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PAUL M. BERTSCH
RONALD L. PHILLIPS
University of Kentucky
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University of California, Davis
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JOHN S. BOYER
KENNETH J. FREY
University of Delaware
Iowa State University
EUGENE J. KAMPRATH
MARTIN ALEXANDER
North Carolina State University
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Prepared in cooperation with the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America Book and Multimedia Publishing Committee DAVID D. BALTENSPERGER, CHAIR LISA K. AL-AMOODI
CRAIG A. ROBERTS
WARREN A. DICK
MARY C. SAVIN
HARI B. KRISHNAN
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DONALD L. SPARKS Department of Plant and Soil Sciences University of Delaware Newark, Delaware, USA
AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier
Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 32 Jamestown Road, London, NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2009 Copyright # 2009 Elsevier Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email:
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CONTENTS
Contributors Preface
1. Advances in Assessing Bioavailability of Metal(Loid)s in Contaminated Soils
vii ix
1
Kirk G. Scheckel, Rufus L. Chaney, Nicholas T. Basta, and James A. Ryan 1. Introduction 2. Metal Risks in Soil 3. Biological Metal Uptake 4. Metal Extractability to Predict Availability 5. Metal Chemistry 6. Understanding Metal Bioavailability, Bioaccessibility, and Speciation 7. Conclusions Acknowledgments References
2. Nitrogen in Rainfed and Irrigated Cropping Systems in the Mediterranean Region
3 7 12 16 22 28 41 43 43
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John Ryan, Hayriye Ibrikci, Rolf Sommer, and Ann McNeill 1. Introduction 2. Mediterranean Agroecosystems 3. Perspective on Nitrogen in Agriculture 4. Fertilizer use Trends in the Mediterranean Region 5. Response of Rainfed Crops to Nitrogen Fertilizer 6. Assessing Soil Nitrogen Status for Crop Yields 7. Nitrogen Fixation Under Mediterranean Dryland Conditions 8. Potential Losses of Nitrogen in Dryland Cropping 9. Integrated Cropping Systems: Implications for Nitrogen 10. Nitrogen in Supplemental Irrigation Systems 11. Nitrogen Tracer use in Rainfed Cropping Systems 12. Modeling of Nitrogen in Rainfed Cropping Systems 13. Future Perspective Acknowledgments References
55 57 63 66 68 80 85 92 95 105 107 113 120 121 121 v
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Contents
3. Biogeochemical Processes Controlling the Fate and Transport of Arsenic: Implications for South and Southeast Asia
137
Scott Fendorf and Benjamin D. Kocar 1. Introduction 2. Arsenic Aqueous Chemistry 3. Arsenic Surface and Solid Phases 4. Desorption of Arsenic in Soils and Sediments 5. Biogeochemical Processes 6. Processes Controlling Arsenic Concentrations in South(east) Asia 7. Summary and Conclusions Acknowledgments References
4. Inorganic and Organic Constituents and Contaminants of Biosolids: Implications for Land Application
138 139 139 146 149 154 157 158 158
165
R. J. Haynes, G. Murtaza, and R. Naidu 1. Introduction 2. Sewage Treatment Processes 3. Composition of Biosolids 4. Nutrient Content and Release 5. Heavy Metal Contaminants 6. Organic Contaminants 7. Synthesis and Conclusions References Index
166 168 169 175 182 208 234 237 269
CONTRIBUTORS
Numbers in Parentheses indicate the pages on which the authors’ contributions begin.
Nicholas T. Basta (1) School of Environment and Natural Resources, The Ohio State University, Columbus, Ohio, USA Rufus L. Chaney (1) USDA-ARS, Environmental Management and Byproduct Utilization Laboratory, Beltsville, Maryland, USA Scott Fendorf (137) Stanford University, Stanford, California, USA R. J. Haynes (165) School of Land, Crop and Food Sciences/CRC CARE, The University of Queensland, St Lucia, Australia Hayriye Ibrikci (53) Soil Science Department, Faculty of Agriculture, C ¸ ukurova University, Balcali, Adana, Turkey Benjamin D. Kocar (137) Stanford University, Stanford, California, USA Ann McNeill (53) Adelaide University, Roseworthy Campus, Adelaide, South Australia, Australia G. Murtaza (165) Centre for Environmental Risk Assessment and Remediation, Division of Information Technology, Engineering and the Environment, University of South Australia, Mawson Lakes Campus, South Australia, Australia and Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad, Pakistan R. Naidu (165) CRC CARE, Salisbury, South Australia, Australia James A. Ryan (1) USEPA, Cincinnati, Ohio, USA John Ryan (53) International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria vii
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Contributors
Kirk G. Scheckel (1) USEPA, National Risk Management Research Laboratory, Cincinnati, Ohio, USA Rolf Sommer (53) International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria
PREFACE
Volume 104 contains four outstanding reviews on timely topics that will be of interest to plant, soil, and environmental scientists. Chapter 1 is a comprehensive review on frontiers in assessing the bioavailability of metal (loids) in contaminated soils. Topics that are covered include metal risks in soils, biological metal uptake, metal chemistry, metal extractability and prediction of availability, and advances in understanding metal bioavailability, bioaccessibility, and speciation. Chapter 2 discusses nitrogen in rainfed and irrigated cropping systems in the region including Mediterranean agroecosystems, fertilizer use trends, response of rainfed crops to nitrogen fertilizer, nitrogen fixation under Mediterranean dryland conditions, and modeling of nitrogen in rainfed cropping systems. Chapter 3 covers the biogeochemical processes that impact the fate and transport of arsenic with specific emphasis on South and Southeast Asia. Processes that are critical include ion displacement, desorption, reduction of arsenate to arsenite, and reductive dissolution of Fe- and Mn-(hydr)oxides. Chapter 4 provides a thorough treatment on inorganic and organic contaminants in biosolids and impacts on application to land. Discussions on sewage sludge treatment processes, nutrient content and release, heavy metal contaminants, and organic contaminants are provided. The authors are congratulated on their first-rate reviews. DONALD L. SPARKS Newark, Delaware, USA
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Advances in Assessing Bioavailability of Metal(Loid)s in Contaminated Soils Kirk G. Scheckel,* Rufus L. Chaney,† Nicholas T. Basta,‡ and James A. Ryan§,1 Contents 3 7 7 8 11 12 12 13 14 16 16
1. Introduction 2. Metal Risks in Soil 2.1. Bioavailability and soil element risks 2.2. Phytotoxicity risks from soil elements 2.3. Risks to soil organisms 3. Biological Metal Uptake 3.1. Risks through soil ingestion 3.2. How much soil do children ingest? 3.3. Food-chain transfer and risks 4. Metal Extractability to Predict Availability 4.1. In vitro bioaccessibility 4.2. Common soil extractions to predict risk of phytotoxicity or food-chain risk 5. Metal Chemistry 5.1. Metal equilibrium in soils 5.2. Metal speciation in soils 6. Understanding Metal Bioavailability, Bioaccessibility, and Speciation 6.1. Lead 6.2. Arsenic 7. Conclusions Acknowledgments References
* {
{ } 1
21 22 22 25 28 28 35 41 43 43
USEPA, National Risk Management Research Laboratory, Cincinnati, Ohio, USA USDA-ARS, Environmental Management and Byproduct Utilization Laboratory, Beltsville, Maryland, USA School of Environment and Natural Resources, The Ohio State University, Columbus, Ohio, USA USEPA, Cincinnati, Ohio, USA Retired.
Advances in Agronomy, Volume 104 ISSN 0065-2113, DOI: 10.1016/S0065-2113(09)04001-2
#
2009 Elsevier Inc. All rights reserved.
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Abstract The term bioavailability has many different meanings across various disciplines of toxicology and pharmacology. Often bioavailability is concerned with human health aspects such in the case of lead (Pb) ingestion by children. However, some of the most contaminated sites are found in nonpublic access facilities (Department of Defense or Energy) or in remote regions as a result of mining or industrial practices in which ecoreceptors such as plants, animals, and soil organisms are the primary concerns as well as the potential for food-chain transfer. In all cases, the endpoint requires movement of the element across a biological barrier. The still utilized approach to base risk assessment on total metal content in soils is an outdated endeavor and has never been proved to be scientifically sound. Yet to reverse this trend, much work is required to establish baseline bioavailability measurements and to develop complementary methods that are capable of predicting bioavailability across a whole range of impacted media in a cost-efficient manner. Thus, regulators have recognized site-specific human health risk assessments play a key role in decision-making processes at contaminated sites. Bioavailability issues surrounding metal-contaminated soils and media have been an area of intense research. For obvious ethical reasons, we cannot solicit humans, in particular the sensitive population of children, from the general population for experimental purposes to examine the long-term harmful effect of metals in soils. However, some adult human feeding studies have been accomplished under tight medical supervision and with very small doses. One option to understand and relate bioavailability in humans is to employ animal surrogates; however, the physiology of most animals is different than that of humans but good correlations have been achieved despite the dose–response paradigm not being identical. The biggest drawback of in vivo studies to examine metal bioavailability to an appropriate ecoreceptor, be it human, plant, or soil organism, is the tremendous cost and time involved relative to chemical and physical surrogates. Chemical surrogate methods generally only require knowledge of the total metal content so that a percent bioaccessible number can be generated from in vitro extractions that simulate digestive systems or mimic responses to sensitive ecoreceptors. However, there is not a consensus as to which of the many in vitro methods is the best analogy to an ecoreceptor uptake and the same can be said for in vivo animal models to mimic human response as well. Further, there is yet to be a single in vitro method that can account for more than a few elements for a specific exposure pathway (e.g., Pb and/or arsenic (As) for human health). These in vitro tests require honest and accurate validation against in vivo bioavailability measurements, but most of all would benefit from metal speciation methods to identify the forms of metals allowing their release. Adaptation of spectroscopic speciation techniques to identify metal(loid) phases is extremely beneficial in bioavailability research to understand the variability of biologically available metal uptake, to manipulate the ecosystem to reduce bioavailability via in situ amendments, to monitor the long-term stability of elements to ensure bioavailability indicators do not change over time, and to develop comprehensive predictive models based on speciation.
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1. Introduction In most cases, the toxicity of contaminants depends on how much of it is absorbed into the body or taken up by plants. For soil contaminants where human exposure is by ingestion of soil or plants and organisms produced on the soil, toxicity depends on absorption into the gastrointestinal (GI) system. Information on how well a contaminant is absorbed into the GI system is important to determining how much of a contaminant humans can be exposed to before health effects occur. Because typical health effect dose– response assessments (and resulting oral reference doses (RfDs) and cancer slope factors (CSFs)) are generally expressed in terms of ingested dose (rather than absorbed dose into the organism), accounting for potential differences in absorption between different exposure media can be important to site risk assessment (USEPA, 1989). Thus, if the oral RfD for a particular metal is based on bioavailability studies in water, risks from ingestion of the metal in soil or plant produced on the soil might be (likely is) overestimated. Minor adjustments in oral bioavailability based on nonrelevant exposure pathways can have significant impacts on estimated risks and cleanup goals for hazardous waste sites (USEPA, 1989). It is increasingly recognized that the response of an at-risk population is not controlled by the total metal concentration, but instead is controlled by only the biologically available portion, which is dependent on the route of exposure, the pharmacokinetics of the organism, and the speciation of the contaminant. In spite of the earlier understanding, the complexity of metal-contaminated sites has and continues to be simplified to a measure of the total metal content. Regulations on the fate and effects of metals in the environment based solely on total concentrations are no longer (perhaps never has been) valid, state-of-the-art, or scientifically sound. A vast amount of knowledge clearly illustrates the decisive role of metal speciation when metal bioavailability and phytoavailability in the environment have to be assessed (McNear et al., 2007; Ryan et al., 2004). While total metal content is a critical regulatory measure in assessing risk of a contaminated site, total metal content alone does not provide predictive insights on the bioavailability, mobility, and fate of the metal contaminants. Thus, a better understanding of the nature of the chemical and physical interactions of contaminants with soil constituents can increase the scientific understanding and lead to regulatory and public confidence in the use of bioavailability adjustments. Predictions of long-term stability rely on a mechanistic understanding of how contaminants are stored or sequestered within the soil. Bioavailability processes are defined as the individual physical, chemical, and biological interactions that determine the transfer of chemicals associated with soils to plants and animals. Bioavailability processes are
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embedded within existing human health and ecological risk frameworks to reduce uncertainty in exposure estimates and improve risk assessment (USEPA, 2007b). In both ecological and human health risk assessment, bioavailability is usually reflected in default values or site-specific data that are inserted into exposure equations. Although a multitude of processes can affect bioavailability, a typical risk assessment generates one value that is used to adjust the applied dose. For this reason, many bioavailability processes are hidden within risk assessment, and assumptions made about these processes are sometimes not clear. Although long employed in toxicology and agricultural sciences, the concept of bioavailability has recently sparked the interest of the hazardous waste industry as an important consideration in deciding how much waste to clean up. This interest stems from observations that some contaminants in soils appear to be less available to cause harm to humans and ecological receptors than is suggested by their total concentration, such that cleanup levels expressed as total concentrations poorly correlate with actual risk. Correct characterization of bioavailability in contaminated soils and sediments may indicate that greater levels of contamination can be left untouched without increased risks, thus, reducing cleanup costs and reducing volumes of contaminated media requiring intrusive remedial options (USEPA, 2007c). However, in order to pursue this concept in risk assessment critical knowledge of bioavailability processes and spectroscopic speciation techniques are required to develop a mechanistic understanding of the bioavailability processes to improve the science of risk assessment to develop predictive models derived from sound research. Further, chemical, environmental, and regulatory factors must align in considering bioavailability processes that influence risk-based decision-making (NRC, 2003). Because the fraction of a soil element which can actually be absorbed by an organism to cause harm depends on the chemical forms present and physical/chemical properties of the soil, in both risk assessment and remediation evaluation, the fraction of a soil element which can actually cause harm must be identified. This fraction is ultimately defined as the bioavailable fraction, and because measurement of the bioavailable fraction is timeconsuming and expensive via in vivo animal feeding studies, in vitro chemical methods are being developed to estimate the bioavailable fraction. In the case of ingestion of soil, the in vitro or chemical estimation method has been labeled ‘‘bioaccessible’’ (to avoid confusion with ‘‘bioavailable’’) and is a measure of the amount of metal that can be liberated from the soil matrix, thus not a measure of the amount of metal that moves across the GI epithelium to harm internal target tissues and organs. Extensive progress has been made in development of soil Pb and As bioavailability testing in conjunction with bioaccessibility methods (Drexler and Brattin, 2007; Rodriguez et al., 2003; Ruby et al., 1993, 1996). Additionally, great effort has been wasted in planning inconsequential research efforts to develop
Advances in Assessing Bioavailability of Metal(Loid)s in Contaminated Soils
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bioaccessibility methods, which try to match all digestion processes without a valid bioavailability endpoint as a comparison. In the end, an in vitro bioaccessibility method only needs to be well correlated with an acceptable in vivo bioavailability model. Actually, the simpler and less expensive the bioaccessibility method can be made, the better, as long as the correlation with bioavailability is high. Further, it is necessary for the tests to be reproducible in laboratories across the globe, which has not been the case for many of the bioaccessibility methods available today. Further, for such methods to be relevant to testing of remediation methods, changes in bioavailability due to field treatments should be reflected in the bioaccessibility test results. In the case of soil Pb, in situ remediation using phosphate and other treatments have been proved to reduce bioavailability to pigs, rats, and humans, but the bioaccessibility test conducted at pH 1.5 does not measure this 69% reduction in bioavailability to human adults while testing at pH 2.2 or 2.5 does reflect the effectiveness of the soil treatment (Ryan et al., 2004). Other simple chemical tests have been shown to suffer significant flaws in that the extraction causes changes in chemical speciation during the test, and have not been shown to correlate with bioavailability changes due to soil treatments. Further, it is necessary to have a valid measure of why the bioavailability or bioaccessibility of samples are different and whether the changes are persistent; thus, the need for metal speciation. For sensitive ecoreceptors (plants, animals, and soil organisms), where testing with the organism to be protected is more readily conducted, chemical methods have been developed which integrate potential toxicity across soil properties including pH which often strongly affects bioavailability. Mild neutral salt extractions (similar to the first extraction step of a sequential extraction procedure) are often found to be effective methods. However, assessment of potential toxicity by adding metal salts to uncontaminated soils substantially fails to mimic field contaminated soils because elements react with soils, and metal salt additions alter soil pH and do not account for the aging effect of metals in soils. Traditional toxicology approaches of adding element salts and immediately measuring toxicity are clearly inappropriate, and can cause serious artifacts due to pH change resulting from the metal salt addition, or formation of soluble metal complexes which temporarily increase or decrease element bioavailability. Thus, testing of potential toxicity has as many problems as testing of bioaccessibility. It seems clear that by taking present knowledge into account, effective toxicity testing, bioaccessibility evaluation, and risk assessment can provide massive savings to the public in dealing with contaminated soils. The extent to which metals are bioavailable has significant implications on human and ecological health following exposure and on potential remediation of contaminated sites. Characterization via speciation of insoluble metal phases in contaminated soils and sediments may indicate that greater levels of contamination can be left untouched without increased risks, thus,
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driving reduced cleanup costs and limited volumes of contaminated media through less intrusive remedial options. A mechanistic understanding of the bioavailability process in relation to metal speciation will allow development of predictive models and improvement of risk assessment. Further, chemical, environmental, and regulatory factors must align in considering bioavailability processes that influence risk-based decision-making (NRC, 2003). In both ecological and human health risk assessment, bioavailability is usually reflected in default values or site-specific data that are inserted into exposure equations. Although a multitude of processes can affect bioavailability, a typical bioavailability assessment generates one value that is used to adjust the applied dose. The Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation (Part A) (RAGS) (USEPA, 1989) supports the consideration of bioavailability in the determination of site-specific human health and environmental risks. This guidance has been used to support bioavailability adjustments across different routes of exposure at contaminated sites. However, the use of bioavailability information in site-specific risk assessment has not been widespread (due to limited data, uncertain methodologies, and lack of method validation). The primary impediment to the broad use of bioavailability data in risk assessment and decision-making is the absence of rapid and inexpensive tools that can generate reliable relative bioavailability (RBA) estimates in the receptors of concern. It is in this context that coupling in vivo bioavailability, in vitro bioaccessibility, and speciation research can fill many data gaps to aid in understanding and predicting bioavailability. The speciation, or chemical form, of metals governs their fate, toxicity, mobility, and bioavailability in contaminated soils, sediments, and water. Different chemical forms of metals, for example, can differ greatly in the amounts taken up by organisms. The varying bioavailability values of different metal species is a large reason for the wide range of bioaccessibility values measured using standardized in vitro analyses of different soils. Other interactions between metals and soil components also govern speciation and affect bioavailability. The influence of the soil matrix on metal(loid) availability is in constant dynamic equilibria with multiple independent variables such as solid mineral phases, exchangeable ions and surface adsorption, nutrient uptake by plants, soil air, organic matter, and microorganisms, and water flux. However, determining speciation is not a trivial task, particularly at low concentrations in a complex matrix such as soil. To assess these chemical properties and to accurately gauge their impact on human health and the environment we need to characterize metals at the atomic level with spectroscopic techniques. This research must move beyond operationally defined sequential extraction methods and utilize analytical instruments that are capable of identifying metal species (D’Amore et al., 2005) Researchers have used advanced synchrotron radiation methods to elucidate the true, in situ speciation of metal contaminants. Synchrotron techniques include X-ray absorption near-edge spectroscopy (XANES), which identifies the
Advances in Assessing Bioavailability of Metal(Loid)s in Contaminated Soils
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oxidation state and first coordination shell and X-ray absorption fine structure (XAFS) spectroscopy provides information on coordination environment of a selected element as well as interatomic bond distances and identity of nearest-neighboring atoms to determine speciation. These methods can also be used in conjunction with statistical methods (principal component analysis and linear combination fitting) to determine chemical phases via a finger printing process with a library of known reference standards. Although most soil criteria and regulations for metals are still based on the total concentration of the metal in question, it is becoming more and more evident that spectroscopic speciation is vital for regulatory risk assessment of environmentally relevant metals in conjunction with in vivo animal data and validated in vitro extractions for human health effects and plant uptake/foodchain transfer for sensitive ecoreceptors. These innovative research tools are expanding our ability to directly identify the role of metal speciation on many dynamic processes that influence bioavailability and risk. The application of synchrotron techniques for the speciation of metals to assess bioavailability seems logical to this chapter, but to the common regulator a simpler approach has been to pick a fractional number relative to the total concentration of a metal in order to establish a cleanup standard. Fortunately from a human health perspective, the common regulator approach is significantly conservative almost to a point that hinders common sense for site remediation. A good example of this is arsenic which is regulated assuming 100% bioavailability, yet several studies have demonstrated that absolute bioavailability of arsenic at most sites can be as low as 20% through matrix effects or natural attenuation processes. If a lower bioavailability value can be utilized at a site, then the effective cleanup standard is raised resulting in significant savings in remedial clean up costs without harm to human health or the natural environment. However, few speciation studies have truly taken on the task of addressing bioavailability from start to finish—meaning many synchrotron-based studies will broadly state that their results support an understanding or prediction of bioavailability but provide no real data on bioavailability to support the claim. There is much speciation research needed to complement in vivo and in vitro research on metal bioavailability that can lead to effective predictive models on the long-term fate of contaminants.
2. Metal Risks in Soil 2.1. Bioavailability and soil element risks The focus of this chapter is on the potential for adverse effects of soil elements to organisms; specifically soil organisms, plants, livestock, wildlife, and humans which ingest soils and crops grown on soil. The most common
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understanding of bioavailability of a soil element is the fraction of total soil element which can be absorbed into an organism and cause an adverse or beneficial effect in the exposed organism. In its concern with direct ingestion of soil, the USEPA has defined bioavailability as the fraction of an ingested dose that crosses the GI epithelium and becomes available for distribution to internal target tissues and organs (USEPA, 2007b). From this definition, bioavailability can be divided into two kinetic steps: (1) dissolution and liberation of the metal in GI fluids and (2) absorption of the metal across the GI epithelium into the blood stream. Either of which can be ratelimiting to element bioavailability. Combining the variability of geochemical forms of elements in contaminated soils with dissolution chemistry and biological absorption processes in the GI tract is a complex endeavor but should be a call to arms for the many researchers pursuing this effort. The scientific and regulatory communities must push further convoluting of this complexity by recognizing that each element has its own specific environmental toxicology; meaning the organism to which a specific element can cause an adverse effect at the lowest environmental exposure and the interaction of other factors with that element such as Ca with Pb, Zn with Cd, Fe with As, and Cu with Mo. In some cases, the key interaction which affects element risk is related to dissolution from ingested soil, while in other cases, interaction during intestinal absorption is the key process which controls risk from an element. This understanding must come from assessment of the specific pathway from soil to organism for each element which can harm a sensitive exposed organism. Often children are the most exposed and sensitive organisms with respect to contaminated soils in urban areas, but for remote contaminated areas, it is wildlife, plants, or soil organisms that are likely to be the most exposed and sensitive organisms. But each element has its specific chemistry in soils, potential for uptake by plants or soil organisms, and potential to affect consumers of plants or soils.
2.2. Phytotoxicity risks from soil elements The most sensitive adverse effect of some elements in soils is phytotoxicity. It seems clear that the first limiting effect of Zn, Ni, Cu, Mn, Al, and possibly some other elements are phytotoxicity to sensitive plants. Of course, plant species vary in tolerance of soil elements. And soil properties can strongly affect phytotoxicity. For cations, acidic soil pH strongly promotes element toxicity, and the elements react over time increasingly strongly to lower phytoavailable forms. In the case of Ni, it was shown by Singh and Jeng (1993) that Ni was about 10-fold less accumulated by perennial ryegrass over a 3-year test period using experimental methods which are highly defensible. Initially, such results were explained in terms of adsorption and diffusion into micropores of the sesquioxides (Bruemmer et al., 1988). Since then, research has shown that new mineral phases may
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form in Ni enriched soils, both Ni–Al layered double hydroxides (LDH) and Ni-silicates (Scheckel and Sparks, 2001). And although Zn can also form such LDH species, the Zn forms are weaker than the Ni forms (Roberts et al., 2003). Cu and Cd apparently do not form the LDH species in soils; however, Co may form them (Scheinost and Sparks, 2000). Figure 1 summarizes known soil reactions of Ni in relation to plant uptake and Ni phytotoxicity. Some industrial compounds can land on soils and persist for long periods. For example, NiO dissolves very slowly, with a half-life of 20.4 years at pH 7.25, and slower with larger particle size (Ludwig and Casey, 1996). A study of Ni species in a smelter-contaminated soil at Port Colborne, Ontario found particles of NiO remaining in the soil more than 30 years after smelting ceased (McNear et al., 2007). They also found that Ni-LDH had formed in these soils over time, confirming the practical significance of Ni-LDH formation in contaminated soils. Ni-sulfides deposited on soils can be oxidized by microbes. Other Ni phases enter into equilibria with soil sorption surfaces and ligands. Much soluble soil Ni2þ is chelated or complexed, but the free ion shuttles among sites based on free energy and binding site specificity. As shown in Fig. 2, grasses suffer an unusual symptom of Ni-induced Fe deficiency chlorosis in which the severity follows a diurnal pattern (banded chlorosis). Phytosiderophores (PSid) are secreted by young grass roots to dissolve soil Fe, and the Fe-PSid is absorbed by a transport protein specific to the Fe-PSid. At low pH Ni fills the PSid and can push Fe out by competition, but during the morning pulse of PSid secretion, some Fe is dissolved and absorbed so part of the growing
Grasses PSid
Chelated to organic matter humics and fulvics
Adsorbed on Fe/Mn oxides
Occluded in Fe/Mn oxides
FeOx
Plant shoots
Plant roots
Soil solution Ni2+ + L
NiL
Inorganic solids Ni(OH)2 NiO
L = ligands organic inorganic Soil microbes
Ni-silicate Ni-Al-LDH
Figure 1 Equilibria of Ni in soils in relation to uptake by both dicots and grasses; note formation of Ni-Al-LDH and Ni-silicate over time which reduces Ni phytoavailability. PSid are phytosiderophores such as deoxymugineic acid secreted by wheat to chelate soil Fe.
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Oat
Barley
Ni toxicity symptoms in oat and barley seedlings.
Figure 2 Unique symptoms of Ni-induced Fe deficiency (Ni-phytotoxicity) with diurnal variation in severity which results from Ni preventing Fe-phytosiderophore formation in the rhizosphere except during morning pulse secretion of phytosiderophore by young grass roots.
leaf blade receives Fe before it emerges from the culm. As pH is raised, Ni is bound increasingly strongly by soil sorbents, and forms new solids (Ni-LDH, Ni-silicates) such that insufficient Ni remains reactive to compete for filling the PSid in the rhizosphere (Kukier and Chaney, 2004). Simply making soils calcareous can remediate Ni phytotoxicity potential for species which are very sensitive at acidic pH (Siebielec et al., 2007). Interestingly, Cu is more bound by organic matter than Fe and Mn oxides, nor does it form LDH compounds in soils, so as pH is raised and Fe is less available for chelation by PSid, Cu inhibits Fe uptake in a simple Fe deficiency pattern (Michaud et al., 2007) rather than the banded chlorosis caused by Ni and Co. Zn forms LDH compounds, and is readily converted to lower phytoavailability forms in soil, so that making a high Zn soil calcareous with reasonable soil fertility remediates Zn phytotoxicity to sensitive plants (Li et al., 2000). Unfortunately, others followed the toxicological approach to establish limits for soil Ni, by adding soluble Ni salts followed by immediate cropping, failing to correct for the metal salt-induced drop in soil pH (Speir et al., 1999) resulting in exaggerated soil solution Ni concentrations (Oorts et al., 2006; Rooney et al., 2007; Thakali et al., 2006). Yet others studied nutrient solutions but did not understand basic metal chelate equilibria in nutrient solutions and observed apparently higher toxicity at higher pH (Weng et al., 2003), in strong contrast with the real world (Kukier and Chaney, 2004; Siebielec et al., 2007). McNear et al. (2007) examined the
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speciation of Ni in Welland loam and Quarry muck soils around a refinery and relate these findings to Ni mobility and bioavailability. XAFS and X-ray fluorescence (XRF) showed that Ni–Al LDH phases were present in both the limed and unlimed mineral soils, with a tendency toward more stable Ni species in the limed soil, possibly aided by the solubilization of Si with increasing pH. Precipitation of some mineral phases in wetland sediments can potentially limit metal bioavailability through sequestration in low-solubility compounds, such as metal sulfides. Analysis of XAFS data confirmed that sulfide compounds dominated zinc speciation throughout the sediment in a study by Peltier et al. (2003). Uptake of trace metals in Phragmites plants was limited primarily to plant roots, while concentrations of both Pb and Zn in other aquatic vegetation were significantly elevated, representing a potential bioaccumulation hazard and possible food-chain transfer concern for local wildlife. Another example of synchrotron research to understand plant uptake of contaminants was conducted by Punshon et al. (2005). Synchrotron XRF (S-XRF) demonstrated changes in Ni and U distribution in wheat grown on contaminated soil and the distribution of Ca, Mn, Fe, Ni, and U in roots of willow growing on a former radiological settling pond, with U located outside of the epidermis and Ni inside the cortex with confirmation by microtomography. Further, XRF and XANES linked the elevated Se concentrations in sediments of a coal fly ash settling pond at the site with oral deformities of bullfrog tadpoles.
2.3. Risks to soil organisms Toxicity to soil microbes and fauna has received much study, but often the methods used suffered from serious artifacts much as noted earlier for phytotoxicity. Addition of metal salts to soils is even more inappropriate in study of soil organisms because the organism receives the shock of soluble added elements rather than the metals equilibrated with the soil. Complexes of the metals with anions can cause persistence of soluble ions, and high rates of metal cations can drive pH several units lower greatly increasing soil metal solubility. The effects of diverse soil properties on metal toxicity to earthworms are considered by Lanno and Basta (2003), Bradham et al. (2006), and Dayton et al. (2006). In addition, remediation of phytotoxicity is often successful for remediation of toxicity to soil microbes and fauna (Brown et al., 2004, 2005, 2007; Conder et al., 2001). As we have noted, when metals are present at phytotoxic levels, the recommended remediation treatment would be to make the soil calcareous to minimize metal phytoavailability and provide a persistent remediation. Because these treatments give lower and lower metal bioavailability over time, it generally provides effective protection of soil
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organisms. And consumers of soil organisms appear to be protected except for soil ingestion risks (Pb, As, F) where earthworms can carry a high fraction of dietary soil into diets of earthworm consumers. Risks from soil Cd to earthworms and earthworm consumers have often been overestimated (Brown et al., 2002a,b). In estimating bioaccumulation ratios, one needs to take into account that the ratios are 10-fold higher for background uncontaminated soils than for contaminated soils. Predictions of risks to earthworm consumers have not been confirmed except for the case of a Cu–Cd smelter at Prescott, UK. Because Zn was not present with the Cd, earthworms accumulated high body burdens of Cd without injury that would have occurred from Zn in most contamination cases. In mine waste studies, Cd bioaccumulation was clearly limited by the presence of Zn (Andrews et al., 1984). Tolerance of soil microbes to metals is very complex, and traditional methods of study by adding metal salts to soils clearly confound the tests. Soils with deficient Zn have microbes which are less resistant to Zn additions than found in soils with Zn contamination. These findings led McLaughlin and Smolders (2001) to introduce the concept of ‘‘metalloregion’’ to suggest that some soils may be much more resistant to additions of Zn than other soils; that is, it would be an error to apply results from the most sensitive soil to all soils. Although it is clear that white clover rhizobium is relatively sensitive to excessive soil Zn, it is also very sensitive to simple soil acidity; causation in selection of ineffective nodulating strains was more affected by low soil pH than by soil Cd or Zn levels (Ibekwe et al., 1997). In our experience, sensitive plants are less resistant to excessive bioavailable soil metals than are the microbes in the soil, such that protection against phytotoxicity protects soil function.
3. Biological Metal Uptake 3.1. Risks through soil ingestion For selected elements, the element in ingested soil can comprise a risk to animals or humans and is especially well studied for Pb and As, but also considered important for F, Hg, and other elements. Soil ingestion circumvents the soil-plant barrier whereby limited plant uptake limits significant exposure. In soil ingestion, an element must have sufficient bioavailability/ solubility that it can be absorbed in the intestine to a greater extent than if garden foods growing on the soil were consumed. It has been recognized for decades that Pb deposited on the outside of forages can cause adverse effects in grazing livestock. Then, as risks from Pb in the urban environment were studied in more detail, it became apparent that Pb-rich exterior soil and dust can be carried into homes and provides
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exposure to young children who do not play outdoors. And that Pb paint dust ingested by hand-to-mouth transfer could be the important pathway for Pb exposure. Additional research eventually showed that interior paint Pb comprised far greater risk than soil Pb (Lanphear et al., 1998). But a key learning was that soil Pb was a greater risk through soil ingestion than through uptake by garden food crops (Chaney and Ryan, 1994). Pb uptake by plants can occur, but uptake of equilibrated soil Pb is small; soil adhering on low-growing crops is a more important source of Pb risk than is Pb uptake by plants. Gardening in urban soils is a difficult issue; if gardeners avoid growing low-growing leafy and root vegetables, and take care to exclude soil from their homes, gardening can be a safe practice until soils exceed levels, which comprise a clear risk by soil/dust ingestion. Soil Pb became a worrisome source of risk to children because Pb has become widely dispersed in urban soils (Mielke et al., 1983, 2007) as well as at industrial and DOD sites. Paint, building demolition dispersing interior paint (Farfel et al., 2005a,b), stack emissions, and automotive exhaust emissions contributed to urban soil Pb loadings. Center city soils are considerably more contaminated than suburban soils, although exterior Pb-paint scrapped to soil can cause massive soil contamination wherever it occurs, easily causing soil to exceed 10,000 mg Pb kg 1.
3.2. How much soil do children ingest? Several studies have been conducted to estimate soil ingestion by young children. Some investigators measured soil on hands of children and how long after starting play it took for their hands to become contaminated. The most widely accepted estimate of chronic soil ingestion by young children were reported by the team of Calabrese, Barnes, and Stanek at University of Massachusetts. They used ICP-AES and later ICP-MS to measure tracer elements in feces of children recovered from diapers. They analyzed diets to allow correction for dietary intake of elements, and provided toothpaste low in Ti so that fecal Ti might measure soil. Over time, they discovered that some of the elements they originally used as tracers were present at lower levels in the fine soil fraction (<250 mm) than in bulk soil (<2 mm), and thus they had to reassess their whole calculation method (Calabrese et al., 1996; Stanek et al., 1999). In the end, the data for two populations they investigated are reported by Stanek et al. (2001). These final estimates of the distribution of soil ingestion by young children are considerably lower than the original estimates (final median ¼ 24 mg d 1; SD ¼ 16 mg d 1; 95th percentile ¼ 91 mg d 1. These data were the original source of information for the development of the 200 mg soil d 1 assumed soil ingestion by children used in Superfund Risk Assessment. The original estimate (based on 2 mm soil, and a different set of elements than used in later estimates) is
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now known to be an overestimate of high end normal soil ingestion by exposed children.
3.3. Food-chain transfer and risks Plant uptake is essentially the inverse of leaching, with further limitation by plant processes and tissue barriers to element transport. Chaney (1980) introduced the soil–plant barrier concept to describe why nearly all animals are protected from food-chain transfer of nearly all elements in soils. Most elements are so insoluble or so strongly adsorbed in soils or in plants roots that they do not reach plant shoots in levels, which comprise risk to highly exposed individuals. Examples include Au, Ag, Hg, Pb, Cr3þ, Ce, Sn, Ti, Zr, etc. Another group of elements does not comprise food-chain risk because they are phytotoxic to plants before the concentration in the plant comprises risk to consumers; Zn, Cu, Ni, Mn, F, and As are included in this group. One key group does comprise potential risk to ruminant livestock consuming forages grown on alkaline soils: Mo and Se. Both of these elements are less strongly adsorbed in alkaline soils, so that if the alkaline soil is Mo or Se enriched, plants may accumulate higher concentrations. Under worst case conditions, plants accumulate high levels without suffering phytotoxicity, and ruminant livestock are sensitive to Mo. Excessive Mo intake inhibits absorption or use of Cu in ruminants. Cu deficiency has commonly occurred when forages contained excessive Mo. The Mo case is focused on ruminants because monogastric animals are much less sensitive to dietary Mo. Plants are essentially insensitive to Mo at levels which are already toxic to ruminants. Soil and biosolids Mo risks were reviewed by O’Connor et al. (2001) and a limit of 40 mg Mo kg 1 dry biosolids suggested as a regulatory limit. This suggested limit considered the mixture of grass and legume crops normally consumed by ruminants, and the usual mixture of feedstuffs provided by producers, and that forage production on an alkaline soil which promoted Mo uptake also promotes Mo leaching over time which reduces Mo risks. McBride and Cherney (2004) considered this much Mo in biosolids to be a significant risk but focused on feeding legumes only, a ridiculously impractical diet, and assumed all feed was grown on alkaline soils enriched in Mo. Ruminants must be kept on the high Mo diet for some months to deplete body Cu reserves before an actual adverse effect occurs, and simple Cu supplementation counteracts the Mo toxic effect. Se is potentially toxic to both monogastrics and ruminants, but because the leaves contain higher concentrations than grain or other storage tissues, grazing livestock are usually the most sensitive to excessive bioavailable soil Se. Under rare conditions, humans have suffered Se toxicity when normal crops could not be grown due to inadequate rainfall and the alternative food crops accumulated higher Se than the usual food crop, such as rice (Yang et al., 1983).
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The principal exception to protection of humans by the soil–plant barrier is Cd. Cd can be accumulated by plants to levels that harm animals which chronically ingest the crops. Longer-lived animals are at greater risk, and humans have experienced Cd disease from crops grown on contaminated soils (Reeves and Chaney, 2008). Another possible exception is Co which can be accumulated to about 25 mg kg 1 before phytotoxicity is evident, but ruminant livestock can tolerate only about 10 mg kg 1 in chronic diets. No case of food-chain Co toxicity to cattle or sheep has been reported perhaps because Co contamination is so rare. Cd has caused renal tubular dysfunction and osteomalacia in farm families who ingested rice for decades from fields contaminated by mine and smelter discharges of Zn and Cd. The osteomalacia effect, ‘‘itai-itai’’ disease with repeated bone fractures, has occurred at several locations but in only a small fraction of the population with severe renal tubular disease. Thus, renal tubular dysfunction is the first adverse effect which must be prevented by regulatory controls. Other possible adverse effects of dietary Cd have been suspected, but not observed. Chaney et al. (2004) and Reeves and Chaney (2008) have discussed the key role of Zn, Fe, and Ca deficiency in subsistence rice diets which promote human absorption of Cd. These nutritional deficiencies due to subsistence rice diets are a significant international malnutrition problem for which agronomists and nutritionists are seeking rice cultivars with improved grain bioavailable Fe and Zn to prevent widespread adverse effects (Graham et al., 2007). A paper by Reeves and Chaney (2004) showed that the kinetics of Cd movement through the intestine was significantly altered in rats with marginal Fe, Zn, and Ca diets such that net Cd retention was increased 10-fold compared to rats with adequate nutrition. Growing rice in flooded soils, but draining the soil at flowering to improve yields allows CdS formed during flooding to be oxidized and Cd (but not Zn) to be readily absorbed and translocated to grain. In soils with the normal geogenic ratio of Cd to Zn (about 1 mg Cd per 200 mg Zn), and crops other than rice, Zn inhibits Cd uptake by the crop and reduces the bioavailability of Cd in the crop. No adverse Cd effects have been shown for agricultural food-chains other than subsistence rice. Biosolids can increase both Cd and Zn in crops such that when Cd in Swiss chard was increased fivefold, no increase in kidney or liver Cd occurred in guinea pigs fed the chard (Chaney et al., 1978b); while high increase in lettuce Cd from a high Cd:Zn ratio biosolids caused large increase in kidney Cd (Chaney et al., 1978a). Interestingly, Cd in spinach was significantly less bioavailable than Cd in lettuce to Japanese quail or rats consuming these foods (Buhler, 1985), and increased plant Zn significantly reduced retention of plant Cd by quail (McKenna et al., 1992). Oysters accumulate high levels of Cd, but also accumulate Zn and Fe which reduce risk from Cd in shellfish. A few sources of Cd are of especially high potential risk, those without normal Zn cocontamination (Ni–Cd
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batteries, Cd pigments, Cd plastic stabilizers, Cd plating wastes, Cd–Cu smelter emissions). Failure to find Cd-induced renal tubular dysfunction at a number of sites (UK, US, Germany, and France) where smelter emissions or mine wastes have caused garden soils to contain 100 mg Cd and 10,000 mg Zn kg 1, while finding 80% incidence of renal disease in older persons ingesting home-grown rice, highlights the role of rice diets increasing dietary Cd bioavailability in human risk (reviewed in Chaney et al., 2004). Consuming threefold normal daily Cd intakes from shellfish diets did not increase blood Cd in Swedish young women (Vahter et al., 1996), nor did consumption of high amounts of high Cd oysters by New Zealand residents cause Cd disease (McKenzie-Parnell and Eynon, 1987; Sharma et al., 1983). Several northern European populations have been reported to possibly suffer adverse effect of dietary Cd at much lower dietary Cd, blood Cd, and urinary Cd (Buchet et al., 1990; Ja¨rup et al., 2000) than other populations without identified adverse Cd effects (Ikeda et al., 2003). These reports are not explicable in terms of known aspects of Cd metabolism, and remain debated among scientists.
4. Metal Extractability to Predict Availability 4.1. In vitro bioaccessibility As mentioned, one of the major exposure pathways of heavy metals to humans is through the incidental ingestion of soil. This is of special concern for children due to their increased hand-to-mouth activity and enhanced pharmacokinetics. The availability of metals to the target organism is a function of many factors, including the way in which the contaminant is held within the soil matrix and the source of the contaminant. These concerns have driven the development of in vitro bioaccessibility assays which introduce a soil sample to a reaction environment similar to that of the human GI system to mimic bioavailability and typically under worst case situations (i.e., fasting conditions, low pH, etc.). However, often overlooked in the scenario for incidental soil ingestion is the way in which the human (animal) GI system treats a contaminant in either a synergistic or antagonistic manner. The first step for in vitro studies is to determine the ‘‘total’’ metal content of a particular sample. However, what researchers call ‘‘total’’ and what is total can be two distinctly different numbers. Whether using EPA Method 3050B (Acid Digestion of Sediments, Sludges, and Soils) or EPA Method 3051A (Microwave Assisted Acid Digestion of Sediments, Sludges, Soils, and Oils) (see http://www.epa.gov/epawaste/hazard/testmethods/sw846/
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online/index.htm) it is important to realize that these methods are not intended to accomplish total decomposition of the sample and the extracted analyte concentrations may not reflect the total elemental content in the sample. However, these methods will dissolve almost all elements that could become ‘‘environmentally available.’’ For total decomposition of soil samples, EPA Method 3052 (Microwave Assisted Acid Digestion of Siliceous and Organically Based Matrices) is the most appropriate method, but unfortunately requires the use of hydrofluoric acid that often turns into a health and safety nightmare. Regardless, after extraction for any of the methods mentioned earlier or with a number of other methods (i.e., aqua regia), the next step is the proper use of either atomic absorption (AA) or inductively coupled plasma (ICP) spectrometries to determine the concentration of select elements in solution with back calculations to resolve the amount of each element extracted from the solid sample. As one can imagine, there are many opportunities for analytical errors in just doing the extraction and measuring solution concentration for ‘‘total.’’ Further, the combination of options for extraction (acid digestion methods) and measuring solution concentration (AA vs. ICP) illustrates the lack of consensus in determining ‘‘total’’ metal concentration meaning that the same soil sample analyzed by different groups utilizing different extraction and measurement methods likely produce different values. And, we have not even discussed the in vitro extraction methods yet! However, determination of ‘‘total’’ metal concentration is vital for in vitro extraction studies in order to determine bioaccessibility: Bioaccessibilityð%Þ ¼
Amount of in vitro metal extracted 100 ‘‘Total’’ amount of metal in soil
It is worth noting that there are several ‘‘total’’ digestion methods available outside the EPA methods mentioned earlier. Another point to be made is that total concentrations can be achieved without chemical extraction via analytical instrumentation. Two examples are XRF spectroscopy and neutron activation analysis (NAA). XRF determines the presence and concentration (but not speciation) of elements in various materials by measuring the intensity of X-ray emission energy of a sample that has been probed with a high-energy X-ray source. XRF is rapid, accurate, and usually nondestructive to samples. XRF instruments are modestly priced meaning if a research team is seeking total elemental concentrations on a regular basis, the investment may be worthwhile. NAA is also a direct elemental analysis method that does not require sample decomposition. In this method, the soil sample is introduced into the intense radiation field of a nuclear reactor and is bombarded with neutrons, causing the
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elements to form radioactive isotopes. The emissions of the produced radioisotopes are used to quantify the elemental. Elemental analysis by NAA is available from select commercial laboratories and is inexpensive. It is highly desirable to confirm elemental content determined using acid soil decomposition methods (i.e., EPA Method 3050B, 3051A) with nondestructive methods (i.e., XRF and NAA). The second step for in vitro studies is to determine which in vitro method to employ. Several in vitro tests will be mentioned throughout this chapter and many countries are pushing to develop validated models for regulatory purposes. Highlighted earlier, extensive global progress has been made in development of soil Pb and As in vitro bioaccessibility methods, yet great effort has been wasted in planning inconsequential research efforts to develop bioaccessibility methods, which try to match all digestion processes. Keep in mind that in vitro tests are empirical and nonmechanistic so there is no real meaning behind the number gained from the study—it is just the amount of metal that could be extracted under the kinetic and thermodynamic constraints of a particular test’s parameters. Because in vitro methods are only a simulation of the human GI tract and not the real conditions, we feel the simpler, less expensive, and statistically robust the in vitro method can be made, the better, as long as the correlation with an acceptable bioavailability model is high. Occam’s razor, Entia non sunt multiplicanda praeter necessitatem or ‘‘Entities should not be multiplied unnecessarily’’ should be adopted when selecting in vitro methods. Occam’s razor should be used to ‘‘shave off’’ unnecessary procedural steps that do not improve the correlation between in vitro bioaccessibility and in vivo bioavailability. Further, these tests must be reproducible in laboratories across the globe (not only in the testing method itself but in the analytical equipment employed), which has not been the case for many of the in vitro bioaccessibility methods available today. While in vitro tests have been available for many years to examine nutritional issues, the bulk of the work to investigate and develop in vitro tests for contaminated soil bioaccessibility was started in the 1990s. Some of the initial and most validated tests involved a simple stomach phase extraction that utilized a glycine buffer solution and acidification with HCl to a desired pH (Drexler and Brattin, 2007; Medlin, 1997; Ruby et al., 1993). Typically, the extraction involves 1.0 g of soil added to 100 mL of glycine buffered solution (0.4 M). The pH is set at 1–2.5 and the temperature at 37 C in a rotary water bath for 1 h. A solution sample is taken after filtration through a 0.45 mm filter for AA or ICP analysis. The basis of the test has evolved as needed; primarily readjustment of solution pH to improve in vivo correlation but the test has been shown to work well for Pb in contaminated soils. Similar in vitro procedures have been correlated with bioavailable As determined using the juvenile swine model (Basta et al., 2007a; Rodriguez et al., 1999). This method, the Ohio State University in vitro gastrointestinal
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(OSU IVG), does not use a buffered gastric solution but pH is maintained at 1.8 and includes a subsequent small intestinal extraction. Some in vitro tests are significantly more comprehensive and complex. The TNO gastrointestinal model (TIM) (see http://www.tno.co.jp/ Pharma/TIM.pdf ) is a dynamic model and experimental apparatus that simulates transfer through the GI tract which monitors/adjusts the gastric and intestinal pH profiles and secretes digestive juice over time at computer regulated intervals (Minekus et al., 1995). It is a well-validated instrument for pharmaceutical testing and demonstrated highly accurate and predictive. While definitely more cost effective than in vivo studies, the cost is significant in comparison to simple in vitro one-step extractions, but the precision and reproducibility may offset that disadvantage. The biggest disadvantage of the TIM method is time in which over 6 h and numerous experimental steps are dedicated to one sample. The members of the BioAccessibility Research Group Europe (BARGE) have worked to develop the unified BARGE in vitro method (UBM). A founding member of BARGE, the National Institute for Public Health and the Environment (RIVM, the Netherlands), has performed research on bioaccessibility of oral ingested soil contaminants and, after consideration, the RIVM in vitro method was selected with key adaptations. The RIVM in vitro method is innovative in that it contains procedures for both fasted and fed conditions. There has been much discussion on the use of fasted and fed models and in the example of which mode represents the worst case scenario of biological uptake, each approach is metal dependent. Lead has been clearly shown to be most bioavailable under fasted conditions (Schroder et al., 2004) particularly in diets low in Ca and P. Likewise, recent research has shown that fed conditions represent higher bioavailability and bioaccessibility for arsenic (Basta et al., 2007a,b) likely due to competition of phosphate and other oxyanions with arsenic. To illustrate the complexity of multi-step in vitro procedures, below are the full details of the RIVM in vitro method for fed and fasted examination (Oomen et al., 2006): Fed conditions: The in vitro digestion starts by introducing 0.04–0.4 g of soil (dry weight) to 6 mL stimulated saliva (pH 6.8 0.2) and 4.5 g infant formula (product number 282, Olvarit (NutriciaÒ , the Netherlands), supplemented with 2 mL sunflower oil per 100 g). Immediately, 12 mL of stimulated gastric juice (pH 1.30 0.02) is added and the mixture is end-over rotated (55 rpm) for 2 h. The pH of the gastric fluid is determined with an allowed interval of 2.5 0.5. Next, 12 mL stimulated duodenal juice (pH 8.1 0.2), 6 mL stimulated bile (pH 8.2 0.2), and 2 mL sodium bicarbonate (1 M) are added simultaneously. The mixture is rotated for another 2 h and the pH of the chyme (the semifluid mass of partly digested food expelled by the stomach into the duodenum) is determined, with the allowed pH interval 6.5 0.5. Separation of chyme and pellet is obtained
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by centrifugation at 3000 g for 5 min. The whole process is performed at 37 2 C. Samples can be taken from the stomach and intestinal phase to obtain information on the bioaccessibility of the contaminant. Fasted conditions: The in vitro digestion starts by introducing 9 mL of saliva of pH 6.5 0.2 to 0.06 or 0.6 g of soil (dry weight). This mixture is rotated end over end for 5 min at 55 rpm. Next, 13.5 mL of gastric juice (pH 1.07 0.07) is added, and the mixture is rotated for 2 h. The mixture of saliva and gastric juice has a pH of about 1.2, and the allowed pH interval in the presence of soil is 1.5 0.5. Finally, 27 mL of duodenal juice (pH 7.8 0.2) and 9 mL bile (pH 8.0 0.2) are added, and the mixture is rotated for another 2 h. The allowed pH interval for this step is 6.0 0.5. Mixing is done in a rotator that is also heated to 37 2 C. The end step requires the digestion tubes centrifuged for 5 min at 3000 g, yielding the chyme (the supernatant) with and the digested soil (the pellet). Chemical analysis: For determining metal concentration in chyme, 0.9 mL chyme is diluted 10-fold with 8.1 mL HNO3 (0.1 M). For determination of metal concentration in gastric juice, 0.1 mL of gastric juice (stomach compartment) is diluted with 8.9 mL HNO3 (0.1 M). If necessary to destruct pellets, the pellets of the in vitro model are dissolved by aqua regia. Finally, the metal concentration is measured by ICP-MS. Numerous single- and multi-step in vitro models exist. Under ideal conditions, the scientific community would unify behind one test for each element so that consistent and reproducible results could be shared. Unfortunately, site risk assessment is a viable financial endeavor for consultants and contractors; so vigorous promotion of self-developed in vitro models is observed. In order for the model to be accepted by a regulatory agency, the model must be validated against in vivo data that is inclusive of various soil types, various contamination sources, and soils relevant to the intended target organism. For example, we accomplish very little in validating a human bioaccessibility in vitro model for five samples from one human-isolated mining site with 50,000 mg Pb kg 1; such a model is of no use for a high population urban environment contaminated with 1000 mg Pb kg 1 from leaded gasoline and lead-based paint since the model was not validated with these types of soils, sources, and levels of contamination. Validation cannot be emphasized enough to ensure that an in vitro model has a basis to support in vivo bioavailability. Oomen et al. (2002) demonstrated very clearly the variability that can occur with in vitro assessment of metal-contaminated soils via a round robin, a multi-laboratory comparison and evaluation of five in vitro digestion models. A wide range of bioaccessibility values were found for the three soils examined (As 1–95%, Cd 5–99%, and Pb 1–91%) by the five in vitro tests. The authors determined that the variability in values was attributed to solution pH in which some tests only utilized a low pH stomach phase to produce elevated release while
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others used a higher pH intestinal step to provide lower bioaccessibility sums. Missing in all of this work were actual in vivo animal results to determine which in vitro test was accurate to describe actual bioavailability. Several methods, including the relative bioaccessibility leaching procedure (RBALP) of Drexler and Brattin (2007) for Pb and the OSU IVG for As (Basta et al., 2007a), have met the USEPA requirement that an IVG method used for human health risk assessment must be correlated with an acceptable in vivo model (USEPA, 2007a). However, these soils in vitro methods were developed using soils contaminated with mining wastes. The ability of these and other in vitro methods to predict bioavailable Pb and/or As in soils contaminated from other sources (i.e., pesticides) should be evaluated. Accuracy and proper QA/QC controls are essential for in vitro studies. There are many opportunities to introduce error into in vitro methods. Whether by incomplete balance transfer of milligram-sized soil samples to beakers or nonmatrix matched standards for AA or ICP analysis, analytical error is an unexplored and devastating issue for in vitro research particularly when the push is to be faster and cheaper.
4.2. Common soil extractions to predict risk of phytotoxicity or food-chain risk Many soil extraction tests have been developed to assess phytoavailability of soil elements, especially nutrients required for maximum plant yields. These tests are commonly conducted in most countries in usual agricultural crop production. The key factor in development of such tests was that the extraction result was highly correlated with the potential for economic yield response to fertilizer applications. One of the requirements of a successful soil test (one where plant response is correlated with nutrient extracted by the soil test) is that the soil test measures ‘‘some or all of the (phyto)available pool’’ (Bray, 1948). Soil extraction methods correlated with plant uptake of trace element include those based on solutions containing chelates, such as diethylenetriaminepentaacetic acid (DTPA), and neutral salt solutions (CaCl2). The extensive use of such methods to estimate trace element availability in residual-treated soils has been reviewed by McLaughlin (2002) and Pierzynski (1998). In recent years, mechanistic tests are preferred for estimation of element uptake, but the key to adoption of any method is the correlation with the potential for phytotoxicity or excessive plant uptake, or correction of deficiency due to element levels in soils. Extractions such as the DTPA-TEA method (Lindsay and Norvell, 1978) have become widely adopted in its original form, or as modified for analysis of even more elements as the DTPA-NH4-bicarbonate extraction (Soltanpour, 1985).
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Several authors have illustrated that chelation methods can become saturated and thus underestimate phytoavailable element levels in soils (Kukier and Chaney, 2000; Li et al., 2000). In our experience, neutral salt noncomplexing solutions can predict plant relevant Zn and Ni uptake across soils and soil pH (e.g., 0.01 M Sr(NO3)2 at 10 g soil/20 mL, Siebielec et al., 2007). Soil extraction with dilute Ca(NO3)2 solution is correlated with plant uptake of Cd (Basta and Gradwohl, 2000). The presence of chloride rather than a noncomplexing anion such as nitrate necessarily increases extractability of metals which can be complexed by chloride; whether that is useful or a problem lies in the eye of the beholder. Using high levels of CaCl2 in extractions increases dissolved metals and makes measurements easier, but may give a false picture of the relative phytoavailability of several elements in the soil sample. In the last few years a new soil testing strategy has been tested, the DGT (diffusive gradients in thinfilms) method (Davison and Zhang, 1994; Lehto et al., 2006). Although this may give significant correlations with plant uptake, it takes considerably longer and costs much more than simple neutral salt extraction methods. A problem with mild extraction methods is the low concentration of analyte present in the extract. If it takes an ICP-MS to be able to make useful measurements, a method is of lesser utility than a method which can use ICP-AES or AA methods. On the other hand, when a method integrates metal phytotoxicity over soils and soil pH levels, so that the instantaneous phytotoxicity potential of that soil for a specific plant species can be estimated, it is a powerful method for risk assessment (Siebielec et al., 2007).
5. Metal Chemistry 5.1. Metal equilibrium in soils Each element has its own dynamic equilibrium chemistry in soils in relation to solid mineral phases, soil solution chemistry, exchangeable ions and surface adsorption, nutrient uptake by plants, soil air, organic matter and microorganisms, and water flux. A good summary of soluble element speciation in soils is provided by Langmuir et al. (2005). If the element is only weakly bound by a soil, it may be leached through the soil to impact ground water. Considering pH and element chemistry, the monovalent anions and cations are usually leachable. Divalent anions such as sulfate are readily leached, while selenate, molybdate, tungstate, and some others are only leachable at alkaline pH; at acidic pH, these elements can be sorbed well by Fe and other sesquioxides.
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Arsenate is sorbed well at acidic pH and precipitated as a Ca mineral at higher pH. Arsenic has become a subject of greater concern in recent years as the acceptable intake level for humans was lowered. Human As poisoning has been recognized from contaminated drinking water (millions of humans are exposed to excessive well water As in Bangladesh), but never observed in humans from ingested soil or crops. Crop accumulation of As is weak, and translocation to edible crop tissues even lower. In aerobic soils, As is present as arsenate, but upon soil reduction, arsenite is generated. Arsenite is much less strongly adsorbed by soil surfaces, so root uptake and phytotoxicity are greater in crops grown in anaerobic soil. That is essentially rice. Further, when rice is grown in flooded soils, accumulation of As and transport to grain is higher than when rice is grown in drained or upland soil conditions (Xu et al., 2008). Meharg et al. (2008) used synchrotron X-ray fluorescence spectroscopy to locate arsenic in polished (white) and unpolished (brown) rice grains from the United States, China, and Bangladesh. In brown rice As was found to be preferentially localized at the surface, in the region corresponding to the pericarp and aleurone layer. Copper, iron, manganese, and zinc localization followed that of arsenic in brown rice, while the location for cadmium and nickel was distinctly different, showing relatively even distribution throughout the endosperm. The localization of As in the outer grain of brown rice was confirmed by laser ablation ICP-MS. Arsenic speciation of all grains using spatially resolved micro-X-ray absorption near-edge structure (m-XANES) and bulk extraction followed by anion exchange HPLC-ICP-MS revealed the presence of mainly inorganic As and dimethylarsinic acid (DMA). It is believed that arsenate is absorbed by plants through a phosphate permease of the roots (Zhao et al., 2009); further, added phosphate competes with arsenate for adsorption by soil oxides, and added phosphate can increase soluble arsenate temporarily to phytotoxic levels (Peryea, 1998). Soil organic matter, pH, and clay content are soil chemical properties that influence metal bioavailability and toxicity to ecological receptors (i.e., earthworms and plants). A comprehensive study of 21 natural soil types, multiple contaminants and multiple plant and earthworm endpoints were conducted to determine the simple and combined effects of soil chemical properties on metal bioavailability and toxicity (Lanno and Basta, 2003). Soils were selected to produce a combined range of soil pH, organic C content, CEC, reactive Al and Fe oxide, and clay content (Lanno and Basta, 2003). In this novel approach, soil type not contaminant concentration, was the driver to produce a range of metal bioavailability and exposure doses. Metal bioavailability and toxicity were determined using 28-day bioassay using mature earthworms (Eisenia andrei) and lettuce bioassays (Lactuca sativa cultivar Parris Island Cos). Soil properties greatly affected metal bioavailability (Lanno and Basta, 2003). Lettuce tissue Pb ranged from 3.22 to 233 mg Pb kg 1 and relative dry matter growth ranged
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A
7 Dry matter growth (DMG) [1.91, 0.13-6.44 (g)]
6 5 4 3 2 1 0 B 100
Relative dry matter growth (RDMG) [31.8, 2.47–88.5 (%)]
80 60 40 20 0 C 250
Lettuce tissue Pb [63.8, 3.22–233 (mg/kg)]
200 150 100 50 0
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Figure 3 Range in lettuce biological endpoints for lettuce grown in Pb spiked (2000 mg Pb kg 1) soils. Numerical values in figures are (means, range(units)) (Dayton et al., 2006).
from 2.5% to 88.5% of their respective controls (Fig. 3; Dayton et al., 2006). Similarly, soil type greatly affected metal bioavailability and toxicity to earthworms. Earthworm mortality ranged from 0% to 100% acute mortality following exposure to the same total concentration of Pb (2000 mg kg 1) in
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amended field soils. Internal Pb concentrations in earthworms ranged from 28.7 to 782 mg kg 1, with a mean of 271 mg kg 1 (Bradham et al., 2006).
