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Environmental effects of copper mine tailings reclamation with biosolids : Field and laboratory experiments Renken, Karin 1995

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ENVIRONMENTAL EFFECTS OF COPPER MINE TAILINGS RECLAMATION WITH BIOSOLIDS - FIELD AND LABORATORY EXPERIMENTS by KARIN RENKEN B.Sc. (Hon. Phys.), University of Victoria, 1984 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES DEPARTMENT OF BIO-RESOURCE ENGINEERING We accept this thesis as conforming to the required standard THE UNIVElWTY OF BRITISH COLUMBIA April 1995 © Karin Renken, 1995 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of T£)iO- jZ&SQUjrCe~ ^ ^ g f dn€-€-T~i7)cj The University of British Columbia Vancouver, Canada Date Tfarfl 2Z-/SSS~ DE-6 (2/88) II ABSTRACT Anaerobically digested biosolids (treated sewage sludge) were applied to copper mine tailings (pH 8.0) in Princeton, B.C. to determine how well biosolids could achieve land reclamation on a site prone to wind erosion in a semi-arid climate (350 mm mean annual precipitation). In October 1992, biosolids at 62, 77 (two plots), and 179 dry tonnes/ha (dt/ha) were applied to 0.5 ha plots. In the first growing season, vegetation established on all plots without irrigation, and the 77 dt/ha treatment led to the best vegetation quality and yield (5500 kg/ha). Trends in the first growing season included: lower foliar Mo concentrations, higher foliar Cu:Mo ratios, decreased soil pH, and increased concentrations of TKN, NH4-N, NO3-N, Total P, Bray P-1, Total Fe, and Total Hg with increasing application rates. Nitrate in the tailings below 60 cm was negligible. Metal concentrations were below the CCME criteria (1991) for agricultural and residential soils except for Cu. Associated with the field trial were laboratory leaching experiments consisting of two runs of 26 columns and one run of 10 pots testing application rates of 0, 30, 100, and 300 dt/ha biosolids. Leaching experiments primarily estimated the magnitude of nitrate leaching, the mineralization rate of biosolids, and the behaviour of metals. The first column run was conducted under wetter conditions than the other trials. Under wetter conditions, the leaching of nitrate, TKN, and TP was minimal. Under dryer conditions, TKN leaching was below 0.6 kg/ha for all columns except col. H (103 kg/ha), and nitrate leaching was less than 0.4 kg/ha for all columns except col. G (123 kg/ha) and col. H (79 kg/ha). The high nitrate concentrations were probably due to a preferential flow. Mineralization rates ranged from 17 to 31 % for the wetter run (10 weeks) and from 29 to 43% for the dryer run (13 weeks). Mineralization was highest for 30 dt/ha treatments. For the 300 dt/ha treatments, soil mineral N ranged from 200 to 745 kg/ha under wetter conditions and from 1200 to 3000 kg N/ha under dryer conditions. Nitrogen losses increased with application rate (30-34% of added N was lost for 300 dt/ha biosolids). Metal concentrations were below the CCME criterion for residential use except for Cu. iii TABLE OF CONTENTS ABSTRACT ii TABLE OF CONTENTS iii LIST OF TABLES vi LIST OF FIGURES vii ACKNOWLEDGEMENT viii 1.0 INTRODUCTION • 1 2.0 LITERATURE REVIEW 4 2.1 Nutrients 5 2.1.1 Nitrogen 5 2.1.1.1 Mineralization and Immobilization of N 8 2.1.1.2 Nitrification 9 2.1.1.3 Denitrification 11 2.1.1.4 Volatilization 12 2.1.1.5 Nitrogen Fixation 13 2.1.1.6 Nitrate in Feed 14 2.1.2 Phosphorus 15 2.2 Metals in Vegetation 15 2.3 Metals in Soil 18 2.4 Biosolids and Pathogens 21 2.5 Nitrate Leaching in Soil Columns 22 3.0 METHODS AND MATERIALS - LABORATORY EXPERIMENTS 24 3.1 Overview of Leaching Experiments 24 3.2 Water Regime 26 3.3 Column Design 29 3.4 Loading and Saturation of the Soil Columns 29 3.5 Emptying of Soil Columns 34 3.6 Sample Collection & Data Analysis - Leaching Experiments 34 3.7 Methods of Data Analysis 37 3.7.1 Factorial Model 38 3.7.2 Main Effects Model 39 4.0 DISCUSSION OF RESULTS - LEACHING EXPERIMENTS 40 4.1 Laboratory Observations 41 4.2 Nitrogen, pH and Electrical Conductivity in Soil 42 4.2.1 Nitrogen, pH, and EC in Soil - Leaching Run 1 42 4.2.2 Nitrogen, pH, and EC in Soil - Leaching Run 2 45 4.3 Mineral Nitrogen 47 4.3.1 Mineral Nitrogen - Leaching Run 1 47 4.3.2 Mineral Nitrogen - Leaching Run 2 48 4.4 Soil Nitrogen Balance - Leaching Experiments 50 4.5 Metals in Soil 56 4.5.1 Metals in Soil - Leaching Run 1 56 4.5.2 Metals in Soil - Leaching Run 2 (Soil Columns) 57 iv 4.6 Leachate Quality 60 4.6.1 Leachate Quality - Leaching Run 1 61 4.6.1.1 Leachate Quality - Run 1 - Nitrate 61 4.6.1.2 Leachate Quality - Run 1 - TKN 61 4.6.1.3 Leachate Quality - Run 1 - TP 63 4.6.1.4 Leachate Quality - Run 1 - pH and EC 64 4.6.2 Leachate Quality - Leaching Run 2 64 4.6.2.1 Leachate Quality - Run 2 - Nitrate 64 4.6.2.2 Leachate Quality - Run 2 - TKN 67 4.6.2.3 Leachate Quality - Run 2 - TP 68 4.6.2.4 Leachate Quality - Run 2 - pH and EC 68 4.7 Sampling and Analytical Errors in the Leaching Experiment 70 5.0 SUMMARY OF MAIN RESULTS - LEACHING EXPERIMENTS 72 6.0 METHODS AND MATERIALS - FIELD EXPERIMENT 77 6.1 Plot Treatments 77 6.2 Soil Sample Collection and Analysis 80 6.3 Vegetation Samples and Data Collection 82 6.4 Methods and Limitations of Data Analysis - Field Experiment 83 7.0 DISCUSSION OF RESULTS - TAILINGS PROJECT 84 7.1 Field Observations 85 7.2 Vegetation in the First Growing Season 85 7.3 Soil Fertility (0-15 cm Layer) 88 7.4 Soil Nitrogen and Phosphorus 91 7.4.1 Nitrogen Balance and Summary 94 7.5 Total Metals in Soil 97 7.6 Problems and Errors in Sample Collection of Field Samples 98 8.0 SUMMARY OF MAIN RESULTS - FIELD EXPERIMENT 103 9.0 CONCLUSION 105 10.0 RECOMMENDATIONS 107 LITERATURE CITED 109 APPENDIX A Environmental Data for Princeton, B.C 114 APPENDIX B Biosolids Characteristics & Seed Mix 118 APPENDIX C Leaching Experiments - Water & Temperature Information 121 APPENDIX D Leaching Run 1 - Soil Nitrogen, pH, and EC 131 APPENDIX E Leaching Run 2 - Soil Nitrogen, pH, and EC 143 APPENDIX F Leaching Run 1 - Total Metals in Soil 157 APPENDIX G Leaching Run 2 - Total Metals in Soil 163 APPENDIX H Leaching Run 1 - Nitrogen, TP, pH, and EC in Leachate 170 V APPENDIX I Leaching Run 2 - Nitrogen, TP, pH, and EC in Leachate 178 APPENDIX J Field Experiment - Bulk Density & Particle Size Distribution 189 APPENDIX K Field Experiment - Vegetation 192 APPENDIX L Field Experiment - Soil Fertility 203 APPENDIX M Field Experiment - Soil Nitrogen and Total Phosphorus 212 APPENDIX N Field Experiment - Total Metals in Soil 241 APPENDIX O Laboratory Methods 249 APPENDIX P Photographs 255 vi LIST OF TABLES TABLE 1 BACTERIA LEVELS IN BIOSOLIDS (GVRD, 1993a) 5 TABLE 2 BIOSOLIDS CHARACTERISTICS - LABORATORY EXPERIMENTS ....25 TABLE 3 WATER REGIME FOR THE LEACHING EXPERIMENTS 28 TABLE 4 SOIL NITROGEN, pH, EC - RUN 1 43 TABLE 5 SOIL NITROGEN, pH, EC - RUN 2 46 TABLE 6 MINERAL N IN SOIL - LEACHING EXPERIMENTS 49 TABLE 7 SOIL NITROGEN BALANCE - LEACHING EXPERIMENTS 52 TABLE 8 PERCENT OF ADDED N AS MINERAL N AND UNACCOUNTED N 55 TABLE 9 TOTAL METALS IN SOIL - RUN 1 58 TABLE 10 TOTAL METALS IN SOIL - RUN 2 59 TABLE 11 NITRATE IN LEACHATE - RUN 1 ...62 TABLE 12 TKN IN LEACHATE - RUN 1 62 TABLE 13 NITRATE IN LEACHATE - RUN 2 66 TABLE 14 TKN IN LEACHATE - RUN 2 69 TABLE 15 BIOSOLIDS TREATMENTS - FIELD EXPERIMENT 78 TABLE 16 BIOSOLIDS CHARACTERISTICS - FIELD EXPERIMENT 78 TABLE 17 SEED MIX USED IN THE PRINCETON DEMONSTRATION PROJECT 78 TABLE 18 TAILINGS VEGETATION 87 TABLE 19 SOIL FERTILITY RESULTS 90 TABLE 20 NITROGEN AND PHOSPHORUS RESULTS (GVRD) - FIELD EXPERIMENT ........ 92 TABLE 21 NITROGEN BELOW 60 cm - FIELD EXPERIMENT 95 TABLE 22 TOTAL METALS IN SOIL - FIELD EXPERIMENT 99 vii LIST OF FIGURES FIGURE 1 SIMPLIFIED NITROGEN CYCLE 7 FIGURE 2 COLUMN SETUP FOR ONE LEACHING RUN 30 FIGURE 3 COLUMN DESIGN FOR'45 cm'COLUMN 31 FIGURE 4 LOCATION OF FIELD SITES IN PRINCETON, B.C 79 FIGURE 5 PLOTS 2a, 2b, 3a, AND 3b (MAY 13, 1993) ...256 FIGURE 6 PLOTS 2a, 2b, 3a, AND 3b (MAY 23, 1993) 256 FIGURE 7 PLOTS 2a, 2b, 3a, AND 3b (AUG. 19, 1993) 256 FIGURE 8 PLOT 2a - 77 dt/ha (AUG. 19, 1993) 257 FIGURE 9 PLOT 3a - 179 dt/ha (AUG. 19, 1993) 257 FIGURE 10 UNSEEDED CONTROL PLOT - 0 dt/ha (AUG. 19, 1993) 257 FIGURE 11 LEACHING RUN 2 - COLUMNS H AND I 258 FIGURE 12 LEACHING RUN 2 - COLUMN SETUP 258 FIGURE 13 LEACHING RUN 2 - COLUMNS 1 THROUGH 5 258 ACKNOWLEDGEMENT The successful completion of this thesis could not have been realized without the cooperation of numerous people. I would like to thank my committee members for being approachable and helpful in the various stages of this project. My special thanks goes out to Dr. Sie-Tan Chieng for his continued lessons, assistance, advice, and encouragement throughout my studies, and to Dr. Art A. Bomke for his advice and critical reviews, especially in the last stage of the thesis preparation. I would also like to thank the Greater Vancouver Regional District, especially Craig C. Peddie, for their willingness to accept research proposals from students, for their financial support, and for getting me involved with the Princeton Demonstration Projects. For their contributions to particular project phases I would like to thank Micheal D. Van Ham (U.B.C. Forestry, proposal preparation), Donna Salahub (GVRD, project engineer), Dr. Lawrence E. Lowe (U.B.C. Soil Science, soil chemistry), Dr. Ping Liao and Adeline Low and Yuncai Gao (U.B.C. BIOE, laboratory methods and interpretation of results), Peter Zadorozny (GVRD, laboratory methods), J . Pehlke and Neil Jackson (U.B.C. BIOE, column setup), Tom Smith and Arlene Daniels (GVRD, field work), Dr. Antal Kozak (U.B.C. Forestry, statistical analysis), and Katherine Prairie (U.B.C. BIOE and U.B.C. Budget & Planning, statistical analysis). I would like to dedicate this thesis to my parents, Jan and Lotte Renken, as a token of appreciation for their life-long support and encouragement of self-directed work. Finally, I would like to thank my husband Steve for his patience and proofreading. 1 1.0 INTRODUCTION The revegetation of mine spoils can only be achieved with difficulty. The major difficulty in mine reclamation lies in the establishment of a nitrogen mineralization cycle. Mine tailings are generally low in organic matter which contributes to the soil characteristics of low nitrogen content, low moisture retention, low infiltration rate, and high bulk density all of which hamper plant establishment and growth (Hall and Vigerust, 1983). Low nitrogen content and low organic matter are correlated since the majority of nitrogen in soils is in organic form (Salisbury and Ross, 1992). Conventional mine reclamation techniques involve regrading of tailings where appropriate which may be followed by deep cultivation and/or spreading of overburden before the application of inorganic fertilizer and a mixture of grass and legume seeds. Mulch may also be added to the soil surface to add moisture holding capacity and to provide wind protection. Common practice in B.C. has been to fertilize and seed tailings directly without overburden or mulch, but with repeated fertilizer applications. Stroo and Jencks (1982) found mine spoils reclaimed with fertilizer, seed, and mulch were initially productive, but that little nitrogen (N) tended to remain in the soil which made repeated refertilization and reseeding necessary to achieve plant establishment. Studies have shown that periodic maintenance fertilizations seem to be necessary until the ecosystem has accumulated at least 1000 kg N/ha (Hall and Vigerust, 1983). Another mine reclamation technique uses biosolids (municipal sewage sludge) instead of inorganic fertilizer to facilitate plant establishment and growth. The organic matter in biosolids contains nutrients, especially N and phosphorus (P), and microorganisms and their metabolites. Biosolids have the ability to complex metals and nutrients and are a longer term source of nutrients than inorganic fertilizers as most N in biosolids is in organic form and is not available for plant use until it is mineralized. Microbial processes like mineralization and biosynthesis are particularly enhanced in the rhizosphere after biosolids application and both improve mineral nutrition and enhance plant growth (Tomati et al., 1984). Biosolids can act as a mulch as well. Sopper (1993) summarized over 75 research projects 2 that investigated the effects of biosolids utilization in mine spoil reclamation and found that a self-sustaining ecosystem can be established quickly. This thesis evaluates the Princeton Tailings Reclamation Project, in which anaerobically digested biosolids produced at the Annacis Island Wastewater Treatment Plant (Delta, B.C.) were applied to Granby tailings (copper mine tailings) in Princeton. The environmental effects of biosolids addition on vegetation quality and yield, soil fertility, nitrate (N03-N) leaching, and total metal concentrations in soil were studied in the field on a demonstration project scale, and N0 3-N leaching, mineralization of organic N, and metal movement were investigated on a laboratory scale at the University of B.C. The laboratory work was conducted under more controlled conditions than the field trial and was done to complement field results. The field project was conducted by the Greater Vancouver Regional District - Residuals Management Group under permit AR-11578 issued by the B.C. Ministry of Environment, Lands, and Parks (B.C. MOE, 1992). The author conducted the laboratory project and evaluated both the laboratory and field projects statistically. Results of the field project were also reported in project progress reports prepared by the GVRD Residuals Management Group for the B.C. Ministry of Environment (GVRD, 1992, 1993b, 1994a, 1994b). The demonstration sites are approximately 5 km southeast of Princeton, B.C., and are located on District Lot 3030-OS Plan 11297, Lot 1 (Lat. 49°27'30" N and Long. 120°29'0" W) at elevation 667 m above sea level. The demonstration plots are sloped less than 0.3% and are 17 m above native till. Princeton is located in a semi-arid climatic zone with a mean annual precipitation of 350 mm, a mean annual temperature of 5°C (-41°C to 38°C), and 104 frost free days . The earliest last frost on record (144 years) was measured on May 22, and the latest last frost was measured on July 5. The main tailings ponds consist of loose silts and clays (Si, SiC, SiL, and SiCL) with a soil pH around 8.0 (alkaline). 3 The Princeton mine tailings (also called Allenby tailings or Granby tailings) originate from the nearby Allenby mill which processed copper ores originating from the Copper Mountain mine. Both the mine and mill were operated by Granby Consolidated Mining, Smelting and Power Company Ltd. which was active intermittently between 1919 and 1957. Total production from Copper Mountain was 39,774,902 tonnes of ore which produced approximately 1,043,000 tonnes of concentrate that averaged 33% copper. About 33,732,000 tonnes of tailings were produced, the majority of which were deposited in the Allenby tailings pond (McDonald and Lane, 1979). Today, this tailings pond is owned by the Town of Princeton. Approximately 4,999,902 tonnes of waste rocks were produced in the mining process. At the Annacis Island Wastewater Treatment Plant, the process that turns raw sewage influent into anaerobically digested biosolids includes the primary treatment of influent, gravity thickening, and transfer of the thickened fraction to an mesophilic anaerobic digester. The digester is operated in continuous mode and material digests between 14 and 17 days at 38°C. After the biosolids have been digested, they are mechanically dewatered by centrifugation. In the field trial, primarily stored dewatered biosolids were applied whereas in the laboratory trials, freshly dewatered biosolids were applied. Stored dewatered biosolids contained 3.4% total N of which 42% was in the form of ammonium (NH4-N) at the time of application, and freshly dewatered biosolids contained approximately 3.7% N of which 11% was in the form of NH4-N. Although it would have been ideal to use the same methods and the same equipment for the analysis of samples collected in the Princeton Demonstration Project and the leaching experiments, this was not feasible. Instead, collected samples were analyzed in one of three laboratories: the Bio-Resource Engineering Laboratory (BIOE Lab), the Greater Vancouver Regional District Laboratory (GVRD Lab), and Norwest Soil Research Inc. (Norwest Lab). Unfortunately, the standard methods or equipment were not always the same in the three laboratories and thus, detailed laboratory methods used in the project are listed in Appendix O by parameter and laboratory to avoid confusion. 4 2.0 LITERATURE REVIEW The application of biosolids to mine spoils is extremely attractive because of the benefit to both the municipality through biosolids disposal and to the environment through land reclamation. In addition, the use of biosolids for land reclamation is expected to reduce the combined costs for land reclamation and disposal of biosolids. The main components of biosolids for reclamation use are organic matter and N. Organic matter in biosolids has been shown to improve soil physical properties by improving granulation, increasing water holding capacity, increasing soil surface temperature, and decreasing bulk density. Furthermore, organic matter in biosolids improves soil chemical properties by increasing the soil cation exchange capacity (CEC), buffering soil pH, and increasing the concentration of soluble nutrient salts (U.S. EPA, 1983). Problems in utilizing biosolids in land reclamation may result from the oversupply of N and occasionally P and from metals, pathogens, or organic compounds that they might contain. The application of excess biosolids might cause N0 3-N addition to groundwater, luxury consumption of N by plants, loss of nutrient cations from soil, metal accumulation in soil, and metal accumulation in plants. A literature review of N behaviour in soil and metals in soil and vegetation after biosolids application follows in sections 2.1.1, 2.2, and 2.3. Anaerobically digested biosolids are not microbiologically sterile. Typical bacterial levels in the biosolids used in this project are listed in Table 1. Possible methods of disease transmission from land applied biosolids include all forms of water and air movement and the consumption of products grown in soils to which biosolids have been applied. This project did not study the microbial effects of biosolids application to land, but a brief literature review on this subject is included in section 2.4. 5 TABLE 1. BACTERIA LEVELS IN BIOSOLIDS (GVRD, 1993a) Biosolids Type Fecal Coliform Enterococci Fecal Streptococci Salmonella (MPN/g) (MPN/g) (MPN/g) (#/g) Annacis freshly dewatered 3.0 E+5(17) 2.0 E+5 (6) 8.6 E+3 (6) 6(5) Annacis stored dewatered 28(13) - 664(7) 0(6) Notes: All results are geometric means. The number of samples are in parentheses. MPN/g Most Probable Number per gram of dry solids. # /g Number of bacteria per gram in dry solids. 2.1 Nutrients The elements required by plants that will ensure good growth have been divided into macronutrients and micronutrients. Macronutrients are required in greater quantities than micronutrients. Macronutrients for plants are N, P, potassium, calcium, magnesium, and sulfur whereas boron, iron, manganese, copper, zinc, molybdenum, cobalt (not essential for all vascular plants), and chlorine are plant micronutrients (Foth, 1984). 2.1.1 Nitrogen Nitrogen is the soil nutrient that most commonly limits plant growth and since the major portion of N in soils is in organic forms (Salisbury and Ross, 1992), soils low in organic matter will also be deficient in N. Nitrogen in biosolids occurs in ammoniacal and organic form and whilst NH 4 + (in the liquid fraction) is immediately available for crop uptake, organic N requires mineralization first. 6 Nitrogen biochemistry in soils consists of the constant turnover of N during organic reactions like mineralization (organic N -> NH 4 +), nitrification (NH 4 + -> N03"), denitrification (N0 3" -> N2), mineral uptake (NH 4 + or N0 3" absorption by plants), immobilization (NH 4 + or N0 3" incorporation into biomass), and N 2 fixation (atmospheric N 2 fixation into biomass). In dry and high pH conditions, the mineralized NH 4 + may also volatilize as NH 3. All but the volatilization and absorption of NH4-N in acid soils require microbial catalysis. Nitrogen losses from the soil result from crop removal (NH 4 + & N03"), leaching (N03"), denitrification (N2), volatilization (NH4+), and soil erosion (all N forms). After the establishment of a vegetative cover, N losses due to crop removal usually outweigh other N losses. A simplified diagram of the N cycle is included in Figure 1. The different stages of the N cycle are discussed in the following sections. Typically in the early spring, a portion of the mineralized or nitrified N from biosolids is available to volatilize, leach, or denitrify due to a higher amount of mineral N available than is taken up by vegetation and due to excess water from spring melt or spring rains that can leach excess N0 3-N to lower soil layers. However, as mineralization, nitrification, and the growth of seedlings are temperature dependent, N0 3-N leaching losses are typically small when nutrients are added in the form of organic matter. In the late fall there may be another period of N0 3-N leaching which depends on soil temperatures and organic matter available for decomposition. Nitrate may be leached or denitrified if sufficient rain is received before the soil freezes. If there is no freeze-up, the potential for leaching may persist throughout the winter although mineralization will normally cease. In most agricultural or grassland soils, the carbon:nitrogen (C:N) ratio of soil organic matter is about 10:1 (w/w) (McGill etal., 1980). When this ratio is changed by N fertilization, addition of organic organic N (b iomass) N fixation atmospheric N denitrif ication organic N (humus, decaying plant & an imal matter) I mineral izat ion N H 4 - N nitrif ication N 0 3 - N leaching volati l ization adsorpt ion clays mineral ferti l izers FIGURE 1. SIMPLIFIED NITROGEN CYCLE 8 matter, or plant uptake, soil microorganisms restore the balance by carbon oxidation, N fixation, or denitrification (Bohn et al., 1985). In the biosolids used in this project, the concentration of N ranged between 3.3 and 3.8% and the concentration of carbon ranged between 30 and 40%, thus the C:N ratio was about 10:1. 2.1.1.1 Mineralization and Immobilization of N Mineralization is the conversion of organic N to NH 4 + which is accomplished through aminization and ammonification (Tisdale et al., 1993). Aminization describes the breakdown of proteins into amino acids, amines, urea and C 0 2 by heterotrophic bacteria and fungi. Ammonification is the breakdown of amino acids and amines and the release of NH 4 + performed by aerobic or anaerobic bacteria, fungi, or actinomycetes (Tisdale et al., 1993). The resulting NH 4 + ions are only stable under strongly reducing conditions (Bohn et. al. 1985). As organic N in biosolids primarily consists of amino acids, hexoamines, and amides (U.S. EPA, 1983) ammonification is the primary process in the mineralization of organic N in biosolids. The mineralization rate of N in soils depends on the C:N ratio, the concentration of heterotrophic bacteria, the stability of organic matter, the availability of water, the pH and Eh, and the soil temperature. Typically, the mineralization rate doubles with every temperature increase of 10°C between 5°C and 35°C. The optimum temperature for mineralization is between 30°C and 35°C. Generally, conditions favourable for nitrification also favour ammonification. Disagreement exists among researchers concerning the effect of the rate of biosolids addition on the percent of added organic N mineralized (Sopper, 1993; Williams et al., 1984). Sopper (1993) summarized a few studies that demonstrate the varying rate of N mineralization in soils amended with biosolids. For example, Voos and Sabey (1987) added biosolids at rates of 0, 40, 80, 120 dry tonnes 9 per hectare (dt/ha) which added 0, 1630, 3260, and 4890 kg/ha N respectively to coal mine spoil samples. The mixtures were incubated for 16 weeks in a laboratory. By the end of the experiment, NH4-N had increased significantly with increasing application rate of biosolids, but only small amounts of N0 3-N had accumulated. A similar finding was reported by Terry et al. (1981). Terry et al. (1981) used biosolids application rates of 11.2, 22.4, and 44.8 dt/ha and found that the percent of added organic N mineralized was significantly greater at higher rates than at lower rates of biosolids addition. However, Epstein et al. (1978) and Magdoff and Cromec (1977) observed no effect on the percent of organic N mineralized at rates ranging from about 20 to 80 dt/ha, and Sabey et al. (1977) observed that the percent of organic N mineralized decreased as the amount of N added increased. Based on varying results for similar experiments that were reviewed by Williams et al. (1984), they suggested that so far unidentified factors play a role in the mineralization of biosolids after incorporation into soil. Immobilization is the conversion of inorganic N to organic N. If decomposing organic matter in soil has a high C:N ratio (as in wood chips), microorganisms will use available N in the soil to multiply and to decompose organic matter making mineral N unavailable for plant use. After low N residues have been decomposed, decomposing microbial activity subsides and immobilized N can be mineralized back to NH 4 +(Tisdale et al., 1993). Approximate C/N (w/w) ratios for mineralization and immobilization are (Tisdale et al., 1993): C/N %N Mineralization < 20 > 2 Immobilization > 30 < 1-1.5. 2.1.1.2 Nitrification Nitrification is the conversion of NH 4 + to N0 3" in a two step process accomplished primarily by aerobic chemo-autotrophs. The formation of nitrite (NH 4 + -> N02") in the first step is carried out primarily by Nitrosomonas spp. and the formation of nitrate (N02" -> N03") in the second step is performed by 10 Nitrobactor spp. In most well-drained soils the reaction rate is faster for the second step than the first step. Nitrification is acidifiying (Tisdale et al., 1993). Nitrification Reaction (Metcalf and Eddy. 1991): Step 1: 55 NH 4 + + 76 0 2 + 109 HC0 3 ' -> C 5 H 7 0 2 N + 54 N0 2" + 57 H 2 0 + 104 H 2 C 0 3 Step 2: 400 NO z" + NH 4 + + 4 H 2 C 0 3 + HC0 3 " + 195 0 2 -> C 5 H 7 0 2 N + 3H 2 0 + 400 N0 3 " Nitrification is affected by the supply of NH 4 + , the population of nitrifying bacteria, the pH and Eh, and the soil temperature and moisture. However, soils differ in their ability to nitrify N H 4 + even under similar conditions (Tisdale et al., 1993) which is likely due to the susceptibility of nitrifying bacteria to a wide variety of inhibitors. A variety of organic and inorganic agents can inhibit the growth and action of nitrifying bacteria. High concentrations of ammonia and nitrous acid can be inhibitory (Metcalf and Eddy, 1991). The optimal pH for nitrification ranges from 7.5 to 8.6, but systems acclimated to lower pH conditions have successfully nitrified (down to 4.5). A dissolved oxygen (DO) concentration in the soil solution above 1 mg/L is essential for nitrification to occur. If DO levels drop below this value, oxygen becomes the limiting nutrient and nitrification slows or ceases (Metcalf and Eddy, 1991). Generally, nitrification appears to proceed most rapidly at moisture tensions between 1/3 and 1 bar when water occupies about 80 to 90% of soil pores (Tisdale et al., 1993). As the soil moisture declines, the nitrification rate declines as well. The quantification of the effect of temperature has been difficult (Metcalf and Eddy, 1991), but the optimum soil temperature for nitrification is believed to between 25°C and 30°C although nitrification can occur over a wide temperature range (Tisdale et al., 1993). Nitrate is only stable under strongly oxidizing conditions. The N0 3" anion is very soluble in water and is only non-specifically adsorbed by soil colloids (Tisdale et al., 1993; Bohn et al., 1985). Therefore, excess N0 3-N tends to leach along the water potential gradient (mass flow). 11 In a comparative study of the reclamation of an acid strip mine spoil in Pennsylvania, Seaker and Sopper (1988) studied the difference between nitrifying populations in 5 sites amended with biosolids and a site amended with fertilizer. The biosolids-amended sites were studied 1 to 5 years following application and the fertilizer site was studied 5 years after application. They found that Nitrosomonas populations were not significantly different on the five biosolids-amended sites, but were two to four magnitudes greater than on the fertilizer-amended site. The Nitrobacter population was not only significantly larger on the most recently biosolids-amended site than on the older biosolids-amended sites, but was also four to six orders of magnitude greater than on the control site. After 5 years following application, the bacterial populations for the biosolids and the fertilizer amended sites were 7*104 g"1 and 30 g"1 for the Nitrosomonas and 5.5*105 g"1 and 18 g"1 for the Nitrobacter respectively. In typical soils, the nitrifying population ranges from a few hundred to 10 s g"1 (Stevenson, 1982). The low nitrifying population on the fertilizer-amended sites suggests a lack of organic N which corresponded with sparse growth on the site after five years. 2.1.1.3 Denitrification Denitrification is the conversion of N0 3" or N0 2" to the gases N 2 0 or N 2. The conversion is primarily performed by facultatively anaerobic bacteria which use N0 3-N, N0 2-N, and nitrous oxide as terminal electron acceptor when the soil is anoxic. Denitrification Reaction: +4H + -2H 2 0 +2H + -2H 2 0 +2H + -2H 2 0 +2H + -2H 2 0 2HN0 3 > 2HN0 2 > 2NO > N 2 0 > N 2 nitrate reductase (Mo.Fe) Denitrification losses can occur after the incorporation of biosolids into soil through the creation of anoxic microsites due to high microbial activity. Furthermore, denitrification losses in fine textured soils 12 tend to be greater than those for coarse textured soils due to their increased water holding capacity, lower permeability, and higher likelihood of anoxic conditions since the 0 2 diffusion coefficient in water in 10000 times less than in air. Denitrification is dependent on the available N0 3" and organic carbon concentrations, the pH and Eh, the soil moisture, and the soil texture and temperature. The dependence of denitrification rate on N0 3" N concentration has been found to be of first order at N concentrations less than 40 mg/L and of zero order at higher concentrations (Firestone, 1982). Denitrification increases with readily available carbon, but researchers have not determined conclusively if available carbon should be measured as total organic, water-soluble, or mineralizable carbon (Elder, 1988). Carbon supplies the energy for N reduction and provides a matrix of compounds into which reduced N can be incorporated and stabilized. Generally, denitrification rates are increased by plants because of their release of readily available C in root exudates and sloughed off root tissues (Tisdale et al., 1993). Denitrification is relatively constant at pH 6 to 8, but tends to decrease under acidic conditions (Firestone 1982). The temperature tolerance of denitrifying bacteria tends to vary with climatic region. Firestone (1982) reported minimum temperatures for denitrification of 2.7°C to 10°C, and maximum temperatures of about 75°C. 2.1.1.4 Volatilization Volatilization of NH 3 occurs naturally in all soils. Volatilization losses depend on the atmospheric partial pressure of NH 3, the concentration of NH 3 and NH 4 + in the soil solution, the pH, the soil temperature, and the cation exchange capacity (CEC). 13 Volatilization losses are especially high in high pH soils, but losses also increase when the soil pH is temporarily raised after a storm or flooding event (Tisdale et al., 1993). Volatilization Reaction: NH 4 + > NH 3 + H + (pK = 9.3) Volatilization losses in the Princeton demonstration project are believed to have been especially high due to the use of stored dewatered anaerobically digested biosolids with 30% of the TKN in the form of NH 4 + . The NH4-N tends not to be tightly bound in the biosolids and the trucking and application operations provided an opportunity for trapped NH 4 + to escape. In general, volatilization increases with increasing temperature up to 45°C. In soils with high CEC, NH 4 + may be retained in Vermiculite or Montmorillonite (lllite). 2.1.1.5 Nitrogen Fixation Nitrogen fixation is the process by which N 2 is reduced to NH 4 + . Principal N fixers include microbes associated with roots, especially those of legumes, free-living soil bacteria, certain free-living cyanobacteria, and cyanobacteria in symbiotic associations with fungi. Nitrogen fixation is influenced by soil pH, mineral nutrient status, photosynthetic activity, climate, and legume management. Nitrogen Fixation Reaction: nitrogenase N 2 > NH 4 + (Mo.Fe) The activities of the roots of nitrogen-fixing plants benefits the roots of surrounding plants through excretion of N from nodules or through microbial decomposition of nodules or whole plants (Ta and 14 Farris, 1987). In legumes, bacterial species of Rhizobium or Rhizobium-Wke species are generally only effective for one legume species or group of species. All rhizobia are aerobic bacteria (Salisbury and Ross, 1993). Rhizobia species differ in their optimum range of soil pH. For alfalfa, a pH below 6 drastically reduces the activity of Rhizobium meliloti in its root zone. High N0 3" concentration in the soil can reduce nitrogenase activity and N fixation. Low photosynthetic plant activity caused by reduced light intensity, moisture stress, or low temperature will also reduce N fixation (Tisdale et al., 1993). 2.1.1.6 Nitrate in Feed In general, biosolids applications on mine land increase the total N concentration in the foliage of vegetation (Sopper, 1993). Normally, N0 3-N taken up by plants is converted to NH4-N which is used to form amino acids and proteins. Unfavorable growing conditions, such as drought, can interfere with the N accumulation in plants and can cause an accumulation of N0 3-N, particularly in the stalk as long as the conditions stay unfavorable (Noller and Rhykerd, 1978). This effect can be amplified by an overfertilization with N which results in a higher accumulation of N in plants. Nitrate toxicity may follow if ruminants eat N0 3-N rich stalks which overwhelm their digestive system and which may lead to an accumulation of N0 2 -N in their bloodstream and a diminished ability of their blood to carry oxygen. Sopper (1993) has been unable to find any documentation of N0 3-N toxicity occurring as a results of biosolids applications to mine land in his review of more than 75 research projects. This result is likely due to the slow-release fertilizer behaviour of biosolids and their additional benefit of providing increased water-holding capacity and mulching. In contrast, most inorganic fertilizers are in an available form and do not provide any water-holding capacity or mulching which makes droughty conditions and high N0 3-N feed more likely to occur. 15 2.1.2 Phosphorus About 70 to 90 percent of P in biosolids is present as inorganic compounds. Therefore, inorganic reactions of P are of greater importance in biosolids utilization than organic reactions (U.S. EPA, 1983). Phosphorus in soils is controlled by chemical reactions. Phosphorus is retained in soils by a multistage process that involves several known mechanisms as well as unknown mechanisms. For example, phosphate ions can be retained by substitution of OH" groups, lattice extension, precipitation, or coordination but to date, the mechanisms of organo-P retention by soils have not been fully established. In the process of OH" substitution, phosphate ions replace singly coordinated OH-groups. Many soils fix large quantities of P by converting readily soluble forms of P to forms less available to plants. In general, the longer P has been in the soil, the slower is the release of P. In addition, P fixation in soils is not fully reversible. Phosphate forms difficultly soluble Fe 3 + and A l 3 + compounds at low pH, more soluble C a 2 + and Mg 2 + compounds at pH values near neutrality, difficultly soluble C a 2 + compounds at pH 7-8, and more soluble C a 2 + compounds at pH > 8 (Bohn et al., 1985). Phosphate fixation is appreciable in all but very coarse textured soils or peat soils and is particularly high in soils rich in amorphous iron and aluminum hydroxide or allophane (Bohn et al., 1985). In general, soil organic matter increases the P availability to plants. 2.2 Metals in Vegetation Typical biosolids contain heavy metals in varying concentrations. The absorption of metals contained in biosolids by plants after the addition of biosolids to soils is complex. Factors that contribute to the complexity include metal concentrations of biosolids, soil pH, Fe and Al concentrations in the biosolids, soil concentrations of Fe, Al, Ca, P, Zn, soil organic matter content, and soil clay content. As 16 well, the phytotoxic metal tolerance of plant species and the amount of metals accumulated by various plant species are highly variable (U.S. EPA, 1983). In general, the plant uptake of metal ions from soil is dependent on the concentration and speciation of metals in the soil solution and the translocation of metals from the roots to other plant tissues. Plants grown on all soils appear to respond to an increased concentration of heavy metals in soils with absorption. However, plants tend to take up metals bound to organic materials slower than metals in ionic form. After biosolids application, one reason for metal uptake by plants is that increased nitrification enhances growth and acidifies the soil which facilitates plant uptake of elements like Zn, Cd, Cr, Pb, and Ni (Henry and Harrison, 1991). Because As, Pb, and Hg are not taken up readily by most plants, the metal of greatest concern is Cd. The reproductive parts of plants (flowers, fruits, seeds) usually contain lesser concentrations of Cd, and respond less rapidly to Cd additions to soils than do vegetative parts. However, the phytotoxic tolerance of plant species to Cd added to soil and the amounts accumulated by various plant species are highly variable (U.S. EPA, 1983). CAST (1980) found that levels of Cd and Zn in plant tissues increased with increasing metal application rates irrespective of whether the metals were applied as inorganic metal salts or with biosolids, and that the Cd and Zn concentrations varied seasonally. Higher accumulations tended to occur at higher soil temperatures and/or moisture stress. According to Corey et al. (1987) and Chaney (1990), plant uptake of trace metals from biosolids-amended soils tends to approach a maximum as the application rates increase. This phenomenon might be explained by the recent discovery of the mechanism that detoxifies metals by chelation with phytochelatins (Gekeler et al., 1989; Steffens, 1990; and Rauser, 1990). Phytochelatins seem to be produced by numerous plant species but so far they have only been identified when toxic amounts of trace elements were present in the soil solution. 17 Other studies indicate that a decrease in trace metal concentrations in vegetation from biosolids-amended sites may occur over time when biosolids are applied on a one-time basis. Metal concentrations in tall fescue from a Ohio mine spoils amended with up to 716 dt/ha of biosolids were considerably lower in the third than in the first growing season (Haghiri and Sutton, 1982). On anthracite refuse in Pennsylvania, Cu, Zn, and Cd increased in reed canarygrass tissues in the first growing season after biosolids application, but in the second and third growing seasons, with few exceptions, metal concentrations decreased to control levels or below (Kerr et al., 1979). Several factors may account for decreasing metal concentrations over time. Iron and P added with biosolids may complex with metals, forming sparingly soluble precipitates. According to Ernst (1976), the absorption rate of heavy metals by plants can be reduced in the presence of high amounts of calcium and P. Metals may also bind with the humic fraction of biosolids (Haghiri and Sutton, 1982). Another reason for reduced metal concentrations in vegetation might be a dilution effect that occurs as a result of increased biomass production after biosolids application (Kerr et al., 1979). To minimize plant uptake of metals, plants can be genetically selected for the property of low translocation of heavy metals as well as their metal tolerance. Copper plant uptake is not fully, understood, but it seems likely that although Cu is almost entirely complexed in the root environment, it dissociates prior to plant absorption. Genotypical differences in Cu absorption by plants clearly exist, for example, ryegrass extracts up to twice as much Cu from the soil as wheatgrass (Graham, 1981). Copper tolerant herbaceous plants have been identified in areas of high soil copper concentration. On British soils, the following Cu tolerant species can be found: Festuca ovina, F. rubra, Agrostis stolonifera, A. tenuis, Deschampsia caespitosa and the dicotyledons Silene maritima, Armeria maritima, and Calluna vulgaris (Woolhouse and Walker, 1981). Studies show that no arborescent species appear to have evolved a high degree of copper tolerance (Woolhouse and Walker, 1981). 