vicinity of the phaseseparate and dissolved TCE.

3.5.5 GROUNDWATER SAMPLING When reviewing groundwater sampling procedures, identify the type of sampling equipment (e.g., bailer, submersible pump, peristaltic pump) and sampling procedures used. Groundwater samplers vary in their impact on sample chemistry. The greatest opportunity for negative bias occurs when sampling groundwater to be testing for volatile organic compounds. Because the true value of a volatile organic compound is unknown, the bias introduced by equipment selection and operation is relative. Sampling equipment and procedures that result in higher levels of volatile compounds are therefore considered most accurate (i.e., unless evidence of a false positive bias is identified). Numerous studies have evaluated the attributes of groundwater sampling equipment and procedures on sample quality (Stolzenberg et al., 1986). Many of these investigations examined the precision (i.e., a measure of the reproducibility of a set of replicate results among themselves or the agreement among repeated observations made under the same conditions) and recovery of volatile organic compound determinations on replicate samples collected in the field or laboratory. Volatile compounds are particularly sensitive to losses by degassing at reduced pressures from suction devices such as peristaltic or centrifugal pumps or turbulence created by mechanical sampling devices such as gas lift samplers and bailers. Volatile organic compound losses from improper sampling equipment selection and use are cumulative in nature. Sampling procedures that represent potential sources of volatile organic compound loss include:

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FIGURE 3.14 State-of-the-art sampling equipment used to strip volatile organic compounds from a groundwater sample by over-pressurizing the pump. (Courtesy of QED; Ann Arbor, MI.)

• Sampling with a bailer and aerating the sample during transfer from the bailer into the sample container • Over-pressurizing (see Figure 3.14) or depressurization (Barcelona, 1990) • Insufficient decontamination between sampling or lack of equipment blank samples between sampling, if non-dedicated sampling equipment is used • Not placing the cap on the sampling container or immediately chilling the sample

This level of information is usually not included in the environmental report but may be available in field notes acquired via deposition testimony of the sampler. In general, positive displacement pumps (e.g., bladder pumps) provide accurate, reproducible sampling performance over a range of lifts, hydraulic heads, and depths. Dedicated sampling systems suitable for both purging and sampling are also preferred based on sample integrity as well as convenience and cost.

3.5.6 SAMPLING EQUIPMENT AND SEQUENCE In general, the compatibility of the sampler material(s) with the analysis to be performed is obvious (e.g., iron bailer when testing for trace metals). Subtle chemical biases can be introduced, however, from a polyethylene bailer manufactured from plastic regrinds or plastics that contain additives vs. a sampler manufactured from virgin material. A bailer manufactured from solid rod or block stock may similarly contain potential cross-contaminants from the machining process, as opposed to a bailer that is injection molded without release agents such as waxes or petroleumbased lubricants. Depending on the level of scrutiny required and the potential bias relative to the allegations in the case, this level of inquiry may or may not be necessary.

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TABLE 3.3 Effect of Sampling Equipment on Benzene and Chlorobenzene Concentrations Sampling Equipment West Bay sampler Bailer Pump with packer Dedicated bladder pump

Benzene (ppb)

Chlorobenzene (ppb)

114 179 205 279

651 1034 1447 1463

Compounds susceptible to chemical changes due to redox shifts from the sampling equipment and field procedures are most vulnerable to bias, as are compounds with low detection limits. With volatile organic compounds, losses are more likely to increase due to operator procedures (Imbrigiotta et al., 1986). Table 3.3 summarizes the impacts of sampling equipment (and procedures) on benzene and chlorobenzene concentrations (Blegen et al., 1988). If the opportunity exists to re-sample the well from which suspect data were collected, the well can be re-sampled with identical equipment but with different procedures or different equipment so that the potential source of the bias can be identified. If a monitoring well is no longer available or if the monitoring well construction is in question, groundwater sampling using direct push technology (e.g., Hydropunch, Geoprobe, Strataprobe, etc.) can be used at the same location. Standardized sampling guides are available for using direct push technologies for collecting groundwater samples (ASTM, 1997c). Comparisons between groundwater sample chemistry obtained from direct push samples and standard monitoring wells are reported to be statistically similar (Bergren et al., 1990; Church et al., 1996; Kaback et al., 1990). Sampling recommendations that minimize sampling bias, especially redox-sensitive and volatile compounds, include the following (Puls et al., 1989a,b; 1992): • Isolate the sampling zone with packers to minimize the amount of purge water. • Use low-flow pumping to minimize sample aeration and turbidity. • Monitor water quality parameters while purging to establish baseline or steadystate conditions to initiate sampling. • Perform filtration to estimate the total dissolved species present and collect unfiltered samples for estimations of contaminant mobility.

In addition to potential chemical biases introduced via the selection of sampling equipment and materials of construction, the sampling sequence can also impact sample chemistry. Figure 3.15 depicts a site with monitoring wells located on and off site with the property boundary depicted by a dotted line. Groundwater flows to the north. PCE concentrations in groundwater for the previous quarter and the sampling sequence were obtained from the chain of custody (see Table 3.4). In addition, the sampling equipment and procedures were described in the work plan. For on- and

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FIGURE 3.15 Map illustrating the impact of sampling equipment and sequence on groundwater chemistry results.

TABLE 3.4 Summary of Sampling Results, Sampling Sequence, and Sampling Equipment for Site Shown in Figure 3.15 Sampling Sequence Well

PCE (mg/L)

On-Site

B3 B6 B14 B9 B10 MW1 MW9 MW5 MW4 MW7 MW3

ND ND 160 230 360 ND ND 30 70 130 250

1 2 3 4 5 — — — — — —

a b

Sampling Equipment

Off-Site — — — — — 1 2 3 4 5 6

Purging

Sampling

Peristaltic Peristaltic Peristaltic Peristaltic Peristaltic Submersible Submersible Submersible Submersible Submersible Submersible

Teflon® bailera Teflon® bailera Teflon® bailera Teflon® bailera Teflon® bailera Submersibleb Submersibleb Submersibleb Submersibleb Submersibleb Submersibleb

Disposal Teflon® bailer. Submersible pump operated at maximum pumping rate for purging and sampling.

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off-site sampling, groundwater sampling proceeded from wells with no detectable PCE to wells with higher PCE concentrations, an observation which may indicate an intent to minimize the potential for cross-contamination via the sampling sequence. The purging and sampling equipment used also suggests a knowledge of the impact of sampling equipment on sample chemistry. Equipment that introduces the least potential of sample chemistry bias (e.g., peristaltic pumps and Teflon® bailers) was selected for on-site wells, while off-site groundwater samples were collected with equipment that introduced a significant potential for sample loss via volatilization (submersible pumps). A conscious attempt by the consultant to minimize the off-site detection of PCE may therefore be suspected. The sampling sequence may also be designed to maximize particular temporal impacts on sample chemistry. Figure 3.16 illustrates the impacts of some of these factors on groundwater chemistry. If such relationships exist, identify whether the sampling schedule results in a systematic impact on sample chemistry, and, if so, incorporate this information into your analysis.

3.5.7 EQUIPMENT DECONTAMINATION The chemical results from equipment decontamination samples allows an assessment of the presence and nature of cross-contamination originating from the sampling equipment. Federal, state, and American Society for Testing Materials (ASTM) standards are available which describe decontamination procedures for contact and non-contact equipment used for soil and groundwater sampling (ASTM, 1990). In general, sampling equipment is washed with a detergent solution followed by a series of water, desorbing agents, and deionized water rinses. A decontamination procedure for sample contact equipment includes the following tasks (Wilson 1998): 1. Wash with a detergent solution (Alconox® or Liquinox® or similar nonphosphate/ ammonia detergent) with a brush made or an inert material. 2. Rinse with water of a known chemical composition. 3. Rinse with an inorganic desorbing agent (10% nitric or hydrochloric acid made from reagent-grade nitric or hydrochloric acid and deionized water); this step may be deleted if the samples will not be tested for organics. 4. Rinse with deionized water. 5. Air dry prior to next use (ascertain whether fugitive or vapors can contaminate the equipment; if this is a possibility, then air dry in an environment where airborne contamination is not a consideration). 6. Wrap the equipment for transport with an inert material such as aluminum foil.

The U.S. Environmental Protection Agency recommends a similar procedure for equipment used to collect samples tested for organic and inorganic constituents according to the sequence in Table 3.5 (U.S. EPA, 1991). Non-sample contact equipment can be rinsed with a portable power washer or steam cleaner. In addition, handwashing with a brush and detergent solution may be required, followed by rinsing with water of a known chemical composition (ASTM, 1990). Examples of

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FIGURE 3.16 Examples of temporal variations on groundwater chemistry and LNAPL thickness.

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TABLE 3.5 Decontamination Procedures for Sampling Equipment Used To Collect Samples for Organic and Inorganic Analysis Organic Compounds

Inorganic Compounds

Tap water Organic-free reagent water Reagent grade acetone Pesticide-quality hexane, methyl alcohol, or isopropanol alcohol, depending on the analysis.

Dilute (0.1-N) hydrochloric or nitric acid Tap water Reagent-grade water

noncontact equipment include drilling augers and cone penetrometer rods (see Figure 3.17). For rigorous quality assurance and quality control situations, the rinse water used for equipment decontamination is sampled and tested for the same compounds to be analyzed as the sample obtained with the decontaminated sampling equipment. Referred to as an equipment rinsate blank, it is a sample of the last decontaminated water poured over the equipment. Equipment rinsate blanks are collected from nondedicated equipment such as pumps used for sampling, interface probes, mixing bowls, sampling scoops, split-spoon samplers, Hydropunches, bailers, and cone penetrometer testing tips. Equipment rinsate blanks should be collected at a rate of

FIGURE 3.17 Decontamination of groundwater sampling equipment and rinsate troughs for cone penetrometer rods.

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TABLE 3.6 Appropriate Sample Containers and Analysis Container Description

Analysis

80-oz amber glass bottle with Teflon®-lined black phenolic cap 40-mL glass vial with Teflon®-backed silicon septum cap 1-L high-density polyethylene bottle with polyethylene-lined, white polyethylene cap 120-ml glass vial with Teflon®-lined, white polyethylene cap 16-oz wide-mouthed glass jar with Teflon®-lined, polylyethylene cap (water analysis) 8-oz wide-mouthed glass jar with Teflon®-lined, black polyethylene cap (water) 4-oz wide-mouthed glass jar with Teflon®-lined, black polyethylene cap (water) 1-L amber glass bottle with Teflon®-lined, black polyethylene cap 4-L amber glass bottle with Teflon®-lined, black phenolic cap 500-mL high-density polyethylene bottle with polyethylenelined, baked-polyethylene cap

Extractable organics Volatile organics Metals, cyanide, and sulfide Volatile organic (soil) Extractable organics/metals Extractable organics and metals in soil Extractable organics and metals in soil Extractable organics Extractable organics Metals, cyanide, and sulfide

one blank per every 10 samples or one per day (U.S. EPA, 1995). Care must be taken to label the rinsate sample and the corresponding sample collected with this equipment correctly, so that any cross-contamination from the decontamination procedure can be identified and quantified.

3.5.8 SAMPLE CONTAINERS Recognized protocols are available that define the proper size and appropriate container material for soil and water samples for a given analysis. When reviewing the chain of custody, identify whether proper containers were used and, if not, whether this represents a potential false or negative bias. Generally, these types of issues are only significant when trace concentrations are of interest. Table 3.6 summarizes containers relative to the analyses to be performed (U.S. EPA, 1995). For liquid samples, the appropriate container for volatile compounds is a 40-mL vial sealed with a Teflon®-lined cap. The vial is filled with the meniscus above the top of the vial so that when the sealed vial is inverted, there are no air bubbles. Most laboratories will note on the sample receipt checklist log if vials are received with bubbles and may not analyze the sample without client authorization. Many laboratories will not accept samples for analysis if the bottles were uncertified clean by a supplier or cleaned by another laboratory. Table 3.7 summarizes recommended cleaning procedures for reused sampling containers (Wilson, 1998). If a concern exists about the chemical integrity of reused sample containers, fill several containers with distilled water and analyze them for the compounds for which the samples will be tested.

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TABLE 3.7 Recommended Decontamination Procedures for Sample Containers Bottles Separate the cap and Teflon® septum, rinse in tap water, and soak in warm, soapy water using laboratory-grade, nonphosphate detergent. Scrub the vials with a brush. Rinse the vials with tap water until the soap residue is gone, followed by a triple rinse of deionized water. Place the vials in a metal basket, right side up, and place in a ventilated oven at 105∞C for at least 3 hr. Remove the vials from the oven and allow to cool for at least 20 min. Cap each vial with a heated septum and store within a sealable (Zip-Lok®) bag. Caps Wash the caps in soapy water to remove dirt. Rinse with tap water to remove the soapy water. Allow to air dry, and store until needed. Septum Wash the septum in soapy water. Rinse with tap water to remove soap residue, then triple rinse with deionized water. Spread the septum in a single layer on a cleaned, stainless steel tray lined with laboratory-grade tissue paper. Dry in an oven at 105∞C for no more than 1 hr. Remove, cool, and immediately cap. Containers used for semivolatile organic compounds should be washed in soapy water, water washed, and rinsed with a methanol or isopropanol alcohol.

Sample cross-contamination can result if samples with significant differences in concentration are shipped together. For example, samples of free-phase gasoline and groundwater samples to be analyzed for BTEX compounds should be shipped separately. The shipping container can also cause cross-contamination. Cross-contamination originating from an ice chest can be identified via the travel blanks results. When designing a sampling plan, buy new ice chests rather than using ones provided by the laboratory (which may have compounds sorbed into their plastic). Consider segregating highly contaminated samples (e.g., oily soil, samples with high photoionization detector readings) from samples without gross indications of contamination in separate shipping containers.

3.5.9 SAMPLE FILTRATION, PRESERVATION, AND HOLDING TIMES Water samples analyzed for metals may require filtration in the field. Generally, samples analyzed for trace metals, inorganic anions, and cations are filtered, while water to be tested for total organic carbon and volatile organic compounds is unfiltered (Barcelona and Morrison, 1988). The U.S. Environmental Protection Agency recommends collecting one unfiltered sample for total metals and one filtered sample for dissolved metals (U.S. EPA, 1986). If the contaminant concentration in an unfiltered sample is higher than for a filtered sample, a portion of the contaminant may be sorbed onto the solid particulate matter in the water. Colloids as large as 0.45 to 3 mm can be mobile and capable of transporting contaminants large

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FIGURE 3.18 Impact of 0.10-, 0.40-, and 10.0-mm filters on elemental analysis of a groundwater sample. (Adapted from Puls, R. and Barcelona, M., Hazardous Waste and Hazardous Materials, 6(4), 385–393, 1989.)

distances. If a chemical is transported via colloidal transport, field filtering can remove this colloid and the associated contaminant. If the purpose of the sampling is to estimate the extent of metal contamination, substantial underestimation of contaminant mobility can result due to metal/colloidal associations with filtered samples. At a Superfund site in California, groundwater samples tested for lead were filtered with a 0.45-mm filter; the lead concentrations in the unfiltered samples were 20 to 600 times greater than the filtered samples. For chromium, concentrations were 6 to 24 times greater in the unfiltered samples than in the filtered samples (Puls and Barcelona, 1989). The standard 0.45-mm filter is the standard opening size, although this is an artificial convention. A 0.45-mm filter used to determine the extent of metal contamination in a dissolved state can overestimate the actual concentration due to the association of metals with colloidal material less than 0.45 mm. If the accuracy of the dissolved metal concentrations is of concern, samples can be field filtered through a 1-mm pore size filter using an in-line filter, and acidified immediately to <2 pH with concentrated HNO3 (Puls et al., 1992). Another option is to filter the sample with multiple filter sizes (the opening of a filter can also clog during filtering, resulting in a diminished filter pore size) and analyze the filtrate and dissolved component. Figure 3.18 illustrates the impact of filtration with three pore sizes on elements from a groundwater sample. Another recommendation is no filtration or a 4-mm filter for the determination of mobile metals and in-line filtration with a large non-metallic (e.g., 142-mm), polycarbonate type, 0.1-mm pore size filter, for geochemical speciation modeling (i.e., the dissolved fraction) (Puls and Barcelona, 1989). Metal analysis is especially sensitive to aeration introduced by filtering. A small volume of oxygen introduced in a reduced groundwater sample can result in decreases of up to 100% of lead, cadmium, zinc, arsenic, vanadium, and phosphate. The amount of adsorption of a trace metal onto ferric hydroxide also depends on the extent of iron oxidation that can be introduced via filtering. It is not unusual to observe differences greater than 10% between filtered and unfiltered samples for many elements. Field filtration devices include in-line filters, positive pressure filtration, and vacuum filtration (Figure 3.19). If sample containers contain a preservative such as

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FIGURE 3.19 In-line field filtering with a disposable cartridge. (Courtesy of QED; Ann Arbor, MI.)

nitric acid, the samples must be field filtered prior to placement in the container. Conversely, if a container does not contain a preservative, the laboratory can filter the sample. Filtering can result in as much disturbance as the process of sample collection (Stolzenburg, 1986). For example, if a sample is anaerobic with a pH greater than 7.4, dissolved ferrous iron oxygenation can result in the precipitation of amorphous ferric iron hydroxide occurring seconds after the initial aeration. The iron precipitation can impact sample pH, total conductance, alkalinity, ionic strength, turbidity, and color. Filtering can also exclude contaminants present in karst terrains, where contaminant transport is more likely to occur in conduit flow via colloidal transport. Contamination from the filter is another possibility; filter blank results should be collected prior to filtering so that this potential bias can be evaluated. A filter blank is an analytefree solution that is passed through the filter and tested. Issues regarding sample filtration may be significant in an environmental case. For example, in May of 1992, a federal appeals court overturned a decision by the U.S. Environmental Protection Agency to place a landfill in Delaware on the National Priorities List (NPL). The reason for this ruling was because EPA acted in an arbitrary and capricious manner in collecting only unfiltered groundwater samples (Wilson, 1998). While the issue is still outstanding, it highlights the need to examine filtered data carefully to determine their impact on the contaminants of interest.

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TABLE 3.8 Preservation and Holding Times Description and Measurement

Preservative

Holding Time

Physical property Color Conductance Hardness Odor pH Residue filterable Residue non-filterable Total residue Volatile residue Settleable matter Temperature Turbidity

Cool, 4∞C Cool, 4∞C HNO2 to pH <2 Cool, 4∞C None required Cool, 4∞C Cool, 4∞C Cool, 4∞C Cool, 4∞C Cool, 4∞C None required Cool, 4∞C

48 hr 28 d 6 mth 24 hr Immediately 7d 7d 7d 7d 48 hr Immediately 48 hr

Samples with low concentrations may require preservation by refrigeration or the addition of chemical reagents to slow physical chemical or biological changes. Chemical preservatives usually have a relatively short shelf-life and should be supplied fresh by the laboratory. Chemical and biological activities altering the sample chemistry include the formation of metal and organic complexes, adsorption/ desorption reactions, acid-base reactions, redox reactions, precipitation/dissolution reactions, and microbiological activities affecting the disposition of metals, anions, and organic molecules. Groundwater samples tested for general chemical parameters are not chemically preserved. Samples analyzed for volatile organic compounds, however, are acidified because hydrochloric acid (HCl) effectively prevents biodegradation of many volatile organic compounds (Maskarinec et al., 1990). The U.S. Environmental Protection Agency requires that samples analyzed for volatile organic compounds by EPA Standard Method 524.2 be preserved with hydrochloric acid to a pH of less than 2. Research has demonstrated that the addition of HCl does not result in the formation of trihalomethanes (Squillace et al., 1999). Water samples analyzed for metals are stabilized by the addition of nitric acid (HNO3) to a pH of 2. Samples tested for nitrogen and phosphorus are stabilized with sulfuric acid (H2SO4). pH adjustments in the field can be performed by using a plastic dropper bottle containing a 1:1 hydrochloric acid (Draper et al., 1998). If residual chlorine in the water is a concern, a reducing agent such as thiosulfate or ascorbate is used. The chain of custody should describe whether preservatives were added to the sample containers. Examine the sample collection times on the chain of custody and compare it with the analysis date to determine if the proper holding time was exceeded. Care is required that the “reporting date” of the laboratory is not confused with the date of analysis. Table 3.8 lists appropriate preservation and holding times for selected analyses (U.S. EPA, 1995).

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TABLE 3.8 (cont.) Preservation and Holding Times Description and Measurement Metals Dissolved Suspended Total Hexavalent chromium (Cr+6) Dissolved mercury (Hg) Total mercury (Hg) Inorganics, non-metals Acidity Alkalinity Bromide Chloride Chlorine Cyanides Fluoride Iodide Nitrogen Ammonia Total Kjeldahl Nitrate/nitrite Nitrate Nitrite Dissolved oxygen Probe Winkler method Phosphorous Ortho-phosphate (dissolved) Hydrolyzable: Total Total dissolved Silica Sulfate Organics Volatile organics Biological oxygen demand (BOD) Chemical oxygen demand (COD) Oil and grease Organic carbon Phenolics a

Preservative

Holding Time

Filter on-site, HNO2 to pH <2 Filter on-site, HNO2 to pH <2 Cool, 4∞C Filter, HNO2 to pH <2 HNO2 to pH <2 —

6 mth 6 mth 6 mth 24 hr 28 d 28 d

Cool, 4∞C Cool, 4∞C None required None required None required Cool, 4∞C, NaOH to pH >12 0.6 g ascorbic acidb None required Cool, 4∞C

14 d 14 d 28 d 28 d Immediately 14 da

Cool, Cool, Cool, Cool, Cool,

28 28 28 48 48

4∞C, H2SO4 to pH <2 4∞C, H2SO4 to pH <2 4∞C, H2SO4 to pH <2 4∞C 4∞C

28 d 24 hr d d d hr hr

None required On-site fixation, store in the dark

Immediately 8 hr

On-site filtration, cool, 4∞C

28 d

Cool, 4∞C Cool, 4∞C, H2SO4 to pH <2 Cool, 4∞C Cool, 4∞C, add 2 mL zinc acetate plus NaOH to pH >9

— 28 d 7d Immediately

Cool, Cool, Cool, Cool, Cool, Cool,

Immediately 48 hr 28 d 28 d 28 d 28 d

4∞C, 4∞C 4∞C, 4∞C, 4∞C, 4∞C,

HCL to pH 2 H2SO4 H2SO4 H2SO4 H2SO4

to pH <2 to pH <2 or HCL to pH <2 to pH <2

The maximum holding time is 24 hr if sulfide is present. Samples may be tested with lead acetate paper to determine if sulfide is present. If sulfide is present, the sulfide is removed by adding cadmium nitrate powder until a negative acetate paper test is obtained. The sample is filtered and NaOH is added until a pH of 12 is attained. b Used only in the presence of residual chloride.

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FIGURE 3.20 Loss of gasoline with time from soil samples. (Adapted from King, A., in Proc. of the National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art and Research Needs, January 12–14, 1993, Las Vegas, NV, sponsored by the U.S. Environmental Protection Agency, American Petroleum Institute, and University of Wisconsin Engineering Extension Program, p. 7.)

The regulatory pre-analytical holding temperature for volatile organic compounds in soil is 4∞C (39.2∞F). A significant body of evidence indicates that this practice results in unacceptably high losses of volatile organic compounds (Jenkins et al., 1993; Maskarinec et al., 1990). Current research suggests that refrigeration at –20∞C (–4∞F) is a more appropriate temperature for soils impacted by volatile organic compounds. Figure 3.20 graphs different concentrations of gasoline from soil spiked with a known concentration of gasoline. Samples were stored according to U.S. Environmental Protection Agency procedures and analyzed for total petroleum hydrocarbons as gasoline (TPHg) from 1 to 14 days after the soil was spiked. As shown in Figure 3.20, the TPH concentration is reduced by one half of the original concentration when analyzed 3 days after storage at 4∞C (King, 1993). Another example is the effect on holding time on toluene in water. Researchers at the U.S. Environmental Protection Agency in Region I found that when a nonacidified water sample was spiked with 300 ppm of toluene, 95% of the sample was lost due to biological degradation after 10 days of storage (see Table 3.9) (Bruya, 1996). For higher toluene concentrations, the loss was less, due to the partially toxic effect of higher levels of toluene on microbes.

3.5.10 FIELD MEASUREMENTS Environmental reports describing field investigations often contain values obtained with X-ray fluorescence or organic vapor meters. Regardless of the equipment, a

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TABLE 3.9 Aerobic Biodegradation of Toluene after 10 Days at Varying Concentrations as Determined Using Gas Chromatography/Mass Spectrometry Initial Concentration (ppm)

Toluene Loss (%)

300 500 1000 2000

95 60 45 40

determination is required concerning the weight given to field measurements and how to use them in concert with other lines of evidence. Descriptions of X-ray fluorescence and organic vapor meters are summarized in Table 3.10. Organic vapor analyzers are used in lieu of laboratory analysis to guide soil excavations on a realtime basis or to select samples for stationary laboratory analysis. The importance of properly calibrating and maintaining this field equipment is critical when relying on these readings for any purpose. Figure 3.21 is an example of a blank multiplecomponent calibration form used for equipment calibration. The qualitative nature of field measurement devices cannot be overemphasized. Figure 3.22 is a plot of 15 organic vapor meter values of soil samples collected and analyzed for total petroleum hydrocarbons as gasoline. The purpose of the OVA measurements was to determine the extent of the soil excavation. The clean-up level was 250 ppm; 11 samples exceeded this value. Fifteen soil samples from the same location were collected during the excavation and tested by a stationary laboratory using EPA Standard Method 8015. Results from the stationary laboratory were provided after the excavation was completed, indicating that, except for five samples, all the samples were less than 250 ppm. The possibility exists, therefore, that some volume of soil was needlessly excavated. In order to confirm this possibility, analysis of the calibration sheets was required to determine if the equipment was properly calibrated. Another example is the relationship between laboratory and headspace analysis for 9 soil samples collected from a manufactured gas plant that were analyzed for BTEX. Values for benzene in parts per million are shown in Figure 3.23. The headspace analysis was performed by piercing the Teflon® septum of the volatile organic analysis vial with a gas-tight syringe, withdrawing between 10 and 400 mL of headspace vapor and injecting this into a portable gas chromatograph equipped with a photoionization detector (Robert and Cutlet, 1989). The generally higher values (5 out of 9) obtained from the laboratory vs. headspace analyses for benzene are believed to be due to differences in the soil/contaminant matrix (i.e., tar and petroleum/soil mixture) and the ability of benzene to volatilize from the matrix.

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TABLE 3.10 Descriptions of Field Equipment Field Equipment

Description and Comments

X-ray fluorescence

X-ray fluorescence (XRF) spectroscopy is a non-destructive qualitative and quantitative analytical technique used to determine the elemental composition of metals (usually in soils, although it is also used for solid, powder, liquid, and thin films or coatings) (Foley, 1998c). The detection limit is usually in the lower parts per million. XRF is based on the bombardment of a sample with photons to produce fluorescence (U.S. EPA, 1997). When interpreting XRF results, examine the equipment calibration charts to confirm that the equipment was properly calibrated. Calibration is properly performed with a full range of target element samples analyzed by atomic absorption or inductively coupled plasma emission spectroscopy (ICAP). A full concentration range of the target element or elements of interest is therefore needed to generate a representative calibration curve. It is recommended that at least five samples per element be used to develop the calibration range.

Photoionization detector (HNu™)

The HNu ™ photoionization detector is a portable, nonspecific, vapor/gas detector that uses photoionization to detect a variety of organic and inorganic volatile compounds. The HNu ™ utilizes two different source lamps for photoionization: a 10.2- or 11.7-eV lamp. An HNu ™ is incapable of detecting compounds with photoionization potentials below 10.2 and 11.7 eV, such as methane. If the lamp window of an HNu ™ meter is not periodically cleaned, complete ionization of the air contaminants may not occur, resulting in biased values. Measurement errors can occur if the probe is held close to an AC power line or transformers. The device should be calibrated daily with a commercially prepared standard (usually 100 ppm of isobutylene). When relying upon HNu™ measurements, obtain the calibration charts to confirm that calibration occurred. If the battery charge is low, the instrument should be recharged before making any measurements, as a low battery can impact the measurement results.

Organic vapor analyzer (OVA)

The OVA has an application similar to the HNu™ for detecting organic vapor meters, but uses a flame ionization detector (FID) rather than a photoionization detector (PID). An organic vapor analyzer provides a measurement of the combined concentration of organic vapors. An organic vapor analyzer has an ionization potential of 11.9 cV and can detect more compounds than an HNu™. Some organic vapor analyzers are equipped with an optional gas chromatograph that allows identification and measurement of specific compounds. An organic vapor analyzer responds differently to different compounds. Because the instrument is factory calibrated to methane, all responses to various compounds are given in percent relative to methane at 100%.

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FIGURE 3.21 Example of an organic vapor analyzer calibration sheet.

3.5.11 FIELD QUALITY CONTROL SAMPLES Quality control samples are used to assess sampling problems such as field contamination from incomplete decontamination or cross-contamination, container crosscontamination, and atmospheric contamination. Common field quality assurance/ quality control samples and their functions are summarized in Table 3.11 (Mabey, 1996; Simes and Harrington, 1993).

3.6 SOIL VAPOR SURVEYS Soil gas surveys were used as early as 1929 as a surface geochemical technique in oil and gas exploration. This technology evolved in environmental investigations as

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FIGURE 3.22 Graph of organic vapor analysis vs. laboratory values for total petroleum hydrocarbons as gasoline.

a means to measure the soil atmosphere as an indicator of the presence, composition, and origin of contaminants in the unsaturated and saturated (groundwater) zones. Soil gas measurements do not permit quantifying soil or groundwater contamination (Robbins et al., 1990). The primary use of soil gas surveys is as a screening method for detecting volatile organic contaminants. Soil gas surveys are traditionally used to provide the following information:

FIGURE 3.23 Comparison of headspace and laboratory results for benzene for nine soil samples.

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TABLE 3.11 Quality Assurance and Quality Control Field Samples QA/QC Samples

Description and Comments

Background sample

A sample taken from characteristics of the media which is sampled at a site but which is outside the zone of contamination. A minimum of two per sampling event is recommended by the U.S. Environmental Protection Agency (U.S. EPA, 1987). Literature or monitoring data should be consulted to determine appropriate background locations. Historical aerial photographs are useful in verifying undisturbed conditions in an area selected for collecting background samples. Ideally, a soil background sample is collected in similar textured materials and at a depth comparable to the on-site samples.

Field blank

A container, usually filled with distilled water from the analytical laboratory, that is opened at the site when sampling occurs. In some cases, it remains opens throughout the time that the sampling team is at the site. The inclusion of a field blank is crucial in deciphering if the contamination is from in situ materials or from the ambient environment.

Field duplicates

Homogenized samples from a single location used to assess the quality of sampling methods and handling. Field duplicates are used to check laboratory procedures. The U.S. Environmental Protection Agency recommends one field duplicate sample for every ten samples collected; if the samples are used as evidence in litigation, a higher number of duplicates may be selected (U.S. EPA, 1987). Split samples are submitted to multiple laboratories and evaluated to determine agreement in accuracy and precision among the labs.

Field reagent blank

Solutions used in the field and submitted to a laboratory for analysis. A field reagent blank evaluates chemicals introduced from the use of field chemicals.

Equipment rinsate blank

Sample of the last decontamination liquid poured over equipment prior to contact with a sample. The U.S. Environmental Protection Agency recommends that equipment rinsate blanks be collected at a rate of one blank for every ten samples collected or one per day (U.S. EPA, 1987).

Matrix spike duplicate (MSD)

A sample that is three times the normal volume required for a specific chemical analysis. One MSD sample per matrix is collected for every 20 samples. A matrix spike duplicate is a second aliquot of sample (matrix) that is spiked and subjected to the same procedure as a matrix spike. The results are used to measure precision.

Matrix spike samples

Samples to which a known quantity of a chemical constituent is added. They are sent to the laboratory without informing the laboratory that the samples were spiked. Sample spiking is undertaken to measure the laboratory’s ability to measure accurately a constituent of concern. In general, one spiked sample per 20 water samples is appropriate.

Trip blank

Used to evaluate the possible introduction of cross-contamination during transit and storage, a trip blank is a sample of laboratory-grade distilled water that is poured into a sample container at the laboratory. The trip blank follows the sample containers, coolers, and samples throughout the field event. The trip blank measures the amount of volatile contaminants absorbed through the container in the field. The trip blank sample is sent to the laboratory at the end of the sampling event. The U.S. Environmental Protection Agency recommends one trip blank per sampling event. If multiple sampling activities occur over a large area, one trip blank per sampling location or one per shipping container is appropriate. The detection of a compound in a sample is considered valid if the concentration is greater than the amount detected in a trip blank.

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FIGURE 3.24 Example of an active soil gas sampler probe.

• • • • •

Identify and assess the distribution of a contaminant present in the soil vapor phase. Approximate the location of soil contamination. Assess the distribution of groundwater contamination. Evaluate the potential risk of upward transport of vapors. Monitor the progress of in situ remediation.

The three types of equipment used to collect soil gas samples are active (Figure 3.24), passive, and flux chambers. An active soil gas survey consists of the withdrawal of an aliquot of soil vapor from the subsurface, typically with a perforated sampling probe, followed by analysis in a mobile laboratory. Vapor analysis is performed with a gas chromatograph and the results reported in units of parts per million in vapor (ppmv). Soil samples can also be collected within a glass or metal container (summa canister) and transferred off-site to a stationary laboratory. This is the most popular soil vapor method due to the availability of companies providing this service and relatively low cost. Active surveys are conducive to locations with highly permeable soils (i.e., high gas permeability) and high concentrations of a volatile compound(s). Passive soil gas surveys are designed for shallow deployment to identify a broad range of volatile and semivolatile organic compounds (Foley, 1998a,b). The adsorbent (usually composed of polymeric and/or carbonaceous resins) is buried 2 to 3 ft below the subsurface. The adsorbent is typically removed in 1 to 2 weeks for extraction and analysis by a stationary laboratory (Tetra Tech, 1998). Reported advantages include smoothing of daily fluctuations in soil gas concentrations due to climatic factors and the collection of a time-integrated sample. Passive technique results are reported only as the total adsorbed mass because the amount of vapor that comes into contact with the absorbent is unknown. Soil gas results, therefore, cannot

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TABLE 3.12 Mean Chemical Concentrations for TCE and PCE Collected with Passive and Active Soil Gas Sampling Methods TCE

PCE

Passive (m mg/Sample)

Active (ng/L)

1.97 108 195 34.8 <0.02 255 318 252 217

<50 1250 9.390 2010 NAa 41,800 89,500 22,200 11,500

a

Passive (m mg/Sample) 0.06 1.02 0.42 0.08 <0.03 411 341 351 327

Active (ng/L) <50 <50 <50 <50 NAa 330,000 223,000 192,000 98,500

NA = not analyzed.

be correlated to soil contamination, the presence of a vapor cloud, or groundwater and/or free product contamination. Trip blanks used for passive soil gas modules are manufactured and packaged the same as soil gas modules placed in the subsurface. The trip blanks, however, remain unopened during all phases of the soil gas survey. In the 1980s, passive soil gas data were obtained primarily from Petrex tubes. Petrex samplers contained a thin ferromagnetic (Curie-point) wire coated with activated charcoal. The wire accumulator is housed within a glass tube (Petrex tube) and buried 6.5 inches below the ground surface for several weeks. When the sample is retrieved, the wire is placed into a vacuum chamber and heated, and the volatile compounds are analyzed by Curie-point mass spectrometry and reported in ion counts. Mean chemical concentrations of data collected with passive and active soil gas sampling methods and tested for PCE and TCE are summarized in Table 3.12. Samples were collected from sites located in Albert City, IA, and Denver, CO (Tetra Tech, 1998). Given that the passive sampler yields results in micrograms per sample and the active soil gas survey produces results in nanograms per liter, a statistical and interpretative comparison of the data is limited to qualitative observations. The higher concentrations obtained with the active soil gas survey may be due to extraction from the polymeric or carbon resins which occurs via placement of the absorbent into a jar from which a headspace analysis is performed. Flux chambers consist of an enclosed chamber that is placed on the ground surface for a specific time period and in which vapor concentrations are measured through time (Figure 3.25). The chamber is equipped with ports for sweep air inlet and outlet, thermocouples for measuring the inside air and surface temperature, and pressure outlets. Flux chamber measurements are common in research applications,

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FIGURE 3.25 Flux chamber used for soil gas measurements. (From ASTM, ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, 1997, p. 211. With permission.)

risk assessments, and toxicological studies when direct vapor fluxes out of the subsurface are required (ASTM 1997b; Hartman, 1998c). For the latter, the emission rate (ER, expressed in mg/min/m2) for a species is equal to (Q)(CI)/A, where Q is the sweep air flow rate (m3/min), CI is the concentration of the contaminant (mg/m3), and A is the sampling area (m2). The term “sweep air” refers to air that is fed into the chamber at a metered flow rate (e.g., 5 L/min or a chamber retention time of about 6 min) and is then withdrawn until steady-state conditions are attained within the chamber. Volatile compounds amenable to detection in a soil gas survey are identified by examining their partition ratio values. Soil/air partitioning is the process by which volatile compounds move between the sorbed phase and a vapor phase. A general rule is that compounds with a Henry’s Law constant of at least 0.05 kPa/m3/mol and a vapor pressure of 1.0 mmHg at 20∞C or greater are amenable to a soil vapor survey (Marrin, 1988). Compounds with low Henry’s Law values do not readily partition out of the aqueous phase into vapor. Another means to identify candidates conducive to soil gas sampling is to identify compounds with partition ratios above 0.1 (Erickson and Morrison, 1995). Table 3.13 lists the partition ratios for commonly encountered volatile compounds.

3.6.1 INTERPRETATION OF SOIL VAPOR DATA A common error associated with soil gas data is confusion about the reported units. Soil gas data are usually reported on a volume-per-volume basis (volume of contaminant per volume of soil air) and mass per volume (mass of contaminant per volume of soil air). Examples of volume-to-volume and mass-per-volume relationships are provided in Table 3.14 (Hartman, 1998b).

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TABLE 3.13 Partition Ratios of Volatile Compounds Compound Methane Ethane Freon-12 Vinyl chloride Cyclohexane Freon-11 1,1,1-TCA Tetrachloroethylene Carbon tetrachloride Trichloroethylene Ethylbenzene Toluene Benzene Xylene Chloroform 1,2-Dichloroethane Bromoform

Partition Ratio 7982.99 874.02 108.87 105.11 8.55 4.86 1.35 1.29 0.88 0.52 0.39 0.30 0.25 0.24 0.17 0.05 0.03

In most cases, soil vapor data reported in mg/L is assumed to be equivalent to parts per billion. While correct for water due to the density of water being equal to 1 gram per milliliter (g/mL), it is not correct for soil gas data. The conversion of vapor data from units of mg/L to ppbv is (Hartman, 1998b): Csoil gas (ppbv) = (Csoil gas [mg/L] ¥ 24,000)/molecular weight of the compound where the 24,000 is the milliliters per mole at 20∞C. For example, the molecular weight of PCE is 165, so 1 mg/L is equal to about 145 ppbv. Soil samples collected

TABLE 3.14 Units Used in Soil Gas Surveys Volume-by-volume basis Microliters of compound per liter of soil air (mL/L) Nanoliters of compound per liter of soil air (nL/L) Parts per billion by volume (ppbv) Parts per million by volume (ppmv) Percent by volume (%) Mass-per-volume basis Micrograms of compound per liter of soil air (mg/L) Milligrams of compound per cubic meter of soil air (mg/m3) Millimoles of compound per cubic meter of soil air (mmol/m3)

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Surface

Deep

Surface and Deep

Co-mingled

FIGURE 3.26 Plot of soil vapor data with depth. (Adapted from Hartman, B., MTBE: Beware the False Positive, LUSTline Bull. No. 26, New England Interstate Water Pollution Control Commission, Wilmington, MA, 1998, p. 18. With permission.)

at multiple depths can be plotted as a function of concentration vs. depth. Figure 3.26 depicts four common scenarios and corresponding interpretations regarding the origin of the contamination. Numerous factors affect the observed distribution of the volatile organic compounds in soil gas. Considerations in the interpretation of soil gas data include the following variables: • • • •

• •

•

•

Presence of contamination at the capillary fringe Liquid/gas partitioning coefficient of the compound(s) detected Velocity or vapor diffusivity of the compound Preferential migration of vapor through soil with different gas permeabilities such as high gas-permeable bedding in utility line trenches or road beds — examples of the gas permeability (in cm/sec) of various soils include gravel, 103 to 10; clean sand, (10 to 10–2; silty sand, 1 to 10–3; loess, 10–1 to 10–5; and glacial till, 10–2 to 10–9 (Peargin, 1994) Vapor retardation and/or biodegradation Presence of low gas permeability (also called pneumatic permeability) layers such as moist silt or clay layers, caliche horizons, a perched water table, or barriers such as building foundations and high moisture content soils caused by uneven surface irrigation Presence of contaminants from discrete surface releases and soil gas displacement via wetting fronts from recharge events or as a result of barometric pressure changes (storm fronts) Comparison of shallow soil gas data collected on different days with significant ambient air temperature differences

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In addition to these issues, differences in the type of data obtained with the specific types of soil gas survey equipment must be considered. Issues specific to passive and active surveys are summarized in Table 3.15 (Hartman, 1999). While it is important to collect sufficient vapor to purge the system, collecting excessive volumes is discouraged. The larger the soil vapor volume withdrawn, the greater the uncertainty regarding the origin of the sample. This subsequently increases the potential that atmospheric air is drawn down the outside of the probe body. Sampling equipment with small internal volumes offers advantages over systems with larger empty volumes, because the former systems require significantly less vapor to be withdrawn.

3.7 ANALYTICAL METHODS The selected analytical method determines what can be identified relative to the goal of the sampling and analysis (e.g., remediation, forensic analysis, cost allocation). The axiom — “What you find is what you look for” — is true for the selection of an appropriate analytical method given the chemical usage history at the site. The first level of analysis is to examine the analytical methods used and compare it with the known chemicals used at a site. The second level of analysis includes examination of the following six sources of potential bias from the analytical measurement process (Mishalanie, 1995): • • • • • •

Misidentification of compounds (false and negative bias) Chemical interference (false and negative bias) Incomplete recovery of analytes from the sample matrix (negative bias) Matrix effects (false and positive bias) Instrumentation calibration (false and positive bias) Cross-contamination (positive bias).

An example of the impact of analytical methods on sample results is the analysis of methyl-tertiary-butyl-ether (MTBE). There currently is no official U.S. Environmental Protection Agency standard method for MTBE analysis (Draper et al., 1998). For MTBE analysis using EPA Standard Method 8020, shortened run times (i.e., 20 to 10 minutes) can result in the co-elution of alkane compounds that elute similarly to MTBE being reported as MTBE (false positive). EPA Standard Methods 8240 and 8260 are gas chromatography methods using a mass-selective detector that can quantify MTBE and other compounds that co-elute with it; as a result, these methods tend to be more reliable. A solution is to use a combination of these methods; EPA Standard Method 8020, for example, is appropriate if the results are non-detect. MTBE values from samples with total petroleum hydrocarbon (TPH) as gasoline less than 5 ppm (water) and 100 mg/kg (soil) are more likely to be reliable because low values of the co-eluting alkanes are likely (Hartman and Hitzig, 1998). As gasoline values increase, the potential for over-reporting MTBE values also increases. Confirmation testing using EPA Standard Method 8020 with a sufficiently long run time

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TABLE 3.15 Effects of Soil Gas Sampling Equipment on Sample Results and Interpretation Passive Soil Vapor Surveys

Considerations

Sample spacing

The selection of sampling locations for passive soil vapor surveys is predicated on considerations identical to those used in active soil vapor methods. These include the program objectives, the need for adequate spatial coverage, and the budget. Predetermined and widely spaced grid patterns are commonly employed for reconnaissance work, while higher density, irregularly situated locations are used to bracket specific source areas.

Collection depth

Passive collectors are buried near the ground surface (6 inches to 3 feet). This procedure originates from the convenience in deploying and retrieving the collector. Ideally, similar to active surveys, collectors are located close to the suspected contamination source to minimize the effects of vapor movement. Collectors buried within several feet of the ground surface are susceptible to air infiltration due to changes in barometric pressure and surface temperature. If the ambient air is contaminated (e.g., at an operating gasoline station or inside of a drycleaning operation), the collector can conceivably adsorb more contamination from infiltration of the surface air than from subsurface contamination. In this situation, it is advisable to bury the collector deeper than 3 feet below the ground surface.

Exposure period

The exposure period for passive collectors is generally selected more for convenience than for technical reasons. An assumption inherent with the interpretation of passive soil gas data is that the each collector is exposed to the same quantity of soil vapor. Passive collectors are typically deployed for the same period (several days to three weeks) so that the data are normalized based on the exposure time. The exposure period for a passive collector can depend on the concentration of the contaminant of interest and the desired detection levels. In areas of suspected high concentration, collectors remain in the ground for shorter periods (1 to 5 days) relative to areas of suspected low concentrations (2 to 3 weeks).

Method blanks

Because the passive soil vapor method does not enable real-time data to be collected, analysis of method blanks is important to verify that detected contamination is not from another source; therefore, a method blank or trip blank should be included as part of the sample batch. If data from method and/or trip blanks are unavailable, it is possible that values from the collectors can be argued as being due to contamination from other sources.

Active Soil Vapor Survey Sample spacing

Considerations The selection of sampling location is dependent on the objectives of the program, the need for adequate coverage, and the budget. Predetermined and widely spaced grid patterns are commonly used for reconnaissance work, while closely spaced, irregularly situated locations are used for identifying specific source areas.

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TABLE 3.15 (cont.) Effects of Soil Gas Sampling Equipment on Sample Results and Interpretation Active Soil Vapor Surveys

Considerations

Collection depth

Collection depths should maximize the probability of detecting contamination, yet minimize the effects of vapor movement, changes in barometric pressure, surface temperature, or breakthrough of atmospheric air from the surface. To optimize the probability of contaminate detection and minimize biases associated with vapor movement, soil vapor samples are collected as close to the suspected contamination source as possible.

Probe seals

For collection systems with large purge volumes or designed to collect large sample volumes, it is often necessary to seal the probe at the ground surface. Surface seals are necessary for small volume systems if the soil is highly porous and the sampling depth is close to the ground surface (approximately 3 ft). Common sealing techniques include packing the upper contact of the probe and the soil with grout or the use of an inflatable seal. Seal integrity is tested with a tracer gas (e.g., propane or butane) that flows around the probe at the contact point with the ground surface. A soil vapor sample is then collected and analyzed for the presence of the tracer compound.

Probe decontamination

All external parts should be wiped clean and washed as necessary to remove any soil or contaminant films. The internal vapor pathway should be purged with a minimum of five volumes of air or an inert gas, or replaced or washed if contamination or water is present in the probe. Probes fitted with internal tubing offer advantages because the internal tubing can be replaced.

Excessive vacuums applied during during sample collection

Soil vapor samples collected under high vacuum conditions may reflect contaminants that are desorbed off the soil grains created by the collection process, rather than contaminants present in the undisturbed soil vapor. For collection systems employing vacuum pumps, the vacuum applied to the probe should be measured and recorded.

Systems with vacuum pumps

Soil vapor samples from collection systems employing vacuum pumps should be collected on the intake side of the pump to prevent potential contamination from the pump. Because the pressure on the intake side of the pump is below atmospheric, soil vapor samples must be collected with appropriate collection devices, such as gas-tight syringes and valves, to ensure that the samples are not diluted by outside air.

Sample containers/ sample storage

On-site analysis is recommended to ensure sample integrity. Soil vapor samples, however, are often collected and analyzed off-site. To minimize potential effects on sample integrity, the maximum storage time should be no more than 48 hr after sample collection. For fuel-related compounds (e.g., BTEX) and biogenic gases (methane, carbon dioxide, and oxygen), only the following containers are allowable: Tedlar bags, gas-tight vials (glass or stainless steel), and summa canisters.

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TABLE 3.15 (cont.) Effects of Soil Gas Sampling Equipment on Sample Results and Interpretation Active Soil Vapor Surveys Purge volume

Considerations Sample collection equipment used for active soil vapor surveys has an internal volume filled with air or some inert gas prior to insertion into the ground. This internal volume must be completely purged and filled with soil vapor to ensure that a representative soil vapor sample is collected. While different procedures are available for obtaining the optimum purged volume, sufficient vapor should be extracted prior to sample collection to purge the probe and collection system of all ambient air or purge gas (one purge volume). Another procedure specifies the removal of four system volumes. Most samplers purge a minimum of one to five system volumes prior to sample collection. Because soil vapor data are interpreted qualitatively, the purge volume should be consistent for all samples collected from the site.

or by GC/MS is one option. Another reported technique is a modified ASTM Method D4815 that was specifically designed to test for MTBE, ETBE, and TAME, as well as methanol, ethanol, and tertiary-butyl alcohol in soil and groundwater (Global Geochemistry, 1998).

3.7.1 MISIDENTIFICATION OF ANALYTES The misidentification and laboratory misrepresentation of compounds is common. A report performed by the Advancement of Sound Science Coalition for the U.S. Environmental Protection Agency found that 11% of 2000 reports showed “serious deficiencies” with pesticide testing (Meyer, 1999). In some cases, fraud is the culprit, such as in the case of the United States v. Hess Environmental Laboratories and United States v. Klusaritz, where the director of a testing laboratory accepted payment for fabricated data from testing that was not performed. Numerous reasons for misidentification are possible, including the co-elution of compounds (e.g., dibromochloromethane, dichloropropene, and 1,1,2-trichloroethane). Laboratories may automatically assign the name of a product type of material that elutes within a given carbon range or retention range — results reported as in the “gasoline range” are not the same as “gasoline”. Another example is shown in Table 3.16 for TPH analysis for gasoline and diesel using a gas chromatograph equipped with a flame ionization detector (Bruya, 1994; 1998). These test results were performed according to standard state- and U.S. Environmental Protection Agency-mandated total petroleum hydrocarbon testing protocols. If the purpose of these data is to demonstrate that common plants contain organic

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TABLE 3.16 Total Petroleum Hydrocarbon Values in Various Materials Matrix Spinach Carrots Orange juice Cedar tree Pine tree Dandelion Daisy Moss

TPH as Gasoline (ppm)

TPH as Diesel (ppm)

<10 <10 300 1400 450 <10 40 <10

60 10 <10 2200 400 140 40 <10

compounds that boil in the same boiling ranges associated with gasoline and diesel, then the data are usable. If the goal is to identify the type of blended fuel for remediation purposes, the value of the data is questionable. The selected extraction method can bias sample results. For example, for TPH analysis, an acetone/methylene chloride extractant is more rigorous than methanol; the former extractant extracts more hydrocarbons from the sample, resulting in a higher sample concentration. The extractant used is often selected from among several recommended compounds. The use of multiple laboratories in a project can produce dramatically different analytical and interpretative results. A 10 to 20% variation in reported concentrations for the same sample (spiked concentration) tested by several laboratories is not uncommon. The presence of laboratory contaminants should also be examined. Common laboratory contaminants and sources are listed on Table 3.17 (Erickson and Morrison, 1995; Mabey, 1995). Benzene, toluene, ethylbenzene, and xylene (BTEX) are common laboratory artifacts due to the large volume of BTEX analyses processed through many laboratories.