5.2. Metal speciation in soils Since soils are usually in pseudo-equilibrium, the common soil factors of pH, soil sorbent phases, soil organic matter, soil redox potential, etc., dictate the form or speciation of a contaminant at a given point of reference. In the context of conducting research to understand the role that metal speciation plays in bioavailability and resulting remediation to eliminate biological availability, there are many tools available to decipher pieces of the total puzzle. In some instances, the human eye can clearly identify the impact of metals at a contaminated site. From this standpoint, researchers can collect representative samples for macroscopic and microscopic laboratory examinations as well as develop field plots to investigate the characteristics responsible for the negative impact of metals. Soil samples taken to the laboratory can undergo an array of analyses including batch reactors to examine kinetics and thermodynamics of release; chemical extractions to determine total metal content, operationally defined speciation (sequential extractions), bioaccessibility (to mimic human bioavailability), and instrument analysis to identify mineralogy and other fundamental properties of the sample. It is at this point where most evaluations are completed and it is determined that characteristics such as metal concentration, soil pH, iron oxide concentration, and soil organic matter are indicative of the dose– response paradigm. However, aside from knowing the total metal concentration, little is often known or determined with regard to the chemistry of the metal. This information is often inferred from the soil properties— which can be a valid approach—but often involves inconclusive guesswork through the use of sequential extraction procedures, elemental associations, or broad-based modeling efforts. To gain a more complete picture of the chemistry of metals, one must employs techniques that definitively determine the speciation (the true chemical form and physical coordination) of contaminants. There are several excellent spectroscopic methods capable of determining metal speciation but the most authoritative approach involves the application of synchrotron methods such as X-ray absorption spectroscopy (XAS). XAS distinguishes the oxidation state, coordination environment, interatomic bond distances, and identity of nearest-neighboring elements relative to a specific metal of concern. Information gained from XAS experiments provides an in situ look at the current chemical form of a metal and can be used to predict the long-term fate of the metal and its potential bioavailability based on known solubility products. The impact of metal speciation on risk assessment has gained much attention over the past couple decades and will continue to grow in acceptance as an important part in our understanding of metal bioavailability and remediation.
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XAS refers to the interaction of how X-rays are absorbed by an atom at energies near and above the core-level binding energies of that particular atom. XAS is the modulation of an atom’s X-ray absorption probability due to the chemical and physical state of the atom. XAS spectra are especially sensitive to the formal oxidation state, coordination chemistry, and the interatomic distances, coordination number and species of the atoms in the surrounding proximity of the selected element of interest. As a result, XAS provides a sound method to determine the chemical state and local atomic structure for a selected atomic species. XAS can be used in a wide variety of environmental samples. Since XAS is an atomic probe, nearly all substances can be studied. Crystallinity is not a factor for XAS measurements making analysis of noncrytalline material, disordered compounds, and solutions feasible and attractive. XAS is easily capable of detection sensitivities of a few parts per million with detector sensitivities improving rapidly. An important aspect from an environmental perspective is that XAS is an in situ spectroscopy allowing for the investigation of samples in their natural state. A typical XAS spectrum is broken into two regimes which include XANES and EXAFS (extended X-ray absorption fine-structure) regions that contain related, but slightly different information about an element’s local coordination and chemical state. X-rays are absorbed by all matter through the photoelectric effect which involves an X-ray being absorbed by an atom, promoting a core-level electron (K, L, or M shell) out of the atom and into a continuum. The electron ejected from the atom is called the photoelectron leaving the atom in an excited state with an empty electronic level (core hole). The excited atom will relax back to a ‘‘ground state’’ of the atom when a higher level core electron drops into the core hole resulting in the emission of a fluorescent X-ray or Auger electron. The intensity of an X-ray beam as it passes through a material of thickness, t, is given by the absorption coefficient, m: I ¼ I0 emt where I0 is the X-ray intensity hitting the material, and I is the intensity transmitted through the material. The absorption coefficient depends strongly on X-ray energy, E, and atomic number, Z, and on the density, r, and atomic mass, A: m
rZ 4 AE 3
In addition, m has sharp absorption edges corresponding to the characteristic core-level energies of the atom. All elements with Z > 15 have either a K-, or L-edge energies between 2 and 35 keV, which can be accessed at
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many synchrotron sources to examine environmentally relevant elements. Due to its need for high-energy X-rays, XAS data collection can only be accomplished with a synchrotron radiation source. There have been many studies of metal speciation in soils with synchrotron techniques but few have made direct connection to bioavailability or phytoavailability. As mentioned earlier, there have been a number of synchrotron studies that determined the speciation of metals in soils in which the authors conclude their results demonstrate or predict a reduction in bioavailability but provide no evidence (neither in vivo nor in vitro data) to substantiate the claim. As in all research, we must restrain ourselves to claim only what we can prove and that universal conclusions based on limited observations should be avoided. Below are some case studies of synchrotron research to understand metal bioavailability behavior in soils. One of the first synchrotron studies to link metal speciation and ecological bioavailability in contaminated sediments was conducted by O’Day et al. (2000) at the East Outfall Site of the Seaplane Lagoon at the former Naval Air Station Alameda (San Francisco Bay). The objective of the study was to assess the bioavailability of five metals (Cd, Cu, Pb, Ni, and Zn) for sand dollar embryos (D. excentricus) and adult amphipods (E. estuarius) using XAS with comparison to simultaneously extracted metals (SEM) to acid volatile sulfide (AVS). ItPwas proposed that if the ratio of the sum of SEM to AVS is greater than 1 ( SEM/AVS > 1) then there was a potential enhancement of metal bioavailability due to insufficient coprecipitation of the metals with P FeS. However, the results demonstrated that SEM/AVS was not a valid assumption P except in the case of Cd. Nontoxic responses were noted when SEM/AVS ranged from 2.7 to 5.25 and 100% toxicity was P documented when SEM/AVS was equal to 0.54 indicating that FeS was not the primary contributor to AVS extraction results. XAS speciation found that metal contaminants were present in the sediment matrix as both sulfide and oxide solid phases invalidating the assumption that the metals were controlled by iron monosulfide partitioning in sediments—a very P important point considering the many assumptions behind the SEM/AVS approach. This study illustrated the need for multiple tests to assess bioavailability processes in ecological receptors and that spectroscopic techniques can verify contaminant speciation to provide a molecular understanding for interpreting toxicity test results. Probably, the most comprehensive field study to link synchrotron metal speciation to human bioavailability was the research of Ryan et al. (2004) in the examination of Pb-contaminated soil treated with phosphate amendments to reduce Pb bioavailability as part of the USEPA’s In-Place Inactivation Natural Ecological Restoration Technologies (IINERT) Soil-Metals Action Team. In the study, Pb speciation via XAFS and XRF mapping, in vitro extraction at three solution pH values, and in vivo animal feedings to swine, rats, and humans were conducted on 12 different treatments at three
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different aging times. The objective of the study was to convert soil Pb to pyromorphite, a Pb phosphate mineral, which is extremely insoluble and, thus, presumed nonbioavailable. A linear trend was observed when comparing the amount of pyromorphite present in the soil samples determined by XAFS to the amount of bioaccessible Pb measured by the in vitro extraction method. It was demonstrated that in situ treatment can reduce soil lead bioavailability and this conclusion was also demonstrated for the in vitro data and its relationship to synchrotron speciation. Therefore, the study illustrated that the conversion of soil Pb to pyromorphite can be quantified by synchrotron speciation techniques to indicate increasing pyromorphite concentration translates into decreasing in vitro and in vivo Pb bioavailability. Further details on this study are discussed in the following sections.
6. Understanding Metal Bioavailability, Bioaccessibility, and Speciation 6.1. Lead 6.1.1. How much soil Pb is too much? Greatest risk from soil Pb depends on getting the soil into the area where it can be ingested by hand-to-mouth play and exploration by children. Growing children are very sensitive to excessive absorbed Pb, and absorb a higher fraction of dietary Pb than do adults. Epidemiologic studies in Pb-dust contaminated housing show that peak blood Pb in childhood occurs at about 18–24 months age, but that is still before children are allowed to play unsupervised in soil. Therefore, interior dust, paint dust, and soil/dust brought into the house must provide the Pb exposure which causes the bulk of excessive soil Pb absorption by children. This process was first proved when the clothing of Pb workers raised Pb levels in house dust and caused Pb poisoning of their children even though their housing did not have high Pb paints (Dolcourt et al., 1978). Although the focus here is on soil Pb, it must be recognized that paint Pb in a home is the much more likely source of high Pb levels in house dust and excessive Pb absorption in children. In several smelter town studies, for at least some of the children the majority of blood Pb came from paint rather than from soil or industrial dusts (Gulson et al., 2004). In the same token, industrial dusts emitted from smelters, or resuspended Pb-contaminated dust in an arid community readily recontaminates household dust and remain key sources of excessive blood Pb. In Trail, British Columbia, it was found that blood Pb dropped substantially when a new flash smelting technology was introduced which caused much lower Pb emissions, with a corresponding drop in house dust Pb (Hilts, 2003).
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For Pb absorption to occur, the chemical forms of Pb in the soil/dust must be absorbable when the soil is ingested. Research has shown that some Pb minerals are poorly absorbed by humans (PbS, chloropyromorphite (CP)), while some others are readily absorbed (PbCO3). Perhaps the most important factor in Pb absorption is the presence of food in the stomach/ intestine when the Pb source is present. Several research teams evaluated Pb isotope absorption by human volunteers fed Pb with meals or specific foods, or on fasting. On fasting, soluble Pb is absorbed at 50–80%, usually assumed by EPA to be 50% for Pb acetate. But when the Pb is ingested with a meal, 1 h before a meal, or up to 4 h after a meal, absorption falls to the range of 2–5% of dose (Heard and Chamberlain, 1982; Heard et al., 1983; James et al., 1985). Particular food ingredients ingested with Pb can greatly reduce Pb absorption, especially Ca (Blake and Mann, 1983); Ca is believed to compete with Pb absorption by a Ca-transport protein in the small intestine, but also to form coprecipitates with phosphate and Pb. Pb incorporated in kidney or spinach had quite low bioavailability to adults (Heard et al., 1983). One key learning in this area of science came from a test of soil removal and replacement. The USEPA conducted a congressionally supported test in three cities of whether removal and replacement of soil would cause a reduction in blood Pb in the children who lived there. The biokinetics of blood Pb in children versus exposure was considered, and it was believed that if soil Pb absorption by children was reduced for a year by the soil replacement, blood Pb should decline significantly if soil were contributing to the Pb which was being absorbed. Tests were conducted in three cities. Children who lived in areas where soils around houses contained at least 500 mg Pb kg 1 were identified and volunteers were assigned to early replacement and late replacement (at the end of 1 year, the second half of the population would have their soil replaced). Blood Pb was sampled before any changes were made, after the first half were replaced, and several more times until the end of the test. The children were randomly (of the general area where they lived) assigned to early or late replacement so it was a randomized test. In Baltimore (Farrell et al., 1998) and Cincinnati, soils which were replaced contained only about 500 mg Pb kg 1, and there was no significant reduction in blood Pb in the children. In Boston, children were assigned to early or late replacement as they joined the study; the soils replaced contained between 1800 and 2000 mg Pb kg 1; soil replacement included dust control post soil replacement to assure full removal of the exposure source that may have been stirred up during replacement; replacement plus dust control was compared with dust control alone versus absolute control, and soil replacement gave a small significant reduction in blood Pb at this high soil Pb level (Weitzman et al., 1993). The ‘‘late’’ replacement also gave a small significant reduction in blood Pb (Aschengrau et al., 1994): ‘‘The combined results from both phases suggest that a soil lead reduction of 2060 ppm is associated with a 2.25–2.70 mg dL 1 decline in
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blood lead levels’’ (from original mean level 12.8 mg dL 1). The most important finding, however, was that other sources (paint) had more important impact on blood Pb than did exterior soil. There was some evidence that the biokinetics of reduction of blood Pb were slower than anticipated, with the second year of reduced exposure yielding somewhat lower blood Pb than 1 year of reduction. As noted earlier, a meta-analysis of the contribution of soil versus house dust to blood Pb of urban children has shown that house dust was considerably more important (Lanphear et al., 1998). It was suggested that the proportion of exposure from soil versus house dust in the IEUBK model needed to be changed to reflect this improved knowledge, but that has not yet occurred. 6.1.2. Bioavailability of soil/dust Pb The earliest tests were conducted with rats (Chaney et al., 1984, 1989; Stara et al., 1973) and urban dust or garden soil samples with varied levels of Pb from the Baltimore, MD, area. An ARCO Coal Company led team investigated chemical speciation of Pb in Superfund soils, and tested the bioavailability to rats and rabbits. Several groups noted that Pb in mining site soils caused less increase in blood Pb than did Pb in smelter site soils (Steele et al., 1990). Davis et al. (1993) found galena and anglesite (PbSO4) with rinding in mine waste soils at Butte, MT. The dissolution of PbSO4 was found to be inherently slow compared to the time needed for clearance of the stomach and intestine of children, helping to explain why this form of Pb caused less uptake into blood. Mineral PbS or chemical PbS both had low bioavailability to rats (Dieter et al., 1993; Fig. 4) while extremely fine PbS formed by adding sulfide to a solution of Pb isotope was somewhat more bioavailable in fasting human tests (Rabinowitz et al., 1980). Thus, part of the lower risk of mining waste PbS has to do with particle size; very fine PbS in cosmetics is apparently more dangerous than PbS in soils. Freeman et al. (1993) conducted tests of methods to assess Pb bioavailability, and found that the usual one dose, area under the curve approach was not workable for environmental levels of Pb exposure. Gavage Pb acetate was absorbed very quickly and disappeared from blood quickly, while soil Pb caused only a small increase in blood Pb over several days. So they moved to a chronic feeding approach using purified diets. It had already been shown that using ordinary rat chow greatly reduced Pb bioavailability, but using the American Institute of Nutrition (AIN) purified diets for rats promoted Pb bioavailability (Mylroie et al., 1978). They fed several levels of two soils compared to Pb acetate (Fig. 5). A number of years later Superfund researchers decided to assess RBA so that more precise decisions about soil treatment could be generated. The lead scientist in that project asserted that juvenile swine were the only animal that could be used to conduct such tests, even if rat tests were conducted to prevent the problems with rat feeding experiments
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350 Data of dieter et al. (1993) Mean ± stnd error
Femur Pb, mg/kg DW
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250 200
200 PbO
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50 Pb-Ore
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Figure 4 Absorption of Pb from different Pb compounds added to the AIN-76 purified diet (Dieter et al., 1993).
80 70 Bone Pb, mg/g FW
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Female rats fed 30 days. Freeman et al., 1992. Mine waste soils. AIN-76 purified diet Mean ± SE
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Figure 5 Effect of soil dose and mining waste soil Pb concentration on Pb in bone of rats fed the test soils in AIN diets for 35 days (Freeman et al., 1992).
(Weis and Lavelle, 1991). After years of research, that team kept asserting that it might be appropriate to use RBA measured using the swine bioassay to adjust soil Pb clean-up levels, but that the IEUBK computer program had to be used and that treatment of soils could not achieve reduction in risk. Over this decade extensive research showed that the bioavailability of soil
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Pb could be reduced by treatment with biosolids or with phosphate sources (Brown et al., 2003; Ryan et al., 2004). A summary of that progress is reported by Ryan et al. (2004) regarding a large multi-year field test of soil Pb remediation at Joplin, MO. Eventually, the EPA Region-8 team (Casteel et al., 1996, 1997; Drexler and Brattin, 2007; USEPA, 2007a) worked to develop an independent bioaccessibility test. How to conduct relative soil Pb bioavailability tests has been debated for many years. Some felt that one had to follow the usual toxicological approach and use fasting animals. However, comparison feeding tests of Pb on fasting or to persons consuming small meals showed that for some time before and after consumption of a meal, a remarkable reduction in Pb absorption occurred in humans ( James et al., 1985). It was common for water soluble Pb to be absorbed between 60% and 80% on fasting, but only 1–5% with food (Heard and Chamberlain, 1982; Heard et al., 1983; James et al., 1985). Many have noted this critical effect and wondered how animal testing should be conducted. Is all soil/dust ingested by children ingested between meals such that only the fasting condition is representative? The juvenile swine test compromised and has fed soil mixed with a ball of the purified ‘‘dough’’ AIN feed used in the test; one can only gavage a young pig so many times before it become too difficult to continue gavage dosing. Thus, one part is fed after long fasting, and the second part is fed after a short fast. So the actual test is a hybrid or confounded method (Casteel et al., 1997, 2006; USEPA, 2007a). One issue seldom discussed is the need for testing soils with high Pb concentration in order to make significant measurements in animal tissues during bioavailability evaluation. Nearly, all of the soils fed were on the order of 10–50 times higher in Pb than the current limit for Pb in bare soils of homes under HUD rules (400 mg kg 1 for bare soil). It is possible that the soil and diet factors which interact with soil Pb bioavailability are different for such highly contaminated test soil materials than in soils to which children are commonly exposed. Ultimately, human tests of soil Pb bioavailability were conducted and these should be the ‘‘Gold Standard’’ for soil Pb bioavailability. Maddaloni et al. (1998) fed human volunteers soil on fasting or with a meal using Pb stable isotopes (206Pb/207Pb ratio) to measure the absolute Pb absorption from the test dose. By selecting subjects with quite different isotope ratios than the soil to be tested, a very sensitive assay was constructed. The soil from Bunker Hill, ID, contained 2240 mg Pb kg 1 whole soil, and 2924 mg Pb kg 1 in the <250 mm sieve fraction. It was found that the humans fed about 225 mg Pb in 80 mg soil absorbed 26.2% of the soil Pb on fasting, but only 2.52% when they ingested the soil with a light breakfast meal. The interpretation of the stable Pb isotope-based bioassay is based on the normal distribution of IV-injected Pb after 24 h, with 55% remaining in whole blood (Maddaloni et al., 1998). Additional consideration suggests that
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individuals who consume much soil are breaking their fast due to the soil ingestion itself. Other work has shown that higher dietary Ca (and to some extent phosphate) inhibit Pb absorption considerably (Blake and Mann, 1983). The apparent reason that Ca has the stronger effect is that phosphate is recirculated in the digestive system, so that diet Ca has plenty of phosphate to coprecipitate dietary Pb with. The effect of dietary Ca cannot be attributed to a role in formation of CP (a very low solubility Pb compound with low bioavailability). The first mention of the possible formation of CP in soil that we know was by Nriagu (1974). Subsequently, Cotter-Howells and Thornton (1991) reported formation of CP in Pb mineralized soils of an old English village. And then Ryan, Logan, Ma, and Traina examined formation of CP with Pb compounds and soil Pb and their work suggested this could be an effective soil Pb remediation technology (Ma et al., 1993). In our view, the ultimate question about soil Pb bioavailability is ‘‘Can you remediate soil Pb to persistently reduce Pb bioavailability?’’ This question was the goal of the IINERT Action Team (of the US-EPA Remediation Technology Development Forum) led by Ryan and Berti (Ryan et al., 2004). A large team applied different promising soil Pb remediation methods to an urban soil contaminated with Pb, Zn, and Cd from smelter emissions in Joplin, MO. Treatments included phosphoric acid, triple superphosphate (TSP), rock phosphate, biosolids compost TSP, and iron oxide phosphate. The amendments were incorporated in replicated randomized plots and incubated for several months at the pH of the mixture, then limed to about pH 7 and seeded with tall fescue. The soils and grass were sampled periodically over the next few years for soil Pb bioaccessibility and bioavailability (Ryan et al., 2004) testing, and analysis of plant uptake (Brown et al., 2004). Phosphoric acid treated and control soils were fed to rats, juvenile swine, and human volunteers. The results of feeding the soil about 1.5 years post field treatment showed a reduction of bioavailability of about 69% (42.2% vs. 13.1% ABA) to fasting adults, about 38% to juvenile swine and 38% to rats. The Ruby et al. SBRC Pb bioaccessibility test showed a reduction of 38% when conducted at pH 2.2 or 2.5, but no change when conducted at pH 1.5, the level specified by Drexler and Brattin (2007). In addition to measurement of Pb bioavailability and bioaccessibility, study of Pb speciation was undertaken by Scheckel and Ryan (2004). Using nondestructive XAS, they were able to measure the fraction of total soil Pb in several chemical forms and found that phosphate applications caused most of the soil Pb to be changed to CP. This finding is very important because CP has very low bioavailability and is stable under normal soil environmental conditions, becoming less and less bioavailable as the solid becomes larger and more ordered over time (Scheckel and Ryan, 2002). Although acidic pH favors the reactions of various P additions with soil Pb species, CP is formed from most Pb compounds, under most normal soil conditions
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(Ryan et al., 2001; Zhang and Ryan, 1998, 1999a, b; Zhang et al., 1997, 1998), and if the mixture of phosphate with soil has occurred the CP formation may occur rapidly in the stomach if it had not already occurred in the soil before ingestion (Scheckel et al., 2003). Actually, this latter publication shows that sequential extraction procedures cause the formation of new Pb compounds during the procedure, and show another failing of sequential extractions in trying to understand forms of metals in the environment. Various P amendments are effective in formation of CP over time including phosphoric acid, TSP, diammonium phosphate, rock phosphate, composts and biosolids (Brown et al., 2003), bone meal (Hodson et al., 2000), etc. (Cao et al., 2008; Hettiarachchi et al., 2001; Knox et al., 2006; Yoon et al., 2007). Rhizosphere soil conditions or soil microbes may promote formation of CP in amended soils (Cotter-Howells et al., 1999). 6.1.3. Bioaccessibility of soil Pb When feeding studies were being conducted to characterize the relative and absolute bioavailability of soil Pb, it was intended to develop a chemical extraction test for soils which correlated well with the RBA determined by feeding. Ruby et al. (1993) reported the initial study and introduced the term ‘‘bioaccessibility’’ for chemical assessment of RBA. There has been a lot of effort to improve this test and to make it simpler or less expensive to conduct since the original paper, and important progress has been made. On the other hand, numerous authors have conducted tests of variation of the extraction method adding different digestion factors from the human digestive system assuming that the more life-like the method, the better the reliability would be (Oomen et al., 2002, 2003a,b). Some authors have simply used dilute HCl ignoring the buffering aspect of stomach secretions (Thums et al., 2008). In our view, the only relevant issue is the relationship of the bioaccessibility test and an acceptable bioavailability measure. Ruby et al. (1996, 1999) extended the development of their extraction method and called it the physiologically based extraction test (PBET). The test was more complicated, but seemed well correlated with results of some feeding studies. Drexler and Brattin (2007) reported their RBA leaching procedure (RBALP using the simplified stomach phase only. They had access to the diverse soil materials from Superfund sites which had been fed to juvenile swine using the Casteel et al. (2006) procedure. The test uses 0.4 M glycine with enough HCl to buffer the solution at pH 1.5 to mimic fasting stomach pH; the extraction is conducted at 37 C for 1 h, using 1 g dry soil/dust per 100 mL extraction fluid. They suggest that if the pH of the extraction fluid is raised by the soil under test that the pH should be manually adjusted to 1.5 until it stays at that pH for the extraction period. The correlation with swine RBA results was found to be R2 ¼ 0.82; the correlation was R2 ¼ 0.75 when conducted at pH 2.5. But as noted earlier, conducting the extraction
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at pH 1.5 left it insensitive to the highly effective soil remediation treatments using phosphate tested at Joplin, which were proved to have lower bioavailability by feeding to swine, rats, and humans. Thus, we believe this method should be conducted at pH 2.5 so that the results have relevance to soil remediation. Further, the extraction test result gave a smaller reduction in soil Pb bioavailability (38%) than found with human volunteers fed the Joplin soil on fasting (69%), as did the pig and rat feeding tests. This is clearly evidence that more soil Pb remediation test materials should be fed to humans to provide the definition of remediation of risk that seems to be obtainable with inexpensive technologies (Ryan et al., 2004). Another attempt to validate an extraction procedure was reported by Schroder et al. (2004). They fed 18 soils to swine following the Casteel et al. (2006) procedure, and tested stomach and intestinal phases on an ‘‘IVG’’ extraction method. The presence of the dough used to dose the soil/dust Pb to swine significantly reduced IVG-Pb perhaps due to the presence of phytate. Their method used pH 1.8, and added porcine enzymes. Strong correlation was obtained between IVG and RBA results. Further, research has indicated that highly effective remediation could be achieved by application of a mixture of soil amendments to revitalize soils which had been severely injured by metal contamination from smelter and mine wastes (Allen et al., 2007). Combinations of biosolids, composts, manures, alkaline byproducts, wood ash, fly ash, limestone, etc., can generate calcareous soil amendment mixtures at low cost, and yield remediated soils that protect humans, wildlife, and other ecosystem components. This approach has now been applied at several Superfund and similar sites with persistent success (Basta et al., 2001a,b; Brown et al., 2003, 2004, 2005; Conder et al., 2001; Farfel et al., 2005a,b; Li et al., 2000; Stuczynski et al., 2007).
6.2. Arsenic 6.2.1. Soil As bioavailability in risk assessment Compounds of arsenic may be absorbed after ingestion or through inhalation. Typically, trivalent arsenic (arsenite) is more toxic than pentavalent (arsenate) compounds and that in aerobic soils arsenate is the predominant form. Arsenate tends to be excreted by the kidneys and does not accumulate extensively. Arsenate can substitute for phosphate in some enzyme complexes but the bond is unstable and decomposes by uncouple oxidation from phosphorylation. Arsenite forms can bind to tissue proteins and concentrated in the leukocytes. Arsenite will accumulate in other body organs (liver, muscles, hair, and skin) via reactions with sulfhydryl groups and is excreted by the bile. Chronic arsenic exposure results in depression, fatigue, disruption of red cell production, and forms of cancer.
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The underlying assumption in quantifying As intake toxicological evaluation is that all of the As measured by the total metal analysis is related to the absorbed dose. However, there is an inherent problem with the above assumption as the forms of As found in soils and waste produces a wide range of As solubility in contaminated media. Most metal and metalloid sulfides, for example, are less soluble than their respective oxidized compounds; for As, the solubility of As2S3 in water is 0.005 g L 1, while the solubility of As2O3 is 37 gL 1. These differences may have a significant impact on the dose absorbed from ingestion of contaminated soil. Other elements or soil chemical factors may influence As dissolution and As absorption in the intestine. Recently, reviewed in vivo models used to measure bioavailable As include juvenile swine, monkey, rabbit, and dog (Roberts et al., 2002, 2007; Ruby et al., 1999; Valberg et al., 1997). In these in vivo dosing trials, soil As bioavailability was evaluated by measuring As in urine, blood, feces, and/or storage tissues (bone, skin, nails, and hair) of some species. The monkey tests used urine As collection to measure the absorbed dose so that animals are not sacrificed during the tests (Freeman et al., 1995; Roberts et al., 2002). Juvenile swine and monkey are the animal models used most often to obtain sitespecific bioavailability of soil As for use in risk assessment at Superfund sites. Both monkey and swine are remarkably similar to humans with respect to their digestive tract, nutritional requirements, bone development, and mineral metabolism (Dodds, 1982). Juvenile swine are commonly used because of several factors, including the economics of husbandry, ease of dose delivery, and the concern of animal rights’ groups regarding animal model selection. Young swine are considered to be a good physiological model for GI absorption in children (Casteel et al., 1996; Weis and LaVelle, 1991). The swine model for bioavailability determinations has gained acceptance for as a method to determine soil Pb RBA at USEPA (2007c). However, dosing trials using primates and swine are expensive. Recently, new findings using laboratory mice, a less expensive animal model, for measuring bioavailable As have been reported (Thomas et al., 2007). 6.2.2. Factors shown to affect soil As bioavailability Coingestion of food and contaminated soil has been shown to decrease bioavailable Pb compared to soil ingestion without food to humans (Maddaloni et al., 1998). Therefore, fasted conditions are considered conservative estimates of Pb RBA. However, fasted conditions may not be conservative estimates for As RBA because phosphate associated with diets may increase As bioaccessibility and perhaps RBA (Basta et al., 2007a). To overcome the difficulty and expense associated with in vivo trials, research effort has been directed toward the development of in vitro methods to simulate human GI conditions. Several of these methods have been reviewed (Oomen et al., 2002; Rodriguez et al., 1999; Ruby et al., 1999).
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More recent IVG methods for measuring bioaccessible As have been described (Basta et al., 2007a; Lowney et al., 2007). Regardless of the method, bioaccessible As measured by an in vitro method must be well correlated with bioavailable As. According to EPA Guidance (USEPA, 2007b): ‘‘In the case that a validated in vitro method is used to estimate bioavailability, it is recommended that the protocol specified in the methodology be followed for making the extrapolation from in vitro data to in vivo values. That is, there is no a priori assumption that all validated in vitro methods must yield results that are identical to in vivo values. Rather, it is assumed that a mathematical equation will exist such that the in vitro result (entered as input) will yield an estimate of the in vivo value (as output).’’ At a minimum, the in vitro method must be correlated with As RBA measured by an acceptable animal model. Thus, in vitro methods that are able to predict bioavailable As, with an estimate of uncertainty, are highly desirable. Because of the cost of animal dosing trials, few studies comparing IVG methods with animal models have been conducted. Basta et al. (2001a,b) and Rodriguez et al. (1999) reported a strong correlation r ¼ 0.91, P < 0.01) of bioaccessible As measured by the OSU IVG method with As RBA determined by immature swine for 14 contaminated soils (Fig. 6). Juhasz et al. (2007) reported a strong correlation r ¼ 0.96, P < 0.01) of bioaccessible As measured by SBET with RBA As determined using swine for 12 contaminated soils. Lowney et al. (2007) reported correlation between bioaccessible As and RBA As determined using Cynomolgus monkey. Ruby et al. (1996) reported comparison of bioaccessible As measured using PBET with RBA As using rabbit and Cynomolgus monkey for three contaminated soils. Bioaccessible As (i.e., PBET) overpredicted RBA As. The small number of soils prevented a thorough evaluation of As-PBET with As RBA. USEPA, 2007b recommends validation of IVG methods described by the Interagency Coordinating Committee for Validation of Alternative Methods (ICCVAM). ICCVAM’s validation criteria for test methods include inter- and intralaboratory round robin studies. To our knowledge, round robin studies of IVG methods for As have not been conducted in the United States. Round robin studies should be limited to IVG methods that have been shown to be well correlated with bioavailable As from animal dosing trials. 6.2.3. Chemical forms of As in soils Versus bioavailability/ bioaccessibility Most studies show that As bioavailability in contaminated soil is much lower than the bioavailability of soluble inorganic As (i.e., sodium arsenate) used for assessing risk from As in drinking water (Ruby et al., 1999). Bioavailability of As in contaminated soil relative to sodium arsenate (i.e., RBA) ranged from 0% to 98% with a median value of 35.5% for 16 contaminated soils and media fed to rabbits (Ruby et al., 1999), from 4.07% to 42.9% with
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60 OSU IVG, gastric phase y = 0.942x + 7.11, r = 0.91**
50 40 30 20 10 0 0
10
20
30
40
60 OSU IVG, intestinal phase y = 1.07x + 7.20, r = 0.91**
50 40 30 20 10 0 0
10
20 30 % Relative bioaccessible, in vitro % Relative bioavailable as, in vivo
40
Figure 6 In vivo RBA As versus OSU IVG relative bioaccessible As. Data regraphed from Basta et al. (2001a,b).
a median value of 25.5% for 14 contaminated soils and media fed to swine (Basta et al., 2001a,b), and 17% (range 5–31%) with most in the 10–20% range for 14 soils fed to monkeys (Roberts et al., 2007). Most contaminated soils have RBA of <50% showing clearly that As was less bioavailable in soil than when dissolved in water. Addition of soluble Na arsenate to soil gave 95% RBA, while addition of arsenopyrite gave 1% RBA. Ng et al. (1998) fed soils to rats and found low bioavailability which they attributed to the chemical speciation of As in their test soils. Another important finding
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regarding soil As risk was that dermal absorption of As from soil was negligible, much lower than the default USAEPA assumption of 3% dermal absorption based on study of solutions (Lowney et al., 2007). Studies measuring bioaccessible As have been conducted on a limited number of soils and contaminant sources. Soil properties have a great influence on As bioaccessibility (Yang et al., 2002). It is unclear whether these methods can be extrapolated to other soils/contaminant sources. Do IVG bioaccessible As versus in vivo RBA As studies have to be conducted for every soil and contaminant source studied? The expense would be huge. A better approach may be to determine the form of arsenic that is bioavailable (i.e., contaminant speciation). Solid phase As species, measured by spectroscopic methods, have been shown to be related to bioavailable As (Basta et al., 2007b). Available pools, measured by traditional soil extraction methods, can also be used to provide information on bioavailable As pools (Rodriguez et al., 2003). However, care must be used when applying these extractions to estimate As chemical speciation of soils or other media (Scheckel et al., 2003). Knowledge of the relationships between As speciation and As bioavailability could allow extrapolation of IVG methods to new soils with similar solid phase As species as the bioavailable arsenic source term. Rodriguez et al. (2003) and Yang et al. (2002) reported most arsenic in contaminated soil that was likely associated with amorphous (i.e., reactive) Fe oxide minerals was not bioavailable. Beak et al. (2006a,b) found Fe oxides surfaces in ferrihydrite greatly reduced As bioaccessibility to <5% relative bioaccessibility. The speciation of As, determined using extended XAFS near-edge spectroscopy was determined to be strong binuclear bidentate bonding with the Fe oxide surface. 6.2.4. Modification of soil As chemical forms to reduce bioavailability/risk Much study has been conducted on the remediation of Pb by using soil amendments to modify the chemical form of Pb and reducing its bioavailability (Allen et al., 2007; Hettiarachchi and Pierzynski, 2004; Ryan et al., 2004). However, studies on the use of soil amendments to reduce As bioavailability or bioaccessibility are limited. Although the ability of Fe to sorb As(V) from water is well known, little research is available on the ability of Fe and other soil amendments to reduce bioavailable or bioaccessible As in soil. In some studies of As uptake by plants from contaminated soils, addition of amorphous Fe hydroxide or ferrous sulfate has substantially reduced As uptake (Doi et al., 2005; Warren and Alloway, 2003). 6.2.5. Arsenic risk assessment across contaminated soils Cancer risk can be expressed by the following equation: Risk ¼ CDI SF, where CDI is the chemical daily intake and SF is the CSF. Noncancer risk can be calculated as CDI/RfD, where RfD is the reference dose. The effect
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of contaminant bioavailability from soil ingestion to human receptors can be evaluated by making adjustments to the dose using the following equation: CDIadjusted ¼ CDI RBA. Alternately, RBA can be used to make site-specific risk adjustments for cancer risk by using the following equation: SFadjusted ¼ SFIRIS RBA, where SF is the slope factor. Site-specific adjustment for noncancer risk can be calculated by the following equation: RfDadjusted ¼ RfDIRIS/RBA. However, the usefulness and/or ability to adjust CDI for bioavailability depend on many issues including (1) the contaminant concentration in the soil and (2) the chemical properties of the soil/geomedia. Because animal models and IVG methods have inherent uncertainty in RBA, CDI adjustments will be less likely used on highly contaminated (>1000 mg kg 1 As) than moderately contaminated soils (<500 mg kg 1 As). Often, the highly contaminated area is much less than the moderately contaminated area of soil on a site. Excavation and replacement of the highly contaminated area may be feasible but is less feasible for large areas of moderately contaminated soil. Thus, RBA adjustments are needed for moderately contaminated soils. Cleanup of many sites are often considered at <50 mg kg 1 soil As. It may not be possible to obtain RBA values for As using animal models for some moderately contaminated soils that contain <200 mg kg-1 As. Arsenic in urine or blood, used to determine RBA from animal diets in dosing studies may determine the soil As detection limit. A strong advantage of IVG methods is the ability to estimate RBA at very low soil As concentrations including background levels of <10 mg kg 1 As. IVG methods are not limited by background arsenic from food as in vivo animal models. However, IVG methods that incorporate a variety of foodstuffs and/or biochemicals that result in high background As in the in vitro solution may suffer poor detection limits for As-contaminated soil. Arsenic bioavailability and bioaccessibility are affected by soil properties. Sorbent solid phases (i.e., Fe oxides), organic C, and soil pH have been shown to affect bioaccessible As. It is more likely that CDI adjustment for RBA As for soils with properties likely to sequester As and decrease its bioavailability. Soil properties that affect As bioavailability and bioaccessibility to human and should be considered in human risk assessment of contaminated soil. 6.2.6. A case for reduction in soil As RBA at remediated sites Studies are available that focus on the ability of soil remediation to reduce As solubility and mobility, including plant uptake. However, comprehensive research to evaluate the effect of soil remediation on As bioavailability to animals has not been conducted. Several studies have shown using Fe oxide amendments can reduce As bioaccessibility. Animal dosing trials are needed to confirm the ability of these soil treatments to reduce As bioavailability. IVG methods may be predictive of bioavailable contaminant in untreated soil but not in treated soil. Research is needed to confirm the ability of IVG
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methods for measuring bioaccessible As are capable of predicting RBA As of remediated soil. Risk from soil As is complex. It is assumed that soil and dust ingestion by children gives the highest exposures, just as for Pb. In the case of As, actual absorbed doses can be reliably measured by measuring As speciation in urine. Two Superfund sites have had extensive evaluation of urine As in children in relation to As in soil and dust (Hwang et al., 1997; Tsuji et al., 2005). These studies seem to indicate that at least up to 40 mg As kg-1, no significant increase in absorbed dose occurred, and perhaps even up to 100 mg As kg 1. Presently, most locations consider that any soil As of 20 mg kg 1 or higher require further detailed risk assessment. But the Soil Screening Level for Superfund (10 5 cancer risk) is 0.429 mg As kg 1 based on the CSF and assumptions about soil ingestion and 100% bioavailability of the ingested soil As. One newer aspect of the USEPA estimate is a further assumption that dietary inorganic As has a 10-fold higher slope factor for children than adults. The CSF still depends on the assumption of linear extrapolation to zero dose, but recent research continues to indicate that the dose–response to drinking water As is a threshold with no observed adverse effects until water concentration exceeds about 100 mg L 1 (Lamm et al., 2004). In light of the low As bioavailability seen in relatively low As concentration soils fed to monkeys and swine, some reconsideration of this risk may be appropriate (adjust soil dose assumption and soil As bioavailability assumption). It seems remarkable that anyone would suggest a lower soil screening level for As than occurs in background uncontaminated soils. As reported by Smith et al. (2005), a recent US Geological Survey sampling of 254 soils in two transcontinental transects of North America yielded a soil As mean S.D. ¼ 5.74 2.96 mg kg 1, geometric mean 4.94 mg kg 1, and 5th–95th percentile range of 2–12 mg As kg 1.
7. Conclusions Information on the oral bioavailability of metals from soil can be quantified in a RBA factor. Implementation of a RBA factor into human health risk assessment of metal-contaminated soils is expected to result in a more accurate exposure assessment. This leads to a more relevant and efficient risk assessment, especially in site-specific risk assessment, without altering human health impacts. Regulations on the fate and effects of metals in the environment based solely on total concentrations are no longer valid, state-of-the-art, or scientifically sound. Bioavailability, defined as the individual physical, chemical, and biological interactions that determine the transfer of chemicals associated with soils to plants and animals, has
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become an area of intense scientific research with the ultimate goal to protect human health and adequately address site assessment. The primary method to understand and relate bioavailability in humans is to employ animal surrogates via in vivo animal feeding studies; however, such studies can be quite expensive and time-consuming. To address this obstacle, many researchers have developed in vitro chemical extractions to mimic the GI environment of animals. Unfortunately, there is a lack of consensus and validation as to which of the many in vitro tests accurately describe in vivo bioavailability. In many instances, the same soil sample can produce a variety of in vitro values depending on the test employed. As mentioned in the chapter, there are many sources of error associated with in vitro studies that must be considered in order for the research to be useful. Most important to remember is that there is not (yet) a single silver bullet in vitro method that can explain the bioavailability of multiple metals. While great success has been accomplished for Pb and/or As, additional research is necessary to examine the bioaccessibility of other key metals encountered in soils on an element by element approach—this also means additional in vivo validation is necessary. Two benchmarks for this research should be relevance and consensus. If we are concerned with children in contact with Pb paint contaminated soil, we should conduct in vivo and in vitro studies on Pb paint contaminated soil rather than in vivo and in vitro studies on mine tailings with uncertain extrapolation to Pb paint contaminated soil. While much of the early work in this area was focused on severely contaminated mining sites (and this work is important), there is little evidence that these results are relevant to urban environments with different Pb sources and concentrations as well as different soil properties. However, in conducting this research, there are various in vivo and in vitro methods to employ. It is becoming more apparent that some methods are better for Pb while others are more adequate for As. In vivo methods seem to fall in line more concisely; however, there are limited direct comparisons of base soil samples fed to multiple in vivo animal models. The biggest issue of consensus deals with in vitro models for which there are dozens available and new one being developed. It would be in the best interest of the scientific community to unite behind a well-validated in vitro model for each element. More importantly from this context would be a repository of soil samples that have undergone in vivo analysis to further validate in vitro models that were initially developed with only a few soil samples. From the earlier discussions on risks of Pb and As from direct soil ingestion it is apparent that many ways to measure bioavailability and bioaccessibility exist, but there are inadequate comparisons between the two measures and, for that matter within either of the measurements independently, the results prove insufficient to support broad policy changes. Further understanding for why two samples provide different
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RBA is often lacking because definitive characterization of the matrix to allow more than speculative conclusions have not been done. These concerns can only be resolved by obtaining results for all tests (bioavailability, bioaccessibility, chemical speciation, and soil characterization) on the same matrix. A number of different matrix samples must be included in order to better understand the variability that occurs in order to support policy change in risk assessment and remediation decisions. A future perspective on bioavailability research lends the need for integrated multidisciplinary research to attack relevant issues in a fruitful manner. Application of expertise in the fields of soil science, toxicology, biology, geochemistry, spectroscopy, and statistics is necessary to push this research forward. While we have a good understanding that contaminant source, speciation, concentration, matrix, soil properties, and the test animal all influence bioavailability, but knowing ‘‘why and how’’ have been the elusive criteria to fully understanding these mechanisms. Additionally, the research groups involved in this field have enjoyed the pleasure of examining soil systems with one primary contaminant. As complex as bioavailability research is, we must consider how we will investigate soils with multiple contaminants which may exhibit synergistic or antagonistic characteristics—factors that may only be evident for in vivo studies and undetectable in in vitro chemical extractions. A stronger emphasis on spectroscopic speciation will be needed to investigate the intricacies of metal speciation on bioavailability. These complexities will make bioavailability a long-lived research endeavor.
ACKNOWLEDGMENTS This work was produced and funded by the National Risk Management Research Laboratory of the US Environmental Protection Agency. This paper has not been subjected to the Agency’s internal review. Therefore, the research results presented herein do not, necessarily, reflect the views of the Agency or its policy.
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Nitrogen in Rainfed and Irrigated Cropping Systems in the Mediterranean Region John Ryan,* Hayriye Ibrikci,† Rolf Sommer,* and Ann McNeill‡ Contents 55 57 58 60 61 63 64 65 66 68 68 69 79 80 83 84 85 86 86 89 91 92 95 96 101 104 104
1. Introduction 2. Mediterranean Agroecosystems 2.1. Climate 2.2. Soils and land features 2.3. Crops and farming systems 3. Perspective on Nitrogen in Agriculture 3.1. Nitrogen use in rainfed environments 3.2. Nitrogen in the mediterranean region 4. Fertilizer use Trends in the Mediterranean Region 5. Response of Rainfed Crops to Nitrogen Fertilizer 5.1. Soil organic matter and total soil nitrogen 5.2. Field responses to fertilizer nitrogen 5.3. Genetic differences of crops for nitrogen fertilization 6. Assessing Soil Nitrogen Status for Crop Yields 6.1. Nitrogen mineralization indices 6.2. Plant analysis for nitrogen management 7. Nitrogen Fixation Under Mediterranean Dryland Conditions 7.1. Food legumes 7.2. Rhizobia, inoculation, and cultivar interactions 7.3. Pasture and forage legumes 7.4. Current perspective on food and forage legumes 8. Potential Losses of Nitrogen in Dryland Cropping 9. Integrated Cropping Systems: Implications for Nitrogen 9.1. The ‘‘Cropping systems productivity’’ trial 9.2. Grazing management rotation trial 9.3. Barley-based rotation trials 9.4. Conservation/compost tillage trial * { {
International Center for Agricultural Research in the Dry Areas (ICARDA), Aleppo, Syria Soil Science Department, Faculty of Agriculture, C ¸ ukurova University, Balcali, Adana, Turkey Adelaide University, Roseworthy Campus, Adelaide, South Australia, Australia
Advances in Agronomy, Volume 104 ISSN 0065-2113, DOI: 10.1016/S0065-2113(09)04002-4
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2009 Elsevier Inc. All rights reserved.
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10. Nitrogen in Supplemental Irrigation Systems 11. Nitrogen Tracer use in Rainfed Cropping Systems 11.1. Fate of N fertilizer with wheat in a cereal–legume rotation 11.2. Implications of 15N for rotation effects 11.3. Estimated N fixation by grain legumes using 15N technique 12. Modeling of Nitrogen in Rainfed Cropping Systems 12.1. Previous nitrogen modeling 12.2. Models for arid environments 13. Future Perspective Acknowledgments References
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Abstract The Middle East region, embracing West Asia and North Africa (WANA), is characterized by a Mediterranean climate which dictates the agriculture of the region. Being one of the centers of origin of settled farming, where cereals and pulses originated along with sheep and goats, crop production is largely rainfed and is dependent on the limited rainfall (200–600 mm) during the cool moist season in late fall to late spring. The agricultural sector has changed in recent decades with intensification and pressure on land use. As elsewhere, increased chemical fertilizer use, especially nitrogen (N), has had an impact on the transition from a traditional system to a more market driven one with increased inputs. This review examines the varied aspects of N in the soils and cropping systems as reflected by research at The International Center for Agricultural Research in the Dry Areas (ICARDA) in Syria in collaboration with other countries of the West Asia–North Africa region, especially in Morocco and other countries north and south of the Mediterranean. The synthesis, therefore, reflects a broad overview of conditions that impinge an N nutrition of crops and the evolution of N research achievements since the advent of commercial fertilization over three decades ago. With few exceptions, the soils of the Mediterranean region are low in organic matter and consequently in the reserves of total N, thus posing a limit of growing crops without fertilizer N or biological N fixation (BNF) through legumes. Soil calibration studies established the value of the soil nitrate test as a predictor of crop response with field trials to establish application rates for the main crops. Applicability is influenced by depth of sampling and the extent of mineralization. Dryland crop responses to N varied widely throughout the region from 30 to 150 kg N ha 1, being dependent on soil N status and seasonal rainfall as the major determinant of yields. Splitting the N application was only advantageous in higher rainfall areas. Residual N from BNF by food and forage legumes influenced soil N supply for cereals and relative responses to N fertilizer. The contribution of rhizobia fixation to all the major legumes was quantified using 15N along with management factors that influenced BNF by legumes. Where legumes were newly introduced to a region, rhizobial
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inoculation was considered necessary. With cereal responses to fertilizer N, differences between varieties were highlighted. Where urea or ammonium–N fertilizers were used, volatilization was the main loss mechanisms rather than leaching or denitrification. Considerable work was done on N use within crop rotation systems and components of the N cycle defined along with inputs from urine and feces from grazing animals. Forage legumes were shown to enhance total soil N and both labile and biomass N, with the least influence from fallow. These N forms were shown to fluctuate during the year as moisture and temperature conditions changed. Fertilizer N use had a positive effect on grain quality with increased protein, as well as soil organic matter (SOM) and thus soil quality. The significant change of the gradual introduction of supplemental irrigation in traditional rainfed cropping areas and its implications for use of models to describe the complex nature of N in dryland cropping systems was described. With the likelihood of a continuation of intensification of the dryland cropping systems in the Mediterranean region, N fertilizer use will inevitably increase and along with it the need for greater use efficiency in the interest of production economics and the environment. While limited use has been made of modeling of N, this approach is likely to be of more significance in integrating the varied facets of N under Mediterranean cropping conditions.
1. Introduction Given the limited natural resources of our planet, the abiding concerns of mankind center around providing an adequate supply of food to sustain healthy populations in developed and developing countries and improving overall living standards and quality of life. This enormous challenge of maintaining the productive potential for global food supplies must be balanced with the need to preserve the environment and its ecosystems, including nature’s flora, fauna, and biological diversity. This consideration adds a moral and esthetic dimension to this ever-increasing dilemma for mankind. Food production is largely dependent on the plant’s soil and water resources (Lal, 2001). Adequate supplies of fertile land and the application of scientific and technological innovations have kept hunger at bay for most of the world’s population for the past century and have been able to maintain a population of 6 billion people (Borlaug, 2003). Achieving that goal has come at a cost of degradation of soil, water, and the atmosphere, and loss in biodiversity; it was driven by over-dependence on fossil fuels. The situation now at the end of the first decade of the twenty-first century is disquieting at best or leaves little hope for optimism at worst. On one side of the food demand-supply equation, world population may double within 50 years, with most of it being in the developing world. On the supply side, land available for agricultural production is shrinking, as
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other uses (cities, highways, factories, recreation areas, etc.) compete for land use. In addition, the greatest threat to biodiversity is expanding of agricultural lands in developing countries into forests, grasslands, and wetlands (Tillman et al., 2002). A contemporary adverse factor in future food production scenarios is the impact of climate change, now perceived as a real threat to the planet. While the pressing concerns about agriculture and its response to sustaining life and safeguarding ecosystems may now be displaced as a major issue facing society by the current global economic depression, these abiding concerns will not go away. Although agriculture is practiced on about one-third of the earth’s land area, with increasing urbanization, the agricultural sector involves a proportionally smaller percentage of the world’s population, being less than 5% in most developed countries. While recognizing that such declines in rural populations can lead to a waning influence in policies and regulations that govern civil society, Cassman (2004) argues for a convergence of interests of agricultural and nonagricultural sectors in order that all citizens have a safe, nutrition and affordable food supply, access to energy sources, clean drinking water, pristine lakes for recreation, and parks for communing with nature. In the past few decades, agricultural production has been characterized by increasing crop yields per unit land area and per unit time due to better crop management, improved germplasm, and greater inputs of fertilizers. With a closing gap between crop yield and crop genetic potential, major breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet future global food demand (Cassman, 1999). A key factor in this puzzle is fertilizer; as much as 50% of global crop output is attributable to commercial fertilizer use, and even a greater proportion as yields increase further (Stewart et al., 2005). As agriculture uses most of the worlds nitrogen (N) of anthropogenic origin, that is, industrial manufacturing (Cassman et al., 2003), concerns about its use underpin both agricultural production and environmental concerns. In the context of linking fertilizer use, specifically N, with agricultural production systems, it is important to bear in mind that three major crops, wheat (Triticum aestivum, L.), rice (Oryza sativa, L.), and maize (Zea mays, L.) provide about two-thirds of all energy in human diets, and production systems involving these crops provide the mainstay of the global food supply (Cassman, 1999). Such cropping systems involve irrigated or favorable rainfall environments, that is, irrigated multiple cropping with rice in Asia; irrigated rice–wheat in Northern India, Pakistan, Nepal, and Southern China; temperate maize-based systems in North America; and favorable rainfed wheat systems in northwest and central Europe. Future expansion in world food production will have to come with ecological intensification, aided by technological innovation at the level of
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the soil, crop, chemical inputs, and management. Given the human–driven demands for land use, considerable attention has been focused in recent years on the potential of the world’s drylands (Peterson et al., 2006; Rao and Ryan, 2004). Cassman (2004) contended that ecological intensification of cropping systems in unfavorable rainfed environments depends as reducing reliance as subsistence cereal production, integration with livestock production, crop diversification, and agroforestry systems that provide higher economic returns to land users. One such region of the world where these conditions apply is the region south and east of the Mediterranean, that is, West Asia and North Africa (WANA), often termed the Middle East or the Near East. This review of N in relation to agricultural systems of this vast and historic region surrounding the Mediterranean is both timely and pertinent to broad societal and environmental issues. It follows a recent review of N use in another major dryland area of the world, that is, central China (Li et al., 2009). The conditions relating to the China’s drylands parallel those in WANA, that is, drylands constitute a large part of the land use in each area of the world and are subjected to land use pressure due to population growth as well as having precarious crop yields due to drought, in addition to serious wind and water erosion. Other common features between the two regions include low levels of soil organic matter (SOM), and thus available N, low fertilizer input, and N deficiency as a widespread crop production constraint. The broad range of issues related to N use in China also pertains to the Mediterranean region. In addition, the region has some unique features related to N use, and has experienced a rapid transformation in the past three decades from a traditional system where virtually no fertilizers were use to one where N use has increased 20-fold and where fertilization is now common in both dryland and irrigated crops (Ryan, 2004). The gradual encroachment of irrigation in formerly dryland areas poses a further dimension for N use, with greatly increased demand. Therefore, as a background to examining the many soil, environment, fertilizer, and crop-related issues pertinent to N in the agricultural systems in the Mediterranean region, a brief description of the climate, biophysical, and cultural conditions which impinge on N in cropping systems of that region.
2. Mediterranean Agroecosystems The climate of the lands surrounding the Mediterranean is characterized by two contrasting seasons, mild winters and hot and dry summers, which dictate the cropping systems unique to the region (Kassam, 1981). The wet winter season with corresponding lower temperature provides a
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climatic ‘‘window of opportunity’’ for dryland rainfed cropping that has characterized the region from two immemorial. While a Mediterranean climate defines the Mediterranean region, such a climate is also found elsewhere such as California in North America, Chile in South America, southeastern Australia, and the southern part of Africa. A brief description of the climate, soils, and cropping systems of Mediterranean region, mainly in North Africa and West Asia, is pertinent to any consideration of N in the agriculture of the region.
2.1. Climate The climate of the Mediterranean region has been described in numerous publications (e.g., Harris, 1995; Kassam, 1981; Ryan et al., 2006a). Similarly, the climate and natural resources of countries of the Near East have been recently described in the context of case studies related to integrated nutrient management (Kafkafi and Bonfil, 2008). In essence, it involves cool-to-cold wet winters and warm to hot dry summers. These general characteristics are modified locally by maritime (in North Africa) and continental (in West Asia) influences. A major feature is the variability in mean annual precipitation (including snow in the highlands) as well as high within-season rainfall distribution, but seasonal variability tends to be greater as mean annual rainfall decreases. With such variability, and despite advances in modeling capability, prediction of rain is beset with difficulties. Generally, highest rainfall occurs in coastal areas, decreasing with distance inland. The general climatic features are indicated in Fig. 1 with respect to rainfall. Typically, rain commences in autumn (September–October), reaching a peak in January/February, and then tapers off in April/May. The peak rainfall is later in West Asia than in North Africa, that is, April–May, with some rain in June/July. Frequently, the first seasonal rains may be delayed 2–3 months, with similar uncertainty at the end of the normal ‘‘rainy’’ season. An average, the amount of precipitation ranges from less than 100 mm in dry desert areas (North Africa toward the Sahara and in the Syrian/Iraqi deserts of West Asia) to over a 1000 mm in mountain’s areas, but the normal range for rainfed agriculture is 200–600 mm. With respect to cropping systems, rainfall has to be considered along with temperature as they both dictate evaporation from the soil and transpiration from the crop (Cooper et al., 1987). Winter temperatures are relatively mild in North African lowlands, but more severe in the highlands; winter temperatures are colder in West Asia and are particularly severe in the plateaus of Turkey and Iran, which are invariably snow covered. Conversely, summer temperatures are hottest in West Asian lowlands, more moderate in North Africa, and less extreme in the highland areas.
Legend Mediterranean zone Country boundaries Annual precipitation (mm) 0−100 100−200 200−300 300−400 400−500 500−600 600−700 700−800 800−900 900−1000 1000−1100 1100−1200 1200−1300 1300−2000 2000−3000 No data
Figure 1
Rainfall sketch of the Mediterranean area.
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The inverse patterns between seasonal rainfall and ambient temperatures dictate the typical Mediterranean rainfed cropping pattern, that is, late autumn to early summer. The early rains in autumn and decreasing temperatures allow for sowing and crop establishment followed by minimal growth in December/January, when rainfall exceeds evapotranspiration (ET). Subsequently, with increasing temperatures in February/March and rapid crop growth, ET increasing exceeds precipitation. Crops subsequently depend on stored soil moisture to complete their life cycle in May/June and invariably experience from a degree of terminal drought (Smith and Harris, 1981). While there is a general relationship between crop growth and seasonal and within-season rainfall, ‘‘effective’’ rainfall is related to rainfall intensity. For instance, Harris (1995) contended that light rain showers less than 5 mm is lost to evaporation and has little or no influence on soil moisture or crop growth; a significant proportion of Mediterranean rainfall occurs in such low-intensity showers.
2.2. Soils and land features The soils of the Mediterranean region are as varied as any part of the world due to differences in factors that influence soil formation and development, that is, parent material, topography, biological factors (limited by moisture), time, and particularly the influence of man (Ryan et al., 2006a). Most soils are derived from limestone residues and are calcareous (Kassam, 1981), a factor that influences crop nutrient availability, particularly phosphorus (P) (Matar et al., 1992), and micronutrients (Rashid and Ryan, 2008). Several of the major soil orders are represented in the WANA region: Entisols, Mollisols, Inceptisols, Vertisols, and Alfisols, all of which occur to varying extends in semiarid rainfed cropping areas extensive areas of arid soils, or arid region soils, which by definition are too dry for rainfed cropping and are characterized by rangelands and irrigated areas. Similarly, a wide range in soil texture, from sands to clays, and in depth from shallow to deep; both properties have a determining influence on the capacity of the soil to mediate soil moisture relations and be cropped sustainably. Characteristic landscape attributes of the Mediterranean region are a high proportion of mountains and steep slopes, with a pervasive influence of man on the landscape (Yaalon, 1997). With cultivation by man for millennia, combined with destruction of the forest cover and overgrazing by animals, much of the original soil cover have been eroded, leaving exposed rock on many hillsides. The ravaging effects of man’s activities have been exacerbated by the seasonal patterns of rain, which comes after the dry period has left the soil bare and exposed. Not surprisingly, the degraded state of today’s landscape has generated concerns about desertification (Thornes, 1996). In many instances, degraded land has ceased to be of economic use and has reverted to scrub. According to Grove (1996),
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degradation of the Mediterranean environment is due to both man and natural forces, with natural erosion being dominant up to about 5000 BC and the influence of man increasing thereafter. Regardless of inherent soil and landscape factors, a key soil component with implications for N is the SOM. As a result of relatively high temperatures (combined with moisture), SOM levels are generally low, due to mineralization; in addition, the amount of organic residues returned to the soil is limited due to animal grazing, and the contribution of root biomass is similarly low due to low crop yields. While soils of arid regions have less than 1% SOM, soils of semiarid favorable rainfall areas can range from 1% to 3% (Lal, 2001) but most are in the 1.0–1.5% range. Though constituting a small component of the soil, SOM serves as a store of N for potential release to the crop as well as mediating soil microbial processes.
2.3. Crops and farming systems All Mediterranean farming systems have a range of common elements: cereals, small ruminant livestock (i.e., sheep, Ovis aries and goats, Capris hircis), olives (Olea europaea), vines (Vitis spp), fruit trees, and vegetables (Gibbon, 1981). Cereals have dominated the Mediterranean region from time immemorial (Harlan, 1992). Indeed cereals have been important in the Mediterranean region since Biblical times, with indications that the inherent physiological yielding potential may not have been altered substantially over the millennia (Amir and Sinclair, 1994). Of the cereals, wheat is dominant, with bread wheat for flour and durum wheat (T. turgidum var durum) for pasta, couscous, and burghoul supplying human nutritional needs. In some areas of North Africa, barley (Hordeum vulgare) is used for bread-baking. Cereal production is largely integrated with production of small ruminants (Cooper et al., 1987). Wheat is grown in the more favorable rainfall areas (>350 mm) where it is cultivated in rotation with fallow, or a range of food legumes (chickpea, Cicer arietinum; lentil, Lens culinaris; faba bean, Vicia faba) and forage legumes such as vetch (Vicia sativa), peas (Pisum sativum), or medic (Medicago spp) as winter-sown crops (Harris, 1995). There is increasing interest in crops such as canola (Brassica napus L.), safflower (Carthamus tinctorius), and sesame (Sesamum indicum L.). With increasing land use pressure, fallow is being replaced by continuous cropping. In West Asia, fallow is clean tilled during the noncropped year to control weeds and thus conserve moisture to improve the fallow efficiency for the subsequent crop, while fallows in North Africa are left to grow weeds as a source of spring food for animals; this reduces the fallow efficiency. Barley is grown extensively, mainly in the relatively dry areas (<350 mm) and used for animal feed where livestock production is important and is more associated with fallow. The extension of barley cultivation
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into drier rangeland areas has generated concerns about the dangers of soil degradation in such environmentally fragile areas. In addition to the main cereal and forage crops, a range of crops are grown in late spring/early summer on residual soil moisture. These include melon (Citrullus vulgaris), sunflower (Helianthus annuus), maize (Zea mays), sorghum (Sorghum bicolor), sesame (Sesame indicum), and variety of vegetables. In recent years, there has been an increase in ‘‘niche’’ crops such as cumin (Cumin sativum L.), coriander (Coriander sativum L.), and camilina or false flax (Camilina sativa L. Crantz). Regardless of how well crops are adapted to the Mediterranean environment, their yielding potential is always determined by the incidence of winter rainfall, the effect of which is modified by radiation and temperature (Smith and Harris, 1981). Low temperatures, together with frost and snow, are a limitation for growth in high-elevation areas. Similarly, high temperatures during grain filling are a constant concern, often resulting in low yields or shriveled grain. A schematic presentation of the various representative farming systems is illustrated in Fig. 2. The dryland farming zone mainly occupies the 200–500 mm rainfall range, with barley/livestock in the less favorable part of that range and wheat-based cropping in the more favorable rainfall zone. Outside the dryland range in the arid (<200 mm) regions are deserts, rangelands, and irrigated areas. Above 500 mm a greater diversity of crops, including horticultural ones, exist because of dependable rainfall. The arrows in the diagram indicate the current trends, that is, increasing irrigation into previously rainfed areas, extension of barley to drier areas, and extension of fruit trees in the zones with relatively favorable rainfall.
st sy d se -b a at he
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Figure 2 Schematic diagram of representative agroecological conditions in the Mediterranean region.
