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 A N D HYDRAULIC CONDUCTIVITY STUDIES USING THREE TYPES OF BENTONITE ADMIXES by  FRANKY LI B. A.Sc. (Civil Engineering), University of British Columbia, 1996 A THESIS S U B M I T T E D I N P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T S F O R THE DEGREE OF MASTER OF APPLIED SCIENCE in T H E F A C U L T Y O F G R A D U A T E STUDIES D E P A R T M E N T OF CIVIL ENGINEERING  We accept this thesis^ as conformi^g"to the  require**'d  standard  T H E UNIVERSITY O F BRITISH C O L U M B I A October, 1999 © Franky L i , 1999  In  presenting  degree freely  this  at the  thesis  in  partial  fulfilment  University  of  British  Columbia, 1 agree that the  available for  copying  of  department publication  this or of  reference  thesis by  this  his  for  and study. scholarly  or  thesis for  her  purposes  of  M  £ s > k , t ^ fvA\  The University of British C o l u m b i a Vancouver, Canada  Date  DE-6  (2/88)  may  representatives.  financial  the  requirements  I further agree  It  gain shall not  permission.  Department  of  <^(?l  be is  Library  an  advanced  shall make  that permission  for  granted  head  by  understood be  for  the that  allowed without  it  extensive of  my  copying  or  my  written  11  ABSTRACT  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 w i t h 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 m g 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 following 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 rigidwalled cells and permeated w i t h 500 m g L" solutions of Pb, Cu, and Cd. The hydraulic 1  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  ABSTRACT  ii  TABLE OFCONTENTS  iv  LIST O F FIGURES  viii  LIST O F T A B L E S ACKNOWLEDGMENTS  x ,  xii  CHAPTER 1 INTRODUCTION  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 2.1.1 Cation exchange 2.1.2 Inner-sphere complexation 2.1.3 Precipitation 2.1.4 The effect of solution pH 2.1.5 The effect of heavy metals on clay structure  11 12 12 14 14 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 2.5.1 Soil organic matter 2.5.2 Spruce bark  23 23 25  CHAPTER 3 MATERIALS AND METHODS  26  3.1  CLAY BARRIER MATERIALS 3.1.1 Origins and Descriptions 3.1.2 Admixtures 3.1.3 Physical properties 3.1.4 Chemical properties  26 26 27 27 28  3.2  CHEMICAL SOLUTIONS  29  3.3  BATCH ADSORPTION TEST METHOD 3.3.1 Batch adsorption test program 3.3.2 Batch adsorption test procedure  30 30 33  3.4  LEACHING CELL TEST METHOD 3.4.1 Leaching cell program 3.4.2 Admix preparation for the Leaching cell test 3.4.3 Compaction procedure 3.4.4 Leaching cell test procedure  36 36 38 39 40  3.5  SELECTIVE SEQUENTIAL EXTRACTION METHOD 3.5.1 Sampling extruded Leaching cell samples 3.5.2 SSE procedure  41 42 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 4.2.1 The multi-heavy-metal sorption model  50 50  4.2.1.1 Isotherm equation selection and general observations 4.2.1.2 Modeling binary heavy metal sorption 4.2.1.3 Modeling ternary heavy metal sorption 4.2.1.4 Summary of sorption equations  4.2.2  64  4.2.2.1 Ranking of materials 4.2.2.2 Ranking of heavy metals  66 67  4.2.3 4.2.4  70  4.2.5 4.3  Heavy metal sorption capacities  51 54 60 63  Heavy metal selectivity and competition Sorption performance of clay barrier materials based on Batch adsorption tests Summary of Batch adsorption test results  THE LEACHING CELL TEST 4.3.1 Hydraulic conductivity results 4.3.1.1 General observations 4.3.1.2 Mechanism of hydraulic conductivity increase  72 73 75 78 78 86  4.4  4.3.1.3 Effect ofheavy metals vs. calcium on hydraulic conductivity 4.3.1.4 Importance of initial saturation 4.3.1.5 The effect of Pb and Cu on hydraulic conductivity 4.3.1.6 Uncertain factors influencing hydraulic conductivity 4.3.2 Heavy metal breakthrough results 4.3.2.1 General observations 4.3.2.2 Migration behavior - non-uniformity andfracturedporous media 4.3.2.3 Retention capacity versus breakthrough point 4.3.2.4 Relative mobility of heavy metals 4.3.3 Performance of admixes 4.3.3.1 Performance based on hydraulic conductivity 4.3.3.2 Performance based on heavy metal breakthrough 4.3.4 Summary of Leaching cell results  87 89 90 91 92 92 98 200 203 104 204 206 108  Selective Sequential Extraction 4.4.1 SSE on a set of Batch adsorption tests 4.4.1.1 Sorption characteristics of the admixes 4.4.1.2 Comparing sorption capacities of mixtures vs. individual materials 4.4.1.3 Comparing the sorption capacities of Batch and Leaching cell samples 4.4.2 SSE on extruded Leaching cell samples 4.4.2.2 Heavy metal migration behavior 4.4.2.2 Heavy metal retention mechanisms 4.4.3 Summary of SSE results and the performance of the admixes  110 Ill 223 224 225 117 227 229 135  CHAPTER 5 CONCLUSIONS & RECOMMENDATIONS  137  5.1  CONCLUSIONS  137  5.2  RESEARCH CONTRIBUTIONS  141  5.3  RECOMMENDATIONS ON FURTHER RESEARCH  143  REFERENCES  145  A P P E N D I X A P H Y S I C A L PROPERTIES O F C L A Y B A R R I E R MATERIALS  152  A P P E N D I X B C H E M I C A L PROPERTIES O F C L A Y B A R R I E R MATERIALS  161  APPENDIX C M E T H O D S SUPPLEMENT  165  APPENDIX D B A T C H A D S O R P T I O N TEST C A L C U L A T I O N S A N D DATA  173  vii  APPENDIX E L E A C H I N G TEST C A L C U L A T I O N S A N D D A T A  198  APPENDIX F SELECTIVE SEQUENTIAL EXTRACTION CALCULATIONS AND D A T A  223  LIST OF FIGURES Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure  1.1.1 1.3.1 2.1.1 2.5.1 3.3.1 3.4.1 3.5.1 4.1.1 4.2.1 4.2.2  Examples of clay barriers F l o w chart of research plan Examples of inner- and outer-sphere complexes Fractionation of soil organic matter and humic substances Diagram of the Batch adsorption test Diagram of Leaching cell test Diagram of the SSE Grain size distribution of clay barrier materials Single heavy metal isotherms Freundlich isotherms of Cu sorption in single & binary heavy metal solutions Figure 4.2.3 Binary sorption data showing how the presence of Cu and Cd affects Pb sorption Figure 4.2.4 Binary sorption data showing how the presence of Pb affects Cu & Cd sorption Figure 4.2.5 Calculated versus actual values for Pb, Cu, and Cd sorption in binary solutions Figure 4.2.6 Calculated versus actual values for Pb sorption i n ternary solutions Figure 4.2.7 Ternary retention data showing how Cu and Cd change each others' sorption capacities Figure 4.2.8 Calculated versus actual values for Cu and Cd sorption in ternary solutions Figure 4.2.9 Heavy metal retention capacities of soil mix materials in single metal solutions Figure 4.2.10 Final p H graphs showing the influence of Pb, C u , and C d , on the final solution p H s of each suspension Figure 4.2.11 Selectivity of heavy metals in ternary and binary systems Figure 4.3.1 Hydraulic conductivity results for leachate blanks Figure 4.3.2 Hydraulic conductivity results for bentonite admix samples Figure 4.3.3 Hydraulic conductivity results for Forest soil admix samples Figure 4.3.4 Hydraulic conductivity results for Spruce bark admix samples Figure 4.3.5 Averaged hydraulic conductivity results grouped by admix type Figure 4.3.6 Averaged hydraulic conductivity results grouped by leachate type Figure 4.3.7 Conceptual model for the mechanism of hydraulic conductivity increase in Leaching cells Figure 4.3.8 Heavy metal breakthrough results for bentonite admix samples Figure 4.3.9 Heavy metal breakthrough results for Forest soil admix samples  4 ...8 13 23 32 37 43 49 52 53 57 58 59 62 62 63 65 67 71 80 81 82 83 84 85 88 93 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 w i t h 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 w i t h Pb 119 Figure 4.4.2 Distribution of heavy metals in bentonite admix samples leached w i t h Cu 120 Figure 4.4.3 Distribution of heavy metals in bentonite admix samples leached w i t h Pb&Cu 121 Figure 4.4.4 Distribution of heavy metals i n Forest soil admix samples leached w i t h Pb 122 Figure 4.4.5 Distribution of heavy metals in Spruce bark admix samples leached w i t h Pb 123 Figure 4.4.6 Distribution of heavy metals i n Spruce bark admix samples leached w i t h Cu 124 Figure 4.4.7 Distribution of heavy metals in Spruce bark admix samples leached w i t h Pb & Cu 125 Figure 4.4.8 Distribution of heavy metals in bentonite admix samples leached w i t h Pb, Cu, & Cd 126 Figure 4.4.9 Distribution of heavy metals in Forest soil admix samples leached w i t h Cu 127 Figure 4.4.10 Distribution of heavy metals i n Forest soil admix samples leached w i t h 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 O F T A B L E S Table 1.1.1 Table 1.1.2 Table 1.1.3 Table 2.2.1 Table 2.3.1 Table 2.3.2 Table 2.4.1 Table 2.5.1 Table 3.3.1 Table 3.3.2 Table 3.3.3 Table Table Table Table Table Table  3.4.1 3.5.1 4.1.1 4.2.1 4.2.2 4.2.3  Table 4.2.4 Table 4.2.5 Table 4.2.6 Table 4.2.7 Table 4.2.8 Table 4.3.1 Table 4.3.2 Table 4.3.3 Table 4.3.4 Table 4.3.5  Historical changes in global production of metals commonly associated w i t h pollution from mining activities Average levels of heavy metals in typical European household waste Typical leachate concentrations of heavy metals for municipal waste in the United States Summary of heavy metal selectivities for clay minerals and soils Summary of correlation results from several heavy metal. adsorption studies SSE results from several heavy metal adsorption studies Descriptions of heavy metal compatibility tests Summary of heavy metal retention studies using bark or bark constituents. ..: Batch adsorption test matrix Heavy metal solution concentrations used in Batch adsorption tests Heavy metal concentration ranges measured by the atomic absorption spectrophotometer The Leaching cell test matrix. The SSE program Physico-chemical properties of soil materials Summary for Batch adsorption test Summary of b and n values fitted for single & binary Cu data Summary of sorption equations for binary heavy metal solutions Summary of sorption equations for ternary heavy metal solutions Single Pb, Cu, and Cd sorption equations and their competition functions Summary of relative heavy metal sorption capacities Characteristics of Pb, Cu, & Cd Summary of competition amongst Pb, Cu, and Cd Summary for the Leaching cell test Physical properties of Leaching cell samples Summary of hydraulic conductivity results from averaged data i n Figures 4.3.5 & 4.3.6 Comparison between retention mechanisms of Ca and the heavy metals Summary of heavy metal breakthrough data from averaged data in  1 2 3 16 18 18 22 25 30 31 34 36 41 48 50 53 56 61 64 .65 68 72 75 77 86 .90  Table 4.3.6 Table 4.3.7 Table 4.4.1 Table 4.4.2 Table 4.4.3 Table 4.4.4 Table 4.4.5 Table 4.4.6 Table 4.4.7  Figures 4.3.11 & 4.3.12. Summary of heavy metal breakthrough points & retentions Heavy metal mobilities of bentonite Summary for the SSE tests SSE results for Batch adsorption tests on admixes Comparison of admixes based on SSE and Batch adsorption samples Averaged sorption characteristics for admixes based on SSE of Batch adsorption tests Sorption capacities of admixes Comparing max. extractions of Leaching cell and Batch adsorption test samples SSE data for Cd from the bentonite admix  102 103 110 112 113 114 115  ACKNOWLEDGMENTS  The author w o u l d 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 i n her life. Dr. Les Lavkulich, 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. M s . Susan Harper, and M s . Paula Parkinson, for their advice, and assistance regarding laboratory equipment and procedures. Kurt, for an excellent job i n constructing any equipment required for the project. W i l l i a m Denham, for his assistance and advice on the project, and for consuming a large quantity of coffee w i t h me during the course of the project. A l l m y friends and colleagues i n the Geoenvironment group, who have been very supportive i n both w o r d and action. Forintek Canada Corporation for providing the Spruce bark.  I w o u l d also like to thank the many friends that I have met along the way. Your lives have kept m y thesis and my life i n perspective. I w o u l d like to thank m y family and relatives for their incredible support, encouragement, and love. Finally, I w o u l d like to thank G o d for H i s grace i n m y life and work.  "There is a time for even/thing, and a season for every activity under heaven" Ecclesiastes 3:1  1  CHAPTER 1 INTRODUCTION  1.1  STATEMENT OF PROBLEM  M i n i n g , 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, w i n d , water currents, and groundwater flow (Fergusson, 1990). Table 1.1.1 shows the global production of metals commonly associated w i t h pollution from mining activities. Of these, Cu and Pb are among the top six metals produced (Allan, 1995).  TABLE  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.)  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  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  Metal  Nickel  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  1.1 S T A T E M E N T OF P R O B L E M  2  The toxicity of heavy metals lead to reduced crop yields, death of marine life (Crosby, 1998), and serious health problems i n humans. Lead (Pb) affects the nervous blood systems. Copper (Cu) causes tremors, laboured respiration, and hemolysis (Crosby, 1998). C a d m i u m (Cd) affects the renal system, cardiovascular system, and the skeleton. Cd also is k n o w n to cause cancer i n 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 i n 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 i n 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 i n the United States.  TABLE  1.1.2. Average levels of heavy metals in typical  European household waste  (Rousseaux et al., 1989). Concentration (ppm)  Hg 1-3  Cd 3-5  Pb 100-700  Zn 400 -1000  Cu 100 - 300  Ni 20-50  Cr 50 -100  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  3  1.1 S T A T E M E N T OF PROBLEM  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  Concentration ND - 3.0 (ppm) ND - non-detectable  Cd  ND - 0.4  Pb  Z M  ND -14.2  ND - 731  Cu  ND - 9.0  Ni  Cr  ND - 7.5  ND - 5.6  Engineered clay barriers are commonly used as vertical barriers and landfill liners (Figure 1.1.1). Clay barriers are constructed from locally found soils amended w i t h clay. The clay may also be mined locally, or bought commercially. Clay barriers are effective primarily because they possess l o w 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 w o u l d be deemed incompatible w i t h that contaminant. Besides having l o w 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; L o 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 i n understanding the extent and mechanism i n which heavy metals affect  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4  1.1 S T A T E M E N T OF PROBLEM  hydraulic conductivity, as well as i n improving the heavy metal compatibility of clay barriers.  b) Surface impoundment liner.  (k<1«10- cm/B>  <k!1«1<r' emit)  7  * Synthetic drainage materta (Trartsmissivity2 3x10~ m s> 4  a  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  5  SCOPE A N D OBJECTIVES  M a n y of the past studies placed emphasis on comparing various permeameters and testing conditions (see section 2.4) i n order to isolate the effect of heavy metals o n 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 i n hydraulic conductivities may be due to differences i n 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 o n the sorption and migration behavior of heavy metals w o u l d be beneficial i n 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 w o u l d improve heavy metal compatibility. These alternative materials w o u l d 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 i n 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.) i n 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 w i t h 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 i n 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 w i t h either Forest soil or Spruce bark. Improved compatibility w o u l d be evidenced by increased heavy metal retention while maintaining a l o w hydraulic conductivity.  1.3  THE RESEARCH PLAN  To accomplish the objectives presented i n the previous section, a research plan was created containing four main sets of tests. A flow chart outlining the research plan is shown i n Figure 1.3.1.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  1.3. RESEARCH P L A N  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  a ji  s o  (0 LU > t— O LU -J DO O  o E  S|B)eUI AAeet) j o uoi)ejB|ui a i n 6ui6euew pue Gujiojpejd u; i s j s s e pue ' s j e i u e q A e p 10 AjMiqnBduioo |e|aui AAeeu, e i n OAOjduii o) U I I B sgsein s i i n j o s e A i p o f q o e m  I-L,  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  1.3. RESEARCH P L A N  1.4  9  RESEARCH CONTRIBUTIONS  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 O R G A N I Z A T I O N OF THESIS  1.5  10  O R G A N I Z A T I O N OF THESIS  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 i n 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 w i 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. M u c h 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 SOIL I N T E R A C T I O N S  The three mechanisms for heavy metal retention i n 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 H E A V Y M E T A L A N D SOIL INTERACTIONS  2.1.1  12  Cation Exchange  Cation exchange describes the phenomenon i n 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 l o w 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 w i t h 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 i n 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 i n which electrons are shared amongst the bound ions. Presented below are important surface functional groups associated w i t h minerals and soil organic matter. For minerals, the hydroxyl groups are important surface functional groups. The divalent transition metals readily form inner-sphere complexes w i t h 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 H E A V Y M E T A L A N D SOIL INTERACTIONS  13  A s 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 o n 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 rO \ q J Ba2+  oxygen  O U T E R  - P S  N E R E  complex  A water molecule  inner-sphere complexes Cu  FIGURE  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  14  2.1 H E A V Y M E T A L A N D SOIL INTERACTIONS  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. A m o n g the most important precipitation reactions, are those that involve the hydroxide (OH ) ligand. Metals that are expected to precipitate as hydroxides are F e , -  3+  A l , C u , F e , Z n , and C d 3 +  2 +  2+  2 +  2 +  (Evans, 1989). In addition, metal ions also commonly  precipitate as carbonates (CO3 ") and sulphides (S *).  Metals that are expected to  2  2  precipitate as carbonates are C a , S r , B a , F e , Z n , C d , and P b . Although 2 +  2+  2+  2+  2 +  2 +  2+  carbonates occur i n both oxidizing and reducing conditions, sulphides are stable only in reducing conditions. Metals that occur as sulphides i n reducing conditions include A g , N i , Z n , C d , H g , F e (Evans, 1989). +  2.1.4  2 +  2 +  2 +  2 +  3+  The effect of solution p H  Heavy metal retention mechanisms are affected by solution p H i n several ways. In regards to cation exchange, the high concentration of H ions associated w i t h l o w +  p H conditions compete w i t h other cations for exchange sites. Also, the H ions may +  bond to negatively charged surface functional groups contributing to an overall reduction i n the negative charge of the soil particle. A s 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 i n metal +  solubility equations. In general, precipitation increases w i t h 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  15  The effect of heavy metals on clay structure  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). W h e n double layer thicknesses are great, repulsive forces dominate, resulting i n a dispersed particle structure. W h e n double layer thicknesses are small, attractive forces dominate, resulting i n a flocculated particle structure. Thus, increasing concentrations of heavy metal solutions w o u l d cause decreases i n 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 i n lower hydraulic conductivity, because "fluid transport through soil pores must overcome the increased energy field established by the repulsive forces" (Yong et al., 1992).  2.2  STUDIES I N H E A V Y M E T A L RETENTION SELECTIVITY  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, i n 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. M a n y studies have been conducted to find and explain the selectivity of heavy metals. A survey of these studies shows discrepancies i n 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.  