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The effect of nutrient solutions on toluene biodegradation in unsaturated sand columns

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Title:
The effect of nutrient solutions on toluene biodegradation in unsaturated sand columns
Creator:
Cuffin, Sally Melinda
Place of Publication:
Denver, CO
Publisher:
University of Colorado Denver
Publication Date:
Language:
English
Physical Description:
xi, 201 leaves : ill. ; 29 cm.

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Subjects / Keywords:
Bioremediation ( lcsh )
Toluene ( lcsh )
Bioremediation ( fast )
Toluene ( fast )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (M.S.)--University of Colorado at Denver, 1994. Civil Engineering
Bibliography:
Includes bibliographical references (leaves 196-200).
General Note:
Submitted in partial fulfillment of the requirements for the degree, Master of Science,
General Note:
Department of Civil Engineering
Statement of Responsibility:
by Sally Melinda Cuffin.

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Source Institution:
University of Colorado Denver
Holding Location:
Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
31508786 ( OCLC )
ocm31508786

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THE EFFECT OF NUTRIENT SOLUTIONS ON TOLUENE BIODEGRADATION IN UNSATURATED SAND COLUMNS by Sally Melinda Cuffm B.S., The Pennsylvania State University, 1974 B.S., The Pennsylvania State University, 1979 A thesis submitted to the Faculty of the Graduate School of the University of Colorado at Denver in partial fulfillment of the requirements for the degree of Master of Science Civil Engineering 1994

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This thesis for the Master of Science degree by Sally Melinda Cuffin has been approved for the Graduate School by H.Wu David W. Hubly

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Cuffm, Sally Melinda (M.S., Civil Engineering) The Effect of Nutrient Solutions on Toluene Degradation in Unsaturated Sand Columns Thesis directed by Adjunct Professor James A Tindall Abstract Extensive research has been performed regarding bioremediation of hazardous waste in the saturated zone, while, in comparison, little has been done with the unsaturated or vadose zone. In order to better understand this process, four nutrient solutions and a control were tested for their relative effectiveness in the biodegradation oftoluene in the unsaturated zone. The solutions included: (1) nutrients and an oxygen source (hydrogen peroxide) for aerobic organisms; (2) nutrients for denitrifiers, (3) nutrients and an oxygen source for aerobic and denitrifying microorganisms; (4) basic nutrients (lacking micronutrients) and an oxygen source for aerobic and denitrifying microorganisms; and (5) water as a control. Each solution was added to three 150 em tall by 30 em diameter columns of 0.2 mm sand, for a total of fifteen columns. Instrumentation included soil gas probes and suction lysimeters. A ten cubic centimeter volume of toluene was added to the top of every column and gas and soil solution samples were collected every third day for 21 days. Gas samples were tested for toluene and nitrous oxide and soil solutions were tested for standard ions. The experiment was repeated after the addition of organic matter containing nutrients similar to the original solutions. iii

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The results showed a dramatic drop in the toluene concentrations after the sixth day of the experiment in all of the columns. Toluene degradation occurred at an even faster rate after the second application, with day 3 measurements showing a decrease of almost two orders of magnitude when compared to the levels recorded for day 6 of the first application. Three of solutions essentially performed equally while the solution which provided the widest range of nutrients performed best if one column was eliminated from the sample or worst (compared to the other nutrient solutions) if that column was included. This study indicated that micronutrients play an important role in the denitrifying population. "Fingering" in the sand columns and improper determination of the column evaporation rate complicated the prediction of soil moisture. This abstract accurately represents the contents of the candidate's thesis. I recommend its publication. Signed iv

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Dedicate to Gary, Lily, and Luna And in loving memory of Loki v

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This project was performed in cooperation with the United States Geological Survey, Water Resources Division, Denver, Colorado. Special thanks to the following individuals who helped make this project possible: Rochelle Grant Jason Salzman Larry Wapensky USGS Personnel and Volunteers: Peter Cutrone Art Moresey Joyce Dickey Ken Stollenwerk Lana Gerlick James Tindall Stephanie Heaslet Betty Jo Vitry Kathy Himes KiddWaddell. Leo House :.::Evelyn Warren April Kobayashi Kathy Wilke Ken Lull Duane Wydoski WendyMaura Tracy Yager V1

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Contents 1. Introduction .................................................................................................... 1 1.1 The Experiment ........................................................................................... ... 3 1.2 Objectives ....................................................................................................... 4 1.3 Substrate Selection .......................................................................................... 5 2. Theory ... ................. ; ......... 7 2.1 Soil Microbiology ........... ................................................................................ 8 2.1.1 Microorganism Classification ......................................................................... 8 2.1.2 Environmental Conditions For Bacterial Growth ......................................... 13 2.1.3 Bacterial Growth ........................................................................................... 20 2.1.4 Bacterial Energy ............ -. ...... .. ....... ; .... ............................... 22 2.1.5 Bacterial Genetics ........................................................................ ................. 32 2.2 Soil Properties .................................................................. 39 2.3 Bioremediation ................................ ; .. .... .................................................... 43 2;3.1 Aerobic Bioremediation ............... .................. ............................................. 43 2.3.2 Anaerobic.Bioremediation. ....... .. ;... ................. ; ... ; .. ; ......... ;.: .. .. .................. 46 3. Materials and M_ethods ..... ........... : ..... ... :. ... .... .. ..... ....... ........... ; ........... 51 3.1 Physical Setup .. .............................................................. 51 3.2 Nutrient Solutions .................... ; .................................................................... 62 3.3 Analytical Equipment ................................................................................... 68 3.3.1 Photovac. Gas Chromatograph., .. .. ....... ;; .............................................. 68 3.3.2 Chrompack Packard Gas Chromatograph .... '. ............ ................................. 72 3.3.3 Wescan Ion Chromatograph ...................................................... ................... 74 vii

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4. Results and Discussion ................................................................................. 77 4.1 Soil Effects ................... ............ .................................................................. 77 4.2 Toluene Degradation ..................................................................................... 79 4.3 Nitrous Oxide Generation ............................................................................ 103 4.4 Nitrate Concentrations ................................................................................. 105 5. Conclusions ................................................................................................. 120 Appendices A Toluene Data ................................. .............................................................. 124 B Nitrous Oxide Data .................... .-......... ................ .. .. ................................. 158 C Nitrate Data. ................................................................................................. 171 D LysimeterData ................................ ........................................................... 184 References ............................................................................................................... 196 V111

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Figures 1.1 Initial Steps in Degradation by Microorganisms ......................................... 6 2.1 The Krebs Cycle ........................................................................................... 31 3.1 Experimental Column .................................................................................. 52 3.2 Suction Lysimeter and Gas Probe ................................................................ 54 3.3 Column Layout. ............................................................................................ 56 3.4 Sample Photovac GC Output ....................................................................... 72 3.5 Sample Chrompack Packard GC Output ..................................................... 74 3.6 Sample Wescan IC Output ........ ................................. 76 4.1 Average Column Toluene Concentrations ....................... 4.2 Average Column Toluene Concentrations with Hypothetical Peak for Column ....................... ..... :; ... .. ; .. .... ...... ..... ......................... 80 4.3 Average Column Toluene Concentrations1st Application .......... ..... ; ..... .. 81 4.4 Average Lab Temperature For SamplingDays ... .. .. ................................ 83 4.5 Average Column Toluene Concentrations (Suspect Column Data Removed) ................ ..... ; ............................................................................ 89 4.6 Average Column Toluene Concentrations 2nd Application ....................... 90 4. 7 Average Column Toluene Concentrations (2nd Application) (Suspect Column Data Removed) ........................... .................................................... 90 4.8a Toluene Concentration Column 4, Level a ................................................. 93 4.8b Toluene Concentration Column 4, Level b ................................................. 93 4.8c Toluene Concentration Column 4, Levelc ................................................. 94 4.8d Toluene ConcentrationColumn 4, Level d ................................................. 94 IX

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4.9a Toluene Concentration Column 4, Level a ................................................. 95 4.9b Toluene Concentration Column 4, Level b ................................................. 95 4.9c Toluene .Concentration Column 4, Level c ................................................. 96 4.9d Toluene Concentration Column 4, Level d ................................................. 96 4.10a Toluene Concentration -.Column 1, Level a ......... ; ....................................... 97 4.10b Toluene ConcentrationColumn 1, Level b ................................................. 97 4.10c Toluene ConcentrationColumn 1, Level c ................................................. 98 4.10d Toluene Concentration Column 1, Level d ................................................. 98 4.11a Toluene ConcentrationColumn 1; Level a ................................................. 99 4.11b Toluene Concentration -.Column 1, Levelb .................... ; ............................ 99 4.11c Toluene Concentration Column 1, Level c ................................................ 1 00 4.1ld Toluene ConcentrationColumn 1, Level d ................................................ 100 4.12 Unidentified Peak Prior to Toluene Elution ................................................. 101 4.13 Average Column Nitrous Oxide Concentrations ......................................... 103 4.14 Unidentified Peak Prior During Nitrous Oxide Sampling ........................... 106 4.15 Average Column Lysiirieter SampleQuantity ............................................ 108 4.16 Average Moisture Distribution Based on Lys1meter Sample Size ............... 108 4.17 Column 3 Average Lysimeter San'lple Quantity ........................................ ':.1 09 4.18 Average Column Nitrate Concentration ....... ............................................... 114 4.19 Average ColumnNitrate Concentration -Level e ........................................ 115 X

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Tables 1.1 Toluene Properties ......................................................................................... 6 2.1 Characteristics Used to Classify Bacteria ....................................................... 11 2.2 Typical SoiVGround Water Bacteria ................................................................ 12 3.1 Randomization of Columns ............................................................................. 57 3.2 Sand Porosity Determination ........................................................................... 60 3.3 Material Additions to the Columns Prior to the Second Application of Toluene ....................................... ; .................................................................... 61 3.4 Container Evaporation Rate Without Mulch .................................................... 63 3.5 Container Evaporation Rate With Mulch ......................................................... 64 3.6 Approximate Analysis of Red Star Arnberex 695 Yeast Extract ................ 66 3. 7 Solution Nutrient Concentrations .................................................... ................ 67 4.1 Maximum Water Loss Due to Evaporation .................................................... 84 4.2 Toluene Loss Due to Evaporation 85 4.3 Possible Average Column Toluene-Levels on Day 6-... .............. ; ................... 86 4.4 Ion Concentrations .......................................................................................... l11 4.5 Solution Concentrations Determined by Ion Chromatograph ......................... 113 4.6 Nitrate to Bromide Ratio ............................. .................................................... 118 4. 7 Nutrient Concentrations Determined From Sacrifice Samples ....................... 119 xi

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Chapter 1 1. Introduction Bioremediation is defmed as "the manipulation of living systems to bring about desired chemical and/or physical changes in a confmed and regulated environment" (Flathman, 1993). While a relatively unknownprocess even a decade-ago, bioremediation is capturing additional attention as test sites prove its viability. A reeent Environmental Protection Agency seminar (June 24-25, 1993) indicated that bioremediation was being considered, planned, or implemented at 159 sites across the country (Rogers, 1993). Bioremediation techniques have been successfully used in the treatment of organic wastes (e.g., oil industry, munitions,,wood.preservation, and manufactured gas plant wastes); treatment of chlorinated organics (e.g., polychlorinated biphenyls PCBs, chlorinated alpihatics, and pesticides); enhancing in-situ biological treatment; and treatment of volatile organic compounds (VOCs). In-situbioremediation ofhazardouswaste$ites offers enormous potential for cost reduction if material delivery and .chemical costs can be minimized. These techniques reduce the need of more costly options such as removing the soil and moving it to a hazardous waste site, soil washing, or thermal treatment which may introduce toxic products of combustion into the att'nosphere. Bioremediation is also useful as a polishing technique in contaminated aquifers where the only other alternative would be to:pump.and.treat for decades. When properly done; bioremediation can convert organic wastes into biomass and byproducts of microbial metabolism such as C02 CH4 and inorganic salts. 1

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One aspect of bioremediation which is viewed as a problem by many engineers and regulators is that it is a naturally slow process. Cleanup projects may require from two months to 10 years or more. Due to pressing legal concerns, this may seem like a long time. However, compared to being considered a potentially responsible party for 30 years or more when waste is sent to a landfill, the option becomes more attractive. The slow pace of bioremediation can at times be misinterpreted to mean that nothing is happening. Recent studies have shown that organic chemicals which were once considered to be nonbiodegradable will in actuality completely biodegrade after a lag phase. The lag phase is the amount of time required for the cells to manufacture' the enzymes and other chemicals necessary to adapt to the new food source. An experiment performed by Bouwer and McCarty (1985) revealed that while the 1,2 and 1,4 isomers of dichlorobenzene degraded readily, the 1,3 isomer did not After a period of one to two years, the organisms became efficient enough to completely remove the 1,3 dichlorobenzene from water within a, 20-minuteresidence time. Due to public health problems associated-with contaminated aquifers, significant research has been done in the use of bioremediation techniques in the saturated zone. Research concerning the unsaturated or vadose zone has been more limited. Thereare significant amounts of land in the arid western United States where the distance to the ground water is large enough to provide ample time for cleanup prior to the contaminant actually reaching the ground water. Ground water provides a mode of transport which potentially moves the contaminant offsite and possibly into the drinking water supply of nearby farms or towns. A successful vadose zone 2

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bioremediation could potentially complete the breakdown with minimal contaminant transfer to the ground water. 1.1 The Experiment The experiment was designed to quantify the biological degradation of a known hazardous .material in the unsaturated zone. Factors to consider included what type of soil to use, how to. quantify the degradation, how to control the ambient conditions within the selected medium, and what parameter to vary for comparison. The decision was made to use three sets of five columns each to perform the study. Each column would contain various types of nutrients which would potentially encourage different bacterial populations. Three columns would serve as controls for the remaining twelve columns. All columns would initially be exposed to a bactericide to reduce the populations of any existing bacteria Sand was chosen as the medium due to its essentially homogeneous properties. Sand is typically sterile when compared to soils containing organic matter. It can be obtained in a dry form which would further reduce the number of bacteria present and is generally low in nutrients, which was another requirement for the medium. Sand is also available in bag form which reduces the labor involved in transportation and handling. Nutrients would be supplied to the colunins in solution form and an attempt would be made to control the moisture content of the soil. The nutrient solution was added to the column in a manner which would produce a arbitrary moisture content of 25%. 3

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The columns were instrumented with gas probes for soil gas samples and suction lysimeters to collect water samples. Samples would be collected at specified depths on all columns to compare the degradation rates at the various levels. The nutrient solutions would be added to the columns, an application of toluene made, and gas and water samples would be taken for. a period. of three weeks. After this initial period, organic material then would be added in place of the chemical solutions, a second application of toluene would be made, and the gas and water sampling would resume. Sample analysis .would be limited io the capability of available equipment and manpower. 1.2 Objectives The primary objective of the experiment was to detemiine the effect of different nutrient solutions on the biodegradation of toluene in the vadose zone. 1bis would be accomplished by monitoring the amount of toluene in the columns over a period of three weeks. The different solutions were to enhancethe perfonnance of the various types of bacteria; presumably a difference should be observed in the rate of toluene consumption. The second objective involved gaining a practical understanding of the bioremediation procesS. This would be accomplished by a review of the literature and perfonning the experiment. Since the experiment would be carried out in large sand columns rather than the typical small laboratory column, it would also provide some insight into the practicality of using these techniques in the field. 4

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1.3 Substrate Selection Considering the wide variety of contaminants which affect the unsaturated zone, the frrst important decision was which substrate to use in the experiment Toluene was fmally selected, primarily due to the large number of studies which have been performed on the compound in the saturated zone (point of comparison) and its wide spread presence in the environment Toluene (C,Hg) is a clear liquid with a distinctive aromatic odor. It was originally manufactured from coal.tars, but now is generated from the catalytic reforming of refmery streams (Kirk et al., 1983). Toluene-is usedo.ilfaWiae variety of products such as saccharin, medicines, dyes, perfumes, TNT, paint solvents, adhesive solvents, etc., but its primary use is as an octane enhancer in gasoline. Toluene comprises 5% to 7% of gasoline by weight, and this is the primary medium through which it enters the environment Leaking underground storage tanks, pipeline and transportation spills, and improper disposal of gasoline products introduce the compound into the unsaturated zone. Toluene is on the EPA priority pollutant list and is a listed hazardous waste (number U220). It is mildly toxic by inhalation and is regulated by the Occupational Safety and Health Administration (OSHA) in the workplace. Teratogenic and mutation effects have been reported (Hodgson et al., 1988). A summary of some of toluene's physical properties is provided in Table 1.1. The literature lists half-lives in surface water between 96 and 528 hours, in ground water between 168 and 672 hours, and in soil between 96 and 528 hours. These numbers are based on biodegradation rates (Howard et al., 1991). 5

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T bl 11 T 1 Pr a e o uene ope rues Property Value Molecular Weight 92.14 Freezing Point (C) -94.965 Boiling Point (C) 110.629 Density (g/cm3) at25C 0.8623 at20C 0.8667 Solubility in Water (mg/L) at25C 524 at20C 515 VaporDensity (giL) at25C 3.77 Vapor Pressure (mni Hg) at30C at20C 21.9 Figure 1.1 shows one of the proposed degradationpaths used by the microorganisms. Figure 1.1 Initial Steps in Degradation by Microorganisms (Verschueren, 1983) (XoH ____. OH Toluene Benzyl Benzaldehyde Benzoic Catechol alcohol acid It was origimilly that only aerobes were capable of cleaving the aromatic ring, but recent studies have suggested that-denitrifiers may be-more effective in this process (Hutchins et al., 1991; 'kyer et al., 1986; Kuhn et al., 1988; Hess, 1993). 6

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Chapter 2 2. Theory The laws of thermodynamics tell us that we are living in a world in which high energy systems are being reduced to a state of lower energy. This _is seen in the natural world as organisms use various forms of energy as "food." Whether using the system of photosynthesis to directly convert the energy of the sun, eating the plant for the energy-stored-primarily as carbohydrates, or eating another organism for the protein "fuel" of its muscles, energy must be obtained somewhere. These are the standard methods of food gathering that are obvious in the macroorganisms of the planet. "Food" for microorganisms can include photosynthesis, the waste products of macroorganisms, consumption of other microorganisms, and the direct breakdown of chemical bonds to release energy. Bioremediation typically takes advantage of the organisms which prefer to use chemical bonds for food. Initially it was thought that one specific bacteria was responsible for the breakdown of a-single pollutant. This lead to the development of organisms biogenetically engineered to attack the problem pollutant The problem with this approach was that while the organism performed well in the laboratory, conditions at the site_(pH, aerobic/anaerobic conditions,moisture content, soil particle size distribution, cation exchange capa:city,etc.) could be dramatically different, and the organism would not perform as expected. Current-research has shown that onsite bacteria is often highly adaptable and when provided with the proper conditions can biodegrade many hazardous materials. Bioremediation is the technique used-to 7

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enhance on-site conditions to allow the microorganisms to take advantage of the energy in the waste. 2.1 Soil Microbiology It is estimated that the first bacteria appeared on earth 3.8 billion years ago. This statement alone reveals the incredible adaptability of this type of microorganism. Where once the world was divided into. physical and biological processes, it becomes increasing evident that this actually is not the case. Microorganisms appear to bridge this gap. Research has revealed that bacteria are responsible for our atmosphere, copper deposits in the Andes, and even gold deposits. What was once considered to be "just dirt" is in actuality very much alive. 2.1.1 Microorganism Classification The numbers and diversity or microorganisms is at" times hard to comprehend. Just looking at the potential habitats for these "simple" organisms provides some insight to their incredible adaptability. They are found in the surface sediments of fresh water or salt water bodies, subsurface sediments in either aerobic or anaerobic environments, the water column of deep or shallow water bodies, hot hydrothermal waters, frozen sediments in theArcticor Antarctic plains, extreme pressure in deep ocean waters, and within the bodies ofhigher plants and animals (Chapelle, 1993). Recent research has even found a form which survives in the vents of active volcanoes. Amazingly, in spite of such diversity. all the organisms belong to four basic groups. These include.the procaryotes, the eucaryotes, the archaebacteria, and the viruses. The procaryotes (pro meaning early orprimitive and karyo meaning nucleus) lack a true nucleus and includes the bacteria and cyanobacteria (formerly called "blue-8

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green algae"). A typical cell is relatively simple and will contain structures such as a cell wall, cell membrane, bacterial chromosome, ribosomes, and cytoplasm. The eucaryotes (eu meaning true) contain a true nucleus and include algae, fungi, and protozoa. It is assumed that the eucaryotes are a more evolved group than the procaryotes. The typical cell is much more complex. Structures found in this cell include the cell wall, cell membrane, nucleus, endoplasmic reticulum, ribosomes, lysosome, mitochondria, golgi body, and chloroplast The archaebacteria were originally considered procaryotic organisms. Research in the past 20 years has revealed that they were a separate, unrecognized kingdom. These organisms are restricted to anaerobic environments, such as organic-rich sediments or the intestines of higher animals. Archaebacteria include three very different organisms: methanogens which produce methane from carbon dioxide and hydrogen (the most common), extreme halophiles which live in concentrated salt brines, and acidophiles which live under extreme conditions of heat and low pH (Chapelle, 1993). Viruses are distinct from the other groups since they are obligate parasites, which means they are not capable of living and reproducing Without a host cell to provide energy. The ongoing debate about viruses involves whether they are truly alive or not It has been argued that they are basically toxic chemicals. The counter arguments is that chemicals do not reproduce. Another group brought up the fact that crystalline substances "grow" from supersaturated solutions, but is this true reproduction? Viruses use subsurface bacteria as hosts and therefore can be present anywhere bacteria are found. 9

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The groups of organisms generally found in the unsaturated zone would primarily include the procaryotic microorganisms and the archaebacteria. Eucaryotic microbes will.be present but they are restricted to oxygenated regions. In a typical ground water system, the abundance of eucaryotes is typically three to four orders of magnitude less than that of bacteria. Viruses are also found in the vadose zone but they are confmed to the bacteria host and impact the environment by their effects on the indigenous bacteria. Bacteria are classified by a sizable number of characteristics. These characteristics can include: cell morphology, type of cell wall, cell growth, biochemical transfonnations carried out by the cell, nutrition, and nucleic acid sequences. Table 2.1 some of these classification characteristics. The nutrition classification is the characteristic most commonly referred to when discussing bioremediation since the method revolVes:'around;the-consumption of the contaminant Nutrition involves the types of substances used for carbon and energy. Heterotrophs use organic carbon for energy and carbon sources. In contrast, lithotrophs use-inorganic carbon, such as carbon dioxide or bicarbonate; as energy and carbon sources. One type of lithotroph; thechemolithotroph, obtain energy by oxidizing reduced inorganic chemicals (e.g., ferrousironorsulfides). Still another lithotroph, the photolithotroph, obtain their energy from light Metabolism is another aspect of nutrition since it involves the ways in which bacteria use their nutrients. To receive the energy from a substrate, microorganisms must remove electrons and transfer them to chemicals which serve as electron acceptors. When inorganic chemicals, such as oxygen, ferric oxide, or sulfate, are used 10

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as electron acceptors, the process is called respiration. When organic chemicals are used the process is called fermentation. Bacteria which use oxygen as an electron acceptor are called aerobes. When the bacteria can only use oxygen as the electron acceptor, they are called obligate aerobes. Another type of bacteria will use oxygen when it is available but are also capable of fermentation. These bacteria are called facultative anaerobes. When microorganisms can only grow in the absence of oxygen they are called obligate anaerobes. Table 2.1 Characteristics Used to Classify Bacteria (Chapelle, 1993) Microscopic characteristics Physiological characteristics Morphology Temperature range and cell shape optimum cell size Oxygen relationships arrangement.of cells pH tolerance range arrangement of flagella Osmotic tolerance capsule Salt requirement and tolerance endospores Antibody sensitivity Staining reactions Nutritional characteristics gram stain Energy sources acid fast stain Carbon sources Growth characteristics Nitrogen sources Appearance in liquid culture Fermentation products Colonial morphology Modes of"-metabolism Pigmentation (autotrophic, Biochemical characteristics heterotrophic; fermentative, Cell wall constituents respiratory) Pigment biochemicals Genetic Characteristics Storage inclusions DNA %0 + C Antigens DNA hybridization RNA molecules Soil and ground-water bacteria can typically be divided into gram-negative and gram-positive rods or cocci (where rods are rod shaped and cocci are spherical). The 11

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gram-negative classification refers to the gram stain used to detennine cell shape and the type of cell wall. Gram positive bacteria are stained a deep purple color when crystal violet is used as a stain. The peptidoglycan composition of the outer cell wall retains the crystal violet, making the cell appear purple. A gram negative bacteria has an outer cell wall which consists of lipopolycaccharides and proteins which do not retain the crystal violet and are instead stained red by the counter stain safranin. Gramnegative bacteiia are typically the most prevalent in ground-water systems, while grampositive are not as numerous. The gram-positive bacteria .is studied extensively, however, due to the number of human pathogens included in this group. Table 2.2 summarizes some of the types of bacteria found in soil and ground-water systems. a e lyptc 0 T bl 22T alS il/G roun dW te B a r actena Type Genera Aerobic Gram-Negative Rods_: .. Pseudomonas, Azotobacter, . Rhizobium, Alcaligenes, Flavobacterium, Bordetella, Agrobacterium, Mycrocyclus, Gallionella, Caulobacter Aerobic Gram-Negative Cocci Neisseria, Maxorella, Actinetobacter Facultatively Anaerobic GramEscherichia coli, Shigella, Negative Rods Salmonella, Klebsiella, Enterobacter Anaerobic Gram-Negative Rods Bacteroides, Fusobacterium, Duulfovibrio ... Gram-Positive Cocci Micrococcus, Staphylococcus, Streptococcus Corynefonn Bacteria Arthrobacter Spore-Fonning Rods Bacillus, Clostidium 12

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Research has shown that many of these bacteria have amazing adaptations. Pseudomonas have the ability to use an extraordinary number of organic substrates for food and many species do not require specific vitamins, growth factors, or amino acids. One study showed that Pseudomonas could grow on 127 different organic carbon compounds. The only reason the study stopped was that investigators ran out of ideas as to what to feed it (Chapelle, 1993) .. Rhizobium. have the ability to take inorganic nitrogen gas and transform it into organic nitrogen compounds (nitrogen fixation). Members of this genus form a symbiotic association with the roots of legume plants (e.g., soybeans) which allow the plantto produce and store high levels of protein. Spore-forming rods such as Bacillus and Clostridium have the ability to form endospores which are specialized structures that develop when environmental conditions become adverse. These specialized structures protect the genome of the bacteria from drying and heat stress. A spore-forming, thermophilic, sulfate-reducing. bacterium isolated from oilfield waters in the North Sea can survive at temperatures up to 131 oc for limited periods of time (Rosnes et al., 1991 ). 2.1.2 Environmental Conditions For Bacterial Growth Until recently it was-widely assumed. that the amount ofmicroorganisms decreased dramatically as the depth of the soil increased. Lackirig oxygen for respiration, light for photosynthesis, and concentrations of substrates (food), what could possibly live down there? Early detection methods for measuring the microorganisms supported the idea that there was little if any life at these depths. As measurement techniques were refined, however, it was discovered that these areas actually teemed with life. Early procedures attempted to wash the cells out of the 13

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soils. It was later realized that the cells were firmly attached to the soil particles and would not "wash" off. Checking samples by microscope was ineffective since a large portion of the cells were obscured by the soil. The technique which finally revealed the hiding microorganisms was the use of fluorescent dye stain for examination of the sample under a microscope using ultraviolet light The dye in the soil glows, but the dye absorbed by the cells glows a different color. It is now estimated that microorganism populations in the saturated zone range between 1 and 10 million cells per gram a soil. This is second only to the oceans in microbiological culture. (Devinny et al., 1990). As with any living system, the physical/chemical environment of a microorganism strongly influences its success or failure to survive.. One set of environmental conditions can favor the survival of one type of organism over another while a different set of conditions could spell disaster for all organisms. Most microbes have a range of tolerance to envrronmental conditions and will effectively grow. The environmental factors which are normally most critical include: temperature, availability of water, molecular oxygen, pH, and.osmotic pressure (Chapelle, 1993; Paul and Clark, 1989). Temperature is an important factor in the growth of all living systems. Life is made possible by a series of enzymatically catalyzed chemical reactions. Increased temperatures accelerate the chemical reactions which, to a-point enhance :the biochemical process. However, the enzymes and nucleic acids that maintain these processes are heat-sensitive. When the temperature rises too high, the structures of some proteins can become distorted to the point that they may no longer be capable of 14

