Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Heavy metal sorption and hydraulic conductivity studies using three types of bentonite admixes Li, Franky 1999

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
831-ubc_1999-0547.pdf [ 13.9MB ]
Metadata
JSON: 831-1.0064115.json
JSON-LD: 831-1.0064115-ld.json
RDF/XML (Pretty): 831-1.0064115-rdf.xml
RDF/JSON: 831-1.0064115-rdf.json
Turtle: 831-1.0064115-turtle.txt
N-Triples: 831-1.0064115-rdf-ntriples.txt
Original Record: 831-1.0064115-source.json
Full Text
831-1.0064115-fulltext.txt
Citation
831-1.0064115.ris

Full Text

HEAVY METAL SORPTION AND HYDRAULIC CONDUCTIVITY STUDIES USING THREE TYPES OF BENTONITE ADMIXES by F R A N K Y L I B. A.Sc. (Civil Engineering), University of British Columbia, 1996 A THESIS SUBMITTED I N P A R T I A L F U L F I L L M E N T OF T H E R E Q U I R E M E N T S FOR T H E D E G R E E OF M A S T E R OF A P P L I E D S C I E N C E in T H E F A C U L T Y OF G R A D U A T E STUDIES D E P A R T M E N T OF CIVIL E N G I N E E R I N G We accept this thesis^ as conformi^g"to the require** 'd standard T H E UNIVERSITY OF BRITISH C O L U M B I A October, 1999 © Franky L i , 1999 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, 1 agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of M £ s > k , t ^ fvA\ <^(?l The University of British Columbia Vancouver, Canada Date DE-6 (2/88) A B S T R A C T 11 This study investigated the sorption and migration behaviour of heavy metals permeating through clay barriers, the effect of heavy metals on clay barrier hydraulic conductivity, and the use of Forest soil and Spruce bark as potential clay barrier materials. Bentonite, Forest soil, and Spruce bark were submitted to Batch adsorption testing to determine sorption capacities and investigate competition effects associated with multi-heavy-metal sorption. The heavy metal solutions consisted of single, binary, and ternary combinations of lead (Pb), copper (Cu), and (Cd) ranging from 0 -1000 mg I A According to sorption capacities, the heavy metals ranked as follows: Forest soil > bentonite = Spruce bark. A n equation based on the Freundlich equation was developed for describing multi-heavy-metal sorption, and expressed the fol lowing ranking in terms of sorption competitiveness: Pb> Cu> Cd. A bentonite admix (100:8 ratio of sand:bentonite), Forest soil admix (100:7:1 ratio of sand:bentonite:Forest soil), and Spruce bark admix (100:7:1 ratio of sand:bentonite:Spruce bark) were submitted to Leaching cell testing to investigate the heavy metal compatibility of clay barriers. The admixes were compacted into r igid-walled cells and permeated with 500 mg L"1 solutions of Pb, Cu, and Cd. The hydraulic conductivities of heavy metal leachates were « 2 orders of magnitude greater than the blank (0.01 M calcium nitrate) leachate. The Forest soil admix ranked the best in terms of heavy metal retention capacity, and breakthrough points. After each Leaching cell test, the admix samples were extruded and submitted to Selective Sequential Extractions (SSEs). The SSE determined the distribution of heavy metals amongst five soil components: cation exchangeable, carbonates, Fe and Mn oxides and hydroxides, organic matter, and the residual. The addition of Forest soil, and Spruce bark in clay barrier mixes promoted stronger heavy metal fixation. In Ill addition, the SSE results showed a linear relation between the sorption characteristics and sorption concentrations of the admixes. The Leaching cell and SSE results showed that heavy metals followed unpredictable pathways, and caused significant short-circuiting. In terms of relative mobility, Cd was «1.5 times more mobile than Cu, and « 4 times more mobile than Pb, respectively. T A B L E OF C O N T E N T S A B S T R A C T ii T A B L E O F C O N T E N T S iv LIST O F FIGURES viii LIST O F T A B L E S x A C K N O W L E D G M E N T S , xii C H A P T E R 1 I N T R O D U C T I O N 1 1.1 STATEMENT OF PROBLEM 1 1.2 SCOPE AND OBJECTIVES 5 1.3 RESEARCH PLAN 7 1.4 RESEARCH CONTRIBUTIONS 9 1.5 ORGANIZATION OF THESIS 10 C H A P T E R 2 B A C K G R O U N D REVIEW 11 2.1 HEAVY METAL AND SOIL INTERACTIONS 11 2.1.1 Cation exchange 12 2.1.2 Inner-sphere complexation 12 2.1.3 Precipitation 14 2.1.4 The effect of solution pH 14 2.1.5 The effect of heavy metals on clay structure 15 2.2 STUDIES IN HEAVY METAL RETENTION SELECTIVITY 15 2.3 HEAVY METAL RETAINING SOILS AND MINERALS 17 2.4 HEAVY METAL COMPATIBILITY STUDIES 19 2.5 POTENTIAL NEW MATERIALS FOR CLAY BARRIERS 23 2.5.1 Soil organic matter 23 2.5.2 Spruce bark 25 CHAPTER 3 MATERIALS AND METHODS 26 3.1 CLAY BARRIER MATERIALS 26 3.1.1 Origins and Descriptions 26 3.1.2 Admixtures 27 3.1.3 Physical properties 27 3.1.4 Chemical properties 28 3.2 CHEMICAL SOLUTIONS 29 3.3 BATCH ADSORPTION TEST METHOD 30 3.3.1 Batch adsorption test program 30 3.3.2 Batch adsorption test procedure 33 3.4 LEACHING CELL TEST METHOD 36 3.4.1 Leaching cell program 36 3.4.2 Admix preparation for the Leaching cell test 38 3.4.3 Compaction procedure 39 3.4.4 Leaching cell test procedure 40 3.5 SELECTIVE SEQUENTIAL EXTRACTION METHOD 41 3.5.1 Sampling extruded Leaching cell samples 42 3.5.2 SSE procedure 44 CHAPTER 4 RESULTS AND DISCUSSION 48 4.1 SOIL MATERIALS 48 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS DETERMINED FROM BATCH ADSORPTION TESTS 50 4.2.1 The multi-heavy-metal sorption model 50 4.2.1.1 Isotherm equation selection and general observations 51 4.2.1.2 Modeling binary heavy metal sorption 54 4.2.1.3 Modeling ternary heavy metal sorption 60 4.2.1.4 Summary of sorption equations 63 4.2.2 Heavy metal sorption capacities 64 4.2.2.1 Ranking of materials 66 4.2.2.2 Ranking of heavy metals 67 4.2.3 Heavy metal selectivity and competition 70 4.2.4 Sorption performance of clay barrier materials based on Batch adsorption tests 72 4.2.5 Summary of Batch adsorption test results 73 4.3 THE LEACHING CELL TEST 75 4.3.1 Hydraulic conductivity results 78 4.3.1.1 General observations 78 4.3.1.2 Mechanism of hydraulic conductivity increase 86 4.3.1.3 Effect ofheavy metals vs. calcium on hydraulic conductivity 87 4.3.1.4 Importance of initial saturation 89 4.3.1.5 The effect of Pb and Cu on hydraulic conductivity 90 4.3.1.6 Uncertain factors influencing hydraulic conductivity 91 4.3.2 Heavy metal breakthrough results 92 4.3.2.1 General observations 92 4.3.2.2 Migration behavior - non-uniformity and fractured porous media 98 4.3.2.3 Retention capacity versus breakthrough point 200 4.3.2.4 Relative mobility of heavy metals 203 4.3.3 Performance of admixes 104 4.3.3.1 Performance based on hydraulic conductivity 204 4.3.3.2 Performance based on heavy metal breakthrough 206 4.3.4 Summary of Leaching cell results 108 4.4 Selective Sequential Extraction 110 4.4.1 SSE on a set of Batch adsorption tests Il l 4.4.1.1 Sorption characteristics of the admixes 223 4.4.1.2 Comparing sorption capacities of mixtures vs. individual materials 224 4.4.1.3 Comparing the sorption capacities of Batch and Leaching cell samples 225 4.4.2 SSE on extruded Leaching cell samples 117 4.4.2.2 Heavy metal migration behavior 227 4.4.2.2 Heavy metal retention mechanisms 229 4.4.3 Summary of SSE results and the performance of the admixes 135 C H A P T E R 5 C O N C L U S I O N S & R E C O M M E N D A T I O N S 137 5.1 CONCLUSIONS 137 5.2 RESEARCH CONTRIBUTIONS 141 5.3 RECOMMENDATIONS ON FURTHER RESEARCH 143 REFERENCES 145 APPENDIX A PHYSICAL PROPERTIES O F C L A Y BARRIER M A T E R I A L S 152 APPENDIX B C H E M I C A L PROPERTIES O F C L A Y BARRIER M A T E R I A L S 161 APPENDIX C M E T H O D S S U P P L E M E N T 165 APPENDIX D B A T C H A D S O R P T I O N T E S T C A L C U L A T I O N S A N D D A T A 173 vii APPENDIX E L E A C H I N G T E S T C A L C U L A T I O N S A N D D A T A 198 APPENDIX F SELECTIVE S E Q U E N T I A L E X T R A C T I O N C A L C U L A T I O N S A N D D A T A 223 LIST OF F IGURES Figure 1.1.1 Examples of clay barriers 4 Figure 1.3.1 Flow chart of research plan ...8 Figure 2.1.1 Examples of inner- and outer-sphere complexes 13 Figure 2.5.1 Fractionation of soil organic matter and humic substances 23 Figure 3.3.1 Diagram of the Batch adsorption test 32 Figure 3.4.1 Diagram of Leaching cell test 37 Figure 3.5.1 Diagram of the SSE 43 Figure 4.1.1 Grain size distribution of clay barrier materials 49 Figure 4.2.1 Single heavy metal isotherms 52 Figure 4.2.2 Freundlich isotherms of Cu sorption in single & binary heavy metal solutions 53 Figure 4.2.3 Binary sorption data showing how the presence of Cu and Cd affects Pb sorption 57 Figure 4.2.4 Binary sorption data showing how the presence of Pb affects Cu & Cd sorption 58 Figure 4.2.5 Calculated versus actual values for Pb, Cu, and Cd sorption in binary solutions 59 Figure 4.2.6 Calculated versus actual values for Pb sorption in ternary solutions 62 Figure 4.2.7 Ternary retention data showing how Cu and Cd change each others' sorption capacities 62 Figure 4.2.8 Calculated versus actual values for Cu and Cd sorption in ternary solutions 63 Figure 4.2.9 Heavy metal retention capacities of soil mix materials in single metal solutions 65 Figure 4.2.10 Final p H graphs showing the influence of Pb, C u , and C d , on the final solution pHs of each suspension 67 Figure 4.2.11 Selectivity of heavy metals in ternary and binary systems 71 Figure 4.3.1 Hydraul ic conductivity results for leachate blanks 80 Figure 4.3.2 Hydraul ic conductivity results for bentonite admix samples 81 Figure 4.3.3 Hydraul ic conductivity results for Forest soil admix samples 82 Figure 4.3.4 Hydraul ic conductivity results for Spruce bark admix samples 83 Figure 4.3.5 Averaged hydraulic conductivity results grouped by admix type 84 Figure 4.3.6 Averaged hydraulic conductivity results grouped by leachate type 85 Figure 4.3.7 Conceptual model for the mechanism of hydraulic conductivity increase in Leaching cells 88 Figure 4.3.8 Heavy metal breakthrough results for bentonite admix samples 93 Figure 4.3.9 Heavy metal breakthrough results for Forest soil admix samples 94 ix Figure 4.3.10 Heavy metal breakthrough results for Spruce bark admix samples. ...95 Figure 4.3.11 Averaged heavy metal breakthrough results grouped by leachate type 96 Figure 4.3.12 Averaged heavy metal breakthrough curves for bentonite admix permeated with Pb+Cu+Cd 97 Figure 4.3.13 Heavy metal concentration profiles of uniformily migrating plumes 99 Figure 4.3.14 Conceptual model for the mechanism of non-uniform heavy metal migration 99 Figure 4.3.15 Discharge p H results grouped by Leachate type 106 Figure 4.4.1 Distribution of heavy metals in bentonite admix samples leached with Pb 119 Figure 4.4.2 Distribution of heavy metals in bentonite admix samples leached with Cu 120 Figure 4.4.3 Distribution of heavy metals in bentonite admix samples leached with Pb&Cu 121 Figure 4.4.4 Distribution of heavy metals in Forest soil admix samples leached wi th Pb 122 Figure 4.4.5 Distribution of heavy metals in Spruce bark admix samples leached with Pb 123 Figure 4.4.6 Distribution of heavy metals in Spruce bark admix samples leached wi th Cu 124 Figure 4.4.7 Distribution of heavy metals in Spruce bark admix samples leached with Pb & Cu 125 Figure 4.4.8 Distribution of heavy metals in bentonite admix samples leached wi th Pb, Cu, & Cd 126 Figure 4.4.9 Distribution of heavy metals in Forest soil admix samples leached wi th Cu 127 Figure 4.4.10 Distribution of heavy metals in Forest soil admix samples leached wi th Pb & Cu 128 Figure 4.4.11 Pb sorption trends over a range of total sorption concentrations 130 Figure 4.4.12 Cu sorption trends over a range of total sorption concentrations. ...131 LIST OF T A B L E S Table 1.1.1 Historical changes in global production of metals commonly associated with pollution from mining activities 1 Table 1.1.2 Average levels of heavy metals in typical European household waste 2 Table 1.1.3 Typical leachate concentrations of heavy metals for municipal waste in the United States 3 Table 2.2.1 Summary of heavy metal selectivities for clay minerals and soils 16 Table 2.3.1 Summary of correlation results from several heavy metal . adsorption studies 18 Table 2.3.2 SSE results from several heavy metal adsorption studies 18 Table 2.4.1 Descriptions of heavy metal compatibility tests 22 Table 2.5.1 Summary of heavy metal retention studies using bark or bark constituents. ..: 25 Table 3.3.1 Batch adsorption test matrix 30 Table 3.3.2 Heavy metal solution concentrations used in Batch adsorption tests 31 Table 3.3.3 Heavy metal concentration ranges measured by the atomic absorption spectrophotometer 34 Table 3.4.1 The Leaching cell test matrix. 36 Table 3.5.1 The SSE program 41 Table 4.1.1 Physico-chemical properties of soil materials 48 Table 4.2.1 Summary for Batch adsorption test 50 Table 4.2.2 Summary of b and n values fitted for single & binary Cu data 53 Table 4.2.3 Summary of sorption equations for binary heavy metal solutions 56 Table 4.2.4 Summary of sorption equations for ternary heavy metal solutions 61 Table 4.2.5 Single Pb, Cu, and Cd sorption equations and their competition functions 64 Table 4.2.6 Summary of relative heavy metal sorption capacities .65 Table 4.2.7 Characteristics of Pb, Cu, & Cd 68 Table 4.2.8 Summary of competition amongst Pb, Cu, and Cd 72 Table 4.3.1 Summary for the Leaching cell test 75 Table 4.3.2 Physical properties of Leaching cell samples 77 Table 4.3.3 Summary of hydraulic conductivity results from averaged data in Figures 4.3.5 & 4.3.6 86 Table 4.3.4 Comparison between retention mechanisms of Ca and the heavy metals .90 Table 4.3.5 Summary of heavy metal breakthrough data from averaged data in Figures 4.3.11 & 4.3.12. Table 4.3.6 Summary of heavy metal breakthrough points & retentions 102 Table 4.3.7 Heavy metal mobilities of bentonite 103 Table 4.4.1 Summary for the SSE tests 110 Table 4.4.2 SSE results for Batch adsorption tests on admixes 112 Table 4.4.3 Comparison of admixes based on SSE and Batch adsorption samples 113 Table 4.4.4 Averaged sorption characteristics for admixes based on SSE of Batch adsorption tests 114 Table 4.4.5 Sorption capacities of admixes 115 Table 4.4.6 Comparing max. extractions of Leaching cell and Batch adsorption test samples Table 4.4.7 SSE data for Cd from the bentonite admix A C K N O W L E D G M E N T S The author would like to express his sincere gratitude to... • Dr. Loretta L i , for her guidance, patience, and encouragement throughout the course of this project, and for being a great role model by combining professionalism and graciousness in her life. • Dr. Les Lavkul ich, for providing valuable comments and advice, and for providing a location for collecting Forest soil. • Prof. Jim Atwater, for providing valuable comments and advice near the end of the project. • Ms. Susan Harper, and Ms. Paula Parkinson, for their advice, and assistance regarding laboratory equipment and procedures. • Kurt, for an excellent job in constructing any equipment required for the project. • Wi l l iam Denham, for his assistance and advice on the project, and for consuming a large quantity of coffee with me during the course of the project. • A l l my friends and colleagues in the Geoenvironment group, who have been very supportive in both word and action. • Forintek Canada Corporation for providing the Spruce bark. I would also like to thank the many friends that I have met along the way. Your lives have kept my thesis and my life in perspective. I would like to thank my family and relatives for their incredible support, encouragement, and love. Finally, I would like to thank God for His grace in my life and work. "There is a time for even/thing, and a season for every activity under heaven" Ecclesiastes 3:1 1 CHAPTER 1 I N T R O D U C T I O N 1.1 S T A T E M E N T O F P R O B L E M Mining, smelting, and industrial activity have caused extensive heavy metal contamination of the environment (Ernst 1995; from Ernst 1974,1990, and Ernst & Joose-van Damme 1983,1989). These activities directly input heavy metals into the surrounding atmosphere, waterways, and soil. The heavy metals may travel long distances due to weathering, wind, water currents, and groundwater f low (Fergusson, 1990). Table 1.1.1 shows the global production of metals commonly associated wi th pollution from mining activities. Of these, Cu and Pb are among the top six metals produced (Allan, 1995). T A B L E 1.1.1. Historical changes in global production of metals commonly associated with pollution from mining activities (x 1000 tonnes). (From Nriagu, 1979; Nriagu & Pacyna, 1987.) Metal Pre-1850 1850-1900 1900-1940 1950 1960 1970 1980 Copper 45,000 13,000 49,000 2650 4212 6026 7660 Zinc 50,000 15,000 40,000 1970 3286 5469 5220 Lead 55,000 25,000 51,000 1670 2378 3395 3096 Nickel 200 1,500 144 327 639 759 Cadmium 6.0 11 17 15 Silver 6.2 7.5 9.4 11 Mercury 4.9 8.3 9.8 7.1 Gold 1.0 1.4 1.5 1.2 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.1 STATEMENT OF PROBLEM 2 The toxicity of heavy metals lead to reduced crop yields, death of marine life (Crosby, 1998), and serious health problems in humans. Lead (Pb) affects the nervous blood systems. Copper (Cu) causes tremors, laboured respiration, and hemolysis (Crosby, 1998). Cadmium (Cd) affects the renal system, cardiovascular system, and the skeleton. Cd also is known to cause cancer in the prostate gland, and lungs (Yasumura, 1980; Fergusson, 1990). Unlike many organic contaminants, heavy metals cannot be degraded; thus, possessing a high potential to bioaccumulate and move up the food chain. For the case in which heavy metal migration is a high threat to sensitive areas, such as drinking water sources, containment is often the most practical solution. A n effective method of containment is the combination of pumping wells and vertical barriers. This method of hydraulic control ensures that contaminated groundwater does not migrate out of the control area. Since heavy metals cannot be degraded, removal is one of the few alternative solutions. The simplest method of removal is excavation of the contaminated soil. Other methods include biological extraction (Ernst, 1995), and soil washing (Ragaini, 1994). Regardless of the removal method, the special waste landfill is often the final disposal facility for heavy metals. Special waste landfills are constructed for containing heavy metals and other hazardous wastes. However, municipal waste landfills also must account for heavy metal input. Table 1.1.2 shows the average levels of heavy metals found in typical European household waste. Of these, batteries account for 45% of the Cd, and scrap iron accounts for 40% of the Pb and 30% of the Cu. (Rousseaux et al., 1989). Table 1.1.3 shows the typical leachate concentrations of heavy metals from municipal waste in the United States. T A B L E 1.1.2. Average levels of heavy metals in typical European household waste (Rousseaux et al., 1989). Hg Cd Pb Zn Cu Ni Cr Concentration (ppm) 1-3 3 - 5 100-700 400 -1000 100 - 300 20-50 50 -100 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.1 STATEMENT OF PROBLEM 3 TABLE 1.1.3 Typical leachate concentrations of heavy metals for municipal waste in the United States (Bagchi, 1990; taken from McGinley & Kmet, 1984, and Lu et al., 1981). H X Cd Pb Z M Cu Ni Cr Concentration (ppm) ND - 3.0 ND - 0.4 ND -14.2 ND - 731 ND - 9.0 ND - 7.5 ND - 5.6 ND - non-detectable Engineered clay barriers are commonly used as vertical barriers and landfil l liners (Figure 1.1.1). Clay barriers are constructed from locally found soils amended with clay. The clay may also be mined locally, or bought commercially. Clay barriers are effective primarily because they possess low hydraulic conductivities. The hydraulic conductivity of a clay barrier is dependent on its composition, and the method used for its construction. Another significant consideration, is the chemical reactivity between the clay barrier, and the contaminant. The current study focuses mainly on the aspect of chemical reactivity. If the contaminant causes the clay barrier to deteriorate, then the clay barrier would be deemed incompatible with that contaminant. Besides having low hydraulic conductivities, clay barriers also possess the ability to sorb many types of contaminants. Since clay barriers are not impermeable, their contaminant retention ability act as important second lines of defense. Therefore, the compatibility of a clay barrier to a specific contaminant depends on two factors: the clay barrier's ability to resist any increases in hydraulic conductivity caused by the contaminant, and its ability to retain the contaminants. Several studies already have indicated that heavy metals increase the hydraulic conductivity of clay barrier materials (Dunn & Mitchell, 1984; Weber, 1991; Cabral, 1992; Lo et al., 1994). In addition, many studies have explored the heavy metal retention abilities of soils and clay minerals (Soldatini et a l , 1976; Rose, 1989; Barry et al., 1995; Arnfalk et al., 1996; Gao et al., 1997). Even though research into the problem of heavy metal compatibility has progressed beyond the initial stage, opportunities abound in understanding the extent and mechanism in which heavy metals affect Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.1 STATEMENT OF PROBLEM hydraulic conductivity, as well as in improving the heavy metal compatibility of clay barriers. 4 b) Surface impoundment liner. (k<1«10-7cm/B> <k!1«1<r' emit) * Synthetic drainage materta (Trartsmissivity2 3x10~4 mas> c) Vertical barrier wall. F I G U R E 1.1.1. Examples of clay barriers, (a) Landfill liner, (b) Surface impoundment liner. (c) Vertical barrier wall. (Sharma & Lewis, 1994; from USEPA, 1984,1989) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.2. SCOPE A N D OBJECTIVES 1.2 S C O P E A N D OBJECT IVES 5 Many of the past studies placed emphasis on comparing various permeameters and testing conditions (see section 2.4) in order to isolate the effect of heavy metals on hydraulic conductivity. However, since many previous compatibility studies, used either distilled water (Weber, 1991; Cabral, 1992), or tap water (Dunn & Mitchell, 1984; Lo, 1994) as blank leachates, the increase in hydraulic conductivities may be due to differences in ionic strength. Past Leaching cell studies generated much hydraulic conductivity and heavy metal breakthrough data (Dunn & Mitchell, 1984; Peirce et al., 1987; Weber, 1991; Cabral, 1992; Lo et al., 1994); however, few conclusions were made regarding the migration behavior of heavy metals, and the retention mechanisms of clay barriers. Since most of the studies used single heavy metal permeants (Peirce et al., 1987; Weber, 1991; Cabral, 1992; Lo et a l , 1994), the effect of competition on heavy metal migration through clay barriers remains uncertain. Within soil science, sorption competition of heavy metals has been the focus of many Batch adsorption studies (Puis & Bohn, 1988; Bladel et al., 1993; Gutierrez & Fuentez, 1993); however, the applicability of the adsorption results to Leaching cell tests remains questionable. More understanding on the sorption and migration behavior of heavy metals would be beneficial in predicting and managing the transport of heavy metals through clay barriers. Heavy metal compatibility research has focused mainly on clay minerals, such as kaolinite and bentonite (Weber, 1991; Cabral, 1992). Few studies (Lo et a l , 1994) focused on finding alternative materials that would improve heavy metal compatibility. These alternative materials would need to be economical, and easily incorporated into clay barriers. The goals of this thesis aim to improve the heavy metal compatibility of clay barriers, and assist in predicting the migration of heavy metals. The specific objectives are as follows: Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.2. SCOPE A N D OBJECTIVES 6 1. To find the effects of heavy metals on the hydraulic conductivity of clay barriers. A l l synthetic leachate solutions were given a background concentration of 0.01 M calcium nitrate (Ca(NOs)2.) in order to maintain similar ionic strengths. If heavy metal incompatibility is dependent only on ionic strength, no differences should be observed between the hydraulic conductivities of heavy metal and blank leachates. 2. To investigate the sorption and migration behavior of single and multi-heavy-metal solutions (Pb, Cu, & Cd), through clay barriers. Specifically, the following issues are investigated: a) Which heavy metals are less compatible with clay barriers? b) What is the mechanism of hydraulic conductivity increase due to heavy metals? c) H o w does competition affect heavy metal sorption and migration? d) What are the preferred retention mechanisms for various heavy metals? 3. To evaluate the applicability of Batch adsorption results to the Leaching cell studies. Batch adsorption test results often were used as inputs for heavy metal transport models. The current study investigates whether the Batch adsorption results could adequately predict heavy metal migration, heavy metal retention capacities. 4. To explore the use of Forest soil and Spruce bark in clay barriers Forest soil and Spruce bark were selected as potential materials for clay barrier construction based on their proven heavy metal sorption abilities (Soldatini et al., 1976; Rose, 1989; Barry et a l , 1995; Arnfalk et a l , 1996; Gao et al., 1997). The current Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.2. SCOPE A N D OBJECTIVES 7 study uses Leaching cell tests to evaluate the performance of clay barrier admixes that contain Forest soil or Spruce bark. The typical clay barrier admix is represented by 100:8 mix of sand and N«-bentonite. Other admixes were created by replacing one part of bentonite with either Forest soil or Spruce bark. Improved compatibility would be evidenced by increased heavy metal retention while maintaining a low hydraulic conductivity. 1.3 T H E R E S E A R C H P L A N To accomplish the objectives presented in the previous section, a research plan was created containing four main sets of tests. A flow chart outlining the research plan is shown in Figure 1.3.1. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.3. RESEARCH PLAN 8 uoi)ej6jUi lejem Aiveaq jo uouojpejd pue 'saaixieq ABIO jo )uauieAOjdiuj pue u6|sap ein J O J suouepuoujuioooy z g (0 CO 3 O (0 Q < K-< Q OT H (0 LU (0 LU > t— O LU -J DO O S|B)eUI AAeet) jo uoi)ejB|ui ain 6ui6euew pue Gujiojpejd u; isjsse pue 'sjeiueq Aep 10 AjMiqnBduioo |e|aui AAeeu, ein OAOjduii o) U I I B sgsein si in jo seAipofqo e m a ji s o o E I-L, Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.3. RESEARCH PLAN 9 1.4 R E S E A R C H C O N T R I B U T I O N S The following list identifies some areas which would benefit from this research: 1. The design of landfill and surface impoundment liners, and vertical barrier walls Insights gained from investigating the sorption and migration behaviour of heavy metals would increase the reliability of clay barrier designs. In addition, the current study investigates possible improvements to clay barriers by adding Forest soil, and Spruce bark. 2. Modeling the migration of heavy metal through soils The relationship between sorption competition and heavy metal migration are relevant to transport modeling. 3. Co-disposal of heavy metal contaminated soil Heavy metal retention characteristics of a clay barrier mix could be altered by the addition of other materials. The results from the current study could be applied to the situation in which heavy metal contaminated soil is mixed with other clean soils or materials. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 1.5 ORGANIZATION OF THESIS 1.5 O R G A N I Z A T I O N OF THESIS 10 The thesis consists of five chapters: Chapter 1: Presents the scope, objectives, and research plan. Chapter 2: Background information on the interactions between heavy metals and soils are provided. In addition, published literature on heavy metal sorption and permeability testing is summarized. Chapter 3: Describes the equipment, materials, and methods used in this study. Chapter 4: Presents the results from research program. In addition, discusses the heavy metal compatibility of the three admixes, the sorption and migration behavior of heavy metals, and the relationship between the Batch adsorption results and the Leaching cell test. Chapter 5: Presents conclusions, research contributions, and recommendations for future research. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 11 CHAPTER 2 BACKGROUND REVIEW The heavy metal compatibility of clay barriers are determined by hydraulic conductivity and retention ability. However, the mechanisms and processes that govern these parameters are complex. A n understanding of the physical, and chemical interactions that occur between heavy metals and soils wi l l benefit the evaluation of heavy metal compatibility. Because of the complexity of heavy metal and soil interactions, conclusive formulations are lacking from the results of heavy metal sorption studies. Several studies used Batch adsorption tests and Selective Sequential Extractions (SSEs) to investigate the sorption capacities of different soils and clay minerals. However, heavy metal compatibility studies on clay barriers have been limited to identifying the occurrence and extent of heavy metal incompatibility. Much opportunity exists in researching the effects of heavy metals, and finding improvements for clay barriers. 2.1 H E A V Y M E T A L A N D S O I L I N T E R A C T I O N S The three mechanisms for heavy metal retention in soils are cation exchange, the formation of inner-sphere complexes, and precipitation. In addition, an important factor that influences the effectiveness of these mechanisms is solution p H . Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.1 HEAVY M E T A L A N D SOIL INTERACTIONS 2.1.1 Cation Exchange 12 Cation exchange describes the phenomenon in which cations electrostatically adsorb onto negatively charged soil particles. Because no chemical bonding occurs, the electrostatically held cations are easily displaced by other cations (Evans, 1989). The exchange of cations depend on the type and concentrations of the cations present, and also the chemical environment of the pore water. Cations of higher concentrations displace those of lower concentrations, and high valence cations displace the low valence cations (Tan, 1998). In general, soil organic matter possesses the highest cation exchange capacity (CEC); clay minerals are second; and then follows the rest of the inorganic minerals. Besides having the highest C E C , soil organic matter also have very high specific surface areas. Organic matter accounts for up to 80% of the C E C of soils (Stevenson, 1982). 2.1.2 Inner-Sphere Complexation When the surface functional group of a soil particle interacts wi th an ion present in the soil solution to create a stable molecular entity, a surface complex forms (Sparks, 1995). Examples of an outer-sphere and inner-sphere complex are shown in Figure 2.1.1. Outer-sphere complexes are bound ionically. By retaining their water of hydration, ionically bonds are considered nonspecific and is classified under cation exchange. Inner-sphere complexes are bound covalently. These are strong bonds in which electrons are shared amongst the bound ions. Presented below are important surface functional groups associated with minerals and soil organic matter. For minerals, the hydroxyl groups are important surface functional groups. The divalent transition metals readily form inner-sphere complexes with hydroxyl groups by displacing an H + from the hydroxyl group and bonding to the - O -. Being divalent, the metal may bond to one or two oxygen atoms (Sparks, 1995). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.1 HEAVY M E T A L A N D SOIL INTERACTIONS 13 As for soil organic matter, many surface functional groups are available for complexation. Donor atoms generally are the more electronegative nonmetallic elements, such as O, N , and S. These elements are contained within the basic functional groups, such as amino, carbonyl, alcohol, thioether; and the acidic groups, such as carboxyl, phenolic, enolic, and thiol (Evans, 1989; Sparks, 1995). Livens (1991), states that for soil organic matter, the ease and strength of bonding depends on following: 1. The affinity of the metal ion for that type of site; 2. Stereochemical factors, i.e. the amount of room for the metal ion to fit into the site. This can be affected by the size of any other ligands on the metal; 3. The chemical environment of the site. The nature of the functional groups around the actual complexing group can influence its behaviour. mineral surface surface (hydroxyl) functional group O Ba2+rO O U T E R - S P N E R E water molecule \ q J oxygen A complex inner-sphere complexes Cu F I G U R E 2.1.1. Examples of inner- and outer-sphere complexes (Adapted from Sparks, 1995; taken from Hayes, 1987). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.1 HEAVY M E T A L A N D SOIL INTERACTIONS 14 2.1.3 Precipitation Precipitation is the formation of an insoluble product from a reaction that occurs in solution (McQuarrie & Rock, 1991). The extent of precipitation and dissolution of a mineral can be described by its solubility product (Tan, 1998). Precipitation w i l l occur when the product of the metal ion and ligand concentrations exceeds their solubility product. Among the most important precipitation reactions, are those that involve the hydroxide (OH -) ligand. Metals that are expected to precipitate as hydroxides are Fe 3 + , A l 3 + , C u 2 + , Fe 2 + , Z n 2 + , and C d 2 + (Evans, 1989). In addition, metal ions also commonly precipitate as carbonates (CO32") and sulphides (S2*). Metals that are expected to precipitate as carbonates are C a 2 + , Sr 2 + , B a 2 + , Fe 2 + , Z n 2 + , C d 2 + , and Pb 2 + . Although carbonates occur in both oxidizing and reducing conditions, sulphides are stable only in reducing conditions. Metals that occur as sulphides in reducing conditions include A g + , N i 2 + , Z n 2 + , C d 2 + , H g 2 + , Fe 3 + (Evans, 1989). 2.1.4 The effect of solution pH Heavy metal retention mechanisms are affected by solution p H in several ways. In regards to cation exchange, the high concentration of H + ions associated with low p H conditions compete with other cations for exchange sites. Also, the H + ions may bond to negatively charged surface functional groups contributing to an overall reduction in the negative charge of the soil particle. As a result, this reduction lowers the cation exchange capacity of the soil particle. The effect of p H on precipitation is described by the presence of H + ions in metal solubility equations. In general, precipitation increases with increasing p H ; however, in some cases, metals redissolve at very high pHs (Lindsay, 1979). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.1 H E A V Y M E T A L A N D SOIL INTERACTIONS 2.1.5 The effect of heavy metals on clay structure 15 Because clays carry a negative charge, cations are attracted to clay surfaces. The negatively charged clay surface, and the surrounding cloud of cations held by electrostatic attraction, form the electric double layer as described by Gouy (1910) and Chapman (1913). The double layer thickness of clay particles greatly influence their structural arrangement. The double layer thickness of clay particles is inversely proportional to the valence, and square root of the concentration of cations (Tan, 1998). When double layer thicknesses are great, repulsive forces dominate, resulting in a dispersed particle structure. When double layer thicknesses are small, attractive forces dominate, resulting in a flocculated particle structure. Thus, increasing concentrations of heavy metal solutions would cause decreases in the double layer thickness of clay particles, leading to more flocculated structures. In relation to hydraulic conductivity, flocculation leads to increased pore spaces around the flocculated structures, thereby increasing hydraulic conductivity (Mitchell et al., 1965). Also, dispersed structures results in lower hydraulic conductivity, because "f luid transport through soil pores must overcome the increased energy field established by the repulsive forces" (Yong et al., 1992). 