Bladel et al., 1992 Yong & Phadungchewit, 1993 Morley & Gadd, 1995  Sorbant Material Montmorillonite Kaolinite Bentonite, illite, vermiculite Montmorillonite, kaolinite, illite, natural clay (pH > 4 or 5) Montmorillonite, kaolinite  Order of Selectivity Cd«Zn>Ni Cd*Zn>Ni Zn>Cd Pb>Cu>Zn>Cd  Mohamed & Antia, 1998  General soils  Mohamed & Antia, 1998  General soils  Ca>Mg>Hg>Cd>Zn (general order for divalent metals) Cu>Ni>Co>Fe>Mn (transitional divalent metals)  Author(s) Puis & Bohn, 1988  Cu»Cd>Zn  Reason HSAB principle* HSAB principle* Ionic potential 1st hydrolysis product Irving-Williams order of stability Ionic radius  Irving-Williams order of stability  * Hard-Soft-Acid-Base principle  Several points can be made to clarify the discrepancies shown i n Table 2.2.1. The Irving-Williams order of stability (Irving & Williams, 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 w o u l d 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 i n 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 H E A V Y 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, i n citing the 1st hydrolysis product, Y o n g and Phadungchewit (1993), were implying that hydroxide precipitation was the dominant factor i n 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 w i t h 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 H E A V Y 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  Soldatini et al., 1976  12 soils side ranging in organic matter, and clay and carbonate content Samples from 2 layers of the Hawthorne Formation Samples from 6 soil horizons within soil profile 14 different types of minerals and soils 9 soils  Pb  Positive Correlations to Heavy Metal Retention Organic and clay content  Pb, Cu, Zn, Cd  Clay content  Cd, Ni, Cu  Organic content  Rose, S., 1989 Barry et al., 1995 Arnfalk et a l , 1996 Gao et a l , 1997  Cd, Cr(III), Organic content Cr(VI), Hg, Pb Ni, Cu, Cd, Zn Organic content  TABLE 2.3.2. SSE results from several heavy metal adsorption studies. Author(s) Hickey & Kittrick, 1984 Yanful et a l , 1988 Ramos et al., 1994  Heavy Metal Cu Cd Cu Pb, Zn, Fe Cu Pb, Zn Cd  Highest Associated Component Organic Exchangeable Organic Carbonate Organic Oxide Exchangeable & Carbonate  The following observations were made from the Batch adsorption and SSE studies:  1. Heavy metal retention often is associated w i t h 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  H E A V Y M E T A L COMPATIBILITY STUDIES  2.4  19  H E A V Y M E T A L COMPATIBILITY STUDIES  M a n y 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 w i t h 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 i n Table 2.4.1. Conclusions from the five studies are summarized below:  1. D u n n 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 w i t h 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 p p m 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 p p m concentration of Pb produced hydraulic conductivity values significantly higher than w i t h distilled water. Heavy metal breakthrough occurred i n all the kaolinite samples, but in the sand/bentonite samples, only the 2500 p p m Pb permeant resulted i n breakthrough. A l l heavy metal breakthroughs coincided w i t h a sudden drop i n 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 i n 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 w i t h 1750 p p m and 2500 p p m of Pb. The retardation factors calculated from the Batch adsorption tests were significantly larger than those calculated from breakthrough curves. 5. L o 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 i n maintaining a l o w hydraulic conductivity while retaining the Pb and 1,2-dichlorobenzene (DCS).  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 L o et al. (1994), emphasis was placed on experimenting w i t h various permeameters, compaction methods, and experimental procedures, such as hydraulic gradient, and confining pressure. This limited the work done i n studying the sorption and migration behavior of heavy metals. L o et al. (1994), developed a new composite liner that improved heavy metal compatibility. However, the process i n 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  Liner Material  Heavy metal leachate 200 ppm Zn + 15 ppm Pb (pH 2.5) £  H  _2 o  y £  ^  DH 0 O  j- °  o ^ e o o c ^5 n  CO  Lo et al., 1994  in  J  composite liner  J  Claymax, humic acid-aluminum hydroxide coated montmorillonite (HA-AIOH-Clay), and HA-AIOHClay & Clay  triaxial cell  7 phosphate buffer  69.2 ppm NaCl + 100.6 ppm Pb + pH  2  62.2 ppm 1, 2 DCB + tap water  3  consolidation cell, triaxial cell  distilled water  ^  250 - 2500 ppm kaolinite, and sand/Naconcentrations of bentonite mixture Pb(N0 ) , and 2000 ppm ZnSOi  s  Cabral, 1992  CH  consolidation cell  °  3 2  t  distilled water  CN  250 - 2500 ppm kaolinite, and sand/Naconcentrations of bentonite mixture Pb(NQ ) (pH3.6)  static  static  Blank Permeameter Compaction leachate method tap water triaxial cell static, impact, and kneading fixed-wall cell, dynamic and triaxial cell  Comining pressure 150 kPa  135.4 kPa  60 - 370 kPa (for triaxial) 35 - 49 kPa (for con. cell)  13.79 - 35.16 kPa  r^. f^.  Weber, 1991  Dunn and 2 silty clay soils Mitchell, 1984 Peirce et 3 clay soils al., 1987  Author  25,50, Batch tests, and and 100 Pb extraction from extruded Leaching cell samples using ammonium acetate 25, 50, Batch tests, and and 100 Pb extraction from extruded Leaching cell samples using ammonium acetate Batch tests  65 - 200 none  Hydraulic Adsorption gradient tests 20-200 none  2.4 HEAVY METAL COMPATIBILITY STUDIES  22  o  00  •43  o  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  23  POTENTIAL N E W MATERIALS FOR C L A Y BARRIERS  2.5  POTENTIAL N E W MATERIALS FOR CLAY BARRIERS  This section aims to provide background evidence that Forest soil and Spruce bark w o u l d improve heavy metal retention if added to clay barrier mixes.  2.5.1  S o i l Organic Matter  Soil organic matter represents all organic compounds i n 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  i.e. recognizable plant debris; plus polysaccharides, proteins, lignins, etc. in their natural or transformed states  Humic substances  fractionation on the basis of solubility  soluble in acid and alkali  FULVIC ACID  insoluble in acid and soluble in alkali  insoluble in acid and alkali  HUMIC ACID  HUMIN  t  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 C L A Y BARRIERS  24  The fact that the heavy metal retention of soils often correlates w i t h their organic contents has been presented i n section 2.3. The following are two heavy metal retention studies i n which humic substances were mixed w i t h soils and clay minerals. Hatton and Pickering (1980), mixed 3 m g of humic acid w i t h 7 - 1 5 m g 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 w o u l d 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 w i t h 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 m g L- ) that simulated 1  average stormwater. Natural organic matter was added to the leachate to produce about a 50 m g L  _ 1  total organic carbon (TOC). The natural organic matter was collected  by extracting standard garden peat w i t h sodium hydroxide (NaOH). Results showed that w i t h 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 i n the previous studies was extracted from soils using alkali solutions. The current study d i d 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 w o u l d 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 C L A Y BARRIERS  2.5.2  25  Spruce Bark  Bark is a common w o o d waste. Because it is produced i n 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 i n 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) Hatton & Pickering, 1980 Deshkar et al.," 1990 Al-Asheh & Duvnjak, 1997 Gloaguen & Morvan, 1997  Heavy Metals Retained Bark (Constituent) Pb, Cu, Cd, Zn Tannic acid (mixed with clay minerals) Formaldehyde-modified Hg Hardwickia Binata bark Pb, Cd, Cu, Ni Pine Bark Pb, Zn, Cr, Fe, Cu Formaldehyde-modified Picea abies, Pinus sulvestris, Pseudotsuga manziesii, Larix kaempferi, Tectona grandis, and Afzelia africna barks  The mentioned studies show that bark has the potential to retain heavy metals. Thus, Spruce (Picea) bark w o u l d be a logical choice for improving the sorption ability of clay barriers. This study evaluates the performance of Spruce bark by adding it i n shredded form, to a typical clay barrier mix.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  26  CHAPTER 3  MATERIALS A N D METHODS  3.1  C L A Y BARRIER MATERIALS  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 C L A Y BARRIER MATERIALS  3.1.2  27  Admixtures  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. Full descriptions are found i n APPENDIX 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 D42263 ( A S T M , 1995) ( A P P E N D I X A . l ) .  Specific gravity Specific gravities were measured for the admixes using the volumedisplacement method described i n A S T M D854-92 ( A S T M , 1995) ( A P P E N D I X A.2).  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  3.1 C L A Y 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 A r n o l d (1973). See A P P E N D I X A.3 for a description of the adapted method.  Atterberg limits L i q u i d 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 ( A S T M , 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 ( A S T M , 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. Full descriptions are found i n A P P E N D I X B.  Soil pH The p H s of the clay barrier materials were measured i n distilled water, and i n 0.01 M calcium chloride (CaCh) w i t h 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  29  3.1 C L A Y BARRIER MATERIALS  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 , & W E F , 1995). See A P P E N D I X T3.2 for a description of the adapted method.  3.2  CHEMICAL SOLUTIONS  A l l blank and heavy metal solutions contained a background of 0.01 M calcium nitrate (Ca(N03)2). nitrate (Pb(N03h),  The heavy metal solutions also contained combinations of lead copper nitrate (Cu(NC>3)2), and cadmium nitrate (Cd(N03)i).  solutions were prepared by dissolving solid crystals of Ca(NOs)2, and Cd(NOs)2,  Pb(N03)i,  All Cu(N03)i,  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 i n 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 - M o d e l 957.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  30  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  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 i n 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 i n Table 3.3.1, and the concentrations of solutions used for each test are shown i n Table 3.3.2. A diagram summarizing the Batch adsorption test is found i n Figure 3.3.1. A n equipment list is shown i n 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 i n a ternary heavy metal system. The ternary data for the bentonite and Spruce bark materials w o u l d 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. Pb  Bentonite Forest soil Spruce bark Bentonite admix Forest soil admix Spruce bark admix  Binary system  Single system  Materials tested  Cu  V V  Cd  V V V  Pb+Cu  Pb+Cd  Ternary system Pb+Cu+Cd  V V V V V  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  31  3.3 B A T C H A D S O R P T I O N TEST M E T H O D  TABLE 3.3.2. Heavy metal solution concentrations used in Batch adsorption tests.  Materials Bentonite Forest soil Spruce bark  Admixes Bentonite admix Forest soil admix Spruce bark admix  Single system Pb, Cu, Cd mgL-i 0 50 100 200 500 1000  500  Binary system Pb+Cu Pb+Cd mgL-i mgL-i 250+0 250+0 250+50 250+50 250+100 250+100 250+250 250+250 250+500 250+500 250+1000 250+1000 1000+0 1000+0 1000+50 1000+50 1000+100 1000+100 1000+250 1000+250 1000+500 1000+500 1000+1000 1000+1000  500+ 500  Ternary system Pb+Cu+Cd mgL-i 203+203+203 797+203+203 203+797+203 797+797+203 203+203+797 797+203+797 203+797+797 797+797+797 0+500+500 1000+500+500 500+0+500 500+1000+500 500+500+0 500+500+1000 500+500+500 203+500+203 203+203+500 500+500+500  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  32  3.3 B A T C H ADSORPTION TEST M E T H O D  2 types of Batch tests (all done in duplicate)  Batch test on admixes  Batch test on admix materials  - 40 ml ofheav metal solutions: Pb, Cu, Cd. - 4.0 g of admixes: 1. Bentonite admix 2. Forest soil admix 3. Spruce bark admix  - 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 A D S O R P T I O N TEST M E T H O D  3.3.2  33  Batch adsorption test procedure 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 i n 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 m l , 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 m l of heavy metal solution were placed into a 50 m l polypropylene centrifuge test tube. For the individual clay barrier materials, 0.5 g (dry weight) of material and 25 m l of heavy metal solution (bentonite, Forest soil, or Spruce bark) were placed into a 50 m l 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 M o d e l 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 i n a Beckman GS-6 centrifuge, the final heavy metal concentration of the supernatant was determined using a Video 22 Thermo Jarrell A s h aa/ ae Spectrophotometer - M o d e l 957 (AAS). In addition, the equilibrium p H of the supernatant was measured using an O r i o n 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  0-500  0-100  0-30  Range (mg L ) 1  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 mob , 63.55 g mob , and 112.4 g mob , 1  1  1  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- ), Ci is the initial concentration 1  of solution (cmol L" ), C/is the equilibrium (final) concentration (cmol L- ), V is the 1  1  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- ) vs. the initial heavy metal 1  solution concentration (mmol L" ). Equilibrium p H graphs were constructed by 1  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  36  3.4 L E A C H I N G CELL TEST M E T H O D  3.4  LEACHING CELL TEST METHOD  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. Binary  Single  Admix  Cu  Pb 500 mg L Bentonite admix Forest soil admix Spruce bark admix  1  500 mg L  V V  V  Pb+Cu 1  Ternary  Pb+Cu+Cd  500 mg L" each  500 mg L each  V  V  1  1  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  37  3 . 4 L E A C H I N G CELL TEST M E T H O D  Reservoir  Leaching cell 101 mm dia. x 56.5 mm  Discharge collector  Pressure gauge  t 500 ppm Pb, Cu, Cd  Solutions 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 L E A C H I N G CELL TEST M E T H O D  38  3.4.2 Admix preparation for the Leaching cell test  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 m l 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 l o w hydraulic conductivities for the admix. The admix was left undisturbed i n 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 i n 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 L E A C H I N G 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. A d d i n g Forest soil to a dry sand/bentonite mixture w o u l d 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 i n 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 i n A P P E N D I X C.2. The compaction procedure was modified from the modified Proctor procedure used i n A S T M D1557-91 ( A S T M , 1995). Weber (1991), and Cabral (1992) used static compaction because it was able to produce more consistent results; however, dynamic compaction, used i n 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 L E A C H I N G CELL TEST M E T H O D  3.4.4  40  Leaching cell test procedure  Figure 3.4.1 shows an illustration of the Leaching cell test setup. Prior to starting the Leaching cell test, the reservoir was filled w i t h 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, i n which the edge port was above the center port. W i t h 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. A s the solution began to flow out, the edge port was sealed w i t h a cap. This procedure removed most of the air bubbles from the influent end. To begin the Leaching cell test, the pressure i n 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, i n order to speed up some tests, pressures up to 7 psi gauge were used. These pressures translated to hydraulic gradients between 65 - 88. A s 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 i n 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  41  3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D  3.5  SELECTIVE SEQUENTIAL EXTRACTION M E T H O D  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 i n A P P E N D I X C l .  TABLE 3.5.1. The SSE program. Admix  Bentonite  Forest soil Spruce bark  Heavy metal solution* Pb Cu Pb+Cu Pb+Cu+Cd Pb Cu Pb+Cu Pb Cu Pb+Cu  Leaching cell samples (4 layers for each cell) Composite sampling Center & edge sampling  V  Batch test samples  V V V V  V V  * All heavy metal solutions contained 500 mg L of each heavy metal specified.  V V V  1  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  42  Sampling extruded Leaching cell samples  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 i n air-tight, 50 m l 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  43  3.5 SELECTIVE SEQUENTIAL EXTRACTION M E T H O D  Leaching Cell  Sample Extruded Sliced into 4 Layers  Plan View  *_  SSE performed on samples to determine amount of heavy metals retained by... 1. 2. 3. 4. 5.  Cation exchange Carbonate portion Fe/Mn hydroxide portion Organic portion 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  44  S S E procedure  The SSE was modified from the method used by Y o n g 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 i n air-tight, 50 m l 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 i n the pore water, 8 m l 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 i n the sample may re-dissolve. After mixing the sample i n 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 w i t h 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 i n section 4.2.2), this rinse procedure w o u l d sufficiently trivialize the error associated w i t h 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 i n 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 w i t h 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 i n 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 (NH OH-HCl) 2  i n 25%  ( v / v ) HO Ac was added to the sample. The entire mixture was then transferred to a pre-weighed 125 m l glass flask, so that it could be placed i n 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 i n 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 (HN0 ), and 5 m l of 30% hydrogen 3  peroxide (H2O2) was added to the sample. The 30% H2O2 was adjusted to p H 2 w i t h HNO3 before it was added. The mixture was transferred to the 125 m l 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 m l 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 m l of 3.2 M NH OAc 4  i n 20% ( v / v ) HNOs was added to  the sample, and the mixture was poured back into the centrifuge tube. Approximately 10 m l 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 m l 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 , AW W A , & W E F ,  1995), because the Environmental laboratory i n the Department of C i v i l Engineering at U B C was not equipped to handle hydrofluoric acid  (HF)  (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 m l of concentrated  HNO3,  were added to the flasks. The  mixture was brought to a slow boil by heating the flask w i t h a hot plate. After the mixture boiled d o w n to about 20 ml, an addition 5 m l of concentrated  HNO3  was  added. Reflux caps were placed onto the flasks, and the mixture was boiled for approximately two more hours. Next, w i t h the aid of distilled water, the mixture was transferred back to the centrifuge tubes, and diluted to the 40 m l 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 m l . Heavy metal sorptions associated w i t h the residual were l o w enough to allow for this simplification.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  48  CHAPTER 4  RESULTS A N D DISCUSSION  4.1  SOIL M A T E R I A L S  The physico-chemical properties are presented i n Table 4.1.1. The particle size distribution curves for bentonite, Forest soil, and Spruce bark are shown i n Figure 4.1.1.  T A B L E 4.1.1. Physico-chemical properties of soil materials. Physico-Chemical Properties Specific gravity  Forest Spruce Nabark Bentonite soil 2.64* n/a n/a  Silica Sand n/a  Admix 1 Admix 2 Admix 3 2.67  2.65  2.65  Specific surface (mVR) Liquid limit  462  n/a  n/a  n/a  n/a  n/a  n/a  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 %  n/a  n/a  n/a  n/a  0.0 n/a 59.7 n/a CEC (meq/100 g) 4.34 7.02 4.21 8.38 Initial pH (in distilled water) 6.45 3.5 4.01 7.61 Initial pH (in CaCb) n/a n/a n/a n/a Max. dry density (kg/m3) n/a n/a n/a n/a Optimum water content * 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  n/a  n/a  n/a  n/a  n/a  n/a  n/a  n/a  n/a  1860  1825  1820  12.7 %  12.7 %  12.3 %  212 % 6.4 %  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  49  4.1 SOIL MATERIALS  Grain Size Distribution 100% 90%  •o  80% 70%  o> 60% 50%  t  40%  0) 0>  30%  0.  20% 10% 0% 10  0.1  0.01  0.001  0.0001  Diameter (mm) - • — Sand a Bentonite (sieve) o Bentonite (hydrometer)  • A- - F o r e s t S o i l (Air-dried) - x — S p r u c e 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 C L A Y BARRIER MATERIALS ...  