3.7.2 LABORATORY DOCUMENTATION The underlying laboratory documentation is required for forensic review of chemical data, including judging the validity of reported analytical results (Maney and Wait, 1991; Zurer, 1991). Depending on the level of review required, the following information can be requested or subpoenaed from the laboratory (Rosecrance et al., 1988). 3.7.2.1 Chain of Custody A copy of the chain of custody is available from the laboratory that performed the analysis as well as the firm that performed the sampling if it was not the laboratory. A chain of custody form provides evidence concerning sampling procedures and

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TABLE 3.17 Common Laboratory Contaminants and Sources Compound

Potential Source

Methylene chloride, MEK, Freon-113 (1,1,2-trichlor-1,2,2-trifluoroethane), chloroform, carbon tetrachloride bis(2-Ethylhexyl)phthalate, di-butylphthalate, adipates Trihalomethanes N-Nitrosodiphenyl amine Toluene 2-butanone (MEK) Acetone, isopropyl alcohol Carbon disulfide, methyl chloride Fluorobenzene, chlorobenzene-d5, 1,4-dichlorobenzene-d4 Bromofluorobenzene; 1,4-difluorobenzene, chlorobenzene-d5 Dibromofluoromethane; 1,2-dichloroethane-d4, toluene d8, 4-bromofluorobenzene

Laboratory solvents

Tubing plasticizers Domestic water Rubber additive (diphenyl amine). Electrical tape Duct tape Field decontamination solvent, drilling aid Natural products Laboratory internal standardsa Laboratory matrix spikes used for volatile organic tests (Bruya, 1994). Laboratory system monitoring compoundsb

a

Internal standards are typically analytes of interest that are spiked into a blank prior to analysis for the purpose of measuring the accuracy of the measurement. b

System-monitoring compounds used by laboratories in volatile compound analyses; detection of these chemicals is usually only considered positive when their concentrations are greater than ten times the amount detected in any blank samples.

sample integrity. A sample chain of custody is a form that documents the collection and possession during each stage of sample collection, shipment, storage, and the process of analysis. The review of the chain of custody is important because it provides information concerning the temporal sequence of sampling, the personnel responsible for sampling, and a means to evaluate if holding times were exceeded. A standard guide for chain of custody procedures has been established by the American Society for Testing Materials (ASTM, 1995). While the chain of custody form differs depending upon the organization, the basic format and information required are similar. This information includes: • Sample identification • Sampling location, sampling point, date, and sampling date interval • Signatures of sampling personnel and signatures of all personnel handling and receiving the samples • Project identification • Sample preservation (type and concentration) • Number of containers and their volume • Air bill or carrier identification • Analyses desired along with specific instructions (e.g., accelerated analyses) • Sample type (e.g., grab, composite)

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When the analytical laboratory takes possession of the samples, they should acknowledge receipt on the primary laboratory chain of custody form. At that point, the recipient should inspect the condition of the samples and reconcile the sample labels with the chain of custody information. While in the custody of the laboratory, the analyst should be able to testify that no one tampered with the samples without their knowledge. The samples should be stored in a secure (preferably locked) environment prior to analysis. If the primary laboratory is subcontracting to another laboratory for specialized testing, the chain of custody should remain with the primary laboratory. The prime laboratory should prepare a receipt providing information about which samples are being split, where they were delivered, the time and date of the transfer, and the persons involved with the transfer. When reviewing a chain of custody form, examine whether more than one person has handled the samples; ideally, the assigned field sampler should be personally responsible for the care and custody of the samples until they are surrendered to the laboratory. The sample is considered to be in the sampler’s custody if the following criteria are met (U.S. EPA, 1995): • The sample is in the possession of the sampler or is in view after collection. • The sample was in the sampler’s possession and then locked up or sealed in a manner to prevent tampering. • The sample is in the sampler’s possession and then placed in a secure area.

When transferring sample possession, the individuals relinquishing and the individuals receiving the samples should sign, date, and note the time on the custody record. If the ice chest or other shipping container was opened, it should be noted on the chain of custody. The field personnel whose signatures are on the chain of custody should be able to testify that no one was able to tamper with the samples without their knowledge. Review the chain of custody to determine the condition of the ice chest upon receipt by the laboratory. The sequence of the sampling is also worth noting (see Section 3.5.6). For example, if cross-contamination is suspected, knowing whether suspected cross-contaminated samples were collected after a sample with a significant contaminant concentration was sampled may assist in this examination. The use of custody seals is recommended when the results are used in litigation. A custody seal has the sample number, date of collection, and the signed and printed name of the sampler. The seal is placed over the sampling cap so that anyone opening the sample container breaks the seal. Custody tape is wrapped around the shipping container and similarly dated and signed by the person in whose custody the samples have remained. If the sample containers or shipping container are tampered or violated in some manner, the analytical laboratory can record this violation. The chain of custody is placed within a Zip-Lok™ bag within the shipping container to prevent melting ice from obscuring the ink on the form. A chain of custody form also originates with the laboratory that prepared the sample containers. Each time samples are exchanged, the chain of custody form is

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signed. Security seals can be placed over the caps of empty, clean sample containers or blanks and signed by the laboratory that prepared the containers. The person who broke the laboratory security seals should be able to testify as to when this occurred. The field logbook should also contain this information. 3.7.2.2 Document Control/Control Log A document control log contains a list of all laboratory documents such as logbooks, forms, quality assurance manuals, standard operation procedures for the laboratory, and software. A document control log includes the title of the document, the assigned document control number, assigned field or laboratory section, location or personnel, the date issued, and the date archived. 3.7.2.3 Signature List A signature list contains the record of the signatures and initials of all personnel that completed log records or approved data. The signature list includes each employee’s typed or printed name and initials, a handwritten signature and initial, the employment start date, and termination date (if applicable). Temporary employees are included on the signature list. 3.7.2.4 Logbook Cover Sheet The logbook cover sheet documents the purpose of the logbook and contains the document control number. The logbook cover sheet includes the document control number, analytical methods and parameters, instrument identification (if applicable), and date issued. 3.7.2.5 Sample Kit Preparation Log Sample kit preparation logs document the preparation of sample bottles and sampling kits. Kit preparation logs include the following information: • • • • •

Project identification and sample kit identification Type of bottles and lot number, if certified bottles are used Intended analysis to be performed for samples placed into each bottle or vial Preservatives and reagent in the sample containers Preparation of field and trip blanks

3.7.2.6 Field Logs Field logs document events associated with sample collection. If personnel from the laboratory performed the sampling, the laboratory maintains the field log. Field logs contain a detailed chronology on numbered log pages that contain information such as sample location, time of sample location, atmospheric conditions, sampling descriptions such as odors and colors, field measurements, and any difficulties in

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TABLE 3.18 Examples of Information in a Field Logbook Well identification Well depth Static water level depth and measurement techniques Presence of immiscible layers and instrument/detection method used Well yield (high or low) Purge volume and pumping rate Time well purged Collection method for immiscible layers and sample identification number(s) Well evacuation procedure/equipment Sample withdrawal procedure/equipment Date and time of collection Well sampling sequence Types of sample containers used and sample identification numbers Preservative(s) used Parameters requested for analysis Field analysis data and method(s) Sample distribution and transporter Field observations during sampling Name of collector Climatic condition Internal temperature of field and shipping (refrigerated) containers Shipper and shipping number Photograph identification, photographer and orientation

obtaining samples or unusual circumstances. An example of information included in a field logbook used to record a groundwater sampling event is shown in Table 3.18. 3.7.2.7 Sample Receipt Checklist and/or Log Sample receipt logs are used to evaluate and document the condition of a sample received by the laboratory. Information contained on the sample receipt checklist includes: • • • • • • • • • •

Client sample identification Laboratory sample identification Presence or absence of custody seals Acceptability of sample container for the analysis requested Volume and preservation (if any) Sample condition at receipt Temperature of the ice chest Presence or absence of headspace in samples submitted for volatile organic analysis Assigned number used by the laboratory in their computer tracking system Any discrepancies between the chain of custody record and sample labels

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A laboratory phone log may be available if the laboratory contacted the client regarding unacceptable samples and/or on a sample condition notification form. The sample condition notification form documents and communicates to the client any noncompliance with the sample condition at the time of receipt by the laboratory, such as: • • • •

Broken bottles Headspace in volatile organic vials Sample labels not matching the chain of custody Incorrect sample containers for the analysis requested

Directions from the client in response to any noncompliance issues are recorded on the sample condition notification form. 3.7.2.8 Sample Preparation Logbook This log documents sample preparation activities such as sample extractions and/or metal digestions. Information includes the sample number, sample type or matrix, parameter and method number, date and time of preparation, the analyst’s signature, initial and final sample volume or weight, the volume and identification of spikes, and surrogate and quality control samples included in the sample batch. 3.7.2.9 Sample Analysis Log This logbook contains information pertaining to the analysis and calculation of the final sample result. Data recorded in this log include the following: • • • • • • • • • • • • • • •

Sample identification number Parameter/analyte to be tested Analytical method number Sample matrix Instrument identification Reagent and calibration standard identification Date and time of analysis The analyst’s signature Sample aliquot Dilution factors and final dilution volumes (if any) Calibration data Calibration correlation coefficient Percent recovery for laboratory control standards and matrix spikes Comments on reruns Unusual observations noted during analysis

3.7.2.10 Instrument Run Log This log maintains an accurate record of the analysis of the calibration standards, field samples, and quality control samples processed during an analytical run. This

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information is included in a contracts laboratory program (CLP) documentation package. 3.7.2.11 Instrument Maintenance Log This log documents the maintenance and repair activities performed on major instruments. This log usually contains the instrument name, manufacturer, model and serial number, date received and placed into service, service contract information, and the date, time, and description of each maintenance activity. The initials of the person who performed maintenance or repair activity on the equipment are usually included on the log. The routine and periodic equipment maintenance record for 30 days prior to sample analysis should be provided to determine whether the analytical equipment was properly maintained. 3.7.2.12 Certificates of Analysis Certificates of analysis for standards and reagents are provided by the manufacturer to document the lot number, composition, purity, and grade of the material. The laboratory should produce this information if issues regarding the integrity of the calibration standards arise. If a CLP data format is produced, the lot numbers associated with the various reagents are identified and further review of the supplier and purity of the standard can be examined. It is not uncommon that reagents used in instrument and sample calibrations are purchased from 40 to 50 different suppliers. If a non-CLP laboratory package is not available, the production of this information is usually burdensome and time intensive. 3.7.2.13 Laboratory Certification Laboratory certification (state and federal) and a laboratory’s internal quality assurance/quality control package should be requested to ensure that the laboratory is certified to perform the requested tests.

3.7.3 LABORATORY QUALITY CONTROL SAMPLES The U.S. Environmental Protection Agency has created a structured process that identifies data quality objectives for accuracy, precision, sensitivity, representativeness, comparability, and completeness. Environmental reports routinely contain the sample quality assurance/quality control (QA/QC) procedures associated with the analytical laboratory. Laboratory QA/QC samples allow evaluation of instrument and laboratory performance in addition to providing a means to determine the quality of the analyses. Terminology and definitions used in QA/QC reports are summarized in Appendix F. Table 3.19 summarizes laboratory QA/QC samples. A reporting item for internal analytical control and included in laboratory packages is the percent recovery of the matrix spike. For example, if bromofluorobenzene

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TABLE 3.19 Description of Laboratory Quality Assurance/Quality Control (QA/QC) Samples QA/QC Sample

Description and Comment

Duplicate sample

Subsamples or aliquots obtained from a sample. A duplicate sample is a measure of the precision of analysis in terms of relative percent difference (RPD).

Instrument blank

An analyte-free sample introduced at the point of detection or measurements for the purpose of evaluating potential artifacts from the instrument or detection system.

Laboratory reagent blank

Reagents used in the laboratory to analyze for the analytes of interest for the purpose of evaluating the introduction of chemicals via the use of laboratory reagents.

Matrix spike (MS) sample

A measure of the method used relative to the sample matrix.

Matrix spike/duplicate (MSD) sample

An MSD sample is collected from a matrix spike sample and measures the precision of analysis in terms of the RPD.

Method blank, reagent blank

Laboratory-grade water or clean soil that is analyzed with the soil or water samples. It provides a measure of interferences introduced by laboratory practices; one method blank per ten samples is required. Some laboratories may perform multiple analyses of a method blank until contaminants are non-detected. If this is suspected, obtain the results of these multiple analyses.

Method spike

Laboratory-grade water that is spiked with the analyte of interest to monitor the accuracy of the laboratory performance.

Performance sample

A quarterly or biannual performance evaluation performed by the Environmental Protection Agency or the National Bureau of Standards.

is added to the sample and less than 70% of it is recovered, then the analysis may be interpreted as inadequate. In order to determine if a surrogate standard falls within an acceptable accuracy and precision limit, perform the following procedure: 1. Calculate the percent recovery of each surrogate in each sample. A surrogate is a compound not normally found in an environmental sample which is spiked into matrix or blank samples and then subjected to the entire preparation/analysis procedure to measure recovery. Surrogate results are used to measure accuracy. 2. Once 30 samples of the same matrix are analyzed, calculate the average percent recovery and standard deviation of the percent recovery for each surrogate. 3. For a given matrix, calculate the upper and lower control limit for method performance for each surrogate standard as follows: upper control limit (UCL) = average percent recovery plus 3 standard deviations, and the lower control limit (LCL) = average percent recovery minus 3 standard deviations. 4. Compare to the control limits in Table 3.20.

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TABLE 3.20 Analytical Control Limits for Selected Surrogate Chemicals Surrogate Compound

Low/Medium for Water

Low/Medium for Soil/Sediment

86–115 76–114 88–110

74–121 70–121 81–117

4-Bromofluorobenzene 1,2-Dichloroethane-d4 Toluene-d8

TABLE 3.21 Acceptance Limits for Duplicate or Matrix Spikes in Groundwater Samples Compound Metals Volatile organic compounds Anions Nutrients Herbicides

Recovery of Matrix Spike (%) 80–120 70–130 80–120 70–130 40–160

While the acceptance limits for the recovery of a matrix spike varies between state and federal programs, typical acceptance limits for duplicate or matrix spike samples for groundwater are shown in Table 3.21. If a significant number of the samples are outside of these deviation standards for various compounds, the reasons for these errors, deficiencies, or analytical reasons should be investigated and documented and a judgment made as to the reliability of these data.

REFERENCES ASTM, 1997a. Specific waste Sampling procedures, in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 558–658. ASTM, 1997b. Standard guide for soil gas monitoring in the vadose zone (D 5314-92), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 185–215. ASTM, 1997c. Standard guide for direct-push water sampling for geoenvironmental investigations (D 6001-96), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 444–457. ASTM, 1997d. Composite sampling and field subsampling for environmental waste management activities (D 6051-96), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 514–520.

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ASTM, 1996. Standard practices for preparation of sample containers and for preservation of organic constituents (D 3694-96), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA. pp. 584– 589. ASTM, 1995. Standard guide for sampling chain of custody procedures (D 4840-95), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 549–556. ASTM, 1993. Standard practice for description and identification of soils: visual manual procedure (D 2488-93), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 103–113. ASTM, 1992. Standard guide for sampling groundwater monitoring wells (D 4448-85a), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 430–443. ASTM, 1990. Standard practice for decontamination of field equipment use at nonradioactive waste sites (D 5088-90), in ASTM Standards on Environmental Sampling, 2nd ed., American Society for Testing Materials, West Conshohocken, PA, pp. 538–540. Barcelona, M., 1988. Uncertainties in ground water chemistry and sampling procedures, in Melchior, E. and R. Bassett (Eds.), Chemical Modeling of Aqueous Systems II, American Chemical Society Symposium Series 416, American Chemical Society, Los Angeles, CA, pp. 310–320. Barcelona, M. and R. Morrison, 1988. Sample collection, handling and storage: water, soils, and aquifer solids, in Proc. of Groundwater Quality Methodology Workshop, November 1–3, Arlington, VA, Cooperative States Research Service, Omaha, NE, p. 13. Barcelona, M., Wehrmann, H., and M. Varljen, 1994. Reproducible well-purging procedures and VOC stabilization criteria for ground-water sampling, Ground Water, 32(1):12–22. Barcelona, M., Holm, T., Schock, M., and G. George, 1989. Spatial and temporal gradients in aquifer oxidation-reduction conditions, Water Resources Research, 25(5):991–1003. Bergren, C., Tuckfield, R., and N. Park, 1990. Suitability of the Hydropunch for assessing groundwater contaminated by volatile organics, in Fourth National Outdoor Action Conference on Aquifer Restoration, Ground Water Monitoring, and Geophysical Methods, National Ground Water Association, Dublin, OH, pp. 387–399. Blegen R., Hess, J., and J. Denne, 1988. Field Comparison of Ground-Water Sampling Devices, National Water Well Association Second Annual Outdoor Action Conference, May, Las Vegas, NV, p. 24. Bruya, J., 1998. Review of analytical data, in Proc. of the 1998 National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, College of Engineering and Engineering Professional Development, University of Wisconsin, Madison. Bruya, A., 1996. Overview of hydrocarbon fingerprinting techniques: sources of analytical error, in Proving the Technical Case: Chlorinated Solvents and Petroleum Hydrocarbons, College of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 80. Bruya, A., 1994. Interpretation of laboratory analysis of chlorinated solvents, in Proving the Technical Case: Soil and Groundwater Contamination Litigation with Emphasis on Chlorinated Solvent Contamination, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 140. Church, P., and E. Gvanato, 1996. Bias in ground-water data caused by well bore flow in long screen wells, in Ground Water, National Ground Water Association, Dublin, OH, pp. 313–327.

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Creasey, C., 1996. Low flow sampling and trace metal clean techniques: demonstrated applicability for trace metal analyses of groundwater, No. H22D-51440h, EOS Transactions, 77(46):1. Csuros, M., 1994. Environmental Sampling and Analysis for Technicians, Lewis Publishers, Boca Raton, FL, p. 320. Draper, W., Remoy, J., and S. Perera, 1998. Getting reliable data from water labs testing for MTBE (or any other volatile contaminant), in The Southwest Focused Ground Water Conference: Discussing the Issue of MTBE and Perchlorate in Ground Water (Suppl.), National Ground Water Association, Dublin, OH, pp. 19–51. Erickson, R. and R. Morrison, 1995. Environmental Reports and Remediation Plans: Forensic and Legal Review, John Wiley & Sons, New York, p. 570. Foley, G., 1998a. Passive Soil Gas Sampler: Gore-Sorber Screening Survey Passive Soil Gas Sampling System, EPA/VS/SCM/19, Environmental Technology Verification Program Verification Statement, U.S. Environmental Protection Agency, Washington, D.C., p. 3. Foley, G., 1998b. Passive Soil Gas Sampler: Emflux Soil Gas Investigation System, EPA-VSSCM-22, Environmental Technology Verification Program Verification Statement, U.S. Environmental Protection Agency, Washington, D.C., p. 3. Foley, G., 1998c. Field Portable X-Ray Fluorescence Analyzer: Sefa-P Analyzer, EPA-VSSCM-05, Environmental Technology Verification Program Verification Statement, U.S. Environmental Protection Agency, Washington, D.C., p. 3. Garabedian, S., LeBlank, D., Hess, K., and R. Quadri, 1987. Natural-gradient tracer test in sand and gravels: results of spatial moments analysis, in U.S. Geological Survey Program on Toxic Waste Ground-Water Contamination: Proc. of the Third Technical Meeting, March 23–27, Pensacola, FL, pp. B13–B16. Gee, G. and J. Bauder, 1986. Particle-size analysis, in Methods of Soil Analysis. Part I. Physical and Mineralogical Methods, 2nd ed., American Society of Agronomy, Madison, WI, pp. 383–411. Gibs, J., Brown, G., Turner, K., MacLeod, C., Jelinski, J., and S. Koehnlein, 1993. Effects of small-scale vertical variations in well-screen inflow rates and concentrations of organic compounds on the collection of representative ground water-quality samples, Ground Water, 31(2):201–208. Global Geochemistry Corporation, 1998. Announcing a New Environmental Test for Oxygenate Additives (promotional material), Canoga Park, CA, p. 2. Hartman, B., 1999. Soil vapor analysis and interpretation, in Chlorinated Solvent Contamination: Legal and Technical Issues, Argent Communications Group, Forresthill, CA, pp. 84–123. Hartman, B., 1998a. To Methanol Preserve or Not To Methanol Preserve?, LUSTline Bull. No. 28, New England Interstate Water Pollution Control Commission, Wilmington, MA, pp. 17–18. Hartman, B., 1998b. MTBE: Beware the False Positive, LUSTline Bull. No. 26, New England Interstate Water Pollution Control Commission, Wilmington, MA, p. 18. Hartman, B., 1998c. Applications and interpretation of soil vapor data, in Petroleum Hydrocarbon Contamination: Legal and Technical Issues, Argent Communications Group, Forresthill, CA, pp. 81–110. Hartman, B. and R. Hitzig, 1998. A Layman’s Guide to the New EPA Methods for VOC Analysis, LUSTline Bull. No. 30, New England Interstate Water Pollution Control Commission, Wilmington, MA, pp. 21–23. Hewitt, A., Miyares, P., Leggett, D., and T. Jenkins, 1992. Comparison of analytical methods for determination of volatile organic compounds in soils, Environmental Science and Technology, 28(10):1932–1938.

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Hillel, D., 1982. Introduction to Soil Physics, Academic Press, Orlando, FL, p. 364. Imbrigiotta, T., Gib, T., Fusillo, J., Kish, G., and J. Hochreiter, 1986. Field evaluation of seven sampling devices for purgeable organic compounds in ground water, prepared for ASTM Symposium on Field Methods for Ground Water Contamination Studies and Their Standardization, February 2–7, Coca Beach, FL, p. 23. Jenkins, R., Bayne, C., Maskarinec, M., Johnson, L., Holladay, S., and B. Tomkins, 1993. Experimental determination of pre-analytical holding times for volatile organics in selected soils, in National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art and Research Needs, January 12–14, sponsored by U.S. Environmental Protection Agency, American Petroleum Institute, and University of Wisconsin Engineering Extension Program, Madison. Kaback, D., Bergren, C., Carlson, C., and C. Carlson, 1990. Testing a ground water sampling tool: are the samples representative?, in Fourth National Outdoor Action Conference on Aquifer Restoration, Ground Water Monitoring and Geophysical Methods, National Ground Water Association, Dublin, OH, pp. 403–417. Kaplan, E., Banerjee, S., Ronen, D., Machlin, A., Sosnow, M., and E. Koglin, 1991. Multilayer sampling in the water-table region of a sandy aquifer, Ground Water, 29(2):191–198. Kearl, P., Korte, N., Stites, M., and J. Baker, 1994. Field comparison of micropurging vs. traditional ground water sampling, Groundwater Monitoring Review, Fall:183–190. King, A. 1993. Evaluation of sample holding times and preservation methods for gasoline in fine grained soils, in National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art and Research Needs, January 12–14, sponsored by U.S. Environmental Protection Agency, American Petroleum Institute, and University of Wisconsin Engineering Extension Program, Madison, p. 7. Kollmorgen Corp., 1975. Munsell Soil Color Charts, Macbeth Division of Kollmorgen Corp., Baltimore, MD, p. 18. Lancaster, V. and S. Keller-McNulty, 1998. Composite sampling II, Environmental Testing and Analysis, 7(5):14–15. Lancaster, V. and S. Keller-McNulty, 1988. Composite sampling I, Environmental Testing and Analysis, 7(4):15–18, 32. Maney, J., and A. Wait, 1991. The importance of measurement integrity, Environmental Laboratory, 3(5):20–25. Marrin, D., 1988. Soil-gas sampling and misinterpretation, Ground Water Monitoring Review, 8(2):54–57. Martin-Hayden, J. and G. Robbins, 1997. Plume distortion and apparent attenuation due to concentration averaging in monitoring wells, Ground Water, 35(2):339–347. Martin-Hayden, J., Robbins, G., and R. Bristol, 1991. Mass balance evaluation of monitoring well purging. Part II. Field tests at a gasoline contamination site, Journal of Contaminant Hydrology, 8:225–241. Maskarinec, M., Johnson, L., Holladay, S., Moody, R., Bayne, C., and R. Jenkins, 1990. Stability of volatile organic compounds in environmental water samples during transport and storage, Environmental Science and Technology, 24(11):1664–1670. Maybey, W., 1995. Verifying data quality-quality assurance, in Environmental Chemistry for Investigating and Remediating Soil and Groundwater Contamination, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 15. Meyer, C., 1999. Distinguishing good science, bad science and junk science, in Meyer, C. (Ed.), Expert Witnessing: Explaining and Understanding Science, CRC Press, Boca Raton, FL, pp. 99–120.

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Mishalanie, E., 1998. Measurement bias in analytical methods for determination of chlorinated solvents and petroleum hydrocarbons in environmental samples, in National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 27. Mishalanie, E., 1995. Testing biases associated with chlorinated solvents and hydrocarbon analyses, in Environmental Litigation: Hydrocarbon, Chlorinated Solvents and Visual Display of Evidence, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 41. Peargin, T., 1994. Unsaturated zone air flow and soil vapor extraction theory, in Designing Air-Based In Situ Soil and Groundwater Remediation Systems, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison. Powell, R., 1997. Hitting the bull’s eye in groundwater sampling, Pollution Engineering, June:51–54. Powell, R. and R. Puls, 1993. Passive sampling of groundwater monitoring wells without purging: multilevel well chemistry and tracer disappearance, Journal of Contaminant Hydrology, 12:51–77. Puls, R. and C. Paul, 1995. Low-flow purging and sampling of ground water monitoring wells with dedicated systems, Groundwater Monitoring Review, Winter:116–123. Puls, R. and M. Barcelona, 1989. Filtration of ground water samples for metals analysis, Hazardous Waste and Hazardous Materials, 6(4):385–393. Puls, R., Clark, D., Bledsoe, B., Powell, R., and C. Paul, 1992. Metals in ground water: sampling artifacts and reproducibility, Hazardous Waste and Hazardous Materials, 9(2):149–162. Puls, R., Eychaner, J., and R. Powell, 1990. Colloidal-Facilitated Transport of Inorganic Contaminants in Ground Water. Part I. Sampling Considerations, EPA/600/M-90/023, Robert S. Kerr Environmental Research Laboratory, U.S. Environmental Protection Agency, Ada, OK, p. 12. Ramsey, C., 1996. Chlorinated solvent and hydrocarbon sampling techniques: what are the biases?, in Proving the Technical Case: Chlorinated Solvents and Petroleum Hydrocarbons, College of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 20. Rhodes, I., 1999. Pitfalls using conventional TPH methods for source identification, in Proc. of Environmental Forensics: Integrating Advanced Scientific Techniques for Unraveling Site Liability, International Business Communications, June 24–25, Washington, D.C., p. 11. Robbins, G. and J. Martin-Hayden, 1991. Mass balance evaluation of monitoring well purging. Part I. Theoretical models and implications for representative sampling, Journal of Contaminant Hydrology, 8:203–224. Robbins, G., Deyo, B., Temple, M., Stuart, J., and M. Lacy, 1990. Soil-gas surveying for subsurface gasoline contamination using total organic vapor detection instruments. Part II. Field experimentation, Ground Water Monitoring Review, Fall:110-117. Robertson, C. and J. Cutler, 1989. Soil Gas Investigations at MGP Sites: An Evaluation of Alternate Compounds, Rep. No. GRI-89/0166, Gas Research Institute, Chicago, IL, p. 58. Robin, M. and R. Gillham, 1987. Field evaluation of well purging procedures, Groundwater Monitoring Review, Fall:85–93. Rosecrance, A. and L. Kibler, 1988. A guide to improved documentation and record keeping, Environmental Testing and Analysis, 7(4):26–30. Rosenberry, D., 1990. Effect of sensor error on interpretation of long-term water-level data, Ground Water, 28(6):927–936.

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Shanklin, D., Sidle, W., and M. Ferguson, 1995. Micro-purge, low-flow sampling or uraniumcontaminated ground water at the Fernald environmental management project, Groundwater Monitoring Review, Summer:168–176. Siegrist, R., 1993. VOC measurement in soils: the nature and validity of the process (abstract), in National Symposium on Measuring and Interpreting VOCs in Soils: State of the Art and Research Needs, January 12–14, sponsored by U.S. Environmental Protection Agency, American Petroleum Institute, and University of Wisconsin Engineering Extension Program, Madison, p. 10. Siegrist, S. and P. Jenssen, 1990. Evaluation of sampling method effects on volatile organic compound: measurements in contaminated soils, Environmental Science and Technology, 24(9):1387–1392. Simes, G. and J. Harrington, 1993. The measurement of contamination in environmental samples, Air and Waste, 43:1155–1160. Squillance, P., Pankow, J., Barbash, J., Price, C., and J. Zogorski, 1999. Preserving ground water samples with hydrochloric acid does not result in the formation of chloroform, Ground Water Monitoring and Review, 19(1):67–74. Stolzenburg, T. and D. Nichols, 1986. Effects of filtration method and sampling devices on inorganic chemistry and sampled well water, in Proc. of the Sixth National Symposium and Exposition on Aquifer Restoration and Ground Water Monitoring, National Water Well Association, Dublin, OH. Sudicky, E., Cherry, J., and E. Frind, 1983. Mitigation of contaminants in groundwater at a landfill: a case study. 4. A natural-gradient tracer test, Journal of Hydrology,63:81–108. Tetra Tech, 1998. Environmental Technology Verification Report: Passive Soil Gas Sampler, EPA/600/R-98/095, Office of Research and Development, U.S. Environmental Protection Agency, Washington, D.C., p. 44. U.S. Corps of Engineers, 1960. Unified Soil Classification System, Vol. 1, rev. ed., Technical Memorandum No. 3-357, Omaha, NE. U.S. EPA, 1997. Field Portable X-Ray Fluorescence Analyzer: Measurement of Metals in Soils, EPA/VS/SCM/03, Environmental Technology Verification Program, Office of Research and Development, U.S. Environmental Protection Agency, Washington, D.C., p. 3. U.S. EPA, 1995. RCRA Sampling Procedures Handbook, U.S. Environmental Protection Agency, Washington, D.C. (revised by A.T. Kearney). U.S. EPA, 1991. Chapter 11 (final draft), in Ground Water-Monitoring, SW-846, U.S. Environmental Protection Agency, Washington, D.C. U.S. EPA, 1987. Data Quality Objectives for Remedial Response Activities, Development Process, EPA/540/G-87/003, Office of Emergency Response and Office of Waste Programs Enforcement, U.S. Environmental Protection Agency, Washington, D.C. U.S. EPA, 1986. RCRA Ground-Water Monitoring Technical Enforcement Guidance Document (TEGD), U.S. Environmental Protection Agency, Washington, D.C., p. 215. Wilson, G., Gwo, J., Jardine, P., and R. Luxmoore, 1998. Hydraulic and physical nonequilibrium effects on multiregion flow, in Selim, H. and L. Ma (Eds.), Physical Nonequilibrium in Soils: Modeling and Application, Ann Arbor Press, Chelsea, MI, p. 492. Wilson, N., 1998. Soil Water and Ground Water Sampling, CRC Press, Boca Raton, FL, p. 188. Zurer, P., 1991. Contract labs charged with fraud in analyses of Superfund samples, Chemical and Engineering News, 69:14–16.

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Plate 3.1 Soil stains of a dyed fluid infiltrating around a coarse-grained sediment via unsaturated flow.

Plate 3.2 Collection of a gasoline-impacted soil sample from the crust of a soil stockpile with a brass tube.

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Plate 3.3

Monitoring well valve-box designs.

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4

Forensic Techniques Used in Environmental Litigation

Scientific method vs. junk science

4.1 INTRODUCTION When evaluating the merits of performing non-intrusive forensic analysis (e.g., contaminant transport modeling or aerial photo-interpretation) and/or intrusive sampling and testing, three questions should be considered: 1. Does the analysis or testing advance the understanding of the technical aspects of the case? 2. Can the test results be damaging to your client? 3. Is the testing cost effective relative to the allegations in the case?

When answering the third question, be aware that many forensic techniques, especially specialty analytical testing, are marketed and monopolized by a small number of companies. These firms, therefore, have a proprietary interest in their use. The following recommendations are offered for consideration when examining the applicability of forensic techniques: • Use multiple forensic methods whenever possible. • To the extent possible, isolate your forensic evidence from other groups of evidence so that each group of forensic evidence is a “stand-alone” line of evidence. This practice avoids the domino effect of multiple lines of evidence being successfully challenged if one domino is successfully challenged. • Corroborate your forensic results with other types of evidence (direct testimony, blueprints, aerial photography, etc.) for consistency.

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A common issue in environmental litigation is the determination of the origin of a contaminant release, timing of the release, and distribution of the contamination. Forensic procedures that provide this information include (Morrison, 1998a): • • • • •

Aerial photography interpretation Underground storage tank corrosion models Identification of the date when a chemical became commercially available Association of a particular chemical with a manufacturing process Chemical profiling (fingerprinting) and chemical degradation models

4.2 AERIAL PHOTOGRAPHY Aerial photography offers an established application for identifying historical information concerning a site’s waste-handling practices, as well as its potential to provide information regarding the timing of a contaminant release (Erb et al., 1981; Lyon 1987; Pope et al., 1996; Weil et al., 1994). Successful use of this technique is dependent on acquiring a complete list of coverage dates and retaining an expert in this discipline. Two fields of discipline within aerial photography are photo-interpretation and photogrammetry. Photo-interpretation is the identification of objects seen on aerial photography. Photogrammetry is the measurement of features on aerial photographs. Both disciplines are important, as aerial photo-interpretation is dependent on the sophistication of the diagnostic equipment as well as the experience of the interpreter. Several sources of aerial photography are available, including the U.S. Geological Survey, the U.S. Department of Agriculture, the U.S. Forest Service, the National Oceanic and Atmospheric Administration (NOAA), the Army Corps of Engineers, the U.S. Soil Conservation Service, the U.S. National Archives, local and state highway departments, and private collections. The U.S. National Archives located in Betheseda, MD, for example, has aerial photography of all of the airfields in the United States in the 1940s. Another source is the Earth Resources Observation Satellites (EROS) collection in Sioux Falls, SD (800-252-4547). A historical search of federal aerial photography can be performed by EROS at no charge within 24 to 48 hours. Acquisition of a complete list of aerial photographs requires the use of a firm specializing in this service. These firms have access to private collections and aerial photography brokers (for example, Chinese and Russian satellite imagery) who can provide crucial evidence for identifying a key surface feature or activity. Acquire stereoscopic (stereo pairs) rather than monoscopic photographs whenever possible so that a three-dimensional analysis of relevant features can be performed. Anaglyphs can also be used for stereo viewing. Analglyphs are red-blue images that allow stereo viewing of the aerial photo with red and blue glasses or on some computer screens. Stereoscopic aerial photography consists of two or more overlapping frames of vertical photography that combine to create three-dimensional coverage of a site. In

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most cases, aerial camera stations are spaced to provide for about 60% forward overlap of aerial photographs along each flight line and a 20 to 30% percent overlap for adjacent flight lines. The U.S. government and private industry have been photographing large portions of the United States in stereoscopic coverage, and most aerial photographs are available as 9 ¥ 9-inch contact prints or negatives. It is better to order the negatives/transparencies, as one can lose up to four times the resolution with a contact print. The emulsion in a contact print provides a less precise resolution than a negative or transparency. Request the provider to document the film scale, focal length of the camera, and the correct date when the photograph was taken. If the photograph is cropped or enhanced, the impacted area should be identified and documented (see Figure 6.7 in Chapter 6). When multiple aerial photographs are obtained from different elevations and angles, registration (also known as geo-referencing) is required. Commercial software is available for translating and registering aerial photographs to a base image. Commercial firms usually scan photographs at a resolution of 12.5 microns (2032 dots per inch) with a photographic scanner, thereby producing high-resolution digital images suitable for trial exhibits (Grip, 1998). Mounted, scaled, and cropped 30 ¥ 40inch prints of selected photos or features are commonly used for trial exhibits. Once the photo is digitally scanned, it is possible to enlarge the photograph up to 50 times without losing resolution. In some cases, an enhancement equal to 1 ft2 for each scanned pixel is possible. Distortion effects in vertical and oblique aerials are removed so that an overheadlike view is obtained from an oblique photograph. Aerial photographs can also be enhanced in a consistent manner between the registered aerial photographs. The benefits of digitally scanning and registering historical aerial photographs include (Soby et al., 1992): • An overhead-like view of the site can be viewed during a period when no vertical aerial photos are available. • Scanning allows a rapid historical and forensic examination of key areas which can then be used as trial exhibits (stills, bar-coded images, or animation). • The photograph can be combined with a geographic information system (GIS) for detailed forensic review of chemical/spatial relationships.

While an aerial photograph can identify a dark “stain” or other evidence of surface contamination, it is two dimensional and does not provide information regarding the depth of contamination. One means to discriminate between a creosote stain and ponded water, for example, is to obtain precipitation records for at least 10 days prior to the date of the aerial photograph to determine whether rainfall was recorded in the vicinity of the site. Another exercise is to ask the photograph interpreter to examine similar-appearing features around the site for several miles to compare with the stain of interest. Aerial photographs must be combined with other causal information (historical, chemical, deposition testimony) to develop a direct link between the aerial photograph and subsurface contamination. In many instances, detailed features such as the number of barrels, their position, and the presence of

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FIGURE 4.1 Aerial photograph with details of 55 gallon barrels.

stains or drainage patterns associated with the barrels can be identified. Figure 4.1 is an example of an aerial photograph with this level of resolution. Aerial photography interpretations are useful for identifying potential source areas indicative of a contaminant release such as drum storage areas, open drainage ditches, standing liquid, landfills, stains, access and egress routes from buildings, and/or storage areas. Aerial photographs can be combined with soil chemistry results to associate the release of specific contaminants with a particular time frame. The technique combines identifying a unique chemical associated with a discrete soil horizon with aerial photo-interpretation to bracket when the contaminant was released. The concept is similar to dating discrete levels in an archaeological excavation. A hypothetical case illustrates this approach. Assume that an asphalt emulsion plant and its associated contaminants are identified by aerial photographs as having been operational between 1960 and 1969. Excavations in the area reveal discrete soil horizons contaminated with asphalt and related compounds indicative of an asphalt emulsion plant overlain by several feet of uncontaminated soil and asphalt/concrete road bases. The various road bases and filling activities are identified in aerial

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photographs, thereby bracketing a time when the release occurred. Given this information, the hydrocarbon release into a discrete soil horizon can be linked to a particular activity and time period. In some cases, the placement of subsequent contaminant layers can be identified, resulting in forming multiple bracketed time periods. Plate 4.1* shows the sidewall of a trench with two layers of concrete and a clean layer between the two concrete pavement layers. The material in the clean fill layers is associated with a nearby quarry which allowed dating of the fill excavation and placement to complement the aerial photography information. Additional layers A through D are similarly associated with discrete activities and time periods. By combining aerial photography depicting the surface features with the chemical profiling information shown on Plate 4.1, the various layers can be associated with various tenants. Historical aerial photographs and tenant information can then be used to establish the causal relationships and provide a basis for allocating remediation costs.

4.3 UNDERGROUND STORAGE TANK CORROSION MODELS The use of tank corrosion to identify the timing of a release from an underground storage tank (UST) has been proposed as a means to age-date a release. Ideally, tank inventory records are available, and variables due to delivery discrepancies, temperature effects, pump meter errors, non-standard UST geometry, and gauging errors can be identified to determine when the leak occurred. In the absence of this direct information, indirect predictive techniques based on tank corrosion are available. In order for tank corrosion to occur, the following components must be present: • • • •

Anode (a negative electrode that is consumed) Cathode (a positive electrode that is protected) Electrolyte (soil seawater, etc.) Metallic connection between the anode and cathode

A corroding steel tank acts as both an anode and a cathode simultaneously but at different locations on the tank. Anodic sites on the tank surface exist where the metal is deformed, the oxygen concentration is low, the rust layer is disrupted, impurities or precipitates exist, higher temperatures exist, and backfill material boundaries (i.e., different soil textures) are present. The corrosion rate is controlled by the following variables: • Voltage between the anode and cathode • Resistance between the anode and cathode • Resistance of the soil backfill * Plate 4.1 appears behind page 242.

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• Resistance of any anodic or cathodic films • Type of fluid and material of tank and/or piping construction

The primary variable is the anodic current density. A steel tank may suffer negligible corrosion even if a substantial anodic current is present but is distributed uniformly over the surface of the tank; however, if the same anodic current is confined to a discrete location, perforations in a tank may occur within a matter of days. Soil characteristics influencing the corrosion rate include soil electrical resistivity, pH, moisture content, sulfide content, and chloride content (U.S. EPA, 1988a). Corrosion rates are increased due to flowing water, the presence of fluctuating saline water in contact with the tank, the presence of certain bacteria, high temperatures, and increasing oxygen concentration. In general, factors indicative of a high corrosion risk include high soil moisture, saline soils, high groundwater levels that fluctuate above and below the tank, low soil pH, and improper backfill placement. Factors considered indicative of a low corrosion risk include high soil resistivity, low soil moisture, high soil pH, low age, non-corrosive tank materials and piping materials, and the presence of cathodic protection devices and coatings. As soil resistivity decreases, soil corrosivity increases. Given that soil corrosivity is closely related to the electrical resistivity of the soil, a general classification of soil resistivity values vs. corrosivity is as follows: • <1000 ohm-cm is extremely corrosive • 1000 ohm-cm to 10,000 ohm-cm is corrosive • 10,000 ohm-cm is progressively less corrosive

The type of liquid and tank and/or piping construction has a significant impact on the corrosion rate. Chlorinated solvents, for example, are transported through pipes and tanks composed of nickel-based alloys. In the presence of water, however, the chlorinated solvents can hydrolyze to form hydrochloric acid which results in accelerated corrosion. External corrosion accounts for approximately 85% of the perforations associated with unprotected steel underground storage tanks. Tank corrosion occurs when underground storage tanks are installed without cathodic protection. The soil surrounding the tank acts as an electrolyte and galvanic current flow from the tank surface to other structures in the vicinity or from various parts of the tank surface to other areas where the metal composition differs. Types of external corrosion affecting steel underground storage tanks include uniform corrosion, pitting, and crevice corrosion (Figure 4.2), dissimilar metal (galvanic) corrosion, concentration cell corrosion, and stray current corrosion (Liebert, 1990). Uniform corrosion results when the galvanic current voltage is uniform over the entire surface of the underground storage tank. This occurs when the backfill surrounding the tank is homogenous and uniform and the tank surface is not scratched or gouged. The corrosion rate is then uniform over the entire tank surface and proceeds until a thin layer of iron oxide coats the tank surface, at which point

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FIGURE 4.2 Mechanism of formation and photograph of pit corrosion. (From Pickering, H. and R. Frankenthal, in Localized Corrosion, International Corrosion Conference Series, National Association of Corrosion Engineers, Houston TX, 1974, pp. 261–269. With permission.)

corrosion ceases, as this iron oxide layer protects it against further deterioration. Corrosion under these conditions occurs uniformly and slowly over the tank surface (Pourbaix, 1971). Pitting (also called crevice, point, or localized corrosion) occurs whenever, in the course of tank installation, a condition arises which concentrates the galvanic current at one or several points on the tank surface. This can occur due to mill scale abrasion, lack of impurity or uniformity in the backfill material, and tank abrasion that may occur during installation (Pickering and Frankenthal, 1974). Given that pit corrosion is not uniform, high corrosion rates are possible because the pit formed at the point of galvanic concentration creates iron oxide, which can fall away from the steel surface, which then becomes susceptible to further corrosion. The corrosion, therefore, continues as long as the corrosion-inducing influences are present. Approximately 77% of the corrosion observed in underground storage tank installations is pit corrosion; uniform corrosion accounts for the remaining 23%.

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A statistical technique based on a survey of underground storage tanks in the U.S. and Canada is often proposed as a means to estimate when an underground tank began leaking. The method, known as the Mean Time to Corrosion Failure (MTCF®) model, assumes that uniform and pitting corrosion are the primary corrosion mechanisms. This method originated from an American Petroleum Institute (API) study that concluded that tank failures due to external corrosion occurred from as little as 5 and up to 35 years. Absent other information, the age of an underground storage tank did not provide a basis to determine the probability of failure due to corrosion. The MTCF® model evolved from the results of a survey from a 1979 survey by the American Petroleum Institute and the Petroleum Association for the Protection of the Canadian Environment in which over 2000 UST sites in the U.S. and Canada were excavated and their condition documented. Based on this research, a field procedure was developed to obtain the necessary information from the tank backfill material to allow a statistical estimation using MTCF®. The MTCF® relies upon characteristics of the tank backfill material (e.g., soil moisture content, pH, soil resistivity, and sulfide content) along with the tank age; the probability of failure at any point in time is then calculated. The mean time to failure for an unprotected carbon steel underground storage tank is described in Equation 4.1 (Warren Rogers & Assoc., 1981): Age = 5.75(R0.05)(S–0.018)exp(0.13 pHsoil – 0.41 M – 0.26 Su)

(Eq. 4.1)

where R = calculated soil resistivity in ohm-cm that is obtained from conductivity measurements (inverse of resistivity, or R = 1/conductivity), because conductivity values are reproducible whereas resistivity measurements are operator sensitive. S = capacity (gallons) of the underground storage tank. M = 1, if soil is saturated; 0 if soil is not saturated. Su = 1, if sulfides are present; 0 if sulfides are not present.

A 90% confidence level is defined if the following values are substituted into Equation 4.1: R(0.049, 0.051), S(–0.019, –0.0170), –0.119, 0.141 pHsoil, 0.31–0.51 and 0.25–0.27 Su. This technique has been implemented at over 30,000 sites in the United States. Actual tank removals and physical examinations have reportedly established its accuracy as being between 95 and 98% (Warren Rogers and Assoc., undated). Another study of 800 tanks at retail service stations in Ohio indicated that at least one tank failure could be expected in 55% of the stations in 15 years and that failure could be expected at 70% of the stations in 20 years (Garrity, 1996). Challenges to the MTCF® approach are that, in many cases, the tank has been removed and measurements of the soil properties of interest are not available. In addition, information concerning where a leak occurred (i.e., a leak in the fill pipe vs. corrosion) may not be resolvable. The MTCF® does not account for mechanical failure, only failure due to corrosion. Studies performed by the U.S. Environmental Protection Agency show that delivery piping releases and spills or overfills are the most common sources of releases and that equipment at the top of tanks leaks during overfills more frequently than do tanks and delivery piping (U.S. EPA, 1987). For

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underground storage tanks, about 65% of all releases are from product lines, 25% are from the tanks, and the remainder from overfilling or spillage. MTCF® data are also skewed to some degree in that primarily tanks that had failed were excavated and examined. In the absence of physical evidence, patterns in contaminant distribution may be inconclusive in terms of the ability to determine whether the contamination occurred via corrosion or from overfilling of the spill boxes (usually ranging from 5 to 25 gallons, with 5-gallon models being the most common) (McCan, 1996). In addition, if stray DC currents are present, parameters other than the nature of the tank backfill material are required to estimate corrosion rates. The National Fire Protection Association (NFPA) is a source for historical standards for underground storage tank installation and maintenance. This association maintains documents that date from the 1920s.

4.4 INVENTORY RECONCILIATION Inventory reconciliation includes (1) review of inventory (sticking records), if available, and (2) precision tank testing as a means to date the release of a fluid from a tank (U.S. EPA, 1988b,c,d 1989; 1990). Inventory control requires recording daily accurate measurements of the fluid level in the tank and performing monthly calculations to determine if the tank is leaking. The examination of inventory records is a straightforward means to assess whether a significant volume of fuel has been lost, as inventory records contain the volume of product dispensed from a tank and deliveries. It is the author’s experience that sources of error in inventory reconciliation include product delivery discrepancies, errors in addition and subtraction, pump meter reading errors, non-standard tank geometry, gauging errors, and theft. Temperature differences between the delivered product and the product in the storage tank can also account for discrepancies found in the inventory reconciliation calculations. Statistical inventory analysis can be performed to detect whether a leak has occurred; the following requirements must be satisfied when using this approach (Kroon and Baach, 1996): • • • •

0.2 gal/hr minimum detectable leak 150 gal/mth minimum detectable leak 95% minimum probability of detection 5% maximum probability of a false positive

Precision tank testing to ascertain tank integrity is used to determine an estimated tank interval during which a tank began leaking. A tank integrity test consists of precisely monitoring the fluid level and the tank temperature for a period of several hours. The fluid level is adjusted for temperature drifts to determine if there is a leak. A 10∞F temperature change in gasoline in a 10,000-gallon storage tank, for example, produces a 70-gallon change in volume.

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Tank testing technology became available in about 1945. Tank tightness tests should be in accordance with ASTM Standards or a method that is certified in accordance with U.S. Environmental Protection Agency and/or state requirements. Tank tightness results should be examined in conjunction with inventory control sheets to identify when a leak may have commenced. A leaking tank is one from which the loss of liquid is greater than 0.05 gal/hr based on National Fire Protection Authority Bulletin #329. Variables in tank tightness tests that can introduce measurement uncertainty include the temperature of the liquid within the tank, vapor pockets, deflection at the ends of the tank, a high water table, nearby road vibrations, operator error, and electronic noise in the measurement equipment (U.S. EPA, 1988b, 1989).