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catalyzing the life-sustaining reactions. High temperatures may also alter the structure of the nucleic acids, distorting the information stored on them arid preventing the production of the enzymes needed for growth. All microorganisms have their own particular range of temperatures in which they can survive. Below a certain temperature, the temperature minimum, the microorganism cannot grow. Increasing the temperature above this minimum results in an increasing growth rate until an optimum temperature is reached and the maximum growth rate is achieved. The temperature maximum is the highest temperature that the microorganism can effectively grow. These minimum, optimum, an:d maximum temperatures are sometimes referred to as the cardinal temperatures of the microorganism. These temperatures are not completely fixed and can be affected by variations in conditions such as pH and salinity (Chapelle, 1993). . Microorganisms are typically divided into three main temperature groups: psychrophiles, mesophiles, and thennophiles. The psychrophiles live in the range of -1 0C to 30C, the mesophiles between 20C to 50 C, ;md the thermophiles grow at temperatures between 35C to 75C (Metcalf & Eddy, 1991). The mesophiles would be the most prevalent fonn of bacteria in the unsaturated .zone, but since this area is in contact with the surface conditions, psychrophiles and thermophiles may also be present. Most psychrophiles operate at an optimum temperature between 10C and 20C but there are bacteria which live in the deep ocean basins that grow quite well between 1 C and 3C. Freezing is the lower limit for bacterial growth, but does not necessarily result in the death of the organism. The microorganism may become 15

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inactive and can remain in that state almost indefinitely, as long as ice crystals do not form within the cell. Ice crystals can be fatal to the cell if they disrupt essential cellular structures. Fast freezing minimizes ice crystal formation and is often used by laboratories to preserve bacteria. Mesophiles are the most common microorganisms. This is the normal temperature range of many natural environments and the majority of life has adapted to operate in this range. Since this is the normal range of warm-blooded animals, this is the cardinal temperature for many pathogens. (The adaptation of the "fever" in mammals is thought to be an evolutionary method of fighting some infections.) Most soil bacteria. grow most efficiently from 20C to 30C, which is the most common temperature range for ground-water systems . Thermophiles are found in very deep aquifers and petroleum reservoirs. Hot vents on the ocean floor also provide a favorable environment for this type of microorganism. The maximum temperature at which these bacteria can survive was considered to be l00C for many years .. Thisconcept was related to the.two phases of water, liquid and vapor, at atmospheric pressure. However, when the water is :located in deep subsurface, it is under more than atmospheric pressure and remains in the liquid phase. The only limitation in these microorganisms would be the efficiency of their enzymes and nucleic acids to operate at these temperatures. Bacteria near hot vents on the ocean floor have been reported to grow at temperatures to 125C. In the deep subsurface, thermophilic bacteria may play major roles.in,petrogenesis, methanogenesis, and reservoir porosity enhancement (Chapelle, 1993). 16

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Water is necessary to all life processes whether macro or microorganisms and all but a few require liquid water for growth. There are many microorganisms which have made special adaptations to resist drying. The well known Staphylococcus has a thick cell wall and is efficient at preserving moisture. This allows it to survive in a relatively dry environment, such as human skin. Many soil microorganisms have similar a adaptation which are important to survival in an environment which experience wet and dry periods. This adaptation is especially required of microorganisms which live in the-unsaturated zone. Since pore spaces can contain either water or gases in this zone, cell drying is a possibility. High clay content makes this effect even more pronounced, due to the affmity of clay mineral surfaces for water. This can be a problem in an aquifer when the clay makes the water unavailable for miCroorganism use. Clayey confming beds typically exhibit less microbial activity than adjacent sandy aquifers .. (Rhelps et 1989; Chapelle and Lovley, 1990) Molecular oxygen is an absolute requirement for the obligate aerobes. The oxygen can be present as gas. or dissolved in soil water. Obligate aerobes produce energy by removing electrons from organic carbon or inorganic electron donors and then transferring these electrons to oxygen in order to produce energy. One type of obligate aerobe, the microaerophilic bacteria, requires oxygen for growth, but cannot tolerate oxygen in high concentrations. Facultative anaerobes prefer the use of molecular oxygen, but when it is not available they can switch to alternative electron acceptors (Chapelle, 1993). Molecular oxygen is toxic to the obligate anaerobes. The presence of molecular oxygen can either inhibit the growth of the microorganism or kill it. Methanogens have 17

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a very low tolerance of oxygen and can only be cultured under strict anaerobic conditions. Sulfate reducers tolerate exposure to oxygen but cannot grow in its presence. This may force this type of bacteria deep into pore spaces where oxygen typically cannot enter. These organisms are then the primary consumers of any contaminant that enters this area. Aerobic microorganisms are predominate around recharge areas where oxygen is delivered along with the infiltrating rainwater. Due to subsurface sediment heterogeneity, however, these same areas may contain small pockets (i.e., microenvironments) which lack molecular oxygen. Anaerobic metabolism may occur within inches of aerobic metabolism in the microenvironments. These types of conditions would typically occur at a remediation site, implying that both types of bacteria would need to be involved in any biodegradation Bacteria can survive in an amazing range of pH. Sulfide-oxidizing bacteria operate efficiently in an acidic pH range of 3.0 to 4.0. These bacteria even produce sulfuric acid (H2S04 ) as a by-product of their metabolism. Alkaline lakes are a normal habitat for other bacteria which have evolved to grow in alkaline environments of 10.0 or above. While the pH on the outside of the cell can cover quite a range, the conditions on the inside of the cell are not as forgiving. Bacteria usually maintain an intercellular pH of 7 .5. To maintain the intercellular pH of 7 .5, microorganisms must employ special proton-transporting mechanisms in order to survive. This is particularly important since bacteria utilize proton gradients across their cell membranes in order to harness energy. 18

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The waste products of actively growing bacteria can significantly affect the pH of the surrounding environment. Buffers such as carbonates or phosphates assist in stabilizing the pH in the media. Pristine ground-water systems generally do not have extremes of pH. Typical extremes in these systems include pH's of 4.0 to 5.0 where there is active oxidation of sulfides and pH as high as 9.0 in carbonate-buffered systems. Carbonate or silicate minerals typically provide buffering in most ground-water systems, narrowing the pH range. The introduction of toxic waste to the system, however, can change the local pH. Municipal waste leachates can have pH's as low as 3.0 due to high concentrations of organic acids. Industrial wastes (e.g., cement manufacturing) can produce pH's as high as 11.0. This change in pH, typically in a short period oftime, can stress the adaptive powers of the indigenous bacteria (Chapelle, 1993). The wide range of salinities present in the subsurface environment requires a large tolerance to osmotic conditions for soil microorganisms. Salinities can vary from that of rainwater to 30% brine solutions. A cell gains or loses water by osmosis depending on the relative concentrations of dissolved constituents inside or outside of the cells. The environment is hypertonic when the concentrations are higher on the outside of the cell and is hypotonic when the cell contains higher concentrations. When osmotic conditions are the same on both sides of the cell wall the environment is isotonic. A hypertonic environment will cause a cell to lose water into the surroundings, resulting in shrinkage and dehydration for the cell. In a hypotonic environment, a cell 19

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swells as it gains water and will eventually burst if it has no mechanisms to control the influx of water. The primary function of the cell wall is to regulate the osmotic flow of water into or out of the cell. The cell wall adapts to the surrounding conditions of the microorganisms do not survive. Bioremediation techniques which ignore the importance of the osmotic adaptations of the indigenous bacteria will probably have limited success. 2.1.3 Bacterial Growth When all the environmental conditions are within a acceptable levels, the microorganisms will begin to "grow." "Growth" is a somewhat misleading term since each cell grows in size, but the "growth" which is most important is the actual reproduction of the cells. The most common measure of cell growth is increase in the cell population. The majority of bacterial cells reproduce by means of binary fiSsion. This occurs when an iil.dividual cell splits to form two daughter cells. The cell accomplishes this by elongating, reproducing the chromosomal DNA, depositing the proper complement of DNA on either side of the cell, and the growth of septum between the two sides. When the septum is complete, the daughter cells can separate. The amount of time required for this process can vary dramatically from species to species. E. coli can double in number in as littl.e as 20 minutes. Micrococcus requires hours to double. Toxic substances or lack of nutrients can lengthen the doubling time or even stop reproduction. Doubling times in deep subsurface environments may be extremely slow due to the surrounding conditions. 20

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Due to the nature of binary fission, the growth rate of a bacteria population is exponential with time. The mathematical relationship which approximates this type of growth is: A(t) = Aoekt (2-1) where A( t) is the number of cells at any time t, A0 is the initial number of cells, and k is the fll'st-order growth constant. If there were no limits to this type of growth, the entire planet would be covered with bacteria in a few weeks. Bacterial popUlations are controlled, however, by environmental factors such as the lack of substrates,. the production of toXic waste products, infection by viruses, or predation by protozoa. Bacterial populations which have been observed in the laboratory pass through several phases. The fll'st phase is the lag phase where the bacteria adjusts to the new conditions. The exponential phase is when the exponential growth of the population becomes obviqus. The popUlation eventually reaches a size where the nutrients begin to be depleted or the toxic waste products buildup to a point where the reproduction rate equals the death rate. The popUlation is now considered to be in the stationary When the nutrients are completely used up the population enters the death phase and all the bacteria die (Sawyer and McCarty, 1978). The challenge of bioremediation is to provide the proper environmental conditions for maintaining a viable population of microorganisms until the substrate (i.e., toxic waste) is eliminated from the soil. 21

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2.1.4 Bacterial Energy Utilization Living entities can be defined as "unstable, organized complexes that maintain a steady-state condition through the constant utilization of energy" (Chapelle, 1993). The methods of obtaining this energy is the subject of the following section. Nature provided microorganisms to function as the planet's ultimate garbage disposal system. Organic matter provides microorganisms with the energy required for metabolic processes. It also is the source of materials for the synthesis of necessary structural chemicals. Some chemicals may be broken down to eliminate their toxic effect on the miCroorganism. Metabolism describes a complex series of energy-utilizing chemical reactions that are carried out within the living cell. There are two basic types of metabolic processes. The first process is catabolism which extracts the energy from organic compounds by breaking them down into their component parts. The second process, anabolism, uses energy to build component parts into the necessary compounds. Cellular metabolic functions include the extraction of ep.ergy from certain compounds, temporary storage of energy within the cell, the use of energy for the construction of cell parts-synthesis of enzymes, micleic acids, and polysaccharides-repairing damage, and general maintenance of the statUs quo. Large quantities are required to carry out all these functions and research has shown that some bacteria can metabolize an amount of nutrient equivalent to their weight in a matter of seconds (Chapelle, 1993). The laws of thermodynamics govern energy transformations in both living and nonliving systems. The first law of thermodynamics describes the energy balance of a reaction, or the amount of energy in the reactants must be equal the amount of energy 22

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in the products. An example of this would be the complete oxidation of glucose which produces carbon dioxide, water, and 686 kilocalories (kcal) of energy. The second law of thennodynamics, however, tells us that not all of that 686 kcal is available to the cell. A portion of that energy, the free energy, will be aVailable for work, while the remainder, the entropy, will be lost as heat and be unavailable for work. Studies have shown that only about 280 kcal will be available to the cell as free energy while up to 60% will be lost as heat. A reaction which releases free energy is known as an exergonic reaction. Reactions which absorb free energy (e.g., ATP synthesis) are known as endergonic reactions. The amount of useful energy released or absorbed during a reaction is called the Gibbs free energy change (AG) of the reaction. When referring to Gibbs free energy at standard conditions (i.e., all reactants present at concentrations of 1.0 M, pH equal to 7 .0, one atmosphere of pressure, and temperature of 25C) it is denoted as AG0 Exergonic reactions have a negative AG and endergonic reactions have a positive AG. Exergonic and endergonic reactions are combined by living cells to generate the life processes. Intennediate reactants are used to temporarily store energy from exergonic reactions. The energy is then transferred to a site where an endergonic reaction takes place. The use of these intermediate reactants allow the cell to generate compounds which otherwise could not be synthesized. The energy transfers from 23

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catabolic (exergonic) reactions to the high-energy intermediate compounds where it is stored until it can be transferred to an anabolic (enderogonic) reaction. The "storage compounds" used by living cells include adenosine triphosphate (ATP), guanosine triphosphate (GTP), acetyl-coenzyme A, and others. ATP is most important of these compounds. Its formation stores energy and its hydrolysis releases energy. ATP is formed when adenosine diphosphate (ADP) is combined with an additional phosphate group using the energy released by a catabolic reaction. The energy stored in this phosphate bond is energy then tranSferred to the anabolic reaction. This type of reaction is called phosphorylation. Living cells also use intermediate compounds to store the electrons that are generated in energy releasing .oxidation reactions. Enzymes that remove electrons from energy-rich compounds (called dehyrogenases) oftenhaveelectron-storing intermediate compounds as their coenzymes. Nicotine adenine dinucleotide (NAD) is one of these coenzymes. NAD can exist in either a reduced (NADH + H+) or oxidized (NAD+) form. '(he electron-transferring reaction is written as follows: NAD+ + 2H+ + 2eNADH + H+ Most metabolic reactions require the services of both A TP and NAD to produce the fmal product In a reaction where glucose is oxidized to produce pyruvic acid, 1 molecule of glucose provides 2 molecules of ATP (glucose + 2phosphate + 2ADP + 2NAD 2 pyruvate+ 2 NADH +2C02 + 2ATP). If all of the free energy which can be obtained 24

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from the oxidation of glucose were made available, 38 molecules of ATP could be produced. The problem is that there must be materials available to accept the electrons generated as the reaction proceeds. Electron acceptors are the inorganic compounds that can accept electrons and allow complete oxidation of organic substrates. The most common electron acceptors used by microorganisms include oxygen, nitrate, ferric iron, sulfate, and carbon dioxide. Respiration is the term used to describe this coupling of oxidation of organic chemicals to the reduction of external electron acceptors. Cells use electron transport systems to physically carry the electrons from the organic molecules to the electron acceptorS. These systems consist of hydrogen c3rriers (e.g., flavoprotein and coenzyme Q) and electron carriers (e.g., cytochromes. and iron-sulfur proteins). There are several different cytochromes (i.e., a, b, c, & d) which have slightly different electronegativities allowing the electron to be passed from one cytochrome to another sequentially. Electron transport particles are sites within the cell where flavoproteins and cytochromes are associated with each other. These sites allow the electrons to be efficiently passed from molecule to molecule in an organized fashion. If NADH is processed through an electron transport system, the cell is able to capture more of the energy pre_sent in the something like glucose than it would be able to capture through phosphorylation alone. While the transport of electrons indicates a movement of energy, the actual mechanism by which the released energy is used by the cell still needed to be identified. It was determined in the mid-1980's that cells use chemiosmosis to convert the electrical energy of electrons moving through the electron transport system to chemical energy (i.e., ATP). 25

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The energy of the electrons moving through the electron transport system is used to transport protons from inside the cell membrane to outside the cell membrane. This movement results in a proton gradient between the outside and the inside of the cell membrane. This proton gradient has an associated potential which is called the proton motive force. The cells then use a complex membrane-bound enzymes to capture this potential energy. These enzymes are called ATP synthase complex or ATP-ase. When protons diffuse through the ATP, their potential energy is captured and stored chemically as ATP. Thermodynamics drives the reactions which are possible in a living system. Reactions which have negative free energy can occur spontaneously and those with positive free energy can be accomplished by using an energy-storing intermediate compound such as ATP. Many reactions, while possessing sufficient free energy to occur spontaneously. do not occur at a rate which is fast enough to be useful to a microorganism. Enzymes are the mechanism used by living systems to increase the chemical reaction rate to a level at which the energy is efficiently used. Enzymes are proteins which serve as the catalysts of all biochemical reactions. Studies have shown that enzymes typically enhance reaction rates by several orders of magnitude (Tabatabai, 1982). In addition, each enzyme is designed to catalyze a specific chemical reaction. They combine chemically with the substrate or combination of substrates and arrange them in the proper sequence so a particular reaction can occur. The following equations summarize a typical reaction which has been catalyzed by enzymes: E S ES enzyme + substrate enzyme substrate complex (2-2) 26

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and E p ES ---+ enzyme + products (2-3) There is typically a limit to the amount of available enzyme which in tum limits the reaction rate even when more substrate is available. This is referred to as saturation kinetics since the enzyme is fully utilized or saturated and the reaction rate can no longer increase. The MichaelisMenton equation is a mathematical expression of this effect and is expressed as: u = YmaxS/(Km + S) (2-4) where t> is the reaction rate, V max is the maximum rate, S is the substrate concentration, and Km is the substrate concentration at which the-reaction rate is half the maximum rate. The classification of enzymes is normally based on the types of reactions they catalyze. There are oxidases and reductases which catalyze oxidation and reduction reactions, lyases which remove functional groups from organic compounds, and transferases which move functional groups from one molecule to' another. In addition there are hydrolases which hydrolize polymers that are linked with covalent bonds and ligases which combine monomers into polymers (ligases are also called polymerases). Enzyme classification can also be based on where they are used in the cell. Cytoplasmic enzymes are used in the cytopla.Sm, membrane-bound enzymes occur in the cell membrane, and exoenzymes are passed out of the cell to dismantle potential substrates into components which can then be moved into the cell. 27

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Soil could be viewed as a dynamic, living system in which biochemical activities occur through the assistance of enzymes. Enzymes accumulate in the soil due to the presence of exoenzymes which are released by living cells and the release of endoenzymes released from dead cells. Soil protease will degrade most of the enzymes released to the soil from microbial tissues and plant and animal residues (Tabatabai, 1982). There are also the coenzymes which are a nonprotein component (often contain vitamins or nucleotides) of enzymes and are required to activate the enzyme. The nonnal function of coenzymes is to transfer components from the enzyme to the substrate. NAD is a coenzyme that transfers electrons and protons. Other coenzymes include ATP (in addition to storing energy) which transfers phosphate groups and coenzyme A which transfer acetyl groups. There are also cofactors which are used by enzymes to act as the reactive center. They typically consist of inorganic ions (e.g., iron or magnesium) and assist the reaction by pulling the substrates together in the proper configuration. Enzymes are crucial in the ability of a microorganism to make use of a substrate. When a cell encounters a new substrate; it often can manufacture (i.e., induce) the enzyme that is required to break down that substrate. The lactose operon (an operon is that portion of a cell's DNA which codes for specific proteins) of E. coli is a classic example of enzyme induction. When there is no lactose in the cell, a repressor protein (a protein molecule) covers the lactose operon and prevents the manufacture of the three eniyrnes needed to break down lactose. When lactose is present, however, the repressor protein binds with the lactose and the repressor protein. 28

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is removed from the lactose operon, allowing the enzymes to be produced. Once all of the lactose has been used up, the repressor protein is again free to cover the lactose operon. This coupling of the inductive-repressive mechanisms allows the cell to operate very efficiently. Energy is not wasted generating enzymes which are not currently required. One drawback to the system is that induction typically takes time. This is the lag time which is observed when a microorganism is introduced to a new substrate. The enzymes can be "fooled" by substances resembling a normal substrate. These substances can include a variety of organic and inorganic chemicals (e.g., fertilizers, pesticides, municipal and industrial wastes, salts of trace elements, etc.). The "impostor" substrates can bjnd with the enzyme, reducing the amount of enzyme available for the break down of the actual substrate. This is termed competitive inhibition. Additionally, an organic molecule may:l?jnd a nonactive site _of an enzyme and change its shape. H the enzyme shape is altered sufficiently, it may become inactivated. This process is called noncompetitive inhibition. Altering the shape of the enzyme can .be used to regulate the rates of biochemical processes in cells. The allosteric effector sites are the binding sites on enzymes that regulate enzyme activity. Allosteric inhibitors are used to shut off the production of a particular enzyme quickly, without affecting the production at the genetic level. This is called feedback inhibition and is used to regulate biochemical pathways. The reverse of this approach is called feedback activation and is used to activate a particular enzyme. 29

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Cells require this ability to regulate their enzyme activity in order to respond to the changing conditions of their environment The ultimate goal of enzyme regulation is to maximize the efficiency of the substrate metabolism. This is accomplished by balancing enzyme production with need and by using the feedback inhibition and feedback activation. Microorganisms use an amazing variety of metabolic pathways to obtain the energy required for cell growth. Some of the pathways used by soil microorganisms include: lactate and acetate fermentation, ferredoxins and the production of hydrogen and acetate in fermentation, methanogenic pathways, sulfate reduction, Fe(lll) reduction, nitrate reduction; and oxygen reduction aerobic metabolism. The pathways which are currently utilized most frequently by.bioremediation include the aerobic metabolism and the nitrate reduction. Aerobic metabolism is the most energetically favorable mechanism used by microorganisms to oxidize organic carbon material. In this process, molecular oxygen is used as a terminal electron acceptor. The primary pathway (of the dozens) is known by several different names, including the tricarboxylic acid(TCA) cycle, the citric acid cycle, or the Krebs cycle. Figure 2.1 is a representation of the essential features of this cycle. The TCA cycle is most common in aerobic bacteria, but it is also used by anaerobic bacteria such as the Fe(ID) reducer GS-15. One energy source harnessed by a large number of microorganisms is the coupling of oxidation of organic substrates with the reduction of nitrate. This process has been extensively studied in regard to agriculture since it removes the nitrate which is a valuable commodity to the farmer. Nitrate reduction becomes important when 30

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hwnan activities have affected ground-water systems (e.g., landfillleachates, agricultural chemicals, septic effluents, etc.). By contrast, nitrate reduction is rarely of concern when dealing with a pristine ground-water system. Figure 2.1 The Krebs Cycle 31

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Denitrification is the result of nitrate reduction when molecular nitrogen (N2) is the major product. An example of this is: glucose + 4.8NOj + 4.8H+ -7 6C02 + 2.4N2 + 8AH20 Some of the bacteria responsible for denitrification include: Alcaligenes, Bacillus, Pseudomonas, and Thiobacillus. Many of the denitrifying bacteria do not reduce the nitrate all the way to nitrogen, but stop at nitrite: glucose + 12NOj -7 6C02 + 6H20 + 12N02 or ammonia: Special enzymes, including nitrate reductaSe," mtrite reductase, ano nitioiis oxide reductase are instrumental in the denitrification process (Chapelle, 1993). 2.1.5 Bacterial Genetics Microorganisms use energy-yielding and energy-consuming chemical reactions allowing them to maintain a structure for life which is inherently unstable. What is the master plan which tells the molecules where to go and what to do? The plan mUst contain infonnation on how to construct each protein, carbohydrate, lipid, and nucleic acid required for survival; the infonnation necessary for reproduction; and have sufficient flexibility to adapt to changing conditions. This "master plan" was finally .located by Francis Crick and James Watson in 1953. The code of life was discovered to be composed of nucleic acids. In particular it was deoxyribonucleic acid (DNA) which carried the infonnation. DNA stores the 32

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genetic infonnation required to synthesize cellular components. Some viruses, including HIV, use ribonucleic acids (RNA), for this purpose (Chapelle, 1993). The highly ordered DNA structure can be described as a double-helix or twisted ladder. The rails of the ladder consist of deoxyribose (a sugar molecule) linked with phosphate groups. The rungs of the ladder are two nitrogenous bases linked together with hydrogen bonds. There are four types of nitrogenous bases including adenine, thymine, guanine, and cytosine. The combination of these bases, however, is very specific. The adenine can only link with the thymine and guanine can only link with cytosine. The sequence of the four bases in each strand of DNA make up the codes which are used for the fonnation of the proteins required for cell maintenance and growth. The DNA strands also have the ability to copy or replicate themselves. Copies of the DNA are necessary for the cell to reproduce. To replicate, the DNA molecule must unwind and divide down the ri:riddle. This leaves a "rail" and half of a "rung" where the bonds between the adenine and thymine or guanine and cytosine are broken. The replication involves each half to reproduce its complementary other half. As with nonnal cell processes, replication is controlled by.the action of enzymes. Specialized enzymes are responsible for unwinding the molecule and then the enzyme DNA polymerase assists in providing the complementary base required for the replication. The sections of the new molecule are linked using enzymes known as DNA ligases. These enzymes also "edit" the new DNA to make sure the new copy fits the template. DNA ligases have the ability to make last minute repairs if necessary. An ability which may be vital when dealing with a contaminated environment 33

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The DNA molecule can be broken down into functional areas, known as operons, which are responsible for specific proteins. Like subroutines in a computer program, each operon has a start, a program or promoter, and a stop sequence. Operons are often called structural regions while the stop, promoter, and stop are called regulatory regions. Only one strand, the informational strand, of the DNA is used for protein synthesis. The other strand, which is known as the complementary strand, is used only for DNA replication (Chapelle, 1993). Bacteria DNA is organiZed differently from most higher life forms. The DNA used for replication is called chromosomal DNA and is organized inclosed loops. It is present only in the nucleoid region of the eell. Bacteria typically also contain DNA which is not part of the chromosomes. This DNA is found in the cell's cytoplasm and is called plasmid DNA. This is the DNA responsible for proteins which provide the cell with special attributes. The plasmids may provide the cell with the ability to deal with the environment This can include allowing the cell to utilize organic compounds as substrates or provide it with antibiotic resistance. A special feature of the plasmids is their ability to transfer between cells. This allows another cell to obtain, specific functions through the plasmid transfer without modifying the chromosomal genome. This would allow bacteria which has acclimated to a particular substrate to pass on the ability to other soil populations. This is the basis of much of the genetic engineenng of microorganisms and is also beneficial to soil remediation methodology. While the DNA is the blueprint of all the pieces required by a cell for life, RNA is the construction worker that puts the pieces together. There are three main types of 34

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RNA including: messenger RNA (mRNA) which transcribes the DNA information and carries it to the protein assembly site, transfer RNA (tRNA) which carries the required amino acids to the appropriate assembly sites, and ribosomal RNA (rRNA) which forms portions of the ribosomes which provide the construction surfaces (Chapelle, 1993). One difference which occurs in the replication of RNA versus DNA is that RNA uses the nitrogenous base uracil rather than thymine. The typical adenine thymine bond in_ DNA is replaced by a adenine uracil bond when RNA is being replicated. The structure of the tRNA is used to deliver the proper amino acid combination required to build the protein. In order to accomplish this, the tRNA have sites designed to bind only to a specific sequences of three ba.Ses (a combination of uracil, adenine, guanine, or cytosine) called codons, which are located on the mRNA. The tRNA can only link up with the portion of mRNA if it has the proper anticodon. This ensures that the proper sequence of amino acids is delivered to the mRNA The ribosomes provide the assembly area for the synthesis of protein. Ribosomes are a combination of rRNA and associated proteins. Once the construction site is ready, the protein synthesis can begin .. The term translation is used to describe the assemble of protein from the coded information of the mRNA, since the concept is to translate the nucleotide sequence of the mRNA into a sequence of amino acids (Le., a protein). The process=begins with the mRNA binding to a sin.all subunit of the ribosome Then a tRNA molecule delivers the particular amino acid encoded on the mRNA to the combined ribosome mRNA 35

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subunit. Another. amino acid is delivered in the proper sequence and the two amino acids bind to a peptide bond. Two tRNA binding sites are available on the ribosome. This controls the assembly process since a tRNA molecule always attaches to the first site where a peptide is attached to an amino acid. When the peptide is attached, the tRNA molecule moves to the next site, opening up a space for the next tRNA molecule, which delivers the next amino acid. The first tRNA molecule is released. starting the sequence again. When the "stop" codon is reached on the mRNA, the protein is released from the ribosome (the protein can be modified by forming or breaking disulfide bridges or be combined with lipids or polysaccharides before it fulfills its niche in the cell biology). The generation of proteins must be controlled to avoid unnecessary use of vital resources, especially in a soil environment with limited resources. It would be unwise for a cell to continuously generate an enzyme for metabolizing a particular substrate if that substrate were only occasionally available. The control for protein production is found in the chromosomal DNA andconsists of the regulator, promoter, and operator regions. .The regulator region builds a: repressor protein which binds to the promoter region of the operon preventing transcription of the operator; An inducer (typically a derivative of the substrate) can remove the repressor.protein from the promoter and allows the operator to be transcribed. When the substrate has been consumed, the inducer is no longer available to remove the repressor and the enzyme is no longer produced. Cells also have the ability to select the type of substrate they wish to consume. An example of this would be a roxie waste site where ample energy is available from 36

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the natuial system. Even if the microorganism is capable of biodegrading the waste, other substrates in the environment may provide energy in a more efficient manner. The cell can designate this preference through the use of catabolite repression, which is controlled by specialized proteins called catabolite activators acting on the promoter regions of the DNA. Many mechanisms are used to prevent errors during the encoding of proteins and the replication of DNA molecules. These include DNA polymerase enzymes which can depolymerize nucleic-acid chains and correct errors in the sequence. There are also ligase enzymes which can correct miStakes in the newly constructed DNA molecule. Radiation is one environmental factor which can prevent the proper functioning of the cell. Certain cells, however, have even developed defense mechanisms to repair this type of damage (i.e., exposure to sunlight). Studies have shown that the copying errors occur at a rate of less than 1 per 100 million base pairs copied (Chapelle, 1993). In spite of these repair mechanisms, there are.environmental conditions which can permanently alter the cell structure. Chemicalsand radiation are the primary agents of mutation. The vadose zone is continually exposed to a wide variety of chemical due to accidental and intentional spills. Radiation in the vadose zone can come from ultraviolet radiation (UV) at the surface or contamination (natural or manmade) by radioactive elements. The vast majority of mutations result in an microorganism which is no longer viable, but some mutations may allow the cell to take advantage of its new envir.onment In addition, mutations may be a way to introduce enough variations in the genetic makeup of the microorganisms to ensure the survival of the species. 37

