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Engineering Properties and Cone Penetration Testing of Municipal Solid Waste to Predict Landfill Settlement

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Title:
Engineering Properties and Cone Penetration Testing of Municipal Solid Waste to Predict Landfill Settlement
Creator:
MCKNIGHT, TOBIN S. ( Author, Primary )
Copyright Date:
2008

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Subjects / Keywords:
Compressibility ( jstor )
Landfills ( jstor )
Methane ( jstor )
Moisture content ( jstor )
Silts ( jstor )
Sleeves ( jstor )
Soils ( jstor )
Volume ( jstor )
Waste paper ( jstor )
Wax paper ( jstor )

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University of Florida
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University of Florida
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Copyright Tobin S. Mcknight. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
5/31/2007
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436098126 ( OCLC )

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ENGINEERING PROPERTIES AND CONE PENETRATION TESTING OF MUNICIPAL SOLID WASTE TO PREDICT LANDFILL SETTLEMENT By TOBIN S. MCKNIGHT A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ENGINEERING UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Tobin S. McKnight

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iii ACKNOWLEDGMENTS First, I would like to tha nk my committee, Drs. Timot hy G. Townsend, Michael D. Annable, and Frank C. Townsend, for their review and comments on this thesis. I especially want to thank my advisor, Dr . Tim Townsend, for the opportunity to work on many interesting research projects. His tirel ess drive and motivation have inspired me, and his support during this res earch has been remarkable. I am deeply indebted to Aaron Jorda n, Matt Farfour, and Sreeram Jonnalagadda from the Solid and Hazardous Waste Manageme nt Group for their hard work during the tough field work while sampling waste fr om the landfill. Hwidong Kim and Aaron Jordan contributed countless hour s to the laboratory analyses, for which I am grateful. I would like to thank several other graduate st udents who have been helpful and supportive throughout my studies: Kim Cochran, Brajes h Dubey, Pradeep Jain, Jenna Jambeck, Jon Powell, and Erik Spalvins. This research was sponsored by the Polk County Solid Waste Division. Special thanks are extended to all of the staff of the Polk County Solid Waste Division and North Central Landfill who contributed to this proj ect, in particular Ana Wood, Brooks Stayer, and Michael Cotter, who have all been a tr emendous help to me throughout my graduate studies. The vertical expansion feasibility st udy was conducted by Jones, Edmunds & Associates, Inc. I am appreciative of the al l of the support, encouragement, and patience of Dennis Davis and Mickey Pollman throughout this study.

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iv Finally, I must thank my parents and Erin for their continuous love, support, and encouragement.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF TABLES.............................................................................................................ix LIST OF FIGURES...........................................................................................................xi ABSTRACT....................................................................................................................... xv CHAPTER 1 INTRODUCTION........................................................................................................1 1.1 Problem Statement..................................................................................................1 1.2 Objectives...............................................................................................................3 1.3 Research Approach.................................................................................................4 1.4 Thesis Organization................................................................................................5 2 RELATION OF LANDFILLED MUNICI PAL WASTE COMPRESSIBILITY, DECOMPOSITION, AND PHYS ICAL CHARACTERISTICS.................................6 2.1 Introduction.............................................................................................................6 2.2 Materials and Methods.........................................................................................10 2.2.1 Site Description and Sample Collection.....................................................10 2.2.2 Measurement of Waste Composition and Moisture Content.....................13 2.2.3 Measurement of Methane Yield, Volatile Solids, and Soil Content..........14 2.2.4 Measurement of Waste Compression.........................................................15 2.2.4.1 Compression testing instrument.......................................................16 2.2.4.2 Procedure..........................................................................................17 2.2.4.3 Compression instrument design assumptions and wall friction concerns....................................................................................................20 2.2.4.4 Data analysis....................................................................................21 2.3 Results...................................................................................................................2 3 2.3.1 Waste Properties: Specific Weight, Moisture Content, and Composition23 2.3.1.1 Moisture content...............................................................................24 2.3.1.2 Composition.....................................................................................25 2.3.2 Decomposition—Biochemical Methane Potential and Volatile Solids......26 2.3.2 Soil Content................................................................................................28 2.3.3 Compression Analysis................................................................................29