4.2  50  SORPTION CAPACITIES OF CLAY BARRIER MATERIALS DETERMINED 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 Bentonite Forest soil Spruce bark  Single Pb, Cu, Cd  V  Binary Pb+Cd Pb+Cu  V V V  Ternary Pb+Cu+Cd  V V  Details of the Batch adsorption test results are shown i n A P P E N D I X D.3. The results i n 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 i n this study was able to quantitatively describe competition for multiheavy-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 C L A Y 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) m  ( 4 1 )  where q is the amount sorbed on the sorbant, i n cmol kg- , C/ and G are the final and 1  initial solution concentrations, i n mmol l i t e r , V is the solution volume, i n liters, and m 1  is the mass of sorbant, i n 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 i n that the C, was used i n place of C/. The modified Freundlich equation is as follows,  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  52  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS .  (4.2)  q = bC?  where q is the amount sorbed on the sorbant, i n cmol k g , Q is the initial solution -1  concentration, i n mmol liter- , and b and n are curve fitting constants. According to 1  Eqn. 4.1, the use of C, or C / for curve fitting is equally valid; however, as shown i n Figure 4.2.1, the use of C, widens the distribution of data, especially at l o w 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  b) Isotherm in terms of initial Pb  concentration.  concentration. 20 —  18  2ra  & n  E  E  oi "5  o  JC  JC  o  E  E  .Q  n  a. •a  Q. "O 01  a>  .Q k_  t_ o  o  tn  w  1  2  3  4  1  5  Final [Pb] (mmol/L)  Bentonite  2  3  4  5  Initial [Pb] (mmol/L)  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 C L A Y BARRIER MATERIALS ...  T A B L E 4.2.2.  53  Summary of b and n values fitted for single & binary Cu data.  Cu  Cu w/ 1.15 mmol/L Pb Cu w/ 4.75 mmol/L Pb  b  n  b  n  3.9706 2.9467 2.4233  0.5028 0.4889 0.5058  8.4984 5.4463 4.3969  0.4876 0.5627 0.5578  a) Bentonite  0  b) Forest soil  10  20  initial [Cu] (mmol/L)  • Cuonly  F I G U R E 4.2.2.  Spruce bark  Forest soil  Bentonite  Solution type  0  b  n  4.4391 3.3798 2.3186  0.4465 0.4197 0.4242  c) Spruce bark  10  20  0  Initial [Cu] (mmol/L)  A C u w / 1 . 1 5 mmol/L Pb  10  20  Initial [Cu] (mmol/L)  o Cu w/4.75 mmol/L Pb  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 w i t h 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  54  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ..  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 i n the last section indicated that the presence of Pb caused a percentage change i n Cu sorption, independent of the initial Cu concentration. For example, the bentonite results i n Table 4.2.2 shows that the addition of 4.75 m m o l L  _ 1  of Pb into a Cu-only solution caused a 39% decrease i n Cu sorption. The  39% decrease was irrespective of whether the initial Cu concentration was 1 m m o l L"  1  or 10 m m o l Lr (Figure 4.2.2). This is represented mathematically by the following 1  equation:  %Aq  -f(C )  M]  (4.3)  M2  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, i n m m o l liter , and/(CM2) is the competition function w h i c h describes the behaviour of %ACJMI i n -1  terms of CMI. To determine the competition function, the single and binary sorption data was first converted to %AqMi by the following equation,  %Aq  m  =  q  M  ^ ~  q  M \ b  x  1 0 0  o  (44)  / o  M\s  a  where, qMis and qmb are the amount of Ml sorbed i n single and binary heavy metal solutions, respectively, i n cmol kg- . Then, these were used to construct plots of %AqMi 1  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.2 SORPTION CAPACITIES OF C L A Y 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(C )  = aC P  M2  (4.5)  M2  where a and p are constants used to describe the unitless competition function. Combining Eqns. 4.3 and 4.4 results in,  M\b=QM\s^-f{ Ml))  a  ( -6)  C  4  Substituting Eqn. 4.2 and Eqn. 4.5 into Eqn. 4.6 results in,  lMib=bC (\-aC ) n  m  (4.7)  p  M2  where, CMI is the initial Ml concentration, in mmol liter , and b and n are the 1  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  56  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ..  T A B L E 4.2.3. Summary of sorption equations for binary heavy metal solutions. Binary System  Sorbed Metal Pb Na-Bentonite in Cu Pb + Cu solution Pb Na-Bentonite in Cd Pb + Cd solution Pb Forest soil in Pb + Cu Cu solution Pb Forest soil in Pb + Cd Cd solution Pb Spruce bark in Pb Cu + Cu solution Pb Spruce bark in Pb Cd + Cd solution  Equation (<JM in units of cmol kg- , and C M in units of mmol L ) 1  1  qn = 4.546 C ( 1 - 0.0642 C „ °- ) q = 3.971 Ccu (1 - 0.234 Cn °- ) q = 4.546 C ( 1 - 0.0167 Ca ) qcd = 2.120 Ccd (1 - 0.300 C °- ) q = 4.829 Cp ( 1 - 0.0429 Co, ) qcu = 8.498 C c ( 1 - 0.248 C ) q = 4.829 Cp ( 1 - 0.0167 Cat ) qcd = 3.238 Cat (1 - 0.289 Cn °- ) qn = 4.971 Cn (1 - 0.0896 C °- ) qa. = 4.439 C „ (1 - 0.216 Cn °- ) qn = 4.971 Cn ( 1 - 0.0122 Cat) qcd = 1.970 C a (1 - 0.340 Cn ) 0747  Pb  574  c  0 3 0 3  292  Cu  0747  Pb  Pb  0 7 6 0  326  Pb  0873  Pb  a772  b  0488  0305  Pb  0873  Pb  a693  b  0 7 1 6  504  0680  688  Cu  0447  491  c  0716  0 7 0 6  a564  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  57  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ...  CQ D u o E E,  CM CO  u  o  O • IH  o o !  MH  «  Dai  &  o I/I  BH  U  H-l  u  at  3^  CT  ((< %)  <S 3  uoijdjos qd "! eBueqo  o E  for  e  TO  o  o c  IO  •<*  u  3  Sol  c  'o ~  D_  ro  100%  CH  c  c-O  _i E to T—  a* oi  V  5 CH W J  i  5£ «° «> 2 H  O PH  O to ra  (%) uojtdjos qd u| 86ueno  (%) uoudjos qd uj aBueqo  <*H  a 0)  Da)  «s  _i  mmol;  O  Co  to  entral  it) c o  imo  GH  o o  H-l  «  a  *j  o  C  for Benl  o o E E.  *5 o  Dai  «  s : ca ^ CN  U -e o o (%) uojidjog qd Uj sBueqo  £ CO  O O O O O O O O O CDCOr^CDWTCOCslT-  (%) uoudjos qd "! sBueqo  D  O — i t UH  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  58  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS .  CN  3  v m o> x ffi*C m \\ CD  \ \L  •<CNl O  >. 1  I  u  o  '•5  \4m a  c  o> CO CO  o  d  o  E E  c  ,—,  o  • iH  \ o  MH  ro w  c  _i  TS  08  o CO  a U  E E  Q  U  ob  •  (%) uojidjos PO u.i aBueno  _j  o  E E (0 c m  o  1/5  1^ o  (fl 0)  o E E  o E E, S" ft  »H  u o  rs rs  To  'E  Q E E  i*^  •s ft.  c g  ZJ  E  CM  T3  _l  o  <  _J  o  o o  oo d  •  e  o  c  0) P9 Ul  O f« 4H  Q  <*) a U 'rT  • CD CN CO  H d  II  >. 1  •sr d  o m  •  i>-'  ia  ut  rs  MH  0»  o  a  w> n  T  OJ  w-  OJ  $  o  O C/5 00  aj  s to o H1/1 H  ^  73  .  .3 «  rt '—' T3 .  - «  ° 2 "H  S  &, * ;  0-  'I  \  1 —  '-5  ui C o OJ <» PQ  c • pa S fN W  TS  D  u  (%) uoijdjos no u| s6uego  E E  o o  E E  01  MH  -B ^  CO  d (%) uoijdjos PO u| a6uei)o  <» j-> u  CM CM  CD CO  U  U  _l  o  O  TS  (%) uojjdjos no UJ aBueqo  •«*  nitia mm  o  o  c  UH  Q-  I—  CO  j->  o  "B  o  M-  Conce moi  i^ 00  tn  "5  (%) uoijdjos no ui aBuego  E E  u o  rs rs  TS  o  ^—s  X CO  a,  .s  \  II  d  2  o E E,  (%) uojtdjos PO ! aBueuo u  (J PH  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  59  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ...  cn  e o  o CM UI  cu  yst  . LO  Co  s  u +  cn  »"*H  fin  01 M  »  +  B- I  (6>|/|0UJD)  qd peqjos o\eo  "55  O  II  . o \  ^ CC n  - to  c c  o> o  o • IH  CO  en  I'o  OH  res  s o  SB o \\ CO  r  -  irbed Pb (cm  (6>|/|oiuo) PO poqjos 3|B0  o co  (6>(/|Oiuo) PO peqjos 0|eo  (6>|/|omo) PO poqjos "0|Bo  3  CM  LO O CO  T -  T -  - o c3  o  a  •g  2  <  (6>i/|oiuo) qd peqjos OIBQ  (6>|/|0iuo)  qd peqjos OIBQ  g OH « CD  u o E o  CO  a U + n  o a o  •43 & O  CO S  U  fin +  '3 o s  01  pa  io A . T— \  o+  sk»  OTT^  ^°  CO CD  T.  II  <M O) QI  o  1  co  CO  cu IH  > PHO  o  fS  CO  li  o co  •o o .O  1  cl  7  HH  H5 • w cu rt '—'  >. i  CO CO  (6>(/|OUJ0)  (6>|/|OUJO)  (6>|/|OUJO)  no peqjos 0 | B O  no peqjos "0|eo  no peqjos "0|eo  -  3 cu cn Bf  a  u + C  O •43  OH K O  cn (6>(/|OUIO)  qd peqjos "0|eo  (6)(/|oiuo) qd peqjos '0|eo  •OH  o E o o.  C\j\ CO,  d X  CO  + PQ  II  0.  s\ o  cn  CJ  cj  "O V  LO  o € o  CO  est  2  OH  II  13 «  r>p  cu u  .tn  (6>|/|oiuo) qd paqjos "0|eo  U PH  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  60  4.2 SORPTION CAPACITIES OF CLAY BARRIER MATERIALS .  4.2.1.3  Modeling ternary heavy metal sorption  In section 4.2.1.2, a model containing a competition function was developed for binary heavy metal sorption. The important next step w o u l d 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 i n ternary systems,  %Aq  m  x 100%  = f(C ,C ) M2  M3  (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 t e r , and /(CM2) is a function of CM 1  2  which describes the behaviour of %AqMi in terms of the initial solution concentrations of Ml and M 3 . 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,  =  >< 100% = f(C )  f*\~" q (M\,M2)  qmb(m  MU  M3  x 100%  (4.9)  mb  where, qMib(Ml,Ml)  is the amount Ml sorbed in binary heavy metal solutions  containing Ml and Ml, i n cmol kg- , qMit is the amount Ml sorbed i n ternary heavy 1  metal solutions, in cmol kg- , and f(CMS) is a competition term that reflects the influence 1  of CMS on Ml sorption. After substitution with Eqn. 4.6, and isolating qMu, Eqn. 4.9 becomes,  9mt  =°M\s*[iy-f( Mi)-f(C )(\-f(C ))] C  M2  M  (4.10)  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  61  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ..  Table 4.2.3, i n section 4.2.1.2, contains the competition functions necessary for calculating Pb sorption i n ternary systems. Comparisons of the calculated Pb sorption data versus experimental data for bentonite and Spruce bark are shown i n Figure 4.2.6. The plots i n 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 i n conjunction w i t h the available binary data could be used to find the missing competition functions by following Eqn. 4.9. Shown i n Figure 4.2.7, are the competition functions solved from the ternary data for Bentonite and Spruce bark. W i t h the competition functions from Figure 4.2.7, another comparison of calculated versus experimental values for Cu and Cd sorption is shown i n Figure 4.2.8. Table 4.2.4 shows the complete set of equations for heavy metal sorption i n ternary solutions.  T A B L E 4.2.4. Summary of sorption equations for ternary heavy metal solutions. Material Bentonite  Forest soil Spruce bark  Sorbed Metal Pb Cu Cd Pb Cu Cd Pb Cu Cd  Equation (<JM in units of cmol kg- , and CM in units of mmol L" ) 1  1  qn = 4.546 C ((1 - 0.0167 C « ) - (0.0642 Co, (1 - 0.0167 Co,))) q = 3.971 C c °- ((1 - 0.234 Cn ) - (0.0106Cc (1 - 0.234 C °- ))) qcd = 2.120 Ccd ( ( l - 0.300 Cn ) - ( 0 . 0 8 0 4 C „ ( 1 - 0.300 C °- ))) q = 4.829 C ((1 - 0.0167 Ccd ) - (0.0429 C c (1 - 0.0167 C ))) (insufficient data) (insufficient data) 0 7 4 7  0 5 7 4  Pb  503  02 9 2  292  Cu  Pb  a 7 6 0  0326  0646  326  C  0873  Ph  0693  cd  a 6 8 0  b  ( ( l - 0.0122 C ) - (0.0896 C c (1 - 0.0122 Ccd))) ((1 - 0.216 C ) - (0.0106C (1 - 0.216 C ))) ((1 - 0.340 C °- ) - (0.0804C , (1 - 0.340 Cn ))) 0 6 8 8  c d  0 4 4 7  Cu  0 7 7 2  Pb  q = 4.971 Cp q = 4.439 C c qcd = 1.970 Ccd Ph  Pb  0 6 9 3  om  0491  Pb  0706  cd  Pb  564  Pb  0646  0564  Q  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  62  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS .  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 60%  20% O ^ 10% a> o C  Q.  -20%  " S 40%  2  0%  JS o -10%  •a ~ 50%  •  y=0.0106x * Fc = 02433__A__. (I  <>2  4*  I  I  6  8  - — —  ^ 1 P  'i c £ o  o 30% ' | 20% C°O10% 0% 1  0  /  0  5  c) Effect of Cd on Cu Sorption for Spruce B.  10  15  Initial [Cu] (mmol/L)  Initial [Cd] (mmol/L)  d) Effect of Cu on Cd Sorption for Spruce B. 160% -,  Initial [Cd] (mmol/L)  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  63  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS .  b) Cd sorption for Bentonite ternary system  a) Cu sorption for Bentonite ternary system  6  •D  o  y = 0.9511x R = 0.8672  |5 4 o oo WE o  5 10 Actual Sorbed Cu (cmol/kg)  2  •Billll...-.  o  CO  O  •  •  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(. M2))  (-)  C  4  6  Equation 4.10, which describes sorption in ternary heavy metal systems, is rewritten as,  Q-fm(C )-f M2  ( C , ) +f  m  M  m  (C  M 1  )f  m  (C  M  ))  (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 - , / ^ (CMI), a n d / M I (CMI), are unitless competition 1  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ...  64  functions for Ml and M3, o n Ml sorption, and CM2 and CM3 are initial solution concentrations for Ml and Ml, i n units of m m o l I A Table 4.2.5 summarizes Pb, Cu, and Cd sorption i n 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 Competition function (unitless) single metal solutions Cu Pb (in cmol kg ) -1  Bentonite  Forest soil Spruce bark  Pb Cu Cd Pb Cu Cd Pb Cu Cd  q = 4.546 C q = 3.971 Co, °qa = 2.120 Ca qPb = 4.829 Cp q = 8.498 C qcd = 3.238 Ca q = 4.971 Cpb °q = 4.439 Ca qa = 1-970 Ca  0 7 4 7  Pb  Pb  503  Cu  0 7 6 0  b  0 4 8 8  Cu  0 7 1 6  Pb  0  M  7  Cu  0 7 0 6  0 5 7 4  C u  0326  a646  0 7 7 2  0 6 9 3  C u  a  0305  504  b  680  Cd  0.0167 Ccrf ** 0.0642 C * n/a * 0.0106Ca * n/a * 0.0804Cc„ ** 0.0429 C * 0.0167 C * n/a * n/a * 0.0122 Co; * 0.0896 C * n/ a * 0.0106C rf ** n/a * 0.0804C „ * *  0 2 9 2  b  0 8 7 3  Cu  n/ a 0.234 Cpb 0.300 Cp n/a 0.248 Cpb 0.289 Cp °n/a 0.216 C °0.340 Cpf,  0 6 8 8  C u  491  Pb  C  0564  0 646  C  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 liter . 1  4.2.2  H e a v y metal sorption capacities  The heavy metal sorption capacities of the clay barrier materials are s h o w n i n 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 i n Figure 4.2.9 are found i n Table 4.2.5. Summarized i n 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  65  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ..  a) Pb solutions  0  2  4  b) Cu solutions  6  8  10  "  0  2  Initial [Pb] (m m ol/L)  4  c) Cd solutions  6  8  10  o Bentonite  d) Bentonite  A Forest Soil  10  0  Initial [Metal] (mmol/L)  2  4  6  8  10  o Spruce Bark  f) Spruce bark  2  4  6  8  10  Initial [Metal] (mmol/L)  • Pb  0  Initial [Cd] (m m ol/L)  e) Forest soil  0 2 4 6 8  "  Initial [Cu] (m m ol/L)  x  Cu  0  2  4  6  8  10  Initial [Metal] (mmol/L)  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 Cu sorption capacity Cd sorption capacity Sorption onto Bentonite Sorption onto Forest soil Sorption onto Spruce bark  Forest soil > Bentonite « Spruce bark Forest soil > Bentonite » Spruce bark Forest soil > Bentonite > Spruce bark Pb>Cu> Cd Cu>Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) Pb>Cu> Cd  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS .  4.2.2.1  66  Ranking of materials  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 g- (Sparks, 1995). Although bentonite also possesses high C E C due to 2  1  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 p H s for bentonite ranged between 5 - 7.5, signifying the likely occurrence of precipitation. The main reason w h y bentonite sorbed less than Forest soil, is because bentonite's specific surface area (462 m g- ; from Table 4.1.1) is smaller than typical 2  1  specific surface areas of Forest soil (800-900 m g ; from Sparks, 1995). Even assuming 2  -1  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. A s for Spruce bark, its sorptive ability is attributed to the surface functional groups associated w i t h tannin compounds (Vazquez et al., 1994, Gloaguen & Morvan, 1997). The main sorptive functional groups i n tannins are carboxyl and phenolic. A s mentioned earlier, Forest soil also relies on surface functional groups; however, these functional groups are associated w i t h humic substances (Sparks, 1995). In addition to carboxlyl and phenolic, humic substances possess many other functional groups useful for heavy metal retention. A s 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 C L A Y BARRIER MATERIALS ...  67  indication, per unit weight, Forest soil contains more surface functional groups than Spruce bark.  c) Spruce bark  b) Forest soil  a) Bentonite  4.5  4.5  I  I Initial solution pH  Initial solution pH  3 2.5 0  2  4  6  8 10  Initial [Metal] (mg/L)  0  2  4  6  8 10  0  x Cu  4  6  8  10  Initial [Metal] (mg/L)  Initial [Metal] (mg/L) |Pb  2  o Cd  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 i n 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 l o w initial metal concentrations, while for Forest soil, the isotherms cross over at a high concentration (4 m m o l L ) . In addition, if the _1  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 C L A Y 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 Ionic radii 1st hydrolysis constant*** 2nd hydrolysis constant*** OH" solubility constant*** * Fyfe, 1964 ** McQuarrie & Rock, 1991 *** Lindsay, 1979  120 pm* 7.7 17.75 8.16  Cu 70 pm** 7.7 13.78 8.68  Cd 97 pm* 10.1 20.3 13.65  Ca 99 pm* 12.7 27.99 22.8  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 w o u l d 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 w o u l d 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 w o u l d be Cu>Pb>  Cd.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.2 SORPTION CAPACITIES OF C L A Y 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 w o u l d 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, w i t h the tested results, surface complexation must be considered dominant at l o w metal concentrations. A s the solution metal concentrations rise, and complexing sites start to fill 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 w o u l d 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 w o u l d 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 i n Figure 4.2.9.f, show that the Pb and Cu isotherms crossed at a very l o w initial concentration ( « 1 m m o l L" ). 1  W i t h i n this section, several reasonable, but speculative explanations were provided to harmonize the predictions i n Table 4.2.7 w i t h actual results i n Table 4.2.6. In section 4.4.3.1, more insights on retention mechanisms w i l l be presented. These insights w i 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 w o u l d be based on the amounts of each heavy metal sorbed. Using this approach, the heavy metal selectivities are shown i n Figure 4.2.11. The graphs i n Figure 4.2.11 were plotted using the equations i n section 4.2.1.4. The concern regarding selectivity graphs is that they are misleading i n 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 i n separate noncompetitive environments, Pb sorption is higher than Cd sorption. In order to identify competition, the selectivity isotherms w o u l d need to be compared to the individual sorption isotherms. If the selectivity graphs i n Figure 4.2.11 were proportional to the sorption capacity graphs i n Figure 4.2.9, then one could conclude that competition amongst the three heavy metals was equal. However, the graphs i n 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  71  4.2 SORPTION CAPACITIES OF C L A Y BARRIER MATERIALS ., b) Spruce bark (Ternary systerm).  a) Bentonite (Ternary system).  12 -,  12  0  1  2  3  4  5  0  Initial [of each metal] (mmol/L)  1  2  3  4  5  0  3  4  5  1  2  3  4  5  Initial [of each metal] (mmol/L)  Initial [of each metal] (mmol/L)  Pb  2  d) Forest soil (Pb+Cd binary system).  c) Forest soil (Pb +Cu binary system).  0  1  Initial [of each metal] (mmol/L)  — 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 i n identifying competition. Competition is shown more effectively by examining the competition functions associated w i t h each sorbent. The competition functions i n Table 4.2.5 were rearranged i n 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 C L A Y 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) less competitive  more competitive Bentonite  Forest soil Spruce bark  4.2.4  Pb sorption Cu sorption Cd sorption  0.0642 C o , 0.234 Cn 0.300 C  Pb sorption Cu sorption Cd sorption  0.0429 C 0.248 C 0.289 C °-  Pb sorption Cu sorption Cd sorption  0.0896 C 0.216 C 0.340 Cpb  0 5 7 4  0 2 9 2  0 3 2 6  Pb  0 7 7 2  Cu  > > > >  0.0167 Ca 0.0106Caf 0.0804Cc« 0.0167 Ca  0 6 4 6  0 6 9 3  0 3 0 5  Pb  504  Pb  0  688  Cu  0 4 9 1  Pb  ?  > 0.0122 Cat > 0.0106C rf > 0.0804Cc„ C  0564  a646  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 i n 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. A s for Spruce bark, its sorption capacity for Pb and Cu is almost identical to that of bentonite. A t higher Cd concentrations (> 4 m m o l / 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 i n 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 u p to the top ranking when Pb and Cu were present i n 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 i n 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 C L A Y 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 w o u l d resolubilize. O n the hand, complexation onto Forest soil and Spruce bark is still effective at l o w p H s (Figure 4.2.10). A potential disadvantage for Forest soil and Spruce bark is i n h o w they w o u l d effect the mobility of heavy metals that remain i n solution. Fractions of soil organic matter (Sparks, 1995) and tannins (Haygreen & Bowyer, 1996) dissolve i n 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 C L A Y BARRIER MATERIALS ...  