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3. Perspective on Nitrogen in Agriculture From the dawn of settled agriculture and the cultivation of domesticated plants as food crops, man has recognized that crops could grow better following the addition of wastes of human or animal origin to the soil. Thus began the practice of fertilization, unwittingly due to N, long before the nature of the element contributing to the increased growth was revealed. In those distant days, the early agriculturalists recognized that some crops grew well without any soil amendment, that is, the N-fixing legumes that we now know. It has long been known that N is pervasive in the biosphere and the atmosphere. The air we breathe is composed of 78% N, virtually all of which is inert as N2, with other forms of N constituting a minor fraction (Hoffman and Van Cleemput, 2004). In the soil itself, N exists mainly in SOM in the form of organic compounds of varying complexity. The mineral fraction of soil N, mainly nitrate (NO3) and ammonium (NHþ 4 ), constitutes the pool from which plants withdraw N to sustain growth. The organic N fraction serves as a reservoir for mineral N following transformation or mineralization. Nitrogen is in a constant state of flux between the atmosphere and the soil, and between various N fractions in soil, that is, the celebrated N cycle. Given its importance in contributing to world food production, and belatedly to the environment, research on N has been a major preoccupation with soil and crop scientists for the past century. The voluminous literature that has been published attests to the extent to which our knowledge of N and its behavior has advanced. The course of N research, especially in the past 50 years, has been periodically marked by comprehensive reviews of the existing state of knowledge (e.g., Bartholomew and Clark, 1965; Stevenson, 1982). These milestones consolidated what was known and highlighted the potential importance of the unknown. Substantial advances have been made in many areas of N research; from in the soil and the dynamic relationship between them, as well as the chemical, physical, and biological reactions that characterize soil N behavior; relationship of soil N with the growing crop; and the complex interface between soil and atmosphere. A recent monograph on ‘‘Nitrogen in Agricultural Systems’’ by Scheppers and Raun (2008) provides the most comprehensive update on all significant aspects related to N. Emphasis is given to: mineralization, immobilization, and nitrification; reactions of urea and gaseous N losses; N transport processes; soil N budget; methodologies in N research; crop N requirements fertilization and monitoring; and N management for improved N-use efficiency (NUE). The volume highlighted the environmental
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implications of N with respect to water quality and land application of N-containing wastes, and included a perspective on N balances at ecosystem, landscape, regional, and global scales. The expanded concerns of N were reflected in another recent review by Mosier et al. (2004), which, in addition to common issues, considered the impact of N on human health, N in relation to both high- and low-input agricultural systems, and the impact of N on global food security. Other recent publications on fertilizer use in general, but with major emphasis on N, have addressed issues related to nutrient management in Asia ( Johnston and Syers, 1998), crop nutrition in relation to food security (Roy et al., 2006), and an approach to efficient fertilizer use currently in vogue, ‘‘fertilizer best management practices’’ (Krauss et al., 2007). The current state of N research and emerging societal concerns has been the subject a number of comprehensive reviews in Advances in Agronomy. Given the importance of cereals in the global economy, factors related to agronomic and physiological efficiency were highlighted along with strategies for management and policy implications (Ladha et al., 2005). With air quality and greenhouse gasses being at the forefront of societal concerns, implications of gaseous emissions from N fertilizer use pose a major challenge to agronomists worldwide (Harrison and Webb, 2001). No crop nutrient can be fully considered in isolation; elements such as N interact with other nutrients, the particular crop, and the environment (Aulakh and Malhi, 2005), especially with respect to rainfall and consequently available soil moisture.
3.1. Nitrogen use in rainfed environments The contrast between low rainfall in semiarid environments and more favorable ones in temperate and tropical conditions are stark (Aulakh and Malhi, 2005). Soil moisture has a dominant influence on all aspects of N, from availability and movement in the soil to crop uptake. A ceiling on crop yield is posed to moisture availability, and water is a determining influence on the efficiency of use of both soil and fertilizer N (Campbell et al., 1993). Dryland or rainfed cropping environments are unique with respect to the overarching influence of limited rainfall and soil moisture. In such environments, the life cycle of a crop is completed on stored soil moisture, and a degree of terminal drought invariably occurs (Cooper et al., 1987; Harris, 1995). Until recently, rainfed semiarid agriculture had received comparatively little research attention (Steiner et al., 1988), but this has changed due to global land use pressure and the susceptibility of drought-afflicted areas to land degradation (Lal, 2001). Indeed, it is now realized that dryland rainfed cropping can contribute to world food supplies and also help in the process of carbon sequestration (Lal, 2002). In both respects, N has a clear role to play.
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Yet the literature on soil and fertilizer N use in dryland environments in sparse, and then pertain to conditions in developed countries (e.g., North America, Australia), with unique cropping systems and weather conditions that dictate their success. While the review of Aulakh and Malhi (2005) briefly refers to N in dryland environments in the context mainly of western Canada and northern India, the recent review of Li et al. (2009) on N use in dryland cropping conditions in China brings the subject of rainfed farming and N use into clearer focus. Despite its antiquity in terms of settled agriculture and one of the centers of origin of many of the world’s food crops, notably cereals, wheat and barley, and pulses (Harlan, 1992), overviews of N in the Mediterranean region’s farming systems are limited.
3.2. Nitrogen in the mediterranean region The issue of N in the Mediterranean region was first addressed in a workshop (Monteith and Webb, 1991), convened in Aleppo, Syria, with special emphasis on the interaction of N with water. That workshop, which was funded by the United Nations Development Program (UNDP), focused on ‘‘increasing the fixation of soil nitrogen and the efficiency of soil water use in rainfed agricultural systems in the countries of North Africa and Western Asia’’ and set the agenda for future N research in the Mediterranean region. Much of the ideas for implementation of N research were outcomes of principles of dryland farming developed elsewhere, especially in Western Australia, which has a Mediterranean type of climate as well as cereal and legume crops in common with the Mediterranean region. A major focus of the early scientific efforts at International Center for Agricultural Research in the Dry Areas (ICARDA) was on nutrients (Anonymous, 1981), particularly N and P, in relation to rainfall and soil moisture under a project jointly funded with UNDP. This involved the establishment of a series of research stations/sites with weather stations across the rainfall transect in northern Syria and protocols for field research. The first initial report from that project (Harmsen, 1984) highlighted concepts of agronomic efficiency with respect to fertilizer N, and clearly showed the potential to increase rainfed wheat yields based on observations from field trials across the range of rainfall (200–500 mm year 1) in northwestern Syria. In many ways, such seminal studies helped to catalyze research on N throughout the countries of the Mediterranean region, mainly to the south (North Africa) and to the east (West Asia), that are included in the mandate area of ICARDA as one of the international agricultural research centers of the Consultative Group on International Agricultural Research (CGIAR) that focuses mainly on dryland agriculture. Since the early 1980s many aspects of the N cycle specific to rainfed areas have been addressed. Substantial gains have been made in areas such as soil
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testing for available N, calibration of fertilizer N application rates in relation to crops, soil and application methods, mineralization of SOM in relation to mineral and biomass N forms, differential responses of crop cultivars, role of soil moisture/rainfall in dictating crop yields, N in rotational systems, N cycling, potential pathways for N losses following application, crop quality, and modeling of N in rainfed agriculture, as well as the impact of supplemental irrigation on N use. Similarly, a wider perspective on plant nutrition was gained, with recognition of the need to identify and eliminate other nutritional deficiencies (Lonergan, 1997) as prelude to effective N use. While the recent review of Ryan et al. (2008a) briefly referred to N within the context of the rotation trials conducted by ICARDA in northern Syria, no review has yet dealt with overall N dryland research accomplishments in the entire region. Therefore, as a background to considering the various aspects of N research, it is pertinent to first examine the evolution of fertilizer use in the region.
4. Fertilizer use Trends in the Mediterranean Region In contrast to the developed countries of the west, the use of chemical fertilizers in agriculture of countries in North Africa and West Asia was a more recent development. In the past, the agriculture of the region was mainly based on dryland cropping with low yields and low inputs (Gibbon, 1981). However, the chemical fertilizer era began in the 1960–1970 period, marking a major departure from the traditional agriculture that existed for millennia. Coincidently, the period following the founding of ICARDA in 1997 witnessed an acceleration in fertilizer use in most countries of the region. In doing so, fertilizer use followed a pattern initiated some decades earlier in the West, with a dominance of N followed by P, and then potassium (K). Global consumption of N increased from 3 million tons (Mt) prior to 1940 to 84 Mt in 2002 (Ladha et al., 2005). Considerable regional differences existed with respect to per capita annual N use, from a low of 1 kg per person in subSaharan Africa to 38 kg per person in the United States. Increasingly, much of the growth in N fertilizer use was in developing countries, with a 17-fold increase in Asia (Dobermann and Cassman, 2004). Notwithstanding the relatively modest fertilizer inputs in the Near East or WANA region (IFA, 2009), the growth rate in N use was substantive. Most of the dryland agriculture countries of the region have experienced a 15–20-fold increase in N use in the past three decades. Fertilizer use is illustrated for the case of Turkey and Syria in Fig. 3. It follows a similar pattern in both countries despite the differences in consumption magnitude. While consumption was influenced by both rainfed and irrigated
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1.5 Turkey Million tons
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Figure 3 Fertilizer consumption (million tons) during the past 46 years in Turkey and Syria (figure drawn based on data from IFA, 2009).
agriculture, the figures generally reflected the total land area devoted to cropping. The consumption patterns reflect the need for N in cereals and nonlegume crops and the need for P. On the other hand, the small amounts of K used reflect the general adequacy of K in Mediterranean soils in general. While increased use of irrigation has partially contributed to expanded fertilizer use, dryland agriculture has been the main contributor. Despite the leveling out in the fertilizer demand in the past decade (IFA, 2009), due to various factors such as escalating energy costs, fertilizer demand worldwide is set to continue in the longer term (Tenkorang and Lowenberg-DeBoer, 2009), notwithstanding the current global economic downturns. The WANA region is unlikely to diverge from those global trends. With plant nutrient removal worldwide exceeding the current fertilizer nutrient input, the implication of negative nutrient balance has to be addressed. In the region, the low levels of K inputs, and in many cases none at all, have raised concerns about imbalanced crop nutrition ( Johnston, 1997), which in turn will negatively impact on N use.
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5. Response of Rainfed Crops to Nitrogen Fertilizer Growth of crops, whether rainfed or irrigated, is largely dependent on the supply of N, whether from the soil or added as fertilizer. If the supply of N from the soil is inadequate—which is mostly the case—the shortfall in optimum crop growth, within the particular growth constraints of the environment, has to be met by added N in the form of fertilizer, mainly commercial chemical fertilizers as organic source are limited and contribute little to the soil N supply. Thus, the need for N is related to the demand by the crop, that is, the yield potential. Under dryland conditions, such yields are conditioned by available soil moisture, soil characteristics, rotations, length of growing season, and management factors, especially weed and disease control. Total N required by the crop also depends on the type of crop and the concentration and distribution of N in the tissue, that is, in the case of cereals (grain and straw). Schlegel and Grant (2006) estimated that a wheat crop needs 30–50 kg N per ton of grain. Thus, a wheat crop of 1.5–2.0 t ha 1, which is common in the more favorable rainfall zone in the WANA region, would require up to 100 kg N ha 1 either from the soil or fertilizer. Given the pressing need to enhance dryland crop output in the Mediterranean region, major emphasis in planning the required research effort was given to N and its interaction with water (Monteith and Webb, 1991). Despite the increased use of N fertilizer in the past three decades, deficiency of N to varying degrees is ubiquitous. Various reports of field trials with N from countries of North Africa and the Middle East all attest the consistent responses to N fertilization, except in extreme moisturelimiting conditions (Ryan, 2004). Prior to considering N responses, it is pertinent to examine SOM in view of its relationship with total N in the soil, which in turn sets a ceiling on the contribution of soil to plant growth.
5.1. Soil organic matter and total soil nitrogen Much attention has been given to organic matter is soils in recent years because of its implications in maintaining the productive potential of soils to meet the world’s need for a stable food supply (Lal, 2001) and to its vulnerability in arid to semiarid regions of the world (Lal, 2002). The relatively limited data reported for SOM from the Mediterranean region indicate a range of 1–3% (Ryan, 1998), with most in the 1.0–1.5% range although some SOM values from shallow soils (Rendoll) in Morocco were up to 4–5% (Ryan and Matar, 1992). By comparison with more favorable climatic zones in the world, such values are low and indicate a
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limitation in terms of soil aggregation and serving as a reserve of N for crop uptake following mineralization. As might be expected from other semiarid regions, both SOM and total N were reported uniformly low in drylands of China (Li et al., 2009). Despite the importance of total N in soils, relatively few references are made to it in the literature, although the normal ratio of C:N is about 10:1. For instance, in one of the regional soil test calibration workshops (Ryan and Matar, 1990), only two countries (Yemen and Iraq) reported values for total soil N, with NO3 N being more frequently mentioned. In a subsequent international workshop, countries that reported total soil N included Pakistan, Morocco, and Iran (Ryan and Matar, 1992). Even in these studies that indicate total N in the soil, no attempt was made to link total soil N levels with the degree of crop response to N fertilization. However, at ICARDA, the significance of characterizing N in soils (as well as other nutrients) of its experimental stations and sites in Syria and Lebanon was recognized (Ryan et al., 1997a). In both dryland and irrigated cropping, nutrient distribution with profile depth is of particular relevance. Thus, in addition to classifying the soils and describing the relevant soil features, the profile distribution of available soil nutrients was described. SOM in the top 20 cm layer ranged between 0.8% and 1.5% at ICARDA main station, Tel Hadya. At sites in colder environments in Lebanon, SOM ranged between 1.2% and 1.4%, but at drier Syrian sites to the east, these values decreased as rainfall decreased, to as low as 0.4%. Regardless of the site, all SOM values showed a consistent decline with depth. Similarly, Kjeldahl or total N ranged from 0.5 to 0.9 g kg 1 at Tel Hadya (Fig. 4), being lower in drier Syrian sites and slightly higher in the colder Lebanon sites. A feature of the total N profiles was their variability even within a uniform agroecological zone or in the same station as illustrated by data from Tel Hadya. As with SOM, total N decreased with depth. However, nitrate and ammonium N fractions were low (0.0–20 mg N kg 1) and highly variable seasonally.
5.2. Field responses to fertilizer nitrogen Though no doubt many studies involved N responses of rainfed field crops in the Mediterranean region in the past few decades, there were two main focal points of dryland research involving N, that is, ICARDA in Aleppo in northern Syria and the Dryland Applied Agricultural Research Project in Settat, Morocco (Ryan et al., 2007). Mention of some of the studies in these two general areas is not to imply that valuable work in N was not done in other countries of the region. However, the general findings from both geographical areas are likely to be applicable to most areas of the Mediterranean region.
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0
0
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Figure 4 Distribution of nitrogen forms with depth at three sites at Tel Hadya station (adapted from Ryan et al., 1997a).
5.2.1. West Asia: The ICARDA experience From its inception in 1977, considerable emphasis was given by the ICARDA to soil nutrient characterization. Initial reports indicated that SOM and both N and P were low in the soil of Syria, but that K was adequate (Subramanian, 1981). These generalizations were likely to be true for the WANA region as a whole. The earliest work on N at ICARDA in the late 1970s–early 1980s was conducted under the auspices of the ‘‘Soil, Water, and Nutrient Research Project’’ and coincided with a period that saw the beginning of the period of fertilizer use in the region, particularly N. The initial work on N was given a boost by the emphasis on soil testing for N (Harmsen, 1986). As the Center is located in an area with ready access to the range of rainfall zone in northern Syria, and had experimental station in each zone (Ryan et al., 1997a), it was possible to conduct field trials from very dry to favorable rainfall areas. The network of experimental sites on this rainfall transect thus served as proxy for the range of rainfall environments in the Mediterranean region as a whole. Though these early agronomic studies demonstrated the overriding influence of seasonal rainfall on crop yields (Cooper and Gregory, 1987; Cooper et al., 1987, 1989; Keatinge et al., 1985a), the positive effect of fertilizer N was shown in all except the drier sites in low rainfall years (Harmsen et al., 1983; Keatinge et al., 1985b). At these sites, the responses to N were related to seasonal rainfall, that is, as rainfall increased so did the responses to N fertilizer.
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These observations from specific sites were borne out by researchermanaged trials in farmers’ fields through the range of rainfed conditions in northern Syria from 1986 to 1990. The overall responses with wheat were directly related to rainfall and negatively related to the initial soil mineral N values (Pala et al., 1996a). Similarly, an extensive series of on-farm trial with barley showed consistent increases to added N, despite the dominant influence of rainfall regime ( Jones and Wahbi, 1992). Despite the perception that fertilizer use, particularly N, was not profitable, economic analysis showed that fertilizer with barley in the drier areas (200–350 mm) was generally profitable at recommended rates (Mazid et al., 1999). Indeed, such analysis provided the basis for a change in government policy to allow for fertilizer allocation in the dry areas of Syria. However, in some early trials at two sites (Wahbi et al., 1994), yield responses to fertilizer, including N, were similar despite considerable differences in rainfall between the two seasons (1987/1988 and 1988/1989). Interestingly, this study did not show any difference between farmer-managed trials and researcher-managed trials in terms of crop yields. With developments in plant breeding leading to new and more productive varieties, and improvements in agronomy and crop management such as in tillage and cultural practices, the role of soil fertility was seen as important as ever (Ryan, 1998). Special emphasis was given to the role of N in integrated crop production systems, especially involving rotations or crop sequences (Ryan and Abdel Monem, 1998). This aspect is discussed in Section 9. 5.2.2. Other countries of West Asia Although research on N in dryland cropping systems occurred in most countries of West Asia to varying degrees, a snapshot of these activities is seen through the regional soil fertility/soil test calibration workshops. The universal concerns about N use in rainfed cropping systems of the Mediterranean region in the early years of chemical fertilization are reflected in topics presented at the First Soil Test Calibration Workshop, which established common protocols for fertilizer field trials (Soltanpour, 1985). These included appropriate soil test methods for determining N fertilizer requirements of rainfed crops in Pakistan and on-station fertilizer trials in Jordan. In the second of these workshops (Ryan and Matar, 1990), addition contributions included N responses of barley grain and forages in Cyprus and soil N forms and N-indices of wheat from Iraq. Despite years of drought that devastated many agronomic field trials in the region, the momentum of applied N research continued. In the third of the soil test calibration workshop series (Ryan and Matar, 1992), the expanded contributions included inorganic N in relation to soil moisture in a trial from Central Anatolia in Turkey.
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The expansion of concerns about fertilizer N in 1990s, and its implications for both crop production and the environment, as reflected in a subsequent soil fertility workshop (Ryan, 1997), was driven by increases in N use, especially in countries of WANA such as Iran, Pakistan, Syria, and Turkey, where rainfed agriculture is a significant contributor to N demand (Abdel Monem and Ryan, 1997). Despite relative percentage increases in N, other countries such as Yemen, Libya, and Jordan use small amounts of N fertilizer. Building on previous N research, Abdel Monem and Ryan (1997) called for increased NUE through a rational approach to N fertilizer recommendations, modifying N fertilizers, and exploiting biological N fixation (BNF) in integrated crop rotation systems. Apart from the contribution to the regional soil fertility meetings, various studies from some countries of West Asia, notably Turkey, Cyprus, and Lebanon are worthy of note. In the relatively favorable rainfall (600 mm) region in the C ¸ ukurova region around Adana in the Mediterranean area of Turkey, a 4-year trial (Kırda et al., 2001) examined yield responses and N recovery (with 15N). In contrast to other dryland N-response studies, maximum yields occurred with N levels as high as 240 kg ha 1 achieving grain yields of 4.9–6.9 t ha 1 over the period of the trial. With 15N recovery of 50–60% at maturity, over 95% of the applied N was accounted for in the crop off-take and in the soil. The authors discounted leaching losses below 90 cm and proposed splitting N application between planting and tillering. A related rainfed trial in the same region of Turkey (Ibrikci et al., 2001) found a similar response range at four sites in the region, and concluded that the amount of mineral N in soils prior to planting should be considered in making N fertilizer recommendations. Cyprus was another site of considerable dryland N research activity in the Middle East (Krentos and Orphanos, 1979; Orphanos, 1994; Papastylianou, 1987, 1993a,b). Much of this work was conducted at two research stations (Dromolaxia, Laxia) with differing mean annual rainfall (250 and 350 mm), and in the context of crop rotations with either fallow or vetch as a replacement for fallow, or in continuous barley. Given the low rainfall in Cyprus and the consequent precarious nature of soil moisture conditions, barley is preferred to wheat as it is more drought-tolerant. Fertilizer N recommendations were linked to rainfall, with 30 kg ha 1 being the norm, increasing to 60 kg N ha 1 in years or locations with higher rainfall. The N application could be adjusted in spring with favorable rain and then applied as a topdressing. Applying excess N is generally shown to have a negative effect on yield, including ‘‘haying off.’’ With the introduction of forage vetch in rotation with barley, the fertilizer replacement value of the legumes was 60 kg N ha 1 or the amount of N required to produce the same yield under continuous barley; the N replacement value was 30 kg N ha 1 for fallow. Nitrogen fertilizer applied to continuous barley was not
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sufficient to compensate for the rotation effect that vetch and fallow (250 mm site) had on the subsequent grain yields of barley. Research on N in Lebanon ranged from fertilization of cereals and N supplementation for legumes to indirect N fertilizer effects. A field trial in the Bekaa Valley showed that N increases yields of dryland semidwarf Nexpak wheat up to 290 kg N ha 1 reflecting the high yield potential of the variety in relatively favorable growing conditions. Grain and straw protein also increased with added N (Barg et al., 1982). Although soybeans (Glycine max L.) are normally grown without added N, there were indications that BNF alone was not adequate for maximum yields, especially at high planting density. This hypothesis was tested with an indeterminate soybean cultivar at high seeding densities (Solh et al., 1986). While seed inoculation with rhizobia was only effective in a site where soybeans had not previously grown, neither soil nor foliar-applied N had any effect. Though not directly related to crop growth, one laboratory study examined the effect of a novel N fertilizer, urea phosphate, on soil properties (Ryan and Tabbara, 1989). In soil where the salinity and sodicity had been artificially raised to various levels, application of this new material in solution, to simulate irrigation, caused leaching of the exchangeable sodium due to the reaction of the fertilizer with soil carbonates to increase the concentration of Ca2þ to replace this sodium. Thus, urea phosphate could be an effective source of N and P, and facilitate irrigation in sodic soils where infiltration and permeability is impaired. 5.2.3. Morocco and the Maghreb countries Following several years of drought in the rainfed cereal-growing belt of central Morocco with rainfall from 250 to 450 mm year 1 in the mid1980s, with its attendant social and political consequences, a major drive was made to stabilize and improve agricultural production in that region of the country. This effort was the main focus of the Dryland Applied Agricultural Research Project as a joint venture between the Mid American International Agricultural consortium, The United States Agency for International Development, and the host country’s agricultural research organization (Ryan et al., 2007). Among the various strategies that were to be adopted to achieve the development goal was an emphasis on soil fertility and chemical fertilizer use (Shroyer et al., 1990), especially in relation to improved cereal varieties. As limited fertilizer had traditionally been used in this area of precarious rainfall and uncertain yields, the focus of the project’s initial efforts was on N and P. In the trial’s first years (with below-average rainfall) N application increased wheat grain yield from 14% to 190% in five out of the nine sites depending on previous crop and level of inorganic N (Soltanpour et al., 1986). Subsequently, in one year of above-average rainfall (1987/1988), responses to N were significant up to 80 kg N ha 1 applied as urea fertilizer, but
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responses were insignificant where a legume was previously grown (Abdel Monem et al., 1990a). Although most field studies with N involved currentyear responses to N, one microplot study with 15N examine a residual or carryover effect (Abdel Monem and Ryan, 1991). With yields being doubled by added N in the wet year (460 mm), recovery of labeled urea N was about 52%, with about 32% left in the soil and 16% lost from the system or uncounted for. In the second drier year (200 mm) there was a residual response to the two N application rates (80, 120 kg N ha 1), with recovery of 7.2% and 8.6% for the added 15N. The data indicated that though unused N can be carried over to the next cropping season, some of the N left in the soil is immobilized and not readily available for crop uptake. Other trials assessing residual N over a 3-year period were inconclusive due to low seasonal rainfall, but in some cases, the 120 kg N ha 1 rate had a carryover effect (Abdel Monem et al., 1990b). The early dryland fertilizer trials in Morocco in the 1980s coincided with similar agronomic studies in countries of the Maghreb region such as Tunisia (Gharbi et al., 1990). Following the early project observation on N with wheat, the fertilization program was expanded to cover other more drought tolerant cereal crops such as barley and triticale (Triticosecale) and a range of sites throughout the dryland rainfall zone. Special attention was given to the interaction of N with wheat varieties susceptible to the ravages of the Hessian fly (Mayetiola destructor). This was the subject of an initial demonstration experiment that incorporated N (at 100 kg ha 1) into an assessment of a resistant variety ‘‘Saada’’ and susceptible ones (Abdel Monem et al., 1990c). Though all varieties significantly responded to N, as it was a high rainfall year (471 mm), no clear effect of N in mitigating the effect of Hessian fly was evident due to low attack incidence. However, a series of on-farm trials across the rainfall zones involving genetic resistance and chemical control of Hessian fly, there were cultivars N interaction in three of the five sites (Ryan et al., 1991a). Regardless of the severity of Hessian fly infestation, there was little evidence that N fertilizer application could effectively compensate for the damage done at tillering. In a more comprehensive treatment of the subject of Hessian fly resistance, Ryan et al. (1998) concluded that the quest for incorporating resistance genes in other varieties should continue, with N being an essential element in exploiting the yield potential of such improved varieties. Given the cost of chemical control in Hessian fly, as well as the cost of N fertilizer, this was considered a key issue for farm profitability. In that five-site trial, grain and straw yields varied with an optimum response of 40 kg N ha 1 (Abdel Monem and Ryan, 1990). Average benefit–cost (B/C) ratios were 4.8 for the genetically resistant Saada and 2.6 for the Nesma variety chemically treated. With increasing N above 40 kg ha 1, B/C values diminished. The study highlighted the economic benefits of N fertilization of insectresistant varieties.
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The ubiquity of N deficiency in cereals throughout the entire rainfall zone in central Morocco was demonstrated in a ‘‘windscreen’’ survey of hundreds of cereal fields from Meknes (500 mm) to Chamia (240 mm) at the tillering to stem elongation (Feekes 5–6) stage (Ryan et al., 1992). Visual ratings were made based on the intensity of green color, while tissue samples were taken from a limited number of fields (25) for N analysis. Most of the fields observed (77–91%) appeared to have varying degrees of deficiency; with decreasing rainfall, the degree of apparent N deficiency increased. However, plant tissue N concentrations were not closely related to the visual observations. Notwithstanding its limitations, visual observations have a role in assessing N fertilizer needs, particularly in developing countries where more sophisticated approaches are not available. An outcome of the field trials involving N in Morocco was the appreciation that mineral N is a dynamic rather than a fixed feature of soils, especially soils high in organic matter. Soil N test values varied widely throughout the season depending on conditions that influenced mineralization (Ryan et al., 1993). Similarly, an intensive field study of a site with shallow soils showed that all nutrients and SOM varied spatially over short distances due to various influences, small fields, the grazing animal, hand-application of fertilizers, and natural soil variation (Abdel Monem et al., 1989). With emphasis in the new Hessian fly-resistant Saade wheat variety, other field trials included this potentially important variety. In one trial that examined timing of N fertilization (Ryan et al., 1989), grain yield was not affected by application timing, but N application as ammonium nitrate in spring or split between fall and spring had slightly higher dry matter yields. However, had urea been used, spring application may have been superior due to NH3 volatilization. (This aspect was assessed in detail by Abdel Monem (1986) in Syria, as discussed in Section 8). The assessment of timing of fertilizer N was applied to a wider range of cereals (two barley varieties, one wheat and one triticale variety) in another study (Ryan et al., 1994). Again, this showed that there was no difference between fertilizer application times. However, application of some N at sowing has the advantage of assessing weather conditions and stored soil moisture in early spring prior to topdressing. Under drought conditions farmers can reduce or eliminate N, or indeed graze the cereal if a reasonable crop yield is not likely. The concept of varying N application was applied in higher rainfall zones in Morocco, considering growth stages of two wheat cultivars (Mosseddaq and Smith, 1994). Using a total of 120 kg N ha 1, 40 kg was applied at floral initiation, and the reminder at onset of stem elongation, at anthesis, or in equal parts at both stages. As expected, there were significant yield responses in both years, but the effect was affected by the timing. The greatest effect occurred when the final increment of N was applied just prior to flower initiation, and the lowest response was when N was withhold at the onset of stem elongation and the final increment was applied at anthesis.
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This study showed that timing of N fertilizer application to coincide with maximum demand for N by the rapidly growing crop can lead to greater N-use efficiency. In an area of Morocco further north with a higher rainfall (>526 mm mean annual) than in the dryland area of central Morocco, the issue of timing of N fertilizer assumed more importance than in the drier areas. In field trials on a Vertisol in the Meknes area, applications of 100 kg N ha 1 was split into 25% at planting, 50% at tillering, and 25% at stem elongation (Corbeels et al., 1999a). The N application increased total dry matter but not grain yield, and reduced mean grain weight from 32 to 26 mg. The absence of such a yield response is attributed to mineral N already within the profile. While total N uptake was increased 50% by applied N, the effect of splitting the N application was not apparent. However, using 15N, recovery of N was influenced by N application timing with recoveries of 31% for the 3-split application and 24% for the 2-split application. More N in the plant was derived from fertilizer when it was applied early in the growing season than late in the season, that is, about 13% when applied at tillering and 5% at stem elongation. Despite the absence of grain yield differences due to splitting N the study showed that as much as 90% of the applied N was recovered either in the plant or the soil. An indirect effect of N fertilization has been its relationship with disease resistance. One trial examined the effect of N fertilization on the incidence of Tan Spot (Pyrenophora tritici-repentis), a major cereal disease in Morocco ( Jones et al., 1990). The rationale was based on indications that N, especially the ammonium form, can affect development and expression of fungal disease. While the three durum wheat lines (two susceptible and one resistant) responded to N up to 40–80 kg N ha 1, there were differential responses with the lines. Interestingly, the effect of increasing N on disease incidence was inconsistent; of the two susceptible lines, added N increased disease incidence in one and decreased it in the other, while the effect was inconsistent for the ‘‘resistant’’ line. Although the main focus of the N trials was grain or straw yields, quality components of grain were considered in one study of durum wheat (Ryan et al., 1997b). This trial with five varieties (Kyperounda, Marzak, Massa, Cocorit, and Karim) showed that N had no effect on grain N or kernel weight, except at the highest N rate (120 kg ha 1), but increasing N application tended to decrease the incidence of ‘‘yellow berry.’’ As consumers prefer durum wheat grain for semolina to be vitreous, with minimum or no ‘‘yellow berry,’’ adequate N fertilization produced a desirable nutritional side effect in addition to yield. As barley had been traditionally grown in Morocco’s dryland area without fertilizers, and as triticale was being heralded as a suitable drought-resistant crop, both were included in the N fertilizer trials (Ryan et al., 1991b) with the trials included N application rates up to 150 kg
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N ha 1 at on-farm sites on a rainfall gradient. While two sites were eliminated because of extreme drought, overall yields and the responses to N were related to rainfall. Maximum increases were at 30 kg N ha 1 in the low rainfall site (270 mm), with consistent increases in added N up to 150 kg N ha 1 for the two wetter sites (370, 396 mm). Both barley and triticale responded similarly to added N. Other trials in the Settat area (386 mm, mean annual rainfall) for 2 years showed that all improved barley cultivars respond well to N (Ryan et al., 2009a). The positive showing of triticale relative to barley in the various field trials led to a consideration of the possible interaction between varying seeding rates and N fertilization (Mergoum et al., 1995). The N by seeding rate interaction was significant at the more favorable Settat site but not at the drier Skhour Rehamma site. Fertilizer N did not compensate for the reduction in seeding rate, probably due to the low tillering capacity of triticale. The authors concluded that seeding rates of 160–200 kg N ha 1 are justified when used with adequate N fertilization. Though N research in Morocco was almost exclusively related to rainfed cereals, legumes, which fix atmospheric N, merited little attention. However, given the need to enhance herbage output from native pastures, the impact of N fertilization was assessed in terms of biomass and botanical composition (Tiedeman et al., 1994). Total forage yield was lowest without N (2.76 t ha 1) and highest with N (3.74 t ha 1). However, the proportion of legumes within the biomass increased with P but decreased with N. Conversely, nonlegumes were increased by N but decreased by P. Thus, N fertilizer can influence plant composition within natural communities or in ‘‘weedy fallow’’ commonly practiced in Morocco’s dryland area. While most of the activities related to N research were in central Morocco’s dryland zone, under the auspices of the Dryland Project in Settat, parallel developments occurred in other countries of North Africa (the Maghreb area), several of which were reported in regional workshop proceedings (Ryan and Matar, 1990, 1992). Numerous on-farm trials in Tunisia (1986–1990) examined the relationship between preplant soil N and grain yields of durum wheat. Based on scatter-response diagrams, the critical response level to N was 10 mg kg 1 in the soil (Gharbi et al., 1992). Agronomic studies with N in Libya revealed considerably more variation than in Morocco, largely due to a higher proportion of sandy soils, and erratically distributed rainfall, with crop growth often constrained by hot desert winds (‘‘Ghibli’’) that occur during maturation (Azabi, 1992). Nevertheless, some trials showed considerable responses to N (30–75 kg N ha 1) depending on location and environmental and soil conditions. Research in Algeria recognized the importance of considering agroecological zones in agronomic studies (Gaid, 1992). Fertilizer N application was split between seeding and tillering, with higher amounts in the higher rainfall zones (>500 mm). Trials with wheat, barley, and oats (Avena sativa)
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showed that 2.6–2.9 kg N was required for each quintal (100 kg) of grain. Based on an application of 33.5 kg N ha 1, widely varying fertilizer efficiencies were indicated, that is, 30% for durum wheat, 53% for bread wheat, and 70% for barley. These brief insights into N research in the Maghreb countries reflect the perceived potential of N to increase dryland agricultural output in the region. Though geographically not part of the WANA region, much of the research on N in Spain was relevant to the Mediterranean region as a whole, where dryland N research paralleled similar efforts in the Maghreb or North African countries. In contrast to most N studies in the Maghreb, assessment of N fertilization in the production system was in the context of long-term crop rotations with considerations of preceding crops, and tillage system. This cropping systems research of Lopez-Bellido and colleagues in Cordoba addressed the impact of rotations on cereal yields (Lopez-Bellido et al., 1996, 2000), soil water content and crop water use (Lopez-Bellido et al., 2007a,b), sunflower, faba bean, and chickpea in the rotations (LopezBellido et al., 2002, 2003, 2004), and soil nitrate (Lopez-Bellido Garrido and Lopez-Bellido, 2001). Of particular interest in these studies was the effect of N fertilizer. The site of the long-term trial was subject to periodic flooding of the heavy clay soil, which negatively affected crop yields. Yet, wheat responded up to 100 kg N in wet years but no response occurred in drier years (Lopez-Bellido et al., 2000). Yields under conventional tillage were higher at all N application rates, while the effect of N was more marked for rotations without a legume. In the long-term trial, it was interesting to note that monoculture led to an accumulation of NO3 in the profile due to consistently lower yields. Other work on N fertilization of barley from a more continental environment in northeastern Spain has also relevance to semiarid Mediterranean conditions (Angas et al., 2005), with a focus on N efficiency in the context of reduced or conservation tillage. In contrast to the work of Mosseddaq and Smith (1994), losses of 30–80% of the applied N occurred each year, especially at high N application rates, with N recoveries of 28–46.5%. The NUE was decreased with increasing N and by tillage, which increased soil mineral N. Implications of this site-specific work are that N fertilization rates could be decreased by 50% and that no-till systems do not require increased amounts of N for barley production in the sites of the study. Only in wet years are higher yields with no-till obtained when same N is applied. Similar to Spain, conditions for growing rainfed wheat in semiarid environments in southern Italy are relevant to the WANA region. Field trials examined the influence of fertilizer N (up to 180 kg ha 1) on soil mineral N, growth parameters, and quality indicators (Montemurro et al., 2007). The 120 kg N ha 1 rate was considered the optimum balance between yield and N utilization. In fact, increasing the N rate to 180 kg ha 1 did not increase grain yield or grain protein content, but did
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increase the residual mineral N in the soil, making it susceptible to leaching loss. As in most other studies of N around the Mediterranean, the variation in weather conditions affected winter wheat yield, grain quality, N utilization, and plant N status. Another study from Italy considered N responses of durum wheat in relation to the previous crop (Pacucci et al., 2004). While yields were limited by low rainfall (1999 and 2000), they were not affected by the previous crop, except for a 5% increase of wheat after vetch. There was no difference between the three N levels (0, 45, and 90 kg ha 1) with wheat after wheat, but the response was significant (þ 20.6%) after vetch. With some genotypes, there were significant interactions between previous crop and N fertilization. The trial clearly shows the limitation of using one variety in such studies involving N.
5.3. Genetic differences of crops for nitrogen fertilization In the past, soil scientists and agronomists, in their quest of improving crop yield, have focused on improving nutrient availability and efficiency for crops without considering differential responses of crop cultivars to N due to genetics. Similarly, breeders have sought improvements in yields and adaptation to abiotic stresses (Ladha et al., 2005). While an improvement in yield stability leads to improvement in the efficiency with which fertilizer N is converted to an economic output, little attention was given to genetic differences between cultivars with respect to N. Crop cultivars that are inherently more efficient at absorbing N from the soil pool, and assimilating it within the growing plant, result in less fertilizer used per unit of crop output. Several studies cited by Ladha et al. (2005) point to genetic differences with respect to N. Differences in NUE were attributed to differences in the amount of N accumulated before anthesis; for wheat, high yields depended on assimilation after anthesis. Similarly, hybrid rice was more efficient at using N than conventional rice. While considerable genetic variability existed with internal NUE depending on whether the environment was a low-N or high-N one, the improvement in efficiency was attributed to higher harvest index (improved sink) rather than better photosynthetic efficiency. In contrast to improved N recovery efficiency, a downside of internal efficiency is reduced grain protein content. With respect to cereal grain production in the Mediterranean region, Fischer (1981) indicated that as improved short-straw cereal lines are already highly N-responsive, they are also highly efficient in terms of yield per unit N supply. He contended that this improved N efficiency was related to more grain per unit of N taken up by the crop rather than more N uptake: it was also related to higher harvest indices and greater proportion of total N uptake in the grain at maturity. Not surprisingly, little or no further effort was expanded by breeders to specifically further improve N efficiency, but rather focused on the normal yield and adaptation goals.
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Despite the absence of deliberate breeding for NUE, a number of studies have shown differential responses with N fertilization of existing cultivars. Following a dryland field trial with 45 genotypes of wheat, barley, and triticale, Anderson (1985a) showed that some lines yielded better under low fertility conditions while others were capable of responding well to higher levels of N fertilizer. He concluded that some lines that are efficient at using soil N may be less efficient in using applied N. Some of the earliest studies with barley and durum wheat (1981–1983) studied the effect of splitting N (sowing and tillering) for various varieties (Anderson, 1985b). In two of the trials, less N was required for maximum yields when all N was applied at the tillering stage. As the proportion of the total N applied at sowing was increased, the amount required for maximum yield also increased. Where three barley varieties were compared, yield responses to N were significantly positive to negative depending on the N application ratios. A side aspect of the trials with wheat was the varying times of N application influenced the percentage of vitreous kernels, an important quality component for durum. A companion study of Anderson (1985c) identified a range of factors that influenced the differential response of the various cereal varieties, that is, soil P availability, initial soil mineral N status and possibly soil water and air temperature. Some years later, trials with increasing levels of supplemental irrigation showed differences in N response among the five varieties of bread wheat (Oweis et al., 1998), but little response differences with five durum varieties (Oweis et al., 1999). Similarly, in a greenhouse study of 30 improved barley lines and landraces, a response ‘‘crossover’’ was observed (Ryan et al., 2008b), with landraces being less responsive to N. Though not directly related to N response, considerable varietal differences among faba bean cultivars were shown for both yield and N fixation (Silim and Saxena, 1992). While the focus of much of the applied agronomic research in Morocco was on assessing crop cultivars under varying rainfall environments, differences between cultivars in terms of responses to N were minimal for some field trials with barley (Ryan et al., 2009a). This suggested that the lines tested were already improved to some degree and therefore N-responsive. However, other studies (Mergoum et al., 1994) had shown differential responses among triticale cultivars to N fertilization. The outcome of such studies is self-evident; where crop cultivars are bred for yield and adaptation, they are also responsive to N. There is little rationale for selecting nonimproved lines.
6. Assessing Soil Nitrogen Status for Crop Yields The extent to which a crop responds in terms of growth to the application of any particular nutrient as a chemical fertilizer or as an organic amendment depends largely on the size of the available pool or amount of
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that nutrient in the soil. The principle of soil testing hinges around a chemical test that extracts the available fraction of the nutrient, thus mimicking or simulating what the plant encounters in the soil. The important criterion is that the test values correlate well with plant uptake from the soil. The subsequent step is to calibrate fertilizer application rates in the field for economic response and optimum use efficiency (Brown, 1987). Where test values are low, that is, deficient level of the nutrient, responses to added fertilizer are highly probable. Conversely, as the soil test level is higher, proportionally less fertilizer is needed, and where the nutrient test value exceeds the ‘‘critical’’ value for nutrient sufficiency, no fertilizer may be needed. Soil testing is now a well established field of soil science, with tests for individual nutrients now widely used with adaptations for specific soils, environments, and crops (Walsh and Beaton, 1990). Practical and economic considerations have given rise to multielement tests. With respect to the Mediterranean region, the approach to the introduction of soil testing was to adapt tests proven to be successfully elsewhere and to assess such tests under soil and cropping conditions in the region. Though total N determined by the Kjeldahl method is a descriptor of soil properties in most studies, it is little or no value as a guide to fertilizer N needs for crops. Specific tests for N are generally less satisfactory than for elements such as P or K largely due to the fact that the extent of SOM mineralization is unpredictable in semiarid rainfed conditions since it is dependent on temperature and soil moisture conditions during the growing season (Dahnke and Johnston, 1990). Nevertheless, the nitrate test has been shown to be a useful predictor of available N in the soil in same conditions (Ward, 1971). Though various studies in the Mediterranean region involved assessment of tests for plant-available N, some examples will be given to illustrate the particular adaptation of the test. In the early years of dryland research at ICARDA, the nitrate test was applied at various sites under field conditions for two years with different antecedent crops (Matar et al., 1990). Both NH4 N and NO3 N were sampled in increments of 20 cm down to 1 m. When all sites were considered, the NO3 N values in the top 60 cm at sowing correlated best with wheat grain yield. The critical NO3 N level, based on the Cate–Nelson graphical method, varied with yield goals and previous crop. Thus, the critical value ranged from 8 mg kg 1 for wheat after legumes (lentil and chickpea) with grain yields less than 2.5 t ha 1 to 15 mg kg 1 when preceded by summer crops (or fallow) and with grain yield exceeding 4 t ha 1. In essence, to be of value as a guide for fertilization, the test value has to consider soil and crop factors. One obvious drawback of the NO3 N as used by Matar et al. (1990) test is that involves sampling to a depth of 60 cm. While it may embrace the root zone, such sampling at such depths is impractical for routine soil testing and is unlikely to be adopted.
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Probably the most extensive work on NO3 N testing was in dryland cropping in Cyprus (Papastylianou, 1997). In contrast to Matar et al. (1990), the Cypriot rainfed barley study involved shallow sampling (0–15 cm), over a 7-year period at two locations of varying mean annual rainfall (250 and 350 mm). Nitrogen was applied at 0, 30, 60, and 90 kg N ha 1. Various approaches were used to establish critical NO3 N levels: regression, Cate–Nelson, quadratic response, and plateau model. However, correlations between soil NO3 N and crop yields were poor. This was attributed to inconsistency in the onset of seasonal rains, which enhances N mineralization and low and uneven rainfall which determines response of cereals to N supply. This led Papastylianou (1997) to conclude that soil testing is not an accurate method for N fertilizer rate recommendations critical levels established should only be used to indicate responsive and nonresponsive sites considering climatic conditions for mineralization before sampling. Efforts to promote soil testing as a basis for fertilizer use recommendations were given considerable inputs by the UNDP-supported Soil Test Calibration Network operated by ICARDA in partnership with the various national programs in the region. Despite the unreliability of using soil nitrate in testing for available N due to the unpredictability of mineralization, the early indicated from field research at ICARDA were that the NO3 N test, based on analysis prior to cropping was well correlated with N uptake by the crop (Harmsen, 1986). However, this relationship was subject to a range of soil, environment and crop-specific influences. Ammonium–N was shown to be more influenced by biological transformation and to be poorly related to plant uptake in contrast to NO3 N. In a survey of forms across the rainfall zones in northern Syria, based on topsoil sampling (0–20 cm), there was no consistent relationship between rainfall and total and mineral N (Ryan et al., 1996). Subsequently, most studies reported in regional workshops of the Network (Ryan, 1997; Ryan and Matar, 1990, 1992) emphasized P, many reported use of mineral N (NH4 þ NO3) tests. Some limited observations from a favorable rainfall area in Morocco indicated that yields were related to NO3 N but poorly related to total mineral N, which included NH4 N. In drier areas of central Morocco, soil N tests were not consistent with crop yields, but generally differentiated between N-deficient and N-sufficient soils. In a more recent report from the more favorable rainfall zone in northern Morocco, Corbeels et al. (1999a,b) followed the dynamics of N in heavy clay Vertisol. Leaching and denitrification was observed to occur after heavy rainfall, but as NH4 N was barely taken up by the wheat crop, NO3 N was considered a better indicator of plant-available N than total mineral N on that soil. Reports from the Anatolian plateau of Turkey showed significant accumulation of mineral N in the soil profile after various legumes in a cereal rotation, but neither NH4 nor NO3 alone was a good index of N requirement.
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Research in Spain has shown that NO3 concentration in soils sampled to a depth of 30 cm was useful for fall-planted sugar beet in distinguishing between sites that were responsive to applied N and those that were not when there was no leaching or moisture stress (Bilbao et al., 1996). In that regard, it is interesting to consider the influence of rainfall even in low rainfall environments. In studies of many field sites in Anatolia, Fox et al. (1970) observed that heavy rainfall events can leach NO3 from the rooting zone and thus contribute to early-season N deficiency even in soils well supplied with N.
6.1. Nitrogen mineralization indices Cognizant of the shortcomings or unreliability of soil N tests involving mineral N forms, and being aware of the influence of moisture and temperature on the microbial mediated transformation of N from organic to inorganic forms (Stanford and Smith, 1972), various laboratory incubation studies were seen as an alternative to sample soil tests. Studies from Syria and Morocco are representative of these attempts. Work in Syria examined the mineralization potential of 18 soils that included several of the soil orders found in the Mediterranean region, that is, Mollisols, Entisols, Gypsiorthid, Vertisols, and Inceptisols (Matar et al., 1991). With incubation at 25 C, samples were leached at 2-week intervals up to 22 weeks and NH4 N and NO3 N determined in the leachate. The mineralization potential (N0) was estimated by an empirical linear equation, exponential, and a hyperbolic model equation (Stanford and Smith, 1972). Estimates of N0 varied among soils, being highest for Mollisols and least for the sandy Entisol, while the hyperbolic model gave higher mineralization estimates, the empirical, and exponential equations gave similar estimates. It was concluded that although mineralization potential varied among soils, the rates of mineralization were similar, indicating that the organic N compounds contributing to mineralizable N were of similar composition in these soils. Attempts were made in Morocco to improve soil testing for N fertilization in dryland cropping conditions by examining mineralization under controlled conditions (El Gharous et al., 1990). In his overview on N in dryland cropping systems, El Gharous (1997) indicated that the mineralization potential of Moroccan soils ranged from 62 to 273 mg N kg 1. This considerable variation was attributed to the quantity and quality of SOM. Supporting this conclusion, Soudi et al. (1990) showed that most of the mineralized N comes from the hydrolyzed fraction of the organic matter in the soil. These various mineralization studies helped explain why soils may vary in response to applied N and why mineral N may not reliably reflect the capacity of soils to supply N to the growing crop. The studies did not, however, enable a more valid and reliable estimate of N fertilizer
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recommendation. However, such studies are valid indicators of the N-supplying capacity of soils where SOM has been built up as a result of multiyear crop rotations involving forage legumes (Ryan et al., 2003a). While mineralization of SOM is mediated by moisture and temperature, the dynamics of inorganic N also depend on the composition of the organic materials added to the soil (Hadas et al., 2004). Organic materials with soluble components mineralize rapidly, while materials with more recalcitrant components such as lignin decompose more slowly. This is a particular relevance in dryland cropping systems that involve soil incorporation of cereal residues.
6.2. Plant analysis for nitrogen management In contrast to studies on soil N in the Mediterranean region, little use has been made of plant analysis as a basis for N fertilizer recommendation despite the well established criteria for analysis of plant material of crops ( Jones et al., 1991). However, N analysis of plant material is used as a basis for examining efficiency in terms of N recovery or uptake (Harmsen, 1984) or assessing the influence of crop management and rotations on nutritional quality, that is, protein in the cereal grain and straw (Ryan et al., 2008c). Much has been written about the Diagnosis and Recommendation Integrated System (DRIS) and its potential for use in the Mediterranean region (Gharbi, 1997). Little actual assessment of the new approach to nutrient diagnosis has been made in the region and, given the state of analytical technology, it is unlikely to be adopted. The DRIS system is based on nutrient ratios in the plant and is independent of plant age. Despite its theoretical advantages in nutrient diagnosis, the analysis and its interpretation requires a level of sophistication that does not yet exist in the region or in developing countries in general. Plant analysis can be a complementary approach to soil analysis in the diagnosis of crop N deficiency. Plant analysis is invariably based on sampling whole plant tissue or specific plant parts at specific growth stages of the crop. Implementation of the nutrient concentration is based on a range of values indicating deficiency, sufficiency, and excess ( Jones et al., 1991). One of the few countries to use plant analysis in diagnosing nutrient constraints in dryland cropping is Pakistan, with conditions reasonably similar to the Mediterranean region. Based on studies in Pakistan, Rashid (1997) presented a range of such data for the major crops in the country as well as critical values in the seeds of various crops. In fact, Rashid and co-workers (Rafique et al., 2006) used plant analysis in the diagnosis of Zn deficiency in wheat, in one of the few studies to employ such an approach. While the use of total nutrient concentration in plants as guide to the nutritional state of the crop and possible interaction with the N fertilization is not common in the WANA region, the use of tissue testing as a basis for
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N use is even rarer. However, one recent study from Turkey adopted this approach to monitor N fertilizer use, particularly, in view of the environmental implications of excessive N fertilizer use (Korkmaz et al., 2008). As soil tests are in essence postmortem approaches to nutrient management, the tissue testing approach can be complementary to soil analysis. Using a color index based on nitrate extracted from fresh samples of the grown crop, it was possible to identify fields that were deficient in N or where N was considerably in excess of crop requirements, especially where well waters used for irrigation were high in nitrate. Through relatively few dryland N studies deal with N color intensity and tissue N concentration, one report on winter wheat grown in dryland conditions in southern Italy (Montemurro et al., 2007) showed that SPAD readings and stem nitrate concentrations can serve as a guide to modify the N fertilization to reach its optimum level during plant growth.
7. Nitrogen Fixation Under Mediterranean Dryland Conditions In the context of atmospheric N2 fixed by leguminous crop and plants, it is pertinent to mention the role of such plants in the historical evolution of the type of dryland agriculture that characterized the Middle East region. Being the center of origin of various legume species, one can surmise that such crops had a significant influence in early settled agriculture (Harlan, 1992). Indeed the written record from Greek and Roman times mentions legumes in rotations with cereals and the predominantly cereal-fallow systems that sustained cropping in such a water-stressed environment (White, 1963, 1970). Both Greeks and Romans recognized that legumes had a benefit to cereal crops, without being aware that it was related to N. Despite the antiquity of legumes in the region, their use had declined over the centuries. However, land use pressure contributed to decreasing fallow leading to continuous cereal cropping. Similarly, with increasing populations of small ruminants, increasing pressure for livestock feed was put on marginal areas, with consequent risks of land degradation. The rationale for the resurgence of interest in food and forage legumes was well articulated by Harris (1995). The belief that legumes could potentially contribute both to cropping sustainability as well as relieving pressure on marginal lands laid the foundation of the extensive research related to N fixation and related areas from 1980 to 1995 at ICARDA. Biological fixation or BNF is a function of the symbiotic Rhizobium and the host legume plant. That symbiosis is fundamental to the success of using legumes in any cropping system (Amarger, 2001). However, this symbiosis is not always optimum in moisture-stressed dryland environments, where
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the rhizobia may have evolved for survival rather than efficient symbiotic N fixation. Therefore, it was important to assess the effect of environmental factors on the occurrence of rhizobia in the soil and their relationship with crops in the Mediterranean region. In the foregoing sectors, we consider the research achievements in both categories of legumes separately followed by a brief discussion on development in assessing BNF.
7.1. Food legumes Though cereals dominate the cropping systems of the Mediterranean region, food legumes play a significant economic and biophysical role. The main food legumes are chickpea and lentil with relatively smaller amounts of peas and faba bean, the latter which is especially important in Egypt and Morocco. Beside, being a rich source of protein for human consumption, the straw of these crops is also a valuable fodder source for animals.
7.2. Rhizobia, inoculation, and cultivar interactions Given the widespread distribution of legume crops, various surveys were conducted in cropped fields throughout the region (Syria, Turkey, Jordan, and Egypt) and characterization of the rhizobia made (Moawad and Beck, 1991). This also involved evaluation for tolerance to high temperature and salt as well as antibiotic resistance. The symbiotic effectiveness of the various rhizobial strains, collected was assessed in a hydroponic gravel-culture system. On the basis of most-probable-number-count, rhizobia varied by several orders of magnitude. For example, lentil fields from Jordan had above-average counts. The symbiotic effectiveness also varied; of the isolates collected, 44% were of low N-fixing effectiveness, with only 21% of the isolates being superior N fixers. Distinct variations in salt- and heat tolerance of the isolates were observed, but none of the heat (40 C) and salt (0.5% NaCl)-tolerant isolates were among the most effective fixers. The necessity for inoculation of legume seeds with superior strains of Rhizobium was evaluated in plastic-house soil cores with and without N so that plants reliant on N fixed in symbiosis could be compared to plants supplied with ample N from the soil. Of 15 chickpea-growing sites in Syria, seven responded to added N; all these samples had low rhizobial populations. These initial observations on the importance of rhizobia led to production of local inoculum and subsequent field and greenhouse studies. After comparing a number of potential inoculant carriers as an alternative to peat, Beck (1991) showed that soil from the Ghab Valley in Syria high in organic matter (>10%), when amended with charcoal, was as effective as peat in maintaining high (>109 g 1) populations of chickpea Rhizobia over a 126-day assessment period.
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With the development of new cultivars of chickpea that were resistant to Ascochyta blight, it was possible to plant this crop in winter rather than in spring and thus make better use of the available soil moisture and produce higher yields. This development allowed for an expansion of chickpea growing to drier areas. Given the likelihood that these new fields may be low in rhizobia, it was important to assess the need for inoculation in such areas. The use of 15N methodology and nonnodulating chickpea and barley as reference crops allowed for accurate evaluation of N2 fixation under a wide range of environmental conditions. Addition of mineral fertilizer at 100 kg N ha 1 served as a basis for comparison in the nonnodulated chickpea and barley. The field trials of Beck (1992) sought to quality N2 fixation using 15N for eight chickpea cultivars as affected by native rhizobial populations and three introduced rhizobial strains and to determine how the host-strain interaction influenced N fixation and grain yield. (These interactions had been shown to be significant in the aseptic hydroponic system). In both years of the trial, inoculation of the chickpea cultivars produced significantly higher aboveground dry matter yields than the uninoculated controls. All yield and N2 fixation parameters differed among cultivars and strains in the wetter of the two years (486 mm) where cultivar-strain interactions were significant for seed yield, N yield, and N fixation. Differences in N yield and fixation were not significant in the dryer year (240 mm). The average amounts of N fixed in inoculated treatments was 68 kg N ha 1 in the wet year and 27 kg N ha 1 in the drier year. Inoculation with the best strain increased the proportion of N derived from the atmosphere (% Ndfa) from 52% to 72%. The interactions between rhizobial strains and chickpea cultivars in relation to yield response to selected rhizobial strains indicate the importance of field inoculation of chickpeas, especially where the crop had not been grown in that area previously. A key question regarding food legumes is how much N can any particular crop fix from the atmosphere under any given soil and environment conditions and management. Understanding how much N2 is fixed and removed in the harvested grain and straw is fundamental to assessing the potential of legumes to contribute to the N-balance of the whole agricultural production system. In three field trials for two seasons in northern Syria, and one season in France, Beck et al. (1991) examined BNF in food legumes. Since cultural practices influence N fixation, chickpea sowing date and Sitona weevil control in lentil were also considered. Pea and lentil had similar or % Ndfa values across locations, seasons, and cultural practices, with an average of 72% Ndfa. With chickpea, winter sowing increased % Ndfa to 72% from 26 in the spring-sown crop. In addition, the large-seeded cultivars fixed more N than smaller-seeded ones. By calculating the % Ndfa, the effects of removal of N in grain and straw in relative to fixed N and plant uptake of mineral N were assessed. Thus, the
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calculated N balance where only grain was removed showed a gain of 44 kg N ha 1 to a loss of 44 kg N ha 1. With the removal of both grain and straw, most estimates were negative with a net loss of 70 kg N ha 1 from the soil. The goal of good crop management should be to maximize the contribution of BNF though legumes as indicated by Beck et al. (1991). However, it is important to realize that the study was related to the two years under consideration and does not relate to the changes that might occur over several years of growing such legumes in rotation with cereals, as is the common practice. As N fixation is influenced by factors other than varietal ones, particular emphasis has been given to the influence of rainfall and mineral nutrition. Using a line-source sprinkler and enriched 15N with six lentil lines at one of the drier sites (Breda, 280 mm) in northern Syria, the effect of moisture on BNF was demonstrated (ICARDA, 1991). Increasing moisture supply greatly increased % Ndfa, from 36% of lowest moisture supply (180 mm) to 72% of moderate supply (330 mm), with only a slight further increase to 77% as moisture was further increased (376 mm). Similar studies with chickpea showed that as moisture increased, so did BNF, that is, 19% at 290 mm, 42% at 407 mm, and 64.5% at 449 mm. Thus, in relation to moisture supply, which controlled yield, it was preferable to have chickpea in the system’s N economy than lentil since lentil was limited in its response of % Ndfa to moisture supply. Under actual field conditions, the impact of any one factor is more difficult to control or isolate. In one of the early studies to deal with BNF at ICARDA, Keatinge et al. (1988) compared improved management of legumes (chickpea, lentil, peas, and faba bean) with traditional practices common in northern Syria at three locations across the rainfall transect (280–460 mm). The improved practices involved addition of 60 kg P ha 1, use of insecticide against Sitona weevil weed control by preemergence herbicides and hand-weeding, and narrower row spacing. The intervention doubled N uptake over crops and locations, that is, 31.8 kg N ha 1 under the traditional system to 68.7 kg N ha 1 with improved management, the proportion of N derived from BNF increased from 55% to 69%. As legumes had been grown previously in those fields, inoculation with rhizobia had little or no effect on N uptake or the proportion of N fixed biologically. The legumes had a residual effect, contributing about 10 kg N ha 1 to the subsequent barley crop. A later study showed that legume yields and BNF were influenced by temperature regime during the growing season as well as rainfall and the length of the growing season (Afandi et al., 1997). For this purpose, a trial was conducted at ICARDA at Tel Hadya in Syria and cooler and wetter sites in Lebanon (Kfardane and Terbal). Thus, yields and N yield followed the order of Tel Hadya, Kfardane, and Terbal. The % Ndfa was high for
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lentil and faba bean (70–85%) being lower for peas and chickpea. Inoculation with Rhizobia had no effect on either winter or spring chickpea, again presumably because of the presence of effective native rhizobia. While an insecticide (Promet) was used in the study, there was no effect, indicating that Sitona weevil was not a problem in the trial. However, an earlier study (Islam, 1982) showed the importance of insect control to maximize BNF by legumes.