18 2.3 Metals in Soil Mine tailings are generally devoid of soil organic matter at the start of reclamation so that the behaviour of metals in soil is primarily dependent on the quantity and quality of soil amendments that are added and the physical and chemical characteristics of the spoil. Right after the addition of biosolids to mine tailings, the behaviour of metals in soil will be controlled by the metal absorption capacity of biosolids, the spoil pH, and the chemical characteristics of the spoil. The metal absorption capacity of biosolids depends on the.organic and inorganic (e.g. Fe and Al oxides) components in the biosolids. Generally, metals in biosolids are bound to organic components as sulfides, chlorides, carbonates, hydroxides, and other compounds that are not readily soluble (Sopper, 1993). If the reclamation effort is successful in establishing a self-sustaining ecosystem, soil organic matter will build up in the spoil and metal interactions with the soil organic matter will become more important over time. The long-term behaviour of metals that were present at the beginning of the site reclamation and that were added with the biosolids will depend more and more on the soil organic matter and soil pH. Smith and Giller (1992) found that concentrations of total metals in biosolids-amended soils increased linearly with soil organic matter content irrespective of the rate or frequency of biosolids addition, the duration of application, or the period which had elapsed since the last treatment. Tiller and Merry (1981) found that high soil concentrations of Cu appeared to affect the microbial, earthworm, and insect populations resulting in a slow breakdown of organic matter and slow turnover of N. In general, the concentration of metals in the soil solution is dependent on various simultaneous equilibrium reactions, including the reactions of precipitation and dissolution (decreasing pH -> increasing solubility), adsorption and desorption, and reduction and oxidation. Metal chelation plays also an important role. These reactions are all directly or indirectly related to soil pH. 19 Aspects of equilibrium reactions concerning metals in the soil solution were summarized well by Kiekens (1983) and a condensed version follows below. The dynamic equilibrium of metals in soil changes with metal additions, metal uptake by plants, leaching, changes in pH, changes in redox, changes in soil moisture, and mineralization of organic matter (Kiekens, 1983). Adsorption and Desorption In most cases, the colloidal fraction in soil is negatively charged and adsorbs and retains cations from the soil solution. The colloidal fractions consists of clay particles, amorphous oxides of Fe and Al, and organic colloids. Laboratory experiments by Kiekens (1980) on the behaviour of Cu, Pb, Zn and Cd in soil showed that the adsorption of heavy metals was strongly reduced in the presence of 0.01 M CaCI2, indicating that C a 2 + competes effectively with heavy metals for the adsorption sites. This competition seemed to be greater for Zn and Cd than for Cu and Pb. This laboratory result was confirmed in field studies by Davis (1983) who conducted tests on calcareous and noncalcareous soils. On calcareous soils, plant response to Cd was limited even at much elevated soil Cd concentrations. On noncalcareous soils, there was nearly a linear relationship between plant and soil concentrations. Adsorption (Kiekens, 1980): in 0.01 M CaCI 2 soil suspension: Cu > Pb > Cd > Zn adsorption at low metal concentrations in soil: There seems to be a hysteresis effect in the reaction: Ca-soil + M 2 + <--> M-soil + C a 2 + Cu > Pb > Cd > Zn Desorption (Cottenie and Kiekens, 1972): pH < 5: Zn 2 + , Cd 2 + , Mn 2 + pH < 3: Cu 2 + , Pb 2 + 20 Redox Potential In oxidizing conditions: pH: decreasing pH => increased solubility (Kiekens, 1983) pH 3-7: soluble Cd > Zn » Cu > Pb (Herms, 1982; Kiekens, 1980) In reducing conditions (Herms, 1982): Fe 2 + and Mn 2 + are initially more soluble and dissolution of their oxides can release occluded trace metals. pH > 7: higher solubility of Cd, Zn, Pb, and Cu than in aerobic conditions (soluble organomineral complexes) pH 4-6: lower solubility of Cd, Pb, Zn, and Cu than in aerobic conditions (insoluble sulfides or organomineral complexes) Chelation and Soil Organic Matter Soil organic matter is an important soil component originating from plant and animal residues which have been converted to the more or less stable product of humic substances consisting of humic and fulvic acids. Humic and fulvic acids have been defined according to their solubilities. Humic acids are soluble in an alkaline medium, and fulvic acids are soluble in acid and alkaline media. Fulvic acids primarily form chelates with metal ions over a wide pH range, thus increasing the solubility and mobility of heavy metals. The stability constant of metal fulvic acid complexes increases with increasing pH and is high for the cations Cu 2 + , Pb 2 +, and Fe 3 + . The interaction and solubilities of humic acids and metals are more complicated but are strongly pH dependent. Humic acids (HA) are insoluble in acid medium (pH < 1) but dissolve gradually as pH increases. Chelation pH 1-6: insoluble Cu-humic acid complexes (Verloo, 1974) pH > 7: Soluble HA can be flocculated by C a 2 + and Mg 2 +, and at higher pH by Fe 3 + and A r (Kiekens, 1983). All metals are either in the form of soluble humates or precipitated as hydroxides (Verloo, 1974). 21 2.4 Biosolids and Pathogens Typically, densities of pathogenic bacteria are reduced but not eliminated by anaerobic digestion. Therefore, some risks to human health exist when applying these biosolids to land. However, land application reduces the bacterial density to low values in less than 30 days when applied to vegetation or the soil surface, especially where exposed to high temperatures, sunshine (UV), and desiccation. The decline is slower when biosolids are incorporated below the soil surface due to the protection from UV light and desiccation (Long, 1993). Studies have indicated that most pathogenic bacteria and viruses are removed after passing through a meter of soil or less (Edmonds, 1979). The potential hazard from surface runoff is low after one month after application (Long, 1993). Adult wastewater borne parasites, protozoa and helminth organisms rarely survive a mesophyilic treatment process, but their cysts and eggs are hardier and often end up in biosolids. Some biosolids can arrive at the land application site with approximately the original ova concentration. Of the various helminths, Ascaris ova are common, have the highest densities of any helminth in typical biosolids, and survive the longest. The survival time of Ascaris ova is estimated to be at least 3 months for biosolids applied to grassed plots and even after 3 years approximately 50% of the Ascaris ova are expected to be viable on biosolids-amended tilled or fallow plots (Long, 1993). The infective dose for helminths is one egg. The principal means of human exposure to pathogens are ingestion and inhalation, but studies conducted in the U.S.A. and Europe showed that the incidences of disease in farm inhabitants and domestic animals on farms applying biosolids did not differ significantly from control farms that did not apply biosolids while following EPA or equivalent regulations (Long, 1993). Good application practices that prevent the transmission of pathogens to humans include changing of exposed clothes, good personal hygiene by applicators, and wearing of face masks if dust is generated in the application of biosolids. Other biosolids management practices include the restriction 22 of public access to treatment sites and the restriction of movement of plants or soil from treatment sites for at least one month after application (Long, 1993). 2.5 Nitrate Leaching in Soil Columns In typical column studies examining the N0 3-N leaching behaviour, N0 3-N is added to saturated, unvegetated soil columns in the form of mineral salts dissolved in distilled water (for example as KN0 3). Sometimes both N0 3 " and chloride (CI") ions are added to saturated soil columns. Nitrate and CI" travel at approximately the same speed through soil, but CI" flows inertly through soil unlike N0 3" that can undergo bacterial conversion to other N forms in the N cycle (Bowman, 1984; Verdegem et al., 1981). In typical experiments, N0 3-N in leachate is then studied either after a one-time or after repeated additions of distilled water to the saturated soil columns. Typically, the leachate is collected either at the bottom or at the bottom and at several depths in between the top and bottom of the columns (Elder, 1988). Leaching experiments discussed in this text were designed differently as N was added in the form of organic N and NH 4 + which had to either mineralize or nitrify before N0 3-N leaching could be investigated. Therefore, the leaching experiments had to be designed to resolve the dilemma of adding enough water to be able to leach N0 3-N to lower soil layers but at the same time to allow nitrification of organic N in biosolids to occur and to discourage denitrifcation losses. The dilemma is that maximum water movement through soil occurs under saturated conditions and that the conversion of NH4-N mineralized from organic N in biosolids nitrifies only under aerobic conditions which are inhibited under saturated conditions. In general, once NH4-N has been converted to N0 3-N, N0 3-N will leach downwards with the wetting front unless it is denitrified or taken up by plants first. 23 In general, the permeability of soil or hydraulic conductivity in soil columns can be estimated with Darcy's Law: If vertical flow under constant head is assumed, Darcy's Law equals (Craig, 1992): k = (q*l/A*h) Eq. 1 and if vertical flow under falling head is assumed, Darcy's Law equals (Craig, 1992): k = (a*l/At1)*ln(h0/h1) Eq. 2 where k hydraulic conductivity [L/T] q volume of water collected per unit time [L3/T] I length of the soil column penetrated [L] A cross sectional area of the soil column [L ] h the hydraulic head difference between the bottom of the soil and the top of the constant depth of water above the soil column [L] a internal area of standpipe connected to the top of the cylinder holding the soil [L2] ^ time it takes for the water level to drop from level h 0 to h, [T] 24 3.0 METHODS AND MATERIALS - LABORATORY EXPERIMENTS 3.1 Overview of Leaching Experiments The leaching experiments consisted of two runs of 26 soil columns and one run of 10 pots which were shorter than the soil columns. Every column run consisted of 2 times 13 columns testing tailings from two field locations. The column runs were designed to estimate the amount and/or potential for N0 3-N leaching and metal movement that might occur after the application of biosolids (municipal sewage sludge) to tailings. The pot trial was designed to compare the mineralization rate of organic N in biosolids between very short columns (15 cm deep pots) and longer soil columns testing 45, 60, and 90 cm deep tailings. In other words, the tests examined the effect of drainage conditions on the mineralization rate of organic N in biosolids. The pot trial was conducted at the same time and under the same environmental conditions as was the second column test. The biosolids application rates 0, 30, 100, and 300 dry tonnes per hectare (dt/ha) investigated. According to the currently valid legislation for beneficial use of biosolids in British Columbia, the biosolids used were Agricultural Low Grade Sludge (B.C. MOE, 1983). In the column runs, a tailings/biosolids mixture was added on top of previously saturated tailings. The tailings/biosolids mixture consisted of an equivalent weight of biosolids for the various application rates, and a quantity of tailings that could fill 15 cm in the columns. The soil columns were 0.64 cm X 13.97 cm (5.5" X 0.25") Plexiglas columns and of varying heights. Out the 13 columns per field locations, 5 columns were 110 cm in length, 4 columns were 85 cm in length, and 4 columns were 70 cm in length. The biosolids application rates 0, 30, 100, and 300 dt/ha were tested in all column lengths, and the 300 dt/ha application rate was duplicated in the longest columns. The pots were 14 cm in diameter and 15 cm in height (typical plastic flower pots). The characteristics of the added biosolids are given in Table 2. 25 TABLE 2. BIOSOLIDS CHARACTERISTICS - LABORATORY EXPERIMENTS Element Run 1 * Run 2 ** B.C. Draft Guidelines for the Disposal of Domestic Sludge (1983) Annacis Freshly Dewatered Biosolids (Mar. 93) Annacis Freshly Dewatered Biosolids (Aug. 93) Agricultural Low Grade Retail High Grade C.V. C.V. (%) (%) % Moisture 74 1 72 0 - < 70 pH (1:2) 8 1 8 2 - -% Loss on Ignition (@ 450 °C) 71 1 74 0 - -Total Kjeldahl N (mg/kg) 35700 3 41900 4 - -Nitrate & Nitrite-N (mg/kg) 2 2 3 12 - -Ammonium-N (mg/kg) - extracted 3730 5 4460 3 - -Ammonium-N (mg/kg) - distilled 3640 2 5210 3 - -Total Phosphorus (mg/kg) 10500 3 13900 14 - -Arsenic (mg/kg) < 9 0 < 17 0 75 75 Cadmium (mg/kg) 4 5 3 4 25 5-20 Chromium (mg/kg) 60 2 58 5 - -Cobalt (mg/kg) 4 9 < 3 0 150 150 Copper (mg/kg) 820 2 904 2 - -Lead (mg/kg) 156 2 139 5 1000 500 Mercury (mg/kg) 5.4 12 5.7 11 10 5 Molybdenum (mg/kg) 7 11 8 15 20 20 Nickel (mg/kg) 28 2 24 6 200 180 Selenium (mg/kg) 7 3 5 13 14 14 Zinc (mg/kg) 621 2 671 1 2500 1850 Notes: * The average concentrations of 5 samples. The average concentrations of 4 samples. Since spring is generally considered to be the period of greatest N0 3-N leaching, the leaching experiments were designed to simulate spring runoff or spring melt and rainfall conditions. 26 Besides being subject to a water regime, the columns were subject to light and temperature changes. The experiments were not conducted under completely controlled conditions. The temperature and light conditions were allowed to fluctuate diurnally and from week to week. The overall average temperature for leaching runs 1 and 2 were 17.8°C and 17.2°C respectively. In leaching run 1, the average weekly temperature increased from 15.3°C at the start to 23.4°C at the end of the run. In leaching run 2, the soil temperature decreased from 20.8°C at the start to 14.1°C at the end of the run. The temperature regime was lower than the optimal temperatures for bacterial conversion of organic N to NH4-N and N0 3-N, but are assumed to be typical for soils. Refer to. Appendix C for details. The light conditions in the laboratory varied with the sunlight and due to a different laboratory setup. Leaching run 1 was set up in a different laboratory than leaching run 2 due to space restrictions set out by the university administration. The room which housed the first experiment was facing west and fairly bright whereas the room for the second leaching run was facing north and relatively dark. Exposure to filtered sunlight (through a window) can lead to photosynthetic algal growth. In the leaching experiments, algal growth was assumed to not have had an effect on N concentrations as algal growth is dependent on sunlight, C0 2 , and minerals. Little algal growth was noticed in the first leaching run and none was noticed in the second leaching run. 3.2 Water Regime The water additions to the leaching columns and pots were supposed to simulate spring conditions in the field. In the original design, all experiments were to be replicated four times, testing the same setup and same water regime with tailings collected from four sites in the field. In the actual leaching runs, two column runs were conducted investigating leaching behaviour for tailings from two sites at a time. The water addition, temperature, and light conditions changed between the leaching runs due to 27 the poorer drainage behaviour of the tailings than had been anticipated, and due to the conducting of the experiment in a different laboratory and at a different time. To determine typical spring conditions for the research site, a data analysis was conducted on 20 years of precipitation data collected at the Princeton Airport (Dec. 1, 1971 - Nov. 30, 1991). The calculations showed that the average precipitation is 350 mm per annum, 130 mm from November 1 to January 31, and 60 mm from February 1 to April 30. An analysis of storm contributions to annual precipitation showed that 2-Day storms contributed the majority of the precipitation followed in importance by 3-Day storms. An analysis of storm contributions to seasonal precipitation showed that in the winter months (November - April) 4-Day and longer storms followed by 2-Day storms contributed the majority to the precipitation whereas in the summer months 2-Day storms followed by 4-Day storms were main contributors to the seasonal precipitation. Based on these results, 2-Day storms were simulated in the leaching experiments as early spring conditions mark the change from winter precipitation, temperature, and light conditions to summer conditions. Refer to Appendix C for a detailed overview of precipitation information. To be able to simulate typical field conditions in the laboratory, the appropriate magnitude of 2-Day storms were estimated with a Single Set Maximum Frequency Analysis (Gumbel, 1954). All water additions were kept below the two year return period for 2-Day storms with exception of the first water addition which was supposed to simulate spring melt water on the tailings surface. The total amount of water added per leaching run was comparable to the 2-year maximum of seasonal precipitation in the 6 months period between November 1 and April 30. Refer to Appendix C for details. In the first leaching run, a total of 180 mm distilled water was added over 10 weeks to all columns whereas in the second leaching run, a total of 163 mm distilled water was added over 13 weeks to all 28 columns and pots. Water was added slowly through the spout of a typical watering can (garden supply). Refer to Table 3 or Appendix C for details on the water regime. TABLE 3. WATER REGIME FOR THE LEACHING EXPERIMENTS Leaching Run 1 Leaching Run 2 and Pot Trial Week Day in Leaching Run Distilled water (Dl) added to Columns (mm) Dl added to Columns/Week (mm) Dl added to Columns (mm) Dladded to Columns/Week (mm) 1 1 2 33 31 64 33 31 64 2 8 9 26 6 32 26 6 32 3 15 16 13 4 17 13 4 17 4 22 23 13 4 17 5 29 30 13 4 17 6 36 37 13 4 17 7 43 44 8 50 51 3 9 12 9 57 58 3 5 8 5 5 10 10 64 65 3 5 8 11 71 72 12 78 79 5 9 14 13 85 86 5 9 14 Total Water added (mm): 180 163 29 In the second leaching run, water additions beyond the first three weeks were spaced out over time compared to run 1 to allow mineralization and nitrification to occur at a higher rate. 3.3 Column Design To estimate the leaching behaviour of N0 3-N in the tailings a diameter of 5.5" (13.97 cm) was chosen to minimize edge effects while at the same time allowing easy loading and unloading of the columns. The columns were manufactured out of 0.25"X 5.5" Plexiglas tubes (0.64 cm X 13.97 cm) fitted with bottom plates with 0.6" holes (1.5 cm) in their centres. Male hose adapters (1.3 cm or 0.5") were screwed into the holes (together with plumber's tape to provide a good seal) to which 30 cm rubber hoses were connected with hose clamps. The rubber hoses were left open to the atmosphere during the leaching runs. Water draining flowed from the soil columns through the rubber hoses into 1 liter plastic receiving bottles. The column setup and the column design are shown in Figures 2 and 3, and photographs of the column setup are included in Appendix P. The longest leaching columns were also fitted with a joint at 50 cm height to allow for easy removal of tailings at the end of the run. These joints proved to be unnecessary in the experiment as the tailings slipped out of the columns relatively easily and without the mixing of tailings in different layers. The joint sealed very tightly and the space between the two halves inside the columns was barely perceptible to the touch. The joints were kept shut throughout the experiments. 3.4 Loading and Saturation of the Soil Columns Before tailings were loaded into the columns, all columns were filled to a height of 10 cm with medium sized rocks (1-2 cm in diameter) to ensure good drainage above the centre outlet. Then tailings were loaded at the same profile depth into the soil columns as they had been found in the field (on unvegetated sites). For example, 60-75 cm tailings from the field were loaded into the 60-75 cm layer 30 cm + to lids cm to cm gs cm CO o> CD m o o c m c o c > CO CO — — CD — CO o jo o in S o CO ro in ro o o r-LLI O 5i O o Si •o cm + CO lids cm to Ol cm gs CD LL ha CO O) c OSI o CO _c m t > CO O T3 o '5 u IO o CO o> CD O cm + CO lids cm co O) cm gs cm CO cm CO O) cm co 92 m o o c to c o c m c o c > CO CO — T o — CD — i - — o> CO '5 bic in 'ra in TO o CO in TO bic CO -<»• CD r-o O o CO CD o o o CO TJ o "D O a. o < LU _l LU Z o a. o LL Q. 3 I-LLI W O o o O c E 3 a. X Q. CO < or CM LU a z> o 31 -0 .64 cm (0.25") 1.3 cm (0.5") plexiglas large enough to a c c o m m o d a t e a 0.5 male hose adap te r - — 1 4 . 0 c m (5.5") ——15.2 c m (6.0") FIGURE 3. COLUMN DESIGN FOR '45 cm' COLUMN 32 of the leaching columns. In the field, tailings had been dug from soil pits and had been bagged into separate large plastic bags according their depths (at 15 cm intervals). The soil texture of the tailings in the different layers in listed in Appendix J . Before the tailings were loaded into the soil columns, they were homogenized by hand down to clumps of 2 cm in diameter. At his stage, the 0-15 cm tailings were moist (9-13% water content), the 15-60 cm tailings were wet (20-31% water content), and the 60-90 cm tailings were very wet (29-36% water content). After homogenization, tailings equivalent to 15 cm in height were weighed out separately for every column and every layer. The weighed out tailings were packed into the columns in 1-2 cm intervals with a square wooden block (12" X 2" X 2"). The final bulk density of the tailings in the columns was 1000 to 1100 kg/m3 compared to a field bulk density of 1150 to 1450 kg/m3 (15-30 cm layer). In leaching run 2, the tailings were slightly tapped into place in the columns as described above but under 1 to 2 cm of distilled water to speed up the saturation phase. Most but not all column layers were 15 cm thick. The thickness varied between 11.5 and 16 cm; however, all column layers testing tailings from the same site received the same amount of tailings. After the lower layers of tailings (15-90 cm) had been loaded into the columns and before the tailings/biosolids mixture was added to the top, the soil columns were saturated with distilled water for a few weeks (2 weeks for run 1 and 4 weeks for run 2). In the saturation phase, the same amount of distilled water was added to all columns at the same time. Between 5 and 20 mm of water was added to columns at any one time. Once the added water had infiltrated into the columns, more water was added in the saturation phase. Water was added slowly to the columns through the spout of a typical watering can (garden supply). 33 In the saturation phase of the leaching experiments, added distilled water was infiltrating so slowly that after a certain amount of time it was assumed that the columns were saturated. The assumption that soil columns were completely or almost saturated at the start of leaching run 1 was confirmed with the collection of 75 to 80% of the added distilled water as leachate in the column run. However, only 50 to 55% of added distilled water was collected as leachate in run 2 which either demonstrates the low permeability of the tailings or might be due to the possible incomplete saturation of the columns. For details on the quantity of leachate collected refer to Appendix C. A 100% recovery of the added water was not expected as the biosolids tend to absorb water which either will be held or will slowly evaporate. Less than 100% recovery of added water was also expected due to periods of standing water on top of the columns, some of which likely evaporated. An evaporation column of the same diameter was set up to estimate an upper bound for water lost during the leaching runs due to evaporation. In leaching run 1, evaporation from the evaporation column was 54 mm or 30% of the added water. In run 2, the evaporation from the evaporation column was 64 mm or 40% of the added water. During the saturation phase in the second leaching run, column H started to become a special case ('45 cm' column with 100 dt/ha of biosolids) as approximately one third of the tailings filled into the column eroded out of the column. This was likely due to preferential pathways in the column. Despite that an effort was made to 'plug the holes' by pushing tailings contained in column H into the holes with a steel rod (1 cm in diameter), column H continued for most of the leaching run to release particulates into the leachate. After the saturation phase, biosolids were weighed out separately for every test column. The biosolids alone would have been about 1.6 cm, 4.8-5.0 cm, or 14.4-15 cm high in the soil columns for the tested application rates of 30, 100, and 300 dt/ha respectively. 34 The weighed out biosolids were mixed by hand in a small wash basin with previously weighed out tailings from the 0-15 cm layer. The mixing of upper layer tailings and biosolids was done separately for every column and every pot and once mixed, the tailings/biosolids mixture was carefully loaded into the appropriate column or pot. The mixing of biosolids and tailings by hand is equivalent to very intensive rotovating in the field. After all columns or pots were completely loaded, water for the first day in the first simulated 2-Day storm was added to all columns or pots. 3.5 Emptying of Soil Columns At the end of leaching run 1, soil columns were emptied out by tapping the columns on a clean sheet of plastic on the floor and by cutting off the tailings mass as it came out at 15 cm intervals. Duplicate soil samples of the 15 cm intervals were then bagged into water-tight plastic bags, and the filled bags were stored in the refrigerator at 4°C for further homogenization and analysis. The samples were approximately 750 cm 3 in size. At the end of leaching run 2, soil columns were emptied out by blowing the tailings slowly out of the columns with compressed air while the columns laid on their side on a clean sheet of plastic. Again, duplicate soil samples were cut off in 15 cm intervals and bagged in plastic bags for further homogenization and analysis. This process was fast and worked very well in only leaving a thin film of residue on the sides of the Plexiglas columns. Duplicate samples were also collected from the pots. 3.6 Sample Collection and Data Analysis - Leaching Experiments In general, the record keeping and analysis of samples were more intensive in the second leaching run compared to the first leaching run except for the leachate analysis. 35 Samples that were analyzed for N0 3-N were also analyzed for nitrite (N02-N). In the discussion of results, N O 3 - N plus N0 2-N concentrations are referred to as N0 3-N concentrations since all N0 2-N concentrations were less than 5% of the N0 3-N concentrations. Prior to starting the leaching runs, representative samples of the tailings used in different layers were analyzed for TKN, N0 3-N, N0 2-N, and NH4-N (in duplicate), and 4 to 5 samples of the biosolids used were analyzed for the concentrations of TKN, NH4-N, N0 3-N, N0 2-N, arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), mercury (Hg), molybdenum (Mo), nickel (Ni), selenium (Se), and zinc (Zn). At the end of the first leaching run, the concentrations of TKN, NH4-N, N0 3-N, and N0 2-N were determined with single samples for most layers and columns, and with duplicate samples for the 0-15 and 15-30 cm layers for columns with 100 and 300 dt/ha biosolids. If the measured concentrations were much higher or lower than was expected or than was measured in other columns with the same application rates, the concentration for these samples were determined anew in duplicate. Then, if all concentrations measured for a column layer were in the same range, the geometric mean was assumed to be the sample concentration. If the majority of the samples were in the same range, but one of the concentrations was much lower or much higher than the other concentrations, that concentration was assumed to be an outlier and was not considered in average calculations for the sample concentration. In leaching run 2, all TKN concentrations were determined with duplicate samples for the 0-15 and 15-30 cm layers and with a single sample in the lower layers. All N0 3-N, N0 2-N, and NH4-N concentrations were determined with duplicate samples for the 0-15, 15-30, and 30-45 cm layers and with single samples in the lower layers. If the concentrations measured differed greatly or were higher or lower than in other columns of same application rate and at the same layer depth, those samples 36 were run again in duplicate. The final sample concentrations were determined according to the rules mentioned in the previous paragraph. At the end of both leaching runs, metal concentrations were determined in the shortest and longest columns for the 0, 100, and 300 dt/ha application rates (for the 0-15, 15-30, and 30-45 cm layers). For both leaching runs, leachate was collected and analyzed on 3 days per week for most weeks (first three days of every week or first three days after water additions). Weekly N0 3-N and N0 2-N concentrations were averaged from three measurements done on leachate collected on Days 1, 2, and 3 with a Technicon Autoanalyzer II equipped with a cadmium reduction column. Weekly TKN concentrations were averaged from two measurements done on leachate collected on Days 1 and 2 with a Technicon Autoanalyzer II. Weekly total P (TP) concentrations, and pH and electrical conductivity (EC) were determined manually for composite samples collected on Days 1, 2, and 3 of every week. Leachate samples were analyzed directly for N0 3-N, N0 2-N, pH, and EC and were digested for the determination of TKN (sulfuric acid digestion) and Total P (nitric and sulfuric acid digestion). The element concentrations were determined colorimetrically for N0 3-N, TKN, and Total P. More details about laboratory methods used are included in Appendix O. The determination of the element concentrations in soil or biosolids samples included either a digestion or extraction phase before the determination phase. Prior to digestion or extraction, soil and biosolids samples were homogenized by hand and only small subsamples were used for further analysis. In the soil or biosolids analyses, the < 2 mm fractions were analyzed for: TKN by sulfuric acid digestion, NH4-N, N0 3-N, and N0 2-N by 1 or 2 M potassium chloride extraction, Total P by nitric and 37 sulfuric acid digestion, Hg by cold vapor atomic absorption, Se by hydride atomic absorption, and all other metals by aqua regia digestion and ICP analysis. Digestions or extraction were followed by a colorimetric determination of concentration for TKN, N0 3-N, N0 2-N, NH4-N, and Total P. More details about laboratory methods are included in Appendix O. The soil temperatures were measured automatically every two hours in 10 soil columns (at 10-15 cm depth) with thermocouplers that were connected via an A/D interface to a computer. 3.7 Methods of Data Analysis All data collected was statistically analyzed with SAS software using the General Linear Models (GLM) procedure. The SAS software 'procedure GLM' does not require a balanced experimental design to statistically compare the results of different treatments. Note that running the GLM procedure with a two parameter factorial model for an unbalanced design is equivalent to running a two-way analysis of variance (ANOVA) on the data set of a balanced design. All statistical analysis was conducted at the 0.05 level of probability. In the field trial, the design was unbalanced because only the application rate of 77 dt/ha biosolids was repeated, and in the leaching experiments, the design was unbalanced due to the replication of the 300 dt/ha application rate for the long columns. In the data analysis, 'procedure GLM' was either run with a factorial model with interactions or with the main effects model. Whenever enough data was available, the factorial model was used because its outcome is statistically more sound than the main effects model for two or more parameters. The interpretation of results generated by a factorial or main effects model is discussed below. 38 As a rule of thumb, the degrees of freedom for the error in statistical models should be 30 or greater. In that case, the conclusion that can be drawn from the analysis are well supported as long as the data set contained representative data. The typical degrees of freedom for the error term (or DF for error) in the analysis of field data were below 10 and often only 1 or 2, meaning that conclusions that can be drawn from the tailings analysis are weakly supported. However, a statistical comparison with a model makes the identification of differences between treatments easier than comparing treatments without that tool. The degrees of freedom of the error term in a model can be increased with more observations for the same experimental parameters. 3.7.1 Factorial Model In general, the factorial model y=(Parameter 1)|(Parameter 2) with interactions determines if there is significant difference between the treatments for every parameter in the model and if there is a significant interaction between these parameters. In cases where the interaction term is not significant and where there is a significant difference between the treatments for one or more of the parameters, a simple functional relationship exists between the two parameters. Knowing the value of one parameter, say total metals added to soil, one can estimate the other parameter, say total concentration of metals in soil after application. In cases where there is a significant interaction between the parameters in a factorial model, the values of both parameters have to be known to estimate the final outcome. For example, the tailings analysis determined significant interaction terms for NH4-N concentrations at different application rates and times. The concentration of NH4-N in soil tended to be higher in the early spring than later in the growing season. Thus, both the time of sample collection and the application rate influenced NH4-N concentrations. 39 3.7.2 Main Effects Model The main effect model determines if there is a direct relationship between one or more of the parameters in the model and the measured outcome in the experiment. If none of the parameters in the main effects model are significant, the analysis is complete. Less certain is the interpretation of a parameter that is significant in the main effects model for two or more parameters. In that case, an interaction may or may not exist between the parameters in the model. Certainty about parameter interactions can only be established through the collection of more data and testing with a factorial model. 40 4.0 DISCUSSION OF RESULTS - LEACHING EXPERIMENTS In the discussion of results, laboratory observations, soil nutrient concentrations, soil pH, EC, and soil metal concentrations are discussed before the leachate quality. To allow for easy comparison between the results of the two leaching runs, the same group of parameters is discussed first for leaching run 1 and then for leaching run 2 before comparing the next group of parameters. In the leaching experiments discussed here, a tailings/biosolids mixture was added on top of previously saturated columns followed by repeated additions of distilled water. During the leaching experiments, unsaturated zones might have formed in the columns which might have led to an underestimation of N0 3-N leaching. However, since the field conditions in Princeton (a semi-arid zone) are not expected to be in a saturated state for long periods of the year, the conclusions drawn from the leaching experiments are expected to be representative of field conditions. In the discussion of results, the Level of Detection (LOD) refers to the lowest concentration of analyte that an instrument could detect and that could be statistically differentiated from the background signal. Typically, the LOD is the mean of replicate blank signals plus 3 times the standard deviation of low level replicates (99% confidence that the analyte was actually detected). However, concentrations close to the LOD are only qualitatively detected. In the discussion of results, the Limit of Quantification (LOQ) refers to the concentration of analyte above which quantitative results may be obtained with a specified degree of confidence. Typically, the LOQ is the mean of replicate blank signals plus 10 times the standard deviation of low level replicates (30% accuracy). In the data analysis, if concentrations were below the detection limit, half the detection limit was assumed to be the sample concentration. 41 4.1 Laboratory Observations The permeability of the tailings was overestimated in the design calculations in which the tailings were assumed to be coarser than was measured in the laboratory. Nitrate movement through coarse tailings can be fast and far. Particle size distribution measurements showed that layers in the 0-90 cm layer consisted of silt, silty clay, silty clay loam, or silty loam with estimated coefficients of permeability ranging from 8.2E-05 m/s to 1.0E-10 m/s. Run 2 laboratory records of the drainage of standing water on top of the control columns led to the calculation of a coefficient of permeability of 2.5E-08 m/s (0.002 m/day) when assuming Darcy's Law for vertical flow and falling head (Eq. 2). This observation seems to be confirmed by field results which showed that mineral N moved downwards at approximately 15 cm per growing season (~0.001 m/day). Lesser downward movement of water is expected in the field compared to the laboratory since in the field, water evapotranspires. For information concerning the particle size distribution and coefficients of permeability, refer to Appendix J and for field data refer to Appendix M. In general, the duplicate soil N0 3-N and NH4-N concentrations did not fluctuate as much as the TKN concentrations which was likely due to the greater sample sizes for the N0 3-N and NH4-N analyses (10-11 g) compared to the TKN analysis (1-3 g). The heights of the standing water measured on top of the leaching columns in the first weeks of the second leaching run were interesting. In general, the shortest columns drained faster than the longer columns followed by columns that received the highest application rates of biosolids confirming the high capacity of biosolids to absorb water. By Day 40 all columns were dry. Refer to Appendix C for details. During leaching run 2, the structural instability of four of the soil columns was noticed. Two of these soil columns were control columns (A and F) and two were short treatment columns (G and H). In these four columns, surface cracks tended to develop which eroded when water was added to the soil 42 columns. It appears that biosolids in the other columns provided greater aggregate stability and mulching on top of the soil columns since no or little surface cracking was noticed. During leaching run 2, erosion of tailings out of columns A, F, G, and H ranged from 1-20 g particulates per collection of turbid leachate. The occurrence of particulates in the leachate is detailed in Appendix C. 4.2 Nitrogen, pH and Electrical Conductivity in Soil In general, the variation between columns which underwent the same treatment was greater than anticipated in the experimental design phase. The statistical analysis was helpful in identifying trends in the element concentrations but in hindsight higher replication of the experiment would have been advised. The statistical analysis consisted of a factorial analysis with the two parameters 'column length' and 'application rate'. The data analysis was conducted for every 15 cm layer separately, but due to fewer long columns, the results for the layers below 45 cm are less well supported than results for the upper column layers. The results of N balance calculations were similar for both leaching column runs and the pot trial and are therefore discussed together in section 4.4. 