W VH1." ‘L V“ "I “ . v - ' . ““r‘w - - ‘3 “may. . .3 ' 7- fi' 5‘- I, .91 A. -\ u}:..‘;‘ 'L b. \‘J" . .' r . 2’22: “a: $316.; “3-: in. n f! I! “:41" . v '1 r+u§ n ‘ A . - v. ‘ ,1. ~‘ "3 3‘3“ g ‘3‘?" rim. ,, ,. 231- w” rid. ... “ ' '23-‘23“ ~ ‘3‘. W1 . 4 X. i. ‘L'. ‘ zux’q§%§gx . ”3.? 32.75.11. .~ _ a m - 'fii‘kh 1(.;;a§~;,g“ . ’ l‘ 9:. u’ 1- "‘95“ ":1 5359* ‘- ‘.H $k’ .‘ \ , .‘ - ' u:", “H ‘ I. .1 ' .-,.v . y- . - ~ g. . ,3;- mag, . u“, I'm , , ‘5- ”! Q1. '1. .3. - g,” :3"? RES" 394?.”59. “it“ ’ ,._ ' 53$; ‘é‘ a “?9 1%???“ .. - A ‘ ‘ . .~ ‘V- - ‘u ' '15 .‘-‘»" ' '. ., u w >" . ' .5. 'u ”1“?! , ' ‘_ . \“TJV 2*". “ b v 4 a *tm' ,. «aw: ' ‘ V ’ ‘ 4‘ , .\'-.~¢‘::- fiffi"§:'¢"'fia' .JFI" 1:1,,“ ' ' h \' --‘ - " ‘ ' " ‘F’r‘ ‘(ifi‘k'u , J}: ' . 1 L. “figs“ . r .- I?“ I '~; "V'! ‘Yrv u .< .’ ‘ u ' l V H - O (_ I >5 -11, w. “‘67-. ‘ ' , 4 "hv-J‘ v3 "“4. k. ”‘9' :';"‘J"."“~}J:)I‘:T‘nz:\ < I . ‘v ' ‘15 ‘5‘ J n; I o '. 4 . 'JcUi‘x ‘ " " ~fl - .- * ”xv. .\ , 1:2, (5. u- c _ . y ' x ‘ . _ ‘ - ‘ . - .. ‘1‘." --.‘.*:r.r\"’:‘:':«‘3}J-' 3'99"" 9 “ "g .. . “ I '5” '-‘~ ”W. t 133;. , '25‘.'~r-‘v."" 0. . . '" b3 3“ ‘ 5 ' . v1, . ‘ ’.' \K"o“‘ \ 4' ‘ ’ ‘ ' ‘.“'.‘L‘.‘\ 'U ¢a v “r .'. . ”w. J‘: 5'); ( u. “ii-Ed": " \{X ‘0‘ " . '. . ., :1. 'z’iflgi ' ‘ “ - my“: ”Jigthr'xtmu. ,u -. ”6‘25... ma 1- - 4 ' w ' max ' " Kiri. '2uzf' 59117.": » ~ " ' . . ' t . . t. v.‘\‘ ‘1' ‘ -I r 'V.Q-)4‘.Wv "‘ . .Iva- I. , .“. . 5‘7."‘.:Y"\,g . {5- -~'-'J . . '1‘ . ‘13,. '."7"Véfl 25"}: .. .4 ‘ 4v . Y! . “ha w p“ ' "'2'qu - - . .. '2’}. sum . «firm - _ .' § 7 3:— . ’11:“:1 ' as o q v ' ~ -. Wh‘gtfifi \ “$333,133 . ' . . a. u. :4 ' V 5?~;:.;_.§,;3 MW.“ "5' . Lv.‘ ”I... ~:.'7:V:,11;.}_)‘. ‘4' ": {€13}. . M“? “ .3 37V .' .33". . N . ,3 ,gg... v’. ",J'.'J ‘1 ‘ L w - M a"; ,. u:‘ o . AL. ) ‘ I‘ , i‘ ' (f. 043:»:- 'fl“ M n .‘ .." 'I'-._-' H“. '1‘)‘:’u:y ‘ :- ‘I‘A'. U ‘ JV" .3. A}. \L'w‘ n. .. "a. -. ' ,9‘ 1:36;. I V“:'“‘.“ . ... , ”In. m. m. I' . TEENe This is to certify that the thesis entitled Kinetics of Heavy Metal Transfer from Sludge to Soii presented by Bahram Setoodeh has been accepted towards fulfillment of the requirements for Ph. D. degree in Sanitary Engineering % ‘29.,” Major rofessor Date May 4, 1978 0-7539 ~¢—_. _.~__,____‘..___ __ ‘— KINETICS OF HEAVY METAL TRANSFER FROM SLUDGE TO SOIL By Bahram Setoodeh A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Civil and Sanitary Engineering 1978 ABSTRACT KINETICS OF HEAVY METAL TRANSFER FROM SLUDGE TO SOIL By Bahram Setoodeh Performance of an adsorption and a desorption system under field and flooding hydraulic regimes was investigated. The adsor- bents were glucose, tryptophane, cellulose, clay and a combination of the clay and one of the organics. The clay was a kaolinite. The adsorbents were leached with one of two solutions of 40 mg/l of zinc and cadmium. The desorbents were raw and anaerobically treated sludges obtained from an activated sludge wastewater treatment plant. The sludges were leached with a simulated rain solution. The leachates were collected and analyzed for their zinc and cadmium content, pH, and total carbon. It was found that the data closely fit the empirical adsorption equation proposed by Freundlich. The data, also, fit well into a logarithmic equation of type Y = a + b ln X. The correlation coefficients of the fit of the data to the above logarithmic model, for different clay and clay-organic adsorbents, were found to be 0.99, in the field condition, and greater than 0.87. Bahram Setoodeh It was found that the modified desorption data fit the Freund- lich equation very closely. These data also were fit to a logarithmic model of the type described before. The correlation coefficients of the fit of the data to the models was 99% for both of the sludges. The rate constants of adsorption and desorption of the cations to or from the active media were found and compared. It was found that under both, field and flooding hydraulic condition the rate of adsorption of the cations to the adsorbents always exceeded the rate of release of them from the raw and anaerobically treated sludges. It was shown that the models can be used for prediction pur- poses. This can be done after a short experimental period to determine the sludge and the soil properties and the constants of the model. To Andrew L. Simon my academic inspirer ii ‘1’ minim. ACKNOWLEDGMENTS I would like to thank Dr. Mackenzie Davis, my advisor and the Graduate Committee Chairman, for his thoughtfulness and support during this research. I would also like to thank the members of my Graduate Research Committee: Dr. David Cornwell for his understanding and friendship; Dr. Bernard Knezek for his encouragement; and Dr. Earl Erickson for his financial support without which this work may never have been started; I am indebted to him. A special thanks goes to Dr. Boyd Ellis for his availability and help. Friendships have developed between many graduate students and myself during the years at MSU, I adore all of them. Members of my family stood behind me, patiently, during this work. In my heart I always recognized and appreciated their conti- nuous and overall support. Finally, I would like to acknowledge the financial support received from the Division of Engineering Research. 111 LIST OF LIST OF CHAPTER I. TABLE OF CONTENTS TABLES .......................... FIGURES ......................... Sludge Generation and Disposal ........... Heavy Metals in Sludge ............... Sludge Application Practices ............ Problems with Land Disposal ............. Role of Kinetics in the Sludge-Soil System ..... Hypothesis and Objectives .............. _.a_a_.4_a._.1_a mmwa—a SYSTEM CHARACTERIZATION ................. 2.l perties of Sludge ................ 1 Physical Properties of Sludge ........ 2 Chemical Composition of Sludge ........ 3 Organic Matter in Sludge ........... 4 Inorganic Matter and Heavy Metals in Sludge . perties of Soil ................. 1 Physical Properties of Soil ......... 2 Chemical Properties of Soil ......... 2.2.3 Adsorption by Soil .............. 2.3 Conclusions Based on the Background Information . . . Pro 2 l 2 l 2. l. 2. l. 2.2 Pr r0 2. 2. 2. 2. MATERIALS AND METHODS .................. 3.1 Column Construction ................. 3.l.l Support Media ................ 3.1.2 Active Media ................. 3 l.3 Desorption Active Media, Sludge ....... 3 l 4 Control Columns ............... 3.1.5 Overlayer Media ............... 3.2 Soil Adsorption ................... 3 2 Selection of Adsorbate ............ 3 2 Preparation of Adsorbate ........... 3 2 Method of Application and Sampling ...... WN-d iv Page vii ix —ul kaD LO O‘hWN-fld CHAPTER SUMMARY APPENDIX A. B C. D 3.3 Sludge Desorption .................. 3.3.l Selection of Leaching Solution ........ 3.3.2 Preparation of Leaching Solution ....... 3.3.3 Method of Application and Sampling ...... 3.4 Sand Adsorption ................... 3.4.1 Field Condition ............... 3. 4. 2 Flooding ................... 3.5 Data Handling and Analysis ............. Rejection of Suspected Values ........ Breakthrough Curves ............. Freundlich Fitting .............. Determination of Kinetics .......... 00000000 01010101 wa—J RESULTS AND CONCLUSION .................. 4.1 Assumptions ..................... 4.2 Problems and Remedies ................ 4.2.1 Release of Organics ............. 4.2.2 Absorption by Support Media ......... 4.2.3 Algal Growth ................. .2. 4 Equilibrium Investigation .......... rption ..................... 1 Field Condition ............... 2 Statistical Analysis ............. 3 Organic Adsorption .............. 4 Adsorption Results .............. 5 6 r l 4.3 do Flooding ................... Comparison of Field and Flooding Conditions e o ption ..................... Observations ................. 4. 4. 2 Field Condition ............... Comparison of the Adsorption and Desorption ..... Conclusion ..................... Engineering Application ............... PD-fibbzbzb-D-Dh so .3 3. .3 .3 .3 .3 s 4 h-h-h \Imm PROPERTIES OF ADSORBENTS USED IN THE ADSORPTION COLUMNS SLUDGE DIGESTION AND METAL MEASUREMENT .......... ANALYTICAL PROCEDURES .................. MEASUREMENT OF REQUIRED SLUDGE .............. 106 112 112 114 131 132 135 137 139 144 147 149 APPENDIX Page E. ORGANIC RELEASE ..................... 150 F. SAMPLE CALCULATIONS ................... 162 G. EXPERIMENTAL DATA .................... 164 H. STATISTICAL ANALYSIS ................... 186 I. FIT 0F FREUNDLICH EQUATION ................ 193 REFERENCES ............................ 212 vi TABLE N 000000“) (A) hbhhbbbhwww 030143 --I acumen-boom LIST OF TABLES Typical Water Content of Sludges ............. Typical Chemical Composition of Raw and Digested Sludge .......................... Heavy Metal Concentrations in Influent Hastewater Typical Chemical Composition of Treated Municipal Sewage Effluent .................. ’. . . Average Concentration of Metals in Digested Sludge . . . . Properties of Clay Used in the Experiment ........ Content on the Adsorption Columns ............ Average Zn and Cd Concentration in Sludge for the City of Grand Rapids, Michigan .............. Properties of the Sludges ................ Metal Content of the Sludges ............... Total Zinc and Cadmium in Sludge Columns ......... Organics Remaining in the Adsorption Columns ....... Adsorption of Cations by the Support Media ........ Total Adsorption by Adsorbent--Fie1d Condition ...... Total Adsorption by Adsorbent and Sand--Field Condition Adsorption per Unit Weight of Adsorbent (mg/g) ...... Adsorption per Unit Weight of Adsorbent (me/g) ...... Adsorption of zinc and cadmium by adsorbent, mg/g Correlation Coefficients for Freundlich Equation Fitting ......................... Page 12 13 14 15 26 27 29 29 3O 31 48 49 52 52 69 69 7O 71 TABLE 4.9 .13 .14 .15 b-b-b-b .16 Comparison of Actual Clay- Organic and Clayi-Organic Columns Adsorption—-Fie1d Condition .......... Modeling of Adsorption Results for Zn Columns-- Field Conditions ................... Modeling of Adsorption Results for Cd Columns-- Field Conditions ................... Value of the Characteristic Number, x0, mg-- Field Condition .................... Adsorption of Zn and Cd, mg--Flooding Condition . . . . Adsorption of Zn and Cd, mg/g--Flooding Condition . . . . Adsorption of Zn and Cd, m1/g--Flooding Condition . . . . Modeling of Adsorption Results in Zn Columns-- Flooding Condition .................. Modeling of Adsorption Results in Cd Columns-- Flooding Condition .................. Value of the Characteristic Number, x0, mg-- Flooding Condition .................. Correlation Coefficients for the Fit of the Freundlich Equation to the Sludge Data ........ Least Square Equations for Freundlich Equation . . . . Modeling of the Desorption Results, Raw and the Digested Sludges ................... Values of "b" in the Adsorption and Desorption Models ........................ viii Page 76 83 83 91 92 92 92 104 104 106 123 124 126 FIGURE 00 ##h-fi ¢. c- c» :> c: o: u) u: 01-wa _. -b c» .10 .11 .12 .13 LIST OF FIGURES Column arrangement .................. Laboratory set-up for flooding tests ......... Typical breakthrough curve .............. Breakthrough curve .................. Adsorption of Zn by selected organics ......... Adsorption of Zn and Cd by cellulose ......... Adsorption of cations by glucose ........... Adsorption of cations by tryptophane ......... Unit adsorption of Zn by the clay and the clay- organic columns .................... Unit adsorption of Cd by the clay and the clay- organic columns .................... Freundlich equation fitting for Zn-clay ........ Release of zinc from the adsorption columns--field condition ....................... Release of cadmium from the adsorption columns-- field condition .................... Comparison of the models and data in Zn columns . . . . Comparison of the models and data in Cd columns . . . . Cumulative adsorption of Zn during flooding ...... Cumulative adsorption of Zn during flooding ...... ix 66 68 73 78 80 85 87 94 96 FIGURE .85 b-h-h-b-D-b-b-h .14 .15 .16 .17 .18 .19 .20 .21 .22 .23 Cumulative adsorption of Cd during flooding ....... Cumulative adsorption of Cd during flooding ....... Zinc adsorption under flooding condition ........ Typical position of adsorption curve .......... Release of zinc from raw sludge--fie1d condition Zinc release from the digested sludge—-fie1d condition Freundlich equation fitting for raw sludge ....... Freundlich equation fitting for digested sludge ..... Comparison of the model and the data for desorption of zinc from the rain sludge .............. Comparison of the model and the data for desorption of zinc from digested sludge .............. Page 98 100 102 108 116 118 120 122 128 130 CHAPTER 1 INTRODUCTION 1.1 Sludge Generation and Disposal Hastewater sludge results from primary and secondary treatment of raw wastewater. The term "sludge" does not usually include grit, scum, and screenings. However, of all of this together sludge forms the most important by-product of the plant.1 Primary sludge is formed as the result of gravitational settling of raw wastewater and is usually coarse and fibrous. Secondary sludge results from biological treatment of the wastewater. It is, indeed, settled flocs of organisms. Treatment of sludge is performed in order to stabilize the organic matter and reduce its water content. Unit processes for sludge treatment and disposal are thickening, stabilization, conditioning, dewatering, heat drying, reduction volume, and final disposal.2 1.2 Heavy Metals in Sludge Heavy metals are found in different concentrations in wastewater. Sources of heavy metals in wastewater may be industry, precipitation runoff, and excretion from man. Upon treatment in a conventional activated sludge or trickling filter treatment plant most of the heavy metals go into the sludgef‘”n Retention of a high per- centage of the influent heavy metals by acclimated sludge was reported by Neufeld and Hermann.9 They indicated that such a system will continue to operate while removing heavy metals. These authors reported that the activated sludge flocs that were exposed to shock loads of mercury (Hg), cadmium (Cd), and zinc (Zn) picked up (adsorbed) these elements from the aqueous carrier. Reid10 reported that the completely mixed aerobic treatment of wastewater is capable of removing heavy metals from the system. 1.3 Sludge Application Practices No matter what the form of sludge dewatering or treatment may be, the final residues are normally deposited in or on soil. Land application of wastewater is the oldest method used for treatment and disposal of wastes with use by cities recorded for more than 400 years.12 Raw sludge in the form of night soil has been used on farm land, as a fertilizer, since ancient times.13 Land spreading of sludge as far as 180 miles from its source has been proven to be cheaper than any other alternative method of sludge disposal.1“ Reedls described techniques for applying sludge to soil. These include ridge-and-furrow, plough- furrow, cover and sub-sod injection methods. Traditionally, sludges have been treated before being deposited on soil, however, application of raw sludge has been practiced.““‘18 For example, 15 communities in northern Ohio, representing a total of 600,000 people, use direct land application of wastewater sludge.19 1.4 Problems with Land Disposal Heavy metals are necessary, in minute quantities, for the growth of many organisms and/or plants. However, excess amounts of these elements may have a considerable toxic effect on living matter. The threshold levels of these contaminants for each species of organism is different. It also varies with regard to other environmental factors. Heavy metals in soil can eventually enter into the human food chain. Soils that have been subjected to sludge application are subjected to heavy metals, and thus, are questionable soils for crop growth. Furthermore, the heavy metals may leach down to the ground water table and contaminate it. Upon application of sludge to soil the liquid and some small solid particles may penetrate into or become incorporated with the soil. Adsorption from a liquid phase to a solid phase will take place more rapidly than the diffusion from a solid phase to another. The solid fraction of the sludge, also, releases its metal content into soil. Lindsay20 indicated that sewage sludge would decompose in the soil and release Zn, Cd, and other heavy metals with intermediate solubility. He added that under many soil conditions these products are soluble. Furthermore, he indicated the need for the quantitative studies to predict the long term fate of the heavy metals due to addition of the sewage sludge in soil. Adjustment of the pH of acidic soils is usually done by the use of lime. This is a necessary step for limiting the availability of heavy metals to the roots, therefore, improving crop growth. The reason for the lime treatment of the acidic soil is that the solubility of macro and micronutrients increases with decreasing pH. Therefore, they may easily be carried down to the deeper strata of the soil where they are out of the reach of the crop roots. The existence of low environmental pH's generally increases the danger of groundwater pollution by leaching from surface sources. The most toxic heavy metals of municipal sludges are zinc, cooper, nickel, and cadmium.“"23 Between these, zinc, copper, and nickel are known for their phytotoxic effect while cadmium can accumulate in vegetation to levels which are toxic to animals before any sign of plant toxicity appears.2“ 1.5 Role of Kinetics in the Sludge-Soil System Kinetics studies indicate how fast a reaction takes place and what factors influence the rate of the reaction. 'Upon application of the sludge to soil a new physical, chemical, and biological system develops which is different from either the soil or the sludge. In other words a reaction will take place such that SOIL + SLUDGE -————-- > "NEW SOIL." This is a dynamic system where time, temperature, and the moisture con- tent of the system have great influences on its eventual stabilization. In this system, decomposition of the sludge is followed by the release of macro and micronutrients into the soil solution. This may be followed by the adsorption of products by the active sites within the soil. Precipitation of these products may occur when the soil solution becomes saturated with respect to a specific matter. When the soil solution becomes unsaturated with respect to any solid phase or mineral that is present, the phase can be redissolved.20 If enough moisture exists, a downward movement of the product will be inevitable because of the fact that the adsorption sites eventually will be exhausted. The extent of the downward movement will vary with the type and the number of adsorption sites (i.e., type of soil) and the constitutents, and their respective concentration, in the sludge. Therefore, the overall process can be summarized as: NEW SOIL ——+ DESORPTION -——>- PRODUCT "MSW” > ADSORPTION + EXCESS PRODUCT If sludge application continues, the soil active sites become exhausted and all of the products escape the system. Lindsay2° summarized the above as: The composition of the soil solution is ultimately controlled by the solubility of various mineral phases in soil. In many reactions the rates of precipitation and dissolution are sufficiently slow that kinetic as well as thermodynamic factors must be considered. Kirkham25 has discussed the discrepancy between investigators over the ultimate amount of organic matter that will be degraded once sludge is added to the soil. The reported variation is from 20 to 30% decomposition for an infinite amount of time to 60% decomposition for a short time period. 1.6 Hypothesis and Objectives In chemical reaction engineering, reactions are classified as homogeneous and heterogeneous. The first term is used when the reaction takes place in one phase, e.g., liquid-liquid, and the second term is used in other conditions such as solid-liquid reactions.26 In this respect the adsorption of soluble metals on solids falls in the second category. In heterogeneous systems, mass transfer becomes an important factor in rate determinations. When the reaction consists of a number of steps, the rate determining step is the slowest step which has control over the whole reaction. Generally speaking, the rate of a reaction may be expressed as: R, = kf (system variables) where Ri is the rate of the reaction with respect to a certain species, k is the reaction constant, where its unit changes with changes in the order of the reaction. The system variables may include the volume of the reacting fluid, volume of the vessel, mass of solid in the fluid- solid system, temperature, and pressure. A rate equation is a dif- ferential equation which expresses the change in the concentration with time, i.e., the rate as a function of concentration. Even though there are ways to predict some theoretical rate equations in engineering work, they are generally of limited value. This is because it is not known before hand whether the calculated rate is close to the empirical value or off by a factor of a million.27 Therefore, for engineering design, the experimentally found rates are generally used in all cases. '4 D (11 H The form of the rate equation may be found as the result of an empirical curve-fitting procedure.27 In natural systems the biodegradability of certain chemical species plays a rather important role in the metal adsorption process. This contribution may result because of the higher soil affinity of secondary products resulting from decomposition of the primary applied organic matter. It also could be as the result of pH changes resulting from the decomposition activities. Both of these situations, when they occur, greatly affect the kinetics of adsorption. The adsorption of organic matter, especially proteins, by clay minerals, as was shown in the early works of Esminger and Gieseking,2‘”29 further complicates the whole process. The following hypotheses were made in the light of previous studies, background information and preliminary investigations for this dissertation: 1. That some organics have ability to adsorb heavy metals and that the rate of adsorption of heavy metals is different for different organic forms. 2. That interaction between clay and organic matter (provided to the clay by application of a wastewater or wastewater sludge) may occur and thus affect the rate of adsorption of the heavy metals. 3. That upon application of a wastewater sludge to land a dynamic state will prevail in which some microorganisms can survive in the new environment. These microorganisms, then, decompose the chelates responsible for holding the heavy metals in the sludge. This decomposition will result, eventually, in the release of the bonded heavy metals to the surrounding environment. 