4.5 COMMERCIAL AVAILABILITY OF A CHEMICAL The date that a compound became commercially available can often bracket the earliest time period of its release. Chlorinated hydrocarbons, chemicals associated with fuel additives, pesticides, herbicides, fungicides, and insecticides are especially amenable to this dating analysis. Chlorofluorocarbons released into the atmosphere since the 1940s have been used for this purpose (Plummer et al., 1993). Knowledge of the synonyms and trade names of the chemical is often necessary to perform this analysis, as a chemical has commercial names often dissimilar to its chemical name. Trade names for commonly encountered contaminants are summarized in Appendix E. Table 4.1 lists dates when commonly encountered compounds became commercially available (IARC, 1979; Morrison, 1999c). A similar issue is the evolution of chlorinated solvent use at a facility as a means to date when a release occurred. General events such as the Montreal Protocol (see Chapter 1, Section 1.2) and state regulations can provide a means to identify when various solvents were used. In California, Rule 66 promulgated by the Los Angeles Air Pollution Control District in July 1966 limited trichloroethylene (TCE) emission from any type of equipment to 40 pounds over 24 hours. The installation of control equipment was required if this limit was exceeded. Tetrachloroethylene (PCE) and fluorinated hydrocarbons were exempt. Given that TCE boils at 184∞F and a steam supply of 15 pounds per square inch at gauge (psig) is required for heating, PCE with a 50- to 60-psig and boiling point at 250∞F was not a viable replacement for a majority of the existing equipment, such as degreasers. 1,1,1-Trichloroethane (1,1,1-TCA), however, with a boiling point of 158∞F, was a viable replacement solvent for many degreasers. A knowledge of these regulations and the operating characteristics of the equipment can provide a basis for bracketing the time period that a solvent was used at a facility. While the gross chronological transitions in solvent usage for an industry can be identified, they cannot be used as evidence of solvent use at a site. Figure 4.3 is an example of solvent usage at Hill Air Force Base (Stewart et al., 1991), an aircraft engine degreasing facility, and a semiconductor manufacturing company. As depicted in Figure 4.3, solvent transitions between these three sites do not correlate.

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TABLE 4.1 Commercial Availability of Selected Compounds Chemical

Date

Aldrin Bromacil Carbon tetrachloride Chlordane Chloroform DDT Dieldrin Dinoseb Dibromochloropropane (DBCP) 1,2-Dichloroethane Parathion Perchloroethylene (PCE) Phorate Trichloroethylene (TCE) 1,1,1-Trichloroethane (1,1,1-TCA) 1,1,2-Trichloroethane Trifluralin Toxaphene

1948 1963 1907 1947 1922 1942 1948 1945 1955 1922 1947 1925 1954 1908 1946 1941–43 1960 1947

FIGURE 4.3 Solvent transitions at three facilities between 1940 and 1990.

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TABLE 4.2 Boiling Point of Selected Chlorinated Solvents Compound Carbon tetrachloride 1,1-Dichloroethane 1,2-Dichloroethane 1,1,1-Trichloroethane (TCA) Trichloroethylene (TCE) Tetrachloroethylene (PCE) 1,1,2,2-Trichloroethane Trichlorofloromethane (Freon-11) 1,1,2-Trichlorotrifluoroethane (Freon-113)

Boiling Point (∞C) 76.7 57.3 83.5 74.1 86.7 121.4 146.4 23.8 47.7

4.6 CHEMICALS AND FORMULATIONS UNIQUE TO A MANUFACTURING PROCESS OR ACTIVITY An understanding of a site’s manufacturing processes and material handling systems can provide insight regarding probable locations of a contaminant release. An example of the former approach is identification of potential source areas at a semiconductor facility. Potential source locations where chlorinated solvents can enter the subsurface include neutralization sumps, corroded sewer and transfer piping, and chemical storage areas. The chemical distribution of chlorinated solvents in the subsurface in relation to these features is used to develop a causal relationship between these features and the observed soil contamination. Chemicals, such as chlorinated solvents, that are unique to particular equipment can provide insight into probable source locations. An example is the use of chlorinated solvents in degreasing operations. A vapor degreaser may be specifically manufactured to use solvents with boiling points within a discrete range. Obtaining the manufacturer’s operating manual or degreaser specifications can provide information concerning the inclusion or exclusion of chemicals used by a particular degreaser model as well as capacity. Degreasing manufacturers such as Phillips, Baron Blakeslee, Deltasonics, Detrex, Sonicor, Talley, and Ultraclean can often provide operating instructions for a particular degreaser model or maintain this information on Web pages on the Internet. The boiling points of selected solvents are provided in Table 4.2 (Montgomery, 1992; Pankow and Cherry, 1996). Opportunities may exist to associate a solvent with a particular activity in order to bracket the location and/or timing of a release. For chlorinated solvents, unique applications or impurities in the solvent may assist in dating or identifying the origin of the release. 1,1,2,2-trichloroethane, for example, is used almost exclusively in military applications. Examples of uses of various chlorinated solvents are summarized in Table 4.3 (Mabey, 1995; Montgomery, 1991; Pankow et al., 1996).

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TABLE 4.3 Uses of Selected Chlorinated Solvents Chlorinated Solvent

Applications

Tetrachloromethane (carbon tetrachloride)

Solvent used as a chemical intermediate, agricultural fumigant, de-worming agent, grain fumigant, and anaesthetic; also used in semiconductor manufacturing, drycleaning operations, fire extinguisher manufacturing, refrigerant manufacturing, veterinary medicine, manufacture of dichlorodifluoromethane, metal degreasing, extraction of seed oils, removal of soot from industrial boilers, and manufacture of paint removers and printing inks.

Chloroform (trichloromethane)

Solvent used for cleaning electronic circuit boards; preparation of fluorocarbon refrigerants, plastics, and refrigerants; and rubber manufacturing. Used as an anesthetic, soil fumigant, insecticide solvent, and solvent for fats, oils, rubber, waxes, and resins. Also used in toothpaste and liniments. Product of chlorination from water treatment.

Chloromethane (methyl chloride)

Natural product in seawater. Used as a coolant and refrigerant, as an herbicide and fumigant, and in the manufacture of silicone polymer pharmaceuticals, tetraethyl lead, synthetic rubber, methyl cellulose, agricultural chemicals, methylene chloride, carbon tetrachloride, methylcellulose, and chloroform. Also used as fluid for thermometric and thermostatic equipment.

Freon-11 (trichlorofluoromethane)

Used as refrigerant, blowing agent for polyurethane foam, fire extinguishing agent, aerosol propellant, solvent.

Freon-12 (dichlorodifluoromethane)

Used as blowing agent, refrigerant, propellant.

Freon-113 (trichlorotrifluoroethane; CFC-113)

Used in fire extinguishers, solvent drying, stripping of flux from printed circuit boards (often combined with alcohol), vapor degreasing, aerosols, cold cleaning, and manufacture of chlorotrifluoroethylene. Also used as drycleaning solvent and feedstock in the production of other CFCs and fluoropolymers.

1,1-DCA (1,1-dichloroethane)

Reduction product of 1,1,1-TCA. Used in paint, varnish, and finish removers; manufacture of vinyl chloride and 1,1,1-TCA; in rubber cement; as a solvent for plastics; and as an insecticide and fumigant.

1,2-DCA (1,2-dichloroethane)

Used as gasoline additive, chemical intermediary, solvent, insecticide, seed fumigant, and solvent for rubber, resin, gums, waxes, fats, and oils. Also used in the manufacture of acetyl cellulose and vinyl chloride.

1,2-Dibromomethane (ethylene dibromide)

Used in anti-knock gasoline, insecticides, medicines, and waterproofing preparations; also used as a grain and fruit fumigant.

1,1-DCE (1,1-dichloroethene)

Hydrolysis product of 1,1,1-TCA and daughter product of TCE. Used as a chemical intermediate in vinylidene fluoride synthesis, coating resins, and synthetic fibers and adhesives. Used in the manufacturing of dyes, plastics, perfumes, paints, and adhesives.

1,2-DCE (1,2-dichloroethene)

Reduction product of TCE. Used as an industrial solvent in the manufacture of dyes, plastics, perfumes, and lacquers.

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TABLE 4.3 (cont.) Uses of Selected Chlorinated Solvents Chlorinated Solvent

Applications

1,4-Dioxane

Used in paint and varnish strippers, dye baths, stain and printing compositions, cosmetics, fumigants, automotive coolant liquids, scintillation counters, and preparation of historical slides. Also used as a stabilizer in 1,1,1-TCA, as a wetting agent and dispersing agent in textile processing, and as a solvent for cellulose acetate.

Methylene chloride (dichloromethane)

Secondary blowing agent in the production of low-density flexible polyurethane foam used to produce upholstered furniture, bedding, and carpet underlay. Also used as an extractant for decaffeinated coffee; as an extraction solvent for hops; as a pill coating in pharmaceuticals (in Western Europe, in 1994, this application accounted for 41% of total usage; ECSA, 1997); as a carrier solvent and reaction medium in the pharmaceutical industry; as an inactive ingredient in pesticide formulations; in various chemical processing applications; in adhesive formulations used to bond contact cements for wood, metal, and upholstered furniture; as a process solvent for production of cellulose esters, polycarbonate, triacetate, and triacetate ester; in solvent welding of plastic parts; dewaxing solvent; in paint stripping for the aerospace industry; as a solvent for cleaning paint booths, paint lines, and spray guns; in food processing; in vapor degreasing; in vapor pressure depressant aerosol; in adhesives for mining applications; as a photoresist stripper in the manufacture of printed circuit boards; as a stripper for aircraft coatings.

PCE (tetrachloroethylene)

Used in drycleaning fluid; as a metal degreaser; as a solvent for waxes, greases, fats, oil, gums; in the manufacture of printing ink; as a paint remover; in the preparation of fluorocarbons and trichlroacetic acid; as feedstock for the production of CFC-113, hydrofluorocarbon refrigerant 134a, and hydrochlorofluorocarbon-123, -142b, and -141b; as a maskant coating used to protect surfaces from chemical etchants in the aerospace and electronics industries; in paper coatings and silicones (in small quantities); as aerosol brake cleaners; in cold cleaning; and as an insulating fluid in some electrical transformers as a substitute for PCBs (Halogenated Solvents Industry Alliance, 1994).

TCE (tetrachloroethylene)

Used as a metal degreasing solvent; in cold cleaning; as a paint remover; as a heating transfer medium in organic synthesis; as a solvent for waxes, greases, fats, oils, and gums; as a solvent base for metal phosphatizing systems; in the preparation of fluorocarbons and trichloroacetic acid; as a chain terminator in the production of vinyl chloride polymerization; as a molecular weight control agent; as a carrier solvent in the textile industry for spotting fluids; in synthesis of hydrofluorocarbons; for degreasing aluminum and cleaning sheet and strip steel prior to galvanizing; and to clean liquid oxygen and hydrogen tanks.

1,1,1-TCA (trichloroethane) Used in the production of vinylidene chloride; as a primary solvent for cold cleaning; in the photoresist process for developing and stripping electronic circuit boards; as ingredients in aerosol pesticides; in adhesive formulation;

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TABLE 4.3 (cont.) Uses of Selected Chlorinated Solvents Chlorinated Solvent

Applications

1,1,1-TCA (cont.)

in coatings for wood furniture, metal substrates, and traffic paints for signs and road lines; as inactive ingredients in pesticide formulations; in California, after 1988, as a blowing agent in the production of flexible foam used to make upholstered furniture, bedding, and carpet underlay; as a solvent for fats, resins, and waxes; as an aerosol; in textiles; in formulations for inks, adhesives, and correction fluid. Also used in the manufacture of plastics and metals.

Vinyl chloride (chloroethene)

Reduction product of 1,1- and 1,2-DCE. Gas is used in the manufacture of polychloride vinyl (PVC) pipes and wire coatings. Also used in the automobile upholstery; in copolymers; in adhesives for plastics; as a refrigerant; as an extraction solvent; and in plastic housewares.

The presence of stabilizers in chlorinated solvents presents another opportunity to date the timing and/or origin of a solvent release. In 1985, for example, 90% of all of the dioxane produced in the U.S. (primarily by Ferro Corp.; Dow Chemical, which also imported dioxane; and Stephan Company) was used as a stabilizer in 1,1,1-TCA. While this application continues, it is being quickly phased out. The author has observed using the detection of 1,4-dioxane to distinguish among multiple sources of 1,1,1-TCA in groundwater where it was associated with TCA at one facility while absent at others. The low concentrations of most stabilizers must be considered when using this approach. The absence of a solvent stabilizer in a sample may not be evidence that it was present in the solvent. Examples of additives and/or chemical impurities in selected chlorinated solvents are listed in Table 4.4 (IARC, 1979; Morrison et al., 1999). Although reliance on signature chemicals unique to a manufacturing process or equipment usually significantly narrows the potential source areas, further site specific identification is required. For example, perchlorate (ClO–4) is used in over 150 facilities in the U.S. While the presence of perchlorate is primarily associated with its use as an oxidizer in solid rocket fuel propellants (approximately 90%), it is also used in the production of fireworks, matches, and pyrotechnics and in analytical chemistry (10%), in addition to its previous use in fertilizers (Brothers and Zikmund, 1998). Similarly, mundane equipment such as cooling towers can be a source of arsenic or cyanide used to control biological growth. Water treatment chemicals such as sodium bisulfide, sulfamic acid, polyacrylate, organophosphonate, orthophosphate, quaternary amines, and chlorine are also used in cooling water. An association of these water treatment chemicals in conjunction with cyanide or arsenic may provide a means to identify the source of these metals.

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TABLE 4.4 Additives in Selected Chlorinated Solvents Chemical

Additive/Impurity

Dichloromethane

Stabilizers (0.0001–1%) may include phenol, hydroquinone, para-cresol, resorcinol, thymol, 1-naphthol, or amines.

Trichloroethylene (TCE)

For technical-grade TCE, the purity is around 99.97% with no free chloride and stabilizers, such as tymiol or hydrochloromonomethylether, present at concentrations greater than about 0 to 2 and 80 to 120 ppm, respectively. Antioxidants such as amines (0.001–0.01%) or combinations of epoxides such as epichlorohydrin and esters (0.2–2% total) are added to TCE.

1,1,1-Trichloroethane

Stabilizers (3–8%) include nitromethane, n-methylpyrrole, 1,4-dioxane, butylene oxide, 1,3-dioxolane, and secondary butyl alcohols. 1,4-Dioxane may constitute 0–4% by weight. An MSDS sheet for Solvent 111® listed 1,4-dioxane at 25 ppm (Unocal, 1989).

Tetrachloroethylene (PCE)

Stabilizers are believed to include amines or mixtures of epoxides and esters.

1,2-Dichloroethane

1,2-DCA produced in Japan is reported to contain polychlorinated ethanes.

Chloroform

Ingredients may include bromochloromethane; carbon tetrachloride; dibromodichloroethane; dibromodichloromethane; 1,1-dichloroethane; 1,2dichloroethane; cis-1,2-dichloroethene; trans-1,2-dichloroethene; dichloromethane; diethyl carbonate; ethylbenzene; 2-methoxyethanol; nitromethane; pyridine; 1,1,2,2-tetrachloroethane; trichloroethylene; and meta-, ortho-, and para-xylene. In Japan, chloroform has a minimum purity of 99.95% and may contain chlorinated hydrocarbons as impurities.

4.6.1 POLYCHLORINATED BIPHENYLS Detailed investigations concerning the commercial availability and formulations can frequently provide valuable information for bracketing the age of a chemical and timing of a release. Polychlorinated biphenyls (PCBs) provide an example of this technique. Monsanto discovered PCBs in 1889 and produced them commercially, primarily from 1930 until 1977, when Monsanto voluntarily halted production. PCBs were manufactured by the catalytic chlorination of biphenyls to produce complex mixtures, with each mixture containing up to 209 possible congener structures (Wait 1999). In the U.S., the manufacture of PCBs was halted on July 2, 1979. While Monsanto was producing PCBs in the U.S., PCBs were also being produced in Italy, Germany, and Japan. Manufacturers of PCBs worldwide and the respective trade names of their products are summarized in Table 4.5 (Fisher 1988). Polychlorinated biphenyls are listed on laboratory reports with a numbered designation, such as PCB-1254; the 12 refers to the number of carbon atoms, while the 54 refers to the number of chlorines. Different carbon and chlorine combinations were manufactured for specific uses during discrete time periods. For example, PCB-1016 was manufactured between 1971 and 1976 and used primarily as an

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TABLE 4.5 Trade Names and Manufacturers of Polychlorinated Biphenyls (PCBs) Trade Name

Manufacturer/Country

Aroclor Phenoclor Kaneclor Clophen Aroclor, Santotherm Fenclor, Apirolio Soval

Monsanto Chemical Corporation/U.S. Prodelec/France Kanegafuchi Chemical Company, Japan Bayer/West Germany Mistubishi-Monsanto/Japan Caffaro/Italy Soval/USSR

insulator fluid for electric condensers and as an additive in high-pressure lubricants. PCB-1254 was used as a secondary plasticizer in the manufacture of polyvinyl chloride (PVC) and in capacitors; it was produced from 1957 to 1977 by Monsanto. Since 1970 in the U.S., over 98% of the PCBs manufactured by Monsanto were Aroclor-1260, -1254, -1248, -1242, -1232, -1221, and -1016; less than 2% were Aroclor-1268 and -1262 (Ramamoorthy et al., 1997). Prior to 1970, analytical limitations precluded the detection of PCBs in environmental samples (Shifrin and Toole, 1998). Subsequent refinements in analytical instrumentation allowed the detection of PCBs that were usually reported as total Aroclors by laboratories. With the advent of high-resolution capillary gas chromatography columns in the early 1990s, all 209 PCB congeners were able to be calibrated (Frame et al., 1996; Frame 1997). Congeners are PCBs with the same structural backbone but differing in the number and or position on the chlorines. PCB congener analysis, in addition to isolation of the formulation period for a particular congener, offers an opportunity to fingerprint PCBs for source identification. Examples of these approaches include PCB pattern recognition in fish tissue collected in the St. Lawrence River, in sediments in the Milwaukee Harbor Estuary in Wisconsin, and in water samples from San Francisco Bay (Hwang et al., 1993; Johnson, 1999; Kannan et al., 1997; Rachdawong and Christense, 1997). The date of formulation can, therefore, be combined with its particular use to bracket the date at which it was available and to identify probable locations at the facility that would use a particular PCB formulation. Table 4.6 lists various applications of polychlorinated biphenyls (Montgomery, 1991; Pankow and Cherry, 1996). In cases where PCBs from multiple manufacturers are present, radioactive isotope analysis can be used to distinguish the manufacturer based on manufacturespecific 13C ratios (Jarman et al., 1998). Significant differences in d13 ratios have been reported for PCBs manufactured in Germany, Italy, Japan, and the U.S. This method assumes that a product sample from each suspected manufacturer is available and that it is chemically identical to the fluid released. Knowledge of the transition from PCBs to other dielectric fluids may provide a basis for dating releases in a relative sense from one another. An example of

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TABLE 4.6 Uses of Polychlorinated Biphenyls (PCBs) PCB

Applications

Aroclor-1016

Used as an insulator fluid for electric condensers and as an additive in very high-pressure lubricants.

Aroclor-1221

Used as a plasticizer for polystyrene; in epoxy resins; as an insulator fluid in electric condensers; as an additive in very high-pressure lubricants; as dielectric fluid in capacitors and gas-transmission turbines; in adhesives.

Aroclor-1232

Used as dielectric fluid in hydraulic oils; as adhesives; as an additive in high-pressure lubricants; as a plasticizer in rubber. Also used as an ingredient in polyvinyl acetate that improves fiber-tear properties.

Aroclor-1242

Used as a plasticizer in vinyl and chlorinated rubbers; as a wax extender; in carbonless reproducing paper; as a plasticizer in cellulosics; in polyvinyl acetate to improve fiber-tear properties; as dielectric liquids; as swelling agents for transmission seals; as an ingredient in lubricants, oils, and greases; as a heat transfer liquid in transformers; as a wax extender.

Aroclor-1248

Used as an additive in high-pressure lubricants; in epoxy resins; as an insulator fluid in electric condensers; as a plasticizer in rubber; in vacuum pumps; as dielectric fluid in gas-transmission turbines.

Aroclor-1254

Copolymer of styrene-butadiene and chlorinated rubber. Used as a secondary plasticizer for polyvinyl chloride (PVC); as an insulator fluid used in capacitors; in hydraulic oils; in vacuum pumps; in adhesives; in wax extenders; in dedusting agents; as an extender in cutting oils, lubricants, inks, and pesticides; as a resin plasticizer.

Aroclor-1260

Used as a secondary plasticizer for PVC; in varnish formulations; as insulator fluid for electric condensers; as an additive in high-pressure lubricants; as an ingredient in polyester resins used in fiberglassing. Included in fire retardants and varnish to improve water and alkali resistance.

segregating the chemical composition of a dense non-aqueous phase liquid (DNAPL) to identify different reservoirs of DNAPLs can be found at the General Electric Hudson Falls Plant located about 200 miles north of New York (Rawson et al., 1998). The plant manufactured capacitors containing primarily Aroclor-1242 which were discontinued in 1977. After 1997, dielectric fluids used were mixtures of bis-(2ethylhexyl)-phthalate (BEHP), phenyl-xylyl-ethane (PXE), and trichlorobenzene (TCB). DNAPLs were characterized by the percent of the relative chromatographic area of PCBs, BEHP, PXE, and TCB in the analysis by: (Area of the individual components)/ (PCB + BEHP + PXE + TCB Area) ¥ 100%

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(Eq. 4.2)

Given the sequential use of PCB, BEHP, PXE, and TCB, DNAPLs that contain >90% PCBs were termed “old” while DNAPLs containing less than 10% area PCBs and primarily BEHP, PXE, and/or TCB were referred to as “new”. DNAPLs containing more than 10% area PCBs but less than 90% PCBs were referred to as “mixed”. This ranking has allowed identification of these DNAPL pools with various locations and activities at the Hudson Falls plant site. When forensically reviewing PCB data for source identification, recognize that sources of uncertainty beyond the analytical discrimination of isolating distinct PCB congeners exist. These include the small variances in PCB formulations, difficulties in accurately quantifying a mixture of PCBs, co-extraction and co-elution of other interfering organic compounds, and co-mingling of multiple PCB mixtures (Wait, 1999). For Askarels (i.e., a generic term used for nonflammable liquids used in transformers and capacitors that are usually mixed with organic solvents such as chlorobenzenes), numerous PCB congeners are present, thereby making individual PCB congener identification difficult. Weathering may also preferentially degrade certain PCB congeners, making it difficult to discern individual PCB fingerprint patterns.

4.7 PETROLEUM REFINERY THROUGHPUT ANALYSIS A variation to the technique of associating a chemical to a particular manufacturing process is used in the case of a petroleum refinery with different historical tenants but similar unit processes. This technique is referred to as a refinery throughput analysis (Morrison, 1998b). This method also assumes that detailed information regarding changes in refinery processes (i.e., detergent alkylate units, polymerization plants, aromatic-isomerization, etc.) and the subsurface characterization of contaminants from these operations are insufficient to “fingerprint” precisely the date of their release and/or origin. This method assumes that solid waste residuals (spent catalysts and catalyst cracker fines, spent caustic, treating clays, API separator bottoms, tank bottoms, cooling tower sludges, trash, etc.) are produced as a function of the crude oil throughput at the refinery and unit process configuration factors. The volume of the crude oil throughput is required for the refinery, along with general information regarding chronological development of the refinery. Unit processes and waste streams associated with a particular distillation process can be associated with a particular time frame; wastes unique to this process that require remediation can be dated for the interval of time that the unit process operated. This technique is used as a basis for cost allocation by acquiring the crude oil throughput for the refinery on at least a yearly or, preferably, monthly basis. Sources for providing the total volume of crude throughput and unit processes for each owner/operator include site documentation and blueprints, historical aerial photographs, Oil & Gas Journal, and state agencies, such as the Texas Railroad Commission (TRC). The Oil & Gas Journal, for example, has summarized the refining capacities of refineries in the U.S. since the early part of the century, while the TRC has crude oil throughput for Texas refineries dating back 50 years.

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TABLE 4.7 Example of Throughput Analysis Information Year

Crude Capacitya

Vacuum Distillation

Thermal Operations

Catalytic Alkylation

Reforming

1950 1951 1952 1953 1954

18,000 38,000 45,000 65,000 70,000

0 0 0 1710 2700

6470 5790 6587 1200 500

1890 1200 2400 1910 2700

6320 2063 5400 6500 7000

a

Barrels of crude oil per calendar day (b/cd).

Once this information is compiled, unit processes and chemicals unique to these processes that are detected in the subsurface and require remediation are identified for the years during which the release may have occurred. Complications in the analysis arise if waste from a nonoperating unit process is stored at the facility for some subsequent time period (i.e., co-mingled waste from multiple sources stored in a surface impoundment). Table 4.7 shows an example of this method and the crude oil throughput for specific unit processes. In instances where multiple parties operated the same unit, a weighing factor based on the crude oil throughput for that unit process is developed for allocation between multiple tenants. Table 4.8 illustrates a simple example of an allocation scheme for a time period for which the unit processes are assumed to be identical for three refinery owners (absent detailed process information). In this example, the three parties would allocate the remediation costs according to the percentage basis shown on Table 4.8. When unit process and specific waste streams are available, further refinement to these the allocation percentages is possible.

4.8 CHEMICAL IDENTIFICATION OF PETROLEUM HYDROCARBONS Chemical identification or “fingerprinting” describes the ability to distinguish the age and often the origin of a chemical. Chemical fingerprinting is most commonly used in hydrocarbon contamination cases. In its simplest form, it identifies the type of hydrocarbon (diesel, gasoline, jet fuels, kerosene, and Stoddard solvent, etc.) as a means of identifying the source and often the timing of a release. This identification is performed through analysis of soil or groundwater samples or more qualitatively with in situ techniques such as a cone penetrometer (CPT) equipped with a laserinduced fluorescence sensor (Kram, 1988; U.S. EPA, 1997). This process of chemical fingerprinting is most commonly performed through “pattern recognition” or

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TABLE 4.8 Example of Throughput Analysis Allocation Year

Crude Oil Throughput (Barrels of Oil per Year) Operator A

1945 1946 1947 1948 1949 Total Operator A 1950 1951 1952 1953 1954 1955 1956 Total Operator B 1957 1958 1959 1960 Total Operator C

Operator B

Operator C

22,545,732 29,673,382 43,456,978 53,567,567 49,876,374 199,120,033 (ª ª29%) 45,567,879 55,556,987 43,456,879 42,345,451 39,354,567 42,345,596 41,956,936 310,584,295 (ª ª45%) 45,987,264 43,659,286 47,978,374 45,867,375 ª26%) 183,492,299 (ª

“pattern matching” of gas chromatogram traces of different samples. For example, comparison of chromatograms of two products designed as hydraulic fluids can provide a means for distinguishing whether the fluid is petroleum or synthetically derived which may assist in identifying a source or performing an allocation analysis. Figure 4.4 shows chromatograms for a petroleum and synthetic hydraulic fluid (Bruya, 1999). Key compounds used in pattern recognition analysis includes the following (Harvey, 1997; Stout, 1999; Stout et al., 1999c): • Light petroleum products (BTEX and heavier aromatics; alkylate paraffins) • Diesel fuels and distillates (normal alkanes and isoprenoid paraffins) • Biomarkers such as sesquiterpanes (C15), diterpanes (C20), triterpanes (C30), steranes (C30), and hopanoid compounds (i.e., present in some petroleum products but not creosote; Butler, 1999) • Crude oils and heavy fuels (substituted polyaromatic hydrocarbons and thiophenes)

Chromatograms for various fuels are shown in Figure 4.5 (Zemo et al., 1993; Bruya, 1999). The use of chromatographic pattern recognition is used to distinguish between products as well as to develop qualitative estimate regarding the age of the product

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FIGURE 4.4 Chromatograms of a synthetic and petroleum-based hydraulic fluid. (Courtesy of Jim Bruya, Friedmand & Bruya, Inc., Seattle, WA.)

by comparing the chromatograms of fresh vs. weathered fuels. More sophisticated analytical methods include examination of the composition of fuels as a function of a unique formulation or additive packages associated with a discrete time interval. These advanced forensic approaches can often reveal whether a chemical release was a single event, a series of events, or a continuous release.

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FIGURE 4.5 Examples of fuel chromatograms. (Courtesy of Jim Bruya, Friedmand & Bruya, Inc., Seattle, WA.)

4.8.1 ANALYTICAL STRATEGY An analytical strategy for performing a first cut to distinguish cumulative differences in a product is a PIANO analysis, organic lead testing, and oxygenate characterization analysis (Uhler et al., 1998). PIANO is an acronym for the primary hydrocarbon constituents in a gasoline (paraffins, isoparaffins, aromatics, naphthenes, and olefins). Depending on the results and interpretation of this analysis, additional testing

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TABLE 4.9 Example of Analytical Strategies and Test Methods Description of Analysis

Method and Analytical Equipment

PIANO analysis of 50+ paraffins, isoparaffins, aromatics, naphthenes, and olefins

Modified EPA Method 8260, HRGC/MS

Organic lead analysis for five organic lead species (TML, TMEL, DMDEL, MTEL, TEL) and associated lead scavengers (EDB, EDC)

HRGC/MS or GC with ECD detector similar to EPA Method 608/8080 for PCB analysis

Testing for oxygenates additives (MTBE, TAME, DIPE, ETBE, and alcohols); GC/MS

Modified EPA Method 8020 or 8260,

Note: TML = trimethyl lead; TMEL = trimethylethyl lead; DMDEL = dimethyldiethyl lead; MTEL = methyltriethyl lead; TEL = triethyl lead; EDB = ethylene dibromide; EDC = ethylene dichloride; MTBE = methyl-tertiary-butyl-ether; TAME = tertiary-amyl-methyl-ether; DIPE = diisopropyl ether; ETBE = ethyl-tertiary-butyl-ether; HRGC/MS = high-resolution gas chromatography/mass spectrometry; GC/MS = gas chromatography/mass spectrometry.

can provide confirmatory evidence. The PIANO analysis and analytical equipment required are summarized in Table 4.9. The bulk PIANO composition, showing relative contents of major hydrocarbon groups in the fuel, is a useful cumulative parameter for fuel type differentiation, especially the octane grade. The higher the relative content of iso-octanes (especially 2,2,4-trimethylpentane, or TCM) and aromatic hydrocarbons, such as toluene, the higher the octane rating (Kaplan et al., 1997). This type of first cut using the octane rating obtained via PIANO analysis thus provides a potential basis to distinguish between gasoline and light petroleum products. Average values of bulk PIANO composition for dispensed gasoline as a relative percentage are shown in Table 4.10 (Kaplan et al., 1995; 1997). These results are often presented in a five-point star diagram, with each arm of the star representing a distinct PIANO percentage. Distinguishing among different

TABLE 4.10 PIANO Composition of Dispensed Gasoline Grade of Gasoline Regular leaded Regular unleaded Unleaded plus Premium unleaded JP-4 Aviation gasoline

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Paraffins (%)

Isoparaffins (%)

Aromatics (%)

Naphthenes (%)

Olefins (%)

10.7 10.2 10.8 9.4 29.3 3.3

32.0 37.6 37.0 34.9 31.02 74.2

45.0 38.7 41.5 48.4 23.9 22.0

7.8 6.0 5.6 2.9 13.2 0.5

4.6 7.1 5.1 3.9 2.6 0.01

TABLE 4.11 PIANO Composition of Selected Fuels Hydrocarbon Gasoline, 87 octane Gasoline, 89 octane Gasoline, 92 octane JP-4 Aviation gasoline Diesel No. 2a Bunker Cc a b c

Paraffins (%)

Isoparaffins (%)

Aromatics (%)

Naphthenes (%)

9.6 9.1 7.5 29.3 3.3 55 21

38.3 38.1 39.7 31.0 74.2 12b 21b

38.6 43.4 43.4 43.4 22.0 24.0 34.0

6.1 3.8 3.3 3.3 0.5 — —

Olefins (%) 7.4 5.6 6.2 6.2 0.01 5.0 —

Residuals account for 4%. Cycloparaffins. Polar and associated residuals account for 45%.

products is often pronounced with this type of presentation, especially if the samples are “fresh” fuels. PIANO ratios are also used for distinguishing among the relative weathering rates of different fuels, whether in soil or groundwater. PIANO results can be correlated with the octane rating of a fuel. The PIANO compositions for different fuels are listed in Table 4.11 (Galerpin, 1997; Kaplan et al., 1996). Due to the alkylation of fuels, the content of the major isoalkane generated (2,2,4-trimethylpentane, or TMP) increases in the finished gasoline relative to the methylcyclohexane (MCH) content. MCH is a common constituent of crude oil and refined volatile fuels. Low-octane fuels (87) have a TMP/MCH ratio less than 2.5, while high-octane gasolines (92 to 93) have TMP/MCH ratios greater than 5. Intermediate-grade gasolines have TMP/MCH ratios in the 2.5 to 5.0 range. Additional analyses to complement the available information may be performed. Table 4.12 summarizes various analyses, target compounds, and the advantages and disadvantages of various tests from a forensic perspective (Uhler et al., 1998). When examining, interpreting, or challenging the results from these tests, the limitations of the tests should be considered. Table 4.13 lists some of these concerns (Uhler et al., 1998). In addition to these standard analytical techniques used to identify the age of a hydrocarbon release, other approaches include analysis of proprietary additives, the composition of anti-knock formulations, trace metals analysis, hydrocarbon profiling, physical characteristics, and degradation models.

4.8.2 PROPRIETARY ADDITIVES: PETROLEUM HYDROCARBONS Proprietary additives are compounds blended with refined products such as fuels. A blended additive is a refinery product manufactured for bulk mixing with the fuel

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TABLE 4.12 Opportunities and Challenges of Analytical Tests for Petroleum Hydrocarbons Analytical Method

Target Compounds

Utility

Modified EPA Method 8015; TPH and product identification

Extractable hydrocarbons; total petroleum hydrocarbons

Basic-level product identification by GC/FID; all petroleum contamination identified — light distillates to asphalts; quantification of these compounds

Modified EPA Method 8015; saturated hydrocarbons by GC/FID

C8 to C40 normal and branched alkanes (acyclic isoprenoids)

Determination of petrogenic vs. biogenic input ratios and degree of weathering; biodegradation of crude oil and middle distillates

Modified EPA Method 8260; volatile organic compounds by GC/MS; purge and trap

C5 to C12 PIANO analysis (paraffins, isoparaffins, aromatics, naphthenes, and olefins); gasoline additives (MTBE, EDB, EDC)

Light distillate product identification and differentiation; determining the refining history of the gasoline and the degree of weathering

Modified EPA Method 8270; PAH and heteroatomic aromatic hydrocarbons by GC/MS

50+ diagnostic PAH; 2 to 6 ring polyaromatic hydrocarbons; C1 to C4 alkyl homologues; nitrogen-, sulfur-, and oxygen-containing PAHs

Long-term product/source identification, particularly middle distillates and crude oil; longterm weathering patterns; biodegradation indices; crude oil vs. other feedstocks (coal, etc.)

and/or product. Additives often have discrete time intervals during which they were introduced into a product formulation. The use of additives for hydrocarbon fingerprinting requires a prior knowledge of the additive package and the ability to detect a unique additive not masked by other chemicals or obscured by environmental degradation. An example of the former is the polybutene additive present in the Chevron detergent F-310 in gasoline in 1982. In practice, identification of an additive is not always straightforward. Many additives contain oxygen in their molecular structure and therefore are soluble and biodegradable. Furthermore, the polymers tend to depolymerize rapidly in the environment and convert into their respective monomers, which can be rapidly metabolized, thereby making it difficult to identify the parent additive compound (Galperin, 1997). Additives are sold to refineries by specialty companies with little or no chemical alteration by the refinery; as a result, the same additive may be present in the parent compounds of a comingled gasoline or fuel plume (Kaplan et al., 1997). Categories of fuel additives for different refined products and examples are shown in Table 4.14 (Ethyl Corporation, 1998; Gibbs, 1990, 1993; Harvey, 1997; Kram, 1988; Morrison, 1999b). The composition of additive packages for refined products varies with time. For ex-

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TABLE 4.12 (cont.) Opportunities and Challenges of Analytical Tests for Petroleum Hydrocarbons Analytical Method

Target Compounds

Utility

Modified EPA Method 8270; biomarkers by GC/MS

>50 steranes, diterpanes, and triterpanes: cyclic alkanes

Target compounds used to distinguish between petroleum sources; refractory marker(s) for improved biodegradation monitoring; identification of terminal petroleum degradation products

Modified EPA Method 8270; semi-volatiles by GC/MS

Polyaromatic hydrocarbons, Distinguishes sources (manufac alkyl polyaromatic hydrocarbons tured gas plants vs. gasoline, etc.)

Trace metal analysis, especially vanadium and nickel (EPA Method 6010 by ICP)

Trace metals, total lead, organic lead, nickel and vanadium

Possible delineation between sources of crude oil and presence of waste/crankcase oil

Ancillary analysis; simulated distillation testing (ASTM Method D3328); density

Carbon, hydrogen, sulfur, nitrogen isotope analysis; dyes, lead speciation, physical testing

Source identification and differentiation; age-dating of gasoline and crude oils

Adapted from Uhler, A. et al., in Proc. of the Environmental National Environmental Forensics Conference: Chlorinated Solvents and Petroleum Hydrocarbons, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, 1998, p. 24. With permission.

ample, a typical additive package for gasoline formulated in the 1980s was 62% tetraethyl lead, 18% ethylene dibromide, and 2% inactive ingredients such as stability improvers, dyes, and antioxidants (Younglass et al., 1985). Diesel and jet fuels contain additive packages. Additive packages for diesel include quality-enhancing packages such as diesel ignition and stability improvers, antistatics, corrosion inhibitors, and surfactants which are associated with discrete periods of time (Barker et al., 1991). Different sources of diesel can often be distinguished by analyzing the sulfur content of the diesel, which is usually different, depending upon the original source of the crude oil. Another method for distinguishing among different sources of diesel is to perform an analysis of the polynuclear aromatic (PNA) compounds in a sample and then perform a “peak-to-peak” comparison of these PNAs results between samples. PNA analysis in addition to the sulfur analysis can usually distinguish between two different diesel sources, prior to co-mingling. The identification of biomarkers such as isoprenoids that are unique to a particular diesel can also be used to distinguish differences between fuels. PNA analysis can assist in defining the relative age or use of motor oil. Used motor oil, for example, will contain more PNAs than a sample of the same oil that has not been used.

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TABLE 4.13 Potential Limitations of Analytical Test Methods EPA Method

Potential Limitations

413.1 Gravimetric

Provides results for total petroleum extractables; subject to interference and detection limit limitations

418.1 Infrared

Provides results for total petroleum extractables; subject to multiple interferences; false positive/negatives common, especially in organic matter; detection limit limitations

8015 GC/FID

Product identification subject to interpretation; similar product types cannot be differentiated (e.g., aviation gasoline vs. gasoline); false positives are common, especially biogenic sources.

8270 GC/MS

Reports only 16 priority pollutant polycyclic aromatic hydrocarbons; ignores important petroleum-related polycyclic aromatic hydrocarbons and provides little or no diagnostic qualitative information; detection limit limitations

8020/8260 GC/PIC and GC/MS

BTEX only (8020); 8260 misses 100+ important volatile hydrocarbons; detection limit limitations

Adapted from Uhler, A. et al., in Proc. of the Environmental National Environmental Forensics Conference: Chlorinated Solvents and Petroleum Hydrocarbons, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, 1998, p. 24. With permission.

TABLE 4.14 Examples of Additives for Selected Fuels Blended Product

Additive Category, Purpose, (Examples)

Gasoline

Anti-knock compounds to increase the octane rating, prevent engine knock, and reduce automobile emissions (alkyl leads, organo-manganese compounds) Antioxidants/stabilizers to prevent gum formation and degradation during storage and transport (p-phenylenediamine; alkyl-substituted phenols) Corrosion inhibitors to prevent storage/pumping failures (carboxylic acids and diimides) Detergents to prevent carbon deposits on carburetors and fuel injectors (amines, amine carboxylates) Dyes to provide color differentiation (azo- and other oil-soluble compounds such as azo-benzene-azo-naphthols, phenyl-azo-naphthols [red, orange, bronze], and alkylamino-anthraquinones [blue]) Anti-icers to prevent icing in carburetor and fuel systems (short-chained nalcohols (freeze-point depressants; amines and ethoxylated alcohols with long hydrocarbon chains)

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TABLE 4.14 (cont.) Examples of Additives for Selected Fuels Blended Product

Additive Category, Purpose, (Examples) Oxygenates to increase the octane number and respond to environmental requirements (methanol, methyl-tertiary butyl-ether [MTBE], methyl ether) Lead scavengers to prevent precipitation of lead in the engine and exhaust system (ethylene dibromide [EDB], ethylene dichloride [EDC]) Metal deactivators to inhibit oxidation and gum formation catalyzed by certain metals, particularly copper (chelating agents) Demulsifiers to improve water separation (polyglycol derivatives) Deposit control agents to prevent and remove deposits throughout the fuel intake system (polybutene amines, polyether amines)

Diesel

Antioxidants, stabilizers, and anti-rust inhibitors such as ethoxylated alkyl phenols, alkenyl succinic acids, and amine phosphates used to prevent degradation and rusting during storage and transport Cetane improvers for consistent combustion characteristics and emission reduction (alkyl nitrates, hydroperoxides) Cold-flow improvers to enhance fuel pumping Conductivity modifiers to neutralize static charge build-up in fuel Detergents/dispersants to prevent carbon deposits on engine parts (synthetic sulfonates, phenates, salicylates, phosphonates, Mannich bases, succinate esters, succinimides) Dyes for fuel identification and leak detection (see dyes for gasoline) Biocides used to inhibit the proliferation of bacteria and fungi (organo-boron compounds) Lubrication agents Pour-point depressants used to reduce the yield stress of the fuel and improve the flow of the diesel at low temperatures (polymethacrylates, alkylated naphthenes, ethylene vinyl acetate copolymers, fumarate-binylacetate copolymers, alkylated polystrene, acylated polystrene, polyolefins, aliphatic amine oxides, and oxidized wax)

Crankcase oils

Antioxidants to resist high-temperature degradation Anti-wear agents to protect metal surfaces from abrasion Corrosion inhibitors to protect metal parts Detergents to prevent carbon and varnish deposits on engine parts Dispersants to keep engine parts clean Pour-point depressants to enable oil flow at cold temperatures Viscosity index improvers to provide uniform flow properties over a wide range of temperatures

Specialty oils (automatic transmissions, hydraulics)

Antioxidants to resist high-temperature degradation Anti-wear agents to protect metal surfaces from abrasion Corrosion inhibitors to protect metal parts Detergents to prevent carbon and varnish deposits on engine parts Friction reducers to facilitate movement

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TABLE 4.15 Chronology of Lead Usage in Gasoline Date

Significant Changes in Lead Usage in Gasoline

1923

Tetraethyl lead marketed by Refiner’s Oil Company, Dayton, OH

1924

General Motors and DuPont Corp. form Ethyl Corp. to market and produce tetraethyl lead

1926

The U.S. Surgeon General recommends 3.17 g/gal as the maximum allowable concentration of tetraethyl lead per an agreement with Ethyl Corp.

1927/8

Approximate time for the introduction of lead scavengers (EDB and EDC)

1959

Maximum permitted lead in gasoline increased to 4.23 g/gal

1960

Trimethyl and tetramethyl lead introduced; tetraalkyl lead (TAL) added to commercial gasoline in the U.S. (Messman and Rains, 1981)

1969

Tertiary butyl alcohol (TBA) introduced

1970

Low-leaded gasoline introduced by Gulf Oil Company (now Chevron)

1974

The U.S. Environmental Protection Agency (EPA) requires major gasoline retailers to sell one grade of unleaded gasoline by July 1, 1974

1975

EPA calls for the reduction of lead in automobile gasoline to 1.7 g/gal in 1975, 1.4 g/gal in 1976, 1.0 g/gal in 1977, 0.8 g/gal in 1978, and 0.5 g/gal in 1979

1980

EPA established the overall lead for large refiners at 0.5 g of lead per gallon

1982

EPA set the average lead concentration for leaded gasoline at 1.10 g of lead per gallon for large refiners

1983

EPA established the average lead content for leaded gasoline of [how much?] lead per gallon for all refiners; lead credits were established

1985

EPA limited the concentration of lead to 0.50 g per gallon in June; lead credits were allowed; many states began phasing out lead in the gasoline during the middle to late 1980s

1986

EPA limited lead content to 0.10 g per gal in January; lead credits were allowed; decrease to 0.10 was scaled from 1986 to 1988

1987

EPA eliminated lead credits

1995

Over 50 countries (20 in Africa) permitted lead in gasoline at concentrations up to 0.8 g/L; maximum concentration in Europe was 0.15 g/L

1996

EPA eliminated lead in all U.S. gasoline per Section 211(n) of the Clean Air Act after 1995

4.8.3 ANTI-KNOCK ADDITIVES (ALKYL LEADS) Chronologies based on gasoline additives and characteristics of gasoline blending are usually useful in providing an age-dating resolution of 5 to 10 years. In many cases, this resolution is sufficient. Alkyl leads, the most frequently encountered anti-knock additives, were added to gasoline to suppress “spark knock” and to increase the octane number. On December 9, 1921, Thomas Midgley and Tom Boyd of General

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Motors Research Corporation discovered that tetraethyl lead (Pb(C2H5)4) was an effective anti-knock additive. Gasoline with tetraethyl lead (also referred to as lead tetraehide, tetraethyllead, and tetraethylplumbane) was first marketed on February 1, 1923, at a service station of the Refiners Oil Company in Dayton, OH (Nickerson, 1980; Rhue et al., 1992). In August of 1924, General Motors and Standard Oil Company of New Jersey (now Exxon Corporation) formed a partnership to create Ethyl Gasoline Company (now Ethyl) to market tetraethyl lead. Ethyl Corporation began marketing TEL at the end of 1947, and DuPont Corporation began marketing TEL in 1948. By 1950, most gasoline in the United States contained lead. In 1960, tetramethyl and trimethyl lead (marketed by Standard Oil Company of California, now Chevron Corporation) were introduced (Stormant, 1960). Consumption of all lead alkyls peaked in 1969 and declined through the 1970s as improvements in catalytic reforming, hydrocracking, and hydrotreating occurred which further improved base gasoline octane levels (Global Geochemistry Corp., 1991; Lee et al., 1992). For premium-grade gasoline, these concentrations were as much as 2.9 g/gal. Subsequent reductions in lead concentrations in gasoline occurred due to regulatory concerns in the late 1970s until 1985. Tetraethyl lead was reportedly the only alkyl lead additive added to leaded fuels after 1980. Only tetraethyl lead is currently used as an additive in leaded gasoline in amounts up to two orders of magnitude less than added before 1980. The history of lead additives in gasoline frequently provides a basis for bracketing the age of the gasoline in the soil or groundwater. Table 4.15 is a chronology of significant changes in the use of lead in blended fuels (Gibbs, 1990; Harvey, 1998; Morrison, 1999b). Tetraethyl, triethylmethyl, and methyldiethyl tetramethyl lead are the most common organic lead alkyl additives. Lead additive packages often contain multiple combinations of these lead additives as well as redistribution reaction mixtures of tetraethyl and trimethyl lead. Redistribution reactions of equimolar amounts of tetraethyl and tetramethyl leads can also produce trimethyl, trimethylethyl, dimethyldiethyl, and methyltriethyl lead (Christensen and Larsen, 1993). Reacted mixtures of leads are typically marketed as RM25, RM50, and RM75, with the number designating the molar percent of trimethyl lead present in the mixture (Sout et al., 1999b). A typical commercial reaction mixture from the use of equimolar amounts of tetraethyl lead and trimethyl lead is 3.8% trimethyl lead, 23.4% trimethylethyl lead, 42.4% dimethyldiethyl lead, 25.6% methyltriethyl lead, and 4.8% triethyl lead (Kaplan et al., 1997). Physical mixtures of unreacted combinations of tetraethyl and tetramethyl leads are described in percentages, such as 20:80, 50:50, 80:20, etc. Tetraethyl lead is a historical gasoline additive used to suppress pre-ignition and to improve the octane rating of the fuel. Older gasoline included tetraethyl lead along with lead scavengers such as ethylene dibromide and ethylene dichloride (1,2dichloroethane). Tetraethyl lead is usually clear, unless red, orange, or blue dyes are added. Tetraethyl lead was blended with gasoline prior to 1985 at about 400 to 500 mg/L. The presence of organic lead in free product is therefore indicative of a pre1985/86 release. Tetraethyl lead is currently being phased out of gasoline. Given that tetraethyl lead has a low water solubility and high organic solubility, it can reside in

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FIGURE 4.6 Lead pool standard at a refinery from 1965 to 1991.

soil after the fuel has evaporated and/or biodegraded. Conversely, tetraethyl lead can be remobilized and dissolved by a subsequent gasoline release migrating through the same soil. Tetraethyl lead is not present in condensate, distillates, or naphtha (Bruce and Schmidt, 1994). The presence and concentration of organic lead in soil or groundwater samples has been argued as a means by which to determine when the fuel was released into the subsurface. In 1982, the maximum lead concentration in gasoline was 4.2 g/gal. In 1984, the U.S. Environmental Protection Agency (EPA) set a maximum of 0.1 g/ gal. This concentration applies to the average quarterly production from a refinery or pool standard. The pool standard is the total grams of lead used by a refinery in a given time period divided by the total amount of gasoline manufactured in the same time frame. As a result, individual batches of gasoline can contain 4.2 g/gal per EPA requirements and 0.8 g/gal in California. It has been argued that these guidelines can be used to predict the time frame during which the product was manufactured or how long the gasoline has been present in the subsurface. This approach is illustrated in Figure 4.6, in which the lead pool standard for a refinery is plotted from 1965 to 1991. A soil sample with a lead concentration of 0.5 g/gal is argued as being representative of a highly weathered gasoline that was released prior to 1985. A challenge to this argument is that lead results of an individual sample are not conclusive because the lead content for any point in time is based on the pool standard. The consequence of this practice is that individual gasoline samples vary from batch to batch and cannot be used to date the year of manufacture. The pool standard may also not reflect any true refinery amount due to lead accounting practices (lead credits are bought or sold) and the fact that they are usually averaged quarterly. In addition, multiple releases of gasoline from 1985 to 1991 with low concentrations could result in an accumulated lead concentration of 0.5 g/gal rather than providing evidence of a pre-1985 gasoline release. Other anti-knock ingredients used in fuels include nickelcarbonyl and ironbased compounds such as dicyclopentadienyl iron and iron pentacarbonyl; the latter

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TABLE 4.16 Chronology of MMT Usage Date

MMT Usage

1953–58

Ethyl Corporation discovered and introduced MMT as an anti-knock compound for gasoline; marketed it as a performance additive under the trade name HiTec 3000 MMT/lead additive package marketed by Ethyl as AK-33X; not widely used MMT first used independently, without lead, in concentrations up to 0.125 g/gal MMT banned from unleaded gasoline per the Clean Air Act amendments in October; temporarily reinstated in the summer of 1979 during the peak summer driving months to help extend crude oil due to the Arab oil embargo; ban on MMT was reimposed in 1979, and MMT is still used in leaded gasoline On July 11, the EPA administrator granted Ethyl Corporation’s application for a fuel additive waiver for MMT use in unleaded gasoline; on October 20, a threejudge panel of the U.S. Court of Appeals ruled that MMT could be used in unleaded gasoline; in December, Ethyl began shipping MMT to oil company customers EPA eliminated leaded gasoline, including those that contained MMT MMT banned in Canada

1959 1974 1978–79

1995

1996 1997

compound was marketed in Germany in the 1930s at concentrations of less than 0.5% by volume (Calingaert, 1938). Iron pentacarbonyl is a common metal compound that was marketed in the 1930s. Another anti-knock compound is the manganese additive, methylcyclopentadienyl manganese tricarbonyl (MMT; CH3C5H4Mn(CO3)), which was introduced in the U.S. in 1957 and used as an anti-knock and lead alkyl supplement until 1978. MMT was later commercialized as a supplement to tetraethyl lead (Ethyl Corporation, 1996; Gibbs, 1990; Hurst et al., 1996). Between 1976 and 1990, nearly 70 million pounds of MMT were blended with gasoline sold in the U.S. Table 4.16 is a chronology of the use of MMT usage in the U.S. (Ethyl Corporation, 1998; Gibbs, 1990a,b, 1993; Harvey, 1998; Stout et al., 1998a,b). MMT synonyms and trade names include CL-2, Combustion Improver-2, manganese tricarbonyl-methylcyclopentadientyl, and 2-methylcyclopentadientyl. Although MMT can be age diagnostic, its absence in gasoline does not necessarily indicate a basis for age-dating, as it was not routinely added by all manufacturers. It is currently an additive in Canadian gasoline. Analytical techniques are not readily available to test for MMT and usually require a specialty laboratory to perform the analyses.