4.2.1 Nitrogen, pH, and EC in Soil - Leaching Run 1 In leaching run 1, levels of TKN, NH4-N, NCyN, and EC were significantly different for either application rate or column length in some of the layers, but the soil pH was unaffected by the treatments. An overview of the results is shown in Table 4 and detailed information is included in Appendix D. As expected, the concentration of TKN increased significantly in the 0-15 and 15-30 cm layers with application rate. For the 30 dt/ha application rate, the TKN concentration increased in the 0-15 cm 43 T A B L E 4. SOIL NITROGEN, pH, EC - RUN 1 DEPTH 1:2 pH 1:2 EC TKN NH4-N N03-N (dS/m) (mg/kg) (mg/kg) (mg/kg) 0 -15 cm Mean 7.3 A P P L sig. A P P L sig. 41.2 A P P L sig. Std. Dev. 0.2 125.6 15 - 30 cm Mean 7.5 A P P L sig. A P P L sig. LENGTH 14.6 Std. Dev. 0.2 sig. 14.2 30 - 45 cm Mean 7.6 A P P L sig. 41.7 14.6 A P P L and Std. Dev. 0.2 32.9 31.5 LENGTH sig. 45 - 60 cm Mean 7.5 0.3 19.5 3.0 0.2 Std. Dev. 0.3 0.1 5.0 2.3 60 - 75 cm Mean 7.6 0.3 24.1 3.6 0.2 Std. Dev. 0.1 0.1 8.9 1.7 75 - 90 cm Mean 7.6 0.4 21.9 A P P L sig. 0.2 Std. Dev. 0.1 0.1 5.2 TKN (mg/kg) Depth / Appl. # of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0-15 cm 26 22 c 490 c 1917 b 5502 a 15 - 30 cm 26 21 b 45 b 250 b 2243 a 30 - 45 cm 26 avg. value: 42 45 - 60 cm 18 avg. value: 20 60 - 75 cm 10 avg. value: 24 75 - 90 cm 10 avg. value: 22 N03-N (mg/kg) Depth / Appl. # of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 26 0.2 b 38 b 139 a 211 a 15 - 30 cm 26 avg. value: 15 30 - 45 cm * 26 0.2 b | 0.4 b | 2.3 a | 0.8 b 45 - 60 cm 18 avg. value: 0.2 60 - 75 cm 10 avg. value: 0.2 75 - 90 cm 10 avg. value: 0.2 1:2 EC(dS/m) Depth / Appl. # of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 26 0.1 c 0.4 c 1 b 2 a 15 - 30 cm 26 0.2 c 0.2 c 0.3 b 0.8 a 30 - 45 cm 26 0.2 c 0.2 c 0.3 b 0.4 a 45 - 60 cm 18 avg. value: 0.3 60 - 75 cm 10 avg. value: 0.3 75 - 90 cm 10 avg. value: 0.4 The concentration of N03-N is also dependent on the length of the columns. 30-45 cm N03-N (mg/kg): LENGTH _0-45 cm Col. _0-60 cm Col. 0-90 cm Col. Duncan Group. Mean N a 1.9 8 b 0.5 8 b 0.4 10 15-30 cm NH4-N (mg/kg): LENGTH _0-90 cm Col. _0-60 cm Col. _0-45 cm Col. Notes: 'Std. Dev. ' refers to the sample standard deviation. Means followed or preceded by the same letter are not significantly different at the 0.05 level of probability. # of Obs. Number of observations in data set Duncan Group. Mean N a 78 10 b 14-, 8 b 13 8 44 layer whereas for the 100 and 300 dt/ha application rates, the TKN concentrations increased in the 0-15 and 15-30 cm layers with the highest increases in the 0-15 cm layer. In the 15-30 cm layer, the TKN concentrations were only significantly higher for the 300 dt/ha application rate. The soil N0 3-N concentration varied significantly in the 0-15 and 30-45 cm layers. As expected, the N0 3-N concentration increased with increasing application rates in the 0-15 cm layer. In the 30-45 cm layer, the concentration of N0 3-N was dependent on the column length and application rate, but N0 3 -N concentrations were low (< 2.3 mg/kg). Since column length is inversely related to better drainage, a higher concentration of N0 3-N in lower layers of shorter columns is not surprising. The concentration of NH4-N varied significantly with column length in the 15-30 cm layer and with application rates in the 75-90 cm layer. The NH4-N concentration in the 15-30 cm layer increased with increasing column length. This result is likely due to decreased aeration caused by poorer drainage in the longer soil columns. The difference between the NH4-N concentrations in the 75-90 cm layer were statistically significant as far as the numbers are concerned but since all the concentrations are below the Limit of Quantification (10 mg/kg), the analytical result is of little importance. The high NH4-N concentrations measured in the 0-15 cm layer for column 5 (445 mg/kg; '90 cm' column) and column 9 (416 mg/kg; '45 cm' column), both of which received 300 dt/ha biosolids were not statistically significant because the high NH4-N concentrations were not repeated in the other columns of same column length and application rate. The EC increased with increasing application rates but was comparable to the control columns for 30 dt/ha biosolids application rate. The EC decreased with depth as was expected. Assuming a factor of 2 for converting the 1:2 extraction EC to saturation extract EC, crops are not expected to be negatively affected for 30 and 100 dt/ha biosolids application rates, but sensitive crops may be affected by the 300 dt/ha application rate (Foth, 1984). 45 4.2.2 Nitrogen, pH, and EC in Soil - Leaching Run 2 At the end of the second leaching run, the levels for Loss on Ignition (LOI), TKN, NH 4-N, N0 3-N, and pH varied significantly for the application rates tested. Table 5 shows an overview of LOI, N, and soil pH and EC results and Appendix E includes further details for leaching run 2. As expected, the percentage of organic matter in the soil columns increased with increasing application rates in the 0-15 cm layer for all application rates and in the 15-30 cm layer for the highest application rate (300 dt/ha). As the dry density of the biosolids is lower than the dry density of the tailings, the biosolids tended to float up to the 0-15 cm layer for the highest application rates even if they had been distributed evenly at the start of the leaching run. Therefore, the %LOI in the 0-15 cm layer was usually higher than the %LOI in the 15-30 cm layer for the 300 dt/ha application rate. For the 0, 30, 100 and 300 dt/ha application rates of freshly dewatered anaerobically digested biosolids, the %LOI is approximately 1.2, 2.5, 5.0, and 11.1 respectively in the 0-15 cm layer, and 1.1, 1.8, 3.4, and 9.9 respectively in the 0-30 cm layer. As expected, the TKN concentration increased with increasing application rates in the 0-15 cm layer and was significantly higher in columns with 300 dt/ha biosolids in the 15-30 and 30-45 cm layers. The absolute TKN concentrations were higher for the 30, 100 and 300 dt/ha application rates than for the 0 dt/ha application rate in the 15-30 and 30-45 cm layers. The concentrations of NH4-N and N0 3-N in the 0-45 cm layer were interesting. In the columns in leaching run 2, the absolute concentrations of NH4-N increased with increasing application rates in the 15-30 and 30-45 cm layers whereas N0 3-N increased with increasing application rates in the 0-15 cm layer. For NH4-N, the statistical increase in the 15-30 and 30-45 cm layers was significant for the 100 and 300 dt/ha application rates and comparable for the 0 and 30 dt/ha application rates. In the pot trial, the NH4-N concentration was only significantly higher for the 300 dt/ha application rate and the TABLE 5. SOIL NITROGEN, pH, EC - RUN 2 Loss on DEPTH: 1:2 pH 1:2 EC Ignition TKN NH4-N N03-N (dS/m) (%) (mg/kg) (mg/kg) (mg/kg) 0 -15 cm Mean 7.3 2.0 APPL sig. APPL sig. 90.4 APPL sig. Std. Dev. 0.2 1.3 87.2 15-30 cm Mean 7.5 1.3 APPL sig. APPL sig. APPL sig. 102.1 Std. Dev. 0.2 1.0 143.6 30 - 45 cm Mean APPL sig. 0.6 n/a APPL sig. APPL sig. 25.7 Std. Dev. 0.3 40.2 45 - 60 cm Mean 7.5 0.5 n/a 28.6 8.2 0.7 Std. Dev. 0.1 0.3 21.1 18.2 1.0 60 - 75 cm Mean 7.4 0.6 n/a 20.0 2.6 0.4 Std. Dev. 0.1 0.3 11.2 2.4 0.5 75 - 90 cm Mean 7.4 0.7 n/a 13.6 1.7 0.1 Std. Dev. 0.1 0.5 8.3 1.2 0.0 Pot Trial Mean n/a n/a APPL sig. APPL sig. APPL sig. APPL sig. Loss on Ignition Depth / Appl. #of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 19 1.2 d 2.5 c 5 b 11 a 15 - 30 cm 21 1 b 1.1 b 1.8 b 8.7 a Pot Trial 10 0.7 d 2.4 c 5.8 b 11.2 a TKN (mg/kg) Depth / Appl. # of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 26 52 d 725 c 2252 b 4791 a 15 - 30 cm 26 40 b 151 b 583 b 4401 a 30 - 45 cm 26 26 b 30 b 69 b 386 a 45 - 60 cm 18 avg. value: 29 60 - 75 cm 10 avg. value: 20 75 - 90 cm 10 avg. value: 13.6 Pot Trial 10 27 c 516 c 1925 b 5008 a NH4-N (mg/kg) Depth / Appl. # of Obs. 0 dt/ha | 30 dt/ha | 100 dt/ha | 300 dt/ha 0 -15 cm 26 avg. value: 90.4 15 - 30 cm 26 1 c 46 c 255 b 723 a 30 - 45 cm 26 1 c 6 be 39 b 251 a 45 - 60 cm 18 avg. value: 8.2 60 - 75 cm 10 avg. value: 2.6 75 - 90 cm 10 avg. value: 1.7 Pot Trial 10 1 b 3.2 b 5 b 19.1 a N03-N (mg/kg) Depth / Appl. # of Obs. 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 26 0.1 c 235 be 702 ab 928 a 15 - 30 cm 26 avg. value: 102 30 - 45 cm 26 avg. value: 25.7 45 - 60 cm 18 avg. value: 0.7 60 - 75 cm 10 avg. value: 0.4 75 - 90 cm 10 avg. value: 0.1 Pot Trial 10 9 c 247 b 295 b 615 a 30-45 cm 1:2 pH: Duncan Grouping Mean N APPL a 7.8 8 _300 dt/ha b 7.5 6 _100 dt/ha c b 7.4 6 _ 30 dt/ha c 7.3 6 0 dt/ha Notes: 'Std. Dev.' refers to the sample standard deviation. Means followed or preceded by the same letter are not significantly different at the 0.05 level of probability. # of Obs. Number of observations in data set 47 N0 3-N concentration tended to increase with increasing application rates, but was comparable for the 30 and 100 dt/ha application rates. The almost complete conversion of NH4-N to N0 3-N in the 0-15 cm layer demonstrates that the soil surface is much better aerated than are lower layers. It is noteworthy that the average N0 3-N concentrations in the 0-15 cm layer tended to be 300 to 400 mg/kg lower for the pots than for the soil columns for the 100 and 300 dt/ha application rates. The lower concentration of N0 3-N in the pots may be a result of droughty conditions. Since the pots drained easily after every water addition, the pots tended to dry out completely (air-dry) between water additions, especially when the water additions were weeks apart. In contrast, the soil surface in the soil columns needed longer to dry out since the tailings were draining poorly. The pH varied significantly in the 30-45 cm layer with the highest pH measured for the highest application rate which seems surprising since soil pH tends to decrease with increased nitrification. Since the absolute differences between the pH levels measured were small, the difference in pH in the 30-45 cm was probably due to variations in the tailings between columns rather than between treatments. 4.3 Mineral Nitrogen 4.3.1 Mineral Nitrogen - Leaching Run 1 In leaching run 1, the available (mineral) N tended to increase with increasing application rates except for the '60 cm' columns filled with tailings from site 1 (P3a-R3) in which the mineral N content was lower for the 300 dt/ha columns than the 100 dt/ha columns. The highest measured mineral N content in the 0-45 cm layer was 745 kg N/ha. Details of the mineral N that was available in the soil columns of leaching experiment 1 are included in the Laboratory Data section of Appendix D. 48 Note that in leaching run 1, the measured background NH4-N concentrations were higher than were measured in the field for similar tailings (see Appendix M). The results seemed to be systematic for the first leaching run and may be the result of NH4-N contamination of the KCI extractant (KCI salt) that was used for the first run. The actual background NH4-N concentrations for run 1 were probably less than 1 mg/kg. 4.3.2 Mineral Nitrogen - Leaching Run 2 Although mineral N in the 0-45 cm layer increased with increasing application rates in both leaching runs, much more mineral N was available in the second leaching run compared to the first leaching run. While in the first leaching run mineral N ranged from 200 to 745 kg/ha, mineral N in the second leaching run ranged from 1200 to 3000 kg N/ha for the 300 dt/ha application rate. Mineral N details are shown in Table 6 or can be found in the laboratory data section of Appendix E. The difference in mineralization rates between the column runs is discussed in section 4.4. The higher mineral N contents in leaching run 2 compared to run 1 are likely due to better mineralization and nitrification conditions, as the soil surfaces of the columns were allowed to dry out between water additions in the latter stages of the run. The drying periods likely facilitated better aeration and hence contributed to better nitrification conditions. In leaching run 2, the mineral N concentrations varied between 1050 and 2100 kg N/ha for the 100 dt/ha application rate and between 1300 and 3000 kg N/ha for the 300 dt/ha application rate. The high variation measured in the 90 cm duplicate columns 4 and 5, and D and E (300 dt/ha) was surprising. In the 0-45 cm layer, the mineral N contents for columns 4 and 5 were 2200 and 1300 kg N/ha respectively and for columns D and E the mineral N contents were 1800 and 3000 kg N/ha respectively. This wide variation stresses the importance of high replication of the experimental setup T A B L E 6. M I N E R A L N IN SOIL - L E A C H I N G E X P E R I M E N T S COLUMN TRIALS (0-45 cm PROFILE) Col.: Column Length: Appl. Rate: LEACHING RUN 1 LEACHING RUN 2 NH4-N N03-N NH4-N + N03-N NH4-N N03-N NH4-N + N03-N (cm) (dt/ha) (kg/ha) (kg/ha) (kg/ha) (kg/ha) (kg/ha) (kg/ha) C1 0-90 0 23 3 25 6 1 7 C 2 0-90 30 81 5 86 71 552 623 C 3 0-90 100 191 340 531 542 539 1081 C 4 0-90 300 361 264 625 900 1345 2245 C 5 0-90 300 671 14 684 1037 293 1329 C 6 0-45 0 17 2 19 6 1 7 C 7 0-45 30 21 113 134 95 349 444 C 8 0-45 100 70 268 338 502 1669 2170 C 9 0-45 300 459 286 744 1003 232 1235 C 1 0 0-60 0 17 1 18 13 1 14 C11 0-60 30 32 130 162 75 183 257 C 1 2 0-60 100 67 245 311 533 790 1323 C 1 3 0-60 300 103 206 309 1606 751 2356 C - A 0-90 0 17 1 18 6 0 6 C - B 0-90 30 65 95 161 50 708 758 C - C 0-90 100 91 140 231 429 946 1374 C - D 0-90 300 260 189 449 815 1009 1824 C - E 0-90 300 200 314 515 1289 1716 3005 C - F 0-45 0 14 1 15 9 0 10 C - G 0-45 30 23 44 67 27 752 779 C - H 0-45 100 12 146 157 240 940 1180 C- l 0-45 300 99 135 234 879 443 1321 C - J 0-60 0 12 1 13 7 0 7 C - K 0-60 30 12 6 18 143 239 382 C - L 0-60 100 18 184 202 710 632 1342 C - M 0-60 300 48 269 316 1037 714 1751 POT TRIAL (0-15 cm PROFILE) Appl. Rate: NH4-N N03-N NH4-N + N03-N (dt/ha) (kg/ha) (kg/ha) (kg/ha) 0 < 3 11 < 14 30 8 316 324 30 2 326 328 30 1 248 249 100 8 355 363 100 6 437 443 100 6 336 342 300 26 974 999 300 25 870 894 300 34 875 909 50 and demonstrates the high variability of the mineralization and nitrification rates under virtually the same conditions. At the end of the second leaching run, the mineral N available in the pots was about 60 mg/kg higher for the 30 dt/ha application rate and 600 and 200 mg/kg lower for the 100 and 300 dt/ha application rates respectively (0-15 cm layer). In the pots, the available N content was probably less than in the columns due to droughtier conditions in the latter weeks of run 2 (below 80-90% water filled soil pores). However, the available N in the pots was much higher than in the first leaching run likely due to the different water regime in the second leaching run, better aeration in the pots (better drainage), and the longer experimental phase. In the pot trials, almost all mineral N was available in the form of N0 3-N as was most of the available N in the columns in the 0-15 cm layer. This result stresses the importance of appropriate N fertilizer application rates for well drained soils since N0 3-N not only leaches faster (hence further), but also constitutes the majority of available N. 4.4 Soil Nitrogen Balance - Leaching Experiments An approximate soil N balance was calculated for all columns in leaching runs 1 and 2 and the pot trial. In the N balance calculations, the tailings background N and N at the end of the runs were calculated from dry weight nutrient concentrations in a soil layer multiplied by the amount of material in that layer using equations 3 or 4 (see below). The amount of N added to the columns or pots was determined from the TKN, NH4-N, and N0 3-N dry weight concentrations in biosolids multiplied by the amount of biosolids added per column. The total soil N was assumed to be the sum of TKN and N0 3 -N (kg N/ha). Refer to Table 7 for a summary of results of the N balance calculations. More details are included in Appendix D for leaching run 1 and Appendix E for leaching run 2 and the pot trial. 51 kgN y mgN z kg 652315.7 * 153.3 cm 2 1 x = * * * Eq.3 ha*15cm kg (15 cm layer) ha 106 where x amount of N per hectare in a 15 cm layer [kg N/ha] y concentration of the parameter determined with one of the methods specified in Appendix O [mg/kg] z dry weight of the tailings or tailings/biosolids mixture in a 15 cm layer z = (wet weight)*(1 - Soil Moisture [%]/100) [kg] 153.3 cm 2 = inside surface area of the soil columns mg N y mg N z kg x = — * E q 4 column kg (45 cm layer) where x amount of N per 45 cm layer [mg N/(45 cm layer)] y concentration of the parameter determined with one of the methods specified in Appendix O [mg/kg] z dry weight of the tailings or tailings/biosolids mixture in a 45 cm layer z = (wet weight)*(1 - Soil Moisture [%]/100) [kg] The absolute N balance numbers differed between the leaching experiments, but all experiments showed a similar trend. At the end of the leaching runs, the absolute amount of N lost and the absolute amounts of total N in the columns increased with increasing application rates. However, separate statistical comparisons for data collected in the two columns runs and the pot trial revealed that N losses were only significantly higher for the 300 dt/ha application rate indicating high variations between columns with the same treatment. Generally, the N losses were much higher than was anticipated by the author. For the highest biosolids application rate (300 dt/ha), the N losses were substantial (30-34%) and were coupled with low retention of mineral N in the soil. For the 300 dt/ha application rate, likely contributors to this result were anaerobic conditions in the 15-30 cm layer resulting from high biological activity in the 30 cm thick tailings/biosolids layer, and mineralization and nitrification in the 52 surface layer. Nitrate close to the soil surface could have easily denitrified after the addition of water to the columns and the temporary creation of anoxic conditions. TABLE 7. SOIL NITROGEN BALANCE - LEACHING EXPERIMENTS Application Rate (dt/ha): 0 30 100 300 Added N : Run1 (mg N/(45 cm layer)) 0 1643 5477 16432 Run2 (mg N/(45 cm layer)) 0 1927 6421 19265 Pot Trial (mg N/(15 cm layer)) 0 1927 6421 19265 Soil N at Start: Run1 (mg N/(45 cm layer)) 138 d 1781 c 5612 b 16551 a Run2 (mg N/(45 cm layer)) 233 d 2135 c 6643 b 19507 a Pot Trial (mg N/(15 cm layer)) 66 d 1995 c 6494 b 19349 a Soil N at End: Run1 (mg N/(45 cm layer)) 129 c 1263 c 4577 b 11647 a Run2 (mg N/(45 cm layer)) 175 d 2001 c 6107 b 13634 a Pot Trial (mg N/(15 cm layer)) 66 c 1408 be 4337 b 12711 a Soil N lost: Run1 (mg N/(45 cm layer)) 9 b 518 b 1036 b 4904 a Run2 (mg N/(45 cm layer)) 57 b 134 b 536 b 5874 a Pot Trial (mg N/(15 cm layer)) 0 b 587 b 2157 b 6638 a % of Added N lost: Run1 (mg N/(45 cm layer)) 32% 19% 30% Run2 (mg N/(45 cm layer)) 7% 8% 30% Pot Trial (mg N/(15 cm layer)) 30% 34% 34% Notes: The data analysis was conducted separately for column runs 1 and 2 (26 observations) and the pot trial (10 observations). Means followed by the same letter are not significantly different at the 0.05 level of probability. Other likely contributing factors to the high N losses were: good mixing of the tailings with the biosolids (higher mineralization rate), no vegetation cover that could take up available N or could impede volatilization, optimal pH for mineralization and nitrification, relatively warm soil temperatures (> 14°C, avg. ~17.5°C), and relatively high concentration of bacteria in the biosolids at the time of application. Anaerobic bacteria, like methanogens which were present in biosolids at the time of application and which established during the anaerobic digestion treatment process (14-17 days retention time), likely mineralized N anaerobically, especially in the first few weeks of the experiments. 53 On average, the total N losses in the column studies were lower in the second leaching run than in the first leaching run, however, most N was lost in the pot trial. Furthermore, the relative N losses were even greater for the pots than the columns because the N balance calculations included the 0-45 cm layer for the leaching columns and the 0-15 cm layer for the pot trial. In the column runs, the majority of N losses were probably due to denitrification followed by volatilization losses and small leaching losses. As mineral N was mainly in the form of N0 3-N in the 0-15 cm layer (at the end of the runs), the addition of water to the columns likely changed the aerobic conditions to anoxic conditions which in the presence of N0 3-N and organic C create excellent conditions for denitrification. Volatilization losses were probably responsible for higher N losses in the early stages of the experiment, especially in the mixing phase of tailings and biosolids which was an odoriferous undertaking, and in the first few weeks of the runs with standing water on top of the soil columns (simulation of spring melt conditions). Volatilization losses throughout the remainder of the runs were probably smaller as N0 3-N dominated the 0-15 cm layer. Generally, NH4-N volatilization from soil is highest when the soil moisture content is near field capacity and when slow drying conditions exist for several days (Tisdale et al., 1993). In the pot trial, denitrification and N0 3-N leaching were likely responsible for the biggest N losses followed by volatilization. Since most of the available N in the pots was in the form of N0 3-N at the end of the run, the addition of water could have created temporarily anoxic conditions which could have favoured denitrification. Possibly, N0 3-N leaching was substantial due to the high N0 3-N concentrations in the pots and good drainage. The extent of N0 3-N leaching cannot be quantified as no leachate was collected for analysis from the pots. Volatilization losses were likely larger at the start compared to the end of the pot trial due to the 11% NH4-N content of TKN in the biosolids. To be able to compare and assess the mineralization behaviour of biosolids added to copper tailings, an overview table based on the soil data was created that details the percentile distribution of the 54 added total N at the end of the run. The overview table, Table 8, shows the percent of added N in the form of soil mineral N, the percent of N that was lost (unaccounted N), and the estimated mineralization rates at the end of the leaching runs. Higher than expected were the mineralization rate and the amount of N lost from the soil columns. For example, the U.S. EPA (1983) assumes that about 20% of the organic N contained in biosolids mineralizes in the soil and that 10 to 15% unaccountable N losses occur in the first year after application. In this study, the average estimated mineralization rates ranged from 17 to 31% over 10 weeks for column run 1, from 29% to 38% over 13 weeks for column run 2, and from 30 to 43% over 13 weeks for the pot trial. These higher mineralization rates are likely due to the same beneficial conditions for mineralization and nitrification that were mentioned in the previous paragraphs discussing factors contributing to high N losses. There appeared to be a trend towards either low mineral N content in the soil and high N losses or higher retention of mineral N in the soil and lower N losses. For example, for the 300 dt/ha application rate, the mineral N in soil ranged from 2-6% in column run 1, from 10-24% in column run 2, and from 7-8% in the pot trial whereas the N losses ranged from 12-51% for column run 1, from 26-37% for column run 2, and from 22-42% for the pot trial. In the leaching columns, errors in estimating the N content in columns could have been introduced by under- or overestimating the amount of material contained in soil layers or by erring in the laboratory analysis. In the laboratory, especially the over- or underestimation of soil TKN could have occurred since only small sample sizes were used for the highest application rates (1.-2 g). To confirm N concentrations measured in the leaching tests, additional samples were analyzed for the 30, 100, and 300 dt/ha application rates and 0-15 and 15-30 cm layers (one sample per column and layer), but the concentrations tended to be all of the same order of magnitude as had been measured previously. 55 T A B L E 8. P E R C E N T O F A D D E D NITROGEN A S MINERAL N A N D U N A C C O U N T E D N COLUMN TRIALS (0-45 cm PROFILE) Col.: Column Length: Appl. Rate: LEACHING RUN 1 LEACHING RUN 2 % o f Added N as Mineral N in soil % o f Added N lost Estimated Mineralization Rate of Organic N % o f Added N as Mineral N in soil % of Added N lost Estimated Mineralization Rate of Organic N (cm) (dt/ha) C 2 0-90 30 8% 27% 25% 50% 1% 39% C 3 0-90 100 15% 7% 12% 26% 13% 27% C4 0-90 300 6% 19% 15% 18% 30% 36% C 5 0-90 300 6% 12% 8% 11% 37% 36% C7 0-45 30 13% 32% 34% 35% 2 1 % 4 5 % C8 0-45 100 9% 25% 24% 5 2 % 2 % 4 2 % C 9 . 0-45 300 7% 15% 12% 10% 28% 26% C11 0-60 30 15% 4% 9% 20% 9% 18% C12 0-60 100 9% 22% 20% 3 2 % 13% 3 3 % C13 0-60 300 3% 14% 7% 19% 2 9 % 36% C-B 0-90 30 15% 4 1 % 46% 60% 1% 50% C - C 0-90 100 6% 26% 2 2 % 3 3 % 5% 26% C-D 0-90 300 4 % 4 3 % 37% 15% 28% 3 1 % C - E 0-90 300 5% 44% 39% 24% 26% 38% C - G 0-45 30 6% 39% 35% 6 2 % 0% 50% C-H 0-45 100 4 % 4 % - 2 % 28% 0% 17% C-l 0-45 300 2 % 5 1 % 4 3 % 11% 34% 3 3 % C-K 0-60 30 2 % 46% 37% 30% 10% 29% C-L 0-60 100 6% 29% 24% 32% 10% 30% C - M 0-60 300 3% 4 1 % 34% 14% 3 1 % 3 3 % POT TRIAL (0-15 cm PROFILE) Appl. Rate: % o f Added N as Mineral N in soil % o f Added N lost Estimated Mineralization Rate of Organic N Average (dt/ha) 30 26% 22% 36% 30 26% 30% 44% 4 3 % 30 20% 3 9 % 47% 100 9% 3 3 % 30% • 100 1 1 % 2 5 % 24% 3 1 % 100 8% 4 2 % 38% 300 8% 2 2 % 18% 300 7% 4 2 % 37% 30% 300 7% 4 0 % 35% COLUMN TRIALS (0-45 cm PROFILE) Appl. Rate: Estimated Mineralization Rate of Organic N RUN 1 RUN 2 (dt/ha) 30 3 1 % 38% 100 17% 2 9 % 300 2 4 % 3 4 % Estimated Mineral. Rate of Organic N in Biosolids = Mineral N in soil + N losses - (NH4-N in biosolids at the time of application) [%] 56 In general, variations in the data could probably have been made smaller by analyzing more samples per column and layer for TKN and N0 3-N to determine better individual estimates and by using larger samples sizes for the TKN analysis than was possible in the BIOE Lab. However, wide variations in the mineralization of organic N in biosolids after incorporation in soils have been mentioned in the literature (Williams et al., 1984; Sopper, 1993) which this study confirms, and high variations in column studies have also been mentioned by Elder (1988). For future research, it is encouraging that the mineralization rates in column run 2 and the pot trial were similar. This result suggests that the mineralization of N can be studied in shorter soil columns which are much easier to set up and to keep in a controlled atmosphere than the longer columns. In the author's opinion, the mineralization rate should be studied in more detail and under more controlled conditions. The samples sizes for the TKN measurement should be increased (at least doubled) and the digestion should be done in larger vessels. 4.5 Metals in Soil In leaching runs 1 and 2, the metal concentrations in the 0-15, 15-30, and 30-45 cm layers were determined for the '45 cm' and '90 cm' columns only. The laboratory results were again compared with a factorial model using 'application rate' and 'column length' as parameters to determine significant differences between the treatments. Refer to Appendices F and G for laboratory and analytical results for leaching runs 1 and 2 respectively. 4.5.1 Metals in Soil - Leaching Run 1 In leaching run 1, the metal analysis of soil samples from the '45 cm' and '90 cm' columns showed that all metal concentrations were below the lowest of the CCME remediation criteria for agricultural or 57 residential soils (1991) except for the Hg concentration in the 0-15 cm layer columns with 300 dt/ha biosolids and Cu in all tested layers. An overview of the data analysis in shown in Table 9 and for more details refer to Appendix F. In leaching run 1, the only significant changes in the element concentration were measured in the 0-15 cm layer for Hg and Zn. The highest measured Hg concentration was 1.2 mg/kg which is above the CCME criterion for agricultural soils but below the CCME criterion for residential soils (1991) and clearly above the Limit of Quantification for Hg (0.6 mg/kg). According to Bohn et al. (1985), the Hg concentrations measured in the samples were above normal soil levels for the 100 and 300 dt/ha application rate in the 0-15 cm layer. The concentration of Zn increased with increasing application rates of biosolids which is not surprising due to the higher concentration of Zn in the biosolids (621 mg/kg) compared to the tailings (69 mg/kg). 4.5.2 Metals in Soil - Leaching Run 2 (Soil Columns) In leaching run 2, more significant differences for metal concentrations were identified than for leaching run 1 which may indicate a greater intrinsic uniformity of the tailings in run 2 than in run 1. In leaching run 2, metal concentrations in the soil columns were below the lowest of the CCME criteria for agricultural and residential use (1991) and were in the normal range for soils according to Bohn et al. (1985) with the exception of the Hg concentrations in the 0-15 and 15-30 cm layers for columns with 300 dt/ha biosolids and Cu concentrations in all layers and columns. Refer to Table 10 or Appendix G for details on run 2 metal concentrations. In run 2, significant increases with increasing application rates were measured in the 0-15 and 15-30 cm layers for Pb, Hg, Se, and Zn whereas the Co concentration decreased with increasing application rates in the 15-30 cm layer. As expected, the highest metal increases were measured in the 0-15 cm 58 N 2 o o CO 0 . < SI E 3 C 0 CD ( 0 a s s a cd I Z D 01 o CO z CO -I < r -LU S - i < i -o m _i m < •o n >. o 3 . 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In the 0-15 cm layer of the 300 dt/ha columns, the Hg concentration was only 0.1 mg/kg above the CCME (1991) remediation criterion for agricultural use and was below the CCME criterion for residential use. According to Bohn et al. (1985), the Hg concentration was above the normal levels for soils in the 0-15 cm layer for the 100 dt/ha application rate and the 0-15 and 15-30 cm layers for the 300 dt/ha application rate. Increasing Hg concentration with increasing application rates is not surprising since the tailings are low in Hg (~0.1 mg/kg) and the biosolids applied contained 5.7 mg/kg Hg. 4.6 Leachate Quality Leachate was collected on a weekly basis from all soil columns in leaching runs 1 and 2. In general, the leachate was as clear as distilled water with exception of particulates in the leachate on some days for some columns. Refer to Appendix C for details on particulates in the collected leachate. Refer to Appendices H and I for detailed results for leaching runs 1 and 2 respectively. Information in Appendices H and I is arranged in the order of N0 3-N data analysis and laboratory results, TKN data analysis and laboratory results, total P laboratory results, and finally leachate pH and EC results. Estimates of the total amounts of N0 3-N, TKN, and TP in the leachate are also included in the laboratory data sections of Appendices H and I. Total amounts of nutrients in the leachate were calculated by summing the products of (weekly nutrients concentrations) times (weekly leachate volume). 61 4.6.1 Leachate Quality - Leaching Run 1 4.6.1.1 Leachate Quality - Run 1 - Nitrate The measured N0 3-N concentrations in the first leaching run were very low. The average N0 3-N concentration measured was 0.02 mg/L and the total amount of N0 3-N lost through leaching was less than 0.37 kg/ha. The highest daily maximum N0 3-N concentration was 2.1 mg/L which is well below the maximum N0 3-N concentration allowed in drinking water (10 mg/L). Thus in leaching run 1, the contribution of N0 3-N in leachate was negligible in the overall N balance. Refer to Table 11 or Appendix H for details on N0 3-N in leachate. 4.6.1.2 Leachate Quality - Run 1 - TKN In leaching run 1, the average TKN concentrations measured were generally low (< 0.5 mg/L) for all weeks except weeks 4, 5, and 6 of the experiment. In these weeks, the TKN concentrations in the leachate tended to be higher for the short columns especially for the highest application rate (300 dt/ha). The highest weekly TKN concentration was 6.7 mg/L measured in week 6 for the '45 cm' columns with 300 dt/ha of added biosolids. The maximum daily TKN concentrations ranged from 0.1 to 24.9 mg/L with an average daily maximum concentration of 3.1 mg/L. In leaching run 1, the contribution of TKN in leachate to the overall N balance was greater than the N0 3-N contribution but was below 0.07% of the N added. Starting in week 4 of leaching run 1, the measured TKN concentration tended to be higher for the higher application rates. Refer to Table 12 or Appendix H for details. The TKN concentrations in weeks 5 and 6 were higher than expected and are likely due to the build-up of preferential channels in the shorter soil columns after a few weeks of water additions. The preferential flow channels may have allowed the flow of small pieces of biosolids to the bottom of the columns and into the leachate collecting bottle, however, the leachate from the short 300 dt/ha columns (columns 9 and I) was as clear as distilled water. The one time measurement of 24.9 mg/L 62 T A B L E 11. N ITRATE IN L E A C H A T E - R U N 1 R-Square C.V. Std. Dev. Mean (%) Total N03-N/Column (mg/col.) 0.419 267 0.13 0.05 Average N03-N /Column (mg/L) 0.419 201 0.04 0.02 Max. N03-N/Col . (mg/L) 0.379 238 0.49 0.21 T A B L E 12. T K N IN L E A C H A T E - R U N 1 R-Square C.V. Std. Dev. Mean (%) Total T K N / C o l u m n (mg/col) 0.625 121 1.2 1.0 Max. T K N / C o l u m n (mg/L) 0.302 177 5.5 3.1 Week 1 - T K N (mg/L) 0.227 354 1.9 0.5 Week 2 - T K N (mg/L) 0.446 162 0.3 0.2 Week 3 - T K N (mg/L) 0.524 199 1.0 0.5 Week 4 - T K N (mg/L) APPL and LENGTH sig. Week 5 - T K N (mg/L) all values <2.7 except for the Columns C-9 and C-l concentrations Week 6 - T K N (mg/L) all values < 1.2 except for the Columns C-9 and C-I concentrations Week 9 - T K N (mg/L) 0.390 186 0.7 0.4 Column: C-9 & C-l Average T K N concentrations App l . Rate: 300 dt/ha Week 5 - T K N (mg/L) 5.8 Week 6 - T K N (mg/L) 6.7 W e e k 4 - T K N (mg/L): Duncan Grouping Mean N APPL a 1.2 8 _300 dt/ha b a 0.3 6 _ 30 dt/ha b a 0.3 6 _100 dt/ha b 0.1 6 0 dt/ha Duncan Grouping Mean N LENGTH a 1.1 8 _0-45 cm Col. b 0.3 10 _0-90 cm Col. b 0.2 8 _0-60 cm Col. Notes: The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed or preceded by different letters are significantly different. 'Std. Dev.' refers to the sample standard deviation, and N refers to the number of observations. 63 TKN for column E ('90 cm' column) appears high especially when considering the sluggish drainage of the longer columns. Therefore, this high concentration may be due to sampling or analytical errors in the laboratory. 4.6.1.3 Leachate Quality - Run 1 - Total Phosphorus In leaching run 1, TP concentrations were all low. The highest weekly TP concentration was 1.7 mg/L measured for column 9 ('45 cm' column with 300 dt/ha biosolids). All other weekly TP concentrations were below 0.9 mg/L with weekly column averages ranging from 0.01 to 0.28 mg/L. The total amounts of P in the leachate were below 0.6 kg/ha for all columns. Refer to Appendix H for details on TP in leachate. In general, the P determination caused a lot of extra laboratory work compared to the measurement of the other parameters in the BIOE Lab. The Stannous Chloride method used for determining P is very sensitive and sample contamination with P from lab benches, pipettes, or glassware was the cause of all initially high P measurements. When a high P concentration was measured in a sample, another two samples of the same leachate were digested and analyzed again with utmost care. No high P concentrations were confirmed in the repeated analyses. Procedures to avoid P contamination errors included the duplicate washing of glassware and pipette tubes with phosphate free soap, followed by rinsing well with tap water and rinsing twice with distilled water. As well, all lab benches were washed twice before use. However, since the same laboratory benches, glassware, and pipettes were used for other projects analyzing high N and high P animal wastes, a slight contamination of the pipettes (top part) from other samples could have caused sample contamination. 64 4.6.1.4 Leachate Quality - Run 1 - pH and EC The pH of the collected leachate varied little throughout the weeks of the experiment and the average pH ranged from 7.9 to 8.3. The highest variation in pH were measured for the control columns 10, F, and J in the last two weeks of the column study. The declining pH in these columns coincided with collection of turbid leachate during those weeks which is detailed in Appendix C. Turbid leachate indicates preferential flow of water in the soil columns so that instead of measuring the pH of water that travelled through the soil column, the pH measured might have been the pH of the added distilled water (5.5) that had been raised somewhat through contact with tailings in the soil columns. The electrical conductivities measured in the soil columns ranged from 0.2 to 2.2 dS/m for individual weekly measurements and from 0.4 to 1.9 dS/m for overall column averages. The EC tended to increase from week to week and with increasing application rates. In the medium length columns, the EC tended to vary from week to week whereas the EC decreased for the longest columns over the run. Based on these results, it is expected that over time the EC will increase in the leachate for the longer soil columns once the leachate collected has travelled from the biosolids amended soil surface to the bottom of the soil columns. In general, the EC was lower for the shorter columns than for the longer columns indicating that ions are picked up by the percolating water from the tailings. 4.6.2 Leachate Quality - Leaching Run 2 4.6.2.1 Leachate Quality - Run 2 - Nitrate The concentrations of N0 3-N in leachate were greater in the second leaching run than in the first leaching run. Overall, the higher N0 3-N concentrations are likely due to the different water regime in run 2 that allowed more N to mineralize and more N0 3-N to be formed, and due to the extended experimental phase. Run 2 was 13 weeks in length whereas run 1 was 10 weeks in length. 