Fate and transport of heavy metals in the Vadose Zone

FATE and TRANSPORT of HEAVY METALS in the

VADOSE ZONE Edited by

H. Magdi Selim Iskandar K. Iskandar

Project Editor: Acquiring Editor Marketing Managers: Cover design: Manufacturing Manager:

Sylvia Wood Skip DeWall Bamara Glunn / Jane Stark Jonathan Pennell Carol Slatter

Library of Congress Cataloging-in-Publication Data Fate and transport of heavy metals in the vadose zone / edited by H.M. Selim, 1.K. Iskandar p. cm. Includes bibliographical references and index. ISBN 0-8493-4112-4 (alk. paper) 1. Soils-Heavy metal content. 2. Heavy metals-Environmental aspects 3. Zone of aeration. 1. Selim, Hussein Magdi Eldin, 1944- .II. Iskandar, 1.K. (Iskandar Karam), 1938- . S592.6.H43F37 1999 628.5'5-dc21

98-26915 CIP

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THE EDITORS

H. Magdi Selim is Professor of Soil Physics at Louisiana State University, Baton Rouge. He received his M.S. and Ph.D. in Soil Physics from Iowa State University, Ames, in 1969 and 1971, respectively, and his B.S. in Soil Science from Alexandria University in Egypt, in 1964. Professor Selim has published numerous papers and book chapters, and is a coauthor of one book and several monographs. His research interests concern the modeling of the mobility of dissolved chemicals and their reactivity in soils and groundwaters. His research interests also include saturated and unsaturated water flow in multilayered soils. Professor Selim served as associate editor of Water Ruource.J Ruearch and the SoiL Science Society ofAmerica JournaL He is the recipient of several professional awards including the Phi Kappa Phi, Gamma Sigma Delta Award for Research, and the Doyle Chambers Career Achievements Award. Professor Selim is a Fellow of the American Society of Agronomy and the Soil Science Society of America.

Iskandar K. Iskandar received his Ph.D. degree in soil science and water chemistry at the University of Wisconsin-Madison, in 1972. He is a Research Physical Scientist at the Cold Regions Research and Engineering Laboratory (CRREL) and a Distinguished Research Professor at the University of Massachusetts, Lowell. He developed a major research program on land treatment of municipal wastewater, and coordinated a number of research areas including transformation and transport of nitrogen, phosphorus, and heavy metals. His recent research efforts focused on the fate and transformation of toxic chemicals, development of nondestructive methods for site assessments, and evaluation of in situ and on-site remediation alternatives. Dr. Iskandar has edited several books and published numerous technical papers. He organized several national and international conferences, workshops, and symposia. He received a number of awards including the Army Science Conference Award, and CRREL Research and Development Award. Dr. Iskandar is a Fellow of the Soil Science Society of America.

PREFACE

During the past decades, phenomenal progress has been made in several areas of biology, ecology, health, and environmental geochemistry of heavy metals in soils. Prior to the 1960s, research was focused on enhancing the plant uptake or availability of selected heavy metals or minor elements (also referred to as micro nutrients) from the soil. More recently, concerns regarding heavy metal contamination in the environment affecting all ecosystem components including aquatic and terrestrial systems have been identified with increasing efforts on limiting their bioavailability in the vadose zone. Moreover, several mathematical models for predicting the forms of metals in soils and the mechanisms of transformations and transport have been developed and evaluated. Because of the concerns regarding the role of heavy metals in the environment, a series of international conferences was held to explore the emerging issues of the biogeochemistry of heavy metals in the environment. In June 1997, the Fourth International Conference on the Biogeochemistry of Trace Elements was held in Berkeley, California. The contributions in this book were presented in part in the special symposium focusing on the fate and transport of heavy metals in the vadose zone as part of this international conference. The first four chapters of this book are devoted to sorption-desorption processes of selected heavy metals in the vadose zone. Kinetics of trace metal sorption-desorption with soil and soil components is the focus of Chapter 1. Importance of slow reactions and sorption mechanisms are also emphasized. In Chapter 2, adsorption of nickel by various soils and their isotherms are discussed. Moreover, a general isotherm approach based on intrinsic soil properties such as cation exchange characteristics and specific surface area is developed. Chapter 3 provides an overview of the sorption-desorption, precipitation, as well as complexation processes for cadmium reactions in soils. A discussion of sorption nonequilibrium during cadmium transport and reversibility of sorption processes are highlighted. Chapter 4 provides a comprehensive treatment of single and multiple retention mechanisms of the linear and nonlinear type which are commonly used to describe sorption-desorption of heavy several heavy metals in soils. Examples include hysteresis, reversibility and ion exchange retention kinetics during transport in soils. In the next three chapters, complexation and speciation processes and their influence on heavy metal mobility are discussed in detail. In Chapter 5, factors influencing complex formation of copper are emphasized. The effect of humic and fulvic acids on the retention of copper by soils and minerals is also presented. In Chapter 6, two sorption models that describe heavy metal binding of copper with solid and dissolved organic matter are presented. The applicability of such models to describe copper retention during transport is assessed. Also, the bioavailability (accumulation and excretion rates and toxicity) of copper for earthworms is discussed in Chapter 6. The effect of dissolved selenium species including metal selenium complexes and other dissolved organic carbon on selenium forms and their retention behavior in soils is presented in Chapter 7. Bioavailability and retention of heavy metals and their mobility in the vadose zone are presented in Chapters 8 through 11. The bioavailability and mobility of several divalent heavy metals as affected by pH and redox conditions are the focus of Chapter 8. Meth-

ods for quantif}ring and predicting the influence on mobility are also illustrated. In Chapter 9, the mobility of lead in calcareous mined soils is presented. The effect of various reagents on the mobility of lead in the vadose zone under different pH and redox conditions is also evaluated. In Chapter 10, an overview of modeling of heavy metal retention is given, along with factors influencing their mobilization/immobilization when organic residue/sewage sludge amendments are incorporated in the vadose zone. The use of a multiple reaction modeling approach is illustrated and the effect on retention parameters when organic waste is incorporated to the soil was also presented. The significance of the rhizosphere and its role on trace element interactions in the soil-plant system is the focus of Chapter 11. In addition, a conceptual model describing the dynamics of trace element processes between plant roots and the soil in the vadose zone is presented. In Chapter 12, plantavailable concentration levels for selected heavy metals in the vadose zone based on several extraction methods is discussed. The potential of various extraction methodologies is also evaluated. In Chapter 13, the authors discuss case studies of metal contamination from emission sources and old abandoned sites. The site investigations, monitoring, and alternative methods for remediation are given. We wish to thank the authors for their contributions to this book. Weare most grateful for their valuable time and effort in critiquing the various chapters and in keeping our focus on the main theme of our topic on heavy metals in the vadose zone. Special thanks are due to Drs. C. Hinz (University of Goettingen) and Giles Marion (U.S. Army CRREL) for their help in reviewing Chapters 3 and 11. Without the support of the Louisiana State University and the U.S. Army CRREL, this project could not have been achieved. Finally, we wish to express our appreciation to Ann Arbor Press for their help. H. Magdi Selim I.K. Iskandar

CONTRIBUTORS

K. Bajracharya Resource Sciences Center Department of Natural Resources Block C, Gate 2, 80 Meiers Road Indooroopilly Queensland 4068 Australia

D.A. Barry Department of Civil and Environmental Engineering University of Edinburgh Edinburgh EH9 3JN United Kingdom Klara Bujtas Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC) P.O. Box 35 H-1525 Budapest Hungary Philippe Cambier INRA Science du Sol Route de St Cyr F -78026, Versailles France Rayna Charlatchka INRA Science du Sol Route de St Cyr F -78026, Versailles France

Stephen Clegg Department of Ecology and Environmental Research Swedish University of Agricultural Sciences Box 7072 S-750 07 Uppsala Sweden Francois Courchesne Departement de Geographie Universite de Montreal C.P. 6128 Succursale Centre-Ville Montreal, Quebec H3C 3J7 Canada J. Csillag Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC) P.O. Box 35 H-1525 Budapest Hungary Carolina Garcia-Rizo University of Murcia Department of Agricultural Chemistry, Geology and Pedology Faculty of Chemistry E-30071 Murcia Spain George R. Gobran Department of Ecology and Environmental Research Swedish University of Agricultural Sciences Box 7072 S-750 07 Uppsala Sweden

Antonius A.F. Kettrup Institute of Ecological Chemistry GSF-National Research Center for Environment and Health N euherberg/Munich Postfach 1129 D-85764 Oberschleissheim Germany R.S. Kookana Cooperative Research Center for Soil and Land Management CSIRO Land and Water, PMB No.2 Glen Osmond SA 5064 Australia A. Lukacs Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC) P.O. Box 35 H-1525 Budapest Hungary

E.V. Mironenko Institute of Soil Science and Photosynthesis Academy of Sciences of Russia Pushchino, Moscow Region 142292 Russia R. Naidu Cooperative Research Center for Soil and Land Management CSIRO Land and Water, PMB No.2 Glen Osmond SA 5064 Australia T. Nemeth Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC) P.O. Box 35 H-1525 Budapest Hungary

Luis Madrid Instituto de Recursos Naturales y Agrobiologia (CSIC) Apartado 1052 E-41080 Seville Spain

G. Partay Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC) P.O. Box 35 H-1525 Budapest Hungary

Mari P.J.C. Marinussen Wageningen Agricultural University Sub-Department Soil Science and Plant Nutrition P.O. Box 8005 6700 Wageningen The Netherlands

Carmen Perez-Sirvent University of Murcia Department of Agricultural Chemistry, Geology and Pedology Faculty of Chemistry E-30071 Murcia Spain

Josefa Martinez-Sanchez University of Murcia Department of Agricultural Chemistry, Geology and Pedology Faculty of Chemistry E-30071 Murcia Spain

Alexander A. Ponizovsky Institute of Soil Science and Photosynthesis Academy of Sciences of Russia Pushchino, Moscow Region 142292 Russia

Katta J. Reddy Department of Renewable Resources P.O. Box 3354 University of Wyoming Laramie, WY S2071

Y.T. Tran Department of Environmental Engineering University of Western Australia Nedlands W A 6907 Australia

S. Schulte-Hostede Institute of Ecological Chemistry GSF-National Research Center for Environment and Health N euherberg/Munich Postfach 1129 D-S5764 Oberschleissheim Germany

Irena Twardowska Institute of Environmental Engineering Polish Academy of Sciences 34 M. Sklodowska-Curie Street 41-S19 Zabrze Poland

H. Magdi Selim Sturgis Hall Agronomy Department Louisiana State University Baton Rouge, LA 70S03

Sjoerd E.A.T.M. Van der Zee Wageningen Agricultural University Sub-Department of Soil Science and Plant Nutrition P.O. Box S005 6700 Wageningen The Netherlands

Donald L. Sparks Department of Plant and Soil Sciences University of Delaware Newark, DE 19717-1303 Daniel G. Strawn Department of Plant and Soil Sciences University of Delaware Newark, DE 19717-1303 T.A. Studenikina Institute of Soil Science and Photosynthesis Academy of Sciences of Russia Push chino, Moscow Region 142292 Russia Erwin J.M. Temminghoff Wageningen Agricultural University Sub-Department Soil Science and Plant Nutrition P.O. Box S005 6700 Wageningen The Netherlands

M. Th. van Genuchten U.S. Salinity Laboratory USDA, ARS 450 W. Big Springs Road Riverside, CA 92507 Walter W. Wenzel University of Agriculture Institute of Soil Science Gregor-Mendel Strasse 33 A-lISO Vienna Austria Franz Zehetner University of Agriculture Institute of Soil Science Gregor-Mendel Strasse 33 A-lISO Vienna Austria

CO.'\'TEl'\TS

Chapter 1. Sorption Kinetics of Trace Elements in Soils and Soil Materials ............... 1

DanieL G. Strawn and Dona{J L. SparlcJ Introduction ....................................................................................................................... 1 Evidence for Slow Sorption and Desorption Reactions ................................................. 3 Diffusion-Controlled Kinetic Reactions ........................................................................... 8 Kinetics and Mechanisms of Adsorption Processes .................................................. 10 Kinetics and Mechanisms of Surface Precipitation .................................................. 18 Summary .......................................................................................................................... 24 References ........................................................................................................................ 25

Chapter 2. Adsorption Isotherms of Nickel in Acid Forest Soils ................................ 29 Franz Zehetner and WaLter W. wenzeL

Introduction ..................................................................................................................... 29 Adsorption ....................................................................................................................... 29 Definition ..................................................................................................................... 29 The Diffuse Double-Layer ......................................................................................... 30 Adsorption Mechanisms ............................................................................................. 30 Adsorption Isotherms ...................................................................................................... 33 Classification ............................................................................................................... 33 The Langmuir Equation ............................................................................................. 34 The van Bemmelen-Freundlich Equation .................................................................. 39 Case Study ....................................................................................................................... 40 Adsorption versus Precipitation ................................................................................. 42 Langmuir and van Bemmelen-Freundlich Isotherms ............................................... 42 Effect of Soil:Solution Ratio on Quantity-Intensity Relationships ......................... 46 Fractionation of Adsorbed Nickel .............................................................................. 50 Adsorption Density and General Adsorption Density Isotherms ............................ 52 Summary .......................................................................................................................... 54 References ........................................................................................................................ 55

Chapter 3. Sorption-Desorption Equilibria and Dynamics of

Cadmium During Transport in Soil ......................................................................... 59 R.S. Kookana, R. NaiJu, D.A. Barry, Y.T. Tran, and K Bajracharya Introduction ..................................................................................................................... 59 Processes Governing Fate of Cadmium in the Soil Profile ........................................... 60 Sorption ....................................................................................................................... 60 Factors Affecting Cd Sorption in Soils ................................................................... 61 Precipitation ................................................................................................................ 69 Kinetics of Cd Sorption .............................................................................................. 70 Sorption Behavior of Cd During Transport Through Soil Columns ....................... 71 Batch versus Flow-Through Systems ..................................................................... 71

Evidence of Sorption Nonequilibrium During Cd Transport Through Soil ........... 74 Asymmetrical Breakthrough Curves ...................................................................... 74 Flow-Interruption as a Test for Sorption Nonequilibrium .................................... 75 Model Fitting ........................................................................................................... 76 Mass Balance Check for Complete BTCs .............................................................. 77 Causes of Sorption Nonequilibrium During Transport ............................................ 78 Cd Transport Under Field Conditions and Its Modeling ......................................... 78 Desorption and Reversibility of Cd Sorption ............................................................ 80 Desorption of Specifically Sorbed Cd .................................................................... 80 Partial Reversibility of Cd Sorption from Calcite and Calcareous Soils .............. 82 Cd Desorption Kinetics ........................................................................................... 82 Sorption Reversibility in Flow-Through Experiments .......................................... 83 Summary .......................................................................................................................... 83 References ........................................................................................................................ 85 Chapter 4. Modeling the Kinetics of Heavy Metals Reactivity in Soils ...................... 91 H. Magdi SeLim Introduction ..................................................................................................................... 91 Linear Retention .............................................................................................................. 92 Nonlinear Retention ........................................................................................................ 93 Langmuir or Second-Order Kinetics ............................................................................. 94 Hysteresis ......................................................................................................................... 96 Irreversible Reactions ..................................................................................................... 96 Specific Sorption ............................................................................................................. 96 Multiple Retention .......................................................................................................... 98 Ion Exchange Retention ................................................................................................ 100 Kinetic Ion Exchange ............................................................................................... 102 Case Study ................................................................................................................. 102 References ...................................................................................................................... 105 Chapter 5. Copper Retention as Mfected by Complex Formation with Tartaric and Fulvic Acids ....................................................................................... Alexander A. PonimIJcflcy, T.A. StUdenilcina, and E. V. Mironenlco Introduction ................................................................................................................... Copper(II) Retention by Soils, Oxides, and Clays ................................................. Solution Complex Formation and Cu(II) Adsorption ............................................ Complexes of Cu(II) with Fulvic Acids .................................................................. Influence of FA and Humic Acids (HA) on the Retention of Cu(II) by Solid Phases ......................................................................................... Copper Retention by Soil (A Case Study) ................................................................... Kinetics of Cu(II) Retention .................................................................................... Cu(II) Retention Isotherms and Cation Balance .................................................... Evaluation of Na2EDTA Ability to Extract Retained Copper ............................... Effect of Tartrate and Fulvic Acid on Cu(II) Retention Isotherms ....................... Modeling of Cu(II) Retention (Exchange) by Soil.. ...............................................

107 107 107 109 110 III III III 112 115 115 119

Summary ........................................................................................................................ 121 References ...................................................................................................................... 122

Chapter 6. Copper Mobility and Bioavailability in Relation with Chemical Speciation in Sandy Soil ........................................................................ E.J.M Temminghoffi MP.J.G. MarinLMden, and S.E.A.T.M Van der Zee Introduction ................................................................................................................... Sorption Models ............................................................................................................ Parameter Assessment Sorption Models ...................................................................... Copper Speciation in a Copper Contaminated SoiL ................................................... Mobility .......................................................................................................................... DOC Mobility Enhanced Copper Mobility ............................................................ Field Site Accumulation in Soil ................................................................................ Bioavailability ................................................................................................................ Bioavailability for Soil Organisms ........................................................................... Field Site Accumulation by Earthworms ................................................................ Summary ........................................................................................................................ References ......................................................................................................................

Chapter 7. Selenium Speciation in Soil Water: Experimental and Model Predictions .................................................................... Katta J. Reddy Introduction ................................................................................................................... Speciation of Dissolved Se ............................................................................................ Experimental and Model Predictions ........................................................................... Dissolved Se Speciation with CuO .......................................................................... Dissolved Se Speciation with GEOCHEM ............................................................ Comparison ............................................................................................................... Future Research ............................................................................................................ References ......................................................................................................................

Chapter 8. Influence of Reducing Conditions on the Mobility of Divalent Trace Metals in Soils ............................................................................... Philippe Cambier and Rayna Charlatchlca Introduction ................................................................................................................... Controversial Studies on Soil-Plant Systems .............................................................. Formation of Insoluble Sulfides and Other Solubility Equilibria .............................. Role of Fe and Mn Oxides as Trace Metal Sorbents .................................................. Reducing Processes Change pH ................................................................................... Role of Soluble Organic Ligands ................................................................................. Transformation of Insoluble Organics ......................................................................... Summary ........................................................................................................................ References ......................................................................................................................

127 127 128 129 130 133 133 136 136 136 139 143 145

147 147 148 149 149 149 150 156 156

159 159 160 161 162 164 168 170 171 172

Chapter 9. Lead Mobilization in Calcareous Agricultural Soils ................................ 177

Carmen Pirez-Sirvent, JOde/a Martinez-Sanchez, and Carolina Garda-Rizo Introduction ................................................................................................................... Soil Formation Factors ................................................................................................. Environmental Conditions ........................................................................................ Nature of the Materials ............................................................................................ Transport ........................................................................................................................ Dissolved Load .......................................................................................................... Particulate Forms: Suspended and Bed Loads ....................................................... Geochemical Processes ................................................................................................. Mobilization-Physical Weathering-Hydration Relations ....................................... Soluble Pb-Adsorbent Precursor Ratio ................................................................ Bicarbonated-Acidic Water Interaction ................................................................... Acid Water-Mineralized Particulate Material-0 2-C0 2 Interaction ................... Acid Water-Carbonated Particulate Material-0 2-C0 2 Interaction .................... Pb Sorption-Desorption ........................................................................................... Mobility .......................................................................................................................... Provoked Pb Mobility: Speciation Study ................................................................ Mobility in the Vadose Zone .................................................................................... Pb Assimilation by Plants ......................................................................................... Conclusion ..................................................................................................................... References ......................................................................................................................

177 178 178 178 180 182 186 186 187 187 188 189 189 190 191 191 193 195 196 197

Chapter 10. Metal Retention and Mobility as Influenced by Some Organic Residues Added to Soils: A Case Study ....................................... 201

LUM Madrw Introduction ................................................................................................................... 201 Soil as a Sink for Trace Metals ................................................................................. 201 Modeling Approaches for Retention of Metals by Soils ......................................... 202 Metal Concentrations in the Soil Solution ................................................................... 204 Factors Causing a Reversal of Immobilization ............................................................ 205 Interaction with Natural Organic Matter .................................................................... 207 Effect of Organic Residues on Metal Solubility .......................................................... 209 The Case of Sewage Sludge .......................................................................................... 210 A Mediterranean Concern: Olive Mill Wastewater .................................................... 211 Setting Up the Problem ............................................................................................ 211 Effect of OMW on Metal Retention Properties of Soils ........................................ 212 OMW in the Aqueous Phase as a Mobilizing Agent of Insoluble Metal Forms ......................................................................................... 215 Summary ........................................................................................................................ 218 References ...................................................................................................................... 219 Chapter 11. The Rhizosphere and Trace Element Acquisition in Soils .................... 225

George R. Gobran, Stephen Clegg, and FrancoM Courchune Introduction ................................................................................................................... 225 History ....................................................................................................................... 226

Rhizosphere - Defmitions ........................................................................................ 226 Methods of Rhizospheric Study ............................................................................... 226 Rhizodeposition ............................................................................................................. 228 Root Distribution and Longevity ............................................................................. 228 Belowground Carbon Flux ....................................................................................... 229 Exudates in the Rhizosphere .................................................................................... 229 Acid-Base Changes in the Rhizosphere ................................................................... 229 Rhizospheric Feedback Loops ...................................................................................... 232 Regulating Processes ................................................................................................ 232 Element Supply and Mobility in the Rhizosphere .................................................. 233 Microbial Activity and Element Accumulation in the Rhizosphere ....................... 234 Case Studies ................................................................................................................... 235 The Conceptual Model ............................................................................................. 236 Field Site and Treatments ......................................................................................... 236 Soil Fractionation ...................................................................................................... 236 Chemical Properties of the Soil Fractions ............................................................... 237 Weathering in Bulk and Rhizosphere Soil .............................................................. 239 Tree Growth and Rhizosphere Chemistry ............................................................... 242 Implications and Future Research ................................................................................ 242 References ...................................................................................................................... 245 Chapter 12. Distribution of Ecologically Significant Fractions of Selected Heavy Metals in the Soil Profile ............................................................. 251

T. Nemetb, K. Bujtd.1, J. CdUlag, G. Pdrtay, A. Lukdcd, and M. Tb. van Genucbten Introduction ................................................................................................................... 251 Sludge Application .................................................................................................... 252 Adsorption and Mobility .......................................................................................... 252 Extractions and Bioavailability ................................................................................ 253 Case Study ..................................................................................................................... 254 Nitric Acid Extraction ................................................................................................... 256 .-\AAc-EDTA Extraction .............................................................................................. 260 Concentrations in Soil Solution .................................................................................... 262 Movement ...................................................................................................................... 266 Summary ........................................................................................................................ 260 References ...................................................................................................................... 270 Chapter 13. Heavy Metal Contamination in Industrial Areas and Old Deserted Sites: Investigation, Monitoring, Evaluation, and Remedial Concepts .......................................................................................... 273

I

Irena Twardowdka, S. ScbuLte-Hodtede, and AntoniUd A.E Kettrup Introduction ................................................................................................................... Impact of Long-Term Stack Emission ......................................................................... Site Characteristics ................................................................................................... Site I: Nowa Huta n/Cracow, Area Adjacent to the Sendzimir Steelwork Complex, Poland ...........................................................

273 274 274 274

Site II: Irena Glasswork, Inowroclaw, Poland ..................................................... Soil Enrichment with Heavy Metals in the Areas Impacted by a Long-Term Stack Emission .............................................................................. Screening Survey and Methods ............................................................................ Metal Distribution in Soil vs. the Duration and Extent of Emission ................. Barrier Capacity of a Surface Soil Layer ............................................................. Heavy Metal Binding Strength and Mobility in Soils ......................................... Monitoring Program Requirements for Risk Assessment from Large-Area Soil Contamination by Trace Metals from Anthropogenic Sources ............... Evaluation of a Large-Area Deserted Industrial Site ................................................. Site Characteristics ................................................................................................... Sources of Heavy Metal Contamination in the Area ........................................... Monitoring Strategy ................................................................................................. Survey of Transfer Pathways and Risk Receptors .............................................. Human Risk Potential Assessment .......................................................................... Approach to Human Risk Potential Assessment ................................................. Applied Model: Quantitative Exposure Assessment (QEA) .............................. Remedial Concepts ........................................... ~ ............................................................ Summary ........................................................................................................................ References ......................................................................................................................