4. That if enough moisture exists the released heavy metals may leach down to lower strata of the soil and contaminate it. The contamination may occur if the rate of release of the heavy metal from sludge is greater than the rate of adsorption of them by the active media of the environment (i.e., mainly the clay and the organic fraction of the soil), or, if the adsorption capacity of the intermediate adsorption sites has been depleted. 5. That a dynamic system will exist until no further decomposition of the organics can occur. The objective of this research is to find out the role of different organic forms commonly found in wastewater or wastewater sludge on the kinetics of heavy metal transfer from sludge to soil; and to investigate the rate of release of zinc and cadmium from sludge to the underlying environment. CHAPTER 2 SYSTEM CHARACTERIZATION 2.1 Properties of Sludge 2.1.1 Physical Properties of Sludge Sludge is a semiliquid. Its liquid fraction may be water, oil, or chemical solvents. Hastewater sludge contains water and solids. The typical water content of sludges are shown in Table 2.1. Table 2.1 Typical Water Content of Sludgesa° Hastewater Percent Moisture Lb water/Lb Treatment Process of Sludge Generated Sludge Solids Primary sedimentation 95 19 Trickling filter Humus-low rate 93 13.3 Humus-high rate 97 32.3 Activated sludge 99 99 Gould and Genetelli31 studied the solid content of an anaerobically treated sludge and reported that over 90% of the solids were in particulate form (diameter > 100 micron), whereas the colloidal, superacolloidal, and the dissolved fraction accounting for O.l-O.3%, 5-8%, and l-3% of the solids, respectively. 10 2.1.2 Chemical Composition of Sludge Sludge contains a variety of chemical and biological substances. The chemical composition of wastewater sludge varies from one plant to another. This variation is due to the contributions received from the local industries, type of the treatment of the wastewater, and climatological factors. 2.1.3 Organic Matter in Sludge Some authors“:33 have reported that cellulose and hemicellulose form a considerable portion of the organic matter of a wastewater. They may account for as much as 50% of the organic fraction. Most of the cellulose fibers are removed in primary settling tanks in the form of sludge. Degradation of cellulose, under aerobic or anaerobic condi- tions, has been shown to be a very slow process. In anaerobic digesters, where the temperature varies from 30-32° C, it was shown that about 90% of the cellulose was degraded after 50 days while only 50% was degraded after 20 clays.33 Edberg and Hofsten33 also reported that dried raw sludge contained about 23% carbohydrates, the large fraction of which was glucose. For activated sludge and digested sludge, the carbohydrate content was found to be much lower, i.e., 3 and 7%, respectively. It was reported that only one-third of the sludge going into the digesters was activated sludge. Other authorss’5’3“ have reported that the settleable activated sludge organisms exist as individual cells covered by a web of rather 11 insoluble organics. This extracellular film consists of polysaccharides, polymer fibrils, high molecular weight proteins, ribonuclic acid and deoxyribonuclic acid. Other varieties of organic matter which might be expected to be found in wastewater and sludge are, proteins, a number of sugars, urea, aminoacids, fats, and waxes.33’35 Vaseen36 indicated that the conventional activated sludge from a domestic wastewater contains 43.1% protein. Table 2.2 shows the composition of typical raw and digested sludge. 2.1.4 Inorganic Matter and Heavy Metals in Sludge 2.1.4.1 Concentration of Metals in Sludge Klein et al.“ reported the concentration of heavy metals in the wastewater from the residential areas of New York City as shown in Table 2.3. The typical chemical composition of treated wastewater as reported by Sank et al.37 is given in Table 2.4. The average con- centration of metals in wastewater effluents and in digested sludge were reported by Ellis38 and by Salotto et a1.,39 and are shown in Table 2.5. The levels of concentration of zinc, copper, nickel, and cadmium in the sludge have also been reported by others.°’37’”° Most of these investigators, however, neglected to report the sludge moisture content. Therefore, it is extremely difficult to assume a narrow range of heavy metal concentrations for a municipal wastewater sludge. 12 Table 2.2 Typical Chemical Composition of Raw and Digested Sludge1 Raw Primary Sludge Digested Sludge Item Range Typical Range Typical Total dry solids (TS), % 2-7 4.0 6-12 10.0 Volatile solids (% of TS) 60-80 65.0 30-60 40.0 Grease and fats (ether soluble, % of TS) 6-30 NA 5-20 NA Protein (% of TS) 20-30 25.0 15-20 18.0 Nitrogen (N, % of TS) 1.5-4.0 2.5 1.6-6.0 3.0 Phosphorus (P205, % of TS) 0.8-2.8 1.6 1.5-4.0 2.5 Potash (K20, % of TS) 0.0-1.5 0.4 0.0-3.0 1.0 Cellulose (% of TS) 8-15 10.0 8-15 10.0 Iron (not as sulfide) 2-4 2.5 3-8 4.0 Silica (SiOZ, % of TS) 15-20 NA 10-20 NA pH 5-8 6.0 r 6.5-7.5 7.0 Alkalinity (mg/1 as CaC03) SOD-1,500 600.0 2,500-3,500 3,000.0 Organic acids (mg/1 as HAC) ZOO-2,000 500.0 100-600 200.0 Thermal content (Btu/lb) 6,800-10,000 7,600.0a 2,700-6,800 4,000.0 aBased on 65% volatile matter. b Based on 40% volatile matter. 13 Table 2.3 Heavy Metal Concentrations in Influent Hastewater“ Concentrations ppm Cu Cr Ni Zn Cd Influent wastewater 0.11-0.33 0.008-0.15 0.01-0.15 0.13-0.37 0.00l-0.007 Sludge 0.46 0.16 0.15 1.6 0.025 2.1.4.2 Forms of Heavy Metal Complexes in Sludge Generally speaking, heavy metals in sludge can be divided into: (a) soluble metals in the sludge liquid, and (b) metals that are bound to the solid particles. Chemical properties of heavy metal complexes in sludge have been the subject of many studies.5’5’"l These studies have revealed that the existence of numerous functional groups in the extra- cellular film of microorganisms provides potential binding sites for heavy metals. However, it has been argued, theoretically, that under anaerobic conditions hydrolysis of the complexes may occur. This results in desorption or release of the heavy metals to the bulk of solution.5 Cheng et al.6 reported that the metal in wastewater are complexes composed of free metal ions and ligands of an organic or inorganic nature. Under aerobic conditions metalorganic complexes will form as the result of metal take-up by the biofloc. In addition, these authors indicated that metal ion precipitation may occur at the higher original concentrations of metals in the influent wastewater. 14 Table 2.4 Typical Chemical Composition of Treated Municipal Sewage Effluent37 Average Concentration Total Amount Applieda Constituents mg/l kg/ha pH 8.1 NA MBAsb 0.37 6 Nitrate-N 8.6 143 Organic-N 2.4 40 NH4-N 0.9 14 P 2.65 44 Ca 25.2 420 C1 41.3 792 Mg 12.9 215 Na 28.1 469 Fe 0.4 9 8 0.169 3.26 Mn 0.061 1.15 Cu 0.109 1.96 Zn 0.211 4.15 Cr 0.023 0.41 Pb 0.104 2.12 Cd 0.009 0.19 Co 0.062 1.24 Ni 0.093 1.82 aTotal amount applied on areas that received 5 cm of effluent per week. bMethylene blue active substance (detergent residue). 15 Table 2.5 Average Concentration of Metals in Digested Sludge (All Figures Are mg/kga Dry Sludge Basis)39 Arithmetic Geometric Median Std. Dev. Std. Dev. 50% Metal Mean (+ and -) Mean (+ and -) Value Ag 250 230 190 1.99 100 B 430 310 380 1.58 350 Cd 75 104 43 2.47 31 Ca 36,500 23,800 31,100 1.77 30,000 Cr 1,860 1,920 1,050 3.22 1,100 Co 350 220 290 1.88 100 Cu 1,590 1,670 1,270 1.95 1,230 Hg 10 18 6.5 2.34 6.6 Mn 1,300 2,290 475 3.67 380 Ni 680 620 530 1.88 410 Pb 2,750 2,350 2,210 1.82 830 Sr 520 670 290 2.70 175 Zn 4,210 3,800 2,900 2.40 2,780 amglkg = ppm- u‘) “‘1 16 2.2 Properties of Soil Soil is a mixture of solids and water. Soil solids may be either organic or inorganic. The primary soil minerals are the parent materials such as feldspar, biotite, and apptite. Secondary minerals are formed as the result of weathering and decomposition of the primary minerals. They also are known as clay minerals. Clay minerals are that fraction of soil smaller than 2 micron in diameter. They are made up of sheets of silicon tetrahydra and aluminum octahydra. 2.2.1 Physical Properties of Soil Bulk density, particle size distribution, porosity, permeability, temperature, moisture content, soil water potential, hysteresis, and other similar properties are known as the physical properties of soil. The physical properties of a soil are dependent upon the age, geographical location, position with respect to the ground surface, and the history man's activities on it. 2.2.2 Chemical Properties of Soil The organic fraction of soil is composed of plant and animal residues in various stages of decomposition as well as living organisms. The organic portion of the soil has a significant effect on certain physical properties of the soil. Among the properties affected are the structure, permeability, and retention of moisture. Compounds obtained as the result of the decomposition of the organic matter cause soil particles to aggregate. Uronic compounds, along with gums and resins are believed to be effective soil binders. The organic fraction 17 in soil is usually small averaging from 2 to 10%.37 Obviously, the degree of decomposition of various organic fractions is different. Cellulose, proteins, and carbohydrates are found in soil. Their source being the plant tissues and dead micro and macroorganisms. Under normal conditions cellulose, fats, and waxes decompose slowly in soil. However, the rate of this decomposition under various physical, chemical, and biological conditions is not known for certain. Resistant materials are known to have little or no nitrogen and protein. This accounts, at least in part, for their resistance.3 When the resistant substances finally decompose, they combine with the newly synthesized proteins (synthesized by soil microorganisms) and form humus. The inorganic fraction of soil is composed of many oxides. Silicates, carbonates, sulfates, etc. are some of the different minerals that are abundant in soil. 2.2.3 Adsorption by Soil Weber“2 indicates that all solids are able to adsorb. The exchange phenomenon is known to occur with a number of natural solids including soil, humus, cellulose, wool, protein, coal, lignin, and metal oxides. The active portion of the soil, as far as adsorption of cations is concerned, are the clay minerals and organic matter. Organic matter, for instance, has typical exchange capacity of about 200 miliequivalents per 100 grams (me/100 9) while the cation exchange capacity (CEC) of 18 kaolinite, which is dominant in humid areas, ranges from 5 to 15 me/100 g. The CEC of montmorillonite, which is dominant in arid areas, is about 100 me/100 9.37 Clay minerals are usually negatively charged. This charge is the result of charges induced by the broken edges (ionization) as well as those due to the isomorphic substitution. The attraction of ions to clay minerals could be the result of van der Walls forces, electrical forces, ion exchange forces, specific adsorption forces, or the forces causing the exchange of the coordinated metal ion with the available cation. Since adsorption is a surface phenomenon, the total available surface area of the soil granule plays a rather sig- nificant role on the overall adsorption process. Clays are known to have a very large surface area to volume ratio. Even in sandy soils more than 95% of the total surface area is associated with clay.37 Wetink and Etzel"3 noticed that the nature of the ion (i.e., its valence, ionic size, and polarizability) can influence the adsorp- tion and replacement of these ions on the exchange site of a soil particle. These workers used three soil types and passed Zn, Cu, and Cr sulfite through them. They studied the rate of adsorption of these ions and concluded that the removal of Zn, Cu, and Cr were the result of an ion exchange mechanism. Berger““ found that the concentration of Zn in a normal soil generally falls in the range of 10-300 mg/l total Zn. He noted that very little is known about the zinc complexes in soil except that they are tightly held in soil. Furthermore, he added that some of the 19 available zinc is held on exchange materials, namely, the clay and the organic matter of the soil. Clays adsorb many organic substances. They can even adsorb enzymes and bacterial cells. The adsorption of organics by clay is referred to as carbon mineralization. Ellis“s feels that the adsorption or bonding processes responsible for the attachment of heavy metals to soil may be divided into the following categories: (1) electrostatic bonding; (2) covalent bonding; (3) hydrolysis; (4) specific adsorption; and (5) bonding to organic matter. In this classification scheme isomorphic substitution in the clay lattice is also included in the fourth category. The removal of heavy metals from wastewater and wastewater sludges by soil is the result of biological activity as well as physico-chemical processes. The biopopulations responsible for the biological activity are expected to be different in the sludge and the soil and yet including some of those in both the soil and in the sludge. The organic portion of soil may play a significant role in the adsorption processes. Adsorption of heavy metals onto the organics is due to the availability of sites and the net attractive forces induced by electrical charges. Fair et a1.“6 indicated their expecta- tion that proteins would adsorb heavy metals to form organometalic complexes. Their reasoning relies on the fact that a protein molecule carries a net negative charge. The quantity of this charge changes with factors such as the degree of ionization and as the result of the pH of the medium. This charge may be depicted as NH2 - R - COO', 20 NH; - R - COOH, or as NH; - R - COO' (zero) at high pH, low pH, and at the isoelectric points, respectively.‘ Based on Lahav and Hochberg,"7 it appears that the cations from a strongly chelated metal ion solution such as solutions of Zn-EDTA and Fe-EDDHA are not adsorbed by soil. These authors indicated that neither adsorption nor decomposition, aerobically or anaerobically, of Fe-EDDHA was observed in a period of two months. Other authors27 have reported that no adsorption of cadmium was found when a solution of Cd-EDTA was applied to a soil. These types of solutions, therefore, when applied on a soil are potential sources of ground water contamination. Furthermore, adsorption of cationic species from the chelated solutions are strongly dependent upon the pH.37 Among the organic fractions of soil humic and fulvic acids are probably the main active group of chemical compounds responsible for the adsorption of metals. Riffaldi and Levi-Minzi27 indicated that the presence of functional groups, chiefly COOH and 0H, conduct the first stage of the adsorption or ion exchange reaction. The authors also referred to previous work that showed that the organic acids of the soil contain various types of OH groups and both ali- phatic and aromatic COOH groups. It seems, therefore, that dis- sociation of these functional groups plays a major role in the adsorption process by providing available sites for the cations in solution. 21 2.3 Conclusions Based on the Background Information In general, when sludge metal concentrations and characteristics are considered with respect to soil and its parameters, the following conclusions may be drawn. 1. 2. Heavy metals from sludge will be released upon decomposition. Heavy metals can be adsorbed by soil. The adsorption process of soil includes an ion exchange process. This is due to the fixation (addition of the ion in the coordination complex form) and chelation of cations by the soil organic matter. It is possible to overaccumulate some of the heavy metals by continuous and unmanaged application of sludge to soil. High doses of heavy metals are toxic to plants, animals, and man. A minimum metal content in sludge is desirable for the land application of sludge. Pretreatment of soil by the lime application, to adjust the pH, will reduce the solubility of the metallic compounds, thus reducing the danger of ground water contamination. The life expectancy of a soil disposal site may be significantly increased through a good management program, i.e., using proper crops, correct sludge application rates, etc. Ground water and the crop contamination may be avoided by the proper soil testing and analysis before and during the sludge application. o .15 no .1 .llu CHAPTER 3 MATERIALS AND METHODS To test the hypothesis made in this research and to fulfill the objective of this research it was decided that a synthetic soil should be made rather than using a naturally occurring one. This was done by manually combining known amounts of organic, clay, and sand of certain characteristics. The soil was placed in adsorption columns and leached with metallic solutions. The leachates were examined for their metal content. Another set of columns was made to study the rate of release of the cations from the sludge. 3.1 Column Construction Columns were made up of 30 centimeter (cm) long, 5 cm inside diameter glass tubing. A glass funnel acted as a base for the columns (Figure 3.1). Overlaying medi Active media Support media lf Figure 3.1 Column arrangement. 22 23 The columns were set up on wooden frames which could hold up to 32 columns. After cleaning of the columns they were packed with the supporting, active, and overlayer media. 3.1.1 Support Media The support media is the material underlying the active media. Ideally, it is to hold, yet not interfere with the performance of the active media. Selection of the support media, therefore, was made with respect to (a) hydraulic considerations, (6) economical reasons, and (c) inertness with respect to the elements under this study. The base of each column was filled with 6 glass raschig rings of 4 milimeter (mm) diameter purchased from Fisher Scientific Corporation. The base was then filled with 10 cm3 (content of one 10 ml test tube) of each of 5, 4, and 3 mm solid glass beads also purchased from Fisher Scien- tific Corporation. Glass was used because the preliminary investi- gations indicated that the adsorption of zinc and cadmium by glass was negligible. Silica sand of 99.9% purity and 4011 micron mesh was used for the subsoil make-up. Sand was purchased from Wedron, Illinois and labeled as being "thoroughly washed, bone dry, accurately graded." The volume of the sand placed in each column was 250 cm3. This volume has an average air dried weight of 398 grams. It yielded a total depth of about 13 cm. The underlayer of glass beads was wetted with about 10 cm3 of distilled water prior to placing the sand. This was 24 necessary to wet the first sand grains and thus cause the sand particles to hold each other by the surface tension and other interfacial forces and, as a result, prevent the dry sand from penetrating into the glass bead phase. The sand layer was immediately saturated with distilled water by applying from the top. The saturation of the sand was determined considering soil physics principles and visual observations (i.e., addition of each drop resulted in release of one drop). Soil has a capability to retain water against the gravitational force of leaching. The matric potential (suction or tension) also contributes to the holding of the water by the soil. This is explained as wetting front movement in classical soil physics.3 The entire bed was washed with distilled, deionized water a few times each day, for a week. The wash water was discarded. The bed was deaerated by virtually fluidizing it during the washings by deep injection of distilled water. It was determined that, on the average, 105 cm3 of water was needed to saturate the dry sand (as received) after'which each drop of water that was added caused one drop to leach out of the system. 3.1.2 Active Media Organic matter and clay were used in construction of a synthetic soil in the adsorption columns. The clay was a kaolinite and the three organic compounds selected were tryptophane, dextrose (also known as D-glucose), and cellulose. 25 3.1.2.1 Selection of Clay Selection of a kaolinitic clay over the other types was made based on the following: (a) kaolinitic clays are 1:1 mineral (one octahydra, one tetrahydron) as opposed to montmorilonitics and illitics (hydrous mica) clays that are 2:1 minerals. This arrangement does not allow the soil to swell and, thus, limit the drainage of the applied solution; (6) kaolinites, in general, are coarser than the montmoril- lonites and the illites and, thus, are more favorable for drainage; (c) kaolinitic clays are the predominant clay form in humid areas, therefore, the results of research using kaolinite might prove locally applicable whereas the others would not; and (d) the CEC of the kao- linite is usually around 5-15 me/100 g. This is much less than the values reported for the other forms of clay. This is because the cation exchange sites, in kaolinite, are the broken edges as opposed to the amorphus substitution sites found in montmorillonite."s With a limited amount of time available, therefore, it was felt that it would be convenient to saturate (exhaust) this soil without a need to choose unreasonably high cationic concentrations. The clay was obtained from Western Michigan University and has the following properties, Table 3.1 (see Appendix A for more information on the clay). 