4.8.4 LEAD SCAVENGERS The initial use of tetraethyl lead as an anti-knock compound resulted in metal corrosion caused by lead oxide formation in the combustion chamber which damaged spark plugs and exhaust valves. The lead scavengers ethylene dibromide (EDB) and ethylene dichloride (EDC) were first introduced in 1928 to alleviate this problem

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(Kaplan et al., 1997). These lead scavengers minimized the precipitation of lead oxide formation within automobile engines. During engine combustion, the ethylene dibromide or ethylene dichloride forms lead bromide or lead chloride, both of which are relatively volatile and pass through the engine with the exhaust. EDB and/or EDC in a lead package is determined by the amount of alkyl lead present. A sufficient amount of scavenger is added to react theoretically with all the lead, which is termed “one theory”. Typically, 1.0 to 1.5 theories were used. A typical mixture for automotive gasoline in the 1980s consisted of about 62% tetraethyl lead, 18% ethylene dibromide, 18% ethylene dichloride, and 2% inactive ingredients such as dyes, antioxidants, petroleum solvent, and stability improvers (Galerpin, 1997). EDB is currently used in aviation piston engines. Ethylene dibromide and EDC are moderately soluble (4321 mg/L and 8.69 g/L, respectively, at 20∞C) and quickly dissolve into groundwater. Given that lead alkyls are strongly adsorbed to soil and tend to be hydrolyzed with water, the presence of lead scavengers may be the only evidence regarding the release of a leaded gasoline at a site. For phase-separate gasoline in groundwater, the longer that the gasoline is in contact with water, the more EDB or EDC will solubilize into the water, thereby providing a relative basis to compare the length of time that the gasoline has been in contact with the groundwater. The ratio of total alkyl lead and EDB and/or EDC concentrations present in phase-separate gasoline in groundwater can be used to identify multiple gasoline releases. Figure 4.7 illustrates the measurement of this ratio in 1980 and 1984; the lower figure indicates both the presence of the initial and subsequent release and the approximate location of the second spill relative to the first release.

4.8.5 OXYGENATES Oxygenates are blended with gasoline for the purpose of increasing the oxygen content and reducing carbon monoxide emissions. The American Society of Testing for Testing Materials defines an oxygenate as “an oxygen-containing, ashless, organic compound, such as an alcohol or ether, which can be used as a fuel or fuel supplement” (Gibbs, 1998). Numerous oxygenates have been used; ethanol, for example, dates back to antiquity, while the tertiary alkyl ethers were first produced in 1907. Table 4.17 lists various oxygenates blended with gasoline (Gibbs, 1998; Davidson and Creek, 1999). Selected chemical and physical properties of these oxygenates at 25∞C can be found in Table 4.18 (Gibbs, 1998; Harvey 1998; Montgomery, 1991), and a more complete list of physical properties is provided in Appendix C. Ethanol was first blended with gasoline in the U.S. in the 1930s and 1940s, although its widespread use did not occur until after 1978. The purpose of blending ethanol with gasoline was to increase the octane quality and to act as a fuel extender. Ethanol has historically been produced via the fermentation of corn or sugar cane. Ethyl-tertiary-butyl-ether (ETBE) was available in 1969 and was blended with methanol in 1981, although methanol blends are no longer used (Gibbs, 1998).

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FIGURE 4.7 Use of the total alkyl lead to EDB concentration ratio to identify multiple releases and approximate locations.

TABLE 4.17 Acroymns and Chemical Formulas for Oxygenates Compound Methanol Ethanol (ethyl alcohol) Methyl-tertiary-butyl-ether Tertiary-butyl alcohol Tertiary-amyl-methyl-ether Ethyl-tertiary-butyl-ether Diisopropyl ether

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Acronym MeOH EtOH MTBE TBA TAME ETBE DIPE

Chemical Formula CH4O C2H5OH (CH3)3COCH3 C(CH3)3OH C(CH3)2(C2H5)OCH3 C(CH3)3OC2H5 (CH3)2CHOCH(CH3)2

TABLE 4.18 Selected Chemical and Physical Properties of Oxygenates Specific Gravity

Henry’s Law Constant (atm m–3)/mol

Water Solubility (mg/L = ppm)

0.796 0.794 0.744 0.791 0.73 0.77 0.73 1.07

4.4 ¥ 10–6 5.1–6.2 ¥ 10–6 1.1 ¥ 10–3–5.8 ¥ 10–4 1.04–1.4 ¥ 10–5 2.6 ¥ 10–3 1.2 ¥ 10–3 4.7-9.9 ¥ 10–3 2.7 ¥ 10–4

Infinitely soluble Infinitely soluble 43,000–54,3000 Infinitely soluble 76,500 20,000 9000 (20∞C) 40,000

Oxygenate Methanol Ethanol MTBE TBA ETBE TAME DIPE Tertiary-butyl formate (TBF)

Atlantic Richfield Company (ARCO) began using methyl-tertiary-butyl alcohol in 1979 via the catalytic reaction of isobutylene (CH3)2C=CH2) and methanol (CH3OH). MTBE usage increased rapidly in the 1980s at a rate of about 40% per year (Steffan et al., 1997; Suflita and Mormile, 1993). In 1992, the production capacity and actual production of MTBE in the U.S. were 11.6 and 9.1 billion pounds, respectively. By 1993, MTBE was the most widely used oxygenate and was the second most produced organic compound in the U.S. (Reisch, 1994). In 1997, approximately 8 billion kg of MTBE were produced in the U.S. (Hitzig et al., 1998). MTBE is currently the most widely used oxygenate, although TAME, ETBE, and DIPE are also blended with gasoline There are currently 27 companies in the U.S. that produce MTBE. MTBE is also imported into the U.S. from Alberta Envirofuels in Canada and from Citgo in Argentina. Methyl-tertiary-butyl-ether was initially added as an octane-enhancing replacement for tetraethyl lead, which was being phased out; it was later used as a fuel oxygenate to decrease the amount of carbon monoxide in automobile emissions and to improve the tolerance for moisture in gasoline (Chapelle, 1999). MTBE is not, however, contained in all post-1980 gasoline. MTBE is blended with reformulated gasoline that is required for severe ozone non-attainment areas that do not meet federal ozone ambient air quality standards. Current unleaded gasoline contains as much as 15% (Oxy-fuels) while many states use MTBE as an octane booster at up to 8% by volume. MTBE was introduced into east coast, gulf, and midwest gasoline after 1979/80 and into west coast gasoline after 1990. Its documented use on the east coast was from 1979, and in California after 1986 (Davidson and Creek, 1999; Squillance et al., 1996). Since the 1990s, it has been used in gasoline in over 15 states to meet federal Clean Air Act of 1990 requirements for oxygenates in wintertime oxygenated gasoline (starting in 1992) and in federal reformulated gasoline in 1995 to meet carbon monoxide ambient air quality standards (CEPA, 1996). As this chapter was being written, Chevron, Tosco, and other oil companies are phasing out MTBE from unleaded gasoline. Tosco, for example, plans to replace MTBE with

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TABLE 4.19 Chronology of Oxygenate Use Date

Usage

1907 1934

First TAME produced; agrol, alkylgas, ethanol fuels used in Nebraska First tertiary alkyl ether synthesis patent in the U.S. issued; methanol fuels used in Germany due to World War II; Alkyl-Gas (ethanol blend) marketed in Nebraska Chevron taxicab field test of MTBE/TAME; ARCO first used tertiary butyl alcohol in gasoline Clean Air Act Amendment required waivers; MTBE first used by ARCO; Nebraska gasohol (ethanol blend) program began; EPA waiver issued for 10% by volume for ethanol EPA waiver issued for 7% volume for MTBE; MTBE use began; EPA waiver issued for 2.5% each for methanol and tertiary butyl alcohol; MTBE included in gasoline in the eastern seaboard from 1979 to the mid-1980s (Garrett et al., 1986; McKinnon and Dyksen, 1984) Experimentation with MTBE, methanol (M85), and ethanol as octane boosters; east coast transmission lines pumped MTBE; EPA “substantially similar” rule issued with 2% by weight oxygen maximum limit (11% by volume for MTBE) Denver began wintertime oxygenated gasoline program using MTBE (ethanol subsequently used); Colorado required oxygenates EPA waiver issued for 15% by volume for MTBE as the maximum amount Phoenix, Las Vegas, Reno, and Albuquerque began wintertime oxygenated gasoline program using MTBE (ethanol used later); Clean Air Act Amendments enacted; “substantially similar” maximum oxygen limit increased to 2.7% by weight (15% by volume for MTBE) Oxygenates required during the winter in carbon monoxide non-attainment areas; ethanol used where economical; federal wintertime oxygenated gasoline program required 2.7% by weight minimum oxygen in 39 carbon monoxide non-attainment areas Tertiary-methyl-ether and ETBE usage became limited; reformulated gasoline ozone nonattainment areas; federal reformulated gasoline program required 2.0% by weight minimum oxygen content; California Phase 2 required reformulated gasoline by requiring 1.8– 2.2% by weight oxygen; 95% of all gasoline sold in California contained MTBE (Davidson and Creek, 1999) California Health and Environmental Assessment of MTBE report recommended the gradual phase-out of MTBE in California gasoline (Keller et al., 1998) Chevron and Tosco begin gradual phase-out of MTBE in unleaded gasoline; town of South Lake Tahoe, CA, banned MTBE because of concerns about its potential impact on the town’s drinking water supply

1968 1977 Late 1970s

1980s

1987 1988 1989

1992

1994

1998 1999

ethanol. Table 4.19 is a chronology of oxygenate usage from 1907 to 1999 (Gibbs, 1998; Harvey, 1998). Methyl-tertiary-butyl-ether is about 25 time more soluble than benzene (approximately 42,000 mg/L) and is not retarded by soil as it travels in groundwater. As a result, MTBE is frequently encountered in post-1980 gasoline releases. Of 5738 sites in California in 1988 that were being monitored by the California State Water Resources Control Board because of groundwater contamination from gasoline, 3180

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(55%) detected MTBE (ranging from 0.5 to 20 mg/L). MTBE plumes in groundwater are longer than BTEX plumes due to the absence of MTBE retardation. In field studies of unconfined, sandy aquifers, MTBE migrated at the same rate as groundwater, while benzene, toluene, and ethylbenzene/xylene migrated at about 90%, 75%, and 67% of the groundwater velocity, respectively (API, 1994). At a site in South Carolina, gasoline containing MTBE was transported at the same rate as groundwater, while benzene was transported about 80% of the same distance (Landmeyer et al., 1998). This retardation factor of 0.8 with respect to groundwater is consistent with observations at other sites. As a result, MTBE is often found at the leading edge of a groundwater plume without the presence of the other BTEX compounds; in these situations, its presence can be used qualitatively as an indicator of the length of the downgradient plume. Methyl-tertiary-butyl-ether and other fuel oxygenated can be determined using purge and trap gas chromatography methods such as EPA Method 502.2 or ASTM D481.5 using gas chromatography with multiple columns (Draper et al., 1998). If EPA Method 8020 is used, there is a 1 to 3% probability of a false positive test result as various methyl pentanes and methyl pentenes often co-elute with MTBE. ETBE, TAME, and DIPE can also be reliably determined using EPA Method 524.2 with low detection limits and high accuracy. MTBE concentrations are reliably determined with mass spectrometry, which bases MTBE identification on the retention time and the mass spectral features of the gas chromatograph peak. When using MTBE and other oxygenated additives in forensic evaluations for age-dating, identify the potential sources of bias impacting the interpretation of MTBE data. Examples include the following (Davidson and Creek, 1998; Hitzig et al., 1998): • • • •

Potential false positives from laboratory testing Additives from non-point sources Incidental blending and/or mixing of additives in gasoline supplies Cross-contamination from one fuel to another, especially in pipelines and tanker trucks • Differences due to seasonal reformulations • Product swapping by the gasoline jobbers or in exchange agreements between refineries and bulk storage facilities (Davidson and Creek, 1998; Hitzig et al., 1998)

Given the high volatilization potential and solubility of MTBE in water, its presence in groundwater may not be indicative of a liquid release. The presence of MTBE in groundwater may be from a non-point source, especially at concentrations <10 ppb (Pankow et al., 1997). Nonpoint sources include stormwater runoff (0 to 15 mg/L) and surface water sources, such as watercraft (0 to 40 mg/L) (Davidson, 1999). Methyl-tertiary-butyl-ether can cross-contaminate non-gasoline products due to shipping and storage in pipelines, tankers, above-ground storage tanks, and trucks. MTBE has been detected in the presence of jet fuel, diesel fuel, heating oil, aviation gas, and waste oil (Hitzig et al., 1998). In Connecticut, for example, 27 of 37 heating oil spill sites detected MTBE in groundwater at concentrations from 1 to 4100 mg/L

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(Davidson, 1999). The classic example of an indirect source of MTBE is its detection in groundwater under an underground storage tank containing gasoline with MTBE that has not leaked. The transport mechanism of MTBE from the tank is usually via vapor leakage from the tank, movement of the vapor cloud through the vadose zone as a function of density and convection, and resolubilization of the MTBE into the groundwater (Hartman, 1998b). This transport mechanism occurs because of the high solubility of MTBE relative to its equilibrium concentration in air. If this transport scenario is suspected, test the soil vapor with a flame ionization detector for the lower alkanes (C4 through C8), as they tend to remain in the vapor phase. In addition, soil and/or groundwater samples should be tested for MTBE with a photoionization detector. Benzene may also be present in the soil vapor and water but not present at significant concentrations in either phase. Field studies of MTBE biodegradation in shallow aquifers indicate that while MTBE is biodegradable, it is low relative to BTEX compounds (Landmeyer et al., 1998). MTBE degrades anaerobically under iron and sulfate reducing (Mormile et al., 1994). Potential biotransformation intermediates of MTBE include tertiary-butyl formate (TBF) and tertiary-butyl alcohol. As a result, it may be useful to perform analysis for tertiary-butyl formate and/or tertiary-butyl alcohol concentrations along with MTBE as an additional confirmation of the presence of MTBE.

4.8.6 TRACE INORGANICS Trace metal analysis can be useful in providing additional information regarding the type of hydrocarbon or fuel. Trace metals include barium, cadmium, copper, lead, mercury, silver, arsenic, cyanide, iron, selenium, nickel, vanadium, cobalt, beryllium, antimony, and zinc. Nickel, vanadium, and sulfur are present in low-gravity crude oils but are absent or present in minimal quantities in refined products. Waste oil is more likely to contain lead, zinc, chromium, copper, or aluminum from the abrasion of an engine than is a fuel or pristine oil. For example, the concentrations of vanadium and nickel are often several thousand times higher in a crude oil and can thereby be used as a marker to identify a crude oil. Vanadium-nickel ratios are used in oil field exploration to identify similar crude oil reservoirs (Potter, 1990). Metals are also fuel additives; the inclusion of barium and zinc to motor oil is one example. Calcium, phosphorous, and zinc are common additives to lube oils but are not predominant in crude oil. While not a trace metal, boron was a common gasoline additive in use from 1956 to 1981 and, if detected with gasoline, may provide an indicator of a pre-1981 formulation. Another example is the addition of borate to gasoline in the 1960s by ARCO.

4.8.7 PETROLEUM DYES Gasoline and other fuels can contain dyes used to distinguish between the fuels. The use of dyes in gasoline was the result of an agreement concerning tetraethyl lead

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between Ethyl Corporation and the U.S. Surgeon General in 1926. The agreement required that a sufficient amount of dye be added to impart staining qualities to leaded gasoline to deter its usage for cleaning or other purposes. Dyes are also used by some states to identify that no highway tax has been paid or that the gasoline is used for non-highway (agricultural) applications. An impurity in a commercial dye may be measurable and thereby provide a means by which to distinguish between products with different dyes. For example, yellow gold and pink/red dyes are added to gasoline to distinguish among different grades of gasoline. Blue, yellow, and red dyes are used to differentiate octane ratings in aviation gasoline (Ward, 1984). Typical concentrations for a dry dye range from 0.7 to 1.3 g/100 gal (Youngless et al., 1985). Plate 4.2* shows dye additives for different gasoline brands obtained via thin layer chromatography. Commercial dyes used as gasoline additives (approximately 1 to 5 ppm) are usually part of a lead anti-knock package containing lead scavengers that are added at the refinery at the in-line blender or the finished fuel-blending tank. Common dyes include (Kaplan et al., 1996a, 1997): • • • •

Red (alkyl derivative of azobenzene-4-azo-2-naphthol) Orange (benzene-azo-2-naphthol Yellow (para-diethyl aminoazobenzene) Blue (1,4-diisopropyl-aminoanthraquinone).

The high-resolution mass spectral chromatograms for 21 commercial dyes were examined by Youngless et al. (1985). The empirical formulas of the dyes suggested azo-, diazo-, and anthraquinone-type structures. In some cases, the dye was multicomponent, such as in the case of a bronze dye. Dyes in gasoline are analyzed with either thin layer chromatography or by ultraviolet-visible absorption spectrometry (Touchstone, 1992). Specialty analytical laboratories that have experience in this analysis are recommended if this analysis is to be performed and relied upon as evidence. While dyes have been used for more than 55 years in gasoline, there is little information on dyes other than in patent disclosures. Furthermore, the movement of gasoline with dyes through the soil can result in contamination by polar compounds that can obscure the dye bands. For example, red and orange dyes can assume a dark brown color (Kaplan and Galperin, 1996a,b). Other challenges include (Galperin, 1997): • The difficulty in distinguishing among dyes when several gasoline blends have comingled (red and orange dyes become dark brown) • The rapid biodegradation of the dyes in the subsurface (probably due to hydrogenation and subsequent destruction of the conjugated structure) • The high solubility of the dyes

* Plate 4.2 appears at the end of the chapter.

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4.8.8 OCTANE RATING Petroleum refineries boost the octane rating or content of a gasoline via alkylation. The alkylation process involves the heating of volatile olefins with sulfuric or hydrofluoric acid to produce branched-chain alkanes. During the alkylation process, the content of the major isoalkane generated is 2,2,4-trimethylpentane (TMP), which increases relative to the content of methylcyclohexane (MCH), which is present in crude oil and refined volatile fuels. Low-octane (87) fuels exhibit a TMP/MCH ratio less than 2.5, while high-octane (92 or 93) gasolines have TMP/MCH ratios of 2.5 to 5.0 (Kaplan et al., 1997). If the octane rating of gasoline in a co-mingled plume is known, these ratios may provide a means to distinguish between the gasoline sources.

4.9 RADIOACTIVE ISOTOPE DATING Radioactive isotopes are used to identify the origin of petroleum hydrocarbons and chlorinated solvents and as well as for estimating contaminant transport travel times. Isotopes (Greek isos, meaning equal, and topos, meaning place) are atoms that differ in mass due to different numbers of neutrons in the nucleus of the atom. Most isotopes are stable (i.e., not radioactive). Those that are radioactive emit particles and energy from the nucleus that eventually produce a stable isotope of a different element. Radioactive isotope dating relies upon isotope ratios for various atoms that are used to distinguish among elements. Isotopes for age-dating are less affected by weathering than many chemical ratios, although isotope ratios of lighter fractions are more heavily altered by weathering than heavier fractions. This dating technique is based on the concept of half-life, which is the time required for half of an original isotope mass to decay. The half-life of carbon-14 (14C), for example, is 5730 years which means that a gram of (14C) decays to .5 g in 5730 years. Half-lives for various radioisotopes range from less than a second to billions of years. Radioisotope units are reported in picoCuries. Tritium (3H) is a short-lived isotope of hydrogen with a half-life of 12.43 years. Tritium concentrations are expressed as absolute concentrations using tritium units (TU). One TU corresponds to 1 3H atom per 1018 atoms of hydrogen, or 3.2 picoCuries per kilogram (pCi/kg) of water (Mann et al., 1982; Taylor and Roether, 1982). Most groundwater has TU concentrations in the <1 to 10 TU range (Clark and Fritz, 1997). These ratios, such as 13C/12C, are denoted as d13C. Isotopic results are usually expressed in standard d-‰ fashion against the Vienna Standard Mean Ocean Water (VSMOW) (d2H) or the Vienna PeeDee belemnite (VPDB) (d13C), according to the following relationship for (13C) (Cane et al., 1999): d13Csample = (Rsample/RVPDB – 1)103 ‰ VPDB where R = 13C/12C.

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(Eq. 4.3)

The analytical equipment used for analyses is either gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) or compound-specific isotope analysis (CSIA). GC/C/IRMS provides rapid, cost-effective analysis with four to five orders of magnitude more sensitivity than conventional techniques. GC/C/IRMS also permits determination of the isotopic composition of individual compounds in complex mixtures. GC/C/IRMS provides a rapid and cost-effective analysis with four to five times orders of magnitude more sensitivity than conventional techniques. This equipment provides the ability to perform d13C analysis on dissolved organic contaminants present at concentrations of parts per million to parts per billion. The sample volumes required for this analysis range from tens to hundreds of millimeters. For samples with dissolved contaminants, such as BTEX, a comparison of d13C values for pure-phase BTEX compounds are identical to d13C values of the compounds after pentane extraction from groundwater with dissolved BTEX (Dempster et al., 1997). In the case of distinguishing multiple sources of crude oil that have undergone extensive weathering and water washing, GC/C/IRMS can complement traditional gas chromatography (GC) or gas chromatography/mass spectrometry (GC/MS). Severe biodegradation of the crude oil can result in the loss of biomarkers (C27 to C29) and demethylation of others (C27 to C35 hopanes) that are often used to distinguishing among different crude oil sources. In addition, the refining process can affect the use of biomarkers for source identification. In straight-run distillate products, biomarkers are affected only by the distillation temperature; while in cracked/ hydrotreated products, biomarkers can be affected by temperature, catalysts, and hydrogen. In cases where the crude oil has lost all of its normal alkanes, isolation and pyrolysis of the asphaltenes followed by GC/C/IRMS of the individual pyrolysis products can be used (Mansuy et al., 1997). For refined products, the correlation of refined products dominated by the normal alkanes in the C10 to C20 region that do not contain biomarkers are especially conducive to GC/C/IRMS analysis and interpretation. When examining pre- and post-1995 isotope values, realize that environmental isotope geochemistry requires standardization between laboratories. Reporting protocols and the use of different reference standards in the analysis may therefore be different between the pre- and post-1995 data. The current organizations providing isotope standards are the National Institute of Standards and Technology (Gaithersburg, MD) and the International Atomic Energy Agency (Vienna, Austria). Since 1995, the isotope community has adopted reporting and calibration standards proposed by the Commission on Atomic Weights and Isotopic Abundances of the International Union of Pure and Applied Chemistry (Coplen 1996; Coplen et al., 1983; IAEA, 1995).

4.9.1 DATING GROUNDWATER WITH ISOTOPES The two common radioactive isotopes used for age-dating groundwater are tritium (3H), which is an isotope of hydrogen and cesium-137 (137Cs) (Aeschbach-Hertig et al., 1998; Clark and Fritz, 1996; Ekwurzel et al., 1994; Fritz, et al., 1991). The half-

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FIGURE 4.8 Tritium chart for Ottawa, Canada, and Waco, TX.

life for cesium is 30.2 years. Tritium- and cesium-dating relies on the assumption that the presence of tritium and cesium above background levels is the result of their introduction from the atmospheric testing of thermonuclear devices. After 1953/54, the amount of tritium in rainfall increased until about 1963, when it began to decline. Secondary peaks were observed in 1973 and 1975 due to atmospheric testing by China and France. The majority of tritium in the atmosphere has therefore been removed. The presence of cesium in sediments was first observed in about 1954, which is the earliest date that this technique was used. Cesium concentrations peaked in 1963 and decreased with the exception of minor increases in 1971 and 1974 (Ritchie and McHenry, 1990). Other isotopes used for this purpose include 39Ar with a half-life of 268 years and 14C with a half-life of 5730 years. In practice, it may be possible to date the age of a groundwater sample relative to the 1963 tritium peak, as shown in Figure 4.8 for Ottawa, Canada, and Waco, TX. Age-dating groundwater is accomplished by computing the early and late ratio of tritium according to Equation 4.4: 3

Hearly sample ¥ elDt/3Hlater sample

(Eq. 4.4)

where l = 0.0565 yr–1 (tritium decay constant). Dt = the time between samples in years.

A ratio greater than 1 indicates that the tritium peak has been passed (later than 1963), while a ratio less than 1 indicates that the peak has not yet arrived (earlier than 1963).

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Another means for dating the age of groundwater is through the measurement of tritium’s decay product, helium (3He). If tritium and helium concentrations are measured, the tritium/helium age can be calculated according to Equation 4.5 (Aeschbach-Hertig et al., 1998): tgroundwater = t1/2/ln2 ¥ ln [1 + (3He/3H)]

(Eq. 4.5)

where t = 12.3 years (half-life of tritium). 3He/3H = helium/tritium concentration ratio (tritium units).

The conversion of concentration units needed to evaluate Equation 4.5 is given by 1 cm3 STP g–1 @ 4.019 ¥ 1014 tritium units (for freshwater). This technique can be used in conjunction with the tritium peak method as another method of verification. Carbon-14 and tritium can also be used to date the age of methane gas (Lundegard et al., 1999). Methane produced by the bacterial degradation of organic matter in the 1950s and 1960s contains elevated 14C concentrations greater than 100% modern carbon (pMC). Typical landfill and sewer gases contain 14C concentrations greater than 100 pMC, as they are typically produced from organic material less than several decades old. The presence of elevated tritium concentrations in methane indicates that it was produced from organic matter only several decades old. The tritium concentration in methane from some landfill gases is very high (Coleman et al., 1995).

4.9.2 ISOTOPIC ANALYSIS FOR PETROLEUM HYDROCARBONS Numerous opportunities exist to date and distinguish among multiple sources of petroleum hydrocarbons with isotope analysis (Murphy, 1998). An advantage to using isotope analysis for petroleum hydrocarbon fingerprinting is that asphaltene pyrolysis results in an isotopic fingerprint similar to the original hydrocarbon (Mansuy et al., 1977). The most widely reported include: • Lead isotopes • Crude oil and BTEX dating • Age-dating gas samples

Stable carbon isotope compositions are used to distinguish among natural gas samples. This application provides differentiation of gases from different sources and of different ages and whether or not they are of microbial or thermogenic origin (Philip, 1988).

4.9.3 LEAD ISOTOPE ANALYSIS A common isotope ratio used for identifying the origin of gasoline-impacted soil or water is lead isotope analysis. Lead naturally occurs as one of five isotopes, of which

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four are stable isotopes (204Pb, 206Pb, 207Pb, and 208Pb). These naturally occurring lead isotopes are the result of the following decays: 208Pb is a decay product of thorium (232Th); 207Pb is a decay product of uranium (235U), and 206Pb is a decay product of uranium (238U); however, 204Pb is not a product of radioactive decay. 210Pb is a radioactive form of lead which has a half-life of 22.6 years. 210Pb dating is used for sediment dating during the past 100 years. The decay sequence is from natural 238Ur (found in bedrock and soil) to radon-222 (222Rn), which decays in the atmosphere through a series of isotopes to 210Pb, which then precipitates from the atmosphere onto sediments. Lead radioactive isotopes are usually reported as ratios of 206Pb/204Pb, 206Pb/207Pb, or as a delta notation (d). Based on international standards, the isotope ratio is usually expressed in d notation. Isotope ratios are given a negative notation if the sample value is lower than the standard value (arbitrarily given as 0%) or as a positive value if the sample ratio is greater than the standard value. An example of delta notation is shown below (Hurst, 1998): d206Pb = 1000[(206Pb/207Pb)sample – (206Pb/207Pb)standard]/ (206Pb/207Pb)standard

(Eq. 4.6)

The stable isotopes of lead occur in different ratios, depending on the geologic formation from which they were mined. American ores, for example, have ratios of 206Pb/207Pb as high as 1.31, while Australian and Canadian ores have ratios of approximately 1.04 and 1.06, respectively. The most frequently used lead ratios for this purpose are 206Pb/207Pb and 206Pb/ 204Pb (Hurst, 1996). High-precision lead isotope ratio analysis is used to calibrate these changes in the lead isotope ratios as a function of time. This method is usually based on 206Pb/207Pb ratios; when plotted as a function of time between the late 1960s and the late 1980s as tetraethyl lead, a systematic trend is observed as a result of manufacturers shifting their source of lead supply. Hurst et al. (1996) plotted 206Pb/ 207Pb ratios between 1960 and 1990 and observed that distinct differences were observed for different years.

4.9.4 LEAD ISOTOPE ANALYSIS FOR GASOLINE FINGERPRINTING The key article introducing the use of the anthropogenic (i.e., gasoline derived) lead archeostratigraphy (ALAS) model to distinguish among multiple sources of dispensed gasoline was authored by Hurst et al. in 1996. The method is predicated on analysis of the lead isotope ratios of 206Pb/207Pb and lead concentration. This approach is based on the observation that the average stable isotope ratios of leaded gasoline were relatively uniform over intervals of one year. From 1964 to 1990, the 206Pb/207Pb ratios in U.S. gasoline and aerosols were measured, thereby providing a characteristic isotopic signature (Rosman et al., 1994). In addition to noting differences in the isotope ratios of the ores used for gasoline lead packages, this information

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provides a standard from which to compare lead isotope ratios from environmental samples From 1902 to about 1968, most industrial lead emissions in the atmosphere originated from geologically old lead ores with 206Pb/207Pb ratios between about 1.141 and 1.167 (Erel and Patterson, 1994). From 1968 to 1978, an abrupt change in these ratios occurred because the major lead source in the U.S. shifted to younger ores mined in Missouri which possessed anomalous high 206Pb/207Pb ratios of about 1.35. These ores constituted about 9% of the total industrial consumption in 1962 but increased to 27% in 1968, to 57% in 1971, and to 82% by 1976. After 1984, the 206Pb/ 207Pb ratios dropped to values of about 1.18 to 1.2 in 1989/90 (Sturkes and Barrie, 1987). A similar pattern reflecting the changes in the isotopic composition of lead in Arctic snow revealed that, between 1960 and 1980, the composition of lead in Greenland snow changed, which was consistent with the unique signature of U.S. lead. Lead in the snow since the mid-1970s reflected a reduction in the isotopic lead ratios which was attributed to the use of unleaded gasoline for motor vehicles in the U.S. (Boutron et al., 1991). Lead concentrations and 206Pb/207Pb ratios in tree rings in Croxteth, England, indicated a similar change believed to be due to vehicle emissions (Watmough et al., 1999). Analysis of the different lead isotope ratios with the lead concentration provides the basis for comparing these results with the ALAS model calibration curve. This relationship is defined as: D206Pb = K[(206Pb/207Pb)sample – (206Pb/207Pb)standard]

(Eq. 4.7)

where K is a constant. By plotting one isotope ratio against the other or a lead isotope ratio vs. the lead concentration, alleged patterns of data arise to distinguish among multiple sources. Other interpretations include observing a single cluster of data if from one source, multiple clusters if from multiple sources, or mixtures if the sources are linear to one another. It is reported that this technique allows one to establish the time of formulation to within 1 to 5 years. Examples of the degree of resolution for different time periods using this analysis include (Cline et al., 1991; Hurst 1998b, 1999c): • Pre-1965 • ±1 year for 1965 to 1980 • ±1.5–2 years for 1980 to 1990, with the larger errors occurring after 1985

After 1990, when gasoline became unleaded, age estimates can only be stipulated to be post-1990. Part-per-billion levels of lead observed in unleaded gasoline post1990 are assumed to be attributable to inherited lead from the crude-oil and refining process (Hurst, 1998). In instances where 206Pb/207Pb ratios are indistinguishable, the use of 206Pb/204Pb ratios may provide the necessary discrimination (Hurst, 1999a,b). Unleaded gasoline can contain lead concentrations in the parts-per-billion range which are amenable to lead isotopic testing. The concentrations detected are assumed to be reflective of both the geologic information from which the lead was obtained

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that is contained within an additive package as well as the refinery where the gasoline was produced (Hurst et al., 1996). This approach to date a contaminant release assumes that the lead additive producers, Ethyl Corporation and E.I. DuPont de Nemours, used similar ore feedstocks for their alkyl lead additive packages. The method also assumes that the same proportions were similar for any given year and that the sample is not reflective of co-mingled or multiple releases of gasoline with different lead additives (Hurst 1996). Other potential challenges include whether the standard used in the ALAS model can discriminate between industrial lead originating from unleaded gasoline and lead from other industrial sources. For example, lead concentrations in organic industrial sewage particles range from 500 to 1200 mg/kg (dry weight) for lead introduced into sediments in addition to lead originating from automobile exhaust and are used as standards for dating a gasoline release (Patterson et al., 1976). The analytical techniques employed should be carefully examined to determine whether natural vs. industrial lead that is indicative of leaded gasoline is discriminated and that no lead artifacts have been introduced. The stable isotope ratio of sulfur can identify source relationships between samples contaminated with heavy hydrocarbons. This information can be combined with other geochemical evidence to differentiate between hydrocarbon plumes and to identify where the plumes co-mingle in the soil and/or ground An interesting application of lead isotope ratios is a case in Benicia, CA, where about 40 horses died from chronic lead poisoning over a 20-year period (Rabinowitz and Wetherwill, 1972). Potential lead sources were a lead smelter, particles from exhaust from leaded gasoline, sandblasting of a lead-painted bridge across Carquiez Straight, and sandblasting of ships. Refineries in the area were believed to emit lead as a tetraethyl vapor. Lead ratios of 206/204Pb and 206/207Pb were used to evaluate the contribution of these sources, along with information such as the distance of these sources from the pasture land used by the horses for grazing and wind direction. The lead content of the horses’ kidneys and livers revealed concentrations of 9 to 16 mg/g on a fresh weight basis. The isotopic composition of the lead from the horseflesh did not coincide with the lead associated with the pasture grasses. Plotting of the 206/204Pb and 206/207Pb ratios for the various samples showed three distinct isotopic groupings: lead from gasoline, lead from the smelter and pasture grass, and the lead isotopic composition of the horse organs. Based on the isotopic ratios, it was concluded that the horses were poisoned from chronic lead poisoning from equal parts of smelter and gasoline lead.

4.9.5 ISOTOPE ANALYSIS OF CRUDE OIL AND BTEX Isotopic analysis has been used for both crude oil and for the aromatic compounds (BTEX) as a means to identify the origin of the petroleum hydrocarbon. Carbon and hydrogen isotopes are most commonly used for this purpose. The low 13C values of fuels and chlorinated solvents manufactured from fossil fuels can differ with the dissolved inorganic carbon in natural groundwaters. The d13C of the dissolved

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organic and inorganic carbon may thereby provide a basis of contrast in areas impacted by chemicals produced from fossil fuels. On a global scale, isotopic analyses of carbon and hydrogen are used to distinguish among crude oils produced from different oil reservoirs in the world. If one assumes that each refinery processes crude oil from a particular geographic area or oil basin for an extended period of time, the isotope ratios for the corresponding refined product are expected to be similar to that found in the crude oil. This approach is compromised if refined products from different crude oil stocks are blended at the refinery; small changes in the carbon isotope ratios of refined fuels can also result during the production of very light gases which tends to concentrate heavy isotopes in the product (Kaplan and Galperin, 1996). Another opportunity for distinguishing between different sources of a refined product or crude oil is to examine differences in sulfur isotopes (32S, 33S, 34S, and 36S). The 32S and 34S isotopes are the most commonly used for this purpose. This ratio analysis in conjunction with a peak-to-peak polynuclear aromatic (PNA) analysis, for example, could provide the basis for clearly distinguishing between different crude or refined products. Isotopic analysis of the BTEX compounds presents a promising opportunity for identifying discrete releases of gasoline from multiple sources. These approaches assume that hydrocarbons enter the subsurface with a distinct isotopic composition, or 13C/12C ratio, that is characteristic of their source. If this isotopic composition is conserved, stable carbon isotopic analysis can be used to identify different sources as well as natural background sources of hydrocarbons. The use of pentane to extract the sample and subsequent analysis of the d13C via GC/C/IRMS has been reported as a means to use isotopic analysis for BTEX in groundwater (Dempster et al., 1997). The authors discovered that the isotope ratios of d13C do not change as a function of the concentration of the BTEX in dissolved or free product samples. GC/C/IRMS analysis of pure phase BTEX indicated that different manufacturers produce chemical with distinct d13C compositions, probably attributable to different raw products and manufacturing processes for a discrete time interval. Cross-plots of deuterium and hydrogen ratios may similarly provide a means to distinguish among multiple BTEX sources. This technique may also be used to distinguish among different sources as function of the enriched d13C values of the BTEX compounds in a co-mingled gasoline plume. A case study of a site with groundwater contamination located at the Naval Construction Battalion Center, Port Hueneme, CA, illustrates the merit of acquiring multiple groups of independent forensic evidence to discriminate among sources (Kelley et al., 1997). In this case, these lines of evidence included: • The stable isotope ratio of 13C/12C reported as d13C • A comparison of degradation patterns of BTEX compounds • The presence or absence of MTBE in the groundwater samples

A full BTEX suite was analyzed before each set of isotope samples. d13C analysis was performed on groundwater samples with BTEX concentrations greater than about

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200 ppb. The d13C values were determined using a GC/C/IRMS system. Samples were analyzed in either duplicate or triplicate, resulting in four to six isotope numbers for each reported BTEX data point. Standard deviations were less than 0.5%. In some wells, a heavier d13C value was observed, indicating another BTEX source or a higher degradation rate and subsequent isotopic fractionation. It is expected that with normal isotopic fractionation, molecules with the lighter isotope (12C) react at a slightly faster rate, resulting in the enrichment of the residual molecules (i.e., 13C). Given the observation that a consistent degradation pattern was not observed in all of the compounds to account for the heavier d13C values, the d13C results indicated the potential for multiple sources of gasoline. The second group of evidence was the apparent difference between the ratio of BTEX compounds in samples for groundwater samples collected from different monitoring wells. Changes in the BTEX data through time revealed little change in concentrations. Given that toluene is the easiest BTEX compound to degrade, followed by xylene, benzene, and ethylbenzene, the presence of this degradation pattern was investigated. Among the individual BTEX compounds, toluene generally had the highest concentration, followed by benzene, para- and meta-xylene, ortho-xylene, and ethylbenzene. One well, however, revealed a BTEX pattern with the para- and meta-xylenes having the highest concentrations followed by benzene, toluene, ethylbenzene, and ortho-xylene. Assuming that similar degradation environments existed for the site, the difference in degradation patterns suggested the potential for multiple sources. Methyl-tertiary-butyl-ether analysis of groundwater samples when compared with samples with heavy d13C values indicated a second source of gasoline. The MTBE data also indicated the release of a leaded and unleaded fuel. These three groups of evidence were therefore corroborative and indicated a source of leaded and unleaded gasoline contamination from two sources. Another option is the use of 206Pb/207Pb as a potential tracer of MTBE sources. Studies in New Jersey and California indicate that shifts in 206Pb/207Pb ratios in groundwater occur with the entry of MTBE into the groundwater (Hurst, 1999a). This approach assumes that MTBE acts as a carrier of lead into the groundwater (Hurst, 1999b) When reviewing d13C values for BTEX compounds used to identify discrete source areas, examine the overall pattern of isotopic variation (e.g., individual BTEX plots) to ascertain if a clear pattern emerges among samples. A particular manufacturer, for example, may not have a single characteristic d13C signature for benzene throughout a given time period. Compound-specific isotope analysis for all of the BTEX compounds may therefore provide a quantifiable means to distinguish among multiple sources (Dempster et al., 1997).

4.9.6 ISOTOPE ANALYSIS OF GAS SAMPLES Isotopic analysis of gas samples (carbon 13C/12C and deuterium hydrogen 2H/1H) can be used to discriminate between landfill and non-landfill gas sources (Baedecker and Back, 1979; Games and Hayes, 1974, 1977). The former technique is based on the

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TABLE 4.20 Differences in Landfill and Non-Landfill d13C Compound

Landfill d13C

Non-Landfill d13C

Methane (CH4) Carbon dioxide (CO2)

–42 to –61‰ –7 to +18‰

–60 to –95‰ –47 to –63‰

differences in 13C concentrations in carbon dioxide (CO2) and methane (CH4). Reported differences in landfill and non-landfill methane and carbon dioxide in units of permills (‰) are shown in Table 4.20 (Hackley et al., 1996; Hoefs, 1997). While the presence of methane (CH4) in groundwater is not conclusive that landfill leachate has entered the groundwater, the d13C in the dissolved inorganic carbon can provide additional evidence, as 13C and 2H in the CH4 are indicators of biogenic methane. Landfills with robust methane production often have co-existing carbon dioxide (CO2) or dissolved inorganic carbon that is enriched in 13C due to methanogenesis (Clark and Fritz, 1997). d13C values for carbon dioxide as low as – 25‰ have been reported for some landfills; these results are believed to be due to either bacterial preference for light methane (12CH4) or maturity of the landfill from which the sample was collected. Isotopic analysis of deuterium (2H) in landfill leachates can be combined with isotopic analysis of landfill gases to identify the source of both the leachates and gases. Values of d2H have been observed to be enriched 30 to 60% as compared to local precipitation. For example, by plotting the differences in d2H vs. d13C for methane, for either gases or leachates, clustering of the data relative to different sources may become apparent (Murphy and Katz, 1998). The origin of nitrogen and sulfur species associated with groundwater contaminated by landfill leachates can be identified by using d2N, d34S, and d18O. The presence of high concentrations of tritium in groundwater may provide another opportunity to confirm the introduction of landfill leachates into an aquifer. In landfills in Illinois, tritium concentrations in landfill leachates were measured at up to 8000 tritium units which were believed to have originated from tritium leaching from luminescent paints containing titrated hydrocarbons (Clark and Fritz, 1997). Sources of methane other than from gasoline degradation include underlying sediments and or decaying organic matter (biogenic) as distinguished from thermogenic (e.g., from natural gas pipeline) gases. Plotting the stable isotope ratios of carbon and deuterium hydrogen can provide a means to differentiate between biogenic and thermogenic gases. Carbon-14 concentration analysis, for example, is used to distinguish between methane associated with spilled gasoline from that associated with other sources (Lundegard et al., 1998). The stable carbon isotope ratios of biogenic vs. thermogenic gases range from –45 to –100 and –15 to 50 permills, respectively. Deuterium hydrogen ranges for biogenic and thermogenic gases range from –150 to –350 and 90 to 400 permills, respectively (Schoell, 1998; Whiticar et al., 1986).

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An example of the application of the isotopic analysis of methane gas in groundwater for source identification was performed at the Beare Road landfill in Toronto, Canada. Isotope analysis was used to isolate sources of methane detected in the shallow groundwater under the landfill (Descrocher and Lollar, 1998). It was argued that the results of the isotopic analysis indicated that transport of leachates from the landfill to the deeper groundwater did not occur. The carbon isotopic analysis of the dissolved and gas phase methane concluded that it originated from naturally occurring microbial methanogenesis in the native formation rather than from the landfill. In another example of isotopic analysis, the source and movement of carbon dioxide in soil gas directly above an aquifer contaminated with organic solvents from a disposal site in southeast Phoenix, AZ, were used as indicators of in situ biodegradation of organic solvents in the subsurface (Suchomel et al., 1990). The carbon dioxide concentrations in the contaminated soil significantly exceeded the concentrations in uncontaminated areas and correlated with the volatile organic compound concentrations measured in soil cores collected in contaminated areas. The d13C values were also indicative of contamination and in situ aerobic biodegradation of the chlorinated solvents (TCE, DCE isomers, and 1,1,1-TCA). In the investigation of sites located at Hill Air Force Base in Utah, the Patuxent River Naval Air Station in Maryland, and Tyndall Air Force Base in Florida, carbon dioxide concentrations and stable carbon isotope ratios in soil gas provided a basis for identifying the contaminant source (Aggarwal et al., 1991). Both the carbon dioxide concentrations and d13C values were used to discriminate between areas of contamination. Carbon dioxide concentrations in soil gas in uncontaminated and contaminated areas ranged from 0.2 to 2.2% and 0.6 to 13%, respectively. Average d13C values as parts per thousand for uncontaminated vs. contaminated locations at each site were as follows: Hill Air Force Base, 23.6 vs. 28.4; Patuxent River Naval Air Station, 24.5 vs. 28.4; and Tyndall Air Force Base, 18.4 vs. 23.3. In addition to developing an isotopic line of evidence, the content of higher molecular weight hydrocarbon gases (e.g., ethane, propane, butane, and pentane) relative to methane can be used (Lundegard et al., 1999). Biogenic gases consist predominately of methane and carbon dioxide and do not typically contain significant concentrations of C2 to C5 hydrocarbons (C1/[C1 – C5] > 0.98) (Rice and Claypool, 1981). Natural gas from pipelines, in contrast, contain significant concentrations of C2 to C5 hydrocarbons (C1/[C1 – C5] = 0.6 to 1.0).

4.9.7 ISOTOPIC ANALYSIS OF CHLORINATED SOLVENTS The use of isotopes to differentiate manufacturers of chlorinated solvents has been proposed as a means to distinguish sources contributing to a co-mingled groundwater plume. Fractionation of 37Cl occurs during the manufacturing of chlorinated solvents (Tanaka and Rye, 1991). A significant difference in the d13C and d37C values is apparent for a single compound, suggesting variations in the manufacturing process.

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FIGURE 4.9 d37Cl vs. d13C of PCE, TCE, and TCA from four different chlorinated solvent manufacturers. (From Van Warnerdam, E. et al., Applied Geochemistry, 10, 550, 1995. With permission.)

The low abundance of 37Cl isotope fraction in organic solvents is bound more tightly to carbon than are 35Cl atoms (Bartholomew et al., 1954). The difference in bond strength results in chlorine isotope fractionation due to temperature and pressure differences during the manufacturing of the chlorinated solvents (Tanaka and Rye, 1991). In one case, the isotopic ratios for 13C/12C and 37Cl/35Cl were used to distinguish among three chlorinated solvent manufacturers. The three chlorinated solvents were PCE, TCE, and 1,1,1-TCA, as shown in Figure 4.9, with the 13C percentage in Standard Mean Ocean Chloride (SMOC) and the 37Cl in the international standard of PeeDee belemnite (PDB) (Van Warnerdam et al., 1995). In a similar application, 13C and 37Cl were used to discriminate between two different pure phase chlorinated solvent batches obtained from various manufacturers using GC/C/IRMS (Beneteau et al., 1996). Data interpretation may also be biased due to the potential for isotopic fractionation in the subsurface and the precision of the GC/C/IRMS measurements (Stout et al., 1998c). The use of this method as evidence in litigation requires that a pure free phase product is available for extraction and testing. The cost of extracting a pure product of the solvent from the environmental sample and concerns about the validity of the subsequent test results should be carefully considered. Additional difficulties in the use of this technique in litigation include being able to find a laboratory that can perform the analysis and identifying an witness who is expert in this area of expertise (K. Beneteau, personal communication, 1999).

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An indirect technique for identifying the distribution and contaminant transport rate is to use a radioactive isotope as an indicator of the transport of a non-isotope contaminant. One example is the use of tritium measurements combined with contaminant transport calculations specific to liquid transport in fractures such as joints or slickensides. For example, based upon transport calculations through a fractured Gulf Coast clay, in addition to the contaminant transport results, it was argued that a dense non-aqueous phase liquid (DNAPL) had not moved through the fracture system and into the groundwater. Samples were collected throughout the several hundred feet of overburden, and the presence or absence of tritium in water within the fractured clay was used to demarcate the vertical extent of the tritium. The tritium values were then argued to be consistent with the slow movement of infiltrating water through the clay which would preclude the movement of a DNAPL that was released subsequent to 1954 into the underlying aquifer. The effects of volatilization on the isotopic composition of TCE for free product and as a dissolved solution at different concentrations were studied (Slater et al., 1998). The stable carbon isotope concentrations were examined and indicated that, while volatilization and dissolution of the TCE did not result in isotopic fractionating, fractionating occurred due to abiotic dechlorination.

4.10 CHEMICAL AND BIOLOGICAL DEGRADATION MODELS: PETROLEUM HYDROCARBONS The degradation of specific petroleum fractions in a fuel has been proposed as a means to age-date a hydrocarbon (Faggan et al., 1975). Forensic techniques used to date the age of a petroleum hydrocarbon release include the degree of weathering, half-lives, pristane and phytane ratios, and BTEX ratios.