7.3. Pasture and forage legumes Given the importance of both naturally occurring forage species and nature pastures and rangelands, as well as sown forages, as a source of animal feed, considerable research was given to such legumes. Issues addressed ranged from characterization of indigenous rhizobial strains from countries of WANA, identifying annual Medicago–Rhizobium relationships, competition and persistence of some inoculant strains, quantifying % Ndfa by the various forage species and examining management factors that influenced BNF in such crops. Much emphasis was given to the self-regenerating species of medic, a crop that was shown to be well adapted to dryland conditions in Australia (Puckridge and French, 1983) and one that was considered to have potential for adoption in the dryland agriculture of the Mediterranean region. Earlier work by Hardarson and Zapata (1984) using soybean as an example had shown that large differences existed between cultivars to fix, leading the authors to conclude that within legume germplasm there exists a potential for breeding for fixation traits. An outcome of the surveys of rhizobial communities in the highlands of west Asia was the appreciation of the wide genetic diversity that existed in soils of that region and their potential importance to cereal–legume cropping (Keatinge et al., 1995a). Rhizobial cultures from Turkey and North Africa were selected based on climatological parameters, for example, average minimal and maximal temperatures in the coldest month ( January). Detailed consideration was give to the major species of Rhizobium, for example, R. leguminosarum (Materon et al., 1995a), R. meliloti (Materon et al., 1995b), and R. ciceri (Keatinge et al., 1995b). Special emphasis was given to the symbiotic relationships of R. melilot (Materon, 1991). Though such surveys are rare, it is reasonable to assume that a similar diversity would exist in other Mediterranean areas with a semiarid climate. As N fixation was a major focus of research for medics (Brockwell et al., 1988; Materon, 1994; Materon and Danso, 1991), some key features of this research are worth mentioning. Using the 15N-dilution method to measure N fixed by three medic species (M. rotata, M. rigidula, and M. truncatula), large genotypic differences in herbage yield production and in symbiotic N occurred. The herbage yield of M. rigidula was, on average, about 3 times that of M. truncatula,
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M. rigidula, derived about 91% or 85 kg N ha 1 of its N from N2 fixation, compared with the 64%, or 23 kg N ha 1 for the other two species. In another study related to BNF in forages, the competition between M. truncatula and wheat was examined in a greenhouse pot study using 15N as influenced by P fertilization (Elabbadi et al., 1996). This work showed that N fixed by the legume can be transformed to the companion cereal, but it does not occur immediately and was only detected in the second cropping cycle. Seedling density did not affect % N2 fixed in the species of medics. However, it had a highly significant effect on total N yields. Thus, high reserves of viable medic seeds in soil may greatly increase the contribution of N2 fixed in cereal–legume rotation system. In a comparison of methodologies to measure BNF in soils low in N (difference vs. 15N dilution), no significant differences were detected in the amount of N fixed by M. rigidula (82% and 88%) and M. truncatula 71% versus 69% (Lolium rigidum). Lolium rigidum was used as a control. Seasonal BNF rates of M. noeana, M. rigidula, and M. truncatula varied from 1 to more than 4 kg N ha 1 d 1 during the growing season, reaching a peak in March and declining during April. Although approximately equal to the indigenous cultivars in winter, M. truncatula (cultivar ‘‘Jemalong’’) fixed much less N2 in spring. Total N2 fixation was 202 kg ha 1 by M. truncatula, 229 kg ha 1 by M. rigidula, and 272 kg ha 1 by M. noeana. Nitrogen budgets for M. scutellata, M. rigidula, and M. rotata were determined using 15N methodology in cereal–medic rotation fields in Tel Hadya (Syria) and in Meknes (Morocco) thus enabling quantification of the input of N by medics in such rotations. Following the progress made on these fronts, a key issue was finding medic–rhizobial associations in forage and pasture that were tolerant to cold conditions that occur in winter in rangelands. As the pasture may grow under such conditions, the rhizobia should also be able to fix N under the same relatively cold conditions. To identify such rhizobial associations, Sultan et al. (2001) assessed the performance of three medic cultivars, that is, M. aculeata—Accessions 80 and 5099, and M. rigidula, under conditions of N fertilization, inoculation with three rhizobial strains (M620, M508, and BZI), and uninoculated and unfertilized control. As the study was conducted in the cold period of January–March, it showed genetic variation in low-temperature tolerance of annual medics. Medicago rigidula Accession 716, inoculated with strains BZI, was the most adopted, while M. aculeata Accession 5099 needed inoculation with a rhizobial strain better adapted to cold winter conditions. While cold temperature is a factor with effectiveness of rhizobial–medic associations, nutrient deficiencies also limit the growth of medics, as with any other crop, and thus limit their potential to contribute to soil and plant N through BNF. Given that P is invariably deficient in the Middle East
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region (Matar et al., 1992) and that crop response to P occur across a range of rainfall zones (Ryan et al., 2008f ), a concern was how P might affect the growth of forage legumes. Similarly, as some soils of the WANA region are now recognized to be zinc (Zn) deficient (Rashid and Ryan, 2008), it was important to also consider this factor in relation to forage legumes. These concerns were enshrined in the greenhouse (Materon and Ryan, 1995) and field (Materon and Ryan, 1996) trials at Tel Hadya that examined inoculation of medic cultivars in relation to P and Zn fertilization. In the greenhouse trial, medic common cultivars (M. polymorpha, M. rotata, and M. noeana) responded to added P, and to Zn only when there was adequate P and mineral N, either added or through inoculation. While the study suggested that inoculation would be needed in the absence of compatible rhizobia, the importance of adequate P and Zn nutrition was vital to enhancing the effectiveness of medics, and thus their capacity to fix N. A subsequent field trial (Materon and Ryan, 1996) considered a number of forage legume species (Lathyrus or grass pea, vetch, and medics) in relation to the same factors, that is, inoculation, P, and Zn. The soil at the site (Calcixerollic Xerochrept) was low or deficient in both P (3.4 mg ha 1 as Olsen P) and DTPA-extractable Zn (0.6 mg kg 1). While P and Zn significantly (5%) increased yields of medics and vetches, there was no response in the case of Lathyrus. There were significant interactions with the medic cultivars, with M. rotata and M. aculeata responding to inoculation but M. rigidula and M. noeana did not respond to either inoculation or applied N. The effect of P was more pronounced for M. rigidula and M. noeana than the other two medics. The effect of Zn was consistent across all P levels. This field study confirmed the findings of the greenhouse study (Materon and Ryan, 1995) and clearly showed that the potential of forage legumes and their associated rhizobia to contribute to the soil’s N economy is dependent upon eliminating any nutritive constraints.
7.4. Current perspective on food and forage legumes The early years after ICARDA’s established witnessed a surge of interest in both food and forage legumes, with involvement of the institution’s scientists and scientists from the WANA region’s national agricultural research programs (Christiansen et al., 1993; Osman et al., 1990). Broad issues related to legumes and their relevance to Mediterranean agriculture were highlighted as well as a perspective of BNF in forages. The early research related to BNF in food legumes laid a firm basis to the widespread adoption of these crops. Chickpea and lentil today is well established in the agricultural system in the region. However, the story of forage legumes was more checkered. With the momentum in forage and pasture legume research, there was considerable optimism, almost euphoria, about the prospects of Medicago species (Abd El-Moneim and Cocks, 1986) and vetch or Vicia species
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(Abd El-Moneim et al., 1988; Keatinge and Chapanian, 1991; Keatinge et al., 1991). Though medics were a central part of long-term grazing (White et al., 1994) and crop management studies (Harris, 1995), there were obstacles to the successful adaptation of this forage at the farm level, for example, poor seed setting due to excessive grazing, problems with seed harvesting and small farm holding size that did not favor such a ley farming systems (Christiansen et al., 2000). However, the prospect of vetch as an annual sown forage being adopted by farmers are favorable since, if well managed, it contributes a valuable feed source and provide an alternative to continuous cropping or fallow. The role of both crops in rotation, especially as influencing soil properties and crop yields is discussed in Section 9.
8. Potential Losses of Nitrogen in Dryland Cropping Nitrogen that is not used by crops can have serious environmental concerns (Pathak et al., 2003). These effects include ground water contamination from NO3 leaching, eutrophication of rivers and lakes from surface runoff, acid rain from ammonia (NH3) volatile loss, and global warming and ozone depletion from nitrous and nitric oxide emissions from soils. The importance of N losses is reflected in the various chapters dealing with pathways of N loss and their implications in the recent monograph of Scheppers and Raun (2008), as well as the economic implications of such losses. There is an increasing growing awareness of the implications of such N losses from fertilizer application with respect to human health (Peoples et al., 1998). The need to produce more food with more fertilizer has to be reconsidered with the need to minimize nonproductive losses of N (Maene, 1998). This dichotomy underlines efforts to reduce N losses from agroecosystems by increasing use efficiency at the level of the fertilizer, soil, and crop (Ladha et al., 2005). This raises the question of the particular agroecosystem since the relative importance of the various awareness of N loss vary with environmental factors as well as the extent of N fertilizer use. Nitrogen losses in dryland agroecosystems are generally lower than in humid temperature and tropical environments, largely because of the limited rainfall, which in turn limits leaching of N from the root zone. Apart from losses of N in the form of SOM with the process of wind and water erosion, the main N losses in dryland agriculture concern mineral N forms. Under such limited rainfall conditions, the soil is rarely saturated for any substantial period to induce denitrification loss from anaerobic conditions (Li et al., 2009). Accordingly, studies of N gaseous loss other than NH3 volatilization are rare. An aerobic inoculation study in Turkey examined emission of CO2, N2, and N2O from addition of NO3 to the soil (Coskan
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et al., 2007). As expected, most of the gaseous loss from denitrification was as N2. The proportions between N2 and N2O varied with the soil. Such studies have implications for climate change as N2O is a potent greenhouse gas. Similarly, under the normal rainfall range and intensity pattern in the Mediterranean region, soil moisture rarely extends beyond the wetting front of 0.5–1 m (Harris, 1995) and thus any N in the soil is available for crop uptake. However, during partial or complete irrigation, some NO3 can be leached below the root zone. Losses of mineral N as NO3 by surface runoff is only likely to be important on sloping land after topdressing or broadcasting of the fertilizer. The elimination of most other pathways of N loss leaves only volatile loss of NH3 and nitrous oxide as the loss mechanisms of any significance in dryland regions such as the Mediterranean region. The process of ammonia volatilization has been the subject of numerous investigations cited by Fenn and Hossner (1985) and more recently by Harrison and Webb (2001) and to some extent by Ladha et al. (2005). The various factors involved in the process leading to volatilization are well researched and understood. The reaction is basically a physiochemical one controlled by the soil’s pH. Under neutral and alkaline conditions, significant loss can occur, especially where urea is used. In essence, the reaction of urea under favorable soil moisture conditions leads to the formation of unstable ammonium carbonate and subsequently to NH3 loss to the atmosphere. Under field conditions, the extent of volatile NH3 loss is conditioned by rainfall and soil moisture, temperature, and wind conditions. As virtually all soils of the Mediterranean region are calcareous (Kassam, 1981), that is, have a high pH, and as fertilizer N use is increasing, with urea globally being the dominant N source, the possible loss in NUE through volatilization attracted some research attention. One of the few early studies of NH3 volatilization in the Mediterranean region was carried out in the laboratory (Ryan et al., 1981). A range of Lebanese soils, mainly calcareous, were placed in sealed, forced-air containers under field-capacity conditions and reacted with solutions of ammonium sulfate. To a noncalcareous soil, CaCO3 was added at the same rate but with varying particle sized (and thus surface area), with and without treatment with 0.25% FeCl2 to simulate a coating of the reactive CaCO3 particles. The NH3 produced during the 24-h period was trapped in a solution of boric acid. Loss of N as NH3 ranged from as low as 5.4% of the N fertilizer applied to as high as 75.5%. This loss was positively correlated with pH, cation exchange capacity and CaCO3, with higher correlation with ‘‘active CaCO3,’’ that is, an index of surface area. Coefficients of determinations were higher with the inclusion of iron, especially the ‘‘amorphous’’ form as opposed to ‘‘free’’ Fe. The effect of Fe coating CaCO3 particles was confirmed by the reduced activity of the CaCO3 following reaction with FeCl2. As Fe oxides occur in nature as discrete or
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amorphous or diffuse coatings of soil particles in Mediterranean soils (Arshad et al., 1980), the presence of Fe oxides may modify or mask the influence of CaCO3 in terms of their reaction with urea or any ammoniumforming N fertilizer. As interesting as the results may be, neither CaCO3 nor Fe may be manipulated under field conditions to influence reactions that lead to volatile NH3 loss. Under field conditions in dryland cropping conditions in the Mediterranean region, potential losses from topdressing or surface application of urea are likely to be influenced by the preventing soil moisture and ambient temperature conditions, and by the rainfall after N applications, which would influence movement of the dissolved urea into the soil. In field study from northern Syria, three urea fertilizers, that is, urea alone, urea with an incorporated urease inhibitor, phenylphosphorodiamidate, and urea with a bran-wax coating, were evaluated (Abdel Monem, 1986) on wheat for two cropping seasons at two experimental stations with varying average seasonal rainfall (Tel Hadya, 340 mm year 1; Breda, 270 mm year 1). The volatile loss of N was assessed with 15N by mass balance. Crop yields and N uptake were related to seasonal rainfall. Losses of N, apparently as volatilized NH3, were relatively low at both sites, that is, 11–18%. However, neither the urease inhibitor nor the bran-wax coating had any effect on yields, N uptake or N loss compared to the unmodified urea. In the detailed microplot cylinder study, initial soil moisture, rainfall after fertilizer application, and soil temperature influenced urea hydrolysis and volatilization. A related study in Lebanon examined the possible effect of urea coatings to modify volatile NH3 loss in a calcareous soil using sulfur-coated urea (SCU) with varying release rates and a synthetic polymer ‘‘Osmocote’’ (Ryan and Hariq, 1986). Within four weeks, 16.2% of the N in urea was lost to the atmosphere compared to a maximum of 4.4% for the coated materials. Crop uptake of N was similarly higher with the coated materials. Despite some advantages of slow-release N materials in the short term, they are not amenable to application to field crops, because of relative costs, and are only likely to be used with high-value crops in greenhouses. Because of technical difficulties, SCU has not shown any promise as a slow-release N fertilizer to reduce application losses. Thus, under the cool-season conditions of rainfed cropping in the Middle East, efficient use of urea in not likely to be achieved by modification of the urea, but by conventional management practices that ensure soil incorporation or topdressing during early spring rains. Of interest in the study was that the estimates of NH3 loss were much less than observed from short-duration laboratory incubation studies such as that of Ryan et al. (1981) with similar kinds of soils. As noted by Fenn and Hossner (1985), because of the conditions associated with measurements of NH3 loss, laboratory studies always overestimate losses from the field. In field trials from Tunisia with 15N, recovery of N with ammonium sulfate and
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ammonium nitrate, ranged from 18% to 47%, with volatilization losses of 15% and N derived from fertilizer (Ndff) of 9% and 21% and no leaching in the dry season (El Mhiri and El Sanaa, 1993).
9. Integrated Cropping Systems: Implications for Nitrogen Dryland cropping in the Middle East region has evolved from antiquity (Harlan, 1992) and although much has changed over the years, the essential characteristics of the system remain the same. It involves around exploiting the rainy period from autumn to late spring to grow crops on stored soil moisture (Cooper et al., 1987). Dryland agriculture in the region is an integrated system that involves people growing crops and feeding their animals, mainly small ruminants, during the cropping period, and afterwards on the crop residues. Despite its acquired resilience, having to cope with the ever present threat of drought (Harris, 1995; Kassam, 1981), the past three decades have seen considerable land use pressure from population growth, and changes from outside in terms of increased mechanization, use of chemical fertilizer and pesticides, and irrigation encroaching in formerly rainfed areas. In line with the new paradigm of sustainability of global productive and environmental resources, author such as Jones (1993) applied such concerns to dryland cropping in the Mediterranean region. In essence, the issue was whether the drive to continue cropping intensification, with increasing animal and human populations, be sustained economically and biologically without detriment to the environment and the soil and water resource base. In any one season, crops growing in the field are influenced not only by the weather conditions of that season, but also by the previous crops and how they affected soil quality with respect to nutrients and soil moisture; these residual effects can be positive or negative. If the antecedent crop is a legume, the fixed N contributes to the following cereal by increasing yield or reducing the need for fertilizer N. Similarly, if the previous crop is high-yielding or deep rooted, causing soil moisture depletion, the following crop yield may be reduced due to moisture stress. In addition, if the same crop has been grown for previous years diseases may build up in the soil causing yield reductions. Conversely, if the field has not been cropped the previous year (i.e., fallow), additional moisture may be carried over to enhance the following crop. In short, rainfed cropping constitutes a system that is influenced by a sequence of crops, repeated in a consistent manner overtime, that is, rotations. Implicit in the research agenda of organization such as ICARDA and the national agricultural research systems was a strategy to ensure cropping sustainability into the future through improvements in crop varieties and
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efficient crop and soil management, including N fertilization and promotion of BNF in food and forage legumes. Central to these efforts was crop rotations, a practice that dated back to Roman times in the Mediterranean region (Karlen et al., 1994). The rationale for the reviewed emphasis on rotation was to replace fallow with an alternate crop of economic value ad to break disease cycles in the case of continuous cropping (Harris, 1995). To assess how sustainable any crop rotation was, or any intervention within a rotational context, a long-term perspective was needed, in contrast to commonly conducted annual field trials ( Johnston, 1997). Despite the existence of many long-term trials of 100 years or more, such as the classical long-term experiments that have unpinned much of the scientific advances in our understanding of crop nutrition and agroecosystem’s change, few trials in their Middle East region even meet the minimum definition of being long term (Ryan et al., 2008a). Notwithstanding the limited number of multiyear trials in the region, and the inherent limitation, the need for such trials is as pressing as anywhere else in the world (Ryan and Abdel Monem, 1998). As most of the region’s long-term trials were conducted by ICARDA at Tel Hadya or other sites in northern Syria, and most involve N either applied as a fertilizer or an outcome of the system, this review will focus on the N aspects of the trials. While early trials in the 1980s showed that improved management of annual vetch crop (inoculation, P fertilizer, and reduced row spacing) improved the yield and N content of the legume hay, it also showed a benefit in terms of added N for the following year’s barley crop (Keatinge and Chapanian, 1991) thus indicating rotational effects that would be amplified in trial involving 2-course (cereal/legume) rotations over several years. These conditions were applicable to three major ‘‘long-term’’ trials at Tel Hadya; ‘‘Cropping Systems Productivity’’ trial with wheat, the ‘‘Grazing Management’’ trial (L-13) involving wheat initially and later modified with barley, and the ‘‘Conservation Tillage/Compost’’ trial with barley and vetch. In the subsequent sections, we deal with cereal responses to N, impact of the rotation in N response, effect of rotations on grain N (and protein), changes in soil N forms with time and seasonally, indirect effects of N on soil properties, and the use of 15N from microplot studies to quantify aspects of N cycling and NUE.
9.1. The ‘‘Cropping systems productivity’’ trial This major trial, initiated in 1983/1984 and terminated in 1998, involved durum wheat grown in rotation with chickpea, lentil, pasture vetch, medic, continuous wheat, and clean-tilled fallow. Secondary treatments included N fertilization of the alternative cereal phase at 0, 30, 60, and 90 kg ha 1, and tertiary treatments involving variable grazing of the cereal stubble (zero grazing or stubble retention, and medium and heavy grazing. The trial was described by
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Harris (1995) and Harris et al. (1995) in varying detail, and following completion by Ryan et al. (2008a). In the context of this article, it is pertinent to highlight the effects of the N treatment on crop yields and soil parameters. 9.1.1. Grain and straw yields of cereals Overall cereal yields were significantly influenced by the rotation, being in the order of follow, vetch, lentil, medic, chickpea, and least for continuous wheat (Ryan et al., 2009d). The stark contrast between the rotations is illustrated in Fig. 5 for the medic and the fallow rotation. Though variable stubble grazing had little or no influence on cereal yields, the addition of N consistently increased both grain and straw yield, with the magnitude of the responses being influenced by the particular rotation. Overall mean grain yields increased by 21, 32, and 43% with the 30, 60, and 90 kg N ha 1. Respective values for the straw increases were 27, 45, and 58%. The relative responses to N dependent on whether that rotation contributed to which it influenced available soil moisture. The highest relative responses were with the continuous cereal which had no N input in the previous year either through N fixation or N fertilizer. The response in the fallow rotation was only slightly less than that for continuous cereal, mainly due to the carryover soil moisture from the uncropped fallow season. The rotation with the least response to applied N was the medic/wheat rotation, mainly due to the higher N availability from N fixation. Responses to N were intermediate between medic and continuous wheat for vetch, lentil, and chickpea to an extent that reflected the influence of these crops on soil mineral N as well as an influence on soil moisture availability.
Figure 5 Comparison of the wheat/medic (w/f ) and the wheat/fallow (w/f ) rotations in the ‘‘Cropping Systems Productivity’’ trial. Note the dark color of the wheat/ medic rotation reflecting the accumulation of soil N due to BNF.
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9.1.2. Grain and straw quality Grain quality, particularly for protein has implication for the consumer. In the Middle East region, where per capita bread consumption is among the highest in the world, having relatively high protein content in the flour is important for maintenance of adequate human nutrition. For export of wheat from Syria, a minimum of 12% protein is required; however, grain protein had not been a factor in the establishment of wheat grain prices domestically in the past. Similarly, where animals are heavily dependent on grazing cereal residues (cut straw or stubble), slight increases in straw protein can influence animal health. In this cereal-based trial, fertilizer N significantly increased N concentrations in both, grain and straw, and therefore protein content, as well as overall N uptake (Ryan et al., 2008c). Thus, with increasing N application rate (0, 30, 60, and 90 kg ha 1), grain N concentration increased (1.79, 1.93, 2.12, and 2.25%) as well as straw N concentration (0.36, 0.40, 0.47, and 0.51%). Similarly, the N uptake values increased with added N, that is, 36.2, 47.0, 57.1, and 65.2 kg ha 1, respectively. Given the variable yields within the rotations, and the fixation of N in same rotations, the rotations themselves significantly influenced N in the grain and straw as well as N uptake (Table 1). Not surprisingly, grain N concentration was highest with medic (2.42%) and vetch (2.11%), least for the fallow (1.79%), and the continuous wheat (1.91%). Nitrogen concentration in the straw followed a similar number ranking as N in the grain, but of a lower order of magnitude, that is, 0.37–0.57%. Again, reflecting the influence of moisture availability and BNF in relation to crop yields, total N uptake in the cereal biomass (grain and straw) was least for continuous wheat (30.8 kg ha 1) and highest for the medic rotation (64.3 kg ha 1), with the other rotations being between those values. In summary, both variables in this long-term cropping systems trial, rotations
Table 1 Grain and straw N concentration and uptake of wheat as affected by rotation; SEM, Standard error of the mean Rotation, wheat . . . Parameter
Fallow
Grain (% N)
1.79 1.91 SEM ¼ 0.03 0.37 0.42 SEM ¼ 0.01 55.7 30.8 SEM ¼ 1.7
Straw (% N) N uptake (kg ha 1)
Wheat
Lentil
Chickpea
Vetch
Medic
2.05
2.05
2.11
2.42
0.42
0.44
0.45
0.57
52.7
42.4
58.6
64.3
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and N fertilizer, significantly influenced protein quality of the crop components, that is, grain for human consumption and straw as animal feed. 9.1.3. Water-use efficiency A key consideration in any dryland cropping system is the efficiency with which crops use the most limiting growth factor. Thus, water-use efficiency (WUE) was considered for the initial years of this long-term trial (Harris, 1995) and for the full 14 years for individual crops and the system, that is, rotations as a whole (Pala et al., 2007). Within a given soil moisture regime, any factor that contributes to increased yield management also increases WUE, especially with N fertilizer (Cantero-Martinez et al., 1995). As N significantly increased crop yields in this rotation trial, it also increased WUE in all six rotation cycles (Pala et al., 2007). Nitrogen had a significant effect on evaporation when applied to the cereal phase. On average, fertilized wheat extracted 17 mm more water from the profile than the unfertilized crop. With N fertilization, WUE was highest for the wheat/ lentil rotation and least for continuous wheat. This poor efficiency of continuous wheat added to the argument for adopting alternative crops to replace it. 9.1.4. Soil nitrogen dynamics As with crop yields and crop quality, especially with respect to proteins, the variables in the trial significantly influenced both total and mineral N in the soil (Ryan et al., 2008d). The influence of these variables was consistent for total N, the largest entity, but less consistent for the much smaller and more variable ammonium and nitrate fractions. In terms of the overall rotations, total N was highest for the two forage legume rotations, medic (870 mg kg 1) and vetch (811 mg kg 1), and least for the fallow rotation (723 mg kg 1), which contribution no N through BNF. The overall mean effect of added N fertilizer application rates increased total N, that is, 744, 749, 789, and 804 mg kg 1, respectively, with the N application rates (0, 30, 60, and 90 kg ha 1); mineral N showed a similar increase with added N (9.3, 10.1, 14.1, and 18.8 mg kg 1). In contrast to both crop yield and quality, there was a significant effect of variable grazing of the straw residues on soil N. Progressing from residue retention to medium and high grazing intensity, values for total N decreased (785, 767, and 764 mg kg 1) while the mineral N significantly increased (12.4, 13.4, and 13.7 mg kg 1). From the data, it was apparent that differences existed between grazing and no-grazing, with no clear distinction between the degrees of grazing intensity. Clearly, the removal of the stubble reduced the total amount of organic N being returned to the soil. In addition to the overall effects of the variables in the trial, seasonality with respect to N forms was exhibited within three growing seasons during
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the trial as indicated by data from uncropped microplots (Ryan et al., 2009a). While total N was consistent with the overall rotations, there were consistent decreases as the cropping season progressed from February to August after harvesting the crop as indicated for the last year (Fig. 6). Total N values decreased from 944 mg kg 1 in the cold period in February just prior to the period of active growth to 798 mg kg 1 after the cropping season in august (798 mg kg 1). However, the labile N fraction showed no marked or consistent change with time. In contrast, the relatively small microbial biomass N fraction was constant throughout the crop growth period but dropped off at the end of May with the onset of higher soil and air temperatures and lower soil water content. Data for 1997 showed even greater fluctuation with little biomass N detected in a very cold rainless period in January/February. Mineral N was relatively constant during the growing season showed an increase at the end. In summary, it appears that total organic N undergoes mineralization as conditions for crop growth improve during the season. While this decrease should be reflected in an increase in more labile or plant-available N fractions, it is not always seen in surface sampling. Where the full 1-m profile was sampled, most of the mineralized N was accounted for by increased mineral N. Though this sampling substudy was confined to the unfertilized or control plots of the rotations, and therefore did not consider the effect of added N to the system, it did clearly show the seasonally dynamic nature of N under Mediterranean dryland cropping conditions. 9.1.5. Soil organic matter Though normally constituting a relatively small fraction of the soil volume, SOM or soil carbon has a disproportionate influence on crop productivity and soil biology and is a holistic indicator of soil quality. When the 200
1000 Labile
N
N (mg kg−1)
900 Total
N (rig
ht axis
100
50
0 1/1/98
)
800
Microbial N
1/3/98
1/5/98
700
Total N (mg kg−1)
150
N Mineral
1/7/98
600 1/9/98
Figure 6 Means of rotation and sampling date on N forms during 1998; modified from Ryan et al. (2009b).
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‘‘Cropping Systems Productivity’’ trial began in 1983/1984, SOM was not a consideration, with emphasis only placed on crop yields. However, in the light of a growing global scientific interest in SOM in relation to food productivity (Lal, 2001) and mitigation of greenhouse gasses, mainly carbon dioxide, especially in dryland ecosystems (Lal, 2002), measurements were made of SOM and C fractions in the latter years of the trial. When measurements of total SOM began in 1989, there were already clear differences due to the crop rotation on this key property, with SOM in the forage legume rotations (vetch, medic) being significantly higher than the other rotations, with fallow and continuous wheat being least (Ryan et al., 2008e). In a parallel study, the increased SOM in the rotation was shown to be positively related to improved aggregate stability and associated infiltration and permeability (Masri and Ryan, 2006). Although the effect of added N was not considered in relation to physical properties, it is reasonable to anticipate positive effect as it also increased SOM. Of particular interest in the context of this review of N in dryland Mediterranean cropping systems was the overall influence of fertilizer N across the rotation and crop residue treatments. A definite trend of N was indicated as SOM increased consistently with fertilizer application rate, that is, 1.12, 1.13, 1.19., and 1.20% for the 0, 30, 60, and 90 kg N ha 1 rates, respectively. Although the effect of added fertilizer N was not considered in relation to within-season determinations of SOM and C fractions, total SOM and labile C were shown to decrease as the cropping season progressed, with biomass C showing considerable fluctuations as moisture and temperature conditions changed (Ryan et al., 2009c).
9.2. Grazing management rotation trial The need to provide feed for the burgeoning populations of sheep in the Mediterranean region was the underlying rationale for the establishment of the grazing management trial in 1985/1986. While the trial had elements in common with the ‘‘Cropping Systems Productivity’’ trial, that is, a range of alternative cropping options in rotation with wheat, it did focus on medic grazing at high, medium, and low intensity; the other rotations were common to the region, that is., vetch, lentil, and fallow. The trial provided a framework for a substudy to consider the impact of the rotations on soil N (White et al., 1994). After 6 years, the forage rotations (vetch, medic) had increased soil N by 15–20%, but there was no effect with the lentil or fallow rotations. While neither N fertilization nor stocking rate had any significant effect on soil N, there was a tendency for N to increase with the low stocking rate and with N fertilization of the cereal phase. In one of the few studies of its kind from this trial, White et al. (1997) emphasized that in rotations involving grazing, a complete picture of the N balance (input–outputs) in the system
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must consider the addition of N through feces and urine and the possibilities of loss N from these sources through volatilization. Total SOM in the trial was more pronounced than total soil N, again showing the positive effect of the forage legumes (Table 2). Regardless of the rotation or the grazing intensity (as in the case of medic), all values were higher with N addition (100 kg ha 1) than the unfertilized treatments. In contrast to both total N and SOM, the treatment effects on mineral N were inconsistent between the cereal and the noncereal phase. Mineral N tended to be higher with the medic grazing treatments, and where N was applied to the cereal phase. In the six years cropping years considered, rainfall was below average in all except one year, thus causing yields and N off-take to be below normal. Despite the contributions of the legume in the rotations to N uptake by the wheat, the amount of N removed by the wheat exceeded fixed N, leaving a negative N balance. Following the first six years, the trial was substantially modified in 1991/1992, mainly to include barley instead of wheat, and continued through the 2003/2004 seasons. Despite the wealth of data gathered from the trial, only one further publication emerged from it (Ryan et al., 2002). The latter study briefly highlighted yields of only three of these years and soil analysis in one year (Table 3). The yield observations indicated that the rotational effects were strongly expressed in the order of fallow, vetch, medic, and continuous barley. A consistent feature of the data was the effect of added N. However, the difference between the þ and N treatments was relatively small in the case of vetch and medic that fixed N. The pattern of treatment effects for straw was similar to that of grain. The sampling for soil properties in 2000 represented a snapshot of the cumulative effect of rotation and fertilizer N on soil parameters. This time the small differences observed in the original wheat-based trial (White et al., 1994) were accentuated. With respect to added N, in all four rotations, SOM values were higher with N than without N. With total N, there were Table 2 Influence of five years of different wheat–legume rotations and N fertilization on soil organic matter; modified from White et al. (1994) þ N (%)
N (%)
Rotation
1987
1991
1987
1991
Medic, low grazing Medic, medium grazing Medic, high grazing Vetch Lentil Fallow
0.99 1.02 1.1 1.04 1.06 1.1
1.28 1.2 1.11 1.24 1 1.08
0.96 1.03 1.06 1.03 0.95 1.1
1.24 1.18 1.08 1.22 1.04 0.94
Table 3 Effect of added nitrogen on yield and organic matter, total soil nitrogen and mineral N in the modified grazing management trial; modified from Ryan et al. (2002) Barley Year
Rainfall (mm)
Fallow
Medic
Vetch
þN
N
þN
N
þN
N
þN
N
1.4 1.3 0.9
0.3 0.9 0.8
3.0 2.5 2.7
1.8 1.5 1.9
2.6 2.5 1.3
1.8 1.9 1.6
3.1 2.8 1.7
2.6 2.1 1.9
1.10 629 4.0
0.86 561 3.6
1.18 714 5.0
1.02 624 4.5
1.25 761 3.7
1.23 752 4.8
1.26 753 4.6
1.18 741 4.2
1
Grain yield (t ha ) 1997/1998 416 1998/1999 311 1999/2000 249 Soil parameters Organic matter (%) Total N (mg kg 1) Mineral N (mg kg 1)
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big differences between þ and N for fallow and continuous barley, but little difference between the N fixers (medic, vetch). As mineral N was such a small fraction, no treatment effect was apparent. Nevertheless when monthly sampling was done throughout the cropping period, mineral N from the N fertilized plots tended to be consistently higher than from the unfertilized plots.
9.3. Barley-based rotation trials Given the importance of barley as a drought tolerant cereal in the dryland cropping systems of the Mediterranean region, long-term trials were initiated in 1982 on this crop at Tel Hadya (340 mm) and at the drier Breda substation (280 mm). The trials centered on the feed needs in dryland Mediterranean condition involving small ruminant production systems. At both sites, 2-course rotations were compared with feed legumes, that is, lathyrus (Lathyrus sativus) and vetch, as well as fallow and continuously grown barley. Superimposed in the cropping comparisons was a standard application of N and P to the barley phase. Nitrogen was applied at 20 kg ha 1 at Breda and 40 kg ha 1 at Tel Hadya. The trials therefore involved N as independent variable and as a dependent variable as N off-take in the crop was considered. The trials were initially described after seven cropping season in terms of crop and N yields ( Jones and Singh, 1995) and subsequently the complete 14-trial results were described in terms of comparison of rotations ( Jones and Singh, 2000a), role of feed legumes ( Jones and Singh, 2000b), and barley monocropping ( Jones and Singh, 2000c). Additionally, a 10-year trial of continuous barley was reported in the latter work. The indications from the initial stage of the trials showed the importance of using fertilizer N, even at a relatively low rate, and the value of including vetch in the rotation with barley rather than continuous barley or fallow. The amount of N in the forage varied with the rotational treatments and was considered a proxy for nutritive value of the forage. Responses to biannual fertilization were significant, while the total N output of legume-based rotations exceeded that of continuous barley by 80% at Breda and 64% at Tel Hadya. With time, yields of unfertilized plots declined relative to fertilized ones; in that context the effectiveness on N and P was interdependent. However, barley yields were depressed by fertilizer N in dry years of below-normal rainfall.
9.4. Conservation/compost tillage trial One of the most recent long-term rotation trials (1996–2008) addressed contemporary issues of conservation tillage and compost addition and straw management (burning, soil incorporation) within a vetch/barley rotation.
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While N was not a major part of the trial, it was applied to the cereal phase (60 kg ha 1). While barley yield were higher with the compost addition, there was no clear advantage of shallow tillage, except reduced energy costs (Pala et al., 2008). What was significant about the study was how the factors involved influenced soil N (Ryan et al., 2003b). The addition of compost had a marked effect on total soil N in the top 0–20 cm. However, the distribution of N within the soil profile (0–60 cm) was greatly influenced by the tillage system. Under conservation tillage the enhanced N was confined to the top 20 cm, while with deep tillage, the N distribution was fairly uniform with depth. As expected, the distribution of SOM followed the same pattern as for total N.
10. Nitrogen in Supplemental Irrigation Systems Though the Mediterranean region is mainly characterized by rainfed cropping, significant developments have taken place with respect to irrigation. As rainfed cropping overlaps with supplemental or deficit irrigation during the normal rainfed cropping season, it is pertinent to consider N in this context. In the past, irrigation was confined exclusively to arid areas (<100 mm rainfall) where surface water sources or ground water sources are available for irrigation, while dryland cropping occurred in the semiarid rainfall zone (200–500 mm). However, with increasing land use, and the uncertainty of crop yields under dryland cropping, recent years have seen an expansion of irrigation in traditionally rainfed areas, based mainly on the exploitation of ground water. The rationale for irrigating rainfed crops in the period of normal growth of such crops, especially for crop establishment and in late spring or early summer was to supplement uneven or deficient rainfall, that is, supplemental irrigation or conjunctive use of water, to stabilize crop yields of mainly cereals. Though the principles of supplemental or deficient irrigation are well known (Musick et al., 1994), applied research, mainly at ICARDA in Syria, has established the potential for such a system in the region. The system involves interaction with N fertilization since increases in crop yields with added water only occur with corresponding increases in applied N (Ramig and Rhoades, 1962). The initial studies of supplemental irrigation focused on varying water amounts up to full irrigation to compensate for crop demand and N application (0–150 kg ha 1) with varying dates of sowing for bread wheat (Oweis et al., 1998) and durum wheat (Oweis et al., 1999). While a delay in sowing date (from November to January) reduces responses to both water and N, the response to N was conditioned by the applied water level (0, 1/3, 2/3, and full irrigation). Without irrigation
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water, that is, rainfed, maximum response was with 50 kg N ha 1, while the higher-yielding cultivars responded to 150 kg N ha 1. Almost maximum yields were obtained by applying 2/3 of the crop water requirement. For both cereal crops, the use efficiency of both water and N was increased by supplemental irrigation. While neither study considered the concentration of NO3 in the irrigation water, and in some year responses to N may have been reduced by residual N from the previous legume crop in the field, it is not possible to precisely relate applied N to crop yield. Nevertheless, the principle of synchronizing both water and N needs of the crop were demonstrated. Parallel to the studies of Oweis et al. (1998, 1999), other field trials at Tel Hadya, near Aleppo in northern Syria, employed the same concept of supplemental irrigation with varying amounts of water (1/3, 2/3, and full irrigation) with varying N application rates in two seasons of differing rainfall (Garabet et al., 1998a,b). As expected, yields were increased by both irrigation and N, with a greater relative response to N in more favorable rainfall season with good distribution in the critical February–April period (323 mm) and to irrigation in the relatively drier year (275 mm). There was a maximum of 50 kg N ha 1 for rainfed conditions and up to 150 kg N ha 1 for the highest irrigation level within-season irrigation influenced N uptake patterns and total N uptake. A higher proportion of the accumulated N at anthesis occurred with irrigation (80%) compared to nonirrigated (60%) conditions. The work of Garabet et al. (1998a) showed the importance of seasonal weather conditions in relation to crop N responses under supplemental irrigation. The implications of irrigation or N uptake efficiency using labeled 15N (Garabet et al., 1998b) is discussed in another section dealing with N efficiency and recovery. These studies provide convincing arguments for using small amounts of irrigation water during the normal rainfed cropping season to supplement natural rainfall, particularly at crucial growth stages such as stem elongation and grain filling, if rainfall is deficient at that time. However, the corresponding crop growth increases from such management interactions are only possible by increased N fertilizer application. Nevertheless, the implementation of such a practice requires accurate monitoring of the soil moisture status and weather conditions to plan such interactions, as well as the availability of irrigation water at that time. In addition, as farmers have incurred the cost of installation of pumps and irrigation equipment and as farmers are not charged for using the water, there is little incentive for farmers to use minimal amounts of water as required by true supplemental irrigation. The subject of irrigation in relation to N fertilization in rainfed area would not be complete without mention of wastewater from urban areas, the only source of irrigation water in the Middle East region that is actually expanding. Currently, with ground water scarcity in the region and the limited prospect of any expansion in conventional sources, the notion of
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harnessing this potentially valuable resource is gaining momentum (Qadir, 2009). This potential is illustrated by the Quake River, which originates in Turkey and passes through the city of Aleppo. Nowadays it is used as an outlet from the city’s sewage. The river is used for irrigation of about 10,000 hectares south of the city. Despite the health hazards of using such water, if not treated properly, its provision of water for growing crops is an overriding factor. Intensive sampling at various points along the river showed that the water is heavily enriched with nutrients, especially N (Ryan et al., 2006b). In many cases, the N content of the water was such as to obviate the use of any additional N in the form of fertilizer. As it is inevitable that water-treatment plants will be installed in urban areas in the Middle East, ‘‘gray’’ water and associated nutrient load will be an important factor in the region’s agriculture in the future whether for full irrigation in arid areas as to supplement rainfall in rainfed areas. Of the trials that dealt with dryland cropping in conjunction, that of Mikhail et al. (2009) is noteworthy. As with the trials of Oweis et al. (1998, 1999), this experiment evaluated improved and landrace wheat varieties in relation to increasing water supply to meet the crop’s full irrigation requirements. As expected, seasonal rainfall influenced overall yield as well as responses to N. The important contribution was the interaction of water and N fertilization in relation to grain protein and other quality parameters. As irrigation increased yield, it also reduced the % N in the grain and thus protein content. This negative effect was counterbalanced by added N. Thus, to maintain grain protein to meet market specifications, N fertilization has to be balanced with the irrigation water. The N applied also increased gluten strength. The combined effect of water and N are important for grain quality, particularly in the Middle East where bread consumption per capita is one of the highest in the world. An early study of Barg et al. (1982) in Lebanon’s breadbasket, the Bekaa Valley, highlighted the need for synchronizing N management of the newly introduced short-strawed Mexipak winter-wheat cultivar. The applied N had little or no effect on ammo acids, especially the essential ones such as lysine. The study showed that some quality parameter can be readily influenced by N and other are not easily influenced.
11. Nitrogen Tracer use in Rainfed Cropping Systems Nitrogen exists in soils in various organic and inorganic ‘‘pool’’ that are in a constant state of flux. The belowground N dynamics involving mineralization of SOM are critical for the maintenance of available N to sustain growth of nonleguminous crops, especially where little or no
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fertilizer N is used. Similarly, fertilizer N added to the soil is subject immobilization and incorporated into soil microbial biomass. An understanding of the various processes involved in the fluxes of N in the soil and its uptake by crops is fundamental to devising strategies to enhance N fertilizer use efficiency. The critical issue is how much of the added fertilizer N is taken up and beneficially used by the crop and whether the unaccounted for N is lost from the system or immobilized for possible later release to the crop. Uptake by the crop only provides an index of efficiency based on apparent recovery, that is, differences between uptake by the fertilized crop compared to the unfertilized crop. As valid as this approach may be, soil-plant N processes can only be accurately defined by the use of stable N isotopes (Hauck and Bremner, 1976; Buresh et al., 1982). The main applications of 15N are in assessing BNF N fixation and N transformations and mass balances in soil-plant systems. Of particular relevance to dryland cropping is the application of tracers to quantify plant N uptake and loss (Harmsen, 2003a) and the significance of mineralization for N recovery (Harmsen, 2003b). Using actual data from a 2-year field trial with rainfed and irrigated wheat, Harmsen and Garabet (2003) showed differences in N recovery as indicated in the apparent recovery fraction and in 15N recovery, with the apparent recovery being higher than the latter method. One drawback of using 15N is the cost of the enriched N fertilizer and the (expensive) equipment required for the analysis of isotope. In early stages of ICARDA’s research, 15N studies largely on N fixation were carried out in collaboration with the International Atomic Agency. The use of 15N received a boost in the 1990s with a collaborative project involving the Reading University and the Overseas Development Agency. Though all the substudies involving 15N were conducted within the ‘‘Cropping Systems Productivity’’ long-term trial (Harris, 1995; Ryan et al., 2008a), it is appropriate to treat in a separate section following that of the integrated cropping systems trials. Thus, in the following section, the various substudies with 15N are briefly described, along with related reference to similar work in the region and other areas of a Mediterranean type climate, that is, Australia.
11.1. Fate of N fertilizer with wheat in a cereal–legume rotation The recovery of 15N-labeled fertilizer was assessed with either urea or ammonium sulfate at varying application rates (0, 30, 60, and 90 kg ha 1) for three seasons (1991/1992, 1994/1995). Nitrogen at 30 kg ha 1 was applied at sowing in autumn and the remainder was topdressed in spring. Recovery of 15N-labeled fertilizer in the aboveground biomass at harvest was low overall, from 8% to 22% (Pilbeam et al., 1997a,b) but comparable to
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the recovery of fertilizer in wheat in other countries of the Mediterranean region; for example, at four sites in central Turkey. Here, N fertilizer recovery in wheat crops using 15N isotope dilution averaged 14%, ranging from 6% to 22% (Halitligil et al., 2000), while at two sites in Tunisia the recovery of ammonium sulfate applied to wheat averaged 21% (Sanaa et al., 1992) and 30% was recovered in wheat grown at Meknes, Morocco (Corbeels et al., 1999b,c). Application of N fertilizer at 30 kg ha 1 had no effect on wheat productivity in 1992, but in the other two seasons grain yields were increased by 550 kg ha 1, on average. More than half the fertilizer in the crop at harvest had been taken up by the end of March, although by March the plants were only about 10% of their mass at harvest. Conversely, 35% of the soil-derived N in the crop at harvest had generally been taken up by early spring (Pilbeam et al., 1997b). This temporal difference in the pools of N utilized by the crop was attributed to the drying of the soil surface layer, where most of the N fertilizer remained. In microplots within the same study (Pilbeam et al., 1997a) the amount of 15N-labeled fertilizer recovered in the crop increased as the rate of application increased, but not in proportion to the amount of N added; labeled N taken up by the crop increased by only 10 kg N ha 1 as the fertilizer rate increased from 30 to 90 kg N ha 1. However, fertilizer application caused a significant increase in the amount of unlabeled soil N taken up by the crop (Pilbeam et al., 1997a,b), suggesting that the application of N fertilizer caused a ‘‘real’’ added N interaction ( Jenkinson et al., 1985), possibly due to alterations in the crop rooting pattern the fertilizer rate increased. Indeed, N fertilizer was shown to increase root growth, depth of rooting, and the amount and length of roots of barley in this region (Brown et al., 1987). Harris (1995) showed that water was extracted earlier in the season from greater depths in fertilized wheat crops than the unfertilized wheat crop in this long-term trial. The study also showed that crop recovery of 15N-labeled fertilizer was unaffected by the form of the fertilizer applied. Buresh et al. (1990) found that the recovery of applied N by wheat grown in large pots (50 kg soil) under simulated Mediterranean conditions in a glasshouse was greater when urea, rather than ammonium salts, was applied. Similarly, in this field experiment, more fertilizer was recovered in 1991 and 1992 (17% on average) when urea was applied than in 1992 and 1993 (9% on average) when ammonium sulfate was applied. This seasonal difference in crop recovery was attributed to differences in rainfall rather than the form of N fertilizer used, because in 1994 and 1995 similar amounts of N were recovered in the crop irrespective of the form of N fertilizer applied (18% recovery from urea and 20% from ammonium sulfate). On average, 31% (14–54%) of the 15N-labeled fertilizer remained in the soil at harvest, mostly in the 0–20 cm layer (Pilbeam et al., 1997a,b). At the lowest application rate (30 kg N ha 1) most of the residual fertilizer
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remained in the organic N fraction of the soil, but at higher rates a greater proportion of the 15N-labeled fertilizer was recovered as inorganic N (Pilbeam et al., 1996), presumably as the result of topdressing N in dry conditions in the spring. The amount of 15N-labeled fertilizer remaining in the soil increased as the fertilizer rate increased. In common with other countries in the Mediterranean region, more fertilizer N was recovered in the soil than in the crop; 50% of the fertilizer N was recovered in the 0–40 cm soil layer in 1991 and 1992 and 1992 and 1993. As with the crop, these recoveries in the soil compared favorably with those for other countries in the region, but contrasted strongly with those from countries outside the region. For example, 32% of the fertilizer N applied to wheat at two sites in Tunisia was recovered in the 0–80 cm soil layer (Sanaa et al., 1992). By contrast, recovery in the soil of N fertilizer applied to wheat in the UK, Belgium, and France was on average 20, 18, and 25%, respectively (Pilbeam, 1996). The N balance for this experiment showed that much of the 15N fertilizer could not be accounted for in the crop and soil at harvest, and was presumed lost. Losses averaged 54%, but ranged from 38% to 69%. Similarly, large percentage losses have been found in Tunisia (Sanaa et al., 1992). It has been shown (Powlson et al., 1992) that as the rate of application of N fertilizer increases above a threshold commensurate with optimum yield, the amount of N fertilizer lost also increases. At high rates of fertilizer application, the supply of N exceeds the demand, and as the excess accumulates it is increasingly subject to loss processes. However, when losses were expressed as a proportion of fertilizer applied they were never greatest at the highest application rate (Pilbeam et al., 1996, 1997a). The large losses of 15N-labeled fertilizer in these experiments may have partly been exacerbated by the application of the 15N fertilizer to microplots in solution. Previously losses of 15N-labeled granular urea fertilizer applied in at this site were much smaller (Abdel Monem, 1986). It was concluded from these studies that while fertilizer use is an important factor in increasing crop productivity in the region, its effect is not direct, but rather indirect. Little of the applied fertilizer is utilized directly by the crop; nevertheless, if rainfall is adequate, fertilizer applications do increase grain yield by stimulating the uptake of soil N. Soil N is derived in part from the large amounts of residual fertilizer remaining in the soil at harvest in the season of application. Therefore, applications of fertilizer are, in effect, maintaining soil fertility rather than directly fertilizing the crop.
11.2. Implications of 15N for rotation effects As the substudy of Pilbeam et al. (1997b) involved microplots with selected rotations (continuous wheat, chickpea, lentil, and fallow) some interferences about rotations could be made. Generally more N was recovered at
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harvest in wheat grown in rotation with chickpea, lentil, or fallow than with continuous wheat (Pilbeam et al., 1997b). The amount of N in the shoots was always least in the continuous wheat rotation in March, and at harvest always greatest in the wheat–lentil rotation This N benefit (12 kg N ha 1 on average) was small, but frequently contributed a large proportion (>25% on average) of the N in the wheat crop. Grain and dry matter yields were also generally greatest when wheat followed a rotation. Based on these data, the effect of a previous legume crop or a fallow on subsequent wheat yield was equivalent to a fertilizer application rate ranging from 0 to 30 kg N ha 1 to a continuous wheat crop, depending on the previous crop, and the season. Indeed, the fertilizer equivalence of a preceding lentil crop exceeded 30 kg N ha 1 in two years of the study. However, an absence of any marked difference in the calculated availability of N between rotations (using A-values) implied that the residues of the preceding phase of the rotation made little direct contribution to the N supply for the succeeding wheat crop and that it was some other factor which caused increased uptake of soil-derived N by the wheat following fallow or grain legume. It was suggested that whilst a fallow may increase the availability of water to the succeeding wheat crop, the benefit from the preceding grain legumes may lie in their effect on the soil physical structure, or on the increased availability of other limiting nutrients (such as P) rather than, simply, release of N.
11.3. Estimated N fixation by grain legumes using 15N technique Quantification of the amount of N fixed by grain legumes is vital for the economy of N in dryland cropping. Various methods, including natural abundance and enriched 15N techniques, are used to estimate BNF legumes with advantages and disadvantages of each (Unkovich et al., 2008). The ‘‘Cropping Systems Productivity’’ trial offered an opportunity to use the classical isotope dilution (ID) technique for measuring BNF by chickpea and lentils over three seasons in Syria (McNeill et al., 1996). The work measured the potential input of N that can occur via grain legumes in these rainfed Mediterranean farming systems. There were marked seasonal variations in amounts fixed, largely due to variable rainfall, but also influenced by pests and diseases. In one season, more than 50% of the aboveground grain legume N was derived from BNF and in the other two seasons it ranged from 68% to 95%; this equated to amounts of N derived from BNF of 20–80 kg N ha 1 in both lentil and chickpea depending on season. Clearly, if all the aboveground material is removed at harvest, as commonly practiced, then N inputs to the system would be minimal and limited to N derived from BNF in fallen leaves and in roots. Such inputs were not quantified in this study but have since been quantified for pasture and grain
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legumes in Australia and shown to be important in providing an N benefit to the subsequent wheat crop. It was noted also from this study in Syria that an application of urea fertilizer equivalent to 10 kg N ha 1, a rate commonly used in other ID studies of BNF in Mediterranean systems (Beck et al., 1991), inhibited BNF in chickpea but not in lentil, although final yield of chickpea was not affected as the crop apparently compensated for lower BNF by increased uptake of N from soil. It was suggested from the results of this study that alternative isotope techniques (natural abundance or slowrelease 15N sources) might be more suitable for estimating BNF for the farming systems in Syria on heavy textured soils where cycling of N from SOM was a dominant factor. Hence a subsequent study assessed BNF by grain legumes using plots where 15N-labeled fertilizer had previously been applied to wheat, and employing the residual 15N in soil as a slow-release source to estimate BNF (termed the IDres technique) and comparing results with those obtained using ID (McNeill et al., 1998b). The data from this work showed that, although estimates of the proportion of N derived from the atmosphere (pNatm) from the IDres method were generally slightly less than those derived using classical 15N ID methodology, the differences were relatively small, in fact less than the difference in estimates of pNatm for chickpea at different growth stages. However, the IDres method was considered to have three important advantages over classical ID. Firstly, there was less variability in the source of labeled plant-available 15N through time when using the IDres method, and to some extent also more uniformity to depth in the soil with the 15N abundance of inorganic N in the top 0–20 cm soil depth being fairly similar to that in the 20–40 cm depth. Secondly, applications of fertilizer N in the season of measurement, as required by the classical ID method, may inhibit nodulation and BNF by legumes (McNeill et al., 1996). Thirdly, compared with classical ID there is potentially a greater return from IDres on the original investment in the experiment because measurements of BNF may be obtained over several seasons from a single application of 15N-labeled fertilizer. The low recovery of residual fertilizer 15N by the reference wheat crop in this work suggested that, if the rate of release of immobilized 15N remained relatively constant, residual 15N could be used for several years to estimate BNF. However, the availability of immobilized fertilizer 15N will be subject to edaphic influences on soil N dynamics and also, particularly at ICARDA, strongly governed by climatic conditions (McNeill et al., 1996; Pilbeam, 1996). Therefore, a long-term supply of 15N-labeled plantavailable N may not be guaranteed. Data presented by McNeill et al. (1996) indicated that, irrespective of the methods (ID or IDres), the proportion of unlabeled to labeled N exploited by both legume and reference plants will sometimes differ through the
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season. Therefore, although residual 15N-labeled fertilizer may increase uniformity in the 15N labeling of plant-available N from a depth of 0– 40 cm, it is likely that uptake of unlabeled N from deeper soils will introduce errors. Under these circumstances, estimates of BNF from all ID techniques that use surface applications of fertilizer N and rely on incorporation via downward movement of water through the soil after rainfall are likely to be imprecise. In this respect the 15N natural abundance technique for estimating BNF has the advantage that it does not require additions of 15N-labeled fertilizer, although this technique still requires comparison of an N2 fixing plant with a reference nonfixing plant. These studies at ICARDA concluded that BNF by grain legumes in rotations represented a valuable N input to the farming system but where large amounts of aboveground residues were removed from the field (for feeding to animals) the value to soil fertility was likely to be negligible, although this was based on assumptions that little fixed N accumulated belowground. The values for estimated BNF derived for chickpea and lentil and the measured shoot dry matter and N yields fit the general regression relationships described by Pilbeam et al. (1997c) for these environments. One could therefore argue that simple measurements such as DM production may provide adequate indications of N inputs by BNF into these dryland agricultural systems. A similar concept has arisen from Australian work (Unkovich et al., 2008) where values from 15 to 25 kg N fixed per ton of grain legume or pasture dry matter produced per hectare have been proposed. Such relationships could prove very useful when constructing N budgets for farming systems. Nevertheless, the widespread application of such relationships needs to be advocated with caution given the enormous variability in edaphic and climatic variables across environments.
12. Modeling of Nitrogen in Rainfed Cropping Systems 12.1. Previous nitrogen modeling Unpredictability of intra- as well as inner-seasonal rainfall distribution and long dry summer periods characterize the Mediterranean environment (Stapper and Harris, 1989). The previous chapters underpinned that the consequential high variation in soil moisture overtime has major influence on soil N dynamics, namely the decomposition of SOM, ammonification and (de-)nitrification, and the availability of N to plants. High temporal variation of these processes characterizes the Mediterranean environment. In this context, N-fertilizer management remains a challenge, and basically the same is true for the simulation of N dynamics by computer models. Whereas such simulations have become very much standard for temperate,
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mesic environments with generally a high accuracy and reliability achieved, in the Mediterranean regions, both, successes and failures have been reported in literature. Clearly attributable to its origin in Australia, one of the crop–soil simulation models that has been applied most widely in Mediterranean environments is the Agricultural Production Systems SIMultor (APSIM) (Keating et al., 2003). It is also one of the few models with a considerable long-lasting history that is still maintained and developed further. Its development started in 1991 together with the formation of the Agricultural Production Systems Research Unit (APSRU). APSIM developers were engaged in biophysical modeling before that time and tools like AUSIM (McCowen and Williams, 1989), PERFECT (Littleboy et al., 1992), or a cotton model (later on called OZCOT) (Hearn, 1994) had been built. APSIM’s development drew on this and other available knowledge of biophysical modeling, with some bits and pieces borrowed from the early models of Wageningen scientists of The Netherlands or the CERES-models from United States. Keating et al. (2003) emphasized that APSIM was developed to address ‘‘important systems’ aspects of cropping.’’ The APSIM’s soil-N routine/module, called SOILN, was based on the CERES-model (Hanks and Ritchie, 1991; Ritchie et al., 1985), that is, from a routine that originally had been built for the description of soil N dynamics in temperate, mesic climates. Probert et al. (1998a) provide a detailed description of SOILN. A schematic representation of the major processes is provided in Fig. 7. To demonstrate its capacities, Probert et al. (1998a) simulated the soil N dynamics under two agricultural sites, one comprising different tillage and N-fertilization treatments, the second considering a fallow soil without crop
Crop uptake FOM Denitrification CO2 CO2
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Figure 7 Pools and fluxes of soil organic matter and nitrogen in the soil as implemented in the SOILN module of APSIM; redrawn from Probert et al. (1998a), FOM, fresh organic matter pool; BIOM, labile, soil microbial biomass pool; HUM, rest of organic matter pool that is subject to decomposition.