65 Notably high concentrations of N0 3-N were measured for the columns G and H in the last few weeks of the run (weeks 8, 9, 12, and 13). The highest daily concentrations measured for columns G and H were 1245 and 1076 mg N03-N/L respectively. However, the maximum daily N0 3-N concentrations for all other columns were below 2.4 mg/L which is well below the Canadian limit for drinking water (10 mg/L). For all columns except columns G and H, the contribution of N0 3-N to the overall N balance was negligible (< 0.4 kg/ha). Detailed results are shown in Table 13 and in Appendix I. As N0 3-N concentrations for the '45 cm' columns G and H (30 and 100 dt/ha) were much higher than for the other columns, a separate data analysis was conducted on data collected for columns 1 through 13 (tailings from site 3) and columns A through M (tailings from site 4). Due to the low concentration of N0 3-N in most leachate samples and due to the low replication of the experiment (one DF for Error), the data analysis showed many significant interactions. However, the average weekly NCyN concentrations for columns 1 through 13 were below 1.7 mg/L. The average weekly N0 3-N concentrations for columns A through M with exception of columns G and H were below 1.2 mg/L. Column H was a special case from the start of the second leaching run. While saturating column H, about one third of the material loaded into the column eroded out of the column into the leachate collection bottle. Due to their fine texture and their low organic matter and clay contents, the tailings possess little shear strength which makes them very susceptible to water erosion. Once one preferential flow channel exists in a leaching column, progressive concentration of flow in that channel can quickly lead to particle entrainment. Particle entrainment can cause localized scour and redistribution of particles in the channel which tends to increase the flow speed even more. Leachate collection data show that particulates were collected from columns A, F, G, and H. Since the columns A and F were control columns, the particulates in these columns were not expected to increase the N concentrations in the leachate. However, the collection of particulates in soil column G 66 T A B L E 13. N ITRATE A N D NITRITE IN L E A C H A T E - R U N 2 Results for columns loaded with site 3 tailings R-Square C.V. Std. Dev.: Mean: Max. Total N03-N/Col. Max. NC-3-N/Col. Week 1 • Week 2-Week 3-Week 4-Week 5-Week 8-Week 9-Week12-Week 13 N03-N N03-N N03-N N03-N N03-N N03-N N03-N N03-N N03-N (mg/col) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) A P P L , L E N G T H , A P P L , L E N G T H , A P P L , L E N G T H , 0.521 A P P L , L E N G T H , A P P L , L E N G T H , A P P L , L E N G T H , A P P L , L E N G T H , A P P L , L E N G T H , and A P P L * L E N G T H sig. and A P P L * L E N G T H s ig. and A P P L ' L E N G T H sig. 79 0.01 and A P P L * L E N G T H s ig. and A P P L * L E N G T H s ig. and A P P L * L E N G T H s ig. and A P P L ' L E N G T H s ig. and A P P L * L E N G T H s ig. but all va lues < 0.3 but all va lues < 2.4 but all va lues < 0.3 but all va lues < 0.1 but all va lues < 0.1 0.02 but all values < 0.1 but all values < 0.6 but all values < 0.4 but all values < 1.7 but all values < 1.6 Results for columns loaded with site 4 tailings Max. Total NC-3-N/Col. (mg/col.) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all values < 0.6 except for Co lumn C - G and C - H concentrations Max. NC-3-N/Col. (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig. , but all va lues < 1.9 except for Co lumn C - G and C - H concentrations Week 1 - N03-N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig. , but all va lues < 0.2 Week 2 - N 0 3 - N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues < 1.2 Week 3 - N 0 3 - N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues < 0.5 Week 4 - N 0 3 - N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues < 0.7 Week 5 -N03 -N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues < 0.4 Week 8 - N 0 3 - N (mg/L) A P P L , L E N G T H , and A P P L 1 E N G T H sig., but all va lues < 0.2 except for Co lumn C - G and C - H concentrations Week 9 - N 0 3 - N (mg/L) A P P L , L E N G T H , and A P P L ' L E N G T H sig., but all values < 0.3 except for Column C - G and C - H concentrations Week12-N03 -N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all values < 0.9 except for Co lumn C - G and C - H concentrations Week13-N03 -N (mg/L) A P P L , L E N G T H , and A P P L T E N G T H sig. , but all va lues < 0.6 except for Co lumn C - G and C - H concentrations Average N03-N concentrations for Col . G and H (0-45 cm Columns): Site 4 Tailings Column G (30 dt/ha) Column H (100 dt/ha) Total N03-N/Col. (mg/col.) 188 121 Max. N03-N/Col. (mg/L) 1245 1076 Week 8 -N03 -N (mg/L) 24 129 Week 9 - N 0 3 - N (mg/L) 32 49 Week12-N03 -N (mg/L) 706 249 Week13-N03 -N (mg/L) 819 693 67 (30 dt/ha) in weeks 8, 9, 12, and 13 and in soil column H (100 dt/ha) in weeks 2, 3, 8, 9, 12, and 13 may have contained biosolids that were washed from the soil surface into the collecting bottle. Unfortunately, only the surpernatant of the collected leachate with particulates was analyzed for N0 3 -N and TKN, not the solid fraction. The particulates in the leachate were separated from the liquid fraction through centrifugation at 2000 r.p.m. for 20 minutes. In retrospect, the solids in the leachate should have been analyzed for N0 3-N and TKN as well to determine if or how much of the N0 3-N and TKN in the leachate may be attributed to sample contamination with biosolids which washed down from the surface. The elevated concentrations of N0 3-N in leachate of columns G and H were confirmed by high soil concentrations of N0 3-N (see Appendix E) which were higher for these columns in the 15-30 and 30-45 cm layers than for any of the other columns with the same application rates. The higher soil concentrations of N0 3-N also support the idea that biosolids were washed from the surface to lower layers. For column G, approximately 109% of the applied N was recovered at the end of the run of which 8.4% (123 kg/ha) was in the form of N0 3-N in leachate and 92% was in soil. Note that 109% of the applied N was recovered for column G indicating that the N balance calculations are approximate. For column H, approximately 102% of the applied N was recovered at the end of the run of which 1.9% (79 kg/ha) was in the form of N0 3-N in leachate. 4.6.2.2 Leachate Quality - Run 2 - TKN In the second leaching run, the behaviour of the leaching columns differed again between tailings from sites 3 and 4. Similar to the second run N0 3-N concentrations, TKN concentrations in leachate were high for column H and elevated for column G. The highest daily maximum concentration was 249 mg TKN/L for column H and 5.6 mg TKN/L for column G. The average TKN concentrations per column 68 were all below 1 mg/L except for column G (1.6 mg/L) and column H (46.2 mg/L). Refer to Table 14 or Appendix I for detailed information. As discussed in the previous section, higher levels of TKN in the leachate of column G in weeks 4, 8, and 9, and in leachate of column H in weeks 2, 3, 4, 8, 9, and 12 are likely due to particulate matter that short-circuits the tailings in the soil columns via preferential flow channels. The contribution of TKN in leachate to the overall N balance was negligible for all columns (< 1 kg/ha) except for column H. At the end of leaching run 2, approximately 102% of the applied N was recovered for column H of which 2.5% (103 kg/ha) was in the form of TKN in leachate, 1.9% (79 kg/ha) was in the form of N0 3-N in leachate, and the remainder was in soil. 4.6.2.3 Leachate Quality - Run 2 - Total Phosphorus As expected, run 2 total P concentrations in leachate were all relatively low with the highest weekly concentration of 0.68 mg/L measured for column H. Again, the somewhat elevated TP concentration for column H could have resulted from biosolids that flushed from the surface soil into the collecting bottle. The average TP concentrations per column were all below 0.19 mg/L or drinking water quality. The contribution of P in leachate to the total P balance was less than 0.4 kg/ha and thus negligible. Details are included in Appendix I. 4.6.2.4 Leachate Quality - Run 2 - pH and EC As in leaching run 1, the pH of the leachate did not change significantly for any of the columns. The average pH ranged from 7.8 to 8.3. The highest pH variation per column was measured for column H (4%) with the pH declining over the period of the leaching run to pH levels similar to the added biosolids. Refer to Appendix I for details on measurements of pH and EC. 69 TABLE 14. TKN IN LEACHATE - RUN 2 Results for columns loaded with site 3 tailings R-Square C.V. (%) Std. Dev. Mean Max. Total TKN/Column (mg/col) 0.982 18 0.06 0.35 Max. TKN/Column (mg/L) 0.995 13 0.28 2.16 Week 1 - T K N (mg/L) A P P L , L E N G T H , and A P P L ' L E N G T H sig. , but all values < 0.6 Week 2 - T K N (mg/L) 0.987 14 0.06 0.40 Week 3 - T K N (mg/L) A P P L , L E N G T H , and A P P L ' L E N G T H sig., but all values < 0.6 Week 4 - T K N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig. , but all values < 3.5 Week 5 - T K N (mg/L) all values < 0.2 Week 8 - T K N (mg/L) 0.918 77 0.58 0.75 Week 9 - T K N (mg/L) 0.988 28 0.09 0.32 Week 1 2 - T K N (mg/L) 0.763 60 0.06 0.09 Results for columns loaded with site 3 tailings R-Square C.V. (%) Std. Dev. Mean Max. Total TKN/Column (mg/col.) A P P L , L E N G T H , and A P P L ' L E N G T H sig., but all va lues except for the Column C - H concentration < 1.0 Max. TKN/Column (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues except for the Column C - H concentration < 5.6 Week 1 - TKN (mg/L) 0.640 177 0.5 0.3 Week 2 - T K N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig. , but all values except for the Column C - H concentration < 0.8 Week 3 - T K N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all values except for the Column C - H concentration < 0.2 Week 4 - T K N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all values except for the Column C - H concentration < 2.5 Week 5 - T K N (mg/L) all values < 0.2 Week 8 - TKN (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues except for the Column C - H concentration < 5.6 Week 9 - T K N (mg/L) A P P L , L E N G T H , and A P P L * L E N G T H sig., but all va lues except for the Column C - H concentration < 3.2 Week 1 2 - T K N (mg/L) 0.992 63 0.3 0.4 TKN concentration for Column H: Site 4 Tailings Column: C-H Appl . Rate: 100 dt/ha Week 2 - T K N (mg/L) 125 Week 3 - T K N (mg/L) 155 Week 4 - T K N (mg/L) 23 Week 8 - T K N (mg/L) 10 Week 9 - TKN (mg/L) 7 70 The electrical conductivities for columns filled with tailings from site 3 were generally 1 to 1.5 dS/m lower than for columns filled with tailings from site 4. The EC did not fluctuate much for columns filled with tailings from site 3 (columns 1 through 13) for individual columns but tended to be lower for the shorter columns than the longer columns (same behaviour as in run 1). The individual weekly electrical conductivities ranged from 0.6 to 1.2 dS/m and overall column averages ranged from 0.6 to 1.1 dS/m. The electrical conductivities for columns filled with tailings from site 4 (columns A through M) ranged from 0.9 to 4.8 dS/m for individual weekly measurements and overall column averages ranged from 1.8 to 2.9 dS/m. Again, the overall column averages tended to be lower for the shorter columns than for the longer columns. The highest fluctuations in the EC per column were measured for column F (38%) and column H (61%). The high electrical conductivities in column H in week 2 (4.8 dS/m) and week 3 (3.4 dS/m) were possibly due to direct contamination of the leachate with biosolids and/or N0 3-N or NH4-N flushed into the collecting bottle during those weeks. 4.7 Sampling and Analytical Errors in the Leaching Experiment Like all data, the laboratory data had associated systematic and random errors. Systematic errors can be traced to a cause while random errors result from many different causes and their effects can be minimized by collecting and averaging more comparable data. In the leaching experiments, probably the largest error was a random error in the TKN analysis, followed by under- or overestimation of the bulk density of the material in the columns. In the leaching runs, the concentration of TKN varied significantly between duplicated samples (average 16%; highest 37%) likely due to small sample sizes used in the analysis (2-3 g for low concentration and ~1 g for high concentration samples). An extra morsel of biosolids in TKN samples could have increased the 71 sample concentration significantly since the biosolids have a high TKN concentration and weigh about one quarter of the tailings. It would have probably been better to digest larger sample sizes to reduce this error. The possibility of digesting larger sample sizes in the Bio-Resource Engineering Laboratory was rejected due to space limitation in the fume hood and due to too few heating elements for larger digestion flasks. The author believes that the larger flasks (800 mL) that were used by the GVRD Laboratory were a better approach to determining TKN concentrations for soil samples in this project. Due to the uncertainty in the TKN results, the interpretation of the TKN and Total N concentrations in the leaching experiments are somewhat limited. However, since the same procedure and apparatus were used for all samples, the author believes that the laboratory results represent the conditions in the leaching columns well enough for interpretation. An erroneous estimation of the bulk density of tailings in the columns could have increased or decreased the estimated nutrient content per hectare. Errors could have occurred by assuming that soil was packed to the same thickness throughout the columns. To avoid errors of this kind, the weight, moisture content, and layer thickness were measured at the time of loading, and the soil moisture and layer thickness were determined at the time of unloading. In retrospect, the weight of the material in every layer and every column should have been determined at the time of unloading to increase the accuracy of the results. Other errors include contamination errors during the emptying of the columns or during the laboratory analysis. In the emptying process, tailings from the bottom of the column had to move past areas previously occupied by biosolids and contamination of the lower samples with biosolids left on the edges of the soil columns might have occurred. However, both the methods of emptying the columns left only a fine film of tailings on the surface thus reducing this contamination error. 72 In the NO3-N analysis, the Limit of Detection (LOD) rose during the leaching runs. The LOD of the newly purchased and installed cadmium reduction column at the beginning of run 1 was 0.01 to 0.02 mg NO3-N/L whereas the detection limit at the end of the leaching run 2 was 0.1 to 0.3 mg N03-N/L. A decline in column sensitivity is normal for cadmium reduction columns, especially for small columns (3 cm long, 10 windings) sold for the Technicon Autoanalyzer II. The higher LOD in run 2 automatically leads to higher average concentrations as the half of the LOD is assumed to be the concentration of samples below the detection limit. 5.0 SUMMARY OF MAIN RESULTS - LEACHING EXPERIMENTS As a reminder, column run 1 was conducted under generally wetter conditions than column run 2 and the pot trial. The pot trial was conducted under the same environmental conditions as the column run 2, however, the pots were very well drained. The 0, 30, 100, and 300 dt/ha application rates of freshly dewatered biosolids were investigated. Nitrogen. pH and Electrical Conductivity in Soil As expected, the TKN concentration and the organic matter content increased with increasing application rates in the 0-15 cm layer. The concentrations of NH4-N and N0 3-N in the 0-45 cm layer were interesting. The absolute concentrations of NH4-N in the columns were higher in 15-30 layer (and 30-45 cm layer in run 2) whereas N0 3-N tended to increase with increasing application rates in the 0-15 cm layer. It is noteworthy that the average N0 3-N concentrations in the 0-15 cm layer tended to be 300 to 400 mg/kg lower for the pots than for the soil columns for the 100 and 300 dt/ha application rates. The lower concentration of N0 3-N in the pots may be a result of droughty conditions. 73 The surface pH did not change significantly in the leaching experiments. The EC tended to increase with increasing application rates, and the growth of salt sensitive crops may be slowed on plots amended with 300 dt/ha biosolids. Mineral Nitrogen in Soil Although mineral N in the 0-45 cm layer increased with increasing application rates in both leaching runs, much more mineral N was available in the second leaching run compared to the first leaching run. While in the first leaching run the mineral N ranged from 200 to 745 kg/ha (1.9-7.0% of added N), the mineral N in the second leaching run ranged from 1200 to 3000 kg N/ha (9.5-24.0% of added N) for the 300 dt/ha application rate. At the end of the second leaching run, the mineral N available in the pots was about 60 mg/kg higher for the 30 dt/ha application rate and 600 and 200 mg/kg lower for the 100 and 300 dt/ha application rates respectively (0-15 cm layer). However, the available N in the pots was much higher than in the first leaching run likely due to the different water regime in the second leaching run, better aeration in the pots (better drainage), and the longer experimental phase. Nitrogen Balance The absolute N balance numbers differed between the leaching experiments, but all experiments showed a similar trend. At the end of the leaching runs, the absolute amount of N lost and the absolute amounts of total N in the columns increased with increasing application rates. Nitrogen losses were only significantly higher for the 300 dt/ha application rate indicating high variations between columns with the same treatment. 74 For the highest biosolids application rate (300 dt/ha), the N losses were substantial (30-34%) and the mineral N retention in the soil was low. There appeared to be a trend towards either low mineral N content in the soil and high N losses, or higher retention of mineral N in the soil and lower N losses. On average, the total N losses in the column studies were lower in the second leaching run than in the first leaching run; however, most N was lost in the pot trial. Likely contributing factors to the high N losses and high mineralization rate were: good mixing of the tailings with the biosolids (higher mineralization rate), no vegetation cover that could take up available N or could impede volatilization, optimal pH for mineralization and nitrification, relatively warm soil temperatures (> 14°C, avg. ~17.5°C), and relatively high concentration of bacteria in the biosolids at the time of application. Higher than expected were the mineralization rate and the amount of N lost from the soil columns. The average estimated mineralization rates ranged from 19 to 35% over 10 weeks for column run 1, from 33 to 43% over 13 weeks for column run 2, and from 34 to 48% over 13 weeks for the pot trial. Similar mineralization rates for the pot trial and the second column run suggest that the mineralization of N can be studied in shorter soil columns which are much easier than longer columns to set up and keep in a controlled atmosphere. Total Metals In leaching runs 1 and 2, metal concentrations in the soil columns were below the lowest of the CCME criteria for agricultural and residential use (1991) with the exception of the Hg concentrations in the upper layers for columns with 300 dt/ha biosolids and the Cu concentrations in all layers and columns. However, all Hg concentrations were below the residential soil criterion. 75 Leachate Quality - Leaching Run 1 The measured N0 3-N concentrations in the first leaching run were very low with an average N0 3-N concentration of 0.02 mg/L and the highest amount of N0 3-N lost through leaching of 0.37 kg/ha. In leaching run 1, the average TKN concentrations measured were generally low (< 0.5 mg/L) for all weeks except weeks 4, 5, and 6 of the experiment. In those weeks, the TKN concentrations in the leachate tended to be higher for the short columns especially for the highest application rate (300 dt/ha). The highest weekly average TKN concentration was 6.7 mg/L measured in week 6 for the '45 cm' columns with 300 dt/ha of added biosolids. In leaching run 1, TP concentrations were all low. The highest weekly TP concentration was 1.7 mg/L, and the P in leachate was below 0.6 kg/ha for all columns. In leaching run 1, the pH of the collected leachate varied little throughout the experiment and with the average pH ranging from 7.9 to 8.3. The electrical conductivities of the leachate were low and ranged from 0.2 to 2.2 dS/m for individual weekly measurements and from 0.4 to 1.9 dS/m for overall column averages. Leachate Quality - Leaching Run 2 The N0 3-N concentrations in leachate were greater in the second leaching run than in the first leaching run likely due the different water regime that allowed more N to mineralize and nitrify in run 2, and due to the extended experimental phase. Notably high concentrations of N0 3-N were measured for the columns G and H in weeks 8, 9, 12, and 13 of the experiment. The highest daily concentrations measured for columns G and H were 1245 and 1076 mg N03-N/L respectively. However, the maximum daily N0 3-N concentration for all other columns were below 2.4 mg/L which is well below the Canadian limit for drinking water (10 mg/L). 76 For all columns except columns G and H, the contribution of N0 3-N to the overall N balance was negligible (< 0.4 kg/ha). For column G, approximately 8.4% (123 kg/ha) of added N was in the form of N0 3-N in leachate. For column H, approximately 1.9% (79 kg/ha) of added N was in the form of N0 3 -N in leachate. In leaching run 2, TKN concentrations in leachate were high for column H and elevated for column G. The highest daily maximum concentrations were 249 mg TKN/L for column H and 5.6 mg TKN/L for column G. The TKN level in leachate was below 0.6 kg/ha for all columns except for column H with 103 kg/ha (2.5% of added N). In leaching run 2, total P concentrations in leachate were all relatively low with the highest weekly concentration of 0.68 mg/L measured for column H. The average TP concentrations per column were all below 0.19 mg/L or drinking water quality. The high N0 3-N and TKN concentrations in leachate of columns G and H, and the elevated TP concentration in leachate of column H may be due to the preferential flow of percolating water. Furthermore, column H was a special case from the start of the second leaching run since about one third of the material loaded into the column eroded out of the column in the saturation phase. In leaching run 2, the pH of the leachate did not vary greatly and ranged from 7.8 to 8.3. The electrical conductivities for columns filled with tailings from site 3 ranged from 0.6 to 1.1 dS/m and were generally 1 to 1.5 dS/m lower than for columns filled with tailings from site 4. 77 6.0 METHODS AND MATERIALS - FIELD EXPERIMENT 6.1 Plot Treatments In October 1992, biosolids were applied to six tailings plots of which four 0.5 ha plots are discussed in this thesis as they were studied in more detail. The biosolids were applied with hydraulic ram manure spreaders at application rates of 62, 77 (two plots), and 179 dt/ha (55000, 69000, and 160000 lb/acre respectively). Subsequently, the biosolids were incorporated with a 20 cm (8") farm disk, and the demonstration sites were seeded with a no-till, seed-drill seeder and rolled (680 kg roller) to minimize seed loss through wind erosion. A nurse crop seed mix was seeded at 30 kg/ha and a reclamation seed mix was seeded at 65 kg/ha. The field application rates are given in Table 15 and the characteristics of the biosolids and the seed mix are shown in Tables 16 and 17 while treatments are depicted in Figure 4. Photographs of the field trial are included in Appendix P (Figures 5-10). The original project design was based on the application of freshly dewatered biosolids throughout, but stored dewatered biosolids were applied on most plots since not enough freshly dewatered biosolids were available at the time of transport. Furthermore, a switch from stored dewatered to land-dried biosolids took place on the unfinished plot 2b (northern 1/3 of 2b) due to odor complaints from residents. Stored dewatered biosolids were approximately 6 months old and contained about 3.4% total N of which 42 % was in the form of NH4-N at the time of application whereas land-dried biosolids contained approximately 1.1% total N of which 2.3% was in the form of NH 4-N. The switch to land-dried biosolids introduced another variable into the study. Application rates were not adjusted to compensate for the lower N content of the land-dried biosolids. The biosolids were applied as homogeneously as was possible with manure spreaders. The biosolids were flung off the drums of manure spreaders in clumps of 2 to 10 cm in diameter. These clumps, once distributed on the tailings, were somewhat broken up and incorporated into the tailings by the disking operation, but the drill seeding and rolling of the tailings after disking also compacted and flattened some clumps on the surface. This effect was more pronounced for portions of plots 3a and 78 T A B L E 15. BIOSOLIDS T R E A T M E N T S - FIELD EXPERIMENT Plot Site Conditions Plot size (ha) Application Rate (dt/ha) Biosolids type 2a Tailings without vegetation 0.5 77 Stored dewatered 2b Tailings without vegetation 0.5 62 41 dt/ha Stored dew. & 21 dt/ha Land-dried 3a Tailings without vegetation 0.5 179 Stored dewatered 3b Tailings without vegetation 0.5 77 Stored dewatered T A B L E 16. BIOSOLIDS C H A R A C T E R I S T I C S - FIELD EXPERIMENT Element: Field Ex Annacis Land-dried Dewatered Biosolids Oct-92 periment Annacis Stored Dewatered Biosolids Oct-92 B.C. Draft Gu Disposal of Dom Agricultural Low Grade idelines for the estic Sludge (1983) Retail High Grade Total Kjeldahl N (mg/kg) 11000 33785 - -% Moisture 31 74.9 - < 70.0 Nitrate/Nitrite-N (mg/kg) 101 5 -Ammonium-N (mg/kg) - extracted 241 12072 - -Ammonium-N (mg/kg) - distilled 266 16733 - -Arsenic (mg/kg) < 12 < 17.0 75 75.0 Cadmium (mg/kg) 1 5.0 25 5-20 Chromium (mg/kg) 40 50.0 - -Cobalt (mg/kg) 5.0 4.1 150.0 150.0 Copper (mg/kg) 219 1050 - -Lead (mg/kg) 88 190 1000 500 Mercury (mg/kg) 3 6.7 10 5.0 Molybdenum (mg/kg) < 4 6.6 20 20.0 Nickel (mg/kg) 31 37 200 180 Selenium (mg/kg) 1 6.0 14 14.0 Zinc (mg/kg) 193 915 2500 1850 T A B L E 17. S E E D MIX U S E D IN T H E PRINCETON D E M O N S T R A T I O N P R O J E C T Reclamation Mix: 20% B O R E A L Creeping Red Fescue Festuca rubra 15% Hard Fescue Festuca ovina var. duriuscula (L.) Koch 10% C A R L T O N Bromegrass Bromus inermis 10% S T R E A M B A N K Wheatgrass Agropyron riparium Scribn. & Smith 10% FAIRWAY Crested Wheatgrass Agropyron cristatum (L.) Gaertn. 5% Canada Bluegrass Poa compressa L. 5% A L M A Timothy Phleum pratense L. 10% R A N G E L A N D E R Alfalfa Medicago sativa L. 5% White Clover Trifolium repens L. 5% S C Red Clover Trifolium pratense L 5% C I C E R Milkvetch Astragalus cicer L. Nurse Crop Seed Mix: 67% Fall Rye Secale cereale 33% Hairy Vetch Vicia villosa 79 FIGURE 4. LOCATION O F FIELD SITES IN PRINCETON, B.C. (1992-1993) SCALE 1:10.000 80 3b due to higher application rates. Micro-site application rates varied between zero and approximately twice the specified application rate. 6.2 Soil Sample Collection and Analysis Composite soil samples were collected prior to, and 6 and 12 months after biosolids application from the 0-15, 15-30, 30-60, 60-90, 90-120, and 120-150 cm soil layers. Care was taken to collect representative soil samples by collecting 10-15 subsamples per plot from the 0-15 and 15-30 cm layers and 5 subsamples for the lower spoil layers. Composite soil samples were either collected with a 0.5" (1.3 cm) or 1" (2.5 cm) soil probe attachment using a JMC Backsaver Handle Soil Probe (Clements Associates Inc.). Half of the probe part of the JMC probe is open to the surrounding environment to allow easy access to soil cores. To avoid contamination of soil samples, about one third to one half of every soil sample in the probe (the portion that was open to the surrounding soil) was wasted. The remainder of every soil sample was collected in water-tight plastic bags. Despite the effort that was made to collect representative composite samples, there might have been a sampling bias in the upper layers due to the sampling procedure. The sampling probe had a tendency to part the biosolids on the soil surface rather than core them, leading to lower nutrient and organic matter results than had been expected. A discussion of the problems encountered during soil sampling and recommendations for future projects is included in section 7.6. All composite soil samples were analyzed for the parameters: TKN, N0 3 -N (N0 3-N + N02-N), NH4-N, and total P. In addition, composite soil samples from sites 2a and 3a were analyzed for the elements: As, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Se, and Zn. Soil fertility was also assessed for all 0-15 cm soil samples. Soil fertility analyses included the parameters: pH, EC, NH4-N, N0 3 -N (N0 3-N + N02-N), Bray P-1, potassium (K), calcium (Ca), magnesium (Mg), boron (B), Cu, Zn, iron (Fe), manganese 81 (Mn), sulfate, organic matter, and CEC. Discrete soil samples (0-15 cm layer) collected in April 1993 were also analyzed for Olsen-P in the BIOE Lab. In the original design, three discrete samples were to be collected from all treatment sites to estimate the variations in biosolids application and treatment effects. To lower the project costs, this design was changed from 3 to 2 discrete samples for one of the sites with the duplicated biosolids application rate (77 dt/ha). However, instead of duplicating the application rate 77 dt/ha on sites 2a and 2b, the field applicator applied 77 dt/ha to sites 2a and 3b leading to the collection of only 2 discrete background samples for plot 2b (62 dt/ha). Discrete samples were collected from the 0-15, 15-30, 30-45, 45-60, and 60-90 cm layers at the same time as composite soil samples were collected. Discrete soil samples were collected with trowels from edges of 90-100 cm deep soil pits. The samples were analyzed for TKN, NH 4-N, N0 3 -N (N0 3-N + N02-N), total P, and metals. To minimize errors resulting from local site differences, discrete samples were collected repeatedly from the same two to three discrete areas per treatment site. The discrete areas were approximately 5m X 5m in size and the samples were labelled: Site_Name - R1, Site_Name - R2, and Site_Name -R3. The previously sampled sites in a discrete area were marked so that they would not be sampled again. This sampling technique was based on the assumption that the collection of discrete samples from the 'same' area over time establishes treatment differences better than the collection of randomly located discrete samples at every sampling event. Once a soil sample was collected, the sample was stored in a cooler in the field and in a refrigerator once delivered to a laboratory (at 4°C). The samples were analyzed for the various parameters as quickly as possible by established laboratories. 82 In the soil analyses, the < 2 mm fractions were analyzed for: TKN by sulfuric acid digestion, NH4-N and NO3-N by 1 or 2 M potassium chloride extraction, exchangeable K, Ca, and Mg by NH4-N acetate extraction, total P by sulfuric and nitric acid digestion, available P by Bray P-1 extraction (composite samples) and by Olsen-P extraction (April 1993 discrete samples), sulfate by calcium chloride extraction, available Zn, Fe, Cu, and Mn by DTPA-TEA extraction, B by hot water extraction, organic matter by total carbon determination (org. matter = TC*1.78), Hg by cold vapor atomic absorption, Se by hydride atomic absorption, and all other metals by aqua regia digestion and ICP analysis. Digestions or extraction were followed by a colorimetric determination of concentration for TKN, N0 3 -N, NH4-N, total P, Bray P-1, and B; by turbidimetric determination for sulfate; or by atomic absorption spectrophotometry (A.A.S) for exchangeable K, Ca, and Mg, and available Zn, Fe, Cu, and Mn. More details about laboratory methods are included in Appendix O. 6.3 Vegetation Samples and Data Collection Vegetation samples were collected in July and September 1993 of which July samples were used to estimate species establishment and September samples were statistically compared. In July 1993, composite vegetation samples were collected from areas of low vegetation establishment and high vegetation establishment. The density of vegetation cover on the treatment plots was classified into areas of low and high vegetation establishment by visual inspection. Sketches of the density of vegetation cover were made for every plot at the time of sample collection to estimate the yield per hectare. In July 1993, at least 3 subsamples were collected for every composite sample per plot and classification (low and high vegetation establishment). The sampling areas for the low and high vegetation areas were 4 m 2 and 0.5 m 2 respectively. For the low vegetation areas, composite sampling continued until about 1000 cm 3 of vegetation had been cut. The vegetation was cut about 4-5 cm above the ground. 83 In September 1993, vegetation was collected from five discrete, predetermined locations per treatment (pattern '5' on a die). The vegetation was cut from 0.25 m 2 areas about 4-5 cm above the ground. However, only one of the samples from plot 3a yielded enough vegetation for analysis. The samples were analyzed for TKN, N0 3 -N (N0 3-N + N0 2-N), NH4-N, yield, As, Cd, Cr, Cu, Pb, Hg, Mo, Ni, Se, and Zn. From the control plot, three discrete samples were collected which were analyzed separately for TKN and N0 3 -N and were composited for metal and yield analyses. Species within the discrete vegetation samples were not analyzed separately. Vegetation clippings were not washed before analysis so that Cu concentrations in vegetation samples might have been elevated due to the adherence of Cu tailings to plant samples resulting from air-borne particulates from surrounding untreated tailings. Vegetation samples were sealed in plastic bags and kept in coolers in the field (at approximately 4°C). Before analysis, plant samples were dried (60°C), milled, and passed through a 1 mm sieve as recommended by U.S. EPA (1983). The < 1 mm fraction was analyzed for: TKN by sulfuric acid digestion, N0 3 -N by 1 M potassium chloride extraction, Hg by cold vapor atomic absorption, Se by hydride atomic absorption, and all other parameters by nitric/perchloric acid digestion. Digestions or extractions were followed by colorimetric determination of concentration for TKN and N0 3-N; by A.A.S. for Cu and Zn; and by ICP analysis for As, Cd, Cr, Pb, Mo, and Ni. In July 1993, vegetation yield was determined after the samples had been dried at 60 CC. More details about laboratory analysis are included in Appendix O. 6.4 Methods and Limitations of Data Analysis - Field Experiment The analytical methods of data analysis for field data were the same as for laboratory data. Refer to section 3.7 for details. 84 The data analysis and interpretation of field results was difficult due to the inadequate collection of control data. For example, fewer samples were collected from the control sites (seeded and unseeded) than from the treated sites in the vegetation sampling program. In addition, vegetation samples from the control sites were composited for most parameters whereas discrete samples from the treatment sites were analyzed separately. This approach to sample collection and analysis is not scientific. In future projects, the sampling from the control sites and the treatment sites should be identical to be able to evaluate the effects of different treatments better. A similar situation existed in the collection of soil fertility data. Instead of collecting composite samples from every treatment site and the control sites at every sampling time, only one discrete sample was collected from the unseeded control site (before biosolids application) and analyzed for soil fertility parameters. This approach to data collection has led to the identification of significant treatment differences in the data analysis for the factor 'time' (different 'before' and 'after' parameter concentrations on individual plots) rather than for the factor 'application rate'. This problem manifested itself in the interpretation of the analytical results for the soil fertility parameters: pH, NGyN, NH3-N, and B. If the control site concentrations had been determined throughout the experiment, significant differences for the different application rates might have been identified. This approach to data collection also led to conflicting results for exchangeable Ca (increased concentrations after biosolids application and decreased concentrations with increasing application rates). 7.0 DISCUSSION OF RESULTS - FIELD EXPERIMENT The following is a discussion of results for the field data that was collected in the Princeton Demonstration Project between October 1992 and October 1993. All laboratory and analytical results for the tailings samples are summarized in tables in Appendices J through N. The appendices include an overview of the analytical results, detailed field data, and a more detailed version of analytical results. The characteristics of the biosolids used in the project are included in Appendix B. 85 7.1 Field Observations Growth on the tailings started early in the spring and continued well into the fall even after surrounding vegetation had turned brown. Vegetation was very lush for a non-irrigated site, likely due to a combination of moisture holding capacity of the biosolids, improved nutrient status, and moisture content of the tailings. In the first growing season, the establishment of vegetation on site 3a (179 dt/ha) seemed to be negatively correlated with the thickness of biosolids applied (visual observation). Field observations include the sighting of deer, cattle, bees, and insects on the treatment sites. Deer started grazing on the treatment sites in July 1993. Deer grazed heavily on the tailings vegetation over the winter 1993/1994. Numerous deer droppings were found on sites 2a, 3a, and 3b in the spring of 1994, but deer droppings were also found on site 2b. In addition, cattle grazed on the sites in the spring of 1994. Grazing did not hamper the vegetation growth in 1994. During the summer of 1993, many bees and other insects were feeding on blossoms on the treatment sites. 7.2 Vegetation in the First Growing Season The July 1993 vegetation sampling showed that most of the species which were seeded in 1992 grew in 1993. They included fall rye, brome, timothy, crested wheatgrass, fescues, alfalfa, and hairy vetch of which fall rye was visibly the most prominent. The control sites were dominated by weeds and grasses and the treatment sites tended to be dominated by fall rye and grasses. Virtually no legumes were present on the seeded and unseeded control sites, but legumes (primarily alfalfa) contributed 13-15% to the vegetation yield on plots 2a and 2b and 5-7% to the vegetation yield on plots 3a and 3b. In July 1993, the vegetation yield was highest on plot 2b (62 dt/ha) and lowest on the seeded control plot. For details on the July sampling results refer to Appenidx K. The five discrete vegetation samples collected in September 1993 from tailings sites 2a (77 dt/ha), 2b (62 dt/ha), and 3b (77 dt/ha), and the three discrete samples collected from the control site (0 dt/ha) 86 were statistically compared. For the 179 dt/ha treatment, only yield was compared to the other treatments since only one out of five samples from site 3a yielded enough vegetation for analysis. Results of the data analysis are summarized in Table 18. Refer to Appendix K for details on vegetation results and to section 6.4 for details on limitations of the vegetation data analysis. The biosolids application to sites 2a (77 dt/ha), 2b (62 dt/ha), and 3b (77 dt/ha) had no significant impact on the foliar concentrations of As, Cd, Pb, Hg, Ni, Se, or Zn. However, the application of biosolids influenced the concentrations of N0 3-N, TKN, Cu, Mo, Cr, and the yield. The foliar N0 3-N concentration increased after the biosolids application, especially for the 77 dt/ha sites (from 0.003% to 0.04%). The TKN concentration was higher in the vegetation of the 77 dt/ha sites (2.0%) and lower in the vegetation of the 62 dt/ha site (1.2%) in comparison with the control site (1.5%). The concentration of Cu in the vegetation was lowered substantially after the application of biosolids despite the fact that the available Cu concentration in soil increased slightly after application. This reduction is likely due to a dilution effect caused by good growth and due to less exposure of vegetation to fine Cu dust (less wind erosion and less adherence of Cu onto the surface of vegetation). The measured Cu concentration in the tailings vegetation was close to the upper normal level in vegetation and was higher than the recommended 4 to 10 mg/kg for cattle consumption (Gould Gizikoff, 1994). However, the measured Cu concentrations in vegetation would not present a hazard to cattle grazing if their diet would not be limited to this feed (BCMAFF, 1991). The Cu concentrations are consistent with previous vegetation research results reported in studies on Princeton mine wastes (Gizikoff, 1990). 