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vi 2.4 Correlations and Discussion.................................................................................38 2.4.1 Waste Degradation.....................................................................................39 2.4.2 Compressibility and Wa ste Index Properties.............................................42 2.4.3 Compressibility and Waste Degradation...................................................46 2.5 Summary and Conclusions...................................................................................51 3 CONE PENETRATION TESTING FO R CHARACTERIZING LANDFILLED MUNICIPAL SOLID WASTE...................................................................................53 3.1 Introduction...........................................................................................................53 3.2 Materials and Methods.........................................................................................56 3.2.1 Site Description..........................................................................................56 3.2.2 Cone Penetration Testing...........................................................................57 3.2.2.1 CPT equipment.................................................................................57 3.2.2.2. CPT procedure and data..................................................................58 3.2.2.3 CPT statistical an alysis and summary..............................................61 3.2.3 Waste Boring, Sample Collection, and Characterization...........................62 3.2.4 Statistical Comparison of Wa ste Properties and CPT Data........................63 3.3 Results...................................................................................................................6 3 3.3.1 Piezocone Penetration Test Results............................................................63 3.3.2 Large Diameter Boring Results..................................................................67 3.4 Discussion.............................................................................................................67 3.4.1 Landfill Stratification.................................................................................67 3.4.1.1Comparison of CPT data be tween soil and waste layers..................67 3.4.1.2 Intermediate soil cover layer within waste.......................................69 3.4.1.3 Statistical differences.......................................................................70 3.4.2 CPT Data and Waste Properties.................................................................73 3.4.2.1 CPT data and depth of waste............................................................76 3.4.2.2 CPT data compared to degree of degradation..................................79 3.4.2.3 CPT data and soil content.................................................................81 3.4.3 Correlation of Cone Penetratio n Tests with Compressibility.....................82 3.4.4 Comparison of CPT Data with Other Studies............................................85 3.4.5 Cone Penetration Data and Soil Classification...........................................85 3.5 Summary and Conclusions...................................................................................87 4 PREDICTION OF MSW LANDFILL SETTLEMNT AND COMPARISON TO CONICAL TEST LOAD FOR MEASUR ING WASTE COMPRESSIBILITY.......89 4.1 Introduction...........................................................................................................89 4.2 Methods................................................................................................................91 4.2.1 Site Description..........................................................................................91 4.2.2 Waste Properties Analysis and Laboratory Compression Testing.............92 4.2.3 Conical Test Load.......................................................................................92 4.2.4 Settlement Analysis and Comparison.........................................................96 4.3 Results.................................................................................................................100 4.3.1 Conical Test Load Settlement..................................................................100 4.3.2 Waste Properties.......................................................................................101

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vii 4.3.3 Finite Element Modeling..........................................................................102 4.3.4 Settlement Analysis..................................................................................104 4.4 Discussion...........................................................................................................107 4.4.1 Historical load..........................................................................................108 4.4.2 Waste rebound and compression under lo ads less than historic load......108 4.5 Conclusions.........................................................................................................108 5 SUMMARY AND CONCLUSIONS.......................................................................110 5.1 Summary.............................................................................................................110 5.2 Conclusions.........................................................................................................111 5.3 Implications........................................................................................................112 APPENDIX A COMPRESSION–ANALYSIS WALL FRICTION DISCUSSION AND CALCULATION......................................................................................................114 B LARGE DIAMETER BUCKET AU GER BORING LOG AND SPECIFIC WEIGHT CALCULATIONS...................................................................................116 C WASTE SAMPLE COMPOSITION DATA...........................................................119 D BIOCHEMICAL METHANE POTENTIAL, MOISTURE CONTENT, VOLATILE SOLIDS, AND SOIL CONTENT DATA; BMP CUMULATIVE VOLUME PLOTS....................................................................................................122 E MSW BIOCHEMCIAL METHANE POTEN TIAL VALUES FROM PREVIOUS STUDIES..................................................................................................................135 F LABORATORY SCALE WASTE CO MPRESSION–ANALYSIS DATA............136 G STATISTICAL ANALYSIS OF LEVEL OF DEGRADATION AND SOIL CONTENT RELATED TO OT HER WASTE PROPERTIES................................146 H SUMMARY OF WASTE DATA.............................................................................151 I LOGNORMALITY OF CONE PENETRATION DATA.......................................153 J CONE PENETRATION TEST DATA PLOTS.......................................................159 K CONE PENETRATION SUMMARY DATA AND STATISTICAL COMPARISON........................................................................................................176 L SETTLEMENT PREDICTION METHODOLOGY................................................182 M FINITE ELEMENT MODEL PARAMETERS AND CHANGE IN VERTICAL STRESS OUTPUT USING SIGMA/W...................................................................184