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Cells use a variety of methods to exchange genetic material which can potentially increase their ultimate survival. These methods include: recombination where the material from two separate cells is combined into one, giving the new cell characteristics of each donor (the mechanism for this to occur is still not completely understood); transformation where the DNA released from a cell when it dies is taken up by a living cell and integrated into its genome; conjunction where plasmids allow two cells to connect and transfer DNA; and transduction where parasitic viruses (bacteriophages) transfer genetic material from a previous host to a new host. The term engineering arose in the 1970's when microbiologists began to experiment with these genetic transfer mechanisms. The purpose was to program cells to produce certain products or perform certain functions. Genetic engineering has had a mixed reception from the public. Some consider it evidence of the continuing triumphs of technology, while others are wary of the possibility of a new Frankenstein or "the blob". There has been a great deal of interest in using genetically engineered microorganisms to degrade pollutants which have been introduced into the environment This method gained considerable attention when specially designed bacteria were found to have the ability to efficiently destroy certain chemical wastes. Unfortunately, their performance in the laboratory far exceeded what could be accomplished in the field. This is primarily due to the mability to precisely control the environmental conditions (i.e., temperatUre, pH, soil moisture, etc.) at a field site. There have been a number of success stories, however, including the organisms that 38

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degrade aromatic hydrocarbons which have shown great promise in clean-up efforts for the large numbers of oil spills. Plasmids have been extensively studied to understand how particular substrates are utilized for energy. The TOL plasmid in particular codes for the degradation of toluene, xylene, and other aromatic hydrocarbons. The species of the genus Pseudomonas has various configurations of this plasmid. The degradation of toluene requires at least eleven separate steps, each step using a different enzyme. There are the "upper" pathway enzymes, which oxidize the methyl group of the toluene to from benzoate. These enzymes are coded on one operon. There are also the "lower" pathway enzymes which cleave the aromatic ring and are coded in another operon. The pathways are organized by the functions of converting the hydrocarbons to aromatic carboxylic acids and of converting the carboxylic acids into aliphatic metabolites. Toluene, xylene, and related compounds induce the generation of the necessary enzymes (Chapelle, 1993). There is currently a debate going on as to the safety of releasing genetically engineered microorganisms into the environment There are concerns that while the new organism is highly successful in degrading the target pollutant, it may also be able to evolve into a deadly pathogen for which existing species have no defense. While this scenario is typically considered highly unlikely, one mistake could lead to a potential disaster. 2.2 Soil Properties The unsaturated zone is a unique habitat that can vary from a totally saturated state after a rainfall event to a relatively dry environment during periods of low 39

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precipitation. It contains both water and air in the voids between the soil particles. Any water which recharges an aquifer must flow through the unsaturated mne first In this area highly reactive gases such as oxygen and carbon dioxide are freely exchanged with this recharge water. The microbial processes in the unsaturated zone are important since this is the first line of defense for an aquifer. Bacterial processes such as oxygen consumption, carbon dioxide production, nitrification, and denitrification will affect the chemistry of the water reaching the water table. When anthropogenic compounds such as petroleum hydrocarbons, herbicides, pesticides, and numerous others past through the unsaturated zone, bacterial processes will affect their fate and transport The unsaturated zone consists of three components: (1) The soil zone which includes the first one to two meters supports plant growth and contains living roots. Porosity and permeability is generally greater in the soil zone than in the deeper mnes; (2) The intermediate zone underlies the .soil zone and can vary in thickness from place to place. It consists of sediments or rocks which have not been exposed to extensive soil forming processes such as weathering; and (3) The capillary fringe which is the deepest component of the unsaturated zone and lies between the unsaturated zone and the saturated zone. The capillary fringe is the result of the capillary effect This is the result of two forces: the mutual attraction (cohesion) between water molecules and the molecular attraction between water and solid mineral surfaces. The pore spaces between soil particles can be thought of as numerous small tubes and water will rise to various levels above the normal water surface depending on the soil type. Finer-grained 40

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sediments will normally have a thicker (up to 1 meter) capillary fringe than sandy sediments (generally 1 to 10 centimeters). Movement of contaminants and microorganisms in the unsaturated zoneis a function of gravity, hydrostatic forces or pressure gradients, osmotic forces, adsorptive forces such as van der Waals, and the total soil water potential. Negative pressures occur in this area due to the surface tension of the soil moisture held between the soil grains (the capillary effect). As the moisture increases, the radius ofcurvature of the meniscus increases, lowering the tension heads. As the soil dries out the reverse is true, but the relationship between moisture content and the tension pressure is hysteretic and produces a different curve for drying as compared to wetting. The fluid pressure in the unsaturated zone is typically than atmospheric and the pressure head is less than zero. Hydraulic conductivity and moisture content in the unsaturated zone are functions of the pressure potential (Freeze and Cherry, 1979). There are five interactive factors that lead to the development of soil: climate, topography, parent material, time, and biologic processes. Soil microbiologists have long recognized that soil organisms play a significant role in the development of their own habiiat This is certainly true, to varying degrees, in.other subsurface environments but is most easily observed in soils. Soil formation is initiated by chemical and physical weathering of rocks or sediments. The release of nutrients by the weathering processes allow colonization by algae and lichens. This initiation of primary production leads to the establishment of a heterotrophic bacterial population. In turn, these combined microbial processes speed the weathering processes by increasing the partial pressure of carbon dioxide and by releasing organic acids. Once a 41

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suitable combination of weathered rock debris and organic matter is achieved, plants are able to initiate growth. Plant growth increases organic carbon production which in tum increases the activity of heterotrophic bacteria. The net result is a more efficient weathering processes. Soil development may be viewed as a combination of processes that are linked in positive feedback loops. When one process becomes more efficient, the efficiency of the other processes is enhanced. Soil formation produces a stable, well defined soil proflle at the top of the unsaturated zone. Clay organic complexes stabilize clay, sand, and silt particles into aggregates. Polysaccharides from roots and microorganisms are the glue which hold these aggregates together. The microorganisms move into the aggregates and live in the pore throats of the soil aggregates, generally. attached. to particle surfaces. The porosity and size of pore throats in the soil are important structunil features because they form living space and allow access nutrients. The agricultUral revolution generated a great deal of interest in the abundance and distribution of bacteria in the unsaturated zone over the last 150 years (Alexander, 1977). When it was recognized thatmicrobial processes w.ere directly involved in soil fertility, research was aimed at.increasing agricultural production. One example this was discovering the mechanism which converted composted manure into a valuable fertilizer, nitrate. Farmers had been composing for centuries, but it was the soil microbiologist S. Winogradsky who showed that this proceSs is brought about by bacteria oxidizing ammonia, present. in the manure, to nitrates. Winogradsky isolated a pure culture the bacterium which carried out the nitrification process, in 1891. also isolated an anaerobic bacterium of the genus Clostridium that was 42 )

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capable of nitrogen fixation: the process of converting atmospheric nitrogen into organic nitrogen. A Dutch bacteriologist named M. Beijerinck isolated a nitrogen fixing bacteria from the roots of legumes in 1888. Discoveries such as these are the core of crop fertilization and crop rotation strategies still used today. With so much interest in the soil microbiology associated with soil fertility and crop production, the microbial processes in sediments just below the root zone were almost totally ignored. The unsatUrated zone between the root zone and the water table is probably the least studied of any subsurface environment This is understandable areas where there are only a few meters between the root zone and the water table, but in some parts of the world, particularly in arid climates, there may be hundreds of meters of unsaturated material below the root zone. This is an area of major interest in regards to hazardous waste remediation, but has only recently caught the attention of researchers. 2.3 Bioremediation 2.3.1 Aerobic Bioremediation The most common approach to bioremediation in recent years has been to provide more oxygen to the system, thus favoring the. aerobic microorganisms. Oxygen concentrations in the unsaturated zone have been increased by tilling and draining the soil. There is also the method of air sparging or bioventing in which air is forced through the soil system, providing additional air to the aerobic microorganisms. Another process which has been mainly used in ground-water systems is the addition of hydrogen peroxide (H202) which will increase the oxygen content in the water. This method has been successful in the biodegradation of jet fuel components such as 43

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benzene, toluene, and xylene. The majority of the literature reviewed for this project revolved around the use of hydrogen peroxide to increase the available oxygen to the microorganisms (de MarsHy et al., 1992; Thomas and Ward, 1989). Hydrogen peroxide bioremediation was typically favored in the literature because "(1) it is relatively cheap and available (Britton, 1985; Ainsworth, 1989; Piotrowski, 1989); (2) oxygen from its disproportionation is available for use by microorganisms (Schlegal, 1977); (3) it can be added to the environment at high concentrations, providiiig an oxygen supply several orders of magnitude more concentrated than possible from saturating water with pure oxygen; and (4) it does not persist in the environment."(Pardieck et al., 1992). H202 does have its disadvantages, however, including: "(1) it is toxic to microorganisms; (2) its use in situ bioremediation is largely unproven (Lee and Ward, 1985); and oxygen will bubble out of solution, becoming unavailable to microorganisms and possibly decreasing the permeability of the subsurface formation into which it is injected (Spain et al., 1989). Conversely, slow disproportionation of H 2 0 2 means that derived oxygen is unavailable for aerating ground water" (Pardieck et al., 1992). Since H 2 0 2 is a respiratory waste product from bacteria, they have developed enZymatic defenses to guard against its effects. Hydroperoxidases (catalases and peroxidases) are found in most cells and provide the enzymes for the decomposition of the H202. The reactions involved are as follows: catalase 2H202 2H20 + 02 peroxidase 2H202 + XH2 2H20 +X 44

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where X can be NADH, glutathione, or other biological reductants. These reactions show that catalase is the necessary enzyme required for the microorganism to make use of the hydrogen peroxide (Britton, 1985). The H 2 0 2 concentration, however, must be in the proper range to avoid destruction of the microorganism. A review of the literature has suggested that if the H 2 0 2 concentration is initially kept at a low level and then gradually increased, toxic effects would be minimized (Britton, 1985). This effect is most likely related to the number of bacteria available to produce the catalase required for the breakdown of the H202. Reactions with the several ions present in many soil are largely responsible for the rapid decomposition of H 2 0 2 This decomposition has been observed to produce a half-life of as little as fo\lr hours (Spain et al., 1989; Croft et al., 1992). Iron salts are the major players in-this decomposition. Some of the involved reactions are as follows: Fe+ 2 + H202 Fe+3+ OH+ OH" (hydroxyl radical) OH" + H202 H20 + H+ + 02 (superoxide radical) 02+ H202 02 + OH+ OH" Fe+3 + H 0 Fe+ 2 + 2H+ + o2 2 2 Fe+3 + 02 02 In an attempt to minimize the effect of the non-enzymatic decomposition without totally preventing the decomposition, the effects of a potassium phosphate stabilizer and pH were investigated in laboratory studies (Britton, 1985). While pH made no significant effect on H202 decomposition, potassium phosphate had a major 45

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effect The stabilization effect occurred with a solution which had a concentration of 0.0 1M potassium. phosphate (monobasic). Another verification of this effect was provided in An experiment with Aquifer Remediation Systems Restore 375 nutrient mixture which contains 800 ppm orthophosphate The addition of this mixture increased the half-life of the H2(h to 12 hours (Spain et al., 1989). Since phosphate is also a major nutrient required by the microorganisms, it fits into the bioremedial scheme quite nicely. 2.3.2 Anaerobic Bioremediation Anaerobic bacteria have shown promise with a wide variety of contaminants which are not readily used as a substrate by aerobic bacteria. Highly chlorinated solvents such as polychlorinated biphenyls (PCBs), trichloroethylene (TCE), tetrachloroethylene (PCE), and carbon tetrachloride (CI) have all been degraded by anaerobic microorganisms (Frederickson et al., 1993). The two dominant anaerobic processes are denitrification and methanogenesis. Both of these have been shown effective with the biodegradation of benzene, toluene, and the xylenes (BTX) but the denitrifiers have been studied the most extensively (Major et al., 1988; Hutchins, 1992; Evans, 1991; Taylor, 1970). It was once assumed that denitrification process occurred only under total anaerobic conditions, but further research revealed that the process is actually a modification of aerobic pathways and is more preciSely termed anoxic. Most of the bacteria involved in this process are facultative and will use oxygen when it is available, but easily switch to anaerobic respiration when the oxygen runs out. The presence of oxygen inhibits the synthesis and activities of the denitrifying enzymes. In contrast, the 46

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oxygen respiring enzymes remain functional during denitrification (Tiedje, 1982). Some of the genera of bacteria include: Achromobacter, Aerobacter, Alcaligenes, Bacillus, Brevibacterium, Flavobacterium, lActobacillus, Micrococcus, Proteus, Pseudomonas, and Spirillum (Metcalf and Eddy, Inc., 1991). One aspect of the anaerobic microorganisms which gives them an advantage in the unsaturated zone is that they are typically smaller than the aerobes (Taylor et al., 1970; Hess, 1993). This allows them to enter pores which would not be accessible to the larger microorganisms and permits them more access to the contaminant. Another disadvantage of the aerobes is they can reproduce at such as high tate that they will actually clog the pores, thereby reducing the permeability of an aquifer or soil. This can limit the flow of vital nutrients to some areas and prevent the further biodegradation (Hess, 1993). Since anaerobes are not as metabolically efficient, they are not as prone to poreclogging. For the same amount of nutrients, anaerobes produce less biomass than aerobes (Alexander, 1977; Golterman, 1985). This can be seen energetically by comparing the Gibbs Free Energies of the oxidation of toluene (C7Hs) using nitrate (NOj) or oxygen . C1Hs + 6NOj ---+ 3N2 + 7C02 + 4H20 (AGOr = -2923.96) C1Hs + 902 --+ 7C02 + 4H20 (AGOr = -3594.58) where AGOr is the Gibbs Free Energy of Reaction. Comparing the two energies it is easy to see that the denitrifiers obtain approximately 20% less energy from the biodegradation of toluene which translates to less biomass (Hess, 1993). 47

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The reactions involved with denitrification include: There is some controversy as to whether nitric oxide (NO), nitrous oxide (N20) are obligatory intermediates. The evidence is strong that N20 is an intermediate for most denitrifiers, but the evidence for NO is not as clear. Current research indicates that the NO may actually be bound with an enzyme during the process. Nitrite (N02) and N20 often accumulate temporarily during denitrification due to the different reaction rates for the reaction sequence (Tiedje, 1982). Nitrate and nitrite typically move rapidly into the ground water due to their negative charge. Nitric oxide, nitrous oxide, and nitrogen (N2 ) are gases which can be released to the atmosphere. Field experiments have shown that not all of the intermediate gaseous products are converted to nitrogen gas. A percentage of these intermediate gases escape to the atmosphere. Detection of these gases is one of the indicators that denitrification is occurring (Paul, 1989). A method which.has been used to determine the true amount of nitrous oxide being produced is the acetylene blockage method. The acetylene inhibits the nitrous oxide reductase allowing the N20 to accumulate for measurement by a gas chromatograph (Paul, 1989; Yoshinari et al., 1977). Some denitrifiers do not produce the intermediate nitrogen oxide compounds, releasing only gaseous nitrogen as a byproduct Campy/obacter sp. is the only commonly found bacteria currently known to have this ability (Hess, 1993; Goltennan, 1985). 48

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It appears that denitrifiers are not the only microorganisms responsible for nitrous oxide production. Nitrifiers can also produce quantities of N20 in addition to a number of other NO) and NOi reducing bacteria. Bacteria of the following species have shown these properties: Bacillus, Enterobacter, Klebsiella, Citrobacter, Escherchia, and Erwina (Tiedje, 1982). The influence of these other common soil bacteria would complicate the mass balance when investigating denitrification. Denitrification appears to be the answer for a great many bioremedial problems, but there are also problems associated with the process. Nitrate is rapidly becoming the chemical of greatest concern for ground water. Levels of nitrate in ground water have been increasing throughout the country especially in agricultural areas where chemical fertilizers and feedlots wastes leach into the ground. The greatest danger from nitrate is to new born babies (both human and animal) which-can develop a disorder known as methemoglobinemia in which the nitrate interferes with the ability of blood to carry oxygen(Gianessi and Peskin, 1981). While most sites where this approach would be used are small in comparison to agricultural usage, it is a potential problem which is attracting attention for possible legislative action. The nitrate balance should be well documented at any field site. The other problem associated with denitrification is the generation of nitrous oxide, a known 11 greenhouse gas 11 Atmospheric nitrous oxide concentrations have been increasing globally and the increased N20 generation has been linked to the excessive use of nitrates for fertilizers. It is estimated that the levels of N20 are up 30% from unperturbed levels (Dickenson and Cicerone, 1986). Since N20 has a 49

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lifetime in the attnosphere of approximately 150 years, it is a potential problem which requires close monitoring. 50

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3. Materials and Methods 3.1 Physical Setup Chapter3 The experiment was perfonned at the United States Geological Society (USGS) Unsaturated Zone Soils Laboratory at the Denver Federal Center, Denver, Colorado. Fifteen packed soil columns were used which were 30.5 em (12 in) in diameter and approximately 150 em (5 ft) high. The columns were constructed of polyvinyl chloride (PVC) irrigation pipe and an appropriate eild cap. The sections were cut from 9.14 m (30 ft) lengths of pipe which required hand trimming once transported to the lab. The pipe sections and end caps were washed with a laboratory grade soap to remove any organic residue from the manufacturing process and any soil which accumulated during storage. The end cap was attached using commercially available PVC pipe cleaner and glue. It was determined prior to the purchase of the PVC pipe that another material such as Teflon or stainless steel would be more appropriate due to toluene's ability to react with PVC. The effect of solvents can range from swelling to degradation of the PVC (HCl is a byproduct of PVC degradation) (Rosen, 1982). A decision was made to use the PVC since the area of contact with the column was minimal when compared to the surface area of the sand particles. Also, since all the columns were PVC, any effect would be standardized. The cost factor was another consideration. Seventy-five suction lysimeters were constructed for the collection of water samples from the columns (five per column see Figure 3.2). The lysimeters 51

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ViewAA Figure 3.1 Experimental Column ., A 30cm Suction Lysimeters consisted of a 1 bar, high flow porous cup (Soilmoisture Equipment Corp.), a 20 em (8 in) section of 1.3 em (0.5 in) diameter Schedule 80 PVC pipe, two pieces of 0.32 em (0.125 in) diameter nylon tubing (one piece acted as a pressurization port while the other was used for the sample collection), and a two hole, number 0, butyl rubber 52

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stopper. The lysimeters were assembled and sealed with commercially available, slow drying, 2-ton epoxy. The specifications for the porous cup include: a bubbling pressure of 19 to 28 psi, an approximate porosity (% volume) of 45%, a saturated hydraulic conductivity of 8.6 x 1 Q-6 em/sec, a pore size of 2.5 Jlm, and a flow rate through a 114" plate of the material of 50 mL/hr/cm2!14.7 psi. According to Soilmoisture, the high flow porous cups consist of a mixture of 90% Alumina (A1203) with small amounts of Si02, Fe203, and Ti02. Mter the epoxy had dried, the lysimeters were soaked in a 0.1M solution of hydrochloric acid. This removed any unwanted organics from the cup. The acid saturated all exchange sites with H+, thus preventing undesired adsorption of other materials. The lysimeters were soaked in the acid solution for 24 hours, then rinsed and dried. Sixty gas sample probes were constructed for the collection of soil gases in the columns (four per column-see Figure 3.2). The probes consisted of 17.8 em (7 in) lengths of0.32 em (0.125 in) diameter stainless steel tubing which were crimped on one end and cut in four locations with a 0.3 mm cutting wheel to provide gas openings. The tube was fitted with a modified Swagelok tube fitting which had the ferrules removed and replaced with.a.piece of0.32 em (0.125 in) inner diameter neoprene tubing which acted as a gasket The open end of the tube was then attached to a 2.5 em (1 in) piece of 0.32 em (0.125 in) diameter Tygon tubing which was in tum fitted with a two-way Luer lock valve. Cotton wadding was inserted in the Tygon tubing 53

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between the value and the stainless steel tubing to prevent sand from entering the sampling devices. Figure 3.2 Suction Lysimeter and Gas Probe *Not to scale 54 Suction Lysimeter*

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Starting at a position approximately 8.9 em (3.5 in) above the bottom of the column Gust above the end cap), 2.5 em (1 in) diameter holes were drilled at intervals of 30 em (12 in) for the installation of the suction lysimeters. These oversized holes allowed :the lysimeters to be installed at an angle (approximately 15)_ to minimize the likelihood of the sample interfering with the pressurization port. The lysimeters were installed with the center of the porous cup located at the center of the column. Dow Coming aquarium silicon sealant was used to seal the lysimeters in place. The gas probes were installed at the same elevation as the upper four lysimeters, approximately 10 counterclockwise from the lysimeter holes. These holes were tapped for the 118 in (0.32 em) NPT fittings and sealed with the silicon sealant No probe was installed at the bottom of the column due to the likelihood of the area becoming saturated. A drainage port was installed approximately 2.5 em ( 1 in) from the bottom of the column to allow for the drai11age of excess This consisted of 114 in hose connector which attached to the column with l/8 in (0.32 em) NPT and sealed with the silicon sealant A 4.0 em piece of 0.64 em (0.25 m) diameter Tygon tubing was attached to the hose connector and the opening was closed with a 0.64 em (0.25 in) diameter septum. The septum provided a means to perfonn gas sampling if the lower sections of the column did not become saturated. The opening inside the column was packed with steel wool to prevent the movement of sand from the column. 'I'h,e columns were then placed in their positions for the duration of the experiment (see Figure 3.3) and filled with commercial sandblasting sand (sieve size 55

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70-0.2 mm diameter). An attempt was made to add the sand to the columns slowly in a rotating fashion (Chiang, 1993). This was not always possible, however, due to space limitations. The sand had an unsaturated hydraulic conductivity (K(9)) of 0.65 to 0.74 em per day (findall, per conversation, 1994). Bench Figure 3.3 Column Layout Solution The loaded columns were then allowed to settle for approximately two weeks. The sides of the columns were occasionally struck down the length and on all sides to encourage settling. The nutrient loading of the three sets of columns was randomized using a batch randomization method (Gomez and Gomez, 1984). The columns were first numbered 56

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(lA, 2A, 3A, etc.) and then one number was arbitrarily chosen from a random number table and assigned to column IA. The next fourteen numbers in the random number table were assigned to the corresponding next fourteen columns. The order in which the fonnulas would be applied was then detennined by assigning the frrst column to the lowest random number, the second to the next largest random number, etc. Table 3.1 provides the results of this procedure. Table 3.1 Randomization of Columns Column Random Solution Number Column IA 827 4A 2A 898 5A 3A 267 IA 4A 336 2A 5A 788 3A IB 421 3B 2B 011 IB 3B 545 5B 4B 426 4B 5B 174 2B IA 678 4B IB 972 5B IC 373 3B ID 128 IB IE 197 2B In order to minimize the amount of time required to add the various solutions to the columns, a distribution system was constructed. Two 121 L containers (32 gallon Rubbennaid trashcans) were fitted with standard 112 inch (1.3 em) outdoor hose valves. Each container was connected with 1.3 em (0.5 in) diameter plastic tubing to a manifold system which provided for three solution outlets per container. The manifolds consisted of a 15 em (6 in) section of 1.3 em (0.5 in) diameter Schedule 80 57

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PVC pipe which was fitted with four 1.3 em (0.5 in) nylon hose connectors and sealed with two number 1 neoprene rubber stoppers and silicon sealant Plastic tubing continued on from the three hose connectors to three individual rings formed by a 1.3 em (0.5 in) nylon hose connector tee attached to a 25.4 em diameter ring of 1.3 em (0.5 in) drip irrigation tubing. This tubing was fitted with four 1.9 L per hour (0.5 gal per hour) drip fittings (this flow rate was calculated for a water line pressure of 69 to 414 kPa (10 to 60 psi)). The irrigation rings were attached to the columns using a base formed from hardware cloth. A bench was constructed and added to an existing bench to position the containers at a sufficient distance above the columns to provide head pressure. Due to space limitations, no method was available to provide the recommended pressure for the drip fittings. It was therefore assumed that the flow rate would be less than the specified.flow . Prior to placement above the columns, the containers were calibrated with the addition of water in increments of 5 liters. The water level was marked on a wooden "dip stick". Each container required a separate calibrated stick since the residual volume varied due to the placement of the hose valve. The appropriate amount of solution for three columns was mixed in the containers and applied to the columns with the drip system. To minimize evaporation and prevent drip "wells" (which would create preferential pathways), the sand surface of all the columns was covered with a landscaping fabric and a vermiculite mulch. Tests were performed which indicated that the evaporation rate could be reduced with the use of the fabric and mulch. 58

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A decision was made to attempt to maintain the columns at a 25% moisture content (70% degree of saturation). In order to determine the proper amount of solution to be added to each column, the porosity of the sand needed to be detennined. A test was performed to determine the range of porosity which the sand could possess. Dry sand (dried in an 100C oven for 24 hours) was slowly poured into a container of known weight and volume and the container was then weighed. The container was then sealed and placed in a vibrator (used for sieve analysis). The change in volume of the sand was determined by measuring the amount of settling which occurred (Danielson and Sutherland, 1986). Porosity was determined using the relationship: (3-1) where 4> is porosity, Pb is the dry bulk density of the sand, and Ps is the density of the solid sand. Table 3.2 summarizes the results of that test and the determination of the loose and packed porosities. On the 18th of May after the solutions were added to the columns and any background level oftoluene was measured, 10 mL ,of toluene was added to each column. The toluene was injected with a: syringe into the sand approximately 1 em below the landscaping material. This was done to minimize surface volatilization and contact with the vermiculite. Mter the toluene was injected, approximately 0.7 L of water was sprayed on the column to simulate a 1 em rainfall. This was done to ensure the toluene would be carried into the column rather than remaining near the surface 59

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where it could easily volatilize. Gas and water samples were collected from the columns every third day for 21 days. Table 3.2 Sand Porosity Detennination Container Weight 29.50 g Sand + Container Weight .. .. 293.20 g Sand Weight 263.70 g Container Volume ASand Volume Packed Sand V Bulk Density (loose sand) Bulk Density (packed sand) Dry Density (sand) Porosity (loose sand) Porosity (packed sand) 184.40 cm3 29.25 cm3 155.15 cm3 1.43 g/cm3 1.70 g/cm3 2.65 glcm3 0.46 0.36 On June 9th, the top 5 em (2 in) of sand was removed from all of the columns except the controls. The sand was replaced with the materials detailed in Table 3.3. This 5 em of material was thoroughly mixed with the remaining top 10 em of sand, resulting in a sand/material mix to 15 em. Mter this process was perfonned the landscaping fabric and venniculite cover was replaced. When the material substitution was completed, another 10 mL of toluene was added to the columns using the method previously discussed and testing resumed every third day. Water or water with hydrogen peroxide was added to the columns initially on a daily basis. Approximately 160 mL of water was added per column. This rate was detennined by the results of an experiment in which water was added to a container of sand and placed on a scale. Weight measurements were then made every five minutes 60

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Table 3.3 Material Additions to the Columns* Prior to the Second Application of Toluene Material Solution Solution Solution Column Column Column 2 3 4 Top Soil (parts) 1 1 2/3 Compost (parts) 113 Vermiculite (parts) Bloodmeal 3 3 (g)**. -. -'" Compost Starter 5 5 5 (g)t Commercial Fertilizer (g)tt *Control columns were not modified **Bloodmeal composition12.().() tCompost starter contained a seaweed base ttCommercial fertilizer composition6-4 Solution Column 5 1 5 5 initially and up to several hours later in the process. Readings were made for approximately 24 hours and an average evaporative flux was determined. This flux. was applied to the column surface to determine the average losses to evaporation. The column loses were determined to vary from 80 mL to 220 mL per day or 0.1 em to 0.3 em per day (160 mL to 380 mUday or 0.2 em to 0.5 em per day without the mulch). The results of this experiment are provided in Tables 3.4 and 3.5. After several days it became obvious that this rate was in excess of what the column was actually losing (the bottom of the columns were becoming increasingly 61