87 TABLE 18. TAILINGS VEGETATION September 1993 Foliage Quality Literature Values Element Mean SD Normal Cone. Excess. Cone. Arsenic, mg/kg 7.6 3.3 Cadmium, mg/kg < 0.50 > 3 (3) Chromium, mg/kg AAPPL sig. > 2 (3) Copper, mg/kg AAPPL sig. 5.0 20 > 20 (2,5) Lead, mg/kg 5 1.7 > 10 (3) Mercury, mg/kg 0.01 0.004 Molybdenum, mg/kg AAPPL sig. 0.1 ? (6) Nickel, mg/kg 1.15 0.57 0.1 1 > 50 (3,4) N03-N, % AAPPL sig. Selenium, mg/kg 0.19 0.08 > 4 (6) Total N (TKN), % AAPPL sig. 1.5 (1) Zinc, mg/kg 30.5 7.8 25.0 150 > 400 (2) Yield, dt/ha AAPPL sig. 1993 Foliage Quality Application Rate Element 0 dt/ha 62 dt/ha 77 dt/ha 179 dt /ha Chromium, mg/kg 3.0 a 1.8 b 1.8 b not compared Copper, mg/kg 68 a 23 b 21 b not compared Molybdenum, mg/kg 24 a 5.7 b 4.4 b not compared N03-N, % 0.003 b 0.010 ab 0.039 a not compared Total N (TKN), % 1.5 ab 1.2 b 2.0 a not compared Yield, dt/ha 0.2 b 4.3 a 5.5 a 0.6 b The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed by different letters are significantly different. SD Sample Standard Deviation (1) Salisbury and Ross, 1991 (2) Mortvedtetal., 1972 (3) CAST, 1976; Melsted, 1973; Univ. of Georgia Coop Ext., 1979 (4) Tisdale etal., 1993 (5) Cokeretal., 1982 (6) Walsh and Beaton, 1973 A remarkable trend of lower molybdenum concentration in the vegetation was found, and despite the lowered concentration of Cu in the vegetation, the Cu:Mo ratio increased in the vegetation samples from treatment sites 2a, 2b, and 3b. A higher Cu:Mo ratio is beneficial for ruminants that might graze 88 on the sites. The lower Mo concentration in foliage may be due to the different species composition on the control and treatment sites or due to increased nitrification (lowered pH) and/or increased Fe concentration in soil. The concentration of chromium was lower in the vegetation after the application of biosolids. The concentration of chromium was lowered below the excess concentration of 2 mg/kg (CAST, 1976; Melsted, 1973; Univ. of Georgia Coop. Ext., 1979). The yields for the 62 dt/ha and 77 dt/ha treatment sites were much higher after the biosolids application, but the yields for the 179 dt/ha site and the control were comparable. Poor incorporation of the biosolids into the tailings likely contributed to the poor vegetation establishment on site 3a (179 dt/ha site) during the first growing season. Therefore, the southern two thirds of site 3a was rotovated and reseeded in October 1993. 7.3 Soil Fertility (0-15 cm Layer) In the soil fertility data analysis, NH4-N and N0 3 -N concentrations measured by Norwest Labs and the GVRD Lab were analyzed together to increase statistical accuracy, despite that their laboratory methods were similar but not identical. The NH4-N and N0 3 -N data measured by the GVRD Lab is discussed separately in section 7.4. The Norwest NH4-N and N0 3 -N data is listed in Appendix L and the GVRD data is listed in Appendix M. Limitations of the soil fertility data analysis are discussed in section 6.4. A factorial analysis with time and application rate as parameters determined that the levels of NH4-N, N0 3-N, Cu, Bray P-1, Fe, pH, and B were significantly higher after biosolids application. Unaffected by the application of biosolids were the levels of EC, CEC, organic matter, K, Mg, Mn, sulfate, and Zn. 89 Ammonium, N0 3 -N, and Cu concentrations increased after application, although there were significant interaction terms. Bray P-1 and Fe concentrations were dependent on time and application rate, whereas pH and B levels were only dependent on time. Organic matter and CEC were expected to increase after biosolids treatment, and the non-significant result may indicate sampling errors. Sampling errors and recommendations to minimize sampling errors in future projects are discussed in section 7.6. Results of soil fertility analyses are summarized in Table 19 and detailed in Appendix L. As expected, increased NH4-N concentrations were measured with increasing application rates. The highest NH4-N concentration was measured in April 1993. The NH4-N concentrations in October 1992 (before biosolids application) and in September 1993 were low for all sites, but still higher after treatment than before treatment. The concentration of N0 3 -N was very low before biosolids application, slightly higher 6 months after biosolids application (spring 1993), and much higher one year after application (fall 1993). As expected, the N0 3 -N concentration increased with increasing application rates. The Bray P-1 concentration increased with increasing application rates due to the 1% concentration of total P in biosolids. An approximate comparison of Bray P-1 results with Olsen-P results conducted for April 1993 soil samples showed that both methods tended to lead to similar P fertilizer recommendations. For details refer to Appendix L. The available iron concentration increased after biosolids application, but remained in the optimum range as before treatment. An increased iron concentration is beneficial since it increases the availability of iron to plants, and since iron oxides can form compounds with metals in biosolids which makes them less available for plant uptake. 90 T A B L E 19. SOIL FERTILITY R E S U L T S Literature Values Parameter Mean Std. Dev. Low Cone. Normal Range pH TIME sig. EC, dS/m 1.5 0.9 Boron mg/kg TIME sig. < 0.5 0.5 (4) Bray P-1 mg/kg TIME and A A P P L sig. < 7 7 - 20 (D Calcium mg/kg A A P P L sig. 30 - 300 (2) CEC, cmol/kg 7.3 1.3 Copper mg/kg TIME and T I M E * A A P P L sig. < 0.2 (3) Iron mg/kg TIME and A A P P L sig. < 4.5 (3) Magnesium, mg/kg 182 18.1 5 - 50 (2) Manganese, mg/kg 4.8 2.2 < 1.0 (3) NH4-N TIME and T I M E * A A P P L sig. N03-N & N02-N TIME and T I M E * A A P P L sig. %Organic Matter 1.3 1.3 Potassium, mg/kg 263 53 < 40 40 - 600 (2) Sulfate, mg/kg 224 102 < 5 5 (2) Zinc, mg/kg 9.6 8.3 < 0.8 (3) Application Rate Parameter 0 dt/ha 62 dt/ha 77 dt/ha 179 dt/ha Bray P-1, mg/kg * 3 b 4 b 22 b 83 a Calcium, mg/kg * 5016 a 4605 a 3851 b 3376 b Iron, mg/kg * 28 b 75 ab 96 a 95 a The concentration of the nutrient is also dependent on time. Parameter Oct. 1992 Time Apr. 1993 Sept. 1993 PH 8.2 a 8.2 a 7.5 b Boron, mg/kg 0.6 a 0.7 a 0.2 b Bray P-1, mg/kg** 1.6 b 45 a 51 a Calcium, mg/kg ** 3411 c 4116 b 4638 a Iron, mg/kg ** 38 b 63 b 168 a The concentration of the nutrient is also dependent on the application rate. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed by different letters are significantly different. (1) Page e t a l , 1982 (2) Tisdale e ta l . , 1983 (3) Lindsay and Norvell, 1978 (critical levels for corn) (4) Walsh and Beaton, 1973 N 0 3 - N , NH4-N, and C u results are detailed in Appendix L. 91 The pH declined from 8.2 to 7.5 on the treatment sites probably due to increased nitrification. This decrease in pH improves soil fertility as it makes Mo less available and all other micronutrients more available to plants. After the biosolids treatment, the concentration of B decreased likely due to increased B uptake by legumes or due to local site differences. The concentration of Ca decreased with the increasing application rates, but was on average higher after biosolids application. The concentration of Ca is very high on the tailings due to the calcareous nature of the ore (see Appendix A). 7.4 Soil Nitrogen and Phosphorus In this section, N and P data measured by the GVRD Lab are discussed. First, the results of statistical comparisons of concentrations are reviewed which is followed by a discussion of results of soil N balance calculations. This data set does not include control data. All soil samples were analyzed on a wet basis for N to minimize volatile losses. Please read section 6.4 before reading the discussion of soil N and P results. Nitrogen and total P data were statistically compared for the application rates of 62, 77, and 179 dt/ha biosolids and layers 0-15, 15-30, 30-60, 60-90, 90-120, and 120-150 cm. A factorial model with time and application rate as parameters was used in the analysis. Data from every layer was analyzed separately. Table 20 shows the results of the data analyses, and Appendix M includes detailed results. Information in Appendix M was divided into an overview section of statistical results, a N balance section, a field data section, and a detailed analytical results section. 92 T A B L E 20. NITROGEN AND PHOSPHORUS RESULTS (GVRD) - FIELD EXPERIMENT Depth TKN (mg/kg) N03-N (mg/kg) NH4-N (mg/kg) TOTAL P (mg/kg) 0 - 15 cm Mean TIME sig. TIME sig. TIME TIME sig. AAPPL, and TIME* AAPPL sig. 15 - 30 cm Mean 102 11.5 9.7 TIME and Std. Dev. 49 19.2 25.5 AAPPL sig. 30 - 60 cm Mean 54 1.1 0.4 1577 Std. Dev. 35 1.5 0.3 180 60 - 90 cm Mean 56 TIME sig. 0.2 1530 Std. Dev. 11 0.1 217 90 -120 cm Mean 55 TIME sig. 0.2 1637 Std. Dev. 18 0.2 167 120-150 cm Mean 57 TIME, 0.2 1541 Std. Dev. 14 AAPPL and 0.3 132 TIME*AAPPL sig. Parameter Depth Oct. 1992 Time Apr. 1993 Sept. 1993 N03-N 0 - 15 cm 0.2 b 5.4 b 136 a 15 - 30 cm average for all times: 11.5 30 - 60 cm average for all times: 1.1 60 - 90 cm 0.1 b 0.3 ab 0.5 a 90 -120 cm 0.1 b 0.3 ab 0.5 a 120-150 cm all values: < 3.0 TKN 0 - 15 cm 65 b 861 a 1254 a Total P 0 - 15 cm 1432 b 1628 ab 1868 a 15 - 30 cm * 1437 b 1548 ab 1655 a * Total P cone, in the15-30 cm profile is also dependent on the application rate. 15-30 cm TOTAL P (mg/kg): Duncan Group. AAPPL N Mean a _179 dt/ha 3 1685 a _ 77 dt/ha 6 1585 b _ 62 dt/ha 3 1332 4H4-N (mg/kg): Level of Level of NH4-N -TIME AAPPL N Mean SD _Oct. 1992 _ 62 dt/ha 1 0.1 _Oct. 1992 _ 77 dt/ha 2 1.5 1.6 _Oct. 1992 _179 dt/ha 1 0.2 _Apr. 1993 _ 62 dt/ha 1 67 _Apr. 1993 _ 77 dt/ha 2 215 14.1 _Apr. 1993 _179 dt/ha 1 347 _Sep. 1993 _ 62 dt/ha 1 0.3 _Sep. 1993 _ 77 dt/ha 2 1.4 1.3 _Sep. 1993 J 79 dt/ha 1 5.2 Notes: The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed or preceded by different letters are significantly different. 93 The concentration of TKN was only significantly different in the 0-15 cm layer for the three application rates. The average concentration of TKN in April and September 1993 was more than 16-fold the concentration in October 1992. The trends of NH4-N and N0 3-N concentrations in the 0-15 cm layer measured by the GVRD Lab and Norwest Labs were similar. The combined results were already discussed in section 7.3. The results for NH4-N and N0 3-N concentrations measured by the GVRD follow below. The concentration of NH4-N was only significantly different in the 0-15 cm layer for the three application rates. The concentration was low in October 1992 (pre-application), high in April 1993, and low in September 1993 for all application rates. The April 1993 concentrations were higher for the higher application rates and ranged from 62 to 347 mg/kg for application rates 62 and 179 dt/ha respectively. This result was expected as NH4-N is the first product in the conversion of organic N to mineral N. The conversion process is temperature dependent and therefore starts anew in spring. The concentration of N0 3-N was significantly different in the 0-15, 60-90, 90-120, and 120-150 cm layer for the three application rates. The difference was with respect to time. Nitrate in the 120-150 cm layer was also significantly different with respect to application and time*application which means that there was significant interaction between time and application rate. In the 0-15 cm layer, the N0 3 -N concentration was low before biosolids application and in the spring following application but was high in September 1993. A high concentration of NO3-N was expected in the fall due to available organic N for conversion, an established microbial population, reduced nutrient uptake by plants, and generally dry conditions. As expected, the highest N0 3 -N concentration in the fall was measured for site 3a with the highest application rate of 179 dt/ha (301 mg/kg). The concentrations of NO3-N in the 60-90 and 90-120 cm layers were significantly different with respect to time, but the absolute increases were negligible. The average pre-application concentration for the sites was 0.1 mg/kg and the average 94 post-application concentration was 0.3 and 0.5 mg/kg for April and September 1993 respectively. In the 120-150 cm layer, the N0 3 -N concentration was highest for September 1993 samples and was highest for the 179 dt/ha application rate (3.0 mg/kg, site 3a). This increase might stem from sample contamination as the tailings are not very permeable. ( The total P concentration was higher after biosolids treatment in the 0-15 and 15-30 cm layers. The concentration of total P for the 15-30 cm layer also increased with increasing application rates. Since the total P concentration in biosolids is about 1%, this result is not surprising. 7.4.1 Nitrogen Balance and Summary An approximate N balance was computed for all sites. The N balance discussion includes the N content measured in vegetation shoots at the end of the first growing season; however, the amount of N in roots or fixed over the growing season was not estimated.The sampling intensity and treatment replication were insufficient to define mass balances between applied TKN, NH 4-N, and N0 3 -N, but sufficient to indicate trends that were generally consistent with previous expectations. The data show that nitrification was easily established on all plots as indicated by the nearly complete conversion of NH4-N to N0 3 -N over the first growing season. Complete N balance calculations are included in Appendix M, and Table 21 shows the amount of mineral N measured in the 60-150 cm layer. The discussion of N balances follows in order of increasing biosolids application rates. 95 TABLE 21. NITROGEN BELOW 60 cm - FIELD EXPERIMENT Plot Appl. Rate (dt/ha) Ratio of (60-150 cm Mineral N) to applied TKN Oct. '92 Apr. '93 Sept. '93 2b 62 % of TKN applied 0.25% 0.35% 0.38% 2a 77 % of TKN applied 0.16% 0.20% 0.33% 3b 77 % of TKN applied 0.09% 0.28% 0.25% 3a 179 % of TKN applied 0.04% 0.14% 0.39% Plot Appl. Rate (dt/ha) Ratio of (60-150 cm Mineral N) to originally applied Mineral N Oct. '92 Apr. '93 Sept. '93 2b 62 % of Min. N applied 0.6% 0.8% 0.9% 2a 77 % of Min. N applied 0.3% 0.4% 0.7% 3b 77 % of Min. N applied 0.2% 0.6% 0.5% 3a 179 % of Min. N applied 0.1% 0.3% 0.8% Application Rate 62 dt/ha - Plot 2b The spring 1993 composite soil data account for only 34% of the estimated applied TKN and the fall 1993 data was only marginally better (55%), probably due to problems in sample collection. Soil TKN concentration only increased in the 0-30 cm layer. During the first growing season, soil mineral N appears to have been taken up or lost to either volatilization or denitrification since there was no residual N in the fall of 1993 and N0 3 -N leaching below 60 cm was negligible (< 6 kg/ha). The results for the discrete soil samples were much lower than for the composite soil samples except for mineral N in the 60-150 cm layer (< 16 kg/ha). At the end of the first growing season, N in the shoots accounted for 3% (52 kg/ha) of the applied N. 96 Application Rate 77 dt/ha - Plot 2a The spring 1993 TKN concentrations in composite soil samples accounted for only 49% of the applied TKN indicating sampling difficulties. However, the fall 1993 data accounted for 84% of the applied TKN. The TKN results were variable but as expected, TKN did not appear to migrate downwards. The spring 1993 mineral N data accounted for 41% of the applied mineral N indicating high initial volatile losses. During the first growing season, about 270 kg N/ha was lost which corresponds to the high yield measured on plot 2a (5100 kg/ha). At the end of the first growing season, N in the shoots accounted for approximately 4% of the applied N. Virtually no N0 3 -N leaching below 60 cm occurred (< 9 kg/ha). The average results for discrete soil samples were much lower than for composite soil samples and do not appear to be representative. Application Rate 77 dt/ha - Plot 3b The 1993 composite soil data for plot 3b shows very good recovery of the applied TKN (75% in spring and 85% in fall) and poor recovery of mineral N (33% in spring and 35% in fall). As was the case for all of the other plots, spring 1993 mineral N was predominantly NH4-N indicating that no nitrification occurred over the winter and early spring. The fall 1993 data shows again the complete nitrification of the NH4-N present in the spring, but fails to show any significant N losses over the growing season suggesting that the rate of mineralization and plant uptake where comparable. Nitrate leaching was not evident over the first growing season. The discrete soil sampling data for plot 3b showed very good agreement with the composite soil samples for TKN and NH4-N, but N0 3 -N concentrations were very high in the spring of 1993 (799 kg/ha in 0-15 cm layer). This.high value for N0 3 -N in the early spring contradicts the results from all other plots and is not reflected in the fall 1993 data and may have resulted from sample contamination. 97 At the end of the first growing season, N in the shoots accounted for approximately 5% of the applied N. Application Rate 179 dt/ha - Plot 3a The TKN recovery in spring 1993 soil samples was very poor (22%) but somewhat better in the fall (43%) again probably due to sampling difficulties. Soil mineral N recoveries were similarly low (17%) but may reflect significant volatile losses due to the large quantity of biosolids exposed on the soil surface. The high NH4-N concentration in the spring of 1993 was almost completely nitrified over the growing season. Slightly elevated N0 3 -N levels at the 120-150 cm depth appear to be due to a sampling error (biosolids falling into the hole) as there is no indication that moisture penetrated from the surface to that depth in 1993. The discrete soil samples for plot 3a were in much closer agreement with the composite soil samples than for the other plots. Discrete mineral N levels were approximately 100 kg N/ha less on average than composite levels. At the end of the first growing season, N in the shoots of the one sample collected from site 3a accounted for 1% of the applied N. 7.5 Total Metals in Soil The metal concentrations in tailings samples collected in October 1992, and April and September 1993 were statistically compared for application rates 77 dt/ha (site 3b only) and 179 dt/ha (site 3a). The data analysis was accomplished with the main effect model with parameters 'time' and 98 'application rate'. Results of the data analysis are summarized in Table 22 and are detailed in Appendix N. Note that in the data analyses, concentrations below the detection limit were assumed to be half the concentration of the detection limit. In the data analysis for application rates 77 and 179 dt/ha, statistically significant differences were only identified for the metals Al, As, and Hg. The concentration of Al was significantly different in the 90-120 and 120-150 cm layers. However, since Al is abundant in soils and the Al concentrations in the different tailings plots varied between 16200 and 40000 mg/kg before treatment, the difference in Al concentrations is likely due to a site difference rather than a treatment difference. Since As does not leach readily, the difference in As concentrations in the 30-60 and 90-120 cm layers is also probably due to a site difference rather than a treatment difference. Arsenic concentrations tended to be highest in April 1993, but were close to the detection limit (7 mg/kg). All measured As concentration were well below the Level of Quantification (21 mg/kg). The Hg concentration went up in the 0-15 cm layer from below the detection limit (0.2 mg/kg) to 0.2 to 0.4 mg/kg after biosolids application. Since the Level of Quantification for Hg is 0.6 mg/kg, changes in Hg concentrations are only subtle. All soil metals were below the CCME criteria (1991) for agricultural or residential soils except for Cu. 7.6 Problems and Errors in Sample Collection of Field Samples The Princeton Biosolids Demonstration Project is believed to be the first of its kind in British Columbia and was very successful in achieving revegetation. The following paragraphs point out some of the problems that were encountered during soil and vegetation sampling and include suggestions to minimize problems and errors in future projects. 99 TABLE 22. TOTAL METALS IN SOIL - FIELD EXPERIMENT Metal Selenium Mercury Arsenic Aluminum Cadmium Chromium (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) Depth 0 -15 cm Mean 0.5 T I M E <5 .0 21633 <0 .5 37.8 Std. Dev. 0.1 s ig . 1297 2.2 15 -30 cm Mean 0.5 <0 .2 <5 .0 28450 <0 .5 48.7 Std. Dev. 0.1 1911 3.3 30 - 60 cm Mean 0.4 <0 .2 T I M E 33333 0.5 52.3 Std. Dev. 0.1 s ig . 3747 0.04 1.6 60 - 90 cm Mean 0.4 < 0.2 3.8 32017 0.6 53.8 Std. Dev. 0.1 2.7 2763 0.3 4.4 90 -120 cm Mean 0.3 <0 .2 T I M E A A P P L 0.5 55.7 Std. Dev. 0.07 s ig . s ig . 0.3 2.2 120-150 cm Mean 0.32 <0 .2 2.9 A A P P L 0.35 54.2 Std. Dev. 0.04 0.61 s ig . 0.04 1.08 Normal Range * 0.1 - 2 0.02 - 0.2 1 - 50 1 0 0 0 0 -200000 0.01 - 7 5 - 1000 Typical Concentration: * 0.5 0.05 5 50000 0.06 20 C C M E : ** 2 0.8 20 3 250 0 - 1 5 cm Mercury (mg/kg): Duncan Group ing M e a n N T I M E a 0.4 2 _ S e p . 1993 b 0.1 2 _Oc t . 1992 b 0.1 2 _Apr . 1993 30 - 60 cm Arsenic (mg/kg): Duncan Group ing M e a n T I M E 5.0 3.0 2.5 _Apr . 1993 _Oc t . 1992 _ S e p . 1993 Notes: The main effects of A A P P L and T I M E (i.e. no interactions) were examined in the ana lys is . The Duncan multiple range test at the 0.05 level of probability w a s used to determine signif icantly different means . M e a n s preceded by different letters are significantly different. 'Std. D e v . ' refers to the samp le standard deviat ion. Cobal t , n icke l , and z inc concentrat ions remained relatively unchanged. Lead concentrat ion was c lose to the Limit of Detect ion and tended to be lower after treatment. Mo lybdenum concentrat ion w a s below the Limit of Detect ion. Bohn e t a l . , 1985 ** lowest of the remediat ion limits for agricultural or residential so i ls set by the Canad ian Counc i l of Ministers of the Envi ronment (1991) 100 Like all data, the Princeton field data had associated systematic and random errors. Systematic errors can be traced to a cause while random errors result from many different causes and their effects can be minimized by collecting and averaging more comparable data. The main error in the Princeton project is believed to be a systematic error that resulted from the collection of soil samples in the field. The collection of representative samples from the treated plots was very challenging. Finding less total N on the sites than was applied and not measuring a proportional increase in organic matter content and CEC with increasing application rates of biosolids indicates that representative samples were not always collected. Soil Samples Contamination of soil samples might occur during their collection, handling, transport, or analysis in the laboratory. Under dry weather conditions, contamination problems at the time of collection can usually be kept to a minimum, but if it is raining or if the soil surface is wet, contamination is harder to avoid since the biosolids and the tailings tend to get slimy. Contamination during transport to the laboratory could have happened if a sample bag was not properly closed or opened up under the weight of other bags. Composite Soil Samples When biosolids are applied very evenly to a treatment site, the collection of representative composite samples is easy as deviations from the mean are small. Operational scale field application of biosolids with manure spreaders worked well on the tailings when considering soil fertility status and vegetation establishment. The only problem with the manure application was the collection of representative soil samples after application since manure spreaders left biosolids in chunks of 2 to 10 cm in diameter on the ground that were not uniformly distributed. The disking operation after application broke up and incorporated the biosolids fairly well for the lower application rates (62 and 77 dt/ha) but not well for the highest application rate (179 dt/ha). 101 In addition, the sampling probe had a tendency to part the biosolids on the soil surface rather than core them, leading to lower nutrient and organic matter results than were expected. In hindsight, although the size of the sampling probe was probably adequate for soil samples for layers below the zone of incorporation, it was not large enough for the 0-15 cm layer. A subsample volume of 10 cm in diameter and 15 cm in depth would have been able to sample typical soil surface conditions on the tailings. Ten subsamples per sample would probably have been adequate. To avoid sample contamination, the soil probe was cleaned after the collection of every subsample and the soil probe was kept off the soil surface when emptying soil cores into sample bags. In addition, the exposed part of soil cores was discarded. Sample contamination from the surrounding soil could be overcome by collecting samples into small hollow plastic tubes that fit into the sampling probe. An appropriate plastic tube has still to be investigated since some subsurface layers of the tailings are hard and might break the plastic tube inside the soil probe. Once collected, the plastic tubes can be sealed at the bottom and top in the field and the bottom and top sections can be wasted in a laboratory to avoid contamination. Another source of contamination is from biosolids that fell into a sampling hole from the soil surface. To avoid this problem, biosolids were cleared away around sampling holes (15-20 cm in diameter) and the top 2 cm of every soil core was discarded. Discrete Soil Samples Discrete soil samples were collected from the edges of freshly dug soil pits with trowels. While collecting a soil sample, care was taken to collect a vertical layer of the same diameter throughout. Contamination errors might have occurred through biosolids that fell into the pit. In hindsight, it would probably have been better to collect two to three extra composite samples from every treatment site rather than discrete samples since site variations were great and many more 102 discrete samples (at a high cost per sample) would be necessary to determine the site variation well. In comparison, a few composite samples per treatment could have established a treatment mean and provided an estimate of variance about that mean with reasonable accuracy and at a reasonable price. A good estimate of the treatment means would have led to a better base for comparative study of different treatments. Vegetation Samples The fertilization benefit of biosolids application on plant health was difficult to assess due to the lateness of the sampling season affecting the maturity of plants. In addition, the vegetation samples were only analyzed as a whole and not separated according to species although the time of sampling and the maturity of plants make an extreme difference in nutrient levels between species. Contamination errors in vegetation samples might have resulted from tailings and biosolids adhering to vegetation samples since they were not washed before analysis. In future monitoring efforts, vegetation samples should be analyzed by species and sampling should be conducted prior to the flower stage (preferably late June) to determine the effect of biosolids application on macronutrient and metal contents and/or during the grazing season (spring/early summer) to determine forage suitability for animal consumption (cattle and deer). Other Errors Other errors that were associated with data collected during the Princeton Demonstration Project include inadequate collection of crucial data or the collection of data that were not comparable. For example, the analysis of characteristics of biosolids added to the tailings did not include the analysis of TKN in land-dried biosolids. Therefore, an approximate TKN concentration had to be estimated from historical data. Records on the application of different types of biosolids to site 2b are not complete which impeded the interpretation of results and calculation of mass balances. 103 Ideally, all sample data that are to be compared have to be collected, composited, and analyzed in the same fashion. In the field project, control and treatment samples were sometimes composited differently making the results less comparable and the data interpretation difficult. Laboratory methods used were not always as recommended for high pH soils. For example; available P should have been determined with the Olsen-P method (Page et al., 1982) and organic matter should have been measured with an organic C (TC-IC) rather than a total C method (Page et al., 1982). Actual concentrations of exchangeable C a 2 + might have been different than were measured due to the presence of free C a 2 + (Page et al., 1982). 8.0 SUMMARY OF MAIN RESULTS - FIELD EXPERIMENT The demonstration project was very successful. Nitrification was easily established on all plots as indicated by the nearly complete conversion of NH4-N to N0 3 -N over the first growing season. Vegetation was established within one growing season on all sites. The established vegetation was more vigorous than on the control sites and the wind erosion from the demonstration sites has stopped, and all site improvements were accomplished without irrigation. Over the last two growing seasons, there has been vigorous growth, especially of alfalfa, a N fixing legume. Compared to the sparse natural revegetation over the past 40 years, the growth rate is remarkable. Tailings Soil Fertility NH4-N, N0 3-N, Fe, and the organic matter content tended to increase with increasing application rates. 104 The concentration of NH4-N tended to be high in the early spring and low in the fall, whereas the N0 3 -N concentration tended to be low in the early spring and high in the fall, indicating high nitrifier activity through the growing season. Nitrate leaching from plots 2a (77 dt/ha), 2b (62 dt/ha), 3a (179 dt/ha), and 3b (77 dt/ha) was negligible in the first growing season. For details, refer to Table 21 or Appendix M (Nitrogen Balance Section). Plant available Cu in the tailings tended to increase following biosolids application. Tailings Vegetation In 1993, fall rye, brome, timothy, crested wheatgrass, fescues, alfalfa, and hairy vetch grew of which fall rye was visibly the most prominent. The control sites were dominated by weeds and grasses and the treatment sites tended to be dominated by fall rye and grasses. Virtually no legumes were present on the seeded and unseeded control sites, but legumes (primarily alfalfa) established on the treatment sites. The treatment of Princeton tailings with 77 dt/ha stored dewatered biosolids led to improved vegetation quality and yield for all parameters tested. Levels of Cu and Mo decreased in foliage whereas other metals remained essentially unchanged. A notable trend of a higher Cu:Mo ratio was determined for vegetation collected from sites of 2a, 2b, and 3b. The trend toward lower Mo levels in foliage is possibly a result of the different species composition on the control and treatment sites, increased nitrification resulting in lowered soil pH and reduced Mo availability to plants, or increased Fe concentration in soil. 105 Cattle and deer grazing in 1993 has not hampered the vegetation growth. In future vegetation monitoring, vegetation should be sampled by species and treatment site, and preferably prior to the flower stage (late June) to allow for a better interpretation of results. Tailings - Total Metals The Hg concentration increased with increasing application rates, but the increases were very slight and below the Level of Quantification. All soil metals were below the CCME criteria (1991) for agricultural or residential use except for Cu. 9.0 CONCLUSION The revegetation of copper mine tailings in Princeton B.C. (pH 8.0) with biosolids and seeds was very successful. Vegetation established without irrigation within one growing season on all sites, and was more vigorous on the treated sites than on the control site. Nitrification was easily established on all plots as indicated by the nearly complete conversion of NH4-N to N0 3 -N over the first growing season. Positive environmental effects after biosolids application were major: accelerated reclamation, reduced wind erosion, improved vegetation quality, increased yield, improved soil fertility, and good establishment of alfalfa {Medicago sativa) whereas the negative effect was minor: increased but not quantifiable Hg concentrations in the 0-15 cm layer. The laboratory experiments showed that the growth of salt sensitive vegetation may be reduced when applying 300 dt/ha freshly dewatered anaerobically digested biosolids to the Princeton tailings (soil EC ~ 4dS/m). The laboratory leaching experiments demonstrated that although N0 3 -N concentrations were relatively high in the 0-15 cm layer (up to 3000 kg/ha for the 300 dt/ha application rate), N0 3 -N in 106 leachate was less than 2.4 mg/L for most columns; however, the experiments also showed that N0 3 -N leaching can be substantial when biosolids are applied to tailings which are prone to water erosion as biosolids can be swept with the tailings downstream. The potential of N0 3 -N contamination of groundwater after further applications of biosolids to the Princeton tailings (at similar rates) is very low due to the low permeability of the tailings, the low annual precipitation, the flat terrain, and the increased evapotranspiration after good vegetation establishment. The mineralization rates measured in the laboratory experiments ranged from 17 to 31% under wetter conditions and from 29 to 43% under dryer conditions, and were higher than the EPA guideline level of 20% (U.S. EPA, 1983). Besides measurement errors that could have overestimated the N losses leading to a high estimate of the mineralization rate, the high mineralization rate is likely due to the good mixing of biosolids with the tailings, and due to close to optimum conditions for mineralization and nitrification in soil (pH > 7.5; temperature ~ 17°C). Furthermore, EPA guidelines were based on a number of projects, many of which were acid generating spoils in which the mineralization and nitrification rates are lower even after the pH was raised to 6.5 before the application of biosolids. Nitrogen losses in the laboratory and field experiments were high, especially for the highest application rates, although the actual N losses were probably smaller. This could have been proven by better sampling and/or laboratory procedures. Nitrogen losses were about 30% for the 300 dt/ha application rate in the laboratory and in the 50% range for the 179 dt/ha application rate in the field. The author believes that the silty nature of the tailings contributed to the slow N0 3 -N leaching which in turn led to an accumulation of N0 3 -N in the upper layer from which N was lost through denitrification after temporary flooding of the soil (storm events). In addition, the high pH likely contributed to volatilization losses. 107 As expected in calcareous tailings, metals did not leach in the field or the laboratory experiments. Only the Hg levels in the 0-15 cm layer and for the 300 dt/ha application rate were above the maximum recommended metal concentration in soil in B.C. (B.C. MOE, 1983). In future projects, the results of the field project and laboratory experiments can be applied to all of the Princeton tailings and likely to other copper mine tailings in the semi-arid interior of B.C. Furthermore, the successful reclamation of the Princeton tailings with biosolids suggests the possibility of waste rock reclamation with a mixture of tailings and biosolids in cases where not enough overburden is available for reclamation. Another project for further research may be the study of the environmental effects after the application of biosolids and seeds to acidic mine wastes in B.C. (after raising the spoil pH to 6.5), something extensively practiced in Pennsylvania (Sopper, 1993). 10.0 RECOMMENDATIONS In the author's opinion, the mineralization rate should be studied in more detail and under more controlled conditions. To study the mineralization rate, one experimental design could include the setup of 100 short columns (20 cm in height) which are all exposed to the same environmental conditions. The contents of five of the columns could be analyzed weekly for TKN, N0 3 -N, and NH4-N to expose the mineralization behaviour of organic N in biosolids when mixed with soil or tailings (exponential, logarithmic, quadratic, or linear behaviour). Recommendations - Field Experiment Conduct of same procedures of sample collection and analysis for the control and treatment sites. Collection of larger soil subsamples from the zone of biosolids incorporation to obtain representative samples. 108 Monitoring of vegetation samples by species and treatment. Monitoring of vegetation for macronutrient and metal content prior to the flower stage and/or during the grazing season. Higher replication of the application rates (at least treatment duplication). Establishment of a database for background and control site concentrations. Establishment of a database for average concentrations of all major elements in biosolids and where and when they were applied. Recommendations - Laboratory Experiments Analysis of particulates in leachate for N0 3 -N and TKN to determine if or how much of the N0 3 -N and TKN in leachate may be attributed to sample contamination with biosolids. Increased sampling intensity and a switch to larger sample sizes (2-4 g) for the TKN analysis to improve the accuracy of Total Nitrogen results. 109 REFERENCES ASCE (Am. Soc. of Civil Engineers). 1990. Evapotranspiration and Irrigation Water Requirements. No. 70. B.C. MAFF (Min. of Agriculture, Fisheries, and Food). 1991. Minerals for Beef Cattle. Fact Sheet. Agdex 420. B.C. MOE (Ministry of Environment, Lands and Parks). 1992. Letter of Approval to apply dewatered, anaearobically digested sewage sludge to demonstration plots at the Town of Princeton tailings pile site. B^C. MOE Penticton. File: AR-11578. B.C. MOE. 1983. Draft Guidelines for Disposal of Domestic Sludge under the Waste Management Act. 19p. Bohn, H.L., B.L. McNeal and G.A. O'Connor. 1985. Soil Chemistry. Second Edition. John Wiley & Sons. New York. 341 p. Bowman, R.S. 1984. Evaluation of some new tracers for soil water studies. Soil Sci. Soc. Amer. Jour. 48:987-993. BS 8004. 1986. British Standard 8004. British Standards Institution. CAST (Council for Agricultural Science and Technology). 1976. Application of Zewage Sludge to Cropland: Appraisal of Potential Hazards of the Heavy Metals to Plants and Animals. Rep. No. 64. Office of Water Programs. U.S. EPA-430/9-76-013. CAST (Council for Agricultural Science and Technology). 1980. Effects of Sewage Sludge on the Cadmium and Zinc Content of Crops. Rep. No. 83. ISSN 0194-4088. 77p. CCME (Canadian Council of the Ministers of the Environment). 1991. Interim Canadian Quality Criteria for Contaminated Sites, Rep. CCME EPC-CS34 prepared by the CCME subcommittee on Environmental Quality for Contaminated Sites. Sept. 1991 Chaney, R. L. 1990. Food Chain Impact: Public Health and Sludge Utilization. In BioCycle. Oct. 1990. p.68-73. Coker, E.G., R.D. Davis, J.E. Hall, and C.H. Carlton-Smith. 1982. Field Experiments on the use of consolidated sewage sludge for land reclamation: Effects on crop yield and composition and soil conditions, 1976-1981. Tech. Rep. TR 183. Wat. Research Ctr., Medmenham, U.K. p. 83. Corey, R.B., L.D. King, C. Lue-Hing, D.S. Fanning, J .J . Street, and J.M. Walker. 1987. Effects of sludge properties on accumulation of trace elements by crops. In Land Application of Sludge and Food Chain Implications. Lewis Publishers Inc. Chelsea, Mi, pp. 25-51. Cottenie, A. and L. Kiekens. 1972. Exchange of Zn, Mn, Cu, and Fe in relation to saturation of the soil complex. Potassium in soil, 9th IPI-Colloquium, Landshut. 91-101. Craig, R.F. 1992. Soil Mechanics. Chapman & Hall. London. Davis, R.D. 1983. Long-term Effects of Metals. In Utilisation of Sewage Sludge on Land: Rates of Application and Long-term Effects of Metals. S. Berglund, R.D. Davis and P. L'Hermite (eds.). D. Reidel Publishing Company, Dordrecht, Holland, pp. 218-224. 