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vegetation. Simulation results closely matched observed data, but simulations had one bottleneck: for the long-term data set (conventional tillage, zero-N), the model was reinitialized each season and no continuous simulation of the observed period (1987–1994) was carried out. The authors concluded that the tested APSIM modules are ‘‘robust in the sense that they will be widely applicable’’ and further that ‘‘the modules do capture the dynamics of nitrate N in soil sufficiently well to be used along with other modules in the simulation of diverse farming systems.’’ In the same year, Probert et al. (1998b) published a status report of work on the APSIM simulations of legume–cereal rotations systems under Mediterranean climate conditions. The apparent difficulty of the SOILN module to simulate correctly the dynamics of the decomposition of incorporated residues, and the ‘‘less advanced stage’’ of the modules for the legumes of interest were identified by the authors as two aspects requiring further improvement. Extrapolating beyond the bounds of experimental data, the authors simulated a hypothetical chickpea–wheat rotation (as did 9 years later Moeller et al., 2007, see below). The average simulated chickpea grain yield was somewhat less than 3 tons per hectare. Crop and root residues of chickpea remaining in the field for the following wheat crop were estimated to substitute for approximately 40 kg of N ha 1 fertilizer. APSIM was used to evaluate the accuracy of predictions of soil mineral N, NO3 leaching, and N uptake of wheat grown on sandy soils in the 500 mm rainfall zone west of Moora in Western Australia (Asseng et al., 1998). Crop growth and yield could be simulated reasonably well, but soil mineral N dynamics were less well predicted. Simulation of 81 years— discontinuously one by one, that is, focusing on the year-to-year climate variability—of wheat–lupine rotation revealed 50% probability that 53 kg N ha 1 could be leached under wheat following lupine. Leaching of N thus was high, and the authors argued that the high drainage and leaching potential of the sandy soils were responsible for yields that were lower than predicted by the approach of French and Schultz (1984), who estimated that 20 kg of grain yield could potentially be produced per 1 mm of rainfall. In line with common recommendations for Mediterranean production systems and taking into consideration the low water (and nitrate) retention capacity of sandy soils, simulations furthermore showed that higher grain yields were to be expected from split application compared with a single application of N fertilizer. With the aim to guide agronomic management practices, including fertilization strategy Asseng et al. (2001) used APSIM to assess the WUE and NUE of wheat grown under Mediterranean climate of central Western Australia. Long-term simulations, based on between 82 and 87 years of available weather data, for different soil and rainfall areas (low, medium, and high) underpinned the inherently high degree of seasonal variability in yield, WUE and NUE of wheat, depending on soil type, N fertilizer
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input, rainfall amount and, in particular, rainfall distribution. The authors claimed that ‘‘simulations confirmed findings from a limited number of field experiments and extended these findings both qualitatively and quantitatively across soil types, rainfall regions, and crop management options’’. Being criticized on the usefulness of crop modeling, Carberry et al. (2002) tackled the question whether crop models could assist the research community in contributing to purposeful change in farming practice. To underline that this indeed has been the case, they, among others, detail two case studies that address strategies—developed with the help of modeling— of augmenting traditional farming practices with small applications of N and P fertilizer. In a more recent publication, Moeller et al. (2007) applied APSIM to simulate a wheat–chickpea rotation trial at ICARDA headquarters in northwestern Syria, with the aim to assess the sustainability of crop and soil management practices in wheat-based cropping systems. The authors encountered difficulties of APSIM’s soil N routine to simulate mineral N dynamics in the clay soil (compare also with findings of Probert et al., 1998b—see above), which in consequence hampered any further modelbased assessment of the sustainability of the production system. The study of Brennan et al. (2007) is an example for biophysical model application APSIM in a more integrated economic-agro-ecological context. The authors tackle the issue of economic benefits of precision agriculture for Australian farmers. They present a framework for a systematic investigation of the effect of the interaction between temporal variability (driven by climate variability) and spatial variability, that is, the field heterogeneity that may result in varying application of N fertilizer by means of precision agricultural practices, on the overall economic performance of farms in Australia. Following this, they assessed the value of spatially variable N management (i.e., precision agriculture) to a farmer with and without knowledge about the coming season. Results of a scenario analysis showed that seasonal and spatial interactions in N management are important aspects within the decision making process, and that knowledge of the coming season is worth more than knowledge of spatial variability, but knowledge of both creates the greatest value. Besides APSIM, other major crop models have been applied, though less frequently, for an assessment of N dynamics in Mediterranean climate regions. Hasegawa and Denison (2005) used the CERES-wheat crop simulation model to determine average effect of 46 years of winter weather observed at University of Davis, California, USA, on soil N dynamics, N uptake and wheat yield within six different types of rotations. Nitrate leaching and mineral N decomposition, release and availability were particularly focused on. Simulated nitrate leaching was above at least 50 kg N ha 1 year 1 throughout, and was highest (108 kg N ha 1 year 1) in the wheat–legume cover crop (LCC) rotation with a high input of N from
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the legume phase. On the other hand, the N balance of the LCC-rotation with low legume N-input was 147 kg N ha 1 season 1, if it was assumed that Ndfa by fixation was 50%. Even with 100% Ndfa, the low LCC-input system would fail to maintain a neutral N-balance. The authors concluded that it seemed impossible to decrease N leaching (e.g., by decreasing LCC input) without sacrificing availability of inorganic soil N to wheat in these systems and to maintain soil fertility in the long run. The CERES-wheat model was used to analyze to what degree improved N fertilization, besides the constraining factor water, could contribute to reducing the gap between attainable and potential yield of wheat in northeastern Spain under rainfed conditions (Abeledo et al., 2008). Wheat performance and yield were simulated for a period of 17 years for which weather data were available. As expected, water availability (stress) was the most yield-limiting factor. The crop response to N fertilization was comparably poor. For instance, increasing soil N availability beyond 100 kg N ha 1 at sowing time generated a gain in yield only in 6% of the years. Excessive N fertilization was, therefore, judged unwise for economic but also ecological reasons (risk of nitrate leaching). Only in rainy years characterized by low potential yields and mild water stresses, N management could significantly increase yields and effectively reduce the yield gap. Severe water stress in some years, however, nullified any efforts to improve crop-N nutrition by fertilizer application. The study underlines that N-fertilizer management remains a challenge, due to the strong interlinkage with, but at the same time unpredictability of, water availability in Mediterranean types of environments. The Root Zone Water Quality Model (RZWQM) was used to simulate N transformation, uptake and transport for basin-irrigated grain corn on a silty loam and sprinkler-irrigated forage corn on a sandy soil in Portugal (Cameira et al., 2007). The emphasis of the study was laid on the calibration of the SOM pools and selected soil N transformation processes (mineralization, hydrolysis, and nitrification). Crop growth, yield and N uptake were well predicted for an independent model evaluation data set (same sites, but different year) that covered four different fertilizer levels. Also, soil nitrate dynamics could be well reproduced, whereas, no results on observed or simulated ammonium dynamics were presented. The publication also did not elaborate any further on the usefulness of the simulations with regard to irrigation, or fertilizer management, nor were scenario analyses included in this publication. The study of Corbeels et al. (1999a,b,c) is an example of a less successful application of crop–soil models to Mediterranean climate regions. They authors used NCSOIL to simulate N-dynamics in soils (Chromic Calcixerert with clay texture) from an experimental wheat plot in Mekne`s, Morocco, that had been exposed to a range of different soil incubation. The authors had to introduce into the model what they called a retardation
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factor; a new parameter that would account for the fact that organic matter decomposition was greatly influenced by the lignin content of the incorporated residues. They further more could not precisely simulate the N-turnover of sheep manure, which they concluded was related to a different allocation of N in animal manure to N-containing soil fractions compared to that of plant residues. Data on growth, yield, and water and N use of two durum wheat cultivars grown under rainfed as well supplementary irrigated conditions at different levels of N-fertilization at ICARDA headquarters in Syria were used to parameterize the CropSyst model (Pala et al. (1996b). The model was generally able to simulate with sufficient accuracy, ET, crop N content, green leaf area, aboveground biomass, and grain yield of these two cultivars. Nevertheless, some discrepancies between predicted and observed grain yield in some years could not be eliminated. The authors concluded that this was due to the influence of harsh environmental conditions (late frost or strong hot winds) in some years, in response to which plant growth processes were disrupted by stress, which was difficult to simulate. Finally, Sadras (2002) also applied CropSyst to assess the problem of terminal drought of winter crops such as wheat in southeastern Australia. In this context, N fertilizer application is a difficult business, whereas farmers rather tend to apply less fertilizer to minimize risks. The authors evaluated best management strategies for three different rainfall environments by simulating three level of N fertilizer application (in total, 5, 35, and 55 kg N ha 1). Simulation results indicated that with the prices of wheat and fertilizer encountered around the turn of the millennium, farmer practice involving a very low input of N fertilizer ensured the greatest economic stability at all sites. Nevertheless, at the sites with more rainfall, the authors detected opportunities for improving gross margins and reduce deep drainage by increasing the dose of N fertilizer in the wetter season.
12.2. Models for arid environments It can be concluded from the discussion above that simulation models that have been developed elsewhere and in part also primarily for temperate environments/cropping systems, are applicable to describe N dynamics of cropping systems in the Mediterranean regions. Not more or less successes or failures of model application have been reported for these systems as compared to, for example, cropping systems in temperate regions. Comparing different models; there are only a few publications in which more than only two crop models were compared (as opposed to a merely reviewed)—in general (Diekkru¨ger et al., 1995; Semenov et al., 1996; Wolf et al., 1996) or focusing on the model capability to simulate water dynamics and the influence of drought ( Jamieson et al., 1998), irrigation and drainage management (Bastiaanssen et al., 2007) or the dynamics of SOM
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(Smith et al., 1997). The comparison of model capacities for simulating N dynamics, let alone a focus on dry environments, has received less attention, and the publication of De Willigen (1991) and Gabrielle et al. (2002), to our knowledge, are the only accounts. Some attempts were made to raise the awareness of model improvement. Jeuffroy et al. (2002) describe ways in which recent molecular plant physiology findings could be integrated into some major crop models. The potential value of this approach for improving current agronomic models and diagnostic tools, and for breeding more efficient varieties is also discussed. The authors concluded that more information is required about plant and crop N economy. Latest findings could/should be used for updating the classical subroutines of major agronomic models, namely the way in which N absorption and use within the plant and crop is described and how plant responses to deficiencies and excesses of nitrogen are tackled (see Fig. 8). Collins et al. (2008) emphasized the importance of so-called fungal loops in arid ecosystems, and the need for considering those in conceptual models of (soil) nutrient dynamics. They also stress the importance of episodic precipitation events that stimulate biological activity which in turn generates reserves of biomass and organic matter that prime the ecosystem to respond rapidly to subsequent precipitation—a dynamic also known as the ‘‘pulse-reserve model.’’ Describing the role of fungi in the N cycle they state: ‘‘Both bacteria and fungi have pathways for transforming N. In mesic systems, the bacterial processes of dissimilatory denitrification and autotrophic nitrification dominate redox reactions, while fungi are generally considered to dominate N mineralization and translocation within the litter and
Soil-N availability
Crop growth and development
Absorption, Assimilation
N available for crop growth Potential growth and N storage
>=<
Potential growth
N demand
Reduced growth
Figure 8 General classical framework for simulating N-availability and crop uptake; redrawn from Jeuffroy et al. (2002).
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upper mineral soil horizon. Emerging evidence . . . suggests, however, that fungi may control all these processes in some aridland soils . . . principally because they can metabolize at higher temperatures and lower water potentials than either plants or bacteria . . .. Consequently, the N cycle of arid ecosystems may be distinct from that of wetter systems in that prokaryotic processes make a more modest contribution to annual N fluxes than do fungi. In arid ecosystems, as in other ecosystems, primary producers (grasses, biological soil crusts) have extensive symbioses with fungi . . .. These symbioses may enhance desiccation resistance during dry periods and act as networks for water and nutrient transport during pulses of water availability . . ..’’ Modeling N-dynamics in arid environment might benefit from inclusions of latest findings into the existing concepts, such as the ones stated above. However, judging from previous successes in modeling N-dynamics in these environments, clearly biophysical modeling has not yet exhausted the classical concepts. Rather the contrary, more complex, multipool SOM (and thus N) modules, that had been realized in models such as CENTURY (Parton et al., 1994) already some 15 years ago, only recently were included in some major crop models, such as CropSyst or DSSAT, with more comprehensive assessments only now being done.
13. Future Perspective The review sought to present an overview of N in the dryland cropping conditions in the Mediterranean region, indicating the various areas of research involving N, from soil to plant. It highlighted a chronology in N research over the past three decades since the early days of widespread N fertilizer use in the region. These research achievements provided a basis for the indispensable need for using N in today’s agriculture. Despite the accomplishments in various areas of N research, gaps in knowledge still exist. The significance of deficiencies in our understanding of this most complex and ubiquitous of elements is likely to change with time. Understandably, the focus of N in Mediterranean agriculture in the past has been on increasing crop production, but the future will inevitably embrace environmental aspects of N use as well. Given the fact that much of the N applied to the crop does not affect the crop in terms of uptake and growth, the quest to improve N-use efficiency through improved management will continue. Under more favorable rainfall areas of the Mediterranean, and under irrigated conditions, more emphasis will be given fine-tuning application methods as called for in ‘‘fertilizer best management practices.’’ With increasing irrigation, the potential loss of N through leaching will be greater, and will require
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monitoring. Where ground water or surface waters are enriched with nitrate, the agriculture sector will be required to mitigate such losses in view of the human health hazards. Though little or no consideration has been given to N content in the crop end product in terms of nutritional quality, which is likely to change in view of the implications for human health in an area of the world that has the highest per capita bread consumption. While the importance of considering N in the longer term of cropping systems rather than in a single season has been shown, the ‘‘bigger picture’’ needs to be elucidated for various other cropping systems in the region. Special emphasis will be given to the impact of N use on soil quality, with respect to carbon sequestration in addition to its effect on the productive potential of the soil and cropping sustainability. Though some avenues of N loss from the system were documented, much more research is needed to quantify such losses, especially with respect to nitrous oxide, one of the most potent greenhouse gasses. In that context, more research emphasis will, in future, be given to N in relation to conservation agriculture; the practice is in its infancy in the Mediterranean region, and N did not get much attention in this system so far. In an educationally seamless world, much of what is known about N in the world will impact developing areas of the world such as some countries of the Mediterranean region. In future, issues dealing with N, from soil to crop to human and animal, will be more complex requiring correspondingly more complex technologies. Inevitably, modeling will assume a greater role in integrating the various aspects related to N in the future.
ACKNOWLEDGMENTS This review had its genesis in The Nitrogen Working Group at ICARDA in the mid-1990s The group consisted of J. Ryan (Chair), L. Materon, M. C. Saxena, F. Afendi, H. Harris, and A. V. Goodchild. The discussions that took place and the unpublished report that emanated from the Group provided the seed that was subsequently to emerge. We thank all concerned in that effort.
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Agriculture’’ (G. A. Peterson, P. W. Unger, and W. A. Payne, Eds.), 2nd Edn. Agronomy Monograph, pp. 577–624. Am. Soc. Agron, Madison, WI, USA. Ryan, J., El_Mourid, M., Shroyer, J. P., and El Gharous, M. (2007). The Dryland Agriculture Applied Research Project in Morocco: A perspective 12 years after completion. J. Nat.Resour. Life Sci. Educ 36, 120–128. Ryan, J., Singh, M., and Pala, M. (2008a). Long-term cereal-based rotation trials in the Mediterranean Region: Implications for cropping sustainability. Adv. Agron. 97, 273–319. Ryan, J., Masri, S., Ceccarelli, S., Grando, S., and Ibrikci, H. (2008b). Differential responses of barley landraces and improved barley cultivars to nitrogen-phosphorus fertilizer. J. Plant Nutr. 31, 381–393. Ryan, J., Pala, M., Masri, S., Singh, M., and Harris, H. (2008c). Rainfed wheat-based rotations under Mediterranean cropping conditions: Crop sequences, nitrogen fertilization, and stubble grazing in relation to grain and straw quality. Eur. J. Agron. 28, 112–118. Ryan, J., Masri, S., Singh, M., Pala, M., and Ibrikci, H. (2008d). Total and mineral nitrogen in a wheat-based rotation under dryland Mediterranean conditions. Basic Appl. Dryland Res. 2, 34–46. Ryan, J., Masri, S., I˙brikc¸i, H., Singh, M., Pala, M., and Harris, H. C. (2008e). Implications of cereal-based crop rotations, nitrogen fertilization, and stubble grazing on soil organic matter in a Mediterranean-type environment. Turk. J. Agric. Forest. 32, 289–297. Ryan, J., Ibrikci, H., Singh, M., Rashid, A., Matar, A., Masri, S., and Pala, M. (2008f). Response to residual and currently applied phosphorus in three Syrian agroecosystems. Eur. J. Agron. 28, 126–137. Ryan, J., Abdel Monem, M., and Amri, A. (2009a). Nitrogen fertilizer response of some local and improved barley varieties in semi-arid conditions in Morocco. J. Agric. Sci. Technol. 11, 227–236. Ryan, J., Masri, S., Pala, M., and Singh, M. (2009b). Nutrient dynamics in a long-term cereal-based rotation trial in a Mediterranean environment: Nitrogen forms. Commun. Soil Sci. Plant Anal. 40, 931–946. Ryan, J., Masri, S., and Singh, M. (2009c). Seasonal changes in soil organic matter and biomass and labile forms of carbon as influenced by crop rotations. Commun. Soil Sci. Plant Anal. 40, 188–199. Ryan, J., Pala, M., Singh, M., Makboul, R., Masri, S., and Harris, H. C. (2009d). Crop sequences, nitrogen fertilizer, and stubble grazing in relation to wheat yields in rainfed Mediterranean cropping systems. J.Agric. Sci. (Camb.) (Final stages of review). Sadras, V. O. (2002). Interaction between rainfall and nitrogen fertilization of wheat in environments prone to terminal drought: Economic and environmental risk analysis. Field Crops Res. 77, 201–215. Sanaa, M., Van Cleemput, O., Baert, L., and Mhiri, A. (1992). Field study of the fate of labeled fertilizer nitrogen applied to wheat on calcareous Tunisian soils. Pedologie 42, 245–255. Scheppers, T. S., and Raun, W. A. (2008). Nitrogen in Agricultural Systems. Agronomy Monograph No. 49. Am. Soc. Agron., Crop Sci. Soc. Am., Soil Sci. Soc. Am., Madison, WI, USA. Schlegel, A., and Grant, S. (2006). Soil fertility. In ‘‘Dryland Agriculture’’ (G. A. Peterson, P. W. Unger, and W. A. Payne, Eds.), pp. 141–194. Am. Soc. Agron., Crop Sci. Soc. Am., Soil Sci. Soc. Am., Madison, WI, USA. Semenov, M. A., Wolf, J., Evans, L. G., Eckersten, H., and Iglesias, A. (1996). Comparison of wheat simulation models under climate change. II. Application of climate change scenarios. Climate Res. 7, 271–281.
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Shroyer, J. P., Ryan, J., Abdel Monem, M., and El Mourid, M. (1990). Production of fall-planted cereals in Morocco and technology for its improvements. J. Agron. Educ. 19, 32–40. Silim, S. N., and Saxena, M. C. (1992). Comparative performance of some faba bean (Vicia faba) cultivars of contrasting plant types. 1. Yield, yield components and nitrogen fixation. J. Agric. Sci. (Camb.) 118, 325–332. Smith, R. C. G., and Harris, H. C. (1981). Environmental resources and restraints to agricultural production in a Mediterranean-type environment. Plant Soil 58, 31–57. Smith, P., Smith, J. U., Powlson, D. S., McGill, W. B., Arah, J. R. M., Chertov, O. G., Coleman, K., Franko, U., Frolking, S., Jenkinson, D. S., Jensen, L. S., Kelly, R. H., et al. (1997). A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments. Geoderma 81, 153–225. Solh, M. B., Hamid, S., Itani, H., and Ryan, J. (1986). Nitrogen supplementation of inoculated and non-inoculated soybeans at two planting densities. Dirasat 13, 63–73. Soltanpour, P. N. (1985). Use of ammonium bicarbonate-DTPA soil test to evaluate elemental availability and toxicity. Commun. Soil Sci. Plant Anal. 16, 323–338. Soltanpour, P. N., El Gharous, M., and Azzaoni, A. (1986). Nitrogen and phosphorus soil test calibration studies in Morocco. In (P. N. Soltanpour, Ed.), ‘‘Proceedings, First West Asia and North Africa Soil Test Calibration Workshop’’, pp. 85–96. The International Center for Agricultural Research in the Dry Areas, Aleppo, Syria and MidAmerica International Consortium, Settat, Morocco. Soudi, B., Sbai, A., and Chiang, C. N. (1990). Nitrogen mineralization in semi-arid soils of Morocco: Rate constant with depth. Soil Sci. Soc. Am. J. 54, 756–761. Stanford, G., and Smith, S. J. (1972). Nitrogen mineralization potentials of soils. Soil Sci. Soc. Am. Proc. 36, 465–472. Stapper, M., and Harris, H. C. (1989). Assessing the productivity of wheat genotypes in a Mediterranean climate using a crop simulation model. Field Crops Res. 20, 129–152. Steiner, J. L., Day, J. C., Papendik, R. I., Mayer, R. E., and Bertrand, A. R. (1988). Improving and sustaining productivity in dryland regions of developing countries. Adv. Agron. 8, 79–122. Stewart, W. M., Dibb, D. W., Johnston, A. E., and Smyth, T. J. (2005). The contribution of commercial fertilizer nutrients to food production. Agron. J. 97, 1–6. Stevenson, F. J. (1982). Nitrogen in agricultural soils Am. Soc. Agron., Crop Sci. Soc. Am., Soil Sci. Soc. Am., Madison, WI, USA. Subramanian, V. S. (1981). A summary of soil survey and soil fertility work done in the dry farming regions of the Syrian Arab Republic.The International Center for Agricultural Research in the Dry Areas, Aleppo, Syria Unpublished report. Sultan, K., Gintzburger, G., Obaton, M., Robin, C., Touchane, H., and Guckert, A. (2001). Growth and nitrogen fixation of annual Medicago-Rhizobium associations during winter in the Mediterranean region. Eur. J. Agron. 15, 221–229. Tenkorang, F., and Lowenberg-DeBoer, J. (2009). Forecasting long-term global fertilizer demand. Nutr. Cycl. Agroecosyst. 83, 233–247. Thornes, J. B. (1996). Desertification in the Mediterranean. In ‘‘Mediterranean Desertification and Land Use’’ ( J. Brandt and J. B. Thornes, Eds.), pp. 1–11. John Wiley & Sons, Chichester, UK. Tiedeman, J. A., Mergoum, M., and Ryan, J. (1994). Effect of nitrogen and phosphorus fertilization a native annual plant community in central Morocco. In ‘‘Abstract of oral presentation, Society of Range Management Annual Meeting’’, Colorado Springs, CO, USA. Tillman, D., Cassman, K. G., Matson, P. A., Naylor, R., and Polasky, S. (2002). Agricultural sustainability and intensive production practices. Nature 418, 671–677.
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Unkovich, M. J., Herridge, D. F., Peoples, M. B., Boddey, R. M., Cadisch, G., Giller, K., Alves, B., and Chalk, P. (2008). Measurement of plant-associated nitrogen fixation in agricultural systems. ACIAR Monograph No. 136. Australian Center for International Agricultural Research, Canberra. Wahbi, A., Mazid, A., and Jones, M. J. (1994). An example of the farming systems approach: The fertilization of barley in farmer and researcher managed trials in northern Syria. Exp. Agric. 30, 171–176. Walsh, L. M., and Beaton, J. D. (1990). Soil Testing and Plant Analysis. Soil Sci. Soc. Am, Madison, WI, USA. Ward, R. C. (1971). Nitrate-N soil test: Approaches to use and interpretation. Commun. Soil Sci. Plant Anal. 2, 61–71. White, H. (1963). Roman agriculture in North Africa. Niger. Geogr. J. 6, 39–49. White, H. (1970). Fallowing, crop rotation and crop yields in Roman times. Agric. Hist. 44, 281–290. White, P. F., Nersoyan, N. K., and Christiansen, S. (1994). Nitrogen cycling in a semi-arid Mediterranean region: Changes in soil N and organic matter under several crop/livestock system. Aust. J. Agric. Res. 45, 1293–1307. White, P. F., Treacher, T. T., and Termani, A. (1997). Nitrogen cycling in semi-arid Mediterranean zones: Removal and return of nitrogen to pastures by grazing sheep. Aust. J. Agric. Res. 48, 317–322. Wolf, J., Evans, L. G., Semenov, M. A., Eckersten, H., and Iglesias, A. (1996). Comparison of wheat simulation models under climate change. I. Model calibration and sensitivity analyses. Climate Res. 1996, 253–270. Yaalon, D. H. (1997). Soils in the Mediterranean region: What makes them different? Catena 28, 157–169.
C H A P T E R
T H R E E
Biogeochemical Processes Controlling the Fate and Transport of Arsenic: Implications for South and Southeast Asia Scott Fendorf and Benjamin D. Kocar Contents 1. 2. 3. 4.
Introduction Arsenic Aqueous Chemistry Arsenic Surface and Solid Phases Desorption of Arsenic in Soils and Sediments 4.1. Comparative desorption of arsenite to arsenate 5. Biogeochemical Processes 5.1. Microbial arsenate reduction 5.2. Arsenic desorption upon anaerobiosis 6. Processes Controlling Arsenic Concentrations in South(east) Asia 7. Summary and Conclusions Acknowledgments References
138 139 139 146 147 149 149 150 154 157 158 158
Abstract Arsenic is a ubiquitous toxin present in soils and waters resulting from both natural and anthropogenic sources. Within South and Southeast Asia, tens of millions of people are drinking groundwater having arsenic concentrations exceeding the recommended standard of the World Health Organization (10 mg L1). Arsenic originates within minerals of the Himalaya. During weathering and erosion, arsenic is transported down the large river systems draining the mountains in the sediment load primarily as arsenic-bearing iron oxides and then deposited in the Bengal Basin, and Irrawaddy, Mekong, and Red River Deltas. The key biogeochemical step leading to human exposure of arsenic via drinking water is a result of arsenic release from soil/sediment solids into pore water. With the exception of ‘extreme’ pH values (pH < 4 or pH > 9) or high concentrations of competing anions such as phosphate, arsenic Stanford University, Stanford, California, USA Advances in Agronomy, Volume 104 ISSN 0065-2113, DOI: 10.1016/S0065-2113(09)04003-6
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2009 Elsevier Inc. All rights reserved.
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release is predicated on the aeration (or redox) status of the environment. Within aerated soils and sediments, arsenic predominates in the As(V) oxidation state and typically binds strongly to soil solids. Upon a transition to anaerobic conditions, arsenic is reduced to As(III), and while binding appreciably to Fe(III) (hydr)oxides, provided they are present, is labile and thus subject to migration and biological uptake. The transition from As(V) to As(III) is, in fact, an important transformation impacting As within reducing environments (discounting sulfogenic systems). The fate and transport of arsenic under anaerobic conditions, however, is further modified by reactions of and with Fe. Although transformation products of ferrihydrite reduction can lead to transient sequestration of arsenic, iron (hydr)oxide reductive dissolution further promotes dissolved concentration of arsenic. Within the aquifer systems of South and Southeast Asia, organic matter (co-deposited, incorporated, or dissolved) promotes anaerobic conditions in soils/sediments residing below the water table, leading to reductive release of arsenic. Arsenic release is most prominent in environments where organic matter is incorporated into anaerobic systems (such as permanently saturated wetlands), yielding the greatest magnitude of arsenic and iron reduction.
1. Introduction Arsenic is a naturally occurring trace element that poses a human health risk when incorporated into food or water supplies. The greatest risk imposed by arsenic results from contamination of drinking water, for which the World Health Organization recommends a maximum limit of 10 mg L 1. Continued ingestion of drinking water having hazardous levels of arsenic can lead to arsenicosis and cancers of the bladder, skin, lungs, and kidneys (Mandal and Suzuki, 2002). Unfortunately, arsenic tainted drinking waters are a global threat (Mandal and Suzuki, 2002; Smedley and Kinniburgh, 2002) and presently having a devastating impact on human health within Asia. At present, more than 100 million people are consuming drinking water having arsenic concentrations exceeding the World Health Organization’s recommended limit of 10 mg L 1, with the vast majority living in Asia and principally in Bangladesh and West Bengal, India (Ravenscroft et al., 2009). Arsenic pollution often results from human activities such as mining or pesticide application, but it is now recognized that the vast majority of arsenic contamination results from natural source. Arsenic becomes problematic from a health perspective principally when it partitions into the aqueous rather than the solid phase. Processes favoring the partitioning of As into the aqueous phase, potentially leading to hazardous concentrations, vary extensively but can broadly be grouped into four categories: (1) ion displacement, (2) desorption (or limited sorption) at pH values >8.5,
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(3) reduction of arsenate to arsenite, and (4) reductive dissolution of Fe and Mn (hydr)oxides (Cullen and Reimer, 1989; Smedley and Kinniburgh, 2002; Smith et al., 1998). Although various processes may liberate arsenic from solids, a transition from aerobic to anaerobic conditions, and commensurate arsenic and iron/manganese reduction, appears to be a dominant global means by which high concentrations of dissolved arsenic are generated. Dissolved concentrations, and the resulting mobility, of arsenic within soils and sediments are the combined result of biogeochemical processes linked to hydrologic factors—unifying forces for the fate and transport of elements in general. Within the subsequent sections of this chapter, we explore and describe the biogeochemical processes controlling arsenic fate and describe current conditions within South and Southeast Asia.
2. Arsenic Aqueous Chemistry Two oxidation states of arsenic, As(V) and As(III), predominate in surface and near-surface environments. In solution, arsenic exists primarily as oxyanions; arsenate [As(V) as H3AsO4] has pKa’s of 2.2, 6.9, and 11.5 while arsenite [As(III) as H3AsO3] has pKa’s of 9.2, 12.1, and 13.4 (Goldberg and Johnston, 2001; Smith et al., 1998). Thus, at circumneutral pH, H2AsO4, HAsO42, and H3AsO3 species dominate. Plant and microbial activity may methylate As(V) or As(III), forming, for example, dimethylarsenic acid (DMAA) and monomethylarsonous acid (MMAA) (Cullen and Reimer, 1989). However, methylated species are usually not abundant in aqueous solutions compared to inorganic forms of arsenic (Smedley and Kinniburgh, 2002; Smith et al., 1998). Thio- (Helz et al., 1995; Rochette et al., 2000; Wilkin et al., 2003) and carbonato- (Kim et al., 2000; Lee and Nriagu, 2003) complexes of arsenic also exist within natural waters; thiolated forms of arsenic may, in fact, represent an important reactive component within sulfidic environments (Wilkin et al., 2003).
3. Arsenic Surface and Solid Phases Partitioning of arsenic onto soil solids is foremost dependent on its oxidation state. In general, As(V) binds extensively and strongly to most mineral constituents of soils and sediments, while As(III) retention is more dependent on specific soil chemical conditions, particularly pH and mineralogy (Table 1). As a consequence of arsenate’s strong retention, arsenic tends to impose a limited impact on environmental quality in aerobic soils except under extreme pH conditions (pH > 8.5). Surface complexes of arsenate on iron and aluminum oxides, examined using both infrared
140 Table 1
Retention maxima for arsenic on various solids common to soils and sediments derived from adsorption isotherms at fixed pH
Adsorbent
Al oxides Gibbsite Amorphous Al hydroxide
Activated alumina Bauxite Aluminosilicates Montmorillonite Kaolinite Fe (hydr)oxides Hydrous ferric oxide Goethite Magnetite
As(V) (mmol kg 1)
pH
As(III) (mmol kg 1)
pH
– – – – – – –
References
Approximate Hingston et al. (1971)
35 4 – 15 9 – 1500 4 – 600 9 – 1600 5 – 1200 7 – 500 9 – Twofold higher for As(V) than As(III) 67 6–7 14 52 6–7 16
6.5–8.5 6.5–8.5
8 7
5 5
3 1
5 5
Anderson et al. (1976) – – Gosh and Yuan (1987) Gosh and Yuan (1987) Gosh and Yuan (1987) Using landfill leachate Frost and Griffin (1977) Frost and Griffin (1977)
3514 173
4 4
2675 173 332
8 8 8
Dixit and Hering (2003) Dixit and Hering (2003) Dixit and Hering (2003)
Hingston et al. (1971)
Two-line ferrihydrite
a
Two-line ferrihydrite on quartz sand Others Birnessite (d-MnO2) Pyrolusite Cryptomelane Calcite (CaCO3)
2000 1500 483
4.6 9.2 7.1
100 10 25 NDa
6.5 6.5
Activated carbon Humic acids
10 90–110
3–4 5.5
Not detected.
6000 6000 1206
4.6 9.2 7.1
Raven et al. (1998) Herbel and Fendorf (2006)
Lenoble et al. (2004) Thanabalsingam and Pickering (1986b) ND
5.5
Oscarson et al. (1983) Goldberg and Glaubig (1988) Gupta and Chen (1978) Thanabalsingam and Pickering (1986a)
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(Lumsdon et al., 1984; Sun and Doner, 1996) and extended X-ray absorption fine structure (EXAFS) spectroscopy (Arai et al., 2001; Fendorf et al., 1997; Manceau, 1995; Sherman and Randall, 2003; Waychunas et al., 1993), are dominated by bidentate, binuclear (double-corner sharing) moieties. EXAFS spectroscopy is nearly blind to outer-sphere complexes when inner-sphere moieties are present, but the results obtained from this technique are consistent with infrared studies of phosphate on iron (hydr)oxides (Arai and Sparks, 2001; Parfitt et al., 1975)—a factor supporting the analogous strong retention of phosphate. However, recent X-ray scatter studies (Catalano et al., 2008) illustrate that although arsenate is strongly retained by Fe (hydr)oxides, a portion of the anion is retained as an outer-sphere complex on both hematite and corundum surfaces. Arsenic desorption from ferrihydrite, goethite, and hematite under advective flow is consistent with a portion of outer-sphere complexes that are more labile (more rapid desorption) than the large fraction of inner-sphere complexes (Tufano and Fendorf, 2008). Aluminum hydroxides and aluminosilicate clay minerals may also retain appreciable concentrations of arsenate, and they exhibit a strong preference for arsenate relative to arsenite (Tables 1 and 2) (Manning and Goldberg, 1997a,b; Smith et al., 1998; Xu et al., 1988). Similarly, Mn oxides may impart a strong influence on arsenic binding. Reaction of arsenite solutions with Mn oxides such as birnessite results in extensive and rapid uptake (Oscarson et al., 1981). However, arsenic is retained as arsenate surface complexes (Manning et al., 2002) owing to arsenic oxidation by Mn (III/IV) (Driehaus et al., 1995; Manning et al., 2002; Oscarson et al., 1981). Arsenic may also bind to organic matter in soils and sediments (Grafe et al., 2001, 2002; Ko et al., 2004; Redman et al., 2002; Thanabalsingam and Pickering, 1986a), with As(V) and As(III) having maximum adsorption on humic acids at pH 5.5 and 8, respectively (Thanabalsingam and Pickering, 1986a). Arsenic(V) adsorbs onto solid-phase humic acids more extensively than As(III), with amine (NH2) groups suspected as the primary functional group responsible for arsenic retention (Thanabalsingam and Pickering, 1986a). Arsenic adsorption by humic substances is also enhanced by cation addition, particularly Fe, Al, and Mn, whereby the cations act as bridging complexes for arsenate on humic acids (Lin et al., 2004). Nevertheless, organic matter tends to be poorly correlated with total As in comparison to Fe, Al, or P (Chen et al., 2002), suggesting that its contribution to arsenic retention in soils and sediments is often limited. In contrast to arsenate, arsenite exhibits a limited affinity for most soil minerals with the exception of iron (hydr)oxides, for which it exhibits a high degree of retention (see Table 1). Ferric (hydr)oxides and magnetite, in fact, adsorb arsenite more extensively than arsenate at all but acidic conditions (Dixit and Hering, 2003; Raven et al., 1998), as illustrated for hydrous ferric hydroxide (Fig. 1). Similar to arsenate, arsenite also forms a bidentate,
Table 2 Adsorption envelopes for As(V) and As(III) on various soil and sedimentary solids
Adsorbent
As(V)aqa; As(V)adsb
Al oxides Amorphous Al hydroxide 1600; 1700 (4.5) 133; 900 (4.5) 20; 20 (2–10) Activated alumina 53.4; 26.5 (3–7) Bauxite 53.4; 26.5 (3–7) Aluminosilicates Montmorillonite 20; 0.41 (5, 12.5) 20; 0.35 (5) Kaolinite 20; 0.5 (5) Illite 20; 0.5 (4–6) Fe (hydr)oxides Hydrous ferric oxide 20; 40 (2–9) 100; 2100 (4)
pH c maximum
4–7 4–7 2–10 3–7 3–7
As(III)aq a; As(III)adsb
pH c maximum
References
Anderson et al. (1976) 20; 16 (8.5) 26; 11 (8.2) 16; 9 (8.5)
7–9.5 3–10 3–10
Goldberg (2002) Gupta and Chen (1978) Gupta and Chen (1978) Goldberg and Glaubig (1988) Goldberg (2002) Goldberg (2002) Goldberg (2002)
5–7, >11 5–7 3–9 3–7
20; 0.4 (3) 20; 0.25 (8–10) 20; 0.22 (8–9)
3–4 7–11 7–10
2–10 <7
20; 40 (2–11)
2–11
Goldberg (2002) Dixit and Hering (2003)
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(continued)
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Table 2 (continued) Adsorbent
Hydrous ferric oxide Goethite Magnetite Two-line ferrihydrite Others Hydrous manganese oxide Calcite (CaCO3) Activated carbon Humic acids a b c
As(V)aqa; As(V)adsb
pH c maximum
As(III)aq a; As(III)adsb
pHc maximum
References
100; 140 (4)
<8
100; 1500 (8–9) 100; 120 (8–9) 100; 140 (9)
5–9.5 4–10 8–9.5
Dixit and Hering (2003) Dixit and Hering (2003) Dixit and Hering (2003)
10; 16 (3)
2.5–5
20; 2 (11)
9–13
19.4; 5.3 (4) 5–100; 80–140 (6)
3–5 5–7
Initial aqueous concentration (mM). Maximum adsorption (mmol kg 1) at indicated pH. pH range over which maximum adsorption occurred.
20; 110 (8)
7–9
Thanabalsingam and Pickering (1986b) Goldberg and Glaubig (1988) Gupta and Chen (1978) Thanabalsingam and Pickering (1986a)
145
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100
Adsorbed As (%)
As(V)
As(III)
0 4
6
8
10
pH
Figure 1 Magnitude and pH-dependency of As(V) (arsenate) and As(III) (arsenite) adsorption on hydrous ferric oxide; reaction conditions were 50 mM arsenic reacted with 0.03 g L 1 hydrous ferric oxide (data from Dixit and Hering, 2003).
binuclear complex, albeit with a slightly longer As–Fe distance, on goethite (a-FeOOH) (Manning et al., 1998; Ona-Nguema et al., 2005) and lepidocrocite (g-FeOOH) (Ona-Nguema et al., 2005); on ferrihydrite and hematite, arsenite again forms bidentate, binuclear complexes but also is present in bidentate, mononuclear and, to a small degree, monodentate coordination on the mineral surface (Ona-Nguema et al., 2005). Despite the multitude of potential surface complexes on ferric (hydr)oxides, the observation of inner-sphere arsenite moieties appears to account for its extensive retention on such phases (Dixit and Hering, 2003). However, surface complexes of arsenite, although extensive, are far more labile than for its oxidized counterpart, arsenate (Tufano et al., 2008). Both As(V) and As(III) may also precipitate within soils and sediments, but the constituents inducing precipitation vary dramatically. Arsenate, similar to phosphate, tends to precipitate with hard, multivalent cations such as aluminum and ferric-iron under acidic conditions and calcium and magnesium under alkaline conditions; arsenate may also replace SO42 or, in particular, PO43 in minerals due to similar size and charge characteristics (Smedley and Kinniburgh, 2002). Various heavy metals (e.g., Mn, Cd, Pb) and alkali earth metals (Ca, Mg, Ba) also have the capacity to precipitate with arsenate (see, e.g., Sadiq, 1997), albeit that these phases tend to be relatively soluble and thus have a limited impact on dissolved concentrations of arsenic—particularly in reducing environments (Rochette et al., 1998). Arsenite, in contrast to arsenate, undergoes ligand displacement and incorporation into sulfidic solids. In fact, the solubility of As(III) is often controlled by sulfide precipitates, particularly in regions where sulfidogenesis occurs, limiting As(III) concentrations in highly reducing environments (Moore et al., 1988). Under hydrothermal conditions with high Fe2þ,
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sulfides may coprecipitate with Fe and As as arsenopyrite (FeAsS) or arsenicrich (arsenian) pyrite [Fe(S,As)2]; at lower levels of ferrous iron, orpiment (As2S3) or realgar (AsS) may form. Dissimilatory SO42 and As(V) reduction may similarly induce precipitation of orpiment and realgar under ambient surface conditions (Ahmann et al., 1994; Newman et al., 1997a). Furthermore, adsorption of As(III) onto metal sulfides is often followed by incorporation of As into mineral structures (Bostick and Fendorf, 2003; Bostick et al., 2003).
4. Desorption of Arsenic in Soils and Sediments In surface and subsurface environments, changes in water chemistry often result in release of As from solid phases through various desorption pathways. Introduction of waters containing high concentrations of competing ligands such as phosphate or waters that lead to dramatic shifts in pH can displace arsenic. The most destructive alteration, from an environmental quality perspective, results from incursion of dissolved, labile organic carbon that stimulates microbial activity leading to changes in arsenic speciation and/or enhanced dissolution of Fe(III) and Mn(III/IV) minerals hosting arsenic. Transition from aerobic to anaerobic conditions induced by organic carbon and limited oxygenation, in fact, appears to be the dominant condition leading to high levels of dissolved arsenic. The converse, exposure of reduced soils/sediments to aerated water, leads to oxidative dissolution of arsenic-bearing sulfides, such as arsenopyrite, realgar, and orpiment. However, oxygenation generally leads to the production of arsenate, having a high affinity for various minerals, inclusive of ferric (hydr)oxides. Additionally, Fe(II) oxidation would occur concurrently and lead to an arsenic-bearing iron (hydr)oxide. As a consequence, arsenic undergoes secondary partitioning back onto the solid phase (i.e., aeration leads to a shift in solids hosting arsenic but not to a partitioning of arsenic into the aqueous phase). Competitive ion displacement can represent an important means by which arsenic is released to the aqueous phase and subject to transport. Displacement and mobilization of As by phosphates is of particular concern (Dixit and Hering, 2003; Manning and Goldberg, 1996; Reynolds et al., 1999; Violante and Pigna, 2002), and regions where fertilizer or pesticide runoff and leaching occurs are specifically at risk for this mobilization pathway ( Jain and Loeppert, 2000; Peryea and Kammerack, 1997). Carbonate can also compete with arsenic for adsorption sites on mineral surfaces (Appelo et al., 2002; Van Geen et al., 1994; Villalobos and Leckie, 2001), but the extent of arsenate displacement may not be appreciable. Natural organic matter may also compete with As and inhibit arsenic adsorption onto iron (hydr)oxides due to competitive adsorption reactions (Redman
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et al., 2002; Xu et al., 1991). Other anions, such as Cl, SO42, and NO3, have minimal impact on As desorption, yet these ions can contribute to ionic strength and salinization effects on As retention in soils and sediments (Gupta and Chen, 1978; Smith et al., 1998) that are potentially important in the desorption of arsenite.
4.1. Comparative desorption of arsenite to arsenate The conception that arsenite is a more mobile species than arsenate has been displaced during the past decade on the basis of arsenic retention to various ferric (hydr)oxides (see, e.g., Fig. 1). At circumneutral pH values and higher, arsenite generally adsorbs to a greater extent on ferric (hydr)oxides than arsenate (Dixit and Hering, 2003; Manning et al., 1998; Raven et al., 1998), and forms inner-sphere complexes comparable to arsenate (Manning et al., 1998; Ona-Nguema et al., 2005). However, unlike arsenate, which tends to have a high affinity for numerous solids, inclusive of metal oxides and aluminosilicates, appreciable binding of arsenite appears relatively specific to ferric (hydr)oxides (Manning and Goldberg, 1997a). Thus, the expectation arises that arsenic mobilization will be predicated on iron reduction within anaerobic environments—not on arsenic reduction. Recognizing that arsenite forms inner-sphere complexes helps to rectify its extensive binding on iron (hydr)oxides. Caution, however, should be used in drawing conclusions regarding binding strength from the magnitude of retention when considering solids with multiple operational binding mechanisms. In addition to various inner-sphere complexes (which include monodentate, bidentate–binuclear, and bidentate–mononuclear complexes), outer-sphere complexes arising from electrostatic interactions and hydrogen-bonding can result. Catalano et al. (2008) illustrate that even for arsenate, a portion of the adsorbed phase on hematite and corundum resides as an outer-sphere complexes. Given the protonation of arsenite species, H-bonding should be more prevalent for As(III) and thus give rise to greater desorption, a trend born out in advective column systems (Tufano and Fendorf, 2008). Despite the greater extent of arsenite retention on ferric (hydr)oxides relative to arsenate, greater quantities and resulting aqueous concentrations occur for arsenite desorption (Fig. 2). In particular, higher surface coverage (expressed as proportion of the adsorption maximum) enhances the difference between desorption from arsenite-loaded as compared to arsenateloaded columns—with much higher proportion of arsenic being desorbed as arsenite. At surface coverages near 50%, arsenite desorption results in initial aqueous concentrations exceeding 500 mM while for arsenate concentrations are below 200 mM (Fig. 2). For both arsenite and arsenate, desorption decreases exponentially with time (represented by pore-volumes eluted through the column at a flow rate of ca. 3 pore-volumes per day);
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by 20 pore-volumes, both species of arsenic are below 50 mM aqueous concentration and continuing to diminish. The rapid decline in desorption is indicative of a fixed surface population residing in a highly labile state, which rapidly responds to disequilibrium. The difference in arsenite/ arsenate desorption from ferrihydrite is also striking (Herbel and Fendorf, 2006). Rather than exhibiting a rapid decay in the concentration desorbing from ferrihydrite, aqueous concentrations remain greater than 70 mM even after 20 pore-volumes (under similar condition to those used for
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the goethite experiments described above). Furthermore, the cumulative loss of As(III) from ferrihydrites and columns (27.4% of the initial loading) was more than twice that of As(V) (10.8%) (Herbel and Fendorf, 2006). Arsenate desorption from iron (hydr)oxides is measurable but limited, while arsenite, in comparison, undergoes extensive release under hydrodynamic conditions. The extensive yet apparently weaker adsorption of arsenite can again be rectified simply by considering the multitude of potential surface complexes resulting on mineral surfaces. Arsenite, in particular, is thought to bind on iron (hydr)oxides through multiple inner-sphere complexes (Ona-Nguema et al., 2005), having a range of binding strengths, in combination with outer-sphere and H-bonded moieties, giving rise to extensive but weak complexes. As a consequence, an appreciable fraction of arsenite appears to reside in weakly adsorbed complexes that rapidly desorb in response to decreases in aqueous concentrations. The observation that arsenite forms more labile complexes on ferric (hydr)oxides challenges the presumption that iron reduction is the primary factor liberating arsenic to the aqueous phase. Arsenic reduction, in fact, may have a more pronounced role in destabilizing arsenic and allowing its transport within soils. Although iron reduction has been suggested as a means for arsenic desorption, and in fact would lead to the depletion of a prominent sorbent, arsenic reduction may be more influential (a topic covered more extensively in the following section). The expression of the arrA gene, responsible for respiratory arsenate reduction (Saltikov and Newman, 2003), may be useful as a proxy for arsenic migration (Malasarn et al., 2004), although the actual transport of arsenic will depend on a host of reactions far more extensive than just Fe(III) or As(V) reduction.
5. Biogeochemical Processes 5.1. Microbial arsenate reduction Because of arsenic’s inherent toxicity, many organisms have evolved mechanisms to convert As to forms that are readily removed from the cell (Oremland and Stolz, 2003). Certain higher eukaryotic organisms (e.g., fungi) along with specific archaea and aerobic eubacteria can convert As(V) to As(III), which is then methylated to form monomethyl- (MMA), dimethyl- (DMA), or trimethylarsine (TMA) (Cullen and Reimer, 1989). The most common means of arsenic detoxification involves the ArsC enzyme system; As(V) is brought into the cytoplasm, reduction transpires, and then As(III) is pumped with a specific transporter across the cell membrane into the external milieu. Unlike respiratory reduction of As (V), the detoxification pathway requires energy. Even dissimilatory As(V)
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reducing microorganisms may have the ArsC enzyme system, as recently shown for Shewanella strain ANA-3 (Saltikov et al., 2003). Microbial As(V) detoxification mechanisms may affect the overall As speciation in contaminated environments; however, dissimilatory Fe(III) and As(V) reduction processes are more likely to mobilize arsenic within reducing environments ( Jones et al., 2000; Langner and Inskeep, 2000). In arsenic-resistant bacteria, As(V) enters the cell via nonspecific outer membrane porins or through phosphate specific transporters (Oremland and Stolz, 2003; Oremland et al., 2002; Rosen, 2002). It can then undergo respiratory reduction in the periplasm or be transported into the cytoplasm for detoxification. The As(V)-detoxifying ArsC enzymes typically reside in the cytoplasm, and As(III) formed in the process is exported across the cell membrane using the ArsA and ArsB enzymes (Mukhopadhyay et al., 2002; Oremland and Stolz, 2003). In contrast, As(V)-reductases (ArrA, ArrB, etc.) reside interior to the outer membrane—within the periplasm for Gram() bacteria (Afkar et al., 2003; Oremland and Stolz, 2003; Saltikov and Newman, 2003). Over the last decade, As(V)-respiring bacteria and archaea have been isolated from a diversity of natural environments, including freshwater sediments, alkaline and saline lakes, and hot springs (Huber et al., 2000; Oremland and Stolz, 2003; Oremland et al., 2002; Stolz and Oremland, 1999). Dissimilatory As(V) reduction transpires in environments ranging from estuarine sediments to gastrointestinal tracts of animals with the addition of arsenate and electron donor (Dowdle et al., 1996; Herbel et al., 2002), suggesting that As(V)-respiring microorganisms are widespread. Additionally, As-respiring bacteria are capable of reducing As(V) within solids such as scorodite (Newman et al., 1997b), with dissolution and subsequent uptake of As appearing to precede reduction on the basis of the reductases residing within, rather than outside, the outer membrane (Saltikov and Newman, 2003). These prokaryotic organisms can link the reduction of soluble, adsorbed, or mineralized As(V) with the oxidation of a wide variety of electron donors, including lactate, acetate, pyruvate, glucose, and H2, in order to gain energy for cell growth. To date, no obligate As(V)-respiring microbes have been identified; all of the As(V)-reducing organisms can respire on other electron acceptors inclusive of NO3, Fe (III), and SO42. The ability to utilize a variety of electron acceptors and donors implies that the As(V)-respiring prokaryotes are opportunists, and that they can thrive on other available electron acceptors in environments when As(V) concentrations become depleted.
5.2. Arsenic desorption upon anaerobiosis The greatest likelihood for As release in soils and sediments typically occurs upon a transition from oxidizing to reducing conditions. Under saturated conditions, the rapid consumption of O2 by aerobic microbes combined
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with the low solubility of O2 induces anaerobic bacteria to utilize alternative electron acceptors. Arsenic may be displaced either through reduction of arsenate to arsenite or through mineralogical transformations (inclusive of dissolution) of the soil matrix. Many bacteria and archaea can respire on Mn(III/IV)- and Fe(III)oxides leading to their dissolution with the potential for concomitant displacement of arsenic into the aqueous phase (Cummings et al., 1999). In fact, within most soils and sediments, total As levels correlate with Fe content rather than Al or clay content (Smedley and Kinniburgh, 2002), and thus reductive dissolution/transformation of Fe(III) phases should have a major impact on arsenic. Respiratory reduction of Fe in sediments generally occurs in zones where O2, NO 3 , and Mn(IV) (all being oxidants of Fe(II) and alternative electron acceptors) are diminished (Lovley, 2000). The most readily bioreducible Fe(III) (hydr)oxides are the high surface area, least thermodynamically stable phases such as ferrihydrite (Lovley, 1991; Roden and Zachara, 1996; Schwertmann and Taylor, 1989). Reduction of Fe(III) within such phases, however, does not lead to simple congruent dissolution but rather initiates production of a convoluted assortment of secondary phases (Fig. 3). Ferrous iron produced during Fe(III) reduction induces a transformation of ferrihydrite (or lepidocrocite) to more stable minerals such as goethite (a-FeOOH) and magnetite (Fe3O4) (Hansel et al., 2003; Zachara et al., 2002). Hansel et al. (2003), for example, illustrate that dissimilatory respiration on Fe(III) within ferrihydrite results in a cascade of geochemical reactions that lead to a series of secondary solids induced by back-reaction with Fe(II) (Fig. 3). Ferrihydrite (when supported by a quartz sand substrate) undergoes a mineralogical shift to goethite at Fe (II) loadings less than 1 mmol g 1 (resulting from 0.3 mM aqueous Fe(II) in their experiments) or to magnetite at higher Fe(II) loadings. Despite having a nearly equal affinity for As (Dixit and Hering, 2003), transformation of ferrihydrite to more crystalline phases (goethite, hematite, or magnetite) decreases the available surface area (Appelo et al., 2002) and thus diminishes, one would think, their capacity to retain arsenic. Congruent dissolution of Fe(III) (hydr)oxides would be expected to release arsenic until the surface site concentration is depleted below the level of adsorbed arsenic (in combination with other high-affinity anions such as phosphate). Secondary mineralization of iron, however, convolutes this view, leading to the potential for arsenic to be incorporated on or in the newly forming solids. Elution trends of arsenic from ferrihydrite under ironreducing conditions are, in fact, inconsistent with arsenic desorption upon reductively induced mineralogical transition (Herbel and Fendorf, 2006; Kocar et al., 2006; Tufano et al., 2008). The impact of ferrihydrite reductive transformation is illustrated (Fig. 4) for an As(III) loaded ferrihydrite-coated sand under advective flow in the absence (abiotic) and presence of Shewanella putrefaciens, strain CN32 (Kocar et al., 2006). During the period of
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greatest As release, which occurs at the onset of flow, a rapid mineralogical transition occurs within the inoculated column as (principally) magnetite is generated at the expense of ferrihydrite. The initial pulse of As, however,
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also results in abiotic columns lacking biological activity or Fe(II). Moreover, the extent of desorption is greatly suppressed upon the production of Fe(II) within biologically active columns, a factor supported by Fe(II) addition to abiotic systems (Herbel and Fendorf, 2006; Kocar et al., 2008). Formation of a ferrous–arsenite precipitate (Thoral et al., 2005) may also limit As(III) concentrations, but much higher (millimolar) levels of both arsenite and Fe(II) concentration are required for this phase at pH <7.5. Within natural environments, anaerobic conditions are often going to lead to concomitant arsenic and iron reduction. Previously, we examined the impact of a model freshwater anaerobic bacterium, Sulfurosprillum barnesii strain SES-3, that reduces both Fe(III) and As(V) through respiratory processes (Oremland et al., 1994; Zobrist et al., 2000), on the desorption of arsenic (Herbel and Fendorf, 2005, 2006). Arsenic release from As(V)loaded ferrihydrite is most pronounced during the initial influx of waters containing labile carbon but quickly decreases once Fe(II) levels increase. Again more arsenic (as As(V) and As(III)) is released under advective flow in abiotic columns from ferrihydrite-sands, and over longer periods of time, than in systems containing bacteria respiring on As(V) and Fe(III) (Herbel and Fendorf, 2006). More recently, we have examined reductive desorption of arsenic from iron (hydr)oxide surfaces using a single bacterial species, Shewanella sp. ANA3, and knockout mutants designed to have restricted enzymatic capacity (Tufano et al., 2008); the mutant strains have the ability to reduce (a) only arsenic or (b) only iron (Fig. 5). The greatest amount of
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arsenic release to solution results from the mutant having the capacity to only reduce As (and not Fe). The least amount of arsenic desorption resulted upon iron reduction alone, where As(V) was retained on Fe(II)-induced restructuring solids. These series of recent studies clearly reveal that As(V) reduction to As(III) is a strong contributing factor to arsenic release to porewater in soils/sediments under anaerobic conditions. Iron reduction is more convoluted. If ferrihydrite (or, by comparison, lepidocrocite) is present, Fe(II)-induced transformation to goethite (an Oswald ripening step) or magnetite will lead to As sequestration. By contrast, if the soil/sediment has limited short-range order Fe-phases, then Fe dissolution without precipitation will prevail and arsenic desorption will be promoted. In fact, even for soils having substantial amounts of ferrihydrite, once the transformation process has ceased, continued iron reduction will result in dissolution and thus arsenic release (Tufano and Fendorf, 2008).
6. Processes Controlling Arsenic Concentrations in South(east) Asia Millions of people in South and Southeast Asia are drinking groundwater with unsafe concentrations of arsenic (Berg et al., 2001, 2007; Smith et al., 2000; Yu et al., 2003)—present estimates are more than 100 million people are being exposed to water having arsenic concentrations greater than 10 mg L 1, the maximum concentration recommended by the World Health Organization. Arsenic originates naturally from Himalayan sediments, is transported down the major river systems, and deposited in lowlying regions (sedimentary basins and deltas). The question then becomes, how is the arsenic being released from the solids into the water? There have been various mechanisms postulated for the transfer of arsenic from the solid to the aqueous phase that generally follow those described in the preceding sections. Oxidative weathering of As-pyrite and As-biotite have been mentioned as a means by which arsenic may enter the aqueous phase, but oxidation of either phase, although destroying the host solid, would lead to ferric (hydr)oxides which have a high affinity for arsenic. Thus, while arsenic would be released from the original solid, the ultimate fate would be a change in partitioning from one solid to another. A similarly discounted release process is from displacement by a competing ligand such as phosphate, carbonate, or silicate. Groundwater profiles show no correlation between dissolved As and competing anion levels (Harvey et al., 2002). (It is possible that such anions, and in particular phosphate, may compete with As, their largest role may be under Fe-reduction conditions where surface sites are diminishing.) Likewise, the pH of the surface and groundwaters
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trends toward neutrality (Harvey et al., 2002; Polizzotto et al., 2008) and are thus not in the range expected for prominent release. The culprit for arsenic release to the aqueous phase is As(V) and Fe(III) reduction. Aerobic or oxidized (particularly with respect to Fe) aquifers are nearly universally low in arsenic within the region. The prominence of reduced conditions where high arsenic is noted lead to the conclusion that microbial reduction of As(V) and Fe(III) induced the desorption of As from the solids into the aqueous phase (McArthur et al., 2004; Nickson et al., 1998; Smedley and Kinniburgh, 2002; van Geen et al., 2003), a process that now is supported by measured indicators of microbial metabolism and isolation and Fe- and As-reducing organisms from the sediments (see, e.g., Harvey et al., 2002; Islam et al., 2004; Polizzotto et al., 2008). The overall reduction reaction liberating As is summarized as þ 2þ 4FeOOHðH3 AsO3 Þx þ C3 H5 CO þ CH3 COO 3 þ 7H ) 4Fe þHCO3 þ 6H2 O þ xH3 AsO3
ð1Þ where As is bound to Fe-(hydr)oxide (here written as goethite, which is replaceable with other Fe (hydr)oxides), and where x is the stoichiometric coefficient of As (typically very low for South and Southeast Asian sediments, 0.0002). Thermodynamic calculations for Reaction 1 illustrate that As(V) reduction is more favorable than Fe(III) (or sulfate) reduction over a wide range of field conditions relevant for the Asian aquifers, and it is independent of the type of iron (hydr)oxide given typical Fe(II) concentrations (Kocar and Fendorf, 2009). For example, within the Mekong Delta, goethite, hematite, and within the first 50 cm from the ground surface, ferrihydrite, exist as reducible, As-bearing Fe(III) (hydr)oxides. Throughout the sediment profile, the thermodynamic favorability of As(V) reduction is much greater than Fe(III) (hydr)oxide reduction at measured Feaq2þ concentrations. Although As reduction yields the highest energy across a range of field conditions, the reduction of ferrihydrite is also clearly thermodynamically favorable for microbial respiration under the conditions reported in the Mekong Delta (Kocar and Fendorf, 2009). Reductive release of arsenic to pore-water thus sits at the origin of groundwater contamination in South and Southeast Asia. However, the location within the sediment profile, the time period, and the influence of hydrology on arsenic release and distribution in the aquifer remain unresolved, limiting our ability to predict arsenic concentrations both temporally and spatially (Harvey et al., 2002; McArthur et al., 2004; Polizzotto et al., 2005, 2008; van Geen et al., 2003). Reductively induced desorption rates of arsenic will be greatest where the highest concentration of labile organic matter and arsenic reside under anaerobic conditions. Within the Mekong Delta of Cambodia, where we have investigated coupled hydrologic and
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biogeochemical processes impacting arsenic (Benner et al., 2008; Kocar et al., 2008; Polizzotto et al., 2008), this clearly resides at the point of the transition to anaerobic conditions—typically a few meters below the ground surface. Reductive release of arsenic thus commences at the water table and with continued sediment burial in the delta, arsenic release will continue until it is either depleted from the solids or reduction becomes limited (e.g., due to labile organic carbon depletion). Within the Mekong Delta, we note transitions to anaerobic conditions and ensuing iron and arsenic reduction at or near the water table—where we also observe the steepest gradients in arsenic release to the pore-water (Kocar et al., 2008), as similarly noted for an arsenic-contaminated Red River Delta site (Postma et al., 2007). Observed near-surface sources of arsenic do not preclude, nor necessarily conflict with, continued arsenic release at depth through native or introduced carbon sources—or through exchange reactions (Harvey et al., 2002; Lear et al., 2007; McArthur et al., 2001; Rowland et al., 2007). Once released from the solids, arsenic will either undergo transport with advecting waters or secondary geochemical reaction (e.g., adsorption). We must recognize that the geochemical profile of arsenic in any aquifer, but specifically those of South and Southeast Asia, is the result of coupled biogeochemistry and hydrology—importantly, an observed chemical profile does not necessarily reflect the distribution of biogeochemical processes but rather those that may have occurred upstream. Within the sedimentary basins of Asia, transporting water will flow nominally vertically through the surface clay layers (that persists from a few up to 20 m) and then horizontally through the sandier, aquifer material below. Arsenic released via reductive dissolution within the upper clay layer(s) will transport downward into the aquifer and then horizontally toward a point of discharge, which are usually either a river or, in the case of Bangladesh, an extraction well (see Benner et al., 2008; Harvey et al., 2006). Along the transport lines, arsenic will be subject to adsorption/desorption reactions with aquifer solids. When arsenic is being released from reductive dissolution reaction upstream, its transport will be retarded via adsorption reactions with downstream aquifer solids; the extent of retardation will depend primarily on the solid-phase constituents but also on the aqueous chemistry (particularly anion composition and concentration, along with pH). However, once the reductive release process is exhausted, the downstream aquifer solids will switch from being a sink for arsenic to a source. In other words, arsenic that has been loaded onto aquifer solids with high arsenic concentration waters will then undergo desorption when water with lower arsenic concentrations migrate through, giving rise to an extended temporal (and spatial) ‘‘tailing’’ in arsenic concentrations even after reduction processes have ceased. The ultimate distribution of arsenic in aquifers of South and Southeast Asia are the result of these coupled (bio)geochemical and hydrologic process, which vary depending on the sedimentology of a specific area and the local human perturbations to the aquifer system.
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7. Summary and Conclusions Arsenic retention on soil solids is critical for regulating the dissolved concentrations of this hazardous element, thus helping to limit its exposure to living organisms and migration within the environment. Strong partitioning of arsenic on soil solids is most prevalently disrupted by the onset of anaerobic conditions (anaerobiosis), leading to increased aqueous concentrations of arsenic. Variations in arsenic chemistry, compounded by biogeochemical transformations of the soil matrix, upon the onset of anaerobic conditions transpire to produce a convolution of reactions that have varying impacts on arsenic retention. Arsenic desorption upon anaerobiosis has been ascribed to both the reduction of arsenic, from arsenate to arsenite, and iron(III)—the latter leading to the reductive dissolution of ferric (hydr)oxides that act as principal sinks of arsenic (Delemos et al., 2006; Islam et al., 2004; Jones et al., 2000; McCreadie et al., 2000; McGeehan and Naylor, 1992; Zobrist et al., 2000). Recent advances in our knowledge of arsenic reduction mechanisms, binding affinities, and (bio)reductive transformation of Fe(III) (hydr)oxides lead to a more complex view of arsenic dynamics under reducing conditions. Reduction of As(V) to As(III) leads to a large alteration in the types of solids retaining arsenic, with a large specificity for Fe(III) (hydr)oxides relative to other soil solids (Manning and Goldberg, 1997a); in comparison to arsenate, the adsorption capacity of arsenite is small on Al (hydr)oxides and aluminosilicates (see Table 1). The extensive binding of arsenite on Fe (hydr) oxides is, in part, a result of labile complexes in combination with stronger inner-sphere complexes, contrasting the binding of arsenate which is dominantly via strong inner-sphere complexation. As a consequence, As(III) desorption is rapid in response to a decrease in aqueous concentrations (i.e., a shift from equilibrium with respect to the surface complexation reactions). Iron reduction will also take place under anaerobic conditions, and thus we need to consider its implications on arsenic partitioning and transport. Iron reduction will lead, in part, to the dissolution of the mineral phase and thus diminish the number of adsorption sites. However, Fe (hydro)oxides may undergo dissolution alone or transformation (dissolution–reprecipitation) to secondary phases that can serve as a host for arsenic. For soils with labile iron oxides (typically ferrihydrite, but also possibly lepidocrocite or proported nano-goethite), stimulation of iron reduction would lead to a sequence of iron transformations and arsenic incorporation and adsorption. Summarizing the fate of arsenic under anaerobic conditions we should note two important points: (1) dissolved concentrations and migration of arsenic are typically promoted under reducing conditions, but (2) the extent
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of iron (hydr)oxide transformation to secondary phases will be the primary variable influencing the extent of release. Arsenate reduction may be the largest single factor promoting arsenic release but will be invariant under reducing conditions (it will always lead to arsenic desorption, unless sulfide is produced). Iron reduction, by contrast, may have opposing (and possibly nonlinear) impacts on arsenic release: dissolution will lead to As release while dissolution–reprecipitation will lead to sequestration. Given common impurities of iron (hydr)oxides, that may include organic matter, silica, phosphate, or other ions, it is likely that in most soils and sediments, it is less likely that reprecipitation will transpire (even for ferrihydrite) and thus iron reduction should lead to enhanced desorption. So what does this synopsis tell us about the expected fate of arsenic under anaerobic conditions? First, owing to the weaker surface complexes of As (V) versus As(III), arsenic migration will be greater under anaerobic than aerobic conditions (with the exception of environments having high dissolved concentrations of sulfide, which can lead to sequestration of As). Sedimentary basins of Southeast Asia experiencing high concentrations of As in groundwater, for example, have prolonged periods (months) of anaerobic conditions; arsenic within these environments would therefore be expected to be relatively mobile. However, the extent of arsenic release will be appreciably modified by the fate or Fe. Under conditions where ferrihydrite (or similar unstable iron (hydr)oxide) exists, which is typically in the surface horizons, conditions conducive to its transformation (anaerobic conditions, high concentrations of labile DOC, and warm temperatures), secondary mineralization will help to sequester arsenic. Within aquifer systems of South and Southeast Asia, arsenic cycling between solids of aerobic and anaerobic periods may occur if iron (hydr)oxides are indeed produced. Once the solids are buried below the water table, persistent reducing conditions lead to both As and Fe reduction, and the resulting release of arsenic into pore-water.