4.10.1 WEATHERING AND BIOMARKERS Weathering of a petroleum hydrocarbon includes processes such as evaporation, water washing, adsorption and/or sequestration, chemical precipitation, biodegradation, and advective transport. One advantage of the examination of weathering patterns is that it may provide a basis to (1) associate products or fuels from a similar origin, and (2) to provide a qualitative basis for age-dating. The presence of gaseous hydrocarbons, isobutane, n-butane, isopentane, and npentane in a sample contaminated with gasoline, for example, is used to determine whether a gasoline released into the subsurface is “fresh” or “weathered”. Fresh gasoline normally contains n-hexane and n-heptane in higher concentrations than methylcyclohexane (MCH) and n-octane. After the gasoline weathers in the subsurface, the MCH concentration increases relative to n-hexane and n-heptane and carbon-7 (C7) normal paraffins. It is common to plot chromatograms showing the different hydrocarbons and weathering correlations on a base map. Testimony is then

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offered regarding chromatograms representing “fresh” vs. “weathered” crude or refined product. The difficulty with this analysis and testimony is that the terms “fresh” and “weathered” are relative terms that allow a wide range of interpretations by forensic geochemists. “Biomarkers” are commonly introduced as evidence to distinguish among sources of a petroleum hydrocarbon. Biomarkers are complex markers that are resistant to weathering and biodegradation. Biomarkers have been defined as “organic compounds present in oils and source rocks having carbon skeletons related to their functionalized precursors which occur in the original source material” (Philip, 1998). As a result, they are used to determine the source of a petroleum hydrocarbon even if it has been present in the environment for a significant period of time. Most crude oil and Bunker C fuel, for example, contain biomarkers such as terpanes and steranes which are highly resistant to biodegradation (Walker et al., 1976). Terpanes and steranes are high-molecular-weight hydrocarbons originating from the polycyclic lips present in plants and bacteria. Because of their particular structure, these biomarkers represent a large number of different chemical compounds as well as a set of isomers of the same compound (Kaplan et al., 1995). Because of their stability, they are useful in comparing fuel patterns between samples. Specific biomarkers used to identify the source of a release include the following: C2-dibenzothiophenes/C2-phenanthrenes; C3-dibenzothiophene/C3-chrysene; C29-a,bpentacyclic hopanes/C30-a,b-pentacyclic hopanes; C23-tricyclic hopane/C24-tricyclic hopane; and 4-methyldibenzothiophene/2-/3-methyldibenzothiphenes ratios (Douglas et al., 1996; Wang et al., 1994; Wang and Fingas 1995). The C30-pentacyclic terpane (hopane) and certain tricyclic terpanes are among the most stable biomarkers in crude oil (Peters and Moldowan, 1993). Of the tetracyclic steranes, the diasteranes are the most stable. In environmental litigation, pentacyclic triterpanes (C27 to C35) and steranes (C27 to C30) are used, although they are relegated to use for distinguishing between crude oil or heavy distillate fuels due to their high molecular weight (Stout et al., 1999). For middle distillate fuels, biomarkers using GC/MS-selected ion monitoring techniques can be used to distinguish among different fuels. Biomarkers that can be identified using this technique include bicyclic sesquiterpanes (C14 to C16), acyclic regular isoprenoids (C13 to C25), tricyclic diterpanes (C17 to C20), aromatic diterpenoids (C18 to C20), tricyclic terpanes (C19 to C25), and various polycyclic aromatic hydrocarbons (PAHs) such as naphthalenes and phenanthrenes (Stout et al., 1999a). Dibenzothiophenes are associated with the sulfur content of the fuel and can vary significantly between sources. Crude oil and most mid-range distillates such as coal-derived liquids, coke production plants, creosote, and manufactured gas plant residues contain an abundant number of PAHs. Manufactured gas plant residues containing PAHs include lampblack, tar, and spent oxides (usually composed of sulfur, cyanide, and ammonia compounds bound with iron). The presence or absence of a PAH may, therefore, provide an indication of a distillation or pyrogenic process unique to the material as well as a means to distinguish among residue materials containing the PAHs (coal tar, lampblack, etc.). One analysis of PAHs, for example, provided the basis for distinguishing

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TABLE 4.21 Polyaromatic Hydrocarbons Used To Identify Multiple Sources Acenaphthenea Acenaphtylene a Benzo(a)anthraceneb Benzo(a)pyreneb Benzo(b)fluorantheneb Benzo(b)thiophenes C2-benzo(b)thiophenes C3-benzo(b)thiophenes C4-benzo(b)thiophenes Benzo(e)pyrene Benzo(g,h,i)perylenea Benzo(k)fluorantheneb Biphenyl Chrysenesb C1-chrysenes C2-chrysenes C3-chrysenes C4-chrysenes Decalins C1-decalins C2-decalins C3-decalins C4-decalins a b

Dibenzo(a,h)anthraceneb Dibenzofuran Dibenzothiophene C1-dibenzothiophene C2-dibenzothiophene C3-dibenzothiophene C4-dibenzothiophene Fluoranthenea and pyrenea C1-fluoranthenes/pyrenes C2-fluoranthenes/pyrenes C3-fluoranthenes/pyrenes C4-fluoranthenes/pyrenes Fluorenesa C1-fluorenes C2-fluorenes C3-fluorenes Indeno(1,2,3-c,d)pyreneb Perylene Phenanthrenesa and anthracenesa C1-phenathrenes/anthracenes C2-phenathrenes/anthracenes C3-phenathrenes/anthracenes C4-phenathrenes/anthracenes

Non-carcinogenic compound. Carcinogenic compound.

Adapted from Stout, S. et al., Soil and Groundwater Cleanup, October, 1998, p. 25. With permission.

between PAH contamination that originated from manufactured gas plants and atmospheric deposition that was released into the atmosphere by various pyrolysis sources (Haeseler et al., 1999). In order to examine differences in PAHs from a number of possible sources, an extended list of PAHs is required, beyond the standard EPA Priority List that contains 16 PAH compounds or only carcinogenic PAHs (i.e., benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, chrysene, dibenzo(a,h) anthracene, and indeno(1,2,3-c,d)pyrene) (Haeseler et al., 1999). A recommended list of PAHs that can be used to identify different types of hydrocarbons are summarized in Table 4.21 (Stout et al., 1998b). These results can be plotted and compared. Figure 4.10 shows bar charts of the concentrations of PAHs in crude oil, gasoline, Bunker C, and creosote samples (Stout et al., 1998b).

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FIGURE 4.10 Polyaromatic hydrocarbons (PAHs) associated with four petroleum hydrocarbons. (From Stout, S. et al., Soil and Groundwater Cleanup, October, 1998, p. 26. With permission.)

Because polyaromatic hydrocarbons are some of the compounds least affected by weathering, selected PAHs may be identified from the type of analysis shown in Figure 4.10 and used as target compounds for further delineation between hydrocarbons. For example, phenanthrene and dibenzothiophene isomers may be altered in a manner that provides a relative basis to compare weathering rates between samples.

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TABLE 4.22 Polycyclic Aromatic Hydrocarbon Ratios in a Diesel No. 2 Sample

C4-Alkylbenzenes/ C2-Phenanthrenes

C1-Naphthalenes/ C2-Phenanthrenes

1.6 1.2 1.0 1.7 0.3

4.3 3.4 2.2 3.2 1.7

New diesel (gw)a Degraded diesel (gw) Severely degraded diesel (gw) Degraded diesel (soil) Severely degraded diesel (soil) a

gw = groundwater.

Examples include C4-alkylbenzenes/C2-phenanthrenes and C1-naphthalenes/C2phenanthrenes, which can be useful in determining alteration changes in free phase diesel floating on groundwater and in soil (Kaplan et al., 1995). Table 4.22 lists selected PAH ratios for a diesel No. 2 present as free phase product floating on the groundwater and present in soil (Kaplan et al., 1995). Polycyclic aromatic hydrocarbons can be analyzed from tissue samples of crustaceans and bivalves to identify the origin of the oil in the tissue sample (Douglas, 1988). Organisms conducive to this type of testing include bivalves and crustaceans; fish are generally not well suited unless they have been exposed to extremely high dosages. Birds and mammals are least suited due to the metabolism of many polycyclic aromatic hydrocarbons by the animals. The procedure for this analysis includes collection of the tissue sample and extraction of the tissue with CH2Cl2 and Na2SO4 using a tissumizer. The extractant is then passed through an alumina cleanup column, followed by gel permeation high-pressure liquid chromatography (HPLC) with an optional silica gel HPLC, and finally analysis via gas chromatograph/mass spectrometry/selected ion monitoring (GC/MS/SIM).

4.10.2 BIODEGRADATION MODELS A popular petroleum degradation model is based on the biodegradation half-life of hydrocarbon compounds in the soil or groundwater, the estimated half-life being the time required for one half of the compound to biodegrade. The two approaches most often encountered are the modeled half-life BTEX concentrations in support of a release date or the use of published half-life values. Table 4.23 summarizes biodegradation rates of selected BTEX and PAH compounds (API, 1994; Raymond et al., 1976; Walker et al., 1976). Numerous models exist for calculating the degradation rate of BTEX and other compounds. Assumptions routinely used in first-order biodegradation models for BTEX include the following (Odermatt, 1999):

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TABLE 4.23 Biodegradation Rates of BTEX and PAH Compounds Biodegradation Half-Life (hr)a Compound Acenaphthene (C12H10) Anthracene (C14H10) Benzene (C6H6) Benzo(a)pyrene (C20H12) Chrysene (C18H12) Ethylbenzene (C6H5C2H5) Fluoranthene (C10H10) Fluorene (C13H10) Naphthalene (C10H8) Phenanthrene (C14H10) Pyrene (C16H10) Toluene (C6H5CH3) o-, m-, p-Xylene (C6H4(CH3)2 a

Soil

Groundwater

299–2448 1200–11,040 120–384 1368–12,720 8904–24,000 72–240 3360–10,560 768–1440 398–1152 384–4800 5040–45,600 96–528 168–672

590–4896 2400–22,080 240–17,280 2736–25,440 17,808–48,000 144–5472 6720–21,120 1536–2880 24–6192 768–9600 10,080–91,200 168–672 336–8640

Measured at 25∞C.

• The degradation rate is uniform in time and space. • First-order degradation rates do not depend on the status of the in situ microbial population. • Contaminant loading rates and the toxic effects of contaminants are ignored (e.g., first-order degradation rates may only be valid over a portion of a concentration range). • The first-order biodegradation process is instantaneous and 100% effective, regardless of location in the soil or aquifer.

Given these assumptions, techniques have been proposed to estimate the transformation rate of a chemical downgradient of a source and for estimating the date of a release. An example of a method to estimate the degradation rate (l) of a compound in a one-dimensional idealization is described in Equation 4.8 (Brown et al., 1997; Buscheck and Alcantar, 1995; Westervelt et al., 1997). l = vc/4ax([1 + 2ax(k/vx)]2 – 1) where l vc ax k vx

= = = = =

degradation rate. contaminant velocity along the x-axis adjusted for retardation). longitudinal dispersivity. attenuation rate. groundwater linear velocity.

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(Eq. 4.8)

The term (k/vx) is the slope of the regression line fit to the log contaminant concentration data as a function of distance along the centerline of the contaminant plume (McNab and Dooher, 1998). The difficulty in relying on this inverse solution relationship is that dispersive processes can produce concentration distributions that decline with distance from a continuous source. In many instances, especially when analyzing a small number of data points, it is often possible to fit a straight line through log concentration vs. distance data with a high degree of correlation even when degradation is insignificant or absent. A linear trend in log concentration values as a function of distance from the contaminant source does not constitute proof of the existence of transformation processes. Other factors that can introduce bias into this approach include (McNab and Dooher, 1998): • • • • • • • •

An assumption that steady-state conditions exist Fluctuations in source strength with time Non-Fickian dispersion of solutes Strongly heterogeneous flow and transport Well locations not aligned with the contaminant plume centerline Dilution effects due to well-screen length Sampling and analytical bias Non-uniform degradation rate distribution

Many of these factors are universal to inverse or reverse types of modeling due in part to the non-uniqueness of the problem and mathematical instabilities resulting from small variations in the input data; therefore, it is possible to derive misleading degradation rates in support of reverse modeling or contaminant source identification models. The use of sensitivity analysis can be performed through Monte Carlo simulations using a range of physical parameter values and biodegradation rates to generate a large number of simulations for the purpose of producing confidence levels for the various input parameters. Realize that the use of first-order reaction rates to describe hydrocarbon biodegradation may not be universally appropriate. In a study of 1029 leaking underground storage tank sites in California, the applicability of first-order degradation rates was concluded to be appropriate in about 625 instances, due primarily to the observation that these degradation rates were valid for only a portion of the BTEX concentration range. In general, the authors recommended questioning first-order approximations if the maximum concentration of benzene is ≥1 ppm or if the total BTEX is >5 ppm (Bekins et al., 1998; McNab and Dooher, 1999).

4.10.3 PRISTANE/PHYTANE RATIOS Pristane and phytane are isoparaffins known as isoprenoids. They are present to the right of C17 and C18 peaks on chromatograms of crude oils, middle distillates, and lubricating oils. In fresh crude, middle distillates, or lubricating oils, the n-paraffin C17 and C18 peaks are more prominent than the pristane and phytane peaks. As the

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petroleum hydrocarbon is biodegraded, the bacteria preferentially consume the C17 and C18 which results in the pristane and phytane peaks becoming more pronounced on the chromatogram. Examination of the C17/pristane and C18/phytane ratios is therefore argued as a qualitative basis for determining the degree of degradation and, hence, weathering (Kaplan and Galperin, 1996). A linear relationship extending for about 20 years is approximated by Equation 4.9 (Kaplan et al., 1995, 1997): T (yr) = –8.4[n – C17/Pr] + 19.8

(Eq. 4.9)

where an average initial value for the [n – C17/Pr] ratio is about 2.3 for a No. 2 diesel fuel. The genesis of the pristane/phytane approach is described in an article by Christensen and Larsen (1993), who evaluated changes in the composition of diesel No. 2 as a function of time in Denmark and the Netherlands. The authors analyzed 11 diesels from five different oil companies and concluded that the average C17/ pristane ratios was 1.98 (2.0) with a standard deviation of 0.83. The authors concluded that an analysis of the C17/pristane ratios provided a means to estimate the length of time that the diesel had been in the environment. The ratios for 26 refined and “fresh” distillates and motor oils from the U.S. were also examined; these C17/ pristane ratios were found to be 1.95 (2.0) with a standard deviation of 0.29. As a rule of thumb, a C17/pristane ratio of a fresh diesel is >2.0. Because crude oil is the parent of refined products, the C17/ pristane ratios of 2509 crude oils from ten states in the U.S. and crude oils from Mexico and Canada were examined; the ratio for these crude oils was 2.1. Crude oils from 14 countries representing 1420 crude oils were also examined and resulted in a C17/pristane ratio of 2.0. Fresh refined products were found to have a C17/pristane ratio of between 1.8 and 2.2. The C17/pristane ratios of refined distillate products in the U.S. are shown in Table 4.24. These ratios have also been promoted as a means to evaluate the relative weathering and, hence, age of hydrocarbons. The C17/pristane and C18/ phytane ratios of a diesel No. 2 and Bunker C soil extract are summarized on Table 4.25 to illustrate this approach.

4.10.4 BTEX RATIOS Benzene, toluene, xylene, and ethylbenzene (BTEX) ratios in groundwater have been proposed and used as a qualitative indicator of the time that the product has been in the subsurface and, therefore, to date the age of a release (Kaplan et al., 1997; Luhrs and Pyott 1992; Odermatt, 1994). These results can be combined graphically with the results of a pristane/phytane analysis. These methods are based on the sequence of BTEX volatilization and biodegradation. The sequence of BTEX loss in groundwater begins with benzene because it diffuses most rapidly out of free phase gasoline and partitions into groundwater followed by toluene, ethylbenzene, and xylene. The reverse sequence often occurs with BTEX in soils; toluene, ethylbenzene, and xylenes are preferentially retained by soil relative to benzene, and ethylbenzene and

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TABLE 4.24 C17/Pristane Ratios of Refined Products in the U.S. Geographic Location

Product

West Texas Minnesota Tennessee Colorado New York New England Western U.S. (Chevron) Western U.S. (Amoco)

Diesel Diesel Kerosene Diesel Diesel Diesel Diesel Diesel (summer) Jet-A fuel Refinery tank (diesel) Reduced oil Kerosene Heating oil Diesel No. 1 Diesel No. 2 Gas oil Residual oil Fuel oil Heavy fuel oil Diesel Motor oil (30W) Diesel Kerosene Jet-A fuel Middle distillate Cracked distillate

Oklahoma Indiana

Average

C17/Pristane Ratio 2.1 1.9 2.0 2.5 2.6 1.9 1.6 1.4 1.8 1.7 1.6 1.8 1.8 1.9 1.5 1.8 2.2 2.2 2.2 2.2 1.9 1.8 2.1 2.1 2.0 1.9 2.0

From Schmidt, G., in International Business Conference Environmental Forensics: Determining Liability through Applied Science, September 24– 25, International Business Communications, Southborough, MA, 1998, p. 13. With permission.)

xylenes are also more resistant to degradation than benzene or toluene. Chemists reviewing hydrocarbon chromatograms often observe that ortho-xylene is removed first in hydrocarbon-contaminated soils, followed by ethylbenzene, toluene, metaand para-xylene, and finally benzene. BTEX degradation at each site is therefore unique due to different biological populations and original composition of the BTEX compounds in the gasoline. Calculating ratios between these four compounds is used in environmental cases to identify the relative age of a hydrocarbon release. Because the relative content of BTEX compounds in gasoline has changed, initial BTEX ratio values are rarely

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TABLE 4.25 C17/Pristane and C18/Phytane Ratios of a Diesel No. 2 and Bunker C Sample New diesel No. 2a Degraded diesel No. 2a Severely degraded diesel No. 2a Degraded diesel No. 2 (soil) Severely degraded diesel No. 2 (soil) New Bunker C (soil) Degraded Bunker C (soil) Severely degraded Bunker C (soil) a

C17/Pristane Ratio

C18/Phytane Ratio

2.6 1.2 0 1.1 0 2.2 1.6 0

3.6 1.4 0 0.8 0 2.6 2.0 0

Free-floating diesel No. 2 on groundwater.

Adapted from Kaplan, I. et al., Pattern of Chemical Changes in Fugitive Hydrocarbon Fuels in the Environment, SPE 29754, Society of Petroleum Engineers, Houston TX, 1995, p. 601. With permission.)

available, thereby limiting the value of the technique to estimate the timing of a release. One method proposed to smooth out the variations in the composition of manufactured gasoline and to accommodate processes that preferentially remove benezene from the groundwater is to use a cumulative (B + T)/(E + X) ratio (Kaplan, et al., 1996). The cumulative BTEX ratio is defined as Rb = (B + T)/(E + X) and is assumed to decrease exponentially with the time since a spill occurred (t) according to Equation 4.10 (Kaplan et al., 1995, 1997; Montgomery, 1991): Rb = 6.0 exp(–0.308t)

(Eq. 4.10)

Given that this empirical relationship is only valid for initial (B + T)/(E + X) ratios of 6.0, it may only represent a small percentage of gasoline formulations. BTEX partitioning studies indicate that immediately after a spill, Rb values range from 1.5 to 6, depending on the amount of gasoline in contact with groundwater. If this ratio falls to between 1.5 and 6.0, the spill probably occurred within the last 1 to 5 years (Kaplan and Galperin, 1997). The ratio of benzene plus toluene to ethylbenzene plus xylenes decreases with time as a result of the higher solubility of the benzene and toluene to water. This ratio decreases as a function of time, with values below 0.5 indicative of a gasoline residence longer than 10 years. The accuracy of this technique may be improved by using a best-fit regression line from historical site data collected over an extended time interval. An exponential approximation of changes in Rb is also reasonable for a dissolved hydrocarbon plume near a floating gasoline layer. An exponential regression function assumes that the Rb decreases with time near the source of a sudden gasoline release. An example of an exponential approximation of the BTEX-monitored data from an actual case study

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FIGURE 4.11 BTEX ratio curve used for dating a gasoline where Rb = 6 exp(–0.308T).

reported by Galperin 1997 is shown in Figure 4.11. The high Rb value at the time of the initial measurement is indicative of free phase gasoline that occurred approximately 4 years prior to the initial measurement. The extrapolation curve shows that at the time of the gasoline release, Rb = 6, confirming the presence of a thick free-product layer, while a twofold decrease in Rb occurred in about 2.3 years (Kaplan et al., 1997). A technique used to present BTEX ratios includes multivariate plotting such as trilinear and star diagrams. Examples are shown in Figure 4.12 (Kaplan et al., 1996; Lesage and Lapcevic, 1990; Morrison, 1999a). For star diagrams, the “rays” of each star are usually logged so that a single component with a high concentration does not overwhelm the lower concentration components of the fuel. A multicolor plot or different line types can be created for diagnostic purposes or for the trial exhibit. These techniques are also useful in that they allow for the simultaneous plotting of several data sets.

4.10.5 CHALLENGES TO BTEX RATIO METHODS Numerous challenges to using BTEX ratios for age-dating are available (Alvarez et al., 1998; Landmeyer et al., 1998). Most challenges to this method argue that transformation of BTEX compounds in the subsurface are impacted by many variables, including but not limited to the following: soil texture, composition, microbial diversity, electron acceptor availability, volume of the release, groundwater chemistry, and hydrodynamic characteristics (Landmeyer et al, 1998). Rarely are these variables quantified.

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FIGURE 4.12 Examples of trilinear and star diagrams.

The most commonly encountered challenges to BTEX ratios as a means to agedate a release include: • • • •

Uncertainty regarding the initial gasoline composition Uncertainty regarding the volume of the release Variability in the subsurface chemical and biological system Chromatographic separation

The composition of gasoline varies considerably with the octane rating, changes in seasonal composition, the geographic area, and time of formulation. In colder climates in the U.S., the composition of gasoline can change up to four times a year to accommodate the Reid vapor pressure which is high in wintertime to provide easy startup and low in summertime to prevent vapor lock. Premium gasoline with an antiknock additive package generally has a higher fraction of benzene, as it has a higher octane rate (115) than other BTEX or alkane species. Changes in the composition in gasoline have also occurred due to regulatory changes. The Clean Air Act Amendments of 1990, for example, restricted benzene concentrations in gasoline to 1.6% by volume. Gasoline blended prior to 1990, therefore, generally has a higher benzene content (6% by volume) (Johnson et al., 1990). Because other non-benzene compounds are not similarly restricted, (B + T)/(E + X) ratios are generally lower for groundwater equilibrated with post-1990 gasoline. Table 4.26 summarizes BTEX ranges in different grades of dispensed gasoline (Kaplan et al., 1995). There is a common misconception that BTEX is only associated with gasoline and not diesel or other types of products. The BTEX ranges for a diesel No. 2, Jet-A, and gasoline fuel are shown on Table 4.27 (Harvey, 1997; Kaplan et al., 1995). The initial composition of the gasoline is the major variable in the interpretation of gasoline weathering in the subsurface. The BTEX composition detected in the groundwater depends on the initial gasoline composition and the relative volume of the equilibrated water, as well as the total time during which contact between the gasoline and water has occurred. The importance of this relationship is illustrated with a mass balance equation such as that described by Equation 4.11 (Landmeyer et al., 1998):

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TABLE 4.26 BTEX Ranges in Dispensed Gasoline Gasoline Grade

Benzene

Toluene

Ethylbenzene

Xylene

Leaded gasoline Regular unleaded Unleaded plus Super unleaded

6.6–14.8 5.0–19.4 7.1–18.2 6.6–18.9

18.6–64.4 17.9–56.6 21.6–62.8 22.4–72.2

6.2–14.0 5.8–15.4 6.0–15.1 6.6–19.1

32.1–77.4 27.1–76.6 28.6–81.5 33.4–90.8

a

To convert to mg/L, multiply by 1000.

Adapted from Kaplan, I. et al., Pattern of Chemical Changes in Fugitive Hydrocarbon Fuels in the Environment, SPE 29754, Society of Petroleum Engineers, Houston TX, 1995, p. 601. With permission.)

w f fw –n Ciw(n) = Cif(∞)/K fw i [1 + V /V K i ]

(Eq. 4.11)

where Ciw(n) Cif(∞) K fw i Vw Vf

= = = = =

the aqueous phase concentration after leaching with n batches of water. the initial concentration of the particular BTEX compound (i) in the fuel. the partition coefficient. the volume of n batches of water. volume of gasoline.

This relationship assumes that the dissolution process does not significantly affect the total volume of the gasoline. Figure 4.13 is an example of the BTEX ratios for unweathered gasoline blends equilibrated with water to illustrate the wide range of BTEX ratios between gasoline

TABLE 4.27 BTEX Range for Selected Fuels Compound Benzene Toluene Ethylbenzene Xylenes a

Diesel No. 2a

Jet-Aa

Gasolinea

1–50 10–250 50–350 25–100

20–350 100–2500 50–1500 100–2500

4000–30,000 40,000–150,000 4000–50,000 40,000–50,000

mg/L = parts per million (ppm).

Adapted from Kaplan, I. et al., Pattern of Chemical Changes in Fugitive Hydrocarbon Fuels in the Environment, SPE 29754, Society of Petroleum Engineers, Houston TX, 1995, p. 601. With permission.)

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FIGURE 4.13 Variation in BTEX ratios for equilibrated water and brands of gasoline. (Adapted from Alvarez, P. et al., in Ground Water Monitoring and Remediation, Fall, 69, 1998. With permission.)

grades and the importance of knowing the initial composition of the gasoline (Landmeyer et al., 1998). BTEX ratios are also affected by the volumes of water to fuel that have equilibrated. With greater volumes of water, leaching of the BTEX constituents can be significant, resulting in a change in the composition of the gasoline. The preferential leaching of benzene and toluene from spilled gasoline always results in a decrease value of the B/X and (B + T)/(E + X) ratios in free product relative to its presence in groundwater. For example, given the higher solubility of benzene relative to xylene, benzene is preferentially leached from the fuel, resulting in decreasing B/X ratios with increasing volumes of water. Reported B/X ratios of 0.2 to 0.9 for water equilibrated with “weathered” gasoline, for example, are lower than the majority of the B/X ratios shown in Figure 4.13 (Hinchee and Reisinger, 1987; Luhrs and Pyott, 1992). The biodegradation of BTEX in the subsurface environment is highly variable, and abrupt changes in rates can occur on both a micro- and macro-scale. Under anaerobic conditions, toluene may be more rapidly degraded than benzene. These uncertainties result in a wide range of ratios for identically aged spills, especially in different soils. Another potential issue associated with BTEX ratio analysis is the case when BTEX compounds are a component of numerous contaminants, some of which may impact the BTEX degradation rates. For example, no benzene or ethylbenzene degradation was detected in a landfill-contaminated anaerobic aquifer in Denmark (Berg, et al., 1999; Johnston et al., 1996). It is also reasonable that variations in the organic substrates in an aquifer will result in variations regarding the degradation rates of BTEX compounds and therefore the legitimacy of a BTEX ratio analyses. The transport of BTEX compounds through this changing setting results in differences in biodegradation kinetics that are rarely quantified in a field setting. In aquifers, BTEX biodegradation rates are assumed to occur via first-order kinetics

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FIGURE 4.14 Hypothetical example of the impact on aerobic and anaerobic degradation on B/X ratios. (Adapted from Alvarez, P. et al., in Ground Water Monitoring and Remediation, Fall, 69, 1998. With permission.)

where the rate (dC/dt) is proportional to the contaminant concentration and where –lC = dC/dt. BTEX degradation rates also vary based on whether they are measured in situ or in the laboratory (Chapelle et al., 1996). Laboratory-measured biodegradation rate estimates are highly sensitive to ambient redox conditions and must be carefully matched to field conditions to obtain reliable results. The assumption that BTEX components degrade via first-order kinetics may be inappropriate when extrapolating laboratory-derived degradation rates to field-scale BTEX degradation (Bekins et al., 1998). Figure 4.14 is a hypothetical example where aerobic biodegradation depletes the available oxygen in 10 weeks. First-order decay coefficients used in Figure 4.14 for benzene and xylene are 0.040 day–1 and 0.025 day–1, respectively (Howard et al., 1991). Changes in the B/X ratio change dramatically, especially for anaerobic conditions where benzene degrades slowly, which is consistent with the literature (Alvarez and Vogel, 1995; Lovely et al., 1989). Another impact on the BTEX ratio analysis is the chromatographic separation of the BTEX compounds as they are transported in both the soil and groundwater (i.e., the individual BTEX compounds are transported at different velocities). Where the sample is collected will, therefore, affect the concentration of the individual BTEX compounds as a function of chromatographic separation of the individual compounds and due to the age of the release. Figure 4.15 illustrates the situation where three samples are collected at different distances from the source of the gasoline release. An evolving isotopic variation to the BTEX ratio analysis is the extraction of a BTEX-impacted sample with pentane for which the 13C concentration is then measured (Dempster et al., 1997; Kelley et al., 1997). This technique has been used to distinguish the origin of BTEX from three different sources. In some instances there may be a need to discriminate between “natural” gasoline and refined gasoline. BTEX-to-TPH ratios are lower in natural gasoline than in refined gasoline. Refined gasoline contains olefins, which are not found in natural gasoline, as well as additives such as MTBE. Natural gasoline contains polyaromatics (multi-ring aromatic compounds) that are not found in refined gasoline.

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FIGURE 4.15 Hypothetical example of the impact of the sampling location on the B/X ratio due to chromatographic separation of the BTEX compounds in soil (upper) and groundwater (lower) at various distances from the source of the release.

4.11 CHEMICAL DEGRADATION MODELS: CHLORINATED SOLVENTS The presence of chlorinated solvents and their breakdown products has been proposed as a means of identifying how long a chemical has been in the subsurface. This approach is based on the measured degradation rates of chlorinated solvents, primarily of the parent compounds tetrachloroethylene (PCE), trichloroethane (TCA), and carbon tetrachloride (PCM) into their respective daughter products. The presence or absence of a particular breakdown product is argued as evidence that the parent compound was present for a particular period of time. For example, the compound 1,1-dichloroethene (1,1-DCE) is a breakdown of both TCA and PCE, while chloroethane is a degradation product of TCA or 1,2-dichloroethane. The presence of 1,1-DCE and chloroethane is evidence that PCE, TCA, and possibly 1,2-DCA were present (Feenstra et al., 1996). Another example is the presence of chloroform which can indicate the presence of carbon tetrachloride as its parent compound (see Figure 1.5 in Chapter 1)

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A variation to this dating approach assumes that if the original concentration of a chlorinated solvent introduced into the subsurface is known, then a knowledge of the half-life for that chemical can provide a basis for estimating the time that the chemical was released into the subsurface. One reported method uses the ratio of the rate constant for the hydrolysis of 1,1,1-trichloroethane (TCA) to 1,1-dichloroethene and acetic acid to estimate the time when 1,1,1-TCA enters groundwater according to the following relationship: TCA fi 1,1-DCE (22%) + CH3CO2H (78%). This method assumes that the groundwater temperature (yearly average), the concentration of TCA in the sample, and the amount of 1,1-DCE in the sample are known (Smith, 1999). The method also assumes that the TCA and 1,1-TCA in the groundwater are known with an excellent degree of accuracy and precision. The age of the TCA in the groundwater (T) is then approximated by Equation 4.12 (Smith and Eng, 1997): T = ln ([TCA]o/[TCA]t)/k

(Eq. 4.12)

where T [TCA]o [TCA]t k

= = = =

age of the TCA in groundwater. initial concentration of TCA (assumes 1000 molecules). TCA concentration at time t. pseudo first-order rate constant (0.097 yr–1).

The contaminant migration rate is then determined by dividing the horizontal distance to each well by the age of the 1,1,1-TCA in the well. The following factors may result in inaccurate age estimations (Smith and Eng, 1997): • Chemical results may be more qualitative than quantitative. • The number of samples and the test results may be inadequate. • A 1,1-DCE/TCA ratio exceeds 0.50 — given that the ratio curve is exponential, when the ratio approaches 1.0 the error in the age prediction increases. An age estimate in warmer climates is not advised when the ratio approaches 1.0. • Significant transformation of TCA to 1,1-dichloroethane — the ratio of 1,1-DCE to TCA will be lower than if the ratio is the result of the hydrolysis reaction; the age prediction will, therefore, be older. • When TCE biodegradation is significant and the cis-1,2-dichloroethene (cis-1,2DCE) concentration is approximately two orders of magnitude greater than the 1,1DCE concentration — because some amount of TCE biodegrades to 1,1-DCE relative to the concentration of cis-1,2-DCE, this reaction will affect the 1,1-DCE/ TCA ratio by resulting in a higher 1,1-DCE concentration than what is attributable to TCA due to hydrolysis of TCA.

Several challenges to this dating approach have been made. One challenge is the reasonableness of selecting one retardation value for an entire well field. Site-specific information may also be unavailable for comparison with laboratory-derived degradation rates. Wide ranges of half-lives are also reported in the published literature. For example, published half-lives for PCE at 10 to 25∞C range from 0.7 to 1.3 ¥ 106

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TABLE 4.28 Reported Half-Lives for Selected Chlorinated Solvents Compound Dichloromethane Dibromomethane Chloroethane 1,1-Dichloroethane 1,2-Dichloroethane 1,1,1-Trichloroethane 1,1,2-Trichloroethane 1,2-Dibromomethane 1,1-Dichloroethylene Trichloroethylene Tetrachloroethylene 1,2-Dichloroethylene

Half-Life (yr)a 704 180 0.12 61 (72) (1–30) (1.1) (1.7) (2.5) (140) (170) 2.5 1.2 ¥ 108 (0.9) (1.3 ¥ 106) (0.7) (1.3 ¥ 106) 2.1 ¥ 1010

a Numbers in parentheses represent different reports of rates by various authors.

yr (Luhrs et al., 1992; Pankow and Cherry, 1996). A more specific half-life for PCE in groundwater is between 8640 and 17,280 hours based on estimated aqueous aerobic biodegradation rates (Pankow and Cherry, 1996). For surface waters, the half-life of PCE based on aerobic river die-away test data and saltwater grab sample data is between 4320 and 8640 hours. For 1,1,1-trichloroethane (1,1,1-TCA), published half-lives at 10 to 25∞C range from 1.1 to 12 years (Haag and Mill, 1988). Published half-lives for selected chlorinated solvents at 10 to 25∞C are summarized in Table 4.28 (Cline and Delfino, 1989; Dilling et al., 1975; Howard et al., 1991; Jeffers et al., 1989; Mabey and Mill, 1989). The half-life for the dechlorination of TCE, for example, proceeds at different rates between the daughter products; therefore, each half-life must be examined when developing a model for the mass balance between daughter products to develop a degradation model to support the timing of a chlorinated solvent. An example is the range of half-lives for the degradation of TCE to ethene as shown in Table 4.29 (Woodbury and Li, 1998). In addition, the media through which the compound is migrating can impact the half-life of the model. When evaluating a half-life model, confirm that the half-live used is representative of the model in which the compound is detected. Table 4.30 lists selected half-lives of organic compounds in soil and groundwater (Montgomery et al., 1991). Furthermore, the heterogeneity of the physical and chemical systems at a site introduces tremendous uncertainty into degradation rates. An example is whether site-specific information is available to determine if soils are anaerobic or aerobic;

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TABLE 4.29 Half-Lives of Trichloroethylene (TCE) Degradation Products Transformation

Half-Life Range

TCE to DCE cis-1,2-DCE to vinyl chloride trans-1,2-DCE to vinyl chloride 1,1-DCE to vinyl chloride Vinyl chloride to ethene Ethene

2.4 days to 0.9 years 7.2 to 140 days 6.2 to 244 days 53 to 132 days 56 days to 7.92 years 10 years

this determination is significant for determining whether the biological environment exists for the degradation of the chlorinated solvent and its rates of degradation. TCA, for example, degrades to 1,1-DCE abiotically, while TCE degrades to 1,2- and 1,1DCE anaerobically. Another aspect associated with the impact of the subsurface environment on the degradation rate is whether the apparent biodegradation rate is actually an artifact of the distance from the contaminant source, the monitoring wellscreen length, and/or the degree of well desaturation that occurred during purging (Martin-Hayden and Robbins, 1997). In 1995, in Carroll v. Litton Systems, Inc., the plaintiff’s chemodynamics expert used the concept of half-lives to develop information regarding the origin of trichloroethylene in water wells prior to 1986. The lead author of the article used to determine the half-life values submitted an affidavit stating that the approach was imprudent and prone to enormous error. The plaintiff’s expert furthermore conceded that the rate of error of his approach could not be reduced to below 1400%. The court found the testimony unreliable and therefore inadmissible under Federal Rules of Procedure, 702. The presence of solvents can potentially inhibit their microbial degradation (Barker, 1996). These complications introduce significant uncertainty in the use of degradation rates as an indicator of the timing of a release (Vogel and McCarty, 1987).

TABLE 4.30 Half-Lives of Selected Compounds in Soil and Groundwater Compound DDT Carbon tetrachloride Methyl ethyl ketone Vinyl chloride 1,2-Dichlorobenzene

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Half-Life in Soil

Half-Life in Groundwater

2 to 15.6 years 6 to 12 months 1 to 7 days 4 weeks to 6 months 4 weeks to 6 months

15 days to 31.3 years 7 to 365 days 2 to 14 days 8 weeks to 85 months 8 weeks to 12 months

Impurities present in the original product can similarly introduce uncertainty in the reliance of degradation rates for chlorinated solvents as an age-dating technique. Based on data from chemical manufacturers, individual compounds present as impurities can range from 0.1 to 25% (may be greater for recycled solvents). Industrialgrade PCE can contain up to 1 to 3% impurities, including degradation products (TCE; 1,2-DCE; etc.). If 10,000 ppb of PCE are detected in a groundwater sample, the impurities could range from 1 to 25 parts per billion. The presence of high chloride concentrations may provide insight as to whether the chlorinated solvents detected originated as impurities or from degradation. The presence of these impurities and/or additives may provide an opportunity for source identification. Half-lives are used in developing natural degradation half-lives to support natural attenuation remediation. This information in addition to hydraulic data can be used to estimate the time required for the contaminant plume to be flushed with water to a particular concentration for a given compound.

4.12 RAPID OPTICAL SCREENING TOOL™ TESTING The Rapid Optical Screening Tool (ROST™) is an in situ screening used in conjunction with a cone penetrometer to provide a continuous record of fluorescence in the soil. ROST™ testing provides a rapid technique to determine qualitatively whether petroleum hydrocarbons are present. This method is conducive to on-site sampling during discovery when site access or availability does not allow extended time for more traditional sampling and testing approaches (Lieberman et al., 1991). ROST™ techniques characterize petroleum hydrocarbons in real time from the fluorescence response induced in the polycyclic aromatic hydrocarbon compounds present in soil. Fluorescence intensity is measured at 340, 390, 440, and 490 nm and is assumed to be generally proportional to the concentration of hydrocarbons present in the soil. Laser-induced fluorescence (LIF) spectroscopy is used to excite the petroleum hydrocarbons; the intensity and duration of the fluorescence as well as the spectrum of wavelengths of light emitted by the petroleum hydrocarbon are recorded. In some cases, a qualitative determination of the type of petroleum hydrocarbon present is possible by comparing the waveform signatures of common petroleum hydrocarbon products with those encountered with the ROST™ (Taer and Liberman, 1998). Figure 4.16 is an example of the waveform log produced by ROST™. A demonstration project was performed at the Naval Construction Battalion Center located at Port Hueneme, CA, to evaluate the ability of ROST™ to define a petroleum hydrocarbon plume (Bujewski and Rutherford, 1997). Figure 4.17 illustrates the results of this evaluation when soil samples were used for comparison. False-positive and false-negative values were generally located along the contaminant plume boundaries. Sources of potential fluorescence from non-petroleum analytes include fluorescent minerals, naturally occurring organic material, de-icing agents, antifreeze additives,

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FIGURE 4.16 Fluorescence vs. depth waveform log produced with Rapid Optical Screening Tool (ROST™) testing. (From Taer, A. and S. Liberman, in National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, August 27–28, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, 1998. p. 7. With permission.)

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FIGURE 4.17 Comparison of ROST™ laser-induced fluorescence (LIF) detections and laboratory results for petroleum hydrocarbons in soil at Port Hueneme, CA.

and detergent products (Bujewski and Rutherford, 1997). Background sources of interferences that may contribute to the total intensity include window fluorescence, cladding/bugger fluorescence, Raman signals generated within the fiber and stray monochromator light. Appropriate control experience can be performed to distinguish these potential biases from true fluorescence signals. While a screening tool, the combination of a ROST™ and cone penetrometer testing technology provides the ability to perform several hundred feet of pushes in a single day, depending on soil depth and number of individual pushes. Such a day can be quickly mapped three-dimensionally to identify locations from which to collect samples. Targeted geochemical testing can then be performed on these samples. This technology also offers the ability to identify discrete horizons of petroleum hydrocarbon contamination and therefore additional sources that may not be identified by soil samples collected at 5- or 10-ft intervals.

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Aggarwal, P. and R. Hinchee, 1991. Monitoring in situ biodegradation of hydrocarbons by using stable carbon isotopes, Environmental Science and Technology, 25(6):1178–1180. Alexander, M., 1985. Biodegradation of organic chemicals, Environmental Science and Technology, 18:106–111. Alvarez, P. and T. Vogel, 1995. Degradation of BTEX and their aerobic metabolites by indigenous microorganisms under nitrate reducing conditions, Water Science Technology, 31:15–28. Alvarez, P., Heathcote, R., and S. Powers, 1998. Caution against interpreting gasoline release dates based on BTEX ratios in ground water, Ground Water Monitoring and Remediation, Fall:69–76. Baedecker, M. and W. Back, 1979. Hydrogeological processes and chemical reactions at a landfill, Ground Water, 17(5):429–437. Barker, J., 1996. Intrinsic plume remediation: chlorinated solvents and selected pesticides, in Dissolved Organic Contaminants in Groundwater, University Consortium Solvents-inGroundwater Research Program, San Francisco, CA, May 13–16, 1996, p. 29. Bartholomew, R., Brown, F., and M. Lounsbury, 1954. Chlorine isotope effect in reactions of tertbutyl chloride, Canadian Journal of Chemistry, 25:1173–1180. Bekins, B., Warren, E., and E. Goody, 1998. A comparison of zero-order, first-order, and monod biotransformation models, Ground Water, 36(2):261–268. Beneteau, K., 1999. Personal communication, 1999. Golder Associates, Calgary, Alberta, Canada. Beneteau, K., Aravena, R., Frape, S., Abragano, T., and R. Drimmie, 1996. Chlorinated Solvent Fingerprinting Using 13C and 37Cl Stable Isotopes, presented at the Section 121, H31B-12, American Geophysical Union Spring Meeting, Baltimore, MD. Berg, P., Rugge, K., Corsen, J., Nielsen, P., and T. Christensen, 1999. Degradation of aromatic and chlorinated aliphatic hydrocarbons in the anaerobic part of the Grinsted Landfill leachate plume: in situ microcosm and laboratory batch experiments, Ground Water, 37(1):113–121. Boutron, C., Gorlach, U., Candelone, J., Bolshov, M., and R. Delmas, 1991. Decrease in anthropogenic lead, cadmium and zinc in Greenland snows since the late 1960s, Nature, 356:153–156. Brothers, K., and K. Zikmund, 1998. Perchlorate: The Las Vegas Valley experience, in Proc. of the Southwest Focused Ground Water Conference: Discussing the Issue of MTBE and Perchlorate in Ground Water, June 3–4, National Ground Water Association, Anaheim, CA, pp. 85–109. Brown, A. and J. Clark, 1999. MTBE: air today, gone tomorrow, California Environmental Law and Remediation Reporter, 9(2):21–30. Brown, K., Sererka, P., Thomas, M., Perina, T., Tyner, L., and B. Sommer, 1997. Natural attenuation of jet-fuel impacted groundwater, in In-Situ and On-Site Bioremediation, Vol. 1, Battelle Press, Columbus, OH, pp. 83–88. Bruce, L. and G. Schmidt, 1994. Hydrocarbon fingerprinting for application in forensic geology: review with case studies, American Association of Petroleum Geologists Bulletin, 78(11):1692–1710. Bruya, J., 1999. Friedmand & Bruya, Inc., 3012 16th Avenue West, Seattle, WA 98119. Bruya, J., 1992. Petroleum Hydrocarbons: Analysis of Sample and Degradation in the Environment, a workshop presented at R&D, San Francisco, CA, p. 123. Bujewski, G. and B. Rutherford, 1997. The Rapid Optical Screening Tool (ROST™) LaserInduced Fluorescence (LIF) System for Screening of Petroleum Hydrocarbons in Subsurface Soils, Innovative Technology Verification Report, EPA/600/R-97/020, U.S. Environmental Protection Agency, Las Vegas, NV, p. 57.

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Buscheck, T. and C. Alcantar, 1995. Regression techniques and analytical solutions to demonstrate intrinsic bioremediation, in Hinchee, R., Wilson, J., and D. Downey (Eds.), Intrinsic Bioremediation, Battelle Press, Columbus, OH, pp. 109–116. Butler, E., 1999. Forensic applications of petroleum hydrocarbon fingerprinting at a wood treating site, in Proc. of Environmental Forensics: Integrating Advanced Scientific Techniques for Unraveling Site Liability, International Business Communications, Washington, D.C., June 24–25, p. 1. Calingaert, G., 1938. Anti-knock compounds, in The Science of Petroleum, Vol. 4, Oxford University Press, pp. 3024–3029. Cane, G. and I. Clark, 1999. Tracing ground water recharge in an agricultural watershed with isotopes, Ground Water, 37(1):133–139. Carrol v. Litton Systems, Inc., 1995. 47 F.3d 1164 4th Circuit. CEPA, 1996. Draft Policy for Cleanup of Petroleum Discharge, letter dated October 29, 1996, from Harry Schueller to Regional Water Quality Control Board Executive Officers, State Water Resources Control Board Resolution No. 1021b, California Environmental Protection Agency, Sacramento, CA, p. 4. Chapelle, F., 1999. Bioremediation of petroleum hydrocarbon contaminated groundwater: the perspective of history and hydrology, Ground Water, 37(1):122–132. Chapelle, F., Bradley, P., Lovley, D., and D. Vroblesky, 1996. Measuring rates of biodegradation in a contaminated aquifer using field and laboratory methods, Ground Water, 34(4):691–698. Christensen, L. and T. Larsen, 1993. Method for determining the age of diesel oil spills in the soil, Ground Water Monitoring and Remediation, 23(4):142–149. Clark, I. and P. Fritz, 1997. Environmental Isotopes in Hydrogeology, Lewis Publishers, Boca Raton, FL, p. 328. Cline, P. and J. Delfino, 1989. Transformation kinetics of 1,1,1-trichloroethane to the stable product 1,1-dichloroethene, in Larson, R.A. (Ed.), Biohazards of Drinking Water Treatment, Lewis Publishers, Chelsea, MI, pp. 47–56. Cline, P., Delfino, J., and S. Rao, 1991. Partitioning of aromatic constituents into water from gasoline and other complex solvent mixtures. Environmental Science and Technology, 25:914–920. Coleman, D., Liu, C., Hackley, K., and S. Pelphrey, 1995. Isotopic identification of landfill methane, Environmental Geosciences, 4:95–103. Coplen, T., 1996. New guidelines for reporting stable hydrogen, carbon and oxygen isotoperatio data, Geochimica et Cosmochimica Acta, 60:3359–3360. Coplen, T., Kendall, C., and J. Hopple, 1983. Comparison of isotope reference samples, Nature, 302:236–237. Davidson, J., 1999. The study of MTBE in forensic environmental investigations, in Proc. of Environmental Forensics: Integrating Advanced Scientific Techniques for Unraveling Site Liability, International Business Communications, Washington, D.C., June 24– 25, p. 6. Davidson, J. and D. Creek, 1999. Using the gasoline additive MTBE in forensic environmental investigations, International Journal of Environmental Forensics, 1(1):57–67. Davidson, J. and D. Creek, 1998. Using MTBE and other gasoline additives in forensic environmental investigations, in Proc. of the 14th Annual Conference on Contaminated Soils (abstract), University of Massachusetts at Amherst, p. 1. Dempster, H., Lollar, B., and S. Feenstra, 1997. Tracing organic contaminants in groundwater: a new methodology using compound-specific isotopic analysis, Environmental Science and Technology, 31(11):3193–3197.

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Steffan, R., McClay, K., Vainberg, S., Condee, C., and D. Zhang, 1997. Biodegradtion of the gasoline oxygenates methyl-tert-butyl ether, ethyl-tert-butyl ether and tert-amyl-methyl ether by propane oxidizing bacteria, Applied Environmental Microbiology, 63:4216–4222. Stewart, P., Lee, J., Marano, D., Spirtas, R., Forbes, C., and A. Blair, 1991. Retrospective cohort mortality study of workers at an aircraft maintenance facility. II. Exposure and their assessment, British Journal of Internal Medicine, 48:531–537. Stormant, D., 1960. SOCAL jilts ethyl for methyl, Oil and Gas Journal, 58(18):74. Stout, S., 1999. Use of biomarkers in assessing liability for fugitive petroleum products and crude oil, in Proc. of Environmental Forensics: Integrating Advanced Scientific Techniques for Unraveling Site Liability, International Business Communications, Washington, D.C., June 24–25, pp. 58–59. Stout, S., Seavey, J., Dahlen, D., McCarthy, K., and A. Uhler, 1999a. Application of low boiling biomarkers in assessing liability for fugitive middle distillate petroleum products. Session 2. Environmental forensics, in Conference Abstracts, 9th Annual West Coast Conference on Contaminated Soils and Water, Association for the Environmental Health of Soils, Oxnard, CA, p. 1. Stout, S., Davidson, J., McCarthy, K., and A. Uhler, 1999b. Gasoline additives: usage of lead and MTBE, Soils and Groundwater Cleanup, February/March:36–37. Stout, S., Uhler, A., and K. McCarthy, 1999c. Biomarkers — underutilized components in the forensic tool kit, Soil and Groundwater Cleanup, June/July:58–59. Stout, S., Uhler, A., Naymik, T., and K. McCarthy, 1998a. Environmental forensics: unraveling site liability, Environmental Science and Technology News, June 1:260–264. Stout, S., Uhler, A., and K. McCarthy, 1998b. PAH can provide a unique forensic “fingerprint” for hydrocarbon products, Soil and Groundwater Cleanup, October:25–29. Stout, A., Uhler, M., Philip, P., Allen, J., and A. Uhler, 1998c. Source differentiation of individual chlorinated solvents dissolved in groundwater using compound specific carbon isotopic analyses, Extended Abstracts from 216th American Chemical Society National Meeting, Environmental Chemistry Division, p. 6. Stukas, W. and L. Barrie, 1987. Lead 206/207 isotope ratios in the atmosphere of North America as tracers of U.S. and Canadian emission, Nature, 239:144–146. Suchomet, K., Kreamer, D., and A. Long, 1990. Production and transport of carbon dioxide in a contaminated vadose zone: a stable and radioactive carbon isotope study, Environmental Science and Technology, 24(12):1824–1831. Suflitia, J. and M. Mormile, 1993. Anaerobic biodegradation of known and potential gasoline oxygenates in the terrestrial subsurface, Environmental Science and Technology, 27:976– 978. Taer, A. and S. Liberman, 1998. Use of rapid optical screening tool technology to identify the distribution and composition of petroleum hydrocarbons, in Proc. of the National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 7 Tanaka, N., and D. Rye, 1991. Chlorine in the stratosphere, Nature, 353:707. Taylor C. and W. Roether, 1982. A uniform scale for reporting low-level tritium measurements in water, International Journal of Applied Radioactive Isotopes, 33:377–382. Touchstone, J., 1992. Practice of TLC, John Wiley & Sons, New York, p. 337. Uhler, A., Stout, S., and K. McCarthy, 1998a. Fingerprinting of light refined petroleum products, in Proc. of the National Environmental Forensic Conference: Chlorinated Solvents and Petroleum Hydrocarbons, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 24.