2.2 S T U D I E S I N H E A V Y M E T A L R E T E N T I O N S E L E C T I V I T Y Retention capacity refers to the maximum amount of heavy metals that a soil could retain. The retention capacity for a particular heavy metal is determined by performing sorption tests, in which the soil is placed into solutions containing various concentrations of the heavy metal. Selectivity is based on the relative sorption capacities of many heavy metals contained within the same solution. Often, the order Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.2 STUDIES IN H E A V Y M E T A L RETENTION SELECTIVITY 16 of selectivity for a group of heavy metals is the same as the order of their individual capacities. Many studies have been conducted to find and explain the selectivity of heavy metals. A survey of these studies shows discrepancies in the orders and explanations for selectivity. Table 2.2.1 contains a selection of studies. T A B L E 2.2.1. Summary of heavy metal selectivities for clay minerals and soils. Author(s) Sorbant Material Order of Selectivity Reason Puis & Bohn, 1988 Montmorillonite Cd«Zn>Ni HSAB principle* Kaolinite Cd*Zn>Ni HSAB principle* Bladel et al., 1992 Bentonite, illite, vermiculite Zn>Cd Ionic potential Yong & Phadungchewit, 1993 -Montmorillonite, kaolinite, illite, natural clay (pH > 4 or 5) Pb>Cu>Zn>Cd 1st hydrolysis product Morley & Gadd, 1995 Montmorillonite, kaolinite Cu»Cd>Zn Irving-Williams order of stability Mohamed & Antia, 1998 General soils Ca>Mg>Hg>Cd>Zn (general order for divalent metals) Ionic radius Mohamed & Antia, 1998 General soils Cu>Ni>Co>Fe>Mn (transitional divalent metals) Irving-Williams order of stability * Hard-Soft-Acid-Base principle Several points can be made to clarify the discrepancies shown in Table 2.2.1. The Irving-Williams order of stability (Irving & Wil l iams, 1953), based on ionic radius and ionization potential, is limited to a subset of the first transitional metal series. In fact, one of the goals of their paper was to stress that no general order exists for transitional metals outside the Irving-Williams list. The selectivity of transitional metals outside the Irving-Williams order would vary depending on the following: 1. The radii and ionization potentials of the metals 2. The type of adsorbents 3. The presence of other ligands in solution, and 4. The chemical environment (pH, redox potential) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.2 STUDIES IN HEAVY M E T A L RETENTION SELECTIVITY 17 Thus, researchers that explained selectivity using only ionic radius or ionic potential were ignoring other important factors. For example, in citing the 1st hydrolysis product, Yong and Phadungchewit (1993), were implying that hydroxide precipitation was the dominant factor in heavy metal retention. This may or may not have been true depending on the factors stated earlier. The Hard-Soft-Acid-Base principle, cited by Puis and Bohn (1988), is not directly linked with fundamental properties, but is a useful classification system. Their efforts to classify the hardness and softness of heavy metals and clay minerals may prove to be useful if a sufficient database can be successfully constructed. 2.3 H E A V Y M E T A L R E T A I N I N G SOILS A N D M I N E R A L S Two approaches were used to investigate the retaining abilities of materials. The simpler method involved the Batch adsorption test. The Batch adsorption test was used to determine the amount of heavy metals retained by several different materials. These results were then correlated with certain characteristics, such as clay and organic content, and mineralogy. Table 2.3.1 highlights the correlation results of several studies. The second method for heavy metal retention studies used the SSE procedure to directly measure the amount of heavy metals retained by four components of a mineral or soil: exchangeable, carbonate, oxide/hydroxide, and organic. Table 2.3.2 shows the SSE results of several studies performed on various soils. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.3 HEAVY M E T A L RETAINING SOILS & MINERALS 18 TABLE 2.3.1. Summary of correlation results from several heavy metal adsorption studies. Author(s) Soil Description Retained Heavy Metals Positive Correlations to Heavy Metal Retention Soldatini et al., 1976 12 soils side ranging in organic matter, and clay and carbonate content Pb Organic and clay content Rose, S., 1989 Samples from 2 layers of the Hawthorne Formation Pb, Cu, Zn, Cd Clay content Barry et al., 1995 Samples from 6 soil horizons within soil profile Cd, Ni, Cu Organic content Arnfalk et al , 1996 14 different types of minerals and soils Cd, Cr(III), Cr(VI), Hg, Pb Organic content Gao et al , 1997 9 soils Ni, Cu, Cd, Zn Organic content TABLE 2.3.2. SSE results from several heavy metal adsorption studies. Author(s) Heavy Metal Highest Associated Component Hickey & Kittrick, 1984 Cu Organic Cd Exchangeable Yanful et a l , 1988 Cu Organic Pb, Zn, Fe Carbonate Ramos et al., 1994 Cu Organic Pb, Zn Oxide Cd Exchangeable & Carbonate The following observations were made from the Batch adsorption and SSE studies: 1. Heavy metal retention often is associated with the organic and clay fractions of soils. 2. Studies involving clay minerals showed that montmorillonite retained heavy metals better than illite and kaolinite, mainly due to its higher buffering capacity. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.4 HEAVY M E T A L COMPATIBILITY STUDIES 19 2.4 H E A V Y M E T A L C O M P A T I B I L I T Y STUDIES Many compatibility studies have been conducted to investigate the compatibility of clay barriers to different types of permeants. Over the last 20 years, much work has been done with organic contaminated permeants (Acar et al., 1985; Fernandez & Quigley, 1985; Foreman & Daniel, 1986; Uppot & Stephenson, 1989; Meegoda & Rajapakse, 1993). In comparison, significantly fewer studies have focused on investigating heavy metal compatibility. Descriptions of five heavy metal compatibility stuies are presented in Table 2.4.1. Conclusions from the five studies are summarized below: 1. Dunn and Mitchell (1984), found that a synthetic leachate of Pb and Zn produced hydraulic conductivities 5 -100 times greater than tap water. They also found that static compaction produced the best quality of soil samples with the least effort. 2. Peirce et al., (1987), found that hydraulic conductivity values were within one order of magnitude for all scenarios tested using three clay soils. Also, heavy metal breakthrough occurred only for the samples permeated with 300 ppm nickel nitrate (Ni(NC>3)2). 3. Weber (1991) found that for kaolinite clay, hydraulic conductivity values were similar for all conditions tested. For the sand/bentonite mixture, only the 2500 ppm concentration of Pb produced hydraulic conductivity values significantly higher than with distilled water. Heavy metal breakthrough occurred in all the kaolinite samples, but in the sand/bentonite samples, only the 2500 ppm Pb permeant resulted in breakthrough. A l l heavy metal breakthroughs coincided with a sudden drop in p H . They also found that the sorption isotherms produced from Batch adsorption tests were Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.4 H E A V Y M E T A L COMPATIBILITY STUDIES 20 significantly higher than those produced from the ammonium acetate extractions. 4. Cabral (1992) found that hydraulic conductivity values were similar for all conditions tested using kaolinite clay. The consolidation cell produced hydraulic conductivities two orders of magnitude lower than the triaxial cell results when using the sand/bentonite mixtures. These differences were attributed to the incomplete saturation of the consolidation cells. Also, the hydraulic conductivities of the triaxial cells varied significantly depending on the initial gradient applied, saturation and compaction procedures, the heavy metal concentration of permeants, and the type of heavy metal used. Zn permeants resulted in higher hydraulic conductivities than Pb permeants. In contrast, the hydraulic conductivities of consolidation cell tests were insensitive to the initial gradients applied and the presence of Pb. Heavy metal breakthrough occurred for samples permeated with 1750 ppm and 2500 ppm of Pb. The retardation factors calculated from the Batch adsorption tests were significantly larger than those calculated from breakthrough curves. 5. Lo et al. (1994), found that for Claymax and composite liners, hydraulic conductivity values were three times greater using the synthetic leachate than tap water. The composite liner was effective in maintaining a low hydraulic conductivity while retaining the Pb and 1,2-dichlorobenzene ( D C S ) . Of the five studies presented, only Peirce et al. (1987), used a blank solution that contained a standardized ionic concentration. Because his was also the only study that found no heavy metal incompatibilities, one must confirm whether heavy metal incompatibilities were a result of differences in ionic strengths. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.4 H E A V Y M E T A L COMPATIBILITY STUDIES 21 In all the presented studies except for Lo et al. (1994), emphasis was placed on experimenting with various permeameters, compaction methods, and experimental procedures, such as hydraulic gradient, and confining pressure. This limited the work done in studying the sorption and migration behavior of heavy metals. Lo et al. (1994), developed a new composite liner that improved heavy metal compatibility. However, the process in preparing the soils is potentially expensive. Ideally, new materials should be inexpensive and easily incorporated into clay barrier mixes. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.4 HEAVY METAL COMPATIBILITY STUDIES 22 Adsorption tests none none Batch tests, and Pb extraction from extruded Leaching cell samples using ammonium acetate Batch tests, and Pb extraction from extruded Leaching cell samples using ammonium acetate Batch tests Hydraulic gradient 20-200 65 - 200 25,50, and 100 25, 50, and 100 o 00 Comining pressure 150 kPa r^. f^ . 13.79 - 35.16 kPa 60 - 370 kPa (for triaxial) 35 - 49 kPa (for con. cell) 135.4 kPa Compaction method static, impact, and kneading dynamic static static Permeameter triaxial cell fixed-wall cell, and triaxial cell consolidation cell consolidation cell, triaxial cell triaxial cell Blank leachate tap water CN t ° distilled water distilled water tap water Heavy metal leachate 200 ppm Zn + 15 ppm Pb (pH 2.5) _2 o y £ s £ ^ CH H j - ° ^ DH 0 O n o ^ e o o c 5^ 250 - 2500 ppm concentrations of Pb(NQ3) 2 (pH3.6) 250 - 2500 ppm concentrations of Pb(N0 3) 2, and 2000 ppm ZnSOi 62.2 ppm 1, 2 DCB + 69.2 ppm NaCl + 100.6 ppm Pb + pH 7 phosphate buffer Liner Material 2 silty clay soils 3 clay soils kaolinite, and sand/Na-bentonite mixture kaolinite, and sand/Na-bentonite mixture Claymax, humic acid-aluminum hydroxide coated montmorillonite (HA-AIOH-Clay), and HA-AIOH-Clay & Clay J J composite liner Author Dunn and Mitchell, 1984 Peirce et al., 1987 Weber, 1991 Cabral, 1992 Lo et al., 1994 CO i n o •43 a> in u QJ IH C3 Ol 73 O o 2 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.5 POTENTIAL NEW MATERIALS FOR CLAY BARRIERS 23 2.5 P O T E N T I A L N E W M A T E R I A L S F O R C L A Y B A R R I E R S This section aims to provide background evidence that Forest soil and Spruce bark would improve heavy metal retention if added to clay barrier mixes. 2.5.1 So i l Organic Matter Soil organic matter represents all organic compounds in soil excluding undecayed plant and animal tissues, their "partial decomposition" products, and the soil biomass (Stevenson, 1982). Figure 2.5.1 shows the fractionation of soil organic matter based on chemical and physical separation techniques. Nonhumic substances Soil organic matter Humic substances i.e. recognizable plant debris; plus polysaccharides, proteins, lignins, etc. in their natural or transformed states fractionation on the basis of solubility soluble in acid and alkali insoluble in acid and soluble in alkali insoluble in acid and alkali FULVIC ACID HUMIC ACID t HUMIN F I G U R E 2.5.1. Fractionation of soil organic matter and humic substances (Sparks, 1995; taken from Hayes & Swift, 1978) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.5 POTENTIAL NEW MATERIALS FOR CLAY BARRIERS 24 The fact that the heavy metal retention of soils often correlates with their organic contents has been presented in section 2.3. The following are two heavy metal retention studies in which humic substances were mixed with soils and clay minerals. Hatton and Pickering (1980), mixed 3 mg of humic acid with 7-15 mg of three types of clays: Na-montmorillonite, kaolinite, and illite. The mixtures were subjected to Batch adsorption tests involving Pb, Cu, Zn, and Cd. For pHs set below 6, the humic acids tended to dominate the adsorption process, while for pHs set above 6, heavy metal retention as metal hydroxyl species dominated. Overall, the heavy metal retention of the clay-humic acid mixtures were lower than would be predicted by the addition of individual retention capacities, but higher than the retention capacities of the individual components. This indicated that clays and humic acids interfered with each others' heavy metal retention abilities. Igloria et al. (1998), conducted leaching tests using two field soils. The artificial leachate solutions had Cd, Cu, Pb, and Zn concentrations (< 1 mg L- 1) that simulated average stormwater. Natural organic matter was added to the leachate to produce about a 50 mg L _ 1 total organic carbon (TOC). The natural organic matter was collected by extracting standard garden peat with sodium hydroxide (NaOH). Results showed that with the addition of natural organic matter, Cu and Zn attenuation improved by as much as 40%, while Pb and Cd attenuation improved by > 10%. Igloria et al (1998) concluded that the results encouraged further studies into the application of peat "covers" onto the bottom of infiltration basins. The organic matter in the previous studies was extracted from soils using alkali solutions. The current study did not use extracted organic matter, but added soils high in organic matter (Forest soil) directly to the barrier mix. The direct addition of Forest soil would avoid the costly step of first extracting the organic matter. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 2.5 POTENTIAL NEW MATERIALS FOR CLAY BARRIERS 2.5.2 Spruce Bark 25 Bark is a common wood waste. Because it is produced in large quantities, efforts have been made to find other uses for it. Bark has been successfully used as industrial fuel, soil amendment, and ground cover (Haygreen and Bowyer, 1996). However, barks from some trees such as Spruce, contain high levels of toxic tannins (Field & Lettinga, 1991). This limits its reusability as well causes disposal problems. Shown in Table 2.5.1, are several studies that have used bark, or bark constituents to retain heavy metals. T A B L E 2.5.1. Summary of heavy metal retention studies using bark or bark constituents Author(s) Bark (Constituent) Heavy Metals Retained Hatton & Pickering, 1980 Tannic acid (mixed with clay minerals) Pb, Cu, Cd, Zn Deshkar et al.," 1990 Formaldehyde-modified Hardwickia Binata bark Hg Al-Asheh & Duvnjak, 1997 Pine Bark Pb, Cd, Cu, Ni Gloaguen & Morvan, 1997 Formaldehyde-modified Picea abies, Pinus sulvestris, Pseudotsuga manziesii, Larix kaempferi, Tectona grandis, and Afzelia africna barks Pb, Zn, Cr, Fe, Cu The mentioned studies show that bark has the potential to retain heavy metals. Thus, Spruce (Picea) bark would be a logical choice for improving the sorption ability of clay barriers. This study evaluates the performance of Spruce bark by adding it in shredded form, to a typical clay barrier mix. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 26 CHAPTER 3 M A T E R I A L S A N D M E T H O D S 3.1 C L A Y B A R R I E R M A T E R I A L S 3.1.1 Origins & Descriptions Bentonite The Nfl-bentonite was obtained from Canadian Clay Products in Wilcox, Saskatchewan. Sand The sand is a commercial product named Wedron 130. Forest soil The Forest soil was sampled at a site near 48th Avenue, East of 152nd Street, in Langley, British Columbia. After removing about 5 cm of forest litter, samples were taken from the top 30 cm of forest soil. The soil samples were placed directly into doubled layered plastic bags, and were kept cool using freezer packs during transport. At the lab the samples were stored under a constant 4 °C, and 100% humidity. Spruce bark The Spruce bark provided by Forintek Canada Corporation. Forintek obtained wood waste materials from various sawmills in BC. The Spruce bark material was a mixture of 85% Spruce bark chips, and 15% sawdust. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.1 CLAY BARRIER MATERIALS 3.1.2 Admixtures 27 The clay barrier materials were used to create three admixes (see section 3.4.2 for admix preparation procedure): Bentonite admix - 100:8 ratio of sand:bentonite. Forest soil admix - 100:7:1 ratio of sand:bentonite:Forest soil. Spruce bark admix - 100:7:1 ratio of sand:bentonite:Spruce bark. The three admixes were designed to have equal parts of reactive material. The bentonite admix represents the typical clay barrier mix to which the other admixes were compared. 3.1.3 Physical properties Summaries are provided for each test. Ful l descriptions are found in A P P E N D I X A . Particle size distribution Particle size distributions of the sand, bentonite, Forest soil, and Spruce bark were determined by dry sieving and the hydrometer method according to A S T M D422-63 (ASTM, 1995) (APPENDIX A . l ) . Specific gravity Specific gravities were measured for the admixes using the volume-displacement method described in A S T M D854-92 (ASTM, 1995) (APPENDIX A.2). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.1 CLAY BARRIER MATERIALS 28 Specific surface area The specific surface of bentonite was determined using an ethylene glycol monoethyl ether (EGME) method adapted from Eltantawy and Arnold (1973). See A P P E N D I X A.3 for a description of the adapted method. Atterberg limits Liquid limits were obtained for the bentonite material, and the three admixes. The plastic limit was obtained only for the bentonite, because the admixes contained too much coarse material. The Atterberg limits were done according to the procedure outlined by A S T M D318-93 (ASTM, 1995). Maximum dry density and optimum water content The maximum dry densities and optimum water contents for the admixes were determined using a method adapted from A S T M D1557-91 (ASTM, 1995). See A P P E N D I X A.4 for a description of the adapted method. 3.1.4 Chemical properties Summaries are provided for each test. Ful l descriptions are found in A P P E N D I X B. Soil pH The pHs of the clay barrier materials were measured in distilled water, and in 0.01 M calcium chloride (CaCh) with a method adapted from McLean (1982). See A P P E N D I X B.l for a description of the adapted method. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.1 CLAY BARRIER MATERIALS 29 Cation Exchange Capacity (CEC) The cation exchange capacity of bentonite was obtained using a method adapted from Standard method 9081 ( A P H A , A W W A , & WEF, 1995). See A P P E N D I X T3.2 for a description of the adapted method. 3.2 C H E M I C A L S O L U T I O N S A l l blank and heavy metal solutions contained a background of 0.01 M calcium nitrate (Ca(N03)2). The heavy metal solutions also contained combinations of lead nitrate (Pb(N03h), copper nitrate (Cu(NC>3)2), and cadmium nitrate (Cd(N03)i). A l l solutions were prepared by dissolving solid crystals of Ca(NOs)2, Pb(N03)i, Cu(N03)i, and Cd(NOs)2, into distilled water. To ensure that all the cations remained dissolved, all solutions were set to a p H of 4.0, using nitric acid (HNO3). The combinations and concentrations of heavy metals used, are described in later sections that detail the individual tests. A l l heavy metal solution concentrations were confirmed using a Video 22 Thermo Jarrell A s h aa/ ae Spectrophotometer - Model 957. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3 . 3 B A T C H ADSORPTION TEST M E T H O D 3.3 B A T C H A D S O R P T I O N TEST M E T H O D 30 3.3.1 Batch adsorption test program The Batch adsorption test was used to find the heavy metal sorption isotherms of the clay barrier materials and admixes. Each Batch test was performed in duplicate to ensure accuracy. The sorption isotherms developed for single, binary, and ternary heavy metal solutions, were used to evaluated sorption capacities, selectivities, and competition. The combinations of materials and heavy metal solutions tested are shown in Table 3.3.1, and the concentrations of solutions used for each test are shown in Table 3.3.2. A diagram summarizing the Batch adsorption test is found in Figure 3.3.1. A n equipment list is shown in A P P E N D I X C . l . The admix samples submitted to Batch testing were later submitted to Selective Sequential Extraction (SSE). Because of time constraints, Forest soil was not tested in a ternary heavy metal system. The ternary data for the bentonite and Spruce bark materials would be sufficient to investigate competition in ternary systems. The set of heavy metal solutions used on the admix materials was the same as that for the Leaching cell samples (Table 3.4.1). This allowed for direct comparisons to be made between the Batch adsorption and Leach cell test results. T A B L E 3.3.1. Batch adsorption test matrix. Materials tested Single system Binary system Ternary system Pb Cu Cd Pb+Cu Pb+Cd Pb+Cu+Cd Bentonite V V Forest soil V V Spruce bark V V V Bentonite admix V V Forest soil admix V Spruce bark admix Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.3 B A T C H ADSORPTION TEST M E T H O D TABLE 3.3.2. Heavy metal solution concentrations used in Batch adsorption tests. 31 Single system Binary system Ternary system Pb, Cu, Cd Pb+Cu Pb+Cd Pb+Cu+Cd mgL-i mgL-i mgL-i mgL-i Materials 0 250+0 250+0 203+203+203 Bentonite Forest soil Spruce bark 50 250+50 250+50 797+203+203 100 250+100 250+100 203+797+203 200 250+250 250+250 797+797+203 500 250+500 250+500 203+203+797 1000 250+1000 250+1000 797+203+797 1000+0 1000+0 203+797+797 1000+50 1000+50 797+797+797 1000+100 1000+100 0+500+500 1000+250 1000+250 1000+500+500 1000+500 1000+500 500+0+500 1000+1000 1000+1000 500+1000+500 500+500+0 500+500+1000 500+500+500 203+500+203 203+203+500 Admixes Bentonite admix Forest soil admix Spruce bark admix 500 500+ 500 500+500+500 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.3 B A T C H ADSORPTION TEST M E T H O D 32 2 types of Batch tests (all done in duplicate) Batch test on admixes - 40 ml ofheav metal solutions: Pb, Cu, Cd. - 4.0 g of admixes: 1. Bentonite admix 2. Forest soil admix 3. Spruce bark admix Batch test on admix materials - 25 ml of heavy metal solutions: Pb, Cu, Cd. - 0.5 g of material: 1. Bentonite 2. Forest soil 3. Spruce bark 50 ml polypropylene centrifuge tube 1. Batch Samples agitated for 24 hrs. 2. Heavy metal concentrations measured before and after agitation. 3. Admixes stored at 4° C to await Selective Sequential Extraction. 4. Heavy metal concentrations used to graph adsorption isotherms. FIGURE 3.3.1. Diagram of the Batch adsorption test. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.3 B A T C H ADSORPTION TEST M E T H O D 3.3.2 Batch adsorption test procedure 33 A l l the materials were tested at their natural water contents (see Table 4.1.1). Prior to the Batch test, the Forest soil, and Spruce bark were mechanically sieved to remove coarse fractions. A t its natural state, the Forest soil tended to stick together i n clusters. To account for this overestimation in particle size, a larger sieve was used for the Forest soil. Thus, an 840 micron sieve was used for the Forest soil, and a 500 micron sieve was used for the Spruce bark. Two soiksolution ratios were used in this study. For the admixes, a 1 g : 10 ml , soiksolution ratio was used as recommended by the E P A (1987). For the individual materials, the soiksolution ratio was lowered to 1:50, because more solution was required to create a bentonite suspension. For the admixes, 4 g (dry weight) of material and 40 ml of heavy metal solution were placed into a 50 ml polypropylene centrifuge test tube. For the individual clay barrier materials, 0.5 g (dry weight) of material and 25 ml of heavy metal solution (bentonite, Forest soil, or Spruce bark) were placed into a 50 ml polypropylene centrifuge test tube. The test tubes were inserted into a mechanical rotator, and rotated for 24 hr. The mechanical rotator was powered by a Dayton Model 4Z134 motor, and set to rotate at approximately 22 rev/minute. After 24 hr., the test tubes were removed from the rotator, and then placed into a centrifuge. After centrifuging the test tubes for 15 min. at a G force of about 2200 in a Beckman GS-6 centrifuge, the final heavy metal concentration of the supernatant was determined using a Video 22 Thermo Jarrell Ash aa/ ae Spectrophotometer - Model 957 (AAS). In addition, the equilibrium p H of the supernatant was measured using an Orion model 1 420A p H meter. The Forest soil and Spruce bark contained fractions that floated even after centrifuging. For such materials, test tube pre-filters were used to remove the floating fractions before the heavy metal concentration and p H determinations. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.3 B A T C H ADSORPTION TEST M E T H O D 34 The concentration ranges measured by the AAS are shown in Table 3.3.3. For heavy metal concentrations outside these ranges, dilution was required. After discarding the supernatant, the Batch samples prepared for SSE were stored in the centrifuge tubes at 4°C . TABLE 3.3.3. Heavy metal concentration ranges measured by the atomic absorption spectrophotometer. Heavy metal Pb Cu Cd Wavelength 283 327 228 Range (mg L 1 ) 0-500 0-100 0-30 Prior to further data analysis, the heavy metal concentrations were converted from mass to moles. The conversion calculations are shown APPENDIX D.l . The conversion of data from mass to moles was necessary, because sorption phenomena is best described in terms the number of molecules, as opposed to the mass of molecules. The atomic weights of Pb, Cu, and Cd, are 207.2 g mob1, 63.55 g mob1, and 112.4 g mob1, respectively. Thus, for equal masses of Pb, Cu, and Cd, the number of Cu moles would be 3.3 times greater than Pb, and 1.8 times greater than Cd. The heavy metal sorption concentration for the sorbent was calculated with the following equation: ^(ci-cfYv q M where q is heavy metal sorption concentration (cmol kg-1), Ci is the initial concentration of solution (cmol L"1), C/is the equilibrium (final) concentration (cmol L-1), V is the volume of the solution (L), and M is the mass of sorbent (kg). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.3 B A T C H ADSORPTION TEST M E T H O D 35 Sorption isotherms were constructed by plotting q (cmol kg-1) vs. the initial heavy metal solution concentration (mmol L" 1). Equilibrium p H graphs were constructed by plotting equilibrium p H vs. initial heavy metal solution concentration (mmol L" 1). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.4 LEACHING CELL TEST M E T H O D 3.4 LEACHING CELL TEST METHOD 36 3.4.1 Leaching cell test program The Leaching cell test was used to find the hydraulic conductivities of the compacted admix samples. In addition, the breakthrough results were used to determine the breakthrough points, retention capacities, and migration behavior of the heavy metals through the compacted admix samples. All tests were done in triplicate to provide contingency, and assess variability. The combinations of admixes and heavy metal solutions tested are shown Table 3.4.1. Only the bentonite admix was used to investigate heavy metal sorption and migration behaviour in ternary systems. Data from the single and binary systems would be sufficient for comparing the performances of the different admixes. Shown in Figure 3.4.1, is a diagram of the Leaching cell test. TABLE 3.4.1. The Leaching cell test matrix. Admix Single Binary Ternary Pb Cu Pb+Cu Pb+Cu+Cd 500 mg L 1 500 mg L 1 500 mg L"1 each 500 mg L 1 each Bentonite admix V V V Forest soil admix Spruce bark admix V V V A list of equipment is shown in APPENDIX C l . Also included are schematics of the compaction hammer, compaction mold, and the Leaching cell. All equipment used were made of materials that are non-reactive with heavy metals. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3 . 4 LEACHING CELL TEST M E T H O D 37 Reservoir Pressure gauge 500 ppm Pb, Cu, Cd Solutions Leaching cell 101 mm dia. x 56.5 mm t Discharge collector Compacted Soil F I G U R E 3.4.1. Diagram of Leaching cell test. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.4 LEACHING CELL TEST M E T H O D 3.4.2 Admix preparation for the Leaching cell test 38 Bentonite admix Each set of admix prepared was enough for about four Leaching cells. Three cells were made for the triplicate Leaching cell test, and the fourth was compacted for water content confirmation. Three thousand five hundred grams of sand was weighed into a plastic container. To achieve a 100:8 sand:bentonite ratio, 280 g (dry mass) of bentonite was measured out. The dry mass was calculated using the natural water content of the bentonite (Table 4.1.1). Because bentonite tends to aggregate when wetted, the sand and bentonite must be thoroughly mixed before adding water. The sand was divided into six parts, and the bentonite was evenly mixed into the six portions. After each portion was individually mixed, they were combined to form three portions. Then the three portions were combined into one large mixture. In order to ensure an even water content and thorough mixing, the sand/bentonite mixture was again divided into smaller portions. The dry sand/bentonite mixture was divided into six portions, and an equal amount of tap water was added to each portion. The portions then were mixed individually; combined to form three portions; and then combined into one. A total of 550 ml of water was added to give the mixture a water content of 14.5%. This water content -which was 2% greater than the optimum water content - was selected to produce consistently low hydraulic conductivities for the admix. The admix was left undisturbed in a 100% humidity room to allow the water content to equilibrate throughout the whole mixture. After one day, the water content was checked again. After re-adjusting the water content to 14.5% (if necessary), the admix was stored in the 100% humidity room for 1 - 3 days before compaction. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.4 LEACHING CELL TEST M E T H O D 39 Forest soil and Spruce bark admixes The Forest soil and Spruce bark admixes contained a 100:7 sand:bentonite ratio. A dry mass of 245 g of bentonite was measured out for 3500 g of sand. The procedure for mixing and wetting the sand and bentonite, was exactly the same as for the bentonite admix. To prevent the Forest soil from drying, it was added after the sand/bentonite mixture was wetted. Add ing Forest soil to a dry sand/bentonite mixture would dry out the Forest soil, and alter its sorption properties. For consistency, the Spruce bark was added the same way as the Forest soil. Before adding the Forest soil or Spruce bark, the wetted sand/bentonite mixture was divided into six portions. A dry weight of 35 g of Forest soil or Spruce bark was measured out, and mixed evenly into the six portions. The dry weights of the Forest soil and Spruce bark were calculated from their natural water contents (Table 4.1.1). Next, the six portions were combined to form three portions; and then into one. The resulting ratio was 100:7:1 of sand:bentonite:Forest soil or Spruce bark. The water content check, and storage specifics were the same as for the bentonite admix. 3.4.3 Compaction procedure N o standardized method exists for rigid-wall Leaching cells; however, the hydraulic conductivity results in Daniel (1995), showed good agreement between the flexible-wall, and rigid-wall Leaching cells. The admix sample was compacted directly into the Leaching cell. Detailed compaction procedures are shown in A P P E N D I X C.2. The compaction procedure was modified from the modified Proctor procedure used in A S T M D1557-91 (ASTM, 1995). Weber (1991), and Cabral (1992) used static compaction because it was able to produce more consistent results; however, dynamic compaction, used in the current study, causes higher remolding of the soil (Mitchell et al., 1965). The higher remolding was expected to negate any inconsistencies from uneven mixing. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.4 LEACHING CELL TEST M E T H O D 3.4.4 Leaching cell test procedure 40 Figure 3.4.1 shows an illustration of the Leaching cell test setup. Prior to starting the Leaching cell test, the reservoir was filled with 5 L of heavy metal solution. This was enough heavy metal solution to permeate nine pore volumes through each of the triplicate samples. Two ports were located at the influent end of the Leaching cell. The center port was where the influent tube was connected. The edge port was used to remove air bubbles from the influent end before the start of permeation. To remove air bubbles, the Leaching cell was turned onto its side, in which the edge port was above the center port. Wi th the edge port open, heavy metal solution was allowed to flow into the Leaching cell. The heavy metal solution filled the influent end of the Leaching cell and flowed out of the edge port. As the solution began to flow out, the edge port was sealed with a cap. This procedure removed most of the air bubbles from the influent end. To begin the Leaching cell test, the pressure in the reservoir tank was increased to 0.5 psi gauge. Every 2 hours, the pressure was increased about 1 psi, until the desired pressure was reached. For most of the tests, the pressure was increased to about 5.2 psi gauge; however, in order to speed up some tests, pressures up to 7 psi gauge were used. These pressures translated to hydraulic gradients between 65 - 88. As the heavy metal solution permeated through the Leaching cell, the time and volume of discharge was noted, periodically. In addition, the discharge was analyzed for heavy metal concentrations, and p H . From these data, graphs of hydraulic conductivity vs. discharge volume, breakthrough concentration vs. discharge volume, and p H vs. discharge volume, were created. The calculations for hydraulic conductivity are found in A P P E N D I X E . l . The tests were terminated when heavy metal breakthrough concentrations attained near equilibrium, or when discharge volumes reached about 1500 m l 8.5 pore volumes). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 41 The purpose of the Selective Sequential Extraction (SSE) is to determine the distribution of metals amongst the various constituents of the soil. Specifically, the SSE determines the distribution of metals amongst five components of the soil: exchangeable, carbonates, Fe and Mn oxides, organic matter, and residual (within the crystal structure of primary and secondary minerals). For the current study, the SSE was used to determine heavy metal distributions within the Leaching cells, and the sorption characteristics of the admixes. SSEs were performed on Leaching cell, and Batch adsorption samples. For the Leaching cell samples, two sampling methods were used. Table 3.5.1 shows the SSE program. A list of important equipment is shown in A P P E N D I X C l . TABLE 3.5.1. The SSE program. Admix Heavy metal solution* Leaching cell samples (4 layers for each cell) Batch test samples Center & edge sampling Composite sampling Bentonite Pb V V Cu Pb+Cu V Pb+Cu+Cd Forest soil Pb Cu V Pb+Cu V Spruce bark Pb V V Cu V V Pb+Cu V * All heavy metal solutions contained 500 mg L 1 of each heavy metal specified. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 3.5.1 Sampling extruded Leaching cell samples 42 After stopping the Leaching cell test, and before extruding the admix sample, the cell was weighed to get a final weight of the sample. The extruded sample was sliced into four, 14 m m layers using a wire saw. Two sampling methods were used on the extruded samples. For most of the extruded samples, two 5 g admix samples were taken from the center and edge regions of each layer for duplicate testing (Figure 3.5.1). For three Leaching cell trials, each layer was thoroughly remolded into uniform mixtures; then two 5 g composite samples were taken from each mixture. The composite samples represented average heavy metal concentrations for each layer. A l l admix samples were placed in air-tight, 50 ml polypropylene centrifuge test tubes, and stored at 4 °C to await SSE. In addition to taking samples for SSE, samples were taken from each layer for water content analysis. The weight of the extruded admix sample, and the water contents, were used to calculate the degree of saturation. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 43 Leaching Cell Sample Extruded Sliced into 4 Layers Plan View *_ SSE performed on samples to determine amount of heavy metals retained by... 1. Cation exchange 2. Carbonate portion 3. Fe/Mn hydroxide portion 4. Organic portion 5. Residual F I G U R E 3.5.1. Diagram of the SSE. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 3.5.2 SSE procedure 44 The SSE was modified from the method used by Yong et al. (1993). The procedure includes the following: 1. Initial rinse 2. Exchangeable cations extraction 3. Carbonates digestion 4. Fe and Mn oxides and hydroxides digestion 5. Organic matter digestion 6. Residual digestion A t the sampling and sample preparation stage, the Batch adsorption (section 3.3.3) and Leaching cell samples were stored in air-tight, 50 ml polypropylene tubes, at 4 °C. The weight of each tube was measured before and after the admix was placed into them. Each sample consisted of 4 - 5 g (equivalent dry weight) of admix, and was submitted to the same SSE procedure. After the SSE, the data was plotted onto sample layer vs. sorbed concentration graphs. Initial Rinse To remove the heavy metals dissolved in the pore water, 8 ml of distilled water was added to the admix sample. The distilled water was not adjusted to the initial p H (4.0) of the heavy metal solutions (Yong et al., 1993), because at such a p H , precipitated heavy metals in the sample may re-dissolve. After mixing the sample in the rotator for 15 min., the sample was centrifuged at a G force of about 2200 for 15 min., and the supernatant was discarded. Subsequent use of the centrifuge employed the same conditions. Considering the large sorption capacities associated with bentonite (see Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 45 sorption results in section 4.2.2), this rinse procedure would sufficiently trivialize the error associated wi th the pre-contaminated pore water. Exchangeable cations extraction For the same reason mentioned earlier, the p H of the reagent, 1 M potassium nitrate (KNO3), was left at 6 - 7. Eight milliliters of 1 M KNO3 was added to the admix sample. After the centrifuge tube was weighed, the mixture was agitated for 1 hour in the rotator, and then centrifuged. The atomic absorption spectrophotometer was used to analyze the heavy metal concentration of the supernatant. After discarding the supernatant, the centrifuge tube was weighed again. Eliminated from this work, was the step of rinsing the admix sample with distilled water after each extraction (Yong et al., 1993). This step was eliminated to prevent additional loss of sample from the decanting process. Weighing the centrifuge tube before and after each extraction kept track of the amount of residual reagent transferred from one extraction to the next step, The amount of heavy metals associated with the residual reagent was subtracted from the next extraction. Carbonates digestion Eight milliliters of 1 M sodium acetate (NaOAc) adjusted to p H 5.0 using acetic acid {HOAc), was added to the sample. After weighing the centrifuge tube, it was agitated for 5 hr in the rotator, and then centrifuged. The atomic absorption spectrophotometer was used to analyzed the supernatant for heavy metals. After discarding the supernatant, the centrifuge tube was weighed again. Fe and Mn oxides and hydroxides digestion Twenty milliliters of 0.04 M hydroxylamine hydrochloride (NH2OH-HCl) in 25% (v/v) HO Ac was added to the sample. The entire mixture was then transferred to a pre-weighed 125 ml glass flask, so that it could be placed in an oven heated to a Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 46 temperature of 96 ± 3 °C. A reflux cap was placed onto the flask to prevent the mixture from drying. The sample was left in the oven for 6 hr, and was agitated occasionally by manually swirling the flask. Next, the flask was allowed to cool at room temperature, and the mixture was transfer back to the original centrifuge tube. The flask, containing some residual sample, was weighed again. After centrifuging the mixture, the supernatant was analyzed for heavy metals, and then decanted. The centrifuge tube was weighed before heavy metal analysis, and after decanting. Organic matter digestion Three milliliters of 0.02 M nitric acid (HN03), and 5 ml of 30% hydrogen peroxide (H2O2) was added to the sample. The 30% H2O2 was adjusted to p H 2 with HNO3 before it was added. The mixture was transferred to the 125 ml flask, and placed in the oven at 85 ± 2 °C. A reflux cap was placed onto the flask to prevent the sample from drying, and the sample was agitated occasionally by manually swirling the flask. After 2 hr, the sample was taken out of the oven, and an additional 3 ml of 30% H2O2 was added to the mixture. The mixture then was placed back into the oven for 3 more hours for further digestion. The mixture was allowed to cool for 15 min. at room temperature, after it was removed from the oven. Then, 5 ml of 3.2 M NH4OAc in 20% (v/v) HNOs was added to the sample, and the mixture was poured back into the centrifuge tube. Approximately 10 ml of distilled water was used to transfer more of the mixture from the flask into the centrifuge tube. Next, the mixture was diluted to the 30 ml mark, and the centrifuge tube was agitated for 0.5 hr in the rotator. During this time, the flask was weighed. Then the centrifuge tube was centrifuged; the heavy metal concentrations were analyzed; and the supernatant was decanted. The centrifuge tube was weighed before heavy metal analysis, and after decantation. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D 47 Residual digestion The rest of the admix sample was digested with HNO3 ( A P H A , A W W A , & WEF, 1995), because the Environmental laboratory in the Department of C i v i l Engineering at U B C was not equipped to handle hydrofluoric acid ( H F ) (Yong et a l , 1993). The HNO3 digestion method does not digest silica sand. Fifteen milliliters of distilled water was used to rinse the admix sample into the flask. Boiling beads, and 5 ml of concentrated HNO3, were added to the flasks. The mixture was brought to a slow boil by heating the flask with a hot plate. After the mixture boiled down to about 20 ml , an addition 5 ml of concentrated HNO3 was added. Reflux caps were placed onto the flasks, and the mixture was boiled for approximately two more hours. Next, with the aid of distilled water, the mixture was transferred back to the centrifuge tubes, and diluted to the 40 ml mark. After centrifuging, the supernatant was analyzed for heavy metals. Instead of determining the volume of the supernatant using mass differential, it simply was estimated at 40 ml . Heavy metal sorptions associated with the residual were low enough to allow for this simplification. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 48 CHAPTER 4 R E S U L T S A N D D I S C U S S I O N 4.1 SOIL M A T E R I A L S The physico-chemical properties are presented in Table 4.1.1. The particle size distribution curves for bentonite, Forest soil, and Spruce bark are shown in Figure 4.1.1. T A B L E 4.1.1. Physico-chemical properties of soil materials. Physico-Chemical Properties Na-Bentonite Forest soil Spruce bark Silica Sand Admix 1 Admix 2 Admix 3 Specific gravity 2.64* n/a n/a n/a 2.67 2.65 2.65 Specific surface (mVR) 462 n/a n/a n/a n/a n/a n/a Liquid limit 146 % n/a n/a n/a 17.2 % 18.3 % 15.0 % Plastic limit 70 % n/a n/a n/a n/a n/a n/a Natural water content 6.8 % 212 % 6.4 % n/a n/a n/a n/a CEC (meq/100 g) 59.7 n/a n/a 0.0 n/a n/a n/a Initial pH (in distilled water) 8.38 4.21 4.34 7.02 n/a n/a n/a Initial pH (in CaCb) 7.61 3.5 4.01 6.45 n/a n/a n/a Max. dry density (kg/m3) n/a n/a n/a n/a 1860 1825 1820 Optimum water content n/a n/a n/a n/a 12.7 % 12.7 % 12.3 % * From Denham, 1999 Note: Admix 1 -100:8 of Sand.Bentonite Admix 2 -100:7:1 of Sand:Bentonite:Forest soil Admix 3 -100:7:1 of Sand:Bentonite:Spruce bark n/a - not analyzed Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.1 SOIL MATERIALS 49 Grain Size Distribution o> 100% 90% 80% 70% 60% 50% 0) 0> 0. t 40% 30% 20% 10% 0% 10 • o 0.1 0.01 Diameter (mm) 0.001 0.0001 - • — S a n d a Bentonite (sieve) o Bentonite (hydrometer) • A- - Forest So i l (Air-dried) - x — Sp ruce Bark F I G U R E 4.1.1. Grain size distribution of clay barrier materials. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 50 4.2 S O R P T I O N C A P A C I T I E S OF C L A Y B A R R I E R M A T E R I A L S D E T E R M I N E D F R O M B A T C H A D S O R P T I O N TESTS Heavy metal sorption capacities were determined for bentonite, Forest soil, and Spruce bark, using the Batch adsorption test. The sorption capacities were used to evaluate the suitability of these materials for clay barriers. In addition, the results were used to develop a sorption model that predicted multi-heavy-metal sorption. Table 4.2.1 summarizes the Batch adsorption test. T A B L E 4.2.1. Summary for Batch adsorption test. Materials Single Binary Ternary Pb, Cu, Cd Pb+Cu Pb+Cd Pb+Cu+Cd Bentonite V V Forest soil V Spruce bark V V V Details of the Batch adsorption test results are shown in A P P E N D I X D.3. The results in the following sections used the averaged values of the duplicate samples. 4.2.1 The multi-heavy-metal sorption model The development of a multi-heavy-metal sorption model is useful for predicting the sorption behavior of different heavy metal systems. For example, a sorption model provides a basis for interpolating and extrapolating data. In addition, a model facilitates the quantitative evaluation of different sorbents. The sorption model developed in this study was able to quantitatively describe competition for multi-heavy-metal systems. The multi-heavy-metal sorption model is based on an existing model for single heavy metal retention. The extension of the single heavy metal retention equation into Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 51 the multi-heavy-metal equation was done empirically based on the Batch adsorption data. A summary of all the equations developed for the single, binary, and ternary retention of heavy metals onto bentonite, Forest soil, and Spruce bark is provided at the end of this section. 4.2.1.1 Isotherm equation selection and general observations The adsorption isotherm (Sparks, 1995) is a common and convenient form used to describe Batch adsorption data. The isotherm is constructed by plotting the sorbed amount of heavy metal versus the equilibrium (or final) solution concentration of heavy metal. The sorbed concentration of heavy metal is calculated using the following equation, q = V(Ci-Cf) ( 4 1 ) m where q is the amount sorbed on the sorbant, in cmol kg- 1, C/ and G are the final and initial solution concentrations, in mmol l i ter 1 , V is the solution volume, in liters, and m is the mass of sorbant, in kilograms. Two equations widely used to describe sorption on soil surfaces are the Freundlich and Langmuir equations. Both equations were originally used to describe gas phase adsorption onto metal surfaces. The assumptions made for their original use are not applicable for sorption onto soil surfaces; therefore, their application for soils can only be considered as empirical (Hinz et al., 1992). For this study, the Freundich equation was chosen because it could be represented as a general form of the Langmuir equation (Sheindorf et al., 1981). A modification was made to the Freundich equation in that the C, was used in place of C/. The modified Freundlich equation is as follows, Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . q = bC? 52 (4.2) where q is the amount sorbed on the sorbant, in cmol kg - 1 , Q is the initial solution concentration, in mmol liter-1, and b and n are curve fitting constants. According to Eqn. 4.1, the use of C, or C/ for curve fitting is equally valid; however, as shown in Figure 4.2.1, the use of C, widens the distribution of data, especially at low solution concentrations. The wider spread reduces the sensitivity of the Freundlich model to experimental error, thus leading to a more accurate fit. a) Isotherm in terms of final Pb concentration. & n E o JC o E n Q . "O 01 .Q k_ o w 1 2 3 4 5 Final [Pb] (mmol/L) b) Isotherm in terms of initial Pb concentration. 20 — 18 2 ra E oi JC "5 E .Q a. •a a> t_ o tn 1 2 3 4 5 Initial [Pb] (mmol/L) Bentonite A Forest soil o Spruce bark F I G U R E 4.2.1. Single heavy metal isotherms plotted in terms of (a) Final Pb solution concentration, and (b) Initial Pb solution concentration. In the Figure 4.2.2, the modified Freundlich equation is applied to single and binary Cu sorption data. Table 4.2.2 shows the b and n values obtained for each set of data from Figure 4.2.2. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 53 T A B L E 4.2.2. Summary of b and n values fitted for single & binary Cu data. Solution type Bentonite Forest soil Spruce bark b n b n b n Cu 3.9706 0.5028 8.4984 0.4876 4.4391 0.4465 Cu w/ 1.15 mmol/L Pb 2.9467 0.4889 5.4463 0.5627 3.3798 0.4197 Cu w/ 4.75 mmol/L Pb 2.4233 0.5058 4.3969 0.5578 2.3186 0.4242 a) Bentonite b) Forest soil c) Spruce bark 0 10 20 0 10 20 0 10 20 initial [Cu] (mmol/L) Initial [Cu] (mmol/L) Initial [Cu] (mmol/L) • Cuon ly A C u w / 1 . 1 5 mmol/L Pb o Cu w/4.75 mmol/L Pb F I G U R E 4.2.2. Freundlich isotherms of Cu sorption in single and binary heavy metal solutions, (a) Bentonite. (b) Forest soil, (c) Spruce bark. The following observations were made from the Cu sorption data: 1. The modified Freundich equation provided a good fit for all sets of single and binary Cu sorption data. 2. The decreasing b values with increasing Pb background concentration were evidence of competition for sorption sites between Cu and Pb. 3. The n values were similar within each sorbent. This indicated that the Cu isotherm was proportionately reduced by the presence of Pb. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS .. 54 The above observations provide a good basis for developing a sorption model for binary heavy metal systems. 4.2.1.2 Modeling binary heavy metal sorption The third observation made in the last section indicated that the presence of Pb caused a percentage change in Cu sorption, independent of the initial Cu concentration. For example, the bentonite results in Table 4.2.2 shows that the addition of 4.75 mmol L _ 1 of Pb into a Cu-only solution caused a 39% decrease in Cu sorption. The 39% decrease was irrespective of whether the initial Cu concentration was 1 mmol L" 1 or 10 mmol Lr 1 (Figure 4.2.2). This is represented mathematically by the following equation: %AqM] -f(CM2) (4.3) where, %AqMi is the percentage change of heavy-metal-1 (Ml) sorption due to the presence of heavy-metal-2 (Ml), Cm is the initial solution concentration of Ml, in mmol liter - 1, and/(CM2) is the competition function which describes the behaviour of %ACJMI in terms of CMI. To determine the competition function, the single and binary sorption data was first converted to %AqMi by the following equation, %Aqm = q M ^ ~ q M \ b x 1 0 0 o / o (44) aM\s where, qMis and qmb are the amount of Ml sorbed in single and binary heavy metal solutions, respectively, in cmol kg- 1. Then, these were used to construct plots of %AqMi Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 55 versus CM2. For each plot, a relationship was found for/(CM2) by using the 'trendline' tool in Microsoft EXCEL. Figures 4.2.3 - 4.2.4 show that the relationships found for /(CM2) could be described as power functions, f(CM2) = aCM2P (4.5) where a and p are constants used to describe the unitless competition function. Combining Eqns. 4.3 and 4.4 results in, aM\b=QM\s^-f{CMl)) (4-6) Substituting Eqn. 4.2 and Eqn. 4.5 into Eqn. 4.6 results in, lMib=bCmn(\-aCM2p) (4.7) where, CMI is the initial Ml concentration, in mmol liter1, and b and n are the Freundlich constants for Ml. Table 4.2.3 shows the binary sorption equations written out in full for Pb+Cu, and Pb+Cd binary systems. Shown in Figure 4.2.5, is the level of fit for each equation by plotting actual values versus calculated values. According to Figure 4.2.5, the calculated values closely matched the Batch adsorption data. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS .. 56 T A B L E 4.2.3. Summary of sorption equations for binary heavy metal solutions. Binary System Sorbed Metal Equation (<JM in units of cmol kg-1, and C M in units of mmol L 1 ) Na-Bentonite in Pb + Cu solution Pb qn = 4.546 CPb 0 7 4 7(1 - 0.0642 C c„ °-5 7 4) Cu qCu = 3.971 Ccu 0 3 0 3 (1 - 0.234 Cn °-292) Na-Bentonite in Pb + Cd solution Pb qPb = 4.546 CPb 0 7 4 7(1 - 0.0167 Ca ) Cd qcd = 2.120 Ccd 0 7 6 0 (1 - 0.300 CPb °-326) Forest soil in Pb + Cu solution Pb qPb = 4.829 Cpb 0 8 7 3(1 - 0.0429 Co, a 7 7 2) Cu qcu = 8.498 C c 0 4 8 8(1 - 0.248 CPb 0305) Forest soil in Pb + Cd solution Pb qPb = 4.829 Cpb 0 8 7 3(1 - 0.0167 Cat a693) Cd qcd = 3.238 Cat 0 7 1 6 (1 - 0.289 Cn °-504) Spruce bark in Pb + Cu solution Pb qn = 4.971 Cn 0680(1 - 0.0896 CCu °-688) Cu qa. = 4.439 Cc„0447(1 - 0.216 Cn °-491) Spruce bark in Pb + Cd solution Pb qn = 4.971 Cn 0 7 1 6(1 - 0.0122 Cat) Cd qcd = 1.970 C a 0 7 0 6 (1 - 0.340 Cn a564) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 57 (%) uoudjos qd uj aBueqo CQ D u CM CO u o MH « Dai U GH 3^ o o CT (< to O for «s Da) 3 CH 100% ( *j C o Benl for « Dai U -e o o o E E, !o o (%) uoijdjos qd "! eBueqo o E e TO o %) uojtdjos qd u| 86ueno it) c o _i entral mmol; o IO c c--Co •<* O c o ' ~ _i Sol imo E D_ to T— ro c o E E. *5 o (%) uojidjog qd Uj sBueqo O O O O O O O O O C D C O r ^ C D W T C O C s l T -(%) uoudjos qd "! sBueqo O • IH & o I/I BH H - l u at <S 3 <*H V a* 5 a CH 0) W J oi u i £ ° 5 « «> 2 H O O to ra H - l « a o PH £ CO s : ca ^ CN D O i—t UH Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 58 a U 'rT m o> x ffi*C m \ CD \ •<- \ CNl \ L O \ II \ >. 1 I u 4m a o E E, .s '•5 c o ^—s (%) uoijdjos no ui aBuego o E E "B Q-^ (%) uojjdjos no UJ aBueqo o E E o E E i^ 00 1^  o o E E i*-o E E o oo d • v 2 a , o MH rs rs Q 08 T S U 1/5 j-> (fl 0) »H o UH u o rs rs Q •s ft. T S U e o c 0) P9 U l O f« 4 H Q <*) TS u CN 3 d X CO o> CO CO d \ o ,—, ro o w c (%) uojidjos PO u.i aBueno o E E, S" ft To 'E (%) uoijdjos PO u| a6uei)o CD CN CO H • d ' I II \ >. 1 1 — o o o m i>-' 0-'-5 _i "5 E E o CO ob • _j o E (0 E c m o M-CO •«* I— c o ce _ l Con moi c E g CM ZJ CM o CM CO T3 _ l O o nitia mm CD CO d < _ J o E E •sr d • c o • i H u o tn TS U a U <» j-> u 01 MH ia ut rs (%) uoijdjos no u| s6uego (%) uojtdjos PO u ! aBueuo M H 0» o a w> n T OJ OJ w--B ^ $ o O C/5 00 aj s to o ^ H H 73 1/1 . .3 « rt '—' T3 . - « ° 2 " H S &, *; ui C o OJ <» PQ c • pa S fN W D (J P H Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 59 (6>|/|oiuo) PO poqjos 3|B0 »"*H M fin » 01 (6>|/|0UJD) qd peqjos o\eo n o a o •43 & O CO S U a U + fin + '3 o s 01 pa CO io A . T— \ o sk» + O T T ^ ^ ° T. CO II 1 CD <M 1 O) QI cl li >. i o E o •o o . O o CO (6>(/|OUJ0) no peqjos - 0 | B O (6>(/|OUIO) qd peqjos "0|eo (6>|/|omo) PO poqjos "0|Bo s o I' o cn B- I "55 o CM o> UI cu o yst . LO (cm Co s SB o \ . o Pb u + CO \ O II \ irbed ^ CC irbed OH n - to CO + en - o 3 res 3 LO O CO c < CM T - T -(6>i/|oiuo) qd peqjos OIBQ (6>|/|OUJO) no peqjos "0|eo (6)(/|oiuo) qd peqjos '0|eo (6>(/|Oiuo) PO peqjos -0|eo (6>|/|0iuo) qd peqjos OIBQ (6>|/|OUJO) no peqjos "0|eo C O •43 OH K O cn •OH 3 cu cn Bf a u + + PQ cu u 2 OH cn C \ j \ CO, d s\ X CO o V r>-p II o E o o. 0. "O o LO € o CO (6>|/|oiuo) qd paqjos "0|eo cn e o o co r c c o • IH o a •g 2 g OH « CD u 7 o co > o co CO cu IH O PH fS HH H5 • w cu rt '—' CO CO .tn II 13 « CJ cj est U PH Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 4.2.1.3 Model ing ternary heavy metal sorption 60 In section 4.2.1.2, a model containing a competition function was developed for binary heavy metal sorption. The important next step would be to test the validity of the model for ternary heavy metal sorption. Eqn. 4.3 in section 4.2.1.2 is modified accordingly for application in ternary systems, %Aqm = f(CM2,CM3) x 100% (4.8) where, %AqMi is the percentage change of heavy-metal-1 (Ml) sorption due to the presence of heavy-metal-2 (Ml) and heavy-metal-3 (M3), CM2 and CMS are the initial solution concentrations of Ml and M 3 , in mmol l i ter 1 , and /(CM2) is a function of CM2 which describes the behaviour of %AqMi in terms of the initial solution concentrations of Ml and M3 . If the competition functions developed from the binary systems are assumed to be independent of any other heavy metals in the system, then CM2 and CMS within the ternary competition function could be separated; thus, Eqn. 4.4 is modified for ternary systems as, = qmb(mf*\~"MU >< 100% = f(CM3) x 100% (4.9) qmb(M\,M2) where, qMib(Ml,Ml) is the amount Ml sorbed in binary heavy metal solutions containing Ml and Ml, in cmol kg- 1, qMit is the amount Ml sorbed in ternary heavy metal solutions, in cmol kg- 1, and f(CMS) is a competition term that reflects the influence of CMS on Ml sorption. After substitution with Eqn. 4.6, and isolating qMu, Eqn. 4.9 becomes, 9mt =°M\s*[iy-f(CMi)-f(CM2)(\-f(CM))] (4.10) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS .. 61 Table 4.2.3, in section 4.2.1.2, contains the competition functions necessary for calculating Pb sorption in ternary systems. Comparisons of the calculated Pb sorption data versus experimental data for bentonite and Spruce bark are shown in Figure 4.2.6. The plots in Figure 4.2.6 indicate a high correlation between calculated and experimental data. Because binary data was not available for Cu+Cd systems, Table 4.2.3 does not contain the necessary competition functions to form ternary equations for Cu and Cd sorption. However, the ternary Batch adsorption data in conjunction with the available binary data could be used to find the missing competition functions by following Eqn. 4.9. Shown in Figure 4.2.7, are the competition functions solved from the ternary data for Bentonite and Spruce bark. With the competition functions from Figure 4.2.7, another comparison of calculated versus experimental values for Cu and Cd sorption is shown in Figure 4.2.8. Table 4.2.4 shows the complete set of equations for heavy metal sorption in ternary solutions. T A B L E 4.2.4. Summary of sorption equations for ternary heavy metal solutions. Material Sorbed Metal Equation (<JM in units of cmol kg-1, and CM in units of mmol L"1) Bentonite Pb qn = 4.546 CPb 0 7 4 7 ((1 - 0.0167 C « ) - (0.0642 Co, 0 5 7 4 (1 - 0.0167 Co,))) Cu qCu = 3.971 C c °- 5 0 3((1 - 0.234 Cn 0 2 9 2) - (0.0106Cc (1 - 0.234 CPb °-292))) Cd qcd = 2.120 Ccd a 7 6 0 ( ( l - 0.300 Cn 0 3 2 6) - (0 .0804C C „ 0 6 4 6 (1 - 0.300 CPb °-326))) Forest soil Pb qPh = 4.829 CPb 0 8 7 3((1 - 0.0167 Ccd 0 6 9 3 ) - (0.0429 C c 0 7 7 2 (1 - 0.0167 Ccd 0693))) Cu (insufficient data) Cd (insufficient data) Spruce bark Pb qPh = 4.971 Cpb a 6 8 0 ( ( l - 0.0122 C c d ) - (0.0896 C c 0 6 8 8 (1 - 0.0122 Ccd))) Cu qCu = 4.439 C c 0 4 4 7 ((1 - 0.216 CPb om) - (0.0106Ccd (1 - 0.216 CPb 0491))) Cd qcd = 1.970 Ccd 0 7 0 6((1 - 0.340 CPb °-5 6 4) - (0.0804CQ,0646(1 - 0.340 Cn 0564))) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 62 F I G U R E 4.2.6. Calculated versus actual values for Pb sorption in ternary solutions, (a) Bentonite. (b) Spruce bark. a) Effect of Cd on Cu Sorption for Bentonite b) Effect of Cu on Cd Sorption for Bentonite 20% O ^ 10% a> o 0% C Q. JS o -10% -20% y=0.0106x * • Fc2 = 02433__A__. (I <>2 4* I I 6 8 1 - — — 60% •a ~ 50% " S 40% ' i o 30% ^ c ' | 20% P £ ° 10% o CO 1 0 / 0 0% Initial [Cd] (mmol/L) 5 10 15 Initial [Cu] (mmol/L) c) Effect of Cd on Cu Sorption for Spruce B. Initial [Cd] (mmol/L) d) Effect of Cu on Cd Sorption for Spruce B. 160% -, Initial [Cu] (mmol/L) F I G U R E 4.2.7. Ternary retention data showing how Cu and Cd change each others' sorption capacities, (a - b) Bentonite. (c - d) Spruce bark. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 63 a) Cu sorption for Bentonite ternary system CO O 5 10 Actual Sorbed Cu (cmol/kg) b) Cd sorption for Bentonite ternary system 6 •D o o |5 4 o o o W E o • y = 0.9511x • R2 = 0.8672 •Billll...-. 1— 2 4 Actual Sorbed Cd (cmol/kg) b) C M sorption for Spruce B. ternary system c) Cd sorption for Spruce B. ternary system Actual Sorbed Cu (cmol/kg) Actual Sorbed Cd (cmol/kg) F I G U R E 4.2.8. Calculated versus actual values for Cu and Cd sorption in ternary solutions, (a - b) Bentonite. (c - d) Spruce bark. 4.2.1.4 Summary of sorption equations Equation 4.6 describes sorption in binary heavy metal systems: <lM\b=<lM\s(y-fm(.CM2)) (4-6) Equation 4.10, which describes sorption in ternary heavy metal systems, is rewritten as, Q-fm(CM2)-fm ( C M , ) + fm ( C M 1 )fm (CM )) (4.11) where C\MIS, c\Mib, and qmi are the amounts of Ml sorbed in single, binary, and ternary solutions, in units of cmol k g - 1 , / ^ (CMI), a n d / M I (CMI), are unitless competition Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 64 functions for Ml and M3, on Ml sorption, and CM2 and CM3 are initial solution concentrations for Ml and Ml, in units of mmol I A Table 4.2.5 summarizes Pb, Cu, and Cd sorption in single, binary, and ternary solutions for bentonite, Forest soil, and Spruce bark. T A B L E 4.2.5. Single Pb, Cu, and Cd sorption equations and their competition functions. Material Sorbed Metal Sorption equation in single metal solutions (in cmol kg-1) Competition function (unitless) Pb Cu Cd Bentonite Pb qPb = 4.546 CPb 0 7 4 7 n/ a 0.0642 C C u 0 5 7 4 * 0.0167 Ccrf ** Cu qCu = 3.971 Co, °-503 0.234 Cpb 0 2 9 2 * n/a 0.0106Ca * Cd qa = 2.120 Ca 0 7 6 0 0.300 Cpb 0326* 0.0804Cc„ a 6 4 6** n/a Forest soil Pb qPb = 4.829 Cpb 0 8 7 3 n/a 0.0429 C C u 0 7 7 2 * 0.0167 C a 0 6 9 3 * Cu qCu = 8.498 CCu 0 4 8 8 0.248 Cpb 0305* n/a -Cd qcd = 3.238 Ca 0 7 1 6 0.289 Cpb °-504* - n/a Spruce bark Pb qPb = 4.971 Cpb °-680 n/a 0.0896 C C u 0 6 8 8 * 0.0122 Co; * Cu qCu = 4.439 Ca 0 M 7 0.216 CPb °-491* n/ a 0.0106CCrf ** Cd qa = 1-970 Ca 0 7 0 6 0.340 Cpf, 0 5 6 4* 0.0804CC„0 6 4 6 ** n/a n/a - not applicable * Solved from binary data ** Solved from ternary data Notes: 1. Sorption equations for binary and ternary solutions shown within this section. 2. C M in units of mmol liter1. 4.2.2 Heavy metal sorption capacities The heavy metal sorption capacities of the clay barrier materials are shown in Figure 4.2.9. In Figure 4.2.9, the isotherms are grouped according to clay barrier material, and heavy metal type. The equations for the isotherms in Figure 4.2.9 are found in Table 4.2.5. Summarized in Table 4.2.6, are the relative sorption capacities of the soil materials, and the sorption orders of the heavy metals. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS .. 65 a) Pb solutions b) Cu solutions c) Cd solutions 0 2 4 6 8 10 " 0 2 4 6 8 10 " 0 2 4 6 8 10 Initial [Pb] (m m ol/L) Initial [Cu] (m m ol/L) Initial [Cd] (m m ol/L) o Bentonite A Forest Soil o Spruce Bark d) Bentonite e) Forest soil f) Spruce bark 0 2 4 6 8 10 0 2 4 6 8 10 0 2 4 6 8 10 Initial [Metal] (mmol/L) Initial [Metal] (mmol/L) Initial [Metal] (mmol/L) • Pb x Cu o Cd F I G U R E 4.2.9. Heavy metal retention capacities of soil mix materials in single metal solutions, (a-c) Grouped according to heavy metal, (d-f) Grouped according to soil mix material. T A B L E 4.2.6. Summary of relative heavy metal sorption capacities. Ranking Pb sorption capacity Forest soil > Bentonite « Spruce bark Cu sorption capacity Forest soil > Bentonite » Spruce bark Cd sorption capacity Forest soil > Bentonite > Spruce bark Sorption onto Bentonite Pb>Cu> Cd Sorption onto Forest soil Cu>Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) Sorption onto Spruce bark Pb>Cu> Cd Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 4.2.2.1 Ranking of materials 66 The data shows that for all three heavy metals, Forest soil possesses the highest sorption capacity, while bentonite and Spruce bark are approximately equal. These results could be explained by the retention characteristics of each material. Forest soil, composed almost entirely of soil organic matter, relies on its surface functional groups to retain heavy metals by way of cation exchange and complexation. These retention mechanisms are enhanced by a high specific surface area ranging of up to 800-900 m 2 g-1 (Sparks, 1995). Although bentonite also possesses high C E C due to isomorphous substitution, its C E C is significantly lower than that of soil organic matter (Sparks, 1995). In addition to cation exchange, precipitation is also associated to bentonite, provided that the equilibrium p H is greater than 5 (Phadungchewit, 1989). Figure 4.2.10 shows that the equilibrium solution pHs for bentonite ranged between 5 - 7.5, signifying the likely occurrence of precipitation. The main reason why bentonite sorbed less than Forest soil, is because bentonite's specific surface area (462 m 2 g-1; from Table 4.1.1) is smaller than typical specific surface areas of Forest soil (800-900 m 2 g - 1 ; from Sparks, 1995). Even assuming that bentonite's combination of precipitation plus C E C could match the Forest soil's combination of complexation plus C E C , Forest soil simply has more area available for sorption. As for Spruce bark, its sorptive ability is attributed to the surface functional groups associated with tannin compounds (Vazquez et al., 1994, Gloaguen & Morvan, 1997). The main sorptive functional groups in tannins are carboxyl and phenolic. As mentioned earlier, Forest soil also relies on surface functional groups; however, these functional groups are associated with humic substances (Sparks, 1995). In addition to carboxlyl and phenolic, humic substances possess many other functional groups useful for heavy metal retention. As an indication of sorption site availability, Spruce bark is composed of 5 - 37 % weight tannins (Field et al., 1988), while soil organic matter is composed of 33 - 75% weight humic substances (Sparks, 1995). According to this rough Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 67 indication, per unit weight, Forest soil contains more surface functional groups than Spruce bark. a) Bentonite 0 2 4 6 8 10 Initial [Metal] (mg/L) b) Forest soil 4.5 I Initial solution pH 0 2 4 6 8 10 Initial [Metal] (mg/L) | P b x Cu o Cd c) Spruce bark 4.5 I Initial solution pH 3 2.5 0 2 4 6 8 10 Initial [Metal] (mg/L) F I G U R E 4.2.10. Final pH graphs showing the influnce of Pb, Cu, and Cd on the final solution pHs of each suspension, (a) Bentonite. (b) Forest soil, (c) Spruce bark. 4.2.2.2 Ranking of heavy metals The order of sorption capacity for bentonite and Spruce bark is Pb> Cu> Cd, while for Forest soil, the order is Cu> Pb> Cd. These orders are only for the range of concentrations tested. The isotherms shown in Figure 4.2.9.d - f, show that within the tested range, are crossover points between Pb and Cu. For bentonite and Spruce bark, the isotherms cross over at very low initial metal concentrations, while for Forest soil, the isotherms cross over at a high concentration (4 mmol L _ 1 ) . In addition, if the isotherms are extrapolated beyond the tested range, the Cu and Cd isotherms also are expected to cross over. Therefore, even though overall orders of sorption capacity are presented, the crossing over of isotherms indicates that the sorption capacity orders are dependent on the concentration range of the heavy metal solutions tested. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 68 The results are explained by comparing the reaction characteristics of each heavy metal and how they relate to the three main heavy retention mechanisms: cation exchange, surface complexation, and precipitation. Table 4.2.7 shows the ionic radii, the 1st and 2nd hydrolysis products, and the OH solubility constants for Pb, Cu, and Cd. T A B L E 4.2.7. Characteristics of Pb, Cu, & Cd. Pb Cu Cd Ca Ionic radii 120 pm* 70 pm** 97 pm* 99 pm* 1st hydrolysis constant*** 7.7 7.7 10.1 12.7 2nd hydrolysis constant*** 17.75 13.78 20.3 27.99 OH" solubility constant*** 8.16 8.68 13.65 22.8 * Fyfe, 1964 ** McQuarrie & Rock, 1991 *** Lindsay, 1979 Cation exchange, is described as the nonspecific adsorption of positively charged hydrated ions (Evans, 1989). According to Coulombs' law, the energy attraction of two ions is proportional to the product of their charges and inversely proportional to the distance between the two centers. Since Pb, Cu, and Cd possess the same charge (+2), the adsorption capacity of these cations can be explained by differences in their hydrated radii. Cations with smaller hydrated radii would be able to pack closer, and take advantage of the stronger attraction energy of being closer to the sorbent. Since the hydrated radii of cations are inversely related to their ionic radii, the order of sorption capacity would be Pb > Cd> Cu. To estimate the importance of complexation, one could examine hydrolysis reactions. The general tendency for a metal to complex can be seen by its degree of hydrolysis. The use of hydrolysis products also are useful because surface complexation on minerals and organic matter often involves the OH group. Thus according to the 1st and 2nd hydrolysis products, the order of sorption would be Cu>Pb> Cd. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 69 Finally, to estimate the importance of precipitation, one could examine hydroxide (OHr) solubility products. According to hydroxide (OH) solubility products, the order of precipitation would be Pb> Cu> Cd. The dominant sorption mechanisms for each material was presented in section 4.2.2.1. For bentonite, cation exchange and precipitation were expected to dominate. According to hydrated radii, hydrolysis products, and OH- solubility products (Table 4.2.7), Pb sorption was predicted to be the greatest. In regards to Cu and Cd, cation exchange and precipitation provided opposite predictions. The Batch test results show that the actual ranking is Pb> Cu> Cd. This suggests that for bentonite, precipitation dominates over cation exchange. Since for bentonite, sensitivity to declining p H is much higher for precipitation than cation exchange, the p H results in Figure 4.10.a, supports the presented hypothesis. For Forest soil, cation exchange and surface complexation were expected to dominate. The Batch adsorption results show that below initial heavy metal concentrations of 4 mmol IA, the ranking is Cu> Pb> Cd, and above concentrations of 4 mmol I A the ranking becomes Pb> Cu> Cd. To harmonize the predictions in Table 4.2.7, with the tested results, surface complexation must be considered dominant at low metal concentrations. A s the solution metal concentrations rise, and complexing sites start to fi l l up, cation exchange becomes more dominant. The cross-over point between the Pb and Cu isotherms in Figure 4.2.9.e, indicates the point at which cation exchange dominates over complexation. Since Spruce bark also relies on cation exchange and surface complexation for heavy metal sorption, one would expect its order of sorption capacity to be the same as the Forest soil's; however, the results in Table 4.2.6 appear to show that the ranking is Pb> Cu> Cd, throughout the entire range. This discrepancy is resolved by pointing out that Forest soil probably has many more complexing sites than Spruce bark. This suggests that cation exchange would begin to dominate at much lower concentrations. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 70 The Spruce bark isotherm in Figure 4.2.9.f, show that the Pb and Cu isotherms crossed at a very low initial concentration ( « 1 mmol L" 1). Within this section, several reasonable, but speculative explanations were provided to harmonize the predictions in Table 4.2.7 with actual results in Table 4.2.6. In section 4.4.3.1, more insights on retention mechanisms w i l l be presented. These insights wi l l support the explanations presented in this section. 4.2.3 Heavy metal selectivity and competition Heavy metal selectivity is determined by placing the sorbent into a solution containing equal concentrations of each heavy metal. The order of selectivity would be based on the amounts of each heavy metal sorbed. Using this approach, the heavy metal selectivities are shown in Figure 4.2.11. The graphs in Figure 4.2.11 were plotted using the equations in section 4.2.1.4. The concern regarding selectivity graphs is that they are misleading in showing heavy metal sorption competition. For example, Figure 4.2.11.a seems to clearly show that Pb out-competes Cd for sorption sites. However, the individual sorption isotherms in Figure 4.2.9.d show that even in separate non-competitive environments, Pb sorption is higher than Cd sorption. In order to identify competition, the selectivity isotherms would need to be compared to the individual sorption isotherms. If the selectivity graphs in Figure 4.2.11 were proportional to the sorption capacity graphs in Figure 4.2.9, then one could conclude that competition amongst the three heavy metals was equal. However, the graphs in Figure 4.2.11 and 4.2.9, show that some heavy metals were more competitive than others. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ., 71 a) Bentonite (Ternary system). 12 0 1 2 3 4 5 Initial [of each metal] (mmol/L) b) Spruce bark (Ternary systerm). 12 -, 0 1 2 3 4 5 Initial [of each metal] (mmol/L) c) Forest soil (Pb +Cu binary system). 0 1 2 3 4 5 Initial [of each metal] (mmol/L) d) Forest soil (Pb+Cd binary system). 0 1 2 3 4 5 Initial [of each metal] (mmol/L) Pb — i — C u Cd F I G U R E 4.2.11. Selectivity of heavy metals in ternary and binary systems. (a) Bentonite. (b) Spruce bark, (c - d) Forest soil (binary systems). The previous discussion demonstrated that selectivity graphs, alone, were insufficient in identifying competition. Competition is shown more effectively by examining the competition functions associated with each sorbent. The competition functions in Table 4.2.5 were rearranged in Table 4.2.8 to show the order of heavy metal competition for each barrier material. Within the tested range, the order of heavy metal competition for all materials is Pb> Cu> Cd. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 72 T A B L E 4.2.8. Summary of competition amongst Pb, Cu, and Cd. Material Type of sorption Competition functions (unitless) more competitive less competitive Bentonite Pb sorption 0.0642 C o , 0 5 7 4 > 0.0167 Ca Cu sorption 0.234 Cn 0 2 9 2 > 0.0106Caf Cd sorption 0.300 CPb 0 3 2 6 > 0.0804Cc« 0 6 4 6 Forest Pb sorption 0.0429 CCu 0 7 7 2 > 0.0167 Ca 0 6 9 3 soil Cu sorption 0.248 CPb 0 3 0 5 Cd sorption 0.289 CPb °-504 ? Spruce Pb sorption 0.0896 CCu 0 688 > 0.0122 Cat bark Cu sorption 0.216 CPb 0 4 9 1 > 0.0106CCrf Cd sorption 0.340 Cpb0564 > 0.0804Cc„ a 6 4 6 4.2.4 Sorption performance of clay barrier materials based on Batch adsorption tests Based solely on heavy metal retention capacity, Forest soil and Spruce bark, both compare favorably to bentonite under most of the experimented conditions . The single heavy metal sorption isotherms in Figure 4.2.9.a-c, show that Forest soil has the highest sorption capacity for all three heavy metals. In fact, Forest soil's sorption capacity for Cu is twice as large as bentonite's and Spruce bark's capacity. As for Spruce bark, its sorption capacity for Pb and Cu is almost identical to that of bentonite. A t higher Cd concentrations (> 4 mmol /L) , the sorption capacity of Spruce bark is approximately 20 % less than bentonite. In binary and ternary heavy metal solutions (Figure 4.2.11), the three barrier materials rank similar to that in single heavy metal solutions. The only exception was with Cd. Because Cd sorption by Forest soil and Spruce bark was greatly inhibited by the presence of Pb and Cu, bentonite moved up to the top ranking when Pb and Cu were present in significant concentrations. Cd sorption was inhibited so greatly for Spruce bark, that its isotherm developed a negative slope at higher concentrations. Forest soil and Spruce bark have a distinct advantage over bentonite in terms of retention strength. Although all three clay barrier materials rely on cation exchange, Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS . 73 Forest soil and Spruce bark also rely significantly on surface complexation. Heavy metals bound by complexation are not displaced as easily as heavy metals bound by cation exchange. In addition, because the migration of heavy metals is usually within an acidic medium, the bentonite's reliance on precipitation is of concern. Once the neutralizing ability of the bentonite is spent, the precipitated heavy metals would re-solubilize. O n the hand, complexation onto Forest soil and Spruce bark is still effective at low pHs (Figure 4.2.10). A potential disadvantage for Forest soil and Spruce bark is in how they would effect the mobility of heavy metals that remain in solution. Fractions of soil organic matter (Sparks, 1995) and tannins (Haygreen & Bowyer, 1996) dissolve in water. These fractions may strengthen the solubility of the dissolved heavy metals by forming soluble complexes (Evans, 1989; Livens, 1991). Further studies are required to quantify the extent of this phenomenon. 4.2.5 Summary of Batch adsorption test results 1. A n empirical model based on the Freundlich equation was developed for the sorption of Pb, Cu, and Cd, onto bentonite, Forest soil, and Spruce bark. This model was capable of predicting single, binary, and ternary heavy metal systems. See Table 4.2.5 for the full set of equations. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS ... 74 2. The sorption capacity rankings of heavy metals and barrier materials are as follows: Ranking Pb sorption capacity Forest soil > Bentonite « Spruce bark Cu sorption capacity Forest soil > Bentonite « Spruce bark Cd sorption capacity Forest soil > Bentonite > Spruce bark Sorption onto Bentonite Pb>Cu> Cd Sorption onto Forest soil Cu> Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) Sorption onto Spruce bark Pb>Cu> Cd 3. The order of selectivity for Pb, Cu, and Cd is similar to the order of sorption capacities. Thus, competition amongst heavy metals cannot be directly observed from the order of selectivity. 4. Competition amongst heavy metals was described by the competition functions incorporated in the sorption model. According to the competition functions, the order of competition related all materials tested is Pb> Cu> Cd. 5. The Pb, Cu, and Cd sorption capacities of Forest soil and Spruce bark compared favorably to bentonite under most experimental conditions. The exception occurred with Cd sorption in competitive environments. The Cd sorption capacities of Forest soil and Spruce bark were low in comparison to bentonite when significant concentrations of Cu and Pb were present. Despite this exception, the sorption performance of Forest soil and Spruce bark was sufficient to incorporate them into Leaching cell testing. The Leaching cell test w i l l determine the sorption and hydraulic conductivity effects of adding Forest soil and Spruce bark into a typical clay barrier mix. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 4.3 T H E L E A C H I N G C E L L TEST 75 Leaching cell tests were used to investigate the heavy metal compatibility of clay barriers, and the migration behavior of the heavy metals. The Leaching cell tests generated hydraulic conductivity, retention capacity, and heavy metal breakthrough data for evaluating the performance of the three admixes. The bentonite, Forest soil, and Spruce bark admixes were permeated with single and binary solutions of Pb, and Cu. These results would be sufficient for comparing the different admixes. Only the bentonite admix was permeated with a ternary solution of Pb, Cu, and Cd, to investigate heavy metal migration in a ternary system. Each heavy metal contained in the leachate solutions was present at concentrations of 500 mg L"1. Converted to molar values, the Pb concentration was 2.41 mmol L"1; the Cu concentration, 7.87 mmol L 1 ; and the Cd concentration, 4.45 mmol L"1. To maintain similar ionic strengths, all leachate solutions including the blanks, also contained 0.01 M Ca(N03)i. The testing matrix is summarized in Table 4.3.1, and detailed Leaching test results are shown in A P P E N D I X E.3. T A B L E 4.3.1. Testing matrix for the Leaching cell test. Admix Leachate (500 mg L 1 for each metal) Pb Cu Pb+Cu Pb+Cu+Cd Bentonite (100:8 of Sand:Bentonite) V Forest soil (100:7:1 of Sand:Bentonite:Forest soil) V V Spruce bark (100:7:1 of Sand:Bentonite:Spruce bark) V V A l l the Leaching cell tests were done in triplicate to increase the reliability and gauge the variability of the results. The data analysis, and averaging of the Leaching test triplicate results are shown in A P P E N D I X E . l . A Leaching cell test was terminated when discharge heavy metal concentrations reached near equil ibrium after breakthrough. A l l of the heavy metal breakthrough concentrations in the current study Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 76 attained this state before discharge volumes reached 1500 ml . Table 4.3.2 shows some physical properties of the Leaching cell samples, as well as the number of test failures. A failed test was identified by high hydraulic conductivities at the start of permeation. This signified side-wall leakage. The high number of test failures is attributed to improper sample handling. Over-handling of the Leaching cell after the compaction procedure may have disturbed the admix sample while it was in the Leaching cell. Movement of the admix sample within the Leaching cell would increase the possibility of side-wall leakage. A l l of the hydraulic conductivity data up to a discharge volume of 1500 ml (section 4.3.2) were shown in Figures 4.3.1 - 4.3.4. The averaged hydraulic conductivity data is grouped according to admix type in Figure 4.3.5, and grouped according to leachate type in Figure 4.3.6 (section 4.3.1). Figures 4.3.8 - 4.3.10, present all the breakthrough data up to 1500 ml of discharge, and Figures 4.3.11 - 4.3.12, presents the averaged heavy metal breakthrough curves (section 4.3.2). Shown in Figure 4.3.15 is the discharge p H data (section 4.3.3). Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 77 T A B L E 4.3.2. Physical properties of Leaching cell samples. Permeant Triplicate Initial water Initial dry density Initial Final saturation # content (kg/m3) saturation Bentonite Blank 1 14.5% 1800.1 80% admix Blank 2 14.5% 1800.1 80% Blank 3 14.5% 1812.8 82% Pb 1 14.9% 1793.5 81% Pb 2 14.9% 1826.9 86% Pb X Cd 1 14.6% 1828.5 85% Cd X Cd X Pb+Cu 1 14.9% 1797.9 82% Pb+Cu X Pb+Cu X Pb+Cu+Cd 1 14.6% 1804.1 81% Pb+Cu+Cd 2 14.6% 1806.2 81% 89% Pb+Cu+Cd X Forest Blank 1 14.8% 1814.9 85% soil Blank X admix Blank X Pb 1 15.3% 1784.4 84% Pb 2 15.3% 1783.5 83% Pb 3 15.3% 1786.9 84% Cu 1 14.3% 1799.3 80% 88% Cu 2 14.3% 1810.6 82% 96% Cu X Pb+Cu 1 14.5% 1803.0 82% 88% Pb+Cu 2 14.5% 1800.5 81% 90% Pb+Cu 3 14.5% 1789.1 80% 88% Spruce Blank 1 14.0% 1779.8 76% bark Blank 2 14.0% 1765.7 74% admix Blank X Pb 1 15.0% 1767.1 80% Pb 2 15.0% 1777.3 81% Pb X Cu 1 14.8% 1757.5 77% Cu 2 14.8% 1789.2 82% Cu 3 14.8% 1791.1 82% Pb+Cu 1 15.5% 1750.7 80% Pb+Cu 2 15.5% 1741.3 79% Pb+Cu 3 15.5% 1745.7 79% x - failed tests Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 T H E LEACHING CELL TEST 78 4.3.1 Hydraulic conductivity results The main interests of this section are in determining whether Pb, Cu, and Cd, negatively affect the hydraulic conductivity of clay barriers, and the nature and extent of the negative effects. 4.3.1.1 General observations The hydraulic conductivity curves in Figures 4.3.2 - 4.3.5, show that all heavy metal permeated samples behaved similarly. Most samples made from bentonite and Spruce bark admixes started at low hydraulic conductivity values, but after discharge volumes of about 100 - 200 ml («1 pore volume), the hydraulic conductivities increased rapidly. After the short period of rapid increase, the hydraulic conductivity values quickly approached almost constant values. Relative to the other admixes, samples made from the Forest soil admix started at higher hydraulic conductivities, but after a general decline for about 200 ml of discharge, the Forest soil samples experienced the same increase and leveling off as the other admix samples. A l l samples that were permeated with blank solutions of 0.01 M Ca(N03)2, maintained very low hydraulic conductivities for the duration of the tests. To facilitate the comparison of results, the triplicate hydraulic conductivity data seen in Figures 4.3.2 - 4.3.5, were averaged and grouped together in Figures 4.3.6 and 4.3.7. Specific hydraulic conductivity values were taken from these and summarized in Table 4.3.3. Cabral's (1992) results did not show the same, large hydraulic conductivity increases as in the current study. The reason for the discrepancy is likely because Cabral (1992) applied large confining pressures (60 - 370 kPa) to his samples. The confining pressures may have partially collapsed the widened pore channels caused by flocculation. The confining pressures used by Cabral (1992) would be representative of landfills that have already received several lifts of waste. In actual conditions, exposure Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 79 to contaminated leachate may occur earlier, at much lower confining pressures. For example, one 3 m lift of waste with a unit weight 5.9 k N m 3 (Tchobanoglous et al., 1993), plus 0.3 m of cover material with a unit weight of 20 k N m 3 , would result in a confining pressure of 23.7 kPa. Although confining pressures were not used in the current study, water boundary pressures of 36 - 48 kPa were generated because of the large hydraulic gradients (65 - 88). These pressures would be more representative of landfills in their initial stages of operation. These conditions would also be representative of surface impoundments. Further testing is recommended to better understand the effect of confining pressures on heavy metal permeated clay barriers. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 80 a) Bentonite admix samples permeated with 0.01 M Ca(N03)i i " 1.00E-09 o •o 1.00E-10 c ,— O o ~ 1.00E-11 3 "O X 1.00E-12 200 400 Discharge Volume (mL) b) Forest soil admix sample permeated with 0.01 M Ca(N03)i S 1.00E-08 •S 1.00E-09 o <o o £ 1.00E-10 1.00E-11 3 ro 200 400 Discharge Volume (mL) 600 800 c) Spruce Bark admix samples permeated with 0.01 M Ca(N03)i 1.00E-09 i Discharge Volume (mL) Tripl icate # x Test 1 • Test 2 A Test 3 F I G U R E 4.3.1. Hydraulic conductivity results for leachate blanks, (a) Bentonite admix, (b) Forest soil admix, (c) Spruce bark admix. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 81 a) Pb permeants through bentonite admix samples «T 1.00E-08 600 800 1000 Discharge Volume (mL) b) Cu permeants through bentonite admix samples J5 1.00E-08 o l 1 2« 1.00E-09 s :> "g,o 1.00E-10 o 1.00E-11 o 600 800 1000 Discharge Volume (mL) c) Pb + Cu permeants through bentonite admix samples J» 1.00E-08 o l 3 2> 1.00E-09 ra 1 S. " 1.00E-10 600 800 1000 Discharge Volume (mL) d) Pb + Cu + Cd permeants through bentonite admix samples « 1.00E-08 o l = * 1.00E-09 ro > S. " 1.00E-10 600 800 1000 Discharge Volume (mL) Triplicate # xTest 1 o Test 2 A Test 3 F I G U R E 4.3.2. Hydraulic conductivity results for bentonite admix samples. (a) P b permeant. (b) Cu permeant. (c) Pb+Cu permeant (d) Pb+Cu+Cd permeant. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 82 a) Pb permeants through Forest soil admix samples f 1.00E-08 o I _ 1.00E-09 o to " I .2 — 1.00E-10 3 CO 3* 1.00E-11 X 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 b) Cu permeants through Forest soil admix samples § 1.00E-08 u I _ 1.00E-09 o « W E .2 — 1.00E-10 3 2 •a >> -ft*— ;-| p ri A X x • X — u • c "• • 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 c) Pb + Cu permeants through Forest soil admix samples 1.00E-08 2> > S3 o 1.00E-09 O <A ° E .a — 1.00E-10 2 1.00E-11 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 Tripl icate # x Test 1 • Test 2 A Test 3 F I G U R E 4.3.3. Hydraulic conductivity results for Forest soil admix samples. (a) Pb permeant. (b) Cu permeant. (c) Pb+Cu permeant. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 83 a) Pb permeants through Spruce Bark admix samples 1.00E-08 1.00E-09 o w O 1 .2 — 1.00E-10 3 <<J •D >. I X X 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 b) CM permeants through Spruce bark admix samples 3 1.00E-08 1.00E-09 o » .2 w 1.00E-10 1.00E-11 x 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 c) Pb + Cu permeants through Spruce bark admix samples U E .y — 1.00E-10 x 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 Triplicate # x Test 1 • Test 2 A Test 3 F I G U R E 4.3.4. Hydraulic conductivity results for Spruce bark admix samples. (a) Pb permeant. (b) Cu permeant. (c) Pb+Cu permeant. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 84 a) Bentonite admix -100:8 of sand:bentonite 1.00E-08 > | 1.00E-09 c .— o «> o I 3 1.00E-10 2 •D 1.00E-11 * _ :T-—- * * — — . - -- — - — i » ^ ^ 9 i 0 150 300 450 600 750 Discharge Volume (mL) b) Forest soil admix -100:7:1 of sand:bentonite:Forest soil 1.00E-08 900 1050 1200 0 150 300 450 600 750 Discharge Volume (mL) 1050 1200 c) Spruce bark admix -100:7:1 of sand:bentonite:Spruce bark 1.00E-08 2t U 1.00E-11 150 300 450 600 750 Discharge Volume (mL) 900 1050 1200 •Pb Leachate • Pb & Cu Leachate Cu Leachate — - - Pb, Cu, & Cd Leachate F I G U R E 4.3.5. Averaged hydraulic conductivity results grouped by admix type. (a) Bentonite admix, (b) Forest soil admix, (c) Spruce bark admix. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 85 a) Pb Leachate 1.00E-08 -r-T3 >> X 1.00E-11 1 1 1 1 1 1 1 1 1 0 150 300 450 600 750 900 1050 1200 Discharge Volume (mL) b) Cu Leachate 1.00E-08 T , 1 1 1 1 1 1 1 =5 1.00E-10 >< X 1.00E-11 -I 1 1 1 • 1 1 1 1 0 150 300 450 600 750 900 1050 1200 Discharge Volume (mL) c) Pb+Cu Leachate 1.00E-08 5 1.00E-10 S •o 1.00E-11 -I 1 1 1 1 1 1 1 1 0 150 300 450 600 750 900 1050 1200 Discharge Volume (mL) Bentonite admix Forest soil admix - - - -Spruce bark admix F I G U R E 4.3.6. Averaged hydraulic conductivity results grouped by leachate type, (a) Pb leachate. (b) Cu leachate. (c) Pb+Cu leachate Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 T H E L E A C H I N G C E L L T E S T 86 T A B L E 4.3.3. Summary of hydraul ic conductivity results f rom averaged data i n Figures 4.3.5 & 4.3.6. Admix Leachate Initial hydraulic conductivity HydrauUc conductivity at 1200 ml of discharge m s 1 m s 1 Bentonite admix Blank 2.4E-11 (test stop] Ded before 1200 ml of discharge) Pb 7.2E-11 4.7E-09 Cu 5.0E-11 4.8E-09 Pb+Cu 3.5E-10 4.3E-09 Pb+Cu+Cd 3.1E-10 2.4E-09 Forest soil admix Blank 2.8E-11 (test stop] ped before 1200 ml of discharge) Pb 3.0E-09 5.0E-09 Cu 8.0E-10 1.8E-09 Pb+Cu 4.9E-10 3.3E-09 Spruce bark admix Blank 1.4E-11 (test stop] ped before 1200 ml of discharge) Pb 8.9E-11 6.4E-10 Cu 8.4E-11 2.7E-09 Pb+Cu 1.6E-10 3.4E-09 4.3.1.2 Mechanism of hydraulic conductivity increase According to the Gouy-Chapman theory, solutions of increasing ionic strength causes increased flocculation of clay particles (Tan, 1998); thus, the higher the heavy metal concentration, the higher the degree of flocculation. However, the relationship between flocculation and changes in hydraulic conductivity remains uncertain. Figure 4.3.7 shows a proposed mechanism for hydraulic conductivity increase. The proposed mechanism was deduced from the shape of the hydraulic conductivity curves (Figures 4.2.3 - 4.3.4). The characteristics of the hydraulic conductivity curves can be separated into three parts. In the initial portion, the hydraulic conductivity values were low. During this stage of initial permeation, the heavy metal solution was causing the bentonite particles to flocculate; however, the hydraulic conductivity remained low because of the resistance provided by the uncontaminated region in front of the heavy metal flow (Figure 4.3.7.a). Heavy Meta l Sorpt ion and Hydraul ic Conduct iv i ty Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 87 After the initial portion, a period of rapid hydraulic conductivity increase occurred. This rapid increase was probably initiated upon the ful l penetration of heavy metals (Figure 4.3.7.b). The breakthrough of heavy metals meant that complete heavy metal widened pathways had formed. The flow concentrated towards these preferential pathways, and further widened them. The initial set of preferential pathways caused large increases in hydraulic conductivity. However, the impact of subsequent preferential pathways were limited by the structural fabric of the compacted sample. Thus, depending on the structural fabric of the compacted sample, and the size and number of preferential pathways formed, the hydraulic conductivity eventually reached an equil ibrium value (Figure 4.3.7.c). According to the proposed mechanism, hydraulic conductivity increase coincides with heavy metal breakthrough. Later, the presentation of heavy metal breakthrough results in Figures 4.3.8 - 4.3.10, (in section 4.3.3) wi l l confirm this occurrence, giving additional credibility to the proposed mechanism. 4.3.1.3 Effect of heavy metals vs. calcium on hydraulic conductivity The Leaching cell tests in this study were performed with the same set of experimental conditions. Also, all leachate solutions were set to the same initial p H , and similar ionic strengthens. A n important weakness in applying the Gouy-Chapman theory (Tan, 1998) to heavy metal contaminated soils was revealed through the current study. The Gouy-Chapman theory identifies cations only by their valence. Since the blank (Ca2+) and heavy metal (Pb2+, Cu2+, Cd2+) leachates all contain +2 cations, and possess similar ionic strengths, no differences in hydraulic conductivities should have been observed. However, the results in Figures 4.3.1 - 4.3.4 reveal that the heavy metal leachates had hydraulic conductivities over one magnitude greater than the blank Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 88 a) Initial permeation of heavy metals through Leaching cell t tt tt11 tttttt tttttttttt ttt b) Initial penetration of heavy metals t tttt ttt tttt t t t tt tt Initial inflow and discharge Heavy metal pathways (Flocculation occuring along pathways) Penetrated H. M. pathways Flow increases & concentrates towards penetrated H. M. pathways c) Long-term flow pattern mw 11 tttt r i t n t H. M. pathways become preferential channels Bulk of flow is along preferential channels New preferential pathways slower to develop and impart lesser impact on flow volume F I G U R E 4.3.7. Conceptual model for the mechanism of hydraulic conductivity increase in Leaching cells, (a) Initial permeation, (b) Initial heavy metal penetration, (c) Long-term flow pattern. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 89 leachates. Specifically, Pb and Cu leachates caused significantly higher hydraulic conductivities than the Ca (blank) leachate. Hydraulic conductivity data for Cd was insufficient to make any conclusions. The current study showed that cations of the same valence may have wide ranging effects on hydraulic conductivity. Thus, valence is not a sufficient parameter in identifying the effect of cations. Shown in Table 4.3.4, is a comparison between the sorption mechanisms of Ca and the heavy metals. In comparison to Pb, Cu, and Cd, Ca possesses a much lower potential for complexation, and precipitation. This comparison suggests that specific sorption characteristics may give indication to their effect on clay barrier hydraulic conductivity. Further research into calcium sorption capacities and characteristics would lead to stronger conclusions relating sorption characteristics and hydraulic conductivity. Furthermore, if flocculation is assumed to be the main mechanism that influences change in hydraulic conductivity, then one would need to investigate the relationship between sorption and flocculation, in order to bridge the gap of understanding. T A B L E 4.3.4. Comparison between the sorption mechanisms of Ca and the heavy metals. Retention mechanism Associated Reaction parameter * Order from greatest to least potential Cation exchange Ionic radii Pb>Ca>Cd> Cu Complexation 1st hydrolysis constant 2nd hydrolysis constant Cu>Pb>Cd>Ca Precipitation OH- solubility constant Pb>Cu>Cd> Ca * See Table 4.2.7 for parameter values. 4.3.1.4 Importance of initial saturation Barriers with high heavy metal retention capacities are preferable, because they are expected to retard the migration of heavy metals. However, Figures 4.3.1 - 4.3.4 show that the initial portions in the current study usually did not last more than 200 m l ( » 1 pore volume), before large hydraulic conductivity increases occurred. Even though Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 90 the Batch adsorption tests showed that the clay barriers possessed high heavy metal sorption capacities, the short initial portions indicated that the barriers were not able to retard the migration of heavy metals. In contrast, the results of Weber (1991), and Cabral (1992) were more in line wi th expectations. Each had one sample that d id not show significant increases until after 7 and 5 pore volumes, respectively. Also, many of their samples d id not show any increases for the duration of their tests. The reason why the current study failed to delay hydraulic conductivity increases, may be due to initial saturation. The admix samples of Weber and Cabral were 100%, or near 100% saturated before Pb permeation. In contrast, the current study began heavy metal permeation on samples that were only « 80% saturated (Table 4.3.2). The presence of air voids would increase the heterogeneity of the soil/pore media; thus, increasing the likelihood of preferential channeling. Also, in comparison to water-filled voids, air voids would provide less resistance to structural changes within the compacted admixes. The structural changes brought about by seepage force and the flocculation of clay particles, may also lead to preferential channeling. In actual field conditions, clay barriers require time to reach full saturation after construction. Thus, the current study represents the case in which clay barriers are required to perform, before full saturation is reached. 4.3.1.5 The effect of Pb and Cu on hydraulic conductivity The Batch adsorption tests in section 4.2.2, showed that for bentonite, its Pb sorption capacity was higher than its Cu sorption capacity. The different sorption capacities of Pb and Cu, suggest that they also may cause different degrees of flocculation. However, the hydraulic conductivity results in Table 4.3.3 d id not show any significant differences separating the effects of Pb and Cu. In addition, significant Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 91 differences could not be distinguished between the single and multi-heavy-metal results. The fact that almost all heavy metal permeated samples attained hydraulic conductivity values between 1.8 x IO - 9 - 5.0 x IO"9 m s 4 , indicated that the admixes were limited to a maximum hydraulic conductivity. This maximum hydraulic conductivity likely is determined by the structural fabric of the compacted samples. Apparently, all of the tested heavy metal concentrations were sufficient to bring the admixes to their maximum hydraulic conductivities. Further investigations are needed to determine the minimum heavy metal concentrations required to bring about hydraulic conductivity changes. 4.3.1.6 Uncertain factors influencing hydraulic conductivity Further investigations are need to identify the effect of the following: 1. The high gradients used (i = 65 - 88) may cause particle migration. This phenomenon may decrease hydraulic conductivity by causing the clogging of pores, or increase hydraulic conductivity by causing the unplugging or erosion of pores. Since suspended solids were rarely detected in the discharge, increases in hydraulic conductivity due to particle migration, were unlikely. 2. Bacterial growth was observed in the discharge tubes leading from the Forest soil and Spruce bark admix barriers. Bacterial growth would decrease hydraulic conductivity, but its effect could not be isolated. 3. The heavy metal permeants dissolve certain components of Forest soil and Spruce bark. These may alter the viscosity of the permeants. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 92 4.3.2 Heavy metal breakthrough results The heavy metal breakthrough results gave insight into the migration and mobility of heavy metals. In addition, the breakthrough results were used to evaluate the usefulness of sorption capacities obtained from Batch adsorption tests. Finally, heavy metal breakthrough points (when heavy metal breakthrough concentration reached half the source concentration) were used to evaluate the performance of the admixes. 4.3.2.1 General observations Similar to the hydraulic conductivity curves in Figures 4.3.2 - 4.3.4, the heavy metal breakthrough curves in Figures 4.3.8 - 4.3.10, show two distinct parts. Most of the tests started with an initial period of low heavy metal concentration, followed by a log-shaped increase. To facilitate the comparison of results, the triplicate breakthrough data was averaged together in Figures 4.3.11 - 4.3.12. Specific breakthrough concentrations taken from Figure 4.3.11 - 4.3.12 are summarized in Table 4.3.4. O n average, the initial period concentrations ranged between 0 - 227 mg l / 1 , and lasted between 50 - 350 ml of discharge (0 - 2.5 pore volumes). A t a discharge volume of 1200 ml (7 pore volumes), breakthrough concentrations ranged between 269 - 506 mg L r 1 (54 -100+ % of source concentration). The comparison point was chosen at a discharge volume of 1200 ml , because by this point, all breakthrough concentrations had reached near equilibrium. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST a) Pb permeants through bentonite admix samples. £ 500 §> 400 g J 300 | f 200 s s 100 I o "A N7 x x x -A —A — • nrd^— — w l tl I M # : — A n 200 400 600 800 1000 Discharge Volume (mL) b) C M permeants through bentonite admix samples. 1200 1400 £ 500 i> 400 8 5" 300 | I 200 03 0 * V v < * y v X xx X X X X * - ^  X X A X X • 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 c) Pb+Cu permeant-Pb data. d) Pb+Cu permeant -Cu data. at 3 O 500 400 _ _ 300 | | 200 | ~ 100 m n V V X , x * v * 5 < A ,NV X X x* 500 400 300 at 3 S d I f 200 S ~ 100 m 0 >r^-x-i x x zxrxiK 400 800 1200 Discharge Volume (mL) 400 800 1200 Discharge Volume (mL) e) Pb+Cu+Cd permeants - Pb data f) Pb+Cu+Cd permeants-CM data ^ 500 §> 400 S ? 300 | f 200 S ~ 100 ffi 0 <-a n5« VP— £ 500 -r O) 3 400 kthro - J 300 kthro Bui) 200 -CO £ Bui) 100 CD o i p>px^<^ v E S S * — X > Q # 0 400 800 1200 Discharge Volume (mL) g) Pb+Cu+Cd permeants-Cd data 500 400 800 1200 Discharge Volume (mL) §> 400 2 d 300 | f 200 £ ~ 100 ED n rM~i's>rvf3 : • MP # — -Br Triplicate # x Test 1 • Test 2 A Test 3 0 400 800 1200 Discharge Volume (mL) F I G U R E 4.3.8. Heavy metal breakthrough results for bentonite admix samples. (a) Pb permeant. (b) Cu permeant. (c - d) Pb+CM permeant. (e-g) Pb+Cu+Cd permeant. 93 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 94 a) Pb permeants through Forest soil admix samples. £ 500 ? 400 S d 300 £ |> 200 g - 100 m 0 x V in n r I ] x ZS A 1 •Ma.*-* fl fc -^—A-SA— U L. M ~ * £ - R - * - Q & - C , 4s B -U uA 1 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 b) Cu permeants through Forest soil admix samples. 500 400 £ 5" 300 f | 200 <0 " m 100 u f=i B r xn # n X X tr — yc *~ H X v X v A '-gtj -ft 200 400 600 800 1000 Discharge Volume (mL) 1200 1400 c) Pb + Cu permeants - Pb data. 500 o) 400 S 5" 300 S E 200 co — P m 100 0 X N r' V A X n • n n n 400 800 1200 Discharge Volume (mL) d) Pb + Cu permeants - Cu data. 500 o> 400 2 d 300 | f 200 P 100 0 0Q - r r — ^ 3 D u Q B 11 ' v , X x— — X rP X ( X X -X r ^ X * g$»x— ' BSD— . . ™ 4»£ 400 800 1200 Discharge Volume (mL) Triplicate # x Test 1 a Test 2 A Test 3 FIGURE 4.3.9. Heavy metal breakthrough results for Forest soil admix samples. (a) Pb permeant. (b) Cu permeant. (c - d) Pb+Cu permeant. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 95 a) Pb permeants through Spruce Bark admix samples. 500 g> 400 2 d 300 1 f 200 S ~ 100 m 0 0 200 400 600 800 1000 Discharge Volume (mL) b) Cu permeants through Spruce bark admix samples. «3> O ' £ 9 500 400 300 E 2 0 0 | 100 ffi 0 200 400 600 800 1000 Discharge Volume (mL) > V X V i—ttaxx" j k 1200 1400 1200 1400 A X v A V — x = x x-1 x X • X * 1 A L WmMMSJfi c) Pb + Cu permeants - Pb data. re 2 m 500 400 d 300 E 200 w 100 0 -X n t r X AX X — • — > Ck X -0 400 800 1200 Discharge Volume (mL) d) Pb + Cu permeants - Cu data. 500 400 2 d 300 | f 200 S "~ 100 m 0 M>b<=x- 1, X J . - - E - A - a - o —A -Q !ft 400 800 1200 Discharge Volume (mL) Triplicate # x Test 1 • Test 2 A Test 3 F I G U R E 4.3.10. Heavy metal breakthrough results for Spruce bark admix samples. (a) Pb permeant. (b) Cu permeant. (c - d) Pb+Cu permeant. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 96 a) Pb Leachate o '•3 2 _ c d § E o ~ u n C L 500 400 300 200 | 100 0 b) C M Leachate o '•3 2 _ = ? I f o — u 3 o 500 400 300 200 100 0 150 450 600 750 Discharge Volume (mL) 150 300 450 600 750 Discharge Volume (mL) 900 1200 • h—m—mm^ 1 \ U Breakthrough concentration 1 — i 1 1050 1200 c) Pb+Cu Leachate-Pb data o 500 400 • £ J 300 t5 ~ 100 J Q C L 0 150 300 450 600 750 Discharge Volume (mL) 900 1050 1200 d) Pb+Cu Leachate - C M data c o c 0) u c o o 3 O 500 400 300 200 100 0 • — — ~~ — —•—1—1 1 1 1 1 Breakthrough concentration 1 1— 150 300 450 600 750 Discharge Volume (mL) 900 1050 1200 •Bentonite admix Forest soil admix - - Spruce bark admix F I G U R E 4.3.11. Averaged heavy metal breakthrough results grouped by leachate type, (a) Pb leachate. (b) Cu leachate. (c) Pb+Cu leachate. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 97 500 Discharge Volume (mL) Pb Cu - - - -Cd F I G U R E 4.3.12. Averaged heavy metal breakthrough results for bentonite admix permeated with Pb+Cu+Cd leachate. T A B L E 4.3.5. Summary of heavy metal breakthrough data from averaged data in Figures 4.3.11 & 4.3.12. Admix Leachate Heavy metal Initial breakthrough Heavy metal analyzed concentration concentration at 1200 ml of discharge mgL- 1 m g L 1 Bentonite Pb Pb 0 418 admix Cu Cu 0 429 Pb+Cu Pb 0 343 Pb+Cu Cu 1 398 Pb+Cu+Cd Pb 1 348 Pb+Cu+Cd Cu 1 449 Pb+Cu+Cd Cd 10 460 Forest soil Pb Pb 12 321 admix Cu Cu 227 439 Pb+Cu Pb 17 269 Pb+Cu Cu 104 474 Spruce bark Pb Pb 7 384 admix Cu Cu 3 410 Pb+Cu Pb 1 417 Pb Cu 2 506 Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 4.3.2.2 Migration behavior - non-uniformity and fractured porous media 98 Non-uniform flow The conceptual mechanism for hydraulic conductivity increase presented i n Figure 4.3.7, predicted the coincidental increase of breakthrough concentrations and hydraulic conductivities. A comparison of the breakthrough curves in Figures 4.3.11 -4.3.12, with the hydraulic conductivity curves in Figures 4.3.2 - 4.3.4, show that at the point of breakthrough, the two curves increased as predicted. According to contaminant transport theory, a uniformly migrating contaminant front would look like Figure 4.3.13 (Freeze & Cherry, 1979). Notice that both the retarded and non-retarded species, showed symmetric breakthrough profiles. Furthermore, their profiles increased smoothly from 0-100% of the source concentration. In contrast, most of the averaged breakthrough curves in Figure 4.3.11, approached zero slope at below 100% of the source concentration. Some of the curves reached to merely 60% of the source concentration. The studies performed by Weber (1991), and Cabral (1992), also showed the same phenomena. The conceptual model in Figure 4.3.7, is used to explain why the breakthrough concentrations d id not reach 100% of the source concentration. Figure 4.3.7.b, in section 4.3.2.2 showed that when heavy metals initially penetrate the entire cell, the flow concentrates towards the penetrated pathways. The higher volume of flow through these preferential channels results in higher heavy metal loading to the channel walls. In addition, the higher velocity of flow through these channels decreases the heavy metal migration time (or detention time) through the cell. As a result, the higher velocity and volume of heavy metals would quickly overwhelm the sorptive ability of the channel walls. A conceptual model for non-uniform heavy metal migration (Figure 4.3.14) shows that at the discharge end, the higher heavy metal concentrations from the preferential channels, would mix wi th the Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 99 lower heavy metal concentrations of the surrounding areas. This mixing of flows is what causes the breakthrough curve to reach near equilibrium at less than 100% of the source concentration. F I G U R E 4.3.13. Heavy metal concentration profiles of uniformly migrating plumes (Freeze & Cherry, 1979). The mixing of flows results in temporarily stable breakthrough concentrations of less than 100% of the source concentration - A -mtfftttttt Source flow Preferential channels Flow from preferential channels contain high heavy metal concentrations Surrounding flow contains low heavy metal concentrations due to sorption F I G U R E 4.3.14. Conceptual model for the mechanism of non-uniform heavy metal migration. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST Fractured porous media 100 The breakthrough curves for the Spruce bark admixes (Figure 4.3.11) experienced greater concentration jumps than the other admixes. Assuming that significant short-circuting was occurring, the compacted admix could be viewed as a porous media containing fractures (Freeze & Cherry, 1979). In this case, most of the leachate would be migrating through the fractures. According to contaminant transport theory for fractured media, the slope of breakthrough curves is determined . by the degree in which the contaminant diffuses through the walls of the fractures into the surrounding porous media (Freeze & Cherry, 1979). Reasonably, penetration into the surrounding porous media may not be limited to diffusion, but could also be advective i n nature. Greater degrees of diffusion, and advective flow from the fractures into the surrounding porous media results in flatter breakthrough curves. The steep breakthrough slopes for the Spruce bark admixes indicate a low degree of diffusion and advective flow into the general media. The specific reasons for this observation could not be determined from the breakthrough data; however, differences in the slopes of breakthrough curves are probably due to differences in the physical structures of the compacted admix samples. 4.3.2.3 Retention capacity versus breakthrough point The main question related to clay barrier performance is ... "when, if ever, will contaminant breakthrough occur?" A second important question related to the first, is ... "how much contaminant will get through?" Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 101 These two questions lead to two important points. Firstly, the main purpose of using highly sorptive materials in clay barriers is to delay the migration of heavy metals. Secondly, sorption capacities may be misleading, because in field conditions, a clay barrier may allow the breakthrough of large quantities of heavy metals, before its sorption capacities are reached. In the following analysis, the sorption capacities of Batch adsorption tests are evaluated for their ability to predict breakthrough points, and retention capacities of the Leaching cells. Using the averaged data in Figures 4.3.11 - 4.3.12, the breakthrough points were determined for each curve, and summarized in Table 4.3.5. The breakthrough point for continuous sources was specified at one-half the source concentration (Freeze & Cherry, 1979). Table 4.3.5 shows that the breakthrough points ranged between 50 -1100 m l (0.25 - 6.25 pore volumes) of discharge. In addition, Table 4.3.5 summarizes for each curve, the heavy metal retention values up to the breakthrough point, as well as up to 1200 m l of discharge. The amount of each heavy metal retained, was calculated by determining the area above each breakthrough curve in Figures 4.3.11 - 4.3.12, minus one pore volume of clean discharge (see A P P E N D I X D.2 for calculations). The amount of heavy metals retained up to the breakthrough points ranged between 0 - 335 mg, and the amount of heavy metals retained after 1200 m l of discharge ranged between 0 - 359 mg. Finally, shown in Table 4.3.5 are the predicted sorption capacities calculated from the Batch adsorption test results in section 4.2.1. Even after running the Leaching cell for 1200 ml of discharge (7 pore volumes), the amounts of heavy metals retained were still far less than the predicted capacities. Furthermore, the predicted capacities gave little indication to the timing of breakthrough points. For example, many of the Cu permeated samples showed zero retention up to the point of breakthrough even though according to the Batch adsorption tests, the samples were capable of sorbing 300 - 513 mg of Cu. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 102 Following the same argument as in section 4.3.1.4, the discrepancy between the Leaching cell and Batch adsorption results may be due to under-saturation. Weber's (1991) and Cabral's (1992) samples, which were 100% saturated, had heavy metal breakthroughs at 5 - 7 pore volumes. In contrast, the breakthrough results in Table 4.3.5 show that most of the samples in the current study had breakthrough points at less than 2 pore volumes. The presence of air voids may have promoted preferential channeling within the admix samples. These results show that sorption capacities from Batch tests were insufficient in predicting the breakthrough points and retention capacities of Leaching cells. In addition, these results show that for clay barriers, saturation may have been a significant factor in retarding the migration of heavy metals. T A B L E 4.3.6. Summary of heavy metal breakthrough points & retentions. Leaching Cells Batch adsorption tests ** Admix Leachate HM* Breakthrough HM retained HM retained HM retention Percentage Type point up to break, pt. up to 1200 ml predicted of predicted ml mg mg mg % Bentonite Pb Pb 370 82 239 1102 22% admix Cu Cu 130 0 99 433 23% Pb+Cu Pb 600 131 250 873 29% Cu 330 32 171 302 57% Pb+Cu+Cd Pb 670 166 270 808 33% Cu 230 0 116 287 40% Cd 170 0 89 188 48% Forest Pb Pb 850 244 318 1160 27% soil Cu Cu 340 7 124 513 24% admix Pb+Cu Pb 1100 335 359 919 39% Cu 290 12 114 355 32% Spruce Pb Pb 320 44 192 1107 17% bark Cu Cu 150 0 125 432 29% admix Pb+Cu Pb 240 0 135 854 16% Cu 50 0 0 300 0% * H M - Heavy metal ** Calculated from formulas in Table 4.2.5, in section 4.2.1.4. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4 . 3 THE LEACHING CELL TEST 103 4.3.2.4 Relative mobility of heavy metals Figure 4.3.11 shows that for single and binary heavy metal systems involving Pb and Cu, Cu was always the first to breakthrough the soil column. In fact, an examination of the breakthrough points in Table 4.3.5, shows that Cu was « 2.5 times more mobile than Pb. As for the relative mobilities amongst Pb, Cu, and Cd, the Leaching cell test involving these three metals, indicated that Cd was «1 .5 times more mobile than Cu, and « 4 times more mobile than Pb. Using the sorption equations in section 4.2.1.4 (Table 4.2.5), heavy metal mobilities were calculated by dividing sorption concentrations with initial solution concentrations (Table 4.3.6). This was done to account for the differing molar concentrations of Pb, Cu, and Cd. Table 4.3.6 shows that the Cd sorption capacity for bentonite was «1 .5 times less than the Cu sorption capacity, and « 4.5 times less than the Pb capacity. Thus, a comparison between the Batch adsorption tests results with the breakthrough results, shows that the Batch adsorption tests are good indicators for the relative mobilities of Pb, Cu, and Cd. T A B L E 4.3.7. Heavy metal mobilities for bentonite. Leachate HM* analyzed Relative HM Mobility for bentonite (from sorption equations in section 4.1.2.4) sorption/initial solution concentration Pb Pb 3.6 Cu Cu 1.4 Pb+Cu Pb 2.9 Pb+Cu Cu 1.0 Pb+Cu+Cd Pb 2.7 Pb+Cu+Cd Cu 0.9 Pb+Cu+Cd Cd 0.6 * HM - heavy metal Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 104 The Batch adsorption tests show that due to competition, the sorption capacity of heavy metals in single heavy metal systems are higher than in multi-heavy-metal systems. However, this competition effect could not be seen in the breakthrough results. The breakthrough points for individual heavy metals were similar between the single and multi-heavy-metal systems. The competition effect was probably overshadowed by the variability associated with the Leaching cell test. Earlier in this section, under-saturation was suggested to be a significant factor in causing early heavy metal breakthroughs. Since the initial saturations shown in Table 4.3.2 (section 4.3), broadly ranged between 74 - 86%, this may have had a significant impact on the variability of the breakthrough results. Further studies are required to determine whether the competition effect would be seen in samples that were 100% saturated before heavy metal permeation. 4.3.3 Performance of admixes A n objective of the Leaching cell tests was to determine whether the Forest soil and Spruce bark admixes would be an improvement compared to the bentonite admix. Improvements were identified by increased heavy metal retention capacity, and delayed heavy metal breakthrough, while causing little change to the hydraulic conductivity of the admix. 4.3.3.1 Performance based on hydraulic conductivity After 1200 ml of discharge (~ 7 pore volumes), most heavy metal permeated samples stabilized at hydraulic conductivity values between 1.8 x 10~9 - 5.0 x 10~9 m s - 1 (Table 4.3.3). In contrast, samples permeated with blank solutions of 0.01 M Ca(N03)2 resulted in hydraulic conductivities between 1.4 x 10 - 1 1 - 2.8 x 10"11 m s_1. This difference Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 105 of two orders of magnitude, shows that heavy metal compatibility is a significant design concern for clay barriers. The results from the current study show that for cases where significant concentrations of heavy metals are expected, Leaching cell testing is required to determine the hydraulic conductivity values caused by heavy metal permeation. Further investigation is recommended to determine specific values that constitute "significant" heavy metal concentrations. The hydraulic conductivity curves in Figure 4.3.6, show that the initial portions of the Forest soil admix consistently averaged higher than the other admixes. This may be attributed to differences in p H , as observed in the discharge p H results in Figure 4.3.15. The discharge p H curves show that the Forest soil admix produced discharge p H values consistently lower than the other admixes. Since Forest soil possesses much lower initial p H (3.5 p H in CaCh) in comparison to bentonite (7.61 p H in CaCh), the presence of Forest soil would reduce the overall initial p H of the admix. The reduced initial p H may have several consequences: 1. Higher concentration of H + ions may cause a decrease in double layer thickness. 2. The reduced initial p H may reduce the potential for precipitation. Both of these consequences could have been contributing factors to the higher initial hydraulic conductivities seen in the Forest soil admixes. Confirmation of these effects would require further investigation. Regardless of the differences in initial hydraulic conductivity, almost all samples permeated with heavy metals eventually converged to a narrow range of values. Thus, in comparison to the bentonite admix, the other admixes performed equally well . The current study concludes that the substitution of one part bentonite from a 100:8 sand:bentonite admix, with one part of Forest soil or Spruce bark, does not cause significant increases in hydraulic conductivities. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 106 a) Pb Leachate 9 ~ 8 CL I 7 - A — + -^ - 4 -0-4-150 300 450 600 750 Discharge Volume (mL) 900 1050 1200 b) Cu Leachate 9 1 a a o a> 7 . c 6 u .2 5 *** ti* 0 0 (J* -A AA 4 . 0 A • Jk A A A 0 150 c) Pb+Cu Leachate 9 300 450 600 750 Discharge Volume (mL) 900 1050 1200 a. a at eg . c o (A :r — . . . O w <s — A 1 — * ^ — A - * A — A A * i A X ~ * 150 300 450 600 750 Discharge Volume (mL) 900 1050 1200 o Bentonite admix A Forest soil admix * Spruce bark admix F I G U R E 4.3.15. Discharge pH results grouped by leachate type, (a) Pb leachate. (b) C M leachate. (c) Pb+Cu leachate. 4.3.3.2 Performance based on heavy metal breakthrough As mentioned in section 4.3.2.3, the main concern in contaminant migration is not how much heavy metal would be retained, but how long a barrier could delay the breakthrough of heavy metals. According to the retention and breakthrough results in Table 4.3.5, the admixes rank as follows: Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 107 1. Forest soil admix 2. Bentonite admix 3. Spruce bark admix Since Forest soil possessed the highest heavy metal sorption capacities (section 4.2.1.4), the Forest soil admix was predicted to have the highest heavy metal retentions, and latest heavy metal breakthrough points. Although the Forest soil admix performed the best, the results show that sorption capacity was not the only factor. For this study, the initial saturation was suspected to have been a factor influencing heavy metal breakthrough. Another important factor that influenced breakthrough was the physical structures of the compacted admixes. Differences in structure were identified by variations in the slopes of the breakthrough curves. By visual inspection, the breakthrough slopes in Figure 4.3.11 had the following order of steepness: Forest soil admix < Bentonite admix < Spruce bark admix. The importance of admix structure is supported by similarities between the breakthrough point ranking and the breakthrough slope order. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.3 THE LEACHING CELL TEST 108 4.3.4 Summary of Leaching cell results Heavy metals' effect on hydraulic conductivity 1. In comparison to the blank solutions of 0.01 M Ca(NOs)i, the hydraulic conductivity increases due to heavy metal permeation, were approximately two orders of magnitude (from » 2 x 10-11 m s 1 to « 3 x 10-9 m s 1 ) . 2. The current study shows that valence was not a sufficient parameter in identifying the effect of cations on hydraulic conductivity. A comparison of between Ca and the heavy metals suggests that their potential for specific sorption mechanisms such as complexation and precipitation may be factors in determining the hydraulic conductivity of clay barriers. 3. A conceptual mechanism describing hydraulic conductivity change and non-uniform heavy metal migration was presented in Figures 4.3.7 and 4.3.14. 4. The lack of confining pressures caused the hydraulic conductivities in the current study to increase much more than observed in other studies (Weber, 1991; Cabral, 1992). 5. Pb and Cu solutions produced similar hydraulic conductivities. 6. Single and multi-heavy metal solutions produced similar hydraulic conductivities. The migration behavior of heavy metals 7. By comparing with the hydraulic conductivity, and heavy metal breakthrough results from Cabral (1992) and Weber (1991), under-saturation was suspected to be a factor in causing large hydraulic conductivity increases, and early heavy metal breakthroughs in the current study. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4 . 3 THE LEACHING CELL TEST 109 8. Batch adsorption tests were insufficient in predicting the breakthrough points and retention capacities of Leaching cell tests, but adequate in predicting relative heavy metal mobilities. 9. Based on the heavy metal breakthrough points, Cd is « 1 . 5 times more mobile than Cu, and « 4 times more mobile than Pb, respectively. Performance of admixes 10. A l l three admixes produced similar hydraulic conductivity values (Table 4.3.3). 11. Based on heavy metal retention and breakthrough points, the admixes rank as follows: 1. Forest soil admix 2. Bentonite admix 3. Spruce bark admix Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 4.4 S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N 110 The migration behavior and retention mechanisms of heavy metals were investigated using Selective Sequential Extractions (SSEs). SSE measures the amount of heavy metals sorbed onto the admixes in the form cation exchange (exchangeable component), precipitation (carbonate and hydroxide components), and complexation (hydroxide, and organic components). After the termination of a Leaching cell test, the admix sample was extruded and sliced into four layers. Two sampling procedures were used to collect material from each layer. For most extruded admix samples, the center and edge regions of each layer were sampled. For three sets of Leaching cell tests, each layer was remolded into uniform mixtures; then two composite samples were taken from each mixture to determine the average heavy metal concentration of each layer. SSEs were also performed on a set of Batch adsorption samples. The purpose for these Batch adsorption tests was to examine the comparability between the Batch adsorption and Leaching cell tests, as well as determine the accuracy of the SSE procedure. The SSE test program is summarized in Table 4.4.1. T A B L E 4.4.1. Summary for the SSE tests. Admix HM* solution Center & edge sampling Composite sampling Batch adsorption test samples Bentonite Pb V Cu V Pb+Cu V Pb+Cu+Cd V V Forest soil Pb Cu V V Pb+Cu V V Spruce bark Pb V Cu V Pb+Cu * HM - heavy metal Note - all heavy metal solutions contained 500 mg L 1 of each heavy metal specified. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 111 4.4.1 SSE on a set of Batch adsorption tests The SSE results for the Batch adsorption test samples are shown in Table 4.4.2. The SSE results for the Batch adsorption test samples were used for four types of comparisons: 1. The sorption characteristics of the three admixes were compared based on the Batch adsorption test samples. 2. The Batch adsorption tests in this section were performed on mixtures (bentonite, Forest soil, and Spruce bark admixes), while the Batch adsorption tests in section 4.2 were performed on individual materials. Comparing the two sets of Batch adsorption tests, showed whether the sorption capacities of mixtures could be predicted by adding their individual sorption capacities. 3. A comparison of the SSE results from the Batch adsorption and extruded Leaching cell samples showed the similarities between Batch adsorption and Leaching cell sorption capacities. 4. The SSE results on the Batch adsorption test samples were used to evaluate the accuracy of the SSE (see A P P E N D I X F. l ) Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 112 T A B L E 4.4.2. SSE results for Batch adsorption tests on admixes (see notes at bottom). Admix Heavy metal HM Exchangeable Carbonates Hydroxides Organics Residue Total solution analyzed ug/g soil ug/g soil ug/g soil Ug/g soil ug/g soil soil Bentonite Blank C M n/a 1 1 0 0 3 admix Blank Pb n/a 1 4 2 0 3 C M 1st Cu 326 205 35 4 4 574 Cu 2nd Cu 325 196 35 4 5 565 Pb 1st Pb 817 584 178 17 7 1604 Pblnd Pb 970 637 138 12 4 1760 Pb+Cu 1st Cu 284 105 29 3 1 423 Pb+Cu 1st Pb 830 231 106 6 0 1174 Pb+Cu 2nd Cu 311 104 28 3 3 449 Pb+Cu 2nd Pb 852 264 106 12 5 1238 Pb+Cu+Cd 1st Cd 251 14 0 2 0.1 267 Pb+Cu+Cd 1st Cu 242 102 28 3 3 378 Pb+Cu+Cd 1st Pb 785 186 98 8 3 1079 Pb+Cu+Cd2nd Cd 250 12 0 1 0.2 264 Pb+Cu+Cd2nd Cu 244 90 28 3 2 367 Pb+Cu+Cd2nd Pb 798 182 98 9 2 1090 Forest Blank Cu n/a 1 0 1 2 3 soil Blank Pb n/a 1 3 1 0 4 admix C M 1st Cu 350 206 116 51 14 738 Cu 2nd Cu 332 206 122 46 16 721 Pb 1st Pb 832 753 255 67 5 1912 Pb2nd Pb 826 790 398 70 4 2088 Pb+Cu 1st Cu 249 137 89 39 11 526 Pb+Cu 1st Pb 632 360 216 39 4 1252 Pb+Cu 2nd Cu 242 141 89 40 11 523 Pb+Cu2nd Pb 642 377 220 40 1 1280 Spruce Blank Cu n/a 1 0 0 1 2 bark Blank Pb n/a 0 3 3 0 6 admix C M 1st Cu 285 172 74 61 8 599 Cu 2nd Cu 285 163 74 22 9 552 Pblst Pb 592 423 189 60 4 1268 Pb2nd Pb 606 436 194 61 1 1297 Pb+Cu 1st Cu 240 93 51 12 2 399 Pb+Cu 1st Pb 480 184 116 46 0 825 Pb+Cu 2nd Cu 228 96 43 14 8 389 Pb+Cu 2nd Pb 462 185 103 50 3 803 Notes - Heavy metal solutions contain 500 mg L 1 of each heavy metal specified. - Data rounded off to whole numbers. - Admix'.solution ratio was 4 g of soil to 40 ml of solution. - n/a - not available Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 4.4.1.1 Sorption characteristics of the admixes 113 Table 4.4.3 displays the total amount of heavy metals extracted from each Batch sample using the SSE procedure. The Forest soil admix had an average sorptive advantage of 18% over the bentonite admix, while the Spruce bark admix had an average sorptive disadvantage of 16%. Figure 4.2.9 in section 4.2.2.1, showed that the heavy metal sorption capacities for bentonite and Spruce bark were approximately equal; thus, according to these individual sorption capacities, the bentonite and Spruce bark admixes should also be equal. These findings highlight the importance of testing potential barrier materials in clay barrier mixes rather than individually. The 16% discrepancy may be related to the contrasting pHs of the two materials. In water, the initial p H of bentonite is 8.38, while for Spruce bark, it is 4.34 (Table 4.1.1). The low p H of the Spruce bark may inhibit the cation exchange and precipitation . reactions associated with bentonite. T A B L E 4.4.3. Comparison of admixes based on SSE of Batch adsorption samples. Heavy metal HM Total sorbed concentrations based on extractions solution analyzed Bentonite admix Forest s. admix % Spruce b. admix % ug/gsoil Ug/gsoil Diff. Ug/gsoil Diff. Cu C M 570 730 28% 576 1% Pb Pb 1682 2000 19% 1282 -24% Pb+Cu Cu 436 525 20% 394 -10% Pb 1206 1266 5% 814 -32% Average 18% -16% The average percentages of Pb and Cu associated to each soil component of the three admixes are shown in Table 4.4.4. In comparison to the bentonite admix, the Forest soil and Spruce bark admixes retained more Pb within the carbonate, hydroxide, and organic components, and less within the exchangeable component. In addition, the Forest soil and Spruce bark admixes retained more Cu within the hydroxide and organic components, and less within the exchangeable component. These findings Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 114 show that the addition of Forest soil and Spruce bark into clay barrier mixes inhibited cation exchange, but promoted the retention mechanisms associated with the carbonate, hydroxide, and organic components. T A B L E 4.4.4. Averaged sorption characteristics for admixes based on SSE of Batch adsorption tests. Heavy metal Admix Exchangeable Carbonate Hydroxide Organic Residue Total extracted type (Xg/gsoil Pb Bentonite 65% 25% 9% 1% 0% 1324 Forest soil 46% 34% 17% 3% 0% 1633 Spruce bark 52% 28% 14% 5% 0% 1048 Cu Bentonite 63% 28% 7% 1% 1% 460 Forest soil 47% 27% 17% 7% 2% 627 Spruce bark 54% 27% 12% 5% 1% 485 4.4.1.2 Comparing sorption capacities of mixtures vs. individual materials Shown in Table 4.4.5, are the total concentration of heavy metals extracted from the admix samples submitted to Batch adsorption tests. As well , Table 4.4.5 shows a predicted set of sorption capacities for the admixes (see A P P E N D I X F.2 for calculations). These predicted values were calculated from the sorption capacities of the individual admix materials (see section 4.2.1.4). The comparison in Table 4.4.5, shows that most of the mixtures had higher sorption capacities than the summation of individual capacities. These results seem to suggest that the sorption capacities of individual materials were enhanced when the materials were mixed together. However, a more likely explanation is that the difference in sorption capacities was due to different soiksolution ratios. If the inert sand was excluded from the soiksolution ratio, then the ratio for the admixes would be 1 g of reactive material to 135 ml of heavy metal solution. The ratio for the individual materials was 1:50. This suggests that the soiksolution ratio used for the individual materials was not low enough to calculate the true heavy metal capacities. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 115 T A B L E 4.4.5. Sorption capacities of admixes. Admix Heavy metal H M Total extraction Total sorption by summation % solution analyzed from admixes of individual materials* Diff. ug/g soil ug/g soil Bentonite Cu Cu 570 528 -7% admix Pb Pb 1682 1344 -20% Pb+Cu Cu 436 368 -16% Pb 1206 1065 -12% Pb+Cu+Cd Cd 265 229 -14% Cu 373 351 -6% Pb 1084 983 -9% Forest soil Cu Cu 730 598 -18% admix Pb Pb 2000 1376 -31% Pb+Cu Cu 525 414 -21% Pb 1266 1089 -14% Spruce bark Cu Cu 576 527 -8% admix Pb Pb 1282 1350 5% Pb+Cu Cu 394 366 -7% Pb 814 1041 28% * Sorption capacities for individual materials calculated from formulas in Table 4.2.5. 4.4.1.3 Comparing the sorption capacities of Batch and Leaching cell samples Yong et al. (1993), said that "because of the soil structure, and because of pore geometry and pore continuity, only a fraction of the total surface area of the soil particles [in Leaching cell samples] comes in direct contact with the permeating leachate". In addition, sorption capacities are affected by several other differences between the Batch and Leaching cell tests. The soil particles in a Batch container are exposed to a fixed amount of solution, while the soil particles in a Leaching cell are exposed to a continuous flow of fresh leachate. In terms of soiksolution ratio, the Batch adsorption test possesses a fixed ratio, while the ratio for the Leaching cell test varies wi th the volume of discharge. In terms of reaction time, the Batch adsorption test allows for enough time to bring about equilibrium, while the reaction time for the Leaching cell test may not allow for the completion of sorption reactions. Finally, in terms of heavy metal concentration, the Batch adsorption test possesses one Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 116 concentration for all soil particles, while for the Leaching cell test, the heavy metal concentration of the leachate changes as it permeates through the Leaching cell sample. These differences raise concern over the applicability of Batch sorption capacities to Leaching cell results. A comparison of the sorption capacities of the influent end of Leaching cells, with the sorption capacities of the Batch adsorption tests is shown in Table 4.4.6. With the influent end samples, one was certain that exposure was to heavy metal concentrations of 500 mg LA. Because of sorption, the heavy metal leachate concentrations within the Leaching cells were unpredictable. Table 4.4.6 shows that the sorption capacities of the admix Batch adsorption tests were similar to that of the Leaching cells. This comparison shows that the 1:10 soihsolution ratio of the Batch adsorption tests was adequate to represent the conditions at the influent end of the Leaching cell samples. T A B L E 4.4.6. Comparing max. extractions of Leaching cell and Batch adsorption test samples. Total heavy metals extracted Admix Leachate solution Sample region (1st layers only) H M analyzed From Leaching cells From Batch adsorption tests % Diff ug/gsoil ug/gsoil Bentonite Cu Center Cu 534 570 7% Pb Center Pb 1569 1682 7% Pb+Cu Edge Cu 471 436 -7% Center Pb 1175 1206 3% Pb+Cu+Cd Composite Cd 252 265 5% Composite Cu 367 373 1% Composite Pb 877 1084 24% Forest soil Cu Composite Cu 826 730 -12% Pb Edge Pb 1938 2000 3% Pb+Cu Composite Cu 568 525 -8% Composite Pb 1069 1266 18% Spruce bark Cu Center Cu 651 576 -11% Pb Center Pb 1895 1282 -32% Pb+Cu Center Cu 404 394 -3% Edge Pb 536 814 52% Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 4.4.2 SSEs on extruded Leaching cell samples 117 Selective sequential extractions (SSEs) were performed on extruded Leaching cell samples to investigate the migration behavior, and retention mechanisms of heavy metals. Since the Leaching cell tests were terminated well after heavy metal breakthrough, the SSEs only showed the heavy metal distributions after a significant amount of heavy metals have migrated through the samples. These heavy metal distributions indicated the uniformity of migration, as well as migration patterns. The insights gained on migration behavior are valuable in evaluating and developing heavy metal transport models through clay barriers. The SSE results also were used to investigate the sorption characteristics of the various heavy metals (Pb, Cu, Cd) and admixes (bentonite, Forest soil, Spruce bark). This investigation was based on the broad range of sorption data (0 -1900 ug g"1) obtained by performing SSEs on different regions of the Leaching cell samples. The insights on reaction mechanisms were valuable in evaluating the performance of the admixes, as well as furthering the development of sorption models. 4.4.2.1 Heavy metal migration behavior To determine the heavy metal distribution within the Leaching cell samples, the extruded cells were sliced into four layers, and each layer was submitted to the SSE. For most cell samples (Figures 4.4.1 - 4.4.7), the center and edge regions were tested separately to determine the heavy metal distribution within each layer. For three leaching cell runs (Figures 4.4.8 - 4.4.10), composite sampling was done to determine the average concentration of heavy metals sorbed onto each layer. A small diagram on the top right hand corner of each figure acts as a visual reference to the explain the graphs. For example, Figure 4.4.1.a shows the concentrations of Pb sorbed onto the center region of each layer. Layer 1 is the influent end of the cell sample, and the layer Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 118 numbers increase towards the discharge end. Figures 4.4.1 - 4.4.7 show that heavy metal concentrations in the center regions varied significantly from the concentrations in the edge regions. In addition, layers 2 and 3 often contained very low concentrations compared to layers 1 and 4. Similarly, Figures 4.4.8 - 4.4.10 also frequently show low heavy metal concentrations in layers 2 and 3. These results indicate that short-circuiting occurred in many samples. This supports the findings in section 4.3.3.1, that heavy metals migrated non-uniformly through preferential channels. Consistent sampling of high heavy metal concentrations in the 4th layer, was probably due to the decision in permeating the Leaching cell from bottom to top. Since the permeant exited at the top, it would sit for a period of time as a pool of leachate on top of the Leaching cell, before exiting through the discharge tube (see Figure 3.4.1). This probably resulted in an over-estimation of heavy metal sorption in the 4th layer. Since the sorption capacities of Leaching cell samples were already found to be much lower than predicted (section 4.3.2.3), this error would not significantly affect any of the previous findings. This error may have been mitigated by permeating from top to bottom, or by slicing a thin layer of admix off the top of the 4th layer before sampling. Since only two regions (center and edge) in each layer were sampled, a detailed distribution of heavy metals could not be determined. From the graphs in Figures 4.4.1 - 4.4.10, no migration patterns could be identified. A recommendation for future research is to perform SSEs on an exhaustive sampling of the entire cell. If each layer was cut according to a grid pattern and SSEs were performed on each cube, then 3D heavy metal distribution graphs could be mapped. The SSE results from this research emphasize the challenges in developing suitable transport models for the migration of heavy metals through clay barriers. The lack of uniformity discourages the application of simplistic transport models, since homogeneity is often an important assumption. The lack of migration patterns imposes a high degree of uncertainty to numerical transport modeling. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 119 Admix type: Bentonite Leachate: Pb # of sample cells: 2 Type of sampling: center & edge Layer 4 Layer 3 | Layer 2 | | Layer 1 ~ | ' 1 t Center sample in f luent end Edge sample a) Center sample of 1st cell b) Edge sample of 1st cell " 1 1 T 500 1000 1500 2000 0 500 1000 1500 2000 Adsorption (ug/g) Adsorption (ug/g) c) Center sample of 2nd cell d) Edge sample of 2nd cell 0 500 1000 1500 2000 0 5 0 0 1 0 0 0 1 5 0 0 2 ° 0 0 Adsorption (ug/g) Adsorption (ug/g) • EXCHANGEABLE • CARBONATES • HYDROXIDES MORGAN ICS • RESIDUE F I G U R E 4.4.1. Distribution of heavy metals in bentonite admix samples leached with Pb. (a - b) Center & edge samples of 1st cell sample, (c - d) Center & edge samples of 2nd cell sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 120 Admix type: Bentonite Leachate: Cu # of sample cells: 1 Type of sampling: center & edge Layer 4 Layer 3 Layer 2 | Layer 1 t influent end Center sample Edge sample a) Center sample b) Edge sample 250 500 Adsorption (ug/g) 750 1000 250 500 750 Adsorption (ug/g) 1000 • EXCHANGEABLE • CARBONATES O HYDROXIDES BORGANICS • RESIDUE FIGURE 4.4.2. Distribution of heavy metals in bentonite admix sample leached with Cu. (a) Center sample, (b) Edge sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 121 Admix type: Bentonite Leachate: Pb+Cu # of sample cells: 1 Type of sampling: center & edge I Layer 4 ~J Layer 3 1 Layer 2 | I Layer 1 I I 1 t Center sample influent end Edge sample a) Pb extracted from center sample c) Pb extracted from edge sample 1200 b) Cu extracted from center sample 300 600 900 Adsorption (ug/g) 1200 d) Cu extracted from edge sample 300 600 900 Adsorption (ug/g) 1200 • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS P RESIDUE FIGURE 4.4.3. Distribution of heavy metals in bentonite admix samples leached with Pb & Cu. (a - b) Pb & Cu extracted from center sample, (c - d) Pb & Cu extracted from edge sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 122 Admix type: Forest soil Leachate: Pb # of sample cells: 3 Type of sampling: center & edge a) Center sample of 1st cell b) Edge sample of 1st cell 500 1000 1500 Adsorption (ug/g) 2000 O. E 500 1000 1500 Adsorption (ug/g) 2000 c) Center sample of 2nd cell d) Edge sample of 2nd cell 0 500 1000 1500 2000 0 5 0 0 1000 1500 2000 Adsorption (ug/g) Adsorption (ug/g) e) Center sample of 3rd cell f) Edge sample of 3rd cell 0 500 1000 1500 2000 0 500 1000 1500 2000 Adsorption (ug/g) Adsorption (ug/g) • EXCHANGEABLE • CARBONATES D HYDROXIDES •ORGANICS O RESIDUE FIGURE 4.4.4. Distribution of heavy metals in Forest soil admix samples leached with Pb. (a - b) Center & edge samples of 1st cell sample, (c - d) Center & edge samples of 2nd cell sample, (e - f) Center & edge samples of 3rd cell sample Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 123 Admix type: Spruce bark Leachate: Pb # of sample cells: 1 Type of sampling: center & edge Center sample influent end Edge sample a) Pb extracted from center b) Pb extracted from edge 0 500 1000 1500 2000 0 500 1000 1500 2000 Adsorption (ug/g) Adsorption (ug/g) • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS • RESIDUE FIGURE 4.4.5. Distribution of heavy metals in Spruce bark admix sample leached with Pb. (a) Center sample, (b) Edge sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N 124 Admix type: Spruce bark Leachate: C M # of sample cells: 2 Type of sampling: center & edge Center sample influent end Edge sample a) C M extracted from center of 1st cell b) Cu extracted from edge of 1st cell 0 200 400 600 800 0 200 400 600 800 Adsorption (ug/g) Adsorption (ug/g) c) Cu extracted from center of 2nd cell 200 400 600 Adsorption (ug/g) 800 d) Cu extracted from edge of 2nd cell 200 400 Adsorption (ug/g) 600 800 • EXCHANGEABLE • CARBONATES DHYDROXIDES BORGANICS • RESIDUE F I G U R E 4.4.6. Distribution of heavy metals in Spruce bark admix sample leached with C M . (a - b) Cu extracted from center & edge of 1st cell, (c - d) C M extracted from center & edge of 2nd cell. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 125 Admix type: Spruce bark Leachate: Pb+Cu # of sample cells: 3 Type of sampling: center & edge a) Pb extracted from center of 1st cell in 0 150 300 450 Adsorpt ion (ug/g) b) Cu extracted from center of 1st cell 150 300 450 Adsorpt ion (ug/g) e) Pb extracted from center of 2nd cell 150 300 450 Adsorpt ion (ug/g) f) Cu extracted from center of 2nd cell *4 §3 » o. 1 1 in 150 300 450 Adsorpt ion (ug/g) i) Pb extracted from center of 3rd cell 0 1 5 0 AdsorP3fi8n(ug/g, 4 5 0 j) Cu e x t r a c t e d f r o m c e n t e r o f 3rd c e l l - 4 I | 3 | 2 §" 1 150 300 450 Adsorpt ion (ug/g) 600 600 600 c) Pb extracted from edge of 1st cell 0 150 300 450 Adsorpt ion (ug/g) d) Cu extracted from edge of 1st cell 600 150 300 450 Adsorpt ion (ug/g) 600 g) Pb extracted from edge of 2nd cell 150 300 450 Adsorpt ion (ug/g) 600 h) Cu extracted from edge of 2nd cell 150 300 450 Adsorpt ion (ug/g) 600 k) Pb extracted from edge of 3rd cell 300 450 Adsorpt ion (ug/g) 600 1) Cu extracted from edge of 3rd cell 150 300 450 Adsorpt ion (ug/g) • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS • RESIDUE FIGURE 4.4.7. Distribution of heavy metals in Spruce bark admix samples leached with Pb &Cu. (a - b) Pb & Cu extracted from center of 1st cell, (c - d) Pb & Cu extracted from edge of 1st cell, (e - f) Pb & Cu extracted from center of 2nd cell, (g - h) Pb & Cu extracted from edge of 2nd cell, (i - j) Pb & Cu extracted from center of 3rd cell, (k -I) Pb & Cu extracted from edge of 3rd sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 126 Admix type: Bentonite Leachate: Pb+Cu+Cd # of sample cells: 2 Type of sampling: composite influent end a) Pb extracted from 1st cell sample d) Pb extracted from 2nd cell sample 0 250 500 750 1000 0 250 500 750 1000 Adsorption (ug/g) Adsorption (ug/g) b) Cu extracted from 1st cell sample e) Cu extracted from 2nd cell sample 0 250 500 750 1000 0 250 500 750 1000 Adsorption (ug/g) Adsorption (ug/g) c) Cd extracted from 1st cell sample f) Cd extracted from 2nd cell sample 250 500 750 Adsorption (ug/g) 1000 o ra _) a a. S ro 250 500 750 Adsorption (ug/g) 1000 • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS • RESIDUE FIGURE 4.4.8. Distribution of heavy metals in bentonite admix samples leached with Pb, Cu, & Cd. (a-c) Pb, Cu, &Cd extracted from 1st cell sample, (d-e) Pb,Cu, &Cd extracted from 2nd cell sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N 127 Admix type: Forest soil Leachate: Cu # of sample cells: 1 Type of sampling: composite Layer 4 I Layer 3 I Layer 2 | Layer 1~ t influent end a) Composite sample of 1st cell b) Composite sample of 2nd cell 250 500 750 Adsorption (ug/g) 1000 250 500 750 Adsorption (ug/g) 1000 • EXCHANGEABLE • CARBONATES • HYDROXIDES MORGAN ICS ORESIDUE F I G U R E 4.4.9. Distribution of heavy metals in Forest soil admix samples leached with Cu. (a) Composite sample of 1st cell, (b) Composite sample of 2nd cell. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 128 Admix type: Forest soil Leachate: Pb+Cu # of sample cells: 3 Type of sampling: composite Layer 4 Layer 3 Layer 2 Layer 1 t influent end a) P b extracted from 1st cell 300 600 900 Adsorption (ug/g) 1200 b) Cu extracted from 1st cell u. 4 Q. E 300 600 900 Adsorption (ug/g) 1200 c) P b extracted from 2nd cell 300 600 900 Adsorption (ug/g) 1200 d) Cu extracted from 2nd cell 300 600 900 Adsorption (ug/g) 1200 e) P b extracted from 3rd cell 300 600 900 Adsorption (ug/g) 1200 f) C M extracted from 3rd cell * 1 300 600 900 Adsorption (ug/g) 1200 • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS • RESIDUE FIGURE 4.4.10. Distribution of heavy metals in Forest soil admix samples leached with P b & C M . (a - b) P b & Cu extracted from 1st cell sample, (c -d) P b Sc. Cu extracted from 2nd cell sample, (e - f) P b & Cu extracted from 3rd cell sample. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 4.4.2.2 Heavy metal retention mechanisms 129 The Batch adsorption tests results presented in sections 4.2.1 and 4.4.1 produced a wide range of sorption capacities; however, they offered little insight on how the heavy metals were sorbed onto clay barriers. The SSE program of this study allowed the opportunity to examine the nature in which heavy metals were sorbed over a large range of sorption concentrations. Although only one concentration value (500 mg L _ 1 ) was used for the leachate solutions, the permeation process produced soil samples that sorbed a wide range of heavy metal concentrations (0 -1900 ug g - 1). By performing SSEs on these soil samples, one was able to identify distinct trends in which the heavy metals were sorbed. Because of the imprecision of the SSE procedure, the lower values (< 100 ug g-1) were not included in the analysis. Figures 4.4.11 - 4.4.12 show that a linear relationship exists between the percentages of Pb and Cu retained by the various soil components (exchangeable, carbonate, hydroxide, and organic), and the total amount of heavy metals sorbed by the admix samples. For clarification, to obtain the "total amount of heavy metals" for binary systems, the sorbed Pb and sorbed Cu quantities were added together. Because this calculation involves the addition of different types of heavy metals, molar quantities were used. In comparison to Pb and Cu, very few SSEs were performed involving Cd. The data collected involving Cd sorption was not sufficient to create the same type of plots as seen in Figures 4.4.11 - 4.4.12. Instead, the Cd SSE data is presented in Table 4.4.7. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 130 a) Exchangeable Pb component of total heavy metals sorbed. 0> 100% j 3 03 c 80% -0) S) c o 60% e cs D. 40% -O o 20% UJ 0% -0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) b) Carbonate Pb component of total heavy metals sorbed. 100% : 80% 0.00 2.00 4.00 6.00 8.00 10.00 12.00 Total heavy metal concentration (mmol/kg soil) 14.00 c) Hydroxide Pb component of total heavy metals sorbed. 100% cu •£ 80% * m 60% 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) d) Organic Pb component of total heavy metals sorbed. 50% „ c 40% c 2 30% f CB O S> o- 20% ° i 10% o 0% » - @- » ° °J® 0.00 2.00 f &'&%T -v -r — -y 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) « Bentonite admix x Forest soil admix o Spruce bark admix F I G U R E 4.4.11. Pb sorption trends over a range of total sorption concentrations. (a) Exchangeable component, (b) Carbonate component, (c) Hydroxide component, (d) Organic component. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 131 a) Exchangeable Cu component of total heavy metals sorbed. 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) b) Carbonate Cu component of total heavy metals sorbed. 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) c) Hydroxide Cu component of total heavy metals sorbed. 