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saturated). To compensate for this the water addition was performed every other day for the remainder of the experiment. 3.2 Nutrient Solutions The first component of all the solutions was the bactericide. Formaldehyde was selected since the literature indicated that it was the most effective against a wide range of bacteria (Cooper and Zepp, 1990) .. Unlike many of the experiments in theliterature which investigated only one type of bacteria, this experiment was expecting a full spectrum of bacteria which made formaldehyde the better choice. The half-life for formaldehyde is 24 to 168 hr (1 to 7 days) in soil and surface water and 48 to 336 hr (2 to 14 days) in groimd water (Howard et al., 1991).This short half life ensures that the interference by the formaldehyde will be minimal within several days of its application. The formaldehyde was applied to the columns at the recommended concentration of the 0.025M (Cooper and Zepp, 1990). The basic nutrient formulas for the coltimns were modifications of the formulas used in an experiment for the microbial degradation of toluene in aquifers of low hydraulic conductivity (Hess,.1993). These formulas were designed to encourage the growth of either aerobic bacteria or anaerobic bacteria. A mineral salts solution was designed to supply vital nutrients to the aerobes while a nitrate mineral salts solution provided the nutrients required by anaerobes (primarily denitrifying Certain nutrients are especially important to all microorganisms. Phosphate is utilized' for the synthesis of nucleic acids and is a major component of A TP. Potassium is required by all microorganisms since it activates enzymes used in the production of proteins. Nitrogen is needed for protein and nucleic-acid synthesis. 62

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a e T bl 3 4 C on tamer E vaporation ate 1 out uc R W"th M I h Container TJDle (date Elapsed Time A Time A Weight A Weight/ Temperatwe Flux Weight (g) hour:mioute) (hour:min) (minutes) (g) A Time (OC) (g/minlcm2) (g/min) 189.06 3/9/94 14:05 0:00 0 0.00 19.0 189.01 3/9/94 14:10 0:05 s 0.05 0.010 19.0 2.598E-04 188.95 3/9/94 14:15 0:10 10 0.11 0.012 19.0 3.118E-04 188.88 3/9/94 14:25 0:20 20 0.18 0.007 24.0 1.819E-04 188.84 3/9/94 14:30 0:25 25 0.22 0.008 24.0 2.079E-04 188.79 3/9/94 14:35 0:30 30 0.27 0.010 2.598E-04 188.74 3/9/94 14:40 0:35 35 0.32 0.010 22.0 2.598E-04 188.69 3/9/94 14:45 0:40 40 0.37 0.010 21.2 2.598E-04 188.63 3/9/94 14:50 0:45 45 0.43 0.012 20.6 3:118E-04 188.60 3/9/94 14:55 0:50 so 0.46 0.006 20.4 1.559E-04 188.56 3/9/94 15:00 0:55 55 0.50 0.008 20.3 188.49 3/9/94 15:05 1:00 60 0.57 0.014 20.0 3.638E-04 188.44 3/9/94 15:10 1:05 65 0.62 0.010 20.0 2.598E-04 188.40 3/9/94 15:15 1:10 70 0.66 0.008 19.8 2.079E-04 188.24 3/9/94 15:30 1:25 85 0.82 0.011 19.8 2.858E-04 188.05 3/9/94 15:51 1:46 106 1.01 0.009 19.8 2.339E-04 187.93 3/9/94 16:05 2:00 120 1.13 0.009 19.8 2.339E-04 187.43 3/9/94 17:05 3:00 180 1.63 0.008 2.079E-04 178.43 3/10/94 11:16 21:11 1271 10.63 0.008 19.8 2.079E-04 178,34 3/10/94 11:28 21:23 1283 10.72 0.008 19.6 2.079E-04 177.92 3/10/94 12:24 22:19 1339 11.14 0.008 20.3 2.079E-04 177.24 3/10/94 13:34 23:29 1409 11.82 0.010 20.3 2.598E-04 Median 0.009 Median 2.339E-04 Stand Dev 1.88E-03 Stand Dev 4.884E-05 Variance 3.53E-06 Variance 2.386E-09 Max Value 0.014 Max Value 3.638E-04 Min Value 0.006 Min Value 1.559E-04 Average Evap Rate for Column (g/min) 1.706E-Ol Water Loss per Day (g "" ml) 2.457E+02 Maximum Evap Rate (glmin) 2.654E-01 Water Loss per Day (g = ml) 3.822E+02 Minimum Evap Rate (g/min) 1.138E-Ol Water Loss per Day (fi = ml) 1.638E+02 63

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a e T bl 3 5C on tamer E vaporatton te 1 c Ra W"thMul h Cootaioer Time (date Elapsed A Time A Weight A Weight/ Temperature Flux Weight (g) bour:mioute) Time (minutes) (g) ATune (OC) (g/mio/cm2) (bour:min) (g/mio) 202.29 3/24/94 10:00 0:00 0 0.00 17.5 202.26 3/24/94 10:05 0:05 5 0.03 0.006 17 5 1.S59E-04 202.22 3/24/94 10:10 0:10 10 0.07 0.008 17.5 2.079E-04 202.19 3/24/94 10: 16 0:16 16 0.10 0.005 17.5 1.299E-04 202.17 3/24/94 10:20 0:20 20 0.12 0.005 17.5 1.299E-04 202.14 3/24/94 10:25 0:25 25 0.15 0.006 18.5 1.559E-04 202.11 3/24/94 10:30 0:30 30 0.18 0.006 19.0 1.559E-04 202.07 3/24/94 10 : 37 0:37 37 0.22 0.006 19. 0 1 559E-04 202.05 3/24/94 10 : 40 0:40 40 0.24 0.007 18.7 l.819E-04 202.02 3/24/94 10:45 0:45 45 0.27 0.006 18.5 201.99 3/24/94 10:5 1 0:51 51 0 .30 0.005 18.2 1.299E-04 201.97 3/24/94 10:55 0:55 55 0.32 0.005 18.0 1.299E-04 201.93 3/24/94 11:01 1:01 61 0.36 0.007 18.0 1.819E-04 201.91 3/24/94 11 :05 1:05 65 0.38 0.005 18.0 1.299E-04 201.87 3/24/94 11:12 1:12 72 0.42 0.006 18.0 1.559E-04 201.80 3/24/94 11:25 1:25 85 0.49 0.005 18.5 1.299E-04 201.41 3/24/94 12:30 2:30 150 0.88 0.006 18.0 1;559E-04 201.12 3/24/94 13:15 3:15 195 1.17 0.006 19.0 1.559E-04 201.06 3/24/94 13:25 3:25 205 1.23 0.006 18.5 1.559E-04 200.93 3/24/94 13:41 3:41 221 1.36 0.008 .. -18 0 200.83 3/24/94 13:58 3:58 238 1.46 0.006 18.0 i.559E-04 200.52 3/24/94 14:40 4:40 280 1.77 0.007 20.0 1.819E-04 200.45 3/24/94 14:50 4:50 290 1.84 0.007 19.0 1.819E-04 200.38 3/24/94 15:01 5:01 301 1.91 0.006 18.5 1.559E-04 195.11 3/25/94 9:46 23:46 1426 7.18 0.005 17.0 1.299E-04 194.97 3/25/94 10:16 0:16 1456 7.32 0.005 17.0 1.299E-04 194.86 3/25194 10:48 0:48 1488 7.43 0.003 17.5 7.795E-05 194.72 3/25/94 11 :24 1:24 1524 7.57 0.004 18.0 1.039E-04 194.56 3/25/94 12:03 2:03 1563 7.73 0.004 20. 0 1.039E-04 194.34 3/25/94 12:53 2:53 1613 7.95 0.004 21.0 1.039E-04 193.85 3/25/94 14:36 4:36 1716 8.44 0.005 72 . 2 .. l.299E-04 Median 0.()06 Median 1.559E-04 Staod Dev 1.15E-03 StaodDev 3.000E-05 Variance 1.33E-06 Variance 9.003E-10 Max Value 0.008 Max Value 2.079E-04 Min Value 0.003 Min Value 7.795E-05 Average Evap Rate for Column (g/min) 1.138E-01 Water Loss per Day (g = ml) 1.638E+02 Maximum Evap Rate (g/mio) 1.517E-01 Water Loss per Day (g = ml) 2.184E+02 Minimum Evap Rate (glmio) 5.688E-02 Water Loss oer Dav (e.-= ml) 8.191E+01 64

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Magnesium activates enzymes and is required for the production and activity of ribosomes, nucleic acids, and cell membranes. Calcium is important for the function of cell walls and the production of bacterial endospores. Iron is an essential trace element which is necessary for the electron transport system of many microorganisms. In addition copper, zinc, cobalt, manganese, and molybdenum are trace elements which important for various functions within the cell (Chapelle, 1993). The original solutions were modified slightly for this experiment. Calcium was added in the form of calcium nitrate and/or calcium chloride since this element is vital to the construction of cell walls. A bromide tracer was added in the form of potassium bromide in order to track the nutrients through the columns. Yeast extract was used in place of a trace solution. Yeast extract is known to contain essential nutrients, but in undefmed amountS. Typically when microbiologists are dealing with microorganisms with unknown nutritional requirements, they will use yeast extract as a catch-all ingredient (Chapelle, 1993). The yeast extract was supplied by Red StarTM Specialty Products in two varieties which were mixed in equal proportions for the solutions. The extracts are essentially composed of yeast which has been specially processed to break open the cell wall. This process allows the.nutrients to be easily utilized. Table 3.6 summarizes the nutritional content of one of the yeast extracts. Hydrogen peroxide was used in the columns which were designed to encourage the growth of aerobes. Oxygen has a low solubility (typically 8-10 mg/L) in water which makes it difficult to supply necessary oxygen to aerobic bacteria which are not in direct contact with atmospheric oxygen. H202 has been one method used for 65

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T bl 3 6 A a e Anal fR d S :rM Ambe 695 Y E act lySIS 0 e tar rex east xtr Vitamins mg/100g mgi100g Thiamine 6.1 Biotin 0.1 Riboflavin 4.1 Pyridoxine 4.2 Hydrochloride Niacin 60.1 Folic Acid 1.3 Pantothenic ACid 4.8 Vitamin B12 <0.1 Minerals mg/100g mg/100g Aluminum 0.4 Magnesium 338.0 Barium 0.2 Manganese 0.8 Calcium 15.9 Phosphorous 2320.0 Chromium 0:2 Potassium 2605.0 Copper 0.3 Sodium 1550.0 Iron 5.7 Zinc 7.0 Alnino Acids mg/g mg/g 39 Lysine 48 Arginine 28 Metethionine 9 Aspartic Acid_ 58 Phenylalanine 24 Glumatic Acid 83 Proline 25 Glycine 29 Threonine 28 Histidine 15 Serine 29 Isoleucine 29 Tryptophan 5 Cystine 7 Tyrosine. 20 Leucine 43 Valiile 34 providing the necessary oxygen supply since the maximum theoretical solubility of pure oxygen released from H202 is 40 mg/L (Spain et al., 1989). Since the H202 addition occurred on a daily or seniidaily basis (mixed in the evaporation makeup water), the concentrations were kept low (30 ml.IL) to reduce the risk of toxic levels being reached (Huling and Bledsoe; 1990). The contents of the various solutions are provided in Table 3.7. 66

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Table 3.7 Solution Nutrient Concentrations Solution Solution Solution Solution Solution 1 2 3 4 5 Nutrients (giL): Ca(N03)H20 -2.36 2.36 2.36 CaCl 0.70 0.50 0.66 -FeNH4 citrate 0.005 0.005 0.005 -KBr -1.00 1.80 1.80 1.80 KH2P04 1.50 1.59 1.50 1.50 MgS04H20 0.17 0.10 0.17 Na2HP04 -4.00 4.18 4.00 4.00 NH4Cl -0.50 0.30 0.30 -Micronutrients (giL): Yeast Extract -1.00 1.00 1.00 -Bactericide (mUL): Fonilaldehyde 2.3 2.3 2.3 2.3 2.3 Oxygen Supply (mUL): H202 -1.003 -1.003 1.003 Solution 1 was placed in the control column and consisted only of tap water and formaldehyde. The decision was made to use tap water in preferericeto distilled or deionized water since this would probably be the most'likely source of water at a field site. Water was added on a daily basis to make up for evaporation losses. Solution 2 was designed to encourage the growth of aerobic bacteria by providing the basic nutrients and trace elements. Hydrogen peroxide was added to the original solution and also to the water added for evaporation losses. The phosphate contained in the nutrient solution provided the stabilizer for the hydrogen peroxide. Nitrogen was added in the form of Nf4Cl, but no nitrate was added to minimize denitrifying effects. 67

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Solution 3 was designed to encourage the denitrifying bacteria. It contained the basic nutrients and trace elements, but the primary source of nitrogen was in the nitrate form (calcium nitrate). No hydrogen peroxide was added to this column and evaporation makeup consisted only of water. Solution 4 encouraged all forms of bacterial action. It contained quantities of nitrate for use by the denitrifiers and H202 was added to the solution and evaporation makeup water for the aerobes. Since the vadose zone contains both aerobic and anaerobic areas, this approach seemed to hold the most promise for active bacteria. Solution 5 was a modification of Solution 4, eliminating the micronutrients. It was hoped that this would provide better information on how vital the trace elements were to this type ofbioremediation. Hydrogen peroxide was added to the original solution. and the makeup water. 3.3 Analytical Equipment Two gas chromatographs and an ion chromatograph were required to analyze the gas and water samples for the experiment. 3.3.1 Photovac Gas Chromatograph A Photovac Model 10S30 portable photoionization gas chromatograph (GC) was initially used to analyze the soil gas for toluene. The Photovac uses a photoionization detector (PID)which is very sensitive to many aromatic hydrocarbons (e.g., Photovac indicates that the 10S30 can detect benzene to an air concentration ofO.l parts-per billion (ppb)). Soil gas samples are removed from the columns using small volume gas syringes (250 J.1L Hamilton syringe) and then injected into the Photovac through a 68

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septum. The sample then passes through the gas chromatograph column which separates the gas into its various components and then on to the photoionization detector. The sample is carried through the machine by the "carrier gas" which was nitrogen in this case (zero grade air and helium may also be used). The carrier gas was supplied at a rate of 20 mUmin by a gas cylinder and regulated to a pressure of 280 kPa (40 psi) prior to use in the instrument. The PID portion of the instrument operates using an ultraviolet (UV) light. illtraviolet light has a high energy of about 11 electron volts (eV) which is directed into a small chamber through which the gas-stream passes. The detector consists of two electrodes which have a potential of 300 V across them with the negative electrode connected to an extremely sensitive amplifier. Any gas component which has an ionization potential of less than 11 e V will be ionized by. the electrodes. These ions are "counted" by the detector and generate a signal which is recorded as a peak on a chromatograph. IIi order to maintain its portability, the Photovac has a different approach to the thennal stability of the GC column. Most laboratory gas chromatograph columns are heated and maintained at a steady temperature. This allows compounds to pass more quickly through the column and ensures the compound will come through at approximately the same retention times. There is also the problem that some compounds (typically large molecules such as PCBs, dioxin, most pesticides and herbicides) will never even make it through the column unless they are heated. Temperature variations can also affect the strength of the signal. 69

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This model of Photovac remains portable by not usmg an oven and instead, calibrating the instrument frequently using a known standard. Its main focus is on the detection of contaminants in air or vapors which typically do not contain the large "problem" molecules. The toluene stock-standard solution for the experiment was prepared by the USGS National Water Quality Lab in Arvada, Colorado. The stock-standard solution consisted of 60 J.lg toluene being added to a 1 mL container with the remainder of the volume being filled with methanol. This solution was placed in 1 mL brown vials with Teflon-lined screw caps and was stored at 0C. Three of these vials were supplied for the experiment The working-standard solution was prepared by adding 5 J.1.L of the stock-standard solution to 20 mL of organic-free water (deionized water which has been boiled for 30 minutes). The 5 J.1.L is obtained using a Drummond microcap and adding it to a 40 mL volatile organic analysis (VOA) vial which contains the 20 mL of organic-free water. The VOA vials contain a septum which allows the headspace gas to be sampled. Typically two working standards were prepared each day, one for the morning and another for the afternoon. Three volumes of the gas probes were removed prior to sample collection. This ensured the sample consisted of soil ga:s and not products of reaction with the probe or outside air which had leaked into the system. The typical sample size was lOOJ.l.L, but occasionally larger or smaller samples were taken due to toluene concentrations. Standards were injected after 10 to 20 samples depending on how rapidly the room temperature was changing. 70

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The Photovac provided a strip chart recording of the chromatograph from which a peak height can be determined. Figure 3.4 illustrates an example of the Photovac output The peak height of the sample was compared to the peak height of the standard to determine the concentration of the sample. This method was used for the first three test days. On later test days the detector signal was supplied to a Spectra Physics integrator which provided the area under the trace of the chromatograph. This method compares the area of the sample peak to the area of the standard peak and is slightly more accurate than the peak height method. The integrator reduced the time required to analyze the data since peak heights did not have to measured by hand. Occasionally, however, the integrator would produce false data due to an inappropriate selection of the signal baseline. On these occasions the peak heights would be used to determine the concentrations. No toluene samples were collected for the test date of.6/14/94 due to a problem with the Photovac. When the instrument was turned on the signal out of range and no adjustments would bring it back into range. The instrument was returned. to Photovac, which replaced its detecto.r and cycled the column through a high temperature oven. A contamination due to a large sized molecule was the suspected cause of the problem. The last four sampling days of the experiment were performed by a Photovac ModellOS50. This instrument used the same principles as the ModellOS30 but had a self contained integrator which used the standard for calibration and automatically determined the sample concentration. 71

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Figure 3.4 Sample Photovac GC Output IPHOTOUAC I SfPIH ------------------------------(" I I . srPr 8------------.. I'T I JU" '25 .9 a TOLU["[ TEr.P n 100 UL GfJioi '21a0 UI'ICI'OUJ< 1 ze.a us 3''1 I"MI 3.3.2 Chrompack Packard Gas Chromatograph A Chrompack Packard Model 439 gas chromatograph equipped with an electron capture detector (ECD) was used to measure the nitrous oxide concentrations in the soil gas. The ECD is the most sensitive GC detector for certain types of compounds which capture electrons. It uses a beta ray emitting radioactive source (63Ni) which is used to ionize the carrier gas into pairs of positive ions and electrons. The electrons on the carrier gas are available for capture by the compounds contained in the sample. The 72

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resulting drop in measurable current due to the captured electrons is measured by two electrodes across which a potential is periodically applied (Ravindranath, 1989). The ECD is particularly sensitive to many halo, haloacyl, nitro, pentafluorophenyl, and boronic acid derivatives (these include environniental hazards such as pesticides and polychlorinated biphenyls). The GC column was a Supelco 1.8 m x 0.32 em (6ft x 1/8 in) stainless steel packed column with Chromosorb Q as the packing material. The carrier gas for the Chrompack was P5, a mixture of95% argon and 5% methane, and was supplied by a gas cylinder and regulated down to 280 kPa (40 psi) at a rate of 40mUmin. Compressed air was used as the service gas to open and shut the GC valves. Gas samples were collected with a 10 cc glass B&D syringe. Three volumes of the gas probe was removed using the syringe prior to collecting a sample for analysis. This ensured that the analysis included only soil gas and minimized the possibility of collecting gases that leaked into the system between tests. The valve on the gas probe was kept closed between test days to minimize contamination from outside air and also the introduction of oxygen into the system. The samples were compared to a set of three different standard concentrations which were obtained from Scott. Specialty Gases. The standard concentrations included 3.11, 30.7, and 301 ppm of nitrous oxide. The signal from the Chrompack was interpreted by a Spectra Physics Model 439 integrator which supplied peak areas. Figure 3.5 is an example of the Chrompack output 73

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Figure 3.5 Sample Chrompack Packard GC Output INJECT 06/05/94 99:21:11 . . 5z ER 0 HITRO 09:21:11 CH= "A" PS= 1. FILE 1. t1ETHOD 0. 27 IHDEX 27 PEAK# A REAr. RT AREA BC 1 0.079 0.27 780 02 2 0.075 0.3:9 745 e:::o J 95.71 0.52 948582 08 4 0.018 0.95 182 06 5 0.821 1.12 8134 06 6 0.01 1. 3.2 101 07 7 3.287 2.29 32581 01 3.3.3 Wescan Ion Chromatograph Water samples from the columns were analyzed for standard anions with a Wescan Ion Chromatograph (IC) System. The system consisted of a Wescan VersaPump ill, an ICM-Ion Chromatograph Module, and an Autosampler. The IC was equipped with a Wescan Anion!R Column and used 5 millimolar p hydroxybenzote with a pH of 8.5 as an eluant. The eluant was prepared prior to each run by adding a 50 mL bottle of Alltech EZ-LUTE to a 2 liter container and filling the container the rest of the way with 74

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degassed, deionized water. The pH of the solution was then adjusted to 8.5 using lithium hydroxide. The eluant was pumped through the IC at a rate of 1.8 mUrnin. Samples were injected into the system by the autosampler which had the capacity for 64 samples. The ion chromatograph determined the concentration of the anions in the eluant by measuring the conductivity of the solution. This was compared to a standard (Alltech Multi-Anion Solution Mixture A) of known concentration. The standard contained 30Jlg/mL of POt and Sbj; 20 Jlg/mL of Br-, Cr, NOj, and NOi; and lOJ.lg/mL of F. Standard solutions and deionized water blanks were randomly placed in the autosampler for quality control. The IC signal was recorded with a Spectra Physics Model439 integrator and the peak areas were compared to determine the concentrations. Figure 3.6 is an example of the IC output The IC pump failed on 6/22/94 and needed to be sent to a specialty instrument company for repairs. Since the pump was originally manufactured in Australia, repairs required a lengthy period of time. This resulted in the use of a Dionex Ion Chromatograph for the completion of the sampling. The Dionex was already set up for analyzing standard anions, but its configuration did not detect phosphates. The Alltech Multi-Anion Solution Mixture A standard was used to ensure consistent results with the Wescan IC. 75

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Figure 3.6 Sample Wescan IC Output CHAHHEL A INJECT 06/18/94 04:24:25 32 9. 39 --=========-:11. 46 15. 139 19.]6 29.32ER e 6.96 NITRO 06/18/94 04:24:25 CH= "A.. PS= 1. FILE 1. PEAK# 1 2 ] 4 s 6 7 8 9 1.13 :11 12 13 i4 TOTAL 0. AREA% (1. 001 47.335 7.:37:1 3.1.134 2.197 1.:1.45 1:1.378 8 .. 977 9.922 4.652 1.375 0.097 0. 1319 0.018 108. RT 13.75 1.44 2.05 3.05 3.56 4.49 6.96 8. ]2 11.46 15.09 17.16 19.36 20.32 RUt! 131 BC 42 131 1353183 02 225009 02 88723"02 62797 02 89905 02 325252 l,j] 256616 132 283642 09 132992 0:1 393.19 0:3 203 05 535 132 505 13] 2858723 76

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4. Results and Discussion 4.1 Soil Effects Chapter 4 The fll'St major surprise produced by this experiment occurred during the initial addition of solutions 1 and 3 to the columns. The solutions were added beginning at approximately 10:30 AM on the 9th of May. By approximately 7:30AM the following morning there was evidence of saturation at the bottom of most of the columns with water dripping out of any opening which was not properly sealed. The drainage ports were opened to allow excessive water to drain off and maintain an unsaturated state The flrst suspect was an improper calculation of the porosity. The porosity experiment was repeated but with similar results. In the approximate 20 hours that the drip system was on, a little less than two-thirds of the prepared solution had been added to the columns. This would correspond to approximately 60 L of solution distributed to 3 columns or 20 L per column (an application rate of 1 L per hour per column compared to a design rate of7.6 L per hour). The second set of solutions was prepared (4 and 5), but additional safety factors were added which resulted in a demand for 18 L of solution per column.(this corresponded to a porosity of0.24 at a degree of saturation of0.70). Solutions 4 and 5 were added to the columns beginning at 11:00 AM on May 12th. Once again by 7:00AM the following morning there was evidence of saturation at the bottom of several of the columns. 77

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Since the tests and the literature indicated that the porosity for a uniform sand should be within the range of 0.35-0.36, it was not immediately obvious what was occurring. Several articles which were presented at the USGS Unsaturated-Zone Hydrology class provided a clue. Often flow through a uniform sand is modeled assuming a homogeneous, isotropic media Experiments have increasingly pointed out, however, that in actuality these uniform sands have heterogeneous properties (Ghodrati and Jury, 1990; Jardine et al., 1988; Jaynes et al., 1988; Kung, 1988). These materials in actuality exhibit preferential flow which can be called wetting front instability, partial volume flow, or "fingering". This effect was found to occur with particular frequency in air-dry sands (Baker and Hillel, 1991). Instead of the columns "wetting up" in a uniform manner, fmgering would allow preferential pathways to fonn. This would result in sections of the columns remaining dry while the bottom ofthe column would become a reservoir for the solution. The column instrumentation was also a possible_ cause of preferential pathways. Since the., suction lysimeters and gas ports were installed prior to the addition of the sand, nonuniform packing around these probes potentially could cause variations in porosity. The net result could be the formation of a type of macropore. The overburden of the sand under the lysimeters would be different from the sand next to the lysimeter since the probe was supported by the wall of the column. This also would affect the porosity of the surrounding sand. Since it was impossible to predict the actual moisture content of the columns, each column was drained to ensure that the majority of the sand would be unsaturated. 78

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The original plan was to quantify all moisture added to and removed from the columns, but this plan was abandoned due to the fmgering. One method to counter this in any future experiment would be to position each of the columns on a scale. 4.2 Toluene Degradation Figure 4.1 summarizes the average amount of toluene in the different types of columns over the course of the experiment (detailed graphs of the levels in each type of column and tabular data are provided in Appendix A, Table A1 & Figures A1). After experiencing toluene levels as high as 350 ppm in portions of the columns on day 6, levels fall to less than 1 ppm by day 9. This corresponds to what would be expected in population dynamics of microorganisms (see mathematical relationship on page 21). The literature lists the half-life of toluene in soil to be 96 hours (4 days) to 528 hours (22 days) (Howard et al., This level of degradation was achieved in the columns somewhere between 6 and 9 days. The length of time required for the degradation is largely dependent on the population of microorganisms acclimating to the substrate. The control column data shows a plateau between the third and sixth sampling day. The most probable explanation for this would be a missed peak, Figure 4.2 shows a theoretical peak generated by extrapolation of the slopes on either side. Of course the other peaks show evidence of this effect, but were not as easily extrapolated. It was surprising to see how effective the microorganisms were even in the control columns. The lag period was expected to be longer since the columns initially contained dry sand (typically not high in microbial activity) and were treated with formaldehyde as a bactericide. There was some delay, however, between the addition 79

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Figure 4.1 Average Column Toluene Concentrations 300000 250000 1: 200000 Colt Avg '-' c .s b c 8 c c u .c c. .Col2Avg 150000 Col3 Avg A Col4Avg 100000 Col5 Avg 50000 0 3 6 9 12 15 18 21 24. 27 -30 33 36. -39" 42 Sampling Day Figure 4.2 Average Column Toluene Concentrations with Hypothetical Peak for Column 1 400000 Colt Avg Col2Avg Col3 Avg ,so 300000 :6 Col4Avg c c ;: .. c Gl u c c u Col5 Avg ---D-HypColt Avg 200000 100000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day of the fonnaldehyde and the beginning of the experiment due to the time required to add the solutions to the columns. This may have degraded a large portion of the 80

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formaldehyde even before the experiment started. The control columns experienced a slightly longer lag period (as seen by the higher concentrations on day 6), but by day 9 achieved results almost equal to the columns supplied with nutrients. Figure 4.3 shows the difference between the columns from day 9 through the day 21. Detailed graphs of all the columns are provided in Appendix A, Figures A2. Figure 4.3 Average Column Toluene Concentrations 1st Application -.c g. g. c .s = "' -c u Col c Q u 700 600 500 400 300 200 100 0 9 12 15 Sampling Day Colt Avg 0 Col2 Avg 0 Col3 Avg 6 Col4Avg ColS Avg 18 21 In order to verify that the toluene loss was the result of biodegradation and not other physical effects, the water balance for the columns was closely examined. Since the water added to the columns for evaporative losses proved to be in excess of the actual column need, another method was used to determine the probable losses. The temperatures which occurred during the course of the experiment ranged from 16 to 30C, with an average temperature of approximately 25C (Figure 4.4 shows the average temperatures which occurred on the test days). The maximum amount of water which can be absorbed by dry air is the vapor pressure. The vapor 81

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pressures corresponding to the temperatures experienced during the experiment were located in the literature (Wark, 1977). By combining Dalton's law of partial pressures with Henry's law, it can be shown that the partial pressure and the vapor pressure are related by relative humidity (Sawyer and McCarty, 1978; Sears and Zemansky, 1970). . partial pressure of water vapor Relauve humtdtty (%) = 100 x vapor pressure at same temperature (4-1) The air flow through the room containing the columns was detennined by assuming 200 cfm of ventilation air and an additional 500 cfm being removed by two operating laboratory exhaust fans (the fans were both rated at 250 cfm and were left running the duration of the experiment to ensure toluene levels in the air did not exceed the 100 ppm, 8 hour exposure limit established by OSHA). Table 4.1 shows the amount of water which can be absorbed over the 16C to 30C range of temperatures and relative humidities from 20 to 80%. It also specifies the expected amount of moisture which could be lost by each column under these conditions. Values range from 46.2 g of water per day (or 0.06 em per day) at 30C and 20% relative humidity to 5.2 g per day (or 0.01 em per day) at l6C and 80% relative humidity. The average measured toluene concentrations in the various columns on day 6 was then used to detennine how much toluene would be lost in the corresponding amount of water. Values ranged from 6.8x10-3 to 2.9x10-4 g toluene per day. Since 8.6 g (10 cc) of toluene was added to the columns, the evaporation would only account for 0.2% to 0.01% of the total loss of toluene over a 3 day period. This method, however, assumed that the toluene thoroughly mixed with the solution in the column. If instead the toluene achieved its maximum solubility in portions of the water and did 82