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viii N CONICAL TEST LOAD SETTLEMENT MEASUREMENT................................189 LIST OF REFERENCES.................................................................................................190 BIOGRAPHICAL SKETCH...........................................................................................194

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ix LIST OF TABLES Table page 2-1 Broad Classification of Waste Pa rticles from Landva and Clark.............................10 2-2 Moisture Content, Volatile Solid s and Biochemical Methane Potential..................27 2-3 Compressibility Indices 1000 and C of Compression Samples................................37 2-4 Summary of Co mpression Study Data.....................................................................38 3-1 Summary of Previous Cone Penetration Test in Landfills.......................................55 3-2 Soil Classification Numbers, Descripti ons and USCS Class for Cone Penetration Testing......................................................................................................................61 3-3 Summary of Cone Penetrat ion Testing Data in Waste.............................................65 3-4 Summary of Waste I ndex Data for Samples............................................................68 3-5 Summary Data for CPT Soundings Comp ared to Auger Boring Sample Depths....74 3-6 Correlation Factors of Wa ste Properties and CPT Data...........................................75 3-7 CPT Data Compared to Wa ste CPTs from Other Studies........................................86 4-1 Conical Test Load Di mensions and Volumes..........................................................93 4-2 Waste Layer Compressibility Parameters................................................................98 4-3 Phase III Settlement Calculati on for Center Settlement Plate................................105 B-1 Boring Waste Removal Weights an d Specific Weight Calculations.....................117 C-1 Waste Sample Composition Data...........................................................................120 D-1 Biochemical Methane Potentia l Raw Data and Calcluation..................................123 D-2 Fines, Volatile Solids, and Soil Content Data and Calculations............................125 E-1 Biochemical Methane Potential Values for Waste and Wast e Components from Previous Studies.....................................................................................................135

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x F-1 Waste Compression Analysis Data........................................................................137 G-1 Summary of Waste Property Data for Less-Degraded Samples ..........................147 G-2 Summary of Waste Property Data for Degraded Samples.....................................147 G-3 Statistical T-test Comparison betwee n Less-Degraded and Degraded Sample Sets.........................................................................................................................14 8 G-4 Summary of Waste Property Data for Low Soil Content Samples........................149 G-5 Summary of Waste Property Data for High Soil Content Samples.......................149 G-6 Statistical T-test Comparison between High and Low Soils Content Sample Sets150 H-1 Complete Summary of Waste Property Data.........................................................152 K-1 CPT Summary Statistics for Cover Soil Layers.....................................................177 K-2 CPT Summary Statis tics for Waste Layers............................................................178 K-3 CPT Summary Statistics for Subgrade Soil Layers...............................................179 K-4 Statistical Analysis for Difference of Population Means CPT Data between Known Waste Layers.............................................................................................180 K-5 CPT Summary Statistics for Waste Sampling Layers............................................181 M-1 Finite Element Model Parameters Summarized.....................................................185 M-2 Summary of Cha nge in Vertical Stress for Phase I................................................186 M-3 Summary of Cha nge in Vertical Stress for Phase II...............................................187 M-4 Summary of Cha nge in Vertical Stress for Phase III.............................................188 N-1 Conical Test Load Settlement Data........................................................................189