74  2. The sorption capacity rankings of heavy metals and barrier materials are as follows:  Ranking Pb sorption capacity Cu sorption capacity Cd sorption capacity Sorption onto Bentonite Sorption onto Forest soil Sorption onto Spruce bark  Forest soil > Bentonite « Spruce bark Forest soil > Bentonite « Spruce bark Forest soil > Bentonite > Spruce bark Pb>Cu> Cd Cu> Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) 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 i n 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 w i t h Cd sorption i n competitive environments. The Cd sorption capacities of Forest soil and Spruce bark were l o w i n 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  75  4.3 T H E L E A C H I N G CELL TEST  4.3  T H E L E A C H I N G CELL TEST  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 w i t h single and binary solutions of Pb, and Cu. These results w o u l d 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 i n a ternary system. Each heavy metal contained i n the leachate solutions was present at concentrations of 500 m g L" . Converted to molar 1  values, the Pb concentration was 2.41 mmol L" ; the Cu concentration, 7.87 m m o l L ; 1  1  and the Cd concentration, 4.45 mmol L" . To maintain similar ionic strengths, all 1  leachate solutions including the blanks, also contained 0.01 M Ca(N03)i. The testing matrix is summarized i n Table 4.3.1, and detailed Leaching test results are shown i n 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. Leachate (500 mg L for each metal) 1  Admix  Pb  Cu  Bentonite (100:8 of Sand:Bentonite) Forest soil (100:7:1 of Sand:Bentonite:Forest soil) Spruce bark (100:7:1 of Sand:Bentonite:Spruce bark)  V V  Pb+Cu Pb+Cu+Cd  V V V  A l l the Leaching cell tests were done i n 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 i n A P P E N D I X E . l . A Leaching cell test was terminated when discharge heavy metal concentrations reached near equilibrium after breakthrough. A l l of the heavy metal breakthrough concentrations i n the current study  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 CELL TEST  76  attained this state before discharge volumes reached 1500 m l . 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 i n the Leaching cell. Movement of the admix sample within the Leaching cell w o u l d increase the possibility of side-wall leakage. A l l of the hydraulic conductivity data up to a discharge volume of 1500 m l (section 4.3.2) were shown i n Figures 4.3.1 - 4.3.4. The averaged hydraulic conductivity data is grouped according to admix type i n Figure 4.3.5, and grouped according to leachate type i n Figure 4.3.6 (section 4.3.1). Figures 4.3.8 - 4.3.10, present all the breakthrough data up to 1500 m l of discharge, and Figures 4.3.11 - 4.3.12, presents the averaged heavy metal breakthrough curves (section 4.3.2). Shown i n 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  77  4.3 T H E L E A C H I N G CELL TEST  T A B L E 4.3.2. Physical properties of Leaching cell samples. Permeant  Bentonite admix  Forest soil admix  Spruce bark admix  Triplicate Initial water content #  Blank Blank Blank Pb Pb Pb Cd Cd Cd Pb+Cu Pb+Cu Pb+Cu Pb+Cu+Cd Pb+Cu+Cd Pb+Cu+Cd Blank Blank Blank Pb Pb Pb Cu Cu Cu Pb+Cu Pb+Cu Pb+Cu Blank Blank Blank Pb Pb Pb Cu Cu Cu Pb+Cu Pb+Cu Pb+Cu  Initial dry density (kg/m3)  Initial saturation  Final saturation  1  14.5%  1800.1  80%  2 3  14.5% 14.5%  1800.1 1812.8  80% 82%  1  14.9%  1793.5  81%  2  14.9%  1826.9  86%  14.6%  1828.5  85%  14.9%  1797.9  82%  14.6% 14.6%  1804.1 1806.2  81% 81%  14.8%  1814.9  85%  15.3% 15.3%  1784.4  84%  1783.5  15.3%  1786.9  83% 84%  14.3% 14.3%  1799.3 1810.6  80% 82%  88% 96%  1  14.5%  1803.0  82%  88%  2  14.5%  1800.5  90%  3  14.5%  1789.1  81% 80%  1  14.0%  1779.8  76%  2  14.0%  1765.7  74%  15.0% 15.0%  1767.1 1777.3  80%  1  14.8%  1757.5  77%  2  14.8%  1789.2  82%  3  14.8%  1791.1  82%  1  15.5%  1750.7  80%  2 3  15.5%  1741.3  79%  15.5%  1745.7  79%  X  1 X X  1 X X  1 2  89%  X  1 X X  1 2 3 1 2 X  88%  X  1 2  81%  X  x - failed tests  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 CELL TEST  4.3.1  78  Hydraulic conductivity results  The main interests of this section are i n 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 i n 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 m l ( « 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 m l 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 l o w hydraulic conductivities for the duration of the tests. To facilitate the comparison of results, the triplicate hydraulic conductivity data seen i n Figures 4.3.2 - 4.3.5, were averaged and grouped together i n Figures 4.3.6 and 4.3.7. Specific hydraulic conductivity values were taken from these and summarized i n Table 4.3.3. Cabral's (1992) results did not show the same, large hydraulic conductivity increases as i n 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) w o u l d 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 T H E L E A C H I N G 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 (Tchobanoglous et al., 3  1993), plus 0.3 m of cover material with a unit weight of 20 k N m , w o u l d result i n a 3  confining pressure of 23.7 kPa. Although confining pressures were not used i n the current study, water boundary pressures of 36 - 48 kPa were generated because of the large hydraulic gradients (65 - 88). These pressures w o u l d be more representative of landfills i n their initial stages of operation. These conditions w o u l d 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  c ,—  1.00E-10  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 3  ro  1.00E-11 200  400  600  800  Discharge Volume (mL)  c) Spruce Bark admix samples permeated with 0.01 M Ca(N03)i 1.00E-09 i  Discharge Volume (mL)  Triplicate #  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 T H E L E A C H I N G 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 o  1.00E-11 600  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  82  4.3 THE LEACHING CELL TEST a) Pb permeants through Forest soil admix samples 1.00E-08  f o I _ o to  1.00E-09  .2 —  1.00E-10  3* X  1.00E-11  "  I  3 CO  200  400  600  800  1000  1200  1400  Discharge Volume (mL)  b) Cu permeants through Forest soil admix samples §  1.00E-08  u I o W .2  _ « E —  1.00E-09  -ft*— ;-| p ri  x  X A  •  X  —u  •  1.00E-10  3  c "• •  2 •a >>  200  400  600  800  1000  1200  1400  1200  1400  Discharge Volume (mL)  c) Pb + Cu permeants through Forest soil admix samples 2> >  1.00E-08  S3  o  1.00E-09 O  °  <A  E  .a — 1.00E-10 2  1.00E-11 200  400  600  800  1000  Discharge Volume (mL)  Triplicate #  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  83  4.3 T H E L E A C H I N G CELL TEST  a) Pb permeants through Spruce Bark admix samples 1.00E-08 1.00E-09 o w O 1 .2 — 3  X  X  1.00E-10  <<J  •D >. I  200  400  600  800  1000  1200  1400  1200  1400  1200  1400  Discharge Volume (mL)  b) CM permeants through Spruce bark admix samples 1.00E-08 3  1.00E-09  o » .2  w  x  1.00E-10 1.00E-11 200  400  600  800  1000  Discharge Volume (mL)  c) Pb + Cu permeants through Spruce bark admix samples  U E  .y — 1.00E-10 x  200  400  600  800  1000  Discharge Volume (mL)  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  84  4.3 T H E L E A C H I N G CELL TEST a) Bentonite admix -100:8 of sand:bentonite 1.00E-08 >  *  | 1.00E-09 c .— o «> o  3  2  I  _  :T-—-  *  *  —  .  —  - --  —  - —  » ^ ^9 i i  1.00E-10  •D  1.00E-11 0  150  300  450 600 750 Discharge Volume (mL)  900  1050  1200  1050  1200  1050  1200  b) Forest soil admix -100:7:1 of sand:bentonite:Forest soil 1.00E-08  0  150  300  450 600 750 Discharge Volume (mL)  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)  •Pb Leachate • Pb & Cu Leachate  900  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  85  4.3 T H E L E A C H I N G CELL TEST a) Pb Leachate 1.00E-08 -r-  T3 >> X  1.00E-11 1 0  1 150  1 300  ,  1  1 150  1 300  1 150  1 300  1 1 1 450 600 750 Discharge Volume (mL)  1 900  1 1050  1 1200  1  1  1  1  1 • 1 1 450 600 750 Discharge Volume (mL)  1 900  1 1050  1200  1 1 1 450 600 750 Discharge Volume (mL)  1 900  1 1050  1 1200  b) Cu Leachate 1.00E-08 T  =5  1  1  1.00E-10  >< X  1.00E-11 -I 0  c) Pb+Cu Leachate 1.00E-08  5  S  1.00E-10  •o  1.00E-11 -I 0  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  86  4.3 T H E L E A C H I N G C E L L T E S T  T A B L E 4.3.3. S u m m a r y of hydraulic conductivity results f r o m averaged data i n Figures 4.3.5 & 4.3.6.  Admix  Leachate  Initial hydraulic conductivity  m s 2.4E-11 (test stop]Ded before 1200 7.2E-11 5.0E-11 3.5E-10 3.1E-10 ped before 1200 2.8E-11 (test stop] 3.0E-09 8.0E-10 4.9E-10 ped before 1200 1.4E-11 (test stop] 8.9E-11 8.4E-11 1.6E-10 1  Bentonite admix  Blank  Forest soil admix  Blank  Pb Cu Pb+Cu Pb+Cu+Cd Pb Cu Pb+Cu  Spruce bark Blank Pb admix Cu Pb+Cu  4.3.1.2  HydrauUc conductivity at 1200 ml of discharge m s ml of discharge) 4.7E-09 4.8E-09 4.3E-09 2.4E-09 ml of discharge) 5.0E-09 1.8E-09 3.3E-09 ml of discharge) 6.4E-10 2.7E-09 3.4E-09 1  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 i n 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. D u r i n g this stage of initial permeation, the heavy metal solution was causing the bentonite particles to flocculate; however, the hydraulic conductivity remained l o w because of the resistance provided by the uncontaminated region i n front of the heavy metal flow (Figure 4.3.7.a).  H e a v y M e t a l Sorption a n d H y d r a u l i c Conductivity Studies using Three Types of Bentonite A d m i x e s  87  4.3 T H E L E A C H I N G CELL TEST  After the initial portion, a period of rapid hydraulic conductivity increase occurred. This rapid increase was probably initiated upon the full 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 i n 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 equilibrium value (Figure 4.3.7.c). According to the proposed mechanism, hydraulic conductivity increase coincides w i t h heavy metal breakthrough. Later, the presentation of heavy metal breakthrough results i n Figures 4.3.8 - 4.3.10, (in section 4.3.3) w i 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 i n this study were performed w i t h 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 i n 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 (Ca ) and heavy metal (Pb , Cu , Cd ) leachates all contain +2 cations, and 2+  2+  2+  2+  possess similar ionic strengths, no differences i n hydraulic conductivities should have been observed. However, the results i n 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  88  4.3 T H E L E A C H I N G CELL TEST  a) Initial permeation of heavy metals through Leaching cell  t tt tt11 tttttt Initial inflow and discharge  tttttttttt ttt  Heavy metal pathways (Flocculation occuring along pathways)  b) Initial penetration of heavy metals  t tttt ttt tttt t  Penetrated H. M. pathways Flow increases & concentrates towards penetrated H. M. pathways  t t tt tt c) Long-term flow pattern  mw 11 tttt  H. M. pathways become preferential channels Bulk of flow is along preferential channels  ritnt  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  89  4.3 T H E L E A C H I N G CELL TEST  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 i n identifying the effect of cations. Shown i n 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 w o u l d lead to stronger conclusions relating sorption characteristics and hydraulic conductivity. Furthermore, if flocculation is assumed to be the main mechanism that influences change i n hydraulic conductivity, then one w o u l d need to investigate the relationship between sorption and flocculation, i n 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 Cation exchange Complexation  Associated Reaction parameter * Ionic radii 1st hydrolysis constant 2nd hydrolysis constant OHsolubility constant Precipitation * See Table 4.2.7 for parameter values.  4.3.1.4  Order from greatest to least potential Pb>Ca>Cd> Cu Cu>Pb>Cd>Ca Pb>Cu>Cd>  Ca  Importance of initial saturation  Barriers w i t h 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 i n the current study usually d i d 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 T H E L E A C H I N G 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 w i t h expectations. Each had one sample that d i d not show significant increases until after 7 and 5 pore volumes, respectively. Also, many of their samples d i d not show any increases for the duration of their tests. The reason w h y 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 w o u l d increase the heterogeneity of the soil/pore media; thus, increasing the likelihood of preferential channeling. Also, in comparison to water-filled voids, air voids w o u l d 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 i n 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 i n 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 i n Table 4.3.3 d i d 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 T H E L E A C H I N G 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 - 5.0 x IO" m s , indicated that the admixes were -9  9  4  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 m i n i m u m 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 i n the discharge, increases i n hydraulic conductivity due to particle migration, were unlikely. 2. Bacterial growth was observed i n the discharge tubes leading from the Forest soil and Spruce bark admix barriers. Bacterial growth w o u l d 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  92  4.3 T H E L E A C H I N G CELL TEST  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 i n 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 w i t h an initial period of low heavy metal concentration, followed by a logshaped increase. To facilitate the comparison of results, the triplicate breakthrough data was averaged together i n Figures 4.3.11 - 4.3.12. Specific breakthrough concentrations taken from Figure 4.3.11 - 4.3.12 are summarized i n Table 4.3.4. O n average, the initial period concentrations ranged between 0 - 227 m g l / , and lasted 1  between 50 - 350 m l of discharge (0 - 2.5 pore volumes). A t a discharge volume of 1200 m l (7 pore volumes), breakthrough concentrations ranged between 269 - 506 m g L r (54 1  -100+ % of source concentration). The comparison point was chosen at a discharge volume of 1200 m l , because by this point, all breakthrough concentrations had reached near equilibrium.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  93  4.3 T H E L E A C H I N G CELL TEST a) Pb permeants through bentonite admix samples. £  §>  g | f J  s I  s  500 400 300  "A  200 100 o  —  A  —  A  w  l tl I M  : —  # A  x x x -  N7  nrd^— —  •  n  200  600  400  800  1200  1000  1400  Discharge Volume (mL)  b) C M permeants through bentonite admix samples. 500  i> 400 8 5" 300 | I 200  £  X  X  X  X  y v * - ^ X  X X  A  X  xx  v  V  <  X  *  0 *•  03  400  200  600  800  1200  1000  1400  Discharge Volume (mL)  d) Pb+Cu permeant -Cu data.  c) Pb+Cu permeant-Pb data. 500 400 3 _O _ 300 | | 200 | ~ 100 m n at  ,NV  X  v * X  5  , x *  <  V X  V  at 3  Sd  A  500 400 300  >r^-x- i  I f 200  S ~ 100  x*  m  0 400 800 1200 Discharge Volume (mL)  400 800 1200 Discharge Volume (mL)  f) Pb+Cu+Cd permeants-CM data  | f S~  ffi  <-a  n5« VP— 0  400  £ O) 3  CO  £  -J  Bui)  S?  500 400 300 200 100 0  kthro  e) Pb+Cu+Cd permeants - Pb data ^ §>  zxrxiK  xx  500 -r 400 300 vESS* 200 - — X > Q # 100  CD 800  1200  Discharge Volume (mL)  o  i  p>px^<^  400  800  1200  Discharge Volume (mL)  g) Pb+Cu+Cd permeants-Cd data  §>  2d  | f £ ~ ED  500 400 300 200 100 -Br n  rM~i's>rvf3  :•  MP— #  0  Triplicate # x Test 1  400  800  • Test 2  A  Test 3  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. Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  94  4.3 THE LEACHING CELL TEST  a) Pb permeants through Forest soil admix samples. 500 400 S d 300 £ |> 200 g - 100 m 0 £  ?  x  x ~*£-R-*-Q&-C  B  -U  u  V  1 ^-—A-SA—  A  •Ma.*-* fl  in  n U  r  L.  I ] M  fc  1  A  200  , 4s  ZS  400  600  800  1200  1000  1400  Discharge Volume (mL)  b) Cu permeants through Forest soil admix samples.  £ 5"  f  |  <0  "  m  500 400 300 200 100  f=i  H  X  v  A  X  trv — yc  x  B r  *~  #  n  n  X  X  u  '-gtj -ft  200  400  600  800  1200  1000  1400  Discharge Volume (mL)  c) Pb + Cu permeants - Pb data. o)  S  1200  500 3 D u -11r r — ^ ' — X 400 B ( X X, - X x— 2 d 300 rP X | f 200 X r ^ X * P 100 g$»x— ' BSD— . . 0Q 0 ™—4»£ 400 800 1200  Discharge Volume (mL)  Discharge Volume (mL)  500 400  o>  5" 300  S E 200 co — P 100 m 0  d) Pb + Cu permeants - Cu data.  n 400  X  V A  Nr'  X  •  Q  v  n  n  n  800  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  95  4.3 T H E L E A C H I N G CELL TEST  a) Pb permeants through Spruce Bark admix samples. g> 2 d 1 f  S  ~  m  500 400 300 200 100 0 i—ttaxx" 0  >  X  V V  jk 200  400  600  800  1200  1000  1400  Discharge Volume (mL)  b) Cu permeants through Spruce bark admix samples. «3>  O '  £ E9 | ffi  500 400 300 2  0  A  X  •  1  v  A  V  *  X  —x=  x  X  x  x-1  0  A L 100 0 WmMMSJfi 200  400  600  800  1200  1000  1400  Discharge Volume (mL)  d) Pb + Cu permeants - Cu data.  c) Pb + Cu permeants - Pb data. 500 400  re 2 m  d  300  E  200  w  X —  tr  n  -X  •  AX  —  >  Ck  X  500 400  - - E - A - a - o  M>b<=x-X  1,J  .  2 d 300 —A | f 200 S "~ 100 -Q m !ft  X-  100  0  0 0  400  800  400  1200  800  1200  Discharge Volume (mL)  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  96  4.3 T H E L E A C H I N G CELL TEST a) Pb Leachate o  '•3  2 _ c d  § E o ~ u n CL  500 400 300 200 | 100 0 450  150  600  750  1200  Discharge Volume (mL)  b) C M Leachate o '•3  2 _ = ?  If  o — u 3  o  500 400 300 200 100 0  Breakthrough concentration •  h—m—mm^  150  1  300  \  450  1  U  600  750  i  1  900  1050  1200  900  1050  1200  —  Discharge Volume (mL)  c) Pb+Cu Leachate-Pb data o •£  J  t5 ~ JQ CL  500 400 300 100 0 150  300  450  600  750  Discharge Volume (mL)  d) Pb+Cu Leachate - C M data c o c 0) u  c o o 3  O  500 400 300 200 100 0 —•—1—1 150  • — — ~~  —  Breakthrough concentration  1 300  1 450  1 600  1 750  1  900  1—  1050  1200  Discharge Volume (mL)  •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  97  4.3 T H E L E A C H I N G CELL TEST 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 analyzed  Heavy metal Initial breakthrough concentration at 1200 ml concentration of discharge mgL mgL418 0 429 0 343 0 398 1 348 1 449 1 460 10 321 12 227 439 269 17 474 104 384 7 410 3 417 1 506 2 1  Pb Cu Pb+Cu Pb+Cu Pb+Cu+Cd Pb+Cu+Cd Pb+Cu+Cd Forest soil Pb Cu admix Pb+Cu Pb+Cu Spruce bark Pb Cu admix Pb+Cu Pb Bentonite admix  Pb Cu Pb Cu Pb Cu Cd Pb Cu Pb Cu Pb Cu Pb Cu  1  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 CELL TEST  4.3.2.2  98  Migration behavior - non-uniformity and fractured porous media  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 i n Figures 4.3.11 4.3.12, w i t h the hydraulic conductivity curves i n 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 w o u l d 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 i n 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 i n Figure 4.3.7, is used to explain w h y the breakthrough concentrations d i d not reach 100% of the source concentration. Figure 4.3.7.b, i n 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 i n 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. A s a result, the higher velocity and volume of heavy metals w o u l d quickly overwhelm the sorptive ability of the channel walls. A conceptual model for nonuniform heavy metal migration (Figure 4.3.14) shows that at the discharge end, the higher heavy metal concentrations from the preferential channels, w o u l d mix w i t h 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-  Preferential channels  mtfftttttt Source flow  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  100  Fractured porous media  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 w o u l d be migrating through the fractures. According to contaminant transport theory for fractured media, the slope of breakthrough curves is determined . by the degree i n 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 i n flatter breakthrough curves. The steep breakthrough slopes for the Spruce bark admixes indicate a l o w 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 i n 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 i n clay barriers is to delay the migration of heavy metals. Secondly, sorption capacities may be misleading, because i n 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 i n Figures 4.3.11 - 4.3.12, the breakthrough points were determined for each curve, and summarized i n 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 i n 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 i n Table 4.3.5 are the predicted sorption capacities calculated from the Batch adsorption test results i n section 4.2.1. Even after running the Leaching cell for 1200 m l 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 m g of Cu.  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 CELL TEST  102  Following the same argument as i n 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 i n Table 4.3.5 show that most of the samples i n 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 i n 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 i n retarding the migration of heavy metals.  