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not thoroughly mix, 0.8% to 0.09% could be lost in three days (see Table 4.2). There is also the possibility of pockets of toluene which did not mix with the water and volatilized according to air and soil conditions. This loss would be difficult to quantify without extensive testing of the gas at the surface of the column (which was not perfonned due to time constraints). Figure 4.4 Average Lab Temperature For Sampling Days u 0 -f :1 ... .. u 1:1. E e: ... u 28 26 24 22 20 18 16 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Using average measured toluene concentrations in the various levels, the amount of which could still be in the columns .on day 6 was calculated. Assumptions included: all of the toluene was contained in the solution; the concentrations were essentially the same throughout the level; porosity varied slightly from the top to the bottom of the column, and the water content varied from the top to the bottom (this was based on the amount of sample obtained by the lysimeters at the.different levels). Calculated values for water content varied from 7.3 g to 5.1 g (15% to 40% decrease) 83

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of toluene by the sixth day (see Table 4.3). Since the evaporation rate with thoroughly mixed toluene can not account for this and the only possibilities are that biological agents are at work and potentially some of the toluene vaporized at an initial rapid rate a e axnnwn ater ss ueto vaporation T bl 41 M W Lo D E . Maximum Amount of Water Which Air Can Absorb at Various Relative Humidities (per day) Temp Vapor RH= RH= RH= RH= RH= RH= RH= (oC) Pressure 20% 30% 40% SO% 60% 70% 80% 16 0.018 310.9 272.0 233.2 194.3 155.4 116.6 77.7 18 0.021 350.5 306.7 262.9 219.1 175.3 131.4 87.6 20 0.023 394.5 345.2 295.9 246.6 197.3 147.9 98.6 22 0.026 443.1 387.7 332.3 276.9 221.5 166.2 110.8 24 0.030 496.7 434.6 372.5 310.4 248.3 186.3 124.2 26 0.034 555.8 486.4 416.9 347.4 277.9 208.4 139.0 28 0.038 .620.9 543.3 465.7 388.1 310.5 232.9 155.2 30 0.042 692.5 .606.0 519.4 432.8 346.3 259.7 173.1 Maximum Amount of Water Loss Per Column Due to Evaporation Temp RH= RH= RH RH= RH= RH= RH= (OC) . 20% 30% =40% 50% 60% 70% 80% 16 20.7 18.1 15.5 13.0 10.4 7.8 5.2 18 23.4 20.4 17.5 14.6 11.7 8.8 5.8 20 26.3 23.0 19.7 16.4 13.2 9.9 6.6 22 29.5 25.8 22.2 18.5 14.8 11.1 7.4 24 33.1 29.0 24.8 20.7 16.6 12.4 8.3 26 37.1 32.4 27.8 23.2 18.5 13.9 9.3 28 41.4 36.2 31.0 25.9 20.7 15.5 10.3 30 46.2 40.4 34.6 28.9 23.1 17.3 11.5 84

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a e ouene T bl 42 T 1 Lo D ss ueto E vaporation Column 1 Column2 Column 3 Column4 ColumnS Average 1.46E+05 7.94E+04 6.36E+04 5.98E+04 5.51E+04 Toluene (' Conditions Daily Water Toluene Toluene Toluene Toluene Toluene Loss (g) Lost with Lost with Lost with Lost with Lost with Water Water Water Water Water Column 1 Column 2 Column 3 Column 4 Column 5 (g) (g) (g) (g) (g) 30C@ 20% 46.17 6.75E-03 3.66E-03 2.94E-03 2.76E-03 2.54E-03 RH 23C@ 50% 19.55 2.86E-03 1.55E-03 1.24E-03 1.17E-03 1.08E-03 RH .. . .. 16C @80% 5.18 7.58E-04 4.11E-04 3.29E-04 3.10E-04 2.85E-04 RH Toluene Lost with Daily Water Water Conditions Assuming Loss (g) Max Solubility (g) 30C@ 20% 46.17 2.42E-02 RH 23C@ 50% 19.55 1.02E-02 RH 16C@ 80% 5.18 2.71E-03 RH Solubility in Water (mg/L) @ 25C 524 85

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T bl 4 3 P "bl A a e OSSl e verage c 1 T 1 o umn o uene Le Is D 6 ve on ay Average Average Average Average Average Toluene Toluene Toluene Toluene Toluene Level ContentContentContent-Content-Content-Column 1 Column 2 Column 3 Column4 Column (ppb) (ppb) (ppb) (ppb) 5 (ppb) a 146269 79365 63594 59798 55100 b 317187 232654 158081 185783 136220 c 240807 193146 426174 261988 253152 d 317663 305305 318444 356713 227733 QtyToluene 0.67 0.36 0.29 0.27 0.25 Level a (g) Qty Toluene 1.91 1.40 0.95 1.12 0.82 Level b (g) QtyToluene 1.75 1.41 3.10 1.91 1.84 Levelc (g) QtyToluene 2.97 2.86 2.98 3.34 2.13 Level d (g) Total Toluene 7.31 6.03 7.33 6.64 5.05 in Column (g) Level Porosity Degree of Possible Assumed (assumedj Saturation Water Water (assumed) Content Content (mL)-(mL) 100% Saturated a 0.42 0.40 11492 4597 b 0.40 0.55 10945 6020 c 0.38 0.70 10398 7278 d 0.36 0.95 9850 9358 The odor of toluene was present for the first several days of the experiment The observed odor would indicate toluene in concentrations above the human detection limit of 0.26 ppm to 26.0 ppm. This would correspond to water concentrations of 0.9 ppm to 90 ppm using the non-dimensional Henry's law constant (H): 86

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H'-Csl (4-2) where Csg is the concentration of the compound in the gas phase and C61 is the concentration of the liquid phase (Lyman et al., 1990). Water containing the maximum amount of toluene which can be absorbed would contain approximately 600 ppm of the compound. One other path for the loss of toluene is the loss of solution due to sampling or drainage. Several of the columns became sufficiently saturated to cause solution to escape through the drainage port of the level e lysimeter without any suction applied. When this occurred, a suction would be applied to the system and the excess water would be removed. Up to one liter of solution would be removed from some of the columns in this manner. This method of drainage was not used until after the eleventh day of the experiment, two days after the large drop in toluene levels was observed. Sampling should not have been a major factor in the removal of toluene since the average amount of solution removed from each column per sampling day was approximately 24 mL. This represents less than 0.1% of the total fluid volume. The combined total of all the samples taken over the course of the experiment would amount to 1.0% of the column moisture content The sudden drop in toluene levels from day 6 to day 9 can only be explained by biological activity. The high concentrations measur in every part of the columns on day 6 show that the toluene was widely distributed and not subject to severe volatilization from the top of the column. Using the concentration difference between the two sampling days, a rate of somewhere between 1.5 and 2.3 g per day of toluene 87

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was destroyed. This is two to three orders of magnitude above the expected evaporation losses. The toluene levels recorded on the third day of the experiment are more difficult to explain than the rate of toluene destruction seen between day 6 and 9. All of the toluene measurements are lower than the concentrations recorded three days later. One possibility is that the toluene followed the "fingers" and did not mix thoroughly with the rest of the column moisture. Another possibility would be instrument error, but that raises the question of which day was in error, the third or sixth day. It is understandable that several measurements could be-wr-ong;but all of the data follows the general trend of one level on the third day and a higher level on the sixth day. If the toluene failed to move down into the column it could easily volatilize from the surface, which would explain day 3 but.not day 6. With no additional information available, the data muSt be assumed to be-correct.-...... .. ... .. . .... '" ---As a comparison, two of the columns which appeared to be anoiUalous were removed from the data set in order to see what the effects where on the average toluene levels (see Figure 4.5). Solution column 1C was removed from the data set since the sand in this column was different from the other columns. The sand in 1 C was the same grid size but was white in color rather than the tan of the other sand. Solution column 4A was also eliminated since it experienced a much higher flux of nitrous oxide than the other columns with the same solution: Thereswt when these two columns were removed from the data was that solution column 4 had the highest concentrationon the sampling day 6, increasing by approximately 100 ppm. Tabular "scrubbed" average data is provided in Appendix A, Table A3. 88

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4.5 Average Column Toluene Concentrations (Suspect Column Data Removed) 300000 .c g. g. -c 0 -.... .. .... c u Col c 0 u Coil Avg Col2Avg 200000 0 Col3 Avg .. Col4Avg ColS Avg 100000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure 4.6 provides the average toluene concentrations for the second half of the experiment (graphs of each column type are provided in Appendix A, Figures A3). It is provided at a different scale since the results are not apparent on Figure 4.1. The data in Figure 4.6 show that the average levels of toluene are two orders of magnitude less than what occuned after the first application. This indicates that an efficient population of bacteria exist iD: all of the columns, with the control column having the least efficient population. Columns 2, 3, and 5 appear to be the most efficient (respective concentratipn standard deviation: 169 ppb; 170 ppb; 172 ppb), but column 4 is within a similar range (291 ppb). Tabular average data is provided in Table A2. Using the "scrubbed" data, column 1 has slightly higher values (866 ppb), but column 4 now appears to be the most effective by day 24 (104 ppb) (see Figure 4.7). 89

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Figure 4.6 Average Coli.Jmn Toluene Concentrations 2nd Application ............................................................ ......................... 700 600 .,Q Cl. Cl. 500 .._, Coil Avg Coi2Avg c Col3 Avg .s 400 .. eG "" A Coi4Avg CoiS Avg .. 300 c Gl Col c 200 u 100 0 21 24 27 30 33 36 39 42 Sampling Day Figure 4. 7 Average Column Toluene Concentrations (2nd Application) (Suspect Column Data Removed) 1000 800 .,Q Cl. Coil Avg Cl. -600 c Coi2Avg a Col3 Avg .. eG "" A Coi4Avg .. 400 c Gl CoiS Avg Col c u 200 0 21 24 27 30 33 36 39 42 Sampling Day 90

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A missing piece of infonnation is the toluene concentration data from day 6 after the second application. This is the day that the Photovac failed Since the highest toluene levels were recorded on day 6 'after the first application, there is the possibility that this occurred again on the second application. An obvious observation which makes this unlikely was the lack of toluene odor near the columns shortly after the second application. While the odor was quite noticeable for at least a week after the first application, there was little if any odor by the first sampling day after the second application. As expected, the control columns had the highest remaining amount of toluene but this level was two orders of magnitude less than the concentrations experienced six days into the first application. Essentially 99.8% of the toluene had disappeared from the coluinn within three days. In comparison, 99.9% had been removed from the treated columns. However, additional factors could be involved in the second application. Replacing the top 5 em of sand with top soil, compost, and/or vermiculite introduced new unknowns into the experiment. The idea behind this addition was to provide a medium which would contain approximately the same nutrients as contained in the original solutions and also provide the organic material which should be rich in enzymes to assist in the utilization of the toluene as a substrate. The venniculite was added to solution columns 5 to provide a mixing material without adding extra nutrients. The problem with this introduction of materials was that the top soil, compost, and venniculite added media with a higher cation exchange capacities (CEC) which could adsorb some of the toluene. 91

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Figures 4.8a through d and 4.9a through d present a representative graphs of the concentrations of toluene throughout a column. A general trend observed in some of the columns can be seen with column 4C. After the first application the majority of the toluene appeared to move to the bottom of the columns, but after the second application the concentration seemed to remain approximately the same throughout the column or decrease near the bottom. This indicated that the toluene was being degraded at a rate equal to or greater than the rate that it could move down through the column. A similar distribution of toluene can be observed in some of the control columns. This suggests that the effect was due to biodegradation rather than' CEC (see Figures 4.1 Oa through d and 4.11 a through d). Graphs of the remaining columns are presented in Appendix A, Figures A4 through A9. A secondary peak showed up on the chromatographs of several of the columns on the last two test days (see Figure 4.12). It appeared in solution column 2C at the lowest level on the 23th of June and then appeared in columns 2A, 2B, 2C and 3C on the 25th of June. Its appearance in all of the number two columns suggests that there is a similar process occurring in these <;:olumns and not in the others (except 3C). The peak's retention time was close to that of benzene, but could be several other aromatic compounds. Analysis on a mass spectrometer would be the only method of accurately determining the identity of the compound. One of the main objectives of this experiment was to determine the effectiveness of the various solutions compared to a control. The solutions performed a more complete cleanup throughout the experiment when compared to the control. The average data indicates that order of performance, best to worst, is column 5, 2, 4, and 2 92

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Figure 4.8a Toluene Concentration Column 4, Level a 600000 500000 ..= 8:400000 c b c 200000 c u 100000 4Aa 4Ba 4Ca 0 3 6 9 12 15 18 21 24 2730 33 36 39 42 Sampling Day Figure 4.8b Toluene Concentration Column 4, Level b 500000 :ii' 8:400000 -c 200000 u 100000 4Ab o 4Bb 4Cb 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 93

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Figure 4.8c Toluene Concentration Column 4, Level c 500000 oCI 8:400000 -c i 200000 8 100000 4Ac 4Bc 4Cc 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure 4.8d Toluene Concentration Column 4, Level d 4Ad 4Bd 4Cd 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 94

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-""' ""' c 0 -.. "" .. c u 0 u ""' ""' c 0 .. .t: c 8 c 0 u Figure 4.9a Toluene Concentration (2nd AppUcation) Column 4, Level a 1000 800 600 400 200 0 21 24 27 30 33 Sampling Day 36 4Aa O 4Ba 4Ca 39 Figure 4.9b Toluene Concentration (2nd AppUcation) Column 4, Level b 1000 800 600 400 200 0 4Ab 0 4Bb 4Cb 42 21 24 27 30 33 36 39 42 Sampling Day 95

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-,Q ca. ca. -c 0 -.... "' .... c u 1:1 0 u -,Q ca. ca. -c 0 -.... ... .... c u u c 0 u Figure 4.9c Toluene Concentration (2nd Application) Column 4, Level c 800 D-4Ac 600 4Bc 4Cc 400 200 0 21 24 27 30 33 36 39 42 Sampling Day Figure 4.9d Toluene Concentration (2nd Application) Column 4, Level d 800 D-4Ad 600 4Bd 4Cd 400 200 0 21 24 27 30 33 36 39 42 Sampling Day 96

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Figure 4.10a Toluene Concentration-Column 1, Level a 600000 1Aa 1Ba 1Ca 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure 4.10b Toluene Concentration-Column 1, Level b 600000 Cl. '-' j 400000 = u DlAb o 1Bb lCb 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 97

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Figure 4.10c Toluene Concentration Column 1, Level c 1400000 1200000 -c 800000 lAc 0 lBc = b 600000 0 lCc c u 400000 c 0 tJ 200000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure 4.10d Toluene Concentration Column 1, Level d 600000 500000 ,!; 400000 ... b300000 c u 8 200000 tJ 100000 lAd 0 lBd lCd 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 98

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-,.CI c. c. c .s .. b c c 0 u ::ci' c. c. c 0 -.. .. .. c c 0 u Figure 4.11a Toluene Concentration (2nd Application) Column 1, Level a 2000 1800 1600 1400 1200 1000 800 600 400 200 0 lAa lBa lCa 21 24 27 30 33 36 39 42 Sampling Day Figure 4.11b Toluene Concentration (2nd Application) Column 1, Level b 1800 1600 1400 1200 1000 800 600 400 200 0 21 24 27 30 33 Sampling Day 99 36 lAb o lBb lCb 39 42

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.c ==--c 0 -II "' c a ==--c 0 -II b c II u c 0 u Figure 4.11c Toluene Concentration (2nd Application) Column 1, Level c 1800 1600 1400 1200 800 600 400 200 0 21 24 27 30 33 Sampling Day 36 39 lAc lBc ICc Figure 4.11d Toluene Concentration (2nd Application) Column 1, Level d 1800 1600 1400 1200 1000 800 600 400 200 0 lAd lBd lCd 42 21 24 27 30 33 36 39 42 Sampling Day 100

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Figure 4.12 Unidentified Peak Prior to Toluene Elution IPHOTOUAC I Sf PitT-------_----------------------. Clot" a 7 ... g.11 Sf'l1f"L LJBRPR.,. I Jill< '25 1391 15,46. f'f'f'LTSIS R '11 TOLUE:,. Sf'flf'LE I,.TEI' .. f'L T' ']<; Jl!ll Ill &JtoiJ(I"DUf'l. J J2.D' vs '2 JD'2.1 ,.us TDLU[I
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having the most nutrients and oxygen to work with; column 2 having the appropriate nutrients and an oxygen supply for aerobic degradation; column 3 taking advantage of the denitrifiers, which typically have a slower metabolism; and column 5 lacking micronutrients was expected not to perform as well. Instead column 5 was a consistent performer, along with columns 2 and 3. Column 4's performance varies depending on the data set used. Even the control columns are essentially in the appropriate range when compared to the toluene maximum contaminant limit (MCL) of 1 ppm for ground water. Toluene levels dropped to very low levels by the end of the experiment The .. final average concentrations in the columns are as follows: column 1, 89 ppb; column 2, 23 ppb; column 3, 10 ppb; column 4, 16 ppb; and column 5, 10 ppb. The resulting ranking would be (best to worse): column 5, 3, 4, 2, and 1. Column 4 and 5 are obviously not following their predicted rankings. The quality of the data needs to be examined prior to passing judgment on one solution or another. The Photovac is a field instrument and is used to prove the existence. of hydrocarbons to extremely low concentrations. The actual number generated by the instrument, however, should be viewed as qualitative rather than quantitative data. Temperature, pressure variations, along With slight variations in the collection methods affect the readings. The standard provides information about the amount of toluene in the headspace volume above an equal volume of water. This comparison may not be totally appropriate when dealing with soils which have varying ratios of soil gas to soil moisture ratios within the pores. 102

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4.3 Nitrous Oxide Generation One method used to verify the existence of denitrifying bacteria is to perform soil gas sampling and look for the generation of nitrous oxide. All of the gas ports were sampled prior to the addition of the toluene and were found to have N20 levels approximately equal to the surrounding air (0.4 ppm). The average nitrous oxide concentrations for the various columns is presented in Figure 4.13 (detailed graphs of each column and tabular data are provided in Appendix B, Table B 1, Figures B1-1 through 5). The graph indicates that while there was a small rise in N20 around the 9th day of the experiment, the majority of the nitrous oxide generation occurred after the second application of.the toluene on day 21. .-. .= Cl. Cl. c .i .... f c Gl (,1 5 u Figure 4.13 Average Column Nitrous Oxide Concentrations 50000 40000 30000 o-Coll Avg Col2Avg D Col3 Avg 20000 Col4Avg Col5 Avg 10000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day The major exception to this is solution column 4 which experienced a dramatic jump in N20 levels between the 18th and 21st day of the experiment Nitrous oxide 103

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concentrations jumped from a column average of 1.2 ppm on June 5th io 113.1 ppm on June 8th. This type of increase is consistent with the population dynamics of bacterial growth. This also indicates that the denitrifiers required a lag period of at least 18 days. A closer look at the data reveals that solution column 4A was the frrst to develop the denitrifying population. Column 4B followed approximately six days later with not quite as dramatic a rise. Column 4C, however, showed a small rise on the 11th of June, but then returned to a fairly steady level of approximately 1.0 ppm. Solution 3 also contained nitrate and solution column 3B shows a sharp increase on the 11th of June (1.0 ppm to 32.0 ppm at some levels) but then drops back down to a more steady rate. Columns 3A and 3C do not show the same sharp rise, but this may be a function of the time period between sampling days. The actual peaks may have been missed. Solution 2 had no nitrate but column 2 shows a gradual rise in nitrous oxide concentration after the second toluene application. This can be easily explained by the addition of the top soil. prior to the. second application. Tests with the ion chromatograph indicated that the top soil contained approximately 0.11% nitrate and 0.10% nitrite. The generation of nitrous oxide indicates a viable denitrifying population was contained in the soil. The most surprising result occurred in solution column 5. This column had an initial application of nitrate and additional nitrogen was provided prior to the second application. The column performed well in the biodegradation of the toluene, but very little nitrous oxide was generated. This column received only macronutrients. The application of commercial fertilizer after the second application may have contained 104

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some micronutrients. There are small variations in N 2 0 in the first 21 days, but after the second application, levels actually drop and then begin a slow rise. This rise would be consistent with the other columns with nitrate, only it occurred at the end of the second application rather than the frrst The column remained aerobic until late in the experiment even in the presence of nitrate. This suggests that micronutrients are important to the growth of denitrifiers, but not as important to the aerobic microorganisms which established themselves in the column. The numbers presented for nitrous oxide concentrations only represent the amount of N20 present in the soil gas. No attempt was made to obtain an overall estimate of N 20 in the columns which would include the nitrous oxide dissolved in the solution (Moraghan and Buresh, 1977). The data is presented to show which columns experienced the largest populations of denitrifiers. One interesting phenomenon which occurred during the nitrous oxide sampling was the occurrence of a small peak just before the N 2 0 peak (see Figure 4.14). This peak typically appeared just prior to jumps in N 2 0 production. Data provided by a GC column manufacturer did not correspond to the retention time of the peak. It was suggested that the only method to identify the responsible compound would be through the use of a mass spectrometer. 4.4 Nitrate Concentrations Soil water samples were obtained from five levels of each column using suctions lysimeters. It was expected that samples could be obtained on each level for every sampling day, but this did not tum out to be the case. Samples could typically be obtained from the lower levels (which were approaching saturation), but infrequently 105

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Figure 4.14 Unidentified Peak Prior During Nitrous Oxide Sampling A IHJECT 06/05/94 08:53:23 NITRO FILE 1. PEAK# 1 ., ;;.. ] 4 5 6 7 8 9 10 11 12 TOTAL 3:.49 ER 0 06/05/94 08:53:23 tETHOD 13. 21 21 AREA;-; 0.1 0.l127 93.793 0.311 2.444 0.001 0.001 0. 0.001 0. 3.283 0.04 100. RT AREA 8C 0 ? 1261 02 0.39 335 02 0.52 1179697 08 0.92 3907 06 1.11 .30740 07 1. 38 10 06 1. 47 10 06 1.54 5 07 1. 88 8 135 2.19 4 06 2.28 41287 07 3.49 499 01 1257763 CH= "A" PS= 1. from the upper levels. Obtaining samples from the top level (level a) seemed to depend on catching the wetting front shortly after evaporation makeup water had been applied to the columns. In addition, there were occasional problems with the lysimeter clamps, which made it difficult to determine whether there was no sample or the lysimeter failed to hold pressure. Lysimeters on solution column ports lAb, lAd, and 2Ac failed near the end of the experiment due to frequent flexing of the sample collection line. Limited space for the experiment resulted in these ports being located in a frequently used passageway. 106

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Another problem was getting a sufficient quantity of sample for analysis. To achieve concentrations similar to the anion standards, one milliliter of sample was diluted 5 to 1. Due to the 0.45J.1 ftltration requirement, approximately 2 mL were required to produce the 1 mL for the solution. 11ris eliminated a large number of samples from the analysis. Figure 4.15 shows the average amount of sample per port obtained from each column. When broken down to the various levels, a representative column (see Figure 4.16) shows where the majority of the solution resides (tabular data and graphs of the remainder of the columns are provided in Appendix D, Figures D 1-1 through 5). When this same data is plotted as a scatter plot and simple curve fit is performed. an upward trend is found in the sample quantities (see Figure 4.17). This reflects the increasing saturation .of the columns due to excessive makeup water being applied (graphs of the other columns are provided in Appendix D, Figures 02-1 through 5). The ion chromatograph had the capability to determine concentrations of fluoride (F). chloride (Cr). nitrite (N02), bromide (BO. nitrate (NO)). phosphate (P04), and sulfate (S04). The main focus of the analysis was toward the nitrate, since it was the required nutrient for the denitrifiers. Analysis of nutrient uptake would be useful if both the aerobic and anaerobic populations could be monitored. Unfortunately. no method was available for the measurement of carbon dioxide (a useful aerobic bacteria indicator) when the experiment began and determining the mass balance is not possible without some type of information about the aerobic population. The C02 generation would have provided useful information about the population dynamics of the aerobic bacteria (e.g . is the 107

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-1 -= = Cll :s Cl Gl "S. E Cll 1'1::1 i u -.c:l .. Figure 4.15 Average Column Lysimeter Sample Quantity 10 8 6 4 Coil Avg 0 Col2 Avg 2 Col3 Avg A Col4 Avg ColS Avg 0 0 3 6 9 12 15 18 21 24 27 30 33 36 Sampling Date Figure 4.16 Average Moisture Distribution Based on Lysimeter Sample Size 30 60 90 39 g. Gl Q 120 150 Level e 0 5 10 15 20 Lysimeter Sample Size (mL) 108 42

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Figure 4.17 Column 3 Average Lysimeter Sample Quantity 10 8 ...;l E 0 -o '-' 6 0 0 0 0 0 c 0 0 0 Ill :I 0 01 4 0 II 0 "S. E Ill 2 rl.l 0 Coi3Avg 0 I I I I I I I I I I I I 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date greatest amount of C02 generated when the most toluene diSappears or is there a lag period?). This information would also quantify the rate of C02 generation for comparison with toluene degradation rates. Phosphate is a difficult anion to accurately detect with an ion chromatograph. Colormetric methods typically provide more accurate results. Microorganisms also use sulfate for metabolism, but one again the proper instrumentation was not available forthis purpose. Bromide movement was monitored to provide an idea of how the anions were moving through the column. Nitrate is used as a major energy source for the denitrifiers and should be consumed as the denitrifying population increases. Bromide is a minor nutrient and should not be consumed as rapidly as the nitrate. The relative 109

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concentrations of these substances should provide information on the uptake of nitrate by the denitrifying population and correspond to a similar amount of nitrous oxide generation. Table 4.4 summarizes the quantities of nutrients added to the solutions and what the theoretical corresponding ion concentrations should be in those solutions. Table 4.5 summarizes what the ion chromatograph actually found (new eluant was added during the solution 2 run, which invalidated the sample). It became immediately obvious that the modified solutions were not totally soluble when a white precipitate formed when originally mixed. The solubility of each component was checked to verify the concentrations were not in excess of the solubility limit None of the individual components should have caused a problem. Another explanation would be that some of the components had favorable reactions with other components, resulting in a precipitant The net result was decreases in concentrations of approximately 25% for nitrate, 40% to 60% for 63% for bromide, and 34% to 47% for phosphate (the ion chromatograph was set at flow rate of 1.6 mL per minute for these runs and the sulfate did not elute during the sample time). The average column nitrate concentrations are presented in Figure 4.18 (graphs of the average nitrate concentrations for each column are provided in Appendix C, Figures C1-1 through 5). Nitrate levels in solution column 3, 4, and 5 seem to initially agree with the original solutions added to the columns, but then slowly decline until the new materials are added prior to the second application of toluene. The decline can be the result of the nitrate moving down through the column and water loss from the 110