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xi LIST OF FIGURES Figure page 2-1 Overall Site Plan for North Central Landfill with Vertical Expansion Feasibility Study and Test Area Shown.................................................................12 2-2 Locations of Large Diamet er Bucket Auger Borings............................................13 2-3 Compression Analysis Instrument Schematic.......................................................18 2-4 Compression Analysis Instrument Photograph......................................................19 2-5 Compression Testing Time Effects........................................................................20 2-6 Example Power Law Compressi on Regression Analysis with 1000 and C ............22 2-7 Average Bulk Specific Weight of Waste with Respect to Depth..........................24 2-8 Average Moisture Content at Various Levels in Waste.........................................25 2-9 Average Waste Composition.................................................................................26 2-10 Methane Yield Box Plot with Respect to Sample Depths.....................................28 2-11 Soil Content Box Plot at Various Sample Depths.................................................29 2-12 Example Compression Analysis Data for Sample 6-2...........................................30 2-13 Specific Weight versus Applied Pr essure for all Compression Data Bounded by Dry Fresh Waste and Mature Old Waste at Field Capacity..............................32 2-14 Specific Weight versus A pplied Pressure for Boring 2.........................................33 2-15 Specific Weight versus A pplied Pressure for Boring 6.........................................34 2-16 Specific Weight versus A pplied Pressure for Boring 7.........................................34 2-17 Specific Weight versus A pplied Pressure for Boring 12.......................................35 2-18 Specific Weight versus A pplied Pressure for Boring 13.......................................35 2-19 Specific Weight versus Applied Pressu re for Cardboard and Compost Samples..36

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xii 2-20 Waste Degradation Box Plots................................................................................41 2-21 Compression Indices versus Moisture Content......................................................43 2-22 Compressibility Indexes versus Soil Content........................................................45 2-23 Bulk Specific Weight Compression Coe fficient versus In-Place Bulk Specific Weight....................................................................................................................46 2-24 Compressibility Indices for Unde graded and Degraded Samples.........................47 2-25 Compressibility Indices versus Volatile Solids Content........................................49 3-1 Layout of Test Parcel, Cone Penetr ation Tests, and Bucket Auger Borings.........58 3-2 Typical Piezocone Tip Schematic..........................................................................59 3-3 Lognormal Distribution of Tip Resistance of Waste in CPT 7..............................62 3-4 Cone Penetration Data Plots for CPT 7.................................................................66 3-5 Landfill Stratification.............................................................................................69 3-6 Tip Resistance and Penetration Media Box Plot....................................................71 3-7 Sleeve Friction and Penetration Media Box Plot...................................................71 3-8 Friction Ratio and Pene tration Media Box Plot.....................................................72 3-9 Pore Pressure and Pe netration Media Box Plot.....................................................72 3-10 Box Plot of Tip Resistance w ith respect to Depth in Waste..................................76 3-11 Box Plot of Sleeve Friction with respect to Depth in Waste.................................77 3-12 Box Plot of Friction Ratio w ith respect to Depth in Waste...................................78 3-13 Box Plot of Pore Pressure w ith respect to Depth in Waste....................................78 3-14 Box Plot of Tip Resistance for De graded and Less Degraded Samples................80 3-15 Box Plot of Friction Ratio for De graded and Less Degraded Samples.................80 3-16 Box Plot of Tip Resistance for High and Low Soil Content in Waste..................81 3-17 Box Plot of Friction Ratio for High and Low Soil Content in Waste....................82 3-18 Compression Coefficient versus Tip Resistance....................................................83 3-19 Compression Exponent ve rsus Tip Resistance......................................................83

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xiii 3-20 Compression Coefficient versus Friction Ratio.....................................................84 3-21 Compression Exponent versus Friction Ratio........................................................84 3-22 Cone Penetration Data and Soil Classification Plot...............................................87 4-1 Settlemen t Plate.....................................................................................................95 4-2 Conical Test Load Settlement Plate Arrangement.................................................96 4-3 Waste Settlement Model Parameters.....................................................................99 4-4 Measured Settlement for Three Phases of Test Load and Additional Settlement101 4-5 Cross Section of Vertical Stress Dist ribution for Added Stress from CTL Phase I using Finite Element Software SIGM A/W from GeoSlope International.........102 4-6 Cross Section of Vertical Stress Dist ribution for Added Stress from CTL Phase II using Finite Element Software SIGM A/W from GeoSlope International.......103 4-7 Cross Section of Vertical Stress Dist ribution for Added Stress from CTL Phase III using Finite Element Software SIGM A/W from GeoSlope International......103 4-8 Settlement Analysis Results for Phase I of the Conical Test Load......................105 4-9 Settlement Analysis Results for Phase II of the Conical Test Load....................106 4-10 Settlement Analysis Results for Ph ase III of the Conical Test Load...................106 4-11 Settlement Analysis Results for Phase III after 4 Months of the Conical Test Load.....................................................................................................................107 B-1 Theoretical Compression Cylinder Sidewall Model............................................115 D-1 BMP Cumulative Methane Volume for Sample 2-2............................................127 D-2 BMP Cumulative Methane Volume for Sample 2-4............................................127 D-3 BMP Cumulative Methane Volume for Sample 2-5............................................128 D-4 BMP Cumulative Methane Volume for Sample 2-6............................................128 D-5 BMP Cumulative Methane Volume for Sample 6-2............................................129 D-6 BMP Cumulative Methane Volume for Sample 6-3............................................129 D-7 BMP Cumulative Methane Volume for Sample 6-4............................................130 D-8 BMP Cumulative Methane Volume for Sample 6-5............................................130