3.1.2.2 Selection of Organics Three organic compounds that are commonly found in wastewater and wastewater sludge were selected. The selections were made with 26 Table 3.1 Properties of Clay Used in the Experiment (Average Values) Clay pH CEC Kaolinite 5.8 4.9 me/lOO g respect to the information reported in the previous chapter. The organics chosen were those that also are found in soil. These were cellulose, glucose, and an amino acid, tryptophane. These organics are known to differ by their removal points in a wastewater treatment plant (as discussed in the introduction) and thus represent the entire plant operation. The tryptophane and dextrose were ACS reagent grade obtained from Eastman, and Fisher Scientific Corporation, respectively, and were used as received. The cellulose sheets were obtained from Western Michigan University. The fibers were prepared by shredding the sheets to about 5 cm2 sizes, soaking them in distilled water for about one hour, and then dispersing in water in small aliquots, using a blender. The cellulose was then freeze dried at 38° C, 65 micron mercury vacuum pressure, and 2% moisture content for 72 hours. The freeze dried fibers were finally dispersed in air using the blender. Throughout this work the clay, tryptophane, D-glucose, and cellulose are denoted as C, T, G, and Cel, respectively. Some prop- erties of the organic compounds used in this work may be found in Appendix A. 27 3.1.2.3 Selection of Mix Ratio The quantities of the above substances that were used in each column are shown in Table 3.2. Selection of the mixing ratio of the organic to clay of 1:20 was to simulate the average condition of 5% organic matter in soil. The amount of the clay (therefore the organic matter) was chosen by trial and error to be able to reach the total exhaustion of the bed adsorption capacity in four months. This was done by assuming the average reported CEC values for kaolinite and organic matter and choosing 40 mg/l cationic solutions to be applied to the system. The reason that the amount of adsorbent in the cadmium cases is half of that in the zinc case is the fact that the miliequiv- alent weight of the cadmium (112/2 = 56 mg) is almost twice that of zinc (65/2 = 32.5 mg). Table 3.2 Content of the Adsorption Columns Clay Organic (9) (9) Zn columns 20.000 1.000 Cd columns 10.000 0.500 3.1.2.4 Method of Mixing The adsorbing substances (adsorbents) were mixed in a 125 cm3 erlenmeyer prior to placing in columns. Twenty cubic centimeters of silica sand was added to and mixed with adsorbent in each case to facilitate drainage. The exception being the clay and clay organic 28 columns which were leached with zinc, where 40 cm3 of the silica sand was added during the mixing. Since the amount of sand used for the support media was relatively large (250 cm3) in comparison to the amount added to facilitate drainage, the amount of the sand was assumed to be the same in all of the columns. 3.1.3 Desorption Active Media, Sludge Wastewater sludge was the active media for the desorption test. Both raw and digested sludges were used for this investigation. 3.1.3.1 Selection The objective of this study required selection of a sludge having a high zinc and cadmium content. A preliminary survey of accessible sewage treatment plants showed that the city of Grand Rapids wastewater treatment plant was a suitable place for sludge sampling. This is a conventional activated sludge plant of 49 M00 capacity that treats municipal and industrial wastewater conveyed to the plant by a combined sewer. The plant manual (1975-76) expressed high zinc and cadmium concentrations in the raw and the anaerobically digested sludges (Table 3.3). This plant is equipped with a complete environmental engineering laboratory. The values, in Table 3.3, are the monthly averages or the values that are reported for April 1976, whichever is applicable. The high zinc and cadmium content of these sludges is due to the contributions from the numerous metal plating sh0ps in the city. 29 Table 3.3 Average Zn and Cd Concentration in Sludge for the City of Grand Rapids, Michigan"8 Plant Product Zinc Cadmium Unit Raw inflowa 493 36.8 g/l Final effluent 250 36.8 g/l Primary sludge 3.22 NA mg/g dry Digested sludge 5.35 NA mg/g dry aThis is not a plant product but the input. 3.1.3.2 Sampling and Characteristics The raw and anaerobically treated sludges were obtained on Friday, April 22, 1977. Twenty liters of each of the sludges were placed in plastic containers and carried to East Lansing where they were refrigerated until use. The samples were grab samples. The properties of sludges shown in Table 3.4 were determined in duplicate, using the procedures described in the 14th edition of Standard Methods for the Examination of Water and Wastewater“9 unless otherwise stated. Table 3.4 Properties of the Sludges TS TVS Ash Content Type of Sludge pH % % % Raw 6.25 5.5 3.2 2.3 Digested 7.2 3.2 1.66 1.53 30 The initial concentration of zinc and cadmium in sludge were found by the digestion technique (see Appendix 8) followed by measure- ment with an atomic Adsorption Unit (see Appendix C). The metal content of the sludges is shown in Table 3.5. Table 3.5 Metal Content of the Sludges, mg/g dry Sludge Zinc Cadmium Raw 6.763 0.029 Digested 5.055 0.014 3.1.3.3. Preparation and Placement The volume of the sludges that were added to the desorption* columns were chosen to satisfy a field practice condition of 22.45 dry tons/hectare (10 dry tons/acre). The volumes were computed to be 83 cm3 and 143 cm3 of the raw and the anaerobically digested sludges, respec- tively (see Appendix D for detailed calculations). They were added to the columns where they were mechanically mixed with an additional 100 cm3 of sand and 5 cm3 microdiameter glass beads to facilitate drainage. The total dry sludge, zinc and cadmium content of each column is shown in Table 3.6 (see Appendix E for detailed calculations). * Desorption, as is used in this work, includes any process that results in the release of heavy metals, i.e., decomposition, solublization, . . . 31 Table 3.6 Total Zinc and Cadmium in Sludge Columns Sludge Used per Column Dry Content Total Zn Total Cd Type of Sludge m1 9 mg mg Raw 83 4.565 30.873 0.132 Digested 142 4.544 22.970 0.064 3.1.4 Control Columns Besides the columns mentioned above, sand columns with no active media were constructed to be subjected to the same hydraulic and chemical regime as the adsorption or desorption columns. This was to detect and, therefore, take into account, any interferences by the support media. 3.1.5 Overlayer Media Fifteen cubic centimeter each of 5 and 4 mm solid glass beads followed by 10 cm3 of 3 mm beads were placed on top of the active media to facilitate the distribution of the flow over the entire soil surface area. They, also, were necessary to prevent local soil distrubances during the application of the liquid from some 20 cm height. In the same sense the existence of the glass beads did reduce the velocity of passage of the fluid through the media, by defusing the impact forces, thus reducing the Reynold's number. This increased the like- lihood of having a laminar flow through the top portion of the active media. 32 3.2 Soil Adsorption 3.2.1 Selection of Adsorbate Zinc and cadmium are known to have similar chemical properties. They are found in the same ore and are readily exchangeable in chemical reactions. However, zinc is an essential micronutrient while cadmium is one of the major environmental contaminants. Furthermore, replace— ment of zinc by cadmium in certain enzymes could cause diseases to man. Zinc deficiency in the plant and crops is common, therefore, a moderate zinc application to crop land, in the form of sludge, may sometimes be beneficial. Cadmium on the other hand is reported to be a toxicant. Acute exposure to cadmium is known to cause erythrocyte destruction, tescular damage, and renal degradation in man. Chronic exposure, however, may cause respiratory disorder, anemia, osteomalcia, and hypertensive heart disease.5° The source of zinc in wastewater or wastewater sludge is from human excretion and industry. Many industries, such as metal and food industries, are known to use zinc or zinc compounds in their operation. Cadmium, on the other hand, is only known to be used in the metal finishing industries. Due to the significance of these two heavy metals, they were chosen for this study. It was decided to use a cationic concentration of 40 mg/l. This level of concentration was necessary to be able to detect the changes in the concentration due to the adsorption without sample pretreatment to raise the concentration to detectable levels. 33 They may appear to be high; however, under the existing time and budget limitations no other reasonable alternative appeared to be available. 3.2.2 Preparation of Adsorbate Solutions of 40 mg/l of zinc and cadmium were made up from the nitrate salt of these elements, using ACS reagent grade chemicals purchased from Fisher Scientific Corporation and distilled water. The conductivity of the distilled water was about 31:1 pMHO/cm. The nitrate salts used were Zn(NO3)2 - 6H20, and Cd(NO3)2 - 4H20. Other properties of these compounds, as obtained from their manufacturer, are shown in Appendix A. 3.2.3 Method of Application and Sampling Field and flooding conditions of the liquid application to the land were simulated. The liquid applications to the columns were made 3 days apart in the field condition studies while the flow was continuous in the flooding condition. 3.2.3.1 Field Condition The field condition was defined in this work as the application of the liquid to soil (adsorption columns) at a rate comparable to that of wastewater spray irrigation. It was intended originally to simulate a spray irrigation practice for the field condition studies. However, any sprayer for this purpose had to be made of an inert substance (preferably glass) in order to eliminate any possible interferences. This was technically 34 hard to manufacture and economically difficult to justify. It was then decided to manually apply the solutions to the columns. Approximatly 10 ml aliquots of the solutions were poured into a testtube which was subsequently applied over the entire surface area of each column by a rotating motion. The existence of the overlayer of glass beads (see Sec. 3.1.4) helped in the distribution of the flow over the entire area of the column. The operator had to repeat the process for a total of seven times. Having a total of 102 columns under the field condition investigation, the time necessary to finish one round of the liquid application varied between 20 and 30 minutes. The total volume of the liquid added was 65 cm3. This volume was applied to the columns over a period of 2.5 to 4 hours. Pouring of 10 cm3 liquid into the columns will, mathematically, indicate an instant hydraulic loading of: (10 cm3)/(2~2.54)2(n/4) cm2 = 0.49 cm. However, it was observed that the hydraulic head varied between zero (i.e., the liquid immediately entered the media) in the control, G and T columns to an accumulation of 3 cm in a few of the clay and clay- organic columns. It also was observed that the leaching process was completed in all of the columns no later than six hours after the start of the liquid application. The leachates were collected in 70 cm3 glass bottles. 35 3.2.3.2 Flooding Condition The flooding condition as referred to in this work means the continuous application of liquid to the adsorption media. Flooding condition experiments were performed under one of the following arbitrarily adopted hydraulic conditions: (a) 5 cm of hydraulic head at all times; or (b) application of 0.12 l/cmZ-hr (0.2 gal/inZ-hr), where "a" could not be satisfied. The choice of the hydraulic condition was dictated by the type of active media in the columns. The "a" condition worked for the clay and clay- organic columns, and the "b” condition was used for the blank and the organic columns. Three milliliter samples of the leachates were collected (see Tables 0.2 to 0.9 in Appendix G for time intervals) during the flooding and were tested for their metal concentrations. In the flooding experiments with the clay and the clay-organic columns, the test was stopped after the leachate concentration exceeded 95% of the applied concentration. This was necessary due to time considerations. This method proved to be justified based on the linearity observed for the last portion of the plotted data of log cumulative adsorption versus the cumulative cation applied. The laboratory set—up of the flooding condition experiments is shown in Figure 3.2. A 2,000 cm3 separatory funnel (C) was used as a reservoir. The stop cock (A) was adjusted to maintain the desired hydraulic condition (see Section 3.2.3.2). Reservoir (B) was a 1,000 cm3 volumetric flask and was filled with the cationic solution 36 Figure 3.2 Laboratory set-UP for f10061109 tEStS- and placed as shown. A constant head (CH) was then maintained. This was necessary to produce a constant flow rate to the testing columns. It was observed that the small variations in the positions of CH did not affect the flow rate. These small variations inevitably occurred when reservoir (8) was replaced. 3.3 Sludge Desorption Microbial activity in the sludge columns was expected to decompose the organic matter and release their heavy metal content. In order to investigate this behavior there was a need for a liquid carrier to leach the released heavy metals out of the sludge columns. 37 3.3.1 Selection of Leaching Solution Simulated rain water was chosen to be the leaching solution. This selection was due to the fact that rain is naturally applied to land. Furthermore, the unique properties of the rain in the north- eastern United States made it important to study. Likens51 reported that the precipitation falling in the northeastern United States is acidic with a pH ranging from 5.0 to 6.0 in 1966 for Michigan. This value dropped to about 4.5 in 1973. He indicated that sulfuric and nitric acids are the major sources of acidity in precipitation. The average concentration of these acids in precipitation collected at Ithaca, New York, being 4.4 and 5.1 mg/l for the nitric and sulfuric acids, respectively. In comparison, the equilibrium concentration of carbonic acid was reported to be 0.62 mg/l. Nordel52 investigated the chemical composition of precipitation in England. He reported, among other things, that the hardness of rain water varied between 3 and 43 mg/l as CaC03. 3.3.2 Preparation of Leaching Solution Simulated rain water was made up using distilled water. Tap water, H2504, HNO3, and KOH, where necessary, were used to adjust the hardness and the pH of the solutions. Selection of the above acids was made based on the reported values for the N03 and $04 anions in rain water.52 However, the total amount of the acid required to adjust the pH was minute, such that it was about 0.1 ml for 15 liters of distilled water. 38 The hardness and pH were adjusted to 20 mg/l as CaCO3 and 5.4, respectively. Method No. 3098 of the 14th edition of Standard Methods”9 was used for the hardness measurements. 3.3.3 Method of Application and Sampling 3.3.3.1 Field Condition The sludge columns were leached with simulated rain water for 4.5 months. This period started in early May and went on until mid- September. The experiment was stopped when the concentration of zinc in the leachates decreased to low levels and the result indicated that the major portion of the zinc in the columns was leached out. The sludges were leached at 3 day intervals with 70 cm3 of the simulated rain water. The leachates were collected in glass bottles and analyzed for their zinc and cadmium content and for conductivity and pH. The method of field condition was similar to what was described in section 3.2.3.1. Observations indicated that the accumulation of the applied liquid in the sludge columns was, on some occasions, as high as 3 cm. 3.3.3.2 Flooding Condition It was not possible to examine the flooding regime of appli- cation of the simulated rain water to the sludge columns because of the very small infiltration rates in these columns. 39 3.4 Sand Adsorption The sand used in the supportive media proved to adsorb cations. The following methods, therefore, were adopted to measure the amount of adsorption of zinc and cadmium for the two different hydraulic regimes. 3.4.1 Field Condition Two sand columns that had already been saturated with the cations (this measurement was performed on the control sand columns after the field condition experiment was stopped) were used. Each was washed with 150 m1 of distilled water to replace the cationic solution retained in the columns. They were then leached with 50 ml of 25% by volume H2504 followed by a volume of distilled water to collect 125 ml of the leachate. The first 60 m1 of the leachate, after the addition of the H2504 solution was discarded based on the assumption that 105 ml of solution saturated the bed. The concen- tration of the cations was determined and the adsorption by the columns was calculated as follows: Amount Adsorbed (mg) = Concentration (mg/1)(125 ml)(l l/l,000 m1) 3.4.2 Flooding In the flooding condition, the sand column was treated as an independent adsorption column. Therefore, the method used (see Sections 3.2.3.2 and 3.5.2.2) were also used for the sand. 40 3.5 Data Handling and Analysis 3.5.1 Rejection of Suspected Values The results obtained for each set of columns were studied. Rejection of a suspected observation took place using the following procedure. R was calculated such that: R = Rl/R2 (3.1) where, R1 is the difference between the biggest and the smallest observation, and R2 is the difference between the biggest and the smallest observation including the suspected value. A value was rejected if R>’2.8 and replaced with the mean of the other four values. Using this rejection factor the chance of an extreme value being rejected when it should have been retained is equal or less than 5%.53 Using this procedure, a total of 51 observations out of 2,528 taken were rejected. Thus, 2% of the results were discarded as being defective. 3.5.2 Breakthrough Curves These curves show the change in the leachate concentration versus another parameter such as time, volume, or weight from when the liquid application starts. A typical breakthrough curve is shown in Figure 3.3, where C0 is the initial concentration in the applied solution. The significance of the breakthrough curve is in their usage in rate studies. In this respect the slope of the curve gives an indication of the rate at which leaching proceeds. 41 l l Leachate Concentration Time Figure 3.3 Typical breakthrough curve. 3.5.2.1 Field Condition The leachate concentrations were plotted against the cumulative cation applied. The vertical axis (the leachate concentration) was plotted in logarithmic scale due to the wide spectrum of the results. 3.5.2.2 Flooding Condition In this hydraulic condition adsorption was calculated with the "traposoidal rule." The amount adsorbed between two consecutive concentration measurements (p and q) when a total of'V ml was leached out between these two measurements, was calculated. Amount of Adsorption (mg) = (p + (q- p)/2)(V/l,000) (3.2) where, the p and 0 were measured in mg/l. In this method of calculation the change in concentration with time was assumed to be linear. There- fore, the total calculated adsorption will be close to the actual value. 42 Figure 3.4 indicates that, using the above procedure, the calculated adsorption is less than the actual value before the center, A, in the diagram and more than that after the center. This difficulty was minimized by sampling at short time intervals. Adsorbed E3223 Leached [j / fl... Leachate Concentration // // Time Figure 3.4 Breakthrough curve. 43 3.5.3 Freundlich Fitting The well known Freundlich equation has been extensively used in experimental works for testing and interpretation of adsorption data. Other adsorption models have been pr0posed by different authors to suit their works.5“ The Freundlich equation is expressed as: X/M = kcl/n (3.3) where, X = me of solute adsorbed; M = grams adsorbent; C = equilibrium concentration of solute; k and n are constants. This equation also may be written as: log (X/M) = log k + 1/n log C (3.4) Equation 3.4 represents a straight line when the values of X/M and C are plotted on a log-log system of coordinates. In other words, if the data represent a straight line on a log-log paper they may be fit to the Freundlich equation. From the background information gathered in this work, it appears that adsorption is the likeliest reaction to be expected. Therefore the fit of the data, in each case, to the Freundlich model was examined as a means of showing that adsorption could be an explana- tion of the pheonomena which were occurring. The adsorption process is a dynamic process. Therefore, a true equilibrium will not be attained until the end of reaction. Nevertheless, intermediate equilibria can be assumed if the aliquots 44 of the product (leachate), resulting from the interaction of adsorbate and adsorbent, are separated from the system. This must be such that no further reaction occurs in the sample. Indeed, this is the way the models are developed and that any adsorption equation or isotherm may be utilized. The equilibrium concentration, C, in the Freundlich equation can be determined by analyzing samples taken at different time intervals. In the field condition, the equilibrium concentrations, C, were normalized by dividing them by the blank values. This was necessary due to minor changes in concentration of the applied solution. The deviation from the exact concentration of 40 mg/l was due to errors of measurement and tendency of the nitrate salts of zinc and cadmium to adsorb water. Using a regression analysis by the least squares technique, the correlation coefficient of the fit of the data to the line given by equation 3.4 was determined. Since the adsorption and desorption mechanisms are, in fact, the same phenomenon in opposite directions, the equation for one should also suit the other. Since the Freundlich equation was originally developed for the adsorption process, it was necessary to adopt the following logic: that a hypothetical adsorption of zinc to the sludge occurred; and that it started at the end of the experiment and proceeded with the time unit having negative signs. Therefore, the very last value that was reported for the desorption becomes the first value, the one before the last value for the desorption becomes the second value and so on. 45 3.5.4 Determination of Kinetics Kinetic studies are necessary to measure the rate at which a reaction proceeds toward completion. The rate of adsorption at each point of the experiment may be found by the slope of the adsorption curve at that point. Modeling of the data, therefore, greatly simplifies kinetic studies. This is because the rate studies will be reduced to the determination of the first derivative of the model, g¥u Then applying the coordinates of the point of interest to find the slope (if y' is not a constant). Slope = %%l x,y The models can be used for predictions. They therefore reduce the amount of time spent in future studies of the same type or in actual practice. 3.5.5 Modeling of Data For the rate analysis, an empirical curve-fitting procedure was utilized. Breakthrough curves similar to Figure 3.5 were obtained where the slope of the curve at each point, 99-, represents the rate of dC change in the concentration with respect to the cumulative cation applied (time and cumulative cation applied can be used interchangeably when the rate of application and the concentration of the cationic solution is known). A curve fitting procedure, using the least square method, was adopted using a programmable HP 96 desk calculator. Different points 46 of the empirically drawn curve (data points) were supplied and the parameter of the suitable model along with the coefficient of deter- mination, r2, for the fit were found. CHAPTER 4 RESULTS AND CONCLUSION 4.1 Assumptions The following assumptions were made for interpretation of the data obtained in this research: 1. That the diameter of the glass columns was large enough to assume a negligible wall effect on the outcoming solution; 2. That the applied liquid passed through the media as a complete plug flow; 3. That all of the active media was utilized in the adsorption or the desorption process; 4. That no channeling of the applied liquid occurred through the media of the column; and 5. That the support media was inert with respect to incoming cationic solutions. 