281 287 287 291 292 293 298 300 300 300 302 302 304 304 306 316 319 319

Index .............................................................................................................................. 323

CHAPTER I

Sorption Kinetics of Trace Elements in Soils and Soil Materials Daniel G. Strawn and Donald L. Sparks

INTRODUCTION Environmental contamination resulting from the extensive use of metals and semimetals in industry, agriculture, and in manufactured products has magnified the threat of toxicity for plants, animals, and society. Since soils and sediments have a large capacity for sorbing trace elements, an understanding of metal reaction mechanisms with natural materials is critical. Many studies have appeared in the literature on various aspects of metal sorption. Results from these studies have been used to develop government regulations, devise cleanup strategies, and develop models that predict the fate of trace elements in the environment. However, in conducting these studies researchers often overlook two important aspects: (1) the length of time soils are exposed to a contaminant (residence time) in the laboratory is relatively short compared with the much longer residence times that exist in field contaminated soils, and (2) the kinetics of metal sorption and desorption are often slow. These oversights lead to improper evaluation of contaminant behavior in the environment, resulting in regulations that may be improper, and models and remediation strategies that may be unsuccessful. This chapter will investigate the effects of residence time (aging) and slow kinetics on sorption and desorption reaction mechanisms of metals with soils and soil materials (e.g., clay minerals, metal oxides, and organic matter). Such information is important, and can be used in combination with transport models to predict the fate of trace metals through the vadose zone, and can provide information on metal bioavailability and speciation. Trace elements exist in the soil as either aqueous species, as structural elements in solids, or sorbed onto the surfaces of soil materials. While many of these trace elements are present naturally in the environment, their indigenous levels are usually nonthreatening. The buildup of these elements to dangerous levels is a result of commercial use and disposal practices. The following are a few examples of common sources of contamination: disposal of batteries that contain Pb, Cd, and Hg; exhaust from automobiles that

2

Fate and Transport of Heavy Metals in the Vadose Zone

burn gasoline with Pb additives; application of pesticides that contain Pb and As, e.g., Pb3 (As0 4)2; the use of Pb in paint; trace elements which are used in manufacturing that end up in waste disposal and the environment from either discarding the product or as a by-product of the manufacturing process; desiccation of agricultural runoff water in ponds which results in Se and As concentrating to dangerous levels; disposal of sewage which contains several trace elements, in particular heavy metals; and mine drainage which is often acidic and can increase the mobility of metals. Scientific studies have clearly shown that exposure to metal contaminants at higher than natural levels is toxic. As a result, many past uses and disposal practices of metals are now illegal, and trace element contamination of the environment is now regulated more closely. However, due to the relatively low solubility of many trace metals, and often strong sorption to soils, environmental contamination persists, and the threat from contaminants remains a problem that merits continued scientific investigation. While toxicity from trace elements, and their presence in the environment at dangerous levels are well-established facts, the questions remain: how does one remediate contaminated soils effectively, and how can significant risks be accurately evaluated? Finding effective answers to these questions hinges on a clear understanding of the behavior and interactions of trace elements with soils. In particular, an understanding of slow desorption and release kinetics from environmental settings which have been contaminated for long periods is critical. For example, Smith and Comans (1996) conducted sorption and desorption experiments on Cs contaminated sediments. They found that failure to include slow reactions in their model gave much lower estimates of the remobilization potential of the Cs. They concluded from model fits that sorption half-lives were between 50 and 125 days, and desorption half-lives were on the order of 10 years. Many studies rely on an equilibrium approach to predict the retention of contaminants on natural materials and subsequent migration through the vadose zone. Researchers often focus on determining parameters such as distribution coefficients, and the maximum amount of sorption possible. These studies are often based on the contaminantsolid interactions over a short period (24 hours or less) because it is assumed that the reaction has reached completion (Griffin et aI., 1986). However, field soils are seldom, if ever, at equilibrium, often laboratory studies are also far from equilibrium, and slow sorption may change the distribution between solid and solution over a period of time (Smith and Comans, 1996; Sparks, 1998). This is primarily due to slow metal sorption and desorption kinetics. The failure to account for the slow kinetics results in either underpredictions of the amount of contaminants retained by soils and minerals, or overpredictions of contaminant availability in the environment. A better approach is to base mobility estimates, remediation strategies, and risk assessments on the true availability of the contaminant, which is often controlled by a rate-limited sorption reaction. Most soils are heterogeneous media that contain a host of different minerals, solids, and organic materials. Thus, the interaction of trace elements with soils is a heterogeneous process. Several possible sorption mechanisms have been proposed (Figure 1.1): diffusion into micropores and solids followed by subsequent sorption onto interior surfaces; sorption to sites of variable reactivity, including sites which involve different bonding mechanisms, i.e., inner-sphere vs. outer-sphere and monodentate vs. bidentate; and surface precipitation (Fuller et aI., 1993; Loehr and Webster, 1996; Scheidegger and Sparks, 1996). Due to the heterogeneity of soil, these processes can occur simultaneously. A

Sorption Kinetics of Trace Elements in Soils and Soil Materials

3

Figure 1.1. Schematic of soil particles illustrating the different types of sorption that are possible. See text for definitions.

measured sorption or desorption rate often reflects a combination of all of the sorption mechanisms. However, it is possible that one mechanism may dominate at a particular time in the sorption reaction and the measured rate is primarily an expression of that reaction rate. For example, outer-sphere complexation can precede inner-sphere complexation, which can precede surface precipitation. The significance of this continuum in sorption is that while many sorption and desorption reactions may appear to have reached equilibrium, in fact the reaction can be continuous, and the slow process will not be measured if the experimentalist studies a short reaction time. In such cases, important secondary processes which are slower than the primary process may be completely overlooked. Thus, predictions on the fate of the contaminant may be inaccurate. This can cause increased threats of toxic exposure, improper evaluation of risks, and/or misappropriation of valuable cleanup and public safety funds. To protect human health and the environment from overexposure there must exist effective cleanup strategies, accurate risk assessment technologies, and models that correctly predict the fate of trace elements. For these tasks to be accomplished, time dependent reactions of trace elements with soils must be taken into consideration. Thus, the goals of this chapter are to discuss the kinetics of trace element interactions with soil and soil components, including the importance of slow reactions and possible sorption mechanisms.

EVIDENCE FOR SLOW SORPTION AND DESORPTION REACTIONS There are two separate phenomena associated with slow kinetic sorption processes: (1) a continuous slow removal of the sorptive from solution (sorption), and (2) a slow release of the sorbate from the sorbent (desorption). The second of these phenomena, desorption or release, may be influenced by the length of time in which the contaminant is in contact with the sorbent; i.e., there may be a decrease in the ability of the sorbate to be removed from the surface with increasing incubation or residence time. As mentioned above, several hypotheses for the cause of these two phenomena have been proposed (they are discussed in detail in later sections). An early report on the effect of incubation time on desorption reactions of metals from soils was given by McKenzie (1967). It was observed that manganese nodules present in Australian soils accumulated a large amount of Co. To account for this selective accumulation, a continuous sorption reaction was hypothesized. To test this, McKenzie (1967)

4

Fate and Transport of Heavy Metals in the Vadose Zone

determined both sorption and desorption kinetics of Co on manganese nodules isolated from soils. He found that removal of Co from solution slowed considerably after two days, but the extent of desorbability showed a continuous decrease with increasing aging periods. Thus, Co that was sorbed would become increasingly resistant to desorption from the nodule with time, resulting in an accumulation over time. Sorption processes commonly come to a state of quasi-equilibrium rapidly, and many researchers terminate their sorption experiments at relatively short times. However, it has been shown that sorption is a continuous process, and that the sorption mechanism can change over time, with little additional uptake. For example, Nyffeler et aI. (1984) found that the distribution coefficients for Be, Mn, Zn, Co, and Fe sorption on particulate matter from surface sediments and sediment traps increased over the entire time of observation, 108 days (Figure 1.2), suggesting that sorption is a slow process. Similarly Bruemmer et al. (1988) found that Ni, Zn, and Cd uptake by soils was continuous for times up to 42 days; e.g., Ni removal from solution at pH = 6 was 12% in two hours and 70% in 42 days. Bibak et al. (1995) studied the retention of Co by various goethite polymorphs and impure goethite. They found that Co sorption behavior varied between the different polymorphs and minerals, but in all samples the Co uptake increased with contact time (sorption kinetics measured from two hours to 504 hours). McBride (1982) found that sorption of Cu on noncrystalline aluminum oxide increased over periods of weeks, and proposed that different bonding mechanisms were responsible for the slow sorption process. McLaren et al. (1983) studied the desorption of Cu from humic acid, ferro-manganese concretions, and montmorillonite. In the desorption procedure the sorptive solution was replaced by the electrolyte solution (no metal), the suspension was allowed to incubate for four hours, and then, new electrolyte solution was added. The repeated washing of the soil removed little of the Cu, demonstrating that Cu sorption was strong. Young et al. (1987) compared Cu sorption and desorption reactions on river sediments with Cr and Zn. They observed that sorption of Zn was complete in four hours, Cr sorption was far from complete after 48 hours, and Cu sorption kinetics were intermediate. In addition, Young et al. (1987) concluded that desorption was not irreversible as McLaren et al. (1983) found, but that the observed irreversibility was a result of the slow kinetics involved. This slow desorption phenomenon was also observed for phosphate by Lookman et al. (1995). They found that slow phosphate desorption from soils continued for up to 1,600 hours, and showed no signs of reaching a plateau. In fact, using a rate constant derived from a first-order fit of the slow reaction, they predicted that 500 days would be required for desorption of 90% of the phosphate. Several researchers have noted that not only are trace elements strongly sorbed and exhibit slow desorption kinetics, but that the rate of desorption decreases with increasing residence times. Padmanabham (1983) conducted desorption experiments ofCu from goethite and concluded that Cu was sorbed in two different ways: a fraction was associated with low bonding energy and the rest was associated with high bonding energy. It was observed that a gradual interchange with increasing incubation time occurs between the readily desorbed fraction (low energy) and the less readily desorbed fraction (high energy). Similar results were found by Kuo and Mikkelsen (1980), Schultz et al. (1987), and Backes et al. (1995), who showed that the desorption rate of several transition metals (Zn, Co, and Cd) from soils and soil components decreased with increasing

Sorption Kinetics of Trace Elements in Soils and Soil Materials --- --------

5

---~-"'------

10000000 1000000 o Fe

~

100000

'ai

10000

0

a:

_____ ---------------------------.:e

:eMn oBe

aCo .Zn

c 0

.';=

::s .c ·c "Iii

is

1000 100 10

o

20

40

60

80

100

120

Incubation Time (Days)

Figure 1.2. Effect of incubation time on the distribution coefficient (1Cd>Co, hysteresis increased. However, Bibak et al. (1995) predicted that the mechanism responsible for the slow reaction of Co on various iron oxides was diffusion. This prediction was based on a good fit of the data to a diffusion model. An important point to note about comparing these two systems is that in the experiments of Ainsworth et al. (1994) the initial Fe-oxide was amorphous and underwent recrystallization, while the Fe-oxides used in the experiments of Bibak et al. (1995) were crystalline and did not undergo a solid phase transformation. Such differences can have important consequences on sorption mechanisms. Despite this discrepancy, one can conclude from these studies that in order to better predict the mechanisms responsible for the slow kinetic processes, microscopic as well as macroscopic data are necessary.

DIFFUSION-CONTROLLED KINETIC REACTIONS Diffusion is an activated process driven by the necessity of a system to be at its lowest possible energy, i.e., uniformly distributed throughout space. Since soils are porous materials containing both macropores (>2 nm) and micropores «2 nm) (Pignatello and Xing, 1996), diffusion is a mechanism that can control the rate of sorption of trace elements on soils. These pores can be interparticle (between aggregates) or intraparticle (within an individual particle). Intraparticle pores can form during weathering, upon solid formation, or may be partially collapsed interlayer space between mineral sheets; i.e., vermiculite and montmorillonite. The rate of diffusion through a pore is dependent on pore size, particle size, tortuosity, chemical interactions, chemical flux through the soil, and whether the pore is continuous or discontinuous. Besides pore diffusion, solid-

Sorption Kinetics of Trace Elements in Soils and Soil Materials

9

phase diffusion is also a transport-limited process. Solid phase diffusion is dependent on the characteristics and interactions of the diffusant and the solid (Pignatello and Xing, 1996). Since there exists a range of diffusion rates in the soil, it follows that with increasing exposure time the fraction of contaminants in the more remote areas of soil particles (accessible via slow diffusion) will increase. This slow sorption phenomenon is often the explanation researchers use to account for the slow continuous sorption and desorption observed between metals and soil (Sparks, 1989; Burgos et aI., 1996). Bruemmer et aI. (1988) measured sorption and desorption of Cd, Zn, and Ni with goethite, a porous iron oxide known to have defects within the structure in which metals can be incorporated to satisfy charge imbalances. They found that the kinetics were described well with a solution to Fick's second law (a linear relation with the square root of time), and proposed that the uptake of the metal followed a three-step mechanism: "(i) adsorption of metals on external surfaces, (ii) solid-state diffusion of metals from external to internal sites,O and (iii) metal binding and fIxation at positions inside the goethite particle," suggesting that the second mechanism is responsible for the slow reaction (Bruemmer et aI., 1988). Similar observations on sorption of divalent metal ions were made by Coughlin and Stone (1995). They suggested that the slow sorption and desorption could be a result of slow diffusion that occurred because their synthetic goethite may have had an unusually high level of pores and cavities. Axe and Anderson (1997) also found that sorption of Cd and Sr could be characterized by a model which included two steps: a rapid reversible sorption step followed by a slow, rate-limiting process involving the diffusion of the cations through small pores existing along the surface. While the above examples have hypothesized that diffusion is the rate-limiting step based on good model fIts to data and some speculation, macroscopic sorption experiments are not defInitive proof of a mechanism (Sposito, 1989, p. 150). To give additional support to diffusion as a mechanism for sorption onto porous media, Papelis (1995) measured surface coverages of Cd and selenite on porous aluminum oxides using X-ray photoelectron spectroscopy (XPS). Papelis (1995) calculated the expected thickness of sorbed Cd and selenite from the total metal loss from solution using both external and internal surface areas. A good agreement was found between the calculated and the measured (using XPS) surface coverage thickness when the total surface area (i.e., internal and external surface area) was used. When the surface layer thickness was calculated without considering internal surface area, then the calculated thickness exceeds the thickness observed using XPS. Therefore, the most likely sorption mechanisms were sorption to external sites, diffusion of Cd into the internal structure, and subsequent sorption. While Papelis (1995) didn't measure the kinetics of the reaction, it seems probable that the sorption to the interior sites is slower than the exterior sites, and thus a slow kinetic sorption step would exist. Fuller et aI. (1993) combined kinetic sorption and desorption experiments with spectroscopic observations (Waychunas et aI., 1993) to conclude that the rate-limiting process in arsenate sorption by ferrihydrite is diffusion into the solid structure. Using X-ray

• Classical solid-state diffusion is a very slow process in crystalline structures, and usually only significant at very high temperatures (McBride, 1994, p. 28). In this case, solid state diffusion should be interpreted as diffusion processes through faults and micropores.

10

Fate and Transport of Heavy Metals in the Vadose Zone

0.12

60

0.1

__--------r---------r---A---~50

'0 0.08

40

CI>

1!i

'0.

e Il.

CI>

eo

o

III

~ 0.06

30 ~

...as

(5

::!!

CI>

u.

~

"C

.--------_......._.._..._...._....•..•....

0.04

_

............................

_ _ ...•....•...•.•..

~

-

....................... ....

20

:.!! 0

~/

0.02

/

/

./

10

0+----------.---------.----------.----------+0 o ~ 100 150 ~o Time (Hours)

Figure 1.6. Pore-space diffusion fit of As(V) adsorption density as a function of time for total (dark line), diffusion-limited (dotted line) and exterior surface components of adsorption (thin solid line). The solid triangles represent the adsorption data. Exterior sites are modeled based on equilibrium. From Fuller et al. (1993), with permission.

absorption fine structure (XAFS) spectroscopy, Waychunas et al. (1993) found that arsenate is sorbed predominantly as inner-sphere bidentate complexes, regardless of whether the arsenate was adsorbed post-mineralization of the ferrihydrite, or present during precipitation. Thus, at the pH of their study (8.00), arsenate surface precipitates were not formed. Slow sorption and desorption were explained as slow diffusion of the arsenate to or from interior surface complexation sites that exist within disordered aggregates of crystallites. The arsenate sorption and desorption kinetics (Figure 1.6) were explained well using a model which included two types of sorption sites: those easily accessible were described assuming equilibrium (thin solid line), while the sites which had limited accessibility (dotted line) were well represented by an equation which is based on Fick's second law of diffusion.

Kinetics and Mechanisms of Adsorption Processes Adsorption is a phenomenon in which matter accumulates at the interface between a solid phase and a solution phase; it is largely considered to be two-dimensional (Sposito, 1989, p. 132). Adsorption reactions are governed by the laws of thermodynamics: energy is conserved, and the entropy of a system increases to a maximum. These two concepts can be combined to create the Gibbs free energy (G) function. For a reaction to occur, the products must have a lower free energy than the reactants (~G < 0). This can occur by either a decrease in enthalpy, an increase in entropy, or both. It is important to note that a change in enthalpy can dominate the free energy function creating a negative ~G even when the entropy is decreased in the reaction, and vice versa. Therefore, an

Sorption Kinetics of Trace Elements in Soils and Soil Materials

11

adsorption process leads to an association between an ion and a surface, driven by the desire of the system to achieve an overall lower free energy. While thermodynamics can be used to determine if a reaction is favorable, it does not indicate the rate of the reaction, nor the pathways involved in arriving at the state with the lowest free energy. This information can be gained by measuring reaction kinetics. In real systems, such as soils and sediments where there exist several different types of sorption sites, reaction mechanisms and kinetics can be heterogeneous. In these systems kinetics plays an important role in the fate of trace elements since such systems are not at equilibrium, but are continuously undergoing chemical changes as they seek to produce the most stable species (Steinfield et al., 1989, p. 1). The change may be slow, resulting in the sorbate becoming less available with time (aging) (Koskinen and Harper, 1990), and can result in a change from one type of sorbed complex to another. This process is similar to the concept of the Ostwald-step rule: the first product in a precipitation reaction is that which has the highest solubility, followed by a slow continuous transformation to a more stable species (Stumm and Morgan, 1996, p. 807). An analogous process in adsorption would result in a multitude of adsorbed complexes, some of which may be in a metastable equilibrium state, undergoing continuous transformation to the most stable species. Evidence for this slow, continuous change to a more stable species is commonly observed for solid materials. Upon initial precipitation the solid is in an active form that has a disordered lattice (amorphous), and exists in a metastable equilibrium with the solution (Stumm and Morgan, 1996, p. 356). With time the solid slowly converts to the more stable inactive form. The inactive form is more crystalline-like, and has a lower solubility. This slow kinetic phenomenon may continue for geological time spans. An example is aragonite (a polymorph of calcite), which is found in rocks < 300 million years old. Aragonite is not thermodynamically stable, but forms under surficial temperatures and pressures, and slowly reverts to the more stable calcite (Blackburn and Dennen, 1994, p. 102). Waychunas et al. (1993), using XAFS data fitting, found that aging and continued polymerization of ferrihydrite resulted in a transformation of the number of linkages and interatomic distances to those suggesting a progression to the more ordered polymorph goethite. The slow transformation of a solid to a state with a lower free energy is often observed as an aging mechanism for precipitates, but transformations between sorption mechanisms is more difficult to distinguish, and little direct evidence exists for such processes. However, it seems reasonable to suggest that the energetics of sorption and desorption reaction processes are analogous to those of precipitation; i.e., kinetically limited by a transformation to the most stable sorption configuration (lowest ~G). Adsorption reactions occur via three different mechanisms: inner-sphere complexes, outer-sphere complexes, and diffuse ion (Figure 1.7, diffuse ion not indicated) (Sposito, 1989, p. 132). Outer-sphere bonds consist of a solvated ion that forms a complex with a charged functional group; the primary bonding force is electrostatic. An inner-sphere complex is partially dehydrated; the ion forms a direct ionic or covalent bond with the surface functional groups. A diffuse ion exists in the water layers near the surface, and is held by electrostatic attraction from permanent charges that exist in the solid structure. A major difference between the outer-sphere complex and the diffuse ion complex is in the strength of the electrostatic force, which is directly correlated to the proximity of the ion to the surface (McBride, 1994, p. 73). The type of sorption and bonding mechanism

12

Fate and Transport of Heavy Metals in the Vadose Zone

Metal

Oxygen H+

j

'H

a

Other Examples

aerD 0

"d Doa

Outer-Sphere Surface Complexes

Monodentate

Inner-Sphere Surface Complexes Bidentate

Figure 1.7. Schematic showing the different types of adsorption complexes that can occur on solid surfaces. See text for definitions. From Hayes (1987), with permission.

depends on several factors: (1) ionic radius, (2) electronegativity, (3) valence charge, (4) surface type, and (5) ionic strength of the sorptive solution. There are two major types of surface sites: variable charged sites, e.g., silanol and alumino!; and permanent charge sites that result from isomorphic substitution. To model surface complexation and understand the controlling mechanisms, scientists often assign a hypothetical bonding mechanism between an ion and a given surface. However, ions can bond to surfaces via several different mechanisms, and can undergo a continuous transition between adsorption mechanisms (Stumm and Morgan, 1995, p. 586). Waychunas et al. (1993) found that arsenate adsorbed onto ferrihydrate by both monodentate (30%) and bidentate bonding mechanisms. Bargar et al. (1996) used X-ray

Sorption Kinetics of Trace Elements in Soils and Soil Materials

13

absorption spectroscopy (XAS) to distinguish between outer- and inner-sphere sorbed Pb on CX-AI 20 3. They found that on the planar 0001 surface Pb-O-AI distances were consistent with an outer-sphere bond, while on the 1102 plane Pb was sorbed as an inner-sphere complex. Benjamin and Leckie (1981) conducted sorption experiments at several different loading levels and equilibrium pHs for Cd, Cu, Zn and Pb on amorphous iron oxyhydroxide. Their data suggested that there exist several types of bonding sites with variable bonding strengths, and that measured equilibrium constants are average values from these different types of sites. McBride (1982) found similar results on pure noncrystalline aluminum oxide using electron spin resonance (ESR) spectroscopy to study the change in Cu sorption mechanisms with time. He found that sorption involved sites of varying reactivity. The first reaction step was the rapid sorption of a low level of Cu; the second reaction occurred over several weeks and resulted in the uptake of a greater amount of Cu and ESR spectra distinct from the first reaction step. Such heterogeneity is enhanced in natural systems that contain materials with a variety of organic and inorganic surface sites. Adsorption reactions are often considered to form the most stable bond immediately, but commonly there are intermediates which can be metastable for long times. In fact, adsorption may consist of a series of chemical and physical reactions that may limit the overall reaction rate; i.e., ion and surface dehydration, breaking of a strong bond, bond formation, and surface diffusion (Stumm and Morgan, 1996, p. 761; McBride, 1994, p. 135). Hayes and Leckie (1986) and GrossI et al. (1994) used pressure-jump relaxation to measure the kinetics of Pb sorption on aluminum oxide and Cu(II) sorption on goethite, respectively. They found that the best fit to the data was obtained by fitting a kinetic model that included a transformation from outer-sphere to inner-sphere complexation. Their results also suggested that sorption behavior was biphasic, which they explained by suggesting that the slower reaction was a result of sites with lower affinities. This concept is similar to the high and low affinity site model proposed by Dzombak and Morel (1990, p. 92). While the kinetics of these reactions are quite rapid (reactions considered on a millisecond time scale), the demonstration of a multiple step adsorption mechanism rationalizes the hypothesis that in some systems one step may be slow enough to be responsible for the slow adsorption and desorption reactions often observed in soils (Sposito, 1989, p. 150). The kinetics of Pb sorption on y-AI203 are shown in Figure 1.8. These data show a fast initial reaction followed by a slow sorption reaction continuing for several hours. Such biphasic behavior is likely a result of sorption to sites of variable reactivity and/or diffusion limited sorption. Slow surface precipitation reactions can be ruled out because analysis of the radial structure function obtained using XAFS (Figure 1.9) does not exhibit any major features (e.g., second peaks indicative of second shell neighbors) beyond the primary Pb-O structural peak at -1.9 A (uncorrected for phase shifts) with long incubation times. Biphasic sorption reactions have also been observed in soils. An example is the result of Lehman and Harter (1984) who measured the kinetics of chelate-promoted Cu release from a soil to assess the strength of the bond formed. Their sorption/desorption data were biphasic, which they attributed to high and low energy bonding sites. They also found that with increased residence time, 30 minutes to 24 hours, there was a transition of the Cu from low energy sites to high energy sites (as evaluated by release kinet-

14

Fate and Transport of Heavy Metals in the Vadose Zone

--.

60

c:

50

. ~ 0

0 .;::;

::J

(5

C/)

E 0 ....

-"0 Q)

40 30

>

20

E Q)

c:

10

a..

0

0

• •

•

•

•

.n

0

2

4

6

8

188

190

192

Time (hours) Figure 1.S. Kinetics of Pb removal from solution by y-AI 2 0 3 • Ionic strength = 0.1, pH = 6.50, initial Pb concentration = 0.002 M.

"C

1.0 0.5

±::

0

Q)

:::I

c:

, -__~__~__________~70Days

g> ~

8 Days

E ....

~~------------

.E en c:

~

48 Hours

r-

24 Hours

o

2

3

4

5

R (A)

6

7

8

9

Figure 1.9. Radial distribution function (uncorrected for phase shifts) for Pb sorbed on y-A1 2 0 3 incubated for 24 hours to 70 days. Incubation conditions are the same as in Figure 1.8.

ics). Incubations for up to four days showed a continued uptake of Cu and a decrease in the fraction released within the first three minutes, which was referred to as the low energy adsorbed fraction. The results of Smith and Comans (1996), already mentioned, also showed that Cs sorption onto sediments is biphasic. They modeled exchange reactions assuming exchangeable and fixed fractions. The fixed fraction was assigned to Cs that was incorporated in the mineral lattice, i.e., predominantly specific exchange sites on illitic clay. The Cs adsorption mechanisms proposed by Smith and Comans (1996)

Sorption Kinetics of Trace Elements in Soils and Soil Materials

15

'were based on kinetic experiments, i.e., macroscopic observations. Kim et al. (1996) used nuclear magnetic resonance (NMR) spectroscopy to make microscopic observations of Cs sorption mechanisms on kaolinite, boehmite, silica gel, and illite. Their experiments coincide with those of Smith and Comans (1996), suggesting that Cs formed two distinct types of complexes on the surfaces of the minerals: inner-sphere and outersphere. The energy and stability of adsorbed species varies depending on the type of surface complex formed. It is generally accepted that surface complexes with more than one bond are more stable than complexes with a single bond (Stumm and Morgan, 1996, p. 276; McBride, 1994, p. 134), and likewise for inner-sphere vs. outer-sphere sorption (McBride, in Bolt, 1991, p. 168). One explanation for the increased stability of a multidentate bond over a monodentate bond may be the increased entropy gained from a more stable configuration (steric effect) (Steinfield et al., 1989; McBride, 1994, p. 80) . .w analogous phenomenon is the Chelate Effect; for example, the ~G for the ethylenediamine complex, a chelate ring with bidentate bonding to a cation, is lower than ~G of the diamine complex, which forms monodentate complexes with cations (Stumm and Morgan, 1996, p. 279, from Schwarzenbach, 1961). The lower ~G for the ethylenediamine complex means it is more stable. Since the enthalpies for the complexation of cations by the two chelates are similar, the lower ~G is a result of an increased entropy for the bidentate ring complex; as mentioned above, this phenomenon is often referred to as a steric effect or configurational entropy (Stein field et al., 1989, p. 250; McBride, 1994, p. 80). Since the reactive sites on minerals (silanol and aluminol sites) and organic matter (carboxyls and phenolic-OH) are often considered to be analogous to ligand functional groups, the steric effect is likely to be an important consideration when determining mechanisms of trace element adsorption reactions in soil. Thus, it is reasonable to conclude that if the coordination environment is appropriate, multidentatebonding will be favored (thermodynamically) over monodentate bonding. However, the formation of multiple bonds may have intermediate products that have a higher activation energy than a complex with only a single bond. As discussed below, an increase in the activation energy may limit the kinetics of complex formation. The formation of a surface complex, or conversion of an adsorbate from one bond type to another, may be thermodynamically favored but inhibited by an activation energy, which is the extra energy, beyond the difference in the free energy between the products and reactants (~GO), required to complete the reactions (Figure 1.10). The activation energy results from the energy required to form intermediate products not accounted for in the reaction stoichiometry (Noggle, 1989, p. 532). A large activation energy will result in slower adsorption and desorption kinetics compared to sorption processes which have a lower activation energy. Since the strength of adsorption varies depending on the surface and adsorptive being considered, the adsorbate availability (via desorption) and kinetics are variable (Pignatello and Xing, 1996). For many adsorbed ions it is found that the rate of adsorption is faster than desorption (McBride, 1994, p. 134; Swift and McLaren, in Bolt, 1991, p. 285). A possible reason for the slower rate of desorption is an increase in the activation energy required to break the adsorption bonds. The activation energy for desorption can be quantified as follows: ~G:j:desorption = ~G:j: adsorption + ~Go adsorption' where ~G:j: desorption = activation energy for desorption, ~G:j:adsorption = activation energy for adsorption (~O), and

16

Fate and Transport of Heavy Metals in the Vadose Zone

Activated Complex*

~G

Aque?us---------l-~~;-------

---

Species

--------------- ---------------- ------------------------------

Sorbed Complex

........E---------Desorption Sorption - - - - - - - -...