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Table 4.4 Ion Concentrations Solution 2 Nutrient Duantitv (e.' lAt. Wt.Nut Br Ca a Fe H K M Na NH4 eaa 0.70 15.533 0.3714 0.3286 FeNH4 citrale 0.005 488.168 0.0008 0.0004 KBr 1.00 119.011 0.6714 0.3286 KIUP04 1.50 136.089 0.0222 0.4310 MgS04H2( 0.17 246.481 0.0168 Na2HP04 4.00 141.959 0.0284 1.2956 NH4a 0.50 53.492 0.3314 0.1686 7.875 Totals (g) 0.6714 0.3714 0.6599 0.0008 0.0506 0.7595 0.0168 1.2956 0.1690 %of' Total 8.5262 4.7167 8.3803 0.0098 0.6428 9.6450 0.2129 16.4517 21459 Solution 3 Nutrient IOuantitv (2' [At, Wt. Nut Br Ca a Fe H K M Na NH4 Ca(N03)2o41l 2.36 236.151 0 .4005 eaa 0.50 75.533 0.2653 0.2347 FeNH4 cilrale 0.005 488.168 0.0008 0.0004 KBr 1.80 119.011 1.2086 0.5914 KH2P04 1.59 136.089 0.0236 0.4568 MgS04H2C 0.10 246.481 0.0099 Na2HP04 4.18 141.959 0.0297 1.3539 NH4a 0.30 53.492 0.1988 0.1012 10.835 Totals (g) 1.2086 0 .6659 0.4335 0.0008 0.0532 1.0483 0.0099 1.3539 0.1015 %of Total 11.1546 6.1454 4.0011 0.0072 0.4913 9.6747 0.0910 12.4954 0.9372 Solution 4 Nutrient rc.>uantitv -{2' Br Ca a 'Fe H K ME Na NH4 Ca(N03)2l 2.36 236.151 0.4005 eaa 0.66 75.533 0.3502 0.3098 FeNH4 citrate 0.005 488.168 0.0008 0.0004 KBr 1.80 119.011 1.2086 0.5914 KH2P04 1.50 136.089 0.0222 0.4310 MgS04H2< 0.17 246.481 0.0168 Na2HP04 4.00 141.959 0.0284 1.2956 NH4a 0.30 53.492 0.1988 0.1012 10.195 Totals (g) 1.2086 0.1508 0.5086 0.0008 0.0506 1.0224 0.0168 1.2956 0.1015 %of Total 11.1959 6.9547 4.7116 0.4689 9.4710 0.1553 12.0016 0.9406 Solution 5 Nutrient l6uantitvc2 fAt. Wt. Nut Br Ca a Fe H K Me. Na NH4 Ca(No3)2-4E 2.36 236.151 0.4005 KBr 1.80 119.011 1.2086 0.5914 KH2P04 I .SO 136.089 0.0222 0.4310 Na2HP04 4.00 141.959 0.0284 1.2956 9.660 Totals (g) 1.2086 0.4005 0.0000 0.0000 0.0506 1.0224 0.0000 1.2956 0.0000 %of Total 12.5113 4.1464 0.0000 0.0000 0.5240 10.5838 0.0000 13.4117 0.0000 111

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Table 4.4 Ion Concentrations (con't) Solution2 Nutrient r (I!' lAt. Wt.Nut N03 P04 S04 Citrll!e H20 Mise Total CaCI 0.70 7S.S33 0.70 FeNH4 citrate 0.005 488.168 0.0038 0.0001 0.005 KBr 1.00 119.011 1.00 KH2P04 1.50 136.089 1.0468 1.50 MgS04H2C 0.17 246.481 0.0663 0.0870 0.17 Na2HP04 4.00 141.959 2.61(:1) 4.00 NH4CI 0.50 53.492 0.50 1.815 Totals (g) 0.0000 3.7228 0.0663 0.0038 0.0870 0.0001 7.875 % otr" 0.0000 47.2738 0.8413 0.0476 1.1045 0.0013 100.000 Solution 3 Nutrient !Quantity (g: lAt. Wt. Nut N03 P04 S04 Cilr.lle H20 Mise Total Ca(N03)2-4E 2.36 236.151 1.2393 0.7202 2.36 CaCl 0.50 15.533 0.50 FeNH4 citrate o.oos 488.168 0.0038 0.0001 o.oos KBr 1.80 119.0l1 1.80 KH2P04 1.59 136.089 1.1096 1.59 MgS04Hl< 0.10 246.481 0.0390 0.0512 0.10 Na2HP04 4.18 141.959 2.7964 4.18 NH4CI 0.30 53.492 0.30 10.835 Totals (g) 1.2393 3.9060 0.0390 0.0038 0.7113 0.0001 10.835 %of Total 11.4380 36.0502 0.3591 0.0346 7.1187 0.0009 100.000 Solution4 Nutrieot At. Wt.Nut N03 P04 S04 CiiJale. H20 Mise Total Ca(N03)2ll 2.36 236.151 1.2393 0.7202 2.3(:1) CaCl 0.66 75.533 0.660 FeNH4 citrate 0.005 488.168 0.0038 0.0001 o.oos KBr 1.80 119.011 uoo KH2P04 1.50 136.089 1.0468 1.500 MgS04H2C 0.17 246.481 0.0663 0.0870 0.170 Na2HP04 4.00 141.959 2.67(:1) 4.000 NH4CI 0.30 53.492 0.300 10.795 Totals (g) 1.2393 3.7228 0.0663 0.0038 0.8071 0.0001 10.195 %of Total 11.4804 34.4865 0.6138. 0.0347 7.4769 0.0009 100.000 SolutionS Nutrieot r lAt. Wt.Nut N03 P04 S04 Citrate H20 Mise Total Ca(N03)2-4l: 2.36 236.151 1.2393 0.7202 2.3(:1) KBr 1.80 119.011 1.800 KH2P04 1.50 136.089 1.0468 1.500 Na2HP04 4.00 141.959 2.6760 4.000 9.660 Totals (g) 1.2393 3.7228 0.0000 0.0000 0.7202 0.0000 9.660 %of Total 12.8292 38.5385 0.0000 0.0000 1.4550 0.0000 100.000 112

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Tb145sl c a e o utton oncentrations De db I Ch ternune >Y on h romatograpl Tap Solution Solution Solution Solution Solution Water 1 2 3 4 5 Nitrate (area) 0 0 400774 399028 380309 (ppm) 0 0 954 950 905 (giL) 0.00 0.00 0.95 0.95 0.91 Chloride (peakht) 2.25 0.40 25.70 19.75 0.00 23 4 257 198 0 ( ) 0.02 0.00 0.26 0.20 0.00 Nitrite (peak ht) 0.00 0.00 0.00 0.00 0.00 (ppm) 0 0 0 0 0 (giL) 0.00 0.00 0.00 0.00 0.00 Bromide (peak ht) 0.00 0.00 26.20 26.40 26.40 (ppm) 0 0 448 451 451 (g/L) 0.00 0.00 0.45 0.45 0.45 Phosphate (peakht) 0.00 ? 24.10 18.40 20.40 (ppm) 0 ? 2582 2186 (i/L) 0.00 ? 2.58 1.97 2.19 Peak StdConc Area/Heigh1 (ug/mL) *Addition of new eluant during this Nitrate Std 42000 20 run invalidated this sample (area) Chlonde 10 20 Std (peak Nitrite Std 6.25 20 (peakht) Bromide 5.85 20 Std (peak Phosphate 1.4 30 Std (peak bottom. Column 2 shows an increase in nitrate levels after the second application of toluene which can be explained by the nitrate in the top soil. Since level e was the most reliable for the availability of a sample, the average concentrations at this level was plotted (see Figure 4.19). The general decline is again evident for the first fifteen days. The jump between day 15 and day 18 is anomaly 113

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which at flrst seemed to defy .explanation. One possible explanation is an attempt to adjust the pH of the columns. The solutions for the columns were measured for pH on May 27th. Solutions 3, 4, and 5 were found to lie outside or at the lower edge of the optimum pH range for bacteria of 6.5 to 7.5 ( 6.48, 6.22, and 6.50 respectively). In an attempt to move the solution back into the proper range, a small amount potassium hydroxide (KOH) was added to the columns over a period of four days beginning on the 30th of May. The more reactive hydroxyl ion possibly knocked the nitrate ion off of any available adsorption sites in the sand and resulted in increased concentrations at level e. Figure 4.18 Average Column Nitrate Concentration 800 Colt Avg 0 Col2Avg 0 Col3Avg 6 Col4Avg Col5 Avg 0 3 6 9 12 15 18. 21 24 27 30 33 36 39 42 Sampling Day 114

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Figure 4.19 Average Column Nitrate Concentration L_evel e 1250 [1000 Cl.o -c .2 750 -jsoo 0 u 250 0 3 6 9 .12 IS 18 21 24 27 30 33 36 39 42 Sampling Day After this event, however, the nitrate concentrations continue to fall until the introduction of new nitrate reaches the lower level Nitrogen sources in the materials added prior to the second application of toluene included top soil (0.11% nitrate, 0.10% nitrite), compost (0.31% nitrate, 0.14% nitrite), bloodmeal (12.0.()), and commercial fertilizer (6-1Q.4). Both the average column nitrate and level e nitrate graphs show this increase. Neglecting the nitrate lost through water leaking from columns nitrate loss rates of 10.7 to 27.3 ppm per day can be determined by applying a simple curve fit to a scatter plot of columns 3, 4, and 5 data. (These rates correspond to the loss from day 0 to day 15 and the loss from day 18 to day 27.) The larger loss rate approximately 115

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corresponds to the period of time when nitrous oxide production dramatically increased. Moisture losses, in comparison, could generate concentration reductions of 0.3 ppm per day, by taking an average 24 mL sample from the column every three days, to 36.7 ppm per day, by removing a one liter quantity of solution from the level e lysimeter. The steady decline Witnessed in the graph of average level e nitrate concentrations would include the moisture loss due to. sampling, but there is no evidence of a major loss of solution. This section of the graph even appears to follow the relative concentration levels which were firsf placed in the columns. The 27.3 ppm per day loss rate would translate into approximately 0.74 g of nitrate disappearing from the column per day. Of this amount approximately 0.17 g would be nitrogen. If all the nitrogen was converted to N20, the nitrous oxide produced by the column per day would be 0.08 g. Making several assumptions about the amount of air contained within the column and an average air density, the 0.08 g can be converted to approximately 4300 ppm of N20 in the soil gas. Solution column 4A and 4B generated concentrations of N20 of this order of magnitude. Using the lower rate of 10.7 ppm per day produces a concentration of 1600 ppm of N20 in the soil air, again an order of magnitude only seen for columns 4A and 4B. This suggests that the nitrate removal mechanism was most likely denitrification in columns 4A and 4B, but other mechanisms were at work in columns 3, 5, and 4C. Another mechanism for the decrease in nitrate would be an overall increase in moisture content in level e. This could be evidence of the makeup water which was in excess of the evaporation rate. 116

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One final method for checking the rate of decrease in the nitrate levels is to compare the nitrate to bromide ratio from the start of the experiment to the sampling day 21. Any comparisons beyond this point would not be valid since new sources of nitrate were introduced. The results of this comparison (see Table 4.6) show a drop in nitrate concentrations of 12.2% in solution column 3, 10.2% in solution column 4 and 0.8% in solution column 5. This compares favorably with the generation of nitrous oxide in columns 3 and 4, while only small quantities were generated until near the end of the experiment in column 5. Denitrifiers reduce nitrate to nitrite and eventually to nitrous oxide. Assumingthat the majority of the nitrogen in the nitrate is converted to nitrous oxide, one gram of nitrous oxide (N20) should be generated for two grams of nitrate (N03). At the completion of the experiment five sacrifice samples were removed from randomly selected columns at various levels. Two grams of sample. were mixed with 20 mL of deionized water. A water sample was filtered, diluted, and then measured on the Dionex IC. The 5 mL sample required by the Dionex was achieved by dilution, resulting in a very low concentration for analysis. Due to these low concentrations, most of the data is suspect ( peak heights were essentially in the noise level). The nitrate concentrations at level d in column 4A appeared to be of the appropriate magnitude. Table 4.7 details this analysis. Some of the results of the ion chromatograph should be considered qualitative rather than quantitative. This is due to the nature of the autosampler, which ran samples continuously for approximately 24 hours and the fact that the pump was in the process of failing. The net result was occasional baseline drift, which caused the 117

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integrator to misinterpret peaks. This caused small errors on the larger peaks, but larger errors on the smaller peaks. The data was reviewed to eliminate most of this effect, but a certain percentage of the runs contain a small amount of error. Table 4.6 Nitrate to Bromide Ratio 5118/94 5118/94 6/8/94 6/8/94 Solution Bromidt Nitrate Ratio Bromide Nitrate Ratio %Drop .ANitrate Column (pk area (pk area (N03/Br (pk area (pk area (N03/Br inN03 Cone (ppm) 3Ae 242262 265408 1.10 3Be 375977 310063 0.82 235857 258702 1.10 3Ce 330769 369426 1.12. 201816 216794 1.07 MeaJJ 0.97 Mean 1.09 12.2 124 Std De1.1 0.21 Std Dev o.o1 4Ae 370395 408913 1.10 355624 421439 1.19 4Be 361513 387836 1.07 232016 252906 1.09 4Ce 394638 347337 0.88 269037 294356 1.09 MeaJJ 1.02 Mean 1.12 10.2 104 Std Dev 0.12 Std Dev 0.05 5Ae 326651 320292 0.98 224997. 241017 1.07 SBe 359393 391735 1.09 see 330769 369426 1.12 245400 263515 1.07 Mean 1.()6 MeaJJ 1.07 0.8 8 Std Dev 0.07 Std De1.1 0.00 The sampling only looked for the anions. This provided information concerning nitrate concentrations which are important to the denitrifiers, but no information was gathered concerning nutrients such as potassium and calcium. Future experiments should consider analysis of the cations to gather a more complete picture of the nutrient uptake. 118

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Tabl 4 7 N tri t C e u en tr ti Dete d F S rifi S 1 oncen a ons nome rom ac tee amp1es Nutrient N02. N02 Br Br N03 N03 S04 S04 Lysimeter PeakHt Cone Peak Ht Cone PeakHt Cone PeakHt Cone Position (ppm) (ppm) (ppm) (ppm) Where Sample Obtained 1Be 4216 69 0 0 4216 115 5220 115 2Ab 10110 167 648 23 4788 130 5048 112 3Ca 5545 91 4154 145 4154 113 3154 70 4Ad 28400 468 22380 780 18450 502 6083 134 5Cc 4052 67 4403 153 4770 130 1968 43 Standard N02 305800 20 Br 144700 20 N03 185300 20 S04 342200 30 119

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Chapter 5 5. Conclusions The data generated by this experiment demonstrated the complexity of bioremediation. The large numbers of microorganisms introduce a degree of uncertainty to the process and show that each process needs to be tailored to a specific site and its population of microorganisms. It was hoped that a clear winner would emerge from the different types of solutions applied to the columns. Instead it appears that the microorganism which operated best in that medium became the primary consumer of the toluene. Even in the control column, toluene degradation was amazingly complete. The generation of the secondary gas chromatograph peak in column 2 shows that different columns were using different methods to degrade the toluene. Solution column 4 was predicted to be the clear winner in the experiment since it provided nutrients to both the aerobic and anaerobic populations of the unsaturated zone. Columns 4B and 4C showed.this trend, although not tO the expected magnitude, but column 4A performed poorly in comparison. A possible explanation is that this column became more saturated than the others, forcing the system to anaerobic biodegradation. While the column eventually consumed nearly as much toluene as the 4B and 4C, the initial rate was at the slower metabolic rate of the denitrifiers (whose presence was confirmed by the copious amounts of nitrous oxide generated and the decreased quantities of nitrates in the column). 120

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The performance of solution column 5 was unexpected due to the lack of micronutrients. This appeared to have minimal effect on the assumed (assumed due to the lack of carbon dioxide measurements) aerobic biodegradation. Likewise, the control columns performed much better than predicted since they contained little or no nutrients. One explanation would be a population of Pseudomonas. Various types of this bacteria have been mentioned as the primary toluene consumer and, as mentioned previously, many species do not require specific vitamins, growth factors, or amino acids. Solution column 5 probably outperformed the control columns because the availability of nutrients supported a larger population. Micronutrients do appear to be important to the denitrifying population. Solution column 5 contained nitrates at the same levels as columns 3 and 4, but little nitrous oxide was generated in the column until nearly the last day of the experiment. The vermiculite and commercial fertilizer added to the column prior to the second toluene application most likely contained quantities of essential micronutrients (this needs to be confirmed with analysis). Nitrous oxide appeared in greater quantities in the column after approximately the same amount of time for the establishment of the denitrifiers in columns 3 and 4 (approximately 18 days), but was delayed 21 days due to the lack of micronutrients. The addition of organic soil which contained bacterial populations, complete with enzymes, was expected to produce a meaSurable difference on the biodegradation rate. The performance of column 5 is an argument against this, but the results are clouded due to possible adsorption by the vermiculite. The experiment would need to be repeated with separate organic soil columns to accurately assess these effects. 121

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The inability to accurately measure soil moisture made any determination of mass balance very difficult Future experiments should be instrumented with soil moisture probes and/or the columns could be placed on scales to provide an record of soil moisture gain and loss. Measurements such as these would rapidly point out unwanted changes in moisture content The instrumentation was probably responsible for some of the problems with the moiSture content of the columns. Any future experiments of this type should consider the use of modified suction lysimeters, consisting of only a small suction cup and small diameter pressurization and sample removal lines. This type of probe would float freely in the soil (no support from the side wall) reducing the probability of macropore formation. This would alSo reduce the amount of cross-sectional area that would be affecting the moisture movement in the column. It was difficult to assess the impact of the hydrogen peroxide on the biodegradation of the toluene. The rate of toluene consumption could be determined, but which portion could be contributed to the aerobic bacteria could not be quantified since the carbon dioxide generation was not measured. The low concentrations used for this experiment may or may not have been effective. Gas sampling for toluene needs to be done on at least a daily basis in the early portion of the experiment, to gain a better understanding of the contaminant's movement through the columns. Increased testing would also clarify when the population dynamic occurs. The presence of different lag periods could indicate that a variety of bacteria are a work. 122

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The sheer volume of data generated by this experiment made it extremely difficult to conduct the analysis on a real time basis. This often eliminated the possibility of making additional tests while certain trends took place. Tests for moisture content, cations, C02 generation, methane generation, dissolved oxygen content, and continuous pH measurements would have been helpful to the analysis, but the existing tests proved to be at the limit of the capabilitY of one person. Future tests of this nature should have a reduced number of sampling ports or an increase in manpower. Operating at the limit of available time also introduces an increased possibility for error and eliminates the time required for retesting when necessary. This experiment provides the hardware that could be used to examine a variety effects in the vadose zone, including: additional types of nutrient solutions, variation in moisture content, cycling from wet to dry to wet, variations in nutrient concentrations, investigating different contaminants, variations in contaminant concentrations, additions of different "seed" bacteria, different soil types, varitations in hydrogen peroxide concentrations, etc. This type of setup could also be used in conjunction with field tests to assist in the identification of potential problems. The experiment did document the potential for bioremediation in the vadose zone. While the nutrient solutions did not perform as dramatically as flrSt expected, there wa8 an measurable difference between them and the controls. Different soils with different contaminant concentrations may show a more pronounced result Biodegradation is an important feature of any soil system and improving the knowledge about this process will assist in accurately assessing the movement of contaminants at a field site. 123

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Appendix A Toluene Data 124

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Table Al Summary of Toluene Data Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5/18/94 5121194 5/24/94 5127/94 5/30/94 612194 lAa 0 9500 78400 203 282 171 lAb 0 9120 109333 480 494 149 lAc 0 19000 126667 832 563 63 lAd 0 51933 566667 734 1455 28 lBa 0 92892 171806 101 121 8 lBb 0 114328 588794 358 159 295 lBc 0 164347 236233 220 122 237 lBd 0 124332 268447 120 186 llO tea 0 626879 188601 115 81 75 lCb 0 420669 253433 146 143 108 ICc 0 1237262 359521 243 654 134 1Cd 0 478408 117876 203 1059 ll3 2Aa 0 27867 45333 157 197 70 2Ab 0 19000 53333 306 469 303 2Ac 0 48387 88000 1059 330 415 2Ad 0 76000 109333 1024 201 86 2Ba 0 4922 145611 183 79 30 2Bb 0 97856 352885 489 152 34 2Bc 0 7383 358828 140 335 115 2Bd 0 9024 514841 239 252 126 2Ca 0 136099 47150 64 75 65 2Cb 0 107229 291742 99 71 193 2Cc 0 70112 132610 198 196 254 2Cd 0 206210 291742 156 186 165 3Aa 0 83093 28634 115 28 64 3Ab 0 7860 161068 609 54 26 3Ac 0 107540 230506 1049 295. 104 3Ad 0 87533 314978 732 228 4 3Ba 0 91463 75165 200 47 8 3Bb 0 19007 130286 433 83 106 3Bc 0 10004 245539 977 307 46 3Bd 0 10004 408397 1599 548 22 3Ca 0 190000 86983 180 62 42 3Cb 0 492593 182888 308 30 70 3Cc 0 11822 802477 181 273 1039 3Cd 0 118222 231955 587 1397 292 4Aa 0 2429 32667 46 95 46 4Ab 0 5464 8333 88 271 59 4Ac 0 2429 52333 102 618 333 4Ad 0 1214 36000 674 799 54 4Ba 0 225964 100294 35 46 32 4Bb 0 95760 374430 136 199 89 125

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Table Al Summary of Toluene Data (can't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5118/94 S/21/94 S/24/94 5/27/94 5130194 6/2194 4Bc 0 83790 507040 230 392 242 4Bd 0 27360 577246 222 508 238 4Ca 0 59768 46432 52 26 36 4Cb 0 55667 174585 77 16 so 4Cc 0 123052 226589 53 30 so 4Cd 0 90824 456893 232 29 108 SAa 0 8986 68333 230 114 80 SAb 0 14571 114333 309 53 368 SAc 0 9107 68667 508 1066 319 SAd 0 3036 192000 1176 503 472 SDa 0 59850 72434 38 40 72 SBb 0 106875 111437 76 96 14S SBc 0 29925 340627 360 57 231 SBd 0 167946 308310 164 38 235 sea 0 4S037 24S34 150 19 42 SCb 0 270222 182888 324 65 114 sec 0 99081 3S0164 392 84 136 SCd 0 370148 182888 S19 17S 147 *No data collected 6/14/94 126

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Table Al Summary of Toluene Data (can't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 6/5/94 6/8/94 6/11194 6/14194 6/17/94 6/20/94 1Aa 178 86 576 101 90 lAb 272 142 803 118 157 lAc 671 151 1762 176 169 lAd 619 284 972 417 374 lBa 44 92 563 30 106 lBb 60 125 969 88 63 lBc 88 200 613 93 263 1Bd 154 249 1283 35 291 lCa 100 17 228 87 84 lCb 120 18 684 211 273 lCc 215 25 342 0 192 lCd 158 40 143 0 386 2Aa 49 29 240 33 30 2Ab 73 99 220 21 34 2Ac 180 91 402 4 16 2Ad 191 141 143 7 29 2Ba 19 11 89 47 10 2Bb 21 4 43 14 9 2Bc 51 9 57 11 7 2Bd 85 5 217 14 13 2Ca 21 29 71 16 74 2Cb 60 25 171 18 59 2Cc 191 21 207 49 55 2Cd 134 35 167 26 92 3Aa 40 91 30 48 42 3Ab 47 36 40 20 15 3Ac 90 76 45 15 14 3Ad 134 172 47 21 36 3Ba 15 37 86 23 20 3Bb 49 55 39 24 10 3Bc 130 90 235 16 16 3Bd 174 125 335 30 2S 3Ca 40 37 75 39 13 3Cb 87 36 93 21 6 3Cc 243 46 563 35 32 3Cd 316 128 456 55 so 4Aa 41 26 298 163 63 4Ab 222 20 654 51 45 4Ac 203 45 719 172 28 4Ad 300 56 991 100 38 4Ba 17 17 43 31 2S 4Bb 61 23 62 28 19 127

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Table Al Summary of Toluene Data (con't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb)* (ppb) (ppb) 6/5/94 618/94 6111/94 6/14194 6/17/94 6no/94 4Bc 67 13 228 26 42 4Bd 224 97 124 49 53 4Ca 30 2 128 84 43 4Cb 40 8 llO 20 23 4Cc 66 0 46 15 1 4Cd llO 8 89 19 77 SAa 89 24 253 36 17 SAb 78 21 91 54 11 SAc 300. so 330 47 18 SAd 426 87 266 99 29 SBa 16 so 29 12 32 SBb 35 74 29 16 28 SBc 93 117 43 6 19 SBd 64. 223 128 7 12 sea 30 6 175 24 37 SCb 53 16 ll4 19 16 sec 143 26 146 15 0 SCd 120 48 467 24 17 *No data collected 6/14/94 128

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Table Al Summary of Toluene Data (con't) Formula Column Concentration Concentration (ppb) (ppb) 6123194 6/25194 lAa 180 37 lAb 408 67 lAc 602 98 lAd 726 205 1Ba 37 25 lBb 41 44 lBc 105 54 lBd 90 167 1Ca 76 26 lCb 164 103 ICc 179 83 lCd 271 163 2Aa 61 39 2Ab 33 8 2Ac 18 10 2Ad 50 12" 2Ba 7 10 2Bb 6 7 2Bc 3 7 2Bd 16 12 2Ca 27 56 2Cb 19 27 2Cc 20 38 2Cd 51 47 3Aa 73 15 3Ab 33 7 3Ac 21 5 3Ad 94 22 3Ba 12 14 3Bb 4 5 3Bc 5 5 3Bd 10 9 3Ca 15 6 3Cb 15 8 3Cc 6 2 3Cd 27 27 4Aa 16 20 4Ab 34 8 4Ac 55 4 4Ad 19 19 4Ba 4 10 4Bb 3 8 129

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Table Al Summary of Toluene Data (con't) Formula Column Concentration Concentration (ppb) (ppb) 6/23194 6125194 4Bc 12 12 4Bd 16 35 4Ca 49 26 4Cb 1S 17 4Cc 9 8 4Cd 10 22 SAa 20 s SAb 16 8 SAc 31 11 SAd 40 30 SBa 10 13 SBb 10 7 SBc 6 10 SBd. s 1 SCa 19 10 SCb 9 10 sec 11 4 SCd 11 12 *No data collected 6/14/94 130

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Table A2 Average Toluene Concentrations Formula Column Average Average Average Average Average Average Concentration Concentration Coucentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5/24/94 5/27/94 1_a 0 243090 146269 139 161 84 1_b 0 181372 317187 328 265 184 1_c 0 473536 240807 432 446 145 1_d 0 218224 317663 352 900 84 Coil Mean 0 279056 255481 313 443 124 StdDev 0 132109 81275 124 326 49 2_a 0 56296 79365 135 117 55 2_b 0 74695 232654 298 231 177 2_c 0 41960 193146 465 287 261 2_d 0 97078 305305 473 213 126 Co12Mean 0 67507 202618 343 212 155 StdDev 0 23836 94389 160 71 87 3_a 0 121519 63594 165 46 38 3_b 0 173153 158081 450 55 67 3_c 0 43122 426174 736 292 396 3_d 0 71919 318444 973 725 106 Col3Mean 0 102428 241573 581 279 152 StdDev 0 57197 161899 350 318 165 4_a 0 96054 59798 44 56 38 4_b 0 52297 185783 100 162 66 4_c 0 69151 261988 128 347 208 4_d 0 39800 356713 376 445 133 Col4Mean 0 64477 216070 162 252 111 StdDev 0 24374 125469 147 176 76 5_a 0 37958 55100 139 58 65 5_b 0 130556 136220 236 72 209 5_c 0 46038 253152 420402 229 5_d 0 180371 227733 620 239 285 Col5 Mean 0 98732 168051 354 193 197 StdDev 0 68675 90508 212 162 94 *No data collected 6/14194 131

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Table A2 Average Toluene Concentrations (con't) Formula Column Average Avemge Avemge Average Average Avemge Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 615194 618/94 6111/94 6/14/94 6/17/94 6n.0/94 l_a 107 65 456 0 73 93 l_b 151 95 819 0 139 164 l_c 325 125 906 0 89 208 l_d 310 191 799 0 150 350 Coil Mean 223 119 745 0 113 204 StdDev 110 54 198 0 38 108 2_a 30 23 133 0 32 38 2_b 51 43 145 0 18 34 2_c 141 40 222 0 22 26 2_d 137 61 176 0 16 45 Col2Mean 90 42 169 0 22 36 StdDev 51 15 40 0 7 8 3_a 32 55 63 0 37 25 3_b 61 42 57 0 22 10 3_c 154 71 281 0 22 21 3_d 208 142 279 0 35 37 Col3 Mean 114 78 170 0 29 23 StdDev 82 44 127 0 8 11 4_a 29 15 156 0 92 44 4_b 108 17 275 0 33 29 4_c 112 19 331 0 71 23 4_d 211 54 401 0 56 56 Col4Mean 115 26 291 0 63 38 StdDev 74 18 103 0 25 15 5_a 45 27 152 0 24 29 5_b 55 37 78 0 30 19 5_c 179 64 173 0 22 12 5_d 203 119 287 0 43 19 Col5 Mean 121 62 172 0 30 20 Std Dev 82 42 87 0 9 7 No data collected 6/14/94 132

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Table A2 Average Toluene Concentrations (con't) Formula Column Average Average Concentration Concentration (ppb) (ppb) 6/23/94 6125/94 1_a 98 29 1_b 204 71 1_c 295 78 1_d 362 178 Co11 Mean 240 89 StdDev 115 63 2_a 32 35 2_b 19 14 2_c 14 18 2_d 39 24 Co12Mean 26 23 Std Dev 11 9 3_a 33 12 3_b 17 7 3_c 11 4 3_d 44 19 Co13Mean 26 10 StdDev 15 7 4_a 23 18 4_b 17 11 4_c 2S 8 4_d 15 2S Co14Mean 20 16 StdDev 5 8 5_a 16 9 5_b 12 8 5_c 16 8 5_d 19 14 Co15Mean 16 10 StdDev 3 3 *No data collected 6/14/94 133