110 Edmonds, R.L. 1979. Microbiological Characteristics of Dewatered Sludge following Application of Forest Soils and Clearcut Areas. In Utilization of Municipal Sewage Effluent and Sludge on Forest and Disturbed Land. W.E. Sopper and S. N. Kerr (eds.). Pennsylvania State University Press, University Park. pp. 123-136. Elder, Linda A. 1982. Water Table Height and Nitrate Leaching in Undisturbed Soil Columns. M.Sc. Thesis. Univ. of British Columbia. Bio-Resource Engineering. Epstein, E., D.B. Keane, J .J . Meisinger, and O.J. Legg. 1978. Mineralization of nitrogen from sewage sludge and sludge compost. J . Environ. Qual. 7:217-221. Ernst, N. 1976. Physiological and Biochemical Aspects of Metal Tolerance. In Effects of Air Pollutants on Plants. T.A. Mansfield (ed.). Cambridge University Press. Cambridge, pp. 115-133. Firestone, M.K. 1982. Biological Denitrification. In Nitrogen in Agricultural Soils. F.J. Stevenson (ed.). Agronomy 22. ASA-CSSA-SSA, Madison Wise. pp. 289-326. Foth, H.D. 1984. Fundamentals of Soil Science. Seventh Edition. John Wiley & Sons. New York. 435p. Gekeler, W.E., E. Grill, E. Winnacker, and M.H. Zenk. 1989. Survey of the plant kingdom for the ability to bind heavy metals through phytochelatins. Zeitschrift fuer Naturforschung. 44c: 361-369. Gizikoff, K.L. 1990. Soil Management and Revegetation Success on Waste Rock Dumps at a Southern Interior B.C. Copper Mine. Master Thesis. University of British Columbia. Gould Gizikoff, K.L. 1994. Princeton Demonstration Projects - 1994 Vegetation Monitoring Program. Report prepared for the Greater Vancouver Regional District (Residuals Management Group). Graham, R.D. 1981. Absorption of Copper by Plant Roots. In Copper in Soils and Plants. J.F. Loneragan, A.D. Robson and R.D. Graham, (eds.) Academic Press. Sydney, pp. 141-163. Gumbel, E.J. 1954. Statistical Theory of Extreme Values and some Practical Applications. GVRD (Greater Vancouver Regional District). 1992. Progress Report to the Ministry of the Environment (Environmental Protection Division) for Approvals AR-11576, AR-11577, AR-11578. July-December 1992. GVRD. Residuals Management Group. GVRD (Greater Vancouver Regional District). 1993a. Wastewater Residuals Management Plan. June 30, 1993. GVRD (Greater Vancouver Regional District). 1993b. Progress Report to the Ministry of the Environment (Environmental Protection Division) for Approvals AR-11576, AR-11577, AR-11578. January-July 1993. GVRD. Residuals Management Group. GVRD (Greater Vancouver Regional District). 1994a. Progress Report to the Ministry of the Environment (Environmental Protection Division) for Approvals AR-11576, AR-11577, AR-11578. July-December 1993. GVRD. Residuals Management Group. GVRD (Greater Vancouver Regional District). 1994b. Final Progress Report to the Ministry of the Environment (Environmental Protection Division) for Approvals AR-11576, AR-11577, AR-11578. 1992-1994. GVRD. Residuals Management Group. 111 Haghiri, F. and P. Sutton. 1982. Vegetation establishment on acidic mine spoils as influenced by sludge application. In Land Reclamation and Biomass Production with Municipal Wastewater and Sludge. W.E. Sopper, E.M. Seaker, and R.K. Bastian (eds.). The Pennsylvania State University Press. University Park, PA. pp. 68-74. Hall, J.E. and E. Vigerust. 1983. The Use of Sewage Sludge in Restoring Disturbed and Derelict Land to Agriculture. In Utilisation of Sewage Sludge on Land: Rates of Application and Long-term Effects of Metals. S. Berglund, R.D. Davis and P. L'Hermite (eds.). D. Reidel Publishing Company, Dordrecht, Holland, pp. 91-103. Henry, C.L. and R.B. Harrison. 1991. Literature Reviews on Environmental Effects of Sludge Management. Univ. of Washington, Coll. of Forest Resources, Seattle, Washington 98195. 193p. Herms, U. 1982. Untersuchungen zur Schwermetalloeslichkeit in kontaminierten Boeden und kompostierten Siedlungsabfaellen in Abhaengigkeit von Bodenreaktion, Redoxbedingungen und Stoffbestand. Doctoral Thesis, Kiel, p. 269. Kerr S. N., W.E. Sopper, and R.B. Edgerton. 1979. Reclaiming anthracite refuse banks with heat-dried sewage sludge. In Utilization of Municipal Sewage Effluent and Sludge on Forest and Disturbed Land. W.E. Sopper and S.N. Kerr (eds.). The Pennsylvania State University Press. University Park, PA. pp. 333-352. Kiekens, L. 1983. Behaviour of Heavy Metals in Soils. In Utilisation of Sewage Sludge on Land: Rates of Application and Long-term Effects of Metals. Berglund, S., R.D. Davis and P. L'Hermite (eds.). D. Reidel Publishing Company, Dordrecht, Holland, pp. 126-134. Lindsay, W.L, W.A. Norvell, 1978. Development of a DTPA test for zinc, iron,, manganese, and copper. Soil Sci. Soc. Am. J . 42:421-428) Long, Tom. 1993. Biosolids Pathogen & Vector Reduction - What it Means & Understanding the Methods. Washington State Department of Health. Community Environmental Health Programs. 19p. Magdoff, F.R. and F.W. Chromec. 1977. N mineralization from sewage sludge. J . Environ. Sci. Health. A12:191-201. McDonald, J.D. and D.P. Lane. 1979. Irrigation with Sewage Effluent on the Old Granby Tailings at Princeton, B.C. In Proceedings of the Third Annual British Columbia Mine Reclamation Symposium, pp. 111-119. McGill, Paul, and Ladd (eds.). Soil Biochemistry. New York. Marcel Dekker. Vol. 5. p. 238. Melsted, S.W. 1973. Soil-plant Relationships In Recycling Municipal Sludges and Effluents on Land. Nat. Assoc. of State Univ. and Land Grant Colleges, Washington, D.C. pp. 121-128. Metcalf and Eddy. 1991. Wastewater Engineering. Third Edition. Revised by G. Tchobanoglous and F.L Burton. 1334 p. Mortvedt, J .J . , P.M. Giordano, and W.L. Lindsay (eds.). 1972. Micronutrients in Agriculture. Soil Sc. Soc. Am., Madison, Wisconsin, U.S.A. pp. 319-347. Noller, C.H. and C.L. Rhykerd. 1978. Nitrate Accumulation in Corn and Nitrate in Animals. In Better Crops with Plant Food. 62:29-31. 112 Page, A.L., R.H. Miller, and D.R. Keeney (eds.). 1982. Methods of Soil Analysis. Am. Soc. Agron, Soil Sc. Soc. of Am. Madison, Wisconsin, U.S.A. Rauser, W.E. 1990. Phytochelatins. Annual Review of Biochemistry 59: 61-86. Salisbury, F.B. and C.W Ross. 1992. Plant Physiology. Fourth Edition. Wadsworth Publishing Co., Belmont, Ca. U.S.A. 681 p. Seaker, E.M. and W.E. Sopper. 1988. Municipal sludge for minespoil reclamation: I. Effects on microbial populations and activity. J . Environ. Qual. 17:591-597. Sopper, W.E. 1993. Municipal Sludge Use in Land Reclamation. Lewis Publishers. Boca Raton. 163p. Smith S.R. and K.E. Giller. 1992. Effective Rhizobium Leguminosarum Biovar Trifolii present in five soils contaminated with Heavy Metals from long-term Applications of Sewage Sludge or Metal Mine Spoil. Soil Biol. Biochem. 24(8): 781-788. Steffens, J.C. 1990. The heavy-metal binding peptides of plants. Annual Review of Plant Physiology and Plant Molecular Biology. 41:553-575. Stevenson, H.F. 1982. Humus Chemistry. John Wiley & Sons. New York. Stroo, H.F. and E.M. Jencks. 1982. Enzyme activity and respiration in mine spoils. Soil Science Society of America Journal. 46:548-553. Ta, T.C. and M.A. Farris. 1987. Species variation in the fixation and transfer of nitrogen from legumes to associated grasses. Plant and Soil 98:265-274. Terry, R.E., D.W. Nelson, and L.E. Sommers. 1981. Nitrogen Transformations in sewage-sludge amended soils as affected by soil environmental factors. Soil Sci. Soc. Am. J . 45:506-513. Tiller, K.G. and R.H. Merry. 1981. Copper Pollution in Agricultural Soils. In Copper in Soils and Plants. J.F. Loneragan, A.D. Robson and R.D. Graham, (eds.) Academic Press. Sydney, pp. 119-137. Tisdale, S.L., W.L. Nelson, J.D. Beaton, and J.L. Havlin. 1993. Soil Fertility and Fertilizers. Fifth Edition. Macmillan Publishing Co., New York, N.Y., U.S.A. 634 p. Tomati, U., A. Grappelli and E. Galli. 1984. Soil Microorganisms and Long-term Fertility. In Long-term Effects of Sewage Sludge and Farm Slurries Applications. Williams, J.H., G. Guidi and P. L'Hermite (eds.). Elsevier Applied Science Publishers, New York. pp. 14-21. Univ. of Georgia Coop. Extension Service. 1979. Plant Analysis Handbook of Georgia. Bulletin No. 735, Univ. of Georgia, Athens, GA p.42. U.S. EPA (Environmental Protection Agency). 1983. Process Design Manual: Land Application for Municipal Sludge. Env. Res. Info. Ctr., Cincinnati, Ohio, U.S.A. EPA 625/1-83-016. Section 8 and Appendix C. Verdegem, L, O. van Cleemput, and J . Vanderdeelen. 1981. Some factors inducing the loss of nutrients out of the soil profile. Pedologie 31:309-327. Verloo, M. 1974. Komplexvorming van sporenelementen met organische bodemkomponenten. Doctoral thesis, State University Gent. 113 Voos, G. and B.R. Sabey. 1987. Nitrogen mineralization in sewage-sludge-amended coal mine spoils and topsoils. J . Environ. Qual. 16:231-237. Wagner, A.A. 1957. Unified Soil Classification System In Proceedings of the Fourth International Conference SMFE. London, Vol. 1. Walsh, L.M., and J.D. Beaton. 1973. Soil Testing and Plant Analysis. Soil Sci. Soc. of America, Inc. Madison, Wisconsin, U.S.A.) Williams, J.H., G. Guidi and P. L'Hermite (editors). 1984. Long-term Effects of Sewage Sludge and Farm Slurries Applications. Elsevier Applied Science Publishers, New York. Woolhouse, H.W. and S. Walker. 1981. The Physiological Basis of Copper Toxicity and Copper Tolerance in Higher Plants. In Copper in Soils and Plants. J.F. Loneragan, A.D. Robson and R.D. Graham, (eds.) Academic Press. Sydney, pp. 235-262. A P P E N D I X A Environmental Data for Princeton, B.C. 115 PRINCETON DEMONSTRATION PROJECT - RESEARCH SITE INFORMATION Owner of Tailings: Township of Princeton, B.C. Location: Lat.: 49°27'30"N Long.: 120° 29' 0" W Distance from Princeton (SSE): 4 km Distance from Similkameen River: 275 m Elevation of Research Sites: 667 m Height above Shores of Similkameen River: 43 m Depth to Native Till: 17 m Slope: < 0.25 % Average Climatic Data for the Princeton Airport (Canadian Climatic Normals (Vol. 6); Dec. 1,1971 - Nov. 30,1991) The climate is semi-arid with wide ranging variations. Temperature: The mean temperature is 5oC with extremes of -41 oC to +38oC. Frost free days (144-year average): 104 Earliest Last Frost on Record: May 22 Latest Last Frost on Record: Jul. 5 Earliest First Frost: Aug. 1 Latest First Frost: Oct. 7 Precipitation: Mean yearly PPT: Mean PPT between May 1 and Sept.30: Evapotranspiration: Mean ET between May 15 and Sept. 15: 354 mm, s = 188mm 138 mm 752 mm (110 % Hargreaves) SITE INFO.XLS 116 z g < a LU CO LU LU Of O < X LU X g i -| 0_ z r-o Q. LU LU O LU I-< £ r-M LU o a> to re | I £= CO co "5 3 2 o E » « • X j2 CD C  E I CD (U 3 £ CO E 5 CD <S • a T ai J2 CD CD "s •§ s I s * CD 2 | S-uJ <5 £ g E ° §3 led on CO E 8 c "S CD Q. CD CD T J C 3 CD O ' ~ c CO 'co sz -CD > CD nt, MO CD X E CD o o CO O) CO CD E CE CD CO 0) < E LO lysi lion CD CO O) u CO _o CD T J > CO CO CD c O c 9i iqual I pen < CD CO CO <S CD .£ £ x ** o . E Q. 8 t 2 o CD -J= CO CO = CD fc> c § M 1 .2 • ° a> 5 c x : 2 •2 ~ o ™ - 2-Q. CO > to. CD ® CO CO CD « ffl o 5 = CD 5 2 & CO CO = S P S !» e f i LU o O ? s i T- D. 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Minfile #092HSE001) Dominant host rock: Volcanic Commodities: Copper Gold Silver Minerals: Chalcopyrite Pyrite Bornite Chalcocite Alteration: Biotite Albite Epidote K-Feldspar Scapolite Deposit Classification: Porphyry Hydrothermal Isotopic Age: 193+-7Ma Mineralization Age: Lower Jurassic Lithology: Andesitic Basaltic Tuff Breccia Andesitic Basaltic Tuff Andesitic Basaltic Flow Andesitic Basaltic Agglomerate Diorite Diorite Porphyry Dyke Felsite Dyke Pegmatite Vein c u ORE.XLS A P P E N D I X B Biosolids Characteristics & Seed Mix 119 £ vi (A U C in » 2 n •a £ oo — o o> O " — « o 2 n ° 8 q & CO Q S I o a> .O Q. <q x _i LU u £ ai = i s § 8 < S s S | o a> xi a. ro x _ l UJ " - S o .2 5") o > o S o ™ LU T3 O S « to <i> = .2 ? § o 5 o (0 CD = C Q CO LU •a — <u X -a = 2 a: I I O) o < -> N c j „ Q. . 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LU x a UJ X a UJ UJ (0 x i c o n E n u ro ^ i l c: o . 8 8 3 a 3 E 51 8 e Li- LL CQ ' ro 8 5 £ g 8 S I S a - S s S a J c co w CO £ 8 i 8 11 2 ro ^ £ £ a> o .c O> ^ S < H L 5 h h to O) £ ro ro Q) O) r" O) CO o * m i to < m "5 OT 0) (A O ro co x S O < * ro < K < ro O CO L L O -- i - ^ LU > 5 E 5 § S- ro I- UJ O co IT <£ UJ o in in in CO > O cd co X £ 0) 1 (0 a Si o e 3 co a> >. > 121 A P P E N D I X C Leaching Experiments - Water Regimes & Related Princeton Precipitation Data Leaching Experiments - Quantity of Leachate Collected Leaching Experiments - Days with Particulates in the Leachate Leaching Experiments - Standing Water on Top of Test Columns Leaching Experiments - Temperature Regimes WATER REGIME FOR THE LEACHING EXPERIMENTS Leaching Run 1 Leaching Run 2 and Pot Trial Week Day in Leaching Run Distilled Water (Dl) added to Columns (mm) Dl added to Columns/Week (mm) Dl added to Columns (mm) Dl added to Columns/Week (mm) 1 1 2 33 31 63 33 31 64 2 8 9 26 6 32 26 6 32 3 15 16 13 4 17 13 4 17 4 22 23 13 4 17 5 29 30 13 4 17 6 36 37 13 4 17 7 43 44 8 50 51 3 9 12 9 57 58 3 5 8 5 5 10 10 64 65 3 5 8 11 71 72 12 78 79 5 9 14 13 85 86 5 9 14 Total Water added (mm): 180 163 Summary of Single Set Maximum Frequency Analyses of Exceedence for 20 Years of Rainfall Data recorded at the Princeton Airport, B.C. (Dec. 1,1971 to Nov. 30,1991) * Return Period in years: 1-Day Maximum Precipitation (mm) 2-Day Maximum Precipitation (mm) 3-Day Maximum Precipitation (mm) 5-Day Maximum Precipitation (mm) 1.01 8 9 14 18 2 23 31 35 39 5 32 44 47 51 10 38 53 56 59 20 44 61 64 67 25 45 64 66 70 50 51 72 74 77 100 57 80 82 85 assuming Gumbel distribution WATEREG.XLS 123 Summary of Frequency Analyses for Rainfall Data recorded at the Princeton Airport between Dec. 1,1971 and Nov. 30,1992 Return Period Yearly Maximum Seasonal Maximum Precipitation (mm) Precipitation (mm) (Nov. 1 -> Apr. 30) (Feb.. 1 -> Apr. 30) 12 months 6 months 3 months 1.01 200 65 3 2 343 179 58 5 429 247 92 10 486 293 114 20 540 336 135 25 557 350 142 50 611 392 162 100 664 434 183 assuming Gumbel distribution Summary of Frequency Analyses for Rainfall Data recorded at the Princeton Airport between Dec. 1,1971 and Nov. 30,1992 Average Contribution of Storms to Yearly Precipitation in 20-year Period: Average Contribution of Storms to Seasonal Precipitation in Seasons: (Dec. 1,1971 -> Nov. 30,1991) (Nov. 1 -> Jan. 31) (Feb.. 1 -> Apr. 30) (May 1 -> Jul . 31) (Aug. 1 -> Oct. 31) 1-Day Storm 16 .9% 1-Day Storm 12.2% 2 1 . 3 % 2 4 . 6 % 2 1 . 5 % 2-Day Storm 2 3 . 1 % 2-Day Storm 20 .7% 2 6 . 7 % 2 8 . 2 % 3 2 . 2 % 3-Day Storm 2 0 . 5 % 3-Day Storm 18.4% 18 .3% 2 1 . 5 % 2 2 . 8 % 4-Day Storm 1 6 . 1 % 4-Day or 4 8 . 7 % 33 .8% 2 5 . 7 % 2 4 . 1 % 5-Day Storm 11 .2% longer Storm 6-Day or 12 .2% longer Storm 20-year A v g . 354 133 63 87 68 Precipitation (mm) Sample Std. 188 42 31 41 33 Deviation (mm) GUMBELP.XLS 124 I T T | T K O *D | o O O O ICM O | 0 | C M | I T llO ICO l O |CD ICS,! |t£) |CM|O|O|C0| m fl A « A | £4 E t = » M A § | S r i •w » in 2 » s ? 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CD .2: j= i f : ** o 3 | CD U CO _^ g> 6 CO CD > - £ co .E-E g £| 1 8 - E p 5 CD CD CD E E 3= CD T J 3 ,2 CO H= co O CD CD C Q . E CO o •s i CO o CD iz — u > £ CO CO s ° Q . to E 9 CD 5 * * CD CD C O) .E co •9 a CD CD h- CO z 0J o z 131 A P P E N D I X D Leaching Run 1 - Soil Nitrogen, pH, and EC LEACHING RUN 1 - NITROGEN BALANCE IN THE 0-45 cm LAYER C l a s s Level Information C l a s s Leve ls V a l u e s L E N G T H 3 _0 -45 c m C o l . _0-60 cm C o l . _0-90 c m C o l . A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha Number of observat ions in data set = 2 6 (DF for Error = 14) Notes: Al l samp les were ana lyzed in the B I O E Lab. The factorial model with parameters L E N G T H (column length) and A P P L (application rate) w a s run on the data. The Duncan multiple range test at the 0.05 level of probability w a s used to determine signif icantly different means . Th is test controls the type I compar isonwise error rate, not the exper imentwise error rate. ' N ' refers to the number of s a m p l e s for average calculat ions. M e a n s p receded by different letters are signif icantly different. Start Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 16551 8 _300 dt/ha B 5612 6 _100 dt/ha C 1781 6 _ 30 dt/ha D 138 6 0 dt/ha End Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 11647 8 _300 dt/ha B 4577 6 _100 dt/ha C 1263 6 _ 30 dt /ha C 129 6 0 dt/ha Soil N lost (mg N/column): Duncan Group ing M e a n A 4904 B 1036 B 518 B 9 A P P L _300 dt/ha _100 dt/ha _ 30 dt/ha 0 dt/ha SNEN12CT.XLS 133 LEACHING EXPERIMENT - RUN1 - NITROGEN, pH, EC - OVERVIEW Class Level Information Class Levels Values Data for 0-45 cm Layers: A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha L E N G T H 3 _0-45 cm Col . _0-60 cm Col . _0-90 cm Co l . Number of observations in data set = 26 (DF for Error =14) Data for 45-60 cm Layer: A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha L E N G T H 2 _0-60 cm Col . _0-90 cm Col . Number of observations in data set = 18 (DF for Error =10) Data for 60-90 cm Layers: A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha L E N G T H 1 _0-90 cm Col . Number of observations in data set = 10 (DF for Error = 6) LEACHING RUN 1 DEPTH: 1:2 pH 1:2 EC TKN NH3 N03-N (dS/m) (mg/kg) (mg/kg) (mg/kg) 0 -15 cm Mean 7.3 APPL sig. APPL sig. 41.2 APPL sig. Std. Dev. 0.2 125.6 15-30 cm Mean 7.5 APPL sig. APPL sig. LENGTH 14.6 Std. Dev. 0.2 sig. 14.2 30 - 45 cm Mean 7.6 APPL sig. 41.7 14.6 APPL and Std. Dev. 0.2 32.9 31.5 LENGTH sig. 45 - 60 cm Mean 7.5 0.3 19.5 3.0 0.2 Std. Dev. 0.3 0.1 5.0 2.3 60 - 75 cm Mean 7.6 0.3 24.1 3.6 0.2 Std. Dev. 0.1 0.1 8.9 1.7 75 - 90 cm Mean 7.6 0.4 21.9 APPL sig. 0.2 Std. Dev. 0.1 0.1 5.2 Notes: All samples were analyzed in the BIOE Lab. The factorial model y = L E N G T H | A P P L and the Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. D e v . ' refers to the sample standard deviation. NUTS12C.XLS L E A C H I N G E X P E R I M E N T - RUN1 - N ITROGEN, pH, E C - SIG. P A R A M E T E R S Class Levels Values Data Analysis for 0-15,15-30, and 30-45 cm Layers: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 3 _0-45 cm Col. _0-60 cm Col. _0-90 cm Col. Number of observations in data set = 26 (DF for Error = 14) Data Analysis for 45-60 cm Layer: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 2 _0-60 cm Col. _0-90 cm Col. Number of observations in data set = 18 (DF for Error = 10) Data Analysis for 60-75 and 75-90 cm Layers: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 1 _0-90 cm Col. Number of observations in data set = 10 (DF for Error = 6) Notes: All samples were analyzed in the BIOE Lab. The factorial model y=LENGTH|APPL and the Duncan multiple range test at the 0.05 level of probability were used to determine significantly different means. Means followed or preceded by different letters are significantly different. 'N' refers to the number of samples for average calculations. TKN (mg/kg) Depth/Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 22 c 490 c 1917 b 5502 a 15 - 30 cm 21 b 45 b 250 b 2243 a 30 - 45 cm avg. value: 42 45 - 60 cm avg. value: 20 60-75 cm avg. value: 24 75 - 90 cm avg. value: 22 N03-N (mg/kg) Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 0.2 b 38 b 139 a 211 a 15 - 30 cm avg. value: 15 30 - 45 cm * 0.2 b 0.4 b 2.3 a 0.8 b 45 - 60 cm avg. value: 0.2 60 - 75 cm avg. value: 0.2 75 - 90 cm avg. value: 0.2 * The concentration of N03-N is also dependent on the length of the columns. 30-45 cm N03-N (mg/kg): Duncan Group. Mean N LENGTH a 1.9 8 _0-45 cm Col. b 0.5 8 _0-60 cm Col. b 0.4 10 _0-90 cm Col. 15-30 cm NH4-N (mg/kg): Duncan Group. Mean N LENGTH a • 78 10 _0-90 cm Col. b 14 8 _0-60 cm Col. b 13 8 _0-45 cm Col. 75-90 cm NH4-N (mg/kg): Duncan Group. Mean N APPL a 6.4 2 0 dt/ha b 3.3 2 _100 dt/ha b 3.3 2 _ 30 dt/ha b 1.8 4 300 dt/ha NUTS12D.XLS - Page 1 L E A C H I N G E X P E R I M E N T - RUN1 - N ITROGEN, pH, E C - SIG. P A R A M E T E R S 1:2 EC(dS/m) Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 0.1 c 0.4 c 1 b 2 a 15 - 30 cm 0.2 c 0.2 c 0.3 b 0.8 a 30 - 45 cm 0.2 c 0.2 c 0.3 b 0.4 a 45 - 60 cm avg. value: 0.3 60 - 75 cm avg. value: 0.3 75 - 90 cm avg. value: 0.4 NUTS12D.XLS - Page 2 136 ICO ICO CO) CO o l d d d NTCOT C O " o d d CO CO d d Icq Icq l o T o T o " c 0 1 1 i S i e L 0) O) z s w in in in to to co CD CM IT- I CM |co|co o to s ^ <J> CO CM O) CM co co m CM CO I CO CO CO I CM I CO I CM in o CM T m I in I in I in I in I CO I CO I CO I CO I CM I CM N O ) O ) CO CO CM CO CO k u) ho I m m 2 CO CO CO CO CM U ) CO CN CO CM CO CO CN Tf" un m CM in s \a> h- to I CO CM CN m m I in co co co co^co" o l d in CM a^- co ^ - CM CN t m ^-CO CO co d |m to m co co co O I CO I CO CM CN I CM CoTtol d d l en en N ^ co CN in co to in co co o> CN in cn co CM CD co w in ** co Io |h-co CN h- to I S - oo CM Ico CO co | co T- CN O TT O T-in in TT co \t>~ n CM o | co co to m ( o " ~ ~ to co to to in in Ifl r CO to in o CN co co r- •<* |-«r cojio OO CO CO CO in m ICO 1 CD Ico I T _ c l ! m to a> CN CN CN h- co CO CN T CM c =1 ct u JZ o •a c Ul o £ ro c 0) £ as z _y_ t - t - io d ft CD CO CO TT CN ft o to CN CO S - - t o to CN r*- o co o to co to |co IN- ITJ-CD T-CM CO j^- in CN o o o o d d To" Io H<=> U) N ^ CO m co co in o" o" o" o" o o o o d o d o CD CD CN CM d d h- CO CN to in m to | o" o" o o o" d to o o o co in •<*• o7 o7 CN CN d d o o co m CO CO CM CM CM m in m m CM CM in in in in o o o CD CD m m to co in in l o l o l o CD CD m io CO CO in m o CD T- d IO CM O O CD O -r- T- T- d CO CO TT d d O _i LU l " a. < a o m I CM I CD H i d lO l O ICD CN CM CO ICO I CD Id d o o « CD CO I CD CO CO CO I T— I CO I CD ^ IN-1CO CO CD h-co o d T- CO JO l O I CM CD m co co' to' d CN o o cn to T- T- r>i N oi o a CO IcO tO CM | co to I m dl O N CM CM to I in S C O CM T- N CM CO CO CO tO lO co I co CM in co r» h- h- hr co \u> to CM CM N Uo in CN CN I co Kr h r I n co n co ra co c c c c c c to to CO CO c c c c CO CO to (0 CO CO "c "c "c c c c CO CO CO CO to (0 e c "c c c c = p" CO CO I co I co I CO c c c c c CO 3 en m «* r - CM CM o d d o to CO d d O CM CO CO CO CM ^ d d o o o CO CN CM CD CO CO d d in in cv CD CO CN CO d d d d •5. £ a. tg < 01 o o CO CO o o o o o o o o o o o o o o o o o o o o o o o o CO CO CO CO CO to o o o o o o o o o o o o CO CO CO CO to CO o a O - J o o o 6 6 6 o CD 6 o o CD CD 6 6 o o o o CD CD CD CD 6 6 6 6 o CD 6 o o o o o o O CD CD CD CD CD 6 6 6 6 6 6 o o o o o o CD CD CD CD CD CD 6 6 6 6 6 6 o o o o o o CD CD CD CD CD CD 6 6 6 6 6 6 I ? • a. a o co in 6 to in o in r CO ^ 6 in o T- CO o in CO N. in 6 co o CO in io 6 co o CO If) o b o u u u CM CM CM CM CM CN O O O O O O I CO i CO I CO I CO I CO I CO u u u u u u -^ hr\ir\vt\vt O O O O O inLoinmmiol O O O O O o l J > I 2 I 2 s V 5 <0.3| 2 5 49.9| CO Csi 2 5 2 2 V 2 V 2 V <0.3| fe a <0.3| 2 V 3 i 2 <0.3| a 2 2 V I z I 2 « ' CO V s V in in CO V « 9 S3 CD CO to w V LO CO V m V LO CO V in V 2 V m CO V a in in CO V o CO O) to to CM m CO V i 2 2 a uo a r-CM LO in | 1620]  8 | 7726| | 1480] CD Si a 5 LO s a a | 1403| 5 8 s | 64071 8 CM 5! 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(DFfor Error = 14) _100 dt/ha _300 dt/ha _0-90 cm Col. (DFfor Error = 10) .100 dt/ha 300 dt/ha (DF for Error = 6) Notes: All samples were analyzed in the BIOE Lab. The factorial model y=LENGTH|APPL and the Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'R-Square' refers to the RA2 of the factorial model in the SAS procedure GLM. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. In the analysis, if the concentration measured was below the detection limit, half the concentration of the detection limit was used for that element. 0-15 cm Layer: R-Square: C.V.: Std. Dev.: Mean: 1:2 pH 0.468 3 0.2 7.3 1:2 EC (dS/m) APPL sig. TKN (mg/kg) APPL sig. NH4-N (mg/kg) 0.331 305 125.6 41.2 N03-N (mg/kg) APPL sig. N03-N + NH4-N APPL sig, (mg/kg) 0-15 cm 1:2EC(dS/m): Duncan Grouping Mean N APPL A 2.1 8 300 dt/ha B 1.0 6 100 dt/ha C 0.4 6 30 dt/ha C 0.1 6 0 dt/ha 0-15 cm TKN (mg/kg): Duncan Grouping Mean N APPL A 5502 8 300 dt/ha B 1917 6 100 dt/ha C 490 6 30 dt/ha C 22 6 0 dt/ha 0-15 cm N03-N (mg/kg): Duncan Grouping Mean N APPL A 211 8 300 dt/ha A 139 6 100 dt/ha B '38 6 30 dt/ha B 0.2 6 0 dt/ha 0-15 cm N03-N + NH4-N (mg/kg): Duncan Grouping Mean N APPL A 328 8 300 dt/ha B 149 6 100 dt/ha C B 48 6 30 dt/ha C 4 6 0 dt/ha APPL 4 _ 0 dt/ha _ 30 dt/ha LENGTH 3 _0-45 cm Col. Number of observations in data set = 26 Data for 45-60 cm Layer: APPL 4 _ 0 dt/ha _ 30 dt/ha LENGTH 2 _0-60 cm Col. Number of observations in data set = 18 Data for 60-90 cm Layers: APPL 4 _ 0 dt/ha _ 30 dt/ha LENGTH 1 _0-90 cm Col. Number of observations in data set = 10 NUTS12B.XLS - Page 1 LEACHING EXPERIM. - RUN 1 - NITROGEN, pH, EC - LONG FORM OF DATA ANALYSIS 15-30 cm Layer: 1:2 pH 1:2 EC TKN NH4-N N03-N (dS/m) (mg/kg) (mg/kg) (mg/kg) N03-N + NH4-N (mg/kg) R-Square: 0.429 APPL Sig. APPL sig. LENGTH sig. 0.572 APPL sig. C.V.: Std. Dev.: Mean: 3 0.2 7.5 97 14.2 14.6 15-30 cm 1:2EC(dS/m): Duncan Grouping A B C C Mean 0.8 0.3 0.2 0.2 APPL 300 dt/ha 100 dt/ha 30 dt/ha 0 dt/ha 15-30 cm TKN (mg/kg): Duncan Grouping A B B B Mean 2243 250 45 21 APPL _300 dt/ha _100 dt/ha 30 dt/ha 0 dt/ha 15-30 cm NH4-N (mg/kg): Duncan Grouping A B B 15-30 cm N03-N + NH4-N (mg/kg): Duncan Grouping Mean 78 14 13 Mean 107 61 22 4 10 8 8 LENGTH _0-90 cm Col. ~0-60 cm Col. ~0-45 cm Col. APPL _300 dt/ha 100 dt/ha _ 30 dt/ha ' 0 dt/ha 30-45 cm Layer: 1:2 pH 1:2 EC TKN NH4-N N03-N (dS/m) (mg/kg) (mg/kg) (mg/kg) N03-N -i- NH4-N (mg/kg) R-Square: 0.578 APPL sig. 0.626 0.420 C.V.: 79 216 APPL and LENGTH sig. 0.417 204 Std. Dev.: 0.2 32.9 31.5 31.6 Mean: 7.6 41.7 14.6 15.5 30-45 cm 1:2EC(dS/m): Duncan Grouping A B C C 30-45 cm N03-N (mg/kg): Duncan Grouping A B B B Duncan Grouping A B B Mean 0.4 0.3 0.2 0.2 Mean 2.3 0.8 0.4 0.2 Mean 1.9 0.5 0.4 8 8 10 APPL 300 dt/ha _100 dt/ha _ 30 dt/ha 0 dt/ha APPL _100 dt/ha _300 dt/ha _ 30 dt/ha 0 dt/ha LENGTH _0-45 cm Col. ~0-60 cm Col. ~0-90 cm Col. NUTS12B.XLS - Page 2 LEACHING EXPERIM. - RUN 1 - NITROGEN, pH, EC - LONG FORM OF DATA ANALYSIS 45-60 cm Layer: R-Square: 1:2 pH 0.149 1:2 EC (dS/m) 0.602 TKN (mg/kg) 0.162 NH4-N (mg/kg) 0.333 N03-N (mg/kg) 0.000 N03-N + NH4-N 0.333 (mg/kg) C.V.: Std. Dev.: Mean: 3 0.3 7.5 36 0.1 0.3 26 5.0 19.5 78 2.3 3.0 0.2 74 2.3 3.1 60-75 cm Layer: R-Square: 1:2 pH 0.676 1:2 EC (dS/m) 0.194 TKN (mg/kg) 0.082 NH4-N (mg/kg) 0.650 N03-N (mg/kg) 0.000 N03-N + NH4-N 0.650 (mg/kg) C.V.: Std. Dev.: Mean: 0.9 0.1 7.6 17.4 0.1 0.3 36.9 8.9 24.1 45.9 17 3.6 0.2 44.0 1.7 3.8 75-90 cm Layer: R-Square: 1:2 pH 0.380 1:2 EC (dS/m) 0.015 TKN (mg/kg) 0.131 NH4-N (mg/kg) APPL sig. N03-N (mg/kg) 0.000 N03-N + NH4-N APPL sig. (mg/kg) C.V.: Std. Dev.: Mean: 1.5 0.1 7.6 12.6 0.1 0.4 23.8 5.2 21.9 0.2 75-90 cm NH4-N (mg/kg): Duncan Grouping Mean N APPL A 6.4 2 0 dt/ha B 3.3 2 _100 dt/ha B 3.3 2 30 dt/ha B 1.8 4 300 dt/ha 75-90 cm N03-N + NH4-N (mg/kg): Duncan Grouping Mean N APPL A 6.5 2 0 dt/ha B 3.5 2 100 dt/ha B 3.4 2 30 dt/ha B 1.9 4 300 dt/ha NUTS12B.XLS - Page 3 A P P E N D I X E Leaching Run 2 - Soil Nitrogen, pH, and EC LEACHING EXP. - RUN 2 (COLUMNS) - NITROGEN BALANCE IN THE 0-45 cm LAYER C l a s s Level Information C l a s s Leve ls V a l u e s L E N G T H 3 _0 -45 c m C o l . _0-60 c m C o l . _ 0 - 9 0 c m C o l . A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha Number of observat ions in data set = 26 (DF for Error = 14) Notes: Al l samp les were ana lyzed in the B I O E Lab. The factorial model with parameters L E N G T H (column length) and A P P L (application rate) w a s run on the data. The Duncan multiple range test at the 0.05 level of probability w a s used to determine signif icantly different means . Th is test controls the type I compar isonwise error rate, not the exper imentwise error rate. ' N ' refers to the number of samp les for average calculat ions. M e a n s p receded by different letters are signif icantly different. Start Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 19507 8 _300 dt/ha B 6643 6 _100 dt/ha C 2135 6 30 dt/ha D 233 6 0 dt/ha End Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 13634 8 _300 dt/ha B 6107 6 _100 dt/ha C 2001 6 _ 30 dt/ha D 175 6 0 dt/ha Soil N lost (mg N/column): Duncan Group ing M e a n N A P P L A 5874 8 _300 dt/ha B 536 6 _100 dt/ha B 134 6 30 dt/ha B 57 6 0 dt/ha SNEN34CT.XLS LEACHING EXP. - RUN 2 (POTS) - NITROGEN BALANCE IN THE 0-15 cm LAYER C l a s s Level Information C l a s s Leve ls V a l u e s A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha Number of observat ions in data set = 1 0 (DF for Error = 6) Notes: Al l samp les were ana lyzed in the B I O E Lab. The main effect model with parameter A P P L (application rate) w a s appl ied to the data. The Duncan multiple range test at the 0.05 level of probability w a s used to determine signif icantly different means . Th is test controls the type I compar isonwise error rate, not the exper imentwise error rate. ' N ' refers to the number of samp les for average calculat ions. M e a n s p receded by different letters are signif icantly different. Start Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 19349 3 _300 dt/ha B 6494 3 _100 dt/ha C 1995 3 30 dt/ha D 66 1 0 dt/ha End Soil N (mg N/column): Duncan Group ing M e a n N A P P L A 12711 3 _300 dt/ha B 4337 3 _100 dt/ha C B 1408 3 _ 30 dt/ha C 66 1 0 dt/ha Soil N lost (mg N/column): Duncan Group ing M e a n N A P P L A 6638 3 _300 dt/ha B 2157 3 _100 dt/ha B 587 3 _ 30 dt/ha B 0 1 0 dt/ha SNEN5CT.XLS 146 LEACHING EXPERIMENT - RUN 2 - NITROGEN, pH, E C , LOI - OVERVIEW Class Levels Values Data for Columns (0-15,15-30, 30-45 cm Layers): A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _ 3 0 0 dt/ha L E N G T H 3 _0 -45 c m C o l . _0-60 c m C o l . _0 -90 cm C o l . Number of observat ions for LOI in the 0-15 c m Layer =21 (DF for Error = 9) Number of observat ions for LOI in the 15-30 c m Layer = 19 (DF for Error = 7) Number of observat ions for all other parameters = 26 (DF for Error = 14) Data for Columns (45-60 cm Layer): A P P L 4 _ 0 dt/ha _ 3 0 d V h a _ 1 0 0 dt/ha _ 3 0 0 dt/ha L E N G T H 2 _0-60 c m C o l . _0-90 cm C o l . Number of observat ions in data set = 1 8 (DF for Error = 10) Data for Columns (60-75 and 75-90 cm Layers): A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _ 3 0 0 dt/ha L E N G T H 1 _ 0 - 9 0 c m C o l . Number of observat ions in data set = 1 0 ( D F for Error = 6) Data for Pot Trials (0-15 cm Layer): A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _ 3 0 0 dt/ha Number of observat ions in data set = 1 0 (DF for Error = 6) LEACHING RUN 2 Loss on DEPTH: 1:2 pH 1:2 EC Ignition TKN NH4-N N03-N (dS/m) (%) (mg/kg) (mg/kg) (mg/kg) 0 -15 cm Mean 7.3 2.0 A P P L sig. A P P L sig. 90.4 A P P L sig. Std. Dev. 0.2 1.3 87.2 15 - 30 cm Mean 7.5 1.3 A P P L sig. A P P L sig. A P P L sig. 102.1 Std. Dev. 0.2 1.0 143.6 30 - 45 cm Mean A P P L sig. 0.6 n/a A P P L sig. A P P L sig. 25.7 Std. Dev. 0.3 40.2 45 - 60 cm Mean 7.5 0.5 n/a 28.6 8.2 0.7 Std. Dev. 0.1 0.3 21.1 18.2 1.0 60 - 75 cm Mean 7.4 0.6 n/a 20.0 2.6 0.4 Std. Dev. 0.1 0.3 11.2 2.4 0.5 75 - 90 cm Mean 7.4 0.7 n/a 13.6 1.7 0.1 Std. Dev. 0.1 0.5 8.3 1.2 0.0 Pot Trial Mean n/a n/a A P P L siq. A P P L siq. A P P L siq. A P P L siq. Notes: Al l samp les were ana lyzed in the B I O E Lab. The factorial model y = L E N G T H | A P P L w a s used for the co lumns and the main effect model y = A P P L w a s used in the data ana lys is for the pot trials. The Duncan multiple range test at the 0.05 level of probability w a s used to determine signif icantly different means . 'S td . D e v . ' refers to the samp le standard deviat ion. NUTS345C.XLS 147 LEACHING EXP. - RUN 2 - NITROGEN, pH, EC, LOI - SIG. PARAMETERS Class Levels Values Data for Columns (0-15,15-30, 30-45 cm Layers): APPL 4 _ 0 dt/ha _ 30 dt/ha LENGTH 3 _0-45 cm Col. Number of observations for LOI in the 0-15 cm Layer Number of observations for LOI in the 15-30 cm Layer Number of observations for all other parameters Data for Columns (45-60 cm Layer): APPL 4 _ 0 dt/ha LENGTH 2 _0-60 cm Col. Number of observations in data set Data for Columns (60-75 and 75-90 cm Layers): APPL 4 _ 0 dt/ha LENGTH 1 _0-90cmCol. Number of observations in data set Data for Pot Trials (0-15 cm Layer): APPL . 4 _ 0 dt/ha Number of observations in data set 30 dt/ha 30 dt/ha 30 dt/ha _100 dt/ha 0-60 cm Col. _100 dt/ha 0-90 cm Col. 100 dt/ha 100 dt/ha _300 dt/ha _0-90 cm Col. = 21 (DF for Error = 9) = 19 (DF for Error = 7) = 26 (DF for Error = 14) _300 dt/ha = 18 (DF for Error = 10) _300 dt/ha = 10 (DF for Error = 6) _300 dt/ha = 10 (DF for Error = 6) Notes: All samples were analyzed in the BIOE Lab. The factorial model y=LENGTH|APPL was used for the columns and the main effect model y=APPL was used for the pot trials. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'N' refers to the number of samples for average calculations. Means followed or preceded by different letters are significantly different. Loss on Ignition Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 1.2 d 2.5 c 5 b 11 a 15-30 cm 1 b 1.1 b 1.8 b 8.7 a Pot Trial 0.7 d 2.4 c 5.8 b 11.2 a TKN (mg/kg) Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 52 d 725 c 2252 b 4791 a 15 - 30 cm 40 b 151 b 583 b 4401 a 30 - 45 cm 26 b 30 b 69 b 386 a 45 - 60 cm avg. value: 29 60 - 75 cm avg. value: 20 75 - 90 cm avg. value: 13.6 Pot Trial 27 c 516 c 1925 b 5008 a NH4-N (mg/kg) Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 - 15 cm avg. value: 90.4 15 - 30 cm 1 c 46 c 255 b 723 a 30 - 45 cm 1 c 6 be 39 b 251 a 45 - 60 cm avg. value: 8.2 60 - 75 cm avg. value: 2.6 75 - 90 cm avg. value: 1.7 Pot Trial 1 b 3.2 b 5 b 19.1 a N03-N (mg/kg) Depth / Appl.: 0 dt/ha 30 dt/ha 100 dt/ha 300 dt/ha 0 -15 cm 0.1 c 235 be 702 ab 928 a 15-30 cm avg. value: 102 3 0 -45 cm avg. value: 25.7 45 - 60 cm avg. value: 0.7 60 - 75 cm avg. value: 0.4-75 - 90 cm avg. value: 0.1 Pot Trial 9 c 247 b 295 b 615 a 30-45 cm 1:2 pH: Duncan Grouping Mean N APPL a 7.8 8 _300 dt/ha b 7.5 6 _100 dt/ha c b 7.4 6 _ 30 dt/ha c 7.3 6 0 dt/ha NUTS345D.XLS 1 •s 1 1 z I s J ? ? v-? | <0.14| ? ? | <0.14| a 8 CM-? | <0.14| 461.6| <0.14| <1.53| <0.14| <0.14| <0.14| 1 i 2 <0.14| <0.14| <0.14| | 361.6| <0.14| q <0.14| <0.14| <0.14| I z CM V CM V CM V CM V CM V CM V u CM V CM V CM V CM V a 8 a CM V CM V CM V 8 ! CM V CM V CM V § a CM V CM V CM V 1 z s 8 V s r- EM H t 2 s 5 1 s 8 I 1 a in V s 1 8 ? CO a> Z 1 "5 1 z t i s a V 81 o s 5 1 z CO a s 1 fe 1 1 8 8 o i 1 i s z 1 I * 1 z I 5 s 3 s co- ? s s !S 1 s s fe 1 I 8 8 8 8 | 7047| I S 8 v - s 1 i 0 1 1 I I i 1 z I I to v CM v CM v CO v •cr v rn V 5 IS CO CO V IO V a a CO v •* v m v 1 IS v v v 5 1 •» v •* v •» v N03-N | 1 z I 1 2 V o" V 5 V 2 V s 2 V ! i s CO 2 V 2 V s o V V 2 V 2 V 2 V ! d in 2 V 2 V 2 V a 2 V CM 2 V 2 V 2 V I 1 IS z I 1 CM V CM V CN V CO V V V ? > s CM V CO V V V a a CO V V V 8 fe V V T V 8 5 s V V V 1 1 s z i I s a V o s s s V a s | 2573| 1 fe | 4423| 1 8 CO V | 3796| | 3336| 8 1 j I 1 z I looo 1 | 0.00| 1 [ o.oo| 8 d | 0.00| 1 000 1 ! 1 | 0.00| d 1 | 0.00| 0.00| | 0.00| looo I 3 d § d 1 | 0.00| I 0.22| d | 0.00| | 0.00| 1 o.ool I 1 z I I o o o o o o ! ° o o o o 8 o o o o O m s o o o o 1 s o o o I I z o o o o o o r o o o o | 3927| a o o o o \ 7008| 1 o o o o | 7008| 1 o o o o Background Nitrogen In Tailings N03-N | I 2 2 2 d 5 2 c< 32 2 -* s CO d 2 2 2 d S 2 d d 2 S 5 2 d d 2 5 S 2 Background Nitrogen In Tailings I f s 0 S3 s CM s CM •T d s JM S o d 5 3 o Background Nitrogen In Tailings 1 I I s 5 s s s fe 3 ; s s s 8 & s s s s 8 fe 8 s 8 8 s 8 8 8 s 8 o S j i I I 1 1 1 1 i \* s 1 1 s 1 1 1 5 CO i 1 1 1 2 i 1 1 I d c 2 2 2 I s c 3 d s 2 2 2 s o a o 2 a o 8 O 8 CM o 2 o 2 d S CM I C 2 2 °° «. 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LEACHING EXP. - RUN 2 (COLUMNS) - NITROGEN, pH, EC, LOI - LONG FORM OF DATA ANALYSIS Class Levels Values Data for 0-45 cm Layers: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 3 _0-45 cm Col. _0-60 cm Col. _0-90 cm Col. Number of observations for LOI in the 0-15 cm Layer =21 (DF for Error = 9) Number of observations for LOI in the 15-30 cm Layer =19 (DF for Error = 7) Number of observations for all other parameters = 26 (DF for Error = 14) Data for 45-60 cm Layer: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 2 _0-60 cm Col. _0-90 cm Col. Number of observations in data set =18 (DF for Error = 10) Data for 60-90 cm Layers: APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 1 _0-90 cm Col. Number of observations in data set =10 (DF for Error = 6) Notes: All samples were analyzed in the BIOE Lab. The factorial model y=LENGTH|APPL and the Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'R-Square' refers to the RA2 of the factorial model in the SAS procedure GLM. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. In the analysis, if the concentration measured was below the detection limit, half the concentration of the detection limit was used for that element. R-Square: C.V.: Std. Dev.: Mean: 5 cm Layer: 1:2 pH 0.481 2.8 0.2 7.3 1:2 EC (dS/m) 0.293 66 1.3 2.0 LOI (%) APPL sig. TKN (mg/kg) APPL sig. NH4-N (mg/kg) 0.633 96 87.2 90.4 N03-N (mg/kg) APPL sig. 0-15 cm Loss on Ignition (%): Duncan Grouping Mean N APPL A 11.1 8 300 dt/ha B 5.0 6 _100 dt/ha C 2.5 4 30 dt/ha D 1.2 3 0 dt/ha 0-15 cm TKN (mg/kg): Duncan Grouping Mean N APPL A 4791 8 _300 dt/ha B 2252 6 100 dt/ha C 725 6 _ 30 dt/ha D 52 6 0 dt/ha 0-15 cm N03-N (mg/kg): Duncan Grouping Mean N APPL A 928 8 300 dt/ha B A 702 6 100 dt/ha B C 235 6 30 dt/ha C 0.1 6 0 dt/ha NUTS345B.XLS - Page 1 LEACHING EXP. - RUN 2 (COLUMNS) - NITROGEN, pH, EC, LOI - LONG FORM OF DATA ANALYSIS R-Square: C.V.: Std. Dev.: Mean: •30 cm Layer: 1:2 pH 0.341 3.1 0.2 7.5 1:2 EC (dS/m) 0.462 75 1.0 1.3 LOI (%) APPL sig. TKN (mg/kg) APPL sig. NH4-N (mg/kg) APPL sig. N03-N (mg/kg) 0.645 141 144 102 15-30 cm Loss on Ignition (%): Duncan Grouping Mean N APPL A 8.7 8 300 dt/ha B 1.8 6 100 dt/ha B 1.1 3 30 dt/ha B 1.0 2 0 dt/ha 15-30 cm TKN (mg/kg): Duncan Grouping Mean N APPL A 4401 8 300 dt/ha B 583 6 100 dt/ha B 151 6 30 dt/ha B 40 6 0 dt/ha 15-30 cm NH4-N (mg/kg): Duncan Grouping Mean N APPL A 723 8 300 dt/ha B 255 6 100 dt/ha C 46 6 30 dt/ha C 1 6 0 dt/ha R-Square: C.V.: Std. Dev.: Mean: -45 cm Layer: 1:2 pH APPL sig. 1:2 EC (dS/m) 0.192 60 0.3 0.6 LOI (%) not analyzed TKN (mg/kg) APPL sig. NH4-N (mg/kg) APPL sig. N03-N (mg/kg) 0.604 156 40.2 25.7 30-45 cm 1:2 pH: Duncan Grouping Mean N APPL A 7.8 8. 300 dt/ha B 7.5 6 100 dt/ha C B 7.4 6 30 dt/ha C 7.3 6 0 dt/ha 30-45 cm TKN (mg/kg): Duncan Grouping Mean N APPL A 386 8 300 dt/ha B 69 6 100 dt/ha B 30 6 30 dt/ha B 26 6 0 dt/ha 30-45 cm NH4-N (mg/kg): Duncan Grouping Mean N APPL A 251 8 300 dt/ha B 39 6 100 dt/ha C B 6 6 _ 30 dt/ha C 1 6 0 dt/ha NUTS345B.XLS - Page 2 LEACHING EXP. - RUN 2 (COLUMNS) - NITROGEN, pH, EC, LOI - LONG FORM OF DATA R-Square: 45-60 cm Layer: 1:2 pH 0.574 1:2 EC (dS/m) 0.047 LOI (%) not analyzed TKN (mg/kg) 0.544 NH4-N (mg/kg) 0.432 N03-N (mg/kg) 0.623 C.V.: Std. Dev.: Mean: 1.3 0.1 7.5 61 0.3 0.5 74 21.1 28.6 220 18.2 8.2 133 1.0 0.7 R-Square: 60-75 cm Layer: 1:2 pH 0.457 1:2 EC (dS/m) 0.039 LOI (%) not analyzed TKN (mg/kg) 0.249 NH4-N (mg/kg) 0.179 N03-N (mg/kg) 0.312 C.V.: Std. Dev.: Mean: 1.1 0.1 7.4 56 0.3 0.6 56 11.2 20.0 91 2.4 2.6 143 0.5 0.4 R-Square: 75-90 cm Layer: 1:2 pH 0.300 1:2 EC (dS/m) 0.069 LOI (%) not analyzed TKN (mg/kg) 0.229 NH4-N (mg/kg) 0.304 N03-N (mg/kg) 0.000 C.V.: Std. Dev.: Mean: 1.5 0.1 7.4 63.3 0.5 0.7 61.3 8.3 13.6 72.4 1.2 1.7 0.0 0.0 0.1 NUTS345B.XLS - Page 3 LEACHING EXP. - RUN 2 (POTS) - NITROGEN, pH, EC, LOI - LONG FORM OF DATA ANALYSIS Class Levels APPL 4 Number of observations in data set Values 0 dt/ha .30 dt/ha _100 dt/ha = 10 _300 dt/ha (DF for Error = 6) Pot Trial: 1:2 pH 1:2 EC LOI TKN NH4-N N03-N (dS/m) (%) (mg/kg) (mg/kg) (mg/kg) not analyzed not analyzed APPL sig. APPL sig. APPL sig. APPL sig. Loss on Ignition (%): Duncan Grouping A B C D TKN (mg/kg): Duncan Grouping A B C C NH4-N (mg/kg): Duncan Grouping A B B B N03-N (mg/kg): Duncan Grouping A B B C Mean 11.2 5.8 2.4 0.7 Mean 5008 1925 516 27 Mean 19.1 5.0 3.2 1.0 Mean 615 295 247 9 APPL _300 dt/ha _100 dt/ha _ 30 dt/ha 0 dt/ha APPL _300 dt/ha _100 dt/ha _ 30 dt/ha 0 dt/ha APPL _300 dt/ha _100 dt/ha _ 30 dt/ha 0 dt/ha APPL _300 dt/ha _I00 dt/ha _ 30 dt/ha 0 dt/ha NUTS345B.XLS - Page 4 157 A P P E N D I X F Leaching Run 1 - Total Metals in Soil 158 5 UJ > or LU > O _ i LU s < I-o D or LU s cc LU 0. X LU o z X u < Ul C D II g LU i o o ro " C O o 3 3 TJ o o ro > CU > cu 'ci O § ° T O io o T I I o3 cu > CD O ro O - I 0 9- z D_ LU < =J N a U) c IS or ra E ro ra cu c E .2 92 — "G £ g 2 i— CD § £ •§ i f . ! i i i i r ' F » 5. o co .g> c S; m o u cu " r C I) E E S S 5 i £ ra > •8 1 15 "? cu "S '> CO CO T3 a. D_ < •3 c ra " to Q cu a ra " co *— W . W — 9> •« -S a. S to S? cu cu f | 2 -J3 ra T3 c ra "co a> _ Q. CU *i 0) <U to S CU i f s f c c 3 ro Q cu = ro ro £ fi cu o to • =5 <" > £ "5. » ^  c r_ co B It " w 2 < o cu •g to 3 o C O ro ,o ro cu E C O £ 2 cu 5 i o CO o o o m - i CO x d 159 5 S E 1 5 o u , CD S a "8 O CO — CU <S Q. O Q-I— O O E _ 3 S E 5 P E cn o _ o °3 8% in _ o) E ffi c o •-= £ W ra a Q o o IO P o CD a. < T3 CO 43 co z a : CO CO CO £ o cu E m 8 a) " b g.