ACKNOWLEDGMENTS We are grateful for the valuable discussions and analytical contributions of Shawn Benner, Matt Polizzotto, Guangchao Li, Yoko Masue, and Kate Tufano. This research was supported by the Stanford NSF Environmental Molecular Sciences Institute (NSF-CHE-0431425).
REFERENCES Afkar, E., Lisak, J., Saltikov, C. W., Basu, P., Oremland, R. S., and Stolz, J. F. (2003). The respiratory arsenate reductase from Bacillus selenitireducens strain MLS10. FEMS Microbiol. Lett. 226, 107–112. Ahmann, D., Roberts, L. R., Krumholz, L. R., and Morel, F. M. M. (1994). Microbe grows by reducing arsenic. Nature 371, 750.
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Inorganic and Organic Constituents and Contaminants of Biosolids: Implications for Land Application R. J. Haynes,* G. Murtaza,†,‡ and R. Naidu§ Contents 166 168 169 169 174 175 175 179 181 182 183 185 187 202 207 208 211 227 234 237
1. Introduction 2. Sewage Treatment Processes 3. Composition of Biosolids 3.1. Organic matter 3.2. Inorganic components 4. Nutrient Content and Release 4.1. Nitrogen 4.2. Phosphorus 4.3. Other nutrients 5. Heavy Metal Contaminants 5.1. Total concentrations 5.2. Extractable fractions 5.3. Application to the soil 5.4. Plant response and metal uptake 5.5. Ingestion by animals 6. Organic Contaminants 6.1. Organic compounds present 6.2. Potential transfer to groundwater, plants, and animals 7. Synthesis and Conclusions References
Abstract Large amounts of biosolids are produced as a by-product of municipal wastewater treatment. They are composed of about 50% organic and 50% inorganic material. The organic component is partly decomposed and humified material * {
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School of Land, Crop and Food Sciences/CRC CARE, The University of Queensland, St Lucia, Australia Centre for Environmental Risk Assessment and Remediation, Division of Information Technology, Engineering and the Environment, University of South Australia, Mawson Lakes Campus, South Australia, Australia Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad, Pakistan CRC CARE, Salisbury, South Australia, Australia
Advances in Agronomy, Volume 104 ISSN 0065-2113, DOI: 10.1016/S0065-2113(09)04004-8
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2009 Elsevier Inc. All rights reserved.
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derived from human feces and bacterial biomass while the inorganic component is derived from materials such as soil, sediment, and inorganic residuals (e.g., silica). The major contaminants in biosolids are heavy metals (e.g., Cu, Zn, Cd, Pb, Ni, Cr, and As) plus a range of synthetic organic compounds. Following land application, biosolids-borne metals are typically immobile in soils. They can be toxic to soil microflora, small amounts may leach with soluble organic matter, they can be accumulated in plants and sometimes transferred to grazing animals (mainly by soil ingestion). Regulations and guidelines for biosolids applications are still principally based on total metal loadings and in the future the use of bioavailable metal concentrations in biosolids-treated soils should be considered. The significance, effects, and fate of biosolids-borne organic contaminants in soils are not well understood and require further study. In the majority of cases, neither heavy metal nor organic contaminants are considered a significant hazard to the soil–plant system. Indeed, land applications of biosolids can be highly beneficial to crop production since they supply substantial amounts of N, P, Ca, and Mg and added organic matter can improve soil physical properties and stimulate soil microbial activity. To avoid ground/surface water pollution, application rates should be based on the N need of the crop and potential N mineralization rate of biosolids-N, and the high P loadings need to be managed.
1. Introduction Biosolids are derived from the treatment of wastewater (sewage) that is primarily derived from domestic sources being a combination of human feces, urine, and graywater (from washing, bathing, and meal preparation). Sewage also contains discharges from commercial and industrial enterprises and often some stormwater. As the wastewater is treated, it goes through a series of processes that reduce the concentrations of organic material that were originally present. Primary sludge (principally fecal material) results from settling of solids as they enter the treatment plant. Secondary sludge originates from the conversion of suspended and soluble organic matter in sewage into bacterial biomass. The biomass is removed and combined with the primary sludge to produce material termed sewage sludge. This material then undergoes treatment (usually anaerobic but sometimes aerobic digestion) to reduce the volume and stabilize the solid organic matter component as well as to reduce the presence of disease-causing organisms. The final product is termed biosolids. The safe disposal of biosolids is a major environmental concern throughout the world. Disposal alternatives include dumping at sea, incineration, landfilling, and land application (Epstein, 2003). Land application is generally seen as the most economical and beneficial way to deal with
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biosolids (Shammas and Wang, 2007a). Indeed, about 60% of all biosolids produced in both United States and United Kingdom are land applied (Pepper et al., 2006). Biosolids contain organic matter and nutrients and when applied to farmland can improve productivity and reduce the need for manufactured fertilizer inputs (Singh and Agrawal, 2008). Biosolids have also been used successfully as a topsoil substitute for landscaping (Wu, 1987) and to enhance revegetation process on disturbed sites (e.g., mined land and tailings dumps) (Sopper, 1992). The organic matter acts as a soil conditioner, improving soil physical conditions and stimulating soil microbial activity while macro- and micronutrients present serve as a source of plant nutrients. However, there are potential hazards with land application since a range of contaminants can be present in biosolids including heavy metals, recalcitrant organic compounds, and pathogens (Hue, 1995; Jenson and Jepsen, 2005; Mininni and Santori, 1987; Pepper et al., 2006; Singh and Agrawal, 2008). Their presence greatly influences public perceptions regarding the safety of land applications. That an enormous volume of literature has been, and is continuing to be, published on the nature and content of biosolids and the agronomic and environmental aspects of land application is testament to the relevance and importance of the topic. Several workers have reviewed agronomic and environmental aspects of land application of biosolids (During and Gath, 2002; Epstein, 2003; Hue, 1995; Singh and Agrawal, 2008) and the presence of pathogens in biosolids was recently discussed (Pepper et al., 2006). However, a detailed understanding of the nature and content of biosolids, and how this develops during sewage treatment, helps greatly in predicting their effects on the soil and the wider environment. In this chapter we provide an overview of findings on the nature of inorganic and organic constituents and contaminants of biosolids in relation to the impact that land application has on soil properties, crop growth, and the wider environment. Biosolids are well characterized materials and the nature and content of organic and inorganic constituents, their nutrient content, and nutrient release characteristics are well documented and are reviewed here. Similarly, voluminous literature exists on the fate of contaminant heavy metals during wastewater treatment and, more particularly, the fate of biosolidsborne heavy metals in soil following land application. Consequently, an overview of this information is also presented here. By comparison, research into organic contaminants in biosolids is in its infancy and the majority of studies are surveys of the presence and concentrations of various compounds found in a range of biosolids samples. Current knowledge on the occurrence of organic contaminants is therefore reviewed and using the scarce data that exists, their fate during wastewater treatment and in the soil after land application of biosolids is discussed.
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2. Sewage Treatment Processes Prior to treatment, the influent sewage water is screened to remove large objects and then undergoes grit removal in which heavy inorganic coarse, sand-like, material is removed by settling. The water is then pumped to large sedimentation tanks where it undergoes primary treatment. This involves sedimentation in which most of the suspended solids are removed as sludge material which sinks to the floor of the tanks. The sludge is then pumped as a slurry (primary sludge) to storage tanks. The liquid remaining enters secondary treatment which is designed to degrade the remaining dissolved and colloidal organic content in the sewage. During the secondary stage, most of the organic matter remaining in the waste water is consumed by microbes under aerobic conditions. This is accomplished by bringing together wastewater, bacteria (and other microbes), and oxygen and can be achieved by either fixed film or suspended growth systems. In fixed film methods (e.g., trickling filters and rotating biological contactors) the microbial biomass grows on a medium and the sewage passes over its surface. The microorganisms remove and oxidize the organic material. The most common suspended growth system is the activated sludge process. Primary-treated sewage combined with microorganisms is aerated by bubbling O2 through a tank. A biological floc (composed of saprophytic bacteria and associated protozoa and rotifers) develops which removes and oxidizes the organic material. The treated supernatant is runoff and a portion of the settled sludge is returned to the head of the aeration system to reseed the new sewage entering the tank. Secondary treatment commonly removes about 60–90% of dissolved and suspended organic matter. The waste sludge from this process (secondary sludge) consists predominantly of saprophytic bacterial biomass, some other microorganisms and adhering microbial by-products. It is removed and normally mixed with the sludge from the primary treatment process. The accumulated sludges are then treated before disposal. Treatments usually include thickening, stabilization, and then dewatering. Thickening is used to increase the solids content and reduce the volume that needs to be handled. It increases the solids content of sludge from 1–2% to 4–5% and can reduce volumes to as low as 20% of unthickened sludge. The most common stabilization treatments are anaerobic and aerobic digestion. The sludge is digested to reduce the amount of organic matter and the number of disease-causing microorganisms present in the solids. In anaerobic digestion, (Taricska et al., 2007) sludge is passed into a closed container held at either the mesophilic (e.g., 36 C) or thermophilic range (e.g., 55 C). Bacteria decompose organic matter in the absence of O2 to produce CO2 and methane (biogas), the latter gas is used as a fuel to heat the digester.
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In aerobic digestion, air is continuously pumped into the digester and bacterial activity breaks down organic matter to produce CO2 and it also generates heat to kill pathogens (Shammas and Wang, 2007b). Other lesser used stabilization methods include lime stabilization and thermal treatment. Lime stabilization involves mixing the sludge with lime to achieve a pH of 12 or more and maintaining it for 2 h or longer. The alkaline conditions produced drastically reduces microbial activity and causes death of many pathogens. Thermal treatment subjects the sludge to high temperatures (e.g., 150–180 C) and pressures up to 3 mPa in a closed reaction vessel. This results in rupture of cell walls of microorganisms present (including pathogens) and causes chemical oxidation of organic matter. Following digestion, the treated sludge is often dewatered to reduce the volume and mass for transport. Belt filter presses, vacuum filtration, or centrifugation are used to increase the solids content of sludge to 25–45% whereupon the material takes on the properties of a solid rather than a liquid. It can also be composted to further reduce volume, produce a more stabilized product, and reduce the incidence of pathogens (Parr et al., 1978). Composting usually involves blending dewatered biosolids with a bulking agent (e.g., bark chips) and composting the product in windrows. Heat is generated during the intense microbial activity of composting and thermophilic temperatures (55 C) can be reached which cause death of many pathogenic organisms.
3. Composition of Biosolids 3.1. Organic matter 3.1.1. Nature of organic matter Biosolids samples are typically made up of 40–70% organic matter (as measured by loss of mass on ignition). They typically have an organic C content ranging from 20–50%, a total N content of 2–5%, and a C/N ratio of about 10–20 (Alonso et al., 2006, 2009; Alvarez et al., 2002; Cai et al., 2007a; Solis et al., 2002; Sprynskyy et al., 2007; Wang et al., 2005, 2006a). The organic matter originates principally from human feces (primary sludge) and bacterial cells (secondary sludge) and has undergone some degree of decomposition and humification during anaerobic or aerobic digestion. The organic fraction of biosolids has been identified as a mixture of fats, proteins, carbohydrates, lignin, amino acids, sugars, celluloses, humic material, and fatty acids. Live and dead microorganisms constitute a substantial proportion of the organic material and provide a large surface area for sorption of lipophilic organic contaminants in the sludge. Because much of the insoluble inorganic matter settles out during primary sedimentation,
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the organic matter content of primary sludge (47–70%) is normally less than that of secondary sludge (62–82%) (Alvarez et al., 2002; Solis et al., 2002). The organic matter content of mixed sludge typically declines during digestion as organic matter is decomposed and lost as CO2 (Alvarez et al., 2002; Solis et al., 2002). Solis et al. (2002), for example, recorded an organic matter content of 65% for mixed sludge but a content of only 56% after anaerobic digestion. There is a further decline (as much as 30–60%) in organic matter content if the biosolids are composted (Alvarez et al., 2002; Liu et al., 2007a,b; Solis et al., 2002), although this will not necessarily be the case if a slowly decomposable organic bulking agent (e.g., shredded bark chips) is added prior to composting (Nomeda et al., 2008). Humification is a natural process by which plant and animal residues decompose in the soil and a dark colored, more or less stable portion of organic matter remains. The humic materials remaining are high molecular weight organic molecules made up of a core of phenolic polymers produced from the products of biological degradation of plant and animal residues and the synthetic activity of microorganisms (Stevenson, 1994). They exist as heterogeneous, complex, three-dimensional amorphous structures. The humic fraction of biosolids differs from that of soils because the former has undergone a relatively short period of decomposition/transformation by a technological process rather than a long-term transformation under natural soil conditions. Characterization of humic substances is complex and involves a wide range of techniques including elemental and functional group analyses, gel filtration chromatography, electrophoresis, pyrolysis, thermochemolysis, and ultraviolet/visible, infrared, nuclear magnetic resonance (NMR), electron spin resonance (ESR), and fluorescence spectroscopies (Senesi et al., 2007). These techniques have shown that in comparison with native soil humic substances, humic substances from biosolids are characterized by lower molecular weights, higher contents of S- and N-containing groups, lower C/N ratios and contents of acidic groups, much lower metal binding capacities and stability constants, a prevalence of aliphaticity, extended molecular heterogeneity, and lower degrees of polycondensation and humification (Amir et al., 2004; Ayuso et al., 1997; Boyd et al., 1980; Leinweber et al., 1996; Mao et al., 2003; Rowell et al., 2001; Senesi et al., 1991; Smernik et al., 2003a, 2004; Soler Rovira et al., 2002). Part of the heterogeneity of the humic material probably arises because it is derived from two separate sources (primary and secondary sludge). For example, Smernik et al. (2003b) showed that organic matter in biosolids consisted of two spatially and chemically distinct ‘‘domains’’ derived from partially degraded plant material (i.e., human feces) and bacterial residues, respectively. Results of a comparative study of the humic substances from anaerobically and aerobically digested biosolids (Hernandez et al., 1988) showed that the
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type of digestion process has little effect on elemental composition or functional group content. Composting organic wastes is an established method of obtaining chemical stabilization, biological maturation, and sanitization and involves controlled, aerobic, decomposition of organic waste to form a smaller volume of relatively stable humus-like material (Senesi and Plaza, 2007). Thus, composting of sewage sludge results in further decomposition and humification and as a result the chemical and physicochemical properties of the biosolids-derived humic substances more closely approach those of native soil humic substances (Amir et al., 2004, 2005a; Garcia et al., 1991a; Jouraiphy et al., 2005; Sanchez-Monedero et al., 2002; Zbytniewski and Buszewski, 2005). For example, Amir et al. (2004) demonstrated that during composting there was a steady decrease in C content, a more substantial decrease in N content, an increase in C/N ratio, and a decrease in aliphatic compounds which was accompanied by an increase in the relative abundance of aromatic structures. These changes occur because during composting, oxidative degradation of readily accessible compounds (e.g., aliphatic side chains of lipidic and N-containing peptide structures) occurs. This leads to a more oxidized, polycondensed aromatic structure. Digested biosolids contain a significant portion of water-soluble ‘‘labile’’ organic matter. This fraction often makes up 2–3% of total organic C content (Garcia et al., 1991b; Zbytniewski and Buszewski, 2005) and consists of sugars, aliphatic organic acids, amino acids, and soluble low molecular weight polyphenolic humic substances. The amounts of such substances can sometimes increase during the initial stages of composting (Zbytniewski and Buszewski, 2005) as more complex organic substances are broken down and, in addition, organic metabolites are excreted by the decomposer microbial community. However, over the composting period (usually 50–150 days), there is typically an overall decline in soluble C concentrations (both absolute concentrations and those as a percentage of total organic C content) until they account for about 1–2% of organic C (Garcia et al., 1991b; Zbytniewski and Buszewski, 2005). Indeed, a decline in water-soluble organic C is often used as an indicator of compost maturity since fresh compost consists of many easily degradable and water-soluble substances, whereas mature compost is rich in stable, decomposition-resistant, high molecular weight, humic substances (Zmora-Nahum et al., 2005). 3.1.2. Application to the soil Following application of biosolids to soils, there is a rapid phase of decomposition as the easily decomposable fractions are degraded. This is accompanied by a period of intense microbial activity in the sludge-amended soil (see below). This can lead to a ‘‘priming effect’’ and result in some concomitant decomposition of native soil organic matter (Terry et al., 1979).
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Nevertheless, when biosolids are applied to soils at high rates and/or repeatedly, there is typically a substantial increase in soil organic matter content (Gupta et al., 1977; Kladivko and Nelson, 1979; Moffet et al., 2005; Navas et al., 1998; Rostagno and Sosebee, 2001). The effect is particularly pronounced on degraded soils with a low initial organic matter content (Garcia-Orenes et al., 2005). Indeed, using 14C-labeled biosolids, Terry et al. (1979) showed that a major portion of biosolids-C was resistant to decomposition in the soil and had a turnover rate in the order of hundreds of years. Not only is the soil organic matter content increased, but also the quality of organic matter is changed. That is, as expected based on the above discussion, amending soils with biosolids generally causes an increase in aliphaticity and N, H, and S contents and a decrease of C/N ratios, O and acidic functional group contents and metal binding capacities of soil humic materials (Adani and Tambone, 2005; Boyd et al., 1980; Garcia-Gil et al., 2004; Han and Thompson, 1999; Piccolo et al., 1992; Plaza et al., 2005, 2006). These effects are most evident at high rates of addition of biosolids. With increasing time after application, the characteristics of the amended soil humic substances return to those of the unamended soil since the biosolids-derived humic materials undergo further humification and become incorporated within the soil humic fraction (Senesi et al., 2007). Amending soils with composted biosolids, however, has a much lesser effect on the characteristics of soil humic substances compared to uncomposted material. Increases in concentrations of dissolved organic matter in soil solution, and its downward movement in the soil profile, following biosolids applications have been noted by a number of workers (Ashworth and Alloway, 2004; Han and Thompson, 1999; Neal and Sposito, 1986; Toribio and Romanya, 2006). Han and Thompson (1999) also observed that the molecular weight distribution of soluble organic matter in soils shifted to lower weights (e.g., <14,000 Da) following biosolids applications. The significance of dissolved organic matter to the mobility of biosolids-derived heavy metals is discussed in Section 5.3.5. The cation exchange capacity (CEC) of the soil is often increased following land application of biosolids (Clapp et al., 1986; Epstein et al., 1976; Gaskin et al., 2003; Navas et al., 1998; Udom et al., 2004). This is attributable to the high CEC of biosolids organic matter conferred by the many negatively charged functional groups present on humic material. The extent of the increase will depend on such factors as soil texture, initial soil organic matter content and CEC, nature of biosolids, and period since last application. Over time, there will be a subsequent decrease in CEC as the added biosolids organic matter decomposes (Clapp et al., 1986). The increase in organic matter content following biosolids application often results in a concomitant improvement in soil physical properties
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(Clapp et al., 1986; Khaleel et al., 1981). There is often an increase in water stable aggregation (Epstein, 1975; Gupta et al., 1977; Kladivko and Nelson, 1979; Pagliai et al., 1981) due to the binding properties of organic matter and the associated microflora. Because of increased aggregation, total pore space is typically increased resulting in measured deceases in bulk density and increases in total porosity (Garcia-Orenes et al., 2005; Navas et al., 1998; Rostagno and Sosebee, 2001; Table 1). Because of the increased porosity, increases in infiltration rate (Table 1) and hydraulic conductivity also tend to occur (Epstein, 1975; Gupta et al., 1977; Tsadilas et al., 2005) and as a result there can be decreased runoff and water erosion (Moffet et al., 2005; Rostagno and Sosebee, 2001). Water-holding capacity often increases at both field capacity and wilting point (Kladivko and Nelson, 1979; Gupta et al., 1977; Table 1) but the amount of available water (held between field capacity and wilting point) is often not greatly affected (Gupta et al., 1977; Kladivko and Nelson, 1979; Tsadilas et al., 2005). Addition of an organic substrate to a soil generally results in an increase in the size and activity of the soil microbial community as well as the activities of soil enzymes. Such stimulation of microbial activity can occur following biosolids applications and/or inhibitory effects can occur due to the presence of heavy metals and other pollutants (see, Section 5.3.6). Where there is little or no inhibition of microbial activity from pollutants, substantial increases in microbial activity induced by biosolids applications have been recorded in both laboratory incubations and field studies. For example, in a two-month incubation experiment Dar (1996) showed that biosolids amendment at 0.75% increased soil microbial biomass by 8–28%, arginine ammonification rate by 8–12%, and dehydrogenase and alkaline phosphatase enzyme activities by 18–25% and 9–23%, respectively, compared to unamended soils. Increases in the activities of other soil
Table 1 Effect of annual biosolids applications over a 3-year period on soil organic matter content and some soil physical properties Bulk Field Wilting Biosolids Organic mattera density capacity point rate (Mg ha 1) content (%) (g cm 3) (g g 1) (g g 1)
0 10 30 50 a
2.57aa 2.86b 3.38c 3.75d
1.41b 1.32a 1.3a 1.27a
27.46a 29.46b 30b 33.85c
14.23a 16.01b 16.51c 18.39d
Available Final water infiltration (g g 1) rate (cm h 1)
53.13a 53.25a 53.41a 58.62b
1.95a 1.95a 3.6b 4.05b
Numbers in the same column followed by different letters differ significantly at probability level p < 0.05 to the LSD test. From Tsadilas et al. (2005); copyright Taylor & Francis.
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enzymes such as urease, amidase, proteinase, b-glucosidase, and arylsulphatase in response to biosolids addition have also been noted in incubation studies (Gomah et al., 1990; Hattori, 1988; Kizilkaya and Hepsen, 2004; Topac et al., 2008). In field experiments, increases in microbial biomass C and N, basal respiration, metabolic quotient (qCO2), and FDA hydrolysis rate have been noted following biosolids applications (Fernandes et al., 2005; Garcia-Gil et al., 2004; Sanchez-Monedero et al., 2004) as have increases in the activities of dehydrogenase, protease, urease, amylase, catalase, b-glucosidase and alkaline phosphatase (Fernandes et al., 2005; Furczak and Joniec, 2007; Garcia-Gil et al., 2004; Sastre et al., 1996). The stimulatory effect on microbial activity is most intense during the first few months following biosolids applications (i.e., during the rapid phase of decomposition (Garcia-Gil et al., 2004). Even where levels of heavy metals in biosolids are high, there can be an initial increase in microbial activity during the initial phase of decomposition which is then followed by a later phase where microbial activity is inhibited (Kizilkaya and Bayrakli, 2005). The stimulating effect on soil microbial activity of the application of composted biosolids has been shown to be lower but more persistent than that of uncomposted biosolids ( Jimenez et al., 2007; Pascual et al., 2002; Sanchez-Monedero et al., 2004). Nevertheless, substantial increases in microbial biomass C and N, basal respiration rate, potentially mineralizable N, and the activities of some soil enzymes have been noted following field applications of composted biosolids ( Jimenez et al., 2007; Speir et al., 2004; Zaman et al., 2004). Increases in concentrations of dissolved organic matter in soil solution, and its downward movement in the soil profile, following biosolids applications have been noted by a number of workers (Ashworth and Alloway, 2004; Han and Thompson, 1999; Neal and Sposito, 1986; Toribio and Romanya, 2006). Han and Thompson (1999) also observed that the molecular weight distribution of soluble organic matter in soils shifted to lower weights (e.g., <14,000 Da) following biosolids applications. The significance of dissolved organic matter to the mobility of biosolids-derived heavy metals is discussed in Section 5.3.5.
3.2. Inorganic components The inorganic content of biosolids, as measured by ash content, commonly ranges from 30–60% ( Jaynes and Zartman, 2005; Sommers et al., 1976; Terry et al., 1979). This high ash content (i.e., about 50%) results from the effective removal of many of the inorganic components from wastewater during primary and secondary treatment. The inorganic component of biosolids consists mainly silt- and clay-sized particles that arise from a range of sources including local soil and sediment materials, broken glass
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washed into stormwater drains, inorganic residues in human feces (e.g., relatively high concentrations of SiO2 are found in foods originating from plant material; 1–4%), cosmetics, and other products washed down residential drains. X-ray fluorescence analysis on dried sludge by Thawornchaisit and Pakulanon (2007) indicated that oxides of Si, Al, and Fe (with a combined total of 62%) were the three main inorganic constituents of biosolids. X-ray diffraction analysis of biosolids has been performed by a number of workers ( Jaynes and Zartman, 2005; Mun et al., 2005; Sommers, 1977). Jaynes and Zartman (2005) observed an inorganic matrix consisting mainly of Quartz (SiO2) and feldspars (crystalline minerals that consist of aluminum silicates containing K, Na, Ca, or Ba) and kaolinite, mica, and expandable clays were also present. Sommers (1977) identified quartz, calcite, dolomite, feldspars, and layer silicates while Mun et al. (2005) found quartz was the dominant mineral but there were also significant amounts of feldspars, muscovite, and chlorite. In biosolids ash, Hartman et al. (2007) identified quartz and haematite as the predominant minerals. Jaynes and Zartman (2005) also found significant amounts of poorly crystalline Al and Fe phosphates (thought to be formed during anaerobic digestion) and talc residues originating from cosmetics.
4. Nutrient Content and Release 4.1. Nitrogen The N content of biosolids can vary greatly (Sommers, 1977) but is typically in the range of 2.8–3.8% (Epstein, 2003; Hue, 1995). Accumulation of total N in the surface soil, 15 years after an application of 500 ton ha 1 of biosolids to a forest soil is evident in Fig. 1. Because 50–90% (often quoted as 80%) of N in biosolids is in organic form (Sommers, 1977), information on the N mineralization rate is necessary to predict N availability following land application. Because nitrification (the microbial conversion of NH4þ to NO 3 ) is predominantly an aerobic process, in anaerobically digested biosolids the content of mineral N consists of about 99% NH4þ–N and 1% NO3–N (USEPA, 1995). However, in aerobically digested biosolids the bulk of the mineral N is present as NO3–N (Sommers, 1977). Mineralization of biosolids-N in soils has been widely studied in laboratory incubations. Such studies with anaerobically digested sludge have reported mineralization rates of 4–48% in 16 weeks (Ryan et al., 1973), 14–25% in 13 weeks (Magdoff and Chromec, 1977), 40–42% in 15 weeks (Epstein et al., 1978), 15% in 16 weeks (Parker and Sommers, 1983), and 24–68% in 32 weeks (Lindermann and Cardenas, 1984). The N mineralized tends to be greater from aerobically than anaerobically digested biosolids (Hseu and
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Total P (mg g−1)
Total N (mg g−1) 0
0
10
0
10
20
0
50
50
Soil depth (cm)
20
Control Sludge-treated
Control Sludge-treated 100
100
150
150
Figure 1 Total N and P concentration with depth in a forest soil treated with 500 Mg ha 1 municipal biosolids 15 years previous to sampling and in a control (untreated) plot. From Harrison et al. (1994); copyright Elsevier.
Huang, 2005; Magdoff and Chromec, 1977) and composting greatly decreases biosolids-N mineralization potential (Epstein et al., 1978; Parker and Sommers, 1983). In biosolids, N mineralization potential has been related to total organic N content and more particularly to various indices of protein content. A large proportion of biosolids organic N is thought to be proteinaceous in origin and this fraction represents a labile pool of organic N (Hattori and Mukai, 1986; Lerch et al., 1992). Hattori and Mukai (1986) found a correlation between mineralization of biosolids-N and crude protein content while Hattori (1988) found a correlation with proteinase enzyme activity in the biosolids-amended soil. Lerch et al. (1992) also found a correlation between N mineralization and low molecular weight amines (assumed to be proteins) in biosolids while Rowell et al. (2001) found a correlation with the alkyl index and the alkyl to O-alkyl ratio (as determined by solid state13C NMR spectroscopy). This was explained as a reflection of proteins in the alkyl region of the CPMAS NMR spectra and Rowell et al. (2001) suggested that N mineralization from biosolids is mainly a consequence of catabolism of the protein pool rather than decomposition of the material as a whole. In soils, N mineralization is carried out by the heterotrophic microbial community and is therefore highly dependent on environmental factors which affect microbial activity (e.g., soil type, temperature, water content, aeration). Thus, under field conditions, the proportion of the potentially
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mineralizable pool of organic N that is actually released will be highly variable depending on soil and seasonal conditions. Furthermore, mineralization will proceed over a period of several years. For agronomic and environmental purposes, it is often assumed that 20%, 10%, and 5% of biosolids organic-N is mineralized in the first, second, and third year, respectively, after application (USEPA, 1995). As expected, actual field mineralization rates are variable and depend on the interaction of a number of factors including biosolids composition and rate of application, soil type, pH, soil temperature, soil water content, and aeration (Artiola and Pepper, 1992; Barbarick et al., 1996; Sims and Boswell, 1980). Based on field trials in Wisconsin, Keeney et al. (1975) suggested an organic N decay rate series of 15–20%, 6%, 4%, and 2% for the first, second, third, and fourth years after application but Kelling et al. (1977a) found a decay rate of 45, 25–30, and 10–15% over a 3-year period. In California, Pratt et al. (1973) found a decay rate of 35, 10, 6, and 5% over a 4-year period. From field trials in Nebraska, Binder et al. (2002) found a decay series of 40, 20, 10, and 5% over a 4-year period. Most data suggests that the USEPA guidelines are conservative and that often more than 20% of biosolids organic N is mineralized in the first year (Barbarick and Ippolito, 2000; Barbarick et al., 1996; Cogger et al., 1998). The agronomic response to applied biosolids-N will be greatly affected by a range of environmental and soil conditions. Binder et al. (2002), for example, showed in a series of field trials that irrigated maize yield response was relatively consistent between years with maximum yields being attained at about 441 kg organic N ha 1 (Fig. 2). However, dryland sorghum yields were less consistent. In 1996, there was no significant yield response because of high residual soil NO3 and mineralizable N originating from a previous soybean crop and a previous 3-year fallow (Fig. 2). Yields in 1997 and 1998 were similar and considered representative of more common rotations and climatic conditions in south east Nebraska. In 1999, cool weather restricted N mineralization rate and sorghum responded to much higher rates of biosolids-N (Fig. 2). For anaerobically digested biosolids, the NHþ 4 initially present and that which is ammonified soon after application is at risk of volatilization loss if biosolids are surface applied. Ammonia volatilization is favored when high concentrations of NHþ 4 are present in an environment with a pH above 7. The typically high pH of 6–8 in biosolids (see, Section 4.3) therefore tends to favor volatilization and losses ranging from 25–80% of the initial NH4þ content have been recorded (Adamsen and Sabey, 1987; Beauchamp et al., 1978; Robinson and Polglase, 2000; Robinson and Roper, 2003; Terry et al., 1981). Incorporation of biosolids into the soil will minimize such losses. Over a period of several weeks following biosolids application, nitrification will typically proceed induced by indigenous autotrophic nitrifier bacteria present in the soil.
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100
90
80 Year applied 1996 1997
70
1998
60
Relative yield, %
1999 Maize
50 100 After soybean 1996
90
Typical year 1997, 1998
80 70
Cool/dry year 1999
60 50 40
Sorghum
30 0
100
600 200 400 300 500 Organic N in applied biosolids, kg ha−1
700
800
Figure 2 Relative yield response of irrigated maize and rainfed sorghum in relation to the amount of organic N applied with biosolids in the year of application. From Binder et al. (2002); copyright American Society of Soil Science.
It is important that the rate of biosolids-N supply matches crop N requirements (i.e., that an ‘‘agronomic biosolids rate’’ is used; USEPA, 1993) since excess N will accumulate in the soil profile as the mobile NO3 anion. This can be lost from the soil as N2/N2O via denitrification under anaerobic soil conditions or can be leached down the profile into groundwater. Indeed, a frequently quoted hazard of biosolids applications is excessive movement of NO3 to groundwater (Keeney, 1989). To estimate
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an agronomic rate that supplies the amount of N required by the crop and minimizes the amount of residual NO 3 available for leaching, the potentially available N (PAN) concentration may be calculated: PAN ¼ NNO3 þ XNNH4 þ YNorg ; where X is the fraction of NH4 that does not volatilize and Y is the fraction of organic N (Norg) that is expected to be mineralized during the first season. It is generally assumed that 100% of biosolids NO3 (NNO3) is available for plant uptake and 100% of NH4 is also available (i.e., X ¼ 1) unless biosolids are surface applied in which case an estimate of the proportion of NH4 volatilized is made. As noted above, Y is difficult to estimate but is often estimated at 0.20 in the year of application. Pierzynski (1994) suggested figures of 0.25 for aerobically digested sludge, 0.15% for anaerobically digested sludge, and 0.05–0.10 for composted biosolids. Several workers have developed models specifically to describe NO3 leaching from biosolids-amended soils (Andrews et al., 1997; Joshua et al., 2001; Vogeler et al., 2006). However, in general, applications of biosolids at agronomic rates cause minimal NO3 leaching (Correa et al., 2006; McLaren et al., 2003; Surampalli et al., 2008). The greater the proportion of biosolidsN initially present in NHþ 4 form (which is rapidly nitrified following soil application) the greater the potential for NO3 leaching since there is more NO3 in the soil profile (Shepherd, 1996; Smith et al., 1998). Deep injection of biosolids exacerbates leaching losses because less drainage is required to leach N below the root zone (Shepherd, 1996). Timing of applications will be an important consideration so that N supply from biosolids is in synchrony with crop uptake requirements. For example, applying biosolids in autumn prior to winter rains (during a period where crop growth and N uptake is slow) is likely to favor leaching losses of NO3 (Shepherd, 1996). Nitrogen mineralization will occur whenever conditions are favorable which on an annual basis is likely to be over a longer period than that for N uptake by the crop. As a result, mineral N will inevitably be produced during periods when there is little chance of plant uptake. It will therefore be advisable, where repeated biosolids applications are being made, to measure soil profile mineral N prior to biosolids applications and reduce the biosolids application rate accordingly (Pierzynski, 1994).
4.2. Phosphorus The P content of biosolids is often in the range of 1.2–3.0% (Sommers, 1977, Sommers et al., 1976). In anaerobically digested sludges, almost all the P (>80%) is present in inorganic form (Ajiboye et al., 2007; Hinedi et al., 1989a,b; Shober et al., 2006; Smith et al., 2006) mainly as phosphate
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adsorbed to ferrihydrite and Al hydroxides, hydroxyapatite and b-tricalcium phosphate (Shober et al., 2006). Using combined sequential chemical extraction, 31P NMR and XANES, Ajiboye et al. (2007) concluded that readily soluble P forms in biosolids mainly originated from easily soluble Ca and Al phosphates while recalcitrant forms were associated with Fe and Al. In aerobically digested sludge, the organic P content is greater (e.g., 50%) and this is present predominantly as phosphate monoesters and diesters (Hinedi et al., 1989a). Organic P must undergo mineralization in the soil before it is plant available. In lime-stabilized biosolids, recalcitrant calcium phosphates (e.g., hydroxyapatite, tricalcium phosphate) become major components (Shober et al., 2006). A typical biosolids sample may contain 3.2% N and 1.4% P (Hue, 1995) and although the biosolids provides about twice as much N as P, agricultural crops sequester about four times as much N as P leading to an overall increase in soil P in relation to N. Pierzynski (1994) calculated that if a typical biosolids sample (containing 13 g kg 1 PAN and 10 g kg 1 total P) were applied to supply 150 kg N ha 1, it would also apply 115 kg P ha 1 which is approximately three times more than would typically be recommended for maize. The imbalance between N and P in biosolids typically leads to a substantial increase in extractable soil P levels (Kelling et al., 1977b; Maguire et al., 2000; Peterson et al., 1994), often to levels much greater than those necessary for adequate P nutrition of crops. This can lead to an increased potential for off-site movement of P via runoff and leaching. The accumulation of total P in the surface layers of a biosolids-amended soil is clearly illustrated in Fig. 1. Current recommendations in both United Kingdom and United States are that the relative effectiveness of biosolids-P, compared to soluble fertilizer P, is 50% (MAFF, 1994; USEPA, 1995). O’Connor et al. (2004) assessed phytoavailability of 12 different biosolids samples in a greenhouse study, relative to triple superphosphate (TSP), and confirmed that most biosolids produced by conventional methods had a relative phytoavailability in the range of 25–70% TSP. Biosolids produced in water treatment plants where Fe, Al, or Ca is added during treatment to lower soluble P (to meet effluent limitations) have a lower P availability (i.e., <25% TSP) (O’Connor et al., 2004). Indeed, in such biosolids, the solubility and availability of P is characteristically low (Lee et al., 1981; Lu and O’Connor, 2001, Maguire et al., 2000; Soon and Bates, 1982) since the phosphate is strongly adsorbed to the surfaces of Fe and Al hydrous oxides and calcium carbonate. Heat-dried biosolids also have low P availability (Chinault and O’Connor, 2008). By contrast, biological P removal biosolids have a high P phytoavailability (>75% TSP) (O’Connor et al., 2004). These biosolids are produced by a modified activated sludge process used to produce low P concentrations in the treated effluent wastewater. It employs aerobic and anaerobic zones to selectively enrich for bacteria
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which take up large amounts of phosphate and store it intracellularly as polyphosphate under cyclic anaerobic and aerobic conditions. Surface runoff is the major pathway for P loss from soils to surface waters (Daniel et al., 1998; Sharpley et al., 1994). Particularly where surface applications of biosolids have been practiced, runoff of particulate matter high in P is a potential danger since P inputs to aquatic freshwater systems can increase the rate of eutrophication (Carpenter et al., 1998). The higher the water-soluble P content of biosolids, the greater the risk of runoff losses of P (Elliott et al. (2005). Due to its strong adsorption onto soil colloids, it is usually considered that there is a low risk of P leaching down the soil profile. However, leaching can be a concern particularly in sandy soils (with low P sorption capacity) with a low pH (because of increased P solubility) and/or where soils have become P saturated, especially following heavy animal manure applications (van Riemsdijk et al., 1987). Some studies have, however, shown that if soil test P values exceed a certain critical ‘‘change point’’ value, soluble P increases and significant leaching losses can occur (Heckrath et al., 1995; Hesketh and Brookes, 2000; McDowell et al., 2001). Such leaching is thought to occur principally by macropore flow (e.g., in cracks, earthworm burrows, and root channels) and much may be as particulate organic matter and as phosphate sorbed to clay particles. Indeed, particlefacilitated transport of P has been found to play an important role in P leaching (de Jonge et al., 2004; Djodjic et al., 2000; Laubel et al., 1999; Siemens et al., 2004). The elevation of soil test P values above change point values, due to repeated biosolids applications, could therefore induce increased P leaching particularly for biosolids low in reactive Fe and Al (Elliott et al., 2002). Certainly, Sui et al. (1999) detected significant downward movement of surface-applied biosolids-P into the 0–5 and 5–25 cm soil layers after 6 years of annual applications.
4.3. Other nutrients The K content of biosolids is very low (e.g., 0.15–0.40%), in comparison with that for N, yet demand for it by crops is often comparable. For that reason, biosolids is generally considered a poor source of K and supplementary fertilizer K applications often need to be made. The reason for this is that most K compounds are water soluble and remain in the sewage effluent or aqueous fraction during sludge dewatering. Nevertheless, the K in biosolids is normally assumed to be 100% available for plant uptake (Pierzynski, 1994). The Ca (2.1–3.9%) and Mg (0.3–0.6%) content of biosolids is similar to that of animal manures (Hue, 1995). Biosolids also supplies micronutrients such as B, Cu, Zn, Mn, Fe, Mo, and Ni (Epstein, 2003) and this may be important where micronutrient deficiencies occur in the soils where land
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application is being practiced. Nevertheless, as discussed below, metals such as Zn and Cu may sometimes be present in biosolids at levels that are considered unacceptable. Addition of biosolids also results in an increase in electrical conductivity (EC) in soil solution (increased salinity) and alterations to soil pH (Clapp et al., 1986). The EC of biosolids can be measured in a number of different ways including directly on the wet sludge, or after drying in either saturation paste extracts or 1:5 solid: water extracts. This contributes to variability in reported values which generally lie between 3 and 12 dS m 1 (GarciaOrenes et al., 2005; Moffet et al., 2005; Navas et al., 1998; Rostagno and Sosebee, 2001). Such values are generally considerably greater than those encountered in nonsaline soils (i.e., 0–2 dS m 1 in saturation paste extracts and 0–0.15 dS m 1 in 1:5 soil: water extracts). The high EC in biosolids is attributable to the high concentrations of ions such as Mg2þ, Ca2þ, and Cl that are present. During heavy rains/irrigation, soluble salts will leach down below the root zone and EC in the surface soil will return to that prior to biosolids application. Increases, decreases, and no effect of biosolids application on soil pH have been noted (Clapp et al., 1986; Epstein, 2003; Singh and Agrawal, 2008). Changes will be dependent on many soil and biosolids properties including the initial pH and buffering capacity of both materials. The buffering capacity of the biosolids will be largely controlled by factors contributing to the CEC of the material and the content of Ca and Mg oxides. The initial pH of biosolids varies greatly but can often be in the range of 6–8 (Epstein, 2003; Merrington et al., 2003; Navas et al., 1998). Thus, in general, pH of acidic soils (e.g., <6) will tend to be increased while that of alkaline soils (e.g., >8) will tend to be decreased. However, in a range of soils a progressive decline in pH following biosolids application has often been observed and this is attributable to nitrification of biosolids NH4þ (Clapp et al., 1986; Harrison et al., 1994; Navas et al., 1998; see, Section 5.3.2). Changes in pH will have indirect effects on the availability of nutrients as well as heavy metals (see, Section 5.3.3).
5. Heavy Metal Contaminants Heavy metal is a term commonly used as a group name for metals and semimetals (often defined as having an atomic number greater than 20 or 21) that have been associated with contamination and/or potential toxicity to animals or plants. Common elements considered include Cu, Zn, Co, Ni, Pb, Hg, Cd, Cr, Se, and As.
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5.1. Total concentrations A significant proportion of the anthropogenic emissions of heavy metals can accumulate in sewage. Industrial wastewater is often the major source. Wastewater from surface treatment processes (e.g., electroplating, galvanizing) can be a source of metals such as Cu, Zn, Ni, and Cr while industrial products may, at the end of their life, be discharged as wastes. Key urban inputs include drainage waters, business effluents (e.g., car washes, dental uses, other enterprises), atmospheric deposition, and traffic related emissions (vehicle exhausts, brake linings, tires, asphalt wear, petrol/oil leakage, etc.) which are transported with stormwater into the sewage system (Bergback et al., 2001; Comber and Gunn, 1996; Sorme and Lagerkvist, 2000). Household effluents can also be important. For example, at an English treatment works, Comber and Gunn (1996) found domestic inputs of Cu and Zn were large representing 64 and 46%, respectively, of total inputs. The bulk of the Cu originated from Cu piping while most of the Zn came from household activities (since it is a component of skin creams, ointments, makeup, deodorant, talcum powder, shampoo, and aftershave). The presence or absence of elevated heavy metal concentrations in sewage varies enormously between treatment works and depends greatly on local factors such as type and number of industries in the region, regulations regarding the quality of industrial discharges allowed to sewers and public awareness of the environmental impacts of metal contaminated discharges. Heavy metal content of sewage often fluctuates due to irregular inputs from industrial and urban sources and as a result influent concentrations can vary greatly on an hourly, daily, or monthly basis (Brown et al., 1973; Oliver and Cosgrove, 1974). As a result the biosolids produced at one treatment works can also vary greatly in heavy metal loadings with time. Although waste water treatment plants are expected to control the discharge of heavy metals to the environment, they are chiefly designed for removal of organic matter. Heavy metal removals are a side benefit. Metal removal occurs both during primary and secondary treatment. During primary treatment, as suspended solids slowly settle out, metals associated with/adsorbed to the solid particles are concentrated in the sediment and are then removed with the sediment. During secondary treatment two main processes lead to removal of metals. These are (i) bioaccumulation in which metals are accumulated into the living bacterial cells and (ii) biosorption in which heavy metals are sorbed onto negatively charged sites on bacterial cell walls and on extracellular polysaccharide gels (Brown and Lester, 1979; Urrutia, 1997). The heavy metals are then removed in the microbial sludge which is mixed with the primary sludge. The heavy metal concentrations in primary and secondary sludges (on a dry weight basis) are typically similar in order of magnitude but concentrations are typically
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30–70% greater in primary sludges (Alonso et al., 2009; Alvarez et al., 2002; Solis et al., 2002). The extent of removal of metals during primary and secondary treatment can vary greatly for different metals in the same treatment plant as well as between plants. For example, in a treatment plant in Poland, Chipasa (2003) recorded removal efficiencies of Zn 84%, Cu 51%, Pb 33%, and Cd 15% and noted that these were directly proportional to metal influent concentrations. From a variety of sources, Lester et al. (1979) and Stoveland et al. (1979) reported removal efficiencies of Cu 71–96%, Pb 91–95%, Cd 78–91%, Zn 60–94%, Ni 11–70%, and Cr 67–79%. Many factors influence removal efficiency including initial concentrations of metals in influents, characteristics of individual metals (e.g., pH/solubility relationships), operating parameters of the plant and other physical, chemical, and biological factors (Brown and Lester, 1979; Chipasa, 2003; Stoveland et al., 1979). Thus, removal efficiency is not a predictable property. A large number of studies in many parts of the world have surveyed the heavy metal content of biosolids samples (e.g., Kuchenrither and McMillan, 1990; Ozaki et al., 2006; Sajjad et al., 2005) and much of this data has been summarized previously (Epstein, 2003; Hue, 1995). Taking account of the great variability in heavy metal inputs which occurs between water treatment plants, some ‘‘typical’’ concentrations of metals encountered in biosolids samples (in mg kg 1 values) are shown in Table 2. It is evident that Zn is commonly present in highest concentrations and that substantial concentrations of Pb, Cu, and Cr are also often present. In the United States and Canada, heavy metal concentrations in biosolids (particularly those of Cd, Cr, Pb, and Ni) have been shown to be decreasing during Table 2 Typical concentrations of heavy metals commonly encountered in biosolids
Element
Concentration (mg kg 1 dry weight)
Arsenic Cadmium Chromium Cobalt Copper Lead Mercury Nickel Selenium Zinc
1–20 1–70 50–500 5–20 100–800 100–600 1–10 10–200 5–10 1000–3000
Calculated from Hue (1995), Mininni and Santori (1987), and Epstein (2003).
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the 1980s and 1990s (Epstein, 2003; Hue, 1995). This is attributable to enforcement by municipalities of regulations regarding the maximum metal loadings in effluents that can be discharged into the sewerage system. As a result, industrial pretreatment of effluents has become common. However, for Zn and Cu, concentrations in biosolids have remained similar over the last two decades (Epstein, 2003) because, as noted previously, they are often not principally of industrial origin. While heavy metal concentrations in biosolids have generally been decreasing and in most situations they are below regulatory limits (see below), their addition to soils still causes disquiet. This is because, unlike organic contaminants, most heavy metals do not undergo microbial or chemical degradation and therefore elevated concentrations persist in the soil for extremely long periods of time. Concerns regarding the heavy metal load in biosolids have resulted in guidelines and regulations being developed in many parts of the world to regulate land applications. These are generally based on the maximum allowable metal concentration limits (mg kg 1 dry weight) in biosolids and/or the allowable loading limits (kg ha 1 yr 1) of metals added in biosolids to soil (Epstein, 2003). The most quoted limits are those of the USEPA (USEPA, 1993) and the European Union also has its own standards. In general, USEPA and UE limits for metal concentration limits in biosolids are broadly similar but maximum loading limits are generally lower for the EU guidelines. Nevertheless, limits can vary quite widely with countries such as Sweden, Denmark, Germany, and the Netherlands generally having lower limits than USEPA or EU guidelines (Smith, 2001). USEPA metal concentration limits in biosolids are: Zn, 2800; Cu, 1500; Ni, 420; Pb, 300; Cd, 39; and As, 41 mg kg 1 (USEPA, 1993). USEPA regulations are risk based and therefore provide an opportunity to modify values as better scientific data becomes available (Epstein, 2003).
5.2. Extractable fractions Total concentrations of heavy metals indicate the extent of contamination but provide little insight into the potential mobility or bioavailability of these metals once the biosolids are soil applied. Depending on their nature, individual metals are associated in a variable manner with different phases making up the biosolids. Sequential chemical fractionation procedures are widely used to characterize the forms of metals present (chemical speciation). These methods involve chemical extractions using a sequence of reagents of increasing strength. For each reagent, a particular chemical form(s) is assigned to the metals extracted. Drawbacks of these methods include (i) lack of specificity, selectivity, and validation; (ii) postextraction readsorption; and (iii) sensitivity to procedural variables (e.g., sample size, pH, temperature, contact time, concentration of extractant, etc.) (Kot and Namiesnik, 2000). Despite such limitations, sequential extractions are
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considered the best available method of gaining knowledge on the forms in which metals are present in biosolids. A wide range of sequential fractionation schemes have been proposed for determination of heavy metal forms present in biosolids (Kot and Namiesnik, 2000; Marchioretto et al., 2002; Sims and Kline, 1991; Tessier et al., 1979). One of the simplest and most commonly used methods today is that specified by the Community Bureau of Reference (CBR) (Ure et al., 1993) in which the sample is extracted with (i) acetic acid to release the easily available ‘‘exchangeable’’ forms present in soluble and exchangeable forms and those associated with carbonate phases, (ii) hydroxylammonium chloride to release the ‘‘reducible’’ fraction associated with Fe and Mn oxide cements and nodules (forms that could become available under anoxic conditions), and (iii) hydrogen peroxide to extract the ‘‘oxidizable’’ fraction that is strongly bound to organic matter constituents. Following the sequential extraction, the amounts remaining in the ‘‘residual’’ fraction (iv) are measured after digestion with aqua regia and these are considered to be highly unavailable and associated with residual solids that occlude metals in their crystalline structures. The amounts present in fractions (i) and (ii) are considered ‘‘available’’ and those in (iii) and (iv) ‘‘unavailable.’’ This method has been extensively used for characterization of biosolids (Alonso et al., 2006, 2009; Alvarez et al., 2002; Fuentes et al., 2004, 2008; Perez-Cid et al., 1999; Scancar et al., 2000; Solis et al., 2002; Sprynskyy et al., 2007; Wang et al., 2005, 2006a,b). To generalize from the results of these studies, Cu is typically found to be concentrated (about 80% of total Cu content) in the oxidizable fraction bound to organic matter. This is in accordance with the high stability constant of the Cu complexes with organic matter (Ashworth and Alloway, 2004). By contrast, Zn is distributed preferentially (usually 40–60%) in the available exchangeable plus oxidizable fractions. Greater than 50% of total Pb content is typically found in the residual fraction with substantial amounts (15–30%) also being present in the oxidizable fraction. Ni and Cd have a similar distribution with 60–70% of total content being present in the unavailable oxidizable and residual forms (usually more or less equally distributed between the two fractions). Co is similarly distributed between unavailable and available fractions with significant amounts (30–50%) being present in the organic fraction. Cr is concentrated in the unavailable forms (usually more than 90% of total content) with over 50% in the residual fraction and a significant proportion also organically bound. For Fe, 80–90% of total content is in unavailable forms with greater than 60% in the residual form and 10–20% in the organic fraction. However, for Mn, 70–80% of total content is in available forms with greater than 50% in the exchangeable form. In summary, Zn and Mn are the metals preferentially found in the mobile fractions of biosolids while the others are mainly concentrated in immobile forms.
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Cu and, to a lesser extent Pb and Co, have a particular affinity for binding to the organic components of biosolids. Solis et al. (2002) showed that for all metals (on a mean basis) the available (exchangeable plus reducible) fractions were higher in secondary than primary sludge. During anaerobic digestion of combined sludge there was a general increase in the percentage of metals in the unavailable oxidizable and residual fractions and during composting of the biosolids there was a further increase in the percentage of metals present in the unavailable fractions. A number of other workers have followed heavy metal fractions during the composting of biosolids with variable results. Amir et al. (2005b) found that potentially available fractions of Cu, Zn, Pb, and Ni tended to decrease over time while Zorpas et al. (2008) observed similar results for Cr, Cu, Mn, Fe, Ni, and Pb. However, Nomeda et al. (2008) showed that available fractions of Pb, Zn, and Cd increased with time but those of Cu decreased. Liu et al. (2007a,b) observed that during composting, the available fractions of Pb and Zn increased while those of Cu, Ni, and Cr were little affected. Thus, although it is clear that heavy metal levels are concentrated during composting, the effects on distribution of metals among fractions are much less clear and may vary depending on conditions of composting, presence or absence of a bulking agent (e.g., sawdust, bark), and other factors such as changes in pH. Where biosolids have a high loading of heavy metals, the material can be cocomposted with an absorbent material such as zeolite (e.g., crushed clinoptilolite rock) added at 10–25% w/w. This results in substantial decreases in the amounts of metals being present in the potentially available exchangeable and reducible fractions (Sprynskyy et al., 2007; Zorpas et al., 2008) since the metals are adsorbed to the zeolite surfaces. Cocomposting with a sodium sulfide/lime mixture (3% w/w) was also shown by Wang et al. (2008) to reduce the percentage of metals in the available fractions. A number of methods have also been developed to remove heavy metals from contaminated biosolids prior to land application. These include chemical extraction, bioleaching, electroreclamation, and supercritical fluid extraction (Babel and del Mundo Dacera, 2006).