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xiv D-9 BMP Cumulative Methane Volume for Sample 7-2............................................131 D-10 BMP Cumulative Methane Volume for Sample 7-3............................................131 D-11 BMP Cumulative Methane Volume for Sample 7-4............................................132 D-12 BMP Cumulative Methane Volume for Sample 7-5............................................132 D-13 BMP Cumulative Methane Volume for Sample 12-2..........................................133 D-14 BMP Cumulative Methane Volume for Sample 12-5..........................................133 D-15 BMP Cumulative Methane Volume for Sample 12-6..........................................134 D-16 BMP Cumulative Methane Volume for Sample 13-3..........................................134 I-1 Normality – Lognormality Test for Ti p Resistance for CPT-1 – 3-13.7 feet......154 I-2 Normality – Lognormality Test for Friction Ratio for CPT 1 – 3 to 13.7 feet....154 I-3 Normality – Lognormality Test for Ti p Resistance for CPT-3 – 3-30 feet.........155 I-4 Normality – Lognormality Test for Friction Ratio for CPT-3 – 3-30 feet...........155 I-5 Normality – Lognormality Test for Tip Resistance for CPT-6 – 3 to 30 feet.....156 I-6 Normality – Lognormality Test for Sleeve Friction for CPT-6 – 3-30 feet.........156 I-7 Normality – Lognormality Test for Fr iction Ratio for CPT-6 – 3 to 30 feet.......157 I-8 Normality – Lognormality Test for Pore Pressure for CPT-6 – 3-30 feet...........157 I-9 Normality–Lognormality Test for Tip Resistance for CPT 12 – 10 to 15 feet....158 M-1 Phase I CTL Finite Element Mesh Table.............................................................186 M-2 Phase II CTL Finite Element Mesh.....................................................................187 M-3 Phase III CTL Finite Element Mesh....................................................................188

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xv Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Engineering ENGINEERING PROPERTIES AND CONE PENETRATION TESTING OF MUNICIPAL SOLID WASTE TO PREDICT LANDFILL SETTLEMENT By Tobin S. McKnight May 2005 Chair: Timothy G. Townsend Major Department: Environmental Engineering Sciences Waste settlement is one of the most difficult engineering challenges of redeveloping closed landfills for structures, highways, or vertical expansion of landfill cells. Traditional theories and methodologies for assessing waste compressibility and models for predicting settlement have lim itations. The settlement waste undergoes immediately and shortly after load applic ation (e.g., primary settlement) may be estimated if the compressibility charact eristics of the waste are known. Waste compressibility has been examined in a few st udies, but relatively little information is available on the impact of characteristics such as degradation, moistu re content, and soil content. Even less information is availabl e on how primary settlements predicted using waste compressibility compare to actual settlement in the field. A comprehensive geotechnical investigat ion of a 20to 30-year old unlined municipal solid waste landfill was conducted. Waste samples collected from various depths along the profile of the landfill were characterized for compressibility and several

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xvi physical properties (i.e., sp ecific weight, composition, so il content, and level of degradation). Waste samples with greater sp ecific weight—a result of degradation and higher soil content—demonstrat ed somewhat less compressibility when compared to samples with lower specific weights (less degraded, less soil). The utility of the cone penetration test (CPT) for landfill exploration to asse ss waste properties, including compressibility, was examined. Although CPT da ta in landfilled waste were found to be extremely variable, piezocone penetration test data for tip resistan ce and friction ratio were found to be statistically different in le vel of degradation, mo isture content, and compressibility. The waste compression data we re used to predict settlement that would occur if a conical load were placed in the la ndfill. These settlement predictions were compared with field data from a conical test load constructed of sand over the same area of the landfill where the compressibility data were gathered and CPTs were performed. Settlement prediction depended heavily on the historic loading history.