4.2 Problems and Remedies During the experiment a few major problems occurred which are described below. 4.2.1 Release of Organics The results of a total carbon analysis of the leachates revealed that a major portion of the G and T leached out of the 47 48 adsorbing columns. The amount of each organic which remained during the course of the experiment is shown in Table 4.1 (see Appendix E for details). Table 4.1 Organics Remaining in the Adsorption Columns, mg Columns G c0 Ta GT Cal 0 Gel Zn column 15 41 17 102 1,000 1,000 ca column 11 30 NA 8 500 500 aNA = Not available. Result of the mass balance was a negative number. No measureable release of cellulose could be detected during the course of the experiment. Visual observation revealed no decomposition of this substance. The releases most probably occurred as the result of solubili- zation. Decomposition of glucose and tryptophane was not considered as a possible explanation for their release, the reason being (a) release of the G occurred very fast; (b) lack of the necessary micro and macronutrients (i.e., P, N, Ca, and Mg) for any growth of micro- organisms in the columns; (c) the toxic environment of the columns due to zinc or cadmium would limit microbial growth. This conclusion is substantiated in part by the fact that no measureable decomposition was detected in the cellulose columns during 4.5 months of the field condition portion of this experiment. The literature supports this reasoning, though not totally. 49 Bond et a1.55 indicated that metals in organic wastes applied to soil can be toxic to soil microorganisms and can reduce their ability to decompose organic substances. With respect to the lack of cellulose degradation, Carpenter and Owens56 indicate that one milligram (mg) of nitrogen must be present to degrade 40 to 50 mg of cellulose. Since the soil system was prepared without any nitrogen, one would expect the cellulose degradation to be highly limited. 4.2.2 Adsorption by Support Media The sand or impurities within the "99.9% pure"* silica sand which was used to construct the column's base were found to have adsorbing sites. In spite of washing for a week prior to use and in spite of the negative findings in the preliminary investigations, the sand adsorbed cations and tryptophane. Adsorptions of Zn and Cd by the sand is shown in Table 4.2. Table 4.2 Adsogption of Cations by the Support Media, mg/g Zn Cd Sand 0.018 0.011 3Average of two values. The method of measurement was described in Section 3.4. A material balance method was used to evaluate the sand behavior in the flooding condition experiments. *As reported by the supplier. 50 Occupation of the sand adsorbing sites by tryptophane caused a reduction in the adsorption of Zn and Cd by the sand in the trypto- phane columns and, perhaps, the C-T columns. Therefore, a negative adsorption of Zn and Cd was recorded for the T columns (see Table 4.3). This is because the leachates from the sand columns were treated as blanks and were used for computations of the net adsorption in the other columns. 4.2.3 Algal Growth A minute growth of algae was observed in the sludge columns. Visual inspection indicated that the growth was only in that portion of the columns which was exposed to the laboratory fluorescent lights which were left on for about a month for security reasons. After this growth was detected the lights were turned off and were used only when necessary. Observations indicated that no further growth of algae could be seen. However, the original growth did not disappear. The effect of the algal growth on the metal release by the sludge columns was assumed to be negligible. 4.2.4 Equilibrium Investigation As was described before, the field condition practice was conducted at 3 day intervals. However, the difference between two consecutive applications of the liquid was raised to 4 days on the third, then again on the thirteenth, fourteenth, and fifteenth application. This was done to investigate if any variation from the 3 days'results might occur. It was found that the data of both 51 the adsorption and the descorption experiments did not indicate any change with respect to the 3 day results (see the figures on the adsorption, also the desorption--field condition, in this chapter). This implies that the equilibrium between the adsorbent or the sludge (desorbent) and their immediate solution (the media solution) maintained at or before 3 days from each solution application. This finding bears a weight later in the analysis of the data. 4.3 Adsorption 4.3.1 Field Condition Results of the Zn and Cd adsorption by the different adsorbents are shown in Tables 4.3 and 4.4.* They are also shown in Figures 4.1 and 4.2. They indicate that all three of the organic compounds, the kaolinite, and the kaolinite- organic mixture had the ability to adsorb Zn and Cd (see Appendix G for the data). Leaching of the glucose (G) and tryptophane (T) from the respective columns and the interaction of the T with the sand, greatly reduces the significance of the values that are reported for the G and 1 columns. Nevertheless, some adsorption of Zn and Cd by these substances did occur. *Sample calculations for all of the tables are shown in Appendix F. 52 Table 4.3 Total Adsorption by Adsorbent--Field Condition (Values Are All in mg)a Adsorbent Cation 0 Tb Cel c coc 131C c Ce1c Zn 0.71 .0 4.98 45.78 41.83 50.81 46.53 Cd 0.12 O 3.68 32.68 31.43 33.68 33.15 aThe total cation applied was 92.67 and 93.95 mg for Zn and Cd columns, respectively. bThe apparent values were -3.03 and -0.25 mg for Zn and Cd, respectively. CCG = clay- glucose; CT = clay- tryptophane; C Cel = clay- cellulose. Table 4.4 Total Adsorption by Adsorbent and Sand--Fie1d Condition (Values Are All in mg) Adsorbent Cation G T Cel C CG Cl C Cel Zn 8.08 4.34 12.31 53.11 49.16 58.14 53.86 Cd 4.52 4.15 8.08 37.08 35.83 38.08 37.55 53 4.3.2 Statistical Analysis To determine whether the results shown in Table 4.3 for CG, CT, and C Cel were different from the values reported for the C columns, the following statistical analyses were performed: F test for differences in standard deviation and student t for differences in the means. Details are given in Appendix H. The standard deviation of the reported results were found using the data obtained for each of five columns that were constructed for each specific adsorbent. This was done utilizing the computer program STAT 1 (see Appendix H). The F test indicated that the standard deviations were not significantly different in the Cd cases. They were found to be sig- nificantly different from each other (clay value versus the others) in the Zn cases. The results of the test of differences of the means indicates that the adsorption values reported for the CG, CT, and C Cel are different from the values reported for the C columns with probabil- ities more than 99%, 99%, and 50% for Zn and 95%, 90%, and 60% for Cd columns, respectively (see Appendix H for the details). This implies that the adsorption of cations by the CG and CT columns were signif- icantly different from those of the C columns. The difference between the adsorption values of C and C Cel columns will be discussed further in Section 4.3.4.2. 54 4.3.3 Organic Adsorption 4.3.3.1 Cellulose Figures 4.1 and 4.2 reveal that adsorption of the respective cation by cellulose occurred. This adsorption increased with time over a period of three months. The total adsorption of the cations by the cellulose are calculated to be: [4.98 mg/(65/2)mg/me](1.0/1 g) = 0.153 me/g for Zn; [3.68 mg/(127/2)mg/me2](1.0/0.5 g) = 0.116 me/g for ca. The difference between the two adsorption capacities is 27%. The abrupt increase in adsorption for the Zn in the cellulose columns as seen in the disrupted portions of Figure 4.1 cannot be explained. Since this phenomenon occurred between two consecutive adsorbate applications and since this was not repeated for any other columns studied under this experiment, all that may be concluded is that unpredictable, unknown change or vandalism* caused the change. Nevertheless, if the first portion of the adsorption curve is continued parallel to the last portion of the curve, the ultimate adsorption of the zinc by the cellulose columns would be 3.7 mg which is [3.7 mg/(65/2) mg/me](l.O/l g) = 0.114 me/g which would make it less than 2% different from the value obtained for cadmium adsorption by cellulose. *Some signs of trespassing were noted over the course of the experiment but no sign of disturbance were noted for these columns. 55 Figure 4.1 Adsorption of Zn by selected organics. 56 ~¢.oo ~¢.oo uw.oo s¢.oo m¢.oo nczchHHHF¢40200 oo.me om.mm oo.mm om.»n oo.m~ om.mfl oo.c OGOX 67 Figure 4.6 Unit adsorption (adsorption per application) of Cd by the clay and the clay-organic columns. 68 A020 0001.000 2002000 m>:¢.5r_00 8.8: 8.8 86.x. 8.8 8.8%. 85m 8.8 83m 8.8. 9 mu 0 .6010 x 8 e .. PU Q 3.7.1 >¢1_0 O muD .Unu 8 a .w .80 ..uN 01 8 O .S 120 08 08 a 3 U _, .. . .m . \, . u. . nu /\ / $0,171.). w... 00'0 69 Table 4.5 Adsorption per Unit Weight of Adsorbent (mg/g) (Field Condition) Adsorbent G T Cel C CG CT C Cel Zn 47.30 NA 4.98 2.289+ 2.087+ 2.528+ 2.216+ co 10.91 NA 7.36 3.268+ 3.133+ 3.365+ 3.157+ clay-organic columns was 92.67 and 93.95 mg for zinc and cadmium, respectively. A total of 17.66, 61.32, and 71.27 mg of Zn was applied to the G, T, and Cel columns while 18.94, 33.62, and 72.86 mg of CD was applied to those columns, respectively. Application of the cationic solution to the adsorption columns was terminated when no appreciable adsorption of the respective cation by the adsorbent was detected. Table 4.5 indicates that in all cases, other than for glucose, more cadmium than zinc was adsorbed per unit weight of adsorbent. This phenomenon is reversed if the values are converted to milliequivalents per gram, Table 4.6. Table 4.6 Adsorption per Unit weight of Adsorbent (me/g) (Field Condition) Adsorbent G T Cel C CG CT C Cel Zn 1.45 NA 0.153 0.070 0.064 0.078 0.068 Cd 0.17 NA 0.116 0.051 0.049 0.053 0.050 70 The order of adsorption for both of the cations is the same, i.e., G>Cel >CT>C>C Cel >CG. The position of T is undefined due to the leaching problems metioned previously. Table 4.5 also reveals that in all cases adsorption by the clay- organic mixtures was less than the summation of adsorption by the respective clay and organic alone. This suggests an interaction between the clay and organic such that they occupy each other's adsorption sites which could otherwise be used to adsorb Zn and Cd. We will return to this argument later in Section 4.3.4.2 of this chapter. Comparison of the data in Table 4.5 and what is reported by Huang61 indicates that all the values obtained for the clay ~0rganics His results fall between the values he reported for pH = 5 and pH = 8. are summarized in Table 4.7. Table 4.7 Adsorption of zinc and cadmium by adsorbent, mg/g61 Zn Cd Adsorbent pH = 5 pH = 8 pH = 5 pH = 8 SiO2 1.95 12.61 -2.79 5.33 01-A1203 0.46 13.00 -2.16 15.24 Metapeak 2.00 12.60 -4.44 3.62 Evesboro 1.23 12.50 -2.10 17.78 71 4.3.4.1 Fitting the Adsorption Equation The data were fit to the Freundlich adsorption equation with the computer program FLICH (see Appendix G). The data fit the Freundlich equation very closely. The correlation coefficients are shown in Table 4.8. A typical scattered diagram of the data is shown for the data obtained as the result of the zinc adsorption by the clay in Figure 4.7. The other scatter diagrams of the data are shown in Figures 1.1 to 1.9 (see Appendix I). In all of these figures the equilibrium concentrations were normalized by dividing them by their respective blank concentrations. This step was necessary to eliminate the effect of variation in the input concentration to the columns. The horizontal axis of the scatter diagrams is therefore described in log (adsorbent/soil) rather than log C (where C is referred to the adsorbent as was described previously). Table 4.8 Correlation Coefficients for Freundlich Equation Fittinga Cel C CG CT C Cel A. For Zn: lst portion - 0.990 (5) 0.980 (5) 0.460(10) 0.663 (6) 2nd portion 0.504(31) 0.970(29) 0.981(30) 0.978(30) 0.980(29) B. For Cd: lst portion - 0.990 (5) 0.100 (5) 0.950 (4) 0.985 (5) 2nd portion 0.454(31) 0.978(33) 0.986(35) 0.988(35) 0.979(33) aThe numbers in parentheses represent the number of the test data used in the fitting. 72 Figure 4.7 Freundlich equation fitting for Zn-Clay. 73 A4000\00004 cone _be.01 om.01 c~.w- om.w1 oo.~- oe.m1 oo.m1 b P A4H0m\ovoon mo.o + um.o u Az\xvooq a A4H0m\ovuoq wH.o + ~0.o n Az\xvoog 00'0 OZ'O' 09’0 I are (W/X1001 OV‘O 09'0 74 As can be seen in the scatter diagrams, two rather distinct straight lines exist for each plot. This exhibits the existence of two different adsorption bonding energies. This phenomenon has been reported by Ellis'+5 for another adsorption isotherm and can be used to interpret this work. The two bond energies in this case being for the actual media and the sand. In each instance the adsorption capacity of the sand (the lower limb of the curve) had to be satisfied before adsorption by the active media could become evident. The two bonding energies represent two types of adsorption. Existence of these two bonds appears not only in the clay- organic columns but also in the clay Columns, and, as will be seen in the desorption studies (Section 4.4.2), it also appears in the sludge columns. Since in all of the above cases the sand layer was present and since the sand layer was found to be active in adsorption of Zn and Cd (see Section 4.2.2), it is conceivable that one of the two bonds is the result of sand adsorption. This leaves the other to be the result of adsorption (or desorption) of the active media. It is obvious that in the early stages of the adsorption experiment, a combination of sand and active media adsorption occurred simultaneously. However, the magnitude of the short term sand adsorp- tion (as can be seen in the flooding and desorption experiments) was much greater than the active media alone. Therefore, the sand adsorp- tion bonding overshadows the other, otherwise we should have had only one bonding energy with one straight line for each of the systems of adsorption. 75 In the field condition the effect of the supporting media was eliminated by comparison with the leachate from the sand alone. Some sand, however, was mixed with active media for drainage purposes as was described in Section 3.1.2.4. This sand is believed to create the extra line. Since the amount of sand was small (see Section 3.1.2.4), the amount of cation required to saturate this phase is small. The lower limbs of the curves always were comprised of a few points. The exchange capacity of the sand (weight = 398 grams) was lower being 0.018 and 0.011 mg/g (see Table 4.2) for Zn and Cd, respectively. This does not allow the second (upper) limb to be sand adsorption because the total adsorption shown by this limb is much more than the adsorption capacity of the sand (see Section 0.2 in Appendix G for an example of the adsorption in each limb). Comparison of the sand adsorption data in the field and flooding condition (see Section 4.3.6) reveals that they are almost the same. This implies that pore and bulk diffusion do not perform a major role in the adsorption of cations by sand. As a result the adsorption capacity of the sand is expected to be depleted as soon as enough cationic solution is passed through it. Therefore, it is satisfied first. 4.3.4.2 Order of Adsorption Cumulative adsorption versus the cumulative cations applied to the columns replotted for the portion of the experiment which was determined to be independent of the sand adsorption. The decision 76 on the extent of these regions was made utilizing the information obtained from the fit of the Freundlich equation. The plotted curves are shown in Figures 4.8 and 4.9 . They clearly define the order of adsorption to be CT>»C Ce1> C> CG. The reason why this order is different from that reported in Section 4.3.4 is that they were reported on the per unit weight basis in that section. Table 4.9 was constructed for comparison of adsorption behavior assuming that adsorption of organics by clay may be "proven'' if the following order exists: Cation Adsorption Adsorption Adsorption by by Organic by the Clay Clay- Organic Table 4.9 Comparison of Actual Clay- Organic and Clayi-Organic Columns Adsorption (mg)--Field Condition Zn Columns for Cd Columns for Adsorbent G T Cel G T Cel Clay 45.78 45.78 45,78 32.68 32.68 32.68 Organic 0.71 NAa 4.98 0.12 NAa 3.68 Clayi-organic 46.49 42.75 50.76 32.80 <32.68 36.36 Clay- organic 41.83 50.81 46.53 31.43 33.68 33.15 aNA = not available. 77 Figure 4.8 Release of zinc from the adsorption columns--field condition. 78 A020 003000 quN 03.53350 00.000 00.»0 00.mh 00. «0 00. 00 0m. 00 00. 0N 00.&— 00.91 L .0 D 00 n #0 o m >00 0 \ .90 1 .0 -\ m... m .\ .. 18.1.1. ”.0 WN 8 0 S 180 .8 08 03 0 1 o fun a J . Tmbo OI o 79 Figure 4.9 Release of cadmium from the adsorption columns-- field condition. 80 2:: 000.0000 222000 u>0h015200 8.8 8.8 8.2. 8.8 8.8 8.8 8.8 8.2 8.0.. F L, F P P p - 0 .0 0 00 x #0 o \ m. l—UUIU fl \ Tun-35'. Ed 0 .\ ow 0 . 3 \ w \\ .mm “\K nooN . “U U 2.0,. . 7:8 . 08 ‘\. 03 a\. 0 .\ \.\V.\ 0'! \..\ 18H . (1 00 I 0“ ..‘D\ 0 3 0 3|. , OO'SE 4.3 0116 81 4.3.4.3 Statistical Analysis To test the hypothesis that the adsorption results expressed in Table 4.9 for clayi-organic were different from the values reported for the clay- organic columns, a statistical analysis was performed. This analysis was similar to what was described in Section 4.3.2 (see Appendix H for details). The results of the test indicated that the adsorption values reported for the clay- organic columns are signif- icantly different from the clayi-organic results with probabilities more than 99%. An exception being the CT column subjected to the zinc solution where the probability of the difference is better than 85% (see Appendix H). 4.3.4.4 Conclusions Based on Table 4.9 and the outcome of the previous statistical analysis, the following conclusions may be drawn: 1. The total adsorption by the CG columns was less than that of the clay columns alone. Therefore, it is hypothesized that the small amount of glucose that remained in the CG column reacted mainly with the clay rather than the cations. 2. The net adsorption of cations by the CT columns was more than the adsorption by the clay alone. This suggests that most of the tryptophane that remained in the CT columns reacted with the cations rather than the clay. 3. The clay and cellulose reacted with each other, therefore occupying each other's adsorption sites. This resulted in 4.3. two both at a cati 4.3. to 4 was 06th suit mode the rlth dist. 7“ 82 a lower adsorption by clayocellulose in comparison to clayi-cellulose. 4.3.4.5 Kinetic Studies Kinetic studies are necessary to find the speed with which the adsorption and desorption mechanisms proceed. A comparison of these two results would then clarify whether or not, in a system composed of both, the release of cations would be a possibility. In other words, at any particular time, if the speed at which the desorption of a cation occurred was greater than the rate of adsorption of that cation, a danger of escape of the cation to lower strata exists. 4.3.4.6 Modeling Modeling of the adsorption and desorption curves (Figures 4.8 to 4.11 in the adsorption and 4.14 and 4.15 in the desorption cases) was performed by matching their apparent shape to different classical mathematical models. A trial and error match was made to find the most suitable form among them. The coefficient of determination of the fit, r2 (see Tables 4.10 and 4.11) was used to judge the suitability of the models. It was found that for both the field and flooding conditions, the data were highly correlated with a lograrithmic model.* The loga- rithmic model was such that: Y==a+blnx (4A) *A program entitled “Curve Fitting" provided with the HP 97 desk calculator was used to determine the constants of the model and r . 83 Table 4.10 Modeling of Adsorption Results for Zn Columns--Field Conditions Coefficient of Correlation Determination Coefficient Adsorbent Cation Model r2 |r| Cel Zn Y = -3.36 + 1.87 1n x 0.79 0.87 C Zn Y = -32.48 + 17.52 1n x 0.99 0.99 CG Zn Y = -23.96 + 14.83 1n x 0.98 0.99 CT Zn Y = -46.47 + 21.94 ln x 0.99 0.99 C Cel Zn Y = -33.47 + 17.99 ln x 0.99 0.99 Table 4.11 Modeling of Conditions Adsorption Results for Cd Columns--Field Coefficient of Correlation Determination Coefficient Adsorbent Cation Model r2 |r| Cel Cd Y = -0.72 + 0.96 1n x 0.91 0.95 0 Cd Y = -15.02 + 10.78 1n x 0.99 0.99 CG Cd Y = -12.60 + 9.93 1n x 0.99 0.99 CT Cd Y = -15.96 + 11.24 1n x 0.99 0.99 C Cel Cd Y = -14.46 + 10.70 1n x 0.99 0.99 84 Figure 4.10 Comparison of the models and data in Zn columns. 85 A02. 000.100 QZHN 0300.52.00 00.00— 00.00 00.00 00.N0 00.00 00.00 00.0w 00.N 00.P1 1? P 8 P r r r L m 0 . s .. 0 .. O 8.x . , \ m 0 0 m... 3 8 Eu .....0 MN 8 0 Em. 18 x x 1 ME 1 x x a U 3 3 ‘ O 9 0 0 C 0 rmflw 0t 0 0 o o o o o 00'39 86 Figure 4.11 Comparison of the models and data in Cd columns. A02. 003000 2002000 0:239:00 8.2: 8.00 84.1. 08% 8.0.0 8.0% 8.0% 8.0.0 8.0.. 0 .0 0 00 x B e m l—MUIU q Toning-“.10.. >000 O .\ w... \\ o 8 \. .mu \1 . 0 m \\ 0N .\ 8 \o W \.\0 TWO -\.. . ow .- x m\.\o 03 3‘ O U _.\ o O 0 1; o .8” X X X 1\ \ . O .00 X X X a .. ..\-\ O 0 WI. 0 e w e\o.,\ o \. 