5.3. Application to the soil 5.3.1. Heavy metal extraction from soils It has often been observed that heavy metal availability in biosolidsamended soils is closely related to total metal content of the added biosolids ( Jamili et al., 2007; Jing and Logan, 1992). Nonetheless, the presence of biosolids constituents that adsorb metals limits the usefulness of total metal content as an indicator of potential metal availability (Merrington et al., 2003). For example, Richards et al. (1997) found total metal contents of a
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range of biosolids samples was not closely related to metal mobility as estimated by the TCLP leaching procedure. Indeed, biosolids application to the soil not only increases the concentrations of heavy metals present but also alters the adsorption capacity of the soil (Alloway and Jackson, 1991). As already noted, biosolids are composed of about 50% inorganic and 50% organic material. The relative importance of the inorganic and organic components in retention of heavy metals by biosolids is a matter of controversy (Basta et al., 2005; Merrington et al., 2003) but is likely to differ for different biosolids samples as well as for different metals. Total loadings of heavy metals in biosolids-amended soils are not necessarily a good indicator of potential metal availability. Sequential fractionation schemes, as discussed in Section 5.2, are often employed to selectively extract metals associated with particular soil phases (Ure et al., 1993). Despite the limitations of such fractionation schemes, their use gives some indication of the fate of biosolids-borne heavy metals once they enter the soil system. In particular, fractionations are useful in studying the partitioning of metals between potentially available (toxic) and residual, occluded (nontoxic) fractions and the association of metals between organic and inorganic soil constituents. A wide range of soil test extractants have been employed to determine heavy metal availability (McLaughlin et al., 2000a; Ure, 1995). The most commonly used extractants are the organic metal complexing agents diethylenetriaminepentaacetic acid (DTPA) and ethylenediaminetetraacetic acid (EDTA). The DTPA test is favored in the United States and EDTA in the United Kingdom. Correlations between DTPA- and EDTA-extractable metals and metal uptake by crops are generally reasonable (Bidwell and Dowdy, 1987; Brun et al., 1998; Hooda et al., 1997; Hseu, 2006; Sanders et al., 1986, 1987; Sukkariyah et al., 2005a). Dilute acids (e.g., 0.05–0.1 M CH3COOH, HCl, and HNO3) are also used as heavy metal extractants (McLaughlin et al., 2000a). Dilute salt solutions (e.g., 0.1 M CaCl2, Ca (NO3)2, NH4NO3) are also effective extractants for predicting metal availability (Alloway and Jackson, 1991; Juste and Mench, 1992; Sukkariyah et al., 2005a). These latter salt solutions extract metals in soil solution plus those in short-term equilibrium with that solution. Complexing reagents and dilute acids extract larger amounts of metals which include a ‘‘potentially available’’ fraction. They, in affect, overestimate phytotoxicity and assess potential rather than immediate toxicity (McLaughlin et al., 2000b). McLaughlin et al. (2000b) suggested that in the future regulations and guidelines should consider extractable fractions of heavy metals in soils. That is, it is the concentration of biologically active (extractable) heavy metals present in biosolids-treated soil that is toxic to plants and soil biota (Merrington et al., 2003), yet present regulations are based on total loadings of metals (see, Section 5.1). McLaughlin et al. (2000b) considered that metals extracted with dilute salt solutions and those extracted with more
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harsh reagents (complexing agents or dilute acids) could be used together to estimate immediately toxic and potentially toxic metals, respectively. Certainly, extractable metal concentrations are likely to give a better indication of bioavailability than values based on total concentrations. Monitoring of extractable metal levels on long-term sites, where biosolids applications are continuing and/or have been terminated, will give valuable data on the long-term trends in bioavailability of various total loadings. Such data could well be used in the future to develop guidelines and regulations based on extractable soil metal levels. 5.3.2. Effects of biosolids properties on availability Following land application, the properties of the biosolids effect metal availability both directly (through heavy metal content and sorptive capacity of inorganic and organic components) and indirectly (through properties such as pH, mineralizable N content, and EC) (Merrington et al., 2003). It is usually assumed that biosolids properties dominate metal bioavailability in the short and medium term in the zone of incorporation but with time, biosolids properties have progressively less influence and soil properties ultimately control availability (Smith, 1996). The effect of biosolids materials on heavy metal retention by amended soils is complex and this is at least partially because a suite of metals is added, and competition between them for adsorption sites occurs. Bergkvist et al. (2005), for example, found Cd sorption was slightly smaller in biosolids-amended soils compared to control even though organic C content was 70% higher and oxalate-extractable Fe was roughly doubled. They attributed this to competition for sorption sites between Cd and biosolids-derived Fe and other metals such as Zn. McBride et al. (2006) found that addition of high Fe, high Al, and biosolids to soils had no long-term effect on their affinity for Cd. By contrast, Vaca-Paulin et al. (2006) observed that biosolids-amended soils showed increased adsorption capacity for Cu and Cd and attributed this to the complexing ability of the biosolids-derived organic matter. Strong metal retention by the inorganic fraction is attributable to the high adsorption capacity of Fe, Al, and Mn hydrous oxides and silicates (Basta et al., 2005; Merrington et al., 2003). The inorganic solids present in biosolids are initially present, at least partially, in noncrystalline form (Baldwin et al., 1983; Rogers and McLaughlin, 1999) and the higher surface area of noncrystalline Fe and Al oxides results in them having a higher adsorption capacity than their crystalline counterparts (Rogers and McLaughlin, 1999). In general, the order of affinity of metals for adsorption surfaces on Al and Fe oxide surfaces follow the order Cu > Pb > Zn > Co > Ni > Cd although for Fe oxides Pb > Cu has been reported and sometimes also Ni > Co ( Jackson, 1998; Sparks, 2003). In addition, carbonate, phosphate, and sulphite present in biosolids can form sparingly soluble solid phases with many metals and thus account for a substantial
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portion of some metals present biosolids (Karapanagiotis et al., 1991). For example, during anaerobic digestion, low solubility Cu and Zn sulfides characteristically form (Nagoshi et al., 2005). The organic component also has the ability to bind to heavy metals. The heterogeneous nature of humic substances and the large number of functional groups present means that binding of metals can be regarded as occurring at a large number of reactive sites with binding affinities that range from weak forces of attraction (ionic) to stable coordinate linkages (McBride, 2000; Sparks, 2003). Indeed, mechanisms involved in metal binding to organic matter are complex and probably involve simultaneous chelation, complex formation, adsorption, and coprecipitation (Stevenson and Vance, 1989). Because of the many variables involved, there are many inconsistencies in reported selectivity orders of metals with organic matter. A generalized order is Cr3þ > Pb2þ ¼ Hg2þ > Cu2þ > Cd2þ > Zn2þ ¼ Co2þ > Ni2þ ( Jackson, 1998; Jin et al., 1996; Stevenson, 1994). As noted previously, there is often a flush of organic matter decomposition following application, and this is followed by a slow decomposition phase. It has been suggested that heavy metals bound to biosolids organic matter could be released to soil solution during decomposition and as a result metal bioavailability would increase over time (Hooda and Alloway, 1994; McBride, 1995). In fact, it is often observed that heavy metal availability is greatest immediately (the first few months) following biosolids additions and this is followed by a reduction in availability (as estimated by metal extractability and/or plant uptake) as well as a reduction in organic matter content (Bidwell and Dowdy, 1987; Hseu, 2006; Logan et al., 1997; McBride et al., 1999; Walter et al., 2002). Nonetheless, the initial high availability may well be partially due to the rapid decomposition of biosolids organic matter and the consequent release of metals. Evidently, the metals released from decomposing organic matter are rapidly readsorbed by inorganic and/or organic components in the soil/biosolids. Biosolids pH will have a substantial controlling influence on the availability of metals following land application. In general, most heavy metal cations become increasingly immobile at high pH. This is because both their adsorption onto reactive oxide surfaces and precipitation reactions are favored at high pH (Sparks, 2003). As noted in Section 4.3, since the initial pH of biosolids is typically in the range of 6–8, their application will have a liming effect on acid soils thus raising their pH (Kidd et al., 2007) and tending to reduce metal availability. The mineralizable N content of biosolids is, however, an important property in relation to their effects on soil pH. During ammonification of organic N to NHþ 4 –N, one OH ion is released per unit of N while during þ nitrification of NH4 –N to NO3 –N, two Hþ ions are released. The overall process of conversion of organic biosolids-N to NO3–N is therefore acidifying. Thus, Hooda and Alloway (1994) observed a progressive
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decrease in soil pH following biosolids application to soil which was accompanied by an accumulation of soil NO 3 –N and an increase in uptake of Cd, Ni, Pb, and Zn by ryegrass growing in the soil. Such an increase in metal bioavailability accompanying acidification induced by nitrification of biosolids-derived N has also been observed by others (De Haan, 1975; Hooda and Alloway, 1993). It is therefore important to monitor pH and apply lime, if necessary, to maintain a relatively high pH (e.g., 6.5) following biosolids application. As noted in Section 4.3, the high EC of biosolids may result in an increase in soluble salts in soil solution. High soluble salts will tend to reduce soil solution pH (by exchange between cations in soil solution and Hþ and Al3þ on soil cation exchange sites) thus increasing the solubility of heavy metal cations. In addition, high concentrations of solution Cl can increase mobilization, availability, and plant uptake of Cd through the formation of Cd–chloro complexes (Weggler-Beaton et al., 2000). 5.3.3. Effects of soil properties on availability Soil properties such as pH, redox potential, EC, clay, hydrous oxide, and organic matter content will also influence heavy metal availability. The most widely recognized factor is soil pH. With the exception of As and Se, heavy metal retention by soils increases with increasing pH (McBride, 1994). As noted above, with an increase in pH, the charge on the variable charge adsorption surfaces (e.g., Fe, Al, and Mn hydrous oxides) becomes increasingly negative thus favoring metal cation adsorption and the high pH also favors surface precipitation of the metals onto the surfaces (Bradl, 2004; McBride, 2000). In general, the more mobile metals such as Ni, Cd, and Zn are more sensitive to increasing pH than other metals such as Pb and Cu that are more strongly complexed with soil organic colloids (Smith, 1996). Manipulation of soil pH has been found to be the most effective way of controlling heavy metal bioavailability in biosolids-treated soils (Alloway and Jackson, 1991). Indeed, a large number of workers have shown that the bioavailability of metals to plants in biosolids-amended soils decreases as pH is raised either by liming or applying lime-stabilized sludges (Basta and Sloan, 1999; Milner and Barker, 1989; Oliver et al., 1998). Liming a range of biosolids-treated soils to pH 7 was shown by Jackson and Alloway (1991) to reduce Cd content of lettuce by an average of 41% and cabbage by 43%. Redox potential is often considered an important factor although both increases and decreases in heavy metal solubility have been recorded following waterlogging and the onset of anaerobic soil conditions (Charlatchka and Cambier, 2000; Chuan et al., 1996; Grybos et al., 2007; Kashem and Singh, 2001a,b; Xiong and Lu, 1992). This is because a number of different processes occur following the onset of anaerobiosis and these often interact to affect metal solubility. In freely-drained soils,
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Fe and Mn occur in their high oxidation states as oxides and hydrous oxides. However, as soils become anaerobic, due to waterlogging, the redox potential decreases and oxide minerals begin to dissolve as soluble Mn2þ and Fe2þ forms (Stum, 1992; Stum and Sulzberger, 1992). This can not only result in an increase in the solubility of Mn and Fe but also of other metals (e.g., Zn, Cu, Co) which were previously adsorbed to, or occluded by, these oxides (Chuan et al., 1996; Grybos et al., 2007). When soils become anaerobic the pH tends to converge to neutrality irrespective of initial pH, whether acidic or alkaline (McBride, 1994). For acidic soils this increase in pH can result in release of organic matter into soil solution and metals bound to the organic molecules are also thought to be released (Grybos et al., 2007). This also tends to increase metal solubility. Nonetheless, the increase in pH up to about 7, favors adsorption/surface precipitation of metal cations thus favoring removal of metals from solution (Kashem and Singh, 2001a). In addition, at low redox potential sulfate ions are reduced to the sulfide form which may form complexes with metals such as Cd, Zn, and Ni (Hesterberg, 1998; Van Den Berg et al., 1998). Most metal sulfides are insoluble even under acidic conditions and so this process also tends to reduce soluble metal concentrations. Oxidation state of the contaminant itself also affects solubility. For example, selenite [Se(IV)] is much more strongly adsorbed to soil colloid surfaces than selenate [Se(VI)] and the presence of selenite is favored under reducing conditions (Martinez et al., 2006; Neal and Sposito, 1989). Se will therefore be less plant available under reducing conditions. Furthermore, under strongly reducing conditions Se may form elemental Se and metal selenides (e.g., FeSe) both of which are insoluble (Elrashidi et al., 1987; Masschelyen et al., 1991). Under oxidizing conditions both arsenate [As(V)] and arsenite [As(III)] are present while under reducing conditions As is present mainly as As(III) (O’Neill, 1995). Compared to other As species, As(III) exhibits the greatest mobility and plant availability because of its presence as the neutral species H3AsO3 (Ascar et al., 2008; Marin et al., 1993). Nonetheless, strongly reducing conditions in biosolids-amended soils can lead to precipitation of As as As2S3 (Carbonell-Barrachina et al., 1999). The ability of soils to adsorb and sequester metals is also an important factor. This is dependent on their content of inorganic (clay and Fe, Mn and Al hydrous oxide content) and organic (soil humic material) binding agents. For example, sandy soils with low oxide content and low organic matter have low sorption capacities and will have greater metal availabilities than loamy or clayey soils containing greater amounts of sorbents (e.g., clays, oxides, and organic matter) provided the soils have similar pH values (Basta et al., 2005). Hue et al. (1988) applied increasing rates of biosolids to three different soils, a limed volcanic ash-derived Andept, an alkaline Vertisol, and a limed manganiferous Oxisol. DTPA-extractable soil metal levels, lettuce growth, and tissue metal concentrations were measured.
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The Andept had the highest metal adsorption capacity and the Oxisol the lowest. As a result, lettuce Cd, Mn, Ni, and Zn concentrations were highest in the Oxisol and Mn levels reached phytotoxic levels. Hue et al. (1988) concluded that the Andept could tolerate the highest biosolids loading rate and the Oxisol the lowest. The calcite (CaCO3) content of soils can also be important. In calcareous soils, calcite represents an effective sorbent for metal ions. The initial reaction is thought to be chemisorption but metals with an ionic radius similar to that of Ca (Cd 2þ, Mn 2þ, Fe 2þ) can also readily enter the calcite structure and form coprecipitates (Gomez de Rio et al., 2004; McBride, 2000). 5.3.4. Metal availability over time The long-term (>10 years) bioavailability of heavy metals in biosolidsamended soils is of great importance in relation to environmental effects of land application of biosolids. As noted previously (Section 5.3.2), following a one-off application of biosolids the extractability of metals generally declines over time (Hseu, 2006; Sukkariyah et al., 2005a; Walter et al., 2002). Sukkariyah et al. (2005a), for example, showed DTPA-extractable Cu and Zn levels progressively decreased following one-time applications of biosolids at rates ranging from 42 to 210 Mg ha 1 (Table 3). Seventeen years after application, extractable concentrations of Cu and Zn had decreased by 58% and 42%, respectively. The decrease is attributable to metals reverting to more recalcitrant forms in the soil such as occlusion in Fe oxides or chemisorption to surfaces. Despite the initial decrease in extractability, concentrations of extractable heavy metals in biosolids-amended soils can remain elevated above Table 3 Long-term effect of biosolids application on DTPA-extractable Cu and Zn DTPA-extractable Zn mg kg 1
DTPA-extractable Cu mg kg 1
a
Biosolids rates Mg ha 1
1984
1995
2001
1984
1995
2001
0 42 84 126 168 210
1.4f a 24.9e 53.0d 73.4c 119.9b 129.4a
3.7f 23.1e 44.3d 64.8c 78.7b 92.8a
3.2f 12.6e 25.4d 33.7c 43.3b 53.6a
1.6f 19.2e 38.9d 52.4c 73.2b 78.2a
2.8f 17.2e 33.3d 49.6c 59.5b 69.9a
2.7f 9.1e 19.8d 27.9c 35.5b 49.7a
Values within columns followed by different letters are significantly different at the 0.05 probability level. From Sukkariyah et al. (2005a); copyright American Society of Agronomy.
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those of control for many decades after applications have ceased (Alloway and Jackson, 1991; Basta et al., 2005; McBride, 1995; McGrath, 1987). Results from a long-term market garden experiment at Woburn (UK) serve to illustrate this point. Sludge was applied in the 1940s until the 1960s and CaCl2-extractable Cd changed little from 1950 until the early 1980s remaining significantly higher than the control soils over the entire interval monitored (McGrath and Cegarra, 1992). Similarly, EDTA-extractable Cu, Pb, Zn, Ni, and Cr changed little following termination of biosolids application and treated soils maintained a much greater proportion of metal in EDTA-extractable form than the control. Such results occurred despite there being a significant loss of biosolids organic matter over the period indicating that heavy metals released from the decomposing organic matter were rapidly adsorbed by inorganic components of biosolids/soil and/or native soil organic matter. Certainly, biosolids-derived heavy metals are strongly sorbed to soil components making them characteristically immobile in soils. Indeed, the vast bulk of the added metals remain in the topsoil in the layer of incorporation and there is a marked reduction in concentration with depth (Alloway and Jackson, 1991; Brown et al., 1997; Chang et al., 1983; Sloan et al., 1997; Sukkariyah et al., 2005b). 5.3.5. Heavy metal mobility and leaching The results of Sukkariyah et al. (2005b) serve to illustrate the immobility of biosolids-borne heavy metals in soil. They found that more than 85% of total applied Cu and Zn was still in the layer of incorporation (0–15 cm) 17 years after a one-time biosolids application. Results for Mehlich I-extractable Cu and Zn at that site are shown in Fig. 3. It is evident that extractable Cu and Zn are concentrated in the 0–15 cm layer but there is some indication of a small amount of movement down into the 15–20 cm layer. Mass balances calculated for several long-term experiments do suggest some losses of heavy metals from the topsoil (McBride, 1995). Lateral movement in the soil due to tillage (McGrath and Lane, 1989) or physical mixing with the lower soil layer by plowing (Sloan et al., 1998) can be responsible for a significant part of the losses from the original amended soil layer. Nevertheless, mass balances calculated for sites where little or no tillage has been performed have shown less than 100% recovery (McBride et al., 1999). Increased extractable heavy metal levels (e.g., for Cu, Zn, Ni, Pb) at depths of 20–150 cm below the level of incorporation have been noted in field experiments (Barbarick et al., 1998; Baveye et al., 1999; Bell et al., 1991; Keller et al., 2002; Schaecke et al., 2002). Leachate sampling below field plots and/or undisturbed monolith lysimeters receiving biosolids has also revealed elevated metal concentrations (Keller et al., 2002; Lamy et al., 1993; McBride et al., 1997, 1999; Richards et al., 1998; Sidle and Kardos, 1977). In addition, column leaching studies have shown that heavy metals can leach through many tens of cm of soil (Al-Wabel et al., 2002;
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0
10
Concentration (mg kg−1) 20 30 40 50 60
70
0–15 Cu 15–20
20–25
25–30
30–35 //
//
80–85
210 Mg ha−1 126 Mg ha−1 Control
Depth, cm
85–90 0
20
40
60
80
0–15 Zn 15–20
20–25
25–30
30–35 //
//
80–85
210 Mg ha−1 126 Mg ha−1 Control
85–90
Figure 3 Distribution of Mehlich-I extractable Cu and Zn with soil depth 17 years after biosolids application. From Sukkariyah et al. (2005a,b); copyright American Society of Agronomy.
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Antoniadis and Alloway, 2002; Ashworth and Alloway, 2004; Parakash et al., 1997; Toribio and Romanya, 2006). In most studies, the annual export of metals from the surface-mixing layer represents a small fraction (i.e., <1–2%) of the total amount of metal added (Holm et al., 1998; Keller et al., 2002; Lamy et al., 1993). Nonetheless, cumulative transport of metals over a long period of time could result in a substantial redistribution into the subsoil layers and/or groundwater. In addition, in some studies, water quality standards have been exceeded in soil solution at depths below the zone of incorporation (McBride et al., 1999; Richards et al., 1998). Dilution by other unpolluted water will normally prevent water quality standards being exceeded in receiving groundwater. The most danger will occur where large areas of land above small, shallow water bodies are treated with biosolids. A major contributor to heavy metal mobility in soils is thought to be the formation of complexes with dissolved organic matter released from the biosolids (Brown et al., 1997; Christensen, 1985; Gerritse et al., 1982; Lamy et al., 1993; McBride et al., 1997). The amount of dissolved organic matter in soil solution and leaching through the profile characteristically increases following biosolids application and it acts as a ‘‘carrier’’ for heavy metals. Elevated concentrations of both heavy metals and dissolved organic matter are frequently found together in leachates below biosolids-treated soils (Al-Wabel et al., 2002; Antoniadis et al., 2007; Ashworth and Alloway, 2004; Keller et al., 2002; Toribio and Romanya, 2006). Antoniadis et al. (2007), for example, found that during a 310-day incubation of soils amended with biosolids at 0, 20, and 100 Mg ha 1, there was a substantial increase in dissolved organic C at about day 23 which was attributed to a flush of microbial activity. This was accompanied by a similar increase in soluble Zn and an increase in calculated activity of Zn-organic matter species (Fig. 4). The formation of strong soluble organic matter–heavy metal complexes in soil solution has been found to reduce heavy metal adsorption to solid soil phases. Neal and Sposito (1986), for example, found that sewage sludge can provide sufficient dissolved organic matter to reduce adsorption of Cd onto soil surfaces. Wong et al. (2007) showed dissolved organic matter had a stronger inhibitory effect on Zn sorption than that of Cd. Liu et al. (2007a,b) also showed dissolved organic matter depressed sorption of Ni, Cu, and Pb by soils. Thus, both heavy metal solubility and mobility is increased. Dissolved organic matter originating from the biosolids may well have a second effect in increasing metal mobility. That is, dissolved organic matter molecules can also be sorbed to the inorganic component of soils (e.g., Al and Fe oxides) (Kalbitz et al., 2005; Shen, 1999) and this could partially block potential sorption sites for metals thus tending to increase their solubility and availability. In drainage waters from biosolids-amended soils, the bulk of heavy metals have been found to be associated with soluble organic matter.
1 6 5
0.6
Zn (µmol L−1)
Soluble Zn (mg kg−1)
0.8
0.4
Day 0 Day 23
4 3 2
0.2 1 0
0 0
50
100 150 200 250 Days of incubation
Control
20 Mg ha−1
300
350
Control
20 Mg ha−1
100 Mg ha−1
100 Mg ha−1
Figure 4 Water-soluble Zn dynamics during incubation of amended and biosolids-amended soils and calculated activities of Zn-dissolved organic matter species (mmol L1) at days 0 and 23. From Antoniadis et al. (2007); copyright American Society of Agronomy.
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Using gel filtration chromatography, Dudley et al. (1987) found that in soil extracts from 80–100% of water-soluble Cu, 48–100% of Zn, and 39–100% of Ni was in organically complexed form. Using differential pulse anodic stripping voltametry, McBride et al. (1999) determined that only 30% of water-soluble Zn, 18% of Cd, and 10% of Cu was present as ionic or inorganic complexes and the remainder was presumed to be complexed with dissolved organic matter. Using the same method, Al-Wabel et al. (2002) concluded that >99% of soluble Cu and Zn in leachates was present in organically complexed form. Heavy metals have, however, also been shown to be present in drainage water associated with suspended clay-sized particles (Keller et al., 2002). The metals become adsorbed to the surfaces of Fe oxide and layer silicate clays present in this leached particulate matter. Keller et al. (2002) calculated that movement of particulate matter accounted for about 20% of Cu, Zn, and Cd leaching from a biosolidsamended soil. An important factor thought to contribute to leaching of metals is preferential flow of water and dissolved metals down the soil profile in downward oriented macropores (e.g., cracks, earthworm channels, root channels) (Camobreco et al., 1996; Keller et al., 2002; Lamy et al., 1993). This water bypasses the soil matrix thus minimizing the chances that the dissolved metals will be adsorbed to soil surfaces. Preferential flow is probably the main pathway of movement of suspended particulate matter and associated metals (Keller et al., 2002). The period of greatest risk of metal leaching is soon after biosolids application. This is when soluble organic matter is present in high concentrations and when preferential flow down surface-connected macropores is most likely. Indeed, leaching losses of metals are normally greatest during this initial period (Antoniadis et al., 2007; Camobreco et al., 1996; Keller et al., 2002; Lamy et al., 1993; Maeda and Bergstrom, 2000). For this reason, it will be important to minimize water inputs (e.g., irrigation) and drainage from soils immediately following land application of biosolids. 5.3.6. Soil microbial/biochemical effects Elevated concentrations of heavy metals in soils are known to affect soil microbial populations and associated activities (Baath, 1989; Brookes, 1995; McGrath, 1994). Baath (1989) concluded that the following order of toxicity to soil microbes is most commonly found (in mg kg 1 values): Cd > Cu > Zn > Pb. However, he showed an enormous disparity between individual studies as to the exact concentrations at which metals become toxic. Giller et al. (1998) suggested that much of the variability in deriving toxic concentrations of heavy metals occurs through comparison of results from short-term laboratory incubation studies with data from long-term exposures of microbial populations to heavy metals in field experiments. This is because laboratory studies measure response to immediate acute
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toxicity (usually from one large addition of metals) whereas monitoring of long-term field experiments measures responses to long-term chronic toxicity which accumulates gradually. Stress caused by heavy metal contamination typically has two interrelated effects on soil microbial communities. The first is a loss of structural and functional diversity since toxicities can suppress and/or kill sensitive parts of the community. Nevertheless, rediversification can occur in the surviving tolerant communities (Barkay et al., 1985). The other is an increase in respiration per unit of microbial biomass (metabolic quotient; qCO2) which is thought to occur because stressed microorganisms direct a relatively larger amount of available energy into maintenance of various biochemical functions (Giller et al., 1998). Thus, in general heavy metal contamination of soils has been shown to result in a decline in microbial biomass C, an increase in metabolic quotient (Brookes, 1995; Giller et al., 1998), and shifts in bacterial community structure (Frostegard et al., 1996; Giller et al., 1998; Tom-Petersen et al., 2003). There are also often negative effects on soil enzyme activity (Belyaeva et al., 2005; Kizilkaya and Bayrakli, 2005). Enzyme reactions can be inhibited by heavy metals through a number of mechanisms including by (i) complexing with the substrate, (ii) combining with the protein-active groups of the enzymes, or (iii) reacting with the enzyme–substrate complex (Dick, 1997). In the case of biosolids application to soils, the addition of organic material increases organic matter content and consequently the size and activity of the microbial community also tend to be stimulated (Section 3.1.2). However, if biosolids contain a high heavy metal load then metal toxicities may have an inhibitory effect on soil microbial activity. Indeed, many workers have observed an inhibitory effect in soils where biosolids high in heavy metals have been applied and these negative effects can remain for decades after application (Giller et al., 1998; Stoven et al., 2005). Numerous short- and long-term studies have been carried out where biosolids contaminated with one or more heavy metals (or biosolids enriched with one or more heavy metals) have been applied to soils and the size and activity of the microbial community measured. Short-term incubation experiments have generally shown a reduction in microbial biomass C and N, usually an increase in metabolic quotient and a variable effect on enzyme activity (Bhattacharyya et al., 2008; Kao et al., 2006; Rost et al., 2001). Long-term (>8 years) field trials have shown similar results with a depression in microbial biomass C and microbial biomass C expressed as a percentage of organic C and an increase in metabolic quotient (Bhattacharyya et al., 2008; Chander and Brookes, 1991; Fliebßach et al., 1994; Stoven et al., 2005; Zhang et al., 2008). Zhang et al. (2008) sampled soils in fields that had been irrigated with heavy metal contaminated wastewater (polluted with Cd and to a lesser extent Zn and Cu) for
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30 years along a gradient of increasing total soil Cd content (1–4) (Table 4). Concentrations of extractable Cd, Cu, and Zn and metabolic quotient generally increased along the gradient while microbial biomass C declined (Table 4). Observed effects on soil enzyme activities have been variable with Bhattacharyya et al. (2008) observing reductions in glucosidase, urease, phosphatase, and sulphatase activities induced by high combined concentrations of Cd, Cr, Cu, and Pb, Zhang et al. (2008) finding dehydrogenase and phosphatase activities were not consistently affected by a combination of high Cd, Cu, and Zn (Table 4) and Stoven et al. (2005) finding dehydrogenase activity was decreased but that of phosphatase was unaffected by high combined concentrations of Cr, Cd, Cu, Hg, Ni, Pb, and Zn. Not only is the size and activity of the soil microbial community affected by heavy metal contamination originating from biosolids but also its composition is altered (Macdonald et al., 2007; Sandaa et al., 1999a,b). Bioluminescence-based bacterial and fungal biosensors can be used to assay the potential toxicity of water-soluble contaminants in soils and this technique was employed by Horswell et al. (2006) to determine the effects of Cu-, Ni-, and Zn-spiked biosolids on the microbial community in the litter layer of a forest soil. They found that increased Cu caused a decline in bioluminescence response of the fungal biosensor, increased Zn caused decline in response of the bacterial biosensor while increased Ni had little effect on either. In a 10-year field experiment where plots received different concentrations of biosolids spiked with a combination of Cd, Cu, Ni, and Zn, molecular techniques were used to show that significant differences, and decreased diversity, were induced in both bacterial (Sandaa et al., 1999a, 2001) and archaeal (Sandaa et al., 1999b) community structures. Using molecular techniques Macdonald et al. (2007) showed that in an 8-year study using Zn-spiked biosolids there were significant differences in microbial community structure for all groups investigated (bacteria, fungi, archaea, actinobacteria, and rhizobium/agrobacterium). Their results showed that fungi, and to a lesser extent archaea, were more negatively affected by Zn addition than was the bacterial community. Results from several long-term experiments have shown that Rhizobium leguminosarum, a N2-fixing symbiotic bacteria of white clover, is considerably more sensitive to the toxic effects of heavy metals than the host plants and that the host plant confers protection from metal stress to the rhizobium (Chaudri et al., 1993; McGrath et al., 1995). The toxic effect is due to toxicity to the free living rhizobium particularly in response to high Zn (Chaudri et al., 2008). Thus, the general effect of heavy metal contamination of soils induced by biosolids applications is a decrease in the size of the microbial community, an increase in metabolic quotient, a change in species composition, and often a decrease in activity of key enzymes involved in C, N, P, and S transformations. Such decreased enzyme activity will tend to reduce the turnover of C, N, P, and S in the soil. The potential effect of a change in
Table 4 DTPA-extractable Cd, Cu, and Zn, microbial Biomass C, metabolic quotient, and the activities of dehydrogenase and cellulose in soils on a gradient of increasing Cd loading from 30 years of irrigation with heavy metal-contaminated wastewater
Site
1 2 3 4
DTPA-extractable (mg kg 1) Cd
Cu
Zn
0.48 0.48 0.52 1.05
5.18 5.00 5.28 13.0
3.42 4.62 2.44 9.32
From Zhang et al. (2008); copyright Elsevier.
Microbial biomass C (mg kg 1)
Metabolic quotient (102 mg CO2–C h 1 mg 1)
Dehydrogenase activity (mg product kg 1 h 1)
Cellulase activity (mg product kg 1 h 1)
207 199 177 142
5.47 5.17 4.91 7.51
1.55 4.21 3.89 2.02
14.8 10.3 16.8 14.3
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species composition and loss of some microbial species is controversial. This is because there is a high degree of functional redundancy among soil microflora and functionally similar organisms can have different environmental tolerances (Nannipieri et al., 2003). Thus, as a stress is imposed on the soil, there will be a progressive extinction of sensitive species among a functional group; below a certain threshold it is speculated that there will be insufficient individuals to sustain a particular function (Giller et al., 1997). Such a situation does not appear to have occurred in biosolids-treated soils. With increasingly stringent regulations being enforced regarding the concentrations of heavy metals that can be released into sewerage systems, the negative effects of biosolids applications on soil microbial activity, induced by their heavy metal loads, is likely to decline over the ensuing years.
5.4. Plant response and metal uptake At agronomically realistic rates of biosolids application (e.g., 2–8 Mg ha 1), heavy metals do not normally represent a serious limitation to crop growth even though relatively large amounts of metals can be added to the soil; indeed as noted previously, the majority of experiments demonstrate a positive effect of biosolids application on crop growth ( Juste and Mench, 1992; Singh and Agrawal, 2008). For example, Juste and Mench (1992) reviewed a large number of field trials in the United States and Europe and concluded that phytotoxicity due to biosolids-borne metals was only rarely observed in grain crops. At one site, Cd toxicity, Ni toxicity, or the combined effects of Cd and Ni caused yield reductions in maize. At very high rates of biosolids application, metal toxicities are likely to occur. Berti and Jacobs (1996), for instance, applied large amounts of biosolids to croplands over a 9-year period (cumulative applications of 240–690 Mg ha 1) and recorded yield reductions in maize, sorghum, and soybean due to the combined phytotoxic effects of Zn and Ni. Leguminous crops are usually more sensitive to metal loadings in biosolids than nonlegumes (Giordano et al., 1975; McGrath et al., 1988). Such effects are explicable in terms of the detrimental effects of heavy metals on Rhizobium nodule function. There are a number of reasons for the low phytotoxic effect of biosolidsborne metals. These can include metal sorption by metal oxides and organic matter (present in both the biosolids and the soil), increased pH, formation of insoluble salts (e.g., with silicate, sulfate, and phosphate), and antagonistic effects of between biosolids metals (Bell et al., 1991; Emmerich et al., 1982; Juste and Mench, 1992). Despite this, heavy metal loadings are often considered the major potentially detrimental effect of land-applied biosolids on the environment. Not only do they accumulate in the soil but also phytotoxic effects on plants can occur. More concerning is the accumulation of metals in crops in edible plant parts. These aspects are considered below.
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5.4.1. Metal toxicity and tolerance Elevated concentrations of both essential (e.g., Cu, Zn) and nonessential (e.g., Cd, Pb, Hg) heavy metals in soils can inhibit plant growth. Toxicity is caused by a range of interactions at both the cellular and molecular levels (Clemens, 2006; Clemens et al., 2002; Hall, 2002; Shaw et al., 2006). It can result from binding of metals to sulfhydryl groups in proteins leading to an inhibition of activity or disruption of structure, from displacement of an essential element resulting in deficiency effects or from stimulation of the formation of free radicals and reactive oxygen species resulting in oxidative stress (Dietz et al., 1999; Hall, 2002; Van Assche and Clijsters, 1990). Metal tolerance is ubiquitous and the main components of metal homeostasis in plants involve transport, chelation, and sequestration processes (Clemens, 2001, 2006; Clemens et al., 2002; Hall, 2002). The regulated activities of these processes ensure proper delivery and distribution of metals at both the organizational and cellular levels (Clemens, 2001). Loss of one of these critical processes (e.g., synthesis of chelating agents for Cd within cells) leads to genotypes that are more sensitive (hypersensitive) than wild-type plants (Howden et al., 1995). By contrast, some plant species and genotypes can grow naturally in soils containing concentrations of metals that would be toxic to the majority of plants. These hypertolerant species possess naturally selected higher levels of tolerance. Potential mechanisms of detoxification are primarily involved in avoiding the buildup of toxic concentrations at sensitive sites within the cell (Hall, 2002) thus preventing the damaging effects outlined above. Some plants not only tolerate high concentrations of metals but also hyperaccumulate them. Hyperaccumulator is a term used to describe plants capable of accumulating more than 1000 mg g 1 Ni, Co, Cu, Pb, for Cd 100 and Zn 10,000 mg g 1 (Love and Babu, 2006). Metal hyperaccumulation is a rare phenomenon limited to about 400 different species belonging to a wide range of taxa (Baker and Brooks, 1989). Hyperaccumulation is mainly observed with Ni, Zn, Co, and Se but there are also reports of it for Pb, Cd, and As (Baker and Brooks, 1989). The existence of hyperaccumulator plants is the basis for the phytoremediation technique in which plants are used to absorb metals and hence remove them from contaminated soils (Chaney et al., 1997). Possible strategies of heavy metal tolerance in plants are diverse and can be extracellular, at the plasma membrane, or intracellular. Extracellular mechanisms include the effects of ectomycorrhizae ( Jentsche and Godbold, 2000) and arbuscular mycorrhizae (Kaldorf et al., 1999; Leyval et al., 1997) in restricting metal movement into the plant host roots. This has been attributed to absorption of metals by the hyphal sheath, chelation by fungal exudates, adsorption onto external mycelium, and reduced access to the plant root cytoplasm ( Jentsche and Godbold, 2000; Leyval et al., 1997). Root exudates (e.g., organic acids such as citrate, malate, and oxalate) have
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also been suggested as agents for detoxification through chelation of metals in the rhizosphere (Dong et al., 2007). In solution culture experiments, addition of a range of organic compounds, such as organic acids, amino acids, and peptides, to the growing medium can alleviate heavy metal toxicities (Hall, 2002) and the Ni chelating ability of citrate and histidine in root exudates has been associated with its nonaccumulation in species of Thlaspi (Salt et al., 2000). Another possible mechanism is the accumulation of heavy metals in root cell walls. Indeed, in many plants that accumulate heavy metals, 60–80% of metals (e.g., Cd, Cu, Zn, Pb, Co, Ni) accumulate in roots and root cell walls are the main region of accumulation (Liu et al., 2007a,b; Nishizono et al., 1987; Sousa et al., 2008; Zornoza et al., 2002). In some cases, this accumulation in the cell wall may reflect active efflux of metals from root cells through the plasma membrane (see below). Furthermore, for some plants (e.g., lettuce) that accumulate metals (e.g., Cd) in leaves, the Cd accumulates principally in the cell walls (Ramos et al., 2002) suggesting it has been deposited there by active efflux across leaf cell plasma membranes. There are three suggested mechanisms at the plasma membrane. Firstly, plasma membrane function may be rapidly affected by high concentrations of metals with increased leakage of solutes (e.g., K) occurring (Hall, 2002). Tolerance could involve protection of plasma membranes against metal damage or improved repair mechanisms (Hall, 2002). The cell membrane could also play an important role in reducing entrance of metals into cells (Clemens, 2006). However, this strategy is thought to be of minor significance since many essential heavy metals must be taken up from the soil for various metabolic functions and the chemical properties of nonessential metals are similar to those of essential ones and their uptake is thought to occur through the same processes/mechanisms (Shaw et al., 2006). An alternative strategy is active efflux of toxic metal ions. In bacteria, most resistance systems are, in fact, based on energy-dependent efflux of toxic ions either by ATPases or chemostatic cation/proton antiporters (Silver, 1996). It seems likely that such a mechanism also occurs in higher plants (Hall, 2002). It is generally accepted that the principal mechanism of detoxification and tolerance is achieved by sequestration of metals inside cells (Shaw et al., 2006). Chelation of metals in the cytosol by organic ligands is an important intracellular mechanism of detoxification and tolerance. Chelates bind with metals and buffer cytosolic ionic metal concentrations. Carboxylic acids (e.g., citrate, malate, oxalate) and amino acids such as histidine are potential ligands (Clemens, 2001) and metallothioneins (low molecular weight, cysteine-rich proteins) may also play a role (Cobbett and Goldsbrough, 2002). Nonetheless, the most studied ligands are phytochelatins which are metalbinding peptides synthesized in plants in response to exposure to metal ions (Cobbett and Goldsbrough, 2002; Rauser, 1999). Hg, Cd, As, and Cu show
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the greatest tendency to induce phytochelatins and Zn, Pb, Ni, and Se have a lesser effect (Shaw et al., 2006). For Cd, the phytochelation pathway consists of two parts. Firstly, metal-activated synthesis occurs and metals in the cytoplasm are complexed. The second stage is active efflux of the metal– phytochelatin complex across the tonoplast and sequestration in the vacuole. The vacuole is known to be the site of accumulation of metals such as Zn and Cd (Ernst et al., 1992). As already noted, active efflux of metals across the plasma membrane with their accumulation in cell walls may be another important mechanism. It is evident that the general strategy of plants is to avoid toxicity by minimizing the buildup of excess metals in the cytosol. This is achieved through the use of a variety of mechanisms. It is likely that a specific mechanism, or combination of mechanisms, is employed for a specific metal in particular plant species. In situations where soils have become highly contaminated with heavy metals, the use of tolerant species/cultivars that employ these mechanisms can be an important consideration. However, since heavy metal toxicities in plants are rarely encountered in biosolids-amended soils, this aspect is of minor importance to land application of biosolids. Accumulation of heavy metals in plants and plant parts can, nevertheless, be of concern. 5.4.2. Metal accumulation in plants One of the major concerns regarding land application of biosolids is that heavy metals may accumulate in plants and subsequently enter the food chain and/or have toxic effects on humans or grazing animals ingesting them. Indeed, the main route of entry of metals into human food chain is their accumulation in edible portions of crop plants and this can pose a potential threat to human health (McLaughlin et al., 1999). Chaney (1980) classified metals into four groups when considering their potential health risks. Group 1 (Ag, Cr, Sn, Ti, Y, and Zr) were considered to pose little risk because their low solubility in soils results in them not being taken up by plants to any great extent. Group 2 (As, Hg, and Pb) are also strongly adsorbed to soil surfaces and while they may be taken up by plants they are not readily translocated to edible portions. They therefore pose little risk to human health. Group 3 (Cu, Mn, Ni and Zn) are accumulated in plants but are phytotoxic at concentrations that pose little risk to human health. Members of Group 4 (Cd, Co, and Se) can pose human health risks at plant tissue concentrations that are not phytotoxic. In general, metals that have most commonly given rise to human health concerns in relation to food safety are Cd, Hg, Pb, As, and Se (Reilly, 1991). McLaughlin et al. (1999) considered that Cd and Se are of greatest concern in relation to terrestrial food chain contamination. In particular, excessive human intake of Cd is of concern since it accumulates in the body and impairment of kidney function is the main adverse effect.
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Concentrations of extractable heavy metals in soils are likely to give the best estimate of metal phytoavailability. Even so, at a broad level, metal concentrations in plants grown on biosolids-treated soils are a function of the annual biosolids loading rate ( Juste and Mench, 1992). Cumulative metal input to the soil is also a major factor determining plant tissue metal concentrations (Chang et al., 1997; Soon et al., 1980). Nonetheless, although plant metal concentrations generally increase with increasing biosolids rates, concentrations in plant tissues often exhibit a plateau response at high loadings (Basta et al., 2005). Indeed, a number of studies have showed that metal uptake reaches a maximum with increasing biosolids application for wheat, maize, and a range of vegetables (Barbarick et al., 1995; Brown et al., 1998; Logan et al., 1997, Sukkariyah et al., 2005a). Although a number of explanations have been forwarded for this (Basta et al., 2005, McBride, 1995) the most likely explanation is that metal availability in biosolids-treated soils shows a plateau at high loadings corresponding to metal availability in the biosolids (Basta et al., 2005; Corey et al., 1987). Plant tissue metal concentrations will, however, not only be related to biosolids application rate but will also be both metal and plant specific. That is, the mobility of individual metals in plants differs and the ability of individual plant species and cultivars to absorb and translocate metals also differs. The transfer coefficient (TC) (the concentration of metal in the plant to that in the soil) gives an indication of its mobility. From a number of studies, Antoniadis et al. (2006) calculated TC values of Cr 0.0005, Pb 0.02, Ni 0.06, Cu 0.21, Cd 0.94, and Zn 1.05. Similarly, Alloway (1995) also noted that TC values were highest for Cd and Zn (1–10) and least for Cr and Pb (0.01–0.10). In a review of a number of long-term (>10 years) biosolids trials, Juste and Mench (1992) concluded that Cd, Ni, and Pb were the most likely to accumulate in plants while for Cr and Pb, plant uptake was insignificant. Generally, metals are present in highest concentrations in roots and lowest concentrations in seeds (Love and Babu, 2006). However, Cd can accumulate in leaves so on Cd-contaminated soils, leafy vegetables can be as much, or more, of a risk than seed or root crops (Alloway and Jackson, 1991). The propensity for plants to accumulate and translocate metals to edible and harvestable parts depends greatly on plant species as well as agronomic, climatic, and soil factors. Different plant species and cultivars are known to accumulate different quantities of metals when grown in the same contaminated soil. Antoniadis et al. (2006) broadly classified crop species in relation to metal accumulation. Crops with a high plant uptake included lettuce, spinach, celery, kale, ryegrass, sugarbeet, and turnip while the low uptake group included potato, maize, peas, leek, onion, tomato, and berry fruit. Nonetheless, plant species differ in their capacity to accumulate individual heavy metals. For example, on biosolids-amended soils Davis
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and Carlton-Smith (1980) found the trend for metal accumulation was tobacco > lettuce > spinach > celery > cabbage for Cd; kale > ryegrass > celery for Pb; sugarbeet > some varieties of barley for Cu and sugarbeet > mangold > turnip for Zn. For Cd, Alloway et al. (1990) showed Cd accumulation followed the order: lettuce > cabbage > radish > carrots. Maize cultivars have been shown to differ considerably in their uptake of both Cd and Zn (Hinesly et al., 1982; Logan and Miller, 1985). For root crops grown in biosolids-amended soils, it may be important to wash of all adhering soil (or peel them) to avoid soil contamination with heavy metals. Indeed, where crops are being grown on biosolids-amended soils, routine monitoring of heavy metal concentrations in edible plant parts is an important consideration. Many countries have set limits for metal concentrations in foods and it is important that these are not exceeded.
5.5. Ingestion by animals Pasture is an attractive option for land application of biosolids since there is greater accessibility for a greater proportion of the year compared to arable land. Nevertheless, a major concern is transfer to, and accumulation of, heavy metals in the grazing animal and the human food chain (Hill, 2005; Hillman et al., 2003). The three main pathways by which this may occur are (i) transport of metals from soil to plants and then ingestion by animals (biosolids–soil–plant–animal), (ii) direct contamination of plants subsequently fed to animals (biosolidsplant–animal), and (iii) ingestion of contaminated soil by grazing animals (biosolids–soil–animal) (Fries, 1996). Accumulation of metals into foliage of grasses is generally low since metals usually accumulate in the roots (Love and Babu, 2006). Thus, pathway (i) is likely to be of minor importance. However, where surface application of biosolids is practiced, adhesion of biosolids-derived metals to pasture herbage occurs (Aitken, 1997; Klessa and Desira-Buttegieg, 1992). The greatest intake will occur when biosolids are applied directly to established pasture and animals have immediate access. Intake will be reduced if access to pasture is delayed so there is time for biosolids to be washed off leaves, foliar concentrations are reduced by dilution through plant growth and the biosolids can move onto/into the soil surface (Aitken, 1997; Hillman et al., 2004). Herbage may also become contaminated through rain splash or from deposition of dust (Aitken, 1997). There are waiting periods imposed in most countries/states/regions following surface application of biosolids to pastures before land can be grazed again. These are generally formulated to minimize the risk of exposure of grazing animals to pathogens rather than to chemical contaminants and can range from as short as 3 weeks in the United Kingdom, Spain, and the Netherlands to 1 year in Denmark (Hill, 2005).
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When pasture is the main diet of grazing animals, the chance for animal ingestion of biosolids-borne metals is greatest since soil ingestion becomes an additional important pathway. Research has shown that when pasture is the sole animal feed source, soil ingestion is generally inversely related to the availability of forage (Beyer and Fries, 2003). Lowest soil ingestion rates (1–2% of dry matter intake) occur in spring when grass growth is greatest while when forage is sparse (autumn and winter) soil intake can be as great as 18%. For sheep that graze close to the ground soil ingestion rates of as high as 30% have been reported on occasions (Abrahams and Steigmajer, 2003). In addition, in winter, poaching, or pugging of pasture can also occur (Drewry et al., 2008). This is when the hooves of grazing sheep and cattle trample the foliage into muddy soil thus causing soil contamination of forage. For grazing sheep and cows (fed no additional forage) average annual soil ingestion commonly amounts to 4.5–5.1% of dry matter intake (Beyer and Fries, 2003). In general, soil/biosolids ingestion is the main pathway for transfer of metals from pasture to the grazing animal (Beresford and Howard, 1991; Hillman et al., 2003; O’Riordan et al., 1994; Rafferty et al., 1994). There is differential accumulation of individual metals in tissues of grazing ruminants with Cd and Pb accumulating in the liver and kidney to a greater extent than muscle and fat tissues (Hillman et al., 2003). Cu tends to accumulate in the liver while Zn and Fe have no clear patterns of accumulation. The percentage of metals retained is generally low (Baxter et al., 1982; Johnson et al., 1981). For example, Johnson et al. (1981) fed steers a diet containing 11.5% biosolids for 106 days. Retention of ingested metals averaged 0.09%, 0.06%, and 0.30% for Cd, Hg, and Pb, respectively, and no retention of Cu and Zn was detected. Nonetheless, this low percentage retention increased tissue Cd, Hg, and Pb concentrations in liver and kidney by 5–20-fold. Overall, the risk to the human food chain from biosolids-derived heavy metals via grazing animals is considered low (Hillman et al., 2003).
6. Organic Contaminants In the last 50-years production of synthetic organic chemicals for industrial and domestic uses has increased enormously. For example, between 1950 and 1970, production increased from 7 million tons to 63 million tons (Rogers, 1996). As a consequence, the occurrence and concentration of organic contaminants in effluents, sewage, and biosolids has also increased. The presence and level of organic contaminants in biosolids depends greatly on the quality of the wastewater, the different local point sources, the physicochemical properties of particular organic compounds,
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and operational parameters of the wastewater treatment plant. Concentrations of organic pollutants are generally greater in industrial sewage than in domestic effluent (Bodzek and Janoszka, 1999; Smith, 2000). Over 300 organic chemicals from a diverse range of classes of compounds have been identified in biosolids and their concentrations vary from the pg kg 1 to the g kg 1 level ( Jacobs et al., 1987; Smith, 2000). Although water treatment plants were designed primarily to remove organic matter, and the mechanisms of degradation of bulk organic components are well studied and understood, the processes by which synthetic organics are degraded have received relatively little study. An organic contaminant could undergo a number of processes including (i) sorption to solid surfaces, (ii) volatilization, (iii) chemical degradation, and (iv) biodegradation. Generally, the more hydrophobic a compound is, the more susceptible to accumulation onto sewage sludge particles it will be. During primary sedimentation, hydrophobic contaminants may partition onto settled primary sludge solids. The tendency to accumulate in sludge solids can be assessed using the octonol–water partition coefficient (Kow) (Byrns, 2001). Contaminants with log Kow values less than 2.5 have low sorption potential and those with values greater than 4 have high sorption potential. Similarly, the tendency for volatilization can be gauged using Kow and Henry’s Law constant (Rogers, 1996). Although there is a scarcity of data on the behavior of organic contaminants during the water treatment and sludge digestion processes, some generalizations can be made (Rogers, 1996; Scow, 1982). For example, molecules with highly branched hydrocarbon chains are generally less susceptible to biodegradation than unbranched compounds and short chains are not as quickly degraded as long chains. In addition, unsaturated aliphatic compounds are generally more susceptible to degradation than saturated analogs. In general, due to their characteristically low water solubility and high lipophilicity, organic contaminants partition into sludges during sedimentation resulting in their accumulation in biosolids in concentrations several orders of magnitude greater than influent wastewater concentrations (Bhandari and Xia, 2005). Some organic contaminants are known, or are suspected to be endocrine disrupting chemicals (EDCs) and this has magnified interest in their presence in sewage, their fate during waste water treatment, and their possible presence in biosolids. The endocrine system is found in nearly all animals and is a complex network of glands that discharge hormones that regulate the body’s functions including growth, development, and maturation as well as the way various organs operate. EDCs possess the ability to alter or disrupt endocrine system function mimicking, antagonizing, or interfering with biosynthesis or biodegradation of endogenous hormones (Sonnenschein and Sato, 1998). Indeed, there is growing concern about the apparently increasing incidence of reproductive disorders and abnormal
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development in wildlife and reduced fertility in human males, problems that may be caused by EDCs that have been released anthropogenically into the environment (Ashby et al., 1997; Sonnenschein and Soto, 1998). A wide range of chemicals have been found, or are suspected to be capable of disrupting the endocrine system (Birkett, 2003a). These include: (i) persistent organochlorines and organohalogens (e.g., PCBs, dioxins, furans, brominated fire retardants), (ii) pesticides (e.g., DDT, atrazine, vinclozolin, TBT), (iii) alkyl phenols (e.g., nonylphenol, octylphenol), (iv) phytoestrogens (e.g., isoflavoids, lignins, B-sitosterol), and (v) natural and synthetic hormones (e.g., b-estradiole, ethynylestradiol). The last group of chemicals (above) is known as estrogenic EDCs and has received particular attention in recent times. Estrogens are a group of female sex hormones involved in the estrous cycle. They are excreted in urine and eliminated in feces and both naturally occurring estrogens and xenoestrogens (man-made analogs) have been identified in sewage, biosolids, and waste water treatment plant effluents (Birkett, 2003b). Analysis of organic contaminants in biosolids presents a number of challenges. The organic molecules are physically and/or chemically bound to the biosolids solid phase matrix and must be extracted with relatively harsh reagents/methods prior to analysis. Because extraction yields a complex mixture of organic compounds, the various organic fractions need to be segregated (cleaned) prior to analysis. Furthermore, concentrations of contaminants are often low, and sometimes below the limits of current analytical techniques. As a result, preconcentration is often necessary prior to analysis. Traditional methods entail soxhlet extraction, concentration using rotary evaporation and cleanup by column chromatography (Rogers, 1996). Contemporary methods, often preferred today, involve pressurized liquid extraction (PLE) followed by combined cleanup and concentration using solid phase extraction (SPE) (Cirelli et al., 2008; Jones-Lepp and Stevens, 2007). Quantification of organic compounds present is performed by one of a number of powerful chromatographic methods such as high performance liquid chromatography (HPLC), gas chromatography (GC), liquid chromatography (LC), and superficial fluid chromatography (SFC) and these are often coupled with molecule analysis by mass spectrometry (MS). In recent times, as methods of extraction, cleanup and analysis have become more rapid, an increasing number of surveys have reported the concentrations of various organic contaminants in wastewater and biosolids samples. However, as yet, there are only a few studies where the fate of such contaminants during wastewater treatment processes has been reported. Similarly, very little information is available on the behavior and degradation of biosolids-borne organic contaminants in soils following land application.
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Organic contaminants certainly have the potential to adversely impact on the soil/crop/animal system receiving land application of biosolids (Bhandari and Xia, 2005). Nevertheless, the relative risk of organic chemicals in biosolids is generally considered to be minimal due to the relatively low concentrations present and the many transformations (especially biodegradation) that can occur in soils (Epstein, 2003).The European Union has proposed limit values for several organic contaminants (or groups of contaminants) in biosolids and several European countries (e.g., Sweden, Germany, Denmark) have enforced a number of them. The European Union limits are for sum of halogenated organic compounds, linear alkylbenzene sulfonates, di-(ethylhexyl) phthalate, nonylphenol and nonylphenol ethoxylates, polynuclear aromatic hydrocarbons, polychlorinated biphenyls, and polychlorinated dibenzo-p-dioxins and -furans. Below, the most frequently detected organic contaminants in biosolids are considered. Their origin in sewage, potential toxicity, fate during wastewater treatment, and persistence or otherwise in the soil following land application are considered.
6.1. Organic compounds present 6.1.1. Phthalic acid esters (PAEs) These materials are manufactured in large quantities and are used predominantly as plasticizers to make plastics more flexible (Bhandari and Xia, 2005). The large majority of phthalates are used to plasticize polyvinyl chloride (PVC) to produce products ranging from kitchen and bathroom flooring to medical tubing, toys, footwear, electrical cables, packaging, and roofing. Di-(2-ethylhexyl) phthalate (DEHP) is the most widely used phthalate. Other common PAEs include Di-n-octyl phthalate (DnOP), butylbenzyl phthalate (BBP), Di-n-butyl phthalate (DnBP), diethyl phthalate (DEP), and dimethyl phthalate (DMP). Phthalates are used in non-PVC applications such as paints, rubber products, adhesives, cosmetics and toiletries (e.g., nail polish, perfumes), epoxy resins, adhesives, and printing inks. The widespread industrial and domestic use of products containing phthalates results in large amounts being washed down drains and into sewage systems (Marttinen et al., 2003; Palmquist and Hanaeus, 2005). Some PAEs are considered to be EDCs and/or carcinogens (Birkett, 2003a). Indeed, DEHP is considered to be an EDC (Hoyer, 2001) and has been shown to cause malformations of the reproductive system in male rats (Gray et al., 1999). BBP and DBP have the strongest estrogenic potencies (Harris et al., 1997). A wide range of bacteria can degrade PAEs under both aerobic and anaerobic conditions (Staples et al., 1997). The extent of biodegradation during anaerobic digestion is apparently related to the size of the alkyl side chain and compounds with the larger C-8 side chain are much more
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resistant to microbial attack ( Jianlong et al., 2000; Staples et al., 1997). As a result, the higher molecular mass PAEs such as DEHP and DnOP are considerably more persistent to anaerobic microbial degradation than lower molecular mass compounds (e.g., DPP and DEP). DEHP is generally considered persistent during sewage treatment (especially with anaerobic sludge digestion) (Bhandari and Xia, 2005; Scrimshaw and Lester, 2003). Total concentrations of PAEs in biosolids typically range from 12 to 200 mg kg 1 (Amir et al., 2005c; Cai et al., 2007b; Gibson et al., 2005; Harrison et al., 2006; Marttinen et al., 2003; Oliver et al., 2005). DEHP is consistently the most abundant in biosolids usually accounting for 25–95% of total PAEs present (Amir et al., 2005c; Cai et al., 2007b; Gibson et al., 2005; Oliver et al., 2005). Other PAEs such as DnOP, BBP, DnBP, DEP, and DMP are commonly present in biosolids in low concentrations (<10 mg kg 1) (Cai et al., 2007b; Zheng and Zhou, 2006). Thus, land application of biosolids generally introduces PAEs to the soil environment. Under aerobic soil conditions PAEs are, however, readily microbially degraded ( Jianlong et al., 1997, 2004; Shanker et al., 1985; Wang et al., 1997) with the less degradable high molecular mass compounds having longer half-lives. Results of Jianlong et al. (2004) are shown in Fig. 5. Degradation of PAEs in soil (added at 100 mg of phthalate g 1) decreased with increasing alcohol chain length with DMP being degraded completely within 15 days while less than 50% of DOP was degraded after 30 days. 100
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Figure 5 Degradation of four phthalate esters in a soil after addition at 100 mg g 1: (▪) DOP, (□) DBP, (△) DEP, (▲) DMP. From Jianlong et al. (2004); copyright American Chemical Society.
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6.1.2. Polycyclic aromatic hydrocarbons (PAHs) PAHs are a complex group of organic compounds containing two or more fused aromatic rings in linear, angular, and cluster arrangements that contain only C and H atoms. PAHs occur in oil, coal, and tar deposits. They are also produced as by-products of incomplete combustion of C-containing fuels such as wood, coal, diesel oil, fat, and tobacco (Wild and Jones, 1995). Important combustion processes include food preparation, internal combustion engines in motor vehicles, house fires, coal-fired power stations, cement works, iron and Al smelters as well as volcanoes, and forest fires. Thus, PAHs enter the environment mostly from releases to the air and then direct aerial fallout. They enter the waste water system from a multitude of sources including runoff from land, from roads containing car exhaust particles, and direct discharge of petroleum products from garages. PAHs are hydrophobic compounds and their persistence within ecosystems is chiefly due to their low water solubility and their tendency to become adsorbed to solid particles (Cerniglia, 1992). In addition, the fused aromatic rings possess dense clouds of P electrons on both sides of the ring structures making them resistant to nucleophilic attack ( Johnsen et al., 2005). Due to this effect, the resonance energy of PAH compounds (a measure of the extra stability of a conjugated system compared to the corresponding number of double bonds) increases with increasing number of aromatic rings present. In general both water solubility and bioavailability of PAHs decrease and lipophilicity increases almost logarithmically with increasing molecular mass ( Johnsen et al., 2005; Zhang et al., 2006). Due to their toxic, mutagenic, estrogenic, and carcinogenic properties, 16 PAH compounds have been identified as priority pollutants by the USEPA and seven of them are considered carcinogenic (IARC, 1983). Due to their lipophilicity, PAHs rapidly become associated with solid sludge particles during waste water treatment and, as a result, significant quantities are typically present in biosolids. Indeed, degradation of PAHs under anaerobic conditions is generally slow (Zhang et al., 2006) so that anaerobic sludge digestion is not very effective at removing them. Nevertheless, some degradation of PAHs (particularly 2- and 3-ring compounds) can occur anaerobically under sulfate-reducing and denitrifying conditions using NO3 and SO42, respectively, as electron acceptors (Christensen et al., 2004; Johnsen et al., 2005; Zhang et al., 2006). The mean concentration of total PAHs in biosolids from industrialized countries is typically in the range of 1–100 mg kg 1 (Blanchard et al., 2004; Dai et al., 2007; Harrison et al., 2006; Stevens et al., 2003, Villar et al., 2006). Concentrations of individual PAHs vary markedly between wastewater treatment plants and regions although the dominant compounds are usually those with 3, 4 or 5 rings (Bodzek and Janoszka, 1999; Cai et al., 2007b; Oleszczuk, 2007). The European Union proposed that for land application, the sum content of
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11 PAHs in biosolids should not exceed 6 mg kg 1 (CEC, 2000). In biosolids from industrial countries this sum can often exceed the limit (Blanchard et al., 2004; Cai et al., 2007b; Harrison et al., 2006; Oleszczuk, 2007). Land application of biosolids inevitably elevates concentrations of soil PAHs and their slow degradation follows (Beck et al., 1995; Oleszczuk, 2006). It is thought that the strong binding of PAHs to biosolids organic matter initially limits their decomposition. However, as the sludge organic matter begins to breakdown, sorptive processes are weakened and PAH degradation proceeds (Baran and Oleszczuk, 2003; Oleszczuk, 2006). During decomposition, there is a rapid disappearance of low molecular mass PAHs and a slower degradation of higher molecular mass compounds (Beck et al., 1995; Oleszczuk, 2006). After cessation of biosolids applications at two long-term monitoring sites, Beck et al. (1995) observed 90% of total PAHs had been lost from soil at one site and about 65% at the other. Halflives ranged from 2 years for naphthalene to over 7 years for fluoranthene and over 9 years for benzol[ghi]perylene and coronene. PAH degradation is greater under arable cropping, with tillage (which stimulates organic matter decomposition) than under undisturbed soils (pasture, trees) (Oleszczuk, 2006; Saison et al., 2004). Aerobic composting of biosolids prior to land application can substantially lower PAH concentrations (Amir et al., 2005d; Cai et al., 2007b; Moeller and Reeh, 2003; Oleszczuk, 2007). Cai et al. (2007c), for example, showed that 56 days composting resulted in removal rates of 64–94%. Removal rates are in the same order for 2, 3, 4, 5, and 6 ring PAHs (Cai et al., 2007c; Oleszczuk, 2007). 6.1.3. Chlorobenzenes (CBs) Chlorobenzenes are a group of cyclic aromatic compounds in which one or more hydrogen atoms have been replaced by a chlorine atom. There are 12 different CBs: monochlorobenzene (MCB), dichlorobenzene (DCB) (three isomers), trichlorobenzene (TCB) (three isomers), tetrachlorobenzene (TCB) (three isomers), pentachlorobenzene (PeCB), and hexachlorobenzene (HCB). CBs (particularly 1,3-DCB, TCBs, and HCB) are used as intermediates in the synthesis of pesticides and other chemicals. 1,2-DCB is used in paintstrippers, engine cleaners, and other solvents, TCBs and PeCBs are used as components of dielectric fluids, TCBs are used as solvents and degreasers and 1,4-DCB is widely used as a toilet deodorant. DCBs, 1,2,4-TCB and HCB have been classified as priority pollutants by both USEPA and the European Union and some CBs (e.g., HCB) are considered as carcinogens ( Jones and Wild, 1991; Wang et al., 1995). CBs are a major group of organics found in biosolids (Rogers, 1996; Wang and Jones, 1994a). Concentrations vary significantly between wastewater sources, sludge type, and treatment technique but are generally higher in biosolids derived from industrial than domestic sewage sources (Rogers
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et al., 1989). Typically total CBs in biosolids range in concentration between 0.1 and 40 mg kg 1 although concentrations as high as 2000 mg kg 1 have been recorded (Beck et al., 1995; Cai et al., 2007b; Harrison et al., 2006; Rogers et al., 1989; Smith, 2000; Wang et al., 1995). In general, DCBs are the most commonly detected and are found in highest concentrations (Harrison et al., 2006; Rogers et al., 1989; Wang et al., 1995) although in a range of Chinese biosolids samples, Cai et al. (2007b) detected TCBs and HCB in higher concentrations than DCBs. Very little is known about the fate of CBs during wastewater treatment. Katsoyiannis and Samara (2004), however, recorded 91% removal of HCB from the aqueous phase in a sewage treatment plant in Greece. Henry’s law constants for CBs suggest that they are likely to be volatilized from aquatic systems. The solubility of CBs in water is, however, low and decreases with increasing chlorination and the octanol to water coefficient increases with increasing chlorination. Thus, CBs are strongly sorbed to organic matter and become associated with sludge during the sedimentation phases of wastewater treatment (Beck et al., 1995). They are, therefore, present in biosolids. CBs can be degraded aerobically by a consortium of bacteria via oxidative dechlorination, followed by ring fission and mineralization (Wang and Jones, 1994a). Less chlorinated CBs are more readily biodegraded. Biodegradation has also been reported under anaerobic conditions (Yuan et al., 1999) but at a much slower rate. Thus, during anaerobic sludge digestion, CB degradation is probably slow (Rogers, 1996). Once introduced to the soil by land application of biosolids, volatilization is thought to be the major loss mechanism for CBs (Wang and Jones, 1994a,b; Wang et al., 1995). Wang and Jones (1994b) showed the half-life for CBs added in biosolids to soil ranged from 13 to 209 days and these increased with increasing chlorination of individual CBs. Wang et al. (1995) showed that only about 10% of added CBs became recalcitrant in soils (i.e., became strongly adsorbed to soil constituents). HCB was found to be the most persistent CB in soils (Beck et al., 1995; Wang et al., 1995). 6.1.4. Polychlorinated biphenyls (PCBs) PCBs consist of a biphenyl ring (two benzene rings) with 10 positions where chlorine substitution may occur. There are 209 possible PCB congeners and most PCB mixtures consist of about 130 of these. Until the 1960s PCBs found wide use as coolants and insulating fluids for transformers and capacitors, stabilizing additives in flexible PVC coatings of electrical wiring and electronic components, pesticide extenders, adhesives, wood floor finishes, paints, and printing inks. However, because PCBs have been found to be persistent organic pollutants that bioaccumulate in animals, and they are EDCs (Birkett, 2003a), industrial usage of PCBs has largely been curtailed since the 1970s. Nonetheless, they still remain a major class of EU priority pollutants (Rogers, 1996).