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Table A3 Average Toluene ConcentrationsScrubbed Formula Column Average Average Average Average Average Average Concentration Coneentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5/18/94 5/21.194 5/24.194 5/27/94 5130/94 6/2J94 l_a 0 51196 125103 152 202 89 l_b 0 61724 349064 419 327 222 1_c 0 9500 63333 416 281 32 1_d 0 88133 417557 427 820 69 Coil Mean 0 52638 238764 353 408 103 StdDev 0 32687 171102 135 280 83 2_a 0 56296 79365 135 117 55 2_b 0 74695 232654 298 231 177 2_c 0 41960 193146 465 287 261 2_d 0 97078 305305 473 213 126 Col2Mean 0 67507 202618 -343 _212 155 StdDev 0 23836 94389 160 71 87 3_a 0 121519 63594 165 46 38 3_b 0 173153 158081 450 55 67 3_c 0 43122 426174 736 292 396 3_d 0 71919 318444 973 725 106 Col3Mean 0 102428 241573 581 279 152 --StdDev 0 57197 161899 350 318 165 4_a 0 142866 73363 44 36 34 4_b 0 75713 274507 107 108 69 4_c 0 103421 366815 142 211 146 4_d 0 59092 517069 227 269 173 Col4Mean 0 95273 307939 130 156 105 StdDev 0 36620 185603 77 104 65 5_a 0 37958 55100 139 58 65 5_b 0 130556 136220 236 72 209 5_c 0 46038 253152 420 402 229 5_d 0 180377 227733 620 239 285 Col5Mean 0 98732 168051 354 193 197 StdDev 0 68675 90508 212 162 94 *No data coUected 6/14.194 134

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Table A3 Average Toluene ConcentrationsScrubbed (con't) Formula Column Average Average Average Average Average Average Coocenlratioo Concentration Concentration Concenlration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 6/5/94 618194 6/11/94 6/14/94 6/17/94 6/20194 l_a 111 89 570 0 65 98 l_b 166 134 886 0 103 110 l_c 335 75 881 0 88 85 l_d 386 267 1127 0 226 332 Coli Mean 250 141 866 0 120 156 StdDev 132 87 228 0 72 118 2_a 30 23 133 0 32 38 2_b 51 43 145 0 18 34 2_c 141 40 222 0 22 26 2_d 137 61 176 0 16 45 Col2Mean 90 42 169 0 22 36 StdDev 57 15. 40 0 7 8 3_a 32 55 63 0 37 25 3_b 61 42 57 0 22 10 3_c 154 71 281 0 22 21 3_d 208 142 279 0 35 37 Col3 Mean 114 78 170 0 29 23 StdDev 82 44 -121 0 .... ... -8 11 4_a 24 9 86 0 57 34 4_b so 16 86 0 24 21 4_c 66 6 137 0 21 21 4_d 167 52 106 0 34 65 Coi4Mean 77 21 104 0 34 35 Std Dev 63 21 24 0 16 21 5_a 45 27 152 0 24 29 5_b 55 37 78 0 30 19 5_c 179 64 173 0 22 12 5_d 203 119 287 0 43 19 Col5 Mean 121 62 172 0 30 20 Std Dev 82 42 87 0 9 7 No data collected 6/14194 135

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Table A3 Average Toluene ConcentrationsScrubbed (can't) Formula Column Average Average Concentration (ppb) (ppb) 61'13194 6125194 1_a 108 31 1_b 225 56 1_c 301 49 1_d 408 186 Col1 Mean 260 80 StdDev 126 71 2_a 32 35 2_b 19 14 2_c 14 18 2_d 39 24 Co12Mean 26 23 StdDev 11 9 3_a 33 12 3_b 17 7 3_c 11 4 3_d 44 19 Col3Mean 26 10 StdDev 15 7 4_a 26 18 4_b 9 12 4_c 11 10 4_d 13 28 Col4Mean 15 17 StdDev 8 8 5_a 16 9 5_b 12 8 5_c 16 8 5_d 19 14 Col5 Mean 16 10 StdDev 3 3 *No data collected 6/14/94 136

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Figure Al.l Toluene Concentrations Column 1, Levels a d 400000 l_a 0 l_b o l_c l_d 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A1.2 Toluene Concentrations Column 2, Levels a -d 400000 i 3()()()()() ; II i 2()()()()() I Ut()()()()() 2_a 2_b 2_c 6 2_d 0 3 6 9 12 IS 18 21 24. 27 30 33 36 39 42 Sampling Day 137

PAGE 149

Figure A1.3 Toluene Concentrations Column 3, Levels a -d -400000 -& ,s. .; 3_a 3_b 3_c 3_d 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A1.4 Toluene Concentrations Column 4, Levels a -d 400000 4_a 4_b 4_c 4_d 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 138

PAGE 150

Figure Al.S Toluene Concentrations Column 5, Levels a -d 400000 i -300000 J Cll .!:: 200COO a: ; 0 utoocoo 5_a 5_b 5_c .. 5_d 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 139

PAGE 151

.c !: 5 f -I: u 5 u Figure A2.1 Toluene ConcentrationColumn 1 (day 9 through 21) 1000 800 600 400 200 0 9 12 15 Sampling Day 18 1_a 1_b 0 1_c: .. 1_d 21 Figure A2.2 Toluene Concentration Column 2 (day 9 through 21) . 1000 800 .c !: 600 5 -Cl .t:l 400 I: u I: = u 200 0 9 12 15 Sampling Day 140 18 2_a 2_b 2_c: .. 2_d 21

PAGE 152

Figure A2.3 Toluene ConcentrationColumn 3 (day 9 through 21) 1000 800 -1:1. 1:1. 600 1: & .:::: 400 1: 21 a 200 0 9 12 15 Sampling Day 18 3_a 3_b 0 3_c .. 3_d 21 Figure A2.4 Toluene Concentration Column 4 (day 9 through 21) 1000 800 -1:1. ,so 1: 600 0 = b 400 1: 41 1:1. 0 u 200 0 9 12 15 Sampling Day 141 18 4_a 4_b 0 4_c 6 4_d 21

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Figure Al.S Toluene ConcentrationColumn 5 (day 9 through 21) 1000 800 i. =600 1: ;: CIS 1 400 4ol I!! u 200 0 9 12 15 Sampling Day 142 18 5_a 5_b a 5_c 5_d 21

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Figure A3.1 Toluene Concentrations Column 1 (Second Application) 1200 1000 ,.CI c. 800 c. -r: c 600 ;: ca .. r: 41 400 r: c u 200 0 21 24 27 30 33 Sampling Day 36 1_a 1_b 1_c 1_d 39 42 Figure A3.2 Toluene Concentration Column 2 (Second Application) 1200 1000 ,.CI c. 800 c. -r: c 600 -ca .. r: 41 400 r: c u 200 0 21 24 27 30 33 Sampling Day 143 36 2_a 0 2_b 0 2_c A 2_d 39 42

PAGE 155

Figure A3.3 Toluene Concentration Column 3 (Second Application) 1200 1000 -.CI Clo 800 Clo ,_. c 3_a c 3_b 600 ... 3_c loo ... 3_d c u 400 u c c u 200 0 21 24 27 30 33 36 39 42 Sampling Day Figure A3.4 Toluene Concentration Column 4 (Second Application) 1200 1000 :=-Clo 800 Clo -c .s 600 ... loo 4_a 4_b 4_c ... c u 400 u c 6 4_d c u 200 0 21 24 27 30 33 36 39 42 Sampling Day 144

PAGE 156

Figure A3.5 Toluene Concentration -Column 5 (Second Application) 1200 1000 IS: 800 S_a ; 600 .... l S_b s_c .. S_d 1: 400 c u 200 0 21 24 27 30 33 36 39 42 Sampling Day 145

PAGE 157

Figure A4-2a Toluene Concentration Column 2, Level a 500000 ::c-8:400000 I: i :: 200000 100000 2Aa o 2Ba 2Ca 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A4-2b Toluene Concentration Column 2, Level b 500000 .c I: .... I: :: 200000 I: 8 100000 2Ab 2Bb 2Cb 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 146

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Figure A4-2c Toluene Concentration Column 2, Level c 600000 500000 :;-15:400000 2Ac a: 2Bc 0 2Cc a: 2S 200000 a: 0 u 1 00000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A4--2d Toluene Concentration Column 2, Level d 600000 5()()()()() ;ii' 2Ad a: 0 2Bd ca 2Cd .. 2S 200000 a u 100000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 147

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.c Q. Q. '-' c 0 -... ... c CJ c 0 u .c Q. Q. -c 0 : ... c CJ c 0 u Figure AS-2a Toluene Concentration (2nd Application) Column 2, Level a 200 100 2Aa 2Ba 2Ca 21 24 27 30 33 36 39 42 Sampling Day Figure AS-2b Toluene Concentration (2nd Application) Column 2, Level b 200 2Ab 2Bb 2Cb 100 21 24 27 30 33 36 39 42 Sampling Day 148

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-.c Cl. Cl. -c .s Ill "" c u c 0 u -.c Cl. Cl. -c Ill "" 'S u c 0 u 500 400 300 200 100 Figure AS-2c Toluene Concentration (2nd Application) Column 2, Level c 21 24 27 30 33 Sampling Day 36 39 2Ac 2Bc 2Cc 42 Figure ASld Toluene Concentration (2nd Application) Column 2, Level d 200 2Ad 2Bd 2Cd 100 21 24 27 30 33 36 39 42 Sampling Day 149

PAGE 161

Figure A6-3a Toluene Concentration Column 3, Level a 8()()()()() 3Aa o 3Ba o 3Ca 0 3 6 9 l2 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A6-3b Toluene Concentration Column 3, Level b 800000 3Ab o 3Bb 3Cb 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 150

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Figure A6-3c Toluene Concentration Column 3, Level c 8()()()()() 1: -600000 c: & i 400000 a 2()()()()() 3Ac 3Bc 3Cc 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A6-3d Toluene Concentration Column 3, Level d 800000 i 1:1. -600000 s 1400000 i u 200000 3Ad e 3Bd 3Cd 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 151

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.= Q. Q. r:::: Ill .1::: r:::: u r:::: Cl u .= Q. Q. r:::: .s Ill "' = u r:::: Cl u Figure A7-3a Toluene Concentration (2nd Application) Column 3, Level a 500 400 3Aa 3Ba 300 3Ca 200 100 0 21 24 27 30 33 36 39 42 Sampling Day Figure A7-3b Toluene Concentration (2nd Application) 500 400 300 200 100 0 21 24 Column 3, Level b 27 30 33 Sampling Day 152 36 3Ab o 3Bb 3Cb 39 42

PAGE 164

t 1: = = b 1: d 1:1. -S< ... f '! '-1 1: = u Figure A7-3c Toluene Concentration (2nd Application) Column 3, Level c 500 400 300 200 100 0 21 24 27 30 33 Sampling Day 36 3Ac 3Bc 3Cc 39 Figure A 7-3d Toluene Concentration (2nd Application) Column 3, Level d 600 500 400 300 200 100 0 21 24 27 30 33 Sampling Day 153 36 3Ad 3Bd 3Cd 39 42 42

PAGE 165

Figure AS-Sa Toluene Concentration -Column 5, Level a i 300000 Ct. -s: 0 = 200000 s: 8 100000 5Aa o 5Ba 5Ca 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure A8-Sb Toluene Concentration -Column 5, Level b ::c-300000 Ct. ,eo s: 200000 f c 8100000 5Ab o 5Bb 5Cb 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 154

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Figure A8-5c Toluene Concentration Column 5, Level c i 300000 Cl. = 200000 b = !':1 g 100000 u SAc 0 SBc 0 sec 0 3 6 9 12 1S 18 21 24 27 30 33 36 39 42 Sampling Day Figure A8-5d Toluene Concentration Column 5, Level d :c-300000 t = 200000 i = 1 ()()()()() u SAd 0 SBd SCd 0 3 6 9 12 1S 18 21 24 27 30 33 36 39 42 Sampling Day 155

PAGE 167

-.c c. c. .: era .. -.: u 1:! 0 u :=-c. .: 0 --era .. c u CJ .: 0 u Figure A9-5a Toluene Concentration (2nd Application) Column 5, Level a 500 400 300 200 100 0 21 24 27 30 33 36 Sampling Day 5Aa 39 5Ba 5Ca Figure A9-5b Toluene Concentration (2nd Application) Column 5, Level b 500 400 300 200 100 0 5Ab o 5Bb 5Cb 42 21 24 27 30 33 36 39 42 Sampling Day 156

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i. g. -c c : .. c ; 8 ;c-g. g. -c .s .. c u c 0 u Figure A9-5c Toluene Concentration (2nd Application) Column S, Level c 500 400 300 200 100 0 21 24 27 30 33 Sampling Day 36 SAc 0 SBc sec 39 Figure A9.;.Sd Toluene Concentration (2nd Application) 500 400 300 200 100 0 21 24 Column S, Level d 27 30 33 Sampling Day 157 36 39 SAd SBd SCd 42 42

PAGE 169

Appendix B Nitrous Oxide Data 158

PAGE 170

Table B 1 Nitrous Oxide Concentration Summary Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5/15/94 5/21194 5124194 5/27194 5131/94 612194 1Aa 523 367 415 437 425 331 lAb 442 425 1362 378 476 303 lAc 365 520 397 460 300 392 lAd 433 369 370 401 466 322 1Ba 566 229 357 624 301 559 lBb 254 892 317 480 276 437 1Bc 319 257 400 257 338 357 lBd 287 304 373 492 584 384 lCa 304 250 287 1583 522 541 lCb 405 266 412 1941 367 477 1Cc 333 537 373 146 520 171 lCd 316 287 362 500 417 2Aa 360 402 353 451 343 582 2Ab 378 370 386 413 365 609 2Ac 449 965 413 389 375 654 2Ad 487 467 500 651 604 304 2Ba 235 217 411 2407 352 369 2Bb 350 271 355 139 553 411 2Bc 422 243 709 140 516 396 2Bd 456 353 347 810 514 469 2Ca 233 320 2156 413 534 2Cb 524 204 333 2070 501 512 2Cc 358 289 421 130 415 625 2Cd 485 268 452 625 395 423 3Aa 303 369 475 364 319 569 3Ab 353 427 551 418 559 493 3Ac 427 1041 528 435 400 377 3Ad 530 418 432 692 676 709 3Ba 437 276 370 593 639 553 3Bb 470 541 439 435 347 535 3Bc 447 346 386 549 360 568 3Bd 339 381 1400 402 519 475 3Ca 268 272 298 2044 469 460 3Cb 276 480 467 691 448 345 3Cc 335 382 389 130 371 553 3Cd 393 471 490 2087 483 614 4Aa 2900 518 498 397 898 564 4Ab 1300 599 659 810 467 528 4Ac 793 509 694 416 596 555 4Ad 571 501 572 460 707 520 4Ba 295 220 658 174 339 1538 159

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Table B 1 Nitrous Oxide Concentration Summary (con't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) S/1S/94 S/21/94 S/24/94 S/27/94 S/31/94 6/2/94 4Bb 272 0 316 1765 300 S36 4Bc 463 238 4S7 14S 44S 769 4Bd 3S2 1171 396 424 S9S S62 4Ca 277 261 33S 1396 494 46S 4Cb 61S 228 302 679 407 478 4Cc 302 240 4S6 1602 S16 60S 4Cd 3S7 286 337 1S48 427 426 SAa 722 443 416 354 362 498 SAb 6S1 481 341 381 366 41S SAc 606 S34 488 346 349 S88 SAd 732 S44 63S SOl 499 SBa 4S4 1323 439 931 333 813 SBb 474 222 272 1423 S63 914 SBc SS2 247 678 1271 297 427 SBd 369 1762 447 14S 411 772 sea 274 210 273 417 36S 378 SCb 329 28S 309 2086 291 405 sec 37S 269 394 130 479 S6S SCd 338 23S 336 438 436 253S *No measurement made 160

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Table B1 Nitrous Oxide Concentration Summary (con't) Formula Column Concenbation Concenbation Concenbation (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 6/5/94 6/8/94 6/11/94 6/14/94 6/17/94 6120/94 lAa 625 440 320 362 311 357 lAb 622 398 398 302 342 364 lAc 426 450 281 298 333 301 lAd 457 447 360 305 389 357 lBa 390 445 476 402 313 551 lBb 334 329 552 388 269 407 lBc 370 341 574 330 283 457 lBd 334 439 304 349 253 678 lCa 372 334 297 299 336 481 lCb 389 543 435 308 464 544 ICc 384 414 415 287 253 379 lCd 401 498 278 325 320 491 2Aa 632 522 910 479 1311 1357 2Ab 570 512 1210 1470 816 1609 2Ac 383 638 1284 1614 1155 1344 2Ad 502 639 1212 1752 1077 1487 2Ba 394 420 2920 1094 1830 1597 2Bb 287 511 889 1406 2221 1243 2Bc 49 528 1021 1407 2154 1020 2Bd 271 501 896. 1401 3865 1123 2Ca 403 520 900 1170 2366 2580 2Cb 403 608 924 1724 5001 2779 2Cc 373 583 948 2426 6904 4492 2Cd 415 525 1111 3338 8615 1697 3Aa 696 579 1219 5965 3437 9163 3Ab 429 811 2120 5925 2568 8513 3Ac 467 933 2874 3525 2738 8299 3Ad 463 1084 3119 5181 3099 8358 3Ba 426 590 12706 3976 1776 6317 3Bb 359 1003 32348 5195 2204 8296 3Bc 489 606 30337 5273 2155 8195 3Bd 523 1158 32504 6805 2412 14146 3Ca 448 395. 748 2517 3217 5301 3Cb 436 572 686 2399 2767 5141 3Cc 521 431 512 342 2961 5145 3Cd 505 666 497 1895 2862 6110 4Aa 178 49561 50729 44483 19037 12716 4Ab 834 83587 95521 48722 42005 26248 4Ac 1376 130268 145226 136612 53823 38143 4Ad 2306 188993 182259 177667 67442 54710 4Ba 448 591 1582 1666 9518 32696 161

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Table B 1 Nitrous Oxide Concentration Summary (can't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 61S/94 618/94 6/11/94 6114/94 6/17/94 6/20/94 4Bb 919 730 2236 2066 18279 61378 4Bc 508 S27 1739 229S 28450 92236 4Bd 487 S93 1462 2204 42144 118239 4Ca 272 469 2488 1S41 1372 941 4Cb 270 487 4744 1647 1696 892 4Cc 246 498 6010 2204 171S 947 4Cd 248 640 6S10 1797 1887 1009 SAa 406 3S7 S24 432 311 320 SAb 364 S9S 399 313 3S3 360 SAc 433 492 472 341 390 33S SAd 440 413 370 369 3SO 4S1 SBa 836 421 328 3S2 268 439 SBb 4S1 382 325 400 300 361 SBc 432 S08 346 41S 264 410 SBd 424 469 478 429 366 404 sea 43S 3S1 294 394 323 S03 SCb 440 487 309 419 383 416 sec 432 S15 368 418 S09 610 SCd 440 S42 414 385 443 S23 *No measurement made 162

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Table B 1 Nitrous Oxide Concentration Summary (con't) Formula Column Concentration Concentration (ppb) (ppb) 6/23/94 6/25/94 lAa 309 368 lAb 289 301 lAc 407 333 lAd 319 326 lBa 593 832 lBb 344 396 lBc 317 301 1Bd 351 384 1Ca 413 356 lCb 323 360 ICc 376 317 1Cd 425 354 2Aa 1398 1110 2Ab 1729 1693 2Ac 1645 1588 2Ad 1956 1532 2Ba 1141 1057 2Bb 1724 1819 2Bc 2005 1267 2Bd 1194 1318 2Ca 1023 964 2Cb 1345 1071 2Cc 1420 1070 2Cd 1538 1171 3Aa 3160 3191 3Ab 4052 3557 3Ac 3940 3801 3Ad 4484 3495 3Ba 6177 9407 3Bb 9467 14164 3Bc 15020 20358 3Bd 20606 25539 3Ca 4470 8715 3Cb 5626 14450 3Cc 9892 25311 3Cd 11866 33876 4Aa 10098 11688 4Ab 17039 26197 4Ac 22249 37542 4Ad 29594 49945 4Ba 26398 42705 163

PAGE 175

Table Bl Nitrous Oxide Concentration Summary (con't) Fonnula Column Concenbation (ppb) (ppb) 6/23/94 6/25/94 4Bb S4482 76724 4Bc 65998 93826 4Bd 87598 13S277 4Ca 773 1434 4eb 8S9 987 4Cc 912 1118 4Cd 983 1760 SAa 29S 488 SAb 425 383 SAc 384 41.9 SAd 433 S18 SBa SS3 S32 SBb 6S3 370SBc 733 986 SBd S68 926 sea 41S 344 Seb 401 3SS. sec 376 664 Sed 882 1079 *No measurement made 164

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Table B2 Average Nitrous Oxide Concentrations Formula Column Average Average Average Average Average Average Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 5/15/94 5121194 5124194 5/27/94 5/31/94 612t94 1_a 464 282 353 881 416 477 1_b 367 528 697 933 373 406 1_c 339 438 390 288 386 307 1_d 345 320 368 447 517 374 Col1 Mean 379 392 452 637 423 391 StdDev 58 112 164 319 65 71 2_a 298 284 361 1671 369 495 2_b 417 282 358 874 473 511 2_c 410 499 514 220 435 558 2_d 476 363 433 695 504 399 Col2Mean 400 357 417 865 446 491 StdDev 75 102 74 604 58 67 3_a 336 306 381 1000 476 527 3_b 366 483 486 515 451 458 3_c 403 590 434 371 377 499 3_d 421 423 774 1060 559 599 Col3 Mean 382 450 519 737 466 521 StdDev 38 118 175 345 75 60 4_a 1157 333 497 656 577 856 4_b 729 276 426 1085 391 514 4_c 519 329 536 721 539 643 4_d 427 653 435. 811 576 503 Col4Mean 708 398 473 818 521 629 StdDev 325 172 52 189 88 164 5_a 483 659 376 567 353 563 5_b 487 329 307 1297 407 578 5_c 511 350 520582 375 527 5_d 354 910 442 406 449 1269 Col5Mean 459 562 411 713 396 734 StdDev 71 276 91 397 42 357 *No measurement made 165

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Table B2 Average Nitrous Oxide Concentrations (con't) Formula Column Average Average Average Average Average Average Concentration Concentration Concentration Concentration Concentration Concentration (ppb) (ppb) (ppb) (ppb) (ppb) (ppb) 6/5/94 618194 6/11194 6/14/94 6/17/94 6/20194 l_a 462 406 364 354 320 463 l_b 448 423 462 333 358 438 l_c 393 402 423 305 290 379 l_d 397 461 314 326 321 509 Coil Mean 425 423 391 330 322 447 StdDev 35 27 65 20 28 54 2_a 476 487 1577 914 1836 1845 2_b 420 544 1008 1533 2679 1877 2_c 268 583. 1084 1816 3404 2285 2_d 396 sss 1073 2164 4519 1436 Col2Mean 390 542 1185 1607 3110 1861 StdDev 88 40 263 529 1137 347 3_a 523 521 4891 4153 2810 6927 3_b 408 795 11718 4506 2513 7317 3_c 492 657 11241 3047 2618 7213 3_d 497 969 12040 4627 2791 9538 Col3Mean 480 736 9973 4083 2683 7749 StdDev so 192 3404 720 142 1204 4_a 299 16874 11i266 15897 9976 15451 4_b 674 28268 34167 17478 20660 29506 4_c 710 43764 50992 4703T 27996 43775 4_d 1014 63409 63410 60556 37158 57986 Col4Mean 674 38079 41709 35242 23947 36680 Std Dev 293 20165 19694 22134 11502 18316 S_a 559 376 382 393 301 421 S_b 418 488 344 377 345 379 S_c 432 sos 395 391 388 452 S_d 435 475 421 394 386 459 Col5Mean 461 461 386 389 355 428 Std Dev 66 58 32 8 41 36 *No measurement made 166

PAGE 178

Formula Column 1_a 1_b l_c l_d Coli Mean StdDev 2_a 2_b 2_c 2_d Col2Mean StdDev 3_a 3_b 3_c 3_d Col3Mean StdDev 4_a 4_b 4_c 4_d Col4Mean StdDev 5_a 5_b 5_c 5_d Col5Mean StdDev *No measurement made Table B2 Average Nitrous Oxide Concentrations (con't) Average Average Conceobation Concenttation (ppb) (ppb) 6123/94 6/25/94 438 519 319 352 367 317 365 355 372 386 49 90 1187 1044 1599 1528 1690 1308 1563 1340 1510 1305 222 199 4602 7104 6382 10724 9617 16490 12319 20970 8230 13822 3426 6136 12423 18609 24127 34636 29720 44162 39392 62327 26415 39934 11259 18277 421 455 493 369 498 690 628 841 510 589 86 216 167

PAGE 179

Figure 81-1 Nitrous Oxide ConcentrationsColumn 1, Levels a -d 3()()()() 25000 1_a ,.Q c. 2()()()() 1_b c. -0 1_c I: .. 1_d Q -15000 .. f .. I: 1()()()() Col I: Q u 5000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure 81-2 Nitrous Oxide ConcentrationsColumn 2, Levels a-d I: .s .. I: 3()()()() 25000 2()()()() 15000 1()()()() 8 5000 2_a 2_b 2_c .. 2_d 0 3 6 9 12. 15 18 21 24 27 30 33 36 39 42 Sampling Day 168

PAGE 180

Figure Bl-3 Nitrous Oxide Concentrations Column 3, Levels a d 30000 25000 .c Cl. 20000 3_a Cl. 3_b = D 3_c .s .. 15000 3_d f .. = 10000 "' = 0 u 5000 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure Bl-4 Nitrous Oxide Concentrations Column 4, Levels a d 80000 70000 60000 .c Cl. Cl. 50000 -D4_a 4_b 4_c = 0 40000 -al 6 4_d .. = 30000 "' = 0 20000 u 10000 0 0 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 169

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Figure Bl-5 Nitrous Oxide ConcentrationsColumn 5, Levels a-d :;; !: -! iu: 8 30000 25000 20000 15000 10000 5000 S_a S_b S_c .. S_d 0 3 6 9 12 IS 18 21. 24 27 30 33 36 39 42 Sampling Day 170

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Appendix C Nitrate Data 171

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Table Cl Nitrate Concentration Summary Fonnula Column Concentration Concentration Concentration Concentration Concentration Concentration 1Aa lAb lAc lAd lAe lBa lBb lBc lBd lBe lCa lCb ICc lCd ICe 2Aa 2Ab 2Ac 2Ad 2Ae 2Ba 2Bb 2Bc 2Bd 2Be 2Ca 2Cb 2Cc 2Cd 2Ce 3Aa 3Ab 3Ac 3Ad 3Ae 3Ba 3Bb 3Bc 3Bd 3Be 3Ca 3Cb 3Cc (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) S/17/94 S/21/94 S/24/94 S/27194 S/30/94 612194 0 .. 0 0 0 0 0 0 0 0 * * 859 1281 1154 894 895 992 909 888 0 * 0 0 0 0 0 0 0 0 0 * 0 ... 0 348 859 354 636 ... ... 8SS * ... 0 * 0 0 * ... ... ... ... 1 0 0 2 ... 0 0 ... ... 4 0 ... 861 1017 ... 908 "' 950 ... 172 ... * 0 1 12 0 0 0 ... ... "' . ... ... ... 0 0 ... 0 896 869 784 632 916 ... 821 683 131 * * 0 0 ... 23 0 ... 1 44 0 0 0 24 0 0 0 IS ... 35 6 ... 591 666 ... 589 496 71 ... 0 0 0 ... ... "' 0 0 0 1 0 26 ... 0 4 2 ... "' "' 945 408 38 ...