| o ~ 9 * TJ 0) CO "D N co c * D. = co < or 160 I— N _ TJ 5 3 a "8 o to H -I — cu <S CL O g-I- ° o E _ 3 •§ E E S i o = o _ o i s °3 Q. ro II o » o -J cn _ ? H = £ w re r -Q. CU O O O o p o Pi cu Q. Q. < T J <U cu 5 € s CO to CU £ u> -E « 8 a> I E cn ro ni => E I I ro = o 2 J3 ro a § 5.1 = 1 T J CU CU T> N ,_ s z cu tz 3 cu tO Q. S = cu < a: a. LEACHING EXP. - RUN 1 - TOTAL METALS - LONG FORM OF DATA ANALYSIS C l a s s Level Information C l a s s Leve ls V a l u e s A P P L 3 _ 0 dt/ha _100 dt/ha _300 dt/ha L E N G T H 2 _0 -45 c m C o l . _0-90 c m C o l . Number of observat ions in data set = 12 (DF for Error = 6) Notes: The factorial model with parameters A P P L (application rate) and L E N G T H (col. length) w a s run on the data. 'R -Squa re ' refers to the R A 2 of the model y = A P P L | L E N G T H in the statistical S A S procedure G L M . The Duncan multiple range test at the 0.05 level of probability was used to determine signif icantly different means . 'Std. D e v . ' refers to the samp le standard deviat ion. ' C . V . ' refers to the coeff icient of variation in percent. ' N ' refers to the number of s a m p l e s for average calculat ions. M e a n s p receded by different letters are signif icantly different. In the ana lys is , if the concentrat ion measured w a s below the detect ion limit, half the concentrat ion of the detect ion limit w a s used for that element. R-Square: C.V.: Std. Dev.: Mean: 0-1S cm Layer: Arsenic (mg/kg) all va lues <8 .0 Cadmium (mg/kg) 0.639 37.1 0.3 0.7 Chromium (mg/kg) 0.273 9.1 3.8 41.6 Cobalt (mg/kg) 0.534 7.7 1.2 16 Copper (mg/kg) 0.766 6.6 71 1080 Lead (mg/kg) 0.96 21.1 3.1 14.6 Mercury (mg/kg) A P P L s ig . Molybd. (mg/kg) 0.607 •. 25.8 0.2 0.7 Nickel (mg/kg) 0.35 11.5 2.2 18.9 Selenium (mg/kg) 0.774 44.6 0.3 0.6 Zinc (mg/kg) A P P L . s ig . 0-15 cm Mercury (mg/kg): Duncan Group ing M e a n N A P P L A 1.2 4 _300 dt/ha B 0.5 4 _100 dt/ha C 0.1 4 0 dt/ha 0-15 c m Z inc (mg/kg): Duncan Group ing M e a n N A P P L A 163 4 _300 dt/ha B 107 4 _100 dt/ha C 69 4 0 dt/ha MTRUN1B.XLS Page 1 LEACHING EXP. - RUN 1 - TOTAL METALS - LONG FORM OF DATA ANALYSIS R-Square: C.V.: Std. Dev.: Mean: 15-30 cm Layer: Arsenic (mg/kg) all va lues <8 .0 Cadmium (mg/kg) 0.242 56.6 0,2 0.4 Chromium (mg/kg) 0.606 4.4 2.2 50.6 Cobalt (mg/kg) 0.365 8.6 1.6 18 Copper (mg/kg) 0.451 10.7 169 1578 Lead (mg/kg) 0.599 57.9 4.7 8.1 Mercury (mg/kg) 0.681 82.8 0.1 0.2 Molybd. (mg/kg) 0.390 31.4 0.2 0.7 Nickel (mg/kg) 0.383 9.4 2.1 22.5 Selenium (mg/kg) 0.571 15.7 0.1 0.4 Zinc (mg/kg) 0.748 9.9 9 92 R-Square: C.V.: Std. Dev.: Mean: 30-45 cm Layer: Arsenic (mg/kg) all va lues <8 .0 Cadmium (mg/kg) 0.371 63.7 0.3 0.4 Chromium (mg/kg) 0.355 11.4 6.3 54.8 Cobalt (mg/kg) 0.135 11.4 2.1 18.5 Copper (mg/kg) 0.643 10.3 157 1528 Lead (mg/kg) 0.463 46.1 1.9 4.1 Mercury (mg/kg) all va lues <0.1 Molybd. (mg/kg) 0.448 29.5 0.2 0.6 Nickel (mg/kg) 0.182 11.4 2.8 24.5 Selenium (mg/kg) 0.492 22.1 0.1 0.3 Zinc (mg/kg) 0.435 7.6 7 89 MTRUN1B.XLS - Page 2 A P P E N D I X G Leaching Run 2 - Total Metals in Soil 164 5 LU > or UJ > o _ i < \-U J 5 _ i 0 1 C O z 2 _l o o or z U J s or U J o. X UJ o o < U J co n b I 111 .b o 13 E . o cu > CD CO > CU > CU o co O « 0 | 0 | 13 T J o o o o <2 E § ° T J m o T l ° l V N CO c g £ a> co O i 2 o o 7? ° a. z a. LU a> J3 E N 0) o> c CO or UJ CO o CD o> CO I cu > CO T J CD CO 3 cn co 3 ro ro T J CD ro ~ t o c o 2 . 2 a5 o5 Sfc T J T J CD > < « I O S O ) c ^ CD CO C CD E E o y ,T j X o aj ro CD -1= ° I T J — CD C to g .•=r CD ~ JZ •Q CO > •§ ° b.i! ° 8 1 "S O CO o *o CD ~ c CO .2 w jo CO T J J3 1 Q 45 ^ TO O o5 a) a) £ _ — a . r -~ c= c -m 1) E CD CD a. £ b 0 ro co J " CO CO >. CO c 3 CO Q CD cu £ c <" " 2 CO CD - I CO s g CO CD CD 3 CO . CD ° i T J » CD E o O c CO T J co c o CO CD T J CO CD O "ro ro T J CD co 2 ? 0) CO o a) w o o ca - i x d i= H £ <P < LEACHING EXP. - RUN 2 (COLUMNS) - METALS - SIG. PARAMETERS Class Level Information Class Levels Values APPL 3 _ 0 dt/ha _100 dt/ha _300 dt/ha LENGTH 2 _0-45 cm Col. _0-90 cm Col. Number of observations in data set =12 (DF for Error = 6) L E A D Depth/Applic. 0 dt/ha 100 dt/ha 300 dt/ha 0-15 cm 6.8 c 11.8 b 27.8 a 15-30 cm 5.6 b 6.8 b 21.0 a 30-45 cm Average value 6.8 M E R C U R Y Depth/Applic. 0 dt/ha 100 dt/ha 300 dt/ha 0-15 cm 0.1 c 0.3 b 0.9 a 15-30 cm 0.1 b 0.1 b 0.5 a 30-45 cm Average value < 0.1 S E L E N I U M Depth/Applic. 0 dt/ha 100 dt/ha 300 dt/ha 0-15 cm 0.4 c 0.7 b 1.4 a 15-30 cm 0.5 b 0.6 b 1.2 a 30-45 cm Average value 0.5 ZINC Depth/Applic. 0 dt/ha 100 dt/ha 300 dt/ha 0-15 cm 82 c 120 b 182 a 15-30 cm 106 b 112 b 153 a 30-45 cm Average value 111 C O B A L T Depth/Applic. 0 dt/ha 100 dt/ha 300 dt/ha 0-15 cm Average value: 18.9 15-30 cm 24.3 a 24.0 a 19.5 b 30-45 cm Average value 24.6 Notes: The factorial model with parameters APPL (application rate) and LENGTH (col. length) was run on the data. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed by different letters are significantly different. All samples were analyzed in the GVRD Lab. MTRUN2D.XLS 166 I— N ra D l E 8 E co ra O) E i co i : o • 5 JS J2 o o I- z ra E _ -a •S-o o h- o Ol Dl E i C D V co v v o fc-oi JC Ol E Bra C O V — a> <S a. O o CM 1 .2° ra J£ E O i C O o oS O c ad cu C L C L < T J CD S I cu £ o tu E « J ra S o cu g l ro o O J * .E co s i o *s 3 ra Q o-5 ? C3 ra 5.1 •=i T J cn cu T J N v_ >-o ro * -S > T > cu c 3 cu CO CL E B 8 j» = cu < C E _ 3 | E .c o 5 m ra JC Ol E E ° i ra o ra Ol E | o V u ra JC Ol E Q. ro E £ II" 82 to _ = £ « ra a a o o IS > m i o C O O • o i o C O LO I 6 i | o co LO I O I 1 f i o co 1 T I o C O in o| 08 ol m |o O 167 ^ 0) (0 "5. 4> o o _ T J — 0) <S a o Q-i - ° o E _ 3 •§ E JZ O E I f o 1 s II o a> o - 1 Rt a. a o o P p p p p P T J C CU a. T J CD cu 3 5 co §! CD £ u> •— O (j) E u> 3 a> m o = E o .B 3 CO 9 ^ CD <o T J (D CD T J N ,_ >- O CO * " s% CD c 3 <D E S <o !K co ,£ = (D < or z a. 168 LEACHING EXP. - RUN 2 (COLUMNS) - TOTAL METALS - LONG FORM OF DATA ANALYSIS Class Level Information Class Levels Values APPL 3 _ 0 dt/ha _100 dt/ha _300 dt/ha LENGTH 2 _0-45 cm Col. _0-90 cm Col. Number of observations in data set =12 (DF for Error = 6) Notes: The factorial model with parameters APPL (application rate) and LENGTH (col. length) was run on the data. 'R-Square' refers to the RA2 of the model y = APPL | LENGTH in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. In the analysis, if the concentration measured was below the detection limit, half the concentration of the detection limit was used for that element. R-Square: C.V.: Std. Dev.: Mean: 0-15 cm Layer: Arsenic (mg/kg) all values: < 8.0 Cadmium (mg/kg) 0.701 27.8 0.2 0.8 Chromium (mg/kg) 0.202 5.7 2.9 50.7 Cobalt (mg/kg) 0.286 7.9 1.5 18.9 Copper (mg/kg) 0.732 5.1 83 1613 Lead (mg/kg) APPL sig. Mercury (mg/kg) APPL sig. Molybd. (mg/kg) 0.699 41.5 0.6 1.4 Nickel (mg/kg) 0.046 10.3 2.2 21.6 Selenium (mg/kg) APPL sig. Zinc (mg/kg) APPL sig. 0-15 cm Lead (mg/kg): Duncan Grouping Mean N APPL A 27.8 4 _300 dt/ha B 11.8 4 _100 dt/ha C 6.8 4 0 dt/ha 0-15 cm Mercury (mg/kg): Duncan Grouping Mean N APPL A 0.9 4 _300 dt/ha B 0.3 4 _100 dt/ha C 0.1 4 0 dt/ha 0-15 cm Selenium (mg/kg): - Duncan Grouping Mean N APPL A 1.4 4 _300 dt/ha B 0.7 4 _100 dt/ha C ' 0.4 4 0 dt/ha 0-15 cm Zinc (mg/kg): Duncan Grouping Mean N APPL A 182 4 _300 dt/ha B 120 4 _100 dt/ha C 82 4 0 dt/ha MTRUN2B.XLS - Page 1 LEACHING EXP. RUN 2 (COLUMNS) - TOTAL METALS - LONG FORM OF DATA ANALYSIS R-Square: 15-30 cm Layer: Arsenic (mg/kg) all values Cadmium (mg/kg) 0.720 Chromium (mg/kg) 0.457 Cobalt (mg/kg) APPL sig. Copper (mg/kg) 0.516 Lead (mg/kg) APPL sig. Mercury (mg/kg) APPL sig. Molybd. (mg/kg) 0.574 Nickel (mg/kg) 0.711 Selenium (mg/kg) APPL sig. Zinc (mg/kg) APPL sig. 15-30 cm Cobalt (mg/kg): Duncan Grouping A A B 15-30 cm Lead (mg/kg): Duncan Grouping A B B 15-30 cm Mercury (mg/kg): Duncan Grouping A B B 15-30 cm Selenium (mg/kg): Duncan Grouping A B B 15-30 cm Zinc (mg/kg): Duncan Grouping A B B C.V.: Std. Dev.: Mean: <8.0 37.2 0.2 0.6 10.9 6.2 56.8 11.3 210 1856 48.9 0.5 1.1 8.3 2.1 25.3 Mean N APPL 24.3 4 _ 0 dt/ha 24.0 4 _100 dt/ha 19.5 4 _300 dt/ha Mean N APPL 21.0 4 _300 dt/ha 6.8 4 _100 dt/ha 5.6 4 _ 0 dt/ha Mean N APPL 0.5 4 _300 dt/ha 0.1 4 _100 dt/ha 0.1 4 _ 0 dt/ha Mean N APPL 1.2 4 _300 dt/ha 0.6 4 _100 dt/ha 0.5 4 _ 0 dt/ha Mean N APPL 153 4 _300 dt/ha 112 4 _100 dt/ha 106 4 0 dt/ha R-Square: 30-45 cm Layer: Arsenic (mg/kg) all values Cadmium (mg/kg) 0.500 Chromium (mg/kg) 0.429 Cobalt (mg/kg) 0.456 Copper (mg/kg) 0.073 Lead (mg/kg) 0.205 Mercury (mg/kg) all values Molybd. (mg/kg) 0.350 Nickel (mg/kg) 0.398 Selenium (mg/kg) 0.349 Zinc (mg/kg) 0.399 C.V.: Std. Dev.: Mean: < 8.0 33.7 0.2 0.5 9.4 5.8 62.5 8.4 2.1 24.6 22.0 476 2168 79.8 5.5 6.8 <0.1 50.8 0.5 0.9 10.7 3.1 28.5 17.0 0.1 0.5 14.5 16 111 MTRUN2B.XLS - Page 2 170 A P P E N D I X H Leaching Run 1 - Nitrogen, Total Phosphorus, pH, and EC in Leachate LEACHING EXPERIMENT - RUN 1 - N03-N IN LEACHATE - OVERVIEW Class Level Information C lass Levels Values A P P L 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha L E N G T H 3 _0-45 cm Col . _0-60 cm Col . _0-90 cm Co l . Number of observations in data set = 26 (DF for Error = 14) LEACHING RUN 1 R-Square C.V. Std. Dev.: M e a n : Total NC-3-N/Column (mg/col.) 0.419 267 0.13 0.05 Average N03-N/Column (mg/L) 0.419 201 0.04 0.02 Max. N03-N/Col. (mg/L) 0.379 238 0.49 0.21 Notes: The factorial model with parameters A P P L (application rate) and L E N G T H (col. length) was applied to the data. 'R-Square' refers to the R A 2 of the model y = A P P L | L E N G T H in the statistical S A S procedure G L M . The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. D e v . ' refers to the sample standard deviation. 'C.V. ' re fers to the coefficient of variation in percent. In the analysis, if the concentration measured was below the detection limit, half the concentration of the detection limit was used for that parameter. RUNSN03B.XLS - Page 1 172 co a I S 3 o S g g o 5 z o w < " g. 6 ro j= o (0 a> -_j 5-"5) oTo m m m i n O O O O O O O O d d ci d ( OTC JTTOTO " T 3 ? 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O O S O O CO o in in o oo n O O 2 o o T— CO ^ o o o D S O O O T - CO CO r-i o o CO ° 8 L ' T- CO 8 | o o CO O O O O cn co cn cn O O O O i o m > 6 o CM CM CM I CM T - CM CO o o o ^CDOQUJl^OX-r-o^-JS 6 6 6 6 6 6 6 6 ° 0 6 0 6 173 LEACHING EXPERIMENT - RUN 1 - TKN - OVERVIEW Class Level Information Class Levels Values APPL 4 LENGTH 3 _ 0 dt/ha _0-45 cm Col _ 30 dt/ha _100 dt/ha _300 dt/ha _0-60 cm Col. _0-90 cm Col. Number of observations in data set = 26 (DF for Error = 14) Notes: The factorial model with parameters APPL (application rate) and LENGTH (col. length) was applied to the data. 'R-Square' refers to the RA2 of the model y = APPL | LENGTH in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. If the concentration measured was below the detection limit, half the concentration of the detection limit was used in calculations. LEACHING RUN 1 R-Square: C.V.: Std. Dev.: Mean: Total TKN/Column Max. TKN/Column (mg/col) (mg/L) 0.625 . 121 1.2 1.0 0.302 177 5.5 3.1 Week 1 - TKN Week 2 - TKN Week 3 - TKN Week 4 - TKN Week 5-TKN (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) 0.227 354 1.9 0.5 0.446 162 0.3 0.2 0.524 199 1.0 0.5 APPL and LENGTH sig. APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Columns C-9 and C-l concentrations < 2.7 Week 6 -TKN (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Columns C-9 and C-l concentrations < 1.2 Week 9 -TKN (ma/L) 0.390 186 0.7 0.4 where: Week 4 - TKN (mg/L): Duncan Grouping Mean N APPL a 1.2 8 300 dt/ha b a 0.3 6 30 dt/ha b a 0.3 6 100 dt/ha b 0.1 6 0 dt/ha Duncan Grouping Mean N LENGTH a 1.1 8 _0-45 cm Col. b 0.3 10 _0-90 cm Col. b 0.2 8 0-60 cm Col. Average TKN concentrations for Columns C-9 and C-l: Column: C-9 & C-l Appl. Rate: 300 dt/ha Col. Length: 0-45 cm Week 5 -TKN (mg/L) 5.8 Week 6 - TKN (mq/L) 6.7 RUNSTKNB.XLS - Page 1 o r ~ - o o o o r - ~ o o > o o o o O C O O O O T f t O O C O O O I O 11 CO i z 1 (•* CO CM CO d o d o 01 ~ 0) (5 A o | E o £ r - f - O O -<J O O O O O O O O nSMtNlOlNrMMOIWCMCMW r N o d d d d d o ' d d d d « Q. A O) 00 „ < CM . JC iJ f 8 3 A CO O -CO Q) C c o 1" c a u c o z >. 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E c o C T 3 O CD TS t> ~ CO c 3 i_ a) CD O > d -, 178 A P P E N D I X I Leaching Run 2 - Nitrogen, Total Phosphorus, pH, and EC in Leachate LEACHING EXPERIMENT - RUN 2 - N03-N IN L E A C H A T E - OVERVIEW Class Levels Values APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 3 _0-45cmCol. _0-60cmCol. _0-90cmCol. Number of observations in data set for Site 3 and Site 4 each =13 (DF for Error = 1) Notes: In Leaching Run 2, the N03-N leaching behaviour differed between the tailings from sites 3 and 4. Therefore, a separate analysis was conducted on the data collected for these sites. The factorial model with parameters APPL (application rate) and LENGTH (col. length) was applied to the data. 'R-Square' refers to the R"2 of the model y = APPL | LENGTH in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. In the analysis, if the concentration measured was below the detection limit, half the concentration of the detection limit was used for that parameter. LEACHING RUN 2 - SITE 3 R-Square C.V. Std. Dev.: Mean: Total N03-N/Col. (mg/col) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.3 Max. NC-3-N/Col. (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 2.4 Week 1 - N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.3 Week 2-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.1 Week 3-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.1 Week 4-N03-N (mg/L) 0.521 79 0.01 0.02 Week 5-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.1 Week 8-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.6 Week 9-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.4 Week 12 - N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 1.7 Week 13 - N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 1.6 LEACHING RUN 2 - SITE 4 Total N03-N/Col. (mg/col.) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.6 except for Column C-G and C-H concentrations Max. NC-3-N/Col. (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 1.9 except for Column C-G and C-H concentrations Week 1 - N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.2 Week 2-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 1.2 Week 3-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.5 Week 4-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.7 Week 5-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.4 Week 8-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.2 except for Column C-G and C-H concentrations Week 9-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.3 except for Column C-G and C-H concentrations Week12-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.9 except for Column C-G and C-H concentrations Week13-N03-N (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values < 0.6 except for Column C-G and C-H concentrations RUNSN03B.XLS - Page 1 LEACHING EXPERIMENT - RUN 2 - N03-N IN L E A C H A T E - OVERVIEW Average N03-N concentrations for Columns G and H (0-45 cm Columns): Col. G (30 dt/ha) Col. H (100 dt/ha) Total NC-3-N/Col. (mg/col.) 188 121 Max. N03-N/Col. (mg/L) 1245 1076 Week 8-N03-N (mg/L) 24 129 Week 9-N03-N (mg/L) 32 49 Week12-N03-N (mg/L) 706 249 Week13-N03-N (mg/L) 819 693 Mass of N03-N in Leachate collected from Columns G and H in Weeks with high N03-N Concentrations: Col. G (30 dt/ha) Col. H (100 dt/ha) Max. NC-3-N/Col. (mg/col.) 125 70 Week 8-N03-N (mg/col.) 1 9 Week 9-N03-N (mg/col.) 3 4 Week12-N03-N (mg/col.) 53 16 Week13-N03-N (mg/col.) 89 62 RUNSN03B.XLS - Page 2 Week 13 Nov. 8-> 14 I 1 1 § ! I l ! 8 I 1 d 8 ! d I I ! S d I I 1 1 I I 1 !1 *i 1 ! 1 1 s 8 8 I ! ! 5 d I ! ! ! I S J d 1 1 Week 9 Oct. 11 -> 17 ! ! 1 1 1 ! ! 5 ! 1 I I CO I 8 I d 1 I 1 § ! Week 8 Oct. 4-> 10 I ! I s 1 d ! I d 3 d CO 3 d 3 d s 5 CO 3 d CO 3 d CO 3 d CO 3 d CO 3 d eachate. Week 5 Sep. 13->19 I ! ! ! ! I | ! 1 !1 !! 1 ! 1 ! d ! | ! itration in li Week 4 Sep. 6->12 I 1 1 ! 1 1 1 i 1 d 1! § 1 1 . i i ! I I O ! I 1 I ! 8 R d • d 3 11 ! I . eekly N03 Week 2 Aug. 23 -> 29 1 r 1 ! I 8 d ! » d ! 1 I Average w Week 1 Aug. 16 -> 22 I I 5 d I I 1 d j ! ! | ! l l i l I d 1 5 3 s s s l s 3 d S 1 3 3 3 d s d Estimated kg/ha N03-N in Total Leachate I 1 1 % 1 1 d d § 5! d ° d i ° d i i S § 1 d d 9 R i I 1 1 § Estimated mg N03-N in Total Leachate I 1 l ! I 5 d 3 1 § 5 d d d S d 5 d d 1 d d 1 I 5 1 1 1 1 i ill 1 5 1 1 1 1 1 1 I 1 » 8 g S § a 1 1 g 1 S3 2 1 1 § I 8 i 5 1 s 1 ! 1 1 1 ! ! § 5 1 1 ! 1 1 u 1 o § 8 o s P 1 o s § 8 o s § § 1 o S P 1 § I § 1 I I I 2 2 2 2 I I 8 s I i ! I I 2 2 2 2 § S 1 i i !I 5 o 3 s 3 8 8 & S S 5 5 5 CO 5 s 3 s 3 3 2 5 3 3 3 3" 3 182 no ^ n CM z a. ~ 0) "5. <a 183 LEACHING EXPERIMENT - RUN 2 (COLUMNS) - TKN - OVERVIEW Class Level Information Class Levels Values APPL 4 _ 0 dt/ha _ 30 dt/ha _100 dt/ha _300 dt/ha LENGTH 3 _0-45 cm Col. _0-60 cm Col. _0-90 cm Col. Number of observations in data set for Site 3 and Site 4 each = 13 (DF for Error = 1) Notes: In Leaching Run 2, the TKN leaching behaviour differed between the tailings from sites 3 and 4. Therefore, a separate analysis was conducted on the data collected for these sites. The factorial model with parameters APPL (application rate) and LENGTH (col. length) was applied to the data. 'R-Square' refers to the RA2 of the model y = APPL | LENGTH in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. If the concentration measured was below the detection limit, half the concentration of the detection limit was used in calculations. LEACHING RUN 2 - SITE 3 R-Square: C.V.: Std. Dev.: Mean: Total TKN/Column (mg/col) 0.982 18 0.06 0.35 Max. TKN/Column (mg/L) 0.995 13 0.28 2.16 Week 1 -TKN (mg/L) APPL, LENGTH, and APPL'LENGTH sig. , but all values < 0.6 Week 2 -TKN (mg/L) 0.987 14 0.06 0.40 Week 3 -TKN (mg/L) APPL, LENGTH, and APPL*LENGTH sig. , but all values < 0.6 Week 4 -TKN (mg/L) APPL, LENGTH, and APPL*LENGTH sig. , but all values < 3.5 Week 5-TKN (mg/L) all values < 0.2 Week 8 -TKN (mg/L) 0.918 77 0.58 0.75 Week 9 -TKN (mg/L) 0.988 28 0.09 0.32 Week 12 -TKN (mg/L) 0.763 60 0.06 0.09 LEACHING RUN 2 - SITE 4 R-Square: C.V.: Std. Dev.: Mean: Total TKN/Column (mg/col.) APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Column C-H concentration < 1.0 Max. TKN/Column (mg/L) APPL, LENGTH, and APPL*LENGTH sig., but all values except for the Column C-H concentration < 5.6 Week 1 -TKN (mg/L) 0.640 177 0.5 0.3 Week 2 -TKN (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Column C-H concentration < 0.8 Week 3 -TKN (mg/L) APPL, LENGTH, and APPL*LENGTH sig., but all values except for the Column C-H concentration < 0.2 Week 4 -TKN (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Column C-H concentration < 2.5 Week 5 -TKN (mg/L) all values < 0.2 Week 8 -TKN (mg/L) APPL, LENGTH, and APPL*LENGTH sig., but all values except for the Column C-H concentration < 5.6 Week 9 -TKN (mg/L) APPL, LENGTH, and APPL'LENGTH sig., but all values except for the Column C-H concentration < 3.2 Week 12-TKN (mg/L) 0.992 63 0.3 0.4 RUNSTKNB.XLS - Page 2 L E A C H I N G E X P E R I M E N T - R U N 2 ( C O L U M N S ) - T K N - O V E R V I E W TKN concentration for Column C-H: Column: Appl. Rate: Col. Length: C-H 100 dt/ha 0-45 cm Week 2 -TKN (mg/L) 125 Week 3 - TKN (mg/L) 155 Week 4 -TKN (mg/L) 23 Week 8 - TKN (mg/L) 10 Week 9 -TKN (mg/L) 7 Mass of TKN in Leachate collected from Column H in Weeks with high TKN Concentrations: Column: Appl. Rate: Col. Length: C-H 100 dt/ha 0-45 cm Week 2 - TKN (mg/col.) 81 Week 3 -TKN (mg/col.) 47 Week 4 -TKN (mg/col.) 1 Week 8 -TKN (mg/col.) 1 Week 9 -TKN (mg/col.) 1 RUNSTKNB.XLS - Page 3 2 g I 1 1 1 I 1 1 ! 1 1 1 I 1 1 1 1 1 1 1 1 1 ! f I i' I 3 d 3 5 2 § d •» S s s d s 2 3 2 3 3 S S 2 s s !! I 3 2 3 3 3 § S 2 3 3 s § 3 3 2 2 d 2 2 3 2 Week 12 Nov. 1 ->7 I 1 V 2 V 3 V 3 V i V ' 3 V 2 V 2 V 2 V 3 V 3 V s 3 V i • 6 3 V S 3 3 V • 3 V Week 9 Oct. 11 -> 17 I 3 s 2 3 V 3 3 1 3 V 3 V 2 3 V 3 3 V § V § V 2 V 3 V 3 V s 8 S 1 s 3 Week 8 Oct. 4->10 i 1 1 2 s s • • 3 i 5 1 I o • i 3 1 1 ? s 3 :hate. Week 5 Sep. 13->19 I 3 V 3 V 3 V 3 V 3 V 1 3 V 3 V 3 V 3 V 3 V 3 V 2 V 2 V 2 V 3 V 2 V i 3 V 3 V 2 V 3 V 3 V tion in lea< Week 4 Sep. 6-> 12 I 3 V 3 V 3 V 3 V 3 V * 3 V 2 V 3 s V 3 V 2 V 3 ? 3 V 3 V 3 V ! i !f ! 3 V 2 V I 3 V 3 V 3 V 3 V 3 V 2 V 2 V 3 V 3 V 3 V 2 V 2 V 2 V 3 V 2 V 3 V 3 V 3 V 2 V 2 V 3 V 3 V I i 4 I 9 1 2 | 3 1 § 3 1 2 3 1 3 2 5 d 2 ! 3 5! d 2 » 1 3 d 2 3 3 : i *. I 3 V 3 V 3 V 3 V 3 V 3 V 3 V 3 2 V 2 V 1 3 V s 3 d 3 3 V 2 3 V 3 d 3 V 3 2 V 2 V 2 3 V .ll'l I 1 5 5 1 g s 8 8 3 3 3 •» 3 3 S •» 3 111! I d 3 3 5! 5 5 d 3 t d d d 2 2 3 3 3 2 3 3 § 2 2 2 § 3 I (mg/col.) I 3 3 3 5 3 3 i 3 2 2 1 3 3 3 S 3 3 3 2 5 S •» 3 3 3 i i i 1 1 1 1 1 I 1 5 1 1 1 S 5 1 1' 1 1 t 1 5 II I 1 8 s 8 1 S a 8 » 1 1 8 8 I m I I 1 ! 1 I 8 1 1 8 1 ! 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X U J o z X o < U J 0) CD O A O ,1 u O CD CD s a CD CD CD CM a. *" CB A CO • CO CO CD 0) CD o m Q. < A 3 1 O JC CD CD A < CO CM 0) CD 5 CM 0 5 A = A < CD — * J o » O a in J3 C3 o O o o o o CO 00 o CO o o CO o o CO o o O O o iO o CO T 3 • -LU S Q CU Q M S CO ^ ^ A P P E N D I X J Bulk Density & Particle Size Distribution PRINCETON DEMO. PROJECT - BULK DENSITY FIELD EXPERIMENT: Average Application Bulk Rate: * Site: Date: Depth: Density/Site: (dt/ha) (cm) (kg/m3) Background P2a Oct. 92 15-30 1193 Background P2b Oct. 92 15-30 1149 Background P3a/3b Oct. 92 15-30 1313 Background Control Oct.92 15-30 1239 Background Average: Oct.92 15-30 1231 Background Std. Dev. Oct.92 15-30 70 Background CV: Oct.92 15-30 5.7% 179 P3a Sep.93 0-15 896 77 P2a Sep.93 0-15 1206 77 P3b Sep.93 0-15 1117 62 P2b Sep.93 0-15 1185 0 Control Sep.93 0-15 1363 179 P3a Sep.93 15-30 1463 77 P2a Sep.93 15-30 1349 77 P3b Sep.93 15-30 1336 62 P2b Sep.93 15-30 1232 0 Control Sep.93 15-30 1324 * In October 1992, stored dewatered biosolids were applied to all sites except the northern one third portion of P2b. Land-dried biosolids were applied to that portion of P2b. LABORATORY EXPERIMENT (RUN 2): Column 1-> 13 (P2a-R1 tailings) 1130 kg/m Column A -> M (P2b-R1 tailings) 1000 kg/m B U L K D . X L S 191 PRINCETON DEMONSTRATION PROJECT - PARTICLE SIZE DISTRIBUTION Site Depth (cm) % Sand % Silt % Clay Percent Particles < 0.001 mm Unified Soil Class. (Wagner 1957) U.S.D.A. Texture Triangle Class. Coefficient of Permeability (BS 8004:1986) (m/s) Ctrl C4 0-15 14.3 56.3 29.5 17.2 ML or C L SiL 1.5E-07 - 1.0E-10 P2a-R1 0-15 31.5 45.0 23.5 12.6 M L or C L S iL 1.5E-07 - 1.0E-10 P2a-R1 15-30 3.5 53.8 42.7 28.3 M L or C L S i C 1.5E-07 - 1.0E-10 P2a-R1 30-45 3.2 56.3 40.5 25.6 M L or C L S i C 1.5E-07 - 1.0E-10 P2a-R1 45-60 3.0 56.8 40.2 26.9 M L or C L S i C 1.5E-07 - 1.0E-10 P2a-R1 60-75 2.8 58.9 38.3 23.7 ML o r C L S i C L 1.5E-07 - 1.0E-10 P2a-R1 75-90 6.7 58.4 34.9 20.5 ML o r C L S i C L 1.5E-07 - 1.0E-10 P2b-R1 0-15 17.2 60.4 22.4 10.8 ML or C L S iL 1.5E-07 - 1.0E-10 P2b-R1 15-30 2.1 60.6 37.3 21.9 ML or C L S i C L 1.5E-07 - 1.0E-10 P2b-R1 30-45 1.4 53.1 45.6 27.8 ML or C L S i C 1.5E-07 - 1.0E-10 P2b-R1 45-60 1.3 53.6 45.1 26.2 ML or C L S i C 1.5E-07 - 1.0E-10 P2b-R1 60-75 0.7 47.1 52.2 33.5 ML or C L S i C 1.5E-07 - 1.0E-10 P2b-R1 75-90 1.0 54.5 44.6 29.1 ML o r C L S i C 1.5E-07 - 1.0E-10 P3a-R1 0-15 30.3 63.0 6.7 3.7 ML or C L S iL 8.2E-05 - 1.5E-07 P3a-R1 15-30 13.2 71.2 15.6 9.5 ML or C L S iL 8.2E-05 - 1.5E-07 P3a-R1 30-45 8.2 76.9 14.9 9.7 ML or C L S iL 8.2E-05 - 1.5E-07 P3a-R1 45-60 1.3 81.6 17.1 9.8 ML or C L S iL 8.2E-05 - 1.5E-07 P3a-R1 60-75 0.5 59.6 39.9 22.3 ML or C L S i C L 1.5E-07 - 1.0E-10 P3a-R1 75-90 5.1 63.3 31.5 19.2 ML or C L S i C L 1.5E-07 - 1.0E-10 P3a-R3 0-15 19.1 76.6 4.3 n/a ML or C L Si 8.2E-05 - 1.5E-07 P3a-R3 15-30 3.5 80.2 16.3 14.6 ML or C L S iL 8.2E-05 - 1.5E-07 P3a-R3 30-45 3.0 76.8 20.2 13.3 ML or C L S iL 1.5E-07 - 1.0E-10 P3a-R3 45-60 1.7 82.8 15.5 9.0 ML or C L SiL 8.2E-05 - 1.5E-07 P3a-R3 60-75 2.1 76.3 21.6 n/a ML or C L S iL 1.5E-07 - 1.0E-10 P3a-R3 75-90 0.4 64.0 35.6 n/a ML or C L S i C L 1.5E-07 - 1.0E-10 P3D-R2 0-15 9.4 66.9 23.7 13.4 M L or C L S iL 1.5E-07 - 1.0E-10 P3b-R2 15-30 3.1 69.8 27.1 15.0 M L or C L S iL 1.5E-07 - 1.0E-10 P3b-R2 30-45 1.6 69.6 28.8 13.4 M L or C L S iL 1.5E-07 - 1.0E-10 P3b-R2 45-60 0.7 55.4 43.9 24.0 M L or C L S i C 1.5E-07 - 1.0E-10 P3b-R2 60-75 1.3 57.3 41.4 25.3 M L or C L S i C 1.5E-07 - 1.0E-10 P3b-R2 75-90 9.0 80.3 10.7 5.0 M L or C L S i 8.2E-05 - 1.5E-07 Notes: Sand particles: Silt particles: Clay particles: ML C L 0.050 0.002 < 0.002 2 0.05 mm mm ML or C L Inorganic silts => more than 50% of particles < 63 urn; liquid limit < 50 => silty or clayey sands with slight plasticity Inorganic clays => more than 50% of particles < 63 urn; liquid limit < 50 => silty or sandy clays of low plasticity soil classification depends on plasticity chart In the leaching experiments, Tai l ings from Sites 1 , 2 , 3 , or 4' refers to tailings originating from the discrete sampling locations ' P 3 a - R V , 'P3a-R3 ' , 'P2a-R1 ' , or 'P2b-R1 ' in the field. 92TEXTUR.XLS A P P E N D I X K Field Experiment - Vegetation P R I N C E T O N D E M O N S T R A T I O N P R O J E C T - F O L I A G E Q U A L I T Y - O V E R V I E W C l a s s L e v e l s V a l u e s A A P P L 3 _ 0 d t /ha _ 6 2 d t /ha _ 7 7 d t /ha N u m b e r of o b s e r v a t i o n s for Y i e l d ( incl . _ 1 7 9 d t /ha data) = 2 2 ( D F for E r ro r = 19) N u m b e r of o b s e r v a t i o n s for al l o ther p a r a m e t e r s 17 ( D F for E r ro r = 14) 1993 F O L I A G E Q U A L I T Y L I T E R A T U R E V A L U E S : Element: Mean: Std. Dev: Normal C . E x c e s s i v e C : Arsen ic , mg/kg 7.6 3.3 C a d m i u m , mg/kg < 0 .50 > 3 (3) C h r o m i u m , mg/kg A A P P L s i g . > 2 (3) Copper , mg/kg A A P P L s i g . 5 .0 - 2 0 > 2 0 (2,5) Lead, mg/kg 5.0 1.7 > 10 (3) Mercury, mg/kg 0 .010 0 .004 Molybdenum, mg/kg A A P P L s i g . 0.1 - ? (6) Nickel, mg/kg 1.2 0.6 0.1 - 1 > 5 0 (3,4) N03-N, % A A P P L s i g . Selenium, mg/kg 0 .19 0 .08 > 4 (6) Total N, % A A P P L s i g . 1.5 (D Zinc, mg/kg 3 0 . 5 7.8 2 5 . 0 - 150 > 4 0 0 (2) Yield, dt/ha A A P P L s i g . N o t e s : T h e ma in ef fect m o d e l wi th p a r a m e t e r A A P P L (app l ica t ion rate) w a s u s e d for the d a t a a n a l y s i s . T h e D u n c a n mul t ip le r a n g e test at the 0 .05 leve l of probabi l i ty w a s u s e d to d e t e r m i n e s ign i f icant ly di f ferent m e a n s . 'S td . D e v . ' re fers to the s a m p l e s t a n d a r d dev ia t i on . A l l s a m p l e s w e r e a n a l y z e d by N o r w e s t L a b s . (1) S a l i s b u r y a n d R o s s , 1991 (2) Mor t ved t et a l . , 1972 (3) C A S T , 1 9 7 6 ; M e l s t e d , 1 9 7 3 ; Un iv . of G e o r g i a C o o p Ext . , 1 9 7 9 (4) T i s d a l e e t a l . , 1 9 9 3 (5) C o k e r e t a l . , 1 9 8 2 (6) W a l s h a n d B e a t o n , 1 9 7 3 TLGFOCB.XLS 194 co or HI K-UJ S < o. < o LL. z CD CO < O UJ 0 < O ui ~~i o a: a. UJ a z o I-UJ o z on a. 5a • a T3 CN CD CO 53 CD T3 •i O _C0 cu > CD CL a. o LU .O 5 S CO c g ro CD to X I o 0 X) E 3 C O 111 _ l < > < a UJ 0 < CO CO un d c\f CO (0 co CM o o CN X UJ A A O c^ -CN 6 "5 i E O T - LO o LO d z T3 "D T3 T3 T3 CD CD CD CD CD i _ L - l _ L_ l -ra ca CO CO CO ca a . CL CL CL CL XI E E E E E CD o o o o o T3 o o o o o O a> o o o o o h- c c c c c 1 XI X) X) co ro co n 00 T _ •0- CD o LO CN CO O CN IO •o O XI XI XI XI XI co co 00 CO CD o CN CO n CN o t/h o XI CM co CO CO XI XI XI CO o 00 CO LO CN CO CD CN o o o ra o £ 33 T3 O 1 D) O) O) ra J£ £! «3 o> D) 0> T3 a> * J E E E ra L_ Q. Q. 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PROJECT - VEGETATION - FIELD DATA Vegetation Yielc Plot 1 in July 199: Application Rate: (dt/ha) } Vegetation Site Yield (kg/ha) Percent of Total Yield (%) Ctrl Seeded 0 W e e d s 61 75 Ctrl Seeded 0 G r a s s e s 20 25 Ctrl Unseeded 0 W e e d s 533 82 Ctrl Unseeded 0 G r a s s e s 114 18 P2b 62 Fal l R y e 903 33 P2b 62 W e e d s 749 27 P2b 62 G r a s s e s 744 27 P2b 62 Alfal fa 289 10 P2b 62 Hairy Ve tch 85 3 P2a 77 Fal l R y e 481 46 P2a 77 G r a s s e s 305 29 P2a 77 Alfal fa 129 12 P2a 77 W e e d s 103 10 P2a 77 Hairy Ve tch 22 2 P3b 77 Fal l R y e 941 66 P3b 77 G r a s s e s ' 354 25 P3b 77 Alfal fa 58 4 P3b 77 W e e d s 58 4 P3b 77 Hairy Ve tch 12 1 P3a 179 Fal l R y e 358 70 P3a 179 G r a s s e s 99 19 P3a 179 Alfal fa 30 6 P3a 179 W e e d s 18 4 P3a 179 Hairy Ve tch 4 1 Total Yield and Legume Establishment in July 1993 Plot Application Rate Total Yield Legume Contribution to Total Yield (dt/ha) (kg/ha) (%) Ctrl Seeded 0 81 0 Ctrl Unseeded 0 648 0 P2b 62 2770 13 P2a 77 1039 15 P3b 77 1422 5 P3a 179 509 7 YIELDJ93.XLS 196 Ico CM > Ci •o •a *-> in 2 CD > < 5 o Ol o o CD CD co co o o o o o co o IT) CM CO co t-; 05 o i r i CD o CO o CO oo d CM o o d CO in I o o < Q a _ l UJ u_ o co o co o c\i CM in o CM d o CM o d to CD o co d UJ O UJ > o U J - J o DC 0. < H W z o s UJ Q UJ O z or o. 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S o JC I <•> ' E cu ! 2 < H E 3 E o L . o cn JC "5) E _ E 3 C a •a J3 >•! o 2 C O IE. 3 ' E o> cu CO O) E _ u c N t o ~ cn CL O => O CD " O 0) T 3 O E to ca W M =5 | £» tu ^ £ £ S o - - 5 - 2 ° a - 2 cu Q -o c n E 1 -to coO tu '" > CO ', to to o tu" - tu o c cu o ^ -i= ~ tu 2 E D : <= tu~: CD O CO TO -. t ; cu Z lu co to cu N cu s c Ui co co E p co o to to I— — D . CU to cz O.C J> CO z i - S r o > 201 P R I N C E T O N D E M O . P R O J E C T - V E G E T A T I O N - L O N G F O R M O F D A T A A N A L Y S I S C l a s s L e v e l s V a l u e s A A P P L 3 _ 0 d t /ha _ 6 2 d t /ha _ 7 7 d t /ha N u m b e r of o b s e r v a t i o n s for Y i e l d ( incl . _ 1 7 9 d t /ha data) = 2 2 ( D F for E r ro r = 19) N u m b e r of o b s e r v a t i o n s for al l o ther p a r a m e t e r s = 17 ( D F for E r ro r = 14) N o t e s : T h e ma in ef fect A A P P L (app l i ca t ion rate) w a s e x a m i n e d . ' R - S q u a r e ' re fers to the R A 2 of the 'mode l y = A A P P L ' in the s ta t is t ica l S A S p r o c e d u r e G L M . T h e D u n c a n mul t ip le r a n g e test at the 0 .05 leve l of probabi l i ty w a s u s e d to de te rm ine s ign i f icant ly di f ferent m e a n s . 'S td . D e v . ' re fers to the s a m p l e s t a n d a r d dev ia t i on . ' C . V . ' re fers to the coef f ic ient of var ia t ion in percen t . ' N ' re fers to the n u m b e r of s a m p l e s u s e d in a v e r a g e ca l cu la t i ons . M e a n s p r e c e d e d by di f ferent let ters a re s ign i f icant ly dif ferent. A l l s a m p l e s w e r e a n a l y z e d by N o r w e s t L a b s . Element: R-Square: C.V. : Std . Dev: Mean: Arsen ic , mg/kg 0 .062 4 3 . 4 3.3 7.6 C a d m i u m , mg/kg al l v a l u e s < 0 .50 Chromium A A P P L s i g . C o p p e r A A P P L s i g . Lead, mg/kg 0.1 35.1 1.7 5.0 Mercury, mg/kg 0 .779 30 .6 0 .004 0.01 Molybdenum A A P P L s i g . Nickel, mg/kg 0 . 0 5 3 50.1 0 .57 1 2 N03-N A A P P L s i g . Selenium, mg/kg 0 . 0 0 5 41.1 0 .08 0.2 Total N A A P P L s i g . Zinc , mg/kg 0 .378 2 5 . 7 7.8 3 0 . 5 Yield, dt/ha A A P P L s i g . C h r o m i u m , m g / k g : D u n c a n G r o u p i n g M e a n N A A P P L A 3.0 2 0 d t /ha B 1.8 5 6 2 d t /ha B 1.8 10 _ 7 7 d t /ha C o p p e r , m g / k g : D u n c a n G r o u p i n g M e a n N A A P P L A 6 8 . 0 2 0 d t /ha B 2 2 . 8 5 6 2 d t /ha B 21 .2 10 _ 7 7 d t /ha M o l y b d e n u m (Mo) , m g / k g : D u n c a n G r o u p i n g M e a n N A A P P L A 2 4 . 0 2 0 d t /ha B 5.7 10 7 7 d t /ha B 4 .4 5 6 2 d t /ha TLGFOCA.XLS - Page 1 PRINCETON DEMO. PROJECT - VEGETATION - LONG FORM OF DATA ANALYSIS N 0 3 - N , %: D u n c a n G r o u p i n g M e a n A A P P L A B A B 0 .039 0 .010 0 . 0 0 3 10 5 2 7 7 d t /ha 6 2 d t /ha 0 d t /ha To ta l N , % : D u n c a n G r o u p i n g M e a n A A P P L A B A B 2 .0 1.5 1.2 10 2 5 7 7 d t /ha 0 d t /ha 6 2 d t /ha Y i e l d , dry t o n n e / h a : D u n c a n G r o u p i n g M e a n N A A P P L A 5 .5 10 7 7 d t /ha A 4 . 3 5 6 2 d t /ha B 0.6 5 179 d t /ha B 0.2 2 0 d t /ha TLGFOCA.XLS Page 2 A P P E N D I X L Field Experiment - Soil Fertility PRINCETON DEMO. PROJECT - SOIL FERTILITY - OVERVIEW TABLE Class Level Information C lass Level Va lues C lass Levels for the C E C Analys is : T IME 2 _Oct . 1992 A A P P L 4 _ 0 dt/ha Number of observat ions for C E C _Apr. 1993 62 dt/ha _ 77 dt/ha _179 dt/ha = 9 (DF for Error = 1) C l a s s Levels for all other parameters: T IME 3 _Oct . 1992 A A P P L 4 0 dt/ha _Apr. 1993 62 dt/ha Number of observat ions for NH4-N and N 0 3 - N Number of observat ions for all other parameters (except C E C ) S e p . 1993 77 dt/ha 179 dt/ha = 28 (DF for Error = 16) = 13 (DF for Error = 1) NUTRIENTS IN THE 0 -15 cm Layer LITERATURE V A L U E S Mean: Std. Dev.: Low: Normal Range: PH TIME s ig. E C , dS/m 1.5 0.9 Boron TIME s ig. < 0.5 0.5 (4) Bray P-1 TIME and A A P P L s ig. < 7 7 - 20 (1) Calcium A A P P L s ig. 30 - 300 (2) C E C , cmol/kg 7.3 1.3 Copper TIME and T I M E * A A P P L sig. < 0.2 (3) Iron TIME and A A P P L s ig. < 4.5 (3) Magnesium, mg/kg 182 18.1 5 - 50 (2) Manganese, mg/kg 4.8 2.2 < 1.0 (3) NH4-N TIME and T I M E ' A A P P L sig. N03-N TIME and T I M E * A A P P L sig. %Organic Matter 1.3 1.3 Potassium, mg/kg 263 53 < 40 40 - 600 (2) Sulfate, mg/kg 224 102 < 5 5 (2) Zinc, mq/kq 9.6 8.3 < 0.8 (3) Notes: The data analysis is based on results for samples analyzed by Norwest Labs for all parameters except ammonia and nitrate. The ammonia and nitrate data used in the analysis is included in this appendix (Norwest Labs -fertility data) and in Appendix M ( G V R D Lab - soi l nitrogen data). The factorial model was used with the parameters A A P P L (application rate) and T IME (time). The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. D e v . ' refers to the sample standard deviation. soi l (D (2) (3) (4) Page e ta l . , 1982 Tisdale et al., 1983 Lindsay and Norvell , 1978 (critical levels for corn) Wa lsh and Beaton, 1973 TLGFT93B.XLS 205 PRINCETON DEMO. PROJECT - SOIL FERTILITY - SIG. PARAMETERS Class Level Information Class Level Class Levels for the CEC Analysis: TIME 2 AAPPL 4 Number of observations for CEC Values Oct. 1992 0 dt/ha _Apr. 1993 62 dt/ha 77 dt/ha _179 dt/ha (DFfor Error = 1) Class Levels for all other parameters: TIME 3 _Oct. 1992 _Apr. 1993 AAPPL 4 _ 0 dt/ha _ 62 dt/ha Number of observations for NH3-N and N03-N Number of observations for all other parameters (except CEC) Sep. 1993 _ 77 dt/ha = 28 = 13 _179 dt/ha (DFfor Error = 16) (DFfor Error = 1) NUTRIENTS IN THE 0 -Parameter/Time: 15 cm LAYER Oct. 1992 Apr. 1993 Sept. 1993 LITERATUR Low E VALUES: Normal Range PH 8.2 a 8.2 a 7.5 b Boron, mg/kg 0.6 a 0.7 a 0.2 b < 0.5 0.5 (4) Bray P-1, mg/kg * 1.6 b 45 a 51 a < 7.0 7 - 20 (1) Calcium, mg/kg * 3411 c 4116 b 4638 a 30 - 300 (2) Iron, mg/kg * 38 b 63 b 168 a < 4.5 (3) The concentration of the nutrient is also dependent on the application rate. NUTRIENTS IN THE 0 -Parameter/Appl. rate: 15 cm LAYER 0 dt/ha 62 dt/ha 77 dt/ha 179 dt/ha LIT. V/l Low iLUES: Normal Range Bray P-1, mg/kg * * 3 b 4 b 22 b 83 a < 7.0 7 - 20 (1) Calcium, mg/kg * * 5016 a 4605 a 3851 b 3376 b 30 - 300 (2) Iron, mg/kg * * 28 b 75 ab 96 a 95 a < 4.5 (3) * * The concentration of the nutrient is also dependent on time. Notes: The data analysis is based on results for samples analyzed by Norwest Labs for all parameters except ammonia and nitrate. The ammonia and nitrate data used in the analysis is included in this appendix (Norwest Labs - soil fertility data) and in Appendix M (GVRD Lab - soil nitrogen data). The factorial model was used with the parameters AAPPL (application rate) and TIME (time). The Duncan multiple range test at the-0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. (1) Page etal., 1982 (2) Tisdale etal., 1983 (3) Lindsay and Norvell, 1978 (critical levels for corn) (4) Walsh and Beaton, 1973 TLGFT93C.XLS PRINCETON DEMO. PROJECT - SOIL FERTILITY - SIG. PARAMETERS NUTRIENTS IN THE 0 -15 cm Layer: N H 4 - N , mg/kg: Level of Level of NH4-N T IME A A P P L N Mean S D Oct. 1992 0 dt/ha 2 3.2 2.5 Oct. 1992 62 dt/ha 2 0.5 0.7 Oct. 1992 77 dt/ha 4 1.3 0.9 _Oct . 1992 _179 dt/ha 2 0.6 0.6 Apr. 1993 62 dt/ha 2 53 20 Apr. 1993 77 dt/ha 4 266 182 _Apr . 1993 _179 dt/ha 2 596 352 _ S e p . 1993 62 dt/ha 2 5.7 7.6 _ S e p . 1993 77 dt/ha 4 7.2 6.8 _ S e p . 1993 179 dt/ha 2 10.6 7.6 N 0 3 - N , mg/kg: Level of Level of N 0 3 - N T IME A A P P L N Mean S D Oct. 1992 0 dt/ha 2 1.7 1.9 Oct. 1992 62 dt/ha 2 1.0 1.4 Oct. 1992 77 dt/ha 4 1.1 1.1 _Oct . 1992 _179 dt/ha 2 1.0 1.4 Apr. 1993 62 dt/ha 2 2.5 0.8 Apr. 1993 77 dt/ha 4 4.8 6.2 _Apr . 1993 _179 dt/ha 2 3.6 2.3 Sep . 1993 62 dt/ha 2 4.9 3.0 S e p . 1993 77 dt/ha 4 126 44.2 S e p . 1993 179 dt/ha 2 297 6.4 Copper , mg/kg: Level of T IME _Oct . 1992 _Oct . 1992 _Oct . 1992 _Oct . 1992 _Apr. 1993 _Apr. 1993 _Apr. 1993 _ S e p . 1993 _ S e p . 1993 _ S e p . 1993 Level of A A P P L _ 0 dt/ha _ 62 dt/ha _ 77 dt/ha _179 dt/ha _ 62 dt/ha _ 77 dt/ha _179 dt/ha _ 6 2 dt/ha _ 7 7 dt/ha 179 dt/ha Copper Mean 70 75 73 75 72 100 121 92 111 79 S D 3.5 5.7 4.9 where N = number of samples analyzed; S D = Std. 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CD LO CO LO co d LO o E 3 CO to ro 4 - < i£ Ol JC I1 a> 4 - « co ->— 3 CO Ol JC Ol E I f Ol E E 3 to a> I1 oi JC | l , oi oi E. -_ ® , °-\ Q-O o oi JC Ol E, c o o m I S " I' a> to d> c to oil re S o x CZ <D a. Q . < T3 CD -Q '__ O CO CD T. CD \ ro cz o 4 - » o ro 4 - » X a> _ ^ CO CM CO CO CO CO O J <=s-_Q < O o o _ ro — o c o CO CO CO JO E CU -4—• Q . O J CO CZ o ro o •o o E a; .c 4 - -TD C ro CO JD ro JD T3 CD N J>. ro c ro CD 1 cu C/) 0. a . E ro CO to CD •4—• O = ro C L C L CD C L ro c ro to o to TJ — " lica O o CO lica CO o CD. O 1Q CD. J D I _ CO 1— CD t/) CD ct-T3 4i ro osoli ro to hs osoli . — . 4 - -£Z J D c o or to 1 o E CD E CN c C CL CD CD ( _!»-CD ro •«—» ro ak CD i CD L _ CD CD 0) i to to CD CD to CD. C L E E CD. ro ro E CO CO ro T — CN to 1 -*—' i 4 - » CD __ CO CO o o C L C L C L CO " O CD tr o C L 0 ro to jD ro rz o ro o "5. C L w _ i x o t-Li_ PRINCETON DEMO. PROJECT - SOIL FERTILITY - FIELD DATA (0-15 cm) COMPARISON OF AVAILABLE P (6 MONTHS AFTER BIOSOLIDS APPLICATION) Plot: Appl. Rate: Layer: Date: Bray P-1 (1:10 w/v) Olsen-P (dt/ha) (cm) for Composite Samples (mg/kg) Average of 3 Discrete Samples (mg/kg) Control 0 0-15 Apr. 93 n/a 1 P2b 62 0-15 Apr. 93 1 7 P2a 77 0-15 Apr. 93 9 6 P3b 77 0-15 Apr. 93 38 15 P3a 179 0-15 Apr. 93 132 13 LITERATURE VALUES: P Sufficiency Level Bray P-1 * (1:7 w/v) Olsen P * Fertilizer P ** Recommendation (mg/kg) (mg/kg) (kg P/ha) very low < 3 25 low 3 - 7 <5 15 medium 7 -20 5 -10 8 high >20 > 10 0 Notes: Bray P-1 and Olsen-P concentrations were determined by Norwest Labs and the BIOE Lab respectively. Page etal. (1982) Tisdale etal. (1993) OLSENP.XLS 210 to ~ II II ,2 L U Q O O L U L U Q Q CO CO < Z < < I -< Q u_ O s CC o u. (3 z o o CO o UJ -J o tc a. m a z O h-UJ O z Q . E o S-fc < o o u j g -I cn ra 2? «> cn ^ • ~ T J I I o cu ro P $ o LU o CO a) 9 i Z CO X . Z ' g g 11 0) 0) to CO J D J D O O 2£ e E a . 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Ol CO S -.: > ,»Uacci:«ni»*(i IO o Gram o o f S I O " o 3 = a i u c o c o U U U ± 2 2 Z Z ^ a . « N PRINCETON DEMO. PROJECT - SOIL FERTILITY - LONG FORM OF DATA ANALYSIS pH: Duncan Grouping A A B Boron, mg/kg: Duncan Grouping A A B Bray P-1, mg/kg: Duncan Grouping A A B Duncan Grouping A B B B Calcium, mg/kg: Duncan Grouping A B C Duncan Grouping A A B B Iron, mg/kg: Duncan Grouping A B B Duncan Grouping A A B A B Mean N TIME 8.2 4 Apr. 1993 8.2 5 Oct. 1992 7.5 4 Sep. 1993 Mean N TIME 0.7 4 Apr. 1993 0.6 5 Oct. 1992 0.2 4 Sep. 1993 Mean N TIME 51.3 4 Sep. 1993 45.0 4 Apr. 1993 1.6 5 Oct. 1992 Mean N AAPPL 83 3 179 dt/ha 22 6 77 dt/ha 4 3 62 dt/ha 3 1 0 dt/ha Mean N TIME 4638 4 Sep. 1993 4116 4 Apr. 1993 3411 5 _Oct. 1992 Mean N AAPPL 5016 1 0 dt/ha 4605 3 62 dt/ha 3852 6 77 dt/ha 3376 3 179 dt/ha Mean N TIME 168 4 Sep. 1993 63 4 Apr. 1993 38 5 _Oct. 1992 Mean N AAPPL 96 6 77 dt/ha 95 3 179 dt/ha 75 3 62 dt/ha 28 1 0 dt/ha TLGFT93A.XLS 212 A P P E N D I X M Field Experiment - Soil Nitrogen and Total Phosphorus PRINCETON DEMO. PROJECT - NITROGEN & TP - OVERVIEW Class Level Information Class Levels Values TIME 3 _Oct. 1992 _Apr. 1993 _Sep. 1993 AAPPL 3 _ 62 dt/ha _ 77 dt/ha _179 dt/ha Number of observations in data set = 1 2 (DF for Error = 3) D E P T H G V R D T K N (mg/kg) G V R D N03-N (mg/kg) G V R D NH4-N (mg/kg) G V R D T O T A L P (mg/kg) 0 - 15 c m Mean TIME sig. TIME sig. TIME TIME sig. AAPPL, and TIME* AAPPL sig. 15 - 30 c m Mean 102 11.5 9.7 TIME and Std . Dev. 49 19.2 25.5 AAPPL sig. 30 - 60 c m Mean 54 1.1 0.4 1577 Std . Dev. 35 1.5 0.3 180 60 - 90 c m Mean 56 TIME sig. 0.2 1530 Std . Dev. 11 0.1 217 90 -120 c m Mean 55 TIME sig. 0.2 1637 Std . Dev. 18 0.2 167 1 2 0 - 1 5 0 c m Mean 57 TIME, 0.2 1541 Std . Dev. 14 AAPPL and 0.3 132 TIME*AAPPL sig. Notes: All samples were analyzed by the GVRD Lab using laboratory methods described in Appendix O. The factorial model was used with the parameters AAPPL (application rate) and TIME (time). The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. TIME sig.' or 'AAPPL sig.' refers to significantly different means with respect to time or application rate. TLG93NTB.XLS PRINCETON DEMO. PROJECT - NITROGEN & TP - SIG. PARAMETERS Class Level Information C l a s s Levels Va lues TIME 3 _Oct . 