00'36 88 where x corresponded with the cumulative cations applied, mg, for adsorption, and with cumulative time, days, for desorption; Y corre- sponded with the cumulative cation adsorbed or desorbed for adsorption and desorption, respectively, and a and b are constants. The models and the coefficients of determination, as well as the correlation coefficients for the field condition are shown in Tables 4.10 and 4.11. A check of the models indicated that they are highly correlated to the data (see Figures 4.10 and 4.11). The models. however, tended to predict slightly higher values than the actual data for the very beginning and the very end of the data points. This variation was at most, 8% for the very beginning point of the Cd-CG and 3.9% for the very last point of the Zn-CT value. As it was discussed in Chapter 3 (see Section 3.5.2) the slope, b, defines the rate of adsorption. The models found can be used for the rate determinations. The rate of adsorption at each point can be found by the slope of the curvature at that point. The slope at each point on the curve can be found as: Y = a+-b 1n x a and b = cte = :91: leIX :51: '1 Slope rate dx b (TTEFTJ x bx (4.2) Equation 4.2 implies that the rate of the adsorption is an inverse function of the cation applied to the adsorbent. Since "b" of a particular adsorbent is a constant, the rate of adsorption decreases with cumulative cationic solution applied, or by increasing time at 89 a constant cation input rate. This means that the rate of adsorption is highest when the adsorbent initially is exposed to the cationic solution. The rate decreases upon increasing exposure of the adsorbent to the cation, let's say upon approaching a saturated state. The model implies that the rate of adsorption approaches zero only when the amount of cation applied approaches infinity. The rate of adsorption of cation at any particular applied cation concentration, x, is only dependent upon "b" (see equation 4.2). Therefore, "b" being directly pr0portional to the rate, it can be used, for comparison purposes, as an indicator of the rate of adsorption. In other words, the higher the magnitude of "b," the higher the adsorption rate will be. Comparison of the models of Tables 4.10 and 4.11, based on their "b" values indicates the following: (1) the "b" values in the cadmium adsorption cases are all less than their counterparts for the zinc adsorption cases; (2) the "b" values are similar for the C and C Cel columns; (3) the "b" value is, for each cation, lowest for the CG column and highest for the CT column, excluding the cellulose column; (4) the “b" value of the adsorption by cellulose alone is considerably lower than the "b" values for the clay- organic columns for both of the cations; and (5) the correlation of the models to the actual data is more in the clay- organic columns in comparison to the cellulose alone. The first parameter in the model expressed by equation 4.1, a, is a characteristic number for the system. This is because when Y = 0, i.e., when no adsorption of the adsorbate by the adsorbent have occurred, equation 4.1 may be written as: 9O Y=0 O = ai-b lnx (4.3) lnx=-% (4.4) x0 = e('a/b) (4.5) x, therefore, has a positive value. Physically, it means that xo milligrams of the cation has to be applied to the adsorbent before any adsorption could occur. 0n the other hand, if x0 is replaced by its equivalent time value (see Section 4.3.6.1), equation 4.5 implies that xt units of time has to pass after the application of the absorbate has started before any adsorption of the cation by the adsorbent can occur. The above may mean a need for a potential build-up of the adsorbate for the adsorption to occur rather than an affinity by the adsorbent for the adsorbate. This is out of the context of this research. However, since the value of xo varies with the changes in the kind of adsorbent, adsorbate, and the hydraulic regime of the cation application, therefore, xo can be related to the indigenous ability of the adsorbent to adsorb a particular cation. It is a characteristic number related to the cation exchange capacity. There is no work in the literature available to speak of this value. More work is necessary to confirm the existence of this value for different soil adsorbate systems. The x values are found, using equation 4.5, for different 0 adsorbents, Table 4.12. The results indicate: (1) the x0 for a 91 Table 4.12 Value of the Characteristic Number, x0, mg-- Field Condition Adsorbents Cd Columns Zn Columns Cel 6.03 2.11 C 4.03 6.38 CG 3.56 5.03 CT 4.13 8.30 C Cel 3.86 6.43 particular adsorbent is lower when the cation applied was cadmium than when it was zinc; and (2) the order of the magnitude of the x0 value for the clay and clay- organic columns was such that CT>>C> C Cel>rCG for Cd and CT >C Cel >C >CG for Zn. Any further discussion for the x0 values is out of the scope of this research. 4.3.5 Flooding Results of the flooding experiments are summarized in Tables 4.13 to 4.15 and shown in Figures 4.12 to 4.15 (see Appendix G for the details) for both of the cations. Figure 4.16 is shown for illustration purposes. It shows the percent concentration of Zn in the leachate with respect to the applied concentration, i.e., C/Co- 100 versus the log of the cumulative zinc applied for the sand and the cellulose columns under the flooding condition. The difference between the two curves is a measure of the adsorption by cellulose alone, whereas, the area over 92 Table 4.13 Adsorption of Zn and Cd, mg--Flooding Condition Adsorbent Adsorbate Ga 1a Cel 0 cc CT 0 Cel Zn 0 0 3.02 19.8 15.97 26.97 20.54 ca 1.48 0.43 1.66 22.17 16.48 30.79 27.07 aThe apparent values were -4.32 and -4.72 mg for G and T, respectively. Table 4.14 Adsorption of Zn and Cd, mg/g--Flooding Condition Adsorbent Adsorbate G T Cel C CG Cl C Cel Zn 0 0 3.02 0.994 0.795 1.337 0.978 Cd 134.5 NA 3.32 2.217 1.643 3.076 2.461 Table 4.15 Adsorption of Zn and Cd, me/g--Flooding Condition e00________________________________., Adsorbent Adsorbate G T Cel C CG CT C Cel Zn NA NA 0.046 0.015 0.012 0.020 0.015 Cd 2.40 NA 0.059 0.040 0.029 0.055 0.044 93 Figure 4.12 Cumulative adsorption of Zn during flooding. 94 .02. 0000000 ozHN w>00¢00200 00.00 00.0w 00.00 0000 00.00 00.00 00.0— 00.0 00.pu b1 P b1 P r .1 F o 0 0 000 X h e o a T006 0200 e 0 11111111011 T, m 0 r9 0 0 l 011 19 w 0 Am 11:1 M (OH) 03880908 95 Figure 4.13 Cumulative adsorption of Zn during flooding. oo.vD 96 Z oo.~m p quota pm 00 >¢40 EDGéNK 00.06 P A02. omuqmmc quN w>Hhmqaznu OD. @N 8.0% 00. Nm oo. an 97 Figure 4.14 Cumulative adsorption of Cd during flooding. 98 oo.¢¢ cm.om b “at. oumgmmc zzmzocu u>~h¢42=zu 09mm om.hu L DD.N~ P 3......— 00."— r om.m 4mm h 0 ozcm OGOX f OV’Z (OH) 0398 003?; 99 Figure 4.l5 Cumulative adsorption of Cd during flooding. lOO 00.0NN om.~m— pr OGOX A020 om~Jmm¢ zauzocu w>-¢4=zzu oo.mm. cm.pm. oo.ow0 om.wo oa.Mm om.mw 101 Figure 4.l6 Zinc adsorption under flooding condition. l02 oo.N 0: 20 0004000 z~ m>_»¢40:00 004 cm." ow. on. o P o..o 00. o o..0w oo.0 .ku ozcm EDlt * .¢:-~z_\4ce «.o. xxuwzuxa ~..o 02.0000 0040000»: oo-o' 103 each curve specifies the adsorption by each of the adsorbents. Figure 4.l6 also indicates that adsorption by sand occurs concurrently with the adsorption by cellulose. This is, however, for the flooding condition when the total period of flooding to saturate the adsorption capacity of the adsorbent was less than 30 minutes (see Section 4.3.4.l for more on this subject). Furthermore, it must be mentioned here that in contrast to the field condition, the sand effect is included in the flooding results. This is because comparison of the leachate concen- trations were made with concentration of the applied solutions and not the sand (blank) columns. 4.3.5.l Modeling The data obtained in flooding condition (see Appendix G for details) were fit to the mathematical model given in equation 4.1. It was f0und that they are highly correlated with the logarithmic model (see Section 4.3.4.5 for details). Tables 4.l6 and 4.l7 show the mathematical models of the adsorption data and the correlation coefficient of the fit for the flooding condition. 4.3.5.2 Conclusion Due to the similarity of the models found for the data of the field and the flooding condition, the rate argument drawn in Section 4.3.4.5 also holds here. Therefore, "b" is a direct indicator of the rate at which the adsorption reaction proceeds. 104 Table 4.16 Modeling of Adsorption Results in Zn Columns-~Flooding Conditiona Coefficient of Correlation Determination Coefficient Adsorbent Cation Model r2 [r] G Zn Y = -0.12 + 0.84 lnx 0.93 0.96 T Zn Y = 1.62 + 0.55 lnx 0.82 0.91 Cel Zn Y = 0.48 + 2.81 lnx 0.96 0.98 C Zn Y = —3.20 + 6.51 lnx 0.98 0.99 CG Zn Y = -3.23 + 5.81 lnx 0.99 0.99 CT Zn Y = -6.69 + 8.45 lnx 0.92 0.96 C Cel Zn Y = -5.78 + 7.94 lnx 0.97 0.98 aY = cumulative cation adsorbed, mg; x==cumulative cation applied, mg. Table 4.17 Modeling of Adsorption Results in Cd Columns-~Flooding Conditiona Coefficient of Correlation Determination Coefficient Adsorbent Cation Model r2 |r| G Cd Y = 1.33 + 0.64 lnx 0.89 0.94 T Cd Y = 0.89 + 0.31 lnx 0.95 0.97 Cel Cd Y = 1.25 + 0.59 lnx 0.97 0.98 C Cd Y = -3.50 + 4.58 lnx 0.94 0.97 CG Cd Y = -1.73 + 3.90 lnx 0.98 0.99 CT Cd Y = -3.51 + 6.90 lnx 0.93 0.96 C Cel Cd Y = -2.80 + 5.66 lnx 0.98 0.99 aY = cumulative cation adsorbed, mg; x==cumulative cation applied, mg. 105 Comparison of the models reported in Tables 4.16 and 4.17 reveals that (1) between the three organics under consideration in this study the "b" value which is indicative of the rate of adsorption (see Section 4.3.4.6) is lowest for T and highest for Cel in the Zn columns. It is lowest for T and highest for G in the Cd columns; (2) all of the "b" values reported for the Cd columns are smaller than their counterparts for the Zn columns; (3) the "b" values of the clay- organic columns are always higher than those reported for the organic columns alone; and (4) between the clay'-organic columns the numerical value of the "b" is in an order such that CT>>C Ce1>TC>TCG for both of the cations. For any given x value, i.e., the total cation applied, the order of the "b" remains unchanged. Therefore, the order of the "b" value automatically defines the order of maximum cation adsorbed that can be found by the model for the different adsorbents. Following the argument drawn for x in Section 4.3.4.6, the 0 x0 values are found in Table 4.18. It appears, from Table 4.18, that the x0 values are higher when the cation applied was zinc than cadmium with the exception of clay column where the order was reverse. A1so, the order of the x0 for the clay- organic columns was found to be CT>C Cel>CG>C for Zn and C>CT>C Cel>CG for Cd. 106 Table 4.18 Value of the Characteristic Number, x0, mg-- Flooding Condition Adsorbent Zn Cd Cel -0.17 -2.11 C 0.49 0.76 CG 0.56 0.44 CT 0.79 0.51 C Cel 0.73 0.49 4.3.6 Comparison of Field and Flooding Conditions Results of the adsorption of Zn and Cd by the adsorbing columns were shown in Tables 4.3, 4.5, and 4.6; also in 4.13 to 4.15. Compar- ison of the results reveals that the adsorption of the two cations under the flooding conditions was in all cases lower than that observed in the field condition. This was to be expected because of the relatively short period of contact between the adsorbent and the adsorbate in the flooding method of cation application. The short contact does not allow for pore diffusion. Therefore, the likeliest adsorptions are those due to film diffusion and surface reactions (such as those due to coulombic attractions, van der Naals adsorption, etc.) as opposed to the pore and bulk diffusion and bulk reactions (such as isomorphic substitution). 107 In the field condition adsorption is through pore diffusion and as such may be categorized as bulk adsorption. This will obviously include surface adsorption and, therefore, adsorption during the flood- ing condition only comprizes of a portion of the long-term adsorption which occurred in the field condition. In the same sense, if the field and flooding data, for a specific adsorbent, are drawn versus the cumulative cation applied, they are expected to follow the same pattern. The flooding curve should fall on the field curve in the early stages of the adsorption and, then fall under it in the latter stages. A sample plot is shown in Figure 4.17. The total adsorption of cadmium by the G and T columns. in the flooding condition, exceeds the values that are reported for their adsorption under the field condition. Since the amount of G and T remaining in the columns could be less in the field than in the flood- ing conditions because the wash out efficiency is reduced, this could account for a major portion of the discrepancy. 4.3.6.1 Comparison of the Models Comparison of the models, found in Tables 4.10, 4.11 and 4.16, 4.17, reveals that (l) the general form of the models is identical for both of the hydraulic regimes. This is expected because although the rates at which adsorption proceeds are different, the processes are the same; (2) all the "a" values of the Model equations, in the clay and clay- organic columns found for the flooding condition are less than their corresponding values in the field condition. This indicates 108 m>g=u copaagomcm we cowpmmog Fmopng u_.v mgzmwm Roz. omaqmmc :DHzoco w>-¢4=z=u Do.www 00.0mm oo.v¢— P) 00.6mm .uo.mwm .uo._wm 007 no. 5 a 0200 0004... ao— .2930 cam—L d O o '0 00 1 03'8 DD'ZI 03132 (0”) 03980906 NOIlUU 16101 00'92 109 that "a" and, therefore, x0, are related, among other factors to the hydraulic regime at which the cationic solution is applied to the adsorbents; and (3) all the "b" values of the Model equations in the clay and clay- organic columns are lower for the flooding condition than their respective values in the field condition. This implies that the adsorption processes were slower (indeed less was observed) for the flooding condition than the field situation (see Section 4.3.4.6 for more on the "b"). Furthermore, the ratio of the corresponding "b" values in the field to flooding condition varied from an average of 2.52 when zinc was applied to the columns to 2.1 for cadmium. The reason for the higher rate of adsorption in the field condition is (1) if the total cation applied is considered (as is the case in finding the models) higher contact period facilitates more adsorption, i.e., due to the pore diffusion which otherwise cannot occur (or partially can occur); and (2) if the time period of appli- cation is considered x with units of mg in equation 4.1 and 4.2, it has to be converted to t with the units of minutes such that: i. for the field condition and for the clay and clay- organic columns the average exchange ratio will be: x = 65 cm3 of 40 mg/l when t = 3 days x = 65' 40' 1 1/1,000 Cm3 when t = 3° 1,400 min/d x = 2.6 mg when t = 4,320 min. or x/t = 2.6/4,320 => x = 6.0- 10’" t 110 ii. for the flooding condition and for the clay and clay- organic columns the average exchange ratio will be: X X X OY‘ x/t = In the flooding condition and for the organics, flow of the 5 cm3 of 40 mg/l when t = l min 5- 40° 1 1/1,000 cm3 0.2 mg 0.2/1 x = 0.2 t II V cationic solution was 40 cm3/min, therefore: X X OY‘ x/t = In equation 40 cm3 of 40 mg/l 1.6 mg 1.6/1 when t = l min. = > x = 1.6 t 4.1, therefore, Y = al-b 1n X for the field condition where .< ll a4-b ln (6 x 10’“)t a+b [ln 6 x10"" + 1n t] ai-b (-7.42 + 1n t) a-7.42 b+b 1n 1'. c+blnt a -7.42 b (4.6) 111 for the flooding condition Y==a+b1n(02)t (49) Y==c+b1nt (4J0) where c = a- 1.61 b (4.11) Equations 4.7 and 4.10 are similar to equation 4.1, therefore, the rate equation, i.e., equation 4.2 remains valid or Rate = bx‘1 mg/mg (4.2) To convert this equation to appropriate rate equation, where x is replaced by t, we must write: . d Rate (mg/min) = %%-= g%---%% = Rate (mg/mg)- d: (4.12) i. for the field condition: x = 6.0- 10’“ t (4 13) dx _ . -“ HE“ 6.0 10 (4.14) Rate (mg/min) = (b x ‘1)(6.0° 10'“) Rate (mg/min) = (b 1 _, )(6.0- 10'“) 6.0- 10 t Rate (mg/min) = b t”1 (4-15) 112 ii. for the flooding condition and clay- organic adsorbents: x 0.2 t (4.16) bt (4.17) Rate (mg/min) for the organic adsorbents, however: 1.6 t X —1 bt Rate (mg/min) where the "b" values of equation 4.15 are those found in Tables 4.10 and 4.11. The "b" values of equations 4.17 and 4.19 are those reported in Tables 4.16 and 4.17. Equation 4.12 and 4.14 indicate that when, in the models, the cation applied is replaced by the appropriate time value, the rate indicator, b, remains unchanged. Comparison of the models indicates that the "b" values for the cellulose columns, in the flooding condition, were higher than those found for the other organics. Furthermore, the similarity of the models in the field and flooding condition' suggests that adsorption proceeds similarly under both the equilibrium (field) and the dynamic (flooding) conditions. 4.4 Desorption 4.4.1 Observations Other than the very first time when some color was noted, the leachate from the sludge columns was quite clear at all times. The 113 first few leachings from the raw sludges were odoriferous. Gas bubbles were observed in the raw sludge columns. These bubbles were small and were dissipated upon application of the liquid. In the course of the experiment growth of one plant was observed in each of two different digested sludge columns. Once observed they were cut close to the sludge surface. The entire plant was left in the column to decompose. The total zinc released from the raw and the digested sludges was 6.53 and 3.44 mg, respectively. The percent release of these metals, with respect to their total input (see Table 3.6), can be calculated as: for the raw sludge 6053 _ 0 for the treated sludge 3044 _ O This heavy release of zinc from the sludge is believed to be as the result of the following dynamic forces: (1) microbial activity in the column; (2) ion exchange of zinc in the sludge with calcium and magnesium in the simulated rain water; and (3) diffusion forces due to the concentration gradient between the content of the columns and the applied rain water. The difference between the percent release of the zinc from the different sludge columns can be interpreted as the amount of zinc 114 that was incorporated by the easily oxidizable organic matter. This is only in the raw sludge and is the matter that will be stabilized in the digester. This signifies the role of the volatile fraction of the sludge in chelation of the cations and is in close agreement with the studies by Gould and Genetelli.31 These authors reported, among other things, that heavy metals of wastewater sludge are more related to the volatile fraction than the nonvolatiles. 4.4.2 Field Condition The result of the field condition desorption are shown in Figures 4.18 and 4.19 (see Appendix G for data and analysis). The results indicate that even though no cadmium was found in the leachates. zinc release occurred at dramatic rates from both types of sludges. In fact, considering the ability of the supportive media to bond cations, as was described before, it could well be argued that the adsorption of zinc by the sand reduced, perhaps significantly, the values that are reported for the early stages of the experiment. To further investigate this effect and to investigate the quality of the desorption data, it was decided to test the fit of the Freundlich equation to the data. 4.4.2.1 Fitting the Adsorption Equation The scatter diagrams for the raw' and digested sludges may be seen in Figures 4.20 and 4.21. As can be seen in these diagrams, there are two distinct straight lines which represent two different major bonding energies (see Section 4.3.4.1 for more details). The top line, 115 Figure 4.18 Release of zinc from raw sludge--field condition. 116 oo.mv~ oo.p~0 00.0w" Am>¢00 wth m>-¢422=o 84%. 88.2. 86.0 8.». 8. Mn 22 il'l‘l m>HFEJDZDQ 0 wgozmw fl wooaqm zcm 00-0" 0'! 03 02 DH F 0*“2 T 09'8 I 08’? (0”) 3983138 JNIZ 3A1181 r 00'9 117 Figure 4.19 Zinc release from the digested sludge--fie1d condition. 118 co.mv~ Aw>¢ow mzmh m>-¢43230 oo.om. co.mw~ oo.amm oo.»m oo.0h 88.0w 88.04 oo.mmu w m>~p¢43230 0 0.52; 4. -mm 9” 3n 1 ”U l TIA r31 0 Z m 3 Thaw-w .1 3 “U S 0.) DH 0 18 r S McDDJw Duhwmauo 119 Figure 4.20 Freundlich equation fitting for raw sludge. 120 2000000200200.0000m 000 00.0 00.0 00.0 0000 00.0- 00.0- 0~.m- 00.w- 00.0- P 1" X 00'8- I‘ J!- mooagm 3cm mom azmphhm zoabcaom Imagozzwxm 121 Figure 4.21 Freundlich equation fitting for digested sludge. 122 ov.o 2000000200200.00000 000 0.10.- 00.0.- 00.0.- 00.0r- 0N;- monzjm oupmuamo mo“. oz:.:-._ zoahmzam :QH-Ezzumn. (I K K ‘ K 14! IJ ‘4 ‘ III K ‘1 J DS'E 00'8- 123 which is almost parallel to the horizontal axis, belongs to the values of the release obtained at the beginning of the release processes. Following the logic expressed in the discussion of the Freundlich lines for the adsorption processes, these lines are the result of desorption from the sludge and consecutive adsorption onto the base sand. This is the same process observed in the adsorption columns. The second line, based on this argument, would be as the result of the zinc desorption. 4.4.2.2 Statistical Analysis and Discussion The correlation coefficients obtained for the fit of the data to the Freundlich equation are listed in Table 4.19. The "first portion" refers to the horizontal section of the scatter diagrams. Table 4.19 Correlation Coefficients for the Fit of the Freundlich Equation to the Sludge Dataa Sludge lst Portion 2nd Portion Raw -O.69 (5) O.91(40) Digested -0.79(10) 0.92(33) 6Values in parentheses refer to the number of data points in each portion. The least square lines which represents the Freundlich equation are shown in Table 4.20. 124 Table 4.20 Least Square Equations for Freundlich Equation Sludge lst Portion 2nd Portion Raw log(X/M) -0.68 - 0.02 log C log(X/M) -2.02 + 2.34 log C -0.84 - 0.01 log C log(X/M) Digested log(X/M) -l.64 + 1.98 log C In these equations the first and the second portions have I'b" values with opposite signs. The reason being the opposite nature of the chemical reactions which produce these lines, i.e., mixed adsorption- desorption for the first portion and desorption for the second portion. The similarities between the least square lines of the scattered diagrams are due to the similar performances by the sand bed and the sludges as was described before. Adsorption of the cations by the support media has been shown before. This requires a significant release of zinc at the early stages of the experiment. The release can be attributed to the organic and inorganic soluble zinc compounds and easily decomposable organometallic compounds which could result in formation of secondary soluble metallic compounds. Bonding of cations to the small, decom- posable, organic compounds has already been reported.31 To this we must add the exchangeable zinc which could be replaced by the calcium and/or magnesium content of the simulated rain water. The decrease in the rate of release of the zinc at the later stages of this experiment could be as the result of the following factors which govern the system: (1) the limitation of the available 125 macro and micronutrients necessary for growth of the microbial community; (2) reduction in the amount of the biodegradable substances in the remaining organometallic compounds of a column; and (3) the depletion of the Zn resource. The data (see Appendix G) also indicate that no significant leaching of the cadmium was detected in the leachate of either of the sludges. Table 3.6 shows that the total Cd content of both the raw and the digested sludge was very low. Therefore, any release would have had a small magnitude. Comparison of the total Cd content of the sludge columns and the base sand's ability to adsorb this element reveals that the expected release ought to be small, if any. It is also mentionable here that in the sludge columns, in contrast to the adsorption columns, there are many cations, negatively charged organic and inorganic compounds which could effectively complete with Zn and/or Cd for binding by the sand adsorption sites. To these we must add the possible resistance of the Cd- organic compounds to decomposition under the conditions of the experiment, and the effect of pH, and Eh within the sludge columns which could cause precipitation and, thus, no release of cadmium. Therefore, a thorough investigation of the microbial, and chemical activities within the sludge columns is necessary to define the mechanism under which no cadmium leachate was detected. 