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Table Cl Nitrate Concentration SWnmary (con't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) S/17/94 S/21/94 S/24194 S/27/94 S/30/94 6/'JJ94 3Cd * S69 798 3Ce 880 466 849 8S1 808 930 4Aa * 4Ab 4Ac 680 760 305 4Ad 848 902 8S1 643 4Ae 974 829 S8S 1049 822 433 4Ba * 100 4Bb 9SS 4S3 4Bc 899 948 962 4Bd * 4Be 923 1046 1180 804 882 927 4Ca * 4Cb 943 * * 4Cc * S42 4Cd 906 943 4Ce 940 91S 639 632 677 684 SAa 887 SAb SAc * * SAd * 429 SAc 763 689 1011 7S8 70S 620 SBa 297 SBb SBc 773 70S 772 625 SBd 6S4 8S7 302 709 624 SBe 933 S92 S48 830 702 63S sea 980 908 * * SCb 797 * * sec * SCd 79 726 803 see 825 807 728 651 810 91S *No sample or insufficient sample 173

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Table Cl Nitrate Concentration Summary (con't) Formula Column Concentration Concentration Concentration Cooc:entration Concentration Concentration lAa lAb lAc lAd lAe lBa lBb lBc lBd I Be lCa lCb ICc lCd ICe 2Aa 2Ab 2Ac 2Ad 2Ae 2Ba 2Bb 2Bc 2Bd 2Be 2Ca 2Cb 2Cc 2Cd 2Ce 3Aa 3Ab 3Ac 3Ad 3Ae 3Ba 3Bb 3Bc 3Bd 3Be 3Ca 3Cb 3Cc (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) 6/5/94 618194 6/11194 6/14/94 6/17/94 6/20/94 0 * * 2 * 12 * * 0 0 0 0 0 0 0 * 38 151 3 174 370 1087 783 271 * 1747 * 0 * 0 * 0 * * 0 0 0 * * 0 0 0 2 3 80 899 885 * 930 862 * 0 * 0 0 0 1 * * 19 0 0 0 0 0 0 9 0 1 0 45 588 782 * 847 824 174 0 0 0 0 0 0 .. * 0 .. 0 .. 0 0 .. 0 .. .o 0 0 0 0 0 3 23 322 672 173 * 686 574 .. 0 * 0 6 * .. .. 0 * .. 721 * 0 .. 0 0 746 174 .. 715 .. 807 * .. * 0 0 .. * 0 0 .. 0 .. 82 .. 0 0 .. 0 0 * 185 428 * * 1097 * 903 821 1021 *

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Table Cl Nitrate Concentration Summary (con't) Formula Column Concentration Concentration Concentration Concentration Concentration Concentration (ppm) (ppm) (ppm) (ppni) (ppm) (ppm) 6/S/94 6/8/94 6/11/94 6/14/94 6/17194 6/20/94 3Cd 876 ll01 894 3Ce 398 723 83S 726 10S1 894 4Aa * 60S 4Ab 4Ac 111 646 3S 4Ad * 46S 663 831 4Ae 979 902 789 87S 874 1074 4Ba 84 8 * 1321 4Bb 479 162 110 SS7 4Bc * 4Bd 939 * 9S3 4Be 923 843 8SO 70S 786 1254 4Ca 4Cb 1S22 210 83 89 271 4Cc S03 4Cd * 846 706 7S2 790 4Ce 1049 981 863 734 8S3 824 SAa * SAb 87 4S 24 4 SAc * SAd * 837 SAe 803 649 S98 910 776 SBa * * 5Bb 47 SS1 84S SBc 31S 5Bd 871 781 S13 SBe 836 709 760 669 1071 827 SCa SCb sos 248 11S * sec SCd 741 773 7S3 .S86 866 see 988 878 78S 646 ll1S 849 *No sample or insufficient sample 175

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Table Cl Nitrate Concentration Summary (con't) Formula Column Concentration Concentration (ppm) (ppm) 6/23/94 6/25/94 lAa lAb 2 lAc lAd lAe 2 0 lBa lBb lBc 0 lBd 1 lBe 0 0 lCa lCb lCc lCd lCe 0 0 2Aa 2Ab 303 2Ac 2Ad 0 2Ae 0 3 2Ba 2Bb 92 2Bc .. . 2Bd 3 2Be 4 4 2Ca 2Cb 2Cc 2Cd 3 2Ce 10 3Aa * 3Ab * 3Ac * 3Ad 3Ae 1164 1223 3Ba * 3Bb 229 3Bc * 3Bd 1261 3Be 1202 6 3Ca 343 415 3Cb 946 3Cc 176

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Table Cl Nitrate Concentration Summary (con't) Fonnula Column Concentration Concentration (ppm) (ppm) 6/23/94 6/25/94 3Cd 1038 3Ce 1243 1238 4Aa 4Ab 4Ac so 10 4Ad 644 4Ae 892 962 4Ba 1468 4Bb 703 4Bc 450 4Bd 839 880 4Be 1220 1219 4Ca 4Cb 684 4Cc 4Cd 4Ce 1194 1247 SAa SAb SAc SAd SAe 1039 1081 SBa 35 SBb SBc SBd 761 SBe 1149 107 sea SCb 96 sec SCd 963 see 1198 1238 *No sample or insufficient sample 177

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Table C2 Average Nitrate Concentrations Formula Column Average Average Average Average Average Average Concentration Concentration Concentration Concentration Concentration Concentration (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) 5/17/94 5/21/94 5124194 5/27/94 5130194 6/2/94 l_a 0 0 12 l_b 0 0 . 0 0 l_c 0 0 l_d 0 23 l_e 0 0 0 1 0 0 Coil Avg 0 0 0 3 8 0 2_a 0 0 2_b 0 0 1 0 28 0 2_c 0 0 0 2_d 0 0 1 12 0 2_e 0 0 0 2 10 Col2Avg 0 0 1 0 10 2 3_a 992 492 382 71 38 3_b 1032 916 3_c 880 859 884 896 591 3_d 753. 693 3_e 1019 558 938 773 657 761 Col3Avg 981 636 911 744 503 399 4_a 100 4_b 949 453 4_c 680 760 602 745 962 4_d 877 902 851 643 943 4_e 946 930 802 829 794 682 Col4Avg 863 864 802 761 659 672 5_a 980 908 887 297 5_b 797 * 5_c 773 705 772 625 5_d 79 654 857 485 709 713 5_e 840 696 763 747 739 723 Col5Avg 674 758 803 575 691 718 *No sample or insufficient sample 178

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Table C2 Average Nitrate Concentrations (con't) Formula Column Average Average Average Average Average Average Concentration Concentration Concentration Concentration Concentration Concentration (ppm) (ppm) (ppm) (ppm) (ppm) (ppm) 6/5/94 618/94 6/11/94 6/14/94 6/17/94 6/20/94 l_a * * * l_b 0 0 0 * l_c: * 0 0 * l_d 0 0 0 1_e 6 0 7 0 2 0 Coil Avg 4 0 2 0 1 0 2_a 0 9 0 2_b 0 0 0 0 82 2_c: 38 0 0 185 2_d 50 0 0 0 0 0 2_e 1 0 1 240 143 Col2 Avg 22 o 2 0 120 102 3_a 271 * .173 174 3_b 174 80 45 23 3_c: 370 930 588 448 715 903 3_d 981 899 847 1101 572 3_e 976 823 814 695 868 1004 Col3 Avg 555 683 573 335 715 826 4_a 84 8 605 1321 4_b 1001 186 96 89 414 4_c: 111 574 ... 35 4_d 939 656 706 707 858 4_e 984 909 834 771 837 1051 Col4Avg 752 342 562 524 455 911 5_a * * 5_b 296 147 62 551 845 4 5_c: 315 5_d 806 777 753 586 852 513 5_e 912 797 731 638 1032 817 Col5 Avg 671 574 465 592 909 445 *No sample or insufficient sample 179

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Table C2 Average Nitrate Concentrations (con't) Formula Column Average Average Concentration Concentration (ppm) (ppm) 6/23/94 6n5/94 1_a l_b 2 l_c 0 l_d 1 l_e 1 0 Colt Avg 0 2_a 2_b 92 303 2_c 2_d 2 2_e 2 6 Col2Avg 32 154 3_a 343 415 3_b 587 3_c 3_d 1261 1038 3_e 1203 822 Col3 Avg 849 758 4_a 1468 4_b 693 4_c 250 10 4_d 742 880 4_e 1102 1143 Col4-Avg 851 677 5_a 35 5_b 49 S_c 5_d 862 5_e 1129 809 Col5Avg 680 422 *No sample or insufficient sample 180

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Figure C1-1 Average Nitrate Concentrations-Column 1, Levels a-e 1500 1250 1_a i 1_b Cl. 1000 1_c Cl. 1_d c 1_e 750 ... Ill "" ... c 500 u u c = u 250 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day Figure C1-2 Average Nitrate Concentrations-Column 2, Levels a-e 1500 1250 2_a E 2_b Cl. 1000 Cl. 2_c -c .. 2_d = 2_e 750 ... Ill "" ... c 500 u u c = u 250 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 181

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Figure Cl-3 Average Nitrate ConcentrationsColumn 3, Levels a-e 0 3 6 9 12 15 18 21 24 27 30. 33 36 39 42 Sampling Day Figure Cl-4 Average Nitrate ConcentrationsColumn 4, Levels a-e 1500 1250 I 1000 1:1. -c = 750 -... f '! u 500 0 = o-4_c u 250 Ill 4_d 4_e 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 182

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Figure Cl-5 Average Nitrate Concentrations .. Column 5, Levels a-e 1500 S_a 1250 S_b S_c i S_d =-1000 S_e ,eo 1: c 750 .. .. = 500 u c u 250 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Day 183

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Appendix D Lysimeter Data 184

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Table D 1 Summary of Lysimeter Sample Quantities Formula Column Sample Sample Sample Sample Sample Sample Sample Sample Quantity Quantity Quantity Quantity Quantity Quantity Quantity Quantity (mL) (mL) (mL) (mL) (mL) (mL) (mL) (mL) 5/17/94 5/21/94 .5/24/94 5/27/94 5!30194 612/94 615194 618/94 lAa 0.0 0.0 0.0 05 0.0 0.0 0.0 0.0 lAb 0.0 15.0 15.0 0.0 15 0.0 20.0 16.7 lAc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 lAd 0.0 0.0 0.0 6.7 13.3 0.0 0.0 13.3 lAe 6.7 10.0 16.7 15.0 20.0 20.0 20.0 20.0 lBa 0.0 10.0 13.3 6.7 0.0 0.0 0.0 0.0 lBb 0.0 0.0 0.0 0.0 10.0 10.0 3.0 0.0 1Bc 0.0 6.7 0.0 10.0 0.0 15 10.0 15 1Bd 0.0 0.0 0.0 16.7 13.3 15 1.0 0.0 lBe 10.0 10.0 0.0 20.0 20.0 20.0 20.0 15.0 lCa 0.0 0.0 o.o 0.0 0.0 0.0 0.0 0.0 ICb 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ICc 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1Cd 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ICe IO.O 5.0 6.7 6.7 6.7 6.7 20.0 I6.7 2Aa 05 0.0 0.0 1.5 0.0 0.0 1.0 0.0 2Ab 5.0 6.7 13.3 0.0 5.0 5.0 2.0 0.0 2Ac 0.0 1.0 16.7 I5 05 I5 0.0 10.0 2Ad 13.3 5.0 I6.7 0.0 0.0 20.0 20.0 20.0 2Ae 10.0 IO.O 13.3 16.7 16.7 IO.O 20.0 20.0 2Ba 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2Bb 5.0 I5.0 05 0.5 IO.O 10.0 5.0 I5 2Bc 0.0 0.0 0.0 0.0 IO.O 05 0.0 0.0 2Bd I3.3 0.0 20.0 0.0 I6.7 1.0 IO.O 1.0 2Be IO.O 10.0 20.0 I6.7 20.0 20.0 5.0 20.0 2Ca 15 0.0 05 0.5 15 05 1.0 4.0 2Cb 0.0 0.0 0.0 6.7 6.7 0.0 1.0 6.7 2Cc 0.0 0.0 0.0 0.0 0.0 5.0 5.0 1.5 2Cd 0.0 0.0 16.7 0.0 20.0 20.0 0.0 20.0 2Ce 6.7 10.0 5.0 6.7 16.7 5.0 20.0 20.0 3Aa 0.0 4.0 15 0.0 0.0 0.0 0.0 0.0 3Ab 0.0 0.0 0.0 0.0 0.0 0.0 2.0 6.7 3Ac 1.0 6.7 05 6.7 10.0 1.0 2.0 1.5 3Ad 0.0 0.0 0.0 15.0 0.0 0.0 15.0 20.0 3Ae 6.7 20.0 20.0 15 6.7 10.0 20.0 20.0 3Ba 0.0 6.7 05 4.0 0.0 0.0 15 1.0 3Bb 6.7 1.0 05 15 15 1.0 1.0 1.0 3Bc 5.0 1.0 5.0 4.0 2.0 05 0.0 6.7 3Bd 0.0 0.0 0.0 16.7 16.7 0.0 1.0 1.0 3Be 10.0 10.0 16.7 15.0 16.7 20.0 15.0 20.0 3Ca 15 0.0 0.0 1.5 4.0 6.7 0.0 0.0 3Cb 15 0.0 0.0 0.0 0.0 0.0 0.0 0.0 185

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Table Dl Summary ofLysimeter Sample Quantities (con't) Formula Column Sample Sample Sample Sample Sample Sample Sample Sample Quantity Quantity Quantity Quantity Quantity Quantity. Quantity Quantity (mL) (mL) (mL) (mL) (mL) (mL) (mL) (mL) S/11194 S/21194 S/24194 S/21194 Sl30194 6/'2J94 6/S/94 618/94 3Cc 10.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3Cd 0.0 0.0 05 20.0 20.0 15 15.0 1.0 3Ce 10.0 1S.O 133 s.o s.o 10.0 20.0 20.0 4Aa 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4Ab 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4Ac 6.7 10.0 05 6.7 1.0 1.0 0.0 20.0 4Ad l.S 10.0 05 20.0 20.0 15 1.0 1.0 4Ae 6.7 133 16.7 s.o 133 20.0 s.o 20.0 4Ba 05 15 0.0 05 15 s.o 2.0 6.7 4Bb 5.0 0.0 05 0.0 10.0 0.0 4.0 0.0 4Bc 0.5 0.0 0.5 6.7 10.0 6.7 1.0 0.0 4Bd 0.0 0.0 05 o.s 05 15 1S.O 1.0 4Be 10.0 10.0 133 16.7 13.3 6.7 20.0 20.0 4Ca 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4Cb 6.7 0.0 05 15 15 05 4.0 0.0 4Cc o.s 1.0 05 05 33 1.0 0.0 0.0 4Cd 20.0 0.0 0.0 0.0 0.0 6.7 0.0 0.0 4Ce 10.0 10.0 20.0 16.7 6.7 20.0 20.0 6.7 SAa 0.0 0.0 15 0.0 0.0 0.0 0.0 0.0 5Ab 0.0 0.0 0.0 0.0, 1.0 0.0 15 0.0 SAc 0.0 0.0 .. 0.0. -. 0.0 ... 0.0 ". O.O .c . 0.0 0.0 5Ad 0.0 0.0 05 16.7 15 0.0 0.0 6.7 SAe 6.7 10.0 05 33' 20.0 20.0 20.0 16.7 SBa 0.0 0.0 0.0 l.S 0.0 0.0 0.0 0.0 5Bb 0.0 0.0 0.0 0.0 0.0 0.0 20.0 0.0 5Bc 0.0 s.o 1.0 3.3 s.o 15 0.0 0.0 5Bd 0.0 20.0 16.7 20.0 20.0 20.0 0.0 20.0 5Be 10.0 10.0 20.0 15 20.0 20.0 20.0 20.0 sea 15 s.o 05 l.S 05 15 0.0 0.0 5Cb l.S 0.0 0.0 0.0 0.0 0.0 15 6.7 sec 0.0 0.0 15 0.0 05 0.0 0.0 0.0 5Cd 1S.O 0.0 05 16.7 1.0 s.o 20.0 20.0 5Ce 10.0 15 05 20.0 33 133 s.o 10.0 186

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Table Dl Summary ofLysimeter Sample Quantities (con't) Formula Column Sample Sample Sample Sample Sample Sample Quantity Quantity Quantity Quantity Quaotity Quantity (mL) (mL) (mL) (mL) (mL) (mL) 6/11194 6/14194 6/17194 6/20194 6123194 6/25194 IAa 0.0 0.0 0.0 0.0 0.0 lAb 13.3 20.0 o.s o.s 20.0 0.0 lAc 0.0 0.0 0.0 0.0 0.0 0.0 lAd 0.0 13.3 0.0 15.0 0.0 0.0 1Ae 20.0 20.0 20.0 20 0 20.0 20.0 1Ba 6.7 0.0 0.0 0.0 0.0 0.0 1Bb 0.0 13.3 o.s 0.0 0.0 0.0 1Bc 3.3 6.7 1.0 1.0 13.3 1.0 lBd 0.0 0.0 13.3 1.0 1.5 1.0 1Be 20.0 20.0 20.0 20.0 20.0 20.0 lCa 0.0 0.0 0.0 0.0 0.0 0.0 lCb 0.0 0.0 0.0 0.0 0.0 0.0 ICc 0.0 0.0 0.0 0.0 0.0 0.0 lCd 0.0 0.0 0.0 0.0 0.0 0.0 ICc 5.0 6.7 5.0 5.0 10,0 5.0 2Aa 0.0 0.0 0.0 0.0 Q.O 0.0 2Ab 2.0 l.S 0.0 5.0 2.0 2Ac 0.0 o.s 0.0 0.0 0.0 0.0 2Ad 16.7 16.7 1.0 l.S o.s 1.5: 2Ae 20.0 20.0 20.0 4.0 20.0 20.0 2Ba 0.0 o.o. 0.0 0.0 0.0 0.0 2Bb 1.5 1.5 1.0 0.0 1.5 o.s 2Bc l.S 0.0_ 0.0 0.0 o.s 0.0 2Bd 0.0 l.S 15.0 2.0 20.0 1.0 2Be 20.0 20.0 20.0 20.0 20.0 20.0 2Ca 2.0 1.5 3.3 0.0 o.s o.s 2Cb 5.0 5.0 1.0 o.s 0.0 o.s 2Cc 0.0 20.0 0.0 4.0 0.5 0.5 2Cd 20.0 0.0 5.0 0.0 1.0 0.0 2Ce 5.0 20.0 15.0 20.0 20.0 20.0 3Aa 0.0 0.0 0.0 0.0 0.0 0.0 3Ab 6.7 6.7 o.s 0.0 o.s 1.0 3Ac 6.7 5.0 o.s 0.5 o.s 0.0 3Ad 1.0 0.0 0.0 1.0 0.0 0.0 3Ae 20.0 13.3, 20.0 20.0 20.0 20.0 3Ba 0.0 2.0 l.S 0.0 0.0 0.0 3Bb 0.0 1.0 1.5 0.5 o.s 0.0 3Bc 1.5 1.5 5.0 6.7 0.5 1.0 3Bd 20.0 l.S 1.5 15.0 4.0 1.0 3Be 10.0 20.0 20.0 20.0 20.0 20.0 3Ca 0.0 0.0 0.0 0.0 6.7 5.0 3Cb 0.0 0.0 0.0 0.0 0.0 0.0 187

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Table Dl Summary ofLysimeter Sample Quantities (can't) Formula Column Sample Sample Sample Sample Sample Sample Quantity Quantity Quantity Quantity Quantity Quantity (mL) (mL) (mL) (mL) (mL) (mL) 6/11194 6/14194 6/17194 6/20194 6123194 6/25194 3Cc 0.0 1S.O 05 0.0 05 o.s 3Cd 0.0 1.0 l.O 20.0 o.s 0.0 3Ce 20.0 20.0 20.0 20.0 20.0 20.0 4Aa 0.0 0.0 4.0 0.0 0.0 0.0 4Ab 0.0 0.0 0.0 0.0 0.0 0.0 4Ac 10.0 05 10.0 1.0 6.7 s.o 4Ad 1.0 1.0 15 20.0 05 l.S 4Ae 20.0 20.0 20.0 20.0 6.7 20.0 4Ba 0.0 0.0 0.0 6.7 s.o 0.0 4Bb 1S.O 1.0 1.0 10.0 1.0 1.0 4Bc 0.0 0.0 0.0 0.0 1.0 0.0 4Bd 0.0 1.0 1.0 20.0 1.0 20.0 4Be 20.0-10.0 20.0. .0 20.0. 20.0 4Ca 0.0 0.0 0.0 0.0 0.0 0.0. 4Cb 1.0 1.0 s.o 10.0 6.7 05 4Cc 15 0.0 1.0 0.0 05 0.0 4Cd 10.0 20.0 20.0 20.0 05 1.0 4Ce 10.0 13.3 20.0 20.0 20.0 10.0 SAa 0.0 0.0 0.0 0.0 0.0 0.0 SAb s.o 1.0 05 s.o 4.0 0.0 SAc 10.0 0.0 0.0 0.0 0.0 0.0 SAd 0.0 0.0 16.7 1.0 0.0 0.0 SAe 0.0 20.0 20.0 20.0 20.0 20.0 SBa 1.0 05 0.0 0.0 05 2.0 SBb s.o 0.0 0.0 0.0 0.0 0.0 SBc s.o 0.0 0.0 0.0 0.0 0.0 SBd 1.0 16.7 16.7 0.0 s.o 1.0 SBe 20.0 20.0 20.0 20.0 20.0 s.o sea 0.0 0.0 05 0.0 1.0 0.0 SCb 10.0 0.0 1.0 05 10.0 1.0 SCc 0.0 0.0 0.0 0.0 0.0 0.0 SCd 6.7 1S.O 20.0 1.0 s.o 1.0 See 10.0 20.0 20.0 6.7 10.0 133 188

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Table 02 Average Lysimeter Sample Quantities Formula Column Average. Average Average Average Average Average Average Average Average Quantity Quantity Quantity Quantity Quantity Quantity Quantity Quantity (mL) (mL) (mL) (mL) (mL) (mL) (mL) (mL) 5/17/94 5/21/94 5/24/94 5/27/94 5130/94 6f2J94 615194 618/94 1_a 0.0 3.3 4.4 2.4 0.0 0.0 0.0 0.0 1_b 0.0 5.0 5.0 0.0 3.8 3.3 7.7 5.6 1_c 0.0 2.2 0.0 3.3 0.0 o.s 3.3 o.s 1_d 0.0 0.0 0.0 7.8 8.9 o.s 0.3 4.4 1_e 8.9 8.3 7.8 13.9 15.6 15.6 20.0 17.2 Colt Mean 1.8 3.8 3.4 5.5 5.7 4.0 6.3 5.5 StdDev 4.0 3.1 3.4 5.5 6.6 6.6 8.3 7.0 2_a 0.7 0.0 .0.2 0.7 o.S 0.2 0.7 1.3 2_b 3.3 7.2 4.6 2.4 7.2 5.0 2.7 2.7 2_c 0.0 0.3 5.6 o.s 3.5 2.3 1.7 3.8 2_d 8.9 1.7 17.8 0.0 12.2 13.7 10.0 13.7 2_e 8.9 10.0 12.8 13.3 17.8 11.7 15.0 20.0 Col2Mean 4;4 3.8 8.2 3.4 8.2 6.6 6.0 8.3 StdDev 4.3 4.5 7.0 5.6. 6.9 5.9 6.2 8.1 3_a o.s 3.6 0.7 1.8 1.3 2.2 0.5 0.3 3_b 2.7 0.3 0.2 OS 05 0.3 1.0 2.6 3_c 5.3 2.6 1.8 3.6 4.0 o.s 0.7 2.7 3_d 0.0 0.0 0.2 17.2 12.2 o.s 10.3 7.3 3_e 8.9 15.0 16.7 7.2 9.4 13 .3 18.3 20.0 Col3 Mean 3.5 4.3 3.9 6.1 5.5 3.4 6.2 6.6 StdDev 3.7 6.2 7.2 6.7 5.1 5.6 8.0 7.9 4_a 0.2 0.5 0.0 0.2 o.s 1.7 0.7 2.2 4_b 3.9 0.0 0.3 0.5 3.8 0.2 2.7 0.0 4_c 2.6 3.7 0.5 4.6 4.8 2.9 0.3 6.7 4_d 7.2 3.3 0.3 6.8 6.8 3.2 5.3 0.7 4_e 8.9 11.1 16.7 12.8 11.1 15.6 15.0 15.6 Col4Mean 4.5 3.7 3.6 5.0 5.4 4.7 4.8 5.0 StdDev 3.5 4.4 7.3 5.2 3.9 6.2 6.0 6.4 5_a 05 1.7 0.7 1.0 0;2 o.s 0.0 0.0 5_b 0.5 0.0 0.0 0.0 0.3 0.0 7.7 2.2 S_c 0.0 1.7 0.8 1.1 1.8 OS 0.0. 0.0 5_d 5.0 6.7 5.9 17.8 7.S 8.3 6.7 15.6 5_e 8.9 7.2 7.0 8.3 14.4 17.8 15.0 15.6 Col5 Mean 3.0 3.4 2.9 5.6 4.9 5.4 5.9 6.7 StdDev 3.9 3.3 3.3 7.6 6.1 7.7 6.2 8.2 189

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Table 02 Average Lysimeter Sample Quantities (can't) Formula Column Average Average Average Average Average Average Average Quantity Quantity Quantity Quantity Quantity Quantity (mL) (mL) (mL) (mL) (mL) (mL) 6/11194 6/14/94 6/17/94 6/20/94 6/23/94 6125194 l_a 2.2 0.0 0.0 0.0 0.0 0.0 1_b 4.4 11.1 0.3 0.2 6.7 0.0 1_c 1.1 2.2 0.3 0.3 4.4 0.3 1_d 0.0 4.4 4.4 5.3 0.5 0.3 1_e 15.0 15.6 15.0 15.0 16.7 15.0 Coil Mean 4.6 6.7 4.0 4.2 5.7 3.1 StdDev 6.1 6.5 6.4 6.5 6.8 6.6 2_a 0.7 0.5 1.1 0.0 0.2 0.2 2_b 2.8 2.7 0.7 1.8 0.5 1.0 2_c 0.5 6.8 0.0 1.3 0.3 0.2 2_d 12.2 6.1 7.0 1.2 7.2 0.8 2_e 15.0 20.0 18.3 14.7 20.0 20.0 Col2Mean 6.2 7.2 5.4 3.8 5.6 4.4 Std Dev 6.9 7.6 7.7 6.1 8.6 8.7 3_a 0.0 0.7 0.5 0.0 2.2 1.7 3_b 2.2 2.6 0.7 0.2 0.3 0.3 3_c 2.7 7.2 2.0 2.4 0.5 0.5 3_d 7.0 0.8 0.8 12.0 1.5 0.3 3:....e 16.7 17.8 20.0 20.0 20.0 20.0 Col3 Mean 5.7 5.8 4.8 6.9 4.9 4.6 StdDev 6.6 7.2 8.5 8.8 8.5 8.6 4_a 0.0 0.0 1.3 2.2 1.7 0.0 4_b 5.3 0.7 2.0 6.7 2.6 0.5 4_c 3.8 0.2 3.7 0.3 2.7 1.7 4_d 3.7 7.3 7.5 20.0 0.7 7.5 4_e 16.7 14.4 20.0 20.0 15.6 16.7 Col4Mean 5.9 4.5 6.9 9.8 4.6 5.3 StdDev 6.3 6.3 7.7 9.6 6.2 7.0 5_a 0.3 0.2 0.2 0.0 0.5 0.7 5_b 6.7 0.3 0.5 1.8 4.7 0.3 5_c 5.0 0.0 0.0 0.0 0.0. 0.0 5_d 2.6 10.6 17.8 0.7 3.3 0.7 5_e 10.0 20.0 20.0 15.6 16.7 12.8 Col5 Mean 4.9 6.2 7.7 3.6 5.0 2.9 StdDev 3.7 8.9 10.3 6.7 6.8 5.5 190

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Figure D1-1 Approximate Lysimeter Sample QuantitiesColumn 1 25 D-1_a 1_b -20 1_c 1 ill 1_d ._.. .... 15 c ::1 e < 10 u c. E Ill 5 r:l.l 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date Figure D1-2 Approximate Lysimeter Sample Quantities Column 2 30 D-2_a 2_b 25 2_c -ill 2_d ..J -20 ;., = .. c 15 Ill ::1 C1 u 10 "S. E Ill r:l.l 5 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date 191

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Figure Dl-3 Approximate Lysimeter Sample Quantities Column 3 30 a-3_a 25 3_b 0 3_c -! Ill 3_d 20 3_e ;;... = c: 15 II :::1 0 10 Cl. E II tl.l 5 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date Figure Dl-4 Approximate LySimeter SaJDple Quantities Column 4 30 a-4_a 25 4_b 4_c -i Ill 4_d -20 4_e .... c: 15 II :::1 0 10 Cl. E II tl.l 5 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date 192

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Figure Dl-5 Approximate Lysimeter Sample Quantities-Column 5 193

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Figure Dl-1 Column 1 Average Lysimeter Sample Quantity 10 8g a 6a 1:1 1:1 1:1 1: Ill = w 1:1 C1 4 1:1 1:1 1:1 u 1:1 1:1 1:1. E Ill 2-= l'l.l 1:1 Coil Avg 0 I I I I I I I I I I I I I 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date Figure D2-2 Column 2 Average Lysimeter Sample Quantity 10 8 -....:I E 6 .... .. .. c Ill = C1 4 u 1:1. E Ill 2 l'l.l Col2Avg 0 I I I .I 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date 194

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Figure Dl-4 Column 4 Average Lysimeter Sample Quantity 10 -8 ..J E 6 -1: Ci 4 .! 1:1. E ca 2 tl.l A Col4Avg 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date Figure D2-5 Column 5 Average Lysimeter Sample Quantity 10 -g- 1 6 ;: 1: ca -:s Ci 4 .! 1:1. E ca 2 tl.l Col5 Avg 0 I I I I I I I 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 Sampling Date 195

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