T A B L E 4.3.6. Summary of heavy metal breakthrough points & retentions. Leaching Cells  Admix  Leachate  HM* Type  Breakthrough point  HM retained HM retained up to break, pt. up to 1200 ml  Batch adsorption tests ** HM retention predicted  Percentage of predicted  ml  mg  mg  mg  %  239  1102  22%  Bentonite Pb  Pb  370  82  admix  Cu  130  0  99  433  23%  Cu Pb+Cu Pb+Cu+Cd  Pb  600  131  250  873  29%  Cu  330  32  171  302  57%  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% 32%  Cu  290  12  114  355  Spruce  Pb  Pb  320  44  192  1107  17%  bark  Cu  Cu  150  0  125  432  29%  854  16%  300  0%  admix  Pb+Cu  Pb  240  0  135  Cu  50  0  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  103  4 . 3 THE LEACHING CELL TEST  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 i n Table 4.3.5, shows that Cu was « 2.5 times more mobile than Pb. A s 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 i n section 4.2.1.4 (Table 4.2.5), heavy metal mobilities were calculated by dividing sorption concentrations w i t h 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 w i t h 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 3.6  Pb  Pb  Cu  Cu  Pb+Cu  Pb  Pb+Cu  Cu  Pb+Cu+Cd  Pb  1.0 2.7  Pb+Cu+Cd  Cu  0.9  Pb+Cu+Cd  Cd  0.6  1.4 2.9  * HM - heavy metal  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  104  4.3 THE LEACHING CELL TEST  The Batch adsorption tests show that due to competition, the sorption capacity of heavy metals i n single heavy metal systems are higher than i n multi-heavy-metal systems. However, this competition effect could not be seen i n 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 w i t h the Leaching cell test. Earlier i n this section, under-saturation was suggested to be a significant factor i n causing early heavy metal breakthroughs. Since the initial saturations shown i n 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 w o u l d be seen i n 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 w o u l d 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 m l of discharge (~ 7 pore volumes), most heavy metal permeated samples stabilized at hydraulic conductivity values between 1.8 x 10~ - 5.0 x 10~ m s 9  9  -1  (Table 4.3.3). In contrast, samples permeated with blank solutions of 0.01 M Ca(N03)2 resulted i n hydraulic conductivities between 1.4 x 10  -11  - 2.8 x 10" m s . This difference 11  _1  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  105  4.3 THE LEACHING CELL TEST 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 i n p H , as observed i n the discharge p H results i n 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 i n CaCh) i n comparison to bentonite (7.61 p H i n CaCh), the presence of Forest soil w o u l d 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 i n 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 i n the Forest soil admixes. Confirmation of these effects w o u l d require further investigation. Regardless of the differences i n initial hydraulic conductivity, almost all samples permeated with heavy metals eventually converged to a narrow range of values. Thus, i n 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, w i t h one part of Forest soil or Spruce bark, does not cause significant increases i n 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 ~CL  I  8 7  - A — + -^  150  300  450  600  -0-4-  -4 900  750  1050  1200  Discharge Volume (mL)  b) Cu Leachate 9 a o  1  a  ***  7 6  a> .c u  ti*  5  .2  A  0  150  300  AA  4  450  0  0  (J*  .  •  Jk  600  750  A  -  A  0 A  A  1050  900  1200  Discharge Volume (mL)  c) Pb+Cu Leachate 9 a.  a at eg .c o (A  :r —... — *  1  A-*  150  300  450  600  A—  750  —A  <s  O w ^ —  X  A  A  *  i  900  ~ *  A  1050  1200  Discharge Volume (mL)  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 A s mentioned i n section 4.3.2.3, the main concern i n contaminant migration is  not how much heavy metal w o u l d be retained, but how long a barrier could delay the breakthrough of heavy metals. According to the retention and breakthrough results i n 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 i n structure were identified by variations i n the slopes of the breakthrough curves. By visual inspection, the breakthrough slopes i n 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 to « 3 x 10-9 m s ). 1  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 i n determining the hydraulic conductivity of clay barriers. 3. A conceptual mechanism describing hydraulic conductivity change and nonuniform heavy metal migration was presented i n Figures 4.3.7 and 4.3.14. 4. The lack of confining pressures caused the hydraulic conductivities i n the current study to increase much more than observed i n 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 w i t h the hydraulic conductivity, and heavy metal breakthrough results from Cabral (1992) and Weber (1991), under-saturation was suspected to be a factor i n causing large hydraulic conductivity increases, and early heavy metal breakthroughs i n 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 i n predicting the breakthrough points and retention capacities of Leaching cell tests, but adequate i n 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  110  4.4 SELECTIVE SEQUENTIAL EXTRACTION  4.4  SELECTIVE SEQUENTIAL EXTRACTION  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 i n 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 i n Table 4.4.1.  T A B L E 4.4.1. Summary for the SSE tests. Admix Bentonite  Forest soil  Spruce bark  HM* solution Pb Cu Pb+Cu Pb+Cu+Cd Pb Cu Pb+Cu Pb Cu Pb+Cu  Center & edge sampling  Composite sampling  Batch adsorption test samples  V  V V V V  V V  V V  V  V  * HM - heavy metal Note - all heavy metal solutions contained 500 mg L of each heavy metal specified. 1  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.4 SELECTIVE SEQUENTIAL EXTRACTION  4.4.1  111  S S E on a set of Batch adsorption tests  The SSE results for the Batch adsorption test samples are shown i n 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 i n this section were performed on mixtures (bentonite, Forest soil, and Spruce bark admixes), while the Batch adsorption tests i n 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 solution  Bentonite Blank admix Blank C M 1st Cu 2nd Pb 1st Pblnd Pb+Cu 1st Pb+Cu 1st Pb+Cu 2nd Pb+Cu 2nd Pb+Cu+Cd 1st Pb+Cu+Cd 1st Pb+Cu+Cd 1st Pb+Cu+Cd2nd Pb+Cu+Cd2nd Pb+Cu+Cd2nd  Forest soil admix  Blank Blank C M 1st Cu 2nd Pb 1st Pb2nd Pb+Cu 1st Pb+Cu 1st Pb+Cu 2nd Pb+Cu2nd  Spruce bark admix  Blank Blank C M 1st Cu 2nd Pblst Pb2nd Pb+Cu 1st Pb+Cu 1st Pb+Cu 2nd Pb+Cu 2nd  Notes  Exchangeable Carbonates Hydroxides Organics Residue Total HM Ug/g soil ug/g soil analyzed ug/g soil ug/g soil ug/g soil soil CM 3 0 0 1 1 n/a Pb 0 3 2 4 1 n/a 574 Cu 4 4 35 205 326 Cu 5 565 4 35 196 325 1604 7 Pb 17 584 178 817 1760 Pb 4 12 138 637 970 Cu 1 423 29 3 284 105 1174 Pb 6 0 106 231 830 Cu 449 3 3 104 28 311 Pb 1238 12 5 264 106 852 267 Cd 2 0.1 0 14 251 Cu 378 3 28 3 102 242 1079 Pb 3 8 98 186 785 264 Cd 0.2 1 0 12 250 367 Cu 2 3 90 28 244 1090 Pb 2 9 182 98 798 Cu 2 3 1 1 0 n/a 4 Pb 1 0 1 3 n/a Cu 14 738 51 116 206 350 721 Cu 16 46 122 206 332 1912 Pb 5 67 255 753 832 2088 Pb 4 70 398 790 826 526 Cu 11 39 89 137 249 1252 Pb 4 39 360 216 632 523 Cu 11 40 89 141 242 1280 Pb 1 40 220 377 642 2 Cu 1 0 0 1 n/a 6 Pb 0 3 3 0 n/a 599 Cu 8 74 61 172 285 552 Cu 9 22 74 163 285 1268 Pb 4 60 189 423 592 1297 1 Pb 194 61 436 606 399 Cu 2 12 51 93 240 825 Pb 0 46 116 184 480 389 Cu 14 8 43 96 228 803 Pb 3 50 103 185 462  - Heavy metal solutions contain 500 mg L 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 1  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  113  4.4 SELECTIVE SEQUENTIAL EXTRACTION  4.4.1.1  Sorption characteristics of the admixes 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 i n 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 i n clay barrier mixes rather than individually. The 16% discrepancy may be related to the contrasting p H s 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 l o w p H of the Spruce bark may inhibit the cation exchange and precipitation . reactions associated w i t h bentonite.  T A B L E 4.4.3. Comparison of admixes based on SSE of Batch adsorption samples. Heavy metal solution Cu Pb Pb+Cu  Average  HM analyzed CM  Pb Cu Pb  Total sorbed concentrations based on extractions Spruce b. admix Forest s. admix % Bentonite admix Diff. Ug/gsoil ug/gsoil Ug/gsoil 576 730 570 28% 1282 19% 2000 1682 394 525 20% 436 814 5% 1266 1206 18%  %  Diff. 1% -24% -10% -32% -16%  The average percentages of Pb and Cu associated to each soil component of the three admixes are shown i n 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 w i t h 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  (Xg/gsoil  extracted  type  Pb  Bentonite Forest soil Spruce bark  65% 46% 52%  25% 34% 28%  9% 17% 14%  1% 3% 5%  Cu  Bentonite Forest soil Spruce bark  63% 47% 54%  28% 27% 27%  7% 17% 12%  1%  4.4.1.2  Total  Organic Residue  7% 5%  0% 0% 0% 1% 2% 1%  1324 1633 1048 460 627 485  Comparing sorption capacities of mixtures vs. individual materials  Shown i n Table 4.4.5, are the total concentration of heavy metals extracted from the admix samples submitted to Batch adsorption tests. A s 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 i n sorption capacities was due to different soiksolution ratios. If the inert sand was excluded from the soiksolution ratio, then the ratio for the admixes w o u l d be 1 g of reactive material to 135 m l 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 l o w 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 solution  Bentonite admix  Cu Pb Pb+Cu Pb+Cu+Cd  Forest soil admix  Cu Pb Pb+Cu  Spruce bark admix  Cu Pb Pb+Cu  HM analyzed  Total extraction from admixes  Cu Pb Cu Pb Cd Cu Pb Cu Pb Cu Pb Cu Pb Cu Pb  ug/g soil 570 1682 436 1206 265 373 1084 730 2000 525 1266 576 1282 394 814  Total sorption by summation of individual materials* ug/g soil 528 1344 368 1065 229 351 983 598 1376 414 1089 527 1350 366 1041  %  Diff. -7% -20% -16% -12% -14% -6% -9% -18% -31% -21% -14% -8% 5% -7% 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 i n 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 i n a Batch container are exposed to a fixed amount of solution, while the soil particles i n 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 w i t h 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, i n 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, w i t h the sorption capacities of the Batch adsorption tests is shown i n Table 4.4.6. W i t h the influent end samples, one was certain that exposure was to heavy metal concentrations of 500 m g L . A  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. Admix  Leachate solution  Sample region (1st layers only)  HM analyzed  Bentonite  Cu Pb Pb+Cu  Center  Cu Pb Cu Pb Cd Cu Pb Cu Pb Cu Pb Cu Pb Cu Pb  Center Edge Center  Pb+Cu+Cd  Composite Composite Composite  Forest soil  Cu Pb Pb+Cu  Composite Edge Composite Composite  Spruce bark  Cu Pb Pb+Cu  Center Center Center Edge  Total heavy metals extracted From Leaching From Batch adsorption cells tests ug/gsoil ug/gsoil 570 534  7%  471  436  7% -7%  1175  1206  3%  252  265  5%  367  373  1%  877  1084  24%  826  730  -12%  1938  2000  3%  568  525  -8%  1069  1266  18%  651  576  -11%  1895  1282  -32%  404  394  -3%  536  814  52%  1569  1682  % Diff  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  117  4.4 SELECTIVE SEQUENTIAL EXTRACTION  4.4.2  SSEs o n extruded Leaching cell samples  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 i n 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 i n 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 i n the center regions varied significantly from the concentrations i n 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 l o w heavy metal concentrations i n layers 2 and 3. These results indicate that short-circuiting occurred i n many samples. This supports the findings i n section 4.3.3.1, that heavy metals migrated non-uniformly through preferential channels. Consistent sampling of high heavy metal concentrations i n the 4th layer, was probably due to the decision i n permeating the Leaching cell from bottom to top. Since the permeant exited at the top, it w o u l d 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 i n an over-estimation of heavy metal sorption i n 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 w o u l d 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) i n each layer were sampled, a detailed distribution of heavy metals could not be determined. From the graphs i n 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  119  4.4 SELECTIVE SEQUENTIAL EXTRACTION  Admix type: Bentonite Leachate: Pb # of sample cells: 2 Type of sampling: center & edge  Layer 4 Layer 3 |  Layer 2  |  Layer 1 ~ |  '  Center s a m p l e  1  t a) Center sample of 1st cell  |  b) Edge sample of 1st cell  "  500 1000 1500 Adsorption (ug/g)  2000  c) Center sample of 2nd cell  0  500 1000 1500 Adsorption (ug/g)  Edge s a m p l e  influent end  0  1  1  T  500 1000 1500 Adsorption (ug/g)  2000  d) Edge sample of 2nd cell  2000  0  5  0  0  1  0  0  0  1  5  0  Adsorption (ug/g)  0  2  °00  • 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  120  4.4 SELECTIVE SEQUENTIAL EXTRACTION  Admix type: Bentonite Leachate: Cu # of sample cells: 1 Type of sampling: center & edge  Layer 4 Layer 3 Layer 2 Layer 1  t  Center sample Edge sample  influent end  b) Edge sample  a) Center sample  250  |  500  750  1000  Adsorption (ug/g)  • E X C H A N G E A B L E • C A R B O N A T E S O HYDROXIDES  250  500  750  1000  Adsorption (ug/g)  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  I  1  Layer 2  |  I  Layer 1  I  Center sample 1  t influent end  a) Pb extracted from center sample  Edge sample  c) Pb extracted from edge sample  1200  b) Cu extracted from center sample  300  600 Adsorption (ug/g)  d) Cu extracted from edge sample  900  1200  300  600 Adsorption (ug/g)  900  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  122  4.4 SELECTIVE SEQUENTIAL EXTRACTION  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  O.  E  500  1000  Adsorption  (ug/g)  1500  2000  c) Center sample of 2nd cell  0  500  1000  Adsorption (ug/g)  500  1000  Adsorption (ug/g)  1000  Adsorption (ug/g)  1500  2000  d) Edge sample of 2nd cell  1500  2000  e) Center sample of 3rd cell  0  500  0  5  0  0  000  1  1500  Adsorption (ug/g)  2000  f) Edge sample of 3rd cell  1500  2000  0  500  1000  Adsorption (ug/g)  1500  2000  • 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  123  4.4 SELECTIVE SEQUENTIAL E X T R A C T I O N  Admix type: Spruce bark Leachate: Pb # of sample cells: 1 Type of sampling: center & edge  Center sample Edge sample  influent end  a) Pb extracted from center  0  500  1000 Adsorption (ug/g)  b) Pb extracted from edge  1500  2000  0  500  1000 Adsorption (ug/g)  1500  2000  • 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  124  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  Admix type: Spruce bark Leachate: C M # of sample cells: 2 Type of sampling: center & edge Center sample influent end  a) C M extracted from center of 1st cell  0  200  400  Adsorption (ug/g)  600  b) Cu extracted from edge of 1st cell  800  c) Cu extracted from center of 2nd cell  200  400  Adsorption (ug/g)  600  0  4.4.6.  200  400  Adsorption (ug/g)  600  800  d) Cu extracted from edge of 2nd cell  800  • EXCHANGEABLE • CARBONATES DHYDROXIDES  FIGURE  Edge sample  200  400  Adsorption (ug/g)  600  800  BORGANICS • RESIDUE  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.  H e a v y M e t a l Sorption and H y d r a u l i c Conductivity Studies using Three T y p e s of Bentonite A d m i x e s  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  c) Pb extracted from edge of 1st cell  in 0  150  300 A d s o r p t i o n (ug/g)  450  600  b) Cu extracted from center of 1st cell  150  150  300 A d s o r p t i o n (ug/g)  450  600  450  600  450  600  450  600  450  600  d) Cu extracted from edge of 1st cell  300 A d s o r p t i o n (ug/g)  450  150  e) Pb extracted from center of 2nd cell  150  0  300 A d s o r p t i o n (ug/g)  450  300 A d s o r p t i o n (ug/g)  g) Pb extracted from edge of 2nd cell  600  f) Cu extracted from center of 2nd cell  150  300 A d s o r p t i o n (ug/g)  h) Cu extracted from edge of 2nd cell  *4  §3 » o. 11 in 150  300 A d s o r p t i o n (ug/g)  450  600  i) Pb extracted from center of 3rd cell  0  1 5 0  Adsor fi8n(ug/g, 3  150  k) Pb extracted from edge of 3rd cell  300 A d s o r p t i o n (ug/g)  4 5 0  P  j)  Cu  -  4  e x t r a c t e d f r o m c e n t e r o f 3rd  300 A d s o r p t i o n (ug/g)  1) Cu extracted from edge of 3rd cell  cell  I | |  3 2  §" 1 150  300  450  150  A d s o r p t i o n (ug/g)  • EXCHANGEABLE  FIGURE 4.4.7.  • CARBONATES  • HYDROXIDES BORGANICS  300 A d s o r p t i o n (ug/g)  450  • RESIDUE  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  126  4.4 SELECTIVE SEQUENTIAL EXTRACTION Admix type: Bentonite Leachate: Pb+Cu+Cd # of sample cells: 2 Type of sampling: composite  influent end  a) Pb extracted from 1st cell sample  0  250  500 Adsorption (ug/g)  d) Pb extracted from 2nd cell sample  750  1000  b) Cu extracted from 1st cell sample  0  250  500  Adsorption (ug/g)  0  250  500 Adsorption (ug/g)  750  1000  750  1000  e) Cu extracted from 2nd cell sample  750  1000  c) Cd extracted from 1st cell sample  0  250  500  Adsorption (ug/g)  f) Cd extracted from 2nd cell sample  o  ra _)  a a. S  ro 250  500 750 Adsorption (ug/g)  1000  250  500 750 Adsorption (ug/g)  1000  • E X C H A N G E A B L E • C A R B O N A T E S • HYDROXIDES B O R G A N I C S • 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  127  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  Admix type: Forest soil Leachate: Cu  Layer 4 I  # of sample cells: 1 Type of sampling: composite  I  Layer 3 Layer 2  t  500  Adsorption (ug/g)  influent end  b) Composite sample of 2nd cell  a) Composite sample of 1st cell  250  |  Layer 1~  750  1000  250  500  Adsorption (ug/g)  750  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.  H e a v y M e t a l Sorption a n d H y d r a u l i c Conductivity Studies using Three Types of Bentonite A d m i x e s  128  4.4 SELECTIVE S E Q U E N T I A L E X T R A C T I O N  Admix type: Forest soil Leachate: Pb+Cu # of sample cells: 3 Type of sampling: composite  Layer 4 Layer 3 Layer 2 Layer 1  t a) P b extracted from 1st cell  influent end  b) Cu extracted from 1st cell u.  4  Q.  E  300  600  900  Adsorption (ug/g)  600  Adsorption (ug/g)  900  300  1200  * 600  Adsorption (ug/g)  900  1200  600  Adsorption (ug/g)  900  1200  900  1200  f) C M extracted from 3rd cell  e) P b extracted from 3rd cell  300  600  Adsorption (ug/g)  d) Cu extracted from 2nd cell  c) P b extracted from 2nd cell  300  300  1200  900  1200  1 300  600  Adsorption (ug/g)  • EXCHANGEABLE • CARBONATES • HYDROXIDES BORGANICS • RESIDUE  FIGURE 4.4.10.  Distribution of heavy metals in Forest soil admix samples leached with  P b  & CM .  (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  129  4.4 SELECTIVE SEQUENTIAL EXTRACTION  4.4.2.2  Heavy metal retention mechanisms  The Batch adsorption tests results presented i n 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 i n which heavy metals were sorbed over a large range of sorption concentrations. Although only one concentration value (500 m g 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 ). By performing -1  SSEs on these soil samples, one was able to identify distinct trends i n which the heavy metals were sorbed. Because of the imprecision of the SSE procedure, the lower values (< 100 ug g- ) were not included i n the analysis. 1  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 i n Figures 4.4.11 - 4.4.12. Instead, the Cd SSE data is presented i n Table 4.4.7.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  130  4.4 SELECTIVE SEQUENTIAL EXTRACTION  a) Exchangeable Pb component of total heavy metals sorbed. 0>  3  03 0)  S) e  cs O  UJ  100% j 80% c o 60% D. 40% o 20% 0% 0.00  c  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.  cu  *  100% •£ 80% 60%  m  2.00 4.00 6.00 8.00 10.00 12.00 Total heavy metal concentration (mmol/kg soil)  0.00  14.00  d) Organic Pb component of total heavy metals sorbed.  c  50% 40% 2 30%  CB  O  „  c  f  S> o- 20%  »  -  @-  » °  °J®  ° i 10% o  f  0.00  0%  &'&%T -v -r — -y  4.00 6.00 8.00 10.00 12.00 2.00 Total heavy metal concentration (mmol/kg soil)  « Bentonite admix  x Forest soil admix  14.00  o S p r u c e 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  131  4.4 SELECTIVE SEQUENTIAL EXTRACTION  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% 40% '5 0) 30% & c 20% •o a. E >» C O 10% X o 0% 0.00 0)  4-1  c  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  F I G U R E 4.4.12.  CM  x Forest soil admix  o Spruce bark admix  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  132  4.4 SELECTIVE SEQUENTIAL EXTRACTION  T A B L E 4.4.7. SSE data for Heavy metal extracted Cd  Layer 1 2 3 4 1 2 4  Cd  from the bentonite admix.  