1992 _Apr. 1993 _ S e p . 1993 A A P P L 3 _ 62 dt/ha _ 77 dt/ha _179 dt/ha Number of observat ions in data set = 12 (DF for Error = 3) Notes: Al l samples were analyzed by the G V R D Lab using laboratory methods descr ibed in Appendix O. The factorial model was used with the parameters A A P P L (application rate) and T IME (time). The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. Means followed by different letters are significantly different. 'TIME sig. ' or ' A A P P L sig. ' refers to significantly different means with respect to time or application rate. ' T I M E ' A A P P L sig. ' refers to a significant interaction term. 'N ' refers to the number of samples for average calculations. 'Std. D e v . ' refers to the sample standard deviation. TKN (mg/kg) DepthYTime: Oct. 1992 Apr. 1993 Sept. 1993 0 - 15cm 65 b 861 a 1254 a 15 - 30 cm average for all t imes: 102 30 - 60 cm average for all t imes: 54 60 - 90 cm average for all t imes: 56 90 -120 cm average for all t imes: 55 120-150 cm average for all t imes: 57 N03-N (mg/kg) DepthVTime: O c t 1992 Apr. 1993 Sept. 1993 0 - 15 cm 0.2 b 5.4 b 136 a 15- 30 cm average for all t imes: 11.5 30 - 60 cm average for all t imes: 1.1 60- 90 cm 0.1 b 0.3 ab 0.5 a 90 -120 cm 0.1 b 0.3 ab 0.5 a 120-150 cm * TIME, A A P P L , and T I M E ' A A P P L significant * S ince T IME, A A P P L , and T I M E * A A P P L are significant, the behaviour of N 0 3 - N concentrations in the tailings are not consistent over time, i.e. T IME and A A P P L are related. Refer to the table below for est imates of N 0 3 - N concentrations for different t imes and application rates. 1 2 0 - 1 5 0 cm N 0 3 - N (mg/kg): Level of Level of N 0 3 - N -T IME A A P P L N Mean Std. Dev. Oct. 1992 62 dt/ha 1 0.1 Oct. 1992 77 dt/ha 2 0.1 0 _Oct . 1992 _179 dt/ha 1 0.1 Apr. 1993 62 dt/ha 1 0.1 Apr. 1993 77 dt/ha 2 0.4 0.071 _Apr. 1993 _179 dt/ha 1 0.3 _ S e p . 1993 62 dt/ha 1 0.4 _ S e p . 1993 77 dt/ha 2 0.4 0.071 _ S e p . 1993 179 dt/ha 1 3.0 TL.G93NTC.XLS Page 1 PRINCETON DEMO. PROJECT - NITROGEN & TP - SIG. PARAMETERS 0 -15 cm NH4-N (mg/kg): Since T IME, A A P P L , and T I M E * A A P P L are significant, the behaviour of N H 4 - N concentrat ions in the tailings are not consistent over time, i.e. T IME and A A P P L are related. Refer to the table below for est imates of N H 4 - N concentrations for different t imes and application rates. Level of Level of N H 4 - N T IME A A P P L N Mean Std. Dev. _Oct . 1992 _ 62 dt/ha 1 0.1 _Oct . 1992 _ 77 dt/ha 2 1.5 1.6 _Oct . 1992 _179 dt/ha 1 0.2 _Apr. 1993 _ 62 dt/ha 1 67 _Apr. 1993 _ 77 dt/ha 2 215 14.1 _Apr. 1993 _179 dt/ha 1 347 _ S e p . 1993 62 dt/ha 1 0.3 _ S e p . 1993 77 dt/ha 2 1.4 1.3 _ S e p . 1993 179 dt/ha 1 5.2 TOTAL P (mg/kg) DepthVTime: Oct. 1992 Apr. 1993 Sept. 1993 0 - 15 cm 1432 b 1628 ab 1868 a 15- 30 cm * 1437 b 1548 ab 1655 a 30 - 60 cm average for all t imes: 1577 60 - 90 cm average for all t imes: 1530 90 -120 cm average for all t imes: 1637 120-150 cm average for all t imes: 1541 Total P concentration in the 15-30 cm layer is also dependent on the application rate. Refer to the table below for averages for the different application rates. 1 5 - 3 0 cm T O T A L P (mg/kg): Duncan Group. Mean N A A P P L 1685 1585 1332 179 dt/ha 77 dt/ha 62 dt/ha TLG93NTC.XLS - Page 2 APPENDIX M Field Experiment - Approximate Nitrogen Balance PRINCETON DEMONSTRATION PROJECT - APPROXIMATE NITROGEN BALANCE A s s u m e d dry densities for the nitrogen balance calculations: Applicat. Bulk Weight per Site: Rate: * Depth: Density/Site: 15 cm layer (dt/ha) (cm) (kg/m3) (tonnes/ha) Control 0 0-15 1340 2010 P2a 77 0-15 1210 1815 P2b 62 0-15 1190 1785 P3a 179 0-15 900 1350 P3b 77 0-15 1120 1680 All Sites 15-150 1340 2010 * Application rate of biosolids in dry tonne/ha The bulk densities are the average of five measurements per site. Notes on information contained in the nitrogen balance tables: Al l s a m p l e s w e r e a n a l y z e d by the G V R D L a b us ing laboratory me thods d e s c r i b e d in A p p e n d i x O . T h e detect ion limit concent ra t ion w a s u s e d for s a m p l e s with concent ra t ions be low the detec t ion limit. '% of T K N app l ied ' refers to the ratio of (60-150 c m Minera l N) to T K N - N app l ied (in percent) . '% of M in . N app l ied ' refers to the ratio of (60-150 c m Minera l N) to M inera l N app l ied (in percent ) . THNITBL.XLW - Page 1 218 PLOT 2a - NITROGEN BALANCE BASED ON COMPOSITE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 2a A p p l i c a t i o n Rate = 77 dt /ha Parameter = Soi l T K N T K N Appl ied = 2601 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. "93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 56 113 709 1287 1174 1030 1869 583 15-30 49 98 147 295 197 212 426 131 30-45 74 149 52 105 -44 100 201 96 45-60 74 149 52 105 -44 100 201 96 60-90 65 261 43 173 -88 80 322 149 90-120 57 229 17 68 -161 78 314 245 120-150 53 213 48 193 -20 72 289 96 Sum 0-60 509 1791 1283 2698 906 Parameter = Soi l A m m o n i u m Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 2.6 5.2 204.5 371.2 365.9 0.4 0.7 -370.4 15-30 0.1 0.2 77 154.8 154.6 0.2 0.4 -154.4 30-45 0.1 0.2 0.9 1.8 1.6 0.3 0.6 -1.2 45-60 0.1 0.2 0.9 1.8 1.6 0.3 0.6 -1.2 60-90 0.2 0.8 0.3 1.2 0.4 0.1 0.4 -0.8 90-120 0.3 1.2 0.1 0.4 -0.8 0.4 1.6 1.2 120-150 0.1 0.4 0.1 0.4 0.0 0.7 2.8 2.4 Sum 0-60 6 530 524 2 -527 Parameter = Soil Nitrate Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. "92 Post - 1 Apr. "93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 0.2 0.4 0.2 82 148.8 148.5 15-30 0.1 0.2 0.3 0.6 0.4 40 80.4 79.8 30-45 0.1 0.2 0.3 0.6 0.4 7.3 14.7 14.1 45-60 0.1 0.2 0.3 0.6 0.4 7.3 14.7 14.1 60-90 0.2 0.8 0.3 1.2 0.4 0.1 0.4 -0.8 90-120 0.1 0.4 0.1 0.4 0.0 0.4 1.6 1.2 120-150 0.1 0.4 0.4 1.6 1.2 0.4 1.6 0.0 Sum 0-60 0.8 2.2 1.4 258.6 256.4 Mineral N: 0-60 cm Mineral N 6.6 531.7 525.1 260.9 -270.8 60-150 cm Mineral N 4.0 5.2 1.2 8.4 3.2 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.15% 0.20% 0.05% 0.32% 0.12% % of Min. N Applied 0.3% 0.4% 0.1% 0.7% 0.2% THNITBL.XLW - Page 1 219 PLOT 2a - NITROGEN BALANCE BASED ON DISCRETE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 2a A p p l i c a t i o n Rate = 77 dt /ha Parameter = Soi l T K N T K N Appl ied = 2601 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 60 121 213 387 266 817 1483 1096 15-30 54 109 48 96 -12 84 169 72 30-45 60 121 40 80 -40 56 113 32 45-60 51 103 46 92 -10 61 123 30 60-90 50 201 80 322 121 53 213 -109 90-120 120-150 Sum 0-60 452 656 204 1887 1231 Parameter = Soil A m m o n i u m Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.3 0.6 28.8 52.3 51.7 0.5 0.9 -51.4 15-30 0.2 0.4 1.3 2.6 2.2 0.1 0.2 -2.4 30-45 0.4 0.8 0.1 0.2 -0.6 0.2 0.4 0.2 45-60 0.1 0.2 2.6 5.2 5.0 0.4 0.8 -4.4 60-90 0.2 0.8 0.3 1.2 0.4 0.6 2.4 1.2 90-120 120-150 Sum 0-60 2 60 58 2 -58 Parameter = Soi l Nitrate Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. '92 Post - 1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 0.1 0.2 63.2 114.7 114.5 63.7 115.6 0.9 15-30 0.1 0.2 9 .18.1 17.9 18.4 37.0 18.9 30-45 0.3 0.6 0.5 1.0 0.4 0.9 1.8 0.8 45-60 0.1 0.2 0.4 0.8 0.6 0.1 0.2 -0.6 60-90 0.1 0.4 1.1 4.4 4.0 0.1 0.4 -4.0 90-120 120-150 Sum 0-60 1.2 134.6 133.4 154.6 20.0 Mineral N: 0-60 cm Mineral N 3.2 194.9 191.7 156.9 -38.0 60-150 cm Mineral N 1.2 5.6 4.4 2.8 -2.8 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.05% 0.22% 0.17% 0.11% -0.11% % of Min. N Applied 0.1% 0.4% 0.3% 0.2% -0.2% THNITBL.XLW - Page 2 220 PLOT 2B - NITROGEN BALANCE BASED ON COMPOSITE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 2b A p p l i c a t i o n Rate = 62 dt /ha Parameter = Soi l T K N T K N Appl ied = 1616 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 95 191 457 816 625 426 760 -55 15-30 75 151 75 151 0 177 356 205 30-45 65 131 48 96 -34 94 189 92 45-60 65 131 48 96 -34 94 189 92 60-90 74 297 58 233 -64 75 302 68 90-120 40 161 100 402 241 58 233 -169 120-150 54 217 52 209 -8 61 245 36 Sum 0-60 603 1159 556 1494 335 Parameter = Soi l A m m o n i u m Nitrogen Mineral N Appl ied = 692 kg/ha Depth (cm) Pre Oct. '92 Post - 1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 66.7 119.1 118.9 0.3 0.5 -118.5 15-30 0.1 0.2 3.8 7.6 7.4 0.2 0.4 -7.2 30-45 0.4 0.8 0.3 0.6 -0.2 0.1 0.2 -0.4 45-60 0.4 0.8 0.3 0.6 -0.2 0.1 0.2 -0.4 60-90 0.1 0.4 0.3 1.2 0.8 0.1 0.4 -0.8 90 -120 0.3 1.2 0.3 1.2 0.0 0.1 0.4 -0.8 120 -150 0.3 1.2 0.3 1.2 0.0 0.1 0.4 -0.8 Sum 0-60 2 128 126 1 -127 Parameter = Soi l Nitrate Nitrogen Mineral N Appl ied = 692 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 1.9 3.4 3.2 2.8 5.0 1.6 15-30 0.1 0.2 0.4 0.8 0.6 7.1 14.3 13.5 30 - 45 0.1 0.2 0.1 0.2 0.0 0.7 1.4 1.2 45-60 0.1 0.2 0.1 0.2 0.0 0.7 1.4 1.2 60-90 0.1 0.4 0.1 0.4 0.0 0.4 1.6 1.2 90-120 0.1 0.4 0.3 1.2 0.8 0.4 1.6 0.4 120-150 0.1 0.4 0.1 0.4 0.0 0.4 1.6 1.2 Sum 0-60 0.8 4.6 3.8 22.1 17.5 Mineral N: 0-60 cm Mineral N 2.8 132.5 129.7 23.4 -109.1 60-150 cm Mineral N 4.0 5.6 1.6 6.0 0.4 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.25% 0.35% 0.10% 0.37% 0.02% % of Min. N Applied 0.58% 0.81% 0.23% 0.87% 0.06% THNITBL.XLW - Page 3 221 PLOT 2B - NITROGEN BALANCE BASED ON DISCRETE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 2b A p p l i c a t i o n Rate = 62 dt /ha Parameter = Soi l T K N T K N Appl ied = 1616 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 81 163 278 496 333 339 605 109 15-30 77 155 59 119 -36 86 173 54 30-45 84 169 74 149 -20 99 199 50 45-60 79 159 48 96 -62 91 183 86 60-90 92 370 65 261 -109 86 346 84 90-120 120-150 Sum 0-60 645 860 215 1160 300 Parameter = Soi l A m m o n i u m Nitrogen Mineral N Appl ied = 692 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.3 0.6 16.5 29.5 28.8 0.1 0.2 -29.3 15-30 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.0 30-45 0.2 0.4 0.1 0.2 -0.2 0.1 0.2 0.0 45-60 0.3 0.6 0.1 0.2 -0.4 0.2 0.4 0.2 60-90 0.4 1.6 0.4 1.6 0.0 0.1 0.4 -1.2 90-120 120-150 Sum 0-60 2 30 28 1 -29 Parameter = Soi l Nitrate Nitrogen Mineral N Appl ied = 692 kg/ha Depth (cm) Pre Oct. '92 Post - 1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 19.5 34.8 34.6 0.5 0.9 -33.9 15-30 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.0 30-45 0.2 0.4 0.1 0.2 -0.2 0.2 0.4 0.2 45-60 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.0 60-90 0.1 0.4 3.4 13.7 13.3 0.2 0.8 -12.9 90-120 120-150 Sum 0-60 1.0 35.4 34.4 1.7 -33.7 Mineral N: 0-60 cm Mineral N 2.8 65.5 62.7 2.7 -62.8 60-150 cm Mineral N 2.0 15.3 13.3 1.2 -14.1 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.12% 0.95% 0.82% 0.07% -0.87% % of Min. N Applied 0.3% 2.2% 1.9% 0.2% -2.0% THNITBL.XLW - Page 4 222 PLOT 3A - NITROGEN BALANCE BASED ON COMPOSITE SOIL SAMPLES Princeton Tailings - Plot 3a Application Rate = 179 dt/ha Parameter = Soil TKN TKN Applied = 6048 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 34 68 1098 1482 1414 2100 2835 1353 15-30 52 105 73 147 42 78 157 10 30-45 62 125 33 66 -58 13 26 -40 45-60 62 125 33 66 -58 13 26 -40 60-90 35 141 33 133 -8 67 269 137 90-120 61 245 39 157 -88 59 237 80 120-150 56 225 40 161 -64 124 498 338 Sum 0-60 422 1762 1340 3044 1282 Parameter = Soil Ammonium Nitrogen Mineral N Applied = 2995 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept.'93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 0.2 0.4 346.6 467.9 467.5 5.2 7.0 -460.9 15-30 0.3 0.6 19.5 39.2 38.6 0.1 0.2 -39.0 30-45 0.3 0.6 1 2.0 1.4 0.3 0.6 -1.4 45-60 0.3 0.6 1 2.0 1.4 0.3 0.6 -1.4 60-90 0.1 0.4 0.7 2.8 2.4 0.3 1.2 -1.6 90-120 0.1 0.4 0.4 1.6 1.2 0.4 1.6 0.0 120-150 0.1 0.4 0.1 0.4 0.0 0.4 1.6 1.2 Sum 0-60 2 511 509 8 -503 Parameter = Soil Nitrate Nitrogen Mineral N Applied = 2995 kg/ha Depth (cm) Pre Oct. '92 Post - 1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 0.1 0.2 5.2 7.0 6.8 301 406.4 399.3 15-30 0.1 0.2 0.3 0.6 0.4 1.8 3.6 3.0 30 - 45 0.1 0.2 0.1 0.2 0.0 0.3 0.6 0.4 45-60 0.1 0.2 0.1 0.2 0.0 0.3 0.6 0.4 60-90 0.1 0.4 0.3 1.2 0.8 1 4.0 2.8 90-120 0.1 0.4 0.3 1.2 0.8 0.7 2.8 1.6 120-150 0.1 0.4 0.3 1.2 0.8 3 12.1 10.9 Sum 0-60 0.8 8.0 7.2 411.2 403.1 Mineral N: 0-60 cm Mineral N 3.0 519.2 516.1 419.6 -99.5 60-150 cm Mineral N 2.4 8.4 6.0 23.3 14.9 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.04% 0.14% 0.10% 0.39% 0.25% % of Min. N Applied 0.08% 0.28% 0.20% 0.78% 0.50% THNITBL.XLW - Page 5 223 PLOT 3A - NITROGEN BALANCE BASED ON DISCRETE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 3a A p p l i c a t i o n Rate = 179 dt /ha Parameter = Soi l T K N T K N Appl ied = 6048 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 41.7 84 1108.5 1496 1413 1660 2241 745 15-30 49.4 99 32.2 65 -35 98.7 198. 134 30-45 53.8 108 29.7 60 -48 72.7 146 86 45-60 58.6 118 28 56 -62 72 145 88 60-90 54.3 218 23.8 96 -123 87 350 254 90-120 120-150 Sum 0-60 409 1677 1268 2730 1053 Parameter = Soi l A m m o n i u m Nitrogen Mineral N Appl ied = 2995 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. "93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.2 0.4 216.6 292.4 292.0 1.1 1.5 -290.9 15-30 0.1 0.2 3.3 6.6 6.4 0.1 0.2 -6.4 30-45 0.2 0.4 5.2 10.5 10.1 0.2 0.4 -10.1 45-60 0.2 0.4 0.6 1.2 0.8 0.2 0.4 -0.8 60-90 0.2 0.8 0.2 0.8 0.0 0.2 0.8 0.0 90-120 120-150 Sum 0-60 1 311 309 2 -308 Parameter = Soil Nitrate Nitrogen Mineral N Appl ied = 2995 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 95.4 128.8 128.6 178.3 240.7 111.9 15-30 0.1 0.2 0.2 0.4 0.2 29.7 59.7 59.3 30-45 0.1 0.2 4.2 8.4 8.2 9.2 18.5 10.1 45-60 0.1 0.2 0.2 0.4 0.2 1.6 3.2 2.8 60-90 0.1 0.4 0.2 0.8 0.4 2.6 10.5 9.6 90-120 120-150 Sum 0-60 0.8 138.0 137.2 322.1 184.1 Mineral N: 0-60 cm Mineral N 2.2 448.7 446.5 324.6 -124.1 60-150 cm Mineral N 1.2 1.6 0.4 11.3 9.6 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.02% 0.03% 0.01% 0.19% 0.16% % of Min. N Applied 0.04% 0.05% 0.01% 0.38% 0.32% THNITBL.XLW - Page 6 224 PLOT 3B - NITROGEN BALANCE BASED ON COMPOSITE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 3b A p p l i c a t i o n Rate = 77 dt /ha Parameter = Soi l T K N T K N Appl ied = 2601 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 75 151 1180 1982 1832 1460 2453 470 15-30 50 101 142 285 185 93 187 -98 30-45 60 121 42 84 -36 16 32 -52 45-60 60 121 42 84 -36 16 32 -52 60-90 55 221 30 121 -101 59 237 117 90-120 56 225 45 181 -44 45 181 0 120-150 45 181 33 133 -48 41 165 32 Sum 0-60 492 2437 1944 2704 267 Parameter = Soil A m m o n i u m Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.4 0.8 225 378.0 377.2 2.3 3.9 -374.1 15-30 0.1 0.2 14.5 29.1 28.9 0.1 0.2 -28.9 30-45 0.1 0.2 0.3 0.6 0.4 0.1 0.2 -0.4 45-60 0.1 0.2 0.3 0.6 0.4 0.1 0.2 -0.4 60-90 0.1 0.4 0.1 0.4 0.0 0.3 1.2 0.8 90 -120 0.1 0.4 0.4 1.6 1.2 0.1 0.4 -1.2 120-150 0.1 0.4 0.3 1.2 0.8 0.1 0.4 -0.8 Sum 0-60 1 408 407 4 -404 Parameter = Soi l Nitrate Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.3 0.6 14.3 24.0 23.4 157 263.8 239.7 15-30 0.1 0.2 0.3 0.6 0.4 87 174.9 174.3 30 - 45 0.1 0.2 0.1 0.2 0.0 3.7 7.4 7.2 45-60 0.1 0.2 0.1 0.2 0.0 3.7 7.4 7.2 60-90 0.1 0.4 0.3 1.2 0.8 0.4 1.6 0.4 90-120 0.1 0.4 0.4 1.6 1.2 0.4 1.6 0.0 120-150 0.1 0.4 0.3 1.2 0.8 0.3 1.2 0.0 Sum 0-60 1.2 25.0 23.8 453.5 428.5 Mineral N: 0-60 cm Mineral N 2.6 433.4 430.8 458.0 24.6 60-150 cm Mineral N 2.4 7.2 4.8 6.4 -0.8 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.09% 0.28% 0.19% 0.25% -0.03% % of Min. N Applied 0.2% 0.6% 0.4% 0.5% -0.1% THNITBL.XLW - Page 7 225 PLOT 3B - NITROGEN BALANCE BASED ON DISCRETE SOIL SAMPLES Pr ince ton T a i l i n g s - P lot 3b A p p l i c a t i o n Rate = 77 dt /ha Parameter = Soil T K N T K N A p p l i e d = 2601 kg /ha Depth (cm) Pre Oct. "92 Post -1 Apr. '93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0-15 68 137 1336 2244 2108 1295 2176 -69 15-30 53 107 31 62 -44 72 145 82 30-45 57 115 33 66 -48 86 173 107 45-60 60 121 34 68 -52 84 169 101 60-90 40 161 23 92 -68 68 273 181 90 -120 120 -150 Sum 0-60 478 2441 1963 2662 221 Parameter = Soi l A m m o n i u m Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. '92 Post -1 Apr. "93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.2 0.4 286.2 480.8 480.4 0.2 0.3 -480.5 15-30 0.3 0.6 0.1 0.2 -0.4 0.1 0.2 0.0 30-45 0.1 0.2 0.4 0.8 0.6 0.2 0.4 -0.4 45-60 0.1 0.2 0.1 0.2 0.0 0.1 0.2 0.0 60-90 0.1 0.4 0.1 0.4 0.0 0.1 0.4 0.0 90 -120 120 -150 Sum 0-60 1 482 481 1 -481 Parameter = Soil Nitrate Nitrogen Mineral N Appl ied = 1288 kg/ha Depth (cm) Pre Oct. "92 Post - 1 Apr. "93 Post-1 minus Pre Post - 2 Sept. '93 Post-2 minus Post-1 mg/kg kg/ha mg/kg kg/ha Diff. kg/ha mg/kg kg/ha Diff. kg/ha 0 -15 0.1 0.2 475.6 799.0 798.8 99.5 167.2 -631.8 15-30 0.1 0.2 0.2 0.4 0.2 48 96.5 96.1 30-45 0.1 0.2 0.4 0.8 0.6 3.1 6.2 5.4 45-60 0.1 0.2 0.1 0.2 0.0 0.4 0.8 0.6 60-90 0.1 0.4 0.1 0.4 0.0 0.4 1.6 1.2 90-120 120-150 Sum 0-60 0.8 800.4 799.6 270.7 -529.7 Mineral N: 0-60 cm Mineral N 2.2 1282.4 1280.2 271.8 -1010.6 60-150 cm Mineral N 0.8 0.8 0.0 2.0 1.2 Ratio of (60-150 cm Mineral N) to TKN applied (or Mineral N applied): % of TKN Applied 0.03% 0.03% 0.00% 0.08% 0.05% % of Min. N Applied 0.06% 0.06% 0.00% 0.16% 0.09% THNITBL.XLW - Page 8 APPENDIX M Field Experiment - Nitrogen & Phosphorus Field Data 227 E Q > C3 & S o = z < 228 co < oo or o co Q Q H C O o Q. E O O < a a _i UJ LU o o or o UJ -> o ar a. C O z o E UJ a z o I-U J o z or o. E Q > CD o = z < 229 E Q a. > S 3 230 E « co i E CO CO a. 0> . CO E CO CO a E . E CO ' CO I E CO ' CO I o a., E ! o I a • E o CO CO a 8 t : x < _i Ul -s _l p 21 z CN o z otl O 9 E TES ? CO •a CO z O CO z CO _ l O) < J£ 1- o> E EN = ROG o CO c z z E I z z o o c E o E < 2 * J AL cen y- c O o 1- o •l<l a. a> . CO E a > C5 a . E 231 o l ! o tf) U J < tf) U J H tf) O a. E O o < Q Q _ J U J o I: o tf) D DC O X 0. tf) o X 0. o U J - > o a. 0. z o tf) U J a U J o a: a. •o o> cn => K 0 1 Q . (0 O X a. 1 I CM O) P 0> o> Jjj ?:& i .a < v O J= CD I f Is CO (0 ?131 1 1 8 8 , a.2 ^  co a -S 5 8 co 2 £ o t- w | 1 c • o - 5- i 'C c c -c CL CO CO o e a. | S 2 £ 8 % % 5 S 5 10 10 u •g -g « S » E E c I ecu • o 9- E <• « -2 E 5 T - N 3 (D « J , J , ~ 5 2 ? t_ O O u. 0. 0 , D. < APPENDIX M Field Experiment - Nitrogen Averages for Discrete Sampl 233 O o >< 8 Q. .E « ra H i ra ±= c= E £1 . 2 <3 -c u> O CO OL -a > 0) O £ CO > £ I TJ « CI) 01 S 8 C O ^= 234 co £ S.E < T3 • 5 E 3 C n 2 "> B - 1 CO O 0) a: T I > CO O £ •D (0 CO CO S o 235 E 5 •= E t5 £ CO — 3 C x> .2 ra U - 1 co O a> or T3 > CO O £ £1 n T3 CO CO co N 3 236 a. .E </> to •o ±= o c p I I o a> '•S £ E E co — 3 c .S « K CO O CO Q: TJ > co C3 £ s 8 237 APPENDIX M Field Experiment - Long Form of Nitrogen & Phosphorus Data Analysis PRINCETON DEMO. PROJECT - NITROGEN & TP - LONG FORM OF DATA ANALYSIS Class Level Information Class Levels Values TIME 3 _Oct. 1992 _Apr. 1993 _Sep. 1993 AAPPL 3 _ 62 dt/ha _ 77 dt/ha _179 dt/ha Number of observations in data set =12 (DF for Error = 3) Notes on the Analytical Results: All samples were analyzed by the GVRD Lab. The factorial model was used with the parameters AAPPL (application rate) and TIME (time). R-Square' refers to the RA2 of the model y = TIME|AAPPL in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. 0-15 cm LAYER: TKN TIME significant NH4-N TIME, AAPPL, AND TIME*AAPPL significant N03-N TIME significant Total P TIME significant 0 -15 cm TKN, mg/kg: Duncan Grouping Mean N TIME A 1254 4 _Sep. 1993 A 861 4 Apr. 1993 B 65 4 _Oct. 1992 0- 15 cm NH4-N, mg/kg: Level of Level of NH4-N TIME AAPPL N Mean SD _Oct. 1992 _ 62 dt/ha 1 0.1 Oct. 1992 77 dt/ha 2 1.5 1.6 _Oct. 1992 _179 dt/ha 1 0.2 Apr. 1993 _ 62 dt/ha 1 67 Apr. 1993 _ 77 dt/ha 2 215 14.1 _Apr. 1993 _179 dt/ha 1 347 _Sep. 1993 _ 62 dt/ha 1 0.3 _Sep. 1993 _ 77 dt/ha 2 1.4 1.3 _Sep. 1993 _179 dt/ha 1 5.2 0- 15 cm N03-N, mg/kg Duncan Grouping Mean N TIME A 136 4 Sep. 1993 B 5.4 4 _Apr. 1993 B 0.2 4 _Oct. 1992 0- 15 cm Total P, mg/kg: Duncan Grouping Mean N TIME A 1868 4 Sep. 1993 B A 1628 4 _Apr. 1993 B 1432 4 Oct. 1992 TLG93NCA.XLS Page 1 PRINCETON DEMO. PROJECT - NITROGEN & TP - LONG FORM OF DATA ANALYSIS 15-30 cm: R-Square: C.V.: Std. Dev.: Mean: TKN, mg/kg 0.781 48 48.6 101.9 NH4-N, mg/kg 0.639 264 25.5 9.7 N03-N, mg/kg 0.856 167 19.2 11.5 Total P TIME and AAPPL significant 15-30 cm Total P, mg/kg: Duncan Grouping Mean N TIME A 1655 4 _Sep. 1993 B A 1548 4 Apr. 1993 B 1437 4 _Oct. 1992 Duncan Grouping Mean N TIME A 1685 3 _179 dt/ha A 1585 6 _ 77 dt/ha B 1332 3 _ 62 dt/ha 30 - 60 cm: R-Square: C.V.: Std. Dev.: Mean: TKN, mg/kg 0.576 64.4 35 54.4 NH4-N, mg/kg 0.798 73.8 0.3 0.4 N03-N, mg/kg 0.879 136 1.5 1.1 Total P, mg/kg 0.777 11.4 180 1577 60 - 90 cm: R-Square: C.V.: Std. Dev.: Mean: TKN, mg/kg 0.892 19.4 10.9 56.2 NH4-N, mg/kg 0.827 60.6 0.1 0.2 N03-N, TIME significant Total P, mg/kg 0.634 14.2 217 1530 60-90 cm N03-N, mg/kg: Duncan Grouping Mean N TIME A 0.5 4 _Sep. 1993 B A 0.3 4 _Apr. 1993 B 0.1 4 _Oct. 1992 90-120 cm: R-Square: C.V.: Std. Dev.: Mean: TKN, mg/kg 0.802 32.4 17.7 54.6 NH4-N, mg/kg 0.483 84.9 0.2 0.2 N03-N, TIME significant Total P, mg/kg 0.339 10.2 167 1637 90- 120 cm N03/2-N, mg/kg: Duncan Grouping Mean N TIME A 0.5 4 Sep. 1993 B A 0.3 4 Apr. 1993 B 0.1 4 Oct. 1992 TLG93NCA.XLS - Page 2 PRINCETON DEMO. PROJECT - NITROGEN & TP - LONG FORM OF DATA ANALYSIS 120-150 cm: R-Square: C.V.: Std. Dev.: Mean: TKN, mg/kg 0.898 26 14.4 56.6 NH4-N, mg/kg 0.477 115 0.3 0.2 N03-N TIME, AAPPL AND TIME*AAPPL significant Total P, mg/kg 0.699 8.6 132 1541 120- 150 cm N03-N, mg/kg: Level of Level of N03-N -TIME AAPPL N Mean SD _Oct. 1992 62 dt/ha 1 0.1 •_Oct. 1992 77 dt/ha 2 0.1 0 _Oct. 1992 _179 dt/ha 1 0.1 _Apr. 1993 62 dt/ha 1 0.1 _Apr. 1993 _ 77 dt/ha 2 0.4 0.071 _Apr. 1993 _179 dt/ha 1 0.3 _Sep. 1993 _ 62 dt/ha 1 0.4 _Sep. 1993 _ 77 dt/ha 2 0.4 0.071 _Sep. 1993 _179 dt/ha 1 3.0 TLG93NCA.XLS - Page 3 A P P E N D I X N Field Experiment - Total Metals in Soil 242 PRINCETON DEMONSTRATION PROJECT - METALS - OVERVIEW C l a s s Level Information C lass Levels Va lues TIME 3 _Oct . 1992 _Apr. 1993 _ S e p . 1993 A A P P L 2 _ 77 dt/ha J 79 dt/ha Number of observations in data set = 6 (DF for Error = 1) Metal: Selenium Mercury Arsenic Aluminum Cadmium Chromium (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) Depth: 0 -15 cm Mean 0.5 T IME <5.0 21633 < 0.5 37.8 Std. Dev. 0.1 sig. 1297 2.2 15 - 30 cm Mean 0.5 <0.2 < 5.0 28450 <0.5 48.7 Std. Dev. 0.1 1911 3.3 30 - 60 cm Mean 0.4 <0.2 T IME 33333 0.5 52.3 Std. Dev. 0.1 sig. 3747 0.04 1.6 60 - 90 cm Mean 0.4 <0.2 3.8 32017 0.6 53.8 Std. Dev. 0.1 2.7 2763 0.3 4.4 90 -120 cm Mean 0.3 <0.2 T IME A A P P L 0.5 55.7 Std. Dev. 0.07 sig. s ig. 0.3 2.2 120-150 cm Mean 0.32 < 0.2 2.9 A A P P L 0.35 54.2 Std. Dev. 0.04 0.6 sig. 0.04 1.1 Normal Range: ' Typical Concent ration: * 0.1 - 2 0.5 0.02 - 0.2 0.05 1 - 50 5 1 0 0 0 0 -200000 50000 0.01 - 7 0.06 5 - 1000 20 C C M E : ** 2 0.8 20 3 250 Notes: Bohn e ta l . , 1985 ** lowest of the remediation limits for agricultural or residential soi ls set by the Canad ian Counci l of Ministers of the Environment (1991) Cobalt , nickel , and z inc concentrations remained relatively unchanged. Lead concentration w a s c lose to the Limit of Detection and tended to be lower after treatment. Molybdenum concentration was below the Limit of Detection. Only the main effects of A A P P L and TIME (i.e. no interactions) were examined in the analysis. Al l samples were analyzed by the G V R D Lab. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. D e v . ' refers to the sample standard deviation. TLGMTCB.XLS P R I N C E T O N D E M O N S T R A T I O N P R O J E C T - M E T A L S - SIGNIF. P A R A M E T E R S 0 - 15 cm Mercury (mg/kg): Duncan Grouping A B B 30 - 60 cm Arsenic (mg/kg): Duncan Grouping A B B 90- 120 cm Arsenic (As), mg/kg: Duncan Grouping A B C 90- 120 cm Aluminum (mg/kg): Duncan Grouping A B 120 - 150 cm Aluminum (mg/kg): Duncan Grouping A B Mean TIME 0.4 0.1 0.1 _Sep. 1993 _Oct. 1992 _Apr. 1993 Mean TIME 5.0 3.0 2.5 _Apr. 1993 _Oct. 1992 _Sep. 1993 Mean TIME 5.0 3.0 2.5 _Apr. 1993 _Oct. 1992 _Sep. 1993 Mean AAPPL 33500 26767 _ 77 dt/ha 179 dt/ha Mean AAPPL 30333 24433 _ 77 dt/ha 179 dt/ha 244 o Q co o v co ~ CO 1.1 s ° o CO !>!> E o ^ N O 8§ CN II CD 0 C o> ra Q O C J "o 1 I 5-§1 i s CD .S m o o co o = 10 S o no E Jtf U> jz o> C M 11 ii O Lfi _ l tz '—' o cz o co o •p £ ro cu => Q O — H— 0 o 1 i CM CO at in a. O 0) LO LO m CO LO LO a (0 V V V V V V n en ID L _ O CL LO LO 1 0 LO LO LO a. < V V V V CM at CO £ CO 0 . 0 O LO 1 0 1 0 co CD CD V V V V V V CM CO *-t 01 CO 0 ep LO LO LO LO LO LO a to V V V V V V o CO 1 CO 5 co 0 a. 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E O) CM II " O 8S _ l c .2 o CO T> I B ro cu => Q a 14— »*— o o £ I o I-s CD o ro Z J o ST CJ Q ro 0 ^ - 1 o J) cO CO M 1 -o ° O CO E cn -— 0 ) | , f c o CM 1 1 ii a 8S —I c •—• o o ro TJ £ ro a o "4— H — 0 o 1 I PRINCETON DEMO. P R O J E C T - METALS - LONG FORM OF ANALYSIS C l a s s Level Information C l a s s Leve ls V a l u e s T I M E 3 _Oct . 1992 _Apr . 1993 _ S e p . 1993 A A P P L 2 _ 77 dt/ha _179 dt/ha Number of observat ions in data set = 6 (DF for Error = 1) Notes: Only the main effects of AAPPL and TIME (i.e. no interactions) were examined in the data analysis. All samples were analyzed by the GVRD Lab. R-Square' refers to the RA2 of the model 'y = TIME AAPPL' in the statistical SAS procedure GLM. The Duncan multiple range test at the 0.05 level of probability was used to determine significantly different means. 'Std. Dev.' refers to the sample standard deviation. 'C.V.' refers to the coefficient of variation in percent. 'N' refers to the number of samples for average calculations. Means preceded by different letters are significantly different. R-Square: C.V.: Std. Dev.: Mean: 0 - 1 5 cm L A Y E R : Selenium, mg/kg 0.438 26.2 0.1 0.5 Mercury T I M E signif icant Arsenic, mg/kg all va lues <5 .0 Aluminum, mg/kg 0.949 6 1297 21633 Cadmium, mg/kg all va lues <0 .5 Chromium, mg/kg 0.929 5.7 2.2 37.8 15-30 cm L A Y E R : Selenium, mg/kg 0.929 14.1 0.1 0.5 Mercury, mg/kg all va lues <0 .2 Arsenic, mg/kg all va lues <5 .0 Aluminum, mg/kg 0.727 6.7 1911 28450 Cadmium, mg/kg all va lues <0 .5 Chromium, mg/kg 0.856 6.9 3.3 48.7 30 - 60 cm L A Y E R : Selenium, mg/kg 0.794 24.9 0.1 0.4 Mercury, mg/kg all va lues <0 .2 Arsenic T I M E signif icant Aluminum, mg/kg 0.457 11.2 3747 33333 Cadmium, mg/kg 0.905 9.1 0.04 0.5 Chromium, mg/kg 0.789 3.1 1.6 52.3 60 - 90 cm L A Y E R : Selenium, mg/kg 0.793 . 18.4 0.1 0.4 Mercury, mg/kg all va lues <0 .2 Arsenic, mg/kg 0.578 70.8 2.7 3.8 Aluminum, mg/kg 0.849 8.6 2763 32017 Cadmium, mg/kg 0.706 45.9 0.3 0.6 Chromium, mg/kg 0.479 8.2 4.4 53.8 TLGMTCA.XLS - Page 1 PRINCETON DEMO. P R O J E C T - METALS - LONG FORM OF ANALYSIS R-Square: C.V.: Std. Dev.: Mean: 90-120 cm L A Y E R : Selenium, mg/kg 0.882 12.9 0.07 0.3 Mercury, mg/kg all va lues <0 .2 Arsenic T I M E signif icant Aluminum A A P P L signif icant Cadmium, mg/kg 0.527 56.7 0.3 0.5 Chromium, mg/kg 0.659 3.9 2.2 55.7 120-150 cm L A Y E R : Selenium, mg/kg 0.6 12.9 0.04 0.32 Mercury, mg/kg all va lues <0 .2 Arsenic, mg/kg 0.561 21 0.61 2.9 Aluminum A A P P L signif icant Cadmium, mg/kg 0.905 11.7 0.04 0.35 Chromium, mg/kg 0.785 2 1.08 54.2 0 - 1 5 cm Mercury (Hg), mg/kg: Duncan Group ing M e a n N T I M E A 0.35 2 _ S e p . 1993 B 0.1 2 _Oct . 1992 B 0.1 2 _Apr . 1993 30 - 60 cm A r s e n i c (As), mg/kg: Duncan Group ing M e a n N T I M E A 5 2 _Apr . 1993 B 3 2 _Oc t . 1992 B 2.5 2 _ S e p . 1993 9 0 - 120 c m A r s e n i c (As), mg/kg: Duncan Group ing M e a n N T I M E A 5 2 _Apr . 1993 B 3 2 _Oct . 1992 C 2.5 2 _ S e p . 1993 9 0 - 120 c m A luminum (Al), mg/kg: Duncan Group ing M e a n N A A P P L A 33500 3 _ 77 dt/ha B 26767 3 _179 dt/ha 120 - 150 cm A luminum (Al), mg/kg: Duncan Group ing M e a n N A A P P L A 30333 3 _ 77 dt/ha B 24433 3 _179 dt/ha TLGMTCA.XLS - Page 2 A P P E N D I X O Laboratory Methods 250 Laboratory Methods used in the Princeton Demonstration Project and the Leaching Experiments: Parameter: pH: B I O E : p H of filtrate of a 1:2 w/v soi l :DI slurry is m e a s u r e d with a p H meter. T h e resul t is repor ted a s 1:2 p H . N O R W : p H of a 1:2 v/v so ihwater slurry is de te rm ined with a p H meter ( M S S 4.13). Electrical Conductivity: B I O E : E C of filtrate of a 1:2 w/v slurry is m e a s u r e d us ing a n E C meter. T h e result is repor ted a s 1:2 E C ( M S A 10-2). N O R W : E C is m e a s u r e d o n wa te r p h a s e of a 1:2 v/v D l extract ion us ing a n E C meter . T h e m e a s u r e d E C va lue is conve r ted to a sa tura ted extract equ iva len t E C by mult ip ly ing by 2 ( M S S 4.13). Total Kjeldahl Nitrogen: B I O E : G V R D : N O R W : P e r c o l a t e W a t e r A n a l y s i s : D iges t ion of 10 m L perco la te wa te r with 5 m L H 2 S 0 4 a n d p o t a s s i u m su l fa te /copper su l fa te / s e l e n i u m d iox ide mixture fo l lowed by the T e c h n i c o n sa l icy la te /hypoch lor i te co lor imet r ic determinat ion (660 nm). So i l A n a l y s i s : D iges t ion of 2 -2 .5 g s a m p l e with 5 -10 m L H 2 S 0 4 a n d p o t a s s i u m su l fa te /copper su l fa te /se len ium d iox ide mixture. S a m e color imetr ic determinat ion a s a b o v e . So i l A n a l y s i s : D iges t ion of 2 .5 g s a m p l e with 5 0 m L M e r c u r i c sul fate ( H g O + H 2 S 0 4 + Dl) a n d p o t a s s i u m sul fate ( K 2 S 0 4 + H 2 S 0 4 + Dl) so lut ion in 8 0 0 m L Kje ldahl f lask. Co lo r imet r i c determinat ion with sa l icy la te /hypoch lor i te me thod ( A P H A (1989); L M M 10 -107 -06 -2 -F ) . P lan t T i s s u e A n a l y s i s : D iges t ion with H 2 S 0 4 a n d p o t a s s i u m sul fa te/ c o p p e r su l fa te /se len ium mixture. Determina t ion of N H 4 + by s t e a m disti l lat ion a n d titration. T h e result is repor ted a s % N . A m m o n i u m : B I O E : G V R D : N O R W : P e r c o l a t e W a t e r A n a l y s i s : N H 4 + is m e a s u r e d us ing the s o d i u m pheno la te / sod ium hypoch lo r i te /po tass ium s o d i u m tartrate co lou r me thod (Techn i con AAII 9 8 - 7 0 W ; 6 3 0 nm). So i l A n a l y s i s : Ext rac t ion (1:10 w/v) with 2 M po tass ium chlor ide. S a m e determinat ion me thod a s a b o v e . So i l A n a l y s i s : Ext rac t ion (1:10 w/v) with 2 M p o t a s s i u m ch lor ide. N H 4 + is m e a s u r e d with the L a c h a t s o d i u m pheno la te / sod ium hypochlor i te me thod ( L M M 1 0 - 1 0 7 - 0 6 - 1 - B ; M S A 33-7) . So i l A n a l y s i s : Ext rac t ion (1:10 w/v) with 1 M po tass ium ch lor ide. N H 4 + is m e a s u r e d with the T e c h n i c o n s o d i u m pheno la te /hypoch lo r i te /po tass ium s o d i u m tartrate co lor imetr ic me thod . Note: BIOE Bio-Resource Engineering Laboratory, U.B.C., Vancouver, B.C. GVRD Greater Vancouver Regional District Laboratory,Burnaby, B.C. NORW Norwest Soil Research Inc. Laboratory, Langley, B.C. 251 Nitrate: B I O E : G V R D : N O R W : P e r c o l a t e W a t e r A n a l y s i s : N 0 3 " is de te rm ined by c a d m i u m reduct ion a n d co lour react ion wi th su l fan i lamide a n d 1-naphthy le thy lened iamine d ihydroch lor ide (Techn i con AAII 1 0 0 - 7 0 W ; 5 2 0 nm). So i l A n a l y s i s : Ex t rac t ion (1:10 w/v) with 2 M po tass ium chlor ide. S a m e color imetr ic de terminat ion me thod a s a b o v e . So i l A n a l y s i s : Ex t rac t ion (1:10 w/v) with 2 M po tass ium chlor ide. N 0 3 " is de te rm ined by c a d m i u m reduct ion a n d co lou r react ion with su l fan i lamide a n d 1-naphthy le thy lened iamine d ihydroch lo r ide (520 nm) ( L M M 10 -107 -04 -1 -B ; M S A 33-8) . So i l A n a l y s i s : Ex t rac t ion (1:10 w/v) with 1 M p o t a s s i u m ch lor ide. N 0 3 " is de te rm ined by c a d m i u m reduct ion a n d co lour react ion with su lphan i l am ide a n d naph thy le thy lened iamine ( A P H A 4 5 0 0 ) . P lan t T i s s u e A n a l y s i s : Ext rac t ion (1:20 w/v) with 1 M p o t a s s i u m ch lor ide. N 0 3 " is de te rm ined by c a d m i u m reduct ion a n d co lou r react ion with su lphan i l am ide a n d naph thy le thy lened iamine . T h e resul t is repor ted in % N 0 3 - N . Available Phosphorus : B I O E : Ext rac t ion (1:20 w/v) with 0.5 M N a H C 0 3 at p H 8.5 ( O l s e n - P extr.). M a n u a l de terminat ion of P with a m m o n i u m paramo lybda te /an t imony p o t a s s i u m tar t ra te /ascorb ic ac i d me thod ( M S A 24-5) . N O R W : Ext rac t ion (1:10 w/v) with 0 .03 N a m m o n i u m f luor ide/0 .025 N hydroch lo r i c a c i d (B ray -P1 extr.). P is m e a s u r e d us ing the T e c h n i c o n a m m o n i u m mo lybda te /an t imony p o t a s s i u m tar t ra te /ascorb ic ac i d me thod S S W 2 6 : 1 7 8 ) . Total Phosphorus : B I O E : P e r c o l a t e W a t e r A n a l y s i s : D iges t ion of 10 m L s a m p l e with 1 m L H 2 S 0 4 a n d 5 m L H N 0 3 . Determina t ion of T P by S t a n n o u s Ch lo r i de M e t h o d (690 nm) ( A P H A (1989) 4 2 4 C & E) . G V R D : So i l A n a l y s i s : D iges t ion of 2 .5 g s a m p l e with 2 5 m L H N 0 3 a n d 10 m L H 2 S 0 4 . De te rmina t ion of T P by S t a n n o u s Ch lo r i de me thod . N O R W : P lan t T i s s u e A n a l y s i s : Ni t r ic /perchlor ic ac i d d iges t ion . Determinat ion of T P by T e c h n i c o n a m m o n i u n mo lyda te /an t imony p o t a s s i u m tar t ra te /ascorb ic ac id me thod . C a 2 + , M g 2 + , K \ N a + : N O R W : So i l A n a l y s i s ( e x c h a n g e a b l e cat ions) : Ex t rac t ion (1:5 w/v) with 1 M neutral a m m o n i u m aceta te . E x c h a n g e a b l e ca t ions a re de te rm ined by A t o m i c Abso rp t i on spec t rophotomet ry (A .A .S . ) ( M S A 9-3). Boron: N O R W : A v a i l a b l e B in so i l : Hot wa te r ext ract ion (1:4 w/v). Determinat ion of B with T e c h n i c o n a z o m e t h i n e - H me thod ( M S A 2 5 - 5 & 25-9) . Note: BIOE Bio-Resource Engineering Laboratory, U.B.C, Vancouver, B.C. GVRD Greater Vancouver Regional District Laboratory.Burnaby, B.C. NORW Norwest Soil Research Inc. Laboratory, Langley, B.C. 252 Sulfate: N O R W : Ext rac t ion (1:2 w/v) with 0.01 M C a l c i u m ch lor ide. S 0 4 2 " is m e a s u r e d turbidimetr ical ly. Sulfur: N O R W : Ni t r ic /perchlor ic ac i d d iges t ion . Turb id imetr ica l determinat ion of S with B a r i u m ch lor ide . Zinc, Iron, Copper , Manganese: N O R W : A v a i l a b l e nutr ients in so i l : Ex t rac t ion (1:2 w/v) with D T P A - T E A so lu t ion. Individual ca t ions a re de te rm ined by A . A . S . ( M S S 4 .65 ; E P A 6010) . P lan t T i s s u e A n a l y s i s (Total ca t ions) : Ni t r ic /perchlor ic ac i d d iges t ion . Determinat ion of C u a n d Z n by A . A . S . Total A s , C d , Cr, C u , Pb, Mo, Ni, and Z n : G V R D : So i l A n a l y s i s : A q u a reg ia d igest ion fo l lowed by a n Inductively C o u p l e d P l a s m a S p e c t r o m e t e r ( ICP) ana l ys i s . N O R W : P lan t T i s s u e A n a l y s i s : Ni t r ic /perchlor ic ac i d d igest ion fo l lowed by a n I C P a n a l y s i s for A s , C d , C r , P b , M o , a n d N i . Total A l , C o : G V R D : A q u a reg ia d iges t ion fo l lowed by a n I C P ana l ys i s . Total Se: G V R D : So i l A n a l y s i s : Ni t r ic /perchlor ic ac id d iges t ion . R e d u c t i o n of inorgan ic S e with hydroch lo r i c ac i d at 90 °C . Hyd r i des genera t ion with s o d i u m borohydr ide . Determinat ion of S e by hydr ide A . A . S . L M C A ; A P H A ( 1 9 8 9 ) ) . N O R W : P lan t T i s s u e A n a l y s i s : Ni t r ic /perchlor ic ac i d d iges t ion . Determinat ion of S e by hydr ide A . A . S . ( A P H A 3 1 1 4 B ) . Total Hg: G V R D : So i l A n a l y s i s : A q u a reg ia d iges t ion ( inorg. Hg) fo l lowed by sul fur ic a c i d / p o t a s s i u m p e r m a n g a n a t e / p o t a s s i u m persu lpha te d iges t ion (org. Hg) . R e d u c t i o n of p e r m a n g a n a t e fo l lowed by reduct ion of mercury with S t a n n o u s ch lor ide fo l lowed by co ld v a p o r A . A . S . ( A M M ; L M C A ; E P A 7471) . N O R W : P lan t T i s s u e A n a l y s i s : Ni t r ic /perchlor ic ac i d d iges t ion fo l lowed by co ld v a p o r A . A . S . L o s s on Ignition: B I O E : Ignition of 4 0 - 6 0 g s a m p l e for 3 hours at 450°C . T h e lost weight i nc ludes o rgan i c matter, wa te r of c rysta l l iza t ion, a n d vo la t i les . Organic Matter: N O R W : Determina t ion of To ta l C a r b o n with a n induct ion fu rnace a n d a n infrared detector . Es t imat ion of o rgan i c matter by mult iplying c a r b o n content by 1.78. Note: BIOE Bio-Resource Engineering Laboratory, U.B.C., Vancouver, B.C. GVRD Greater Vancouver Regional District Laboratory.Burnaby, B.C. NORW Norwest Soil Research Inc. Laboratory, Langley, B.C. 253 Particle Size Distribution: N O R W a n d B I O E : Hyd rome te r M e t h o d ( M S A 15-5). Particle Density: B I O E : P y c n o m e t e r M e t h o d ( M S A 14-3). Pretreatment of Samples: Soil Samples: B I O E : M a n u a l homogen i za t i on of s a m p l e s . A l l const i tuents of the soi l s a m p l e s a n a l y z e d w e r e be low 2 m m in s i z e . S a m p l e s w e r e a n a l y z e d on a wet b a s i s for T K N , a m m o n i u m , a n d nitrate a n d on a n air -dr ied b a s i s for the determinat ion of O l s e n - P , p H a n d E C . G V R D : A f low char t of the s a m p l e pretreatment at the G V R D L a b fo l lows on the next p a g e . N O R W : No rwes t a n a l y z e d the be low 2 m m fract ion of soi l s a m p l e s on a ovend ry b a s i s for al l pa ramete rs . Vegetation Samples: N O R W : A l l plant t i ssue s a m p l e s w e r e dr ied at 6 0 °C a n d g round . T h e be low 1 m m fract ion of the g round s a m p l e s w a s u s e d for further ana l ys i s . References for Laboratory Methods: A P H A A m e r c i a n P u b l i c Hea l th A s s o c i a t i o n . 1992 . S tanda rd M e t h o d s for the E x a m i n a t i o n of A M M A S S W E P A M S S M S A L M C A L M M W a t e r a n d W a s t e w a t e r . 18th e d . A lbe r ta So i l S c i e n c e W o r k s h o p P r o c e e d i n g s . E P A . 1986 . T e s t M e t h o d s for Eva lua t ing So l i d W a s t e . P h y s i c a l / C h e m i c a l M e t h o d s . S W - 8 4 6 , 3rd e d . U . S . E P A , Off. of S o l . W a s t e a n d E m e r g e n c y R e s p o n s e . M c K e a g u e , J . A . . M a n u a l on So i l S a m p l i n g a n d M e t h o d s of A n a l y s i s . 2 n d e d . C S S S . P a g e , A . L . , R . H . Mi l ler, a n d D .R . K e e n e y (eds.) . 1982 . M e t h o d s of So i l A n a l y s i s . A m . S o c . A g r o n , So i l S c . S o c . of A m . M a d i s o n , W i s c o n s i n , U . S . A . B . C . M O E . 1978 . Mercu ry in S e d i m e n t s (Co ld V a p o u r A t o m i c Absorp t ion ) . In Ana ly t i ca l M e t h o d s M a n u a l 1979 & U p d a t e s . Inland W a t e r s Directorate. W a t e r Qual i ty B r a n c h . B . C . M O E . 1976 . A Labora tory M a n u a l for the C h e m i c a l A n a l y s i s of W a t e r s , W a s t e w a t e r s , S e d i m e n t s , a n d B io log ica l Mater ia ls . Da ta S t a n d a r d s G r o u p , W a s t e M a n a g e m e n t B r a n c h . L a c h a t M e t h o d s M a n u a l . Determinat ion of N H 3 a n d N 0 3 in S o i l . Note: BIOE Bio-Resource Engineering Laboratory, U.B.C., Vancouver, B.C. GVRD Greater Vancouver Regional District Laboratory,Burnaby, B.C. NORW Norwest Soil Research Inc. Laboratory, Langley, B.C. 254 Similco - Princeton - Rangeland Soil Analysis TKN digest 2M KCI extraction for NHS & N03/N02 cold vapor generation colorimetnc Q Sample") Mercury digest Phosphorus digest oven dry sample > f homogenize 0 digest Aqua Regia digest - selenium hydride generation APPENDIX P Photographs Princeton Tailings Reclamation Project 2 S 6 Top: Figure 5. Plots 2b & 2a (top I. & r.) and Plots 3b & 3a (bottom II. & r.) (May 13, 1993) Bottom: Figure 6. Plots 2b, 2a, 3b, and 3a (May 23, 1993) Bottom: Figure 7. Plots 2b, 2a, 3b, and 3a (Aug. 19, 1993) Top: Figure 8. Plot 2a - 77 dt/ha (Aug. 19, 1993) Bottom: Figure 9. Plot 3a - 179 dt/ha (Aug. 19, 1993) Bottom: Figure 10. Unseeded Control Plot - 0 dt/ha (Aug. 1993) 2S"8 Leaching Experiment Topi.: Figure 11. Leaching Run 2 - Columns H and I Top r.: Figure 12. Leaching Run 2 - Column Setup Bottom: Figure 13. Leaching Run 2 - Columns 1 through 5 

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