Reaction Coordinates Figure 1.10. Schematic diagram of G vs. reaction coordinate for sorption and desorption processes. Adapted from Sparks and Jardine (1981), with permission.

~Goadsorption

energy of adsorption, see Figure 1.10 (McBride, in Bolt, 1991, p. 168). This equation indicates that desorption of chemisorbed ions yields a larger activation energy than adsorption reactions, causing desorption to be a slower process. This may be the cause of the pseudo-hysteresis that is commonly observed in sorption and desorption experiments; i.e., the forward and reverse isotherms do not overlie when given the same reaction time. The experiments of McLaren et al. (1986) were discussed briefly in an earlier section; however, another look at their results is merited at this point to evaluate possible mechanisms. They found that Co sorbed by a soil oxide demonstrated a continuous decrease in isotopic exchangeability as sorption times increased (only 20% was exchangeable when sorption was carried out for 50 days) (Figure 1.11). For humic acid, the isotopic exchangeability of sorbed Co decreased only slightly with increased sorption incubation time (Figure 1.12) (the amount of Co that was isotopically exchangeable remained as high as 80% for 50 days of sorption incubation time). It is difficult to prescribe a particular mechanism as the cause for the aging observed in McLaren's studies; however, it is possible that a more stable complex is being formed on the oxide with increasing sorption incubation time, increasing the energy required for isotopic exchange. Eliminating diffusion as a slow exchange mechanism seems reasonable in this case since the humic acid fraction, a porous material, lacked a slow exchange portion. However, more detailed studies and measurements of the porosity of the two materials is needed for diffusion to be completely ruled out. Surface precipitation is difficult to eliminate; the authors =

Sorption Kinetics of Trace Elements in Soils and Soil Materials -

- ---- ---- -

---

17

-------

900 800

•

•

•

•

•

700 600

";"0)

~

:; 500 (I)

"§

400

0 (,)

300

III

-g

200 100

a a

10

20

30

40

50

Time (days) Figure 1.11. Isotopic exchangeability of Co sorbed by soil oxide: total Co sorbed (+), and isotopic exchangeable (.). The space in between the two lines indicates the nonisotopic exchangeable fraction. From McLaren et al. (1986), with permission.

20

•

•

18 -16 ~

";"0) 0)

.a.

15 g kg-I) organic carbon content (OC) was the soil constituent mainly affecting adsorption capacity parameters whereas in subsoil horizons

46

Fate and Transport of Heavy Metals in the Vadose Zone 10

•

AEh (soil no. 8)

0 0

......

.,....

•

I

Q)

.::t:. 0

E E ........

a

0.1

0 0

0 0

0.01

0.001 0.0001

.~o

0.001

saturation extract

•

1 : 5 extract

0.1 [mmol L-1]

0.01

C

0

10

Figure 2.9. Quantity-intensity relationships of Ni obtained in saturation extracts and at 1 :5 for soil no. 8.

(oe < 15 g kg-I) dithionite-extractable Mn (Mnd) was the major influencing constituent. Correlation coefficients are presented in Zehetner (1997). In the topsoils, oe displayed tighter correlation with b l than with b 2 whereas in the subsoils, Mnd showed the opposite trend. Thus, organic matter may be strongly involved in (specific) adsorption of Ni on high energy sites. Neither in topsoils nor in subsoils did clay content show significant correlations with adsorption capacity parameters. This may be due to the relatively low variation in the clay content of the studied soils and the old age of the soil material, indicated by low feldspar and smectite contents and high kaolinite contents, which was determined for selected soils by X-ray diffraction. Effect of Soil:Solution Ratio on Quantity-Intensity Relationships The adsorption experiments were conducted in saturation extracts at soil:solution ratios between 1:0.4 and 1:0.7, which are closer to field conditions than tighter soil:solution ratios most commonly applied in adsorption experiments in the literature. For the horizons of a spodosal (soils no. 8-12), the adsorption isotherms obtained in saturation extracts were compared with quantity-intensity relationships at a soil:solution ratio of 1:5 (Figures 2.9 to 2.13). In the low concentration range (Ni solution concentrations in the order of 10-4 to 10-.3 mmol L -I), the quantity-intensity relationships were hardly affected by the soil:solution ratio. At applied initial Ni concentrations of 0.1 and 10 mmol L -I, however, the amounts of Ni adsorbed per mass soil were significantly higher in the 1:5 extracts than in the saturation extracts, and despite a slighter decrease of Ni solution concentrations due to adsorption in the 1:5 extracts, the obtained datapoints were significantly above the adsorption isotherms obtained in saturation extracts. Thus, in the low concentration range quantity-intensity relationships may be satisfactorily described by using tighter soil:solution ratios whereas at higher concentrations these would cause false assessment of adsorption. At a given solution concentration the amount adsorbed per mass soil would

Adsorption Isotherms of Nickel in Acid Forest Soils 10

•

Bhs (soil no. 9)

o

o

.......... ::t:.

o E E .........

a

o

•o

'0>

0.1

o

47

o

~o

0.01

o saturation extract •

1: 5 extract

0.001 +-...,.......,...,........,.".---..-...........rTTTTr-....-r-rTTTnr-.....-.........n-nr--,-.......,..........." 0.1 10 0.001 0.01 0.0001

C [mmol L- 1] Figure 2.1 O. Quantity-intensity relationships of Ni obtained in saturation extracts and at 1 :S for soil no. 9.

10

•

Bs (soil no. 10)

.......... ,

0

0>

::t:. 0

E E .........

a

·0

0

0

0.1 0 0

0.01

0.001 0.0001

~o 0.001

saturation extract

•

1 : 5 extract

0.1 [mmol L- 1]

0.01

C

0

10

Figure 2.11. Quantity-intensity relationships of Ni obtained in saturation extracts and at l:S for soil no. 10.

be overestimated, and at a given adsorbate concentration the corresponding equilibrium solution concentration would be underestimated. Thus, soil:solution ratios of 1:5 and tighter, used in the majority of (Ni) adsorption studies in the literature, may result in quantity-intensity relationships that strongly overestimate adsorption, especially at higher concentrations, and are therefore of limited value for modeling metal mobility in natural systems. Specific adsorption may be responsible for the observed low influence of the soil:solution ratio on quantity-intensity relationships in the low concentration range. Involving covalent and ionic bonding, specific adsorption can be regarded as a chemical

48

Fate and Transport of Heavy Metals in the Vadose Zone 10

Bw (soil no. 11)

•

....... ......

~ ~

• 0

o

0.1

E ........

a

o

o

o 0.Q1

o

o

0.0001

0.001

o saturation extract • 1: 5 extract 0.01

10

0.1

C [mmol L- 1] Figure 2.12. Quantity-intensity relationships of Ni obtained in saturation extracts and at 1:5 for soil no. 11. 10

•

Cw (soil no. 12) o

.......... ...... '0)

•

~

~

0

o 0.1

o

E ........

a

o

o 0.01

o

o saturation extract • 1: 5 extract

o. ro

:;::::;

-50 -

Q)

c::

-

o *

saturation extract

1: 5 extract

-100 -

Figure 2.15. Effect of applied initial Ni concentration and soll:solution ratio on relative adsorption for soil no. 11.

Fractionation of Adsorbed Nickel The h izons of a spodosal (soils no. 8-12) were used to study the influence of applied imtla i concentration on the fractionation of adsorbed Ni (Figures 2.16 to 2.20). e blank treatment displays the distribution of initially present Ni. In all the studied rizons, the dominant initially present Ni fractions were, in the order of decreasing Ni concentration, residual Ni, Ni bound to crystalline Fe-oxides, and Ni bound to amorphous Fe-oxides (fractions 7, 6, and 5). In the Bs, Bw, and Cw horizons (soils no. 10, 11, and 12) these three fractions almost exclusively contributed to the total Ni contents, which were higher than in the horizons above. In the Bhs horizon (soil no. 9), organically bound Ni (fraction 4) also significantly contributed to the total Ni content, and notable Ni contents could be identified, in the order of decreasing Ni concentration, in the mobile, the Mn-oxide bound, and the easily mobilizable fractions (fractions 1, 3, and 2). In the AEh horizon (soil no. 8) besides fractions 7, 6, and 5, only organically bound and mobile Ni were identified in substantial concentrations. According to Tu (1996), previous studies on the distribution of Ni in soils identified 50-80% and 20-30% of native Ni in the residual and in the Fe- and Mn-oxide bound fractions, respectively, and usually less than 2% in the soluble plus exchangeable fractions. Generally, this was observed in the presented study in which, however, the ratio of residual to oxide-bound Ni was shifted toward the oxide-bound fractions. Applied initial Ni concentrations of 0.002 and 0.1 mmol L- 1 were too small to significantly affect total Ni contents and to identify clear trends in the fractionation of adsorbed Ni, ho'Wever, especially in the uppermost horizons AEh and Bhs, the mobile Ni fraction clearly increased with applied initial Ni concentration. At 10 mmol L -I, total Ni contents were significantly raised in all the studied horizons, and the major part of adsorbed Ni was in the mobile fraction that became the dominant fraction in the AEh and

Adsorption Isotherms of Nickel in Acid Forest Soils

51

6

AEh (soil no. 8) ~

5

~

~

Fraction:

o 4 E

.sZ

=

7 56

~ _

3

4 3 2 1

EEEE!I

= = =

"0 Q)

t5 2 ~

x UJ o

0.002

0.1

10

Initial Ni concentration [mmol L-

1

]

Figure 2.16. Distribution of Ni among the seven sequentially extracted fractions at different applied initial Ni concentrations for soil no. 8. 6

Bhs (soil no. 9) ~

5

~ (5 4

Fraction'

E

=

7 5 6

EITEll

4 3 2 1

.sz

= _

3

=

"0

= =

Q)

t5

~

2

x

UJ

o

0.002

0.1

10

Initial Ni concentration [mmol L-

1

]

Figure 2.17. Distribution of Ni among the seven sequentially extracted fractions at different applied initial Ni concentrations for soil no. 9.

Bhs horizons. The easily mobilizable fraction was also increased in all the studied horizons whereas Mn-oxide bound and organically bound Ni were substantially increased only in the AEh and Bhs horizons and to a smaller extent in the Bs horizon. An increase in the fraction bound to amorphous Fe-oxides was identified in the AEh horizon, as well as in the Bw and in the Cw horizons. Fractions 6 and 7 were apparently not affected by adsorption at applied initial Ni concentrations of lO mmol L- 1 and below. The fractionation of adsorbed Ni was conducted immediately after the adsorption experiments, which may explain the strong dominance of mobile Ni in all the studied horizons. Redistribution of adsorbed Ni toward more stable forms may occur with time.

52

Fate and Transport of Heavy Metals in the Vadose Zone 6

Bs (soil no. 10) ~

5

'0)

.::20 years. In another study involving a sewage sludge disposal site, Sidle and Kardos (1977) found that 6.6% of the applied Cd in the form of sludge was recovered in the percolate at 120 em depth in the soil profile. In this study, simulations with a simple transport model based on Freundlich adsorption isotherm of cationic form of Cd predicted virtually no movement of Cd in the soil (Sidle et al., 1977). They concluded that the complexed form of Cd as well as its movement through preferential pathways should be taken into account for any predictive simulation. Recently, in a study by Streck and Richter (1997a), transport of Cd and Zn was investigated at field scale following application of wastewater for 29 years on a sandy soil. They found that Cd and Zn were partly displaced to a depth of 0.9 and 0.7 m, respectively. The simulations of Cd leaching were carried out with various types of modeling approaches employing parallel soil column (PSC) and convective-dispersive (CD E) approaches using either a grid model (points in the field) or Monte-Carlo model (Streck and Richter, 1997b). Sorption was described by an extended Freundlich equation capable of taking the spatially variable organic carbon content and pH at the site into account. The observed profile of Cd agreed well with that predicted with the PSC model, both with grid and Monte-Carlo simulations. Therefore, it was concluded that the spatial variability of sorption could adequately describe the field-scale dispersion of Cd. It is noteworthy that the sorption data used in the simulations were measured in the presence of an electrolyte matching the mean ionic strength of the wastewater used for irrigation and included CI anion (0.0025 M CaCI 2). The simulations with the CDE modeL however, could agree with measured data only when the dispersivity parameter was adjusted to 0.29 m-a value considered to be on the higher side of those commonly reported. As discussed in the earlier section, increased dispersivity may result from the physicochemical heterogeneity or nonequilibrium conditions during sorption. The results from this study highlight that spatial variability of key soil properties affecting Cd sorption, such as pH and organic carbon content, has a greater bearing on transport behavior of Cd than perhaps the nonidealilty of microscale processes, such as sorption nonequilibrium. The importance of heterogeneity of soil properties and spatial variability in determining Cd transport through soil was also demonstrated through simulations with a simple root zone model (using stochastic theory) by Boekhold and Van der Zee (1991) for a sandy soil. In the example they considered (representing a site exposed to combined agricultural and industrial activities with 50 glhafyr rate of Cd input), simulations showed that after 40 years, the average Cd concentration in mean water flux can reach the Dutch reference value for groundwater (1.5 J.lglL). They recommended that when groundwater quality is of major concern, accurate knowledge of sorption parameters and input rates of Cd are crucial for reliable results, because leaching rates are very sensitive to Cd input rate and to flow and sorption parameters. They observed that large areas in the field may

80

Fate and Transport of Heavy Metals in the Vadose Zone

have high leaching rates, which may remain undetected by simulations with the average behavior of Cd. Therefore, soil heterogeneity of both soil physical and chemical properties must be taken into account in an assessment of Cd leaching through soil profIles.

Desorption and Reversibility of Cd Sorption Reports of desorption of Cd from soils are relatively fewer in the literature than those of sorption, except those carried out using specifIc extractants to establish the solid phase speciation of Cd (Tiller, 1996). In sorption-desorption experiments on Cd in soils, both complete and partial reversibility of sorption have been reported in the literature. For example, Christensen (1984b) studied desorption of Cd at low Cd concentrations (0.1 to 6 mg/g in soil) in two Danish soils (loamy sand and sandy loam) at pH 6.0. They observed a full reversibility of Cd sorption in the loamy sand but only partial in the sandy loam. Mayer (1978) also noted similar full reversibility of Cd sorption in an acid subsurface soil over a wide range of solution concentrations of Cd (1-10000 ~/L). Complete reversibility of sorbed Cd from poorly crystalline kaolinite was also reported by PuIs et al. (1991). Similarly, Cd sorption was found to be completely reversible in both column and batch experiments in an Australian Oxisol, whereas hysteresis was observed in AlfIsol (Kookana et al., 1994; Naidu et al., 1997). The ambient pH of the Oxisol was closer to the point of net zero charge and therefore the soil had a very low cation exchange capacity. In contrast, Amacher et al. (1986), while studying the desorption behavior of Cd in fIve different soils also found incomplete reversibility of several metals, including Cd. Mter allowing the sorption reaction between metals and soils to proceed for 336 hr, they carried out desorption in 0.005 M Ca(N03h A signifIcant fraction of the sorbed metals did not desorb from soils (Table 3.1) even after the long desorption period. In this study the Ca was present in suffIciently high concentration as Ca(N03)2 to replace the Cd on exchange sites. It was suggested that the poor reversibility in these studies may have been due to specifically sorbed Cd on metal oxides or organic matter, or due to formation of insoluble compounds or coprecipitated Cd. Recently, Kookana (unpublished data) observed sorption desorption hysteresis in two AlfIsols from South Australia, as shown by the data presented in Figure 3.llA,B. Tran et al. (1998b) reported Cd desorption experiments carried out on a homogeneous sand medium at constant-pH of 5.5 and 6.5. They compared sorption/desorption isotherms and found signifIcant hysteretic behavior (Figure 3.11 C) at a pH of 6.5. The partial reversibility of Cd is likely to be linked to the mechanism of sorption in soils, as discussed below.

Desorption of Specifically Sorbed Cd Tiller et al. (1984b) in their desorption studies on clay-sized isolates from several soils found that at a soil pH of 5, up to 85% of sorbed Cd was easily desorbed rapidly in 0.01 M Ca(N03h However, at pH 7, they noted that the easily desorbed fraction (they called it nonspecifically sorbed) was much lower, particularly from the clay-sized fraction from Oxisol. The lower proportion of desorbed Cd at higher pH may be because the surface may be highly undersaturated relative to the number of sorption sites available for binding (Naidu et al., 1997). Thus, it appears that the reversibility of sorbed Cd is a function of the nature of sorbent and the soil conditions determining the affinity of Cd for soil (Kookana et al., 1997). As discussed earlier, Cd can form high affinity inner-

Sorption-Desorption Equilibria and Dynamics of Cadmium During Transport in Soil

81

Table 3.1. Fraction of Sorbed Cd Released in Solution after 336 hr Desorptiona Cd Released

Freundlich K

pH

CEC cmol(+)/kg

Fe 2 0 3

Soil Type

(%)

(%)

(n)

Typic Hapludults Typic Udifluvents Aquic Fragiudalfs Vertic Haplaquepts Typic Udipsamments

5.1 7.4 6.4 5.4 5.4

3.72 6.20 8.31 31.3 1.20

10.2 0.44 1.14 0.94 2.20

50.3-74.9 5.4-34.1 2.2-15.6 3.6-9.4 24.7-51.5

a

8.0 71.5 147.2 189.2 21.8

(0.89) (0.81) (0.85) (0.92) (0.84)

After Amacher et aI., 1986. 8.0,------------------,

A

6.0

f-

OJ

I

I

0.0 r- B 30.0 I-

I

~e

0-----

.o-~i----

~ 20.0 I~ E /e C 10.01- . /

~o

C/)

~~ ~IL_ ~I_~IL__~I

0.0 ...

__

__

c

~

cp

4.0 -

//

3.5 -

I

3.0 -

__

cp I

10

,.

/'

e

I _ __'__ I _ _I'___--' L__---'-_ _~

2.5 0.0

0.1 0.2 0.3 0.4 Solution concentration (rng/L)

0.5

Figure 3.11. Cd adsorption and desorption batch isotherms for (A) an Alfisol, solution pH 6.1 ± 0.1 , (B) an Alfisol pH 6.6 ± 0.2 (Kookana, unpublished data), and (C) a homogeneous sand; solution pH 6.5 (Tran et aI., 1997b, with permission). The ordinate represents the Cd solution phase concentration, and the abscissa is the solid phase concentration.

sphere complexes as well as coprecipitates with certain minerals and from such sorbent the desorption of Cd is unlikely to be fully reversible. On certain sorbents, the desorption of Cd and other metals has been found to be influenced by the time of metal-sorbent contact (Brummer et al., 1988; Backes et al., 1995). Backes et al. (1995) studied the kinetics of Cd and Co desorption from synthetic Fe and Mn oxides (at pH - 6) by both batch and flow methods. They concluded that not only the oxide sorbed large amounts of Cd and Co but substantial proportions of sorbed metals could not readily be des orbed in soil solution, especially from Mn oxides. The

82

rate and Transport of Heavy Metals in the Vadose Zone

rate of desorption from goethite became progressively slower with contact time between sorbate and the sorbent. While, as the authors state, several mechanisms may cause such effects, it is not clear if the physical or chemical changes were responsible for reduced desorption with contact time.

Partial Reversibility of Cd Sorption from Calcite and Calcareous Soils In batch experiments on calcite surfaces, sorption of Cd has been found to be only partially reversible (Zachara et al., 1991). Similarly, in flow-through experiments on a calcareous soil, Buchter et al. (1996) found that 35% of the applied Cd did not elute from the column, indicating sorption hysteresis. They also reported that, in a batch study on the same soil, pronounced hysteresis in Cd sorption-desorption was observed. Batch desorption experiments on a calcareous soil from South Australia (Kookana, unpublished data in Figure 3.11) also show the sorption hysteresis of Cd. The partial reversibility from calcite may be due to dehydration of sorbed Cd and coprecipitation as suggested by Davis et al. (1987). Cd reversibility may be time dependent and may be so slow that during its transport in natural systems such as groundwater, nonequilibrium behavior could become evident (Zachara et al., 1991).

((1 Desorption Kinetics Desorption kinetics of Cd in soils is relatively little understood. However, from published studies on natural soils and synthetic minerals it appears that desorption kinetics of Cd depend on the sorbent properties as well as experimental conditions. In batch experiments involving shaking, often the desorption equilibrium is achieved within hours. For example, Tiller et al. (1984b) noted that, at pH 5, up to 85% of Cd sorbed on claysize fractions from soils was desorbed rapidly in one quick wash (5 min) with 0.01 M Ca(N03h Kookana et al. (1997) reported that, in two Australian soils, solution concentration of Cd during desorption did not significantly change after 2 hours of shaking. Similarly, Tran et al. (1998b) carried out a series of batch kinetic desorption experiments at pH 6 which showed no significant difference in Cd solution phase concentration between 1 day and 10 days equilibration, indicating that desorption of Cd was not time dependent over that time scale. In contrast, however, Amacher et al. (1986), in their batch kinetic studies on Cd desorption in five soils, noted a rapid initial phase of desorption followed by a slower phase. However, they noted that although the overall retention/release reaction was not in equilibrium, the metal and soil reaction was almost instantaneous. On synthetic Fe and Mn oxides the desorption of Cd has been found to continue for several days and may be diffusion controlled. Using synthetic goethite, Gerth et al. (1993) found that extraction of metals (added at 10-6 M and sorbed during a reaction period of 21 d at 35°C) with 0.7 M HN0 3 for 14 days at 35°C released 89,72, and 60% Ni, Cd, and Zn, respectively. This supported the observations of Brummer et al. (1988) that, during the sorption process, metals become immobilized, possibly by diffusion into highly specific binding sites in goethite micropores, which protect them against acid attack. Recently, Backes et al. (1995) studied the desorption behavior of Cd and Co on Fe and Mn oxide surfaces at 20°C and compared the amounts desorbed from soils in contact with metals for 1- and 15-week periods. In this study, the desorption of metals was in-

Sorption-Desorption Equilibria and Dynamics of Cadmium During Transport in Soil

83

duced by continuous pumping of 0.0 1M Ca(N0 3)2 through oxides at a flow rate of 2.53 mLimin. The results showed a rapid and slower phase of desorption, the latter being the dominant in terms of total desorption. The amount of Cd associated with the slower phase increased with increased contact time between Cd and sorbent during sorption. When sorption was allowed over 15 weeks, the amount of Cd desorbed (within 5 hr) was found to be almost half of that desorbed when the sorption reaction time was only 1 week. Therefore, it appears that both the rate and extent of Cd release is dependent on the nature of the sorbent and mechanism of sorption of Cd.

Sorption Reversibility in Flow-Through Experiments A comparison of the sorption and desorption flanks of the breakthrough curves (BTC), can provide clues about the reversibility of solute sorption during transport. For a solute showing a linear sorption isotherm and symmetrical breakthrough curve, the desorption flank of BTC when inverted and superimposed on the sorption flank should match if the sorption is reversible. However, nonlinearity of sorption isotherm and kinetics of sorption-desorption reactions can influence the shape of sorption and desorption flanks of a BTC and, hence, deviations on superimposition may be seen. In such cases it is important is to assess the mass balance for the solute entering and eluting out of the column. KookanCl. et al. (1994) conducted Cd transport experiments on an Oxisol to obtain both sorption and desorption fronts of a BTC. When the sorption and desorption flanks of the Cd BTCs were inverted and superimposed, some deviation between the two flanks of the Cd BTC was noted, but the mass balance (the areas on the left of the two flanks of the BTCs) were essentially the same during sorption and desorption phases (Naidu et al., 1997). These results show that nearly all the Cd that was introduced into the soil was recovered during desorption. Campbell et al. (1987) similarly carried out Cd sorptiondesorption studies on montmorillonite-humic acid mixtures using the miscible-displacement technique. An examination of their BTCs and mass balance also shows that most of bound Cd did elute from the columns. Partial reversibility of sorption can influence the desorption flank of a BTC markedly, as shown by Tran et al. (1998b). Column experiments were reported by Tran et al. (1998b), in which a 1 mg/L Cd solution was introduced into short (approximately 5 cm) columns containing homogeneous sand, which showed sorption desorption hysteresis for Cd in batch experiments. After the sorption phase was complete (effluent concentration at 1 mg/L), the influent was switched to a Cd-free solution. The resultant breakthrough curve is shown in Figure 3.12. Clearly the symmetry of the influent pulse is not maintained in the breakthrough curve, the asymmetry reflecting the nonsingular or hysteretic sorption/desorption isotherm of Cd. From the above discussion it is clear that Cd sorption in soils is not always reversible. The reversibility is likely to be influenced by the nature of sorbent, pH, and composition of soil solution. Currently the desorption process of Cd is poorly understood and warrants further research.

SUMMARY Cd is sorbed by both specific and nonspecific interactions with soils, depending upon the nature of mineral matter present in soil and soil solution composition. Similarly the

84

Fate and Transport of Heavy Metals in the Vadose Zone

1.0

;J'

bb

5 0 .5 U

o.o~__. . .

o

20

40

60

80

100

Time (h) Figure 3.12. Column effluent concentrations (e) showing adsorption then desorption of a Cd pulse (Tran et aI., 1997b, with permission) at pH 6. The line is a model fit to the experimental data.

extent of Cd sorption is also influenced by the nature of the sorbent as well the composition of soil solution in terms of ionic strength, nature of competing and complexing ions. Ca ions are particularly effective in competing with Cd for sorption sites even at lower ionic strengths. It is therefore important to adequately account for such competition in assessing the mobility of Cd in soils. Similarly, the presence of ligands, especially Cl, in soil solution can markedly influence Cd sorption and mobility. Further research to improve the understanding of the effects of organic ligands on Cd behavior is warranted. In a heterogeneous and dynamic system such as the soil environment, several factors together determine the nature and extent of retention reactions of Cd. While it is difficult to isolate the individual effects of various factors influencing Cd, some workers have been able to develop relations which can quantitate the individual influence of Cd concentration, pH, and ionic strength of Ca, during sorption. Clearly, more efforts are needed in this area to develop a better understanding of influences of various factors in multivariate systems. Most research on Cd sorption desorption equilibria and kinetics has been carried out in well-mixed batch systems. While such systems are easy, quick, and suitable for establishing the fundamental retention reactions, they do not always represent the realistic conditions under which Cd mobility needs to be assessed; e.g., under flow conditions. Cd sorption behavior has been found to be different in flow-through systems as compared to batch systems. However, from the current work it is not possible to conclude whether batch systems over- or underestimate the sorption of Cd. Clearly the sensitivity of Cd sorption to several factors, and the fundamental differences between the techniques, together with varying conditions in different experiments even with the same technique, makes it very difficult to draw any meaningful conclusions. Desorption of sorbed Cd from soil is probably more relevant for the assessment of its mobility and potential adverse impact on the environment. However, it remains a poorly

Sorption-Desorption Equilibria and Dynamics of Cadmium During Transport in Soil

85

understood phenomenon. From the limited work available in literature, it is concluded that sorption of Cd is not always reversible. Indeed, the reversibility of Cd sorption depends upon the nature of the sorbent as well as the desorbing solution. Cd interactions with calcite, which is the essential component of calcareous soils and some aquifers, can have significant implications for Cd mobility in the environment. It has been shown that sorption of Cd followed by coprecipitation and dehydration on calcite can result in partial reversibility and possible nonequilibrium conditions under flow conditions. Also, the high pH in calcareous soils favors Cd retention and therefore its mobility is likely to be limited in such soils. Ease of Cd desorption is likely to be linked to the binding affinity of Cd to the sorbent and, therefore, under conditions where Cd shows feeble binding, its sorption is likely to be reversible. Under such conditions, both sorption as well as desorption processes will favor greater mobility of Cd. Highly weathered acidic soils (e.g., some Australian Oxisols), or acidic sandy soils with inherently low cation exchange capacities, are therefore likely to have greater availability of Cd in soil solution, which may have implications for its plant uptake of leaching through the soil profile.