Exchangeable Carbonates Hydroxides Organics Residue 96% 94% 96% 96% 96% 96% 96%  2% 4% 2% 2% 2% 2% 2%  1% 1% 1% 1% 1% 1% 1%  1% 1% 1% 1% 1% 1% 1%  0% 0% 0% 0% 0% 0% 0%  Total ug/g soil 250 197 118 162 252 188 175  Sorption trends for Pb, Cu, and Cd  A s shown i n 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- , the exchangeable 1  component accounted for only 10-40% of the total amount of heavy metals sorbed. A s 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 m m o l kg- , the exchangeable component accounted for 50 - 80% of 1  the total amount of heavy metals sorbed. In actual values, the amount of heavy metals sorbed onto the carbonate, hydroxide, and organic components increased w i t h 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 i n terms of percentage. In terms of retention mechanisms, Figures 4.4.11 4.4.12 show that precipitation and surface complexation dominated at l o w Pb and Cu sorption concentrations, while cation exchange dominated at higher sorption concentrations. The discussion i n section 4.2.2.2, theorized that for Cu sorption, precipitation and complexation w o u l d dominate at low initial heavy metal solution concentrations, and cation exchange at high initial heavy metal concentrations. These findings are i n agreement w i t h the findings i n 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 m m o l kg" (118 1  250 pg g ), represents l o w values. Considering the sorption trends for Pb and Cu, -1  cation exchange also w o u l d 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 w i t h increasing heavy metal sorption concentrations. This means that greater the contamination concentrations, greater the potential for heavy metals to desorb and reenter into the groundwater. The heavy metal sorption trends also provides direction i n improving the sorption model developed in section 4.2. The sorption model i n section 4.2, was not specific i n 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 w o u l d 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 i n section 4.2. However, these results show that SSE may be a valuable tool in developing new sorption models. Further work i n conducting extensive SSEs on Batch adsorption samples is recommended. The advantage of Batch adsorption samples is that their initial and equilibrium solution concentrations w o u l d be known.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  4.4 SELECTIVE SEQUENTIAL EXTRACTION  134  Sorption differences between bentonite and other admixes 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 w o u l d constitute 12.5% of the reactive material i n 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 w i t h these components include precipitation and complexation. These findings show that the presence of Forest soil and Spruce bark i n clay barrier mixes promoted stronger retention mechanisms, agreeing w i t h the findings i n section 4.4.1.1. Figure 4.3.15 i n section 4.3.3.1, showed that the presence of Forest soil and Spruce bark resulted i n lower discharge pHs. Since Pb and Cu precipitation is associated w i t h 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 w o u l d be exposed to various chemical conditions; thus, sorbed heavy metals risk the chance of remobilization. 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  135  Summary of SSE results and the performance of the admixes  Migration behavior and sorption characteristics  1. M a n y 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 i n the 4th (top) layer. Although this resulted i n an overestimation of heavy metal sorption capacities for the Leaching cells, the error d i d 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 w i t h increasing heavy metal sorption concentrations. 6. The SSE results showed that the sorption model developed Pb and Cu, i n section 4.2.1 w o u l d 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  136  The applicability of Batch adsorption test results to the Leaching cell test  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 i n 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  CONCLUSIONS & RECOMMENDATIONS  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 C M sorption capacity Cd sorption capacity Sorption onto Bentonite Sorption onto Forest soil Sorption onto Spruce bark  Forest soil > Bentonite « Spruce bark Forest soil > Bentonite » Spruce bark Forest soil > Bentonite > Spruce bark Pb>Cu> Cd C M > Pb> Cd (up to initial [metal] of 4 mmol/L, then Pb > Cu) Pb>Cu> Cd  3. Based on the competition functions i n 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  138  5.1 C O N C L U S I O N S  Heavy metal sorption characteristics of the clay barrier admixes  4. The SSE results showed that for all three admixes, precipitation and complexation dominated at l o w 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 m g L" ) permeated samples were 1  greater by approximately two orders of magnitude (from * 2 x 10- m s to 11  _1  « 3 x 10- m s-i). 9  8. The hydraulic conductivity results i n the current study experienced much larger increases than those found i n other studies. This discrepency was probably due to the lack confining pressures used i n the current study. This condition w o u l d represent that of a landfill at the beginning of operation.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  139  5.1 CONCLUSIONS  9. The blank (Ca ) and heavy metal solutions (Pb , Cu , Cd , Ca ), both contained 2+  2+  2+  2+  2+  cations of 2+ valence. Thus, valence was not sufficient i n 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 i n affecting the hydraulic conductivity of clay barriers.  10. Heavy metal solutions containing different combinations of Pb, Cu, and Cd, i n 500 m g L ' concentrations, produced similar hydraulic conductivities. The results 1  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 i n 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  140  Prediction ability of Batch adsorption tests  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 i n 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 i n terms of retention capacity, and points of breakthrough.  21. The Spruce bark admix was better than the bentonite admix i n 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  5.2  141  RESEARCH CONTRIBUTIONS  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 i n the study were under-saturated at the start of heavy metal permeation, and d i d 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 R E S E A R C H 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 w i t h Forest soil as a remedial measure.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  5.3 R E C O M M E N D A T I O N S O N FURTHER RESEARCH  5.3  RECOMMENDATIONS O N FURTHER RESEARCH  1.  Confirmation of proposed sorption model, and mechanism for hydraulic conductivity  143  increase and heavy metal migration.  a) The sorption model developed was able to describe binary and ternary systems of Pb, Cu, and Cd w i t h bentonite, Forest soil, and Spruce bark. Recommended is further work w i t h other cations and materials, and testing on quaternary and higher systems. b) Conducting studies involving the scanning electron microscope w o u l d 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 i n 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 w o u l d 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 o n heavy metal compatibility is recommended.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  5.3 RECOMMENDATIONS ON FURTHER RESEARCH  144  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 m g L ) of heavy metals used i n the current 1  study caused hydraulic conductivity values to reach an upper limit. Further research is recommended i n investigating the m i n i m u m concentrations required to trigger increases i n hydraulic conductivity. e) Further research is recommended i n 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 w o u l d be helpful i n understanding the effects of heavy metals on clay barriers. b) Further research is required to determine w h y 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 i n the current study.  Heavy Metal Sorption and Hydraulic Conductivity Studies using Three Types of Bentonite Admixes  145  REFERENCES Acar, Y.B., H a m i d o n , A . , Field, S.D., and Scott, L. 1985. The effect of organic fluids on hydraulic conductivity of compacted kaolinite. In Hydraulic Barriers i n 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. Allan, R.J. 1995. Impact of mining activities on the terrestrial and aquatic environment w i t h 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, 87:131148. 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, N e w York, U S A . Barry, G.A., Chudek, P.J., Best, E.K., and M o o d y , 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 i n suspensions of various types of clays. Clay Minerals, 28: 33-38. Cabral, A.R. 1992. A study of clay compatibility to heavy metal transport i n permeability testing, Ph.D. Thesis. Department of C i v i l Engineering and A p p l i e d 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 N o . 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 i n 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, B C . 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. F l u i d conductivity testing of fine-grained soils. Journal of Geotechnical Engineering. 110(11): 1648-1665. Eltantawy, I.M., and A r n o l d , 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. M i n e vegetation i n Europe. In Heavy Metal Tolerance i n 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 w i t h simple liquid 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. M c G r a w - H i l l , N e w York. Foreman, D.E., and Daniel, D.E. 1986. Permeation of compacted clay w i t h organic chemicals. Journal of Geotechnical Engineering, 112: 582-589. Freeze, R.A., and Cherry, J.A. 1979. Groundwater. Prentice-Hall, Eaglewood Cliffs, N J . 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 w i t h 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 i n 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, N e w York, pp. 179-230. Haygreen, J.G., Bowyer, J.L. 1996. Forest Products and W o o d Science. Iowa State University Press, Iowa. Hickey, M . G . , and Kittrick, J. A . 1984. Chemical partitioning of cadmium, copper, nickel, and zinc i n soils and sediments containing high levels of heavy metals. Journal of Environmental Quality, 13(3): 372-376. H i n z , C , Buchter, B., and Selim, H . M . 1992. Heavy metal retention i n 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 i n Soils. John Wiley & Sons, N e w York. Livens, F.R. 1991. Chemical reactions of metals w i t h 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 i n 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 A n n u . 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, N e w 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 i n 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 o n clay permeability. Journal of Geotechnical Engineering, 113(8): 915-919. Phadungchewit, Y. 1989. The role of p H and soil buffer capacity i n heavy metal retention i n clay soils, Ph.D. Thesis. Department of C i v i l Engineering and A p p l i e d 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. E C S C , E E C , E A E C , Netherlands. Ramos, L., Hernandez, L . M . , and Gonzalez, M.J. 1994. Sequential fractionation of copper, lead, cadmium and zinc i n 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 i n European household waste components. In Heavy Metals i n 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, N e w 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 L e v i - M i n z i , 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. H u m u s Chemistry: Genesis, Composition, Reactions. Wiley, N e w York. Tan, K . H . 1998. Principles of Soil Chemistry. Marcel Dekker, N e w York. Tchobanoglous, G., Theisen, H . , and V i g i l , S. 1993. Integrated Solid Waste Management: Engineering Principles and Management Issues. M c G r a w - H i 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. U S E P A , 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. U S E P A , 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: 251255. 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 A p p l i e d 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 i n Soils. Developments i n Geotechnical Engineering, 73. Elsvier, Amsterdam, Netherlands. Yong, R . N . , and Phadungchewit, Y. 1993. p H influence on selectivity and retention of heavy metals i n 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 BARRIER MATERIALS  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 OF A D M I X E S A.3. SPECIFIC S U R F A C E A R E A OF 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 DENSITY OF THE A D M I X E S  153 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  Methods Dry sieving, performed according A S T M D422-63 ( A S T M , 1995), was applied to particle sizes larger than 75 pm. The hydrometer analysis, adapted from A S T M D42263 ( A S T M , 1995), was performed to determine the size distribution of particles smaller than 75 m m . D r y 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 m l of distilled water, and was stirred by a high-speed mixer. A s 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 c m high and 56 c m i n 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 w i t h distilled water to store and rinse the hydrometer. The following measurements were taken prior to the hydrometer test: 1. 2. 3. 4.  Internal diameter of the sedimentation cylinder Volume of hydrometer bulb (measured using water volume displacement) Distances between the bulb center and the bulb's graduation marks 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 i n 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 t c . , until the elapsed time was large enough to give the m i n i m u m 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 = [(30nH )/(981)(Gs r  l)(pwt)]  1 / 2  where t (mm) is the time after the start of sedimentation, G is the specific gravity of the particles ( G taken from Denham, 1999), p (g/cm ) is the density of water at temperature T, n (g/ cms) is the viscosity of water at temperature T, and H (cm) is the corrected depth of fall. s  3  w  s  r  The corrected depth of fall H (cm) is, r  H = H + Cm - (V /2A) r  b  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 (cm ) is the volume of the bulb, and A (cm ) is the cross-sectional area of the cylinder. 3  2  The percentage p by weight of particles w i t h diameter smaller than D is, p = (62.26/ W )(R - Cc + m ) [ G / ( G -1)] 0  s  s  where W ( 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. 0  The dispersing agent correction Cd ( g / L ) is, Cd = X d V  s  where Xd (g) is the amount of sodium hexametaphosphate added, and V (L) is the volume of suspension. s  The temperature correction m ( g / L ) is, m = 1000(0.99823 - p - [0.000025(T - 20)]} w  Results The plot of particle size vs. percent finer is found i n section 4.1 (Figure 4.1.1). TABLE  A.1.1.  Sand  Particle size distribution of sand, bentonite, air-dried Forest soil, and Spruce bark (Dry sieving data unless otherwise indicated). Air-dried Forest soil  Size (mm)  Percent Finer  Size (mm)  0.833  99.8%  6.35  0.5  84.3%  2.38  Spruce bark  Bentonite  Size (mm)  Percent Finer  Size (mm)  Percent Finer  6.35  99.9%  0.42  99.5%  99.9%  2.38  86.5%  0.3  99.2%  77.0% 58.8%  0.833  0.25 0.149  98.9%  Percent Finer  0.5 0.3  0.3  51.9% 41.7%  43.5% 26.5% 15.4%  0.25  11.4%  0.125 0.104  0.25  35.1%  0.125  3.8%  0.074  91.3%  0.5%  0.125  16.9%  0.104  2.3%  0.0915  88.8%  0.1%  0  0.0%  0  0.0%  0.0648  88.2%  0.0458  88.2%  0.0325  86.5%  0.0231 0.0164  83.2%  0.42  64.1%  0.833  0.3 0.25  29.5% 17.4%  0.5 0.42  0.149  4.0%  0.125  1.4%  0.104 0.074 0  0.0%  0.0120  98.0% 96.7% 95.2%  81.6% 81.6%  0.0061  78.3% 74.4%  0.0030  70.1%  0.0020  68.5%  0.0014  61.9%  0.0012  56.7%  0.0010  52.1%  0.0085  Dry sieving  Hydrometer  156 APPENDIX A.2. SPECIFIC GRAVITY OF ADMIXES  Specific gravities were measured for the admixes using the volumedisplacement method described i n A S T M D854-92 ( A S T M , 1995).  Calculations The equation for specific gravity G (mass material/mass water) is, s  Gs = W / ( W s + W f + Wfw) S  S  where W is the weight of the dry admix, W f is the weight of the flask filled w i t h admix and water, and W f w is the weight of the flask filled with de-aired water only. s  s  Results T A B L E A.2.1. Specific gravities of the admixes.  Bentonite admix Forest soil admix Spruce bark admix  Temperature (°C) 18 18 17.5  W.(g)  123.4 128.5 133.9  Wfw(g)  Wfs(g)  699.9 666.0 694.1  777.0 746.1 777.5  G 2.67 2.65 2.65 s  157 A P P E N D I X 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  Method The specific surface area was determined using an ethylene glycol monoethyl ether (EGME) method adapted from Eltantawy and A r n o l d (1973). This test was performed i n cooperation w i t h Denham (1999). A samples of air-dried bentonite weighing 1.1 g was placed i n a tared aluminum foil dish and dried at 60 °C for 48 hr. The dish was weighed before and after d r y i n g to determine moisture content and clay dry weight. Approximately 1.5 m l of E G M E (Fisher) was added to the sample, which was then manually stirred to create a clayE 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 i n a dessicator over anhydrous CaC/2 (granular, 20 mesh & finer, Fisher). A dish of E G M E was also placed i n the dessicator. The sample was left to equilibrate for 30 min. The dessicator was then evacuated w i t h 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 i n 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 / g is provided by Carter et al. (1986): 2  A = Wa/(W -2.86) s  where A is the specific surface, i n m / g , W , is the weight of E G M E retained by the sample, i n g, W is the weight of the dry clay, i n g, and 0.000286 g is the weight of E G M E required to form a monomolecular layer on 1 m of surface. 2  a  s  2  158 Results TABLE A.3.1. Specific surface of bentonite. Sample Bentonite (duplicate 1) Bentonite (duplicate 2) Average  Ws(g) 1.0654 1.0600  W (g) 0.1414 0.1397 a  A (mVg) 464.1 460.8 462.4  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 ( A S T M , 1995), except for changes i n 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 i n the Leaching cell test. TABLE A.4.1.  Changes made to the modified Proctor method. #of layers  # of blows per layer  Compactive energy per volume, ft-lb/cu ft  4.6 in x 4 in dia.  5  2.2 in x 4 in dia.  3  25 12,12,13  34700  Test  Cell size  Modified Proctor Current study  56300  Results The compaction curves are shown i n 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. O p t i m u m water content  M a x i m u m dry density ( k g / m )  Bentonite admix Forest soil admix  12.7 % 12.8 %  1860 1830  Spruce bark admix  12.7 %  1815  Admix  3  160  _ e "S, * & c Q £< °  1870.0 1860.0 1850.0 1840.0 1830.0 1820.0 1810.0 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 BARRIER MATERIALS  B.l.  SOILpH  B.2. C A T I O N E X C H A N G E C A P A C I T Y O F B E N T O N I T E A N D S A N D  162  APPENDIX B.l. S O I L p H  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 w i t h 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 m l 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 i n the partially settled suspension. Table B.l.l summarizes the type and quantity of materials used for the p H measurement. T A B L E B . l . l . The type and quantity of materials submitted to soil pH measurement. Material  Liquid added  Bentonite Bentonite Sand Sand  water 0.01 M  CaCh  water 0.01 M  CaCh  Mass (oven-dried) of material (g) 2 2 5 5  Volume of liquid added (ml) 20 20 5 10  Results T A B L E B.1.2. The soil pH results for bentonite and sand. Type of Liquid Water 0.01 M  CaCh  Bentonite p H 8.38 7.61  Sand p H 4.72 7.67  Ratio 1:10 1:10 1:1 1:2  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 , W E F , & 1995). The sodium acetate method is applicable for both calcareous and noncalcareous 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 m l of 1.0 NaOAc solution to the material, the suspension was shaken i n a mechanical wrist-shaker for approximately 5 min. The centrifuge tube was then centrifuged at 3500 r p m 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 i n a mechanical wrist-shaker for approximately five minutes. After decanting the liquid, this washing procedure was repeated two more times. The 2-propanol rinse was for removing all the Na i n solution, without affecting the Na sorbed onto exchange sites. Displacement of the sodium with ammonium To displace the Na from the exchange sites, 33 m l if NHAOAC was added to the sample, and the was shaken i n a mechanical shaker for approximately 5 min. The liquid then was decanted into a 100 m l volumetric flask. This procedure was repeated two more times. Each time, the liquid was decanted into the same flask. Next, the 100 m l flask containing the decanted solution was filled to the 100 m l mark w i t h NH4OAC, and the Na concentration of the solution was determined using Atomic Absorption Spectrophotometry.  Calculations C E C i n centimoles of positive charge per kilogram (cmol/kg) was calculated from the following equation: CEC = C  N a  • Vfi • 1 g/1000 m g • 1000 g/1 k g • 1 m o l / 2 3 g • 100 c m o l / 1 m o l  where C N is the concentration of Na ( m g / L ) i n the volumetric flask, and Vfi (L) is the volume of the flask. 