50% 0) 4-1 c 40% '5 0) c 30% & •o a. E 20% >» X C O o 10% 0% 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) d) Organic Cu component of total heavy metals sorbed. 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Total heavy metal concentration (mmol/kg soil) • Bentonite admix x Forest soil admix o Spruce bark admix F I G U R E 4.4.12. C M sorption trends over a range of total sorption concentrations. (a) Exchangeable component, (b) Carbonate component, (c) Hydroxide component, (d) Organic component. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION T A B L E 4.4.7. SSE data for Cd from the bentonite admix. 132 Heavy metal extracted Layer Exchangeable Carbonates Hydroxides Organics Residue Total ug/g soil Cd 1 96% 2% 1% 1% 0% 250 2 94% 4% 1% 1% 0% 197 3 96% 2% 1% 1% 0% 118 4 96% 2% 1% 1% 0% 162 1 96% 2% 1% 1% 0% 252 2 96% 2% 1% 1% 0% 188 4 96% 2% 1% 1% 0% 175 Sorption trends for Pb, Cu, and Cd As shown in Figures 4.4.11 - 4.4.12, all three admixes had similar, linear sorption trends for Pb and Cu. A t a sorption concentration of 2 mmol kg- 1, the exchangeable component accounted for only 10-40% of the total amount of heavy metals sorbed. As the sorption concentrations increased, the percentage for the exchangeable component increased, while the percentages for the other components decreased. A t a sorption concentration of 12 mmol kg- 1, the exchangeable component accounted for 50 - 80% of the total amount of heavy metals sorbed. In actual values, the amount of heavy metals sorbed onto the carbonate, hydroxide, and organic components increased with increasing sorption concentrations; however, the amount of heavy metals sorbed onto the exchangeable component increased at such a greater extent, that the heavy metal sorption of other components decreased in terms of percentage. In terms of retention mechanisms, Figures 4.4.11 -4.4.12 show that precipitation and surface complexation dominated at low Pb and Cu sorption concentrations, while cation exchange dominated at higher sorption concentrations. The discussion in section 4.2.2.2, theorized that for Cu sorption, precipitation and complexation would dominate at low initial heavy metal solution concentrations, and cation exchange at high initial heavy metal concentrations. These findings are in agreement with the findings in section 4.2.2.2. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 133 Table 4.4.7 shows that 96% of the Cd was sorbed by cation exchange. Compared to the Pb and Cu data, the Cd sorption concentration range of 1.0 - 2.2 mmol kg" 1 (118 -250 pg g - 1), represents low values. Considering the sorption trends for Pb and Cu, cation exchange also would be expected to dominate at high Cd sorption concentrations. Further studies are needed to determine the dominant retention mechanisms for Cd sorption onto organic matter. Information on the influence of various retention mechanisms for clay barriers shows that the desorption potential (future mobility) of heavy metals is dependent on the type of heavy metal, as well as the level of contamination. Because Cd sorption was mainly due to cation exchange, Cd possesses the highest desorption potential among the three heavy metals tested. For Pb and Cu, desorption potential was found to increase wi th increasing heavy metal sorption concentrations. This means that greater the contamination concentrations, greater the potential for heavy metals to desorb and re-enter into the groundwater. The heavy metal sorption trends also provides direction in improving the sorption model developed in section 4.2. The sorption model in section 4.2, was not specific in identifying retention mechanisms, but used two parameters to empirically model the sorption data. Since Cd sorption was dominated by only one retention mechanism, the method used in section 4.2 was adequate; however, because Pb and Cu sorption involved many retention mechanisms, the model would be improved if cation exchange, complexation, and precipitation could be individually identified. Because the heavy metal solution concentrations within the different regions of Leaching cell samples were unknown, the SSE results could not be incorporated into the model developed in section 4.2. However, these results show that SSE may be a valuable tool in developing new sorption models. Further work in conducting extensive SSEs on Batch adsorption samples is recommended. The advantage of Batch adsorption samples is that their initial and equilibrium solution concentrations would be known. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION Sorption differences between bentonite and other admixes 134 Figures 4.4.11 - 4.4.12, show that the Forest soil admix retained 13% more Cu, and 5% more Pb, within its organic component than the bentonite admix. Also, compared to the bentonite admix, the Spruce bark admix retained 5% more Cu, and 11% more Pb, within its organic component. These results correlate well with the compositions of the three admixes. Assuming that the silica sand made no contribution to the retention of heavy metals, the Forest soil and Spruce bark would constitute 12.5% of the reactive material in the Forest soil and Spruce bark admixes. Compared to the bentonite admix, the Forest soil and Spruce bark admixes retained 33% less Cu, and 20% less Pb, within its exchangeable component. In addition, the Forest soil and Spruce bark admixes retained more heavy metals within their carbonate and hydroxide components. The retention mechanisms associated with these components include precipitation and complexation. These findings show that the presence of Forest soil and Spruce bark in clay barrier mixes promoted stronger retention mechanisms, agreeing with the findings in section 4.4.1.1. Figure 4.3.15 in section 4.3.3.1, showed that the presence of Forest soil and Spruce bark resulted in lower discharge pHs. Since Pb and Cu precipitation is associated with higher pHs, surface complexation is probably the retention mechanism that was enhanced by the presence of Forest soil and Spruce bark. Over the long term, one can assume that a clay barrier would be exposed to various chemical conditions; thus, sorbed heavy metals risk the chance of re-mobilization. Since Pb and Cu are bound more strongly by the Forest soil and Spruce bark admixes, these admixes hold an advantage over the bentonite admix. Based on the likelihood of re-mobilization, the admixes rank as follows: Pb mobility - Spruce bark admix < Forest soil admix < Bentonite admix Cu mobility - Forest soil admix < Spruce bark admix < Bentonite admix. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION 4.4.3 Summary of SSE results and the performance of the admixes 135 Migration behavior and sorption characteristics 1. Many admix samples from the 2nd and 3rd layers showed zero or near zero concentrations of heavy metals. The non-uniform and unpredictable migration behavior of heavy metals, presents a challenge to transport modeling. 2. The decision to permeate samples from bottom to top led to excess heavy metal sorption in the 4th (top) layer. Although this resulted in an overestimation of heavy metal sorption capacities for the Leaching cells, the error did not significantly change any conclusions made. 3. Sorption capacities of the admixes were greater than the sum of their individual materials. This was probably because the soibsolution ratio (1 g : 135 ml) of the admixes was lower than the soihsolution ratio (1 g : 30 ml) of the individual materials. 4. The SSE results showed that for all three admixes, precipitation and complexation dominated at low Pb and Cu concentrations, while cation exchange became dominant at higher concentrations. For the bentonite admix, 96% of the Cd was retained by cation exchange. 5. Amongst the three heavy metals tested, Cd was sorbed the weakest; thus Cd has the highest desorption potential. For Pb and Cu, desorption potential increased wi th increasing heavy metal sorption concentrations. 6. The SSE results showed that the sorption model developed Pb and Cu, in section 4.2.1 would be improved if cation exchange, surface complexation, and precipitation were individually identified. Since Cd was retained mainly by cation exchange for bentonite, the identification of individual mechanisms is unnecessary. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 4.4 SELECTIVE SEQUENTIAL EXTRACTION The applicability of Batch adsorption test results to the Leaching cell test 136 7. One came to the same conclusions regarding sorption characteristics using the SSE results for both the Batch and Leaching cell samples. 8. The heavy metal sorption capacities for Batch adsorption tests were comparable to that of Leaching cells. Performance of admixes 9. The SSE results for Leaching cell samples, showed all three admixes experienced a significant amount of preferential channeling. 10. The SSE results for the Batch adsorption test samples showed that on average, Forest soil admix sorbed 18% more heavy metals, and Spruce bark admix sorbed 16% less heavy metals, than the bentonite admix. 11. The SSE results for the Leaching cell and Batch samples showed that the addition of Forest soil and Spruce bark into a typical bentonite admix likely inhibited cation exchange, but promoted surface complexation. 12. The SSE results showed that based on the likelihood of Pb and Cu re-mobilizing in the future, the admixes rank as follows: Pb mobility - Spruce bark admix < Forest soil admix < Bentonite admix Cu mobility - Forest soil admix < Spruce bark admix < Bentonite admix Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 137 CHAPTER 5 C O N C L U S I O N S & R E C O M M E N D A T I O N S 5.1 CONCLUSIONS Heavy metal sorption characteristics of the clay barrier materials 1. A n empirical model based on the Freundlich equation was developed for the sorption of Pb, Cu, and Cd, onto bentonite, Forest soil, and Spruce bark. This model was capable of predicting single, binary, and ternary heavy metal systems. See Table 4.2.5 for the full set of equations. 2. The Batch adsorption tests results produced the following ranking of sorption capacities: Ranking Pb sorption capacity Forest soil > Bentonite « Spruce bark C M sorption capacity Forest soil > Bentonite » Spruce bark Cd sorption capacity Forest soil > Bentonite > Spruce bark Sorption onto Bentonite Pb>Cu> Cd Sorption onto Forest soil C M > Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) Sorption onto Spruce bark Pb>Cu> Cd 3. Based on the competition functions in Table 4.2.7, the competition amongst heavy metals rank as follows: Pb> Cu> Cd. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.1 CONCLUSIONS Heavy metal sorption characteristics of the clay barrier admixes 138 4. The SSE results showed that for all three admixes, precipitation and complexation dominated at low Pb and Cu concentrations, while cation exchange became dominant at higher concentrations. For the bentonite admix, 96% of the Cd was retained by cation exchange. 5. The SSE results for the Batch test samples showed that on average, the Forest soil admix sorbed 18% more heavy metals, and the Spruce bark admix sorbed 16% less heavy metals, than the bentonite admix. 6. The SSE results for both Batch and Leaching cell samples showed that the addition of Forest soil and Spruce bark into a typical bentonite admix inhibited cation exchange, but likely promoted surface complexation. Effect of heavy metals on hydraulic conductivity 7. In comparison to the blank solutions (only containing 0.01 M Ca(N03)2), the hydraulic conductivities of the heavy metal (500 mg L"1) permeated samples were greater by approximately two orders of magnitude (from * 2 x 10-1 1 m s_ 1 to « 3 x 10-9 m s-i). 8. The hydraulic conductivity results in the current study experienced much larger increases than those found in other studies. This discrepency was probably due to the lack confining pressures used in the current study. This condition would represent that of a landfill at the beginning of operation. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.1 CONCLUSIONS 139 9. The blank (Ca2+) and heavy metal solutions (Pb2+, Cu2+, Cd2+, Ca2+), both contained cations of 2+ valence. Thus, valence was not sufficient in identifying the effect of cations on hydraulic conductivity. A comparison between Ca and the heavy metals suggests that their potential for specific sorption mechanisms, such as complexation and precipitation, may be factors in affecting the hydraulic conductivity of clay barriers. 10. Heavy metal solutions containing different combinations of Pb, Cu, and Cd, in 500 mg L ' 1 concentrations, produced similar hydraulic conductivities. The results indicate that the attained hydraulic conductivities represent an upper limit determined by the soil structure of the admixes. The migration and mobility of heavy metals through clay barriers 11. The breakthrough, hydraulic conductivity, and SSE results indicated that heavy metals migrated non-uniformly through the Leaching cell samples. 12. Early heavy metal breakthroughs, increases in hydraulic conductivity, and uneven distributions of heavy metals within the extruded Leaching cells, indicated that short-circuiting occurred. 13. A conceptual mechanism (Figures 4.3.7 & 4.3.15) for the increase in hydraulic conductivity and migration of heavy metals was developed based on the hydraulic conductivity and heavy metal breakthrough curves. 14. Based on breakthrough points, Cd was «1 .5 times more mobile than Cu, and « 4 times more mobile than Pb, respectively. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.1 CONCLUSIONS Prediction ability of Batch adsorption tests 140 15. The Batch adsorption tests were adequate indicators of relative heavy metal mobilities. 16. The SSE results showed that the Batch and Leaching cell samples had the same heavy metal sorption characteristics. 17. The Batch adsorption tests were insufficient at predicting the heavy metal breakthrough points and retention capacities of Leaching cell tests. Performance of admixes 18. The three admixes produced similar hydraulic conductivity values (Table 4.3.3). 19. The Forest soil admix ranked the best in terms of retention capacity, points of breakthrough, and long-term immobilization of heavy metals. 20. The Bentonite admix was better than the Spruce bark admix in terms of retention capacity, and points of breakthrough. 21. The Spruce bark admix was better than the bentonite admix in terms of long-term immobilization of heavy metals. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.2 RESEARCH CONTRIBUTIONS 141 5.2 R E S E A R C H C O N T R I B U T I O N S The conclusions from this study are applied to the following areas: 1. The design of landfill liners, surface impoundment liners, and vertical clay barriers a) The current study found that heavy metal compatibility studies are required when significant concentrations of heavy metals are expected. Leaching cell testing is recommended for determining the parameters for hydraulic conductivity, heavy metal breakthrough, and heavy metal retention. b) The addition of Forest soil into a clay barrier mix, increased the heavy metal sorption capacity, and improved long-term heavy metal retention, without significantly increasing hydraulic conductivity values. c) The addition of Spruce bark provided an improvement to the long-term heavy metal fixation, but reduced the sorption capacity of the clay barrier. d) The clay barriers used in the study were under-saturated at the start of heavy metal permeation, and did not receive direct application of confining pressures. These conditions are comparable to those encountered early after barrier construction. 2. Modeling the migration of heavy metals through soils. a) Sorption capacities attained from Batch adsorption testing, were insufficient for predicting the breakthrough points and retention capacities of Leaching cell tests, but adequately predicted the relative mobilities of Pb, Cu, and Cd. b) The Batch adsorption and SSE results showed that the influence of different retention mechanisms vary with heavy metal type and sorption concentrations. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.2 RESEARCH CONTRIBUTIONS 142 c) This study found that heavy metal migration was non-uniform, and followed unpredictable pathways. These pose as challenges to transport modeling. 4. Co-disposal of heavy me tal con tamina ted soil This study found that the Forest soil admix possessed stronger heavy metal retention than the bentonite admix. These findings suggest the possibility of mixing heavy metal contaminated soils with Forest soil as a remedial measure. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.3 RECOMMENDATIONS O N FURTHER RESEARCH 5.3 R E C O M M E N D A T I O N S O N F U R T H E R R E S E A R C H 143 1. Confirmation of proposed sorption model, and mechanism for hydraulic conductivity increase and heavy metal migration. a) The sorption model developed was able to describe binary and ternary systems of Pb, Cu, and Cd wi th bentonite, Forest soil, and Spruce bark. Recommended is further work with other cations and materials, and testing on quaternary and higher systems. b) Conducting studies involving the scanning electron microscope would confirm the proposed mechanism for hydraulic conductivity increase. Also, a detailed mapping of heavy metal distribution using SSE, is recommended. c) Further work is recommended in creating transport models based on the sorption model, and the proposed hydraulic conductivity increase mechanism. 2. Leaching cell testing. a) The decision to permeate samples from bottom to top caused the contaminated leachate to pool at the top of the Leaching cell. For future studies, permeating the samples from top to bottom is recommended. This w i l l prevent the over-adsorption of heavy metals at the discharge end. Another option would be to slice a thin layer of soil at the discharge end, before taking samples for Selective Sequential Extraction. b) In similating the conditions of a newly operating landfill, the current study did not apply confining pressures to the samples. Further research into the influence of confining pressures on heavy metal compatibility is recommended. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 5.3 RECOMMENDATIONS ON FURTHER RESEARCH 1 4 4 c) Further investigation is recommended regarding the influence of cation sorption characteristics on the flocculation of clays, and the hydraulic conductvity of clay barriers. d) The high concentration (500 mg L 1 ) of heavy metals used in the current study caused hydraulic conductivity values to reach an upper limit. Further research is recommended in investigating the minimum concentrations required to trigger increases in hydraulic conductivity. e) Further research is recommended in determining the influence of bacterial growth, and dissolved components of Forest soil and Spruce bark. 3. Sorption studies. a) In light of the current study, investigation into the sorption capacities and characteristics of calcium would be helpful in understanding the effects of heavy metals on clay barriers. b) Further research is required to determine why admixing Forest soil to bentonite appeared to promote greater precipitation and complexation. c) A n extensive SSE and Batch adsorption testing program is recommended to develop a sorption model that distinguishes specific sorption mechanisms. 4 . Clay barrier studies. a) Recommended, is further investigation on the mechanical (stress-strain) properties of the admixes used in the current study. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes 145 REFERENCES Acar, Y.B. , Hamidon, A . , Field, S.D., and Scott, L . 1985. The effect of organic fluids on hydraulic conductivity of compacted kaolinite. In Hydraulic Barriers in Soil and Rock, A S T M STP 874. Edited by A.I . Johnson, R.K. Frobel, N.J. Cavalli , and C B . Pettersosn. American Society for Testing Materials, Philadelphia, P A , pp. 171-187. Al-Asheh, S., and Duvnjak, Z., 1997. Sorption of cadmium and other heavy metals by pine bark. Journal of Hazardous Materials, 56: 35-51. Al lan , R.J. 1995. Impact of mining activities on the terrestrial and aquatic environment wi th emphasis on mitigation and remedial measures. In Heavy Metals: Problems and Solutions. Edited by W. Salomons, U . Forstner, and P. Mader. Springer-Verlag, Berlin Heidelberg, Germany, pp. 119-140. American Public Health Association ( A P H A ) , American Water Works Association ( A W W A ) , and Water Environment Federation (WEF) 1995. Standard method 9081. In Standard Methods for the Examination of Water and Wastewater. Edited by M . A . H . Franson. A P H A , Washington D C . Arnfalk, P., Wasay, A. , Tokunaga, S. 1996. A comparative study of C d , Cr(III), Cr(VI), H g , and Pb uptake by minerals and soil materials. Water, Air, and Soil Pollution, 87:131-148. A S T M , (1995). Annual Book of A S T M Standards: Soil and Rock (I-II) 4.08-4.09, American Society Testing and Materials, Philidelphia, P A . Bagchi, A . 1990. Design, Construction, and Monitoring of Sanitary Landfill . John Wiley & Sons, New York, U S A . Barry, G.A. , Chudek, P.J., Best, E.K., and Moody, P.W. 1995. Estimating sludge application rates to land based on heavy metal and phosphorus sorption characteristics of soil. Water Research 29(9): 2031-2034. Bladel, R.V., Halen, H . , Cloos, P. 1993. Calcium-zinc and calcium-cadmium exchange in suspensions of various types of clays. Clay Minerals, 28: 33-38. Cabral, A.R. 1992. A study of clay compatibility to heavy metal transport in permeability testing, Ph.D. Thesis. Department of C i v i l Engineering and Appl ied Mechanics, M c G i l l University, Montreal, Canada. 146 Carter, D.L. , Mortland, M . M . , and Kemper, W.D. 1986. Specific Surface. In Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods - Agronomy Monograph No . 9 (2nd Edition). American Society of Agronomy - Soil Science Society of America, Madison, WI, pp. 413-423. Chapman, D.L. 1913. A contribution to the theory of electrocapillarity. Phil. Mag. 25(6): 475-481. Crosby, Donald G . 1998. Environmental Toxicology and Chemistry. Oxford University Press, Oxford, N e w York. Daniel, D.E. 1995. State-of-the-art: laboratory hydraulic conductivity tests for saturated soils. In Hydraulic Conductivity and Waste Contaminant Transport in Soil, A S T M STP 1142. Edited by D.E. Daniel, and S.J. Trautwein. American Society for Testing and Materials, Philadelphia, P A . Denham, W.T. 1999. The hydraulic conductivity and adsorptivity of clay barrier materials containing organoclay, M . A.Sc. Thesis. Department of C i v i l Engineering, University of British Columbia. Vancouver, BC. Deshkar, A . M . , Bokade, S.S., Dara, S.S. 1990. Modified Hardwickia Binata bark for adsorption of mercury (II) from water. Water Research, 24(8): 1011-1016. Dunn, J.R., Mitchell , J.K. 1984. Fluid conductivity testing of fine-grained soils. Journal of Geotechnical Engineering. 110(11): 1648-1665. Eltantawy, I .M., and Arnold , P.W. 1973. Reappraisal of ethylene glycol mono-ethyl ether (EGME) method for surface area estimations of clays. Journal of Soil Science 24: 232-238. E P A , 1987. Batch type adsorption procedures for estimating soil attenuation of chemicals. Office of Solid Wase and Emergency Response, U.S. Environmental Protection Agency, EPA/530-SW-87-006, Washington, D.C. Ernst, W.H.0.1974. Schwemetallvegetation der Erde. Fischer, Stuttgart. Ernst, W.H.0.1990. Mine vegetation in Europe. In Heavy Metal Tolerance in Plants: Evolutionary Aspects. Edited by A J . Shaw. C R C Press, Boca Raton, pp. 21-51. Ernst, W.H.0.1995. Decontamination or consolidation of metal-contaminated soils by biological means. In Heavy Metals: Problems and Solutions. Edited by W. Salomons, U . Forstner, and P. Mader. Springer-Verlag, Berlin Heidelberg, Germany. 147 Ernst, W.H.O. , Josse-van Damme E .N .G 1983. Umweltbelastung durch Mineralstoffe. Fischer, Jena. Ernst, W.H.O. , Josse-van Damme E .N .G 1989. Zanieczyszezenic srodowiska substancjanii mineralnymi. Panstwowe Wydawnictwo Rolnicze i Lesne, Warszawa. Evans, L.J. 1989. Chemistry of metal retention by soils. Environmental Science and Technology, 23(9): 1046-1056. Fergusson, Jack E. 1990. The Heavy Elements: Chemistry, Environmental Impact and Health Effects. Pergamon Press, Oxford, UK. Fernandez, F. and Quigley, R . M . 1985. Hydraulic conductivity of natural clays permeated with simple l iquid hydrocarbons. Canadian Geotechnical Journal 22: 205-214. Field, J.A., and Lettinga, G. 1991. Treatment and detoxification of aqueous spruce bark extracts by Aspergillus Niger. Journal of Water Science and Technology 24(3/4): 127-137. Field, J.A., Leyendeckers, J.H., Alvarez, R.S., Lettinga, G. , Habets, L . H . A . 1988. The methanogenic toxicity of bark tannins and the anaerobic biodegradability of water soluble bark matter. Water, Science, and Technology, 20(1): 219-240. Fyfe, W.S. 1964. Geochemistry of Solids, A n Introduction. McGraw-Hi l l , N e w York. Foreman, D.E., and Daniel, D.E. 1986. Permeation of compacted clay wi th organic chemicals. Journal of Geotechnical Engineering, 112: 582-589. Freeze, R.A. , and Cherry, J.A. 1979. Groundwater. Prentice-Hall, Eaglewood Cliffs, NJ. Gao, S., Walker, W.J., Dahlgren, R. A . , Bold, J. 1997. Simultaneous sorption of C d , C u , N i , Z n , Pb, and C r on soils treated with sewage sludge supernatant. Water, Air, and Soil Pollution, 93: 331-345. Gloaguen, V . , and Morvan, H . 1997. Removal of heavy metal ions from aqueous solution by modified barks. Journal of Environmental Science and Health, A32(4): 901-912. Gouy, G . 1910. Sur la constitution de la charge electrique a la surface d'un electrolyte. Ann. Phys. (Paris), Series 4, 9: 457-468. Gutierrez, M . , and Fuentes, H.R. 1993. Modeling adsorption in multicomponent systems using a Freundlich-type isotherm. Journal of Contaminant Hydrology, 14: 247-260. 148 Hatton, D., and Pickering, W.F. 1980. The effect of p H on the retention of C u , Pb, Z n and C d by clay-humic mixtures. Water, Air, and Soil Pollution, 14:13-21. Hayes, K.F. 1987. Equilibrium, spectroscopic, and kinetic studies of ion adsorption at the oxide/aqueous interface. Ph.D. Dissertation, Stanford University. Hayes, M.H.B . , and Swift, R.S. (1978). The chemistry of soil organic colloids. In The Chemistry of Soil Constituents. Edited by D.J. Greenland, and M . H . B . Hayes. Wiley, New York, pp. 179-230. Haygreen, J.G., Bowyer, J.L. 1996. Forest Products and Wood Science. Iowa State University Press, Iowa. Hickey, M . G . , and Kittrick, J. A . 1984. Chemical partitioning of cadmium, copper, nickel, and zinc in soils and sediments containing high levels of heavy metals. Journal of Environmental Quality, 13(3): 372-376. Hinz , C , Buchter, B., and Selim, H . M . 1992. Heavy metal retention in soils: Application of multisite models to zinc sorption. In Engineering Aspects of Metals-Waste Management. Edited by L K . Iskandar, H . M . Selim. Lewis Publishers, Boca Raton, pp. 141-157. Igloria, V.I. , Hathhorn, W.E., and Yonge, D.R. 1998. Effects of natural organic matter on heavy metal transport during infiltration. Transportation Research Record, 1523:167-172. Irving, H . , and Williams, R.J.P. 1953. The stability of transition-metal complexes. Journal of the Chemical Society, pp. 3192-3210. Lindsay, W.L . 1979. Chemistry Equilibria in Soils. John Wiley & Sons, New York. Livens, F.R. 1991. Chemical reactions of metals with humic material. Environment Pollution, 70:183-208. Lo, I . M - C , Liljestrand, H . M . , Daniel, D.E. 1994. Hydraulic conductivity and adsorption parameters for pollutant transport through montmorillonite and modified montmorillonite clay liner materials. In Hydraulic Conductivity and Waste Contaminant Transport in Soil. A S T M STP1142. Edited by David E. Daniel and Stephen J. Trautwein. American Society for Testing Materials, Philadelphia, 1994. L u , J.C.S, Morrison, R.D., and Stearns, R.J. 1981. Leachate production muncipal landfills: Summary and assessment. In Land Disposal of Municpal Solid Waste. Edited by W.D. Shultz. 7th Annu. Res. Symp., EPA-600/9-81/002a. 1-17. U.S. Environ. Prot. Agency, Cincinnati, Ohio. 149 McGinley, P . M . , and Kmet, P. 1984. Formation, Characteristics, Treatment and Disposal of Leachate from Municipal Solid Waste Landfills. Bur. Solid Waste Manage., Wisconson Dept. of Natural Resources, Madison. McLean, E.0.1982. Soil p H and lime requirement. In Methods of Soil Analysis, Part 2: Chemical and Microbiological Properties. Edited by A . L . Page, R . H . Miller , and D.R. Keeney. American Society of Agronomy, Madison, WI, pp. 199-224. McQuarrie, D.A. , Rock, P .A. 1991. General Chemistry. W . H . Freeman, New York. Meegoda, N.J. and Rajapakse, R. A . 1993. Short-term and long-term permeabilities of contaminated clays. Journal of Environmental Engineering 119(4): 725-743. Mitchell, J.K., Hooper, D.R., Campanella, R.G. 1965. Permeability of compacted clay. Journal of the Soil Mechanics and Foundations Division, Proceedings of the ASCE, 91(SM4): 41-65. Mohamed, A . M . O . , and Antia, H.E . 1998. Geoenvironmental Engineering. Developments in Geotechnical Engineering, 82. Elsevier, Amsterdam, Netherlands. Morely, G.F., and Gadd, G . M . 1995. Sorption of toxic metals by fungi and clay minerals. Mycological Research, 99(12): 1429-1438. Nriagu, J.0.1979. Global inventory of natural and anthropogenic emissions of trace metals to the atmosphere. Nature, 279(5712): 409-411. Nriagu, J.O., and Pacyna, J.M. 1987. Worldwide contamination of air, water and soils with trace metals - quantitative assessment. Nature, 333. Peirce, J.J., Sallfors, G., Peel, T.A., and Witter, K . W . 1987. Effects of selected inorganic leachates on clay permeability. Journal of Geotechnical Engineering, 113(8): 915-919. Phadungchewit, Y. 1989. The role of p H and soil buffer capacity in heavy metal retention in clay soils, Ph.D. Thesis. Department of C i v i l Engineering and Appl ied Mechanics, M c G i l l University, Montreal, Canada. Puis, R.W., and Bohn, H . L . 1988. Sorption of cadmium, nickel, and zinc by kaolinite and montmorillonite suspensions. Soil Science Society of America Journal 52:1289-1292. Ragaini, Richard C. 1994. Technologies for environmental cleanup: toxic and hazardous waste management. In Technologies for environmental cleanup: toxic and hazardous 150 waste management 1-15. Edited by A . Avogadro, R.C. Ragaini. ECSC, EEC, E A E C , Netherlands. Ramos, L. , Hernandez, L . M . , and Gonzalez, M.J. 1994. Sequential fractionation of copper, lead, cadmium and zinc in soils from or near Donana National Park. Journal of Environmental Quality, 23: 50-57. Rose, S. 1989. The heavy-metal adsorption characteristics of Hawthorne formation (Florida, U.S.A.) sediments. Chemical Geology, 74: 365-370. Rousseaux, P., Navarro, and Vermande, P. 1989. Distribution of seven heavy metals in European household waste components. In Heavy Metals in the Environment. Edited by J.P. Vernet. C E P Consultants Ltd. , Edinburgh, U K , 2: 87-90. Sharma, H.D. , and Lewis, S.P. 1994. Waste Containment Systems, Waste Stabilization, and Landfills: Design and Evaluation. John Wiley & Sons, New York. Sheindorf, Ch. , Rebhun, M . , and Sheintuch, M . 1981. A Freudlich-type multicomponent isotherm. Journal of Colloid and Interface Science 79(1): 136-142. Soldatini, G.F., Riffaldi, R., and Levi -Minzi , R. 1976. Pb adsorption by soils. Water, Air, and Soil Pollution, 6:111-118. Sparks, D.L. 1995. Environmental Soil Chemistry. Academic Press, San Diego, California. Stevenson, F.J. 1982. Humus Chemistry: Genesis, Composition, Reactions. Wiley, New York. Tan, K . H . 1998. Principles of Soil Chemistry. Marcel Dekker, New York. Tchobanoglous, G., Theisen, H . , and Vig i l , S. 1993. Integrated Solid Waste Management: Engineering Principles and Management Issues. McGraw-Hi l l , Inc., N e w York. Uppot, J.O. and Stephenson, R.W. 1989. Permeability of clay under organic permants. Journal of Geotechnical Engineering 115(1): 115-131. U.S. Environmental Protection Agency (USEPA) 1984. Slurry Trench Construction for Pollution Migration Control, EPA-540/2-84-001. USEPA, Cincinnati, Ohio, p. 217. 151 U.S. Environmental Protection Agency (USEPA) 1989. Requirement for Hazardous Waste Landfill Design, Construction, and Closure, Seminar Publication, E P A / 6 2 5 / 4 -89/022. USEPA, Washington, D.C. p. 127. Vazquez, G., Antorrena, G., Gonzalez, J., and Doval, M . D . 1994. Adsorption of heavy metal ions by chemically modified pinus pinaster bark. Bioresource Technology, 48: 251-255. Weber, L . 1991. The permeability and adsorption capability of kaolinite and bentonite clays under heavy metal leaching, M.A.Sc. Thesis. Department of C i v i l Engineering and Appl ied Mechanics, M c G i l l University, Montreal, Canada. Yanful, E.K., Quigley, R . M . , Nesbitt, H .W. 1988. Heavy metal migration at a landfill site, Sarnia, Ontario, Canada - 2: metal partitioning and geotechnical implications. Applied Geochemistry, 3: 623-629. Yasumura, S., Vartsky, D., Ellis, K.J., and Cohn, S.H. 1980. Cadmuim in human beings. In Cadmium in the Environment Part 1: Ecological Cycling. Edited by Jerome O. Nriagu. John Wiley & Sons, New York. Yong, R .N. , Mohamed, A . M . O . , and Warkentin, B.P. 1992. Principles of Contaminant Transport in Soils. Developments in Geotechnical Engineering, 73. Elsvier, Amsterdam, Netherlands. Yong, R .N. , and Phadungchewit, Y . 1993. p H influence on selectivity and retention of heavy metals in some clay soils. Canadian Geotechnical Journal, 30: 821-833. A P P E N D I X A P H Y S I C A L PROPERTIES OF C L A Y B A R R I E R M A T E R I A L S A . l . P A R T I C L E SIZE D I S T R I B U T I O N A .2 . SPECIFIC G R A V I T Y O F A D M I X E S A . 3 . SPECIFIC S U R F A C E A R E A O F B E N T O N I T E A .4 . O P T I M U M M O I S T U R E C O N T E N T A N D M A X I M U M D R Y D E N S I T Y O F T H E A D M I X E S A P P E N D I X A . l . P A R T I C L E SIZE D I S T R I B U T I O N 153 Methods Dry sieving, performed according A S T M D422-63 (ASTM, 1995), was applied to particle sizes larger than 75 pm. The hydrometer analysis, adapted from A S T M D422-63 (ASTM, 1995), was performed to determine the size distribution of particles smaller than 75 mm. Dry sieving was performed for the sand, bentonite, Forest soil, and Spruce bark, while the hydrometer analysis was performed for the bentonite only. Details of the hydrometer analysis Five grams of dispersing agent (sodium hexametaphosphate) was added to approximately 700 ml of distilled water, and was stirred by a high-speed mixer. As the solution was stirred, 30.0 g of dry sample was slowly added. After 10 min. of mixing, the mixture was transferred to a 1.00 L sedimentation cylinder (« 45 cm high and 56 cm in diameter). Additional distilled was used to rinse all of the solids into the cylinder, and to fill the cylinder up to the 1.00 L mark. A second cylinder was filled with distilled water to store and rinse the hydrometer. The following measurements were taken prior to the hydrometer test: 1. Internal diameter of the sedimentation cylinder 2. Volume of hydrometer bulb (measured using water volume displacement) 3. Distances between the bulb center and the bulb's graduation marks 4. Height of the meniscus on the hydrometer stem Prior to starting the test, the sample was shaken for 30 s by using one hand to cover the open end of the cylinder, and continually inverting it upside-down and back. The start of the test was marked at the point where the cylinder was set on the table immediately after shaking. The hydrometer was inserted into the suspension to take readings at 0,15,30,60, and 120 s. After each reading, the hydrometer was rinsed and stored in the water-filled cylinder. After the 2 min. reading, the mixture was hand shaken again, and the test was restarted. When a consistent pair of readings was obtained, the test was restarted again, but the first reading was not taken until the 2 min. mark. Subsequent readings were taken at 4, 8,15 min., e tc . , until the elapsed time was large enough to give the minimum particle diameter. In addition to the hydrometer readings, the temperature was measured periodically. After the final reading, the mixture was transferred to a tared container, and dried for 24 hr. at 105 °C to determine the exact dry weight of the sample. 