REFERENCES AkratanakuL S., L. Boersma, and G.O. Klock. Sorption process in soils as influenced by pore water velocity: II. Experimental results. SoiL Sci. 135, pp. 331-341, 1983. Allison, J.D. and D.S. Brown. MINTEQA2/PRODEFA2-A Geochemical Speciation Model and Interactive Preprocessor, in ChemicaL Equilibrium and Reaction Modeu, SSSA Special Publication 42, pp. 241-252. (Soil Science Society of America, Madison, WI), 1995. Alloway, B.J. Cadmium, in Heavy Metau in Soiu. pp. 100-124. B.J. Alloway, Ed., John Wiley & Sons, Inc., New York, 1990. Al-Soufi, R.W. A method for simulating cadmium transport in soil: Model development and experimental evaluation. J. Hydro!' 163, pp. 233-247, 1994. Amacher, M.C., J. Kotuby-Amacher, H.M. Selim, and I.K Iskandar. Retention and release of metals by soils-Evaluation of several models. Geoderma. 38, pp. 131-154, 1986. Backes, C.A., R.G. McLaren, A.W. Rate, and R.S. Swift. Kinetics of cadmium and cobalt desorption from iron and manganese oxides. SoiL Sci. Soc. Am. J. 59, pp. 778-785, 1995. Bajracharya, K Transport of Cadmium in Soil. D. Eng. Thesis. Asian Institute of Technology, Bangkok, Thailand, 1989. Bajracharya, K and D.A. Barry. Accuracy criteria for linearised diffusion wave flood routing. J. Hydro!' 195, pp. 200-217, 1997a. Bajracharya, K and D.A. Barry. Nonequilibrium solute transport parameters and their physical significance: Numerical and experimental results. J. Contam. HydroL. 24, pp. 185-204, 1997b. Bajracharya, K, Y.T. Tran, and D.A. Barry. Cadmium adsorption at different pore water velocities. Geoderma 73, pp. 197-216, 1996. Barrow, N.J. Reactions with variable-charge soils. FertiLizer &d. 14, pp. 1-100, 1987. Barry, D.A. and K Bajracharya. Optimised Muskingum-Cunge solution method for solute transport with equilibrium Freundlich reaction. J. Contam. HydroL. 18, pp. 221-238, 1995. Barry, D.A. and L. Li. Physical Basis of Nonequilibrium Solute Transport in Soil, in 15th InternationaL CongrNJ of SoiL Science TranJactionJ, AcapuLco, Mexico, JuLy 10-16. International Society of Soil Science & Mexico Society of Soil Science, 2a, pp. 86-105, 1994. Barry, D.A. and G. Sposito. Application of the convection-dispersion model to solute transport in finite soil columns. SoiL Sci. Soc. Am. J. 52, pp. 3-9, 1988.

86

Fate and Transport of Heavy Metals in the Vadose Zone

Bingham, F.T., G. Sposito, and J.E. Strong. The effect of sulfate on the availability of cadmium. SoiL Sci. 141, pp. 172-177, 1986 Boekhold, A.E. and S.E.A.T.M. Van der Zee. Long-term effects of soil heterogeneity on cadmium behaviour in soil. J. Contam. HydroL. 7, pp. 371-390, 1991. Boekhold, A.E. and S.E.A. T.M. Van der Zee. A scaled sorption model validated at the column scale to predict cadmium contents in a spatially variable field soil. Soil Sci. 154, pp. 105-112, 1992. Boekhold, A.E., E.J.M. Temminghoff, and S.E.A.T.M. Van der Zee. Influence of electrolyte composition and pH on cadmium sorption by an acid soil. J. SoiL Sci. 44, pp. 85-96, 1993. Boesten, J.J. T.1. and L.J. T. Van der Pas. Modeling adsorption/desorption kinetics of pesticides in a soil suspension. SoiL Sci. 146, pp. 221-231, 1988. Bolton, K.A., S. Sjoberg, and L.J. Evans. Proton binding and cadmium complexation constants for a soil humic acid using a quasi-particle model. SoiL Sci. Soc. Am. J. 60, pp. 1064-1072, 1996. Brummer, G., J. Gerth, and K.G. Tiller. Reaction kinetics of the adsorption and desorption of Ni, Zn and Cd by goethite. I. Adsorption and diffusion of metals. J. SoiL Sci. 39, pp. 35-52, 1988. Brusseau, M.L., Z. GerstL D. Augustijn, and P.S.C. Rao. Simulating solute transport in an aggregated soil with the dual-porosity model: Measured and optimised parameter values. J. HydroL. 163, pp. 187-193, 1994. Brusseau, M.L., P.S.C. Rao, R.E. Jessup, and J.M. Davidson. Flow interruption: A method for investigating sorption non-equilibrium. J. Contam. HydroL. 4, pp. 223-240, 1989. Brusseau, M.L. and P.S.C. Rao. Sorption nonideality during organic contaminant transport in porous media. CRC Crit. Rev. Environ. ControL 19, pp. 33-99, 1989. Buchter, B., C. Hinz, M. Gfeller, and H. Fluhler. Cadmium transport in an unsaturated stony subsoil monolith. Soil Sci. Soc. Am. J. 60, pp. 716-721, 1996. Burgisser, C., A. Scheidegger, M. Borkovec, and H. Sticher. Transport and adsorption of cadmium in columns. Deat. BOden!.:. GeddeLL. MilteiL. 66, pp. 283-286, 1991. CampbelL G.D., H.F. Galcia, and P.W. Schindler. Binding of cadmium by montmorillonitehumic acid mixtures: Miscible displacement experiments. AuAraL. J. SoiL Red. 25, pp. 391-403, 1987. Chardon, W. Mobility of Cadmium in Soil (in Dutch). PhD Thesis. Agricultural University, Wageningen, The Netherlands, 1984. Christensen, T.H. Cadmium soil sorption at low concentrations: Effect of time, cadmium loading, pH and calcium. Water Air SoiL PoLLut. 21, pp. 105-114, 1984a. Christensen, T.H. Cadmium soil sorption at low concentrations: II. Reversibility, effect of changes in solute composition, and effect of soil aging (die.). Water Air SoiL PoLLut. 21, pp. 115125, 1984b. Christensen, T.H. Cadmium soil sorption at low concentrations: V. Evidence of competition by other heavy metals. Water Air SoiL PoLLut. 34, pp. 293-303, 1987. Davis, J.A. and J.O. Leckie. Surface ionization and complexation at the oxide/water interface. J. CoLwiJ Interface Sci. 67, pp. 91-107, 1978. Davis, J.A. Complexation of trace metals by adsorbed natural organic material. Geochimca et COdmochimca Acta. 48, pp. 677-691, 1984. Davis, J.A., C.C. Fuller, and A.D. Cook. A model for trace metal sorption process at the calcite surface: Adsorption of Cd+ 2 and subsequent solid solution formation. Geochimiea et COdmochimiea Acta, 51, pp. 1477-1490, 1987. Doner, H.E. Chloride as a factor in mobilities of Ni(I1), Cu(II) and Cd(II) in soil. SoiL Sci. Soc. Am. J. 42, pp. 882--885, 1978. Dowdy, R.H., J.J. LattereiL T.D. Hinesly, R.B. Grossman, and D.L. Sullivan. Trace metal movement in an aeric Ochraqualf following 14 years of annual sludge applications. J. Environ. QULlL 20, pp. 119-123, 1991.

Sorption-Desorption Equilibria and Dynamics of Cadmium During Transport in Soil

87

Dowdy, RH. and V.V. Volk. Movement of Heavy Metals in Soils, in Chemical MObility and Reactivity in Soil SY 1, sorption of ion Cd is preferred and the isotherms are convex, whereas for K0ICa < 1, sorption affinity is apposite and the isotherms are concave. The capability of the ion exchange approach in describing multiple pulse applications is illustrated in Figure 4.6. Here three input pulses of Cd having a concentration (Co) of 10 mg L -I were consecutively applied to a Windsor soil column (Selim et aI., 1992). The ion exchange model well predicted the position of the BTC peaks. Moreover, the assumption of equilibrium ion exchange with the selectivity coefficient (:KcJCa) based on Figure 4.5 adequately predicts the observed

Modeling the Kinetics of Heavy Metals Reactivity in Soils

->
1). Selim et al. (1992) obtained equally good predictions for multiple input pulse applications with Co of 100 mg L- I . The assumption of equilibrium ion exchange reaction has been employed to describe sorption of heavy metals in soils by several investigators (Abd-Elfattah and Wada, 1981; Harmsen, 1977; Bittel and Miller, 1974; Selim et al., 1992; Hinz and Selim, 1994). In general, the affinity of heavy metals increase with decreasing heavy metal fraction on exchanger surfaces. Using an empirical selectivity coefficient, it was shown that Zn affinity increased up to two orders of magnitude for low Zn surface coverage in a Ca background solution (Abd-Elfattah and Wada, 1981). The Rothmund-Kornfeld approach incorporates variable selectivity based on the amount adsorbed (s) or exchanger com-

102

Fate and Transport of Heavy Metals in the Vadose Zone

position. The approach is empirical and provides a simple equation that incorporated the characteristic shape of binary exchange isotherms as a function of Sj as well as the total solution concentration in solution (Cr). Harmsen (1977) and Bond and Phillips (1990) expressed the Rothmund-Kornfeld as

(Sir:

= R

(sY'

K. 'J

J

[(Cir:]n (C.)Vl

(18)

J

where n is a dimensionless empirical parameter associated with the ion pair i-j, and R~j is the Rothmund-Kornfeld selectivity coefficient. The above equation is best known as a simple form of the Freundlich equation which applies to ion exchange processes. As pointed out by Harmsen (1977), the Freundlich equation may be considered as an approximation of the Rothmund-Kornfeld equation valid for Sj « Sj and Cj « Cj' where

s. ,

=

RK.(c.)n 'J'

(19)

Based on best-fit predictions, Hinz and Selim (1994) showed strong Zn and Cd affinity (compared to Ca) at low Zn and Cd concentrations based on parameter estimates of ionexchange isotherms using the Rothmund-Kornfeld approach.

Kinetic Ion Exchange Recently, Sparks (1989) compiled an extensive list of cations (and anions) that exhibited kinetic ion exchange behavior in soils; e.g., AI, NH 4, K, and several heavy metal cations. According to Ogwada and Sparks (1986a,b,c), kinetic ion exchange behavior was probably due to mass transfer (or diffusion) and chemical kinetic processes. The proposed approach was analogous to mass transfer or diffusion between the solid and solution phase such that, for ion species i,

as· at

-' =

0

a(s· - s,.)

'

(20)

where at any time t, the symbol Sj denotes the amount sorbed, where SjG is the amount sorbed at equilibrium, and a is an apparent rate coefficient Cd-I) for the kinetic-type sites. In Equation 17, the amount sorbed at equilibrium SjG is calculated using the respective isotherm relations similar to Equation 14. Expressions similar to Equation 17 have been used to describe mass transfer between mobile and immobile water as well as chemical kinetics (Parker and Jardine, 1986). For large a, Sj approaches SjG in a relatively short time and equilibrium is rapidly achieved, whereas for small a, kinetic behavior should be dominant for extended period of time.

Case Study We investigated Cu retention by monitoring its concentration in the soil solution with time for a wide range of input concentrations. Cu transport was studied using miscible

Modeling the Kinetics of Heavy Metals Reactivity in Soils

103

displacement methods. Two different soils were studied. Cecil soil was chosen as a benchmark and McLaren soil was obtained from a site near an abandoned Cu mine on Fisher Mountain, Montana. Isotherms were measured using standard ion exchange methods where ten-gram samples of soil were equilibrated with Cu and Mg at varying ratios. The samples were shaken for 24 h on a reciprocal shaker with 30 mL of various proportions of CUS04 and MgS04 solutions. The solutions were then centrifuged and decanted. For the first two steps (24 h each step) total concentration was 0.5 N followed by four time steps at 0.01 N. Triplicate samples were used for each solution ratio. Adsorbed cations were removed by three extractions with 1 N NaOAc and corrections were made for the entrained solution. Cu and Mg in solution and extractant solution were analyzed by ICP. Based on these Cu-Mg exchange isotherm experiments, selectivity for Cecil and McLaren soils were obtained. The transport of Cu in the Cecil and McLaren soils were investigated using the miscible displacement technique. Plexiglas columns (6.4 cm i.d. X 10 cm) were uniformly packed with air-dry soil and were slowly water-saturated. Upon 1 saturation, the fluxes were adjusted to the desired flow rates. A Cu pulse of 100 mg Lwas introduced into each column after it was totally saturated with 0.01 N MgS04 or Mg(CI04h as the background solution. Perchlorate as the background solution was used to minimize ion pair formation. The Cu pulse was eluted subsequently with 0.005 M MgS04 solution. The ionic strength was maintained nearly constant throughout the experiment. In other soil column experiments, similar conditions were used except that no background solution was used in the Cu pulse input solution. This resulted in a condition of variable total ionic concentrations or ionic strength during input pulse application and the subsequent leaching solution. A fraction collector was used to collect column effluent. Figures 4.7 and 4.8 show the effect of total concentration or ionic strength of the input pulse solution on Cu breakthrough results. When Cu was introduced in Mg background solution with minimum change in ionic strength, Cu breakthrough curves (BTCs) appear symmetrical in shape with considerable tailing and peak concentration of 40 mg L- 1• Mg BTC shows an initial increase in concentration due to slight increase in ionic strength followed by a continued decrease during leaching. When Cu was introduced in the absence of a background solution, the total concentration considerably decreased from 0.005 to 0.0015 M. As shown in Figure 4.8, Cu BTC showed a sharp increase in concentration due to chromatographic (or snowplow) effect (Selim et al., 1992). The Cu peak concentration was 94 mg L- 1 and the corresponding Mg concentration in the effluent decreased due to depletion of Mg during the introduction of Cu. Mg concentration increased, thereafter, to a steady state level during subsequent leaching, however. This snowplow effect is a strong indication of competitive ion exchange between Mg and Cu cations. The amount of Cu recovered in the effluent was 53% of that applied in the presence of MgS04 as the background solution, whereas only 38% was recovered when no background solution was used. For McLaren soil (Figure 4.9), the snowplow effect was pronounced as shown in Figures 4.7 and 4.8 due to changes in total concentration of input solutions with a recovery of 60% of that applied. Therefore, miscible displacement or transport experiments indicated that there was strong ion exchange between Cu and Mg cations which was also affected by the counter ion used. Effluent peak concentrations were 3-5 fold that of the input Cd pulse, which is indicative of pronounced chromatographic effect.

104

Fate and Transport of Heavy Metals in the Vadose Zone ----- ----

--

-

-~-

---~-.----

-----

--

200

Cecil Soil

...J

Column I Sulfate

Ol

-

E C 0

150

:;::

...c:

Mg

~ ....

Q)

-~----~--'-

100

0

c: 0

...c:

U

Q)

50

:J

:::: w

Cu 0 0

10

20

30

40

50

60

Pore Volume Figure 4.7. BTCs of Cu and Mg for Cecil soil (Column I).

--

200

c

150

...J

en

-E

Column II Sulfate

Cecil Soil

0 +:i

-

Mg

...cu C

(I)

u

100

c

0

()

c

50

(I)

::::I

tt:

w

Cu

0 0

10

20

30

40

50

60

Pore Volume Figure 4.8. BTCs of Cu and Mg for Cecil soil (Column /I).

In summary, we presented an overview of several models which are used for the description of the retention of heavy metals in soils. Single reactions models were classified into equilibrium and kinetic types. A general purpose multireaction kinetic and transport model was also presented. Major features of multi reaction models are that they are fiexible and are not restricted by the number of solute species present in the soil system

Modeling the Kinetics of Heavy Metals Reactivity in Soils

--

200

c o

150

. .J

McLaren Soil

C)

-E

105

Column V Sulfate Mg

~

~

,..

+"

C

Q) (.)

100

C

o

•

(.)

+"

C

50

Q)

::::J

e W

Cu 0 0

10

20

30

40

50

60

Pore Volume Figure 4.9. BTCs of cu and Mg for McLaren soil (Column V).

nor the governing retention reaction mechanisms. This includes reversible and irreversible reactions of the linear and nonlinear kinetic types. Moreover, these models can incorporate concurrent as well as consecutive type retention reactions which may be equilibrium or kinetic in nature. Ion exchange mechanisms of the instantaneous and kinetic types were also presented. Case studies of Cd and Cu isotherms as well as transport in soil columns provided illustrations of model applications.

REFERENCES Abd-Elfattah, A. and K. Wada. Adsorption oflead, copper. zinc. cobalt. and calcium by soils that differ in cation-exchange materials. J. SoiL Sci. 32. pp. 271-283. 1981. Amacher. M.C.• H.M. Selim. and I.K. Iskandar. Kinetics of chromium (VI) and cadmium retention in soils; A nonlinear multireaction model. Soil Sci. Soc. Am. J. 52. pp. 398-408. 1988. Amacher. M.C.• J. Kotuby-Amacher. H.M. Selim. and I.K. Iskandar. Retention and release of metals by soils-evaluation of several models. Geooerma. 38. pp. 131-154. 1986. Aringhieri. R.. P. Carrai. and G. Petruzzelli. Kinetics of Cu and Cd adsorption by and Italian soil. SoiL Sci. 139. pp. 197-204. 1985. Barrow. N.J. and T.C. Shaw. Effects of solution and vigor of shaking on the rate of phosphate adsorption by soil. J. Soil Sci. 30. pp. 67-76. 1979. BitteL J.E. and R.J. Miller. Lead. cadmium and calcium selectivity coefficients of a montmorillonite. illite and kaolinite. J. Environ. QuaL. 3. pp. 250-253. 1974. Harmsen. K. Behavwr of Heavy Metau in Soiu. Centre for Agriculture Publishing and Documentation. Wageningen. The Netherlands. 1977. Hinz. C. and H.M. Selim. Transport of Zn and Cd in soils: Experimental evidence and modelling approaches. SoiL Sci. Soc. Am. J. 58. pp. 1316-1327. 1994.

106

Fate and Transport of Heavy Metals in the Vadose Zone

Jardine, P.M., J .C. Parker, and L.W. Zelazny. Kinetics and mechanisms of aluminum adsorption on kaolinite using a two-site nonequilibrium transport model. Soil Sci. Soc. Am. J. 49, pp. 867873, 1985. Lapidus, L. and N.L. Amundson. Mathematics for adsorption in beds. VI. The effect of longitudinal diffusion in ion exchange and chromatographic column. J. PhYd. Chem. 56, pp. 984-988, 1952. Ogwada, RA. and D.L. Sparks. A critical evaluation on the use of kinetics for determining thermodynamics of ion exchange in soils. Soil Sci. Soc. Am. J. 50, pp. 300-305, 1986a. Ogwada, R.A. and D.L. Sparks. Kinetics of ion exchange on clay minerals and soil. I. Evaluation of methods. Soil Sci. Soc. Am. J. 50, pp. 1158-1162, 1986b. Ogwada, RA. and D.L. Sparks. Kinetics of ion exchange on clay minerals and soil. II. Elucidation of rate-limiting steps. Soil Set: Soc. Am. J. 50, pp. 1162-1166, 1986c. Parker, J.C. and P.M. Jardine. Effect of heterogeneous adsorption behavior on ion transport. Water Ruour. Ru. 22, pp. 1334-1340, 1986. Rasmuson, A. and I. Neretienks. Migration of radionuclides in fissured rock. The influence of micropore diffusion and longitudinal dispersion. J. GeopPyd. Ru. 86, pp. 3749-3758, 1981. Rubin, J. and RV. James. Dispersion-affected transport of reacting solution in saturated porous media, Galerkin method applied to equilibrium-controlled exchange in unidirectional steady water flow. Water Ruour. Ru. 9, pp. 1332-1356, 1973. Selim, H.M. Prediction of contaminant retention and transport in soils using kinetic multireaction models. Environ. HeaLth Perdpec. 83, pp. 69-75, 1989. Selim, H.M. Modeling the transport and retention of inorganics in soils. Adv. Agron., 47, pp. 331384, 1992. Selim, H.M. and M.C. Amacher. A second-order kinetic approach for modeling solute retention and transport in soils. Water Ruourc. Ru. 24, pp. 2061-2075, 1988. Selim, H.M., B. Buchter, C. Hinz, and L. Ma. Modeling the transport and retention of cadmium in soil: Multireaction and multicomponent approaches. Soil Sci. Soc. Am. J. 56, pp. 1004-1015, 1992. Selim, H.M., J.M. Davidson, and R.S. Mansell. Evaluation of a 2-site Adsorption-Desorption Model for Describing Solute Transport in Soils. Proc. Summer Computer Simulation Con! Wadhington, DC, 12-I4Ju!y, 1976, La Jo!la, CA, Simulation Councils Inc., La Jolla, CA. 1976, pp. 444448. Selim, H.M., M.C. Amacher, and I.K. Iskandar. Modeling the Transport of Heavy Metals in Soils. CRREL Monograph 90-2, U.S. Army Corps of Engineers, 1990, p. 158. Sparks, D.L. Kinet0 of Soil Chemica! ProceddU. Academic Press, San Diego, CA, 1989. Sposito, G. The Surface Chemidtry of Soil!. Oxford University Press, New York, 1984. Theis, T.L., R Iyer, and L.W. Kaul. Kinetic studies of cadmium and ferricyanide adsorption on goethite. Environ. Sci. Techno/. 22, pp. 1032-1017, 1988. van der Zee, S.E.A. T.M. and W.H. van Riemsdijk. Sorption kinetics and transport of phosphate in a sandy soil. Geoderma 38, pp. 293-309, 1986.

CHAPTER S

Copper Retention as Affected by Complex Formation with· Tartaric and Fulvic Acids Alexander A. Ponizovsky, T.A. Studenikina, and E.V. Mironenko

INTRODUCTION Soil solutions from humic horizons and surface waters contain inorganic and organic compounds capable of forming complexes with heavy metals (HM). Complexation can influence mobility of metals and their availability to living organisms. Many experimental studies of the HM retention in soils have been conducted without taking into account complexing ligands. Copper is a trace metal commonly present in many surface waters and soil solutions in detectable amounts. The influence of complex formation on copper behavior in soils and waters is the subject of this chapter.

Copper(lI) Retention by Soils, Oxides, and Clays Copper retention in soils is a rather complex process even without any substances able to associate with the metal ions in solutions. McLaren and Crawford (1973a, 1973b) suggested separating the following pools of natively available copper in soils: • • • • •

present in soil solution and exchangeable Cu (extractable by 0.05 M CaCI2) specifically bound by inorganic sites (soluble in 2.5% acetic acid) specifically bound with organic matter (soluble in K-pyrophosphate) occluded by free oxides (soluble in acid solution of ammonium oxalate) residual (bound in the lattices of minerals, soluble in HF).

These pools are not strictly related to types of chemical bounds. The total amount of copper retained in soil may not be in equilibrium with the Cu(II) in the soil solution, and may not be exchangeable and extractable with salt solutions. Zhang and Sparks (1996) reported that the quantity of Cu extracted by Na2EDTA from the montmorillonite used 10"'7

108

Fate and Transport of Heavy Metals in the Vadose Zone

in Cu-retention experiments was only 1.0 to 1.2% of the Cu-exchange capacity. Copper may be adsorbed by soil colloids in amounts in excess of their conventional exchange capacities, assuming adsorption as the Cu2+ ion (e.g., McLaren and Crawford, 1973a, 1973b). This phenomenon has been termed "specific adsorption" and is shown to occur on clays (Bingham et aI., 1964), organic matter (DeMumbrum and Jackson, 1956), and free oxides (Grimme, 1968). Copper sorption has been actively studied on soil components, such as Mo, Fe, AI oxides, or bentonite. Murray (1975) studied Cu 2+ retention on manganese oxide and found that adsorption of one Cu 2+ion leads to the release of 1.2 H+ ions. An inequivalence of proton released to retained metal was also found for Ca2+, Mg2+, Zn 2+and some other metals. This was explained by the replacement of a proton on the surface by a divalent 2 metal ion. Shindler et al. (1976) found that the number of protons released per Cu + adsorbed increases from 1 to 2 with the enhancement of pH. They attributed such a phenomenon to the retention of [CuOHr complexes instead of free Cu 2+ ions. Infrared spectroscopic studies by Parfitt and Russel (1977) showed that sorption of Cu 2 + on goethite at pH 7 did not lead to direct interaction between copper ions and surface OH groups. According to Rodda et al. (1996), experimental data on adsorption on goethite can be fitted by a model in which monomeric Cu(OH)+ and dimeric CU2(OH)22+ complexes compete for surface sites, with the dimer more strongly adsorbed to the surface. The number of protons released per Cu(II) ion adsorbed at pH 5.0 increased from 1.76 at 25 D C to 1.92 at 70 D C. Bower and Truog (1941) reported enhanced retention of Cu(II) by bentonite from chloride background medium. This was explained by the CuCI+ and [CuOHr ion pair involvement in the ion exchange and/or copper hydroxide precipitation. Sposito et al. (1981) also found that copper sorption by Na-bentonite in chloride solutions exceeds that in perchlorate solution. They suggested that monovalent CuCI+ complex was responsible for this effect, though this ion pair is known to be unstable and its concentration in solutions low. In these experiments, the solution pH was not stabilized and decreased with the increase in exchangeable copper content. Such results were not confirmed in the study of Zhang and Sparks (1996). They obtained values of Cu-exchange capacity for Na-montmorillonite similar for CI-, (CI0 4)-, (N0 3)-, and (S04)2- background at 0.25 M Cu(II) solution concentration and pH from 4.31 to 4.54. This concentration level was rather high, and they suggested that some other relations could be observed at a much lower Cu concentration, when specific adsorption occurs mainly at nonexchangeable sites on clay edges. H-montmorillonite was shown to retain copper from the chloride and acetate solutions at pHd in amounts equal to the standard cation exchange capacity (CEC) (Bingham et aI., 1964). In acetate solutions at pH>3, the amount of Cu 2+ retained exceeded the CEC. Acetate was sorbed by clay, but the sorbed amount was not equal to the excess of Cu2+ retained. Soils selectively adsorb Cu2+. Harter (1992) studied this phenomenon and revealed that the amount of Cu 2+ adsorbed exceeded that of the Ca2+ desorbed. He hypothesized that this discrepancy could be attributed either to nonexchange sorption processes or to the adsorpt~on of both free ITletal ~ons and their charged complexes, e.g., [CuOHr which results in maximum metal retention greater than CEC. McLaren and Crawford (1973b) suggested that specific and nonspecific adsorption of copper by soils and montmorillo-

Copper Retention as Affected by Complex Formation

109

nite take place simultaneously and independently. The specific adsorption exceeds nonspecific adsorption at low copper concentrations, while the relation can be opposite as the concentration increases. They assumed that nonspecific adsorption isotherms can be described by the Vanselow equation, whereas the Langmuir adsorption equation was found suitable for the "specific adsorption" isotherms within solution concentration ranges of 1-5 mg mL- 1 (0.015 to 0.075 mmol L- 1). Sposito et al. (1981) described sodium-copper exchange isotherm on bentonite in the perchlorate solution by the Vanselow equation and obtained the selectivity coefficient independent of exchangeable Na/Cu ratio. The same equation was applied to describe Cu-Na exchange on montmorillonite at pH from 5.17 to 6.50 and total concentration of metal ions in the solution of 0.02 mole L- 1 (Zhang and Sparks, 1996).