3  Results T A B L E B.2.1.  The cation exchange capacity of bentonite and sand. N a concentration ( m g / L )  C E C (cmol/kg)  Bentonite (triplicate 1)  272.9  59.3  Bentonite (triplicate 2)  273.9  59.5  Bentonite (triplicate 3)  276.9  60.2  Sand (triplicate 1)  0  Sand (triplicate 2)  0  Sand (triplicate 3)  0  Average  59.7  0  APPENDIX C METHODS SUPPLEMENT  C l . E Q U I P M E N T LISTS A N D DESCRIPTIONS C 2 . C O M P A C T I O N P R O C E D U R E FOR T H E L E A C H I N G CELL 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 DESCRIPTIONS  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 w i t h heavy metals. • • •  50 m l 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 m l , 50 ml, and 100 m l volumetric flasks • 1 each -1 ml, 2 ml, 4 ml, 6 ml, and 10 m l 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 w i t h heavy metals: Compaction apparatus - compaction hammer, compaction mold, paper disk, saran wrap, ruler, knife Leaching cell apparatus - leaching cell, 100 m l 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 sw  J5  C o •** ** o Rl  a o o  Rt  Q>  . & ts J£ bo »  1.S s c  'I |3  S  •w  £  •  01 o  3  01 to vt* o i  ,2 > Z w  rt  U  va PS  O  Leaching cell - top lid (plan view)  Leaching cell - top lid (side view)  7 mm  Chamber for porous stone  screw holes discharge port  Leaching cell - middle (plan view)  Leaching cell - middle (side view) 114 mm  dia.  T  101 m m  dia.  Leaching cell - bottom lid (plan view)  56.5 mm  Leaching cell - bottom lid (side 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 w i t h heavy metals: • • • • • • • •  wire saw ruler small spoon centrifuge 50 m l centrifuge polypropylene test tube 250 m l 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 i n A S T M 1557-91 ( A S T M , 1995). Figure C.2.1 illustrates the compaction procedure. To improve the seal between the cell wall and the compacted sample, the inner wall of the Leaching cell was smeared w i t h 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 i n 3 lifts. The purpose of the m o l d 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 m o l d 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. D r y density, water content, and saturation were calculated for the Leaching cell samples.  171  -a u  o  IH  CH  c o  •X! u «  o u 01  >£ UH  o  43  n  •5 gi iT  S « CH o " S XI to  w  Cu  to  M  Is s  > a c = 2-3 5 <JH  co  e «  Sb (8  CM  u u tin  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.  173 APPENDIX D  B A T C H ADSORPTION TEST AND  CALCULATIONS  DATA  D . l . C A L C U L A T I O N FOR C O N V E R T I N G M A S S UNITS INTO M O L A R UNITS 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  174 APPENDIX D . l . C A L C U L A T I O N FOR CONVERTING MASS UNITS INTO M O L A R UNITS  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]  l m o l • 100 cmol • 1000 g 1 kg 1000 mg 112.4 g 1 moi  175 APPENDIX D.2. B A T C H A D S O R P T I O N D A T A F O R SINGLE H E A V Y M E T A L LEACHATES  Pb sorption of bentonite Final Pb cone.  Initial Pb cone. mgL-i  mmol L  1  mgL-i  mmol L i  Sorbed Pb concentration  Final  m g Pb per g bentonite cmol Pb per k g 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  14.0  5.38  1000.0  4.8  417.9  2.0  29.1  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 Final C u cone.  Initial Cu cone. m g L-i  mmol L  1  mgL  1  mmol L  1  Sorbed Cu concentration  Final  m g Cu per g bentonite cmol Cu per k g 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 6.50  46.1  0.7  6.5  0.1  2.0  3.1  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 4.99  932.5  14.7  736.5  11.6  9.8  15.4  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 Final Cd cone.  Initial Cd cone. mmol L 0.0  0.0  _ 1  mgL  1  0.0  mmol L  _ 1  Sorbed Cd concentration  Final  m g Cd per g bentonite cmol Cd per k g bentonite  solution p H  0.0  0.0  0.0  7.23  0.0  7.23  0.0  0.0  0.0  0.0  0.0  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 6.57  194.7  1.7  121.2  1.1  3.7  3.3  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 6.25  1018.6  9.1  765.6  6.8  12.7  11.3  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  22.3  5.95  3984.5  35.4  3482.3  31.0  25.1  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  mgL  1  mmol L  0.0  0.0  1  mgL  1  mmol L  Final  Sorbed Pb concentration  Final Pb cone.  Initial Pb cone.  1  m g Pb per g Forest soil cmol Pb per k g Forest soil solution p H  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  23.5  2.99  500.0  2.4  188.5  0.9  48.6  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  44.8  2.79  2000.0  9.7  1405.0  6.8  92.8  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)  mgL  1  mmol L  Sorbed Cu concentration  Final Cu cone.  Initial Cu cone. 1  mgL  1  mmol L  1  Final p H  m g Cu per g Forest soil  cmol C M per kg Forest soil  solution  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 3.01 2.92  0.0  92.9  1.5  25.8  0.4  6.2  9.8  183.8  2.9  79.4  1.3  9.7  15.3  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  27.8  43.8  2.60  2758.0  43.4  2458.8  38.7  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. mgL  mmol L  1  Final Cd cone. 1  mgL-i  mmol L  _ 1  Sorbed Cd concentration  Final p H  m g Cd per g Forest soil cmol Cd per k g 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  5.5  4.9  3.12  194.7  1.7  136.0  1.2  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. mg L  1  mmol L  Final Pb cone. 1  mg L  1  mmol L  1  Sorbed Pb concentration  Final p H  m g Pb per g Spruce bark cmol Pb per k g 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 3.68  500.0  2.4  106.5  0.5  19.7  9.5  1000.0  4.8  420.3  2.0  29.0  14.0  3.5 3.49  1000.0  4.8  421.3  2.0  28.9  14.0  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  19.7  3.24  3000.0  14.5  2183.0  10.5  40.9  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  mgL  1  mmol L  Sorbed C M concentration  Final C M cone.  Initial Cu cone. 1  mgL  1  mmol L-  1  Final p H  m g C M per g Spruce bark cmol C M per k g Spruce bark solution  0.0  0.0  0.0  0.0  3.98  0.0  0.0  0.0  0.0  0.0  4.00  0.7  11.9  0.2  1.7  2.7  3.95 3.96  0.0  0.0  0.0 46.1 46.1  0.7  12.0  0.2  1.7  2.7  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  1.3  5.1  8.0  3.74  7.2  11.3  3.56  183.8  2.9  81.8  7.3  318.7  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  25.8  9.6  15.1  3.28  462.5  5.0  1832.0  28.8  1640.5  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  11.8  3.16  3666.0  57.7  3516.0  55.3  7.5  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  mgL  1  mmol L  Sorbed Cd concentration  Final Cd cone.  Initial Cd cone. 1  mgL  1  mmol L  1  Final p H  m g Cd per g Spruce bark cmol Cd per k g 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 3.92  98.3  0.9  58.6  0.5  2.0  1.8  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  5.6  3.84  498.7  4.4  373.1  3.3  6.3  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  17.7  15.7  3.57  3984.5  35.4  3630.6  32.3  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 LEACHATES  Pb and Cu sorption of bentonite i n mass units Initial Pb cone. Final Pb cone. Initial C M cone. Final C M cone. mgL  1  242.1  mgL  1  46.2  mgL  1  mgL  1  Sorbed Pb  Sorbed C M  m g Pb per g bentonite  m g C M per g bentonite  Final p H  0.0  0.0  9.8  0.0  5.68  9.9  0.0  5.75  242.1  45.1  0.0  0.0  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  51.5  31.4  27.2  1.0  5.24  982.4  438.9  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 5.09  985.0  499.2  250.0  185.1  24.3  3.2  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. mmol L  1  mmol L  1  mmol L  _ 1  mmol L  1  Final p H  Sorbed Pb  Sorbed Cu  cmol Pb per kg bentonite  cmol Cu per kg bentonite 0.0  5.68  1.2  0.2  0.0  0.0  4.7  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 5.08  1.1  0.4  7.9  6.1  3.7  9.0  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 5.36  4.7  2.0  0.0  0.0  13.8  0.0  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  12.8  2.8  5.20  4.8  2.2  1.6  1.1  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  7.6  5.02  4.8  2.6  7.9  6.3  10.8  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  184  Pb and Cu sorption of Forest soil i n mass units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. mgL  1  mgL  1  mgL  1  mgL  1  Sorbed Pb m g Pb per g  Sorbed Cu mg  CM  per g  Forest soil  Forest soil  Final pH  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  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  35.6  36.5  3.4  2.89  238.0  987.4  257.0  104.2  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  500.0  308.0  30.2  9.6  2.77  985.0  382.0  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. mmol L  1  mmol L  _ 1  mmol L  1  mmol L  1  Sorbed Pb  Sorbed Cu  cmol Pb per kg cmol C M per kg Forest soil Forest soil  Final pH  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  5.3  3.5  3.13  1.2  0.1  0.8  0.1  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 2.92  4.7  1.1  0.8  0.2  18.1  3.0  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  15.9  9.8  2.83  4.8  1.6  3.9  2.0  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  11.8  20.0  2.72  4.8  2.4  15.7  11.7  186 Pb and Cu sorption of Spruce bark in mass units Initial Pb cone. mgL  1  Final Pb cone. Initial Cu cone.  mgL-i  mgL  1  Final C M cone. mgL  1  Sorbed mg  Sorbed C M  Pb per g m g  C M  per g  Final pH  Spruce bark Spruce bark 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 4.00  239.7  36.9  50.8  20.2  10.1  1.5  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  6.8  3.49  238.0  141.0  1000.0  865.0  4.9  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  0.8  3.70  982.4  470.1  51.5  35.3  25.6  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  574.8  250.0  193.5  20.5  2.8  3.56 3.49  985.0  500.0  411.0  17.5  4.5  630.0  500.0  412.5  17.8  4.4  3.50  730.0  1000.0  919.0  12.8  4.1  3.41  913.0  13.5  4.4  3.42  985.0  634.5  985.0 985.0 985.0  715.0  1000.0  187 Pb and Cu sorption of Spruce bark i n molar units Initial Pb cone. Final Pb cone. Initial Cu cone. Final Cu cone. mmol L  1.2 1.2  _ 1  mmol L  1  mmol L  1  mmol L  1  Sorbed Pb  Sorbed Cu  cmol Pb per kg cmol Cu per kg Spruce bark  Spruce bark  Final pH  0.1  0.0  0.0  5.2  0.0  4.16  0.1  0.0  0.0  5.2  0.0  4.14  0.3  4.9  2.4  3.98  1.2  0.2  0.8  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  4.6  4.0  3.86  1.1  0.2  1.6  0.8  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  2.0  10.0  3.47  1.1  0.8  15.7  13.7  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  12.2  1.3  3.65  4.7  2.3  0.8  0.6  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  3.9  3.0  9.7  4.4  3.55 3.56  4.8  2.8  4.8  2.8  3.9  3.0  9.9  4.4  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  6.2  6.4  3.41  6.5  6.8  3.42  4.8  3.5  15.7  14.5  4.8  3.5  15.7  14.4  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  mgL-i  mgL-i  mgL-i  mgL-i  m g Pb per g  m g Cd per g  pH  bentonite  bentonite  0.0  10.3  0.0  6.13  0.0  250.0  44.9  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  75.4  10.2  1.2  6.07  250.0  45.9  100.0  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 5.96  500.0  395.2  9.4  5.2  61.4  500.0  390.8  9.4  5.5  5.95  78.4  1000.0  806.9  8.6  9.7  5.88  79.4  1000.0  811.3  8.5  9.4  5.87  0.3  28.5  0.0  5.45  250.0  63.0  250.0 250.0 250.0 1000.0  430.7  0.0  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  82.3  28.3  0.9  5.41  1000.0  433.7  100.0  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. mmol L  1.2  1  Final Pb cone. mmol L 0.2  1  Initial Cd cone. mmol L  1  Final Cd cone. mmol L  1  Sorbed Pb  Sorbed Cd  Final  cmol Pb per kg bentonite  cmol Cd per  pH  kg bentonite  0.0  0.0  5.0  0.0  6.13  5.0  0.0  6.17  1.2  0.2  0.0  0.0  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  4.1  8.6  5.88  1.2  0.4  8.9  7.2  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  0.5  5.42  4.8  2.1  0.4  0.3  13.7  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  2.2  1.8  13.4  2.3  5.39  4.8  2.1  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  7.1  5.35  6.8  5.35  4.8  2.4  8.9  7.5  12.1  4.8  2.4  8.9  7.5  12.1  190  Pb and Cd sorption of Forest soil in mass units Initial Pb cone. mgL  1  Final Pb cone. mgL  1  Sorbed Pb  Sorbed Cd  Final  m g Pb per g  m g Cd per g Forest soil  pH  Forest soil 0.0  11.9  0.0  3.07  Initial Cd cone. Final Cd cone. mgL-  1  0.0  mgL  1  250.0  12.1  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  11.6  4.3  3.03  250.0  17.7  250.0  164.6  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  83.8  39.0  0.8  2.81  1000.0  219.4  100.0  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  4.0  2.77  1000.0  248.3  500.0  419.5  37.6  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 i n m o l a r units Initial Pb cone. mmol L 1.2  1  Final Pb cone. mmol I/  0.1  1  Initial Cd cone. Final Cd cone. mmol L  1  mmol L  1  Sorbed Pb  Sorbed Cd  cmol Pb per cmol Cd per kg kg Forest soil Forest soil  Final PH  0.0  0.0  5.7  0.0  3.07  5.7  0.0  3.08  1.2  0.1  0.0  0.0  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  1.7  3.06  1.2  0.1  0.9  0.6  5.7  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  5.3  10.8  2.91  1.2  0.1  8.9  6.7  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 2.81  4.8  1.0  0.4  0.3  19.0  0.5  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 2.79  2.2  1.8  18.6  2.1  1.1  2.2  1.8  18.6  2.3  2.80  1.2  4.4  3.7  18.1  3.6  2.77  1.2  4.4  3.7  18.1  3.6  2.78  6.9  2.74  6.5  2.75  4.8  1.1  4.8 4.8 4.8 4.8  1.4  8.9  7.5  17.4  4.8  1.4  8.9  7.6  17.3  192 Pb and Cd sorption of Spruce bark i n mass units Initial Pb cone. Final Pb cone. Initial Cd cone. Final Cd cone. mgL  1  mgL  1  mgL  1  mgL  1  Sorbed Pb  Sorbed Cd  Final pH  m g Pb per g  m g Cd per g  Spruce bark  Spruce bark  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  78.0  11.1  1.1  3.90  250.0  27.8  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  444.6  0.0  -1.9  27.8  0.1  3.53 3.51  1000.0  100.0  1000.0  437.6  0.0  -0.1  28.1  0.0  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 3.53  1000.0  448.3  100.0  96.5  27.6  0.2  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 3.50  1000.0  488.4  500.0  478.6  25.6  1.1  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. mmolL  1  mmol L  1  mmol L  1  mmol L  _ 1  Sorbed Pb .  Sorbed Cd  cmol Pb per kg cmol Cd per kg Spruce bark  Spruce bark  Final pH  0.0  0.0  5.5  0.0  3.95  0.1  0.0  0.0  5.5  0.0  3.94  0.1  0.4  0.3  5.4  0.5  3.96  0.1  0.4  0.3  5.4  0.7  4.01 3.90  1.2  0.1  1.2 1.2 1.2 1.2  0.1  0.9  0.7  5.4  1.0  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  5.1  3.4  3.86  1.2  0.2  4.4  3.8  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  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 3.53  4.8  .  4.8  2.2  0.9  0.9  13.3  0.2  4.8  2.2  2.2  2.1  13.2  0.7  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  .  3.52  rH 0 0 CM o iri iri  OH  113 s  IN OS 0 0  o  ID CN iri iri  CN SO i n CN i n i n Os 0 0 rH Os SO 0 0 iri iri <*  CN CN Os Os OS Os  -*  ^ '  O O iri  CN CN iri  be cu  1g  • HH  I* T3  3  c  r  ! ' * o o o N i n N O i n CO CO rH  w>  s -o bo oi  I 01  I-a ^ 1 i<8 S * T3  t x i n c o o N s o c N O s o o c o o o o i n r H r H r H O i n i n c O C O C O C N i n c N  bo  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 mNNvdrtNNdinidHJdvdiri^ioiriiom  g rH 0 0 i n Os 0 0 0 0 CO iri OS iri r-i <# CN CN rH  > g l<8 w 3  so 00  o  rH  rH CN CN O IN i n CN o od CO iri CN rH rH rH rH rH rH  00  H O  u  C o u  13 ha  CO O  bo  s  CO iri i n sO SO rH rH rH  IN  CN rH IN rH  o rH rH SO O 00 o SO O SO  Os IN rH CN iri CO in SO 3 SO  -*  CO i n CN rH 0 0 IN rH CN CO  I N CN CO i n [N ON' IN CN ON ON SO 0 0 CO CO rH  rH 00  IN CO  •i u  C o  o  u  a •a .s  bO  3  rH CN i n O ON O O O CO CN rH O 0 0 CO OS CO CO i n so rH rH sO SO rH rH so NO  00  O  OS CN o so ON o CO CO  in  in  00  IN o CO  00  od CO  in  O  00  00  -*  sd iri iri ON IN CO CO CO CO rH ON  PH U  C o u  "(3  I-J  "* o  bO  Q  3  j  00  CN  CN  rH  in  ON CO  ON  rH  CO CO  CO CN  rH sd C O rH rH C N O rH C N rH C N CO  SO SO CO  ON ON  00  CO m CN rH O CO CO S O CO rH NO so t N N O  O CO  O  in  rH i n 'HH  ON  ON  S O  OS  rH rH  o u  3  13 •43  bo  3  o  00  ON  ON  SO ON ON rH  CM i n CN o tN CN tN  CN CO  IN  O  O  O  ON  00  ON  rH rH rH rH IN  IN in  K  tN  tN  00 00  rH CO CN so 00 <* CO tN OS 0 0 tN  -2.9  ,1 CO i n NO  CO t t ON  in  rH © as t N rH 00  •2 u  C o u  a 13 •43  bo  3  ON  IN IN  O  O Os IN CN rH IN  so o  rH CN 0 0 rH rH CO CN CO ON r-i 0 0 0 0 © rH 0 0 0 0 ON ON Os 0 0 O CN ON -#  -*  -*  u  C o u  IA 143  bO  3  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  CNOOrHOOrHOOrHOO  Os  "# d 00  CN CN - * CO t s [ s H J ^1 OO 0 0 OS OS rH rH  60 4* IO CO CO ^ 00 t o o » 00 N o co uo co i n os Os ^ CM O 00 CO •>* CO o i n co H oo a * iCO n CO CN CNT t i C N O T t i C O C O r H T t ri ri ri O l i ^  l-e l<8  73  l-e  o  s  o 00 44  3  i<8 o  ^ 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 C  6  T3 I OJ  o 60 4H i n 00 o LO CM CN N N H J c O N O S O O H N CO CO t s O OS Os r H rH IN rtl 00 r-i cd rH CN Os CN c d s d t N s d t N s d c N c d CN 00 O in  i<8 u o  u  OsOlNCvlCNrHcOCNsOcOrHsO SO LO CO SO s o •HI-^^jlLOsOLNOOOsinsOCOsO 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 to N Oi nc Oi nr i c cOc  13 u C o  u i—l  ia  00 CO i n i n i n Os O o CN Os CO CN CO o i CN Os © CN CN rH  o o  LO rH CO CO SO OS CO CN CN OS rH cd LO vO SO sd in CN  PH  in 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  o  l-c  1^  2 o  u hJ  13 l :  l  o  S  rH CN O Os LN co o i n co O IN LN IN sO_ CO If) t s r l r lCN rH rH rH r-H rH sd rHrHrHrHsbvOso'sD'^'^  22 P  00 LN oo IN SO rH rH CN CN • 9° ° * CO cd CN CN CO CO CN CN. tN tN LN SO  2 ™  O HI HI VO N LN tN CO 00 in r H  12  tN tN I N tN tN CO  CO CN CN CO 00 CO CN CN LN rH 00 * H  s  cj C o  u  |3 il  o  S £  o  u I *C> XI  LNLNSOLNintNT)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  o  oo f C N o C N i n i n - * <JI i n co CO CO CO CO CO Os Os - * CN CN CN CN CN CN O ©  VD 00 i n CO CO c d  II  rH IN CO CN CO CO  o m cd  tN tN CN HI CO CO  ON rH CO CO CO c d  <N CO o in CO VD CN HI CO c d c d c d CO c d  3 cd  3  SO in in CO c d CO c d  PH  ITS  I  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  01  i<8 » s B PH  I  O) 00  l«8  tj  oo g  ^  >H HO  f" ?H  l<8  r H O O s r H O O O C O s O O s HJdiriiri"*in'iriin'ri  C N t s E N O O s O i n c O C N C N ^NsoiricdtsiiriHJtv  S OH 60  I Ol  8  <" U  H  Its " " S  ^  o  l  o  s  ^  o  ^  ^  Os o  m  Os iri  60 S  o tN 00 00  VO so CM r H CO CM i r i vO SO 00 CO HI HI rH HI  in LN 00 CO  o iri Os CO  o 00 Os CO  00 CM Os CO  Os 00 LN 00 cd HI Os CM r H i n i n rH CO CM  00 CN SO CM  tN CO in CN  o Os OS iri in CM  60  in 00 vO rH  CM CN 00 rH  00 rH 00 rH  tN i n CN vd 00 i n r H tN  Os O o tN  SO IN 00 CO SO o CN cd LN IN CO >P i n CM i n i n SO CO IN CN IN tN HI HI HI HI  ~60  CM iri rH rH  00 od HI rH  in iri HI SO  in CN SO SO  rH CO CM rH  in 00 HI rH  in 00 SO VD  o 00 CO r H i n 00 IN tN 00 o o IN OS CO Os HI i n HI  rH  6  60  i n CO o 00 OS SO CO 00 O o HI VD  so 00 LN O Os i n  CN  cd 1  H!  rH Hi SO HI  o CM' Os rH  00 cd Os rH  IN cd Os rH  O O Os rH  ~60  SO Os Os rH  CN CN O CM  in Os ts LN  H IOs Os cd tN o LN CN  00 r H 00 H i Os rH  CO CM SO CO 00 so t s Os 00 O t s HI HI  SO r-i O CM  CO CN o 00  o  60  CN tN Os rH  CO o CN i r i O Os 00 rH  CO CN o 00  6  6  CO CN Os o rH CO  oi  00 ts in LN  co i n HI CO co i n LN tN  ts  CN SO SO HI  m  60  00 r-i tN LN  o iri SO 00  o cd EN HI  CO Os CO i n i n r-i sd SO CM EN EN HI Os HI HI -  o 00 vO CO  00 Hi Os rH  VD CN CM rH  rH O tN HI  r H CN 00 rH r H CO CM CO Os r-i 00 00 cd r-i 00 00 Os Os Os 00 O Os HI HI HI HI HI CM  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 t s 00 00 00 Os OS HI H I HI HI rH rH OS HI  197 00  I Ol o  01 u  in CM Os CO 00 CO CO CO r H S O H © in CO CO sO in in r H r-i o o © C) o i © © © O  in  K rH  Os O sO O Q  ©  Os so so  Os  rH  ^  oi o  •H*  o  in  o  in r-i  6 u  00 T3  X>  •s  CD U  o  3!  Os o in O CO in r H t N O O CO Os O r H 00 OS CM in CM I N Os CO so in o CM O so 00 CM 00 r H © C N C N Os Os iri CO 00 SO r H sd d 00 00 00 sd "* rH  IH  G CD u  I  OJ 00  (« so SO o  CM u  CO CO CN CO  CN  CO SO  •>*  ON  sO Os r H SO 00 Os C N in CO o CO O O in in o CO CM SO sO 00 CM C N ©i 00 00 iri tri iri iri CM  3  CH  s  CD  u  C o u  13 ,1  rH  00  CN  SO o CM sd sd SO sd 'HH  rH  CM CM  CM OS  SO sO  00 CM O  rH ^  CN C) oo  CO  CN  SO  00  ri  CC  u  G o 1-J  u  O  i3 s "(3 s  rH  00 r-i  CM CM ^ CM CO o Os o -# sO O CO « °°. in CO o CO r H CM CM CiMo o iri sd o  rH  sO  O  rH  CM sO 00 Os CO CM CM r H C N Os  CO sd sd sd sd iri r-i rH  ,1 o  u  I*  I OH  o  CO CM  IN  CN  oo  Tr*  rH  CM O Os  CN  00 CO CN Os ©  CN  •<HH  r-i ©  in o  CN  o ©  CM O CO C N CM CO C N in 00 S O in CN CN CN CM CO CM CM O r-i r-i r-i rH r-i d O CN  r-H  PH U  C o  u  CN in CO r H O CO CO CO o sO 00 C N in C N r H r H CM r H O CO O 00 r-i sd sd sd sd i  T"H  fl  §5  u  C o  u  s o ••c  •3 il o o  c «  a U A*  00 CO CO.  