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Uhler, A., Stout, S., and K. McCarthy, 1998b. Increase success of assessments at petroleum sites in five steps, Soil and Groundwater Cleanup, January/February:13–19. Unocal, 1989. Material Safety Data Sheet for 1,1,1-Trichloroethane, Unocal Chemicals Division, Petrochemical Groups, Schaumburg, IL, p. 2. U.S. EPA, 1997. Environmental Technology Verification Program, Cone Penetrometer-Deployed Sensor, Rapid Optical Screening Tool (ROST), EPA/VSSCM/01, U.S. Environmental Protection Agency, Washington, D.C., p. 3. U.S. EPA, 1990. Standard Test Procedures for Evaluating Leak Detection Methods: Entire Set, EPA/530/UST-90/004–010, U.S. Environmental Protection Agency, Cincinnati, OH, p. 6. U.S. EPA, 1989. Volumetric Tank Testing: An Overview, EPA/625/9/89/009, U.S. Environmental Protection Agency, Washington, D.C., p. 37. U.S. EPA, 1988a. Tank Corrosion Study, EPA/510/K-92/802, U.S. Environmental Protection Agency, Cincinnati, OH, p. 44. U.S. EPA, 1988b. Musts for USTs: A Summary of the New Regulations for Underground Storage Tank Systems, EPA/530/UST-89/011, U.S. Environmental Protection Agency, Washington, D.C., p. 41. U.S. EPA, 1988c. Evaluation of Volumetric Leak Detection Methods for Underground Storage Tanks, EPA/600/2-88/68a, U.S. Environmental Protection Agency, Washington, D.C., p. 19. U.S. EPA, 1988d. Analysis of manual inventory reconciliation, EPA/510-S/92-802, U.S. Environmental Protection Agency, Cincinnati, OH, p. 5. U.S. EPA, 1987. Causes of Release from UST Systems: Report and Attachments, EPA/510-R/ 920702, U.S. Environmental Protection Agency, Cincinnati, OH, p. 76. Van Warnerdam, E., Frape, S., Aravena, R., Drimmie, R., Flatt, H., and J. Cherry, 1995. Stable chlorine and carbon isotope measurements of selected chlorinated organic solvents, Applied Geochemistry, 10:547–552. Vogel, T. and P. McCarty, 1987, Abiotic and biotic transformations of 1,1,1-trichloroethane under methanogenic conditions, Environmental Science and Technology, 21:1208–1213. Vogel, T., Criddle, C., and P. McCarty, 1987. Transformation of halogenated aliphatic compounds, Environmental Science and Technology, 21:722–736. Wait, A., 1999. Evolution of organic analytical methods in environmental forensic chemistry, International Journal of Environmental Forensics, 1(1):68–86. Walker, J., Colwell, R., and L. Petrakis, 1976. Biodegradation rates of components of petroleum, Canadian Journal of Microbiology, 22:1209–1213. Wang, Z. and M. Fingas, 1995. Use of methyldibenzothiophenes as markers for differentiation and source identification of crude and weathered oils, Environmental Science and Technology, 29:2842–2849. Wang, Z., Fingas, M., and G. Sergy, 1994. Study of 22-year-old Arrow Oil samples using biomarker compounds by GC/MS, Environmental Science and Technology, 29:1733– 1846. Ward, C., 1984. Gasoline, in Holland, D. (Ed.), Encyclopedia Americana, Grolier, Danbury, CT, pp. 337–338. Warren Rogers & Associates, 1981. Report on the Statistical Analysis of Corrosion Failures Unprotected Underground Steel Tanks, American Petroleum Institute, Washington, D.C., p. 145. Warren Rogers & Associates (undated). Predicting and Detecting Tank Leaks: The Economics of UST Integrity, Middletown, PA, pp. 14. Watmough, S., Hughes, R., and T. Hutchinson, 1999. 206Pb/207Pb ratios in tree rings as monitors of environmental changes, Environmental Science and Technology, 33(5):670–673.

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Weil, G., Graf, R., and L. Forister, 1994. Investigations of hazardous waste sites using thermal IR and ground penetrating radar, Photogrammetric Engineering and Remote Sensing, 60(8):999–1005. Westervelt, W., Lawson, P., Wallace, M., and F. Fosbrook, 1997. Intrinsic remediation of arctic diesel fuel near drinking water wells, in In Situ and On-Site Bioremediation, Vol. 1, Battelle Press, Columbus, OH, pp. 61–66. Whiticar, M., Faber, J., and M. Schoell, 1986. Biogenic methane formation in marine and freshwater environments: CO2 reduction vs. acetate fermentation —isotopic evidence, Geochimica et Cosmochimica Acta, 50:693–709. Woodbury, A. and H. Li, 1998. The Arnoldi-finite element method for solving transport of reacting solutes in porous media, in Wickramanayake, G. and R. Hinchee (Eds.), Nonaqueous Phase Liquids: Remediation of Chlorinated and Recalcitrant Compounds, Battelle Press, Columbus, OH, pp. 97–106. Younglass, T., Swansinger, J., Danner, D., and M. Greco, 1985. Mass spectral characterization of petroleum dyes, tracers and additives, Analytical Chemistry, 57:1894–1902. Zemo, D. and T. Graf, 1993. The importance and benefit of fingerprint characterization in site investigation and remediation focusing on petroleum hydrocarbons, in Proc. of the 1993 Conference on Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Restoration, National Ground Water Association, Houston, TX, pp. 39–54.

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Plate 4.1

Photograph of petroleum-impacted soil in a trench excavation.

Plate 4.2 Dye additives in different gasoline brands. (From Kaplan, I. et al., Organic Geochemistry, 27(5), 289–317, 1997. With permission.)

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5

Contaminant Transport Modeling

A useful approximation of realty or an intellectual toy?

5.1 INTRODUCTION A contaminant transport model is a work-in-progress hypothesis. Contaminant transport models are useful because they simplify reality for the purpose of predicting outcomes. In environmental litigation, contaminant transport models are used to confirm or challenge the allegation that a contaminant release occurred at a discrete point in time based on the observed presence of a contaminant some distance from the source. This opinion is usually based on knowledge of the location of the release, chemical test results, and a contaminant transport model. When evaluating contaminant transport models, examine the modeling results by dividing the subsurface into the following discrete zones: (1) the surface (paved and unpaved), (2) the soil and capillary fringe, and (3) the groundwater. This division is necessary because each zone requires different governing assumptions and mathematics that cumulatively determine the time required for a contaminant to travel from the ground surface to groundwater. The ability to reliably model contaminant transport is directly proportional to the representativeness of the input parameters. Given uncertainties associated with these input parameters, a range of values should be used that produces a range of contaminant transport probabilities. Practical inversion tools now allow for rigorous determination of optimal parameter values and what the data do and do not support. A key theme of this chapter is that a unique solution for contaminant transport models does not exist (see Figure 5.1).

5.2 LIQUID TRANSPORT THROUGH PAVEMENT A frequent inquiry is the determination of whether a solvent migrated through a paved surface such as asphalt, concrete, crushed rock, or compacted soil and, if so,

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FIGURE 5.1 Concept of a unique solution vs. a range of probable solutions.

the time required. Ideally, direct measurements are performed to answer this question by collecting a representative pavement core sample, ponding the liquid of interest, and recording the time required for the liquid to drip from the bottom of the sample. Absent direct measurement, contaminant transport equations are used. In order to select the correct equation(s), identification of the most likely transport mechanism — such as liquid advection (Darcy flux; see Equation 2.8 in Chapter 2), gas diffusion, liquid diffusion and evaporation — is required. The transport of dense non-aqueous phase liquids (DNAPLs) via liquid advection through pavement is commonly believed to be a rapid process. This assumption is true if the pavement is cracked, allowing unrestricted flow, or if the spill occurs over an expansion/control or isolation joint filled with permeable wood, oakum, or tar. Expansion joints are placed at the junction of the floor with walls, foundation columns, and footings. Given the sorptivity of the material used to fill expansion joints, sampling and testing of these materials are often useful to establish whether a contaminant was transported into the underlying soil via an expansion joint. Isolation joints are used to separate a concrete slab from other parts of a structure to permit horizontal and vertical movement of the concrete slab. Isolation joints extend the full depth of the slab and include pre-molded joint fillers (Kosmatak et al., 1988). In the absence of direct measurements or the presence of cracks or expansion joints or direct measurements with a pavement core, quantifiable transport variables can be identified that determine if and when a liquid permeated a paved surface. Variables used in calculating the time required for a liquid to infiltrate through a paved surface include:

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• • • • • • • •

The temporal nature of the release (steady state or transient) The saturated and unsaturated hydraulic conductivity of the pavement Physical properties of the contaminant (density, viscosity, vapor pressure) Chemical properties of the liquid (pure phase, mixed solvents, or dissolved in water) which affect the evaporation rate Liquid thickness and the length of time that the liquid was present on the paved surface Volume of the release Evaporative flux Pavement thickness, porosity, composition and slope

The circumstances of a contaminant release and pavement composition are key variables. Variables regarding the circumstances of the release include whether the liquid was in contact with the pavement for a sufficient time to allow transport through the pavement to occur. If the model does not account for evaporation and/ or assumes that the liquid thickness on the pavement is constant, the model will overestimate the rate of transport. If clean-up activities were performed coincident with the release (e.g., sawdust, green sand, absorbent socks, crushed clay, etc.) or if the spill occurred in a building with forced air, these activities and evaporative loss will compete for the solvent available for transport through the pavement. Noting the physical condition of the paved surface is needed for its incorporation into the model. Such observations would include: • Is the surface treated with an epoxy coating to prevent corrosion from acid releases (common in plating shops)? • Was the concrete mixed with an additive to reduce its permeability to chemicals (e.g., addition of Dow Latex No. 560 to the concrete)? • What was the nature of the surface prior to the release (e.g., impregnated with oils and dirt, smooth or pitted, sloped toward a drain, etc.)?

Once this specific information is collected, a conceptual model can be constructed. The saturated hydraulic conductivity or permeability value of the paved surface is a key variable. The terms hydraulic conductivity (K) and permeability (k) are associated with the ability of a porous media to transmit a fluid. While permeability and hydraulic conductivity are often used interchangeably, they are not synonymous. Permeability refers to properties associated with the media through which the contaminant is migrating, such as the distribution of the grain sizes, the sphericity and roundness of the grains, and the nature of their packing (Freeze and Cherry, 1979). Fluid properties such as density and viscosity are not included. The saturated hydraulic conductivity of a material is a measurement of the ability of a fluid to move through the material (Lohman et al., 1972). Hydraulic conductivity accounts for fluid density and viscosity. The release of a DNAPL compound such as tetrachloroethylene (PCE) (1.63 g/ cm3 at 20∞C) requires that the water-saturated hydraulic conductivity be adjusted to account for the differences in density and viscosity of PCE relative to water (Pankow and Cherry, 1996). As an example, the saturated hydraulic conductivity of water

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TABLE 5.1 Saturated Hydraulic Conductivity of Concrete for Non-Water Liquids Compound

Saturated Hydraulic Conductivity (K) for Concrete (cm/sec)

Water Trichloroethane (TCA) Trichloroethylene (TCE) Tetrachloroethylene (PCE) Freon-111 Freon-113 (1,1,2-trichlorotrifluoroethane) Methylene chloride Methylethyl ketone (MEK) Xylene Toluene Phenol

1 ¥ 10–10 6 ¥ 10–9 4 ¥ 10–9 6 ¥ 10–9 3 ¥ 10–9 4 ¥ 10–9 3 ¥ 10–9 5 ¥ 10–9 9 ¥ 10–9 7 ¥ 10–9 1.15 ¥ 10–7

through a mature, good-quality concrete is about 10–10 cm/sec. (Norton et al., 1931; Whiting et al., 1988). This value is corrected using the following definition of hydraulic conductivity: K = krwg/mw

(Eq. 5.1)

where K rw g mw

= = = =

intrinsic permeability. fluid density. gravitational constant (980.7 cm/sec2). fluid viscosity.

and k = K (mw/rwg)

(Eq. 5.2)

Table 5.1 lists conversions for non-water liquids assuming a saturated hydraulic conductivity of concrete to water of 10–10 cm/sec. The liquid thickness on the pavement and the duration of time that the liquid is in contact with the pavement are additional model variables. If a trichloroethylene release occurs on a warm sunny day or in a building with forced air, evaporation is rapid. As a consequence, little liquid is available to initiate movement into the pavement. If trichloroethylene accumulates in a blind concrete sump/neutralization pit or clarifier, the trichloroethylene (TCE) may reside for a sufficient period of time with a significant DNAPL hydraulic head to allow penetration into concrete. Numerous models are available to calculate the rate of transport of a liquid through pavement. For saturated flow, a one-dimensional expression for the vertical

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FIGURE 5.2 Difference between saturated and unsaturated hydraulic conductivity values.

transport of the liquid using Darcy’s Law is available. This expression defines the downward velocity (v) of the liquid as being equal to the downward flux (q) divided by the porosity of the pavement. The downward flux is the saturated hydraulic conductivity multiplied by the vertical gradient. Porosity values for paved materials are measured directly or obtained from the literature. This calculation results in a value in units of length over time that is divided into the pavement thickness to estimate the transport time. This approach does not consider the transient nature of the spill in which liquid thickness is changed due to evaporative loss. Pavement transport models that use Darcy’s Law assume that the pavement is saturated with liquid prior to the release. If the pavement is unsaturated, liquid transport is dominated by unsaturated flow resulting in contaminant velocities several times slower than for saturated flow. The importance of moisture content on unsaturated hydraulic conductivity relative to saturated flow conditions (100% saturated) is shown in Figure 5.2. For unsaturated flow, an equation analogous to Darcy’s equation called the Richard’s equation is used (Richards, 1931). A one-dimensional expression of this equation is C(∂y/∂t) = ∂/∂z(K∂y/∂z) + ∂K/∂z

(Eq. 5.3)

where C = the specific water capacity or change in water content in a unit volume of soil per unit change in the moisture content. y = suction head (i.e., matric potential). K = unsaturated hydraulic conductivity.

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TABLE 5.2 Vapor Density of Selected Compounds Compound Gasoline Benzene Xylene 1,1,1-Trichloroethane (TCA) Trichloroethylene (TCE) Tetrachloroethylene (PCE) Vinyl chloride (VC) Methyl-tertiary-butyl-ether (MTBE)

Vapor Density Relative to Air 4.0 3.0 4.0 4.5 4.5 5.7 3.0 3.0

If the pavement is partially or fully water saturated and a hydrophobic fluid such as trichloroethylene is released, the pore water in the pavement will repel the trichloroethylene. While the extent of repulsion is difficult to quantify, the net result is some degree of trichloroethylene retardation.

5.3 VAPOR TRANSPORT THROUGH PAVEMENT Gaseous diffusion through pavement can be more rapid than liquid transport, assuming that no cracks or preferential pathways are present. The development of a model to estimate vapor velocity through pavement requires the following information: • • • • • •

Vapor density and pressure of the contaminant Whether the vapor source is constant or transient above the pavement Henry’s Law constant of the contaminant Pavement thickness, porosity, and moisture content Concentration of the vapor above the pavement Concentration of the vapor within and below the pavement prior to the spill

The vapor density of the compound diffusing through the pavement is a key variable. The vapor density is approximately equal to the molecular weight (MW) of the compound divided by the molecular weight of air (29). The molecular weight of PCE is about 166 g/mol, so the vapor density is 166/29 = 5.7. Table 5.2 lists vapor densities of common compounds relative to air (Montgomery 1991; Pankow and Cherry, 1996). The value in knowing the vapor density of a volatile compound is that it provides a qualitative basis to determine if a sufficient period of time has occurred to allow the vapor to permeate through a paved surface; therefore, the topography of the paved

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surface is required to determine if features exist to allow accumulation of the vapor. Vapor degreasers, for example, are often set in a concrete catch basin to capture any liquid spills. While cement catch basins are effective at mitigating liquid spills, they exacerbate the potential for vapor transport through the concrete because they act as an accumulator for the solvent vapor. The catch basin also minimizes the dilution of the vapor with the atmosphere. Soil samples collected under degreaser catch basins are often non-detect for chlorinated solvents while soil vapor concentrations are high. An explanation for this observation is the presence of a vapor cloud in the soil (Hartman 1999). The significance of vapor clouds is that they migrate through the subsurface and can potentially contribute to groundwater contamination. Using the effective diffusion coefficient for the compound approximates the transport rate of a vapor cloud through soil. For many vapors, this value is about 0.1 cm2/sec. A general approximation is that the soil porosity reduces the gaseous diffusivity by a factor of 10. For many organic vapors, the gaseous diffusion coefficient is approximated as 0.01 cm2/sec. A rule-of-thumb calculation for the distance a vapor cloud moves through soil for many volatile compounds is estimated by Equation 5.4 (Hartman, 1997): Distance = (2)(0.01 cm2/sec ¥ 31,536,000)1/2 = 800 cm = 25 ft (Eq. 5.4) A more rigorous approach to this problem is via a differential equation for the unsteady, diffusive radial flow of vapor from a source (Cohen et al., 1993): ∂2Ca/∂r2 + [1/r(∂Ca/∂r)] = (RaD*)(∂Ca/∂t)

(Eq. 5.5)

where the air-filled porosity (na) is assumed to be constant (see Equation 5.7), Ra is the soil vapor retardation coefficient, Ca is the computed concentration of the vapor in air, and r is the source radius. The effective diffusion coefficient, D* (for TCE, 3.2 ¥ 10–6 m2/sec; for PCE, 0.072 cm2/sec) (Lyman et al., 1982) is equal to: D* = Dta

(Eq. 5.6)

where ta = n a2.333/n2t, n2t is the total soil porosity which is the sum of the air-filled porosity and the volumetric water content (Millington, 1959), and the soil vapor retardation factor (Ra) is determined by: Ra = 1 + nw/(naKH) + rbKd/(naKH)

(Eq. 5.7)

where nw is the bulk water content, na is the air-filled soil porosity, rb is the soil bulk density, Kd is the distribution coefficient, and KH is the dimensionless Henry’s Law constant. Numerous vapor transport equations are available to estimate the travel time of vapor through pavement (Crank, 1985; McCoy and Roltson, 1992). These equations describe specific conditions that best represent the events associated with the vapor release. Appendix A provides a sample calculation for the vapor transport of PCE through a concrete pavement.

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5.4 CONTAMINANT TRANSPORT IN SOIL If a liquid has penetrated the pavement, estimated transport times for the contaminant can be calculated for the second zone (soil). Variables used to perform this calculation include: • • • • •

Saturated hydraulic conductivity and porosity of the soil Variability of vertical vs. lateral hydraulic conductivity Presence of lower permeability horizons such as clay Fluid properties (density, viscosity, etc.) Depth to groundwater

As with contaminant transport through asphalt or concrete, the hydraulic conductivity of a contaminant (if in pure form) is adjusted using the relationship for intrinsic permeability. For diesel, the conversion is described as: (Kdiesel – Kwater)([mwater/mdiesel][rdiesel/rwater])

(Eq. 5.8)

Assuming that diesel viscosity is 0.042 cP (water = 0.1 cP) and diesel density is 0.84 g/cm3 (water = 1.0 g/cm3), then Equation 5.8 yields an expression that describes the saturated hydraulic conductivity of diesel through a soil as equal to about 0.20 the velocity of water; therefore, diesel travels slower than water through this soil. If differences in the viscosity and density of diesel are not considered, the calculated transport time using the hydraulic conductivity for water overestimates the rate of diesel transport. Numerous equations exist to describe contaminant transport through soil (Ghadiri et al., 1992; Selim et al., 1998). A common equation for the one-dimensional transport of a single component via advection and diffusion in the unsaturated zone is described by Equation 5.9 (Jury and Roth, 1990; Jury and Sposito, 1985; Jury et al., 1986). Rl∂Cl/∂t = Du ∂2Cl/∂z2 – V∂Cl/∂z – lmRlCl

(Eq. 5.9)

where Rl Cl Du lm V

= = = = =

liquid retardation coefficient. pore water concentration in the vadose zone. effective diffusion coefficient. decay constant. infiltration rate.

The retardation coefficient (Rl) is estimated by: Rl = rbuKdu + qm + (fm + qm) KH where rbu = soil bulk density. Kdu = distribution coefficient for the contaminant of interest.

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(Eq. 5.10)

qm = soil moisture content. fm = soil porosity. KH = Henry’s Law constant for the contaminant of interest.

The distribution coefficient (Kdu) of the contaminant of interest can be estimated via: Kdu = 0.6 foc,u Kow

(Eq. 5.11)

where foc,u = fraction of organic carbon in the soil. Kow = octanol-partition coefficient of the contaminant of interest.

The degradation rate constant can be estimated by Equation 5.12: lm = ln(2)/T1/2 m

(Eq. 5.12)

where T1/2 m is the degradation half-life of the contaminant of interest. The effective diffusion coefficient is Du = tL DLM + KH tG DGM

(Eq. 5.13)

where tL DLM tG DGM

= = = =

soil tortuosity to water diffusion. molecular diffusion coefficient in water. soil tortuosity to air diffusion. molecular diffusion coefficient in air.

The tortuosity associated with the diffusion of a compound in water and air is described by Equation 5.14 (Millington and Quirk, 1959): tL = qm10/3/fm2 and tG = (fm – qm)10/3/fm2

(Eq. 5.14)

For a non-aqueous phase liquid (NAPL), the NAPL velocity (nu) for the vertical migration via a constant rate release is approximated by Equation 5.15 (Parker, 1989): nu = (rro kro Kn)/(hro fa S) where rro kro Kn hro fa S

= = = = = =

specific gravity of the NAPL. relative permeability of the NAPL. vertical saturated hydraulic conductivity to water. the light non-aqueous phase liquid (LNAPL)-water viscosity ratio. the initial air-filled porosity of the soil. the effective NAPL saturation behind the infiltration front.

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(Eq. 5.15)

The travel time for the LNAPL to move through the unsaturated zone is therefore equal to the distance from the source to the water table divided by the NAPL velocity (nu). A question that arises in environmental litigation is when did the contamination enter the groundwater? This question is answered by using Darcy’s Law. An example is the release of diesel from an underground storage tank. If the diesel flows through more than one soil type, a transport rate through each soil horizon is required. Input variables include the saturated hydraulic conductivity of the soil, soil porosity, and the hydraulic gradient for each horizon. Assuming a knowledge of the underlying soils (pea gravel and mixed sands) and the saturated hydraulic conductivity of these soils between the tank bottom and the groundwater table (ª24.5 ft) and that Darcy’s Law is valid, Table 5.3 is an example of the tabulated results. The total travel time for the release of diesel into the soil is about 225 days. An issue regarding the results in Table 5.3 is that it offers a unique solution. A more defensible approach is the use of a range of input parameter values (primarily the saturated hydraulic conductivity value) (Morrison, 1998). A novel approach for identifying when a DNAPL has been released into a lowpermeability layer of base of an aquifer has been reported (Parker and Cherry, 1995). Soil cores collected at discrete distances from the DNAPL provide the basis for identifying the concentration of the dissolved contaminant. Diffusion calculations are then employed to estimate the length of time that diffusion has occurred and therefore the time since the DNAPL was immobilized. Assumptions include the premise that low-permeability layers of silt and clay underlying the perched DNAPLs have sufficient porosity to allow, without advection, migration of the dissolved constituents into the soils via molecular diffusion and that the location of the DNAPL is precisely known.

5.4.1 CHALLENGES TO CONTAMINANT TRANSPORT MODELS FOR SOIL Transport mechanisms and pathways exist that are rarely included in contaminant transport models. Artificial examples include dry wells, foundation borings, utility trenches, sewer or stormwater backfill, cisterns, and septic lines. Natural preferential pathways include high-permeability soils, mechanical disturbance, and cosolvent transport. Table 5.4 lists some of these pathways and common computer model variables along with their impact on contaminant transport.

5.4.2 COLLOIDAL TRANSPORT Colloidal transport is a mechanism by which a hydrophobic compound preferentially sorbs to a colloid particle in water and is transported to depth. Colloids are generally regarded as materials up to 10 mm (10–6 m) in size. Colloids exist as suspended organic and inorganic matter in soil or aquifers. In sandy aquifers, the predominant

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TABLE 5.3 Summary of Transport Calculations for Individual Soil Layers Layer Pea gravel Sand Sand Sand Total

Kwater (cm/sec)

Thickness (ft)

Kdiesela (cm/sec)

Vb (cm/sec)

Travel Time

0.1 1.1 ¥ 10–4 6.6 ¥ 10–5 2.7 ¥ 10–5

1.0 7.75 10.75 5.0

0.02 2.2 ¥ 10–5 1.3 ¥ 10–5 5.4 ¥ 10–6

20 7.3 ¥ 10–5 4.3 ¥ 10–5 1.8 ¥ 10–5

1.5 sec 900 hr 2100 hr 2400 hr 225 days

Kdiesel – Kwater (mwater/mdiesel)(rdiesel/rwater), where mwater = 0.01 cP and rwater = 1.0 g/cm3 and mdiesel and rdiesel = 0.042 cP and 0.84 g/cm3, respectively. a

b

Porosity = 0.30 and dH/dL = 1.0.

colloids that are mobile range in size from about 0.1 to 10 mm. The importance of colloidal particles on contaminant mobility diminishes as the octanol-water partition coefficient (Kow) decreases. The mass of contaminants associated with colloids may be significant. In a study of PCBs and polycyclic aromatic hydrocarbons associated with different size fractions of groundwater colloids underlying an abandoned landfill, over two thirds of the total amount of contaminants were associated with colloids greater than 1.3 nm (1 nm = 10–9 m) (Villholth, 1999). Another example is the transport of polycyclic aromatic hydrocarbons via colloidal transport, which was examined in two creosotecontaminated aquifers on Zealand island in Denmark. The mobile colloids were dominated by clay, iron oxides, iron sulfides, and quartz particles. The researchers concluded that the sorption was associated with the organic content of the colloids. Creosote-associated contaminants were also found to be associated primarily with colloids that were larger than 100 nm. These findings indicate that colloid-facilitated transport of polycyclic aromatic hydrocarbons exists and may be significant. This transport mechanism is rarely included in a soil or groundwater transport model.

5.4.3 PREFERENTIAL PATHWAYS Preferential pathways provide a means for dissolved and precipitated phase polymeric species and hydrophobic compounds to be adsorbed to colloids and to be rapidly introduced at depth. Preferential flow pathways include natural and artificial features such as worm channels, decayed root channels (Plate 5.1*), soil fractures, swelling and shrinking clays, insect burrows, dry wells (Plate 5.2*), open cisterns, septic lines, macropores, and highly permeable soil layers. The significance of preferential flow is that the actual travel time of a compound to the water table is * Plates 5.1 and 5.2 appear at the end of the chapter.

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TABLE 5.4 Variables of Contaminant Transport in Soil and their Impact on Contaminant Velocity Soil Variables Impacting Transport

Comments and Impacts

Soil porosity

Changes in soil porosity can result in multiple velocities with depth through the soil column. Coarse-grained materials tend to have a higher porosity than fine-grained materials. The porosity of dense crystalline rocks, tight shales, caliche, and unweathered limestone may range from less than 0.01 to 0.10.

Volume of release

Impacts whether saturated or unsaturated flow dominates, the time required for residual saturation to occur, and the degree of contaminant spreading.

Saturated vs. unsaturated flow

Unsaturated flow is slower than saturated flow (see Figure 5.2). Moisture content with depth determines the hydraulic gradient and therefore the rate of transport in unsaturated flow conditions.

Fingering

Impedes flow and introduces uncertainty regarding contaminant velocity and the geometry of the contaminant plume.

Preferential pathways

Increases the flow rate, time-dependent spreading.

Pavement composition, thickness, presence of cracks, presence or absence of surface coatings and/or expansion joints.

Impedes or accelerates flow.

Surface spill volume, duration, evaporation, surface area and thickness of ponded liquid

Determines whether sufficient liquid is available for flow to occur into the subsurface.

Depth to groundwater at time of release

Impacts the time required for entry into the groundwater.

Cosolvation

Increases the depth of penetration of otherwise low-mobility compounds.

Chemical mixture and physical characteristics

Impact liquid density, viscosity, and saturated or unsaturated hydraulic conductivity values of the fluid.

Changes in soil redox and/or pH Increases or decreases the depth of penetration of otherwise lowmobility contaminants, such as metals.

order of minutes or hours rather than days or months (Barcelona and Morrison, 1988). The term “preferential flow” encompasses a range of processes with similar consequences for contaminant transport. The term implies that infiltrating liquid does not have sufficient time to equilibrate with the slowly moving water residing

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in the soil (Jarvis, 1998). Preferential flow includes the following transport processes: finger flow (also viscous flow) (Bisdom et al., 1993; Glass and Nicholl, 1996), funnel flow (Diment and Watson, 1985; Hill and Parlange, 1972; Kung, 1990a,b; Philip, 1975), and macropore flow (Bouma, 1981; Morrison and Lowry, 1990; White, 1985). Finger flow (also dissolution fingering) is initiated by small- and large-scale heterogeneities in soil such as a textural interface between a coarse-textured sand that underlies a silt (Fishman, 1998; Miller et al., 1998). The term “finger flow” refers to the splitting of an otherwise uniform flow pattern into fingers. These fingers are associated with soil air compression encountered where a finer soil overlies a coarse and dry sand layer. The contact interface between the contaminant and the water in the capillary fringe results in an instability (see Plate 5.3*). The spacing and frequency of these fingers are difficult to predict, although they are at the centimeter scale and are sensitive to the initial water content (Imhoff et al., 1996; Ritsema and Dekker, 1995; Wei and Ortoleva, 1990). Numerical simulations of fingering suggest that transverse dispersion is a significant impact on the formation and anatomy of fingers. Aspects of the fingering phenomenon that introduce uncertainty when modeling contaminants such as NAPLs include (Miller et al., 1998): • The effect of dispersion • The impact of heterogeneity on porous media properties and residual NAPL saturation • The validity of fingering when a NAPL solution is flushed with chemical agents such as surfactants and alcohols • Incorporation of the impacts of fingering on NAPL phase mass transfer models when the model is discretized at scales larger than the centimeter scale

Funnel flow occurs in soils with lenses and admixtures of particle sizes. For a saturated soil, the most coarse sand fraction is the preferred flow region; for unsaturated flow, finer textured materials are more conductive. Examination of textural descriptions on boring logs and contaminant concentration depth profiles can provide insight to determine if contaminant transport via funnel flow is a viable transport mechanism. A macropore is a continuous soil pore that is significantly larger than the intergranular or inter-aggregate soil pores (micropores). In general, a macropore is one order of magnitude greater in dimension than the indigenous soil micropores. While a macropore may constitute only 0.001 to 0.05% of the total soil volume, it may conduct a majority of an infiltrating liquid. Plate 5.4* illustrates the impact of liquid transport via macropores in a mature soil in the United Kingdom. Hydrated gypsum was ponded on the ground surface and drained into the underlying soil via macropores. The gypsum then dehydrated, leaving the macropore channels clearly visible. * Plates 5.3 and 5.4 appear at the end of the chapter.

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5.4.4 COSOLVENT TRANSPORT Hydrophobic compounds are generally considered to be immobile in the soil profile, due primarily to their low water solubility and their tendency to be adsorbed by clay, organic matter, and mineral surfaces (Odermatt et al., 1993). Soil contaminant transport models tend to predict low velocities for these compounds. Cosolvation of these compounds with a fluid can introduce these contaminants at depth, but this phenomenon is rarely included in contaminant transport models. Contaminants such as polychlorinated biphenyls (PCBs) or DDT can be re-mobilized by the preferential dissolution of the PCBs into a solvent released into the same soil column (Morrison and Newell, 1999). A variation of this scenario is the preferential dissolution of an immobile chemical into a solvent prior to its release (e.g., PCBs dissolved in a dielectric fluid). A similar transport mechanism occurs when a contaminant sorbed by a soil is washed with a liquid that re-mobilizes the compound. An example is the presence of copper bound in soil under a leaking neutralization pit. Low pH wastewaters leaking through an expansion joint and contacting the precipitated copper will remobilize and transport the copper with the low pH wastewaters to depth until the acidic wastewater and copper solution is buffered and the copper re-precipitates at a lower depth.

5.5 CONTAMINANT TRANSPORT IN GROUNDWATER In environmental litigation, groundwater models are usually used in a predictive, interpretative, or generic application. Predictive models forecast the future of some action and require calibration. Interpretative models are used to study aquifer and contaminant dynamics. Generic models are used to analyze flow in hypothetical systems, such as for regulatory purposes. The transport of a contaminant in groundwater is controlled by the aquifer parameters (advective model) and by physical and chemical processes that are simulated in the contaminant transport portion of the model. The advective portion of a contaminant transport model requires measured groundwater elevations. The primary hydraulic forces in an advective model are the main driving forces, natural transient forces, and manmade transient forces. An example of an advective model is MODFLOW. Since its release by the U.S. Geological Survey in the early 1980s, MODFLOW has become the international standard code for three-dimensional, finite-difference groundwater flow modeling (McDonald and Harbaugh, 1988). Mass transport models such as MT3D (Modular Transport Three-Dimensional) are coupled to an advective model such as MODFLOW to simulate the threedimensional advection, dispersion, and chemical transformations of contaminants (Zeng, 1993, 1994). MT3D is available commercially and in the public domain (the U.S. Environmental Protection Agency provided partial support for the development of MT3D).

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FIGURE 5.3 Effects of aquifer physical parameters on contaminant transport.

The selection of a model is made in large part by identifying the primary processes controlling contaminant transport that the user intends to simulate. These processes include aquifer physical parameters, the initial contaminant concentrations, physical processes, chemical attenuation, and biological attenuation. Figures 5.3 and 5.4 summarize the impact of these hydraulic, physical, chemical, and biological processes on contaminant transport in groundwater (Szecsody, 1992). If the model intends to simulate any or all of these processes, the value assigned and the accuracy of the number should be fully evaluated. The developmental progression of a model used for contaminant transport includes the following steps: • • • • • •

Identification of the goal of the modeling Creation of a conceptual model Selection of the governing equations and computer code Adjustment of the conceptual model for modeling Model calibration with field measurements Sensitivity analysis to establish the effect of input parameters variations on model output • Model verification via calibrated of parameter values and stresses • Performance of computer simulations or runs to predict future events

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FIGURE 5.4 Effects of physical, chemical, and biological processes on contaminant transport.

• Post-auditing to test the reliability of the simulations by comparing simulated results with new acquired field measurements • Model calibrations to reflect changes in the post-audit step

5.5.1 TYPES OF GROUNDWATER MODELS Three types of groundwater models are physical or scale models, analog, and mathematical models. Physical or scale models include physical experiments using boxes filled with a representative media into which fluids are introduced. Analog models use materials such as electrical circuits to represent a groundwater system. While popular prior to the advent of personal computing, they are seldom used. Mathematical models are divided into three types: analytical, numerical, and analytic element and contain the following components: • Definition of the site boundary conditions • Equation(s) describing the contaminant mass balance within the modeled boundary

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• Equations that relate contaminant flux to relevant variables • Equation(s) that describe the contaminant and hydrogeological conditions at an initial time • Equation(s) that describe the interaction of the contaminant within the prescribed boundary conditions

Analytic element models are adaptations of established analytical techniques whereby several analytic functions are solved simultaneously. Analytical models use closed-form equations or solutions to the partial differential equations governing groundwater flow (Bear 1979; Van Genuchten and Alves, 1982). An analytical model is easily solved. This simplification is a limitation, as aquifer homogeneity, isotropy, and an infinite horizontal extent are assumed. For complex hydrogeological settings, they are usually inadequate. A numerical flow model solves partial differential equations governing flow at discrete points or nodes within a groundwater system. Numerical models require elaborate computational methods to solve flow equations at a discrete set of points within an aquifer(s). Examples include: • • • •

Finite-difference Finite-element Boundary-element Particle tracking: method of characteristics (MOC), modified method of characteristics (MMOC), and random walk • Integrated finite-difference models

Numerical models can be converted to a format amenable to visualization. Because the physical properties at each point in the model can be varied, numerical methods can solve flow problems in complex hydrogeological systems. Features such as biodegradation, radioactive decay, sources, and sinks can be included in the model. Analytic element models combine aspects of analytical and numerical models. A set of simultaneous equations with an equal number of unknowns are solved using numerical techniques, while analytic functions are superimposed onto a particular site feature, such as a river or pumping groundwater well. An advantage of an analytic element model is that a small portion of the site can be intensively modeled or multiple aquifer systems can be examined. Most analytic element models are proprietary. Groundwater models can provide greater understanding of a flow system and contaminant transport. Groundwater models are commonly encountered in insurance coverage cases, in litigation to demonstrate that a potentially responsible party has contributed to the contamination of a Superfund site, and to illustrate long-term impacts of an unremediated contaminant plume over time. The following is a brief outline of the use of groundwater modeling and its application in environmental litigation. For a further understanding, numerous texts on groundwater modeling are available (Freeze and Cherry, 1979; Zeng and Bennett, 1995).

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The foundation of groundwater modeling is the advection-dispersion equation. Governing assumptions are that the porous medium is homogeneous and isotropic, the medium is saturated with a fluid, and Darcy’s Law is valid. If these assumptions are violated, the applicability or precision of the model in predicting contaminant flow is compromised to some degree. The selection of the contaminant transport model that is appropriate for the particular site is important and should be carefully considered when evaluating a contaminant groundwater model. If the conceptual model does not represent the relevant flow and contaminant transport phenomena, the subsequent modeling effort is wasted. This is not to say that misuses may not occur during any phase of the modeling process. Common misuses and mistakes associated with modeling include (Bear et al., 1992; Mercer, 1991): 1. Improper conceptualization of a groundwater model relative to the site — for example, selection of a three-dimensional model when a two-dimensional model is sufficient can lead to complications in the modeling effort. Incorrect assumptions concerning the significant contaminant processes, such as contaminant transport, which are then incorporated into the model can magnify the inaccuracy of the model. Disregarding the importance of retardation of a chemical or discounting the impact of biological transformations are other examples. 2. Selection of an inappropriate computer code for solving the problem — it is not uncommon for a consultant to select a computer code that is too versatile or powerful for the site and the availability of input parameters. 3. Improper model applications usually results in the selection of improper values for modeling. Examples include the misrepresentation of aquitards in a multi-level system or identifying and modeling contaminant transport in a series of aquifers which are actually one hydraulically connected aquifer. 4. Misinterpretation of modeling results occurs if mass balance is not achieved or if calibration of the modeling results with field data is not performed. The end result of the model is the ability to simulate contaminant transport based on actual field measurements. 5. Uncertainty is posed by the inability to accurately model various sinks (irrigation wells, spring discharge, etc.) and sources (rivers, lakes, temporal irrigation, or watering, etc.) over time that impact model precision.

Inappropriate model selection is one of the most common shortcomings. It is useful to direct the expert witness to prepare a table describing the model and then compare it to the site. Differences in the capabilities of two computer models are summarized in Table 5.5. The SWIFT model permits a great deal more model complexity and flexibility than does the QUICKFLOW model. This is because the two models address the groundwater flow systems in different ways. The analytical element model QUICKFLOW uses hand-derived analytical solutions which are then incorporated into the program. These analytical solutions are derived for simplified flow situations; otherwise, the mathematics become too difficult to solve. The numerical model SWIFT permits greater complexity because the flow and transport equations are solved by computer code.

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TABLE 5.5 Comparison of SWIFT III and QUICKFLOW Computer Models SWIFT III

QUICKFLOW

Solves for both groundwater flow and transport of contaminants Three-dimensional Allows vertical groundwater flow Numerical model (finite difference grid)

Solves for groundwater flow only

Allows multiple layers Allows partially penetrating wells Pumping rates from wells can vary over time Complex starting head distribution allowed Complex hydraulic conductivity, porosity, and storativity distributions allowed Boundary conditions are required

Two-dimensional Does not allow for vertical groundwater flow Analytical model (continuous analytical elements) Single layer only Assumes fully penetrating wells Pumping rates in all wells are constant over time Assumes uniform regional flow Aquifer must have a uniform hydraulic conductivity, porosity, and storativity Reference head is required

5.5.2 SELECTION OF BOUNDARY CONDITIONS, GRIDS, AND MASS LOADING RATES Boundary conditions are required whenever a computer model is created. For a program such as MODFLOW, general head boundaries are used to define the lateral boundary conditions that define the flux of water recharge or discharge along these boundaries. The boundary conditions are a function of the hydraulic conductivity, groundwater flow gradient, and the absolute difference in water level elevations between the block elements located on the lateral boundaries with locations located outside of the model grid. Common specified boundary conditions include no-flow, specified flux, and fixed head boundaries. While model boundary conditions are fixed and cannot be changed during a single simulation, they can be adjusted between simulations. It is conceptually undesirable to alter the boundary flux conditions to assist in calibration of each stress period vs. accounting for these differences by adjustments in dynamic features such as pumping wells or recharge of surface water bodies located within the grid. The impact of a model boundary can be examined if all model input files and software are available to reproduce the modeling result using different boundary conditions. Grid selection is important. For numerical models, finite difference and finite element grids are used, while block-centered and mesh-centered grids are used for finite element grids. Finite element grids are generally more versatile than finite difference grids. For a finite difference model, examine the grid density to ascertain whether the data support finer mesh nodes or whether higher grid densities are selected in areas of interest but which contain insufficient data to warrant a higher grid density.

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In finite-difference modeling, numerical dispersion is inherent due to errors associated with model design, especially in areas of varying grid size. The threedimensional block size selected must be examined to determine the relative horizontal and vertical element aspect ratio. Aspect ratios less than four are generally acceptable; horizontal and vertical aspect ratios that are greater than four become more susceptible to numerical dispersion. Minimization of numerical dispersion in the model grid used for solute transport is accomplished by selecting a Peclet number (Pe = DL/a) where DL is the length of the elemental box and a is the dispersion coefficient (£1). Grids designed with a DL less than 4a are recommended; if the model violates this value, the model is susceptible to considerable numerical errors. For multiple-layered models, determine whether the vertical gradients between the layers are measured or estimated. To confirm measured vertical gradients, divide the head difference between a shallow and deep well by the vertical distance between the bottom of both well screens. A negative value indicates a downward flow component. If the vertical gradients are estimated, attempt to determine the level of uncertainty associated with these values and their overall impact on solute transport between layers. For contaminant transport models, contaminant loading rates at sources located within a grid are arbitrary. Issues regarding the validity of a particular loading rate and its location include determining whether: • The soil and groundwater chemistry justify the selected location and input rate • The mass loading rate is continuous or is transient in response to groundwater fluctuations or remediation activities • The start date for the mass loading is consistent with the operational history of the contributing surface sources

Most contaminant transport models automatically perform a mass balance, and this output should be obtained. A significant error in the mass balance calculation indicates that the solution is numerically imprecise to some degree.

5.5.3 SOFTWARE APPLICABILITY An individual familiar with contaminant transport models is needed to ascertain if the appropriate computer software was selected and if it was adequate and/or capable of modeling the physical system of interest. In 1984, for example, there were in excess of 400 groundwater flow and transport models around the world (van der Heijde, 1984). A contaminant transport model used to create a trial exhibit should be sufficiently complex to account for all relevant physical processes. Model complexity is determined by the quality of the data available for its design and verification. An example of inappropriate model selection is using a simple two-dimensional model for a complex three-dimensional system. Conversely, a complex three-dimensional model may be selected that is overpowered relative to the available data. Model selection considerations include the following issues (Cleary, 1995):

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• Select a model with the prestige of a state or governmental agency which has a substantial published history in peer-reviewed journals and has already been tested in court. If the model code is obscure, thoroughly scrutinize the code. • The model should include a user’s manual listing its governing assumptions, advantages, and capabilities. • The model can be validated against analytical solutions for comparison. The analytical solution should have the same number of space dimensions as the numerical model. • The model should be benchmarked against a numerical code. • The model should have an available source code. • The selection of a three-dimensional model always has an advantage of better representing reality than a two-dimensional approximation.

The model simulation ultimately selected to create a trial still or animation should be evaluated in the context of all the simulations. It is not unusual for hundreds of simulations to be performed until a simulation is obtained for use as evidence for a particular allegation. Discarded simulations should be obtained and compared with the selected simulation so that the legitimacy of the selected simulation can be evaluated.

5.6 APPLICATION OF GROUNDWATER MODELING IN ENVIRONMENTAL LITIGATION The rate of contaminant transport in groundwater is often alleged to provide a basis for determining the source and the length of time required for the contaminant plume to reach its observed dimensions. Groundwater models used in this context are known as confirmation or reverse models (Morrison et al., 1999a,b).

5.6.1 CONFIRMATION MODELS Confirmation models are used with other corroborative evidence to (1) confirm the time when a reported release occurred, and/or (2) examine the consistency of an observed contaminant plume with contaminant release information (i.e., rate of release, location, and duration) (Morrison, 1999a). Model parameters are adjusted so that model predictions agree with measured hydraulic head and contaminant concentrations at specific monitoring well locations. If the distance between the leading edge of a contaminant plume and the source is known, this distance provides insight into the long-term average groundwater flow rate and direction. A common legal application of a confirmation model is to verify deposition testimony or testing concerning the volume and/or direction of a release (Hughes v. Beagley, 1995; Hughes v. Hartford, 1994). A confirmation model assumes that a release occurred at a specific point in time. Model parameters are adjusted so that model predictions agree with measured water

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and contaminant levels. Plate 5.5* is an example of a confirmation model where the presence of TCE in groundwater is correlated to an estimated release approximately 25 years prior to the TCE plume observed in 1985. In this figure, hydraulic and groundwater chemical data were only available from 1980 to 1985; therefore, groundwater and chemical distributions from 1970 to 1980 are inferred. A variation to this figure would be hydraulic and chemical data available from 1970 to 1985. The observed contaminant distribution from 1970 would then be simulated forward to 1985 to verify the consistency of the testimony concerning the timing of a release with the contaminant plume geometry.

5.6.2 REVERSE MODELS Reverse (also called backward extrapolation and backcasting) models are used to predict, in reverse, when and where a contaminant entered the groundwater (Bois and Luther, 1996; Kezsbom and Goldman, 1991; Kornfeld, 1992; Morrison and Erickson, 1995). Reverse modeling is distinguished from confirmation models in that detailed information about the contaminant release are unknown. In its simplest application, reverse modeling relies upon the observed length of a contaminant plume and a representative groundwater velocity to estimate the timing of a release. As with confirmation modeling, this approach is predominantly used in insurance litigation to identify the timing of an alleged release of a contaminant or to associate a particular release with detection of the released contaminant in groundwater (Carrier Corp. v. Detrex, 1996; Sterling v. Velsicol Chemical Corp.; 1988).

5.6.3 HYDROGEOLOGIC VARIABLES Confirmation and reverse models rely on hydrogeologic and contaminant characteristics to estimate the origin and timing of a release. Hydrogeologic variables include the following: • • • •

Saturated hydraulic conductivity Groundwater gradient Soil porosity Horizontal and transverse dispersivity

The reliability of these values depends on whether they are measured in the field or laboratory or are from published values. Of the hydrogeologic parameters, the saturated hydraulic conductivity value introduces significant variability in the computer simulations (Rong et al., 1998). It is generally recognized that the most representative measurements for determining the hydraulic conductivity of a formation are obtained with a pump test. Hydraulic conductivity values that rely upon slug tests, sieve analyses, and laboratory measurements * Plate 5.5 appears at the end of the chapter.

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of soil cores are considered less reliable. The values obtained from a slug test are generally reliable to about one or more orders of magnitude, with its accuracy increasing for less-permeable aquifers. Because the slope of the groundwater table and changes in soil porosity differ significantly with soil texture, a scientifically defensible approach is to use a range of values for the saturated hydraulic conductivity, hydraulic gradient, and soil porosity. The selected hydraulic gradient value can vary in time and distance. The groundwater gradient can vary considerably in both direction and gradient with distance. If regional or vicinity-wide data are relied upon to define the hydraulic gradient vs. site measurements, considerable differences can occur. Sources of localized variations in the gradient include pumping wells, rivers, streams, and groundwater recharge, or spreading basins. If pumping wells in the immediate vicinity of the site are present, collecting the extraction rates and representative transmissivity values for the aquifer and calculating the radius of pumping influence are useful to demonstrate the potential impact of pumping wells on the local gradient. Historical variations in the hydraulic gradient introduce uncertainty regarding the historical direction of groundwater flow and hence the time required for the contaminant plume to attain its measured leading-edge geometry. Typical values range from 0.1 to 0.001. The soil porosity within an aquifer and with distance can change dramatically. A representative porosity value, especially on a field scale, is usually a fitted parameter within a published range of values for the predominant soil type encountered; as a result, considerable differences in the modeling results can be adjusted by slight variations in the selected porosity value. Typical porosity values range from 0.25 to 0.50 for unconsolidated soils. Dispersivity describes the three-dimensional spreading of a contaminant plume in groundwater with distance. Most contaminant transport models require a horizontal (longitudinal), vertical, and transverse dispersivity value. Longitudinal dispersivity is caused primarily by differences in groundwater flow through aquifer pores at a scale less than that used to characterize values of saturated hydraulic conductivity. Longitudinal dispersivity increases with distance from the source (also known as macrodispersivity). If a model assumes that the contaminant plume length is only due to advective flow, the estimated date of the release will be longer than if dispersivity and advective flows are considered. An expression of longitudinal dispersivity (DL) is given by Equation 5.16 (Gelhar et al., 1992). DL = exp [1.6t – 3.795 + 1.774 ln(x) – 0.093 (ln(x)2]

(Eq. 5.16)

where x = travel distance of the compound in groundwater. t = normalized deviation from the median such that t = 0 is the median; t = ±1 is the lower and upper 67% confidence limits; t = ±2 is the 95% confidence level, etc.