Solution Complex Formation and Cu(1I) Adsorption Copper(II) forms complexes with a number of anions commonly found in natural waters (Yatsimirsky and Vasilyev, 1959). In water solutions free of other ligands, Cu(II) is present mainly as a complex [Cu(H 2 0)6J 2+, a Lewis acid with pK=6.8, and [Cu(OH) (H 20hr, a Lewis base. Simulations of the Cu(II) speciation in fresh waters indicate a possible presence of a variety of complexes with different charges, depending on the solution pH (Vuceta and Morgan, 1978). The discrimination between copper complexes in natural waters remains a challenging analytical problem. A number of direct electrochemical techniques have been used in an attempt to distinguish between chemical forms of metals. Some of the existing methods are based on the separation of the different species. Dialysis, ultrafiltration, and centrifugation have been used to separate "free" metals in natural waters from metals associated with colloid material. Extraction with chloroform and chelating with ion exchange resins have been applied to separate "bound" copper from the free ions. Several studies were carried out on sea water (e.g., Florence and Batley, 1977) and sewage effluents. In sewage effluents Bender et al. (1970) using gel filtration chromatography (Sephadex G-50) found no free Cu 2+ ions. About 13% of the copper in the sample was associated with molecular weights of 104 or greater, while the remaining molecular weights ranged from 500 to 1000. A ligand that can be sorbed on a surface can enhance or inhibit retention of Cu (Davies and Leckie, 1978). Negatively charged Cu 2+ complexes with organic acids can be only slightly sorbed on the surface of layer silicate minerals (Bloomfield et al., 1976). However, glutamic acid increases retention of Cu(II), the influence of salicylic acid is negligible, and picolinic acids inhibits copper retention by hydrous oxides (Davies and Leckie, 1978). Pampura (1993) found that from 1 to 3 mmol L- 1 citric, malic, and salicylic acids decreased the Cu(II) sorption by soil. Such an effect can be explained by the formation of complex ions of various charge and with different abilities to be adsorbed on charged surfaces. Janvion et al. (1995) found that the concentration of acetate affected the distribution coefficient of Cu(II) between the acetate buffer in the mobile and stationary phases having both cation- and anion-exchange groups. This was explained by suggesting that copper retention involves not only Cu 2+ cation exchange, but also anion exchange of copper anionic complexes, e.g., with 2,3-pyrazinedicarboxilic acid (2,3-PDCA), [Cu(PDCA)2f-.

ilO

Fate and Transport of Heavy Metals in the Vadose Zone

Elliot and Huang (1979) reported on a survey of a number of studies on the influence of several chelating agents on the adsorption of various metal ions by some oxides. They presented results on adsorption of Cu(II) complexes with glycine, nitrilotriacetic, and aspartic acids on y-Al203. These authors also studied adsorption of metal-amino acid complexes by y-Al203' which is a relatively hydrophilic and hydrophobic activated carbon, and adsorption of Cu(II) complexes with various ligands by several alumosilicates with different surface charges and ion-exchange properties (Elliot and Huang, 1980, 1981). Their results indicated that several adsorption mechanisms were affecting the retention. Besides hydrophylic complexes, hydrophobic complexes probably could be sorbed on the hydrophobic parts of particle surfaces. This was proved by Baffi et al. (1994), who studied Cu(II) adsorption on inorganic fractions of marine sediments in the presence of aminoacids. Stumm et al. (1976) assumed that the interaction of the surface functional groups with the metal ions to be similar with the complexation with ligands in the solution. That is probably the reason why the modification of the surface of clay minerals, e.g., by polyphosphates, enhances their ability to sorb trace metals (Klimova and Tarasevitch, 1992). Cu (II) adsorption by hydrous oxides was found to decrease in the presence of a complexing ligand (citric acid and EDT A) in a manner that suggests competition between the ligand and oxide surface for complexation of the metal ion (Davies and Leckie, 1978). They studied the influence of several complexing ligands, capable of adsorbing on the surface of amorphous iron oxide on the trace metal uptake by oxide surface. The adsorption edge for Cu(II) was found in the pH range 5 to 6. Adsorption of metal ions on various oxide surfaces increased abruptly in this pH range, where hydrolysis products became a significant fraction of the dissolved metal. The authors suggested that adsorbed CuOH+ was the main form of copper(II) on the surface. The location of the adsorption edge for Cu(II) was influenced by ionic strength and total Cu(II) concentration. Cu(II) binding by amorphous Fe(OH)3 was not affected by the addition of salicylic and protocatecholic acids in the experiments of Davies and Leckie (1978). Adsorption was enhanced by glutamic acid and 2,3-PDCA. Picolinic acid effectively prevented copper(II) removal from the solution. The authors attributed these effects to the adsorption of glutamic acid and 2,3-PDCA on Fe(OHh This adsorption should increase the binding strength of the surface for Cu(II). Adsorbed picolinate could not function as a complexing ligand for metals due to the fact that coordinating groups were bound with the surface and unavailable to the metal ion.

Complexes of CI.I(II) with Fulvic Acids Fulvic acids (FA) are important components of surface waters and soil solutions. The complexing ability of FA is well known but rather difficult to be described quantitatively since FA are high molecular weight substances of complex composition with a great number of functional groups. Complex formation between Cu(II) and FA was studied by different techniques. A set of the methods was applied to calculate stability constants of soil organic matter with Cu(II) (see, e.g., Young et aI., 1982; Hirose et al., 1982; Perdue and Lytle, 1983; Ephraim and Marinsky, 1990; and a review by Bizri et aI., 1984). These methods provide some conditional values, related to definite solution ionic strength, copper and FA concentrations, etc. For example, stability constants calculated

Copper Retention as Affected by Complex Formation

111

by Ruzie and Scatchard plots, obtained by ion selective electrodes and potentiometric stripping analysis, decreased continuously with the degree of site occupation (Soares and Vasconcelos, 1994).

Influence of FA and Humic Acids (HA) on the Retention of Cu(lI) by Solid Phases Humic substances can be sorbed on mineral surfaces containing hydroxylated Al, Fe, or Mn sites (Parfitt et al., 1977; Murphy et al., 1990), thereby changing the mineral surface properties. Surface bound humic substances increase the adsorption of some metal cations on single mineral solids by contributing additional potentially high affinity complexation sites. For copper which forms strong complexes with humic substances, these substances enhance metal binding to Fe and AI oxides at lower pH (e.g., < 6) by cosorption and decrease metal ion retention at higher pH by formation of nonadsorbing

aqueous complexes (Tipping et al" 1983; Allard et al., 1989). For other combinations of metals and sorbents, mineral-bound humic substances exhibit variable effects on metal binding (Xu et al., 1989). It depends on the complexation ability of humic substance for the metaL the distribution of the humic substance between the solution and solid, and the variation of both of them with respect to pH and ionic strength (Zachara et al., 1994). It has not been estimated whether the mineral-bound humic substance exhibits comparable complexation properties for metals to that in solution. Both Davies (1984) and Laxen (1985) concluded that metal-humic substance interactions were stronger on surfaces than in solution. Tipping et al. (1983) suggested that when humic substances bind to goethite, new high affinity metal complexation sites are formed. Dissolved FA decreased Cu(II) retention by montmorillonite, though the effect was less than the influence of citrate and EDTA (Vuceta and Morgan, 1978). Clay in Cuform adsorbs FA and HA (Theng and ScharpenseL 1975). The authors attributed this phenomenon to the precipitation of slightly soluble copper salts of FA and HA due to release of exchangeable Cu(II). Chakrabarti et al. (1984) mentioned that dissolved FA decrease the velocity of the dissolved copper retention by the solid ion-exchange phase. This was perhaps caused by the low velocity of dissociation of the Cu-FA complex. Wershaw et al. (1983) suggested that Cu(II), forming charge transfer complexes with F A, in some conditions coordinates not one, but two or more FA molecules, and this leads to the aggregation of molecules. Such a point of view coincides with the existing conception of humic substances aggregation by metal ions (Gamble et al., 1984). It was found that, while extracting bound copper from bentonite, the amount of Cu(II) released was dependent on the concentration of ligand and the stability constant of the metal complex. The ratio of metal release to complexing sites decreased in the order: EDTA> humic acid> tannic acid (Guy and Chakrabarti, 1976).

COPPER RETENTION BY SOil (A CASE STUDY) Kinetics of Cu(lI) Retention A case study of the Cu(II) retention was carried out on a silty clay Typic Haplustoll soil (leached chernozem) sampled in the Tula region, Russia, from the A horizon (0-20 cm depth). Soil organic C content was 27.5 g kg-I, and exchangeable cation contents,

112

Fate and Transport of Heavy Metals in the Vadose Zone

determined by modified Pfeffer method (Khitrov, 1982) (extraction by 0.1 M NH4 CI solution in 70% alcohol), were 27.4, 1.7,0.13, and 0.70 cmole kg-I ofCa2+, Mg2+, Na+, and K+, respectively, with total cation exchange capacity 29.9 cmole kg-I. pH measured in water extract with 1: 1 soil: water ratio was 5.77. Each of these values is an average of three subsamples. The soil sample was air dried and ground to pass through a 2-mm sieve. To remove carbonates that can be present in the leached chernozem in trace amounts, the sample was leached with 0.1 M HCI until the leachate pH was about 3. Then sediment was washed out with water to remove the excess HCl. Then sample was saturated with Ca2+ by treatments with 0.1 M CaCI2, to diminish to a trace level an exchangeable H+ content, estimated by 1 M KCI extraction with subsequent KOH titration. To remove extra CaCl 2 the sediment was washed with water, until the final Ca2+ concentration in leachates became 2.5 mM (further decrease leads to peptization of the sediment). Then, the solution was decanted, the sample was air dried, ground in a mortar and sieved to pass a 1-mm mesh screen. Soil samples were placed into the flasks and suspended in 3 mM Ca(N03)2 solution as a background. Cu(N03h solution was added and pH value was adjusted by adding HN0 3 or KOH. The flasks were shaken at 25±1 °C for 90 days. The supernatant solutions were decanted, filtered through 0.2 pm membrane filters and copper concentration was measured with atomic adsorption spectroscopy (AAS). The amount retained was taken as the difference between the amount added and the amount recovered in the equilibrium solution. Equilibrium of Cu(n) retention by soil was found to be obtained for the period from 4 to 24 hours (Figure 5.1). Sorption velocity was highest at pH 6 (about 95% of the maximal copper retention was observed already in 1 hour) and lowest at pH 4. Mter 24 h no increase in soil copper content was observed.

Cu(1I) Retention Isotherms and Cation Balance Soil samples were suspended in 3 mM Ca(N0 3h Then some amounts of the 0.1 1\ 1 CU(N0 3)2 solution were added, and pH value was adjusted, adding HN0 3 or KOB The isotherms were obtained for pH 4,5, and 6. The flasks were shaken at 25±1 °C for I day. In some intervals the pH value was corrected by titration with HN0 3 or KOH. The suspensions were centrifuged and supernatant solutions were analyzed. Retained copper was calculated as above. Amount of H+ displaced from soil by Cu 2+ was evaluatec from the amount of HN0 3 or KOH used to adjust the pH value. Isotherms of Cu(n) displacement by Ca2+ from the contaminated soil were obtainec by treatment of the soil residue in the flasks by 3 mM Ca(N03h with the pH adjustmen: as mentioned above. The suspensions were shaken for 1 day, centrifuged, and analyzec Cu(n) retention isotherms at different pH are presented on Figure 5.2. Increase i:pH leads to the enhanced copper sorption. At pH 6 the sorption is much higher, and the' shape of the isotherm is different from those at pH 4 and 5. Cu(n) sorption in all cases was accompanied by the release of both Ca2+ and H+ ions from soil to solution. To maintain pH level, KOH was added to the suspension and Kwas partly retained by soil.

Copper Retention as Affected by Complex Formation 60

---

50

""'"

~-

40

r

";

CI

-.

r-

-.

..w: "5

______ pH = 4 _____ pH = 5

E 30 E

I--

--A-- pH = 6

:, 0

en

20

10

o

o

20

40

60

80

100

120

140

160

180

time, h

Figure 5.1. Kinetics of Cu(11) retention by soil.

350 _ pH=4, Cu retention ___ pH=5, Cu retention ~ pH=6, Cu retention -cr- pH=4, Cu displacement - 0 - pH=5, Cu displacement

300

250

~ a

200

:,

150

E E

0

en

100

50

0 0

1

2

3

meu' mM

Figure 5.2. Isotherms of Cu(1I) retention by soil without ligands at pH 4, 5, and 6.

113

114

Fate and Transport of Heavy Metals in the Vadose Zone 250 ,---------------------------------------,

";"0

200

~

_I>

o E E

150

~ Q)

c:: ·iii

i!....

100

o

"5lVI

m

~

50

VI

c::

.2

B

0

80

100 120 140 160 180 200 220 240 260 280 300 Cu sorbed, mmolc kg·1

Figure 5.3. Cation balance at Cu(1I) retention, pH=5.

It was found that the relations of released and retained ions amounts, e.g., at pH 5 (Figure 5.3) in the studied range can be expressed as 2

Ca \el.

=

0.765 CUsorb.

H+ reI.

=

0.292 CUsorb.

K\orb.

=

0.0332 CUsorb.

Here Ca2+re l.' H+rel.' K\orb., and CUsorb. are amounts of Ca2+, H+ released and K+, Cu(II) retained (mole kg- 1 soil), respectively. Thus total cation balance for copper retention is

Taking into account measurements errors, it could be concluded that amount of iom released is equal to the amount retained. Balance between Cu(II) retained and Ca2+and H+ released at pH 4, 5, and 6 is presented in Table 5.1. Impact of K+ retention or displacement on cation balance is rather small. In all studied cases Cu(II) displaced from soil both Ca2+ and H+. At pH 4 and 6 (Ca2+re l. + H+rel)/Cu2+sorb. ratio was 0.89 and 0.98, respectively, i.e., not so much different from the value of 1.05 at pH 5. Variation of thi;; ratio, caused probably by the measurements errors, doesn't allow rejecting the hypothesis on the exchange equivalence. The "reverse" isotherm of copper displacement by Ca2+ at pH 4 does not diverge significantly from the direct one (Figure 5.2). The increased distinction at pH 5 can be

Copper Retention as Affected by Complex Formation

115

Table 5.1. Cation Balance at Cu(I1) Retention by Soil (mole per mOle Cu(I1)) NL - no Ligands, (1) Cu(1I) Retention, (2) - Cu(I1) Displacement pH=4 (2)

TA (1)

FA (1 )

NL

(1)

(1 )

pH=5 TA (1)

0.64 0.25 0.89

0.64 0.32 0.96

0.54 0.29 0.83

0.63 0.18 0.81

0.76 0.29 1.05

0.43 0.34 0.77

NL

Ca 2 + H+ (Ca 2 ++W)

pH=6 FA (1)

NL (1 )

TA (1 )

FA (1)

0.39 0.19 0.58

0.21 0.77 0.98

0.16 0.76 0.92

0.19 0.77 0.96

attributed to (i) displacement of Cu(II) mainly by Ca2+ and not by H+ ions; (ii) the differences in the solution Ca2+ concentrations in direct and reverse runs; (iii) slower velocity of the reverse process comparatively with the direct one. Thus the Cu2+_(Ca2++ H+) exchange seems to be a reversible process, though it could be difficult to displace all the copper retained due to the higher soil selectivity with respect to Cu (II).

Evaluation of Na 2 EDTA Ability to Extract Retained Copper To extract retained copper, contaminated soil was 3 times extracted with portions of 0.02 mole L- 1 Na2EDTA. To prevent peptization and to improve copper displacement, lO mM Ca(N03)2 was added to the Na2EDT A solution. As it is shown on Figure 5.4, copper was quantitatively revealed from the contaminated soil by 0.02 mole L -I Na2EDTA extraction. Though CuEDTA is a very stable complex (pK = 18.9) (Sillen and Martell, 1970), first treatment revealed only about 80% of the total copper retained amount, and 3 subsequent extractions by Na2EDTA solution were necessary for complete copper displacement. Ca(N03)2 + Na2EDTA solution was shown to extract Cu(II) more efficiently and did not peptisize soil as it was observed for Na2EDTA.

Effect of Tartrate and Fulvic Acid on Cu(lI) Retention Isotherms Tartaric acid (TA) and FA were taken as samples of soluble organic compounds of soil solutions. Tartaric acid (HOOC-CH(OH)-CH(OH)-COOH) is a low-molecularweight dicarbonic hydroxy acid found in root exudates of many plant species (Riviere, 1960; Smith, 1969; Ivanov, 1973; Hale and Moore, 1978), and in leachates from decomposed leaf litter (Nykvist, 1963). The anion derived from dissociation of tartaric acid forms relatively stable complexes with many metals. Therefore, the presence of tartrates may affect the mobility of heavy metals in the root zone and their uptake by plants. Fulvic acids are probably the most common high molecular weight compounds present in soil solutions. Being polyelectrolytes with a variety of functional groups, they are able to form chelate complexes with HM. Baker (1973) has proposed that the metal transport mechanism in soils involves mainly complexes with fulvic and humic acids. For our case study, FA was extracted from the soil samples by 0.1 M KOH with the subsequent sorption on Amberlite XAD-8, as it was recommended by IHSS (Kuwatsuka et aI., 1992), and was purified by dialysis with dialysis membrane "Film 100"

1 16

Fate and Transport of Heavy Metals in the Vadose Zone 150 - - - , - - - - - - - - - - - - - - - - - - - - ; ; ,

CU,eleased =4.29+0,921 *Cu'otoIned

";'

(r=0.989)

120

Cl

~

'0

E E 'ti' Q) tJ)

99%), which shows that the effect of DOC on Cu mobility is of greater importance at higher pH than at lower pH. Quite different conditions than in batch/titration studies are found in column experiments. Still, the model and parameterization for a model substance (purified humic acid) yield an excellent description of Cu in leachate. Provided DOC is mobile itself, we observe that facilitated Cu-transport occurs that leads to faster Cu-Ieaching.

Field Site Accumulation in Soil If the previous speciation modeling captures the main phenomena, not only for conditioned laboratory experiments but also for field situations, we should be able to predict the extractable copper concentration in the soil solution at different depth. From two plots (4A and 3D), soil was sampled from the layers 0-0.20,0.20-0040,0040-0.60,0.600.80, and 0.80-0.90 m. All soil samples were air-dried and sieved « 2 mm). Dissolved organic matter (DOC) varied as a function of depth in the field between 16 and 1 mg/L, solid organic matter (SOC) content between 37.8 and 3.8 g/kg, pH between 3.83 and 5.91, and total Cu content between 1.89 and 0.013 mmollkg. In Figure 604 total Cu content and pH (Figure 6Aa) and solid and dissolved organic matter (Figure 6Ab) are given as a function of depth. Using parameters of Tables 6.1 and 6.2 for describing Cu binding by DOC and Cu binding by (soil) solid organic matter (parameters only determined for the top layers 0-0.20 m), we predicted the extractable Cu concentration in the soil solution at each depth between 0 and 0.90 m with the NICA and the TSF models. In Figure 6.5 the predicted CU ex concentration is given as a function of the measured CUex concentration. The agreement is good for both models. For the NICA model the prediction was slightly better than the TSF model since the correlation coefficients were 0.97 and 0.93, respectively. At the original moment of contamination (1982), soils of plot A and D with the same number had the same (total) Cu content in the plow layer, but currently differences are observed. For soil4A (small pH) the total Cu content in 1994 was already smaller than in soil 3D (large pH) in layer 0-0040 m although the added Cu in 1982 was higher for soil 4A (750 kg/ha) than for soil 3D (500 kg/ha). However, below a depth of 0040 m the copper content in soil 4A is much larger than in soil 3D in 1994. The extractable Cu concentration (CueJ, determined via 0.001 M Ca(N03)2 extraction and the models, is for soil 4A (layer 0-0.20 m), about five times larger than for soil for 3D (large pH), which illustrates the increase in Cu mobility at small pH.

BIOAVAILABILlTV Bioavailability for Soil Organisms Another objective of our research is to determine whether the mobile fraction corresponds with the fraction that is available for organisms. In soil fertility as well as environmental studies involving plant uptake it has been shown that the 0.01 M CaCl2 extractable contents in soil is a better indicator of the fraction that is available for uptake than total extractable contents (Novozamsky et al., 1993). Thus, it may be useful as an indication of availability for soil dwelling organisms too. Marinussen et al. (l997a) ex-

Copper Mobility and Bioavailability in Sandy Soil

137

2.0 , . - - - - - - - - - - - - - - - - - - , 7

,-..

eo

~0 S S '-'

5

1.0

.. CJ

6

1.5

:I:: p..

Cu3D Cu4A pH 3D

::I

u

----

4

0.5

0.0

0-20

20-40

40-60

60-80

pH4A

3

80-90

depth (em)

20

- -EJ- -

SOM 3D

-0-

SOM 4A

g --.--

DOC 3D

-15 ;J'

-10

"& ....... o

- e - DOC4A

o

0-20

20-40

40-60

, 60-80

depth (em)

Figure 6.4. Total copper content (mmollkg) and pH as a function of soil depth (Figure 6.4a) and total organic matter and DOC as a function of soil depth for field plot 4A and 3D (Figure 6.4b).

posed earthworms (LumbriclM rubeLLw) to soil plots 2A, 2D, 3A, and 4 C that were sampled from the Wildekamp site as described above (Table 6.3). The earthworms were exposed under laboratory conditions for 1, 7, 14,28, or 56 days to study tissue Cu accumulation. After sampling, earthworms were rinsed with distilled water and kept for three days in a petri dish on moist filter papers to empty their gut. Earthworms were killed by immersion in liquid nitrogen and dried in an oven at 105°C. Earthworms were individually digested in 5 mL 65% HN03 and 4 mL 20% H2 0 2 . These solutions were analyzed for

eu on a furnace AAS.

138

Fate and Transport of Heavy Metals in the Vadose Zone

-4

]

r-------------------------------------------~

o

NICA

+

TSF

-5

u

t;:s ~

g

-6

§: bO

.£

-7

-8

~--------.----------.---------,--------~

~

~

~

~

4

log[Cu] (moVL) measured Figure 6.5. Extractable copper concentration calculated with the TSF and the NICA model in the Spodosol soil profile as a function of the measured extractable copper concentration for five layer soil 4A and 3D up to 0.9 m depth at 1=0.003 [0.001 M Ca(N03)~. Solid line is the 1:1 line.

Table 6.3. Several Characteristics of the Soil Used in the Experiments [pH CaCI 2, Clay (%), Organic Matter (% C), and 'Total" Cu with Standard Deviation (mmol/kglI Clay

C

pH-CaCI 2

(%)

(%)

1A 2A 3A 4A

3.80 3.91 3.84 3.77

2.9 2.2 1.7 3.4

1.98 2.20 2.16 2.15

0.42 0.98 1.69 1.66

18 28 38 48

4.33 4.24 4.18 3.85

2.4 2.9 1.9 2.4

1.89 2.02 2.14 2.02

0.27 1.13 1.49 1.93

1C 2C 3C 4C

4.73 4.24 4.18 3.85

5.0 3.8 3.3 5.0

2.26 2.34 1.87 2.07

0.38 1.18 1.77 2.26

10 20 3D 40

5.24 5.28 4.95 5.12

3.9 3.8 4.5 3.3

2.21 2.24 2.18 2.10

0.16 1.23 1.77 2.64

3.3 1.0

2.11 0.13

Plot Code

Mean Std

CUT (mmol/kg)

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.02 0.02 0.05 0.09 0.01 0.01 0.02 0.02 0.01 0.03 0.01 0.04 0.005 0.04 0.01 0.06

Copper Mobility and Bioavailability in Sandy Soil

139

Tissue Cu concentrations increased as a function of time and proportionally with total extractable soil Cu content (r2=0.9). Neither the correlation between accumulation and soil pH, nor between accumulation and CU ex (0.01 M CaC1 2), however, was significant. Marinussen et al. (l997a) observed a large mortality of L. rubeLLIM in soils that were high in CU ex (0.01 M CaC1 2). Their data enable us to demonstrate the relationship between mortality and extractable soil Cu content. Speciation of Cu in the soil solution plays a possible role in mortality but this was not investigated. Therefore, we show in Figure 6.6 the average mortality rate in the five contamination levels. It is obvious that the average mortality rate correlates better to CU ex than to CUT. From these observations we conclude that the exposure route for uptake differs from the exposure route that causes mortality. The latter seems to correlate with Cu concentration in soil solution which depends on total soil Cu content and soil pH, as illustrated by Equation 2.

Field Site Accumulation by Earthworms Generally, soil contamination is spatially variable. Hence, in contaminated field sites, exposure of soil-dwelling organisms to soil contamination varies as a function of time. The larger the spatial variability is, the more variation in exposure should be anticipated. Marinussen and Van der Zee (1996) showed that effects of such variation on accumulation of contaminants in organisms depends on the degree of spatial variability and the size of the home-range of the organism. Earthworms are organisms with a limited home range. The mobility of earthworms is influenced by the earthworms' ecology and by environmental conditions; e.g., soil humidity, soil temperature, and food availability (Sims and Gerard, 1985). Mobility and spatial variability are complicating factors for predicting accumulation of heavy metal in earthworms exposed to spatially variable soil contamination. However, this may be a matter of effort rather than of principle. The involved effort may be the reason why field studies on effects of spatial variability of soil contamination on exposure of organisms are rare. Marinussen et al. (l997a,b,c) studied heavy metal accumulation in earthworms under both laboratory and field conditions. The main objective of their studies was to determine whether data on heavy metal accumulation obtained by laboratory studies can be used for predicting heavy metal accumulation under field conditions. Marinussen et al. (l997a) introduced in each of the four differently contaminated plots (Table 6.3), 500 specimens of the earthworm L. rubeLIm. To determine tissue Cu accumulation under field conditions, earthworms were sampled at three times (14, 28, and 70 days after introduction). In Figure 6.7, we show that the decline in tissue Cu concentration between the first and the second sample time coincided with relatively low soil temperatures. These low soil temperatures may have caused a downward migration of L. ruheLLIM. As shown in Figure 6.4a, soil in the upper 40 cm layer is considerably more contaminated than soil at greater depth. Hence, earthworms that move downward are exposed to less contaminated soil and therefore accumulate less copper, which is in agreementwith the data (Figure 6.7). Marinussen et al. (1997a) found that tissue Cu accumulation was significantly correlated with Cup whereas it was correlated neither with soil pH nor with CUex (0.01 M CaCI 2). They also observed large mortality in plots where soil was high in CU ex • These results are in agreement with the laboratory experiments, described above.