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PCBs enter sewage effluent streams mainly via atmospheric deposition and catchment runoff. Total PCB concentrations in biosolids commonly range from 20 to 2000 mg kg 1 (Alcock and Jones, 1993; Blanchard et al., 2004; Eljarrat et al., 2003; Frost et al., 1993; Katsoyiannis and Samara, 2004; McGrath et al., 2000, Stevens et al., 2003). It has been proposed by the European Union that the sum of seven congeners (28, 52, 101, 118, 138, 153, and 180) should not exceed 800 mg kg 1 (CEC, 2000) and often EU PCB levels in biosolids are below this level (Alcock and Jones, 1996, Berset and Holzer, 1999; Katsoyiannis and Samara, 2004; Stevens et al., 2003). Indeed, the concentrations of PCBs in biosolids (Blanchard et al., 2004), and in soils (Alcock et al., 1993), have generally been decreasing over the last 20 years as PCB use has declined. PCBs exhibit a wide range of toxic effects which may vary depending on the specific PCB being considered (Kannan et al., 2000; Masuda, 2005). Many are considered to be EDCs (Raychoudhury et al., 2000) and they are also carcinogens (Knerr and Schrenk, 2006; Ludewig et al., 2008). Because of their lipophilic and hydrophobic properties, PCBs which enter wastewater treatment plants tend to be adsorbed to particulate organic material and are removed during sedimentation. Removal efficiencies typically range from 40% to 80% (Blanchard et al., 2001, 2004) with about 50% of that removed during primary sedimentation and the rest by secondary sedimentation. Removal efficiency generally increases with increasing chlorination level since the highly substituted PCBs are more lipophilic (Beck et al., 1996). As a result, it is the higher chlorinated congeners that are found in the highest concentrations in biosolids. Both Alcock and Jones (1993) and Stevens et al. (2003) found that congeners 28, 52, 101, 138, 153, and 180 were most prevalent in UK biosolids. Although anaerobic cultures have been shown to have the capacity for reductive dehalogenation of PCBs (Mohn and Tiedje, 1992), very little degradation is observed during anaerobic sludge digestion (Buisson et al., 1990). Following biosolids application to soils, there is a slow loss of PCBs. In a long-term study, Alcock et al. (1995) found that total PCB concentrations declined exponentially over a 31-year period (since the last biosolids application) but sludge-amended plots still contained five times more PCBs than the control. They also showed that the 3/4-Cl congeners were lost more rapidly than the 5-Cl homologues and above. Alcock et al. (1993) suggested that volatilization is the major loss mechanism of PCBs from soils since aerobic biodegradation is characteristically slow. 6.1.5. Organochlorine pesticides (OCPs) The term organochlorine refers to a wide range of organic compounds which contain chlorine. The organochlorine pesticides are a diverse group of synthetic chemicals that have mainly been used against insect pests of agricultural crops and diseases of humans and domestic animals that are
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carried by insects (Lal and Saxena, 1982). The most well known OCPs include, DDT, DDD, kelthane, chlorobenzilate, chloropropylate, methoxychlor, aldrin, dieldrin, heptachlor, lindane, endosulfan, isodrin, isobenzan, endrin, chlordane, toxaphene, mirex, and kepone. Their use has been minimized or terminated in most technologically advanced countries because of their persistent nature, susceptibility to biomagnification and toxicity to higher animals (Durdane, 2006; Jorgenson, 2001; Rosario et al., 2007). Some OCPs such as DDT, toxaphane, and methoxychlor are known to be strong EDCs (Birkett, 2003a). Some are also carcinogenic and/or have immunosuppressant properties (Belpomme et al., 2007). OCPs are hydrophobic and associate strongly with the solid phase of raw sewage. They are therefore predominantly removed during sedimentation with a removal efficiency of between 30% and 95% (Garcia Gutierrez et al., 1982, 1984; McIntyre et al., 1981). OCP concentrations have been declining in the environment in recent years because of restrictions regarding their use and as a consequence individual compounds are commonly present in biosolids in only very low concentrations and often some are not detectable (Berset and Holzer, 1999; Falandysz and Strandberg, 2004; Katsoyiannis and Samara, 2004; McIntyre and Lester, 1984; Stevens et al., 2003; Wang et al., 2007; Webber et al., 1996). For example, in a study of Biosolids from Switzerland, Berset and Holzer (1999) observed the most frequent compounds found were DDT and its reaction products (DDD and DDE), lindane, aldrin, heptachlor epoxide, and endosulfan. When present, concentrations of DDT, DDD, DDE, and aldrin ranged from 7.5 to 15.5, 15.4 to 47.9, 36.6 to 97.2, and 4.4 to 28.9 mg kg 1, respectively. In Polish biosolids, Falandysz and Strandberg (2004) also found DDT and its metabolites to be present in highest concentrations (330–490 mg kg 1) with significant amounts of dieldrin also being present (8.6–9.9 mg kg 1). In Greece, Katsoyiannis and Samara (2004) measured heptachlor epoxide, DDD, DDE, dieldrin, and endrin in biosolids in mg kg 1 amounts but did not detect DDT, aldrin, or isodrin. Microbial degradation of OCPs is characteristically slow but promoted under anaerobic conditions (Hill and McCartney, 1967; Neilson, 1996; Olaniran et al., 2001). Thus, some degradation may occur during anaerobic sludge digestion. Under aerobic soil conditions their degradation is very slow (Aislabie and Lloyd-Jones, 1995; Aislaibie et al., 1997; Lal and Saxena, 1982) and therefore, if they are present in biosolids, they will remain for long periods following land application. 6.1.6. Chlorophenols Chlorophenols are organochlorines of phenol that contain one or more covalently bonded chloride atoms. They consist of 19 different compounds and pentachlorophenol (PCP) is the most widely used in the group. Because
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of their broad spectrum biocidal properties, chlorophenols are used as disinfectants, mothproofing agents, miticides, termiticides, herbicides, and fungicides. They are used as preservation agents for wood, paints, and leather and some are important intermediates in the production of pharmaceuticals, dyes, and herbicides. PCP is known to be neurotoxic and immunosuppressant and is a suspected carcinogen and EDC (USEPA, 2008). In addition, dioxins (see below) are common by-products/contaminants in PCP formulations and these are known to be extremely persistent and toxic compounds. Because of concerns about the toxicity of PCP, and associated dioxins, its use has been severely limited (e.g., banned from residential indoor use) in most technologically advanced countries since the 1980s. As a result, concentrations in freshwater and marine environments are generally falling (Muir and Eduljee, 1999). Chlorophenols are considered priority pollutants by both the European Union and the USEPA (Ruzgas et al., 1995). Chlorophenols may enter wastewater through runoff from residential and agricultural land following atmospheric deposition and/or a variety of uses (e.g., herbicides, fungicides, termiticideswood preservatives), through domestic sewers and wastewater from manufacturing processes. During wastewater treatment, chlorophenols can be removed by sedimentation, volatilization, and biodegradation. Ettala et al. (1992) showed that biodegradation during activated sludge treatment accounted for a large proportion of the removal. Further degradation will occur during sludge digestion particularly if it occurs under anaerobic conditions. Indeed, biodegradation is known to be favored under anaerobic conditions with the higher chlorinated phenols (e.g., pentachlorophenol) being sequentially dechlorinated to tetra- tri-, di- and monochlorophenol (Chang et al., 1995; Mikesell and Boyd, 1988; Togna et al., 1995). Phenols substituted in the 2,4 and 6 positions are generally more readily degraded than 3 and 5 chloro compounds. Nevertheless, significant amounts of di-, tri-, tetra- and pentachlorophenols have all been measured in biosolids samples (Bright and Healey, 2003; De Walle et al., 1982; Wild et al., 1993). Concentrations of individual compounds are often in the range of 0.02–10 mg kg 1 but total concentrations in the range of 10–60 mg kg 1 have been measured by some (Wild et al., 1993). Following land application of biosolids, chlorophenols would be expected to degrade relatively quickly since microbial degradation under aerobic soil conditions is well documented (Cho et al., 2000; Okeke et al., 1996). 6.1.7. Polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) Dioxin is a generic term for a mixture of 219 different almost planar tricyclic aromatic compounds belonging to the PCDD and PCDF groups. The most extensively studied is the PCCD 2,3,7,8-tetrachlorodibenzo-p-dioxin
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(TCDD) which was a contaminant in Agent Orange. Dioxin concentrations are usually expressed as International Toxicity Equivalency Factors (I-TEQs) relative to the most toxic dioxin (TCDD). PCCDs and PCDFs are not produced commercially but are formed as unwanted by-products from the production or use of many organochlorine compounds such as chlorophenols and their derivatives, chlorinated diphenyl ethers, polychlorinated biphenyls, and chlorophenoxy herbicides. Earlier and/or ongoing use of pentachlorophenol (principally as a wood preservative; see above) is often considered as the major source of dioxins in industrialized countries. Chlorine bleaching of pulp and paper can be an important source and they are also produced in graphite electrode sludge from chlorine-alkali plants (Rappe, 1994). In addition, dioxins are produced during combustion processes including chlorinated waste incineration, iron and steel production, coal-fired power generation, and in motor vehicle emissions. Dioxins bioaccumulate in food chains and are classified as persistent organic pollutants and under the Stockholm Convention and signatories are obliged to eliminate or minimize all sources. In mammals, they are known to be mutagenic, carcinogenic, immunotoxic, teratogenic, hepatotoxic, and EDCs (Birkett, 2003a; Birnbaum, 1994; Boening, 1998; Peterson et al., 1993). There is often little difference in PCDD/F concentrations in wastewater from industrial and domestic areas (Rappe et al., 1998; Stevens et al., 2001). It is thought that a major source of higher chlorinated dioxins is that they are washed out of textiles and fabrics in washing machines and enter household wastewater (Horstmann and McLaughlan, 1995; McLachlan et al., 1996). By contrast, the lower chlorinated dioxins enter wastewater treatment plants principally by transport of atmospheric deposition in surface runoff (McLachlan et al., 1996; Oleszek-Kudlak et al., 2005). PCDD/Fs generally have low volatility, high octanol water coefficients, and low aqueous solubilities and consequently they sorb strongly onto organic solids and are mostly removed during sedimentation. Although PCDD/Fs can be slowly degraded by reductive dechlorination under anaerobic conditions (Field and Sierra-Alvarez, 2008; Wittich, 1998), total concentrations have been shown to increase during anaerobic sludge digestion due to loss of sludge biomass (Disse et al., 1995; Oleszek-Kudlak et al., 2005). Concentrations of dioxins in biosolids range from 2 to 1270 ng I-TEQ kg 1 with 20–200 ng I-TEQ kg 1 being common (Dudzinska and Czerwinski, 2002; Eljarrat et al., 1999; Hagenmaier et al., 1992; Oleszek-Kudlak et al., 2005; Rappe et al., 1998; Sewart et al., 1995; Stevens et al., 2001). The predominant isomers present are the higher chlorinated PCDD/Fs with octachlorodibenzo-p-dioxin (octCDD) commonly being present in highest concentrations (e.g., 300–30,000 ng kg 1) (Oleszek-Kudlak et al., 2005). Other dioxins commonly present in biosolids include octaCDF, heptaCDD, and heptaCDF (Eljarrat et al., 2003; Martinez et al., 2007;
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Oleszek-Kudlak et al., 2005). In general, PCDD/F levels in biosolids in Europe have decreased since the 1980s (Eljarrat et al., 2003; McLachlan et al., 1996) and this is presumably a consequence of a ban on the use of pentachlorophenol. Once introduced to the soil via biosolids application, PCDD/Fs are very persistent, with half-lives in excess of 10 years (McLachlan et al., 1996; Wilson et al., 1997). It is likely that some slow biodegradation occurs since lower chlorinated dioxins can be degraded by aerobic bacteria and can also be attacked cometabolically by white rot fungi (Field and Sierra-Alvarez, 2008). However, photodegradation and volatilization have a negligible influence on the fate of PCDD/F in soils (McLachlan et al., 1996) and as a result they are exceptionately persistent. 6.1.8. Organotin compounds Organotin compounds are organometallic compounds based on tin with hydrocarbon substituents. A large number of compounds exist which belong to four classes; tetraorganotins (R4Sn), triorganotins (R3SnX), diorganotins (R2SnX2), and monoorganotins (RSnX3). R is usually a butyl, octyl, or phenyl group and X a chloride, fluoride, oxide, hydroxide, carboxylate, or thiloate group. Monoorganotins have limited use mainly for thermal and UV stabilization in PVC products. Diorganotins are also used as stabilizers for PVC and as well as catalysts in production of polyurethane foams and in silicone vulcanization. Triorganotins have biocidal properties and are used in timber protection, protection of textiles, leather and other materials, and for crop and animal protection in agriculture. Some were also used as antifouling agents in marine paints but this use is now prohibited in most countries. Tetraorganotins are mainly used as intermediates in preparation of other organotins. Because of their high toxicity (particularly triorganotins) toward aquatic animals, at concentrations of only a few ng L 1, there is concern about their adverse effects on freshwater and marine environments (Chiavarini et al., 2003; Diez et al., 2005; Rudel, 2003). In mammals, organotins are known to be neurotoxic, carcinogenic, immunotoxic, and also affect reproducibility (Appel, 2004; Dopp et al., 2007). It is thought organotins entering wastewater streams originate from industrial manufacture of PVC, runoff from biocidal applications for wood preservation and agriculture, and even normal leaching and weathering of PVC pipes (Fent, 1996). Significant quantities of organotins are present in wastewater and concentrations usually range from a few ng to a few (Horstmann and McLaughlan, 1995; McLachlan et al., 1996) mg L 1 (Chau et al., 1992; Fent and Muller, 1991). The compounds are primarily associated with the suspended solids in untreated wastewater (Fent, 1996) and they are mainly removed during primary and secondary sedimentation. They become enriched in biosolids since they are not readily degraded
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during sludge digestion (Fent, 1996; Voulvoulis and Lester, 2006). Such enrichment is clearly evident in Fig. 6 where concentrations of organotins in digested sludge at four different sampling times were about twice those in undigested sludge. The most commonly encountered organotins in biosolids are monobutyltin (0.016–43.56 mg kg 1), dibutyltin (0.41–8.56 mg kg 1), tributyltin (0.005–237 mg kg 1), monophenyltin (0.1 mg kg 1),
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Figure 6 Concentrations of monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), and total organotins (Total) in raw sewage (top) and digested sewage sludge (below). From Fent and Muller (1991); copyright American Chemical Society.
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diphenyltin (0.1–0.4 mg kg 1), and triphenyltin (0.3–3.4 mg kg 1) (Arnold et al., 1998; Chau et al., 1992; Fent, 1996; Fent and Muller, 1991; Voulvoulis et al., 2004). The fate of organotins in soils following biosolids applications and their effects on the soil system is not well known (Fent, 1996). However, it is known that organotins can be slowly biodegraded by bacteria and fungi and that this can involve sequential removal of organic moieties to yield less toxic derivatives (Gadd, 2000). 6.1.9. Brominated flame retardants Flame retardants incorporated into potentially flammable materials, such as plastics, rubbers, and textiles, to slow down and/or inhibit the initial phase of a developing fire. Brominated fire retardants are an extremely diverse group of compounds including aromatics, cyclic aliphatics, phenolic derivatives, aliphatics, and phthalic anhydride derivatives (Hyotylainen and Hartonen, 2002). Their flame retardancy mechanism is that with the application of heat, they decompose before the matrix of flammable polymer, thus preventing the formation of flammable gases (Rahman et al., 2001). The brominated fire retardants most commonly used are polybrominated diphenyl ethers (PBDEs), polybrominated biphenyls (PBBs), hexabromocyclododecane (HBCD), and tetrabromobisphenol (TBBPA) (de Witt, 2002). PBDE congeners are named by the number and position of bromines analogous to PCBs (e.g., BDE-47, BDE-99, etc.). Retardants such as PBDEs, PBBs, and HBCD are additives mixed into polymers and are not chemically bound to the plastic or textile so they may separate or leach from the product. Others such as TBBPA are reactive and are chemically bonded to the material and are less likely to be released to the environment. PBDEs and PBBs are lipophilic and resistant to degradative processes and therefore bioaccumulate in wildlife and humans (Hakk and Letcher, 2003; Law et al., 2003, 2006). Mechanisms of toxicity are similar to those of PCBs (Pijnenburg et al., 1995). They are known to be neurotoxins, carcinogen, EDCs and have estrogenic activity (Martin et al., 2004; Rahman et al., 2001; Siddiqi et al., 2003). In 2003, the European Union placed a ban on use of pentaBDE and in Europe production has shifted toward HBCD and TBBPA. Sewage from industrial and domestic areas generally show brominated fire retardant concentrations of a similar order indicating that the major source is diffuse leaching from treated products into wastewater streams from both households and industries (Law et al., 2006; Wang et al., 2007). The water solubilities and vapor pressures of PBBs, TBBPA, HBCD, and PBDEs are very low (Rahman et al., 2001) and they strongly bind to solid particles particularly organic matter (Litz, 2002). As a result, they are removed during sedimentation and North (2004) estimated 96% removal efficiency in a wastewater treatment plant. Concentrations of PBDEs in biosolids have been reported to range from 0.4 to 2600 mg kg 1, with
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100–1000 mg kg 1 being common; congeners 47, 99, 100 and 209 are most prevalent (Christensen et al., 2003; de Witt, 2002; Fabrellas et al., 2004; Hagenmaier et al., 1992; Hale et al., 2003; Law et al., 2006; Moche and Thanner, 2004; Oberg et al., 2002). Concentrations of HBCD of 0.4–650, TBBPA of 0.4–300, and PBB of 0.4–10 mg kg 1 have also been reported (Law et al., 2006; Oberg et al., 2002; Sellstrom et al., 2005). Following land application of biosolids, PBDEs have been shown to be persistent in soils (Eljarrat et al., 2008; Sellstrom et al., 2005). Nevertheless, losses of added PBDEs from soils have been measured (Litz, 2002) and these were greater under anaerobic conditions. Biodegradation is generally not thought to be an important pathway for the PBDEs but photolysis may play an important role (Fang et al., 2008; Rahman et al., 2001). Nevertheless, microbial degradation of PBDEs can occur under aerobic and particularly anaerobic conditions (He et al., 2006; Rayne et al., 2003; Vonderheide et al., 2006). 6.1.10. Surfactants and related residues Surfactants are one of the most ubiquitous groups of anthropogenic organic compounds. The global market is more than 18 million tons per year and about 40% of this is as soaps and household detergents (Cirelli et al., 2008). They are also used by a range of industries in the production of cosmetic, personal care, household, painting, coating, textile, dyes, polymer, food, agrochemical, and oil products. A fundamental property of surfactants is their ability to form micelles (colloidal-sized clusters) in solution. The property is due to the presence of both hydrophobic and hydrophilic groups on each molecule. This gives surfactants their detergency and solubilization properties. Common formulations include anionic, cationic, amphoteric, and nonionic surfactants. The most common surfactant used is the anionic linear alkylbenzene sulfonate (LAS). After use, large quantities of soaps and detergents are released into sewage. During passage through the sewerage system, chemical and biological reactions can result in considerable reductions in concentrations of surfactants present (Matthijs et al., 1995; Moreno et al., 1990). Many studies at waste water treatment plants have shown that LASs are efficiently removed by physical, chemical, and biological processes and concentrations in effluent water are characteristically low. Indeed, due to the amphiphilic nature of surfactants, they are readily adsorbed to suspended solids in sewage. As a result, a significant proportion of LAS in sewage is adsorbed to particulate matter and is removed during sedimentation. Thus, sediment in primary settling tanks is generally rich in LAS with concentrations ranging from 5 to 15 g L 1 (Brunner et al., 1988; De Henau et al., 1982). Most of the remaining LAS in the solution phase are removed by microbial degradation resulting in a reduction of 95–99% of LAS load in the
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liquid phase of most water treatment plants (Cirelli et al., 2008; Painter and Zabel, 1989). In general, LAS, cationic and alkylphenol ethoxylate surfactants are all relatively resistant to degradation in anaerobic environments (Cirelli et al., 2008). By contrast, they are generally rapidly degraded under aerobic conditions. Biodegradation of LAS involves degradation of the linear alkyl chain, the sulfonate group and finally the benzene ring and is carried out by a consortium of bacteria (Cirelli et al., 2008; Perales et al., 2003). Thus, biosolids that have been aerobically digested generally have a low LAS concentration (e.g., 100–500 mg kg 1) compared to anaerobically treated sludge (e.g., 5000–15,000 mg kg 1) (Cirelli et al., 2008; Jenson, 1999). Since anaerobic digestion is the predominant treatment of sludge, biosolids often contain a substantial surfactant load. Once reintroduced into an aerobic environment, such as soil, surfactants such as LAS are rapidly degraded (Cirelli et al., 2008; De Wolf and Feijtel, 1998). Under both aerobic and anaerobic conditions the alkylphenol ethoxylates (nonionic surfactants, e.g, nonylphenol exothylate, nonylphenol diethoxylate) undergo almost complete primary degradation but under anaerobic conditions degradation by-products tend to persist (Ejlertsson et al., 1999). The nonylphenol group is most resistant (Thiele et al., 1997) and has caused concern since it has been shown to be present in anaerobically digested biosolids in significant quantities (i.e., up to several thousand mg kg 1) (Maguire, 1999; Xia and Jeong, 2004) and it is known to be to an EDC (Thiele et al., 1997; Ying et al., 2002). Nevertheless, nonylphenol is rapidly biodegraded under aerobic conditions in soil ( Jenson, 1999) and degradation is stimulated by the addition of organic substrates such as biosolids (Roberts et al., 2006). Surfactants are used both in flushing/washing of heavy metalcontaminated soils and during bioremediation of soils contaminated with organics to promote desorption of contaminants bound to the solid soil phase (Haigh, 1996; Mulligan et al., 1999, 2001). However, such interactions are unlikely to occur to any significant extent in biosolids-amended soils. This is because the concentrations of surfactant necessary to achieve micellization in soil pore water are much greater than those typical in biosolids-treated soils (Cirelli et al., 2008; Haigh, 1996). Other detergent-derived residues which have also been measured in biosolids include quaternary ammonium-based surfactants which are widely used as fabric softeners (Rogers, 1996). These materials are, however, biodegradable under aerobic conditions (Sullivan, 1983). Fluorescent whitening agents are also a component of most modern laundry detergents and these have been measured in biosolids at concentrations of 5–100 mg kg 1 (Poiger et al., 1993, 1998). Such materials are thought to be relatively resistant to biodegradation in the soil (Devane et al., 2006).
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6.1.11. Pharmaceuticals and personal care products Pharmaceuticals and personal care products (e.g., musks) in sewage arise primarily from human excreta and urine which contain residues or metabolites, wash water containing topically applied chemicals, and from any deliberate disposal of unwanted and/or expired prescription medicines ( Jones-Lepp and Stevens, 2007; Rogers, 1996). Materials used in veterinary applications may also be important. Recent advances in chemical analytical methodology have revealed that a wide variety of these chemicals can be present in waste water and biosolids (Bright and Healey, 2003; Kinney et al., 2006; Koplin et al., 2002). For example, chemicals belonging to groups such as synthetic musks (2000–500,000 mg kg 1) (used in perfumes and scents), fluoroquinolones (1000–2500 mg kg 1) (broad-spectrum antibiotics), macrolides (1–150 mg kg 1) (a group of antibiotics), and sulfonamides (1–200 mg kg 1) (antibacterial drugs) have all been identified in biosolids ( Jones-Lepp and Stevens, 2007). Specific chemicals such as acetaminophen (e.g., tylenol, panadol), acetylsalicylic acid (asprin), albuterol (a bronchodilator used in asthma treatment), and gemfibrozil (lowers blood fats and cholesterol) have also been detected (Bhandari and Xia, 2005; Jones-Lepp and Stevens, 2007). There is little information available on the environmental behavior, biological activity, or ecotoxicology of these materials. It is believed that a large proportion of pharmaceutical chemicals will undergo microbial transformations during sewage treatment processes (Kinney et al., 2006; Richardson and Bowron, 1985). The extent of such transformations and the biological activity of any metabolites produced are, however, unknown. At present, there is no evidence that residues of pharmaceutical chemicals present in biosolids are likely to be harmful to either human health or to the environment. Nonetheless, in the future much more accurate data on their concentrations, fate in wastewater treatment facilities, environmental fate and transport, and potential effects on humans and the environment will be required. 6.1.12. Natural and synthetic hormones The major hormones associated with the estrous cycle in women are 17b-estradiol, estradiole, and estrone and all enter sewage in measureable amounts. The xenoestrogen, 17a-ethinylestadiol, is an analog for 17b-estradiol and is used as a key component of oral contraceptives. It is also present in municipal wastewater. Concentrations of estrogenic substances in wastewater consistently fall in the 40–100 ng L 1 range (Layton et al., 2000). The efficiency of biodegradation of both natural and synthetic estrogenic organics and the consequent concentrations in wastewater treatment plant effluents and in biosolids varies according to sewage treatment techniques with aeration notably increasing efficiency (Esperanza et al., 2004;
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Joss et al., 2004; Lorenzen et al., 2004; Servos et al., 2005). The incomplete decomposition of these compounds is of concern since very low concentrations in water can contribute to feminization of male fish (Purdom et al., 1994; Routledge et al., 1998). Purdom et al. (1994), for example, found concentrations of estradiol as low as 1 ng L 1 induced vitellogen (an egg yoke precursor protein) production in male fish. The fate of estrogenic compounds (17a-ethinylestadiol, estradiol, and estrone) in soils treated with biosolids was followed by Lorenzen et al. (2006). They found that under aerated soil conditions at soil temperatures typical of the Canadian growing season, these compounds were rapidly degraded (Fig. 7) in three different soils of different texture and therefore the risk of leaching to groundwaters was minimal. 6.1.13. Other organic compounds A wide range of other organic compounds have been measured, in quantities in the mg kg 1 order, in biosolids samples around the world. These include (a) short-chained and chlorinated aliphatics (e.g., chlorobutane, chloroethane, chloromethane, chloropropane, pentanone, hexanone, butanol, acrylonitrile, propenol), (b) monocyclic and heterocyclic hydrocarbons (e.g., benzene, benzoic acid, analene, styrene, toluene, xylene), (c) nitrosamines and nitroaromatics (e.g., N-nitrosodiphenylamine, 100 Loam Sandy loam Silt loam
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Figure 7 Relative quantity of extracted radioactivity in three agricultural soils varying in texture following applications of C14-labeled ethynylestradiol at 120 ng kg 1. From Lorenzen et al. (2006); copyright NRC Canada.
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N-nitrosodiethanolamine), (d) organophosphates (e.g., diazinon, malathion, flame retardants), and (e) phenoxy herbicides (e.g., 2,4-D, 2,4,5-T, MCPP, MCPA) (Bright and Healey, 2003; Harrison et al., 2006; Rogers, 1996). In general, the fate of such compounds during water treatment processes and sludge digestion and their subsequent breakdown in soils following land application of biosolids are not well known.
6.2. Potential transfer to groundwater, plants, and animals With the transfer of organic contaminants to soils when biosolids are land applied there is the chance of their transfer to the wider environment. The likelihood of this will be highly dependent on the amounts and types of organic compounds introduced to soils and their rates of loss via microbial decomposition/volatilization/photolysis. As is evidenced by the above discussion, at present, the rates of loss of these compounds from soils are not well characterized. Below, the general principals of transfer of soil-borne organic contaminants to groundwater, plants, and animals are discussed. 6.2.1. Groundwater Wilson et al. (1996) used a range of models to assess the potential of organic contaminants in biosolids to leach and cause groundwater contamination. In general, highly mobile chemicals were considered those with low Kow and low organic C/water partition coefficients (Koc). A provisional list of leachable compounds included chloroanalines, nitrobenzene, nitrochlorophenol, dinitrochlorophos, tetrachloroethane, chloroethyl ether, trichlorophon, linuron, atrazine, and simazine. Hydrophobic organic compounds such as PCBs, PAHs, dioxins, and phthalates are not generally mobile in soils since they strongly sorbed to solid soil and biosolids particles (particularly organic surfaces). Thus, organic contaminants in sewage that readily partition into the solid phase and accumulate in biosolids are generally likely to be characteristically immobile in soils. The effect of increasing soil organic matter content is typically to decrease the mobility of these hydrophobic compounds (Petruzzelli et al., 2002). Even so, the presence of dissolved organic matter can result in mobilization of a very small percentage (e.g., <5%) of the organic contaminant (Kretzschmar et al., 1999). As discussed previously, dissolved organic matter released from the biosolids can leach down the soil profile. Other work has shown that dissolved organic matter is involved in transport of organic contaminants in soils (Kretzschmar et al., 1999). In column and batch studies, complexation or association of strongly hydrophobic substances (e.g., polychlorinated biphenyls, polyaromatic hydrocarbons, and organochlorine pesticides) with dissolved organic matter has been shown to result in enhanced aqueous solubility, decreased sorption, and enhanced transport (Chin et al., 1991; Chiou et al., 1986; de Jonge et al., 2002; Dunnivant et al., 1992; Enfield
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et al., 1989; Kan and Tomson, 1990; McCarthy and Jimenez, 1985). Indeed, dissolved organic matter, derived from biosolids, has been shown to enhance transport of organic contaminants through soil (Hassett and Anderson, 1982; Muszkat et al., 1993; Raber and Kogel-Knabner, 1997; Vinten et al., 1983). Thus, biosolids addition to soils can potentially promote leaching of organic contaminants present in the biosolids down the soil profile. Nonetheless, soluble organic matter can also sorb to soil surfaces and this would enhance sorption and retard transport of the associated organic contaminants (Totsche et al., 1997). The potential for losses of organic contaminants via surface runoff and leaching certainly exists. Preferential flow of biosolids colloids down soil macropores could contribute to leaching of organic contaminants. Movement of organic contaminants sorbed to particulate matter is favored where macropore flow occurs (de Jonge et al., 2002). As with heavy metals, the greatest risk of leaching of organic contaminants is likely to be immediately after land application of biosolids when soluble organic matter concentrations are elevated and when preferential macropore flow of biosolids particles is most probable. Minimizing water inputs and drainage during this period is therefore an important consideration. Nonetheless, even where exceptional circumstances promote runoff and/or macropore flow (e.g., storm events), these are likely to be isolated incidents where dilution of ground or surface water from unpolluted water will be large. 6.2.2. Plants There are four main pathways by which organic chemicals in soil can enter plants (Ryan et al., 1988; Topp et al., 1986). These are: (a) root uptake from soil solution and subsequent translocation to shoots (i.e., liquid phase transfer), (b) absorption by shoots (or roots) of volatilized organics from surrounding air (i.e., vapor phase transfer), (c) uptake by external contamination of shoots by soil or dust and subsequent retention in the cuticle or penetration through it, and (d) uptake and transport in oil channels which are found in some oil-containing plants (e.g., carrots). The first three routes are shown in Fig. 8 which demonstrates the importance of the aboveground portion of the plant to uptake of organics. Only a few studies have been published detailing the behavior of organic pollutants in crops after application of contaminated sewage sludge to land but it is generally considered that a combination of (a) and (b) accounts for most of the uptake (Beck et al., 1996; Duarte-Davidson and Jones, 1996). 6.2.2.1. Root uptake and translocation Except for a few hormone-like chemicals such as phenoxy acid herbicides, uptake of organic compounds by plant roots is generally considered as a passive process (Collins et al., 2006). PAHs, chlorobenzenes, PCBs, and PCDD/Fs have all been found to accumulate significantly in plant roots (Duarte-Davidson and Jones, 1996).
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Dry and wet deposition of particles followed by desorption into leaf
Suspension of soil particles by wind and rain
Evaporation and volatilization from leaf Gaseous deposition to leaf via cuticle and stomata Transportation in the transpiration stream within the xylem
Volatilization from soil
Desorption from soil followed by root uptake from soil solution
Figure 8 Principal uptake pathways for the uptake of organic chemicals by plants. From Collins et al. (2006); copyright American Chemical Society.
Lipophilic organic compounds possess a greater tendency to partition into plant root lipids (including lipids in cell walls and cell membranes) than hydrophilic ones (Collins et al., 2006). Indeed, it is generally considered that there is a linear relationship between Kow and retention of organic compounds in roots ( Duarte-Davidson and Jones, 1996); compounds with Kow > 4 have a high potential for retention on plant roots. Such compounds will therefore have a high potential for contamination of the surface of root crops although fortunately the outer layers are usually removed prior to human consumption. Plant species with a higher lipid content may tend to have a greater root accumulation of organic compounds (Gao and Zhu, 2004; Schwab et al., 1998). Gao and Zhu (2004), for example, found the ability of 12 plant species to accumulate phenanthrene and pyrene in roots was positively correlated with root lipid content. The higher retention of organic compounds in the peels of carrots and potato compared to their inner portions has been attributed to the higher lipid content of the peel (Fismes et al., 2002, Wild and Jones, 1992). Uptake of organic compounds into the root system, and subsequent translocation to shoots through the xylem, has been found to be favored for compounds of intermediate solubility (Collins et al., 2006). Log Kow values for maximum translocation have variously been reported as being in the range of 1.8–3.0 (Fismes et al., 2002; Smith and Jones, 2000; Trapp and Pussemeir, 1991). For example, Collins et al. (2006) noted that mono- and dichlorophenols, which have a range of log Kow values between 2.15 and 3.65, have been shown to possess a high potential for root uptake
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and translocation. The reason for the Kow optima is not completely understood but it appears that highly lipophilic compounds with high Kow values (e.g., log Kow > 4) are retarded at the root surface due to sorption while polar chemicals with low values (e.g., Kow < 0.5) are less able to cross hydrophobic lipid membranes (Collins et al., 2006; Duarte-Davidson and Jones, 1996). Water and solutes transported in the xylem may be sorbed by stem components and/or accumulate in shoots and leaves. The organic chemicals accumulate in shoots as a result of equilibration of the aqueous phase in plant shoots with xylem constituents and sorption of the compound onto lipophilic shoot solids (McFarlane, 1994). Plant transpiration streamflow rate and lipophilic solids content of the plant will greatly influence accumulation of compounds in shoots (Collins et al., 2006). The potential for substantial sorption of the compounds to stem components during xylem transport increases with increasing lipophilicity of the chemical (Briggs et al., 1983; McGrady et al., 1987). Plant species can vary greatly in their ability to absorb and translocate organic compounds (Collins et al., 2006). Mattina et al. (2000, 2003, 2004) have shown that among a wide range of crops, plants within the Cucurbitaceae family (e.g., Cucurbita pepo L, zucchini) are especially adept at uptake of soil-bound DDE and chlordane. Similarly, Hulster et al. (1994) showed that courgette and pumpkin absorb and translocate relatively more PCCD/ Fs than most other crops. It has been suggested that these plants release root exudates which mobilize organic compounds from the soil thus increasing their availability (Hulster et al., 1994; Mattina et al., 2000). It is important to note here that soil characteristics are also important factors and that plant uptake of organic compounds is usually inversely related to soil organic matter content (Beck et al., 1996; Ryan et al., 1988). This is because hydrophobic organic compounds with a high Kow are strongly adsorbed to organic matter particles. As a result, plant uptake of organic compounds (e.g., PAHs) from solution culture is characteristically much higher than from soils at the same concentration of compound in soil solution (Gao and Ling, 2006). Biosolids particles are about 50% organic matter, so addition of biosolids to soils will tend to increase sorption (and compounds will already be sorbed to biosolids particles). The desorption process of these compounds from solid phase into soil solution will restrict their uptake into plant roots. The availability of organic compounds in soil solution is, therefore, usually the primary restriction to plant uptake of compounds including chlorobenzenes, organochlorines, and PAHs (Gao and Ling, 2006; Mattina et al., 2003; Wang and Jones, 1994a). Indeed, organic compounds are usually present in biosolids in low concentrations and they are so strongly sorbed by the soil/biosolids matrix that they exhibit very low bioavailability and accumulate in the edible portion of food crops at extremely low concentrations (O’Connor, 1996). Even where root
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accumulation occurs, translocation to shoots is usually negligible due to their low water solubility and high Kow values. Indeed, shoot concentration factors (ratio of concentration of organic contaminant in shoots to that in soil solution) are often an order of magnitude less than the equivalent values for root concentration (Gao and Ling, 2006). 6.2.2.2. Uptake from leaves In general, accumulation of organic contaminants into aboveground vegetation from biosolids-amended soils is thought to be dominated by vegetative uptake of contaminated vapor from the surrounding air (Beck et al., 1996; O’Connor, 1996). This has been demonstrated to be the major uptake pathway into plant foliage for a range of organic compounds including PAHs, PCBs, and PCDD/Fs (Bohme et al., 1999; Simonich and Hites, 1994; Welsch-Pausch et al., 1995). Compounds with high volatility and lipophilicity will have the highest bioconcentration into foliage. Compounds with a Henry’s law constant above 1 10 4 are generally considered susceptible to volatilization (Duarte-Davidson and Jones, 1996). Once volatilized from the soil into the atmosphere, chemicals may subsequently diffuse into plant leaves via the cuticle or stomata. Chemicals entering the leaves will diffuse into intercellular air spaces and partition to aqueous and lipophilic phases of adjacent plant tissues (Collins et al., 2006). Lipophilic leaf tissues include the waxy cuticle as well as membrane lipids, storage lipids, resins, and essential oils. Lipophilicity of the organic compound is therefore important and compounds with a log Kow of greater than 4 and high volatility have the greatest potential for foliar uptake (Duarte-Davidson and Jones, 1996). Partition of volatilized chemicals between plant foliage and air has also been related to the octanol/air partition coefficient (KOA) and a linear relationship between log KOA and shoot concentrations of PAHs and chlorobenzenes has been noted (Kipopoulou et al., 1999; Wang and Jones, 1994a). Differences in cuticular permeabilities and leaf/air bioconcentration for volatile organic compounds between plant species has been related principally to leaf lipid content (Collins et al., 2006). Organic chemicals may also come in contact with foliage following deposition in association with dust, aerosols, or atmospheric particulate matter. Some of this may accrue from resuspension of soil/biosolids particles. More particularly, chemicals may come in contact with foliage following direct application (e.g., surface application of biosolids to pastures). Once in contact with the leaves, particle-bound organic chemicals may diffuse through the cuticle and become sorbed to lipophilic material or permeate into the leaf interior (Collins et al., 2006). The permeability of the cuticle to organic chemicals in solution has been observed to be linearly related to Kow and inversely related to its molecular size (Riederer et al., 2002). Uptake of chemicals from particulate deposits will, however, be
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more complex since it will also depend on the capability of the compound to desorb from particle surfaces. 6.2.2.3. Other roles of plants The presence of plants can be an important factor in increasing the rate of degradation of organic contaminants in soils (Alkorta and Garbisu, 2001; Pilon-Smits, 2005; Salt et al., 1998) including those amended with biosolids (Laturnus et al., 2007). As a result, phytoremediation, which uses plants and associated rhizosphere microorganisms to remove or transform organic contaminants in soils, is an emerging technology (Alkorta and Garbisu, 2001; Susarla et al., 2002). Phytoremediation has been successfully employed to treat soils contaminated with a range of organics including chlorinated solvents, aromatic compounds, surfactants, and explosives (e.g., trinitrotoluene, TNT) (Susarla et al., 2002). Plants release a range of carbonaceous compounds into the rhizosphere as root exudates. As a result, microbial densities are 1–4 orders of magnitude higher than the surrounding bulk soil and the community also has a greater range of metabolic capabilities (Salt et al., 1998). Particular plant species could promote degradation of specific organic compounds. For example, it has been suggested that some species preferentially release phenols capable of supporting PCB-degrading bacteria (Fletcher and Hegde, 1995). Rhizosphere microorganisms may also accelerate degradation by volatilizing organics such as PAHs (Alkorta and Garbisu, 2001). Some bacteria can release biosurfactants that may make hydrophilic pollutants more water soluble (Volkering et al., 1998) and plant exudates can contain lipophilic compounds that increase pollutant water solubility and/or promote biosurfactant-producing microbial populations (Siciliano and Germida, 1998). In addition, both plant roots and microorganisms can release enzymes into soils which are involved in degradation of organic pollutants (e.g., laccases, dehalogenases, nitroreductases, nitrilases, and peroxidases) (Schnoor et al., 1995; Wolfe and Hoehamer, 2003). Enhanced biodegradation of organics induced by rhizosphere microflora has been reported for a number of compounds including pentachlorophenol (Ferro et al., 1994), surfactants (Knabel and Vestal, 1992), TCE (Shim et al., 2000; Walton and Anderson, 1990), PAHs ( Joner et al., 2002), and phenanthrene (Corgie et al., 2004; Fang et al., 2001). It has been suggested that in biosolids-amended soils the above mechanisms are of minor importance because biosolids already contain high concentrations of labile organic compounds and a large, active microbial community (Laturnus et al., 2007). These workers suggested that improved porosity and aeration induced by the presence of growing plants favors microbial activity and their degradative activities in biosolidsamended soils. As already discussed, uptake of organic contaminants by plants is usually low, so phytoextraction as a mechanism of remediation of organic contaminants is not usually a viable option. However, uptake can contribute to
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phytoremediation. Following uptake, organic compounds have multiple fates. They may be transformed to less toxic compounds and bound in plant tissues in nonavailable forms, they may undergo partial or complete degradation (phytodegradation) or they may be volatilized (phytovolatilization) (Alkorta and Garbisu, 2001; Susarla et al., 2002). Phytodegradation occurs when plant enzymes act on compounds and catalyze them partially or fully, thus reducing their concentrations in plant tissue. This can occur in both the root and shoot tissue. Those chemicals where evidence of significant degradation has occurred include trichloroethylene, benzene, pyrene, and TNT (Hannink et al., 2002; Susarla et al., 2002). Phytovolatilization occurs when volatile organic pollutants with a high water solubility and vapor pressure are absorbed, translocated to the leaves and lost to the atmosphere as a gas. Examples of organics that can be volatilized from plants include the solvents benzene and TCE and the fuel additive MTBE (Collins et al., 2006; Ma and Burken, 2003; Pilon-Smits, 2005). In general, concentrations of organic pollutants in biosolids-amended soils will be considerably lower than those present in situations where phytoremediation might be considered a strategy to clean up a contaminated soil. Nonetheless, since biosolids are generally land applied to agricultural land, the presence of growing plants does seem likely to enhance the degradation of many biosolids-borne organic contaminants that are introduced to soils. 6.2.3. Animals When biosolids is applied to agricultural land the potential transport of toxic organic chemicals to human food products is of concern. The pathways causing most apprehension are in animal production systems because persistent, lipophilic compounds bioconcentrate in body fat (i.e., meat products) and fat-containing products (e.g., milk). The pathways through which biosolids-derived compounds enter the grazing animal, and factors affecting this entry, were discussed previously (see, Section 5.5). Since most organic compounds are not particularly mobile and do not accumulate in large amounts in plant tops, the biosolids–soil–plant–animal pathway is usually of minor importance. The greatest intake from herbage will occur when biosolids are applied directly to established pasture, biosolids adhere to the herbage and animals have immediate access. Nevertheless, as with heavy metals, soil/biosolids ingestion during periods when forage is sparse is likely to be the major pathway of entry of biosolids-derived organic compounds into the grazing animals (Fries, 1996). As noted previously, this typically occurs most during winter when forage availability is least. Of the many organic contaminants present in biosolids, lipophilic, halogenated hydrocarbons (e.g., halogenated biphenyls, chlorinated pesticides and hydrocarbons, and PCDD/Fs) are of primary concern since they are resistant to degradation and bioconcentrate in fat of animals and animal
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products (Fries, 1996). Among these, compounds with low degrees of halogenation are metabolized and do not accumulate but higher degrees of halogenation block metabolism and bioconcentration occurs (McLachlan, 1993; Shiu and Mackay, 1986). Other compounds commonly found in biosolids such as phthalates, PAHs, acid phenols, nitrosamines, volatile aromatics, and aromatic surfactants are metabolized and do not generally accumulate in animal tissues (Fries, 1996). Bioconcentration factors (the ratio of concentration of compound in a tissue or product to the concentration in the diet) for halogenated organics (e.g., DDE, dieldrin, hexachlorobenzene, heptachlor, PCBs, chlorodibenzo-p-dioxin, and chlorodibenzofuran) are usually in the range of 5–6 in milk fat of cows and the body fat of sheep and cattle (Fries and Marrow, 1975; Fries et al., 1969; Harrison et al., 1970; Parker et al., 1980; van den Hoek et al., 1975; Willett et al., 1990). To minimize bioaccumulation of halogenated hydrocarbons in grazing animals it is important to allow time for biosolids to be washed off the surface of pasture leaves prior to grazing and minimize the chances of soil ingestion during the winter months.
7. Synthesis and Conclusions Wastewater derived from domestic sources (human feces, urine, and graywater) plus that from commercial enterprises and industry, and that from runoff into stormwater is treated in municipal wastewater treatment plants in a series of processes primarily aimed at removing the dissolved and suspended organic material. Biosolids are by-products of wastewater treatment and consist of approximately 50% inorganic and 50% organic material. The organic components originate principally from two sources: (i) human feces settled out during primary treatment (sedimentation) and (ii) bacterial cells settled out during secondary treatment in which bacterial activity is used to remove the suspended/dissolved organic load from the primary treatment effluent. The organic components undergo a degree of degradation and humification particularly during sludge stabilization (often anaerobic digestion). The inorganic component mainly settles out during sedimentation and originates from sources such as local soil and sediments, broken glass, and inorganic residuals of food/feces (e.g., silica). Biosolids contain both inorganic and organic contaminants which originate from the influent sewage wastewater. The major inorganic contaminants are heavy metals (e.g., Cu, Zn, Cd, Pb, Ni, Cr, As) which mainly originate from discharges from industry and from domestic graywater including leaching from Cu and Pb pipes and Zn from domestic products (skin creams, deodorants, etc.). Heavy metals enter the sludge during primary treatment through their association/adsorption to sedimenting
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particles and during secondary treatment through adsorption to bacterial cell walls and/or accumulation into bacterial cells. Concerns regarding the heavy metal loads in biosolids have resulted in guidelines and regulations being developed in many parts of the world which are usually based on maximum allowable metal concentration limits in biosolids and/or the allowable loading limits of metals added in biosolids to the soil. A limitation of these approaches is that they consider total rather than biologically-active (extractable) concentrations of heavy metals in soils. Where agronomic rates are used (2–8 Mg ha 1), heavy metal toxicities limiting crop growth in biosolids-amended soils are very rare. Nevertheless, a major concern is that heavy metals may accumulate in edible portions of plants and subsequently enter the food chain and have toxic effects on grazing animals and/or humans ingesting them. For the most part, heavy metals are not readily translocated to the aboveground edible portions of crops so toxicities from ingestion of food crops are not likely under current regulations. The main potential pathway for accumulation of heavy metals into the meat of grazing animals is via direct soil/biosolids ingestion and substantial accumulation is unlikely under adequate grazing management. There is a growing body of evidence that biosolids-induced heavy metal accumulation in soils can have negative effects on soil microbial/biochemical activity but the significance/ importance of this has yet to be fully understood. With recent improvements in extraction techniques and analytical chromatographic methods, there is an increasing body of research involving surveys of organic contaminants in biosolids. These include PAEs, PAHs, PCBs, chlorobenzenes, chlorophenols, dioxins, organotins, pesticides, brominated flame retardants, surfactants, pharmaceuticals, and natural and synthetic hormones. Due to their low water solubility and high lipophilicity they are generally believed to partition into sludges during sedimentation. Nonetheless, the fate of these chemicals during wastewater treatment processes is not well characterized. Many are not readily degradable under anaerobic conditions and therefore persist in biosolids following anaerobic digestion. There is very limited information in the literature on the behavior and fate of biosolids-borne organic contaminants in agricultural soils. However, the literature available suggests some are rapidly lost following land application since they are readily degraded under aerobic soil conditions, lost by volatilization or by photolysis. Some are, however, known or thought to be only slowly degraded (e.g., organotins, brominated flame retardants, and high molecular mass PAHs) and some are highly persistent (e.g., dioxins and organochlorines). Uptake of organic contaminants from soil into plants is characteristically low and the main pathway is via volatilization from the soil surface and then uptake of contaminated air by aboveground vegetation. Accumulation of organics into grazing animals could occur through ingestion of biosolids adhering to vegetation directly after is application and by direct soil/biosolids ingestion. Many organics are
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metabolized in animals but halogenated biphenyls, chlorinated pesticides and hydrocarbons, and PCDD/Fs are of primary concern since they are resistant to degradation and bioconcentrate in animal fat and animal products (e.g., milk). The European Union has proposed limit values for several organic contaminants/groups of contaminants in biosolids although the relevance of these is not yet fully understood. A better understanding of the reactions and fate of organic contaminants in soils is required before more rigorous regulations can be drafted. If sewage entering a wastewater treatment plant contains a substantial loading of heavy metals or organic contaminants, it is very likely that biosolids produced at the plant will also have a substantial contaminant load. Thus, to lower contaminant levels in biosolids, reductions in the release of contaminants into the sewer system are required. The most practicable way of doing this is at point source outlets to the sewer. Indeed, in recent years, enforcement of tighter regulations has greatly reduced industrial inputs of heavy metals to wastewater streams since industry is expected to pretreat their wastewater (where appropriate) prior to its release. In addition, the use of extremely persistent organics such as dioxins and organochlorines has been effectively terminated making contamination of wastewater with such compounds less pronounced. As a result, contaminants in biosolids are becoming less of an issue and the positive effects of recycling the biosolids via land application onto agricultural or forestry lands are gaining momentum. Indeed, land application is generally seen to be the most economical and beneficial way to deal with biosolids. They contain high concentrations of N, P, Ca, and Mg but K is usually low and needs to be supplemented for crop production. Biosolids applications need to be based on the N needs of crops to be grown so that excessive applications can be avoided thus minimizing leaching and gaseous losses of N to the surrounding environment. Because the bulk of N in biosolids is in organic form, an estimate of N mineralization potential is required to calculate effective N rates. The P content of biosolids is high relative to the plant requirement (based on optimum N supply) and care needs to be taken to avoid runoff losses of P and/or P leaching if available P becomes very high. Where available soil micronutrient levels are low, supply of micronutrients such as Cu, Zn, Fe, and Mn in biosolids may be important. Biosolids applications have other positive effects. Addition of partly humified organic matter can increase soil organic matter content, thereby improving soil physical conditions (e.g., increased porosity and aggregation) and increasing the size and activity of the soil microbial biomass and soil enzyme activity. Areas where a better understanding is required and where research needs to be concentrated include:
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(1) Development of appropriate measures of the biologically active pool of heavy metals in biosolids-amended soils and development of guidelines using such values. Continued monitoring of long-term field sites using such measures is needed to understand long-term effects. (2) A better understanding of the negative effects of sludge-borne heavy metals on soil microbial and biochemical activity and of the significance of this to the soil system. (3) A better understanding of the fate of organic contaminants in sewage during wastewater treatment processes. (4) An in-depth understanding of the fate of organic contaminants in soils (and the mechanisms of their degradation) following land application of contaminated biosolids. An understanding of the effects of accumulated organic contaminants on soil processes is also needed. (5) Development of scientifically based critical concentrations/loadings for organic contaminants.
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Index
A Agricultural production systems SIMultor (APSIM) legume–cereal rotations systems, 115 SOILN module, 114 water-use efficiency (WUE) and N-use efficiency (NUE) assesment, 115–116 wheat–chickpea rotation trial, 116 Arsenic (As) aqueous chemistry, 139 bioavailability assessment chemical forms, 37–39 factors, 36–37 modification, 39 reliable relative bioavailability (RBA), 40–41 risk assessment, 39–40 soil, 35–36 biogeochemical processes arsenic desorption, anaerobiosis, 150–154 microbial arsenate reduction, 149–150 concentrations controlling processes, South (east) Asia biogeochemical and hydrologic process, 156 microbial reduction of, 155 oxidative weathering, 154 reductive release of, 155–156 desorption, soils and sediments comparative desorption, 147–149 displacement and mobilization, 146–147 oxidative dissolution, 146 pollution and hazardous concentrations, 138–139 surface and solid phases adsorption envelopes, As(V) and As(III), 143–144 arsenate precipitation, 145 arsenite vs. arsenate, 142–145 humic substances adsorption, 142 retention of, 139–142 sulfidogenesis, 145–146 B Barley-based rotation trials, 104 Biodegradation branched hydrocarbon chains, 209 brominated flame retardants, 222
chlorobenzenes (CBs), 215 chlorophenols, 218 dioxin, 220 estrogenic organics, 225 linear alkylbenzene sulfonate (LAS), 224 phthalic acid esters (PAEs), 211–212 polybrominated diphenyl ethers (PBDEs), 223 polychlorinated biphenyls (PCBs), 216 Biogeochemical processes arsenic desorption, anaerobiosis, 150–154 microbial arsenate reduction, 149–150 Biological metal uptake children ingestion of, 13–14 food-chain transfer and risks, 14–16 soil ingestion risks, 12–13 Biosolids heavy metal contaminants animal ingestion, 207–208 definition, 182 extractable fractions, 185–187 plant response and metal uptake, 202–207 soil application, 187–202 total concentrations, 183–185 inorganic components ash content, 174–175 X-ray fluorescence analysis, 175 nutrient content and release calcium (Ca) and magnesium (Mg), 181 electrical conductivity (EC), soil, 182 micronutrients, 181–182 nitrogen (N), 175–179 pH change, soil, 182 phosphorus (P), 179–181 potassium (K), 181 organic contaminants branched hydrocarbon chains, 209 brominated flame retardants, 222–223 chlorobenzenes (CBs), 214–215 chlorophenols, 217–218 endocrine disrupting chemicals (EDCs), 209–210 European union limits, 211 natural and synthetic hormones, 225–226 octonol–water partition coefficient (Kow), 209 organochlorine pesticides (OCPs), 216–217 organotin compounds, 220–222 pharmaceuticals and personal care products, 225
269
270
Index
Biosolids (cont.) phthalic acid esters (PAEs), 211–212 polychlorinated biphenyls (PCBs), 215–216 polychlorinated dibenzodioxins (PCDDs)/ dibenzofurans (PCDFs), 218–220 polycyclic aromatic hydrocarbons (PAHs), 213–214 potential transfer to groundwater, plants, and animals, 227–234 presence and level, 208–209 surfactants, 223–224 organic matter characterization, humic substances, 170–171 composition, 169–170 composting, 171 humification, 170 soil application, 171–174 water-soluble labile portion, 171 sewage treatment processes dewatering method, 169 primary and secondary treatment, 168 stabilization methods, 169 thickening, sludge, 168–169 C CERES-wheat crop simulation model, 116–117 Chlorobenzenes (CBs), 214–215 Chlorophenols, 217–218 Conservation/compost tillage trial, 104–105 E Endocrine disrupting chemicals (EDCs), 209–210
extractable fractions available and unavailable forms, 186–187 chemical speciation, 185–186 cocomposting method, 187 sequential fractionation schemes, 186 plant response and metal uptake accumulation of, 205–207 metal toxicity and tolerance, 202–205 phytotoxicity, 202 soil application biosolids property effect, 189–191 extraction methods of, 187–189 metal availability over time, 193–194 microbial/biochemical effects, 198–202 mobility and leaching of, 194–198 soil property effect, 191–193 total concentrations effluent source, 183 guidelines and regulations, 185 waste water treatment plants, 183–185 I Integrated cropping systems barley-based rotation trials, 104 conservation/compost tillage trial, 104–105 cropping systems productivity trial grain and straw yields and quality, 97–99 soil nitrogen dynamics, 99–100 soil organic matter, 100–101 water-use efficiency, 99 crop sequence effect, 95 grazing management rotation trial, 101–104
F
L
Fertilizers, nitrogen rainfed crops response genetic differences, crops, 79–80 Morocco and the Maghreb countries, 73–79 soil organic matter, 68–69 West Asian countries, 70–73 usage trend, 66–67 Food-chain transfer metals, 14–16 plants, organic chemicals leaves uptake, 231–232 rhizosphere activity, 232–233 root uptake and translocation, 228–231
Leaching, heavy metals, 194–198 Lead (Pb), bioavailability assessment absorption, 29 bioaccessibility, soil Pb, 34–35 blood level reduction, children, 29–30 soil/dust Pb chemical speciation, 30 chloropyromorphite (CP) formation, 33–34 feeding tests, 32–33 RBA assessment, 30–32 source, 28
G Grazing management rotation trial, 101–104 H Heavy metal contaminants, biosolids animal ingestion, 207–208 definition, 182
M Mediterranean agroecosystems climate rainfall sketch and intensity, 59–60 seasonal rains and temperature effect, 58 crops and farming systems agroecological condition, 62 barley production, 61–62 niche crops production, 62 wheat production, 61
271
Index
fertilizer use trends, 66–67 integrated cropping systems barley-based rotation trials, 104 conservation/compost tillage trial, 104–105 cropping systems productivity trial, 96–101 crop sequence effect, 95 grazing management rotation trial, 101–104 land features, 60–61 nitrogen, 65–66 nitrogen fixation, dryland conditions food legumes, 86 pasture and forage legumes, 89–91 rhizobia, inoculation, and cultivar interactions, 86–89 rainfed crops response to genetic differences, crops, 79–80 Morocco and the Maghreb countries, 73–79 soil organic matter, 68–69 West Asian countries, 70–73 soil status assessment Cate–Nelson graphical method, 81 Kjeldahl method, 81 mineralization indices, 83–84 mineral N tests, 82 nitrate test, 81–82 plant analysis, 84–85 Metal(Loid)s, bioavailability assessment arsenic chemical forms, 37–39 factors affect, 36–37 modification, 39 reliable relative bioavailability (RBA), 40–41 risk assessment, 39–40 soil, 35–36 biological metal uptake children ingestion of, 13–14 food-chain transfer and risks, 14–16 soil ingestion risks, 12–13 chemistry equilibrium, soil, 22–25 speciation in, 25–28 extractability, availability prediction chelation methods, 21–22 diffusive gradients in thinfilms method, 22 in vitro bioaccessibility, 16–21 lead (Pb) absorption, 29 bioaccessibility, soil Pb, 34–35 blood level reduction, children, 29–30 soil/dust Pb, 30–34 source, 28 soil risks bioavailability and soil element, 7–8 microbes and fauna toxicity, 11–12 phytotoxicity from, 8–11 Micellization, 224
N Neutron activation analysis (NAA), metal bioaccessibility, 17–18 Nitrogen (N) biosolids agronomic biosolids rate, 178–179 agronomic response, 177 ammonia volatilization, 177 mineralization, 176–177 fertilizer and rainfed crops response field responses, 69–79 genetic differences, crops, 79–80 soil organic matter, 68–69 fixation, mediterranean dryland conditions food legumes, 86 pasture and forage legumes, 89–91 rhizobia, inoculation, and cultivar interactions, 86–89 integrated cropping systems barley-based rotation trials, 104 conservation/compost tillage trial, 104–105 cropping systems productivity trial, 96–101 crop sequence effect, 95 grazing management rotation trial, 101–104 mediterranean region, 65–66 modelling systems APSIM usage, 115–116 arid environment models, 118–120 CERES-wheat model, 117 crop–soil simulation models, 114 CropSyst model, 118 root zone water quality model (RZWQM), 117 SOILN module, 114–115 potential losses, dryland cropping ammonia volatilization, 93–94 environmental concerns, 92 loss mechanisms, 92–93 urea fertilizers effect, 94–95 rainfed environments, 64–65 soil status assessment Cate–Nelson graphical method, 81 Kjeldahl method, 81 mineralization indices, 83–84 mineral N tests, 82 nitrate test, 81–82 plant analysis, 84–85 supplemental irrigation systems seasonal weather effect, 106 wastewater usage, 106–107 yeild responses, 105–106 tracer (15N), rainfed cropping systems N fixation estimation, grain legumes, 111–113 rotation effect implications, 110–111 wheat, cereal–legume rotation, 108–110
272
Index O
Organic contaminants, biosolids branched hydrocarbon chains, 209 brominated flame retardants applications, 222 biodegradation, 223 source, 222–223 chlorobenzenes (CBs) concentrations in, 214–215 derivatives and applications, 214 land application, 215 chlorophenols atmospheric deposition, 218 pentachlorophenol (PCP), 217–218 endocrine disrupting chemicals (EDCs), 209–210 European union limits, 211 natural and synthetic hormones, 225–226 octonol–water partition coefficient (Kow), 209 organochlorine pesticides (OCPs), 216–217 organotin compounds biodegradation, 221 classes and apllication, 220 concentrations in, 221 source, 220–221 pharmaceuticals and personal care products, 225 phthalic acid esters (PAEs) applications, 211 microbial degradation, 211–212 polychlorinated biphenyls (PCBs) applications, 215 atmospheric deposition and soil application, 216 polychlorinated dibenzodioxins (PCDDs)/ dibenzofurans (PCDFs) biodegradation, 220 source, 219–220 toxicity, 219 polycyclic aromatic hydrocarbons (PAHs) land application, 214 source and lipophilicity, 213 potential transfer to groundwater, plants, and animals, 227–234 presence and level, 208–209
surfactants linear alkylbenzene sulfonate (LAS), 223–224 micellization, 224 properties, 223 Organochlorine pesticides (OCPs), 216–217 Organotin compounds, 220–222 P Phosphorus (P), biosolids phytoavailability, 180–181 soil accumulation, 180 surface runoff, 181 Phthalic acid esters (PAEs), 211–212 Phytotoxicity, metal effect Ni–Al layered double hydroxides (LDH), 9 Ni-induced Fe deficiency symptoms, 10 precipitation and synchrotron XRF (S-XRF) analysis, 11 Polychlorinated biphenyls (PCBs), 215–216 Polychlorinated dibenzodioxins (PCDDs)/ dibenzofurans (PCDFs), 218–220 Polycyclic aromatic hydrocarbons (PAHs), 213–214 R Reliable relative bioavailability (RBA) arsenic (As) (see Arsenic (As), bioavailability assessment) lead (Pb) (see Lead (Pb), bioavailability assessment) Root zone water quality model (RZWQM), 117 S Sewage treatment processes biosolids (see Biosolids) dewatering method, 169 primary and secondary treatment, 168 stabilization methods, 169 thickening, sludge, 168–169 Soil-N routine/module (SOILN), 114–115 Sulfidogenesis, 145–146 Surfactants, 223–224