126 4.4.2.3 Modeling and Kinetic Studies The desorption results were modeled using the same principles, as were discussed before. The results are shown in Table 4.21. It was found that the models very closely fit the experimental results (see Figures 4.22 and 4.23) However, lower results are obtained, when the models are used, for the very early stages of the desorption. Table 4.21 Modeling of the Desorption Results, Raw and the Digested Sludgesa Coefficient of Correlation Determination Coefficient Sludge Cation Model r2 |r| Raw Zn Y = -10.86 + 3.50 ln't 0.98 0.99 Digested Zn Y = -10.26 + 2.79 lnt. 0.99 0.99 aY==cumulative cation released, mg; t= cumulative time, days. The rate of release of zinc can be measured using the same principle as was discussed in Section 4.3.4.6. Comparison of the rate of release of zinc from the raw and the anaerobically digested sludge, based on the models found, was done. The "b" value of the models are direct indicators of the rate of release as was shown in equation 4.2. It was found that the rate of desorption of zinc from the raw sludge was higher than that found for the digested sludge (see Table 4.21). This can be attributed to the availability of readily biodegradable metalorganic compounds in the raw sludge as was shown in the work of Gould et a1.31 127 Figure 4.22. Comparison of the model and the data for desorption of zinc from the raw sludge. 128 05.nv— Aw>¢00 wzuh u>-¢40200 00.200 00. 2.0 09% 00.0.0 00.0w... 8.: P 00. mm 00. 0 r mooagw 3mm 00' or‘ 03 DZ 08 0939 09’s or’z 3983138 ONIZ 3A1181 (ON) 00°19 129 Figure 4.23 Comparison of the model and the data for desorption of zinc from digested sludge. 130 00.00— 00.00. 00.00— Am>¢00 ut0p u>~h¢00200 00.000 00.00 00.00 00.00 b 00 0* - 00.m 000040 0wpww000 131 4.5 Comparison of the Adsorption and Desorption At present the wastewater sludge is ultimately deposited in or on soil. In such a system, therefore, adsorbents (soil), and heavy metal desorbents (substances that heavy metals could be desorbed from) are in intimate contact with each other. Comparison of the adsorption and desorption rates, therefore, is necessary to be able to make a prediction on the behavior of the system. Comparison of the adsorption and desorption models indicates that they are exactly the same. The similarity of the models is due to the similarity of the two processes. It also greatly simplifies the rate comparisons. For the material under this investigation, comparison of the models found in Tables 4.10, 4.11, 4.16, 4.17 and those in Table 4.21 is based on their "b" values. The "b" has a unit of1%$% for the models m reported in Table 4.21 and 1n mg for others. They, therefore, have to be converted to the same unit before any comparison can be made. The cumulative cation applied, cumulative liquid applied, and time can be used interchangeably in the adsorption under the field condition. Therefore, the "b" values can be converted to the same unit and are comparable. The rate equations were found before and are repeated here to be: a. for either of the adsorption processes: -1 Rate (mg/mg) = bx or Rate (mg/min) = biz“-1 132 b. for the sludge desorption processes: Rate (mg/day) = bT‘1 (4.18) when the time is converted to minutes, the type of the models remain unchanged, however, the constant "a" will change such that Y = a+-b lnl' T (day) = 1,440 t (min) (4.19) Y = a+-b 1n (1,440 t) Y==c+b1nt (420) where c==a+727b (421) %%-= rate (mg/min) = bt_1 (4.22) Comparison of the rates, i.e., the "b" values in Table 4.22, indicates that in all cases the rate of adsorption of the cations in any hydraulic regime is higher than the rate of desorption of them from any wastewater sludge. An exception being for the organic adsorbents when the rate of release of zinc from the sludges exceeded the rate of adsorption of that by any of the three organics. This comparison is valid for the system used in this study and is subjected to limitations as will be discussed below. 4.6 Conclusion In chemical reaction kinetics the rate of reaction is dependent upon, among other factors, the amount of the reactants. Therefore, the 133 Table 4.22 Values of "b" in the Adsorption and Desorption Models Hydraulic Adsorbent Condition Cation Range of "b" C- organic Field Zn 14.83-21.94 c- organic Field Cd 9.93-11.24 Cel Field Zn 1.87 Cel Field Cd 0.96 C- organic Flooding Zn 5 81-8.45 C- organic Flooding Cd 3.90-6.90 Organics Flooding Zn 0.55-2.81 Organics Flooding Cd 0 31-O.64 Desorbent Raw sludge Field Zn 3.50 Digested sludge Field Zn 2.79 rate of adsorption will certainly change with the changes in the amount of adsorbent. This is such that an increase in the amount of adsorbent, when other factors remain unchanged, will increase the rate of adsorption. Table 4.22 is useful to compare the rate of adsorption also decomposition of heavy metals in a system composed of the adsorbent and desorbent with the amounts used in this work. The volume of the sludges used in construction of the desorption columns was what is normally applied to the soil in agricultural land. Therefore, the following generalizations may be made: 134 l. Twenty grams of a low adsorptive clay, such as the kaolinitic clay used in this work, has a higher rate of adsorption than the rate of desorption of zinc from wastewater sludge. 2. The hydraulic regime of transferring cations to the adsorbent has a considerable effect on the rate of adsorption. Low surface loading of the liquid applied to the adsorbent- desorbent system is favored for greater adsorption rates and for higher total adsorption. 3. The rate of adsorption and desorption of heavy metals in a fixed system decreases with time. This is due to the depletion of the active site and the heavy metal resources, respectively. 4. The existence of organic matter increased the rate and the total amount of the heavy metal adsorption, an exception being the CG columns under most conditions. However, the interaction between the clay and organic matter reduced the adsorption expected if they were acting separately. Finally, wastewater sludges are known to contain a variety of heavy metals and other cations. These cations are expected to effec- tively compete with each other to occupy the adsorbing sites. Therefore, a broader inventory of the negatively charged desorbates and their rate of release is necessary to judge the overall ability of a soil to accommodate a sludge. The problem of working with pure systems and then extrapolating to soil has been amply demonstrated by Lagerwerff and Brower. 135 4.7 Engineering Application Engineering application of the adsorption portion of this study is limited to specific cases when the main fraction of the cationic portion of a desorbent is known. Very few other methods, such as the CEC analysis, are available to predict adsorption of cations by the soil. Therefore, in the lack of other decisive methods the prediction can be done utilizing the models developed in this work. Although desorption of the heavy metals from sludge was expected, no previous modeling of the release of heavy metals from raw and anaerobically treated wastewater sludge has been reported. The original concentration, therefore, the total cation content (for the cation/s of interest) of a sludge can be easily found, using well known techniques. The result of the desorption study can, therefore, be used to predict the rate and the amount of the release for a known time period. The models also may be used to predict the ultimate period of time before all the cation in the sludge is released to the environment. The last is, however, a tentative methods of prediction. The models developed can be used for the prediction purposes. This can be done by experimentally finding the first few points of an adsorption or desorption process, finding the "a" and "b" constants of the model and make prediction. When the wastewater sludge is applied to an agricultural land, and when the metal uptake pattern of the crop is known, a material balance of the cation released to the environment and what has been 136 picked up by the plant can describe the state of the soil pollution by the specific heavy metal. SUMMARY In this work finite well drained soil beds were made up of kaolinite and/or one of the three organics commonly found in the waste- water and wastewater sludge, namely, glucose, tryptophane and cellulose. A monometallic solution of zinc or cadmium was applied to the soil beds under either of the field and flooding conditions. The two hydraulic regimes simulate the ultimate adsorption condition, i.e., the equilib- rium and dynamic, for field and flooding systems, respectively. The leachates were analyzed for their heavy metal contents. It was found that the adsorption data were highly correlated to the Freundlich equation. The data also fit well in a logarithmic model. The effect of hysterises on the adsorption was not considered because the entire bed always was saturated. In the field condition, it was found that the main adsorption or desorption occurred during the period between the two liquid applications. Two sludges known to have high metal content were studied for their heavy metal release. Simulated rain water was used as a carrier for the released cations. The leachates were analyzed for their Zn and Cd content. It was found that a combination of chemical and biological reactions occurred in the desorption columns. These reactions caused the chelated heavy metals to break up and release their cation content which subsequently was washed out of the columns. 137 138 The rate studies were performed utilizing the mathematical models. It was found, in both adsorption and desorption study, that rate is an inverse function of the time from when the process starts. Similarity between the mathematical models found for the adsorption and desorption processes facilitated the comparative kinetic studies. It was shown that, using the quantities of the adsorbent and desorbent studied, the rate of adsorption of heavy metals by the clay and clay- organic adsorbents exceeded the rate of release of the heavy metals from either of the raw or anaerobically treated wastewater sludge. This was true for both of the hydraulic regimes that were considered. Some experimental difficulties were encountered due to the solubility of the glucose and tryptophane, also due to the adsorption of the heavy metals by the support media. APPENDICES APPENDIX A PROPERTIES OF ADSORBENTS USED IN THE ADSORPTION COLUMNS Glucose, tryptophane, and cellulose were chosen as the organics to be used in the adsorption columns. A kaolinitic clay was used as the clay source in the adsorption studies. Some pro- perties of these selected adsorbents are as follow: a) D-Glucose (dextrose*) C6H1206° 1H20 HHOHH HOCH2 - c - c - c - c - CHO OHOHH OH Glucose is a hexose, therefore, a monosaccharide. Dextrose is also known as grape sugar. ACS reagent grade dextrose with the properties shown in Table A.l was used in this work. b) Tryptophane* CllHlZNZOZ C E:/ \E— (i—CH20H(NH2)COOH C C C \c/\--( It is, also, called a-amino- B-indolyl-proprionic acid. Its solubility in 100 g of water at 25° C is 1.136 g. *CRC Handbook of Chemistry and Physics, 56th edition. 139 140 Table A.l Properties of the Selected Organic Matters Organic Matter Properties Tryptophane Glucose Mw 204.23 180.16 Lot No. 8719 765,944 Specific rotation [a], 25°, 0 NA +52.5 Insoluble matter NA 0.005% Acidity (as CH3COOH) NA 0.005% Chloride (as C1) NA 0.002% Starch NA 0.08 ppm Heavy metals (as Pb) NA 4 ppm Fe NA 1 ppm 141 pK = 9.39 p1 = 5.88 p1 = 0(pK + pr + pKw) pK 11.62 a1 1 b1 where pI is the pH at the isoelectric point. ACS reagent grade tryptophane with the properties shown in Table A.l was used in this work. c) Cellulose (C6H1005)x - Glucose, in particular the form known as B-glucose is the unit break from which the cellulose is built. 60 One of the most favorable arrangement of cellulose is proposed to be: ’ \ CHZOH H OH CH OH H OH c—o 'c—c'; é—Z-o -':—'c T A 1 ///0H A\\\T T///A \\\ x/le H\\H S OH H C_0""C H C—O _C OH H 1 —0 —(';\H /& k -\ / \ /. .- 1 ' 1:...0 1_& 1.1- l l I I 6 (E H OH CHZOH H H, J HZOH \ Cellulose,therefore, could indeed be assumed to be a polymer of glucose. Furthermore, the ultimate product of the hydrolysis of cellulose by acids is glucose. d) Kaolinite This type of kaolinite is usually used in the pulp and paper industry. The grain size distribution of the kaolinite is obtained as the result of a hydrometer testing and is shown in Figure A.1. It could be seen in the figure, that more than 60% of the particles are smaller than 2 micron, therefore are clays. Fines 142 Sand Gravel ‘1 4 1 :00 V: O 0 . L C o N-ojfi 0000 1.1- YN - - .- 5 l 0 0 0 '0. 0 Ax a . z I .0 p.- méaaz-iliilfll 111111|liifll1lllhues0 .0 ,0 m .m 8F.°2I1rl.lllvlnIITIII-Ilrllslll Illrlllltnltlltnllllrllll IleVw.° n 0 n m . . 51.9 021 Ill-1 llll!|l.-||l--lli|lll110000 .0 O t. m U 3.021111111111111 211- .11-111111.11-11-1111 [$0.0 e.m 0 m0 .w_m 0.02 v.02! III: III lull!" I'lrllll-IIIILIIIIII .11-II- Ugh.” or .530 m 0 0 0 0 o 5:: E0800 Y Grain diameter. mm Grain size distribution curve for cla (kaolinite).62 Figure A.1 143 Table A.2 Properties of Zinc and Cadmium Compounds* Parameters Zn(N03)2, 6H20 Cd(N03)2, 4H20 Formula weight 297.47 308.47 Lot number 762191 755409 Insoluble matter 0.001% 0.002% Acidity as (HN03) 0.006% NA Cl 0.002% 0.0003% P04 0.0005% NA 504 0.008% 0.003% Alkalies and earth 0.2% 0.03% Pb 0.002% 0.001% Fe 0.0005% 0.0003% Cu NA 0.0005% Zn NA 0.05% NH NA 0.003% 3 * NA = Not available APPENDIX B SLUDGE DIGESTION AND METAL MEASUREMENT The following procedure was adopted to measure the zinc and cadmium in sludge. 8.1 Digestion Procedure Digestion of the sludges was necessary for measurement of the zinc and cadmium by atomic adsorption spectroscopy (See Appendix C for the analytical procedure). The moisture content of the sludges was reduced by placing them on silica sand beds and allowing them to drain for 24 hours. This was necessary to reduce the volume that had to be digested. After 24 hours the moisture content of the raw and treated sludges reduced to 81.35% and 77.1%, respectively. The follow- ing steps were then followed: 1. A sample of the sludge having about 0.5 g dry weight was placed in a 50 ml all teflon beaker. A blank consisting of 10 m1 of distilled water was also prepared to be carried through all the remaining steps. 2. 25 ml concentrated ACS Reagent grade HNO3 was added. 3. The beaker was then placed on a hot silica sand bed having a temperature of 160° C and left to dry (4-6 hrs.). 4. Steps 2 and 3 were repeated. 5. The beaker was then cooled in air and 20 m1 concentrated 144 .-¢- -. —-._7 - 10. 145 Reagent grade HF was added followed by 10 ml concentrated HC104. The beaker was then placed back on the hot sand bed for 24 hours to dry. The contents of the beaker was then washed with 5 ml 6N HCl while still warm to dissolve the residues. The washings were transferred to a 50 ml volumetric flask. The washings were then made up to 50.0 ml by adding distilled water. The samples were then analyzed for metal content by Atomic Adsorption Spectroscopy (See Appendix C for the method). 8. 2 Measurement Result Result of the measurement are shown in Tables 8.1 and 8.2 where the raw, digested and blank samples are denoted as R, D, and B. Table 8.1 Zinc and Cadmium Content of Digested Sludges Slud ea Net Wt. Dry Nt.b Zn Conc. Cd Conc. g 9 9 mg/ 1 rug/1 R] 1.8244 0.3402 50.5 0.35 R2 2.2592 0.4213 56.0 0.40 01 1.5663 0.3587 39.5 0.24 02 1.7962 0.4113 4.25 0.28 81 1.94 0.15 82 2.13 0.15 aSubscripts refer to the sample numbers. b Dry Wt. = wet wt. . dry content. 146 Table B.2 Zinc and Cadmium Content of Sludge (with blank correction) Sludge Zn Conc.a Zn Conc.b Cd Conc.a Cd Conc.b mo/l mg/g dry mg/l mg/g dry R] 48.46 7.122 0.2 0.029 R2 53.96 6.404 0.25 0.030 D] 37.46 5.222 0.09 0.013 02 40.21 4.888 0.13 0.016 aConc. = Conc. - blank conc. (Table 8.1). bTotal metal in sample = Conc. (m9)/l,000 m1 -50m1= 0.05 - Conc. (mg) Conc. in dry state = Total metal in sample/Dry wt. of the sample. As the result of the Table 8.2 information the average zinc and cadmium content of the samples are 6.763 and 0.029 mg/g dry for the raw, and 5.055 and 0.014 mg/g dry for the digested sludges, respectively. APPENDIX C ANALYTICAL PROCEDURES A11 synthetic feed solutions were prepared with reagent grade chemicals and distilled deionized water. All glassware and operation materials were rinsed with tap water, cleaned with either dichromate acid, acetone, or soap cleaning solution, rinsed three times with tap water, and three times with distilled water. The zinc and cadmium standard solutions were reagent grade 1,000 mg/l purchased from Fisher Scientific Incorporation. C.1 Equipment Cadmium and zinc ion concentration of the samples were determined utilizing an Atomic Adsorption Spectrophotometry unit. The unit was an Instrument Laboratories Model 151 with a premixed burner. An acetelene flame was used as recommended inthe Standard 9 Method for Examination of Water, and Nastewater.“ Readings were made at the conditions summarized in Table C.1. These operational factors were so chosen to achieve an optimum sensitivity. In addition, the position of the nebulizer was adjusted to obtain a minimum operational noise. All of the standard solutions, used to obtain standard curves, were made from the 1,000 mg/l zinc and cadmium solutions and distilled water. 147 148 Table C.1 Operational Conditions in the Atomic Adsorption Measurement of Zn and Cd Parameter Description 2n Cd wave length, R 2,139 2,288 Hollow cathod current, mA 5-7 5 Voltage, volts 530 460 Burner height, machine unit 12 12 Slid width, micron 320 320 APPENDIX D MEASUREMENT OF REQUIRED SLUDGE The volume of sludge that was used in each column was based on an assumed application rate of 10 dry tons/acre and was calculated as follows: Converting dry ton/acre to grams per 2 inch diameter column: (10 tons/ac)(2,000 1bs/ton)(454 g/lb)(l ac/43,560 ftz) (l ft2/144 in2)(2 in)2 (n/4) = 4.55 g/column For the raw sludge which had a dry solids content of 5.5 g/100 ml: (4.55 g)/(5.5 g/100 m1) = 83 ml For the treated sludge which had a dry solids content of 3.29 g/ 100 ml: (4.55 g)/(3.2 g/100 m1) = 142 m1 149 APPENDIX E ORGANIC RELEASE As was described before glucose and tryptophane leached out of the adsorption columns, the results of the total carbon measure- ment, Tc’ which are expressed as mg/l Carbon, were converted back to the respective organics as follows: Molecular wt of the organic a ' 12 ' number ofiC in the molecule Therefore, organic concentration in the leachate in mg/l = T = aT cL c where a is 2.75 and 1.545 for glucose and the tryptophane, respectively. The average amount of glucose and tryptophane that were left in the columns, TCr’ were calculated as: TCr - Initial organic added - 20.065 (TcL + e) 5Na e where e is the error due to the dissolved C02 (measured from the blank cationic solution to be 5 mg/l) and N is the number of times carbon was detected (and measured) in the leachate. The release of organics from the adsorption columns were calculated, using the procedures described before, in this appendix. 150 151 The results are shown in Table E.l to E.8.* The net cumulative release of glucose and tryptophane from the adsorption columns versus the cumulative volume of the cationic solution are shown in Figures E.l and E.2. The total glucose and tryptophane remaining in the system are shown in Table E.9. The value reported for the release of the tryptophane in the cadmium-T columns has exceeded the amount originally added to these columns, therefore, is meaningless. The actual number is, therefore, not available. Table E.l Release of Glucose from the-Cadmium Columns Cumulative Cumulative Error Net Cumulative CdG G Concentration G Release (m ) Release (ppm) (mg) 9 (mg) 60 60 3.9 .9 3.0 5,500 5,560 361.4 1.8 359.6 2,002 7,562 491.5 2.7 488.8 *For the sample calculations see the end of this appendix. 152 Table E.2 Release of Glucose from the Cadmium Columns Cumulative Cumulative E Net Cumulative CdCG G Concentration G Release rror Release (ppm) (m9) (mg) (mg) 65 65 4.2 .9 3.3 1,168 1,233 80.1 1.8 78.3 5,005 6,238 405.5 2.7 402.8 1,042 7,280 473.2 3.6 469.6 Table 6.3 Release of Tryptophane from the Cadmium Columns (T) Cumulative Cumulative Net Cumulative CdT T Concentration T Release Egggr Release (ppm) (mg) (mg) 35 35 2.3 .5 1.8 1,062 1,097 71.3 1.0 70.3 1,275 2,372 154.2 1.5 152.7 1,579 3,951 256.8 2.0 254.8 1,635 5,586 363.1 2.5 360.6 1,392 6,978 453.6 3.0 450.6 1,210 8,188 532.2 3.5 528.7 669 8,857 575.7 4.0 571.7 202 9,059 588.8 4.5 584.3 34 9,093 591.0 5.0 586.0 153 Table E.4 Release of Tryptophane from the Cadmium Columns (CT) Cumulative Cumulative Error Net Cumulative CdCT T Concentration T Release (mg) Release (ppm) (mg) (mg) 55 55 3.6 .5 3.1 970 1,025 66.6 1.0 65.6 1,335 2,360 153.4 1.5 151.9 1,477 3,837 249.4 2.0 247.4 1,416 5,253 341.4 2.5 338.9 1,025 6,278 408.1 3.0 405.1 601 6,879 447.1 3.5 443.6 384 7,263 472.1 4.0 468.1 182 7,445 483.9 4.5 479.4 104 7,549 490.7 5.0 485.7 61 7,610 494.6 5.5 489.1 34 7,644 496.9 6.0 490.9 20 7,664 498.2 6.5 491.7 Table E.5 Release of Glucose from the Zinc Columns (G) Cumulative Cumulative Net Cumulative 205 G Concentration G Release Error Release (ppm) (mg) (mg) (moles 96 96 6.2 .9 5.3 7,830 7,926 515.2 1.8 513.4 7,012 14,938 971.0 2.7 968.3 271 15,209 988.6 3.6 985.0 154 Table E.6 Release of Glucose from the Zinc Columns (CG) Cumulative Cumulative Error Net CUmuTative ZnCG G Concentration G Release (mg) Release (ppm) (mg) (mg) 78 78 5.1 .9 4.2 5,250 5,328 346.3 1.8 344.5 7,947 13,275 862.9 2.7 860.2 1,474 14,749 958.7 3.6 955.1 64 14,823 963.5 4.5 959.0 Table E.7 Release of Tryptophane from the Zinc Columns (CT) CUmulative Cumulative Net Cumuiative ZnCT T Concentration T Release Error Release (ppm) (mg) (mg) (mg) 68 68 4.4 .5 3.9 1,093 1,161 75.5 1.0 74.5 1,261 2,422 157.4 1.5 155.9 2,157 4,579 297.6 2.0 295.6 2,340 6,919 449.7 2.5 447.2 2,386 9,305 604.8 3.0 601.8 2,030 11,335 736.1 3.5 732.6 1,438 12,773 830.2 4.0 826.2 737 13,510 878.1 4.5 873.6 262 13,772 895.2 5.0 890.2 98 13,870 901.5 5.5 896.0 36 13,906 903.9 6.0 897.9 15 13,921 904.9 6.5 898.4 155 Table E.8 Release of Tryptophane from the Zinc Columns (T) Cumulative. Cumulative Error Net Cumulative ZnT T Concentration T Release Release (PPm) (mg) (mg) (mg) 31 31 2.0 .5 1.5 862 893 58.0 1.0 57.0 1,208 2,101 136.6 1.5 135.1 1,444 3,545 230.4 2.0 228.4 1,285 4,830 313.9 2.5 311.4 1,074 5,904 383.8 3.0 380.8 1,069 6,973 453.2 3.5 449.7 1,043 8,016 521.0 4.0 517.0 978 8,994 584.6 4.5 580.1 819 9,813 637.8 5.0 632.8 754 10,567 686.8 5.5 681.3 652 11,219 729.2 6.0 723.2 708 11,927 775.2 6.5 768.7 596 12,523 814.0 7.0 807.0 487 13,010 845.6 7.5 838.1 503 13,513 878.3 8.0 870.3 445 13,958 907.3 8.5 898.8 348 14,306 929.9 9.0 920.9 276 14,582 947.8 9.5 938.3 215 14,797 961.8 10.0 951.8 157 14,954 972.0 10.5 961.5 147 15,101 981.6 11.0 970.6 99 15,200 988.0 11.5 976.5 54 15,254 991.51 12.0 979.5 37 15,291 993.9 12.5 981.4 21 15,312 995.3 13.0 982.3 15 15,327 996.2 13.5 982.7 156 Figure E.1 Total release of the glucose and tryptophane from the cadmium columns 157 00. N00 0 m . UTWG um OAOX . m) EL . 