Figure 6.6. Average mortality rate of earthworms exposed to soil samples obtained from the Wildekamp site (see text for details) as a function of CUT (6A) or CU ex (0.01 M CaCI~ (68).

Copper Mobility and Bioavailability in Sandy Soil

141

"--------

,---------------------------.10 1.5 temperature plot 4C

Oil

8

.§.

6

........

~0 1.2 8

0.g 0.9

150 0

plot 2D

d 0

4 0.7

0 ;:l

2

U -----

plot 3A

i

8

d 0

plot2A

IT o

0 ;:l

'"'"

'.0

~----~~T---------------~O

-'0

'"

0.1

o

14

28

42

56

exposure time [days] Figure 6.7. Tissue Cu accumulation under field conditions in earthworms Lumbricus rubel/us exposed to contaminated soil at the Wildekamp site. See text for details.

Marinussen et al. (1997b,c) exposed earthworms Dendrohaena veneta to heavy metal (Cu, Pb, Zn) contaminated soils under both laboratory and field conditions. The soil samples used in the laboratory experiments were obtained from a contaminated field site in Doetinchem, NL [sandy loam soil, 7% clay, 3% organic matter (loss on ignition)]. After homogenization of the soil, subsamples were taken and analyzed for CUT (12.8 ± 1.8 mmollkg), CUex (0.01 M CaCI 2; below detection limit = 0.6 IlmollL), and pH-CaCI 2 (7.0 ± 0.06). Dendrohaena veneta were exposed to the soil for 1, 2, 3, 7, 14,28,56, or 112 days to study tissue heavy metal accumulation under laboratory conditions. To study heavy metal excretion, D. veneta were transferred to uncontaminated soil after exposure to the contaminated soil for 112 days. Both accumulation and excretion of Cu appeared to be fast processes (Marinussen et aI., 1997c). An equilibrium in tissue Cu accumulation was achieved 14 days after introduction in the contaminated soil. Three days after being transferred to uncontaminated soil, earthworms lost about 70% of the accumulated Cu. Lead was accumulated to a very small extent, and Pb excretion stagnated at 40% 56 days after transferring to uncontaminated soil. Zinc was not accumulated. From these data, we conclude that tissue Cu concentration in D. veneta adapt rapidly to changes in exposure which are common in spatially variable soil contamination. In another study of Marinussen et al. (l997b), D. veneta were exposed for 14 days to 10 differently contaminated soil samples (field site in Doetinchem, NL) to determine the relationship between soil Cu content and tissue Cu concentrations. They found that in soil containing 0.16 to 1.57 mmollkg Cu, the earthworm tissue Cu concentration increased proportionally to the total extractable soil Cu content (CUT)' Earthworms seemed to achieve a maximum tissue Cu concentration (Figure 6.8).

ILl2

Fate and Transport of Heavy Metals in the Vadose Zone

1.4

r-------------------------.

•

1.2

j

1

c o

0.8

t

0.6

'.0

•

• •

u

::s

U

g

0.4

'"'" '.0 0.2

o ~---~----~----~----~----~----~----~----~ o 2 4 16 14 6 8 12 10 0.43 M HN03 extractable eu [mmol/kg]

Figure 6.S. Tissue Cu concentrations in earthworms Dendrobaena veneta exposed to Cu contaminated soil under laboratory conditions.

Additionally, Marinussen et al. (1997b) introduced about 100 specimens of D. veneta at each of 20 homogeneously distributed locations in the field site in Doetinchem. The spatial variability of soil Cu contamination in this field site was considerable (Figure 6.9). At three different times, earthworms were sampled and analyzed for tissue Cu concentration (procedure is described above). For each earthworm, the Cu concentration factor was calculated (CFcu is the ratio tissue Cu concentration to the total extractable soil Cu content). An accurate estimation of the total extractable soil Cu content at each location was obtained by geostatistical interpolation (in CadU disjunctive kriging). They also calculated CFCU for earthworms exposed under laboratory conditions (derived from Figure 6.S). It appeared that CF CU values under field conditions were in good agreement with CFcu values under laboratory conditions (Figure 6.10). This successful extrapolation from laboratory to field scale was a result of a high soil sampling density. They took Sl soil samples in the top layer (0-20 cm) in an Sl m 2 experimental plot. The large variation in CFCU under field conditions may be explained by a considerable decrease of soil Cu contamination as a function of depth at this site (Figure 6.11). Since D. veneta moves up and down through the upper layer of soil, the latest exposure level is uncertain as a result of this kind of spatial variability. The field studies by Marinussen et aI. (1997 a,b) show that earthworm heavy metal accumulation under field conditions can be predicted using relationships between soil heavy metal contamination and tissue heavy metal concentrations determined under laboratory conditions. However, a high soil sampling density is required to obtain accurate estimations of exposure levels of individual specimens.

Copper Mobility and Bioavailability in Sandy Soil

143

Figure 6.9. Copper contamination at the field site in Doetinchem, NL. The vertical axis is the total extractable copper in soil (mmollkg). Soil samples were taken from the top layer (0 to 0.20 m). The soil sampling scheme was a squared 8 by 8 grid with 1.0 m node distance, resulting in 81 soil samples at 64 m2.

SUMMARY We presented two models, the NICA and the TSF models that have been developed to describe, among others, heavy metal sorption by soil. For both models, data on pHdependent copper binding by purified humic acid were fitted. The description was good and the determined parameters are in agreement with literature for other humic acids and conditions such as ionic strength. For natural solid soil organic matter it is plausible that the reactivit;y is smaller, whereas the sorption site heterogeneit;y is larger than for dissolved purified humic acid. Adapting

144

Fate and Transport of Heavy Metals in the Vadose Zone

2.5

r--------------------------,

2 1- •

•

....

*

0

u

~

1.5

e::

l-

0

•

'.;::l

o:s

b

e::

(l.l

u

e:: 0

u

1

I-

0.5

t-

;::l

u

0.43 M HN03 extractable eu in soil [mmol/kg]

Figure 6.10. Copper concentration factors in earthworms Dendrobaena veneta exposed to contaminated soil under laboratory conditions (circles) or field conditions (asterisks).

100

eil ~ 0

§

~

;::1

u

10

(l.l

::0 CIl

.... g

~

(1)

0

,.,

~

:E M

~ 0

0.1

V

IV

VI

III

VII

II

VIII

IX

Figure 6.11. Total extractable soil Cu content (CUT) in four consecutive layers of 5 cm thickness at 9 spatially distributed locations in the Doetinchem field site; open = 0-5 cm, hatched = 5-10 cm, cross-hatched = 10-15 cm; fine-hatched = 15-20 cm.

Copper Mobility and Bioavailability in Sandy Soil

145

only the two parameters that are related with reactivity (sorption maximum) and heterogeneity, the two models describe pH-dependent copper binding by natural organic matter also. To further ascertain the applicability of the models, the agreement between model prediction and measured data was considered for two rather different situations. The first of these concerned the leaching of copper for two sandy topsoil columns that have different pH and DOC levels. The other situation was the retention that is apparent in a field soil for depths up to 0.90 m, with significant variations in dissolved and soil organic matter, total copper, and pH. In both cases the agreement between model predictions and observations was good. This indicates that for sandy soil, the two models capture the main phenomena. Hence, with regard to both mobility and the chemical interpretation of a neutral unbuffered salt extraction, an interpretation using the NICA and the TSF models may improve our understanding. The chemical speciation modeling may be necessary to be able to predict, e.g., copper uptake by plants. However, the available information with regard to accumulation of copper earthworms indicates that bioavailability for earthworms depends on the total copper content rather than the fraction that can be extracted with a mild extractant. The latter fraction does appear to control the short-term toxicity of copper for earthworms, possibly due to oral uptake. Copper accumulation by earthworms may be controlled mainly by dermal uptake and is not strongly related with short-term toxicity effects. As the total copper levels in field soils are often spatially variable, copper accumulation in field situations may be difficult to predict. For a field site, we showed that it is in principle feasible to predict copper accumulation using observations from laboratory experiments and a reliable map of total copper contents of the involved site. Unfortunately, to obtain a reliable map may require a high density of soil sampling. In summary, we conclude that tools have been developed to translate laboratory data such that they have relevance for soil in situ. To apply these tools for practical predictions of bioavailability and mobility of heavy metals is currently under investigation.

REFERENCES Aten, C.F. and S.K. Gupta. On heavy metals in soil; rationalization of extractions by dilute salt solutions, comparison of the extracted concentrations with uptake by rye grass and lettuce, and the possible influence of pyrophosphate on plant uptake. Sci. Tot. Environ. 178, pp. 45-53, 1996. Avdeef, A., J. Zabronsky, and H.H. Stuting. Calibration of copper ion selective electrode response to pCu 19. AnaL. Chem. 55, pp. 298-304, 1983. Benedetti, M.F., C.J. Milne, D.G. Kinniburgh, W.H. Van Riemsdijk, and L.K. Koopal. Metal ion binding to humic substances: Application of the non-ideal competitive adsorption model. Environ. Sci. TechnoL. 29, pp. 446-457, 1995. Bruus Pedersen, M., E.J.M. Temminghoff, M.p.J.e. Marinussen, N. Elmegaard, and C.A.M. van Gestel. Copper uptake and fitness of Fouomia candUJa willem in a copper contaminated sandy soil as affected by pH and soil moisture AppL. SoiL &oL. 2(6), pp. 135-146, 1997. Gooddy, D.C., P. Shand, D.G. Kinniburgh, and W.H. Van Riemsdijk. Field-based partition coefficients for trace elements in soil solutions. European J. SoiL Sci., 46, pp. 265-285, 1995. Kinniburgh, D.G., C.J. Milne, and P. Venema. Design and construction of a personal-computerbased automatic titrator. SoiL Sci. Soc. Am J. 59, pp. 417-422, 1995.

146

Fate and Transport of Heavy Metals in the Vadose Zone

Kinniburgh. D.G .• C.J. Milne. M.F. Benedetti. J.P. Pinheiro. J. Filius. L.K. KoopaL and W.H. Van Riemsdijk. Metal ion binding by humic acid: Application of the NICA-Donnan model. Environ. Sci. Techno!. 30. pp. 1687-1698. 1996. Koopal, L.K.. W.H. Van Riemsdyk. J.C.M. De Wit. and M.F. Beneditti. Analytical isotherm equations for multicomponent adsorption to heterogeneous surfaces. J. Coll. Interface Sci. 66. pp. 51-60. 1994. Korthals. G.W.• A.D. Alexiev. T.M. Lexmond. J.E. Kammenga. and T. Bongers. Long-term effects of copper and pH on the nematode community in an agroecosystem. Environ. ToxicoL. Chem. 15. pp. 979-985. 1996. Lexmond. Th.M. The effect of soil pH on copper toxicity for forage maize as grown under field conditions Neth. J. Agric. Sci. 28. pp. 164-183. 1980. Marinussen. M.P.J.C. and S.E.A.T.M. Van der Zee. Conceptual approach to estimating the effect of home-range size on the exposure of organisms to spatial variable soil contamination. &ol. MOdelling. 87. pp. 83-89. 1996. Marinussen. M.P.J.C.• S.E.A.T.M. Van der Zee. and F.A.M. De Haan. Cu accumulation in LumbriclM rubelllM under laboratory conditions compared with accumulation under field conditions. &otox. Environ. Safety 36. pp. 17-26. 1997a. Marinussen. M.P.J.C.• S.E.A.T.M. Van der Zee. and F.A.M. De Haan. Cu accumulation in the earthworm Dendrobaena veneta in a heavy metal (Cu. PB. Zn) contaminated site compared to Cu accumulation in laboratory experiments. Environ. PoLL. 96(2). pp. 227-233, 1997b. Marinussen. M.P.J.C.. S.E.A.T.M. Van der Zee. F.A.M. De Haan. L.M. Bouwman. and M.M. Hefting. Heavy metal (Copper. Lead and Zinc) accumulation and excretion by the earthworm. Dendrobaena veneta. J. Environ. Qual. 26. pp. 278-284. 1997c. Mulder. J .• D. Van den Burg. and E.J.M. Temminghoff. Depodzolization Due to Acid Rain: Does Aluminium Decomplexation Affect to Solubility of Humic Substances? In Humic SubdtancN in the GWbal Environment and Implicationd on Humic Health. N. Senesi and T.M. Miano, Eds .• Elsevier Science. 1994. pp. 1163-1168. Novozamsky. 1.. Th.M. Lexmond. and v.J.G. Houba. A single extraction procedure of soil for evaluation of uptake of some heavy metals by plants Int. J. Environ. Anal. Chem. 55. pp. 47-58, 1993. Sanders. J.R .• S.P. McGrath. and Mc.M. Adams. Zinc. copper and nickel concentrations in soil extracts and crops grown on four soil treated metal loaded sewage sludges. Environ. PoLL. 44, pp. 193-2lO. 1987. Sims. R.W. and B.M. Gerard. Earthwormd, Linnean Society Synopses of the British Fauna (Ne'w Series) No. 31. London and Leiden. E.J. Brill/Dr. W. Backhuys. 1985. Stevenson. F.J. HumUd ChemiJtryj GenNiJ, CompOdition, Reactiond. John Wiley & Sons. Canada. 1982. Ch. 14. Temminghoff. E.J.M.• S.E.A.T.M. Van der Zee. and M.G. Keizer. The influence of pH on the desorption and speciation of copper in a sandy soil. Soil Sci. 158. pp. 398-408. 1994. Temminghoff. E.J.M.• S.E.A.T.M. Van der Zee. and F.A.M. de Haan. Copper mobility in a copper contaminated sandy soil as affected by pH. solid and dissolved organic matter. Environ. Sci. Techno!. 31(4). pp. 1109-1115. 1997. Tipping. E .• A. Fitch. and F.J. Stevenson. Proton and copper binding by humic acid: application of a discrete-site/electrostatic ion-binding model. Eur. J. Soil Sci. 46. p. 95. 1995. Van Dobben. H.F .• J. Mulder. H. Van Dam. and H. Houweling. In Impact of AcwAtmodphm; Depodition on the BiogeochemiJtry of Moorland Poou and Surrounding Terredtrial Environment. Pudoe Scientific Publishers. Wageningen. 1992. Chapter 2. Van Riemsdijk. W.H. Keynote Lecture. 15th World CongrNJ of Soil Science. Acapulco. Mexico; The International Society of Soil Science. Madison. WI. Vol. 1, 1994. p. 46.

CHAPTER 7

Selenium Speciation in Soil Water: Experimental and Model Predictions Katta J. Reddy

INTRODUCTION Selenium (Se) occurs naturally in soils. The main geological source of Se in soils is cretaceous shales. The common range ofSe in soils is between 0.01 and 2 mg/kg-1 (Lakin, 1972). However, in seleniferous soils Se concentrations can be as high as 1200 mg/kg- 1 (Adriano, 1986). Selenium is a required micronutrient for humans and animals. Its requirement, however, for plants is not clearly understood. Human activities introduce Se into soils in many ways. These include burning fossil fuels (coal), disposal of coal combustion by-products, mineral extraction activities, and application of fertilizers (Nriagu, 1989). Selenium as a naturally occurring element is gaining national and international attention because of its potential deficiency and toxicity problems to humans and animals. For example, in China two types of Se human diseases, cardiomyopathy (Se deficiency) and selenosis (Se toxicity) were reported (Yang et al., 1983). In another case, disposal of agricultural drainage water into wetlands of Kesterson National Wildlife Refuge in California, caused bioaccumulation of Se by plants, fish, waterfowl, and animals at levels that were harmful (Ohlendorf, 1989). In soil water Se may exist in different oxidation states. These include Se (+6), Se (+4), Se (0), and Se (-2). Among these, the Se (+6) and Se (+4) oxidation states are thermodynamically stable under the pH and redox conditions that are found in most soils (Elrashidi et al., 1987). However, in low redox environments Se (0) and Se (-2) species may be expected. The Se (+6) and Se (+4) oxidation states in soil water may be comprised of free ions and complexes. These include SeO/-, HSe04-' H 2SeO/, CaSe04o, MgSe040 and SeOl-, HSe03-' H2Se03o, CaSe030, and MgSe03o. Additionally, soil water contains dissolved organic carbon (DOC) due to the plant, animal, and biological activity; therefore, DOC-Se complexes are expected. Very little information exists on the speciation of dissolved Se in soil water because it is difficult to separate Se (+6) and Se (+4) oxidation states without destroying their 147

148

Fate and Transport of Heavy Metals in the Vadose Zone

natural distribution. However, research in surface and groundwater suggest that dissolved Se consists of not only Se042- and Se032- but also metal-Se complexes and DOCSe complexes (Siu and Berman, 1989; Cooke and Bruland, 1987; Tanzer and Heumann, 1991; Wang et al., 1994; Reddy et al., 1995a). Similarly, we can expect different dissolved Se species in soil water because soil water contains higher ionic strength than surface water or groundwater due to an increased concentration of dissolved salts. Thus, isolation, extraction, and measurement of dissolved Se species in soil water are important. Such information may help in predicting the fate (availability, toxicity, adsorption, and precipitation) and transport (mobility) of dissolved Se species in soil vadose zones (Reddy, 1998). To date, there is little documentation on the quantification and model verification of dissolved Se speciation in soil water. Therefore, in this chapter we review procedures proposed for the speciation of dissolved Se, compare experimentally measured dissolved Se speciation with a model prediction, and identiry further research needs in the speciation of Se in soil water. The emphasis will be placed on SeOl- because it is predominant and more toxic than SeOl- in natural environments.

SPECIATION OF DISSOLVED Se The dissolved Se speciation in an aqueous solution can be performed with analytical methods and/or geochemical models. Several methods including hydride generation atomic absorption spectrometry (HG-AAS), fluorometry, (FM), high pressure liquid chromatography (HPLC), and ion chromatography (IC) are available for the speciation of Se. Among these methods, HG-AAS is the most commonly used method for the speciation of dissolved Se in aqueous solutions because it can detect as low as 1 pg L- 1 of Se. The HG-AAS method measures dissolved Se in an aqueous solution as Se (+4), from which Se (+6) and DOC-Se can be measured by altering the pretreatment steps as described below (Cutter, 1978; Workman and Soltanpour, 1980). The concentration of Se (+4) in a sample is measured by generating H 2Se with a NaBH4 solution and 7 M HCl (undigested). Another aliquot of sample is heated for 20 minutes at 85°C with 7M HCl to reduce Se (+6) to Se (+4). The concentration of Se in this solution is considered as the sum of Se (+6) and Se (+4) (digested). Difference between the concentration of Se in digested and undigested samples is considered as the concentration of Se (+6). The undigested or digested samples do not include DOC-Se. The total Se concentration in an aqueous solution is measured by oxidizing organic matter with H 20 2 for 20 minutes at 85°C and then digesting with 7M HCl for another 20 minutes at 85°C. This total Se is the sum of Se (+6), Se (+4), and DOC-Se. The difference between total Se and digested Se is considered as DOC-Se species. However, the concentrations of Se (+6) and Se (+4) in soil water, determined with HG-AAS, may consist of SeOl- and SeOl- species and their solution complexes. If SeOl- and Se032- can be isolated and extracted directly from soil water, then they can be measured using HG-AAS. A geochemical model (e.g., MINTEQA2, GEOCHEM, WATEQFC) could be used to calculate the speciation of dissolved Se in soil waters. Chemical data such as dissolved concentrations of cations and anions, pH, and redox potential of the soil water are required by these models to calculate the chemical speciation (i.e., activity or concentra-

Selenium Speciation in Soil Water: Experimental and Model Predictions

149

tion of free ions and complexes) by solving a series of mass-balance equations through an iterative procedure. However, models are based on the assumption of equilibrium; therefore, soil water should be close to a steady-state condition. The mass-balance equations for each dissolved species should contain all possible solution species to ensure accurate calculation of the speciation; omission of any significant solution species from the mass-balance equation will cause overestimation of the activity of dissolved free ions. Reported values for the equilibrium constants for solution species might vary and the constants for some species that may be present are not known, thus the species cannot be included in the model. All these factors could lead to the misinterpretation of the speciation of dissolved chemicals in soil water. Excellent discussions on this topic are presented by Amacher (1984), Baham (1984), and Sposito (1994). Few studies have examined the speciation of dissolved Se in soil water (See et aI., 1995; Fio and Fujii, 1980; Reddy et aI., 1995a), despite its importance in understanding Se solubility, availability, toxicity, and mobility. Reddy et al. (l99Sa) reported that increasing the pH of CuCl2 solution containing SeOl-, SeOl-, and sulfate (SOl-) by adding NaOH precipitates cupric oxide (CuO). The zero point of charge (ZPC) for CuO occurs at pH 9.S. As illustrated in Figure 7.1, CuO particles adsorb SeOl- and SeOl- at pH 6 and desorb them at pH 13. Reddy et al. (l99Sa) successfully used this phenomenon and isolated SeO42- and Se032- from groundwater samples containing and DOC concentrations greater than 10,000 and SO mglL, respectively.

sol-

EXPERIMENTAL AND MODEL PREDICTIONS Dissolved Se Speciation with CuO The procedure for the comparison of experimentally measured Se speciation in soil water with model predictions is outlined in Figure 7.2. Soil samples were extracted with distilled-deionized H 20 after reacting for 24 hours on a mechanical shaker at 200 rpm under the laboratory temperature. Each soil H 20 suspension filtered and each filtered sample was divided into two subsamples. One subsample was analyzed for Se (+6), Se (+4), and DOC-Se with the HG-AA in addition to major cations and anions, as well as pH (Figure 7.2). The other subsample was used for extracting SeOl- and SeOl- with the CuO particles. The experimental procedure to isolate and extract SeOl- and SeOl- species from soil water involved adding CuO particles to solutions and lowering the pH to 6.0 and reacting for 4 hours, followed by separating the CuO particles from solution and increasing the pH to 12.S and analyzing solutions for SeOl- and SeOl- by HG-AAS. The concentrations of metal-SeO/- and metal-SeOl- complexes in soil water were calculated by subtracting the concentrations of Se042- and SeOl- from Se (+6) and Se (+4) concentrations, respectively. From SeOl-, SeOl-, metal-SeOl-, metal-Se032-, and DOC-Se, the speciation of dissolved Se in soil water samples was calculated.

Dissolved Se Speciation with GEOCHEM As discussed earlier, several geochemical models including GEOCHEM and MINTEQA2 are available to model the speciation of dissolved trace elements in soil

150

Fate and Transport of Heavy Metals in the Vadose Zone

pH=6.0 pH- 13.0 Aqueous Solution Figure 7.1. Illustration of seO/- and SeO/- adsorption and desorption mechanism by the (uO particles in aqueous solution.

water. For this research the program GEOCHEM was used to calculate the speciation of dissolved Se (free ions and metal-SeOl- and metal-SeO/- complexes) in soil water because it computes the highest number of solution species. The pH and the concentrations of cations and anions were used as input to the model to calculate the speciation. For Se input, Se (+6) and Se (+4) concentrations (determined with HG-AAS) were used without redox potential because SeOl- and SeOl- reduction and oxidation reactions are very slow (Reddy et al., 1995b). From the input of pH and concentration of Se (+6), Se (+4), cations, and other anions, GEOCHEM calculates the concentration of free ionic species (e.g., SeOl- and Se032-) and metal-SeO/- and metal-SeO/- complexes using the thermodynamic data of solution species. The thermodynamic data used to calculate metal-Se042- and metal-SeO/complexes in soil water are shown in Table 7.1. The concentration of free SeOl- and SeO/- ionic species and metal-SeO/- and metal-SeO/- complexes predicted by the GEOCHEM were compared with the CuO extraction method (Figure 7.2).

Comparison Selected chemical data of soil water, which are used for the discussion, are presented in Table 7.2. The pH of soil water ranged between 5.8 and 8.4. Total dissolved Se concentrations were between 11 and 162 pg L- 1• These concentrations are well below the limit of quantification of Se analysis with IC (Blaylock and James, 1993). Soil water 1 contained high concentrations of dissolved Mg, Na, and DOC when compared with other soil water samples. Soil water 1, 2, 5, and 6 contained higher concentrations of dissolved Ca than soil water 3 and 4. Dissolved SO/- concentrations in soil water ranged between 15 and 1666 mg L- 1• Dissolved Se analyses with HG-AAS are shown in Figure 7.3. It should be noted that concentrations of Se (+6) and Se (+4) also include SeO/- and SeO/- species plus metal complexes. The soil waters examined in this study were dominated by Se (+6) concentrations. The Se (+6) concentrations ranged between 5 and 136 pg L- 1, whereas Se (+4) concentrations ranged between < 1 and 7 pg L -I. The DOC-Se concentrations were found between 1 and 19 pg L- 1• Similar distribution for dissolved Se species was observed by Fio and Fujii (1990) in soil water from California. Results from the isolation and extraction of SeOl- and SeO/- with CuO are presented in Figures 7.4 and 7.5. These results suggest that the removal of SeO/- ranged between 70 and 83%, except soil water 4, when compared with Se (+6) concentrations

Selenium Speciation in Soil Water: Experimental and Model Predictions

Analyze pH, CatioDl, AniODS, Se (6+), Se (+4), and DOC-Se

151

Isolate and Extract Selenate and Selenite with CuO

Se Speciation with GEOCHEM Input pH, Cations, ADions Se (+6), and Se (+4)

Se Speciation with COO Determine Metal Selenate Complexes Selenite Complexes

Se Speciation Selenate and Selenite Ions Metal Selenate and Selenite Complexes

Se Speciation Selenate and Selenite Ions Metal Selenate and Selenite Complexes

Figure 7.2. Procedures for the dissolved Se speciation comparison between the CuO/HG-MS and geochemical modeling.

Table 7.1. Metal-SeO/- and Metal-SeO/- Complexation Reactions used in the Thermodynamic Database of GEOCHEMa No.

1 2 3

4

Reaction Ca 2+ + SeD 42- Mg2+ + SeD 4 2- Ca 2+ + SeD 3 2- Mg2+ + SeD 3 2- -

J(

CaSeD 40 MgSeD4 0 CaSeD 30 MgSeD 30

102 .8 102 .4 104.2 105.0

a Sposito and Mattigod, 1980.