Another expression for longitudinal dispersivity (ax) is ax = 0.32L0.83 where L is the scale of the plume length or a characteristic length assumed to be equal to 0.10 of the plume length (20 or 15 m, respectively) (Neumann and Zhang, 1990).

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Vertical dispersivity is defined as av = ax/160 (Gelhar et al., 1985). Vertical dispersivity values are commonly encountered in mathematical expressions used to describe the vertical extent that a chemical plume will extend in the saturated zone below the water table from a source in the unsaturated zone. An expression illustrating this technique is described as (Tetra Tech, Inc., 1993): Dp = (2avXa)1/2 + H[1 – exp(–XaI/HVsq)]

(Eq. 5.17)

where Dp av Xa H I Vs q

= = = = = = =

penetration depth. vertical dispersivity. length of the waste disposal site in the primary groundwater flow direction. aquifer thickness. infiltration rate. horizontal seepage velocity. porosity.

Transverse dispersivity controls the dispersion of the contaminant plume in groundwater in the horizontal direction perpendicular to the direction of flow. Transverse dispersivity (DT) is primarily controlled by the degree of aquifer heterogeneity and can be described as DT = aDL, where values for a range from about 0.05 to 0.5. In confirmation and reverse modeling, dispersivity is used as one variable to match the shape of the simulated contaminant plume to the observed plume at one point in time. Longitudinal dispersivity values used with solute transport models are commonly in the range of 90 to 300 ft, while horizontal dispersivity values can be as much as 150 ft. There is little physical evidence for using such large numbers except to simulate contaminant concentrations that compare favorably with observed values. In cases where no data exist to estimate dispersivities, the EPA recommends multiplying the length of the plume by 0.1 to estimate the horizontal dispersivity (Lallemand-Barres and Peaudecerf, 1978; Wilson, et al., 1981). Other authors have used probabilistic theory to estimate transverse and vertical dispersivity as 0.33 and 0.056 times the plume length, respectively (Gelhar and Axness, 1981, 1983; Gelhar et al., 1992; Salhotra et al., 1993; U.S. EPA, 1985). Dispersivity is also considered to be hysteretic with distance from the contaminant source. As a result, a simple linear expression for dispersivity introduces some degree of bias.

5.6.4 CONTAMINANT PROPERTIES Contaminant characteristics that impact the modeled transport of a contaminant include contaminant density, viscosity, retardation, and biodegradation. Of these variables, retardation has the greatest impact on contaminant velocity (see Table 1.20 in Chapter 1).

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Retardation values generally increase with increasing fractions of organic carbon, which increases with the clay content of the soil. If groundwater flow is 6 ft/day and a selected retardation coefficient for perchloroethylene (PCE) is 2, PCE is therefore transported at a rate of 3 ft/day. Published values for the retardation of PCE in sand and gravel aquifers are between 1 (no retardation) and 5 (Barber et al., 1988; Schwarzenbach et al., 1983). The retardation value for trichloroethylene (TCE) is reported as being less than 10 and usually between 1 and 2.5. Given the range in retardation values, these values can be adjusted to correspond to a prescribed time of release of TCE. In general, predicted retardation coefficients are generally two to five times lower than measured values (Ball and Roberts, 1991; Curtis, et al., 1986; MacKay, 1990; MacKay et al., 1986; Mehran et al., 1987). The retardation value of a selected chemical in groundwater is usually a fitted parameter. The selected retardation value can also be an artifact of well design and the purging and sampling processes employed (see Section 3.5 in Chapter 3). Apparent retardation rates in one study were found to be inconsistent between monitoring wells, depending upon the saturated screen length, the degree of screen desaturation during purging, and the distance from the contaminant source (Martin-Hayden and Robbins, 1997; Robbins 1989). The selection of one retardation factor for a compound for an entire well field may therefore be inappropriate in cases where concentration averaging is used (see Section 6.3, Chapter 6). These variables may result in a contaminant plume that appears to be attenuated to some degree being used for the modeling but which grossly under-represents the extent of the contaminant plume due to these monitoring well construction and sampling practices. An example is the apparent retardation factor that was modeled with variables including the distance from the contaminant source, screen length, and screen desaturation during purging. The results indicated that the apparent retardation factor increased with increasing screen length and degree of purging desaturation and decreased with the longitudinal distance from the contaminant source (Martin-Hayden and Robbins, 1997).

5.6.5 CHALLENGES TO REVERSE MODELS The successful review of a reverse model includes an analysis of model parameters and computer code. Examples of model parameters to be examined include: • • • • • • • •

Representativeness of the effective porosity value(s) selected Consistency of the groundwater flow direction over time Validity of the hydraulic conductivity and/or transmissivity values selected Validity of the selected hydraulic gradient values over time and distance from the release Value selected for aquifer thickness Assumptions used to determine when and where the contaminant entered the groundwater Horizontal and transverse dispersivity values Contaminant retardation and/or degradation rates

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FIGURE 5.5 MTBE release scenarios for its use as a tracer to determine the age of a release and for reverse model calibration. (Adapted from Davidson and Parsons, 1996.)

• Identification of the leading edge of the contaminant plume • Effect of recharge/discharge rates (if applicable) of water into the system and its impact on plume geometry and contaminant velocity

Since a reverse model requires an accurate value for the length of the contaminant plume, locating the origin of the release and leading edge of the contaminant plume is required. If the location of the contaminant release into the groundwater and/or the leading edge of the contaminant plume is unknown or approximated (e.g., within ±100 ft relative to a groundwater velocity of 25 ft/yr), significant variations in the estimated age of the release occurs. Uncertainty can also exist relative to where the contaminant entered the groundwater, especially if multiple or overlapping releases occur or if a chemical unique to a release is used as a tracer to date the release. An example is the case of a gasoline plume that is sampled between 4 and 10 years after a release occurred. MTBE is used as a tracer to date the plume for purposes of determining a representative groundwater velocity for use in the reverse model (see Figure 5.5). In the lower panel of Figure 5.5, MTBE is contained in a second release that overlies a pre-existing release of gasoline without MTBE. While MTBE provides a tracer for the second release, it does not provide information for identifying the date of the earlier, non-MTBE-containing gasoline release. An example of the impact of overlapping surface releases on reverse modeling is shown in Figure 5.6. If assumptions include a plume length of 600 ft, a groundwater velocity of 30 ft/yr, and a point source release, then 300 ft divided by 30 ft/yr yields a release date of 20 years ago. If the contaminant plume is the result of overlapping point source releases in 1970 and 1980, then the dividing the plume by contaminant velocity is invalid as illustrated in Figure 5.6. The measured distance to the leading edge of the contaminant plume is important in reverse modeling and often requires considerable judgment. Figure 5.7 illustrates several interpretations of the distance to the leading edge of a contaminant plume. In plume A, the concentration of 5.5 ppb in the downgradient monitoring well was selected as the leading edge. In plume B, the laboratory reported the presence of the ©2000 CRC Press LLC

FIGURE 5.6 Impact of multiple releases on reverse modeling.

contaminant (J flag) but was unable to report the concentration. An estimated value of 3 ppb was included on the laboratory sheet as a footnote. In plume C, the <5 ppb was selected as the leading edge of the plume. Whether A, B, or C is selected represents significant differences in plume length and therefore the maximum estimate for which contaminants have been in the groundwater.

FIGURE 5.7 TCE in monitoring wells down-gradient of a release. Three interpretations for defining the leading edge of a contaminant plume in groundwater.

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FIGURE 5.8 Potential impacts of monitoring well locations and screen intervals on determining the leading edge of a contaminant plume.

In addition, more subtle issues such as the spatial locations of the monitoring wells and the screen interval can introduce considerable variability in defining the leading edge of the contaminant plume (Figure 5.8). Numerous examples can be developed to illustrate these limitations, such as: • Adjust model-input parameters within a reasonable range for those parameters to produce a result consistent with measured values but inconsistent with the alleged released date. For example, the distribution of simulated head measurements depends to some degree on the ratio of the recharge rates to saturated hydraulic conductivity values, not on magnitude. Many recharge and hydraulic conductivity values are therefore possible to produce a ratio resulting in similar distributions of modeled heads. • Identify model uncertainties, such as groundwater direction and velocity, during time periods when these data are absent and query the author as to the level of confidence that these parameters are known during this time period. • Collect water level measurements coincident with an activity, such as a pumping well, that stresses the aquifer. Use the model to simulate this activity and compare the actual measurements with those predicted by the model.

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FIGURE 5.9 Groundwater models with different retardation values.

• Identify whether the water mass balance is conserved. A well-calibrated model will exhibit a small difference in the water balance and is often included as output to the model. • Evaluate model calibration via the preparation of scattergrams comparing values for measured heads with simulated heads for each well. If the calibration is perfect, both data sets will fall along a 45-degree line. the further that the data points are from this line, the greater the model deviation from actual flow conditions (Sklash et al., 1999). Plotting the residuals (the difference between the simulated and observed heads) can also provide insight into model calibration. • Compare the input parameters of the reverse model with other site models for consistency (e.g., remediation models, risk assessment models). It is not uncommon that hydraulic and chemical properties selected for a Risk-Based Corrective Action (RBCA) study or a model used to obtain site closure are different than those for the reverse modeling.

Groundwater velocity, for example, can be adjusted by varying the porosity value used for the sediments through which groundwater is flowing. A change in porosity from 30 to 20% results in an increase of groundwater velocity by one third. Another example is the effect of retardation on plume geometry. In Figure 5.9, the only parameter adjusted in the model is the retardation value (2.5 vs. 1.0). Selection of a retardation factor of 2.5 produces a plume that originated in 1950 while a value of 1.0 produces a contaminant plume originating in 1975. Both shapes are consistent with the contaminant plume geometry measured in 1996.

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In most cases, reverse modeling results provide the alleged time at which a contaminant entered the groundwater at a given location. In cases where groundwater is shallow or the contaminant is introduced into the groundwater via a dry well or cistern, this may be a reasonable assumption. In cases where the release occurred at the surface, the cumulative time required for the contaminant to flow through the surface pavement (if present) and soil prior to entering the groundwater must be considered.

5.6.6 CHALLENGES TO PHASE-SEPARATE REVERSE MODELS If a reverse or confirmation model is used to predict phase-separate migration, a different set of governing equations and additional parameters are needed than for a dissolved species in groundwater. For a light, non-aqueous phase liquid (LNAPL) transport along the water table, its movement can be described by the following (Parker and Lenhard, 1990): Qo = –To—Zao

(Eq. 5.18)

where Qo is the vertically integrated Darcian velocity, To is the light, non-aqueous phase liquid, and Zao is the height at which the water and LNAPL capillary pressures are equal, which corresponds to the LNAPL/air interface. The transmissivity of the LNAPL is then described by: Zu

To = Ú r ro k ro K h / hro dZ y Zo

(Eq. 5.19)

where Zu is the uppermost elevation at which mobile LNAPL occurs, Z yo is the elevation where the water and LNAPL pressures are equal, rro is the specific gravity of the LNAPL, kro is the relative permeability of the NAPL, Kh is the horizontal saturated hydraulic conductivity relative to water, and hro is the LNAPL-to-water viscosity ratio. The pore velocity of the leading edge of the LNAPL at the water table (vn) is then defined as: vn = Qo / VLNAPL

(Eq. 5.20)

where VLNAPL is the mobile LNAPL volume per unit area. A key variable for a reverse or confirmation model for a light, non-aqueous phase liquid is the representativeness of the three-phase (air, water, NAPL) expression that describes the pressure distributions between these fluids for a particular soil texture (Gardner, 1960; Parker and Lenhard, 1990). If this expression is reduced to a monotonic nonlinear relationship, the legitimacy of this non-hysteretic expression requires scrutiny. Challenges to phase-separate confirmation and reverse models include the representativeness of values selected for fluid viscosity, interfacial tension, and soil texture used to describe the interaction between the three liquid phases. Fluid

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viscosity and density measurements are rarely measured and more commonly are published values. As a result, published values used in the model can deviate from field density measurements due to weathering and/or co-mingling of the LNAPL with other compounds.

REFERENCES Ball, W. and P. Roberts, 1991. Long-term sorption of halogenated organic chemicals by aquifer material. 1. Equilibrium, Environmental Science and Technology, 24:1223– 1236. Barcelona, M. and R. Morrison, 1988. Sample collection, handling and storage: water, soils and aquifer solids, in Proc. of a 1988 National Workshop on Methods for Ground Water Quality Studies, Agricultural Research Division, University of Nebraska at Lincoln, pp. 49–62. Barber, L., Thurman, M., Schroder, M., and D. LeBlanc, 1988. Long-term fate of organic micropollutants in sewage contaminated groundwater, Environmental Science and Technology, 22:205–211 Bear, J., 1979. Hydraulics of Groundwater, McGraw-Hill, New York, p. 210. Bear, J., Beljin, M., and R. Ross, 1992. Fundamentals of Ground-Water Modeling: EPA Ground Water Issue, EPA/540/S-92/005, Office of Research and Development, Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington, D.C., p. 11. Bisdom, E., Dekker, L., and J. Schoute, 1993. Water repellency of sieve fractions from sandy soils and relationships with organic materials and soil structure, Geoderma, 56:105– 118. Bois, T. and B. Luther, 1996. Groundwater and Soil Contamination: Technical Preparation and Litigation Management, John Wiley & Sons, Somerset, NJ, pp. 135–144. Bouma, J., 1981. Soil morphology and preferential flow along macropores, Agricultural Water Management, 3:235–250. Carrier Corp. v. Detrex Corp., 1996. Superior Court of the State of California, County of Los Angeles, No. C703625. Cleary, R., 1995. Introduction to applied mathematical modeling in groundwater pollution and hydrology with IBM-PC applications, in Proc. of the NGWA IBM-PC Applications in Groundwater Pollution and Hydrology Conference, August 13–18, San Francisco, CA, p. 164. Cohen, R., Mercer, J., and J. Matthews, 1993. DNAPL Site Evaluation, CRC Press, Boca Raton, FL, p. 48. Crank, J., 1985. The Mathematics of Diffusion, 2nd ed., Oxford University Press, London, p. 21–67. Curtis, G., Roberts, P., and M. Reinhard, 1986. A natural gradient experiment on solute transport in a sand aquifer. 4. Sorption of organic solutes and its influence on mobility, Water Resources Research, 22, 2059–2067. Davidson, J. and R. Parsons, 1996. Remediating MTBE with current and emerging technologies, in Proc. of the 1996 Petroleum Hydrocarbons and Organic Chemicals in Ground Water: Prevention, Detection, and Remediation Conference, National Ground Water Association, November 13–15, Houston, TX, pp. 15–29.

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Diment, G. and K. Watson, 1985. Stability analysis of water movement in unsaturated porous materials: experimental studies, Water Resources Research, 21:979–984. Fishman, M., 1998. DNAPL infiltration and distribution in subsurface: 2D experiment and modeling approach, in Wickramanayake, G. and R. Hinchee (Eds.), Nonaqueous Phase Liquids: Remediation of Chlorinated and Recalcitrant Compounds, Battelle Press, Columbus, OH, p. 37–42. Freeze, R., and J. Cherry, 1979. Groundwater, Prentice-Hall, Englewood Cliffs, NJ, p. 604. Gardner, W., 1962. Approximate solution of a non-steady state drainage problems, Soil Science Society Proceedings of America, 25:129–132. Gelhar, L., and C. Axness, 1983. Three-dimensional stochastic analysis of macrodispersion in aquifers, Water Resources Research, 19(1):161–180. Gelhar, L. and C. Axness, 1981. Stochastic Analysis of Macro-Dispersion in Three Dimensionally Heterogeneous Aquifers, Report No. H-8, Hydraulic Research Program, New Mexico Institute of Mining and Technology, Soccorro, p. 140. Gelhar, L., Welty, C., and K. Rehfeldt, 1992. A critical review of data on field-scale dispersion in aquifers, Water Resources Research, 28(7):1955–1974. Ghadiri, H. and C. Rose, 1992. Modeling Chemical Transport in Soils Natural and Applied Contaminants, Lewis Publishers, Chelsea, MI, p. 217. Glass, R. and M. Nicholl, 1996. Physics of gravity fingering of immiscible fluids within porous media: an overview of current understanding and selected complicating factors, Geoderma, 70:133–163. Hartman, B., 1999. Which Compound Requires More Attorneys: MTBE or Benzene?, LUSTline Bull. No. 31, New England Interstate Water Pollution Control Commission, Wilmington, MA, pp. 15–17. Hartman, B., 1997. Applications and interpretation of soil vapor data to chlorinated solvent contamination, in Legal and Technical Considerations of Chlorinated Solvent Contamination, Argent Communications, Foresthill, CA, pp. 81–110. Hill, D. and J. Parlange, 1972. Wetting front instability in layered soils, Soil Science Society of America Proc., 36:697–702. Hughes Aircraft Company v. Brian Eustace Beagley et al., 1995. Superior Court of the State of California, Los Angeles County, Case No. BC062120. Hughes Aircraft Company v. Hartford Accident & Indemnity Company, 1994. Superior Court of the State of California, Los Angeles County, Case No. 92-6031-LGB (JRx). Imhoff, P., Thyrum, G., and C. Miller, 1996. Dissolution fingering during the solubilization of nonaqueous phase liquids in saturated porous media. 2. Experimental observations, Water Resources Research, 32(7):1929–1942. Jarvis, N., 1998. Modeling the impact of preferential flow on nonpoint source pollution, in Selim, H. and L. Ma (Eds.), Physical Nonequilibrium in Soils: Modeling and Application, Ann Arbor Press, Chelsea, MI, p. 492. Kung, J., 1990a. Preferential flow in a sandy vadose zone. 1. Field observation, Geoderma, 45:51–58. Kung, J., 1990b. Preferential flow in a sandy vadose zone. 2. Mechanism and implications, Geoderma, 46:59–71. Jury, W. and K. Roth, 1990. Transfer Functions and Solute Movement through Soil: Theory and Applications, Birkhauser-Verlag, Basel, p. 226. Jury, W. and G. Sposito, 1985. Field calibration and validation of solute transport models for the unsaturated zone, Soil Science Society of America Journal, 49:1331–1341. Jury, W., Sposito, G., and R. White, 1986. A transfer function model of solute transport through soil. 1. Fundamental concepts, Water Resources Research, 22:243–247.

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Kezsbom, A. and A. Goldman, 1991. The boundaries of groundwater modeling under the law: standards for excluding speculative expert testimony, Environmental Claims Journal, 4(1):5–30. Kornfeld, I., 1992. Comment to the boundaries of groundwater modeling under the law: standards for excluding speculative expert testimony, Tort and Insurance Law Journal, 28(1):59–67. Kosmatka, S. and W. Panarese, 1988. Design and Control of Concrete Mixtures, 13th ed., Portland Cement Association, Skokie, IL, p. 10. Lallemand-Barres, A. and P. Peaudecerf, 1978. Recherche de reltions entre les valeurs mesurees de la dispersivite macroscopique d’un milieu aquifere, ses autres caracteristiques et les conditions de mesure, etude bibliographique, Bull. Bur Rech. Geol. Min. (BRGM), Ser. 2, Sec. III, No. 4, pp. 277–284. Lohman, S., Bennett, R., Brown, R., Cooper, H., Drescher, W., Ferris, J., Johnson, A., McGuinness, C., Piper, A., Rorabaugh, M., Stallman, R., and C. Theis, 1972. Definitions of Selected Ground Water Terms: Revisions and Conceptual Refinements, U.S. Geology Survey, U.S. Government Printing Office, Washington, D.C., p. 14. Lyman, W., Reehl, W., and D. Rosenblatt, 1982. Handbook of Chemical Estimation Methods, McGraw-Hill, New York, p. 960. MacKay, D., 1990. Characterization of the distribution and behavior of contaminants in the subsurface, in Ground Water and Soil Contamination Remediation: Toward Compatible Science, Policy and Public Perception, report on a colloquium sponsored by the Water Science and Technology Board, National Academy Press, Washington, D.C., pp. 70–90. MacKay, D., Freyberg, D., Roberts, P., and J. Cherry, 1986. A natural gradient experiment on solute transport in a sand aquifer. 1. Approach and overview of plume movement, Water Resources Research, 22:2017–2029. Martin-Hayden, J. and G. Robbins, 1997. Plume distortion and apparent attenuation due to concentration averaging in monitoring wells, Ground Water, 35(2):339–347. McCoy, B. and D. Rolston, 1992. Convective transport of gases in moist porous media: effect of absorption, adsorption, and diffusion in soil aggregates, Environmental Science and Technology, 26(12):2468–2476. McDonald, M. and A. Harbaugh, 1988. A modular three-dimensional finite-difference groundwater flow model, in Techniques of Water Resources Investigations. 6. Modeling Techniques, U.S. Geological Survey, U.S. Government Printing Office, Washington, D.C., pp. 1.1–14.39. Mehran, M., Olsen, R., and B. Rector, 1987. Distribution coefficient of trichloroethylene in soil-water systems, Ground Water, 25:275–282. Mercer, J., 1991. Common mistakes in model applications, in Proc. of the American Society of Civil Engineers (ASCE) Symposium on Ground Water, July 29–August 1, Nashville, TN, p. 7. Miller, C., Gleyzer, S. and P. Imhoff, 1998. Numerical modeling of NAPL dissolution fingering in porous media, in Selim, H. and L. Ma (Eds.), Physical Nonequilibrium in Soils Modeling and Application, Ann Arbor Press, Chelsea, MI, p. 492. Millington, R., 1959. Gas diffusion in porous media, Science, 130:100–102. Millington, R. and J. Quirk, 1959. Permeability of porous media, Nature (London), 183:387– 388. Montgomery, J., 1991. Groundwater Chemicals Field Guide, Lewis Publishers, Chelsea, MI, p. 271. Morrison, R., 1999a. Critical review of reverse and confirmation models used to date a contaminant release, Environmental Claims Journal, in press.

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Morrison, R., 1999b. Reverse and confirmation models: applications and challenges, International Journal of Environmental Forensics, in press. Morrison, R., 1998. Estimating the timing of a contaminant release via transport modeling, Environmental Claims Journal, 10(2):75–90. Morrison, R. and R. Erickson, 1995. Groundwater investigations, in Morrison, R. and R. Erickson (Eds.), Environmental Reports and Remediation Plans: Forensic and Legal Review, John Wiley & Sons, Somerset, NJ, p. 155. Morrison, R. and B. Lowry, 1990. Sampling radius of a porous cup sampler: experimental results, Ground Water, 28(2):262–267. Morrison, R. and E. Newell, 1999. The cosolvation transport of DDT and xylene at a pesticide formulation facility, Journal of Soil Contamination, 8(1):63–80. Neumann, S. and Y. Zang, 1990. A quasi-linear theory of non-Fickian and Fickian subsurface dispersion. 1. Theoretical analysis with application to isotropic media, Water Resources Research, 26(5):887–902. Norton, P. and D. Pletta, 1931. The permeability of gravel concrete, Journal of the American Concrete Institute, 27:1093–1132. Odermatt, S., Johnson, T., and R. Hummeldorf, 1993. Distribution of DDT residues (DDT, DDD, and DDE) in California sediments, Journal of Soil Contamination, 2(4):315–329. Pankow, J. and J. Cherry, 1996. Dense Chlorinated Solvents and Other DNAPLs in Groundwater, Waterloo Press, Portland OR, p. 522. Parker, B. and J. Cherry, 1995. Age-dating DNAPL source zones from diffusion profiles in lowpermeability layers, in Innovative Characterization of DNAPL Impacted Aquifers, Geological Society of America Annual Meeting, November 6–9, New Orleans, LA, p. A-403. Parker, J., 1989. Multiphase flow and transport in porous media, Water Resources Research, 2:2187–2196. Parker, J. and R. Lenhard, 1990. Vertical integration of three phase flow equations for analysis of light hydrocarbon plume movement, Transport in Porous Media, 5:618–624. Philip, J., 1975. The growth of disturbances in unstable infiltration flows, Soil Science Society of America Proc., 39:1049–1053. Richards, L., 1931. Capillary conduction of liquids in porous media, Physics, 1:318–333. Ritsema, C. and L. Dekker, 1995. Distribution flow, a general process in the top layer of water repellent soils, Water Resources Research, 31:1187–1200. Robbins, G., 1989. Influence of using purged and partially penetrating monitoring wells on contaminant detection, mapping and modeling, Ground Water, 27(1):155–162. Rong, Y., Want, R., and R. Chou, 1988. Monte Carlo simulation for a groundwater mixing model in soil remediation of tetrachloroethylene, Journal of Soil Contamination, 7(1):87102. Salhotra, A., Mineart, P., Hansen, S., and T. Allison, 1993. Multimed, the Multimedia Exposure Assessment Model for Evaluating the Land Disposal of Wastes: Model Theory, EPA 600/R-93/081, U.S. Environmental Protection Agency, Washington, D.C., p. 122. Schwarzenbach, R., Giger, P., Hoehn, W., and J. Schneider, 1983. Behavior of organic compounds during infiltration of river water to groundwater: field studies, Environmental Science and Technology, 17:472–479. Selima, H. and L. Ma, 1998. Physical Nonequilibrium in Soils Modeling and Application, Ann Arbor Press, Chelsea, MI, p. 492. Sterling v. Velsicol Chemical Corp., 1988. 855 F.2d 1188, 1199 (6th Circuit). Streile, G., 1984. The Effect of Temperature on Pesticide Phase Partitioning, Transport and Volatilization from soil, Ph.D. dissertation, Department of Soil Science, University of California, Riverside, pp. 15–100.

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Szecsody, J., 1992. Solute transport processes in groundwater systems, in Subsurface Investigation and Remediation for Sites Contaminated with Hazardous Wastes, Department of Engineering and Engineering Professional Development, University of Wisconsin, Madison, p. 44. Tetra Tech, Inc., 1993. ROAM Version 1.0 Remedial Options Assessment Model, TR-103202, Electric Power Research Institute, Land and Water Quality Studies Program, Environment Division, Research Project 2485-02. U.S. EPA, 1985. Water Quality Assessment: A Screening Procedure for Toxic and Conventional Pollutants in Surface and Ground Water, Parts I and II, rev. ed., EPA/600/6-85002a (Part I, 609 pp.), EPA/600/6-85/002b (Part II, 444 pp.), U.S. Environmental Protection Agency, Environmental Research Laboratory, Athens, GA. Van der Heijde, P., 1984. Availability and applicability of numerical models for ground water resources management, in Proc. of the National Water Well Association Conference on Practical Applications of Ground Water Models, Battelle Press, Columbus, OH, pp. 3– 18. Van Genuchten, M. and W. Alves, 1982. Analytical Solutions of the One-Dimensional Convective-Dispersive Solute Transport Equation, Tech. Bull. No. 1661, U.S. Department of Agriculture, Washington, D.C., p. 151. Villholth, K., 1999. Colloid characterization and colloidal phase partitioning of polycyclic aromatic hydrocarbons in two creosote-contaminated aquifers in Denmark, Environmental Science and Technology, 33(5):691–699. Wei, C. and P. Ortoleva, 1990. Reaction front fingering in carbonate-cemented sandstones, Earth Sciences Review, 29:183–198. White, R., 1985. The influence of macropores on the transport of dissolved and suspended matter through soil, Advances in Soil Science, 3:95–113. Whiting, D. and A. Walitt, 1988. Permeability of Concrete, ACI SP-108, American Concrete Institute, Chicago, IL. Wilson, J., Enfield, T., Dunlop, W., Cosby, R., Foster, D., and L. Baskin, 1981. Transport and fate of selected organic pollutants in a sandy soil, Journal of Environmental Quality, 10:501–506. Zeng, C., 1994. Analysis of particle tracking errors associated with spatial discretization, Ground Water, 32(5):821–828. Zeng, C., 1993. Extension of the method of characteristics for simulation of solute transport in three dimensions, Ground Water, 31(3):456–465. Zeng, C. and G. Bennett, 1995. Applied Contaminant Transport Modeling: Theory and Practice, Van Nostrand-Reinhold, New York, p. 440.

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Plate 5.1 Thin section of soil impregnated with resin showing a decayed root channel with the remains of the root in the middle of the root channel. The lighter colored soil around the root channel is due to the osmotic stripping of nutrients from the surrounding soil.

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Plate 5.2 A rubble-filled dry well providing a preferential transport pathway for contaminants.

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Plate 5.3

Examples of finger and macropore flow.

Plate 5.4 The impact of liquid transport via macropores in a mature soil in the U.K. Hydrated gypsum was ponded on the ground surface and drained into the underlying soil via macropores. The gypsum then dehydrated, leaving the macropore channels clearly visible. ©2000 CRC Press LLC

Plate 5.5 Example of confirmation modeling exhibit to estimate the date of a contaminant release.

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6

Forensic Review of Environmental Trial Exhibits

An accurate picture is worth a thousand words.

6.1 INTRODUCTION Environmental exhibits that are clear, accurate, and simple are a prerequisite for explaining the technical elements of an environmental case. Exhibits must also be factually and scientifically correct. Exhibit errors are unintentional due to transcription or preparation errors or intentional, as identified by a pattern of bias (Tufte, 1983, 1990, 1997). Intentional errors include: • • • • •

Exaggerated vertical or horizontal scales Selective data presentation Data contouring (manually and computer-generated) Color-coded data that obscure source areas Contaminant transport models based on biased data

When trial exhibits are exchanged, a concerted effort is required to validate their accuracy. Obtain the underlying information such as chemical results, especially in an electronic format, early in the discovery stage so that your expert witness and/or confidential consultant can quickly review the underlying data used to produce the trial exhibits. Determining that a trial exhibit is scientifically accurate benefits all parties.

6.2 EXAGGERATED VERTICAL AND HORIZONTAL SCALES Exhibit scales are often exaggerated, especially for geologic cross-sections and fence diagrams. When portraying a relatively small vertical scale, such as shallow soil

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contamination (<100 ft.), relative to a substantially larger horizontal scale (>1000 ft), exaggeration is a reasonable way to present the data. Conversely, the depiction of subsurface contamination is skewed by excessively increasing the vertical scale relative to the horizontal scale. When vertical or horizontal scale exaggeration occurs, it should be posted on the exhibit and described in the testimony so that the viewer is informed. Plate 6.1* depicts the concentration of trichloroethylene (TCE) in soil with a 1:1 and 1:10 vertical-to-horizontal scale (Morrison, 1998). The TCE distribution is represented as an iso-surface for the purpose of depicting the volume of contaminated soil. While the respective horizontal-to-vertical ratios are accurate in both versions, the perception regarding the extent of contamination is different. Exhibits relying on this technique are routinely employed in cases that address the reasonableness of remediation costs. When an exhibit prejudices the observers’ perspective, prepare a rebuttal exhibit with a 1:1 vertical-to-horizontal scale with the same data or decrease the three-dimensional area so that the exaggeration bias is reduced.

6.3 SELECTIVE DATA PRESENTATION It is the author’s experience that omission of selective data is common in environmental exhibits. Observed practices include: 1. Data omission 2. Use of averages or mean data (i.e., obtaining the average of quarterly data, moving averages, geometric means, time series presentations; using averaged values, averaged value with standard variation, mean plus confidence interval, measured value plus the percentage of relative standard deviation or coefficient of variation, etc.) which results in an underestimation of contaminant concentrations and plume geometry 3. Selection and presentation of the higher or lower value from split samples 4. Creation of multi-chemical composite contour maps (i.e., combining all solvent measurements and reporting them as total volatile organic compounds [VOCs] rather than for each compounds) to mask source identification 5. Arbitrary elimination of anomalous data 6. Data presentation generated from imprecise or non-specific analytical methods 7. Data filtering to reduce or eliminate reported measurements 8. Aerial photo cropping 9. Arbitrary revisions to the original data

There is usually client reluctance to spend the money required for exhibit validation, especially when large data sets are used. For large invalidated data sets (>1000 data entries), a 5 to 15% transcription error between laboratory data and the computer spreadsheets is common. If the data entered onto the spreadsheet are double entered or cross-checked, this error is significantly reduced. * Plate 6.1 appears at the end of the chapter.

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Validating a large data set (e.g., ≥100,000 entries) when the exhibit is based on 500 data points is unproductive. Identification of transcription errors is cost effectively performed by validating only those locations and compounds used in key exhibits. This strategy requires that the underlying chemical data sheets are quickly accessible once the exhibits are exchanged. Once the data used to create an exhibit is validated, it is used with the identical modeling and/or visualization software to determine if the trial exhibit is reproducible. If the animation software is proprietary, additional cost and time can result in purchasing or licensing the software from the company. In addition, the software may require unique hardware as well as a person fluent with the software. These hardware, software, and personnel issues should be resolved in advance of receiving the exhibits. Confirmation of the validity of data used to generate an exhibit may not be straightforward. Consider 100 split soil samples collected and tested for trichloroethylene. Is it more appropriate to use the lowest, highest, or average of the two values in the exhibit or to plot all three? If a trial exhibit relies on averaged values in some instances and alternates between high and low values for others, determine if a pattern of intentional data bias exists. A consistent method should be used and the rationale for the selection clearly stated on the exhibit and/or testimony. Exhibits that rely upon the geometric mean of a data set are often encountered, as water quality results are generally distributed geometrically in time and space. The geometric mean is obtained by taking the log of multiple values, adding the log, and then taking the anti-log of the averaged log values. This technique tends to dampen the impact of data outliers or individual anomalous values that may be important in identifying contaminant sources. Similarly, other statistical averaging techniques that assume a normal distribution should be confirmed. Minimization of biases due to concentration averaging, geometric means, and mean values is accomplished by using the actual values for a point in time. This latter approach improves the validity of the data interpretation, transport modeling, and ultimately the effectiveness of the remediation design (Martin-Hayden and Robbins, 1997). The interpretation of non-detect (ND) results can skew the results of the data set used to create an exhibit. A sample reported as ND can be interpreted as 0, as the value of the method detection limit, or as a value of one half the detection limit or omitted in the data set. If the geometric mean of a data set is used, the central tendency of the geometric mean will be significantly different if non-detects are excluded vs. if values equal to one half the method detection limit are used. For time-series data using single or averaged data (e.g., 10 years of quarterly groundwater sampling data), graphing data from a single quarter or averaging values for several quarters can skew the viewer’s perception if the chosen quarter(s) are anomalous relative to historical trends. Combining 6 or 12 months of non-sequential groundwater data (e.g., annual, quarterly, and biannual sampling) for an aquifer with a high velocity (e.g., >1000 ft per year) onto one exhibit when monitoring wells are spaced less than 1000 ft apart results in an unrepresentative portrayal of contaminant distribution. Creating a rebuttal exhibit depicting seasonal or more consistent historical trends including anomalous sampling quarter data places the trial exhibit in a more balanced historical perspective.

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FIGURE 6.1 TCE concentrations from five groundwater monitoring wells collected by three consultants between 1991 and 1994.

If sample integrity is suspected due to sampling bias, especially for volatile compounds collected by multiple consultants, plotting the chemical results vs. time and labeling the tenure of the various consultants may identify whether this potential exists. Figure 6.1 illustrates trichloroethylene (TCE) concentrations in groundwater samples collected from multiple wells by three consultants between 1991 and 1994. In Figure 6.1, the TCE values for samples collected by Consultants A and B between 1991 and 1993 are smaller than the TCE concentrations from samples collected by Consultant C. The higher TCE concentration collected by Consultant C may indicate the use of different sampling equipment or procedures. Valid reasons exist for eliminating anomalous (e.g., outlier) values from a data set used to create an exhibit; however, the presence of anomalous data may be the only indication that the data are skewed and hence may be one of the most important data points in the population. If data are omitted, the rationale should be prominently posted on the exhibit. An example of omitted data is the presentation of changes in groundwater flow direction via rose diagrams. Figure 6.2 depicts the frequency of the groundwater flow direction from quarterly monitoring reports. The purpose of Figure 6.2 is to demonstrate that a contaminant plume in groundwater is captured with a groundwater extraction system located downgradient of the source. The groundwater extraction system was designed to capture the contaminant plume when the groundwater flow direction is west to southwest (Figure 6.2A). Groundwater flow to the north results in the transport of contaminated groundwater beyond the capture zone of the extraction system. Figure 6.2A shows nine quarters of groundwater flow that is predominately to the west to southwest. Figure 6.2B is a rebuttal exhibit depicting all 13 quarters with the direction of flow alternating between the southwest and northeast. Figure 6.2A does not contain reference to the omitted data.

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FIGURE 6.2 Rose diagrams showing historical groundwater flow directions. (From Morrison, R., in Environmental Claims Journal, 11(1), 93–107, 1998. With permission.)

While omission of anomalous data adverse to one’s position is usually obvious, subtle permutations are also encountered. An example is a chemical or geologic cross-section. A cross-section is a slice through the subsurface with information intersected by the slice displayed two or three dimensionally. A common crosssection manipulation is the inclusion or omission of data points not intersected on the cross-section. Figure 6.3(3a) depicts a plan view of a cross-section (A-A¢) that intersects total petroleum hydrocarbon (TPH)-impacted soil. Figure 6.3(3b), however, is the actual transect line reflecting the sampling points from which soil chemistry was used in the cross-section. In the case of the transect A-A¢ in Figure 6.3(3b), data along the transect that were not used included locations S-EX7 and S43-PL. Sampling locations within 5 ft of the A-A¢ transect from locations S1-EX3 and S9-EX5 (see 3a) were also omitted. Sample locations located 30 ft to the east (S55-PL, S9-7-PL), however, were projected onto the A-A¢ transect in 3a and incorporated into the accompanying cross-section. Another example of data omission is the exclusion of non-CLP (Contract Laboratory Program) data. Contract Laboratory Program data are the documentation required for sample testing associated with the Comprehensive Emergency Cost Recovery Act (CERCLA) or Superfund and Resource Conservation and Recovery Act (RCRA) investigations. The primary components of this program include field and/or trip blanks, field duplicate sample results, and internal laboratory quality control results (e.g., matrix spikes, matrix spike duplicates, and laboratory method blanks). Historical CLP and non-CLP (e.g., Phase I or II investigations) may not be available. If non-CLP data are excluded in an exhibit, plot the CLP and non-CLP data and compare the results. If one component of the CLP documentation is unavailable or has been violated (e.g., broken travel or field blank bottles) and is included in the exhibit, create the same graph or figure with and without the suspected data.

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FIGURE 6.3 Plan view of cross-section transects A-A¢. (From Morrison, R., in Environmental Claims Journal, 11(1), 93–107, 1998. With permission.)

Another data omission example is the case of split samples from one laboratory using CLP procedures and a second data set with non-CLP documentation. Plot the split CLP and non-CLP sample data collectively and individually to determine if significant differences in interpretation occur. If the non-CLP data are significantly dissimilar, the non-CLP data can be used for a different purpose (e.g., qualitatively vs. quantitative) or weighed differently. For example, the CLP data may be used for risk assessment purposes or to provide a quantitative measure of the volume of soil exceeding a clean-up concentration. The combined CLP and non-CLP data can be used to establish the boundaries of the contamination. Determining the reasonableness of an analytical method relied upon to create an exhibit may be required. In Plate 6.2,* 24 soil samples from a soil excavation are split into three discrete samples, with each sample forwarded to an analytical laboratory and tested for total petroleum hydrocarbons as gasoline. When each data set is contoured, different contaminant source areas as well as volumes above a remediation concentration of 100 mg/kg occur. A plan view of the contours from the Method 3 data depicts three source areas, while Method 1 and 2 data indicate two source areas. The exhibit relying on the Method 3 data or an average of the three data sets will result in significantly different interpretations of the distribution of the TPH in the soil. The data set selected for the exhibit influences the interpretation regarding the location of TPH contamination. The solution is to perform an analysis of the representativeness or accuracy of each analytical method to determine which data set is most representative. In Plate 6.2, Method 1 introduced false positive readings, while the methanol extract used in Method 2 was less effective in contaminant removal than * Plate 6.2 appears at the end of the chapter.

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FIGURE 6.4 Excavation cross-section using EPA Methods 418.1 and 8015.

Method 3. For this soil type and contaminant, Method 3 is the most representative data set. A variation of the Plate 6.2 example is reliance on a testing technique such as EPA Standard Method 418.1 to detect total petroleum hydrocarbons (TPHs) in soil samples used to guide the excavation of hydrocarbon-impacted soil. EPA Method 418.1 is a non-chromatographic technique and detects the presence of biogenic compounds in the soil (i.e., peat, pine needles, organic matter) resulting in falsepositive measurements (George, 1992; Zemo et al., 1995). The author has observed cases when EPA Method 418.1 is used to define where to excavate, until the excavation is inhibited by the presence of a building or road. The consultant then changes to an analytical method that does not introduce a false bias (i.e., EPA Method 8015). Testing using EPA Method 8015 results in non-detect sample measurements and becomes the basis for halting the excavation. Whether the original excavation using EPA Method 418.1 was warranted becomes not only a source of contention but also affects the reliability of an exhibit combining test results using EPA Methods 418.1 and 8015. Figure 6.4 is a cross-section of a soil excavation where soil samples were tested for TPHs using EPA Standard Methods 418.1 and 8015. Soil samples collected within the interior of the excavation were tested via EPA Method 418.1, while EPA Method 8015 was selected for confirmation soil sampling along the excavation perimeter. The potential implications of this observation are that over-excavation probably occurred and that the consultant may have intentionally relied upon the false-positive bias results inherent with EPA Method 418.1 to excavate non-petroleum-contaminated soil as a means to generate income. EPA Method 8015 was then used to halt the excavation, in this case when its proximity to subsurface piping presented significant complications to continued excavation. Once the excavated soil

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FIGURE 6.5 Plan view of soil excavation and selective use of EPA Standard Methods 418.1 and 8015.

is remediated or co-mingled with other petroleum-impacted soil, it becomes problematic whether subsequent test results of these excavated soils can determine if the original EPA Method 418.1 results were valid. Figure 6.5 depicts a plan view of excavated gasoline-contaminated soil. The organic-rich subsurface soils provided consistent false-positive measurements when using EPA Standard Method 418.1. Once the excavation proceeded close to a cooling tower and manufacturing building, the consultant switched to soil analysis using EPA Standard Method 8015 which resulted in non-detect sample results. Excavation near the surface structures then ceased. The distribution of analytical methods used for soil analysis relative to the above-ground structures in Figure 6.6 suggests an intent to create non-detect boundaries in areas in which extensive shoring was required. It may be warranted to retain an analytical chemist to reconstruct the validity of the test method(s) used to direct a soil excavation. The chemist can identify data believed to be unreliable which should be omitted from an exhibit. Conversely, if no quality assurance analysis is performed, both parties may erroneously assume that the detection of a particular compound is correctly identified. It is the author’s experience that in the case of gas chromatography/mass spectrophotometry (GC/MS), it is not unusual to find that 5 to 10% of the compounds are misidentified, especially if the interpretations are not manually examined.

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Data filtering is the revision or omission of data based on identification of the removed data as anomalous and/or non-representative. An example is the detection of 20 parts per billion (ppb) of TCE in a rinsate sample collected from a groundwater bailer. The bailer is subsequently used to collect a groundwater sample that results in a reading of 24 ppb. The data (24 ppb) are omitted from the data set based on a concentration of 4 ppb (lower than the maximum contaminant level of 5 ppb) via subtracting the equipment blank value from the measured groundwater sample. Another example of data filtering is assigning a new detection limit at five times the contamination level detected in the rinsate sample. The new detection limit is therefore 5 ¥ 20 = 100 ppb. The detection of 24 ppb in the groundwater sample is now regarded as non-detect, as are trichloroethylene concentrations up to 100 ppb. This method results in significant data omissions. Data filtering may be represented as justified through re-sampling. For example, monitoring wells may be re-sampled immediately after contamination is detected or re-sampled several times until contamination is not detected. The non-detect sample is then reported in the quarterly groundwater monitoring report and relied upon for the trial exhibit. Another technique is repeated groundwater sampling at the same location using a cone penetrometer test (CPT) rig or less quantitative technology (soil gas), with the re-sampling occurring days, months, or years after the original results to confirm the use of the non-detection measurements shown on a trial exhibit. For data sets where measurements are omitted, the major difficulty often lies in identifying the omissions. For large data sets (>1000 entries), omissions may not be apparent without a thorough review. Another difficulty is the testing of split samples by multiple samples, with only those sample results supportive of a particular position being reported. One technique for identifying data omissions is to aggressively pursue any electronic databases kept by the consulting firm or facility operator. Another option is to subpoena the original laboratory sheets and create a separate database. Aerial photo cropping is a technique that can remove undesirable information. Figure 6.6 shows two versions of an aerial photo of a tank farm in 1925 — uncropped and cropped; the cropped version deletes a tank under construction in the upper left corner. Be aware that when a person selects an aerial photo from a repository or dealer, the portion that is selected for the hard copy is usually a subset of the original, usually due to the scale of the parent aerial photograph. When ordering aerial photography, a number of scales and coverage dates are available. It is the author’s experience that all of the coverage dates are rarely ordered. This can result in the omission of aerial photo information if the opposing side obtains copies during discovery and relies on these rather than independently obtaining their own aerial photographs. When forensically evaluating a trial exhibit, examine all the underlying foundational information, especially field and laboratory notes. Figure 6.7 depicts a field and final soil-boring log contained in an environmental report. The field log depicts a 3-ft zone of contamination, while the final log contained in the environmental report shows a contaminant zone that is 7 ft thick. The final boring log was used with other boring logs to estimate the volume of contamination and associated remediation

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FIGURE 6.6 Uncropped (top) and cropped (bottom) aerial photograph.

costs. While the difference between the field and final boring log is small (ª4 feet), this difference extrapolated over a large area results in substantial differences in contaminant distribution and associated remediation costs.

6.4 DATA CONTOURING Data contouring (manual or computer-generated) is the interpolation of numbers of equal value in space (i.e., connecting the dots). Contouring provides useful visual

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FIGURE 6.7 Field and final soil boring logs. (From Morrison, R., in Environmental Claims Journal, 11(1), 93–107, 1998. With permission.)

displays showing regions of elevated concentrations. Contouring can identify contaminant source areas and is useful for designing remedial programs. Whether two or three dimensional, contouring forms the foundation for most environmental exhibits depicting chemical/spatial information (Joseph, 1996). Contour reliability is a function of the following items: • • • •

Data density Mathematical contouring method Nature of the contaminant (a pure phase liquid vs. a dissolved phase contaminant) Site-specific geologic environment that controls contaminant movement (movement in fractured bedrock vs. in a uniform fine sand)

The last item is important, as geologic environments may be encountered (e.g., a highly heterogeneous aquifer) for which contouring of a dissolved contaminant may be misrepresented by concentration contouring. In cases such as groundwater elevations and LNAPL thickness on groundwater, however, contouring may be more appropriate in the same setting.

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6.4.1 MANUAL CONTOURING Manual contouring relies upon the judgment of the author to connect the dots. Whenever a manually generated contour map is offered into evidence, plot the data to confirm that the contouring has honored the data. Plate 6.3* is an example showing the distribution of trichloroethylene in soil gas. The manually generated contour map and shading in Plate 6.3a suggest a single trichloroethylene source bounded within the 1000-ppb contour line. Plate 6.3b is a computer-generated contour map of the same data. By comparing the two maps, differences in the interpretation of the same data arise as to potential contaminant source areas. Plate 6.3a suggests a single contaminant source, while Plate 6.3b indicates multiple sources. Another mapping technique is shown in Plate 6.3c, where the size and color of the symbol are log scaled as a function of trichloroethylene concentration. Plate 6.3c is a useful presentation technique to examine data for source identification and eliminates biases associated with contouring. When these data are overlain with other features such as a sewer piping map (Plate 6.3d), a causal relationship between the presence of the TCE in soil gas and possible releases from the sewer piping becomes apparent. When examining an exhibit using color and size-ramped dots as a function of concentration, determine whether the method used to size ramp the concentrations is consistent or whether it is manually adjusted to bias the viewer’s perception. Plate 6.4* depicts average benzene concentrations in soil. No information is available to ascertain how the size ramping of the benzene concentrations was selected (e.g., linear or logarithmic methods).

6.4.2 COMPUTER CONTOURING Computer-generated contour maps are generated by connecting data points using mathematical equations known as algorithms. The proper algorithm selection and data density exert a profound impact on the contouring. Abrupt shapes or anomalous features are often symptomatic of improper algorithm selection. Peculiar contouring shapes occur in areas with little data. A tendency to draw closed contours or “bull’s eyes” around individual data points rather than enclosing a series of high values within a single contour can occur in areas with few data points. In general, the smaller the data density and smaller the contour interval, the greater the probability of computer artifacts. Figure 6.8 contains examples where a computer program has generated erratic contours in areas where the data are absent or scarce. Areas framed in A, C, and D are patterns where no data are available, while B is a contour which is extended in a direction which is similarly lacking data. Contours in the upper middle of Figure 6.8 reflect a sufficient data density so that the biases observed in frames A through D are not generated. Examine the contours relative to individual data points. If closed contours are offset from discrete data points, the contour and site map may be improperly scaled. The framed contours in Figure 6.9 illustrate these types of features. The closed * Plates 6.3 and 6.4 appear at the end of the chapter.

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FIGURE 6.8 Examples of computer-generated contour biases.

contours in the upper and lower right-hand quadrant are similar to the framed regions in A through D on Figure 6.8. A means to emphasize or minimize environmental data in a computer-generated contour map is to adjust the contour intervals. The selection of a large contour interval can mask a source of contamination, while a smaller contour interval tends to emphasize potential source areas (Erickson and Morrison, 1995).

FIGURE 6.9 Example of contouring errors and scales between data point coordinates and a base map.

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FIGURE 6.10 Adjustment of data contour interval for source identification.