3M” 5 m...“ 140 2E I.- DI OD! m9 50 W. a. a /1 DU 0 0 n.. 8.2.8 8...? 8.8mm 88¢. 8.2m 8.3.. 8...... 8.4% nor: mw¢w4um 0020010 m>:.¢ 3:00 158 Figure E.2 Total release of the glucose and tryptophane from the zinc columns 159 m UTMwG aw 0A0! m1 1....L 3M 5 8 sum U DI 0P mR 1.4.0 U 0 ML [H 1m 1‘1 11H” /./ 0 o 8.8 8.8 9.4... 88.8 8.8... 8.? 844 88: 8.4% .03.. “or: wwcwgux u—z 0x0 m>~._.¢._:z:o 160 Table E.9 Glucose and Tryptophane Remained in the Adsorption Columns, mg G CG T CT Cd columns 11 30 NA 8 Zn columns 15 41 17 102 Sample calculations for Tables E.1 to E.8 The sample calculation is given for Table E.1, i.e., CdG: Col. 1 - Concentration of glucose measured in the leachate sample mg/l, for example 60 mg/l, 5,500 mg/l, etc. Col. 2 - The cumulative concentration of glucose = £Col. 1. Col. 3 - (0.065 1)(Col. 2),examp1e: (0.065)(60) = 3.9 The 65 m1 is the volume applied, and collected to and from a particular adsorption column. Col. 4 - Error = (5 mg/1)(o)(65 ml)(l 1/1,000 ml)(N) N = 1 for the first measurement, therefore: Error = 0.9 mg, where a = 2.75 for glucose (see below) Col. 5 - Net cumulative release = Col. 3 - Col. 4, example 3.9 - .9 = 3.0 mg. a, the correction factor to convert the total carbon measured to the appropriate organic was found as below: 161 For glucose M” C6H1206°H20 _ 198 _ a - 2.75 6 c 7 For tryptophane a M” C11H1202N2 = 204 = 1.545 11 c 13 For cellulose n(C H 0 ) 6 10 5 162 _ on —7—2--225 6nC APPENDIX F SAMPLE CALCULATIONS Columns in each table is numbered, starting from the first data column, Col., in the left side of the table. Table 3.6 Col. 1 See Appendix 0 Col. 2 (83 m1)(5.59/100 m1 dry content) = 4.565 9 Col. 4, Col. 3 (Col. 2)(Cation content from Table 3.6) (4.565 9)(6.763 mg/g dry) = 30.873 mg Table 4.4 Values are all those from Table 4.3 plus 7.37 and 4.4 for the zinc and cadmium columns, respectively. Example for Zn-G columns: 0.71 (from Table 4.3) + 7.32 = 8.03 mg Table 4.5 Values of Table 4.3 divided by their weight left in the adsorption columns (from Table 4.1). Example 0.71 mg/0.015 g = 47.3 mg/Q 162 163 Table 4.6 Values of Table 4.5 divided by equivalent weight of zinc or cadmium. atomic wt (mg) = 65 me Z" = vaTance '72 = 32.5 mg me Cd = _l%§__= 56 mg example: 47.3 / 32.5 = 1.45 me/g Table 4.14 See Table 4.5. Table 4.15 See Table 4.6. APPENDIX G EXPERIMENTAL DATA G.1 Field Condition The result of the adsorption tests under the field condition are shown in Tables G.1 to G.4. The adsorption values that are reported are calculated in comparison to the leachates from the columns. The procedure adopted for this calculation was as follows: 1. Find the average of the cation effluent concentration (i.e., the average of 5 values) for the sand, AVGS, and the test column (AVG X, with X being G, T, Cel, C, CG, CT and CCel). 2. Calculate the total applied cation as mg applied = [Volume applied (1)][AVGS (mg/1)] where the volume applied each time was 65 m1. 3. Calculate the amount adsorbed, at each particular time, for each adsorbent as: (mg applied) - [(Volume applied)(AVGX)] mg adsorbed or 0.065 (AVGS - AVGX) mg adsorbed The total period of the experiment was 4.5 months. The experiment started in early May and continued until mid September. 164 Table G.1-Adsorption of Zinc-Field Condition 165 200wawmomammowuoxMNUMuNOMdmhd~womcodom00ocm Ulcourux v-«V'rnar 0:: km anomv-«anumou wumrsmag camm :mmr m 0.0.0.....0.COOOOOOOOOCOOO...0.0.0.000... dfifiNNfiNNNNndwdudnfiv-Idd on... AOSOPPTI CCEL 20°N®WO0Nm~«NMdOMQMOOhooomwfiodfikR3!occaoooo ozooednw.’0'4NdNN-4000dd0d0°~~0fi~ud00«00096909 H 0.0.0....C0.00000000000000.0.0.0000000000 #4 d I I 00I d I 00000000 2 ONV’V'OIDC‘MNIL IrO‘MQCINDJNONtD-f'IrnutoONQMF-C‘SB NFC dink O Coca-4m. d~o~0mfio~w®m0u~dadawdh O ommnm~~¢mm~na~~¢u Hg ...ooooooooo.oooooooooooococo-0.00.0.0... ddfiNNfiNNNHHflHv-IHv-Iddd v-I Y ‘ dwcwnmmUQon000000000000000000000000000000 0060'!.109:«Nvac-t000000000000000000000000000000 HtO0.0.0.000000.00900000000. 0.000.000...- » I I I 006060000090000000000000000000 0 Z BNNONnONNOMQONNFocdomwcnmwao¢~00~:oaa:ocm oooodnco«0na:Nocwwomsummnowawcccammmmam3~~n NYC-00.000.00.00. coo-00000000..0.00.0000... h dd deNNNNNNfiNHH“Nde “NH at- EU 0 II‘ c q 2 «N3H0mwsooONkfl:ou«°Bw0k:N000m000000000000 DOOM modn¢0a0~~qv40000v400~090 «#000000000000 Hzno...00..o.ocoo.ococo-00000900000000.0000 EPIII IIIII IIIII OII II I .009000000090 d O «n O d 2 aNtdmmsoma‘mofiOOflnfinNF’N«00.00“hornet-000000 O aOv-IWOdNU‘dMNONNOO‘ONOJ‘MvION—I3‘D'DMIDJMIB3’QmNP’MN Hanan... one.coono...ooooooo...o.oo.oa.o.oooo ht dddNNdeddddddo-Iddddd dd a m» 0‘ III-J Do ¢ ZON00990m0m000000000090D0m990U0000900000009 Nm0~00005mu0mmmmmam00m0mm~0m0m0mm00m00m000m “0.0.0.000...0....OOOOOIOOOOOOOOOOOOOOOOOI 04 QNMoONanN:«nos:0mk0Nkoehmhmmkommowooask \a u:d;wnanonwmawowmeoaoao¢«00 N0n00n004~000 O. finoeNOchNde-«nc'«d0nmnGMNBSNm3MOOQOGOOmm q dddNNdNNNNNNNNNNNMNNNdNMNNNNNNNNNNNNNNN «wn on mouuncmos 00 ~n¢mos saw» 0 coca :m T fluwuuduad~3-~~-3$nnn 33 n nngg Table 0.2 Adsorption of Cadmium-Fie1d Condition 166 200 3% Nv-«DvdIDOIDva-IOU‘IDO'” couoweumnm "N9MMMU‘39 UICIDNv-‘NJWNO cu-am~001~01m~m~mu~4mmaamwnnm«narrate-10 H O...00.000.00.000...OOOOOOOOOOOOOOOOOOOOO pd v-INNNNv-Iv-Ido-IHCIH nu. 00 CO I]. D a 200:08wnmosdfimnad0¢n0d0crno0non~dmn00000000 UIOGOdd¢M°QBQdDOBOQODddfiaccdd°N9°°dO°°°°OBD H cocoooooooooooeooOoo0000.00.00.0000000000 PA I 9 I 00000000 am 00 O m U a z eawmtunc:ononcmowmno0505000:500mm0n~nup:0 Owobsuunwackmmmwecscemwoncnuma:n~~~~~«~«nao HIOOOOOOOOOOOOOOOOOOO.OOOOOOOOOOOOOOOOOOOOO :0 HNNNNddv-Iv-Iv-Iv-IH «0 O (h D d Hfooeooooooooooooooooo0.0000000000000000... ID | 0. 000000000000000000000000000009 Z 03mr~000030r~m~000m00omeonspcmmeumowoo: 00000-0 «wwwvcomJnae-ca‘a‘co 0k mm; ”“133'0MMNMHHNHNOD I H e o o o o o o o o o o o o o o e o o o o o o p «~~~~ud.¢ddddv:. o 0.. o. co o. 0000 on Ch (:0 0 m G q z 00*!»:mco0Nd00NMfi‘n000000000090000000000009 00000»000d000d000000000000000000000000 00000 Ht00000000000000.0000.ooooo.ooooooooooooooo t» I I I I0 ||Ig 900000000090090000000000 m 0 In 0 d z 0cm~~gqnm~mmm~ma~mm“mnmooonenommoode O GONdNnNQQmeONv-IOKOm0m3lhsn33-fNMMNNHdeINC-IO H9000. coo-00.00.000.0000.0....000000000.000 : dNNNNddddo-Id—I oo~n9m9mm°m°mmmaeom0ma090000000000m000m0000 00000~05N0~m~~~mmm~0~0eamssmommmmmbmamsooon ”OF...OOOOOOOOOOOOOOOOOOOO .0. 0 00.000.00.00. 04 n:~0«0«0~Nooooommwwoosmos~0unsmh~00:N gm nthdONNONOON“GQN°0ONKdQMMKONNOWODOQHONO I sd~ceecmoocnceccc::mnnnem0mnnmcmamosonn g dNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN Table 0.3 Cumulative Adsorption of Zinc-Field Condition 167 ZLDNQBNNU'IG‘NOQQU" :v-IQKIINO O‘v-Iv-IQIDOB wWJwNfiMNF In?» Nv-IV LLC ’30-'44" 1\DU-'~ wamhauon mosmo' “Nov-OISInv-IJCJO If 0 IOUJJ‘JC Nw D- ooooooooooootooooooocooo00000000000000... I-J HNJWQDNUKO‘v-OM4'DQO‘ONVOIDWB OU‘Odv-‘NNNH": 3 3 ill-mu w LLU wdfiddNNNNNNMnFIMMVJMMJS-C 4444 444 4 J-J J a “L. 0L U D d ZOONC- 4M°N¢IIND'~ NdeONNNOJ380‘IhWWOWDQC C- 00¢! 0‘ SI OOONU‘QNVIMU‘OO‘FOOO‘O ¢ddnnMOMMNIBI~NQQO‘O-0 ‘O‘U‘U‘O‘O‘ 000.0000.000000000000900on. 00.00.000.000. EA «dudNNNNNNNNNNNMMMMnMnMa344::0::3443344 IL “(L C m D 0 2 camped“:ONKU.¢.:a~m0~¢owv-lonkvo~mm¢mows¢~~0~t~¢r 0000.44 MJWUMDOw-O0Is MOO”) :mwh oc-mmcomcrroewwowlc 0~mo HIoooeoooooooooooooooooooo00.00000000000000 I- HNJWCDNJNU‘ONV’U‘BOO‘OHNM;mIDMNOOOU‘O‘O‘OOHflv-IH no uuauaNNNNNNNnnnnnnnnnnnnnnnn:::¢ ~13 uc (.3 O U) D d z vie-IOI'OOII‘O‘O‘MO‘v-‘q-IdHO-Idfldq-Ic-Idv-qu-IddWMHddWHHfidfide-I OQODNNNde3MP~KI~I~NI~I~NNF bk? MBNNMNBKNFNBNKN Ht 000.00....ogooooooooooooo.00.0.000000000000 t- I I no ADSOR z 0mmt000un~m00~00~0danmwwawnonmdkscs:mvmmd ocn003M~¢naonoo¢mroa0¢4¢NNmmmm00M¢80m04¢H:@ HT0.00.0.000000000000000000......00.0.00... h dN”MfiWdanDN:we°dnmoO@6~n3mmo®NKUDOWOOO g8 «dudwwwwwmnnnnnnccc:2:433:3333mmm 0 V) n v z «firom00nonaoNnKOQKN:maoaovoknnnnmnnnnnnnr 00000 :68 o~oo~n0~nduud~n ~n0m0‘000000000000000 HTnoeoooooooo.o00.000.000.000.0000000000000 IIIIddHNNNNNMMMMMFM”~‘n”MMNMNMMMMMMMHMMMM o- IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII ’ AOSORF Z omewammomq-aooodfiovmommageg-oawmomnoc 0 00.43” :wemomucao:nmwummddownmmofioamdc‘skdsk H'Dooooo o cacaoooooooooooooooo.oo.0eon-coo... ht «N;mOONmKOdNJOMOQdNJmmQQOGOOHdNNMMJ:mmm a ddddv-INNNNNNNI'GV MMMMMMJJJ‘.’ 9:: 1- 9.1- ? r 1' z00Noh~~m0nnooaucw0m00~~n0:mmmww0080mmowmos Nwooucncoosunadnc0toso~se0nmnanowcwascuomdo HOOOOOOOOOOOOOICCOOOOO0.00.00.00.00000000. 04 «Naonammhausoo«nmounoo0n00«noodno0~;s0~ ta uuuu«~~~~nnnn:;:3mmmmoooosssscocoa C dNMQIhONOOOdNn“ NO HNM‘MMU‘W n “CO'Od fiddddsdfld NNN NNMngnm 3 -? Table 0.4 Cumulative Adsorption of Cadmium—-Fie1d Condition 168 ZQDQOKOO- WKNG‘ :QDNIM' "2000007: 036.9100 HMONO ”NB OMNIAU‘ U! DDFO HI! 0 «ammo "III 0 V‘NHQU (\O .70me.» Nu I v!" f O «u u 6'04" H .0000000000000000OOOOOOOOQOOOOOOOOOOOOOOO I-...| H lfiDanJWNU'Dv-‘NWJU‘U‘ (emu! QQO'OGOOdHHdNNfi-V '0") g.“ fiflfldv-IWNNNNNNNNNNNNNNN'I'JMWHWIVIWNIVIWJFIPI (.3 00 (I) C <1 2: '3‘: 0" QNIL MO “VFW: ova-«C‘Nov-cwamu «.140?th me tar-U If: 1' 1 0:06! me we 00dv-u'an .1 .1 a sum» 1000a0a~4¢3m®¢w¢o~uo¢o 0....0.0.0.000...00.0.0.0...OOIOOOOOQOI.O E.1 v-Iv-INNNNNNNNNNNNNNNMMMMMMMMMMIf.MMMMV’MMM u no C‘ In l0 2 egcdv0nnh”cowhcfi00mdd03H00w0hhhBKWWcHNOVM UL: cone-oaonmmvas 00001.:"00‘0 mOanmO'N3KO‘N3mC O N :4 H! 00000000000000...cocooooogoggogoogoggooo. h d4om°~¢wkwoadmn::m00~~h000000000000uad no «dduddNNNNNNNNNNNNNNNNNNNNMMMnnnHM U0 A050 ‘ UdbddmvwhONNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN 00 606°COQOQJQHdfidv-Ifiv-Iddddddddddddddfiddddflddfid rt00.0.00000.00.00.00ooooooOooooooooooogoogoo n a O V) Q q z 0:0:«0mkumohm:nnn0::«~bnu:«o~;¢mcooamsmnc 0006» O‘d3sl‘mcwl60‘350‘00‘05n0h NcmmNOH:I~0NmI~O‘q-4Nm@¢: Ht 00000.00coo-Ooooooooeooo.oooOooo oooooooo P d:900~Soboownn:moNs000000«««~~NNNMNNMM 3.5 ddddv-«HNNNNNNNNNNNNNMMMIQMMMMMEM'G'OMM U (I) D Q 2 comukNNO«ama~oommmmmmmmmmmmmmmmwnmmmmmm OD 000V)”HHNfiNNQQddNNNNNNNNNNNNNNNNNNNNNNNNNN Ht .0no.one.c000I...0000.00.00.000000000000O Eh UIIIII'I'IIIIIIIIIIIIIIIIIIIIIIIIIIIIIII M O m D d 2 GJUNO‘VIIRO‘NN 0'00 30.490510‘0 ’OHOIANOONQv-I ¢M fMQQJKT‘D 0 0050umfi8000300:8N0@:«e~¢~0dodms0no*oaNmoo HUG-.0000... coon-QQOQOOOQOO000.000.000.000o b! «:000~:mk@0d~n:tmoossoo¢0000dudddNNNNN O a«dud-INNNNNNNNNNNNNNNMF‘MNIPPMMMHMMn E) 0‘ V3 3.3 CO d 00°:ms0°m~4~3n0mnNNoooouo°on03«c00own00"kam QuasauoamomoeowsNoenancwououowuno:cco;~00.ra~ 04.0.0000... 0.000.000.0000.000.000.00.000... ID.) '4.OOanOo-IMOQfinOQQMmQOMMGQMU‘kBNIflNQMOOdM 8: duddNNNNnnnn:::3mmmmoooossssoocowo c «Nn:mohcoedwncmWN000«~ntwosgoeuNn as dd¢dddddd~~~~~~-~~nnnn nnn 169 0.2 .Adsorption Measurement Based on Freundlich Equation Table G.1 indicates that the amount of adsorptions in the Zn-clay column were 6.42 mg for the first 5 points (see Figure 4. ), excluding the zero value of adsorption. It was 39.36 mg for the re- maining measurements. 6.3 Flooding Condition Data of the flooding condition are shown in Tables 0.5 to 0.20. 0.4 DesorptiOn Data The leachate of the sludge columns were analyzed for both zinc and cadmium. The results are shown in Table G.21. The concentrations are the average of 5 values. The total zinc and cadmium content of the sludge columns may be calculated using the information furnished in Table 3.6, Table G.22. Sample Calculations Raw sludge - Cd (10 dry ton/ac)(2,000 lbs/ton)(454 gr/lb)(1 ac/43,560 ftz) (1 ft2/144 inz) - (22-n/4)(0.029 mg/g) = 0.132 170 Table 0.5 Flooding of the Sand Column with Cd Solution ggmgggggg 33%31123 “518339 C3888“ 132313833. mg “9 mg mg 60 0.569 279. 0.279 0.290 120 2.844 1,306.8 1.585 1.261 160 4.361 1,418.6 3.004 1.357 260 8.153 3,729.5 6.734 1.448 360 11.945 3,782.0 10.519 1.492 First 105 m1 had no Cd content and was discarded. Rate of the flow was measured to be 40 ml/min. Concentration of the Cd solution input was 37.92 mg/l. Table 0.6 Flooding of Glucose Column with Cd Solution ggmgggfigg mm: “21%? .3323. 23:31:33: mg pg mg mg 32 1.058 16 0.016 1.042 72 2.626 500 0.516 2.110 112 4.194 1,160 1.676 2.518 192 7.330 2,848 4.524 2.806 312 12.034 4,560 9.084 2.950 392 15.170 3,120 12.204 2.966 512 19.872 4,704 16.908 2.966 Rate of the flow was measured to be 40.37 ml/min. Concentration of the Cd solution input was 39.2 mg/l. 171 Table 0.7 Flooding of Tryptophane Column with Cd Solution j —i — Cumulative Cumulative Release Cumulative Cumulative Volume Applied Cd Applied of Cd Release Adsorption (m1) (m9) (pg) (mg) (mg) 5 .185 3.125 .003 .182 51 1.891 690.000 .693 1.198 111 4.116 1,925.100 2.618 1.498 171 6.341 2,150.100 4.768 1.573 282 10.457 4,035.405 8.804 1.653 392 14.535 4,010.600 12.814 1.721 530 19.652 5,045.970 17.860 1.792 722 26.772 7,059.84 24.920 1.852 957 35.486 8,664.45 33.585 1.901 1,147 42.531 7,025.25 40.610 1.921 Rate of the flow was measured to be 37.94 ml/min. Concentration of the Cd solution input was 37.08 mg/l. 172 Table 0.8 Flooding of Cellulose Column with Cd Solution ‘— Cumulative Cumulative Release Cumulative Cumulative Volume Applied Cd Applied of Cd Release Adsorption (m1) (mg) (pg) (m9) (m9) 5 .274 0 0 .274 87 3.406 1,234.4 1.234 2.172 167 6.538 2,712.4 3.947 2.591 287 11.236 4,502.4 8.449 2.787 367 14.368 3,047.6 11.497 2.871 487 19.066 4,594.8 16.092 2.974 687 26.896 7,716 23.808 3.088 767 30.028 3,101.6 26.909 3.119 887 34.726 4,664.8 31.574 3.152 1,313 51.412 3.152 Rate of the flow was measured to be 39.7 ml/min. Concentration of the Cd solution input was 39.15 mg/l. 173 Table 0.9 Flooding of Clay Column with Cd Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Cd Applied of Cd Release Adsorption (m1) (mg) (mg) (mg) (mg) 28 1.098 1.82 .002 1.096 65 2.548 124.505 .126 2.422 115 4.508 545.000 .671 3.837 165 6.468 872.500 1.544 4.924 225 8.820 1,367.400 2.911 5.909 265 10.388 1,090.200 4.001 6.387 324 12.701 1,692.120 5.693 7.008 374 14.661 1,456.750 7.150 7.511 441 17.287 1,988.560 9.139 8.148 509 19.953 2,089.640 11.228 8.725 654 25.637 4,646.525 15.875 9.762 814 31.909 5,250.400 21.125 10.784 982 38.494 5,567.520 26.693 11.801 1,182 46.334 6,764.000 33.457 12.877 1,347 52.802 5,763.450 39.220 13.582 1,565 61.348 7,730.280 46.951 14.397 1,825 71.540 9,275.500 56.226 15.314 2,009 78.753 6.587.200 62.813 15.940 2,247 88.082 8,550.150 71.363 16.719 2,577 101.018 11,908.050 83.271 17.747 3,263 127.910 24,960.110 108.128’ 19.782 3,718 145.746 16,748.550 124.809 20.937 4,300 168.560 21,792.990 146.544 22.016 4,860 190.512 21,277.200 167.695 22.817 5,560 217.952 26,747.000 194.291 23.661 Rate of the flow was measured to be 6.10 m1/min. Concentration of the Cd solution input was 39.2 mg/l. 174 Table G.10 Flooding of Clay -Glucose Column with Cd Solution Cumulative Release Cumulative Cumulative Cd Applied of Cd Release Adsorption (m1) (pg) (mg) (mg) 1.564 225. .225 1.339 4.223 669.8 .895 3.338 7.233 1,316.7 2.211 5.022 10.725 1,981.35 4.193 6.532 14.271 2,292.3 6.485 7.786 17.790 2,461.9 8.947 8.843 24.477 5,048.8 13.996 10.481 30.029 4,416.2 18.412 11.617 33.939 3,283. 21.695 12.244 39.804 5,037.75 26.733 13.071 43.127 2,902.75 29.635 13.492 46.451 2,950.8 32.586 13.865 49.970 3,183.75 35.770 14.200 55.248 4,864.7 40.635 14.613 60.527 4,953.8 45.589 14.938 68.269 7,359.7 52.948 15.321 84.886 15,992.75 68.941 15.945 90.751 5,686.5 74.627 16.124 118.004 26,628.9 101.256 16.748 128.756 10,532.5 111.789 16.967 156.908 27,576 139.365 17.543 165.119 8,086. 147.451 17.668 185.647 20,230.9 167.682 17.965 Rate of the flow was measured to be 7.07 ml/min. Concentration of the Cd solution input was 39.1 mg/l. 175 Table G.11 Flooding of Clayl-Tryptophane Column with Cd Solution Cumulative Release Cumulative Cumulative Cd Applied of Cd Release Adsorption (m1) (119) (mg) . (m9) .586 4. .004 .582 3.089 81.6 .086 3.003 5.904 354. .440 5.464 9.032 684 1.124 7.908 12.160 960 2.084 10.076 15.288 1,164 3.248 12.040 '21.270 2,595 5.843 15.427 26.236 2,559. 8.402 17.834 29.794 2,056.6 10.458 19.336 31.749 1,220. 11.678 20.071 33.704 1,302.5 12.981 20.723 35.659 1,354. 14.335 21.324 38.005 1,635. 15.970 22.035 41.524 2,551.5 18.521 23.003 45.747 3,309.7 21.831 23.916 50.204 3,701. 255532 24.672 61.934 10,207.5 35.739 26.195 66.900 4,429. 40.168 26.732 88.210 19,355.7 59.524 28.686 98.962 10,014.l 69.538 29.424 124.377 23,907. 93.445 30.932 132.588 7,783.6 101.229 31.359 152.138 18,625 119.854 32.284 Rate of the flow was measured to be 8.59 m1/min. Concentration of the Cd solution input was 39.1 mg/l. 176 Table 6.12 Flooding of Clay -Ce11ulose Column with Cd Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Cd Applied of Cd Release Adsorption (m1) (mg) (pg) (m9) (mg) 22 0.868 1.1 0.002 0.867 49 1.934 4.32 0.006 1.928 77 3.039 18.48 0.025 3.014 118 4.657 91.84 0.117 4.540 174 6.868 356.44 0.473 6.395 230 9.078 651.00 1.124 7.954 293 11.565 1,004.85 2.129 9.436 362 14.288 1,311.00 3.440 10.848 556 21.945 4,675.40 8.115 13.830 756 29.838 5,840.00 13.955 15.883 936 36.944 5,564.70 19.520 17.424 1,118 44.127 6,016.92 25.537 18.590 1,253 49.456 4,697.32 30.234 19.222 1,458 57.547 7,236.50 37.471 20.076 1,695 66.902 8,492.89 45.964 20.938 2,871 73.848 6,403.76 52.368 21.480 2,119 83.637 9,023.48 61.391 22.246 2,449 96.662 11,936.10 73.327 23.335 3,139 123.896 25,398.90 98.726 25.170 3,569 140.868 16,172.30 114.898 25.970 4,073 160.761 19,068.84 133.967 26.794 4,613 182.075 20,520.00 154.487 27.588 ‘5,413 213.651 30,600.00 185.087 28.564 Rate of the flow was measured to be 5.9 m1/min. Concentration of the Cd solution input was 39.47 mg/l. 177 Table G.13 Flooding of Sand with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (m9) (pg) (mg) (mg) 65 2.226 0.156 2.070 225 7.706 2.247 5.459 425 14.556 7.722 6.834 685 23.461 16.139 7.322 1,025 35.106 27.572 7.534 1,465 50.176 7.534 Rate of the flow was measured to be 40 m1/min. Concentration of the Zn solution input was 34.25 mg/l. Table 6.14 Flooding of Glucose Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (m9) (pg) (mg) (mg) 35.4 1.365 0.848 0.517 96.0 3.705 2.738 0.967 176.8 6.825 5.578 1.247 298. 11.505 9.898 1.607 378.9 14.625 12.778 1.847 443.5 17.121 15.007 2.114 637.5 24.609 21.938 2.671 799.2 30.849 27.874 2.975 1,041.7 40.209 36.994 3.215 1,162.9 44.889 41.614 3.275 Rate of the flow was measured to be 33.7 ml/min. Concentration of the Zn solution input was 38.6 mg/l. 178 Table G.15 Flooding of Tryptophane Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (m9) (pg) (mg) (mg) 55.6 2.145 0.324 1.821 96. 3.705 1.130 2.575 176.8 6.825 4.030 2.795 257.6 9.945 7.090 2.855 338.5 13.065 10.190 2.875 419.3 16.185 13.310 2.875 Rate of the flow was measured to be 40 m1/min. Concentration of the Zn solution input was 38.6 mg/l. Table 0.16 Flooding of Cellulose Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (mg) (pg) (mg) (mg) 65 2.226 5 0.005 2.221 225 7.706 1,336 1.341 6.365 425 14.556 4,460 5.801 8.755 685 23.461 7,767 13.568 9.893 1,025 35.106 11,092 24.660 10.446 1,465 50.176 14,905 39.565 10.611 Rate of the flow was measured to be 40 ml/min. Concentration of the Zn solution input was 34.25 mg/l. 179 Table G.17 Flooding of Clay Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (mg) (119) (m9) (mg) 24 .902 .002 .002 .900 46 1.730 .005 .007 1.723 67 2.519 .002 .009 2.510 71 2.670 .000 .009 2.661 95 3.572 .003 .012 3.560 128 4.813 .010 .022 4.791 180 6.768 .028 .050 6.718 274 10.302 .282 .332 9.970 370 13.912 .936 1.268 12.644 442 16.619 .936 2.204 14.415 706 26.546 6.442 8.646 17.900 715 28.764 1.510 10.156 18.608 816 30.682 1.387 11.543 19.139 876 32.938 1.680 13.223 19.715 948 35.645 2.074 15.297 20.348 1,027 38.615 2.370 17.667 20.948 1,097 41.247 2.128 19.795 21.452 1,315 49.444 6.976 26.771 22.673 1,438 54.069 4.034 30.805 23.264 1,517 57.039 2.528 33.333 23.706 1,603 60.273 2.786 36.119 24.154 2,298 86.405 23.908 60.027 26.378 2,356 88.586 2.042 62.069 26.517 2,580 97.008 7.885 69.954 27.054 2,762 103.851 6.479 76.433 27.418 Rate of the flow was measured to be 1.85 m1/min. Concentration of the Zn solution input was 37.5 mg/l. 180 Table 0.18 Flooding of Clay ~Glucose Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (m9) (119) (mg) (mg) 33 1.237 11.55 .011 1.226 57 2.137 6.72 .018 2.119 83 3.112 9.36 .028 3.084 88 3.3 1.95 .030 3.270 109 4.087 8.4 .038 4.049 139 5.212 26.7 .065 5.147 196 7.35 256.5 .321 7.029 266 9.975 742. 1.063 8.912 333 12.487 837.5 1.901 10.586 409 15.337 1,406. 3.307 12.030 616 23.1 5,212.26 8.519 14.581 668 25.05 1,309.36 9.828 15.222 716 26.85 1,315.68 11.144 15.706 769 28.837 1,472.34 12.616 16.221 833 31.237 1,848.96 14.465 16.772 903 33.862 2,022.3 16.488 17.374 966 36.225 1,913.31 18.401 17.824 1,169 43.837 6,390.44 24.791 19.046 1,282 48.075 3,682.67 28.474 19.601 1,352 50.7 2,281.3 30.755 19.945 1,431' 53.662 2,662.3 33.418 20.244 2,229 83.587 27,187.86 60.605 22.982 2,262 84.825 1,148.73 61.754 23.071 2,403 90.1125 5,013.96 66.768 23.344 2,513 94.237 3,911.6 70.680 23.557 Rate of the flow was measured to be 1.69 m1/min. Concentration of the Zn solution input was 37.5 mg/l. 181 Table G.19 Flooding of Clay Tryptophane Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Applied of Zn Release Adsorption (m1) (mg) (119) (mg) (mg) 25 .946 1.25 .001 .945 55 2.082 16.5 .018 2.064 105 3.974 87.5 .105 3.869 152 5.753 304.3 .410 5.343 202 7.646 455 .865 6.781 270 10.219 561 1.426 8.793 350 13.247 616 2.042 11.205 441 16.692 796 2.838 13.854 551 20.855 1,320 4.158 16.697 618 23.391 1,075 5.233 18.158 700 26.495 1,566 6.799 19.696 820 31.037 2,382 9.181 21.856 940 35.579 2,672 11.854 23.725 1.050 39.742 2,749 14.603 25.139 1,197 45.306 3,897 18.500 26.806 1,559 59.10 10,639 29.139 29.961 1,764 66.767 6,491 35.631 31.136 1,968 74.489 6,676 42.307 32.182 2,213 83.762 8,240 50.547 33.215 2,578 97.577 12,472 63.019 34.558 Rate of the flow was measured to be 2.91 m1/min. Concentration of the Zn solution input was 37.85 mg/l. 182 Table G.20 Flooding of Clay'-Cellulose Column with Zn Solution Cumulative Cumulative Release Cumulative Cumulative Volume Applied Zn Ayplied of Zn Release Adsorption (m1) (mg) (119) (mg) (mg) 58 2.03 1.45 .001 2.029 98 3.43 3.00 .004 3.426 223 7.805 12.50 .017 7.788 363 12.705 252.00 .269 12.436 448 15.680 488.75 .758 14.922 550 19.250 1,020.00 1.778 17.472 703 24.605 2,195.55 3.973 20.632 833 29.155 2,601.95 6.575 22.580 963 33.705 3,250.00 9.825 23.880 1,133 39.655 4,816.95 14.642 25.013 1,540 53.900 12,617.00 27.259 26.641 1,765 61.775 7,275.00 34.534 27.241 1,981 69.335 7,128.00 41.662 27.673 2,253 78.855 9,065.76 50.728 28.127 2,657 92.995 13,600.66 64.335 28.660 Rate of the flow was measured to be 3.00 ml/min. Concentration of the Zn solution input was 35.0 mg/l. Desorption of Zinc from the Raw and Digested Sludges Table 6.21 183 P o 1.1 ‘ O (IIf’IC‘CICfiNhI'NNF \f'r-DFWNVNCMI-J—orali‘Il h—INC‘J(\|U OWN CIR o—UUN p... (In N‘ut’\fl‘"~ (T n 05 o Purified—on PARC! rut-1r naarrfl‘snf mun-o m~r~~a¢masax N..