(Figure 7.4). The Se analysis of the Cu 0 supernatant solutions suggested that 17 to 30% of Se042-was left in the solutions. However, for Se032-the removal rate is 100%, except soil water 2, when compared with Se (+4) concentrations. For soil water 5 and 6, Se032concentrations were below the detection limit of 1 pg L- 1 (Figure 7.5). These results also suggest that other anions such as and DOC did not interfere in the SeOi- and Se032- removal process by CuO particles. If S042- and DOC compete with SeOi- and Se032- for adsorption sites, one would expect no adsorption of these species by the Cu 0 particles, because the ratio of S04 2- and DOC to Se is very high. The results also suggest that metal-SeOl- complexes are not significant. The observed 70 to 83% removal of SeOi- by the CuO particles from the soil water could be due to the presence of other Se (+6) species (e.g., MgSe040, CaSe040), which may not be adsorbed by the CuO particles (Reddy and Gloss, 1993). For example, Giordano et al. (1983) showed that formation of neutral complexes (e.g., CdCI2°) lowers

sOi-

152

Fate and Transport of Heavy Metals in the Vadose Zone ""---,,--,-------

-"'-""""'---------."---

"

~-------

----------

"

--------

Table 7.2. Selected Chemical Data of Soil Water (SW)a Parameter pH Calcium Magnesium Sodium Potassium Sulfate DOC Selenium ~g L- 1

SWl

SW2

SW3

SW4

SW5

SW6

7.5 188 922 745 47 1666 144 162

7.9 214 48 31 14 166 60 21

8.4 58 26 36 16 16 33 13

8.0 39 26 29 7.2 15 24 11

6.1 243 63 18 14 960 19 69

5.8 275 76 31 9.4 1130 7.6 120

a Units are mg L-1. Data for SW2, SW5, and SW6 adapted from Reddy (1998). Reprinted

with permission of John Wiley 8- Sons, Inc.

Legend

-",*--

Se(+6) Se(+4)

.............

DOC-Se

.i

1 ~

..............

....

o - - - . ::::.:::.~-.=.'"".:::-.::-:-:...==I................-...-...-...-...-.. ..... SW1

SW3

SW4

SW5

SW6

Soil Water Samples Figure 7.3. Dissolved Se concentration in soil water as measured by HG..AAS.

the concentration of Cd2+, which decreases the adsorption and increases the mobility of Cd in sewage sludge amended soils (see also Mattigod et aI., 1979; Bowman and O'Connor, 1982; Elrashidi and O'Connor, 1982). There may be a number of reasons why CuO particles adsorb both SeOi- and SeOlin the presence of other ions; however, the most possible reasons include: • On a time scale, the metal-SeO/- and metal-Se032- complexation reactions in aqueous solutions are much faster than adsorption reactions of these species by the CuO particles. Also, SeOl- and Se052- adsorption reactions by the CuO particles are much faster than reduction and oxidation of these species in aque-

Selenlul1l Speciation in Soil Water: Experimental and ModeJ Predictions

D

Initial

•

CuOMethod

SoN3

SlN4

Soil Water Samples Figure 7.4. Extraction of Se (+6) from soil water with CuO method.

SW1

D

Initial

•

CuOMethod

SW2.

Soil Water Samples Figure 7.5. Extraction of Se (+4) from soil water with CuO method.

153

Fate and Transport of Heavy Metals in the Vadose Zone

154 -

-----,-,,--

""--"""---~--.'"-"---"

-".,----""'----

---~----"'-""-,~--

""~--,--'"

-

""

---"'''''"-----,."---

Table 7.3. Speciation of Se in Soil Water with CuO/HG-AASa Species pH SeO/Se0 32 Metal-SeO/DOC-Se Total a

b

SW1

SW2

SW3

SW4

SW5

SW6

7.5 59 4 25 12 100

7.9 43 19 19 19 100

8.4 38 38 8 16 100

8.0 46 46 NSb 9 100

6.1 58 NS 15 27 100

5.8 72 NS 22 6 100

Units are %. Data for SW2, SW5, and SW6 adapted from Reddy (1998). Reprinted with permission of John Wiley a Sons, Inc. NS=not significant

~

-50

CI)

e

0,1

e

~

200 0

u ~

e

~

450

:E

.~

3

-550 -300

......

2

>

~

-50

e1

e

~

200

°

u ~

ns were correlated with the dissolved organic carbon, while Zn and Cd were also infl~ed by low pH and high levels of electric conductivity. They concluded that Cu complex~~ showed high stability, and a considerable part were of high molecular weight and nonlabile. Japenga et al. (1992) also studied the effect of the liquid fraction of animal manure on heavy metal solubilization in soil, and found a significant relationship between dissolved organic carbon and Cu concentrations in aqueous extracts (Figure 10.6). They concluded that, together with pH, complexation involving dissolved, high molecular weight organic matter is the most important driving force for heavy metal solubilization. Metal complexation was also considered to be one of the causes of metal leaching from a soil in a reed bed

210

Fate and Transport of Heavy Metals in the Vadose Zone

1.2

.------,I----~ I - - - - rI -- - - . -I -- - - - ,

1.0 -

-

!l

0

-

00

00

0.8

0

00%

f-

0

0

bi)

e

--g

0

-

0 0

0.6

f-

0.4

f-

0.2

-

-

0

Q (J

=

U

o

o ~o 0

0.0 0

-

o

-

f8

I

I

I

I

200

400

600

800

1000

DOC (mgI;l) Figure 10.6. Relationship between dissolved organic carbon and Cu in aqueous extracts of a soil mixed with liquid animal manure (selected data from Japenga et aI., 1992).

system continuously flooded with sewage (Wenzel et al., 1992). Barrado et al. (1995) also concluded that extracts from eucalyptus and oak leaf litter showed complexation ability for metals, and could estimate the complexing constants for various metals.

THE CASE OF SEWAGE SLUDGE Addition of sewage sludge to soils was found to decrease the sorption of Cd at low concentrations of this metal (Neal and Sposito, 1986). In soils treated with sewage sludge and artificially contaminated with high doses of Cu in the form of Cu carbonate, Cheshire et al. (1994), using electron magnetic resonance, found evidence of Cu solubilization through complexation. The results for organically bound Cu in the soil solution indicate oxygen ligand coordination in equatorial arrangement. Keefer et al. (1994) also found significant metal-organic association in soils amended with sewage sludge, and McGrath and Cegarra (1992) observed large increases in the most soluble fractions of metals in a soil with long-term applications of sewage sludge. They found that the fractionation of metals in the original sewage sludge differed from that observed in the soil treated with the residue. Frequently, sewage sludges have relatively high metal contents, so that their effect on metal mobility in soils has been often attributed to the metals present in the residue itself: Sposito et al. (1982) concluded that the accumulatienohnetals in soils amended with sewage sludge was governed by the metal content in the sludge, and Cavallaro et al.

Metal Retention and Mobility as Influenced by Some Organic Residues

211

Table 10.2. Examples of Maximum Permissible Concentrations of Some Metals in Soil after Application of Sewage Sludge (mg kg- 1 ) Soil pH

5.0-5.5 5.5-6.0 6.0-7.0 > 7.0 > 5.0 < 7.0 > 7.0 a b

Country

Cd

a

UK UKa UKa UKa UKa Spain b Spain b

3 1 3

Cu

Ni

80 100 135 200

50 60 75 11P

50 210

30 112

Pb

Zn

200 250 300 450 300 50 300

150 450

Data selected from Department of the Environment, Code of Practice for Agricultural Use of Sewage Sludge, HMSO Publications, London, 1992, p. 6. Data selected from Boletin Ofloal del Estado, No. 262, Madrid, 1990, p. 3234.

(1993) found that increases in Mehlich-3 extractable eu and Zn in soils treated with sewage sludge were similar to the amounts of these metals added in the residue. Most countries have established regulations concerning the use of sewage sludge on the basis of the maximum permissible contents of potentially toxic elements in soil after application of sewage sludge (Table 10.2) and annual rate of addition of such toxic elements, so that no legal limit exists if the sewage sludge added to a soil shows a low content in toxic metals. It is thus forgotten that solubilization of the metals already present in the soil can be enhanced by complexation, as shown by some of the authors quoted in the previous paragraph. This lack of attention paid to the effect of soil management practices, especially the use of sewage sludge, on the solubility of the metals present in amounts below the legal limits in the soil has been claimed by several authors (McBride, 1994; Evans et aI., 1995), and has been favored by the conclusions of some authors, who even found a decrease in metal mobility in some cases (Emmerich et aI., 1982; Saviozzi et aI., 1983; Hooda and Alloway, 1994).

A MEDITERRANEAN CONCERN: OLIVE Mill WASTEWATER

Setting Up the Problem In areas with extensive production of olive oil, disposing of the residues from manufacturing plants for this agricultural product represent a major concern. The traditional procedure implies generating large amounts of wastewater (called aLpecbin, from now on OMW) with extremely high BOD and other undesirable properties which have caused the existence of regulations prohibiting its disposal in rivers since 1981. Everyyear, about 10 million tons of this waste have to be disposed of in the Mediterranean countries, mainly by storing them in evaporation ponds, composting the resulting sludge with other plant refuse or, in countries where the production of this residue is not especially high, discharging them into watercourses. In recent years, olive oil production plants are being adapted for new techniques using much smaller volumes of water, so that production of OMW is decreasing sharply, but its disposal must still be considered until total substitution of the old manufacturing plants, and the existence of small factories which cannot afford the changes cannot be forgotten, at least during several years in the near future.

212

Fate and Transport of Heavy Metals in the Vadose Zone

While the effect of sewage sludge on heavy metal availability has been extensively studied, as summarized in the previous section, literature on the relationships between heavy metals and OMW is scarce, although in the last few years some authors have found evidence of significant metal solubilizing effects of this residue, both when added to soils and when present in freshwaters. OMW is a slightly acid (pH 4-5), dark-colored aqueous phase with highly variable composition, containing 10-15% organic matter and 1-2% of mineral salts. Its contents in heavy metals' is usually negligible, except Fe (1020 mg L- 1), Mn « 5 mg L-1), and Zn « 2 mg L- 1). Several authors have given detailed descriptions of the composition of this waste (e.g., Gonzalez-Vila et aI., 1992; MartinezNieto and Garrido-Hoyos, 1994).

Effect of OMW on Metal Retention Properties of Soils As with other organic wastes, one of the first ideas that emerge when recycling OMW is considered is its application to soils as fertilizer, and it has been frequently used to irrigate olive trees. Considering previous knowledge of the nature of this residue, SaizJimenez et aI. (1987) deemed it of interest to carry out a detailed study of its chemical composition in order to evaluate its potential value as soil fertilizer. They concluded that the composition of the humic fraction was different from soil humic acids, but still suggested that the residue had good properties as fertilizer. On a relatively short-term basis, applications of a composted olive mill sludge to soils have been found to cause no harmful effects on plants, the improvement of soil physical properties is apparent, and significant increases are found in soil organic N. Also, increases in available Cu, Zn, Mn, and Fe determined by DTPA extraction have been observed (Martin-Olmedo et al., 1995). In a study specifically oriented toward the effect of OMW on metal availability, Perez and Gallardo-Lara (1993) found that although OMW initially caused a slight decrease in Zn availability and hardly any effect on Cu availability, a significant residual increase in Cu availability was observed after growing barley and ryegrass. A fundamental aspect that must be considered is whether the presence of OMW affects the action of soils as a sink of heavy metals which are added in soluble forms. Madrid and Diaz-Barrientos (1994) chose three soils (called A, B, and C) with widely differing contents in organic matter, carbonate, and clay fraction and CECs for that purpose. Soil A had been manured in the field with 150,000 kg ha- I of a compost obtained from OMW and other plant refuse, and soil B had received a similar dose of raw OMW. Soil C was untreated. Moreover, samples of the three soils were aged in vitro with freeze-dried OMW in a proportion corresponding to twice the dose received by soils A and B in the field. The reaction of several metals with the original, manured, and aged samples was studied. Figure 10.7 shows the results for the adsorption isotherms obtained for Cu and Zn. The adsorption of these two metals was strongly decreased by mixing and aging the soils with OMW, while manuring with OMW or compost obtained from it only caused a significant decrease in the case of Zn. Manuring even caused a slight increase in Cu adsorption by soil A. The pH values of the adsorption experiments did not show differences large enough to explain the differences in adsorption. The authors suggested that the decrease in adsorption when OMW was added in large doses could be the result of coating the sorbing surfaces with organic matter. However, in the samples containing

o

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80 60

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40 20

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0

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~

150

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4

6

8

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-I

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:::I C.

~

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0

5

10

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20

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Ii

Zn/A

100 f-

/

~

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~ 100

50

;:;: '70 em

Profile W 100% 80%

0

50

100

0

50

100

150

0-30

60% 30-70

40% 20%

70-100 0%

~

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8

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...

g ~

E

~"

100-130 em

Profile I 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

mg/kg

150

0-30

30-70

70-100

Figure 13.3. Vertical distribution and chemical fractionation of Zn in soil profiles (0-130 cm) in Site I; Metal binding fractions: FO+ 1(EXC): pore solution and exchangeable; F2 (CARB): carbonate associated; F3+4 (EMRO): easily and moderately reducible Mn- and amorphous Fe-oxides; F5(OM): oxidizable, associated with organic matter and sulfides; F6(R): residual (lithogenic matter).

Site II: Irena Glasswork Inowroclaw, Poland (Figures 13.1, 13.8)

~erous

Lead is one of the most and widespread anthropogenic pollutants. Environmental contamination with lead is associated with processing of zinc and lead ores, combustion of leaded gasoline in car engines, production of accumulators, paints, etc. Of

282

Fate and Transport of Heavy Metals in the Vadose Zone

Cd Profile R o

100% 90% 80% 70% 60%

0,1

0,2

mg/kg

0,3

0-30 I----------~r=___,I

50%

40% 30% 20% 10% 0%

20-30

I=llIII!l~.

30-50

PIl~

••

50-70 ~_.

§ g

•

>70 em

Pllml••

Profile W 100% 90%

80% 70% 60% 50%

40% 30% 20% 10% 0%

30-70

70-100

100-130 em

Profile I o

100%

0,1

0,2

mglkg

0,3

90% 80%

70%

0-30

60% 50%

40% 30% 20% 10% 0%

30-70

70-100

100-130 em

·IFO+11 Figure 13.4. Vertical distribution and chemical fractionation of Cd in soil profiles (0-130 cm) in Site I; Metal binding fractions: FO+ 1(EXC): pore solution and exchangeable; F2 (CARS): carbonate associated; F3+4 (EMRO): easily and moderately reducible Mn- and amorphous Fe-oxides; F5(OM): oxidizable, associated with organic matter and sulfides; F6(R): residual (lithogenic matter).

various industries, lead crystal glassworks are a proven source of lead contamination. The scope of this study comprises evaluating the extent of soil enrichment by lead in the vicinity of Irena Glasswork.

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

283

Cu Profile R o

100% 90% 80% 70%

~30

60%

~

5

10

15

________________

mg/kg

20

~

2~3O~• • •_

50%

3O-5OleI_ _ __

40% 30%

20% 10%

""""1I

~70~~• • •

0%

>70cm ~• •_ _

Profile W o

100% 90% 80% 70%

5

10

15

mg/kg

20

60%

50% 30-70

40%

30% 20% 10%

7~loo

0% 1~13Ocm

Profile I 100% 90% 80% 70%

20

60%

50% 30-70

40% 30%

20% 10%

7~loo

0% 1~13Ocm

I]FO+1

I

1IIIIIIIIIIIIIF2

. .I,--FS-l

Figure 13.5. Vertical distribution and chemical fractionation of Cu in soil profiles (0-130 cm) in Site I; Metal binding fractions: FO+ 1(EXC): pore solution and exchangeable; F2 (CARB): carbonate associated; F3+4 (EMRO): easily and moderately reducible Mn- and amorphous Fe-oxides; F5(OM): oxidizable, associated with organic matter and sulfides; F6(R): residual (lithogenic matter).

Locotion, Soil C/w(acteristics, and Land Use

Site II is located in Central Poland in the flat area adjacent to Irena Glasswork, in the NW part of Inowroclaw (Figure 13.8). Geomorphologically it belongs to plains of the moraine upland originating from the Baltic glaciation phase. The area lies at the border