154 Calculations Equation for particle diameter D (mm) is, D = [(30nHr)/(981)(Gs - l ) ( p w t ) ] 1 / 2 where t (mm) is the time after the start of sedimentation, G s is the specific gravity of the particles (G s taken from Denham, 1999), p w (g/cm 3) is the density of water at temperature T, n (g/ cms) is the viscosity of water at temperature T, and H r (cm) is the corrected depth of fall. The corrected depth of fall H r (cm) is, H r = H + C m - ( V b / 2 A ) where H (cm) is the depth of fall measured from the meniscus to the center of the bulb, C m (cm) is the meniscus correction, Vb (cm3) is the volume of the bulb, and A (cm2) is the cross-sectional area of the cylinder. The percentage p by weight of particles with diameter smaller than D is, p = (62.26/ W 0 )(R - Cc + m) [G s / (G s -1)] where W 0 (g/L) is the oven-dried weight of material per liter of suspension, R (g/L) is the suspension unit weight reading from the hydrometer, Cd (g/L) is the dispersing agent correction, and m (g/L) is the temperature correction. The dispersing agent correction Cd (g/L) is, Cd = XdV s where Xd (g) is the amount of sodium hexametaphosphate added, and V s (L) is the volume of suspension. The temperature correction m (g/L) is, m = 1000(0.99823 - p w - [0.000025(T - 20)]} Results The plot of particle size vs. percent finer is found in section 4.1 (Figure 4.1.1). T A B L E A.1.1. Particle size distribution of sand, bentonite, air-dried Forest soil, and Spruce bark (Dry sieving data unless otherwise indicated). Sand Air-dried Forest soil Spruce bark Bentonite Size (mm) Percent Finer Size (mm) Percent Finer Size (mm) Percent Finer Size (mm) Percent Finer 0.833 99.8% 6.35 6.35 99.9% 0.42 99.5% Dry sieving 0.5 84.3% 2.38 99.9% 2.38 86.5% 0.3 99.2% 0.42 64.1% 0.833 77.0% 0.833 43.5% 0.25 98.9% 0.3 29.5% 0.5 58.8% 0.5 26.5% 0.149 98.0% 0.25 17.4% 0.42 51.9% 0.3 15.4% 0.125 96.7% 0.149 4.0% 0.3 41.7% 0.25 11.4% 0.104 95.2% 0.125 1.4% 0.25 35.1% 0.125 3.8% 0.074 91.3% 0.104 0.5% 0.125 16.9% 0.104 2.3% 0.0915 88.8% Hydrometer 0.074 0.1% 0 0.0% 0 0.0% 0.0648 88.2% 0 0.0% 0.0458 88.2% 0.0325 86.5% 0.0231 83.2% 0.0164 81.6% 0.0120 81.6% 0.0085 78.3% 0.0061 74.4% 0.0030 70.1% 0.0020 68.5% 0.0014 61.9% 0.0012 56.7% 0.0010 52.1% APPENDIX A.2. SPECIFIC GRAVITY OF ADMIXES 156 Specific gravities were measured for the admixes using the volume-displacement method described in A S T M D854-92 (ASTM, 1995). Calculations The equation for specific gravity G s (mass material/mass water) is, G s = W S / ( W s + W f S + W f w ) where W s is the weight of the dry admix, W f s is the weight of the flask filled wi th admix and water, and W f w is the weight of the flask filled with de-aired water only. Results TABLE A.2.1. Specific gravities of the admixes. Temperature (°C) W . ( g ) Wfw(g) Wfs(g) G s Bentonite admix 18 123.4 699.9 777.0 2.67 Forest soil admix 18 128.5 666.0 746.1 2.65 Spruce bark admix 17.5 133.9 694.1 777.5 2.65 A P P E N D I X A . 3 . SPECIFIC S U R F A C E A R E A OF B E N T O N I T E 157 Method The specific surface area was determined using an ethylene glycol monoethyl ether (EGME) method adapted from Eltantawy and Arnold (1973). This test was performed in cooperation with Denham (1999). A samples of air-dried bentonite weighing 1.1 g was placed in a tared aluminum foil dish and dried at 60 °C for 48 hr. The dish was weighed before and after drying to determine moisture content and clay dry weight. Approximately 1.5 ml of E G M E (Fisher) was added to the sample, which was then manually stirred to create a clay-E G M E slurry. Clay which adhered to the stirring rod was returned to the slurry by dripping E G M E onto the rod. The sample was then placed in a dessicator over anhydrous CaC/2 (granular, 20 mesh & finer, Fisher). A dish of E G M E was also placed in the dessicator. The sample was left to equilibrate for 30 min. The dessicator was then evacuated wi th a vacuum pump. The pump was disconnected after 45 min., but the dessicator was kept under vacuum for 24 hr. After 24 hr., the vacuum was released through a drying trap. The sample was weighed and returned to the dessicator. Then the dessicator was again evacuated for 45 min. and left for 24 hr. This procedure was repeated 8 more times until 240 hr. had passed, and a stable weight was achieved. In theory, the difference in the weight of the clays before and after the elapsed time represents a monomolecular layer of E G M E covering the internal and external surfaces of the sample. Calculations The equation for the specific surface area i n m 2 / g is provided by Carter et al. (1986): A = Wa/(W s -2.86) where A is the specific surface, in m 2 / g , W a , is the weight of E G M E retained by the sample, in g, W s is the weight of the dry clay, in g, and 0.000286 g is the weight of E G M E required to form a monomolecular layer on 1 m 2 of surface. 158 Results TABLE A.3.1. Specific surface of bentonite. Sample Ws(g) W a(g) A (mVg) Bentonite (duplicate 1) 1.0654 0.1414 464.1 Bentonite (duplicate 2) 1.0600 0.1397 460.8 Average 462.4 159 APPENDIX A.4. OPTIMUM MOISTURE CONTENT AND MAXIMUM DRY DENSITY OF THE ADMIXES The optimum moisture contents and maximum dry densities of the admixes were determined according to A S T M D1557-91 (ASTM, 1995), except for changes in the mold size, the number of compaction lifts, and the number of blows per lift (Table A.4.1). The changes were made to reflect the conditions used in the Leaching cell test. TABLE A.4.1. Changes made to the modified Proctor method. Test Cell size #of # of blows Compactive energy per layers per layer volume, ft-lb/cu ft Modified Proctor 4.6 in x 4 in dia. 5 25 56300 Current study 2.2 in x 4 in dia. 3 12,12,13 34700 Results The compaction curves are shown in Figures A.4.1 - A.4.3. Table A.4.2 summarizes the results for each admix. TABLE A.4.2. Optimum water contents and maximum dry densities of the bentonite, Forest soil, and Spruce bark admixes. Admix Optimum water content Maximum dry density (kg/m 3 ) Bentonite admix 12.7 % 1860 Forest soil admix 12.8 % 1830 Spruce bark admix 12.7 % 1815 160 1870.0 _ 1860.0 e 1850.0 "S, 1840.0 * 1830.0 & 1820.0 c 1810.0 Q 1800.0 £< 1790.0 ° 1780.0 1770.0 11.0% 11.5% 12.0% 12.5% 13.0% 13.5% 14.0% 14.5% 15.0% 15.5% Water Content (%) + Bentonite admix m Spruce bark admix A Forest soil admix FIGURE A.4.1. Compaction curves for the admixes. A P P E N D I X B C H E M I C A L PROPERTIES OF C L A Y B A R R I E R M A T E R I A L S B . l . S O I L p H B.2. C A T I O N E X C H A N G E C A P A C I T Y OF B E N T O N I T E A N D S A N D 162 APPENDIX B.l. SOILpH The p H of the bentonite and sand was measured according to a method adapted from McLean (1982). Soil p H measurements are performed usually with a 1:1 soil material:water ratio, or a 1:2 soil material:!).01 M calcium chloride (CaCh) ratio. These ratios were lowered because more liquid was needed to sufficiently wet the soil materials and to allow for settlement. The materials were measured into 100 ml beakers. After adding the water or 0.01 M CaCh, the suspensions were stirred occasionally for 30 minutes. Then, the suspensions were allowed to settle for the next 30 minutes. The p H was measured by placing the p H probe in the partially settled suspension. Table B.l . l summarizes the type and quantity of materials used for the p H measurement. TABLE B.l . l . The type and quantity of materials submitted to soil pH measurement. Material Liquid added Mass (oven-dried) of material (g) Volume of l iquid added (ml) Ratio Bentonite water 2 20 1:10 Bentonite 0.01 M CaCh 2 20 1:10 Sand water 5 5 1:1 Sand 0.01 M CaCh 5 10 1:2 Results TABLE B.1.2. The soil pH results for bentonite and sand. Type of Liquid Bentonite p H Sand p H Water 8.38 4.72 0.01 M CaCh 7.61 7.67 163 APPENDIX B.2. CATION EXCHANGE CAPACITY OF BENTONITE AND SAND The cation exchange capacity (CEC) of bentonite and sand was measured using the sodium acetate method adapted from Standard methods 9081 ( A P H A , A W W A , WEF, & 1995). The sodium acetate method is applicable for both calcareous and non-calcareous materials, but not acidic materials. Method Sodium saturation of exchange sites Two to four grams (dry mass) of material was placed into a centrifuge tube. After adding 33 ml of 1.0 NaOAc solution to the material, the suspension was shaken in a mechanical wrist-shaker for approximately 5 min. The centrifuge tube was then centrifuged at 3500 rpm for 15 min. After decanting the liquid, this procedure was repeated two more times. Thirty-three milliliters of 2-propanol was then added to wash the sample, and was again shaken in a mechanical wrist-shaker for approximately five minutes. After decanting the l iquid, this washing procedure was repeated two more times. The 2-propanol rinse was for removing all the Na in solution, without affecting the Na sorbed onto exchange sites. Displacement of the sodium with ammonium To displace the Na from the exchange sites, 33 ml if NHAOAC was added to the sample, and the was shaken in a mechanical shaker for approximately 5 min. The liquid then was decanted into a 100 ml volumetric flask. This procedure was repeated two more times. Each time, the l iquid was decanted into the same flask. Next, the 100 ml flask containing the decanted solution was filled to the 100 ml mark with NH4OAC, and the Na concentration of the solution was determined using Atomic Absorption Spectrophotometry. Calculations C E C in centimoles of positive charge per kilogram (cmol/kg) was calculated from the following equation: C E C = C N a • Vfi • 1 g/1000 mg • 1000 g/1 kg • 1 mol/23 g • 100 cmol/1 mol where C N 3 is the concentration of Na (mg/L) in the volumetric flask, and Vfi (L) is the volume of the flask. Results T A B L E B.2.1. The cation exchange capacity of bentonite and sand. N a concentration (mg/L) C E C (cmol/kg) Average Bentonite (triplicate 1) 272.9 59.3 Bentonite (triplicate 2) 273.9 59.5 Bentonite (triplicate 3) 276.9 60.2 59.7 Sand (triplicate 1) 0 Sand (triplicate 2) 0 Sand (triplicate 3) 0 0 APPENDIX C METHODS SUPPLEMENT C l . E Q U I P M E N T LISTS A N D D E S C R I P T I O N S C 2 . C O M P A C T I O N P R O C E D U R E F O R T H E L E A C H I N G C E L L TEST 166 A P P E N D I X C l . E Q U I P M E N T LISTS A N D D E S C R I P T I O N S For the Batch adsorption test Listed below are some important items required for the Batch adsorption test. The equipment was made of materials that are non-reactive with heavy metals. • 50 ml polypropylene centrifuge test tube • rotator or shaker • centrifuge (Beckman GS-6 model) • test tubes and test tube pre-filters (for Forest soil and Spruce bark) for dilutions • 1 each - 25 ml , 50 ml , and 100 ml volumetric flasks • 1 each -1 ml , 2 ml , 4 ml , 6 ml , and 10 ml pipettes For the Leaching cell test The following are important items needed for the Leaching cell test. Figures C.1.1 - C. l .2 , show schematics for the compaction hammer, compaction mold, and the Leaching cell. These equipment were made of materials that are non-reactive with heavy metals: Compaction apparatus - compaction hammer, compaction mold, paper disk, saran wrap, ruler, knife Leaching cell apparatus - leaching cell, 100 ml graduated cylinder (discharge collector), leachate reservoir, pressure gauge dilution equipment - (see equipment for Batch adsorption test) 167 o b o • o • o s C rt u Ol s s w J5 C o •** * * o Rl a c 'I |3 Rt Q> . & ts J£ bo » 1.S s S £ 3 •w 01 to ,2 > vt* Z w o • i 01 o o o rt U va PS O Leaching cell - top lid (plan view) Leaching cell - middle (plan view) screw holes discharge port 114 mm dia. 101 mm dia. Leaching cell - top lid (side view) 7 mm Chamber for porous stone Leaching cell - middle (side view) T 56.5 mm Leaching cell - bottom lid (side view) Leaching cell - bottom lid (plan view) Note: Everything except for porous stones are made of Plexiglas FIGURE C.1.2. Diagrams of Leaching cell. 169 For the Selective Sequential Extraction test The list below outlines some important items needed to perform one SSE extraction. A l l items are non-reactive with heavy metals: • wire saw • ruler • small spoon • centrifuge • 50 m l centrifuge polypropylene test tube • 250 ml glass flask • glass reflux cap • dilution equipment (see equipment for Batch adsorption test) 170 A P P E N D I X C.2. C O M P A C T I O N P R O C E D U R E F O R T H E L E A C H I N G C E L L T E S T The compaction procedure was modified from the modified Proctor procedure used in A S T M 1557-91 (ASTM, 1995). Figure C.2.1 illustrates the compaction procedure. To improve the seal between the cell wal l and the compacted sample, the inner wal l of the Leaching cell was smeared with a thin layer of bentonite/ water paste. Then, a paper disk (cut out from regular plain loose-leaf paper) was fitted into the bottom mold piece. Next, saran wrap was placed over the paper disk; the cell was fitted onto the bottom mold piece; and the entire assembly was weighed. The paper disk was there to prevent the compacted sample from sticking to the mold, and the purpose of the saran wrap was to keep the paper disk dry. Saran wrap used by itself ripped too easily during compaction. The rest of the mold was attached to the cell; then the admix was compacted into the cell in 3 lifts. The purpose of the mold is to prevent the cell from deformation during compaction. Twelve blows were used for the first 2 lifts, and 13 blows were used for the last lift. For consistency, the same pattern of blows were applied for every test (Figure C.2.2). After compaction, the top portion of the mold was removed, and the top of the sample was leveled using a ruler. The sample, leaching cell, and bottom mold piece were weighed together to obtain the wet mass of the sample. A t this point, a small sample was taken from the admix container for water content analysis. The bottom mold piece, paper disk, and saran wrap were then removed from the Leaching cell. A knife was used to scarify the bottom of the sample, and then the top and bottom lids were attached onto the cell. Finally, the cell was attached to the rest of the Leaching cell apparatus, by connecting it to the reservoir, and discharge collection container. Dry density, water content, and saturation were calculated for the Leaching cell samples. 171 -a u o IH CH c o • X ! u « n 43 •5 gi iT S « CH w " S Cu to M Is s > a c = 2-3 5 <JH o XI to o u 01 >£ UH o co e « Sb (8 CM u u t in 172 Compaction pattern for 1st lift Note: Numbers signify sequence and location of blows for each lift. Compaction pattern for 2nd lift Compaction pattern for 3rd lift F I G U R E C.2.2. Striking pattern for compaction hammer. A P P E N D I X D B A T C H A D S O R P T I O N T E S T C A L C U L A T I O N S A N D D A T A 173 D . l . C A L C U L A T I O N F O R C O N V E R T I N G M A S S U N I T S I N T O M O L A R U N I T S D.2. B A T C H A D S O R P T I O N D A T A F O R S I N G L E H E A V Y M E T A L L E A C H A T E S D.3. B A T C H A D S O R P T I O N D A T A F O R B I N A R Y H E A V Y M E T A L L E A C H A T E S D.4. B A T C H A D S O R P T I O N D A T A F O R T E R N A R Y H E A V Y M E T A L L E A C H A T E S A P P E N D I X D . l . C A L C U L A T I O N F O R C O N V E R T I N G M A S S U N I T S I N T O M O L A R U N I T S 174 The equations for converting from [mg/L] to [mmol/L] are, [mmol/L] of Pb = Img/LlofPb 207.2 [mmol/L] of Cu = [mg/Ll of Cu 63.55 [mmol/L] of Cd = [mg/Ll of Cd 112.4 The equations for converting from [mg/g] to [cmol/kg] are, [cmol of Pb/kg of material] = [mg of Pb/g of material] • 1 g • 1 moi • 100 cmol • 1000 g 1000 mg 207.2 g 1 moi 1kg [cmol of Cu/kg of material] = [mg oiCu/g of material] • 1 g • 1 moi • 100 cmol • 1000 g 1000 mg 63.55 g 1 moi 1kg [cmol of Cd/kg of material] = [mg oiCd/g of material] 1000 mg l m o l • 100 cmol • 1000 g 112.4 g 1 moi 1 kg 175 A P P E N D I X D . 2 . B A T C H A D S O R P T I O N D A T A F O R S I N G L E H E A V Y M E T A L L E A C H A T E S Pb sorption of bentonite Initial Pb cone. Final Pb cone. Sorbed Pb concentration Final m g L - i mmol L 1 m g L - i mmol L i mg Pb per g bentonite cmol Pb per kg bentonite solution p H 0.0 0.0 0.0 0.0 0.0 0.0 7.44 0.0 0.0 0.0 0.0 0.0 0.0 7.42 50.0 0.2 0.1 0.0 2.5 1.2 6.84 50.0 0.2 0.2 0.0 2.5 1.2 6.94 100.0 0.5 4.4 0.0 4.8 2.3 6.57 100.0 0.5 4.7 0.0 4.8 2.3 6.53 200.0 1.0 32.7 0.2 8.4 4.0 6.17 200.0 1.0 34.5 0.2 8.3 4.0 6.18 500.0 2.4 108.4 0.5 19.6 9.5 5.87 500.0 2.4 106.2 0.5 19.7 9.5 5.89 1000.0 4.8 412.2 2.0 29.4 14.2 5.30 1000.0 4.8 417.9 2.0 29.1 14.0 5.38 2000.0 9.7 1219.0 5.9 39.1 18.8 5.12 2000.0 9.7 1210.5 5.8 39.5 19.1 5.13 3000.0 14.5 2071.0 10.0 46.5 22.4 4.99 3000.0 14.5 2083.5 10.1 45.8 22.1 5.00 176 Cu sorption of bentonite Initial Cu cone. Final Cu cone. Sorbed Cu concentration Final mg L- i mmol L 1 m g L 1 mmol L 1 mg Cu per g bentonite cmol Cu per kg bentonite solution p H 0.0 0.0 0.0 0.0 0.0 0.0 7.46 0.0 0.0 0.0 0.0 0.0 0.0 7.44 46.1 0.7 6.0 0.1 2.0 3.2 6.45 46.1 0.7 6.5 0.1 2.0 3.1 6.50 92.9 1.5 32.6 0.5 3.0 4.7 5.94 92.9 1.5 30.6 0.5 3.1 4.9 5.87 183.8 2.9 94.3 1.5 4.5 7.0 5.48 183.8 2.9 96.3 1.5 4.4 6.9 5.50 462.5 7.3 324.8 5.1 6.9 10.8 5.23 462.5 7.3 325.8 5.1 6.8 10.8 5.21 932.5 14.7 736.5 11.6 9.8 15.4 4.99 932.5 14.7 740.3 11.6 9.6 15.1 5.00 1862.0 29.3 1615.0 25.4 12.4 19.4 4.81 1862.0 29.3 1622.0 25.5 12.0 18.9 4.83 2792.5 43.9 2516.0 39.6 13.8 21.8 4.72 2792.5 43.9 2490.0 39.2 15.1 23.8 4.74 3748.0 59.0 3403.8 53.6 17.2 27.1 4.59 3748.0 59.0 3452.5 54.3 14.8 23.2 4.61 177 Cd sorption of bentonite Initial Cd cone. Final Cd cone. Sorbed Cd concentration Final mmol L _ 1 m g L 1 mmol L _ 1 mg Cd per g bentonite cmol Cd per kg bentonite solution p H 0.0 0.0 0.0 0.0 0.0 0.0 7.23 0.0 0.0 0.0 0.0 0.0 0.0 7.23 49.4 0.4 24.3 0.2 1.3 1.1 6.85 49.4 0.4 24.2 0.2 1.3 1.1 6.84 98.3 0.9 53.9 0.5 2.2 2.0 6.74 98.3 0.9 53.4 0.5 2.2 2.0 6.71 194.7 1.7 121.2 1.1 3.7 3.3 6.57 194.7 1.7 121.9 1.1 3.6 3.2 6.56 498.7 4.4 351.0 3.1 7.4 6.6 6.38 498.7 4.4 355.3 3.2 7.2 6.4 6.37 1018.6 9.1 761.0 6.8 12.9 11.5 6.22 1018.6 9.1 765.6 6.8 12.7 11.3 6.25 2050.4 18.2 1648.6 14.7 20.1 17.9 6.07 2050.4 18.2 1656.2 14.7 19.7 17.5 6.12 3053.0 27.2 2618.3 23.3 21.7 19.3 6.04 3053.0 27.2 2631.2 23.4 21.1 18.8 6.05 3984.5 35.4 3482.3 31.0 25.1 22.3 5.95 3984.5 35.4 3569.7 31.8 20.7 18.5 6.05 4923.6 43.8 4367.1 38.9 27.8 24.8 5.98 4923.6 43.8 4326.5 38.5 29.9 26.6 5.97 178 Pb sorption of Forest soil Initial Pb cone. Final Pb cone. Sorbed Pb concentration Final m g L 1 mmol L 1 m g L 1 mmol L 1 mg Pb per g Forest soil cmol Pb per kg Forest soil solution p H 0.0 0.0 0.1 0.0 0.0 0.0 3.32 0.0 0.0 0.2 0.0 0.0 0.0 3.31 50.0 0.2 4.1 0.0 7.2 3.5 3.26 50.0 0.2 4.1 0.0 7.2 3.5 3.26 100.0 0.5 13.0 0.1 13.6 6.6 3.21 100.0 0.5 11.4 0.1 13.8 6.7 3.21 200.0 1.0 38.3 0.2 25.2 12.2 3.13 200.0 1.0 40.1 0.2 24.9 12.0 3.13 500.0 2.4 188.5 0.9 48.6 23.5 2.99 500.0 2.4 187.3 0.9 48.8 23.5 2.99 1000.0 4.8 559.0 2.7 68.8 33.2 2.88 1000.0 4.8 556.8 2.7 69.1 33.4 2.88 2000.0 9.7 1405.0 6.8 92.8 44.8 2.79 2000.0 9.7 1451.5 7.0 85.6 41.3 2.79 3000.0 14.5 2325.0 11.2 105.3 50.8 2.75 3000.0 14.5 2314.0 11.2 107.0 51.6 2.75 4000.0 19.3 3230.0 15.6 120.1 58.0 2.70 4000.0 19.3 3311.7 16.0 107.4 51.8 2.71 Cu sorption of Forest soil NOTE: w/c = 212%; weighed sample is 0.8385 g; dry mass is 0.2688 g (other Batch tests used 0.5 g dry mass) Initial Cu cone. Final Cu cone. Sorbed Cu concentration Final p H m g L 1 mmol L 1 m g L 1 mmol L 1 mg Cu per g Forest soil cmol C M per kg Forest soil solution 0.0 0.0 0.0 0.0 0.0 0.0 3.17 0.0 0.0 0.0 0.0 0.0 0.0 3.19 46.1 0.7 8.0 0.1 3.5 5.6 3.07 46.1 0.7 7.8 0.1 3.6 5.6 3.09 92.9 1.5 26.0 0.4 6.2 9.8 3.01 92.9 1.5 25.8 0.4 6.2 9.8 3.01 183.8 2.9 79.4 1.3 9.7 15.3 2.92 183.8 2.9 80.3 1.3 9.6 15.1 2.92 462.5 7.3 299.2 4.7 15.2 23.9 2.80 462.5 7.3 298.2 4.7 15.3 24.0 2.80 932.5 14.7 720.0 11.3 19.7 31.1 2.71 932.5 14.7 728.5 11.5 19.0 29.8 2.72 1832.0 28.8 1583.7 24.9 23.1 36.3 2.63 1832.0 28.8 1608.2 25.3 20.8 32.7 2.64 2758.0 43.4 2419.6 38.1 31.4 49.5 2.58 2758.0 43.4 2458.8 38.7 27.8 43.8 2.60 3666.0 57.7 3421.7 53.8 22.7 35.7 2.56 3666.0 57.7 3420.0 53.8 22.9 36.0 2.57 179 Cd sorption of Forest soil Initial Cd cone. Final Cd cone. Sorbed Cd concentration Final p H m g L 1 mmol L 1 mgL-i mmol L _ 1 mg Cd per g Forest soil cmol Cd per kg Forest soil solution 0.0 0.0 0.0 0.0 0.0 0.0 7.23 0.0 0.0 0.0 0.0 0.0 0.0 3.17 0.0 0.0 0.0 0.0 0.0 0.0 3.18 49.4 0.4 30.2 0.3 1.8 1.6 3.15 49.4 0.4 30.9 0.3 1.7 1.5 3.16 98.3 0.9 64.4 0.6 3.2 2.8 3.15 98.3 0.9 63.9 0.6 3.2 2.8 3.15 194.7 1.7 136.0 1.2 5.5 4.9 3.12 194.7 1.7 136.9 1.2 5.4 4.8 3.13 498.7 4.4 380.1 3.4 11.0 9.8 3.06 498.7 4.4 382.7 3.4 10.8 9.6 3.07 1018.6 9.1 839.4 7.5 16.7 14.8 2.99 1018.6 9.1 821.1 7.3 18.4 16.3 3.01 2050.4 18.2 1764.6 15.7 26.6 23.6 2.92 2050.4 18.2 1766.6 15.7 26.4 23.5 2.94 3053.0 27.2 2760.5 24.6 27.2 24.2 2.88 3053.0 27.2 2792.6 24.8 24.2 21.5 2.88 3984.5 35.4 3675.1 32.7 28.8 25.6 2.85 3984.5 35.4 0.0 2.86 Pb sorption of Spruce bark Initial Pb cone. Final Pb cone. Sorbed Pb concentration Final p H mg L 1 mmol L 1 mg L 1 mmol L 1 mg Pb per g Spruce bark cmol Pb per kg Spruce bark solution 0.0 0.0 0.1 0.0 0.0 0.0 4.02 0.0 0.0 0.1 0.0 0.0 0.0 3.72 50.0 0.2 1.4 0.0 2.4 1.2 3.96 50.0 0.2 1.4 0.0 2.4 1.2 4.01 100.0 0.5 100.0 0.5 200.0 1.0 200.0 1.0 500.0 2.4 106.9 0.5 19.7 9.5 3.68 500.0 2.4 106.5 0.5 19.7 9.5 3.68 1000.0 4.8 420.3 2.0 29.0 14.0 3.5 1000.0 4.8 421.3 2.0 28.9 14.0 3.49 2000.0 9.7 1277.0 6.2 36.2 17.4 3.33 2000.0 9.7 1270.0 6.1 36.5 17.6 3.33 3000.0 14.5 2183.0 10.5 40.9 19.7 3.24 3000.0 14.5 2187.0 10.6 40.7 19.6 3.24 4000.0 19.3 3148.3 15.2 42.6 20.6 3.18 4000.0 19.3 3093.3 14.9 45.3 21.9 3.18 180 Cu sorption of Spruce bark Initial Cu cone. Final C M cone. Sorbed C M concentration Final p H m g L 1 mmol L 1 m g L 1 mmol L - 1 mg C M per g Spruce bark cmol C M per kg Spruce bark solution 0.0 0.0 0.0 0.0 0.0 0.0 3.98 0.0 0.0 0.0 0.0 0.0 0.0 4.00 46.1 0.7 11.9 0.2 1.7 2.7 3.95 46.1 0.7 12.0 0.2 1.7 2.7 3.96 92.9 1.5 28.2 0.4 3.2 5.1 3.88 92.9 1.5 27.9 0.4 3.2 5.1 3.92 183.8 2.9 82.1 1.3 5.1 8.0 3.77 183.8 2.9 81.8 1.3 5.1 8.0 3.74 462.5 7.3 318.7 5.0 7.2 11.3 3.56 462.5 7.3 315.2 5.0 7.4 11.6 3.56 932.5 14.7 755.0 11.9 8.9 14.0 3.41 932.5 14.7 750.0 11.8 9.1 14.4 3.42 1832.0 28.8 1640.5 25.8 9.6 15.1 3.28 1832.0 28.8 1621.9 25.5 10.5 16.5 3.29 2758.0 43.4 2558.8 40.3 10.0 15.7 3.21 2758.0 43.4 2492.1 39.2 13.3 20.9 3.22 3666.0 57.7 3516.0 55.3 7.5 11.8 3.16 3666.0 57.7 3490.0 54.9 8.8 13.8 3.17 4728.0 74.4 4536.0 71.4 9.6 15.1 3.12 4728.0 74.4 4472.0 70.4 12.8 20.1 3.13 181 Cd sorption of Spruce bark Initial Cd cone. Final Cd cone. Sorbed Cd concentration Final p H m g L 1 mmol L 1 m g L 1 mmol L 1 mg Cd per g Spruce bark cmol Cd per kg Spruce bark solution 0.0 0.0 0.0 0.0 0.0 0.0 4.04 0.0 0.0 0.0 0.0 0.0 0.0 4.07 49.4 0.4 28.6 0.3 1.0 0.9 3.93 49.4 0.4 28.8 0.3 1.0 0.9 3.94 98.3 0.9 58.6 0.5 2.0 1.8 3.92 98.3 0.9 59.0 0.5 2.0 1.7 3.92 194.7 1.7 125.1 1.1 3.5 3.1 3.89 194.7 1.7 127.4 1.1 3.4 3.0 3.89 498.7 4.4 373.1 3.3 6.3 5.6 3.84 498.7 4.4 370.1 3.3 6.4 5.7 3.84 1018.6 9.1 808.8 7.2 10.5 9.3 3.74 1018.6 9.1 809.9 7.2 10.4 9.3 3.74 2050.4 18.2 1711.0 15.2 17.0 15.1 3.65 2050.4 18.2 1726.8 15.4 16.2 14.4 3.67 3053.0 27.2 2743.5 24.4 15.5 13.8 3.61 3053.0 27.2 2763.0 24.6 14.5 12.9 3.61 3984.5 35.4 3630.6 32.3 17.7 15.7 3.57 3984.5 35.4 3642.7 32.4 17.1 15.2 3.58 4923.6 43.8 4420.9 39.3 25.1 22.4 3.55 4923.6 43.8 4409.5 39.2 25.7 22.9 3.55 182 A P P E N D I X D .3 B A T C H A D S O R P T I O N D A T A F O R B I N A R Y H E A V Y M E T A L L E A C H A T E S Pb and Cu sorption of bentonite in mass units Initial Pb cone. Final Pb cone. Initial C M cone. Final C M cone. Sorbed Pb Sorbed C M Final p H m g L 1 m g L 1 m g L 1 m g L 1 mg Pb per g bentonite mg C M per g bentonite 242.1 46.2 0.0 0.0 9.8 0.0 5.68 242.1 45.1 0.0 0.0 9.9 0.0 5.75 239.7 56.9 50.8 23.8 9.1 1.4 5.4 239.7 56.7 50.8 23.4 9.2 1.4 5.42 237.9 59.3 100.0 57.8 8.9 2.1 5.31 237.9 61.9 100.0 58.0 8.8 2.1 5.32 238.0 69.9 250.0 171.0 8.4 4.0 5.18 238.0 70.7 250.0 171.6 8.4 3.9 5.2 238.0 84.9 500.0 393.0 7.7 5.4 5.06 238.0 83.7 500.0 385.5 7.7 5.7 5.08 238.0 102.1 1000.0 865.0 6.8 6.8 4.9 238.0 103.4 1000.0 858.0 6.7 7.1 4.98 982.6 408.5 0.0 0.0 28.7 0.0 5.36 982.6 409.1 0.0 0.0 28.7 0.0 5.36 982.4 438.9 51.5 31.4 27.2 1.0 5.24 982.4 431.0 51.5 31.1 27.6 1.0 5.25 987.4 449.9 104.2 67.7 26.9 1.8 5.19 987.4 455.8 104.2 68.5 26.6 1.8 5.2 985.0 499.2 250.0 185.1 24.3 3.2 5.09 985.0 496.2 250.0 184.5 24.4 3.3 5.1 985.0 527.5 500.0 401.5 22.9 4.9 5.01 985.0 539.0 500.0 403.5 22.3 4.8 5.02 985.0 578.0 1000.0 877.0 20.4 6.2 4.91 985.0 577.0 1000.0 887.0 20.4 5.7 4.92 183 Pb and Cu sorption of bentonite in molar units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. Sorbed Pb Sorbed Cu Final p H mmol L 1 mmol L 1 mmol L _ 1 mmol L 1 cmol Pb per kg bentonite cmol Cu per kg bentonite 1.2 0.2 0.0 0.0 4.7 0.0 5.68 1.2 0.2 0.0 0.0 4.8 0.0 5.75 1.2 0.3 0.8 0.4 4.4 2.1 5.40 1.2 0.3 0.8 0.4 4.4 2.2 5.42 1.1 0.3 1.6 0.9 4.3 3.3 5.31 1.1 0.3 1.6 0.9 4.2 3.3 5.32 1.1 0.3 3.9 2.7 4.1 6.2 5.18 1.1 0.3 3.9 2.7 4.0 6.2 5.20 1.1 0.4 7.9 6.2 3.7 8.4 5.06 1.1 0.4 7.9 6.1 3.7 9.0 5.08 1.1 0.5 15.7 13.6 3.3 10.6 4.90 1.1 0.5 15.7 13.5 3.2 11.2 4.98 4.7 2.0 0.0 0.0 13.9 0.0 5.36 4.7 2.0 0.0 0.0 13.8 0.0 5.36 4.7 2.1 0.8 0.5 13.1 1.6 5.24 4.7 2.1 0.8 0.5 13.3 1.6 5.25 4.8 2.2 1.6 1.1 13.0 2.9 5.19 4.8 2.2 1.6 1.1 12.8 2.8 5.20 4.8 2.4 3.9 2.9 117 5.1 5.09 4.8 2.4 3.9 2.9 11.8 5.2 5.10 4.8 2.5 7.9 6.3 11.0 7.7 5.01 4.8 2.6 7.9 6.3 10.8 7.6 5.02 4.8 2.8 15.7 13.8 9.8 9.7 4.91 4.8 2.8 15.7 14.0 9.8 8.9 4.92 1 8 4 Pb and Cu sorption of Forest soil in mass units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. Sorbed Pb Sorbed Cu Final m g L 1 m g L 1 m g L 1 m g L 1 mg Pb per g Forest soil mg C M per g Forest soil p H 242.1 14.8 0.0 0.0 11.4 0.0 3.20 242.1 15.2 0.0 0.0 11.3 0.0 3.20 239.7 20.4 50.8 5.9 11.0 2.2 3.13 239.7 20.7 50.8 5.8 11.0 2.3 3.13 237.9 26.0 100.0 19.1 10.6 4.0 3.08 237.9 23.7 100.0 19.1 10.7 4.0 3.07 238.0 36.8 250.0 90.1 10.1 8.0 2.96 238.0 36.2 250.0 89.4 10.1 8.0 2.96 238.0 53.0 500.0 265.0 9.3 11.8 2.86 238.0 60.0 500.0 261.0 8.9 12.0 2.87 238.0 81.0 1000.0 688.0 7.9 15.6 2.77 238.0 91.0 1000.0 680.0 7.4 16.0 2.77 982.6 205.2 0.0 0.0 38.9 0.0 2.97 982.6 207.0 0.0 0.0 38.8 0.0 2.97 982.4 234.5 51.5 13.7 37.4 1.9 2.93 982.4 232.8 51.5 13.7 37.5 1.9 2.92 987.4 257.0 104.2 35.6 36.5 3.4 2.89 987.4 259.2 104.2 36.1 36.4 3.4 2.89 985.0 328.8 250.0 124.4 32.8 6.3 2.83 985.0 326.0 250.0 125.2 33.0 6.2 2.83 985.0 382.0 500.0 308.0 30.2 9.6 2.77 985.0 382.5 500.0 310.0 30.1 9.5 2.78 985.0 489.0 1000.0 751.0 24.8 12.5 2.71 985.0 494.0 1000.0 746.0 24.6 12.7 2.72 185 Pb and Cu sorption of Forest soil in molar units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. Sorbed Pb Sorbed Cu Final mmol L 1 mmol L _ 1 mmol L 1 mmol L 1 cmol Pb per kg Forest soil cmol C M per kg Forest soil p H 1.2 0.1 0.0 0.0 5.5 0.0 3.20 1.2 0.1 0.0 0.0 5.5 0.0 3.20 1.2 0.1 0.8 0.1 5.3 3.5 3.13 1.2 0.1 0.8 0.1 5.3 3.5 3.13 1.1 0.1 1.6 0.3 5.1 6.4 3.08 1.1 0.1 1.6 0.3 5.2 6.4 3.07 1.1 0.2 3.9 1.4 4.9 12.6 2.96 1.1 0.2 3.9 1.4 4.9 12.6 2.96 1.1 0.3 7.9 4.2 4.5 18.5 2.86 1.1 0.3 7.9 4.1 4.3 18.8 2.87 1.1 0.4 15.7 10.8 3.8 24.5 2.77 1.1 0.4 15.7 10.7 3.5 25.2 2.77 4.7 1.0 0.0 0.0 18.8 0.0 2.97 4.7 1.0 0.0 0.0 18.7 0.0 2.97 4.7 1.1 0.8 0.2 18.0 3.0 2.93 4.7 1.1 0.8 0.2 18.1 3.0 2.92 4.8 1.2 1.6 0.6 17.6 5.4 2.89 4.8 1.3 1.6 0.6 17.6 5.4 2.89 4.8 1.6 3.9 2.0 15.8 9.9 2.83 4.8 1.6 3.9 2.0 15.9 9.8 2.83 4.8 1.8 7.9 4.8 14.6 15.1 2.77 4.8 1.8 7.9 4.9 14.5 14.9 2.78 4.8 2.4 15.7 11.8 12.0 19.6 2.71 4.8 2.4 15.7 11.7 11.8 20.0 2.72 186 Pb and Cu sorption of Spruce bark in mass units Initial Pb cone. Final Pb cone. Initial Cu cone. Final C M cone. Sorbed Sorbed C M Final m g L 1 m g L - i m g L 1 m g L 1 mg Pb per g Spruce bark mg C M per g Spruce bark p H 242.1 26.2 0.0 0.0 10.8 0.0 4.16 242.1 25.9 0.0 0.0 10.8 0.0 4.14 239.7 38.0 50.8 20.4 10.1 1.5 3.98 239.7 36.9 50.8 20.2 10.1 1.5 4.00 237.9 47.4 100.0 48.5 9.5 2.6 3.87 237.9 47.9 100.0 49.0 9.5 2.6 3.86 238.0 78.0 250.0 170.2 8.0 4.0 3.72 238.0 76.4 250.0 165.8 8.1 4.2 3.71 238.0 101.0 500.0 392.5 6.9 5.4 3.59 238.0 108.0 500.0 389.5 6.5 5.5 3.61 238.0 157.0 1000.0 873.0 4.1 6.4 3.47 238.0 141.0 1000.0 865.0 4.9 6.8 3.49 982.6 429.8 0.0 0.0 27.6 0.0 3.68 982.6 414.7 0.0 0.0 28.4 0.0 3.69 982.4 478.2 51.5 35.4 25.2 0.8 3.65 982.4 470.1 51.5 35.3 25.6 0.8 3.70 987.4 493.6 104.2 71.5 24.7 1.6 3.63 987.4 481.9 104.2 70.9 25.3 1.7 3.63 985.0 581.1 250.0 193.5 20.2 2.8 3.55 985.0 574.8 250.0 193.5 20.5 2.8 3.56 985.0 634.5 500.0 411.0 17.5 4.5 3.49 985.0 630.0 500.0 412.5 17.8 4.4 3.50 985.0 730.0 1000.0 919.0 12.8 4.1 3.41 985.0 715.0 1000.0 913.0 13.5 4.4 3.42 187 Pb and Cu sorption of Spruce bark in molar units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. Sorbed Pb Sorbed Cu Final mmol L _ 1 mmol L 1 mmol L 1 mmol L 1 cmol Pb per kg cmol Cu per kg p H Spruce bark Spruce bark 1.2 0.1 0.0 0.0 5.2 0.0 4.16 1.2 0.1 0.0 0.0 5.2 0.0 4.14 1.2 0.2 0.8 0.3 4.9 2.4 3.98 1.2 0.2 0.8 0.3 4.9 2.4 4.00 1.1 0.2 1.6 0.8 4.6 4.1 3.87 1.1 0.2 1.6 0.8 4.6 4.0 3.86 1.1 0.4 3.9 2.7 3.9 6.3 3.72 1.1 0.4 3.9 2.6 3.9 6.6 3.71 1.1 0.5 7.9 6.2 3.3 8.5 3.59 1.1 0.5 7.9 6.1 3.1 8.7 3.61 1.1 0.8 15.7 13.7 2.0 10.0 3.47 1.1 0.7 15.7 13.6 2.3 10.6 3.49 4.7 2.1 0.0 0.0 13.3 0.0 3.68 4.7 2.0 0.0 0.0 13.7 0.0 3.69 4.7 2.3 0.8 0.6 12.2 1.3 3.65 4.7 2.3 0.8 0.6 12.4 1.3 3.70 4.8 2.4 1.6 1.1 11.9 2.6 3.63 4.8 2.3 1.6 1.1 12.2 2.6 3.63 4.8 2.8 3.9 3.0 9.7 4.4 3.55 4.8 2.8 3.9 3.0 9.9 4.4 3.56 4.8 3.1 7.9 6.5 8.5 7.0 3.49 4.8 3.0 7.9 6.5 8.6 6.9 3.50 4.8 3.5 15.7 14.5 6.2 6.4 3.41 4.8 3.5 15.7 14.4 6.5 6.8 3.42 188 Pb and Cd sorption of bentonite in mass units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb Sorbed Cd Final m g L - i m g L - i m g L - i m g L - i mg Pb per g bentonite mg Cd per g bentonite p H 250.0 44.9 0.0 0.0 10.3 0.0 6.13 250.0 42.1 0.0 0.0 10.4 0.0 6.17 250.0 45.6 50.0 32.1 10.2 0.9 6.11 250.0 44.6 50.0 35.0 10.3 0.8 6.10 250.0 45.9 100.0 75.4 10.2 1.2 6.07 250.0 49.3 100.0 72.0 10.0 1.4 6.06 250.0 52.3 250.0 186.3 9.9 3.2 6.02 250.0 53.6 250.0 182.5 9.8 3.4 6.01 250.0 63.0 500.0 395.2 9.4 5.2 5.96 250.0 61.4 500.0 390.8 9.4 5.5 5.95 250.0 78.4 1000.0 806.9 8.6 9.7 5.88 250.0 79.4 1000.0 811.3 8.5 9.4 5.87 1000.0 430.7 0.0 0.3 28.5 0.0 5.45 1000.0 422.5 0.0 -1.6 28.9 0.1 5.44 1000.0 432.7 50.0 38.7 28.4 0.6 5.42 1000.0 424.6 50.0 40.9 28.8 0.5 5.42 1000.0 433.7 100.0 82.3 28.3 0.9 5.41 1000.0 439.0 100.0 83.9 28.1 0.8 5.40 1000.0 442.7 250.0 198.5 27.9 2.6 5.39 1000.0 432.0 250.0 195.9 28.4 2.7 5.39 1000.0 460.3 500.0 410.6 27.0 4.5 5.28 1000.0 465.7 500.0 415.3 26.7 4.2 5.35 1000.0 496.7 1000.0 840.3 25.2 8.0 5.35 1000.0 499.4 1000.0 846.6 25.0 7.7 5.35 189 Pb and Cd sorption of bentonite in molar units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb Sorbed Cd Final mmol L 1 mmol L 1 mmol L 1 mmol L 1 cmol Pb per kg bentonite cmol Cd per kg bentonite p H 1.2 0.2 0.0 0.0 5.0 0.0 6.13 1.2 0.2 0.0 0.0 5.0 0.0 6.17 1.2 0.2 0.4 0.3 4.9 0.8 6.11 1.2 0.2 0.4 0.3 5.0 0.7 6.10 1.2 0.2 0.9 0.7 4.9 1.1 6.07 1.2 0.2 0.9 0.6 4.8 1.2 6.06 1.2 0.3 2.2 1.7 4.8 2.8 6.02 1.2 0.3 2.2 1.6 4.7 3.0 6.01 1.2 0.3 4.4 3.5 4.5 4.7 5.96 1.2 0.3 4.4 3.5 4.6 4.9 5.95 1.2 0.4 8.9 7.2 4.1 8.6 5.88 1.2 0.4 8.9 7.2 4.1 8.4 5.87 4.8 2.1 0.0 0.0 13.7 0.0 5.45 4.8 2.0 0.0 0.0 13.9 0.1 5.44 4.8 2.1 0.4 0.3 13.7 0.5 5.42 4.8 2.0 0.4 0.4 13.9 0.4 5.42 4.8 2.1 0.9 0.7 13.7 0.8 5.41 4.8 2.1 0.9 0.7 13.5 0.7 5.40 4.8 2.1 2.2 1.8 13.4 2.3 5.39 4.8 2.1 2.2 1.7 13.7 2.4 5.39 4.8 2.2 4.4 3.7 13.0 4.0 5.28 4.8 2.2 4.4 3.7 12.9 3.8 5.35 4.8 2.4 8.9 7.5 12.1 7.1 5.35 4.8 2.4 8.9 7.5 12.1 6.8 5.35 190 Pb and Cd sorption of Forest soil in mass units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb Sorbed Cd Final m g L 1 m g L 1 m g L - 1 m g L 1 mg Pb per g Forest soil mg Cd per g Forest soil p H 250.0 12.1 0.0 0.0 11.9 0.0 3.07 250.0 11.8 0.0 0.0 11.9 0.0 3.08 250.0 13.8 50.0 30.0 11.8 1.0 3.07 250.0 14.2 50.0 27.5 11.8 1.1 3.07 250.0 15.3 100.0 60.8 11.7 2.0 3.05 250.0 14.8 100.0 62.7 11.8 1.9 3.06 250.0 17.9 250.0 161.7 11.6 4.4 3.02 250.0 17.7 250.0 164.6 11.6 4.3 3.03 250.0 21.6 500.0 348.4 11.4 7.6 2.98 250.0 20.7 500.0 347.5 11.5 7.6 2.98 250.0 28.7 1000.0 757.5 11.1 12.1 2.91 250.0 28.2 1000.0 748.6 11.1 12.6 2.93 1000.0 208.6 0.0 -2.4 39.6 0.1 2.78 1000.0 204.8 0.0 -0.3 39.8 0.0 2.81 1000.0 213.0 50.0 38.6 39.4 0.6 2.81 1000.0 216.7 50.0 40.6 39.2 0.5 2.81 1000.0 219.4 100.0 83.8 39.0 0.8 2.81 1000.0 227.8 100.0 83.7 38.6 0.8 2.81 1000.0 230.3 250.0 203.7 38.5 2.3 2.79 1000.0 228.4 250.0 198.5 38.6 2.6 2.8 1000.0 248.3 500.0 419.5 37.6 4.0 2.77 1000.0 249.3 500.0 418.6 37.5 4.1 2.78 1000.0 280.6 1000.0 844.3 36.0 7.8 2.74 1000.0 284.1 1000.0 853.6 35.8 7.3 2.75 191 Pb and Cd sorption of Forest soil in m o l a r units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb Sorbed Cd Final mmol L 1 mmol I / 1 mmol L 1 mmol L 1 cmol Pb per kg Forest soil cmol Cd per kg Forest soil P H 1.2 0.1 0.0 0.0 5.7 0.0 3.07 1.2 0.1 0.0 0.0 5.7 0.0 3.08 1.2 0.1 0.4 0.3 5.7 0.9 3.07 1.2 0.1 0.4 0.2 5.7 1.0 3.07 1.2 0.1 0.9 0.5 5.7 1.7 3.05 1.2 0.1 0.9 0.6 5.7 1.7 3.06 1.2 0.1 2.2 1.4 5.6 3.9 3.02 1.2 0.1 2.2 1.5 5.6 3.8 3.03 1.2 0.1 4.4 3.1 5.5 6.7 2.98 1.2 0.1 4.4 3.1 5.5 6.8 2.98 1.2 0.1 8.9 6.7 5.3 10.8 2.91 1.2 0.1 8.9 6.7 5.4 11.2 2.93 4.8 1.0 0.0 0.0 19.1 0.1 2.78 4.8 1.0 0.0 0.0 19.2 0.0 2.81 4.8 1.0 0.4 0.3 19.0 0.5 2.81 4.8 1.0 0.4 0.4 18.9 0.4 2.81 4.8 1.1 0.9 0.7 18.8 0.7 2.81 4.8 1.1 0.9 0.7 18.6 0.7 2.81 4.8 1.1 2.2 1.8 18.6 2.1 2.79 4.8 1.1 2.2 1.8 18.6 2.3 2.80 4.8 1.2 4.4 3.7 18.1 3.6 2.77 4.8 1.2 4.4 3.7 18.1 3.6 2.78 4.8 1.4 8.9 7.5 17.4 6.9 2.74 4.8 1.4 8.9 7.6 17.3 6.5 2.75 192 Pb and Cd sorption of Spruce bark in mass units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb Sorbed Cd Final m g L 1 m g L 1 m g L 1 m g L 1 mg Pb per g Spruce bark mg Cd per g Spruce bark p H 250.0 23.3 0.0 0.0 11.3 0.0 3.95 250.0 23.9 0.0 0.0 11.3 0.0 3.94 250.0 25.6 50.0 38.2 11.2 0.6 3.96 250.0 26.2 50.0 35.2 11.2 0.7 4.01 250.0 27.8 100.0 78.0 11.1 1.1 3.90 250.0 27.5 100.0 78.4 11.1 1.1 3.95 250.0 31.4 250.0 202.6 10.9 2.4 3.84 250.0 31.7 250.0 200.1 10.9 2.5 3.85 250.0 38.1 500.0 422.9 10.6 3.9 3.86 250.0 37.4 500.0 423.5 10.6 3.8 3.79 250.0 46.5 1000.0 868.0 10.2 6.6 3.71 250.0 47.1 1000.0 879.5 10.1 6.0 3.73 1000.0 444.6 0.0 -1.9 27.8 0.1 3.53 1000.0 437.6 0.0 -0.1 28.1 0.0 3.51 1000.0 430.0 50.0 43.7 28.5 0.3 3.53 1000.0 432.4 50.0 47.3 28.4 0.1 3.54 1000.0 444.7 100.0 97.7 27.8 0.1 3.53 1000.0 448.3 100.0 96.5 27.6 0.2 3.53 1000.0 453.8 250.0 233.2 27.3 0.8 3.52 1000.0 451.5 250.0 235.0 27.4 0.8 3.52 1000.0 474.1 500.0 478.4 26.3 1.1 3.50 1000.0 488.4 500.0 478.6 25.6 1.1 3.50 1000.0 507.4 1000.0 962.7 24.6 1.9 3.48 1000.0 513.8 1000.0 962.8 24.3 1.9 3.49 193 Pb and Cd sorption of Spruce bark in molar units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. Sorbed Pb . Sorbed Cd Final m m o l L 1 mmol L 1 mmol L 1 mmol L _ 1 cmol Pb per kg cmol Cd per kg p H Spruce bark Spruce bark 1.2 0.1 0.0 0.0 5.5 0.0 3.95 1.2 0.1 0.0 0.0 5.5 0.0 3.94 1.2 0.1 0.4 0.3 5.4 0.5 3.96 1.2 0.1 0.4 0.3 5.4 0.7 4.01 1.2 0.1 0.9 0.7 5.4 1.0 3.90 1.2 0.1 0.9 0.7 5.4 1.0 3.95 1.2 0.2 2.2 1.8 5.3 2.1 3.84 1.2 0.2 2.2 1.8 5.3 2.2 3.85 1.2 0.2 4.4 3.8 5.1 3.4 3.86 1.2 0.2 4.4 3.8 5.1 3.4 3.79 1.2 0.2 8.9 7.7 4.9 5.9 3.71 1.2 0.2 8.9 7.8 4.9 5.4 3.73 4.8 2.1 0.0 0.0 13.4 0.1 3.53 4.8 . 2.1 0.0 0.0 13.6 0.0 3.51 4.8 2.1 0.4 0.4 13.8 0.3 3.53 4.8 2.1 0.4 0.4 13.7 0.1 3.54 4.8 2.1 0.9 0.9 13.4 0.1 3.53 4.8 2.2 0.9 0.9 13.3 0.2 3.53 4.8 2.2 2.2 2.1 13.2 0.7 . 3.52 4.8 2.2 2.2 2.1 13.2 0.7 3.52 4.8 2.3 4.4 4.3 12.7 1.0 3.50 4.8 2.4 4.4 4.3 12.3 1.0 3.50 4.8 2.4 8.9 8.6 11.9 1.7 3.48 4.8 2.5 . 