-¢r--c;‘ knuna hn (.m’. ODI.ICC..L-C*CJC1C.C’;Ou-u-¢v-4(\saifir~ C' m—«wmtmhmc c-onlh‘au-shhd rr-oc..-r\1n1r\1mr' #6 OLJ_looooeoooo000000IoocooIooooooooooooo0.00.0000o O IoIOC3C- HHc—v—o-tv-‘c-QCVCVO'fvruh f‘quO'n-N‘TV‘mFIN-hvk‘r" I". 0 tr . ‘ P C .BJla L‘JJUlL‘C-(‘C‘N u1u‘-ou-r~')r\r~d'c:>a erect-u. «214.6 \.' Q'J \1 UIC\.L.J* I" 0.1- C'LT‘QQQDHULtF‘C‘uO-NO‘MQ baLr.V.(\.Iv-T‘J\LQ'C.U L. V‘C‘F’tHC‘C C-'C1‘U‘U D7Q‘OC‘.F\OOC’JCJCIC‘CIDCJHHI—‘Hv—Io—Hv—L‘Hv—HHHHCCDC’L-C '3 Dr—Jooooeooooooooooooocooocoooooooooo .J‘nln'C'DCI N§NNCMr¢F~CHIs Hu' aJccerw-uut. (.VH QHLCLC—gJCd Cut:- 0 o e o o o o o o o o C rr C) [,1 o II-EL: (1' 3V: r"..~‘:r~c.r~'~c~1r1rr~.—u~-:ut'-c\:m:r,1~r=cm~uar~r~w c.rv~nor~'11\u c LuUd n-co‘-mmt~oco¢\nmr~~¢\olr1¢<:rmrnaooanmu 3356-015) L' L. n'db‘ir‘c..:r.finm awl‘ .‘T-CJHQII'36 1:.uiNu.1'.xoc.v-4w(ycuz-')Mcc we); 00.00.000.0000000000ooooooooooooo DLLu Hv—HHu-n—u-«NNGIC‘CKRNCutqurfn-mnrfih'.h'zfi'mn0r‘. 0.10’ o o o 0 III 0 0'. coccacomacucumrxcxsmc.mhmmnmsctsrsnmtsrmnno OLUQ GLT-U‘m‘Jnl—lr'.'.5€L'.C-.1L.'TU:N 1“)me CHOW) O mU‘UQNLD'fJLuu-nsfiv-t .OLL; HHHHHPHHOc—HHNHHCQUUCGDDHQOUOC LOGC o_j_1 000000000000.0.0000000000000000on o b! 0 Cr ' l.)-coo.coooncoo.00.000000000000000.ooooooooonooo 5’ 51hh‘t‘1000r—‘Ntfirc cut (.23 C-C NN'D'JOfNN ‘Jo—Hn—h—tu L.‘ \f'H\r U3"? OCL.‘ FIP’v-év-NCJ¢NNCJCXCCCJv-‘CJNI-‘i'JC‘JI—‘HHHHHP- c-u- v—c—w—tv-«Hv—IOL-c..v-4€ 00 0.1.1 O...0.0.0.0...OCOQOCOOOOOIO00.0.....0... 0 NJ 9 h 184 9 V a Q. Q. . = E H: O I EU 0 5 e 9 ”NEIL O 9 ‘ 9.! half 0 X 0 I IXHV = 0 o 0 L Q 1 Q I I DE :5 s I O a I NR 9H 2 0 9 3 h UECT I I S o I 9 I EPN 3 Y I 0 0 E 9 PROD 6 8 5 X 0 9 F 9 F E I 1 2 s . 2 9 O M Z L O H o 9 a 9 .2, I9... C. 0 S 5 C O 9 o HXVL c T 1 I 6 I 1.. I I TGIA 9 I X I I 0 I 9 9 CU" I 0 Y 6 O I I X I I HLOOII 7 G s ' . ’ 2 S O . 0 E0 9 I 0 .. I 9 6 9 I R 9 L =N 3 9 2 Q Y 9 o . a 9 L50 4 9 S S O C 1 O 9 9 0V .9. I 9 O I 2 H. c K I S v» I F W G 9 T 3 I 3 I Q X 1 5 9 S G 9 9 X 9 0 G S S I 1 9 OCE G a o ‘ s x N G 1, w x 9 0 L60. 9 5 E G K k B A G II S 2 9 UOND. I I I I I. I o V93 5 I I CLAO 3 I I C S I N 0 9 S9 1 I 5 H TF H I I I I B I X Z I 2091 I T F E F5 I 5 I L AI II S G 9901 X P 9 S AOBI L I c I I? IX H H O IZSF S 0 I 0 T UL E L I5 0 2 9 550 9. T L I0 1 9 u S 9 A585 CG 3 F/ 5 3A 9: 9 9 0 A I. IX 0 / 9 u CT G CC 9 II I :K 020 X B I II!“ 9 I 9 L 06v, IA I I L ZI 113 s ‘ 6’s 9 o I e L RLNATI I .4 5 E 80 PVC 9 F I 9I II 3I0 n E UPI/I3T I SI 0 0 I 935 Y 0 I 6013 I09 I ¢ ’0 8C3hc CLI- C I U H ‘ 6 x c. 3 x 9" KKI O I CC x T “RGfiIA 05 I C 9 3 9 9 611 I N CI IIYT I03 5 N UF 0VIG9 1+ I G 0 9 b A 9IY S 0 KSIGLSF 13/I 9 Z PIESAHCCL 1 I k. V = X 38 K 2Y5 H I I ICE 9 I I/IIIZ I KOIO9E 03 I A 3 0 s a I Is: 9 T LCCGCIX VIIIFO R UEAA=IIC TI w . S 9 h 4 G 6 0 9 R EKKIIIfl SIY055 0 OF.” c I3A I L L 3 H 8 G F s x 0 CIIOOXIS C X5 90.? F 95 F I49 5 05 II S 2 2 I 0 G 9I3 9 P IGL11341 ISJOCI 9' DOD—DIG I 55. 53LG s L OI IT I XXI I. 106556 I II II13CQ I UOL NITA 1 II 915V 0 = m L ILI 85X I L9IGCOOIX X5I/99 9 PTURACC 9 = 92 1CGA T 1 II 306:.A I :5 Z ESGIILLYTO $1X01 9 9 N 05 I 99.9 I II a IVI 3 H1135 CG 0K I18 I C3002AXIT .85 98 I 0 IS" {IIA I 1L JI‘J o = 5B. I I AIAAI t I3 c ILIIIII IBIzaA I II 0553 II I 15 9.2/5 6 Q I IAA I3K/L XI K RQAGGIIS 90 Y. .I Il x H TERI 4C.) II19 IICG 3 XIKK C3I1... .o SY H 0..IOOOO 926 X019 1 9 0 CHIBOLIflo IZoI JCGOO : 0=IICAocSC I05 2 FCILLSSCII IIYIAX 2 IA RASA90 L9017I9V99 3 3 9A0 AIT0=9 T2: 9 K1AA11K.3ESOXIAD99 LR 09 T1 S5EI9CIAOO 9 JKD I/GAI9 AY3 O a YOIII9$3U93IY929U FGoSTNNHF IF9L1I1=s= = 1 AA1b99A HXIBi 92X11XY3 9N0/SSi/9 OHOH0097 95IS:9IIIIE EZIIOI9BBA1KTERIX19 ulIIISSloQIolII1/9I HRRA/II?I OI1ILDCLLLW U81I4132=KSIN00351I 91$XY @1IET0I=.1I9I APE BSSlT III: 1I999 N: T BBIII:LINF== T 9 :SS T9N3Y10 T T :4 HDINN A ALLO =KKKIII1TAO:=IAF15RI 13TAI9 01....SSTACOISFSTATA GS I:EEDW DHSSZDCIIIT9T3NHDI3KKISCPT YYNHI90V1111NHKC:=51NHNH OI LHHHARIAQIG AGGCCNKN IR BBII N XXIRQ. XIIIIIRI IIOIIRIRD RHSO/IIEO .. :.0FV0.LVG..J.UO : 0 9.0 I G 0 IIROS4 IXYXYPAUF 3ACYJ..OD..0N PTISXUDRFKRFIADEAGAACKC PF CC C SSPFI: SSSSSPFI BACfiPFPFE 9 20 1.0 01 0 Q 3 Z 1 9 7 1 12 00 1 #9 1 1 15 1 9 1 11 1 1 1 11 1 9 1 9 0000 C 9 185 Tab1e 6.22 Total Zinc and Cadmium in Sludges Sludge Zn Cd Raw 30.873 0.132 Digested 22.970 0.064 APPENDIX H STATISTICAL ANALYSIS Program STATl was written in Fortran language and is used in CDC6500 computer. Inputing the data obtained for each adsorption column throughout the field condition study, the program then, compute and print the following: (i) the cumulative adsorption by each individual clay and clay-organic column; (ii) the average adsorp- tion for each set of 5 columns; and (iii) the standard deviation of each average value. A copy of this program is included in this appendix. H.l Statistical Analysis for Table 4.3 The F test, F = (S12)/(Szz), was performed to determine whether or not the variables, or the standard deviations, s, are significantly different from each other. The comparison was made to the standard deviation of the clay columns, Table H.l. Table H.l Standard Deviation of the Total Adsorption by the Clay and Clay-Organic Adsorbents--Field Condition* Cation C CG CT CCel Zn 2.13 0.94 0.53 0.2 Cd 0.79 0.58 0.87 0.78 *Values are all in mg. 186 l87 Table H.2 shows the values of ($12)/(322), where 51 and 52 are chosen to obtain a ratio of greater than one (see Table 4.5 for the standard deviations). Table H.2 Variance Analysis--Ratio of (S12)/(Szz) Cation C CT CG CCel Zn l 16.15 5.l3 ll3.4 Cd l 1.21 1.85 l.02 The F value, for 4 and 4 degrees of freedom, was obtained from the F test table* and is found to be 6.39. Since all the ratios reported for Cadmium, in Table H.l are less than 6.39, therefore, the standard deviations are not significantly different. For the zinc columns, however, they are significantly different from the value reported for the clay columns. H.l.l Student t Statistics Using the famous Student t test for the equality of means of two set of data having the same standard deviation, 5, the cadmium results were tested. Table H.3 expresses the result where the average values are obtained from Table 4.3. “£sz _'32__ , n1+n2 s n1 + n - 2 d.f. *CRC Mathematics Handbook. 188 Table H.3 Student t Analysis for the Cadmium Average “323:?" t ”83:22.? v (mg) CG 31.43 2.6l 8 2.3l (95%) CT 33.68 2.l 8 l.86 (90%) CCel 33.l5 0.98 8 0.71 (60%) t* = t Statistic from statistical tables Therefore, the means are different from the Cd-clay adsorption by the probabilities equal or exceeding the values that are shown in the parentheses (see Table H.3). H.l.2 Student t Test for the Zinc Data Since the variances are different from each other, the following statistical analysis was used. Table H.4 expresses the results where the average values are obtained from Table 4.3. If} ”Y - 2' + 2df t— n1n2- 99 n1+n2-2 n1 n2 189 Table H.4 Comparison of the Means for the Zinc Data Average A3332?" t 0:32:33...“ v (mg) CG 4l.83 4.02 8 3.355 (99%) CT 50.81 4.83 8 3.355 (99%) CCel 46.53 0.784 8 0.7l (60%) t* = t Statistic from statistical tables Study of Table H.4 indicates that the means of the zinc clay-organic columns are different from the Zn-clay adsorption by the probabilities equal or exceeding the values that are shown in the parentheses (see Table H.4). H.2 Statistical Analysis for Table 4.9 The adsorption results obtained for organic columns (e.g., for G: 61,62 . . . GS) were added to the adsorption results obtained for the clay columns (i.e., C1, C2 . . . C5) in a random fashion such that G1 was added to C], G2 to C2, and so on. The standard deviations of the products (i.e., for the 5 points) were found, Table H.5, utilizing the computer program STATl. To test whether or not the standard deviations of the clay + organic columns, found in Table H.5 are significantly different from those of the clay organic columns, reported in Table H.l, Table H.6 was constructed. 190 Table H.5 Standard Deviation of Clay + Organic Columns (mg). Field Condition Cation C CG CT CCel Zn 2.13 2.23 2.40 1.91 Cd 0.79 0.68 0.74 0.69 Table H.6 Variance Ratios (S12)/(522) (S1 > 52) Cation CG CT Ccel Zn 5.63 20.51 91.20 Cd 1.37 1.38 1.28 "The F value for 4 and 4 degrees 0f freedom (5 ' 1 = 4 for 512’ and 5 - 1 = 4 for $22) was found using a F statistical table to be 6.39. Therefore, it is concluded that the standard deviations of the clay + organic columns and clay-organic columns were not significantly different from each other for cadmium columns, also the CG column of the zinc columns. They are different for the CT and CCel columns of the zinc applied columns. H.2.1 Student t Analysis The same method of analysis as was described in section H.l of this appendix was used for the cadmium data, also for the CG column of the zinc columns, Table H.7 and H.8. 191 Table H.7 Student t Analysis of Cd Data Clay + Clay - AVG Adsorbent Cation Organic Organic S t d.f.* t** (mg) (mg) (mg) CG Cd 32.80 31.43 0.63 3.44 8 3.35 (99%) CT Cd <32.80 33.68 0.81 1.72 8 1.63 (85%) (I) Cce1 Cd 36.36 33.15 0.74 6.86 3.35 (99%) * degrees of freedom = n1+n2-2 = 5+5-2=8 **t* = t statistic from statistical tab1es Therefore, the values are different from each other by the probabilities equal or exceeding the values that are shown in the parentheses, see Table H7 and H8. Table H.8 Student t Analysis of Zn Data Clay + Clay - Adsorbent Cation Organic Organic t d.f.* t** (m9) (m9) CG Zn 46.49 41.83 4.63 8 3.35 (99%) CT Zn 42.75 50.81 7.33 8 3.55 (99%) CCe1 Zn 50.76 46.53 6.09 8 3.55 (99%) * d.f. = degrees of freedom **t* = t statistic from statistical table 192 STAT1 pROGRAH I I5 SI IL 7 5. IC 0C 5 I I‘I TC.D UDI FAG .1 IC UI 9 071 I It) TSI UIT FAG N I I III (55 III TLC Asc T SNN 00 1.1:. ASS RNN C12... «U I r? I , I 5 ( L s I I Q 1 I 1. 1L as 0 II I?- I 5 03 90 TI 16 I L :I 5 05 J9 I GO I9 1 II I9 = 92 L9 I 1I I9 I 1].— Jo I ISTIE L 901.: IL SEC—ILO I IF IL 11 IKaISD I OIIIZDA ITI = AI ALLOEF I A IAVGSL-AIJAyLII To 20 999.)12 22 JA)=0.085¢ 009 I5 50 9L 5 O K CI( 5 3090 6: E: J ILCBUnu 1...». 15 903NJLUU EU 91.“ AI h_HQ.rJnURI.LJJA OHM. 1ARIG D..I.I= .20—f4 PDDKFFIL 20 1.. u = .. I I ATIFF JJII I p... N 0T3KIIIOI TNIIIT 6.79793- : JJ 00 : NN o CNNK N:T.:I AALOI OAUODOO = 009.. .. JF E 315 JJCNI 1 9 CCA 100 I 0.“.AAI T I.’ IJ III-J O : JJ I GBJJI IJ 9 I I : + IOIIOI GIJDCCATT. G DACCKGCJCJI TGC 3 12 2 12 1 ad 32 1 1 a 1. 111 a 5 : = :3 43.. p. 3 CCELIJJI=CEL I9 0 95 I TTlUVVA99TCT CELISII/500 IRIICTISII/590 IHIICGISII’590 LI3I‘CCELIQI9C TGC. I3I+C (3I+C ZI+GC TGI I I... IIc 220 III TGI CI II III.— 115 IIC TGC CCI II: :35 C C L NA NAAL INOITG...T.TM:VSDFQFQFQIAQO :T AMT-A PWQTTCCCNNQIH .. P0 N F03 GC 0 9 1 AVGCT,5X,5HAVGCG,5X, AUG 5 CCEL §X95H CTAVchcAV 920X97X, C 2 Z. 1. 1I G u 5 0' 1 1 TA .1 91 9 L ’— 7.0—L. 0‘ 0! GO TaT9IC I I6 . OGOGVI GVGVAA IAIALI GTGGSI VCVAUCL A.A.CE TIGI CC LSPUACAQC 3090 0 : ETEGIL SA 9nd .AVA :- : IIIIIIC & IG AIAIIQ 1LOZ.JT?AGLS I. ESIIQIQp‘ —. I1EGGV28IC:1ISGSCLE. IIRI. 1‘ AGGOITIGICNTPRS T. CIIO HC 9 2 Q: 3.RF7Q PF 95 11“ 115 112 1 WORKING T0 HER59999999999‘I I L E. C S H 4* 9 x 6 I G S H 2 , VA 8 I T S S H I 2 IL N var-I A 805 R I g9 G flu In 0 9 GI R nu. XSF PII/ 23 OGGL II III.‘ xsx 9““0 3 o J/IQ 2 2 I65 I I JnEUI A 1. 55.1011 a u .. Fv : c.5UIvaIOZ IZI T ISISISTHSS-..N M. Na. NR = .. :IRIRD 30TGCD.0RON CFSSSPFPFE 1 Z I 1. 2 APPENDIX I FIT OF FREUNDLICH EQUATION The computer program FLICH is written in Fortran language and was used to find the least square line parameters, correlation coefficients of the fit of the data to a straight line, and also to plot the scattered diagrams. A typical scattered diagram was shown in Figure 4.7. Other scattered diagrams are shown in Figures 1.1 to 1.9. 193 194 Figure 1.1 Freundlich Equation fitting for Zn-Ce] 19S O¢.o AJHow\4muucog ouwb oouo om.mw 0*.mw om.pw 00.3w oo.wn ON.~JU x ..u 0 x 0 To z x 0 x x x 1W X X .7 X 0 x“ xxx ID x x o0. xxuI I0 mu 0 00‘1 (N/XlOOW 196 Figure 1.2 Freundlich Equation fitting for Zn-CG 197 ov.o H4H0m\ou.oog no.0 oc.oa 09.0: o~.~u om.~n oo.un ov.~| om.ua. - b b p p b p 0 x w 0 3830803 35 + 26 a 2:303 un.u a nu 38.0.3884 and + and- u 2,5384 1% 0 0 10 r 0 :0 r 0 I0 y 0 (N/X1001 198 Figure 1.3 Freundlich Equation fitting for Zn-CT 199 00.0 A4H0w\p00004 P 0¢.0I 00.0: 0N.«I 00.~| 00.NI 0*.NI 00.Nl L p p L i-l _ 0N.0| X AAHOm\auvoog om.o - -.~- u X AAHOm\HuVooq 0m.o + o¢.o u Az\xvoog Az\xvooq OEV'I 1 02'1- fl 08'0- I 07'0- (N/XJOOW I 00'0 or?) 200 Figure 1.4 Freundlich Equation fitting for Zn-Ciay Ceiiuiose 201 A0_ow\0.004 o~.o- .om.c- om.c- om.w- o>.w. o_.~- om.~- 00.N AAHOm\uVuog q¢.o + mm.o u Az\xvoog AaHom\uvuoa e~.o + m~.o u Az\xvuoq ov~o-' 0+: 0030 02-0- (N/XJODW I 02°C 09’0 r 09'0 202 Figure 1.5 Freundlich Equation fitting for Cd-Ce] 203 0v.0 .4000\4m00004 o~.o oo.o o~.mn o..mu om.m- oo.o- b p F OD.~I _ 0N.~I oz’o (N/XJOOW I OV'O 02'0 00'0 09'0 09'0 204 Figure 1.6 Freundiich Equation fitting for Cd Clay 205 7200\0 000.. B79: 00.0.: 00.:0p: 004w: 004w: 07—h. 00$»: 00.7..u 3838qu 8.0 + 3.0 n 3,538.— N. / ,o x m 00 x mg: I 0 m / X null Fun 383803 8.0 + 2.0 u 9:303 0:. Lu 9 0 :0 m. 0 206 Figure 1.7 Freundiich Equation fitting for Cd-CG 207 ”4000\000004 oo.o o..o oo.o o..m- . om.m- o~.w- om.~- oo.m- ov.m- b p |P I 112'! 08'0- 09'0- AaHom\uovoog mm.o + ae.o n Az\xvooq I 00'0 07'0 j 08'0 (N/X1001 208 Figure 1.8 Freundlich Equation fitting for Cd-CT 209 00.0 0w.0 ”4000\H00004 8.0 2;... 85... 8. 0... 8.7 8.? 9.. .. b P b x: 02‘1- l x: 138'!)- ord- [N/XJOO'I AAH0m\Huvooq mm.o + mm.o n Az\xvuoa 07‘0 00'0 08'0 210 Figure 1.9 Freundlich Equation fitting for Cd ieached Clay-Cellulose 2H A4000\00004 00.0 0*.0: 00.0: 00.0: 00._: 00.0: 0v.~: 00..:. p P p p b P F o w. 0 . :0 no 0 AAHOm\uVoog «o.o + om.o n Az\xvooq f0 .x mu A4H0m\uvuog mH.o + m~.o : Az\xvoog numw m VA .nu/I menu 0‘ 10 w. 0 09'0 REFERENCES 10. ll. 12. REFERENCES Wastewater Engineering Collection, Treatment, Disposal. Metcalf & Eddy Inc., McGraw-HillfiBook Company, New York, N.Y., 575, 1972. Process Design Manual for Sludge Treatment and Disposal. EPA 625/1-74-006, 2-l3, Oct. 1974. Taylor, S. A., and Ashcroft, G. L., "Physical Edaphalogy," 95-151, w. H. Freeman & Company, 1972. Klein, L. A., Lang, M., Nash, N., and Kirschner, S. L., "Sources of Metal in New York City Hastewater," JWPCF, No. 12, 2653- 2662, 1974. Dugan, P., and Fisher, P., "Implication of Microbial Polymer Synthesis in Waste Treatment and Lake Eutrophication." In "Advances in Water Pollution Research," S. H. Jenkins (Ed.), Proc. 5th Int. Conf. Water Poll. Research, Pergamon Press, Ltd., London, 1971. Cheng, H. M., Ptherson, J. N., and Minear, R. A., "Heavy Metal Uptake by Activated Sludge," JWPCF, 37, No. 2, 362-376, 1975. Argo, D. 6., and Culp, G. L., "Heavy Metal Removal in Nastewater Treatment Processes: Part 1," Water & Sewage Works, 119, 8, 62-65, 1972. Scott, J. D., "The Thermodynamics of the Removal of Heavy Metals from Wastewater and Sludge," M.S. Thesis, Michigan State University, East Lansing, Unpublished, 1-16, 1976. Neufeld, R. D., and Hermann, E. R., "Heavy Metals Removal by Acclimated Activated Sludge," JNPCF, 51, 310-329, 1975. Reid, 6., et al., "Effects of Metallic Ions on Biological Waste Treatment Processes," Water & Sewage Works, 115, 320, 1968. Erickson, A. E., "Soil Management for Hastewater Disposal." In Conference Proceedings in Land Disposal of Wastewater Conf. Proc., Michigan State University, 14-19, Dec. 6-7, 1972. Environmental Pollution Control Alternatives: Municipal Nastewater. EPA Technology Transfer, EPA 625/5-76-012, 1976. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. Ikeda, 1., "Experimental Study on Treatment of Night Soil by the Wet Air Oxidation Process," Water Research, 6, 8, 967-979. Wastewater Sludge Utilization and Disposal Costs. EPA 430/9-75-015 Sept. 1975. Reed, C. H., "Equipments for Incorporating Sewage Sludges into the Soil," Compost Sci., 1g, 4, 31, 1974. Struble, R. G., "Sewage Sludge Aids for Crops in West Chester, Pennsylvania," Compost Sci., 15, 2, 20, 1974. Edmisten, J. A., "Agricultural Utilization of Digested Sludges from the City of Petiecola," Proc. Natl. Conf. on "Municipal Sludge Management," Information Trade, Inc., Washington, D.C., 177, 974. Hatcher, C. L., "Virginia City Uses Liquid Sludge to Grow Crops," Compost Sci., l§, l, 18, 1974. Manson, R. C., and Merritt, C. A., "Land Application of Liquid Municipal Wastewater Sludges," JWPCF, 41, 20, 1975. Lindsay, W. L., "Inorganic Reactions of Sewage Wastes with Soil," In Proceeding of the Joint Conf. on Recycling Municipal Sludges and Effluents on Land, 91-93, July 9-13, 1973. "Reaction of Heavy MetaTS with Soils with Special Regard to Their Application in Sewage Wastes," Dept. of Arm , Corps of Engineers, under contract No. DACW 73-73-C-0026, 70 pp., 1972. Chaney, R. L., "Crop and Food Chain Effects of Toxic Elements in Sludges and Effluents," In Proceeding on the Joint Conf. on Recycling Municipal Sludges and Effluents on Land. EPA/USDA/ Nat'l Assoc. of State Universities and Land Grant Colleges, Champaign, 111., 129-141, July 9-13, 1973. Page, A. L., "Fate and Effects of Trace Elements in Sewage Sludge When Applied to Agricultural Lands," A Literature Review Study, U.S. EPA-670/2-74-005, 1974. Garrigan, G. A., "Land Application Guidelines for Sludges Contaminated with Toxic Elements," JWPCF, 42, 12, 2380-89, 1977. Kirkham, M. 8., "Organic Matter and Heavy Metal Uptake," Compost §g1,, 18, 18-21, 1977. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. Levenspiel, 0., Chemical Reaction Engineering, 2nd ed., John Wiley & Sons Inc., New York, N.Y., 3-18, 1972. Riffaldi, R., and Levi-Menzi, R., "Adsorption and Desorption of Cd on Humic Acid Fraction of Soils," Water, Air, and Soil P011. J., 5, 179-184, 1975. Esminger, C. E., and Gieseking, J. E., "The Adsorption of Proteins by Montmorillonitic Clays,” Soil Sci., 48, 1939. "The Adsorption of Proteins by Montmorrilonitic Clays and Its Effect on Base-Exchange Capacity," Soil Sci., 54, 125-132, 1941. Smith, J. E., Jr., "Ultimate Disposal of Sludge," Technical Seminar/Workshop_on Activated Waste Treatment, Chapel Hill, N.C., Feb. 9-10, 1971. Gould, M. S., and Genete11i, E. J., "Heavy Metal Distribution in Anaerobically Digested Sludge," Proc. 30th Ind. Waste Conf., Purdue University Ext. Ser. 30, 692, 1975. Leeuwenhoek, A. V. "Experiment on the Microbiology of Cellulose Decomposition in a Municipal Sewage Treatment Plant," g, Microbiol. Serol., 29, 185, 1954. Edberg, N., and Hofsten, B. V. "Cellulose Degradation in Wastewater Treatment," JWPCF, 41, No. 5, 1012-1020, 1975. Pearson, A., and Dugan, P., "Production of Extracellular Polysac- charide Matrix by Zoogloea Rumigera," Appl. Microbiol., 24, 657, 1971. Painter, H. A., and Viney, M., "Composition of a Domestic Sewage," J. of Biochem. & Microbiol. Tech. & Eng., 1, 143, 1959. Vascen, V. A., "Protein from Wastewater a Source of Food," Water & Waste Eng., 38-39, 1976. Sank, R. L., and Asano, T., Land Treatment and Disposal of Municipal and Industrial Wastewater, Ann Arbor Science Publishers Inc., 26, 1976. Ellis, B. G., "Sewage Wastewaters--Characteristics," In the North-Central Regional Conf. Workshop on the Utilization of Wastewater Treatment Products on Land, Michigan State University, 6, Sept. 24-26, 1974. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. Salotto, B. V., Grossman, E., and Farrell, J. B., "Elemental Analysis of Wastewater Sludges from 33 Wastewater Treatment Plants in the U.S.," Presented at Research Symposium on Pretreatment and Ultimate Disposal of Wastewater Solids sponsored by U.S. EPA and Rutgers Univ., May 21-22, 1974. Dick, R. A., "Sludge Treatment." In Physiochemical Processes for Water Quality Control, W. J. Weber, Jr._1Ed.), Wiley- Interscience, 533-596, 1972. Dotson, G. K., "Constraints to Spreading Sewage Sludge on Crop Land," EPA-NERC, Cincinnati, AWT, May 31, 1973. Weber, W. J., Jr., Physjochemical Processes for Water Quality Control, Wiley-Interscience, N.Y., 1972. Wentink, G. R., and Etzel, J. E., "Removal of Metal Ions by Soil," JWPCF, 44, 1561-1564, 1972. Berger, K. C., Sun, Soil and Survival, Univ. of Oklahoma Press, Norman, 281-285, 1972. Private communication with Dr. 8. Ellis, Prof., Dept. of Crop and Soil Sciences, Michigan State Univ., 1976. Fair, G. M., Gair, J. C., and Okun, D. A., E1ements of Water Supply and Wastewater Disposal, 2nd Ed., John Wiley & Sons Inc., N.Y., 1971. Lahav, N., and Hochberg, M., "Kinetics of Fixation of Iron and Zinc as Fe DDHA, Fe EDTA, and Zn EDTA in the Soil," Soil Sci. Soc. Amer. Proc., 49, 55-63, 1975. Grand Rapids Wastewater Treatment Plant, 1975-76 Manual. Standard Method for the Examination of Water and Wastewater, prepared and pub1ished jointly by: AWWS, WPCF, and AWHA, 14th Ed., 1975. Krauskapf, K. 8., "Lead, Mercury, and Cadmium as Environmental Contaminants." In Micronutrients in Agriculture, J. J. Mortvedt et a1. (Edsf), Soil Sci. Society of America, Inc., Madison, Wis., 593-628, 1973. Likens, G. E., "Acid Precipitation," Chemical and Engineering News, 29-44, Nov. 22, 1976. Nordel, E., Water Treatment for Industrial and Other Uses, Reinhold Book Corp., N.Y., pp. 14, 1968. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. Fisher, R. B., Quantitative Chemical Analysis, W. B. Saunders Co., Philadelphia, PD. 88, 1961. Kue, S., and Lotse, E. G., "Kinetics of Phosphate Adsorption and Desorption by Lake Sediments," Soil Sci. Soc. Amer. Proc., 38, 50—54, 1974. Bond, H. B., et a1., "Some Effects of Cadmium on Conferous Forest Soil and Litter Microorganisms,“ Soil Sci., 124, 278-287, 1976. Carpenter, W. L., and Owens, E. L., ”Biochemical Oxidation Characteristics of Ce11ulosic Fibers in Aqueous Suspension and in the Soil," National Council Tech. Bu11., No. 224, 1-17, Dec. 1968. Meyer, R. C., "Studies on the Ce1lulose Digesting Cytophaga of the Soil," Dissertation Abstract, 223, 2152, 1962. Alexander, M., Introduction to Soil Microbiology," John Wiley & Sons Inc., N.Y., 150-154, 1961. Huang, C. P., "Adsorption of Tryptophane onto Calcium Carbonate Surface," Environmental Letters, 9, No. 1, 7-17, 1975. Grant, J., Cellulose Pulp and Allied Products, Leonard Hill Book Ltd., London, 3rd Ed., 37-60, 1958. Huang, C. P., Elliott, H. A., Ashmead, R. M., "Interfacial Reactions and the Fate of Heavy Metals in Soil-Water-Systems," JWPCF, 42, 745-756, 1977. Khattak, A. S., "Mechanical Behavior of Fibrous Organic Soils," Ph.D. Thesis, Department of Civil and Sanitary Engineering, Michigan State Univ., Unpublished, 1978.