284

Fate and Transport of Heavy Metals in the Vadose Zone

Pb Profile R o

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

~30

20-30

5

10

15

20

~________________~~~,I

40 mg/kg

~~~II• • •

3~50 ~~• • •

5~70 ~• • • >70em

•••

bE~

Profile W 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

~30

3~70

7~loo

1~13Oem

Profile I o

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

5

10

15

20

~3O

30-70

7~loo

100-130 em

IFO+11

1IIIIIIIIIIIIIF2

fFAjF3+41

IBIL..-FS----,

"L.....

F6 ---,

Figure 13.6. Vertical distribution and chemical fractionation of Pb in soil profiles (0-1 30 cm) in Site I; Metal binding fractions: FO+ 1 (EXC): pore solution and exchangeable; F2 (CARB): carbonate associated; F3+4 (EMRO): easily and moderately reducible Mn- and amorphous Fe-oxides; F5(OM): oxidizable, associated with organic matter and sulfides; F6(R): residual (lithogenic matter).

of a fallow gley podzol on the vadose zone matrix composed of sands and brown soils formed from loess and loessial formations. This results in variable content of clay fraction, ranging from 3.8 to 35.0 wt % and sand fraction occurring within the range from 78.2 to .38.8 wt %. The agricultural land represents mainly wheat complex. Dominating

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

285

Zn 100%

100%

80%

80%

80%

60%

60%

60%

40%

40%

40%

20%

20%

20%

0% I-

Profile

'--r-

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Cd 100% 80%

100%

.,--,

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i

100% 80%

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0% o

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re

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Pb 100%

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7'

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100%

100%

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80%

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80%

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60%

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g

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~

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.... 0

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0%

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g

;;;....

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~ Ii

1IIIIIIIIIIIIIF2

Figure 13.7. Partition of the mobile fraction of trace metals (Zn, Cd, Pb and Cu) in soil profiles (0130 cm) in Site I; Metal binding mobile fractions: FO+ 1 (EXC): pore solution and exchangeable; F2 (CARB): carbonate associated; F3+4 (EMRO): easily and moderately reducible Mn- and amorphous Fe-oxides; F5(OM): oxidizable, associated with organic matter and sulfides.

286

Fate and Transport of Heavy Metals in the Vadose Zone

E

_o;;;':'s~_ _ _....;c~

0-....

km

c e2l 025

0

Figure 13.8. General plan of Site II: area adjacent to Irena Glasswork n/lnowroclaw, Poland). P - Irena Glasswork; 1 - sampling points along the intersections A, B, C, 0; 2 - compact residential area; 3 - railways; 4 - motorways.

winds blow from W, NW, and SW direction, which means that due to unfavorable location, mainly the compact residential area of Inowroclaw City is affected with the emission from the Glasswork. The surveyed site comprised an area of 5000-m radius in NE, NW, W, and partially SW directions from Irena Glasswork, used for intensive agricultural production (mainly arable land and orchards). In the NE, NW, and W-WS directions the area is crosscut with parallel railroads and motorways.

of Antflropogenic Contarnination of Soil by Lead The major source of soil contamination by Pb in Site II is an emission from the stacks of Irena Glasswork. The glasswork has been in operation already for several decades, but as a source of Pb emission it is considered since 1976, when the production of lead crystal glass started. Pb has been emitted to the atmosphere with particulates, mainly in the form of oxides. Another source of Pb contamination occurring in the area is leaded petrol combustion in motor vehicles. The survey of soil contamination by Pb in Site II was focused on the evaluation of the glasswork impact on the extent and character of undisturbed soil contamination in this area. The results of the survey are illustrated in Figures 13.9 and 13.10, which present spatial and vertical distribution of Pb in the un-

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

o-2.5cm

2.5 -5.0 em

5.0 -10.0 em

10.0 -15.0 em

15.0 - 20.0 em

35.0 - 40.0 em

287

Figure 13.9. Site II (area adjacent to Irena Glasswork n/lnowroclaw). Spatial and vertical distribution of lead in an undisturbed surface soil layer (0-40 cm).

disturbed surface soil layer 0--40 em, as well as chemical fractionation ofPb accumulated in soil vs. distance from the source of emission (Glasswork stacks).

Soil Enrichment with Heavy Metals in the Areas Impacted by long-Term Stack Emission

it

Screening Survey and Methods An extent of surface soil and the upper part of the vadose zone (subsoil) matrix contamination by heavy metals in Site I (Nowa Huta, area adjacent to Sendzimir Steel-

288

Fate and Transport of Heavy Metals in the Vadose Zone

°

A-1a 0-2,5

100

200

11111111:·· .::.: ......

300

400

500

600

:-:~

mg/kg

2,5-5,0 1 - - - - - - ' 5,0-10,0 1--_-' 10,0-15,0 1--_.... 15,0-20,0

A-1a

Total

Mobile Fractions

35,0-40,0 em

°

8-8a 0-2,5

100

11111:

200

.....:. :..

300

400

500

600

~

mg/k 2,5-5,0 1--_ _--' 5,0-10,0 1--_-' 10,0-15,0 1--_....

Total

8-8a

Mobile Fractions

35,0-40,0 em

C-15a

°

100

°

100

200

300

400

500

600

mg/kg

0-2,5 2,5-5,0 5,0-10,0 10,0-15,0 15,0-20,0

C-15a 100%

Total

Mobile Fractions

,--"r=',.,..,.=----.,.........,.,.",...---,

35,0-40,0 em

0-22a

80%

0-2,5

60%

2,5-5,0

40%

5,0-10,0

20%

10,0-15,0

300

400

500

600

mg/kg

15,0-20,0

0%

0-22a

200

Total

Mobile Fractions

35,0-40,0 em

Figure 13.10. Vertical distribution and chemical fractionation of Pb in an undisturbed surface soil layer (0-40 cm), Site II. Metal binding fractions (McLaren and Crawford, 1973): fO+ 1 (EXC): pore solution and exchangeable; f2(CARB): specifically sorbed, carbonate-associated; f5(OM): oxidizable, associated with organic matter; f3+4(EMRO) free Mn- and Fe-oxides.

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

289

works in Poland) (Figures 13.1, 13.2A) resulting from the impact of the Steelworks stack emission was evaluated on the basis of metal accumulation and spatial distribution in surface soil layer (Table 13.4, Figure 13.2B-I). Barrier capacity of soil, binding phases, and metal mobility in soiVvadose zone matrix were also taken into consideration (Figures 13.3 to 13.7). The evaluation was based on the random survey of soil for trace metals in node-points of the network of SOxSO m squares carried out according to the EPA guidelines (Barth and Mason, 1984). The survey comprised sampling: (i) surface soil layer in the basic 63 node-points; (ii) surface soil layer in 8 points (one of every 10) taken in duplicate in close proximity to the basic node-points to estimate the variability among sampling units; (iii) soil and subsoil matrix in four layers up to 30 cm thick along the upper part of the vertical profile of the vadose zone up to 130 cm deep, in three points selected at different distances and directions from the Steelworks with respect to the wind rose: Wadow 64-67 (Profile W), Ruszcza 4S-48 (Profile R), and Igolomia 75-78 (Profile I) (Figures 13.2B-I, 13.3 to 13.7). In Site II (Irena Glasswork) (Figures 13.1, 13.8), the undisturbed soil enrichment with Pb against the distance from the source of emission and the depth of soil layer was assessed (Figure 13.9), with a special regard to the vertical migration of Pb into undisturbed soil layers (Figures 13.9, 13.10). The screening survey comprised soil sampling for lead in 2S sampling points along the 4 intersections (A, B, C, D) in the distance from so to SOOO m from the Irena Glasswork, consecutively in 50, 100, 2S0, SOO, 1000, 2S00, and 5000 m from the source ofPb emission (Glasswork stacks). In the investigated area, other sources of Pb than the Glasswork occurred: Pb emission from motor vehicles, pump stations distributing leaded gasoline, and other activities emitting Pb in the compact settlement area of Inowroclaw city, located in the E, SE, and S direction from the Glasswork. The disturbing effect of cultivation on vertical distribution of Pb in the soil layer in the agricultural areas located in SW, W, NW, and N directions from the Glasswork also should have been considered. To exclude effect of these factors that could influence spatial and vertical Pb distribution in the soil layer, it was desisted from the random sampling procedure and from soil sampling within the compacted settlements of Inowroclaw city located in the area most affected by emission from the Irena Glasswork. The samples were thus taken along the intersections laid out in the barren undisturbed land in agricultural area, in the NE, NW, W, and SWW directions from the Glasswork, not closer than SO-100 m from the motorways and buildings. In each point,S consecutive soil layers from 2.5 to S.O cm thick (the uppermost two 2.5 cm thick, the rest 5.0 cm thick), up to the depth of 20 cm, along with the layer 3S-40 cm were sampled and analyzed for Pb. In conformity with the sampling program and a scope of the studies, the material analyzed for trace metals comprised soil and subsoil matrix. Acid-digested (ASTM, D 5198-92, 1992) soil and subsoil matrix samples were analyzed for the total metal content by standard methods using AAS and ICP-AES techniques (AAS Perkin Elmer 1100 B and ICP Perkin Elmer Plasma 40). Binding strength of metals in the selected soiVvadose zone matrix samples from Site I was evaluated using sequential extraction (Tessier et al., 1979, modified by Kersten and Forstner, 1986). Sequential extraction scheme partitions off exchangeable FO+1 (EXC) , carbonate-bound F2(CARB), easily and moderately reducible Mn-oxides and amorphous Fe-oxides F3+4(EMRO), oxidizable sulfidic/organic FS(OM) and residual frac-

N \.0

o

."

III .... fI)

III

::::I C.

~

III

::::I VI "0

o

:4-

a::I:

Table 13.4. Concentrations of Heavy Metals in Soils of Site I (Nowa Huta n/Cracow) Compared to the Geochemical Background in Unpolluted Areas Site Nowa Huta (Site I) Geochemical background"

from-to mean from-to mean

Fe (%)

Mn

1.25-2.50 1.61 0.80-2.78 1.20

254-1160 485 380-700 560

" Kabata Pendias and Pendias, 1992.

Heavy Metals Concentration (mg kg-l) Zn Cu Pb Ni 32-670 120 30-360 65

8.4-22.2 13.8 4.0-53.0 19

10-42 27 19-49 25

11.0-22.8 16.7 10.0-104 25

Cd

Cr

0.1-1.1 0.45 0.08-0.96 0.38

14.4-40.8 24.2 14.0-80.0 38

~re

s:

~ :i" iii

:fI):r

70 to 130 cm) in mg.kg.- 1, Zn association with fractions of a different binding strength followed the order: F6(R) > F2(CARB) > F3+4(EMRO) » F5(OM) »» FO+l(EXC) The residual fraction accounts for about 50%, while 25 to 30% is associated with mobile carbonate-bound fraction. Variable amounts of Zn are bound with mobilizable F3+4(EMRO) and strongly bound with oxidizable fractions F5(OM): the rate of Zn associated with both these fractions ranged from about 15% to approximately 30%. The association of Zn with easily and moderately reducible Mn- and Fe-oxides comprised 14 to 25%, while in oxidizable fraction (generally associated with organic matter and sulfides, here in particular with organic matter), it occurred in a minor amount (1.2 to 5.0%). The role of the exchangeable fraction in Zn binding was negligible in all layers of the surveyed soil profiles.

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

295

In overlaying intermediate subsoil layer 20 to 70 cm, both Zn concentrations and chemical fractionation appeared to be similar to that in the underlying layer >70 to 130 cm, though a tendency to increase of Zn rate associated with reducible fraction was observed. In the surface humic soil layer weakly impacted by the emission from the Steelworks (profiles Wand I), the enrichment of most binding fractions with Zn occurred, but to the different extent. It resulted in the rearrangement of the relative and absolute partitioning order according to the sequence (Figures 13.3, 13.7): F3+4(EMRO) > F6(R) » F2(CARB) > F5(OM) » » FO+1(EXC) The association of Zn with mobilizable reducible oxide-bound fractions and oxidizable fraction associated with organic matter in the surface soil increased up to 51 to 56% of the total Zn, the reducible oxide-bound fraction being dominant (41-48%). The amount of Zn associated with carbonate-bound fraction was generally stable along the soil profile and did not show enrichment in the surface soil, which resulted in the substantial decrease of the proportion of mobile fraction in comparison with the subsoil layer. The results of Zn partitioning are generally in line with those reported by other authors for unpolluted and geochemically polluted soils (McGrath, 1996) and sediments (Tack and Verloo, 1996). All these matrices showed domination of Zn associated with reducible oxide fractions, generally minor role of oxidizable fraction, high rate of stable residuum, and relatively low proportion of mobile fractions associated with carbonates. The role of the exchangeable fraction in zinc binding appears to be negligible. To summarize, in the surface soil layer enriched with zinc anthropogenically, from 30 to 35% of this species comprised immobile lithogenic material, while 65 to 70% of the total concentration comprises mobile or mobilizable fractions of different binding strength (Figure 13.7). Partitioning of cadmium (Figures 13.4, 13.7) in the surveyed soil profiles followed the sequence: - in subsoil layer 30 to 130 cm: F6(R) > F3+4(EMRO) > FO+1(EXC) > F2(CARB) » » F5(OM) - in surface soil layer 0 to 30 cm: FO+1(EXC)

z

F3+4(EMRO) > F6(R)

z

F2(CARB) » » F5(OM)

In the subsoil layer, 35 to 45% of Cd was associated with residual fraction. Reducible oxide-bound Cd comprised 27 to 30%. The mobile exchangeable and carbonatic fractions accounted for 19 to 22% and 12 to 17% of Cd, respectively, while the amount of Cd bound to oxidizable organic fraction was negligible. High content of humic organic compounds in the surface soil layer did not enhance binding Cd with oxidizable organic fraction, whereas the amounts of Cd bound in exchangeable, reducible, and carbonate fractions significantly increased as compared to subsoil. Except the oxidizable fraction, the Cd distribution among the fractions of different binding strength was almost uniform, showing great resemblance to the pattern of Cd partitioning in the moderately polluted soil studied by Harrison et al. (1981). Frac-

296

Fate and Transport of Heavy Metals in the Vadose Zone

tionation of Cd adsorbed onto peat; i.e., predominantly organic matter, displayed dominance of binding mainly onto FO+1(EXC) fraction of the weakest binding strength (Twardowska and Kyziol, 1996). It could be therefore admitted that a significant part of the most labile FO+ 1 (EXC) fraction may be associated with organic matter, besides that of clay minerals. In the case of humic-rich matters, the attribution of metal binding to ion exchange mechanism is questionable. This supports an assumption, expressed also by Kersten and Forstner (1988) and Tack and Verloo (1996), that the mechanism of metal binding onto different or transformed matrices also considerably differs, while the most reliable parameter for comparison is binding strength, adequate to the related fractions (Twardowska and Kyziol, 1996). It should be also emphasized that in general, chemical fractionation of Cd in soil and sediments indicates its predominant binding onto mobile and easily reducible phases (Harrison et al., 1981; Kersten and Forstner, 1988; Forstner, 1992; McGrath, 1996; Tack and Verloo, 1996). Therefore, Cd is susceptible to remobilization resulting from the changes of the chemical environment. The partitioning of Cd is thus also subject to strong changes. The reported data on soils and sediments are consistent with respect to role and significance of exchangeable, reducible oxide-associated and carbonate associated mobile and mobilizable fractions in Cd binding (Figures 13.4, 13.7). A bigger difference in the reported data is concerning oxidizable and residual fraction (Forstner, 1992; McGrath, 1996; Tack and Verloo, 1996). Copper occurrence in the soils of the Site 1, as shown by the spatial distribution and concentration range (Figure 13.2H, Table 13.4) displays weak impact of the emission from the Steelworks and in the surveyed soil profiles is of predominantly geogenic origin. It results in uniformity of Cu distribution and partition along the profiles (Figures 13.5, 13.7). From 44 to 54% of Cu is stably bound in the residual fraction. The predominant part of mobilizable species was found in oxidizable fraction (25 to 33%), that seems to be geogenically specific for soils and sediments and is in conformity with other sources (Tack and Verloo, 1996; McGrath, 1996). It should be mentioned that also in some anthropogenic materials, such as municipal solid wastes, domination of specific linkage of Cu to organic matter was observed (Prudent et al., 1996), though not all the matrices show the same binding pattern (Twardowska and KyzioL 1996). The partitioning of Cu in the surveyed profiles, both in surface soil and subsoil layers, follows the general order: F6(R) > F5(OM) > F3+4(EMRO) » F2(CARB) >FO+1(EXC) In the deeper part of Profile I (Igolomia), predominant binding to the reducible fraction occurred (Figures 13.5, 13.7). No visible increase of Cu association with oxidizable organic matter-bound fraction was observed, despite much higher content of organic matter in this layer. Distribution of lead (Figures 13.6, 13.7) reflects its low mobility in soil and subsoil profIles. Opposite to Cd, association of Pb with mobile fractions, both exchangeable and particularly carbonate-bound appeared to be very low. In all layers of the profiles, including surface soil layer, mobile exchangeable and carbonate-bound fractions comprised 2.5 to 5.5% and 0.0 to 3.2% of total Pb, respectively. The highest, though variable, enrichment of subsoil with Pb occurred in the residual (25 to 66%) and reducible oxide-bound fractions (25 to 66%). The highest lead binding in the residual fraction (56 to 66%) and the lowest in reducible oxide-bound one (22 to 29%) was observed in the R

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

297

(Ruszcza) profile, in the area of the highest impact of the Steelworks. In two other profiles Wand I located in less impacted areas the proportions of the residual and reducible fractions were 25 to 43% and 52 to 66%, respectively. The total Pb contents in the subsoil (> 30 cm) of the R profile ranged from 10 to 12 mg kg-I, while the concentration range in the subsoil of these two other profiles was 10 to 22 mg kg- I and could be thus assumed as falling within the uniform background concentrations. Therefore, it is rather unlikely that enrichment of residual fraction and decrease of reducible one was induced anthropogenically, and probably reflects the geogenic variability of the area in this respect. In the subsoil layer > 70 cm, Pb binding onto organic matter is generally very low or negligible, but increases in the upper transitional subsoil layer (70 to 50 cm). In the surface soil layer, the proportion of Pb associated with organic fraction considerably increases (to 13-23%), which shows good correlation both with the content of organic matter in the soil profile and exposure to the anthropogenic impact. Besides higher rate of organic-bound fraction and general quantitative increase of Pb-enrichment, dependent upon the distance and direction with respect to the emission source, no substantial changes in partitioning of this metal in soil profile was observed. Partitioning of Pb with respect to binding strength and predominant chemical associations in the surveyed soil profiles followed the sequence: - in subsoil layer 30-130 cm: F3+4(EMRO)

>



F5(OM) » FO+1(EXC)

~

F2(CARB)

Comparison of chemical fractionation of Pb in the surface soil layer in Site I (Figures 13.6, 13.7) and in Site II adjacent to the Irena Glasswork (Figure 13.8), where the uppermost 0 to 2.5 cm soil layer is highly contaminated by lead (about one order of magnitude compared to the surface soil layer in Site I) (Figure 13.9), displays clear influence of the extent of anthropogenic impact on Pb distribution among the fractions (Figure 13.10). Partitioning of Pb in the least contaminated soil samples (C-15-a and D-22-a) shows high enrichment of the stable bound residual fraction (62 to 63%). The rest of species was almost equally partitioned over mobile and mobilizable fractions of different binding strength: exchangeable fraction comprised 8 to 9%, the fraction associated with organic matter 12 to 15%, while the rest was distributed among oxide-bound and specifically sorbed (mainly carbonate-bound) fractions: F6(R) » F5(OM)

>

F1+0(EXC)

>




FO+1(EXC)

298

Fate and Transport of Heavy Metals in the Vadose Zone

Comparison between the samples of the highest (A-I-a) and the lowest (D-22-a) Pbcontamination showed that the most anthropogenically enriched fractions appeared to be those associated with organic matter (46%) and stable residuum (28%). Much weaker anthropogenic impact displayed, in the descending order, fractions: specifically sorbed F2(CARB) (14%), oxide-bound F3+4(EMRO) (8%), and exchangeable FO+1(EXC) (4%). The anthropogenic enrichment follows, therefore, the sequence: FS(OM) > F6(R) » F2(CARB) > F3+4(EMRO) > FO+1(EXC) The chemical fractions associated with Pb in the soil samples taken from Site II cannot be directly compared with those in Site I due to use of different sequential extraction methods (by McLaren and Crawford, 1973, in Site II and by Tessier et ai., 1979, modified by Kersten and Forstner, 1986, in Site I). The analysis of Pb partition in both sites, though, clearly shows that the highest enrichment due to the anthropogenic impact (stack emission) occurs in the oxidizable organic matter-bound and stable residual fraction. Mobile chemical associations with exchangeable and carbonate fraction, as well as with reducible step associated mainly with manganese oxides and amorphous iron oxyhydroxides, are subject to the anthropogenic enrichment to much lesser extent. To conclude, heavy metal fractionation in surface soil and the vadose zone matrix differs substantially with respect to binding strength. Surface soil has high barrier properties, which cause enrichment of this layer with heavy metals in the areas impacted by anthropogenic emission. In general, anthropogenic enrichment occurs in all binding fractions, though at a different rate. The highest increase has been observed in mobilizable fractions, which results in the elevation of hazard to higher extent than it can be assumed from the quantitative changes. This leads to the conclusion that for quality-safe risk assessment, not only quantitative but also qualitative transformations of metal associations caused by anthropogenic impact should be considered.

Monitoring Program Requirements for Risk Assessment from large-Area Soil Contamination by Trace Metals from Anthropogenic Sources The results of soil survey in two anthropogenically impacted sites show the importance of assessing such parameters as (i) actual and potential land use and risk receptors; (ii) the thickness of an averaged surface soil layer to be exposed to a direct contact with risk receptors and the form of a contact; (iii) the fractions of the total metal content in soil actually available and implying a risk for the risk receptor; (iv) the fractions of the total metal content in the soil potentially available (mobilizable) and probable conditions of the metal(s) mobilization. These parameters are essential for a quality-safe monitoring and evaluation of an extent of soil contamination by trace metals. The monitoring requirements are based on the character of a vertical distribution of metals in anthropogenically impacted soil from the large-area emission, showing high accumulation in the uppermost layers of soil, 1-2 cm thick. In the areas undisturbed by depth-averaging cultivation treatment (e.g., lawns in childrens' playgrounds, meadows used as grazing areas) this layer will be directly exposed to the contact with receptors (children, farm animals, and wildlife). In agricultural land, the direct receptors (e.g.,

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

299

plants, food crops, fodder crops) will be exposed to a concentration of metal averaged by cultivation treatment. Considering the association of metals in soil matrices with "pools" displaying different binding strength, which reflects direct and potential availability to the different receptors, application of the sequential extraction procedure gives an essential opportunity to avoid false-positive errors in actual risk assessment. Overestimating the risk may be avoided through excluding the rate of metal stably bound in the residual fraction. The correct risk assessment requires an identification of metal-binding fractions directly available to the particular receptors, e.g., mobile fractions FO (pore solution), F1 and F2 displaying the weakest binding strength, and thus susceptible to leaching and groundwater contamination. In general, for the actual risk assessment, evaluation of mobile, mobilizable on/after uptake and immobile (stable) fractions provides adequate required information. For this purpose, the sequential extraction is a proven, reliable tool. The testing in the frame of BCR-interlaboratory studies of two extraction procedures, to be considered as standards by ISO (Quevauviller et al., 1996; Ure, 1996), confirms both their reliability and usefulness for risk assessment needs. As has been shown above, sequential extraction also provides valuable information on quantitative and qualitative changes in partition of a metal in question, resulting from the anthropogenic impact. For the potential risk assessment, long-term prognosis of heavy metal release and selection of the optimal remedial/cleanup actions, not only metal fractionation according to binding strength, but also identification of the geogenic and anthropogenic chemical associations of pollutants, in particular in mobilizable fractions [easily and strongly reducible F3+F4(EMRO) and oxidizable (FS) (OM)] are required. The definition ofparameters, transforming equilibria conditions in matrix, as well as external or internal factors controlling these transformations (e.g., pH, Eh) are also a prerequisite for the correct life cycle risk assessment. The results presented here show the need for a differentiated approach to actual and potential risk assessment from the large-area sources of emission such as stack emission, and point out the pitfalls of data inconsistency in their evaluation. The monitoring program for quality- fe risk assessment and the selection of a both efficient and cost-effective remedial strate minimizing the adverse consequences oElong-term emission should be highly use-specific and target-oriented. Monitoring data on trace metal enrichment in soil and vadose zone matrix caused by wet and dry depositio from industrial sources (mainly stack emission) in the vicinity of operating industrial lants (Sendzimir Steelworks, Site 1, and Irena Glasswork, Site II) showed an essenti role of chemical fractionation of metals in adequate evaluation of soil contaminati n. A substantial part of the total metal load originating from the anthropogenic industrial sources is stably bound in the residual fraction. In some emissions, though, anthropogenic contaminants occur in more labile forms than the species of the lithogenic/geogenic origin, which adequately increases the risk (e.g., anthropogenic enrichment of oxidizable fraction with Pb in Site II). Taking into consideration at risk assessment not only contaminant concentration, but also its chemical fractionation with respect to binding strength could highly improve the classical principle of preliminary evaluation of contaminated sites based on soil threshold values. Application of scientifically proven critical values would also greatly enhance site- and use-specific models of exposure assessment. Up to now, these values are a weak point of the best-constructed

300

Fate and Transport of Heavy Metals in the Vadose Zone

exposure assessment models. Metal fractionation in soil for risk assessment and management has been taken into account in a three-level concept by Gupta et al. (1996).

EVALUATION OF A LARGE-AREA DESERTED INDUSTRIAL SITE Investigation of a large deserted industrial site as a potential human risk was presented in the case study on an abandoned industrial area of Marktredwitz in Germany, impacted by the long-term emission of Hg and Sb from an old chemical plant (Site III) (Figures 13.1, 13.11). The major issue facing old contaminated sites sanitation requirements is the need of a quality-safe evaluation of such areas, taking into account both interests of the environment and nature on one side and economy and industry on the other. Therefore, an optimum model of investigation and assessment of chemical pollution of the site is to be use- and site-specific, in accordance with particular criteria in view of the defined protection objectives, which are determined by further use of the decontaminated area, and corresponding human sensitivities. In Germany, the efforts directed to elaboration of reliable long-term risk assessment methods resulted in developing several models of different applicability. The proposed approach to the assessment of the human risk potential originating from deserted industrial sites has been exemplified in a case study of the large-area soil contamination by mercury and antimony in Marktredwitz city, North Bavaria, FRG (Figures 13.1, 13.11). The study, conducted by the research group of the GSF-Institute of Ecological Chemistry, FRG, has been focused on a site-specific risk assessment and selection of the adequate preventive/remedial action. Unlike the studies in Sites I and II, oriented to one selected measurement endpoint (soil), this study was of a complex character: measurement endpoints included soil, water, air, sediments, dust, plants; while target risk receptors were human: adults and children.

Site Characteristics Site IV is a typical urban area of a city that started to develop in the industrialization period of the end of the eighteenth century as a residential area of one of the oldest plants in Germany, chemical factory Marktredwitz (CFM). Hence the central position of the plant in the town, which is surrounded by a railway (Figure 13.11). The CFM area adjoins the Kossene river course, which belongs to the Elbe River drainage basin. The river was regulated in e 1930s to intercept frequent floods. The reclaimed old riverbed is also adjacent to CFM. ain wind directions are Wand SW. Dominating types ofland development are individu I houses with gardens.

Sources of Heavy

M11 Contamination in the Area

The major sourc~ heavy metal contamination in the area is now the abandoned industrial site of a more than 200-year-old former chemical factory Marktredwitz (CFM) founded in 1788 (Figure 13.11) which used to produce a great variety of inorganic and organic chemicals, among them Hg- and Sb-based compounds and herbicides (Table 13.5) before closure in 1985 for ecological reasons. Maximum concentrations of heavy metals found in soils of the area (Table 13.6) reflect an extent of the environmental damage.

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

301

Figure 13.11. General map of Site III: Marktredwitz urban area with chemical factory site, North Bavaria, F.R.G. with the location of measurement points for Hg.

Table 13.5. Compendium of the CFM Catalog: Heavy Metal-Bearing Chemicals CFM - Products Inorganic and metalorganic products: Hg numerous products, under it Hg, Hg2C1 2, HgX2 (X=CI, Br, I, CN, SCN), Hg(N0 3h, HgO, RHgCI (R=CH 3, C2Hs, C6 Hs), etc. Sb potassium antimony tartrate, potassium antimony citrate As Hg3 (As0 3h, Hg3 (As0 4h

Zn

Zn 3 P2

Cu

3Cu(OHh·CuCl 2

Among 12 groups of CFM products, Hg-bearing chemicals comprised 10 different groups, of them Fusariol® accounted for 5%. One group represented Sb compounds, of which over 90% consisted of potassiu~ antimonyl tartrate (tartar emetic). Mercurybearing chemicals prevailed in the CFM production: the rate of Hg-products accounted for 94%, and Sb-products, 6 Yo. The Hg- and Sb-products delivery from CFM to customers increased since 1961 to 1982 from 67.0 to 116.1 t and from 0.7 to 9.6 t, respectively.

toi

®

Registered trademark of the Chemical Factory Marktredwitz, Inc., Marktredwitz, Germany.

302

Fate and Transport of Heavy Metals in the Vadose Zone

Table 13.6. Detected Heavy Metal Contaminants from CFM and Their Maximum Concentrations in Soil Metal C (mg kg- 1) Metal C (mg kg- 1 )

As

Cd

Co

Crt

Cu

Hg

684

1.64

18.8

560

673

6,140

Mn

Ni 390

Pb

Sb

Sn

Zn

19,364

36,400

13.2

2,532

770

Monitoring Strategy A complex character of the old contaminated site evaluation determined a broad program of preliminary investigations undertaken in the framework of the Marktredwitz project. Due to historically long-term impact of contaminants under the changing conditions of area development/management and extent of anthropopression, detailed preliminary studies were required to most accurately define the monitoring strategy. These studies comprised measured endpoints and risk receptors, sampling points and parameters assuring quality-safe evaluation of the site. The preliminary studies undertaken in the framework of Marktredwitz project (Site III) were focused on making explicit the factors of concern for site evaluation, in particular the kind and pathway of pollutants, past and future area development, availability, and adequacy of the existing database. The target task was to elaborate an optimum sampling and measurement program adequate for a reliable use-specific risk assessment. The studies comprised historical background investigation and elaboration of a geographical information system (GIS) for an investigated site. The objectives of the historical investigations were to identify precisely vs. time: (i) contaminants inventory: industrial products in the area, delivered amounts; (ii) pathways of contaminants: aquatic (surface- and groundwater), terrestrial (controlled and uncontrolled waste disposal and use), air (wet and dry particulate deposition); (iii) uncontrolled waste disposal and use as common fill or soil amendment; and (iv) causes of environmental damage from uncontrolled sources. To identify possible uncontrolled disposal of contaminated material in the Marktredwitz area, the inventory of industrial and other sites (e.g., quarries) where such material could have been disposed was elaborated. For this purpose also, the available archival aerial views were investigated to detect changes of the cityscape in time, where contaminated material could have been involved as a common fill (relocation of the river bed, urban area development, road construction, changes of land use, position and condition of industrial sites in time, land leveling). For the contaminated SIte eva tion, a GIS visualizing any kind of data with reference to their Gauss- Kruger or loca oordinates in the Windows style appeared to be particularly suitable. It served as a spa· ally allocated data bank of required information: general, pathways and input/output 0 contaminants (emission, imission, utilization), sampling and analysis (e.g., Figures 1 .1 L 13.12).

Survey of Transfer Pathways and Risk Receptors A sampling program was designed with use of the GIS spatially related database obtained from the preliminary historical investigations. It was focused on deriving compre-

,"",,,,,7)'1'\1

•

antimony (new values)

•

mercury

•

railway installations

-

river KOsselne

III

residential area

Metal Contamination in Industrial Areas and Old Deserted Sites

303

• Figure 13.12. Site III: Marktredwitz area with the location of circles D=130 m to define sampling paints for Hg and Sb.

hensive and reliable data for evaluation of the extent and propagation of contamination in the areas suspected of being polluted. In these investigations, a human as a risk receptor was a target assessment endpoint, while groundwater was not considered at this stage due to the lack of elevated concentrations of site-specific pollutants in drinking water. The area to be surveyed for Hg could be roughly estimated on the basis of the available qualitative information, while for Sb no such estimation was possible due to insufficient data and weak correlation between the occurrence both metals. The sampling area was thus planned, starting from the old CFM site and define according to the main transfer pathways; i.e., the Kosseine river flow (E) and predomina t wind direction (S, SW), though E direction of wind transport also occurs. As a joint) effect of the major pathways, in the E direction from the old CFM site, "hot spots" of the highest extent of contamination were expected, while in the W direction a somewhaylesser contamination could not be excluded. With the help of the geostatistical analysts' and available data on Hg, the distance of 130 m in diameter was found to be sufficient for the reliable evaluation of the contaminant expansion. On designing the sampling network, the maximum distances of sampling points accounting for 130 m were therefore generated by means of circles centered in proven contaminated points (Figure 13.12). The maximum distance of 130 m was assumed to be valid also for Sb. Thus, an extensive sampling of the surveyed area could be accomplished with a minimum effort. For the quantitative exposure assessment, all relevant transfer pathways comprising soil, food crops, indoor and outdoor ambient air were sampled. Soil samples for analysis were prepared through averaging of a sufficient number of random samples from the

304

Fate and Transport of Heavy Metals in the Vadose Zone

respective area, therefore the results represented mean values for the area. In total, about 200 areas were sampled. The sampling was performed in accordance with ISO/DIN10381. The soil exposed to air contamination was taken from the top layer 0 to 10 cm. The soil enriched with contaminants from a long-term impact was sampled also from the layer 10 to 30 cm, if risk receptors were children. Additionally, in some points layers of 30 to 60 cm were also taken. Sampled food crops grown in contaminated house gardens comprised mainly vegetables and fruits. Particulate samples were taken from the indoor ambient air in the living rooms and outdoor of the residential houses, and a fraction a growing concern must be considered; preventive measures, respectively changes of use, are to be examined

the probability of heath impact is high; remediation action is necessary

Figure 13.148. Flow chart of the quantitative exposure assessment (QEA) for Hg in the neighborhood of the former CFM for the exp~eDario 'Living Area with a House Garden: Calculation of the risk value RW. / .~

\

310

Fate and Transport of Heavy Metals in the Vadose Zone

Table 1 3.9. Survey of the Exposure Pathway-Specific Intake Rates for the Scenario "Living Area with a House Garden" Establishing the Pathway Specific Intake Rate User Group

Exposure Medium Exposure Pathway

BWa

Daily Intake

Exposure Frequency

Intake Rate (average per year)

Little children

soil - oral plant - oral indoor air indoor dust plant - oral indoor air indoor dust

10 10 10 10 70 70 70

1g 3,7 g d-1 ,b 3 mL d-1 3 mL d- 1 20 g d- 1 ,b 20 m d-1 20 ml d-1

200 d a-1 all-year 21 h d-1 21 h d- 1 all-year 21 h d- 1 21 h d-1

55 mg kg- 1 d-1 370 mg kg- 1 d-l,b 0,26 mL kg- 1 d-1 0,26 mL kg- 1 d-1 ,c 290 mg kg- 1 d- 1 0,25 mL kg- 1 d-1 0,25 mL kg- 1 d-l,c

Adults

inhalative - inhalative inhalative - inhalative

kg kg kg kg kg kg kg

BW: body weight. b Homegrown fruits and vegetables (dry weight). C Dust retention: 75%.

a

concentration (UBI). This method, however, is not sufficient for deriving well-founded recommendations of protective measures related to the specific risk receptors. To fill the gap between the toxicological statement on the one hand and the legislative requirements on the other, Konietzka and Dieter (1994) proposed to assess a risk threshold value with regard to the safety factors used for determination of the TRD values. The safety factors are expected to be slightly below the LOAEL of sensitive individuals. According to this proposal, risk indices are transformed into risk values depending on the reliability of data used for estimation of provisional guide values. Estimation of the provisional guide value for the oral uptake of inorganic mercury was based upon oral uptake data for rats, with a safety factor of 200, while the respective values for inhalative uptake of inorganic Hg were derived from LOAEL for humans, with a safety factor of 20. The Fresenius Institute determines risk threshold values by using provisional guide values for oral uptake with a safety factor of 10 and for inhalative uptake with a safety factor of 4.5, referring to Konietzka and Dieter (1994). A risk value (RW) calculated as the total risk index to the risk factor ratio, allows distinguishing between the lack of risk and possible risk for the receptors. To describe the situation for the land-use scenario "Living Area with a House Garden," weighted means are used as risk factors for oral and inhalative uptake. In Figure 15.15, the three RW ranges for Hg of a different probability of risk situations requiring adequate actions are presented. At the lowest stage (RW < 0.25) the risk cannot be entirely neglected, but no specific action is required. At the highest stage of risk, preventive or remedial action has to be taken.

Estimation oj Soil Values jor a Scenario "Living Area with a House Garden. " Marktrec1witz Area (Data up to 1992) The risk assessment using I sensitive scenario "Living Area with a House Garden" applied in Mark edwitz reqUl s database quality for transfer/uptake pathways (soil, plant, indoor concentrations) be evaluated. From Figure 13.16 one can conclude that soil was the only medium exa ined in 61 % of all the areas (quality level

Heavy Metal Contamination in Industrial Areas and Old Deserted Sites

0,25

:s;

<