8.9 8.6 11.7 1.7 3.49 OH 113 s I* T3 I 01 I-a i<8 T3 l<8 u C o u 13 ha • i u C o u a •a .s PH U C o u "(3 ,1 o u 3 13 •43 •2 u C o u a 13 •43 u C o u I A 143 rH 0 0 IN ID o CN SO i n CN i n i n CN CN O CN CM o OS 0 0 CN Os 0 0 rH Os SO 0 0 Os Os OS Os O CN iri iri iri iri <* iri iri -* ^ ' iri iri be cu • HH 3 1 w> g s -o bo oi ^ 1 S * bo g w> g 3 H O bo s bO 3 I-J bO 3 bo 3 bo 3 bO 3 CO O CO CN Os IN o rH rH CO i n 0 0 CN I N CN CO i n rH I N iri rH rH CN iri SO O 0 0 CN rH [N ON' IN 0 0 i n sO SO IN CO 3 i n SO O o IN rH CN ON ON SO IN rH rH rH rH SO SO SO -* CO 0 0 CO CO rH CO t x i n c o o N s o c N O s o o c o o o o i n c r ! ' * o o o N i n N O r H r H r H O i n i n c O C O C O C N i n c N i n CO CO rH m O s ^ a s O i n r H C N C N O O O O O i n ^ C N r H C N C O m N N v d r t N N d i n i d H J d v d i r i ^ i o i r i i o m rH 0 0 i n Os 0 0 0 0 so o 0 0 rH CN CN O IN in CO iri OS iri r-i <# 0 0 o od CO iri CN rH CN rH CN rH rH rH rH rH rH CN rH CN i n O O ON O o 0 0 O i n i n 0 0 i n O 0 0 0 0 O CO CN rH O 0 0 CO OS OS CN o od CO -* sd iri iri CO CO i n so so ON o IN o ON ON IN CO rH rH sO SO rH rH so NO CO CO 0 0 CO CO CO CO rH "* o Q j 0 0 C N i n ON C O ON rH C O rH rH i n C N S O ON ON O C O C O sd C O rH 'HH rH S O C O O C O C N rH CN O O N O S C O i n rH C N rH C N rH rH ON S O o 0 0 IN O 0 0 0 0 CO m CN rH O CO -2.9 CO i n i n 0 0 rH CN ON rH CO O N rH O ON rH O ON rH IN IN i n t N t N CO K S O N O so CO t N rH N O -2.9 N O CO ON t t as rH © t N SO CM i n ON 0 0 rH CO CN so so rH CN 0 0 rH rH CO CN ON CN O 0 0 <* CO 0 0 CO ON r-i 0 0 0 0 © rH ON o tN IN O Os IN tN OS 0 0 o 0 0 0 0 ON ON Os 0 0 O rH CN tN IN CN rH IN tN ON -# -* -* CN s D C O O c O C N c O O C O ^ j C N i n c N r H r H C S J O s c N K c N l r i c N ^ O s " ' * O t N o o o s o o N O O s o t V ' * o o o o r N C N O O r H O O r H O O r H O O Os "# CN CN - * CO d t s [s H J ^1 0 0 OO 0 0 OS OS rH rH l-e l<8 73 l-e i<8 T3 I OJ i<8 u o u 13 u C o u i a P H in o l-c 1^  2 o u 13 l : l cj C o u |3 i l o u I *C> XI 60 4* o s o 00 44 3 o 6 o 60 4H C i—l oo o rH rH S £ CO cd IO CO CO ^ 00 t o o i n co H oo a * i n r i r i r i O l i ^ CO CO CN CN » 00 N Os ^ CM o co uo co i n os O 00 CO •>* CO o T t i C N O T t i C O C O r H T t ^ t m m ^ N C O r i O S O i n f e i H t N i n ^ t o i n i n in 00 o LO rH IN rtl 00 cd r-i rH CN Os CN CM CN CN 00 O N N H J c O N O S O O H N CO CO t s O OS Os rH c d s d t N s d t N s d c N c d O s O l N C v l C N r H c O C N s O c O r H s O • H I - ^ ^ j l L O s O L N O O O s i n s O C O s O SO LO CO SO s o to i n i n cc r i r i r i r i i n i n i n i f l C O C O C O C l O N O c O r i c O i n i n in Os O o CN Os CO CN CO o i CN Os © rH CN CN 00 CO o o CO cd SO LO rH CO OS CO CN CN LO vO SO sd OS rH i n C N O O ' J H O S O O N O O O O O O O O S ^ T f l S T l l i n ^ N N » O H / o s c o N ^ q q i f i i n o o o o \ c > o s c o c o O r H O ' r H O r H © C N O ° C N O r H © 0 © 0 0 0 hJ rH CN O Os LN o I N LN IN sO_ CO S s rH rH r-H rH sd co o in co If) ts r l r l r H r H r H r H s b v O s o ' s D ' ^ ' ^ CN O 22 CO CN CN CO 00 rH P CO CN CN LN rH 00 * H IN SO CN CN CN CN 00 LN CO CO CN CN • 9° ° * . tN SO tN LN 2 O HI HI VO N ™ LN tN CO 00 in rH 12 tN tN I N tN tN CO L N L N S O L N i n t N T ) l | N o s o q o s o q o s o q o s c q o c r i o c d o c d o c d oo f i n co o - * C N o C N i n i n - * <JI CO CO CO CO CO Os Os CN CN CN CN CN CN O © II PH ITS I 01 i<8 I O) l«8 I Ol l<8 VD i n 00 CO rH CO IN CN o m ON CO rH CO tN CN tN HI <N CO CO VD CN o HI i n CO 3 SO CO 3 i n i n CO c d CO CO c d CO cd CO CO c d c d cd CO c d c d c d CO c d » s B PH 00 t j 8 oo g S OH 60 >H ^ H O f ? <" "H U 60 S 60 6 Its ""S H ^ o l o s ^ o ^ ^ m i n CM 00 tN i n Os CO SO o SO IN 00 i n o VO so CM r H 00 CN rH CN vd O CN cd LN IN CO >P tN CO CM i r i vO 00 00 00 i n o CM i n i n SO CO IN CN 00 vO SO 00 CO rH rH rH r H tN tN IN tN HI HI HI HI 00 HI HI rH HI ~60 60 60 6 ~60 60 6 c N s o H i ^ o o c « v o r H i n ^ o ^ o i n i n i n s o e o O O c d o C N O O O P c M P o c M ' o O O r H C N t s E N O O s O i n c O C N C N ^ N s o i r i c d t s i i r i H J t v r H O O s r H O O O C O s O O s HJd i r i i r i"* in ' i r i in ' r i Os o Os i r i CM 00 i n i n rH i n i n i n CO o CO o i n o o 00 o VD ir i od i r i CN CO 00 00 00 OS SO i r i LN i r i 00 CM 00 CN rH HI HI SO CM HI SO 00 O o SO 00 Os Os Os vO CM rH r H SO SO r H rH VD VD HI 00 CO CO CO CO CO r H o 00 CO tN r H i n rH so CN m Os 00 LN 00 tN o 00 IN Os 00 i n o 00 cd H! 00 cd HI CN CO i r i IN OS o LN Os O Os CM r H i n SO i n i n CO HI HI i n 1 i n rH CO CM CM CN CM Os OS o 00 IN O 00 00 co i n CN r H o CO Os CM-CO i n i n 00 r H CM' c d c d O r-i ts HI CO SO H i c d r-i sd H i O Os Os Os Os tN i n co i n SO SO EN SO EN EN Os tN r H rH rH r H LN LN LN tN HI HI HI HI Os HI HI rH HI SO CN i n HI Os CN Os Os Os O ts tN rH CM LN LN Os 00 r H CO CM SO so r H CN 00 rH r H CO CM cd 00 H i CO 00 CO Os r-i 00 00 cd r-i o Os ts ts Os 00 O 00 00 Os Os Os 00 O CN rH ts HI HI Os HI HI HI HI HI CM SO CO o CO CN CO o CO r-i CN oi CN tN CN i r i CN O o Os o Os O Os o CM 00 rH CO rH 00 rH 00 CN i n CM rH 'HI CM CN HI CO Os" H i cd ts' cd LN ts' H i H i HI 00 CO ts 00 00 00 Os OS OS HI HI HI HI HI rH rH 197 §5 s o ••c c « a U A* o s c I Ol T3 •s I OJ u C o u 13 ,1 u G o u i3 "(3 ,1 o u I* I OH r - H PH U C o u fl u C o u •3 il o o i l 00 o 6 u 00 01 u in CM Os CO 00 CO CO CO rH © in CO CO sO in in rH r-i o o © C) o i © © © o G u 00 CH s X> CD U I H CD (« u CD 1-J rH -# O 00 CO s s r-i CM S O in Os H K sO O rH Q O Os O rH © o i Os so so ^ • H * i n i n o o o r-i 3! o in in O CO in rH t N O O CO Os O r H 00 OS Os CM CM I N Os CO so in o CM O so 00 CM 00 r H "* © rH Os iri CO 00 SO rH sd d Os 00 C N C N 00 00 sd CM so SO o sO Os rH SO 00 Os C N in CO o CO CO C N CO O O in in o CO CM SO sO 00 C N CO O N CM C N © i 00 00 iri tri iri iri CM 3 CO SO •>* CM 00 SO C N o SO r H sO 00 CM CM O OS oo rH sd sd SO sd 'HH CO C) C N CM CM C N rH S O 00 ^ r i C C sO CM rH CM O CM CM ^ CM CO CO « °°. i o o o Os o rH sO O CM sO 00 Os CO in CO o r H CM CM rH C N Os iri sd o CO rH sd sd sd sd iri r-i CO CM I N C N oo T r * o 00 CO C N in o C N CM O CO C N CM CO C N in CN Os •<HH o 00 S O in CN CN CN CM CO CM CN © r-i © CN © CM O r-i r-i r-i rH r-i d O rH CM O Os C N CO o in CO rH O CO O CO sO 00 C N in C N rH rH CM rH CO r-i sd sd sd sd O i 00 T"H . CM CN 00 C N CO CO CO CO 00 Os rH C N O C N sO O C N C N C N C N d iri r H C N C N t N C N ' S O C N in rH C N CO* C N C N SO C N in C N C N o 00 CM o CM Os 00 Os CO Os 00 OS 00 o in CO CO CO CO d CO d CO d CO d CO d •*' CN CN CM CM' C M O O 198 APPENDIX E LEACHING TEST CALCULATIONS AND DATA E . l . A V E R A G I N G T H E H Y D R A U L I C C O N D U C T I V I T Y , H E A V Y M E T A L B R E A K T H R O U G H , A N D D I S C H A R G E p H D A T A E.2. C A L C U L A T I O N S F O R T H E H E A V Y M E T A L R E T E N T I O N O F A L E A C H I N G C E L L S A M P L E B A S E D O N B R E A K T H R O U G H C U R V E S E.3. H Y D R A U L I C C O N D U C T I V I T Y , H E A V Y M E T A L B R E A K T H R O U G H , A N D D I S C H A R G E p H D A T A APPENDIX E. l . AVERAGING THE HYDRAULIC CONDUCTIVITY, HEAVY M E T A L BREAKTHROUGH, A N D DISCHARGE pH D A T A 199 Method Figure E . l . l shows the hydraulic conductivity data for the permeation of Pb leachate through the bentonite admix. The hydraulic conductivities of each sample in the triplicate experienced erratic increases and decreases, but all three followed the same trend: they started at low values; increased over an order of magnitude between 175 ml and 400 ml of discharge (1 - 2.5 pore volumes); and then showed little change after 400 ml of discharge (« 2.5 pore volumes). The hydraulic conductivity data in Figure E . l . l represents the typical difficulties in averaging the triplicate data. Discharge Volume (mL) Triplicate # x Test 1 • Test 2 A Test 3 FIGURE E. l . l . Hydraulic conductivity results for permeating Pb leachate through bentonite admix samples In order to combine the triplicate data, the hydraulic conductivity curve was split into two parts. The initial portion of the curve was near horizontal, so a simple mean was calculated for that group of data. The rest of the curve beyond the initial portion resembled a log curve; thus, a best-fit log curve was iterated from that group of data. The curve-fitting was done by the "trendline" feature in E X C E L 5.0 (Microsoft). Figure E . l . l shows the averaged curve plotted with the triplicate data. The method used to combine the triplicate data in Figure E . l . l was applied to all the hydraulic conductivity and heavy metal breakthrough curves. As for the discharge p H curves, the initial portions were left in raw form. Beyond the initial portions, straight lines were used to fit the rest of the data. Table E . l . l summarizes the best-fit parameters used for averaging the hydraulic conductivity, heavy metal breakthrough, and discharge p H data. 200 w w PQ < '•§.1 3 1 ix i o U K a X> cf! g cn '11 1% " 8 2 & 60 4-t ft M > s > ^ E '-g « •xi ^ 3 ^ U cu DH TJ CC O iri CO o o o o o o C N CO SD I "* I CO IN. C N tN CO SO iri in in i5 CO CN CO SO CO cS 00 Os o o in in |u| IS1 DH TJ s S3 cu x i 201 Calculations The best-fit equation used to calculate the log-shaped portion of the hydraulic conductivity curves is, k = [m k • Ln(Dv) + b k] • 0.000000001 where k (m/s) is hydraulic conductivity, mk and bk are best-fit parameters, D v (ml) is the discharge volume, and 0.000000001 is a scaling factor. The best-fit equation used to calculate the log-shaped portion of the heavy metal breakthrough curves is, C = mc • Ln(Dv) + b c where C (mg/L) is the heavy metal breakthrough concentration, and mc and b c are best-fit parameters. The best-fit equation used to calculate the straight-line portion of the discharge p H curves is, p H = m PH • Dv + b P H where m PH and b PH are best-fit parameters. 202 A P P E N D I X E.2. C A L C U L A T I O N S F O R T H E H E A V Y M E T A L R E T E N T I O N O F A L E A C H I N G C E L L S A M P L E B A S E D O N B R E A K T H R O U G H C U R V E S Figure E.2.1 shows a labeled diagram of a typical heavy metal breakthrough curve. Discharge Volume (mL) F I G U R E E.2.1. Diagram of heavy metal breakthrough curve. The amount, Q (mg), of heavy metal retained by the Leaching cell sample represented by Figure E.2.1, is calculated from the following equation: Q b = Qr - Q a - Q a b where Q b (mg) is the amount of heavy metal retained after D b of discharge, Qr (mg) is the total input of heavy metal after D b of discharge, Q a (mg) is the amount of heavy metal discharged after D a of discharge, and Q a b (mg) is the amount of heavy metal discharged between D a and D b of discharge. The equation for calculating Qr (mg) is, QT = 500 • ( D B - 175 ) 1000 where 500 (mg/L) is heavy metal concentration of the leachate, 175 (ml) is one pore volume of the Leaching cell sample, and 1000 is a scaling factor. The equation for calculating Qa (mg) is, Qa = C a • D a 1000 where C a (mg/L) is the breakthrough concentration of the initial portion, and D a (ml) is the discharge volume in which the log-shaped portion begins. 203 The equation for calculating Q a b (mg) is, Q a b = arte • D b • L n ( D b ) - mc • D b + b c • D b l - Tmc • D a • L n ( D a ) - nv • D a + b c • D a l 1000 where mc and b c (see Table E . l . l ) are best-fit parameters for the log-shaped portion. A P P E N D I X E.3. H Y D R A U L I C C O N D U C T I V I T Y , H E A V Y M E T A L B R E A K T H R O U G H , A N D D I S C H A R G E p H D A T A Blank (0.01 M calcium nitrate (Ca(NQ3)2)) leachates Bentonite admix permeated with blank (0.01 M (Ca(N03h) leachate Triplicate # Cumulative discharge Time Hydraulic Discharge volume conductivity P H ml hr m/s T e s t l 2.2 125 2.12E-11 11.2 231 3.12E-11 8.49 19.6 314 9.11E-12 26.1 409 2.54E-11 32.1 527 4.13E-12 34.4 578 1.18E-11 8.51 44.9 653 5.99E-11 8.52 66.7 805 3.99E-11 8.50 86.5 961 2.29E-11 8.53 95.4 1038 9.25E-12 97.4 1061 1.30E-11 101.7 1104 4.14E-11 Test 2 5.4 76 3.06E-11 8.31 11.3 125 3.85E-11 20.3 231 2.54E-11 27.8 314 1.03E-11 31.5 409 1.13E-11 8.51 38.6 526 3.80E-11 8.53 53.3 578 2.79E-11 8.51 67.7 653 1.74E-11 8.56 74.6 805 8.29E-12 76.5 961 1.18E-11 80.3 1038 3.64E-11 Forest soil admix permeated with blank (0.01 M (Ca(NC>3)z) leachate Triplicate # Cumulative discharge Time Hydraulic Discharge volume conductivity p H ml hr m/s Test 1 3.5 188 8.79E-11 9.2 264 3.08E-11 11.4 338 15.4 422 4.28E-11 8.24 21.7 505 2.46E-11 26.2 583 2.22E-11 8.33 30.0 649 2.59E-11 8.42 32.9 695 2.59E-11 8.42 36.4 764 1.98E-11 8.43 39.8 832 3.47E-11 Spruce bark admix permeated with (0.01 M (Ca(N03h) leachate Triplicate # Cumulative discharge Time Hydraulic Discharge volume conductivity p H ml hr m/s T e s t l 5.6 281 2.21E-11 11.8 369 1.46E-11 8.51 17.1 469 1.28E-11 22.1 593 2.54E-11 8.60 26.5 643 1.93E-11 31.6 748 1.45E-11 8.58 35.7 831 5.24E-12 39.0 926 1.26E-11 45.6 1044 1.72E-11 50.0 1095 2.33E-12 8.48 53.2 1170 1.92E-11 60.5 1323 1.38E-11 8.41 67.4 1479 8.07E-12 8.59 70.6 1556 3.71E-12 71.4 1578 5.28E-12 73.4 1622 1.87E-11 Test 2 1.5 135 1.51E-11 6.1 207 2.06E-11 12.8 281 2.37E-11 19.6 369 1.69E-11 8.56 25.6 469 1.41E-11 31.4 593 3.12E-11 8.65 36.6 643 2.21E-11 43.0 748 1.91E-11 8.57 48.4 831 6.66E-12 52.7 926 1.60E-11 8.65 57.9 1044 8.63E-12 60.3 1095 3.16E-12 8.44 64.3 1170 2.36E-11 73.4 1323 1.74E-11 8.38 82.2 1479 1.04E-11 8.68 86.2 1556 4.58E-12 87.3 1578 7.40E-12 89.7 1622 2.26E-11 Single heavy metal leachates - lead (Pb) & copper (Cu) Bentonite admix permeated with 500 mg/L ofPb leachate Triplicate # Cumulative Time Hydraulic Pb cone. Discharge discharge volume conductivity P H ml hr m/s m g / L T e s t l 2.0 16 3.57E-11 5.4 42 6.68E-11 0.1 8.20 9.9 93 5.00E-11 0.0 8.45 16.0 139 4.98E-11 0.0 21.8 186 4.88E-11 0.0 8.55 32.1 308 4.84E-11 0.0 8.61 49.8 476 4.66E-11 0.0 8.70 66.9 626 4.56E-11 0.0 79.8 757 4.34E-11 0.0 8.72 95.3 968 4.32E-11 0.0 8.60 118.1 1083 7.47E-11 0.0 8.60 148.8 1202 1.83E-10 0.0 8.50 179.8 1285 1.60E-10 0.0 8.11 206.3 1363 1.48E-10 0.0 8.56 225.8 1436 1.10E-10 0.0 8.54 242.6 1492 2.77E-10 0.0 8.48 446.3 1544 1.76E-09 185.0 6.18 746.2 1601 6.82E-09 315.3 5.89 874.7 1610 3.91E-09 337.5 5.94 916.5 1615 4.19E-09 346.1 6.06 959.7 1619 4.32E-09 362.1 6.02 1021.2 1625 4.39E-09 372.3 6.01 1092.7 1633 4.20E-09 372.3 5.98 1163.0 1640 4.55E-09 384.3 5.91 Test 2 2.5 34 4.47E-11 6.2 60 5.49E-11 0.0 8.18 10.2 111 4.67E-11 0.0 8.39 15.9 156 4.65E-11 0.3 21.4 203 4.79E-11 0.4 8.53 31.6 308 4.81E-11 8.61 49.0 476 4.52E-11 0.0 8.61 65.4 626 4.27E-11 0.0 77.9 757 4.34E-11 0.0 8.72 93.4 968 3.53E-11 0.0 8.64 112.4 1083 5.35E-11 0.0 8.76 129.7 1202 8.11E-11 0.0 8.72 141.0 1298 6.30E-11 0.0 8.65 150.0 1363 6.26E-11 0.0 8.86 159.1 1436 6.03E-11 0.0 8.84 167.3 1492 1.27E-10 0.0 8.79 266.2 1544 8.57E-10 30.9 6.90 Triplicate # Cumulative Time Hydraulic Pb cone. Discharge discharge volume conductivity P H ml hr m/s m g / L Test 2 continued 420.7 1601 3.87E-09 146.0 6.16 493.6 1610 2.22E-09 218.9 6.16 517.1 1615 2.33E-09 223.0 6.13 541.6 1619 2.48E-09 226.8 6.13 578.1 1625 2.66E-09 256.6 6.10 621.9 1633 2.60E-09 269.8 6.07 666.6 1640 2.97E-09 286.4 5.98 Test 3 12.0 9 5.39E-11 0.0 8.09 14.5 34 4.00E-11 17.7 59 7.88E-11 0.0 8.29 23.2 79 1.36E-10 0.0 8.37 29.3 110 6.58E-11 0.0 8.40 36.6 155 8.46E-11 0.1 8.50 45.5 203 6.74E-11 0.7 8.46 64.3 326 9.58E-11 98.2 476 8.67E-11 0.0 8.61 167.2 693 2.07E-10 12.0 233.7 774 3.30E-10 70.7 6.32 335.2 846 6.13E-10 253.7 6.11 497.9 930 1.95E-09 295.4 6.08 680.7 968 2.54E-09 330.1 6.02 860.2 998 3.08E-09 357.6 5.90 1198.0 1044 3.52E-09 6.01 Bentonite admix permeated with 500 mg/L ofCu leachate Triplicate # Cumulative Time Hydraulic Cu cone. Discharge discharge volume conductivity p H ml hr m/s m g / L T e s t l 5.2 87 4.63E-11 0.0 8.49 13.6 194 5.43E-11 51.2 214 1.44E-09 181.9 6.07 93.8 223 2.58E-09 246.6 5.54 212.9 261 2.11E-09 290.2 5.60 308.7 288 1.48E-09 288.7 5.58 354.9 302 2.63E-09 303.4 5.61 412.2 314 2.91E-09 337.7 5.54 471.4 326 2.68E-09 340.9 5.53 539.2 338 3.17E-09 364.7 5.46 591.2 347 2.96E-09 366.7 5.45 653.8 358 3.12E-09 387.3 5.43 723.5 370 3.33E-09 383.0 5.42 757.5 376 3.58E-09 392.5 5.40 816.5 385 3.78E-09 395.2 5.37 871.0 393 3.93E-09 396.0 5.36 1006.5 407 5.51E-09 432.9 5.30 1179.3 424 6.74E-09 448.0 5.24 1260.1 430 7.68E-09 448.0 5.21 1735.6 482 7.41E-09 Forest soil admix permeated with 500 mg/L ofPb leachate Triplicate Cumulative Time Hydraulic Pb cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L T e s t l 1.5 3 2.03E-09 0.0 5.5 6 2.92E-09 0.0 7.04 13.5 10 1.82E-09 0.0 7.13 25.5 15 2.26E-09 0.2 6.31 42.5 20 2.18E-09 0.2 6.31 68.0 29 1.21E-09 3.8 6.29 95.0 40 1.79E-09 15.5 6.06 114.5 47 1.28E-09 14.0 6.69 134.5 56 1.16E-09 26.8 6.48 156.5 67 9.77E-10 31.2 6.48 176.5 79 8.76E-10 15.4 6.70 202.5 98 6.85E-10 13.5 7.16 228.5 120 5.95E-10 11.6 7.13 245.5 137 5.53E-10 8.7 7.33 262.0 153 6.09E-10 9.5 7.37 284.0 173 5.98E-10 15.4 7.26 304.5 191 7.54E-10 21.2 7.08 324.3 204 9.04E-10 41.4 6.50 358.3 222 1.16E-09 79.6 6.32 391.0 237 1.28E-09 94.9 6.43 430.3 249 1.97E-09 149.9 6.34 515.5 264 4.50E-09 248.4 5.79 618.8 277 4.16E-09 270.2 5.45 694.3 287 4.41E-09 281.5 5.38 783.8 296 6.30E-09 306.0 5.65 905.5 306 7.10E-09 345.6 4.85 1023.5 318 6.93E-09 349.2 Test 2 5.0 0 3.42E-08 16.5 3 8.80E-09 39.0 6 1.87E-08 3.4 6.13 69.5 10 4.81E-09 17.3 5.95 91.5 15 2.61E-09 17.3 106.5 20 1.56E-09 17.3 6.14 126.8 29 1.03E-09 12.4 6.03 147.5 40 1.20E-09 14.7 6.05 164.0 47 1.46E-09 18.4 6.60 187.5 56 1.39E-09 42.2 6.32 215.5 67 1.34E-09 39.3 6.35 246.5 79 1.50E-09 49.8 6.26 298.3 98 1.49E-09 67.0 6.41 359.5 120 1.56E-09 94.1 6.31 411.8 137 2.10E-09 121.7 6.19 466.5 153 1.83E-09 142.5 6.13 536.0 173 1.97E-09 153.6 5.49 600.5 191 2.22E-09 159.4 5.54 Triplicate Cumulative Time Hydraulic Pb cone. Discharge # discharge volume conductivity p H ml hr m/s m g / L Test 2 continued 660.5 204 2.81E-09 180.9 5.35 753.0 222 2.92E-09 206.2 5.45 833.8 237 2.97E-09 217.2 5.56 903.3 249 3.12E-09 229.0 5.35 1003.0 264 4.30E-09 266.4 5.21 1123.0 277 5.86E-09 301.8 4.94 1223.3 287 5.27E-09 313.6 4.87 1304.5 296 4.88E-09 322.5 4.87 1390.5 306 4.52E-09 320.3 4.70 1468.0 318 4.70E-09 325.3 1536.0 326 4.69E-09 320.1 1608.5 335 4.77E-09 326.3 Test 3 1.0 0 6.77E-09 3.5 3 2.01E-09 9.0 6 4.63E-09 0.1 6.95 17.0 10 1.31E-09 0.2 7.18 25.0 15 1.38E-09 0.2 37.5 20 1.75E-09 0.2 6.63 66.8 29 1.66E-09 0.2 6.29 100.0 40 1.85E-09 0.3 6.24 122.0 47 1.61E-09 0.0 7.00 143.0 56 1.05E-09 0.0 7.00 166.0 67 1.17E-09 0.0 6.96 184.5 79 5.79E-10 0.0 7.18 209.0 98 7.67E-10 0.0 7.54 246.8 120 1.14E-09 0.3 7.33 277.8 137 9.06E-10 0.2 7.51 302.5 153 8.44E-10 2.2 7.36 328.0 173 5.68E-10 3.6 7.28 347.0 191 6.59E-10 4.1 7.17 370.5 204 1.28E-09 25.0 6.46 431.8 222 2.28E-09 111.2 6.19 496.5 237 2.47E-09 133.1 6.50 553.0 249 2.47E-09 151.0 6.25 655.0 264 5.18E-09 205.4 5.74 776.0 277 4.89E-09 260.6 5.35 861.5 287 4.56E-09 280.3 5.21 934.0 296 4.38E-09 287.1 5.25 1015.3 306 4.45E-09 304.6 4.98 1089.3 318 4.27E-09 298.5 1151.0 326 4.17E-09 306.0 1215.0 335 4.13E-09 312.1 Forest soil admix permeated with 500 mg/L of Cu leachate Triplicate Cumulative Time Hydraulic Pb Discharge # discharge volume conductivity cone. P H ml hr m/s m g / L T e s t l 4.5 32 3.24E-10 0.9 4.41 24.5 39 1.10E-09 123.0 4.55 68.5 46 2.25E-09 315.2 4.41 125.0 58 1.22E-09 293.0 4.44 172.0 70 8.79E-10 250.8 4.59 242.0 88 1.47E-09 266.1 4.63 325.0 111 7.29E-10 282.5 4.48 387.0 129 8.97E-10 267.4 4.51 473.5 153 1.27E-09 299.4 4.53 578.0 177 1.05E-09 350.8 4.32 704.7 200 1.80E-09 385.0 4.42 865.2 225 1.73E-09 411.7 4.38 1023.7 246 1.91E-09 427.9 4.34 1119.9 258 8.56E-10 419.8 4.17 1244.3 270 4.67E-09 452.5 4.34 1734.1 344 3.90E-09 467.0 4.32 Test 2 7.5 39 5.33E-10 106.8 4.43 36.8 46 1.71E-09 334.9 4.36 72.0 58 5.86E-10 299.5 4.44 92.3 70 3.12E-10 191.2 4.65 118.0 88 5.46E-10 165.6 4.85 148.0 111 2.51E-10 162.0 4.88 176.0 129 5.08E-10 190.9 4.76 199.5 177 1.44E-10 172.7 4.86 211.0 200 1.17E-10 78.6 5.44 222.5 225 1.41E-10 68.8 5.57 239.0 246 2.56E-10 141.4 4.98 255.0 267 1.51E-10 132.2 5.18 289.5 292 6.32E-10 368.0 321 9.20E-10 337.9 4.53 468.5 350 9.22E-10 357.1 4.57 575.5 375 1.17E-09 392.4 4.40 728.1 423 1.05E-09 430.9 4.53 870.1 467 5.48E-10 430.9 4.36 957.9 485 1.28E-09 419.6 4.34 1179.6 522 2.53E-09 480.5 4.53 1834.6 648 1.98E-09 503.8 4.46 2484.6 782 6.91E-10 479.2 4.36 3024.6 890 1.78E-09 480.5 4.30 Spruce bark admix permeated with 500 mg/L ofPb leachate Triplicate Cumulative Time Hydraulic Pb cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L T e s t l 1.0 35 3.05E-11 5.0 61 2.17E-10 10.5 76 2.88E-10 0.6 8.17 15.9 132 5.30E-11 0.5 8.64 27.3 144 1.47E-09 2.4 8.18 38.3 159 1.43E-10 11.4 8.41 43.9 233 4.59E-11 9.5 8.54 49.8 306 2.09E-11 11.0 8.87 54.8 406 1.12E-11 7.8 8.63 59.3 466 8.91E-12 6.3 8.70 72.6 549 3.58E-11 4.2 7.41 102.1 595 6.29E-11 9.0 7.03 129.4 613 3.47E-11 13.5 7.33 156.6 639 9.24E-11 49.0 6.46 183.6 664 1.10E-10 73.3 6.42 196.1 701 3.52E-11 3.2 8.15 205.0 807 3.88E-11 5.9 8.44 213.7 890 4.00E-11 4.3 8.59 258.9 970 3.35E-10 122.0 6.20 334.3 989 2.99E-10 264.0 6.32 412.5 1002 3.66E-10 317.7 6.27 549.5 1025 8.06E-10 357.1 6.12 944.9 1090 1.82E-09 397.7 6.09 1393.1 1156 7.97E-10 440.8 5.93 1883.8 1222 1.40E-09 466.7 5.90 2310.2 1284 3.15E-10 423.4 5.86 2461.5 1307 2.63E-10 436.4 5.88 2620.7 1332 3.43E-10 427.8 5.85 2846.9 1372 6.22E-10 440.8 5.73 3065.4 1399 4.18E-10 424.8 5.63 3268.0 1438 7.00E-10 406.0 5.90 3565.7 1530 7.19E-10 429.5 5.98 3785.3 1610 1.83E-10 358.3 6.01 3878.8 1641 2.22E-10 349.1 6.08 3985.0 1688 2.08E-10 351.4 6.12 4067.6 1723 . 1.22E-10 358.3 6.09 4115.6 1742 1.45E-10 361.8 6.10 4177.6 1765 2.70E-10 360.6 5.93 4260.6 1795 2.54E-10 372.2 6.03 4417.4 1854 5.79E-10 369.9 6.06 4607.1 1927 3.62E-10 372.2 6.06 Test 2 1.9 68 2.77E-11 0.0 8.45 6.6 140 2.09E-11 0.1 8.63 11.6 240 1.12E-11 0.3 8.61 16.3 301 9.49E-12 0.1 8.30 Triplicate Cumulative Time Hydraulic Pb cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L Test 2 continued 21.0 430 7.82E-12 0.4 8.19 26.3 536 2.69E-11 0.3 8.51 31.3 642 1.54E-11 0.3 8.67 35.5 725 2.45E-11 4.1 8.37 41.0 860 2.77E-11 0.7 8.36 47.0 925 1.66E-11 0.6 8.36 52.5 1041 1.03E-11 0.5 8.78 57.8 1207 8.35E-12 0.9 8.84 64.1 1365 1.53E-11 0.3 8.89 70.9 1577 2.17E-11 0.4 8.42 76.8 1689 1.41E-11 0.6 8.60 82.0 1824 9.76E-12 0.6 8.89 88.4 2017 9.67E-12 Spruce bark admix permeated with 500 mg/L ofCu leachate Triplicate Cumulative Time Hydraulic C u cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L T e s t l 3.2 104 2.41E-11 0.3 8.22 7.8 204 3.32E-11 0.3 8.56 12.8 264 2.13E-11 0.2 8.33 17.6 394 2.89E-11 0.1 8.58 41.4 499 3.05E-10 2.0 7.66 69.0 560 1.70E-10 5.8 8.35 78.0 606 9.18E-11 4.4 8.55 151.0 689 1.81E-09 385.1 5.69 280.4 725 9.18E-10 356.0 5.62 372.8 749 7.56E-10 367.0 5.62 470.1 769 1.96E-09 395.7 5.61 608.9 800 3.09E-09 391.8 5.60 777.2 823 2.26E-09 404.5 5.50 1026.1 888 1.29E-09 363.2 5.58 1303.2 954 9.84E-10 421.5 5.46 1991.6 1021 4.49E-09 446.4 5.33 2732.9 1082 1.57E-09 434.5 5.20 3083.7 1105 4.11E-09 454.8 5.17 3492.1 1131 4.85E-09 457.9 5.12 4174.3 1170 5.78E-09 475.2 5.08 Test 2 1.9 183 2.08E-11 0.2 8.37 6.2 283 3.32E-11 0.3 8.68 11.0 344 2.00E-11 0.2 8.26 15.7 473 2.89E-11 0.1 8.24 38.3 578 2.87E-10 1.0 7.91 61.8 685 9.79E-11 2.2 8.62 67.6 768 6.72E-11 1.9 8.42 75.9 848 1.66E-10 2.3 7.97 87.4 902 1.41E-10 5.0 8.50 100.7 968 6.11E-11 2.5 8.46 113.8 1083 2.61E-11 4.2 8.71 136.7 1161 1.22E-10 32.6 6.85 186.3 1184 7.60E-10 274.1 5.74 256.3 1210 7.82E-10 316.9 5.75 Test 3 5.3 67 3.70E-11 3.9 8.61 10.9 167 3.11E-11 1.0 8.65 15.6 228 2.00E-11 0.4 8.54 20.2 357 2.70E-11 0.1 8.47 35.8 463 1.91E-10 0.5 7.71 52.5 523 8.92E-11 2.7 8.50 58.7 569 9.49E-11 2.4 8.30 67.2 652 1.42E-10 3.2 8.55 76.4 713 8.17E-11 3.6 8.02 83.6 786 8.83E-11 1.7 8.71 96.4 852 7.64E-11 1.3 8.02 Triplicate Cumulative Time Hydraulic C u cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L Test 3 continued 109.3 917 2.99E-11 1.6 8.37 120.9 984 6.22E-11 3.7 8.63 143.9 1046 1.36E-10 21.0 6.49 173.4 1068 3.33E-10 202.5 5.71 197.6 1094 2.09E-10 139.6 5.96 319.0 1134 1.43E-09 372.6 5.66 489.2 1161 1.12E-09 439.1 5.68 Binary heavy metal leachates - lead (Pb) & copper (Cu) Bentonite admix permeated with 500 mg/L ofPb & Cu leachate Triplicate Cumulative Time Hydraulic Pb cone. CM cone. Discharge # discharge volume conductivity P H ml hr m/s m g / L m g / L T e s t l 18.0 13 5.00E-10 0.1 8.15 31.5 38 2.83E-10 0.0 0.1 8.27 43.5 64 2.74E-10 0.0 0.6 8.28 52.3 85 2.13E-10 0.0 0.8 8.28 63.9 115 3.15E-10 0.0 0.7 8.23 78.4 133 3.61E-10 0.0 89.7 148 5.13E-10 0.1 1.1 8.26 102.6 161 5.90E-10 0.0 5.8 8.06 127.3 176 1.38E-09 8.8 52.6 6.21 162.1 189 1.64E-09 49.0 159.8 191.6 199 1.65E-09 85.9 203.1 219.3 208 1.62E-09 109.1 230.7 249.3 218 1.56E-09 136.5 246.0 5.74 277.3 230 1.88E-09 161.1 269.7 5.63 304.3 238 2.02E-09 184.4 282.0 5.58 333.6 246 1.83E-09 204.1 296.0 5.58 371.3 257 2.06E-09 213.6 313.2 5.48 449.3 276 2.41E-09 181.5 319.0 5.48 575.8 305 2.47E-09 243.0 332.0 5.40 686.8 329 2.72E-09 269.0 345.0 5.35 798.8 349 3.36E-09 289.5 367.0 5.21 931.8 370 3.50E-09 306.5 380.0 5.30 1035.8 387 3.68E-09 319.0 378.5 5.27 1159.3 405 4.07E-09 356.0 415.6 5.30 1306.8 425 4.33E-09 368.0 418.0 5.25 1415.6 439 4.26E-09 380.8 422.4 5.26 1515.6 452 4.88E-09 391.6 432.0 5.27 1634.8 466 4.99E-09 398.4 440.0 5.23 2019.8 505 5.80E-09 414.0 448.8 5.17 2420.7 545 5.96E-09 2571.7 559 5.96E-09 438.5 459.0 5.09 2715.2 572 5.78E-09 444.0 464.0 5.11 2975.2 615 6.18E-09 436.0 459.5 5.06 3153.7 648 2.14E-09 442.0 465.5 5.08 2840.7 588 2.99E-09 443.5 469.5 5.08 Forest soil admix permeated with 500 mg/L ofPb & Cu leachate Triplicate Cumulative Time Hydraulic Pb C u Discharge # discharge volume conductivity cone. cone. P H ml hr m/s m g / L m g / L T e s t l 10.3 32 7.91E-10 21.1 113.3 4.70 25.5 39 3.77E-10 14.0 141.4 4.77 46.8 46 1.28E-09 48.6 198.5 4.66 74.5 . 58 4.99E-10 23.0 175.4 4.73 93.0 70 3.24E-10 18.9 155.0 4.76 120.5 88 5.95E-10 24.3 146.6 4.82 153.5 111 2.90E-10 26.1 140.6 4.91 178.0 129 3.66E-10 25.3 139.5 4.94 212.8 153 5.23E-10 4.4 140.2 5.03 250.5 177 3.36E-10 4.6 149.4 5.06 297.5 200 7.54E-10 8.6 208.2 4.68 357.3 225 6.02E-10 16.7 253.2 4.50 409.0 246 6.15E-10 15.7 285.5 4.39 460.5 267 6.93E-10 18.8 302.0 4.34 522.5 292 7.65E-10 35.2 312.1 4.26 613.0 321 1.05E-09 151.0 342.0 4.24 707.5 350 7.23E-10 200.5 350.7 4.23 797.5 375 1.09E-09 258.7 433.4 4.20 893.5 408 7.31E-10 330.4 403.1 4.12 Test 2 28.0 32 9.95E-10 12.5 67.3 4.38 42.5 39 1.13E-10 13.5 85.9 4.91 51.5 46 5.91E-10 11.8 85.0 5.04 66.8 58 3.37E-10 20.6 86.1 5.05 81.5 70 3.24E-10 13.9 95.3 4.93 115.0 88 7.69E-10 18.4 164.5 4.65 161.5 111 4.64E-10 35.5 242.4 4.52 206.5 129 7.62E-10 58.1 290.1 4.34 276.0 153 1.02E-09 21.0 339.1 4.23 353.5 177 7.38E-10 30.9 357.3 4.19 465.9 200 1.87E-09 65.4 421.1 4.10 643.2 225 2.13E-09 99.8 462.1 4.09 834.4 246 2.39E-09 112.7 473.1 4.06 956.1 258 1.29E-09 117.2 471.8 4.01 1084.8 270 4.59E-09 116.8 480.1 4.06 1535.0 321 6.54E-09 482.0 480.6 4.14 Test 3 11.0 46 8.85E-10 12.5 81.6 4.50 37.5 88 4.48E-10 13.4 74.6 5.22 58.8 111 1.34E-10 13.2 83.7 5.40 70.0 129 1.68E-10 8.6 61.0 5.58 86.5 153 2.53E-10 2.1 60.1 5.66 113.0 177 3.47E-10 4.4 135.6 5.16 140.5 200 2.83E-10 7.9 118.6 5.25 163.0 225 2.28E-10 5.7 109.6 5.37 185.5 246 3.07E-10 7.7 142.5 5.17 216.0 267 4.66E-10 4.79 Triplicate # Cumulative discharge volume Time Hydraulic conductivity Pb cone. C u cone. Discharge P H ml hr m/s m g / L m g / L Test 3 continued 255.5 292 4.65E-10 223.9 4.78 293.0 321 3.08E-10 64.3 245.6 4.71 320.5 350 2.07E-10 46.4 202.8 4.84 344.8 375 2.82E-10 44.5 204.2 4.86 371.8 408 2.26E-10 67.2 249.8 4.66 Spruce bark admix permeated with 500 mg/L ofPb & Cu leachate Triplicate Cumulative Time Hydraulic Pb cone. C u cone. Discharge # discharge volume conductivity P H ml hr rh/s m g / L m g / L T e s t l 4.0 53 0.9 0.4 6.72 15.3 89 1.79E-10 1.9 1.6 7.17 26.7 150 1.39E-10 1.3 3.1 7.83 33.0 196 7.29E-11 1.5 2.7 8.44 61.6 257 9.00E-10 462.2 499.9 5.21 201.8 279 2.78E-09 406.2 463.0 5.29 399.8 315 1.28E-09 293.7 467.6 5.19 513.7 340 6.43E-10 357.1 457.5 5.19 595.3 359 1.52E-09 375.4 438.6 5.20 709.0 391 2.57E-09 308.7 453.6 5.22 837.2 413 1.59E-09 375.4 461.1 5.16 Test 2 6.5 89 1.61E-10 1.0 1.0 7.40 17.1 150 1.35E-10 1.2 2.6 7.95 26.3 196 1.76E-10 1.2 2.5 8.16 55.0 210 9.39E-10 13.6 134.7 5.82 105.5 224 1.08E-09 57.6 420.4 5.32 202.7 242 2.15E-09 308.7 481.4 5.30 326.9 258 1.84E-09 187.9 446.6 5.35 646.9 279 6.65E-09 468.5 498.0 5.10 1187.8 315 4.17E-09 474.8 513.8 4.95 1551.8 340 1.94E-09 471.6 520.3 4.85 1773.4 359 3.89E-09 446.6 496.7 4.84 2063.5 391 6.56E-09 474.8 510.4 4.82 2287.4 413 1.59E-09 Test 3 6.5 89 1.61E-10 1.0 0.7 7.12 18.6 150 1.87E-10 1.3 2.2 8.01 27.7 196 1.19E-10 1.6 2.8 8.33 38.7 241 2.37E-10 1.6 3.8 8.50 91.2 279 1.10E-09 16.3 252.6 5.57 197.2 315 9.24E-10 79.8 402.6 5.36 283.1 340 5.45E-10 153.3 428.7 5.40 366.5 359 1.71E-09 176.3 434.6 5.37 424.8 378 296.7 465.7 5.33 512.5 413 2.10E-09 372.4 475.2 5.26 Ternary heavy metal leachate - lead (Pb), copper (Cu), & cadmium (Cd) Bentonite admix permeated with 500 mg/L ofPb, Cu, & Cd leachate Triplicate Cumulative Time Hydraulic Pb C u C d Discharge # discharge volume conductivity cone. cone. cone. p H ml hr m/s m g / L m g / L m g / L T e s t l 5.0 50 4.31E-10 0.0 1.2 4.6 8.00 13.3 61 1.68E-10 0.0 1.1 1.9 8.09 34.5 84 3.88E-10 0.0 2.1 20.7 7.76 69.7 112 3.23E-10 2.6 47.2 114.9 6.22 109.3 132 5.48E-10 40.4 162.1 215.1 5.83 140.8 144 3.55E-10 82.0 232.9 267.9 5.71 167.6 160 5.74E-10 104.0 244.7 283.4 5.68 210.8 174 9.34E-10 77.2 286.0 315.3 5.54 267.8 184 1.78E-09 40.4 330.0 354.4 5.49 313.8 195 6.58E-10 54.4 319.0 344.5 5.45 349.8 204 1.21E-09 52.6 319.0 345.9 5.45 394.3 215 1.09E-09 63.7 333.7 360.1 5.35 454.3 229 1.40E-09 82.4 352.1 371.5 5.22 512.3 242 8.85E-10 120.0 363.1 385.2 5.14 582.8 255 1.93E-09 153.2 374.1 392.4 5.09 701.0 279 262.3 381.5 401.8 5.16 807.1 299 9.76E-10 305.3 399.9 411.3 5.11 891.1 311 2.04E-09 320.5 399.9 417.9 5.06 999.1 326 2.23E-09 352.4 407.2 422.4 5.08 1082.5 337 1.08E-09 379.0 407.2 424.6 5.11 1196.2 350 3.71E-09 397.0 418.3 434.2 5.07 1775.3 417 3.79E-09 461.8 469.8 480.7 4.94 Test 2 6.0 44 0.0 1.0 1.9 7.90 14.0 50 0.0 1.2 7.1 7.97 23.6 61 2.35E-10 0.0 2.2 26.6 7.63 44.6 84 3.56E-10 0.4 7.9 52.7 . 6.76 74.4 112 2.49E-10 10.3 64.9 112.0 6.12 105.1 132 4.26E-10 25.1 101.8 143.8 6.01 131.4 144 3.45E-10 47.9 150.4 195.5 5.85 158.9 160 6.06E-10 68.5 176.9 219.8 5.80 206.1 174 1.04E-09 91.6 244.7 283.9 5.66 266.6 184 1.81E-09 33.7 315.3 341.7 5.55 313.1 195 6.58E-10 38.5 315.3 338.9 5.53 347.1 204 1.10E-09 46.9 319.0 343.8 5.54 390.1 215 1.12E-09 95.7 330.0 351.6 5.42 450.1 229 1.39E-09 124.0 344.7 364.4 5.38 507.1 242 8.64E-10 165.4 359.4 378.0 5.30 573.6 255 1.80E-09 158.3 370.4 390.2 5.21 708.1 279 1.94E-09 267.7 392.5 407.0 5.24 838.0 299 1.08E-09 324.9 414.6 427.5 5.20 931.5 311 2.28E-09 338.0 414.6 424.6 5.20 1051.1 326 2.46E-09 385.7 418.3 427.5 5.18 Triplicate Cumulative Time Hydraulic Pb C u C d Discharge # discharge volume conductivity cone. cone. cone. p H ml hr m/s m g / L m g / L m g / L Test 2 continued 1149.7 337 1.52E-09 408.2 422.0 433.4 5.12 1285.0 350 4.23E-09 408.2 425.6 441.6 5.12 1809.3 417 3.27E-09 453.8 469.8 484.5 5.05 APPENDIX F SELECTIVE SEQUENTIAL EXTRACTION CALCULATIONS AND DATA 223 F . l . A C C U R A C Y O F T H E S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N P R O C E D U R E F.2. C A L C U L A T I O N S F O R S O R P T I O N C A P A C I T I E S O F A D M I X E S B A S E D O N B A T C H A D S O R P T I O N R E S U L T S F O R I N D I V I D U A L M A T E R I A L S F.3. S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N D A T A A P P E N D I X F . l . A C C U R A C Y OF T H E S E L E C T I V E S E Q U E N T I A L E X T R A C T I O N P R O C E D U R E 224 Since the sorbed amount of heavy metals were calculated for the admix samples submitted to Batch adsorption tests, heavy metal recoveries could be calculated after submitting the same samples to Selective Sequential Extraction (SSE). The heavy metal recoveries are shown in Table F. l . l . Excluding two outliers, the average recovery of the SSE procedure was 91%. The systematically low recovery probably was due to the loss of sample during the washing and decanting steps of the SSE procedure. Since the recoveries were relatively consistent, the two outliers were probably caused by an error in the Batch adsorption test procedure. Large dilution factors were required to bring some Batch adsorption samples to within measurable range. Large dilution factors coupled with low sorption quantities result in large random errors. TABLE F.l.l. Recovery results for the Selective Sequential Extraction procedure. Admix H M * solution H M * analyzed Total cone, of Total cone. H M Recovery H M sorbed extracted using SSE W?/g soil ug/g soil Bentonite Cu 1st C M 567 574 101% admix Cu 2nd C M . 541 565 105% Pblst Pb : 1803 1604 89% Pb2nd Pb 1 6 8 7 1760 104% Pb+Cu 1st Cu 4 3 9 4 2 3 96% Pb+Cu 1st Pb 1166 1174 101% Pb+Cu 2nd Cu 4 5 5 4 4 9 99% Pb+Cu 2nd Pb 1354 1238 91% Pb+Cu+Cd 1st Cd 4 8 7 2 6 7 55%** Pb+Cu+Cd 1st Cu 861 378 44%** Pb+Cu+Cd 1st Pb 1211 1079 89% Pb+Cu+Cd2nd Cd 4 6 9 264 56%** Pb+Cu+Cd2nd Cu 958 3 6 7 38%** Pb+Cu+Cd2nd Pb 1140 1090 96% Forest Cu 1st Cu 8 5 9 738 86% soil Cu 2nd Cu 936 721 77% admix Pblst Pb 2146 1912 89% Pb2nd Pb 2163 2088 97% Pb+Cu 1st Cu 710 526 74% Pb+Cu 1st Pb 1 3 3 7 1252 94% Pb+Cu 2nd Cu 6 1 9 523 85% Pb+Cu2nd Pb 1356 1280 94% Spruce Cu 1st Cu 591 5 9 9 101% bark Cu 2nd Cu 642 5 5 2 86% admix Pblst Pb n/a 1268 n/a Pb2nd Pb n/a 1 2 9 7 n/a Pb+Cu 1st Cu 4 1 2 3 9 9 97% Pb+Cu 1st Pb 756 825 109% Pb+Cu 2nd Cu 554 3 8 9 70% Pb+Cu 2nd Pb 846 803 95% * H M - Heavy metal ** outliers n /a - not available 226 A P P E N D I X F.2. C A L C U L A T I O N S F O R S O R P T I O N C A P A C I T I E S OF A D M I X E S B A S E D O N B A T C H A D S O R P T I O N R E S U L T S F O R I N D I V I D U A L M A T E R I A L S The calculations for the sorption capacities of the admixes are, CjBentonite admix — CjBentonite qForest soil admix = CjBentonite ' 7/8 + qForest soil '1/8 qSpruce bark admix — CjBentonite * 7/ 8 + qSpruce bark '1/8 where qbentonite admix, qForest soil admix, and qspmce bark admix, are the sorption capacities for the Bentonite, Forest soil, and Spruce bark admixes, qBentonite, qForest soil, and qspmcebark are the sorption capacities for Bentonite, Forest soil, and Spruce bark, and the number fractions are based on the compositions of the admixes. The calculations for the sorption capacities of bentonite, Forest soil, and Spruce bark are, qbentonite qForest soil qSpruce bark Inputs: 500 mg/L of Pb, Cu, and Cd. Sorption equations for different combinations of Pb, Cu, and Cd. where the sorption equations are taken from section 4.2.1.4. The compositions of the admixes are, Bentonite admix Forest soil admix Spruce bark admix = 100:8 sand and bentonite = 100:7:1 sand, bentonite, and Forest soil = 100:7:1 sand, bentonite, and Spruce bark 227 APPENDIX F.3. SSE DATA Single heavy metal leachates ofPb and Cu Bentonite admix permeated with 500 mg/L o/Pb leachate TEST1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gsoil Ug/gsoil ug/gsoil ug/gsoil ug/gsoil Center 1 804 638 96 25 6 2 76 257 18 3 0 3 476 402 74 10 0 4 470 363 71 12 2 Edge 1 679 401 83 11 0 2 2 23 7 5 29 3 1 2 1 0 0 4 1 3 3 0 0 TEST 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gsoil Ug/gsoil ug/gsoil ug/gsoil ug/gsoil Center 1 7 290 286 20 10 2 6 68 82 6 4 3 4 18 167 6 7 4 3 55 24 2 1 Edge 1 13 151 111 9 4 2 0 1 1 0 1 3 3 0 1 0 1 4 1 1 9 1 2 Bentonite admix permeated with 500 mg/L ofCu leachate TEST 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/gsoil ug/gsoil Ug/gsoil ug/g soil ug/gsoil Center 1 378 116 30 5 5 2 372 142 24 4 3 308 146 23 3 5 4 339 133 24 5 8 Edge 1 220 112 24 3 4 2 0 7 5 1 1 3 146 19 11 3 3 4 69 90 20 3 1 228 Forest soil admix permeated with 500 mg/L ofPb'leachate TEST1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gsoil ug/g soil ug/gsoil Ug/gsoil ug/g soil Center 1 7 131 34 15 2 2 16 11 3 3 14 238 64 31 4 3 5 6 2 Edge 1 32 302 61 41 2 1 0 1 0 3 1 0 1 0 4 5 89 26 16 TEST 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/g soil ug/gsoil ug/g soil ug/gsoil ug/gsoil Center 1 241 695 192 68 2 48 377 96 49 3 1 4 0 0 4 127 493 122 54 Edge 1 403 999 215 109 2 0 2 1 0 3 3 4 1 2 4 15 206 64 34 TEST 3 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gsoil ug/g soil ug/gsoil ug/g soil ug/gsoil Center 1 494 754 143 60 2 2 1 1 1 2 0 3 1 1 1 1 0 4 1 2 3 1 0 Edge 1 769 885 209 75 0 2 64 411 78 37 0 3 1 1 1 2 0 4 23 285 55 23 0 Forest soil admix permeated with 500 mg/L ofCu leachate TEST1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /g soil ug /g soil ug /g soil ug /g soil ug /g soil Composite 1 295 243 100 42 23 2 3 48 26 29 11 3 1 23 16 21 12 4 30 125 49 37 16 TEST 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/g soil ug /g soil ug /g soil ug /g soil ug / g soil Composite 1 391 237 124 49 25 2 102 n / a 119 40 23 3 1 29 16 21 11 4 44 149 56 39 18 Spruce bark admix permeated with 500 mg/L ofPb leachate TEST 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /g soil Ug/g soil ug /g soil Ug/g soil Ug/g soil Center 1 156 1533 56 150 2 1 4 3 0 3 2 54 7 22 4 56 534 55 59 Edge 1 25 396 47 61 2 25 351 39 58 3 7 180 20 44 4 147 823 109 73 Spruce bark admix permeated ivithBOO mg/L ofCu leachate TEST 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/g soil Ug/g soil ug /g soil Ug/g soil u g / g soil Center 1 205 361 30 47 7 2 3 49 12 12 6 3 1 4 1 3 1 4 80 137 42 21 5 Edge 1 156 271 32 43 5 2 52 154 25 28 7 3 33 108 21 19 6 4 162 144 56 33 4 230 TEST 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /gso i l ug /gso i l Ug/gsoi l Ug/gsoi l ug /gso i l Center 1 182 . 150 201 29 4 2 0 3 1 3 2 3 0 1 0 1 0 4 1 2 0 5 2 Edge 1 67 229 41 23 9 2 0 2 1 2 0 3 0 3 1 2 1 4 1 13 3 4 2 Binary heavy metal leachates ofPb and Cu Bentonite admix permeated with 500 mg/L ofPb & Cu leachate T E S T 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/gsoi l Ug/gsoi l ug /gso i l ug /gso i l ug /gso i l Pb Cu Pb Cu Pb Cu Pb Cu C M Center 1 703 280 335 97 115 25 14 5 7 2 2 191 154 99 100 57 24 6 4 3 3 3 19 24 40 79 19 21 1 2 2 3 4 520 182 260 120 85 31 10 5 5 3 Edge 1 519 334 135 99 123 30 12 4 5 4 2 75 92 59 92 38 26 2 3 3 2 3 359 231 126 94 98 27 8 3 2 1 4 257 177 120 115 72 29 6 4 3 2 Forest soil admix permeated with 500 mg/L ofPb & Cu leachate TEST 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /gso i l Ug/gsoi l ug /gso i l ug /gso i l u g / g soil Pb C M Pb C M Pb C M Pb C M Pb Cu Composite 1 540 274 361 167 139 74 29 37 0 16 2 29 20 117 84 37 39 14 30 0 13 3 2 15 37 85 17 37 9 32 0 10 4 17 1 91 19 27 11 13 19 0 8 231 T E S T 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/g soil ug /g soil ug /g soil ug /g soil ug /g soil Pb C M Pb C M Pb C M Pb C M Pb Cu Composite 1 293 154 282 143 77 52 18 35 4 19 2 4 2 54 30 19 17 5 21 1 10 3 3 1 37 14 15 8 3 17 1 8 4 52 34 154 106 46 41 14 36 1 12 T E S T 3 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /g soil Ug/g soil ug /g soil ug /g soil Ug/g soil Pb Cu Pb C M Pb C M Pb C M Pb Cu Composite 1 212 151 216 151 72 61 19 37 0 13 2 1 0 13 14 8 7 4 16 0 9 3 1 1 12 6 9 3 6 11 0 7 4 4 3 41 44 18 23 9 25 0 10 Spruce bark admix permeated with 500 mg/L ofPb & Cu leachate T E S T 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /g soil ug /g soil ng/g soil ug /g soil ug /g soil Pb C M Pb C M Pb C M Pb C M Pb Cu Center 1 121 114 208 193 29 35 53 13 2 O 1 1 0 1 1 0 0 2 O 4 36 37 110 117 18 40 38 13 Edge 1 23 28 120 121 6 16 36 11 2 1 0 0 0 1 0 0 1 o 4 54 39 179 134 11 23 47 11 T E S T 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug /g soil ug /g soil ug /g soil ug /g soil u g / g soil Pb C M Pb C M Pb C M Pb C M Pb Cu Center 1 158 143 232 181 36 32 57 13 2 2 1 1 3 2 1 0 2 3 2 1 1 2 2 4 0 1 4 58 44 150 130 9 20 39 15 Edge 1 212 158 228 145 36 23 61 12 2 92 53 163 109 13 16 42 11 3 56 25 157 81 8 15 40 9 4 178 99 253 152 26 31 53 14 232 T E S T 3 Location Layer Exchangeable Carbonates Hydroxides Organics Residue Ug/gsoi l Ug/gsoi l ug /g soil ug/gso i l ug/gso i l Pb Cu Pb C M Pb C M Pb C M Pb C M Center 1 163 140 177 196 78 36 38 21 6 12 2 1 0 1 0 0 0 0 1 0 1 3 1 1 1 0 1 0 0 1 0 1 4 1 1 18 16 5 9 3 5 1 3 Edge 1 77 64 192 136 34 25 40 20 0 3 2 7 6 120 61 11 21 33 7 2 4 3 9 11 108 61 9 20 28 8 0 2 4 53 38 183 104 23 31 39 11 4 8 Ternary heavy metal leachate ofPb, Cu, and Cd Bentonite admix permeated with 500 mg/L ofPb, Cu, and Cd leachate T E S T 1 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gsoi l ug/gsoi l ug/gso i l ug/gso i l ug/gso i l Pb Cu Cd Pb Cu Cd Pb Cu Cd Pb Cu Cd Pb C M Cd Composite 1 592 250 239 168 82 5 93 27 3 24 7 3 0 2 0 2 122 119 186 68 72 7 40 22 2 12 6 2 0 4 0 3 69 45 113 60 48 2 25 16 2 6 3 1 1 3 0 4 152 103 156 78 69 4 34 19 2 9 5 1 0 3 0 T E S T 2 Location Layer Exchangeable Carbonates Hydroxides Organics Residue ug/gso i l ug/gso i l ug/gso i l ug /gso i l ug /gso i l Pb C M Cd Pb C M Cd Pb C M Cd Pb C M Cd Pb Cu Cd Composite 1 521 244 243 133 80 4 83 27 2 32 7 2 0 3 0 2 87 97 181 63 67 5 27 20 1 9 4 1 0 3 0 3 45 29 90 56 42 5 19 14 1 7 4 1 0 2 0 4 182 108 168 91 73 4 34 21 1 15 4 1 0 3 0 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.831.1-0064115/manifest

Comment

Related Items