CM CNCO  CN  CO  00 CN  Os r H sO O  CN  CN  CN CN SO C N in C N o Os 00 Os CO Os 00 OS 00 o CN  o  s c  d  il  CO  d  CO  d  CO  d  CO  d  d  CN  iri  O  CN  CN  CN  CN  SO  CN  CN'  CN  CO*  CM  O  in t N  rH  rH  00  CM o CM in CO CO CO CO  •*'  CN CN CM CM'  O  198  APPENDIX E LEACHING TEST CALCULATIONS AND DATA  E.l. A V E R A G I N G THE HYDRAULIC CONDUCTIVITY, H E A V Y METAL BREAKTHROUGH, A N D DISCHARGE pH 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 CELL SAMPLE BASED O N B R E A K T H R O U G H CURVES 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 DISCHARGE pH DATA  199  APPENDIX E.l. A V E R A G I N G T H E HYDRAULIC CONDUCTIVITY, 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 DISCHARGE p H D A T A  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 i n the triplicate experienced erratic increases and decreases, but all three followed the same trend: they started at l o w values; increased over an order of magnitude between 175 m l and 400 m l of discharge (1 - 2.5 pore volumes); and then showed little change after 400 m l of discharge (« 2.5 pore volumes). The hydraulic conductivity data i n Figure E . l . l represents the typical difficulties i n averaging the triplicate data.  Discharge Volume (mL)  Triplicate # x Test 1  FIGURE E . l . l .  • Test 2  A Test 3  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 i n E X C E L 5.0 (Microsoft). Figure E . l . l shows the averaged curve plotted w i t h the triplicate data. The method used to combine the triplicate data i n Figure E . l . l was applied to all the hydraulic conductivity and heavy metal breakthrough curves. A s for the discharge p H curves, the initial portions were left i n 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 K a  O  X>  iri CO  o o o o  cf!  o o  g  CN  CO IN. SD C N  I "* I CO  tN CO SO  iri in  '11  '•§.1 3  in  cn  1%  1  ix  " 8  2 &  i5 CO CN CO SO CO  io U  cS 00  Os o 60  4-t  >s  ft  o in  M  >  ^  •xi ^  3  E '-g « ^  in  U  |u|  cu  IS  DH  1  w w  S3  cu xi  PQ  <  s  TJ CC  DH TJ  201  Calculations The best-fit equation used to calculate the log-shaped portion of the hydraulic conductivity curves is, k = [m • Ln(Dv) + b ] • 0.000000001 k  k  where k (m/s) is hydraulic conductivity, mk and bk are best-fit parameters, D (ml) is the discharge volume, and 0.000000001 is a scaling factor. v  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 ( m g / L ) is the heavy metal breakthrough concentration, and mc and b are best-fit parameters. c  The best-fit equation used to calculate the straight-line portion of the discharge p H curves is, p H = m H • Dv + b H P  P  where m H and b H are best-fit parameters. P  P  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 LEACHING CELL SAMPLE BASED O N B R E A K T H R O U G H CURVES  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: Qb  = Qr - Q a - Qab  where Q b (mg) is the amount of heavy metal retained after D b of discharge, Q r (mg) is the total input of heavy metal after D b of discharge, Q (mg) is the amount of heavy metal discharged after D of discharge, and Q b (mg) is the amount of heavy metal discharged between D and D b of discharge. a  a  a  a  The equation for calculating Q r (mg) is, Q T = 500 • ( D - 1 7 5 ) B  1000  where 500 ( m g / 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 Q a (mg) is, Qa = C • D a  a  1000  where C ( m g / L ) is the breakthrough concentration of the initial portion, and D (ml) is the discharge volume i n which the log-shaped portion begins. a  a  203 The equation for calculating Q b (mg) is, a  Q a b = arte • D b • L n ( D b ) - mc • D b + b  c  • D b l - Tmc • D  a  • L n ( D ) - nv • D a + b a  c  • Dal  1000 where mc and b (see Table E . l . l ) are best-fit parameters for the log-shaped portion. c  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 BREAKTHROUGH, A N D DISCHARGE pH 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 conductivity  ml  hr  m/s  2.2  125  2.12E-11  11.2  231  3.12E-11  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  5.4  76  3.06E-11  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  volume Testl  Test 2  Discharge PH  8.49  8.31  Forest soil admix permeated with blank (0.01 M (Ca(NC>3)z) leachate Triplicate #  Cumulative discharge  Time  Hydraulic conductivity  ml  hr  m/s  volume Test 1  Discharge pH  3.5  188  8.79E-11  9.2  264  3.08E-11  11.4  338  15.4  422  4.28E-11  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  8.24  Spruce bark admix permeated with (0.01 M (Ca(N03h) leachate Triplicate #  Cumulative discharge  Time  volume ml Testl  Test 2  Hydraulic conductivity  hr  m/s  Discharge pH  5.6  281  2.21E-11  11.8  369  1.46E-11  17.1  469  1.28E-11  22.1  593  2.54E-11  26.5  643  1.93E-11  31.6  748  1.45E-11  35.7  831  5.24E-12  39.0  926  1.26E-11  45.6  1044  1.72E-11  50.0  1095  2.33E-12  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  1.5  135  1.51E-11  6.1  207  2.06E-11  12.8  281  2.37E-11  19.6  369  1.69E-11  25.6  469  1.41E-11  31.4  593  3.12E-11  36.6  643  2.21E-11  43.0  748  1.91E-11  48.4  831  6.66E-12  52.7  926  1.60E-11  57.9  1044  8.63E-12  60.3  1095  3.16E-12  64.3  1170  2.36E-11  8.51 8.60 8.58  8.48  8.56 8.65 8.57 8.65 8.44  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  PH mg/L  hr  m/s  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  0.0  ml  626  4.56E-11  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 6.18  66.9  Test 2  Pb cone. Discharge  conductivity  discharge volume Testl  Hydraulic  446.3  1544  1.76E-09  185.0  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 6.02  959.7  1619  4.32E-09  362.1  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  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  31.6  308  4.81E-11  49.0  476  4.52E-11  0.0  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  8.53 8.61 8.61  Triplicate #  Cumulative  Time  Hydraulic  Pb cone.  conductivity  discharge volume  Discharge PH  ml  hr  m/s  mg/L  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  0.0  8.09  Test 2 continued  Test 3  12.0  9  5.39E-11  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  discharge volume Testl  Hydraulic  Cu cone.  conductivity  Discharge pH  ml  hr  m/s  mg/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 5.60  212.9  261  2.11E-09  290.2  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  # Testl  Test 2  Cumulative  Time  Hydraulic  Pb cone.  conductivity  discharge volume  Discharge PH  ml  hr  m/s  mg/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  5.0  0  3.42E-08  16.5  3  8.80E-09  39.0  6  1.87E-08  3.4  6.13 5.95  69.5  10  4.81E-09  17.3  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.  pH  conductivity  discharge volume  Discharge  ml  hr  m/s  mg/L  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 5.35  Test 2 continued  Test 3  903.3  249  3.12E-09  229.0  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  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  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  166.0  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  # Testl  Test 2  Hydraulic  Pb  Discharge  discharge volume  conductivity  cone.  PH  ml  hr  m/s  mg/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  350.8  4.32  Cumulative  Time  578.0  177  1.05E-09  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  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 4.40  575.5  375  1.17E-09  392.4  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  890  1.78E-09  480.5  4.30  3024.6  Spruce bark admix permeated with 500 mg/L ofPb leachate Triplicate  #  Cumulative  Test 2  Pb cone.  conductivity  discharge volume  Discharge PH  mg/L  hr  m/s  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  ml Testl  Hydraulic  Time  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 7.33  129.4  613  3.47E-11  13.5  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 5.90  1883.8  1222  1.40E-09  466.7  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 5.98  3565.7  1530  7.19E-10  429.5  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  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  301  9.49E-12  0.1  8.30  16.3  .  Triplicate  #  Cumulative  Time  Hydraulic  Pb cone.  conductivity  discharge volume  Discharge PH  ml  hr  m/s  mg/L  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  Test 2 continued  Spruce bark admix permeated with 500 mg/L ofCu leachate Triplicate  # Testl  Hydraulic conductivity  C u cone.  ml  hr  m/s  mg/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  5.8  8.35  560  1.70E-10  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  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  888  1.29E-09  363.2  5.58  1026.1  Test 3  PH  69.0  372.8  Test 2  Discharge  Time  Cumulative discharge volume  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  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  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  5.3  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.  conductivity  discharge volume  Discharge PH  mg/L  ml  hr  m/s  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  Test 3 continued  Binary heavy metal leachates - lead (Pb) & copper (Cu)  Bentonite admix permeated with 500 mg/L ofPb & Cu leachate Triplicate  Cumulative  #  discharge volume  Testl  Time  Hydraulic  Pb cone.  CM cone. Discharge  conductivity  PH  ml  hr  m/s  mg/L  mg/L 8.15  18.0  13  5.00E-10  0.1  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 5.48  371.3  257  2.06E-09  213.6  313.2  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 5.21  798.8  349  3.36E-09  289.5  367.0  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  #  discharge volume  Testl  Time  Cu cone.  Discharge PH  hr  m/s  mg/L  mg/L  10.3  32  7.91E-10  21.1  113.3  4.70  3.77E-10  14.0  141.4  4.77  46  1.28E-09  48.6  198.5  4.66  58  4.99E-10  23.0  175.4  4.73  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  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  39  46.8 74.5 93.0  Test 3  Pb cone.  ml 25.5  Test 2  Hydraulic conductivity  .  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  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 5.25 5.37  140.5  200  2.83E-10  7.9  118.6  163.0  225  2.28E-10  5.7  109.6  185.5  246  3.07E-10  7.7  142.5  216.0  267  4.66E-10  5.17 4.79  Triplicate #  Cumulative discharge volume  Time  Hydraulic conductivity  Pb cone.  Cu  Discharge  cone.  PH  mg/L  mg/L  hr  m/s  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  ml Test 3 continued  Spruce bark admix permeated with 500 mg/L ofPb & Cu leachate Triplicate  Cumulative  #  discharge volume  Testl  Test 2  Test 3  Time  Hydraulic  C u cone.  mg/L  mg/L  0.9  0.4  6.72 7.17  conductivity  ml  hr  4.0  53  rh/s  Discharge  Pb cone.  PH  15.3  89  1.79E-10  1.9  1.6  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  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  6.5  89  1.61E-10  1.0  0.7  7.12  18.6  150  1.87E-10  1.3  2.2  8.01  1.6  2.8  8.33  27.7  196  1.19E-10  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  372.4  475.2  5.26  512.5  413  2.10E-09  Ternary heavy metal leachate - lead (Pb), copper (Cu), & cadmium (Cd)  Bentonite admix permeated with 500 mg/L ofPb, Cu, & Cd leachate Triplicate  Cumulative  #  discharge volume  Testl  Hydraulic  Pb  Cu  Cd  Discharge  conductivity  cone.  cone.  cone.  pH  mg/L mg/L mg/L  ml  hr  m/s  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  104.0  244.7  283.4  5.68  167.6  160  5.74E-10  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  262.3  381.5  401.8  5.16  701.0  279  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  379.0  407.2  424.6  5.11  337  1.08E-09  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  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  0.0  2.2  26.6  7.63 . 6.76  1082.5  Test 2  Time  2.35E-10  44.6  84  3.56E-10  0.4  7.9  52.7  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 5.53  313.1  195  6.58E-10  38.5  315.3  338.9  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  414.6  427.5  5.20  838.0  299  1.08E-09  324.9  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  #  discharge volume  Time  Hydraulic conductivity  Pb cone.  Cu cone.  Cd cone.  Discharge pH  mg/L mg/L mg/L  ml  hr  m/s  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  Test 2 continued  223  APPENDIX F SELECTIVE SEQUENTIAL EXTRACTION CALCULATIONS AND DATA  F.l. A C C U R A C Y OF THE SELECTIVE SEQUENTIAL E X T R A C T I O N PROCEDURE 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 RESULTS FOR 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  224 A P P E N D I X F . l . A C C U R A C Y OF T H E SELECTIVE SEQUENTIAL EXTRACTION PROCEDURE 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  Bentonite Cu 1st  H M * analyzed  CM  Recovery  W?/g soil  Total cone. H M extracted using SSE ug/g soil  567  574  101%  541  565  105%  Total cone, of H M sorbed  Cu 2nd  CM  Pblst  Pb :  1803  1604  89%  Pb2nd  Pb  1687  1760  104%  Pb+Cu 1st  Cu  439  423  96%  Pb+Cu 1st  Pb  1166  1174  101%  Pb+Cu 2nd  Cu  455  449  99%  Pb+Cu 2nd  Pb  1354  1238  91%  Pb+Cu+Cd 1st  Cd  487  267  55%**  Pb+Cu+Cd 1st  Cu  861  378  44%**  Pb+Cu+Cd 1st  Pb  1211  1079  89%  Pb+Cu+Cd2nd  Cd  469  264  56%**  Pb+Cu+Cd2nd  Cu  958  367  38%**  Pb+Cu+Cd2nd  Pb  1140  1090  96%  Forest  Cu 1st  Cu  859  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  1337  1252  94%  Pb+Cu 2nd  Cu  619  523  85%  Pb+Cu2nd  Pb  1356  1280  94%  Spruce  Cu 1st  Cu  591  599  101%  bark  Cu 2nd  Cu  642  552  86%  admix  Pblst  Pb  n/a  1268  n/a  Pb2nd  Pb  n/a  1297  n/a  Pb+Cu 1st  Cu  412  399  97%  Pb+Cu 1st  Pb  756  825  109%  Pb+Cu 2nd  Cu  554  389  70%  Pb+Cu 2nd  Pb  846  803  95%  admix  * 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 O F ADMIXES BASED O N B A T C H ADSORPTION RESULTS FOR INDIVIDUAL MATERIALS  The calculations for the sorption capacities of the admixes are, CjBentonite admix  —  qForest soil admix  =  qSpruce bark admix  CjBentonite CjBentonite ' 7/8 —  + qForest soil  CjBentonite * 7/ 8 + qSpruce bark  '1/8 '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,  Inputs: 500 mg/L of Pb, Cu, and Cd.  qbentonite qForest soil  Sorption equations for different combinations of Pb, Cu, and Cd.  qSpruce bark  where the sorption equations are taken from section 4.2.1.4.  The compositions of the admixes are, = 100:8 sand and bentonite Bentonite admix = 100:7:1 sand, bentonite, and Forest soil Forest soil admix Spruce bark admix = 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 Center  Edge  Layer 1 2 3 4 1 2 3 4  Exchangeable ug/gsoil 804 76 476 470 679 2 1 1  Carbonates Ug/gsoil 638 257 402 363 401 23 2 3  Hydroxides ug/gsoil 96 18 74 71 83 7 1 3  Organics ug/gsoil 25 3 10 12 11 5 0 0  Residue ug/gsoil 6 0 0 2 0 29 0 0  Exchangeable ug/gsoil 7 6 4 3 13 0 3 1  Carbonates Ug/gsoil 290 68 18 55 151 1 0 1  Hydroxides ug/gsoil 286 82 167 24 111 1 1 9  Organics ug/gsoil 20 6 6 2 9 0 0 1  Residue ug/gsoil 10 4 7 1 4 1 1 2  TEST 2 Location Center  Edge  Layer 1 2 3 4 1 2 3 4  Bentonite admix permeated with 500 mg/L ofCu leachate  TEST 1 Location Center  Edge  Layer Exchangeable Ug/gsoil 378 1 2 372 308 3 339 4 1 220 2 0 146 3 69 4  Carbonates ug/gsoil 116 142 146 133 112 7 19 90  Hydroxides Ug/gsoil 30 24 23 24 24 5 11 20  Organics ug/g soil 5 4 3 5 3 1 3 3  Residue ug/gsoil 5 5 8 4 1 3 1  228 Forest soil admix permeated with 500 mg/L ofPb'leachate  TEST1 Location Center  Edge  Layer Exchangeable ug/gsoil 7 1 2 2 14 3 4 3 32 1 2 1 1 3 5 4  Carbonates ug/g soil 131 16 238 5 302 0 0 89  Hydroxides ug/gsoil 34 11 64 6 61 1 1 26  Organics Ug/gsoil 15 3 31 2 41 0 0 16  Residue ug/g soil  Layer Exchangeable ug/g soil 1 241 2 48 1 3 4 127 403 1 2 0 3 3 4 15  Carbonates ug/gsoil 695 377 4 493 999 2 4 206  Hydroxides ug/g soil 192 96 0 122 215 1 1 64  Organics ug/gsoil 68 49 0 54 109 0 2 34  Residue ug/gsoil  Layer Exchangeable ug/gsoil 494 1 1 2 1 3 4 1 1 769 2 64 1 3 23 4  Carbonates ug/g soil  Hydroxides ug/gsoil  Residue ug/gsoil  754 1 1 2 885 411 1 285  143 1 1 3 209 78 1 55  Organics ug/g soil 60 2 1 1 75 37 2 23  TEST 2 Location Center  Edge  TEST 3 Location Center  Edge  2 0 0 0 0 0 0 0  Forest soil admix permeated with 500 mg/L ofCu leachate  TEST1 Location  Composite  Layer  Exchangeable  Carbonates  Hydroxides  Organics  Residue  u g / g soil  u g / g soil  u g / g soil  u g / g soil  u g / g soil  1  295  243  100  42  23  2  3  48  26  29  11  3  1  23  16  21  12  4  30  125  49  37  16  Layer  Exchangeable  Carbonates  Hydroxides  Organics  Residue  U g / g soil  u g / g soil  u g / g soil  u g / g soil  u g / g soil  49  25  TEST 2 Location  Composite  1  391  237  124  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 Center  Edge  Layer  Exchangeable  Carbonates  Hydroxides  Organics  Residue U g / g soil  u g / g soil  U g / g soil  u g / g soil  U g / g soil  1  156  1533  56  150  2  1  4  3  0  3  2  54  7  22  4  56  534  55  59  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  Center  Edge  Carbonates  Hydroxides  Organics  Residue  U g / g soil  U g / g soil  u g / g soil  U g / g soil  u g / g soil  205  361  30  47  7  2  3  49  12  12  6  3  1  4  1  3  1  4  80  137  42  21  5  1  156  271  32  43  5  28  7  Layer  1  Exchangeable  52  154  25  3  33  108  21  19  6  4  162  144  56  33  4  2  230  TEST 2 Location  Layer  Exchangeable ug/gsoil  Center  Edge  182 0 0 1 67 0 0 1  1 2 3 4 1 2 3 4  Carbonates ug/gsoil  Organics  Residue  Ug/gsoil  Ug/gsoil  ug/gsoil  201 1 0 0 41 1 1 3  29 3 1 5 23 2 2 4  4 2 0 2 9 0 1 2  Hydroxides  . 150 3 1 2 229 2 3 13  Binary heavy metal leachates ofPb and Cu  Bentonite admix permeated with 500 mg/L ofPb & Cu leachate  TEST1 Location  Center  Edge  Layer  1 2 3 4 1 2 3 4  Residue  Organics ug/gsoil  Carbonates Ug/gsoil Pb Cu  Hydroxides  Ug/gsoil Pb Cu  ug/gsoil Pb Cu  Pb  Cu  703 191 19 520 519 75 359 257  335 99 40 260 135 59 126 120  115 57 19 85 123 38 98 72  14 6 1 10 12 2 8 6  5 4 2 5 4 3 3 4  Exchangeable  280 154 24 182 334 92 231 177  97 100 79 120 99 92 94 115  25 24 21 31 30 26 27 29  ug/gsoil CM  7 3 2 5 5 3 2 3  2 3 3 3 4 2 1 2  Forest soil admix permeated with 500 mg/L ofPb & Cu leachate  TEST 1 Location  Composite  Layer  1 2 3 4  Exchangeable  Carbonates  ug/gsoil  Ug/gsoil CM Pb  Pb  CM  540 29 2 17  274 20 15 1  361 117 37 91  167 84 85 19  Hydroxides  Organics  Residue  ug/gsoil CM  ug/gsoil CM Pb  u g / g soil Pb Cu  74 39 37 11  29 14 9 13  Pb 139 37 17 27  37 30 32 19  0 0 0 0  16 13 10 8  231 TEST 2 Location  Composite  Layer  1 2  Exchangeable  Carbonates  Hydroxides  Organics  Residue  U g / g soil  u g / g soil  u g / g soil  u g / g soil  u g / g soil  Pb  CM  Pb  CM  Pb  C M  Pb  CM  Pb  Cu  293  154  282  143  77  52  18  35  4  19  30  19  17  5  21  1  10  4  2  54  3  3  1  37  14  15  8  3  17  1  8  4  52  34  154  106  46  41  14  36  1  12  TEST 3 Location  Composite  Layer  Exchangeable  Carbonates  Hydroxides  Organics  Residue  u g / g soil  U g / g soil  u g / g soil  u g / g soil  U g / g soil  Pb  Cu  Pb  CM  Pb  CM  Pb  CM  Pb  Cu  1  212  151  216  151  72  61  19  37  0  13  2  1  0  13  14  8  7  4  16  0  9  6  9  3  6  11  0  7  44  18  23  9  25  0  10  3  1  1  12  4  4  3  41  Spruce bark admix permeated with 500 mg/L ofPb & Cu leachate TEST 1 Location  Center  Layer  Exchangeable  Carbonates  Hydroxides  Organics  Residue  u g / g soil  u g / g soil  n g / g soil  u g / g soil  u g / g soil  CM  Pb  CM  29 1  35  53  13  0  0  2  117  18  40  38  13  121  6  16  36  11  0  0  1  0  0  1  179  134  11  23  47  11  Pb  CM  Pb  C M  1  121  114  208  193  2  1  1  0  1  4  36  37  110  1  23  28  120  2  1  0  54  39  Pb  Pb  Cu  O  O  Edge  o 4  TEST 2 Location  Layer  Exchangeable u g / g soil  Center  Edge  Carbonates u g / g soil  Hydroxides u g / g soil  Organics  Residue  u g / g soil  u g / g soil  Pb  CM  Pb  CM  Pb  CM  Pb  CM  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  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  Pb  Cu  232 TEST 3 Location  Center  Edge  Layer  Exchangeable  Carbonates  Ug/gsoil  Ug/gsoil  Residue  Organics  Hydroxides  ug/gsoil  u g / g soil  ug/gsoil  CM  Pb  CM  Pb  CM  Pb  Cu  Pb  CM  Pb  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 3  4  1  1  18  16  5  9  3  5  1  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  183  104  23  31  39  11  4  8  4  38  53  Ternary heavy metal leachate ofPb, Cu, and Cd  Bentonite admix permeated with 500 mg/L ofPb, Cu, and Cd leachate TEST 1 Location  Layer  Exchangeable  Hydroxides  Organics  Residue  ug/gsoil  ug/gsoil  ug/gsoil  ug/gsoil  ug/gsoil  Composite  Carbonates  Pb  Cu  Cd  Pb  Cu Cd  Pb  Cu Cd  Pb  Cu  Cd  Pb  CM  1  592  250  239  168  82  5  93  27  3  24  7  3  0  2  2  122  119  186  68  72  7  40  22  2  12  6  2  0  3  69  45  113  60  48  2  25  16  2  6  3  1  1  4  152  103  156  78  69  4  34  19  2  9  5  1  0  Cd 0  4  0  3  0 3  0  TEST 2 Location  Layer  Exchangeable ug/gsoil  Composite  Carbonates ug/gsoil  Hydroxides  Organics  ug/gsoil  Residue  ug/gsoil  ug/gsoil  Pb  CM  Cd  Pb  CM  Cd  Pb  CM  Cd  Pb  CM  Cd  Pb  Cu  Cd  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