Figure 6.10 depicts two-dimensional contour maps for trichloroethylene concentrations in groundwater where identical data sets were used. For the map with a trichloroethylene contour interval of 500 ppb, the data are not posted, which does not allow for confirmation that all of the data were used to generate the contours. The 100-ppb contour map depicts multiple potential sources obscured on the 500-ppb map due to the contour interval selection. The 100-ppb contour map also contains posted data, thereby allowing confirmation of the contouring. Common contouring methods used in constructing two- and three-dimensional contour maps and animations include inverse distance, kriging, minimum curvature, Sheppard’s method, and polynomial regression. Characteristics of each method are summarized below. 6.4.2.1 Inverse Distance Method The inverse distance method weights the influence of a single data point over all others. This influence declines as one proceeds farther from the value; the greater the weighting power, the faster the decrease in influence on the interpolation. One of the characteristics of inverse distance gridding is the generation of bull’s eyes surrounding data within a gridded area. 6.4.2.2 Kriging Kriging, or a form of kriging (i.e., indicator kriging), is a geostatistical method that assumes an underlying linear variogram and attempts to express trends suggested by a data set (Cressie, 1990; Delhomme, 1979; Journel et al., 1984; Olea, 1974). Kriging

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obtains estimates by assigning larger weights to nearby sample location measurements and smaller weights to those more distant. Kriging is considered more accurate than the inverse distance method except in areas that have fewer data points relative to other portions of the area being kriged. Because contouring data is usually limited, the results of kriging can be misleading; depending on the parameters used to define the semi-variogram, the same data can yield different results. Kriging honors data, although the estimated values at locations between sample sites is nonunique (Wingle and Poeter, 1993). While kriging can be a good procedure for interpolating between data points, it is usually an inappropriate procedure for extrapolation of data that are beyond the range of the sample locations. Comparisons between conventional least-squares methods and kriging estimators indicate that for samples of size less than about 50, kriging offers no clear advantages over a leastsquares method. Kriging may therefore be more useful for designing a network for collecting data points than for data analysis (Hughes et al., 1981). A variation of kriging is indicator kriging, which combines kriging with stochastic simulation. (Journel et al., 1994). Indicator kriging differs from simple or ordinary kriging in that a range of values is reduced to discrete values by defining threshold values. This arrangement allows the rapid examination of multiple interpretations that are distinctly different but which honor all of the original data and the nature of the model semi-variogram. The consultant can then evaluate the effects of different variations of the parameter being modeled; however, there is a difference between a mathematical solution that while probable is not realistic for the parameter values contoured using kriging. 6.4.2.3 Minimum Curvature Method This method calculates the initial value of the grid based on the data, then repeatedly smooths the gridded surface. For an identical data set, the minimum curvature method projects trends in areas of missing data, which results in a greater degree of variation than in the inverse distance method. Contouring software programs usually allow the degree of projection to be adjusted. 6.4.2.4 Sheppard’s Method Sheppard’s method is similar to the inverse distance method except that the leastsquares method has a tendency to eliminate the bull’s-eye contours frequently created with the inverse distance method (Franke and Nielson, 1980). 6.4.2.5 Polynomial Regression Polynomial regression is used to identify large-scale trends and data patterns. Many variations exist in the degrees of polynomial regression to examine data trends. In addition to selecting a contouring algorithm, an expert or confidential consultant can adjust the data prior to contouring. Such techniques include smoothing or lognormalizing the data. If the underlying data are manipulated prior to contouring, the scientific validity and impact of these changes on the contouring should be examined.

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FIGURE 6.11 Inverse distance, kriging, and minimum distance contours for identical data sets.

Different contouring algorithms can produce different contours for identical data sets, as shown in Figure 6.11. Contours on maps A through C are from the identical data set and contour interval. The contour on map D is an overlay of contours created by inverse distance and kriging. The differences between these two methods may visually appear minor; however, for large areas with limited data, contaminated volume calculations and hence cost and time required for in situ remediation can be dramatically impacted. While Figure 6.11 presents a two-dimensional example, identical issues exist with three-dimensional representations.

6.4.3 COLOR-CODED DATA Two and three-dimensional exhibits can be created that, while scientifically correct and based on a complete and validated data set, obscure key information. An example is selection of the contour interval. The contour maps in Plate 6.5* were prepared using identical data. In the color-shaded contour map in Plate 6.5, the * Plate 6.5 appears at the end of the chapter.

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contour interval selection is not constant. No information is provided regarding the concentration range greater than 1500 parts per billion (ppb); therefore, the viewer is unable to determine if the data in the shaded areas are closer to 1501 or 50,000 ppb. A means to re-examine these data forensically is to reproduce the contour map using a constant contour density (Plate 6.5). The source area absent in the colorshaded contour map becomes apparent when a consistent contour interval density (100 ppb) is selected. An identical forensic methodology can be employed when displaying hundreds or thousands of data points in a three-dimensional, computergenerated animation. Plate 6.6* is an example of two stills from an animation that relies upon a similar principle as Plate 6.5. A similar example is shown in the four colored panels in Plate 6.7*, where differences in the color range are used to mask potential contaminant source areas. When examining three-dimensional stills or animations using iso-surfaces, realize that the contouring programs employed to construct these surfaces default to a confidence and/or probability level used to create these surfaces. Plate 6.8* illustrates contaminant iso-surfaces with two different contouring confidence levels for an identical data set. The iso-surface in both panels is set to include all of the soil concentration data between non-detect and 150 ppb. The upper panel illustrates an iso-surface with a 95% confidence level, while the lower panel is set at a 50% confidence level. Tremendous latitude, therefore, exists for visually manipulating the perceived extent of the subsurface contamination via the selection of lower isosurface confidence levels, especially for small data sets and/or for instances where there are large distances between the data points. Contaminant transport simulations are frequently used as demonstrative evidence associated with contaminant fate and transport analysis. As such, the input data used in the model permit the author to fit the data to produce a prescribed result (see Chapter 5). The forensic evaluation of graphics depicting the results of contaminant transport modeling (stills or animations) includes examination of the following: • The accuracy and representativeness of the input data • Applicability of the visualization software • Selection of the simulation used for presentation (assuming multiple simulations were performed) • Exhibit scaling • Angle of inclination and rotation selected • For iso-surfaces, the statistical confidence level assigned to the iso-surface depicted in the exhibit • Whether the contaminant depicted is representative of other compounds of concern

Several of the tasks are identical to the technique used to evaluate other types of environmental exhibits. The selection of model boundary conditions, the applicability of the computer software relative to the site, data density, and the selection of a particular simulation, however, are unique to contaminant transport models. * Plates 6.6 through 6.8 appear at the end of the chapter.

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REFERENCES Cressie, N., 1990. The origin of kriging, Mathematical Geology, 22:239–252. Delhomme, J., 1979. Spatial variability and uncertainty in groundwater flow parameters: a geostatistical approach, Water Resources Research, 15(2):269–280. Franke, R. and G. Nielson, 1980. Smooth interpolation of large sets of scattered data, International Journal of Numerical Methods in Engineering, 17:1691–1704. George, S., 1992. Positive and negative bias associated with the use of EPA Method 418.1 for the determination of total petroleum hydrocarbons in soil, in Proc. of the 1992 Petroleum Hydrocarbon and Organic Chemicals in Ground Water: Prevention, Detection, and Restoration Conference, National Ground Water Association, Houston, TX, pp. 35–52. Hughes, J. and D. Lettenmaier, 1981. Data requirements for kriging: estimation and network design, Water Resources Research, 17(6):1641–1650. Joseph, G., 1996. Modern Visual Evidence, Law Journal Seminars Press, New York, p. 474 Journel, A. and E. Isaaks, 1984. Conditional indicator simulation: application to a Saskatchewan uranium deposit, Mathematical Geology, 16(7):685–718. Martin-Hayden, J. and G. Robbins, 1997. Plume distortion and apparent attenuation due to concentration averaging in monitoring wells, Ground Water, 35(2):339–347. Morrison, R., 1998. Forensic review of environmental trial exhibits, Environmental Claims Journal, 11(1):93–107. Morrison, R. and Erickson, R., 1995. Environmental Reports and Remediation Plans: Forensic and Legal Review, John Wiley & Sons, Somerset, NJ, p. 570. Olea, R., 1974. Optimal contour mapping using universal kriging, Journal of Geophysical Research, 79(5):695–702. Tufte, E., 1997. Visual Explanations: Images and Quantities, Evidence and Narrative, Graphic Press, Cheshire, CT, p. 157. Tufte, E., 1990. Envisioning Information, Graphic Press, Cheshire, CT, p. 126. Tufte, E., 1983. The Visual Display of Quantitative Information, Graphic Press, Cheshire, CT, p. 197. Wingle, W. and E. Poeter, 1993. Uncertainty associated with semivariograms used for site simulation, Ground Water, 31(5):725–734. Zemo, D., Bruya, J., and T. Graf, 1995. The application of petroleum hydrocarbon fingerprint characterization in site investigation and remediation, Ground Water Monitoring Review, Spring:147–156.

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Plate 6.1 Differences in perception due to exaggeration of the vertical scaling. (Adapted from C-Tech, Environmental Visualization Systems Software, Irvine, CA, 1998.)

Plate 6.2 Total petroleum hydrocarbon (TPH) results from split samples using different analytical and extraction methods and corresponding contour maps. ©2000 CRC Press LLC

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Plate 6.3

Contoured concentration of TCE in soil gas.

Plate 6.4 Color and size ramping of circles to indicate benzene concentrations in groundwater.

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Plate 6.5 Two-dimensional contouring with color-coded data and different contour intervals.

Plate 6.6 Computer animations based on biased data. (Adapted from C-Tech, Environmental Visualization Systems Software, Irvine, CA, 1998.)

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Plate 6.7 Examples of differences in the color range being used to mask potential contaminent source sites.

Plate 6.8 Contaminant iso-surfaces with two different contouring confidence levels for an identical data set.

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Appendices

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Appendix A. Sample Calculation for the Transport of PCE Vapor through Concrete Pavement A.1 INTRODUCTION The basic approach is to consider the diffusion of a liquid through a medium bounded by two parallel plates with the planes at z = 0 and x = 1. After a time, a steady-state is reached in which the concentration remains constant at all locations in the pavement. The diffusion equation in one dimension, therefore, reduces to (Crank, 1985): d2C/dx2 = 0

(Eq. A.1)

provided that the diffusion coefficient (D) is constant. On integrating with respect to x, the following expression arises: dC/dx = constant

(Eq. A.2)

and by introducing the conditions at x = 0 and x = l and integrating, then: [C – C1/C2 – C1] = x/l

(Eq. A.3)

The previous two expressions show that the concentration changes linearly from C1 to C2 through the pavement. The transfer rate of the diffusing substance is the same across all sections of the membrane, as described by the following expression: F = –DdC/dx = D(C1 – C1)/l

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(Eq. A.4)

If the thickness (l) and the surface concentrations (C1 and C2) are known, then D can be deduced from an observed value of F using this equation. If the surface x = 0 is maintained at a constant concentration C1 and at x = 1, then there is evaporation into an atmosphere for which the equilibrium concentration immediately within the paved surface is C2, so that: ∂C/∂x + h(C – C2) = 0, x = l

(Eq. A.5)

(C – C1)/(C2 – C1) = (hx)/(1 + hl)

(Eq. A.6)

F = Dh(C1 – C2)/(1 + hl)

(Eq. A.7)

∂C/∂x + h1(C1 – C) = 0, x = 0; and ∂C/∂x + h2(C – C2) = 0, x = l

(Eq. A.8)

C = [h1C1{1 + h2(l – x)} + h2C2(1 + h1x)]/ [h1 + h2 + h1h2l]

(Eq. A.9)

then

and

If the surface conditions are

then

A.2 SAMPLE CALCULATION Given these relationships, the one-dimensional gas diffusion rate through a paved surface can be approximated using variations of the previous equations. In this example, it is assumed that a vapor cloud of PCE has accumulated within the concrete catch basin housing a vapor degreaser. The concrete is not cracked, nor are there expansion joints (i.e., it was poured in placed). The vapor cloud has been allowed to accumulate and collect within the concrete catch basin over a holiday during which the forced air system in the building is not operating. The question therefore, is can the PCE vapor move through the concrete over the 5-day holiday period and, if so, at what rate? To examine this question using the diffusion mathematics outlined in Crank (1985), a one-dimensional plane diffusion (gas or liquid) through a porous plate is assumed. The following parameters and values are assumed in this example: • Henry’s Law constant for PCE is 2.82 ¥ 10–2 atm m3/mol. • PCE is absent in the concrete and in the soil below it (C2 = Co = 0). • The concentration of PCE in the vapor above the concrete is 1.272 ¥ 10–4 g/cm3.

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FIGURE A.1 Conceptual model of the transport of PCE vapor through concrete.

A graphical representation of this problem is shown in Figure A.1. In this case, the following governing equation becomes: •

Q t / lC1 = Dt / l 2 – 1 / 6 – 2 / p 2 Â (–1) 2 / n 2 exp(– Dn 2 p 2 t / l 2 )

(Eq. A.10)

1

For a steady-state solution where time (t) goes to infinity, the flux rate is defined as Qt = DC1/l(t – l 2/6D)

(Eq. A.11)

which has an intercept L on the t-axis described as: L = l 2/6D

(Eq. A.12)

F( t ) = 2C 1 Â (D / pt )1 / 2 exp{–(2 m + 1) 2 l 2 /( 4 D)}

(Eq. A.13)

For a small period of time, then: •

M =1

For a small period of time, this series converges rapidly to: ln (t1/2F) = ln {2C1(D/p)1/2} – L2/4Dt

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(Eq. A.14)

and t1/2F = exp [ln {2C1(D/p)1/2} – L2/4Dt]

(Eq. A.15)

F = t–1/2 exp [ln {2C1(D/p)1/2} – L2/4Dt]

(Eq. A.16)

and

where D = the effective diffusion coefficient. The effective diffusion coefficient is defined as (Millington and Quirk, 1959): De = Do(A10/3)/PT2

(Eq. A.17)

Assuming that the volumetric air content of the concrete is 0.013 – 0.023, the total porosity is between 0.06 and 0.14, and the gas diffusion rate for PCE is 0.0785 cm2/ sec (for TCE ª 7100 cm2/day), then: De = (0.0785 cm2/sec)((0.013 – 0.023)3.33/(0.06 – 0.14)2)

(Eq. A.18)

= (0.078 cm2/sec)((2.67 ¥ 10–5) – (9.73 ¥ 10–4))

(Eq. A.19)

= (2.67 ¥ 10–6) – (7.64 ¥ 10–5) cm2/sec

(Eq. A.20)

Using this range of values, the flux rate through the concrete per unit area of surface areas at x = L is Time (sec) 10 102 103 104 105 106 107 108

(27 hr) (1.16 days) (11.6 days) (116 days) (1116 days)

Flux Rate (F) (cm/sec)

1.85 2.07 5.89 3.68 1.25

0 0 0 ¥ 10–41 ¥ 10–21 ¥ 10–10 ¥ 10–10 ¥ 10–10

Solving for the quantity of PCE vapor that has moved through the concrete (Q1) yields: Dt/L2 = (7.64 ¥ 10–5 cm2/sec)(t)/(15.2 cm)2

(Eq. A.21)

Q1/LC1 = 0.14 at 106 sec and 0.035 at 5 exp5 sec

(Eq. A.22)

and

and

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Q = (0.14)(15.2 sec)(1.274 ¥ 10–4 g/cm3) at 106 sec

(Eq. A.23)

so for a fast diffusion rate (FD1), Q = 2.71 ¥ 10–4, and 0.27% of the PCE vapor mass has diffused through the concrete in 106 sec (277 hours or 11.6 days); for a slow diffusion rate (FD2), Q = 1.15 ¥ 10–4, and about 0.19% of the PCE vapor mass has diffused through the concrete pavement in 3 ¥ 107 sec or 347 days, according to the following: FD1 = t–1/2 exp[–13.588 – 7.56 ¥ 105/t(sec)]

(Eq. A.24)

FD2 = t–1/2 exp[–15.39 – 2.75 ¥ 107/t(sec)]

(Eq. A.25)

and

Using the expression in Equation A.13 (Crank 1985), the numerical approximation of the time-dependent flux of PCE vapor through the 15.2 cm of concrete pavement where FD1 = 7.64 ¥ 10–5 cm2/sec and FD2 = 2.10 ¥ 10–6 cm2/sec is as follows: T (sec)

2¥ 4¥ 1.5 ¥ 2¥ 4¥ 2¥

a

103 104 104 104 105 105 105 105 106 106 107 108

T (hr/days) 0.278 hr 2.78 5.56 11.1 27.8 41 2.3 days 4.6 11.6 23 115 1157

FD1 (cm/sec) 0.00 1.85 ¥ 10–41 3.4 ¥ 10–25 3.89 ¥ 10–17 2.07 ¥ 10–12 2.11 ¥ 10–11 6.41 ¥ 10–11 3.0 ¥ 10–10 5.9 ¥ 10–10 6.1 ¥ 10–10 — —

Fa (g/day) 0.00 2.97 5.47 6.25 3.32 3.37 1.03 4.82 9.48 9.78 — —

¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥ ¥

10–34 10–18 10–10 10–5 10–4 10–3 10–3 10–3 10–3

FD2 (cm/sec) 0.00 0.00 0.00 0.00 0.00 0.00 8.92 4.54 2.36 1.56 4.19 1.57

¥ ¥ ¥ ¥ ¥ ¥

10–70 10–46 10–22 10–16 10–12 10–11

F (g/day) 0.00 0.00 0.00 0.00 0.00 0.00 1.43 7.31 3.79 2.51 6.73 2.53

¥ ¥ ¥ ¥ ¥ ¥

10–62 10–33 10–15 10–9 10–5 10–4

F cm/cm ¥ 1.61 ¥ 107 = F g/day.

In this sample problem, by day one about 3.3 ¥ 10–5 g have diffused through the concrete. Steady-state conditions are reached in both instances between about 6 and 212 days. Approximately 1 to 23 days are required before any mass starts to emanate through the 15.2 cm of concrete. The diffusion of PCE through the concrete ranges from about 2.1 ¥ 10–6 to 7.64 ¥ 10–5 cm2/sec. This range is due to the variability of the concrete porosity and the values of air porosity selected for this example.

REFERENCES Crank, J., 1985. The Mathematics of Diffusion, 2nd ed., Oxford University Press, New York, p. 345. Millington, J. and J. Quirk, 1959. Permeability of porous media, Nature (London), 183:387–388.

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Appendix B. Sample Calculation for the Transport of PCE Liquid through Concrete via Diffusion B.1 INTRODUCTION Liquid diffusion of a chlorinated solvent through a paved surface is an extremely slow process. The transport of a chlorinated solvent through concrete via liquid diffusion assumes that the paved surface is saturated and that the effective porosity of the pavement provides a continuous pathway for the solvent dissolution. These calculations assume an absence of cracks and expansion joints in the pavement that could provide a preferential pathway for liquid migration into the underlying soil.

B.2 SAMPLE CALCULATION An estimation of perchloroethylene (PCE) transport through a porous media such as concrete via liquid diffusion can be developed based on the mathematics provided in The Mathematics of Diffusion (Crank, 1985). The reader is encouraged to examine this treatise when developing a liquid diffusion model, as numerous mathematical constructs are available for various problem assumptions. In this example, the following conditions are assumed: • Length of the concrete is 15.2 cm. • The diffusion rate of PCE in water = 1.5 ¥ 10–5 cm2/sec (for TCE, the water diffusivity value ª 0.8304 cm2/day). • The diffusion of PCE (DL) = Doq(10/3)/P 2T. • Total concrete porosity is 0.06 to 0.14. • Volumetric content is equal to 0.02 to 0.04%.

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Given these assumptions, DL, then: DL = 1.65 ¥ 10–5 cm2/sec [(0.02 – 0.043.33)/(0.06 – 0.14)2

(Eq. B.1)

= 1.68 ¥ 10–8 to 1.6 ¥ 10–9cm2/sec

(Eq. B.2)

= 1.38 ¥ 10–3 to 1.38 ¥ 10–4 cm2/sec

(Eq. B.3)

Given that the flux rate (F) is defined as (see Appendix A for a more thorough derivation): F = t–1/2 exp[ln (2C1(D/p))1/2] – L2/4Dt

(Eq. B.4)

then the flux rates (Fcm/day) and mass (Fg/cm) for a diffusion rate of PCE in water of 1.65 ¥ 10–5 cm2/sec are Time (days)

Fcm/day

Fg/cm

0.1 1.0 10 102 2 ¥ 102 300 400 1000 2000 2500 2750 3000 4000 5000 6000 7000

0.0 0.0 0.0 0.0 2.61 ¥ 10–92 4.53 ¥ 10–62 5.73 ¥ 10–47 7.16 ¥ 10–20 6.35 ¥ 10–11 3.75 ¥ 10–9 1.64 ¥ 10–8 5.59 ¥ 10–8 1.59 ¥ 10–6 1.16 ¥ 10–5 4.2 ¥ 10–5 1.07 ¥ 10–4

0.0 0.0 0.0 0.0 6.21 ¥ 10–86 1.08 ¥ 10–56 1.36 ¥ 10–41 1.70 ¥ 10–14 1.51 ¥ 10–5 0.00089 0.0039 0.0133 0.378 2.75 10.10 25.50

In excess of about 2000 days or 5.4 years are required before any appreciable (1.51 ¥ 10–5 g/cm) quantity of perchloroethylene diffuses through the concrete. For a brief, transient spill of PCE on concrete, therefore, PCE transport via liquid diffusion through 15.2 cm of concrete is insignificant, especially when mechanisms such as evaporation are considered.

REFERENCES Crank, J., 1985. The Mathematics of Diffusion, 2nd ed., Oxford University Press, New York, p. 345.

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Appendix C. Properties of Alcohol Oxygenates and Ether Oxygenates

Properties of Alcohol Oxygenates Property Chemical name Chemical formula Flash point ∞F ∞C Heating value (Btu/gal) Latent heat of vaporization (Btu/gal) Boiling point (∞F) Composition (%wt) Carbon Hydrogen Oxygen Molecular weight Relative density (60∞F) Water solubility (70∞F) Fuel in water (%) Water in fuel (%) Viscosity (mm/sec) 68∞F –4∞F

MeOH

EtOH

IPA

BuOH

GTBA

Methanol CH3OH

Ethanol C2H5OH

Isopropyl alcohol (CH3)2 CHOH

n-Butanol C4H9OH

Gasoline grade t-butanol (CH3)3 COH

52 11 56,800 3340

55 13 76,000 2378

53 12 87,400 2100

84 29 96,800 1700

52 11 94,100 1700

149

173

180

244

176–181

37.49 12.58 49.93 32.04 0.7963 100 100 0.74 1.44

52.14 13.13 34.73 46.07 0.7939 100 100 1.50 3.58

59.96 13.42 26.62 60.09 0.7899 100 100 3.01 7.43

64.82 13.60 21.58 74.12 0.8137 100 100 3.54 —

65.0 13.7 21.3 73.5 0.7810 100 100 7.4 Solid

From Gibbs, L., in Proc. of the Southwest Focused Ground Water Conference: Discussing the Issue of MTBE and Perchlorate in Ground Water (suppl.), National Ground Water Association, Dublin, OH, 1998. With permission.

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Properties of Ether Oxygenates Property Chemical name Chemical formula Flash point ∞F ∞C Heating value (Btu/gal) Latent heat of vaporization (Btu/gal) Boiling point (∞F) Composition (%wt) Carbon Hydrogen Oxygen Molecular weight Relative density (60∞F) Water solubility (70∞F) Fuel in water (%) Water in fuel (%) Viscosity (mm/sec) 68∞F –4∞F

MTBE Methyl-tertiarybutyl-ether (CH3)3COCH3

TAME

THEME

Tertiary-amylTertiary-hexylmethyl-ether methyl-ether (CH3)2(C2H5) COCH3 (CH3)2(C3H7) COCH3

ETBE

TAEE

DIPE

Ethyl-tertiarybutyl-ether (CH3)3COC2H5

Tertiary-amylethyl-ether (CH3)2(C2H5)COC2H5

Diisopropyl ether (CH3)2CHOCH(CH3)2

–14 –26 93,500 863

11 –11 100,600 870

— — — —

–3 –19 97,000 830

— — — 816

9 –12 100,000 900

131

187

230

163

214

155

70.53 13.81 15.66 102.18 0.7758

72.35 13.88 13.77 116.2 0.7860

70.53 13.81 15.66 102.18 0.7452

72.35 13.88 13.77 116.2 0.7705

70.53 13.81 15.66 102.18 0.7289

1.2 0.5

0.4 0.2

68.13 13.72 18.15 88.15 0.7460 4.8 1.5 0.47 1.44

1.15 0.6 — —

— — — —

— —

— —

— — — —

From Gibbs, L., in Proc. of the Southwest Focused Ground Water Conference: Discussing the Issue of MTBE and Perchlorate in Ground Water (suppl.), National Ground Water Association, Dublin, OH, 1998. With permission.

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Appendix D. Advective and Partitioning Transport Equations of Radon for Detecting Diesel in Groundwater D.1 INTRODUCTION The basis of the advective and partitioning equations for radon (222Rn) as a means to detect diesel in groundwater is described in an article by Hunkeler et al. (1977) in Environmental Science and Technology. It is recommended that the reader interested in this method examine this source paper in addition to references used to solve the various solutions of Darcy’s Law (Freeze and Cherry, 1979; Wang and Anderson, 1982). The derivation of Darcy’s Law for advective transport with dispersion is presented here, along with the partitioning derivation reported by Hunkeler et al. for 222Rn. While this approach is specific to radon, it provides interesting possibilities for other types of contaminants.

D.2 DERIVATION A form of Darcy’s Law for three-dimensional flow through an isotropic media can be expressed as:

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qx = –k(∂f/∂x)

(Eq. D.1)

qy = –k(∂f/∂y)

(Eq. D.2)

qz = –k(∂f/∂z)

(Eq. D.3)

where qx, qy, qz = specific discharge vectors

(Eq. D.4)

x, y, z = Cartesian coordinate system

(Eq. D.5)

k = saturated hydraulic conductivity

(Eq. D.6)

The specific discharge vector with components qx, qy, qz can be expressed as qi, with the notation (i) representing x, y, or z, and the partial derivatives ∂f/∂x, ∂f/∂y, and ∂f/∂z representing the three components of the hydraulic gradient. The hydraulic gradient can then be written as: ∂if = [∂f/∂x), (∂f/∂y), (∂f/∂z)]

(Eq. D.7)

which can be compressed in tensor notation as: qi = –k∂if

(Eq. D.8)

In the general case for three-dimensional flow, Darcy’s Law provides three equations for motion for four unknown variables (qx, qy, qz, and f). The fourth equation (mass balance) is required for groundwater flow and reduces to the equation of continuity used to describe steady-state groundwater flow. This is expressed as: ∂qx/∂x + ∂qy/∂y + ∂qz/∂z = 0

(Eq. D.9)

By combining Darcy’s Law and the continuity equation together, the four equations for the four unknown quantities can be solved. Three of the equations are eliminated by substituting the derivative (–k∂if) for qi in the continuity equation, which yields: ∂/∂x [k∂f/∂x] + ∂/∂y [k∂f/∂y] + ∂/∂z [k∂f/∂z] = 0

(Eq. D.10)

If the saturated hydraulic conductivity (k) is treated as a constant, then Equation D.10 is reduced to (Laplace’s equation in three dimensions): [∂2f/∂x2] + [∂2f/∂y2] + [∂2f/∂z2] = 0

(Eq. D.11)

The technique, described by Hunkeler et al. (1997), included the use of Darcy’s equation in one dimension for solving for 222Rn in a non-aqueous phase liquid (NAPL)-contaminated aquifer. Assumptions included: • The average distribution of 226Ra, the parent nuclide of 222Rn, in the solid phase is homogeneous at a macroscopic scale. • Aquifer porosity is constant. • 222Rn loss from the saturated to the unsaturated zone is neglected. • Partitioning of 222Rn between the NAPL and water phase is in equilibrium.

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• The partition coefficient is independent of the NAPL saturation. • The NAPL is immobile. • Sorption of 222Rn to the soil is neglected.

The one-dimensional advective and dispersive equation for 222Rn transport, 222Rn release from mineral surfaces, and the 222Rn decay and partitioning of 222Rn between the NAPL and water phase are described as: ∂/∂t [(1 – S)qA + qSANAPL] = –∂/∂x [qA – (1 – S)qD ∂A/∂x] + (1 – q)rPl – [(1 – S)qA + qSANAPL]l

(Eq. D.12)

where t S q A ANAPL x q D r P l

= time in seconds. = the NAPL saturation of pore space (NAPL volume divided by the pore space volume). = soil porosity. = the 222Rn activity in the water phase at location (x) at time (t). = the 222Rn activity in the NAPL at location (x) at time (t). = flow distance in meters. = the groundwater discharge. = dispersion coefficient of 222Rn in groundwater (m sec–1). = density of the soil (kg m–3). = the emanation of 222Rn decay from mineral surfaces per mass of dry aquifer material (kBq kg–1). = radioactive decay constant of 222Rn (sec–1).

The partitioning of is described by:

222

Rn between the water phase and NAPL phase at equilibrium ANAPL = KA

(Eq. D.13)

where K = the water and NAPL partition coefficient of 222Rn. Substituting Equation D.13 into D.12 results in: q[1 + S(K – 1)] ∂A/∂t = –∂/∂x [qA – (1 – S)qD ∂A/∂x] + (1 – q)rPl – q[(1 + S)(K – 1)]Al

(Eq. D.14)

D.3 CONCLUSIONS This method provides a natural tracer and requires the measurement of radon activity only once. In order to provide the greatest degree of discrimination from monitoring well, the wells should be installed both within the NAPL-contaminated zone and upgradient and downgradient of the zone.

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REFERENCES Freeze, A. and J. Cherry, 1979. Appendix X, in Groundwater, Prentice-Hall, Englewood Cliffs, NJ, p. 604. Hunkeler, D., Hoehn, E., Hohener, P., and J. Zeyer, 1997. 222Rn as a partitioning tracer to detect diesel fuel contamination in aquifers: laboratory study and field observations, Environmental Science and Technology, 31:3180–3187. Wang, H. and M. Anderson, 1982. Introduction to Groundwater Modeling: Finite Difference and Finite Element Methods, W.H. Freeman, San Francisco, CA, p. 235.

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Appendix E. Chemical and Commercial Synonyms for Selected Chlorinated Solvents and Aromatic Hydrocarbons Solvent and Chemical Formula

Chemical and Commercial Synonyms

Benzene (C6H6)

Annulene; Benzeen (Dutch); Benzen (Polish); Benzin; Benzine; Benzol; Benzole; Benzolene; Benzolo (Italian); Bicarburet of Hydrogen; Carbon Oil; Coal Naphtha; Cyclohexatriene; Fenzen (Czech.); Mineral Naphtha; Motor Benzol; Nitration Benzene; Phene; Phenyl Hydride; Phrobenzol; Pyrobenzole

Bromoform (CHBr3)

Bromoforme (French); Bromoformio (Italian); Methenyl Tribromide; Tribrommethaan (Dutch); Tribrommethan (German); Tribromometan (Italian); Tribromomethane

Carbon tetrachloride (CCl4)

Carbon Bisulfide; Carbon Bisulphide; Carbon Chloride; Carbon Disulphide; Carbon Sulfide; Carbon Sulphide; Dithiocarbonic Anhydride; NCI-C04591; Sulphocarbonic Anhydride; UN 1131; Weeviltox; Benzinoform; Carbona; Carbon Chloride; Carbon Tet; ENT 4705; Fasciolin; Flukoids; Freon-10; Halon-104; Methane Tetrachloride; Necatorina; Necatorine; Perchloromethane; R 10; RCRA Waste Number U211; Tetrachloormetaan; Tetrachlorocarbon; Tetrachloromethane; Tetrafinol; Tetraform; Tetrasol; UN 1846; Univerm; Vermoestricid

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Solvent and Chemical Formula

Chemical and Commercial Synonyms

Chloroform (CHCl3)

Chloroforme (French); Choroformio (Italian); Freon-20; R 20; R 20 refrigerant; Formyl Trichloride; Methenyl Chloride; Methyl Trichloride; Trichloroform; Trichloromethane; Methan Trichloride: Methenyl Trichloride; Methyltrichloride; Trichloromethane; Trichloormethaan (Dutch); Trichlormethan (Czech.); Trichloroform; Trichlorometano (Italian); UN 1888

Chloromethane (CH3Cl)

Arctic R40; Freon-40; Methyl Chloride; Monochloromethane; UN 1063

1,1-Dichloroethane (C2H4Cl2)

Chlorinated Hydrochloric Ether; Ethylidene Dinechloride; Ethyledene Dichloride; UN 2362

1,2-Dichloroethane (C2H4Cl2)

1,2-Bichloroethane; Borer Sol; Brocide; 1,2-DCA; Destruxol Borer-Sol; Dichloremulsion; Dichlormulsion; Dichloroethylene; Dutch Liquid; Dutch Oil; Ethylene Dichloride; Freon-150; EDC; ENT 1656; Glycol Dichloride; NCI-C00511; UN 1184

1,1-Dichloroethylene (C2H2Cl2)

Chlorure de Vinylidene (French); 1,1-DCE; 1,1-Dichloroethene; Sconatex; VDC; Vinylidene Chloride II; Vinylidene Chloride; Vinylidene Dichloride; Vinylidine chloride

Dichloromethane (CH2Cl2)

Aerothene; DCM; Freon-30; MM; Methylene Bichloride; Methylene Chloride; Methylene Dichloride; Narcotil; NCIC50102; Solaesthin; Solmethine; UN1593

Ethylene dibromide (C2H4Br2)

Alphat; beta-Dibromomethane; Bromofume; Celmide; 1,2-Dibromomethane; DBE; Dibrome, Dowfume; 40-Dowfume; Dowfume W-8; Dowfume W-90; Dibromoethane; EDB-85; Ethylene Bromide; Ethylene Bromide Glycol Dibromide, Fumo-Gas; Glycol Bromide; Glycol Dibromide; Iscobrome D; Kopfume; Nephis; Soilfume; Pestmaster; Pestmaster EDB-85; Soilbrome-40; Soilbrome-90; Soilbrom-90C; Soilbrom-100; Soilbrome-85; Unifume

Freon-11 (CCl3F)

Algonfrene Type 1; Arcton 9; Electro-CF 11; Eskimon 11; F11; FC 11; Fluorocarbon 11; Fluorotrichloromethane; Freon-11A; Freon-11B; Freon HE; Freon MF; Frigen 11; Genetron 11; Halocarbon 11; Isceon 11; Isotron 11; Ledon 11; Monofluorotrichloromethane; Refrigerant 11; Trichlorofluoromethane; Ucon 11; Ucon Fluorocarbon; Ucon Refrigerant 11

Freon-113 (FCl2CCF2Cl)

Arcton 63; Arklone P; Daiflon S3; Fluorocarbon 113; F-113; FC-113; Freon® 113; Frigen 113a; TR-T; Genetron 113; Halocarbon 113; Isceon 113; Khladeon; Kaiser Chemicals 11; R-113; R113; Refrigerant 113; TTE; 1,1,2-Trifluoro-1,2,2Trichloroethane; Trichlorotrifluoroethane; 1,1,2-Trichloro-1,2,2Trifluoroethane; 113; Ucon-113; Ucon Fluorocarbon; Ucon 113/Halocarbon 113

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Solvent and Chemical Formula

Chemical and Commercial Synonyms

Methylene chloride (CH2Cl2)

Dichloromethane; DCM; Methylene Dichloride; Methylene Bichloride; Aerothene MM; Freon-30; Narcotil; NCI-C50102; RCRA Waste Number 84.16; RTECS; GY 4640000; Turco 5873; #5141 Chlorinated Solvent

Phenol (C6H60)

Acide Carbolique (French); Baker’s P and S Liquid and Ointment; Benzenol; Carbolic Acid; Carboilsaure (German); Fenol (Dutch, Polish); Fenolo (Italian); Hydroxybenzene; Monohydroxybenzene; Monophenol; Oxybenzene; Phenic Acid; Phenol Alcohol; Phenol Molten; Phenole (German); Phenylhydrate; Phenyl Hydroxide: Phenylic Acid; Phenylic Alcohol

1,1,1-TCA (Cl3CCH3)

a-T; a-Trichloroethane; Aerothene; Aerothene TT; Alpha1,1,1-trichloroethane; Alpha Trichloroethane; Amsco Solv 5620; Baltana; Blaco-Thane; Chloroethane NU; Chloroethene; Chlorten; Crack Check Cleaner C-NF; Genklene; DEV TAP; Devcon; Devon Metal Guard; FL-20 Flexane Primer Lube-Lok 4253; Locquic Primer T; Inhibisol; Methyltrichloromethane; Methyl Chloroform; M-60; NCI-C04626; NU; Rapid Tap; Perm-Ethane; PCN UCD 5620; PCN-UCD 15620; Quik Shield; RCRA Waste Number U226; Solvent 111®; Solventclean SC-A Aerosol; Saf-Sol 20/20; TCA; SKC-NF/ZC-73; Tri-ethane; Turco Lock; UCD 784; VG; UN 2831; #10 Cleaner; #5141 Chlorinated Solvent

Tetrachloroethylene (Cl2Cl4)

Ankilostin; Antisol; Crack Check Cleaner C-NF; Didakene; Carbon Bichloirde; Carbon Dichloride; Dee-Sol; Didakene; Dow-Per; Dow-Clene ECENT 1860; Ethylene Tetrachloride; Fedal-UN; NCI-C04580; Nema; PCE; PER; PERC; Percelene; Perawin; Perchlor; Perchlorethylene; Perchloroethylene; Perclene; Percosolv; Perk; Persec; PerSec 1; Tetlen; Tetrophil; Tetracap; Tetrachloroethylene; Tetrachloroethene; 1,1,2,2Tetrachloroethylene; Tetropil; Tetracap; Tetraleno; Tetravec; Tetroguer; Tetropil; UN 1897; #5141 Chlorinated Solvent

1,1,2,2-Tetrachloroethylene (C2Cl4)

Ankilostin; Antisol 1; Carbon Bichloride; Carbon Dichloride; Czterochloroetylen (Poland); Didakene; Dow-Per; Ent 1.860; Ethylene Tetrachloride; Fedal-UN; Nema; Perawin; Perchloorethyleen Per (Dutch); Perchlor; Perchloraethylen, Per (German); Perchlorethylene; nPerchlorethylene, Per (French); Perclene; Perchloroetilene (Italian); Percosolve; Perkcosolve; Perk; Perklone; Persec; Tetlen; Tetracap; Tetrachlooretheen (Dutch); Tetrachloraethen (German); Tetrachloroethene; Tetrachloroetene (Italian); Tetraleno; Tetralex; Tetravec; Tetroguer; Tetropil

1,1,2-Trichloroethane (C2HCl3)

Cement T-399; Ethane Trichloride; 1,2,2 Trichloroethane; d-T; b-trichloroethane; Vinyl Trichloride

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Solvent and Chemical Formula

Chemical and Commercial Synonyms

Trichloroethene (C2HCl3)

Acetylene Trichloride; Algylen; Anamenth; Anameneth; Benzinol; Blancosolv; Blacosolv; 1-Chloro-2,2dichloroethylene; Cecolene; Chlorylea; Chlorylen; Chorylen; Chlorilen; Circosolv; Crawhaspol; 1,1-Dichloro-2chloroethylene; Densinfluat; Dow-Tri, Dow-TriPhilex; Dukerson; Ethinyl Tri-Plus; Ethylene Trichloride; Ethinyl Trichloride; Fleck-Flip; Flock-Flip; Fluate; Germalgene; Hi-Tri; Lanadin; Lethurin; Narcogen; Narkosoid; Nialk; Neu-Tri; NCIC04546; Petzinol; Perm-a-chlor; Perm-a-clor; Petzinol; Philex; Trichloroethylene; 1,1,2-Trichloroethylene; Trichloroethene; Tri-Clene; Trielene; Trichloran; Trichloren; Trimar; Trline; Trethylene; Trichloride Triad; Trimar; Turco Surjex; Triasol (Trichlooretheen (Dutch); Trichloraethen (German); Trichloran; Trichlorretent, Trichloroethilene, and Trielina (Italian); tVestrol; UN 1710;Vitran; Vestrol; V-strol; Westrosol; Zip Grip Accelerator

Vinyl chloride (C2H3Cl)

Chloroethene; Chloroethylene; Ethylene Monochloride; VC; VCM; 1-Chloroethene; 1-Chloroethylene; Ethylene Monochloride; Monochloroethene; Monochloroethylene; MVC; Trovidur; UN 1086; Vinyl C Monomer; Vinyl Chloride Monomer

Xylene (C8H10)

Dimethylbenzene; Ksylen (Poland); Methyl Toluene; Violet 3; Xiloli (Italian); Xylenen (Dutch); Xylole (German); #5141 Chlorinated Solvent

REFERENCES IARC, 1979. Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, Vol. 20, Halogenated Hydrocarbons, International Agency for Research into Cancer, Switzerland. MacKay, D., Shui, W., and K. Ma, 1993. Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals. Vol. III. Volatile Organic Chemicals, Lewis Publishers, Chelsea, MI, p. 916. Montgomery, J., 1995. Groundwater Chemicals Field Guide, Lewis Publishers, Chelsea, MI, p. 271. Pankow, J., Feenstra, S., Cherry, J., and M. Ryan, 1996. Dense chlorinated solvents in groundwater: background and history of the problem, in Pankow, J. and J. Cherry (Eds.), Dense Chlorinated Solvents and Other DNAPLs in Groundwater, Waterloo Press, Portland, OR, p. 1–46. Ramamoorthy, S. and S. Ramamoorthy, 1997. Chlorinated Organic Compounds in the Environment: Regulatory and Monitoring Assessment, Lewis Publishers, Boca Raton, FL, p. 370.

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Appendix F. Laboratory Terms and Definitions Laboratory Term/ Abbreviation

Definition

Accuracy

The ability of a procedure to determine the “true” analyte concentration.

Batch

A group of 20 samples or less, of similar matrix type, prepared or analyzed together if no sample preparation is required, under the same conditions and with the same analytical reagents. The batch must include a method blank, laboratory control standard, and matrix quality control.

Blank (B)

Indicates that the compound was detected in the sample and blank; the sample value is usually reported without the blank subtraction. If the sample value is less than 10¥ the blank value times the sample dilution factor, the compound may be present as a laboratory contaminant.

Blank result

The result of analyzing a method blank (reagent water that is subjected to the same preparation procedures as the batch samples). The blank result is used to identify laboratory contamination.

BNA

Base-neutral/acid fraction (also called extractable semivolatile fraction). The BNA represents the pollutant that can be extracted from a sample but which boils higher than 120∞C and still passes through a gas chromatography column.

CAM

California Assessment Manual; the original draft of this manual contains California hazardous waste rules, one of which lists 17 toxic or “CAM” metals.

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Laboratory Term/ Abbreviation

Definition

Control

Control limits are determined from historical data for a quality control parameter. The test value must be within this acceptable range for the test to be considered in control. This range usually corresponds to the 99% confidence interval for the historical data.

DCS

Duplicate control sample.

Dilution (D or DIL)

Indicates that the sample was diluted and, as a consequence, the surrogates were too diluted to measure accurately.

Detection limit (DL)

The minimum value that can be detected in the sample with a high degree of confidence taking into account dilution factors and interferences. The reported detection limits are equal to or greater than the method detection limit (MDL) to allow for daily and instrument-to-instrument variations in sensitivity.

EB

Equipment blank.

Instrument detection limit (IDL)

The smallest signal above background noise that an instrument can detect.

Laboratory control standards (LCS)

The laboratory control standard indicates the accuracy of the analytical method. The LCS also provides verification of the calibration because it is prepared from a different source than the standard used for instrument calibration. A LCS is performed by spiking laboratory-grade reagent water with known compounds and subjecting the spiked sample to the same procedures as the samples.

Laboratory test results (LT)

The expected result, or true value, of the Laboratory Control Standard analysis.

Limit of detection (LOD)

The lowest concentration that can be determined to be statistically different from a blank. A LOD is often equivalent to three times the standard deviation from replicate measurements of concentrations near the limit of quantitation.

Limit of quantification (LOQ)

The level above which quantitative results are obtained with a specified degree of confidence. The LOQ is often defined as equal to 10 times the standard deviation from replicate measurements.

Matrix quality control

Quality control tests performed on client samples. For most inorganic analyses, the laboratory uses a pair of duplicate and spiked samples. For most organic analyses, the laboratory uses a pair of spiked samples (also called duplicate spikes).

Matrix spike (D)

Matrix spike duplicate; this refers to a quality control sample that may be a real sample or blank sample spiked with representative target analytes.

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Laboratory Term/ Abbreviation

Definition

Method detection limit (MDL)

The minimum concentration of a substance that can be identified, measured, and reported with a 99% confidence that the concentration is greater than zero.

NA

(1) Not analyzed, or (2) a value is not available for the parameter, usually for a detection limit.

NC

Applies to spike recovery results and RPD. The relative percent difference (RPD) and spike recovery are not calculated when a result value is less than five times the detection limit or if matrix interferences are present. A spike recovery is not calculated when the sample result is greater than four times the spike-added concentration because the spike-added concentration is considered insignificant.

ND (not detected)

Indicates that the compound was not found in the sample at or above the detection limit.

% error

A measure of accuracy based on the analysis of a Laboratory Control Standard. The % error is expressed in percent as the difference between the known value and the experimental value divided by the known value. The Laboratory Control Standard can be a solution-based standard that confirms calibration or a continuing calibration verification. The LCS may also be a reference sample taken during sample preparation and analysis.

Percent recovery

The percentage of analyte recovered. For Laboratory Control Standards, the percent recovery is equal to the Laboratory Control value divided by the Laboratory Test result and multiplied by100. For spiked recoveries, the percent recovery calculation is (S Bar – R Bar)/(True – R Bar) ¥ 100.

ppm

Parts per million; usually equivalent in liquids to mg/L.

ppb

Parts per billion; usually equivalent in liquids to mg/L and in the gas phase to mg/L (mL/m3).

Practical quantification limit (PQL)

The level that can be reliably achieved within a specified limit of precision and accuracy during routine laboratory operation conditions. The PQL is a U.S. Environmental Protection Agency interlaboratory concept that has been estimated at 5 to 10 times the method detection limit.

Precision

The reproducibility of a procedure demonstrated by the agreement between analyses performed on either duplicates of the same sample or a pair of duplicate spikes.

R1, R2 result

The result of analyzing replicate sample aliquots, with R1 indicating the first analysis of the sample and R2 its corresponding duplicate. R1 and R2 results are used to determine precision.

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Laboratory Term/ Abbreviation

Definition

R Bar result

The average of replicate analysis results.

Relative percent difference (RPD)

This is a measure of the precision of the analysis. It is the difference between duplicate results divided by the mean of the duplicates. RPD is calculated by either of the following relationships: (R1 – R2)/(R Bar) ¥ 100 or (S1 – S2)/(S Bar) ¥ 100.

Reporting detection limit (RDL)

A limit similar to but not the same as the method detection limit (MDL) established via U.S. Environmental Protection Agency guidelines. It is set by the analytical laboratory. The RDL is not adjusted for dilution factors and may not be the same as the sample result values.

S1, S2 result

The results of the analysis of replicate spiked aliquots, with S1 indicating one spike of the sample and S2 the second spike. S1 and S2 test results are used to determine precision and accuracy.

S Bar result

The average of spike analysis results.

STLC

Soluble threshold limit concentration; according to California’s hazardous waste regulations, a waste is considered hazardous if the concentration in the leachate from the waste extraction test (WET) exceeds this limit.

Surrogates

Organic compounds similar to the target analytes in chemical composition and behavior in the analytical process, but which are not normally found in environmental samples. All samples are spiked with a surrogate compound(s) prior to analysis. Surrogate percent recovery (%R) provides information about the laboratory performance on individual samples and the possible effects of the sample matrix on the analytical results.

TCLP

Toxicity characteristic leaching procedure; according to U.S. Environmental Protection Agency regulations, a waste is considered hazardous if the leachate from the TCLP extraction exceeds certain levels.

TR (trace)

Indicates that the compound was observed at a value less than the normal reported detection limit. Such values are subject to large errors and should be considered as qualitative.

True value

The theoretical, or expected, result of a spike sample analysis.

TTLC

Total threshold limit concentration; according to California’s hazardous waste regulations, a waste exceeding this concentration is considered a hazardous waste.

VOA

Volatile organic analysis; VOAs are a group of volatile organic solvents with a boiling range from below room temperature to about 150∞C.

WET

Waste extraction test (see STLC).

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Laboratory Flags Definitions A

An analytical and/or post-digestion spike that has not been subjected to extraction or digestion.

B

A target analyte that is detected in a reagent blank but the sample results are not corrected for the amount in the sample blank.

C

An analyte has been confirmed by analysis on a second column on a gas chromatograph.

D

Analytes detected in a secondary dilution factor. Because some compounds can exceed the calibration range of the instrument, an analysis is performed at the concentration of the majority of the analytes and a second analysis is performed with the sample diluted so that high-concentration analytes fall within the calibration range of the instrument.

E

(1) The amount detected exceeds the calibration range of the instrument; (2) the reported value was estimated because of the presence of interferences.

G

A gas chromatography/mass spectrometry (GC/MS) result whose concentration exceeds the calibration range for a specific analysis.

I

A general-purpose flag defined by the individual laboratory.

J

Indicates an estimated value for GC/MS data. A J flag is used when estimating a concentration for a tentatively identified compound where a response factor of 1 is assumed or when the mass spectral data indicates the presence of a compound that is less than the sample quantitation limit.

M

(1) Manual integration; (2) indicates that the duplicate injection precision of the sample was not met.

N

(1) Indicates presumptive evidence of a chemical found as a tentatively identified compound based on a search of a mass spectrophotometry library; (2) indicates spike control samples were not within control limits.

NR

An analyte that was not requested by the client.

NS

(1) Not sampled, or (2) an analyte or surrogate was not spiked to the sample for analysis.

P

Analyte has been confirmed on a second gas chromatograph column. A P flag is applicable to analysis of samples from a regular sampling program as a specific sample source.

Q

A quality control standard that is outside method or laboratory specified control limits, including matrix spike, analytical QC spikes, and surrogate recoveries.

R

(1) The analyte was detected in the reagent blank and the sample results are corrected for the amount in the sample blank; (2) indicates that the data are unusable.

S

A result from a metals analysis has been obtained using the Method of Standard Addition.

U

(1) Confirmation on a second gas chromatograph column of dissimilar phase was not requested; (2) indicates that the analyte was analyzed but not detected above the sample detection limit.

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Laboratory Flags Definitions UJ

Indicates that the chemical was analyzed for but not detected. The associated value is an estimate and may be inaccurate or imprecise.

X

A second gas chromatograph column was used to provide confirmation but the analyte was not confirmed and is probably a false positive.

*

An analytical result that is less than five times the method-specified detection limit and should be considered as approximate. As the method detection limit is approached, analytical uncertainty increases exponentially.

#

The qualifier is out of range.

©2000 CRC Press LLC