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1 CHAPTER 1 INTRODUCTION 1.1 Problem Statement Landfills are not going away. In 2001, the US EPA (2001) reported that 229 million tons of municipal solid waste (M SW), or 4.4 pounds per capita per day, was generated in the United States, with nearly 60% of that disposed in landfills. Modern sanitary landfills are designed and construc ted to minimize environmental impact, with liners, caps, stormwater management systems, and gas and leachate collection systems. Although these pollution control systems represent a dramatic improvement over waste dumps and burn sites from the days before the Resource Conservation Recovery Act (RCRA), landfills remain an undesirable bypr oduct of modern society. Siting and constructing a new landfill is a difficult (if not impossible) and costly process. No one wants a landfill in their backyard. Current efforts to explore more sustainabl e integrated solid waste management and landfill practices include MSW composting, landf ill bioreactors, and practices such as biological or thermal pretreatment of waste. Although these new alternatives decrease the impact of landfills, they do not eliminate the need for landfills altogether. Furthermore, although the process of constr ucting, operating, closing, and monitoring a modern sanitary landfill is quite costly, la ndfill disposal remains the least expensive method for solid waste disposal for much of the world. The development and promulgation of landfill regulations in the late 1980s and early 1990s saw the beginning of a paradigm sh ift in the practice of landfilling to fewer

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2 and larger, high-rise landfills. Because wast e had to be contained in a costly, lined footprint, landfills became taller to gain the gr eatest utility of the liner. As a result, landfill managers and operators have shifted to dealing in the commodity of airspace. Operators try to maximize airspace from the finite footprint by compacting waste and minimizing cover material used. By using landfill cells more efficiently, the use of current landfill cells and need for new sites is prolonged. The need to maximize waste deposited in landfill cells has also given ri se to new landfill practices such as the emerging landfill bioreactor. One of the primary advantages of landfill bioreactor technology is inducing rapid st abilization through leachate recirculation to recapture airspace for further disposal. Because iden tifying and siting new landfill locations is difficult, landfill operators want to achieve the greatest utilization of landfill parcels they can including filling landfill valleys, piggy back landfills (adjacent slopes), and expanding vertically. The motivation of the research described in this thesis was the challenge posed by creating new landfill disposal capacity by cons tructing a lined vertical expansion on top of an old unlined landfill. At the Polk County North Central Landfill in Winter Haven, Florida, the owner/operator sponsored a f easibility study to determine whether a new lined landfill constructed over old, unlined, shallow landfill cells was possible. The waste cells being evaluated date from when the site opened as a landfill in 1975. Waste was deposited in a trench-and-fill manner w ith little or no compac tion. Today, the cells range from 20 to 30 feet above surrounding ground surface. Compared with other landfill cells on site that reach elevations of 150 feet above the ground, the old cells are under used and contain a tremendous amount of airspace that can be recaptured if the

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3 vertical expansion proves feasible. Expanding the unlined cells will dramatically increase the total site capacity of the North Central Landfill. Lateral (piggy-back) expansions, valley fills, and vertical expansions are not uncommon in landfill engineer ing. Although landfill vertical expansion is not a new concept, the science of landfills is still a developing field. Understanding the waste behavior as it compresses and settles is im portant with implica tions that reach beyond this project. The research conducted in asso ciation with the feasibility study aimed at gaining a greater understanding of the geotechnics of old landfill cells and the tools engineers have for predicting the behavior of old waste. This research adds to the body of knowledge of landfill settle ment and compressibility. 1.2 Objectives The overriding purpose of the feasibility study was to inve stigate geotechnical and environmental concerns with siting a new Class I MSW landfill on top of the old landfill cells (Jones, Edmunds & Associates, 2004). I nvestigations were intended to determine the suitability of the waste to support the lo ad of an additional 120 feet of waste while maintaining the integrity of a liner and not cau sing further environmental impact. A large part of the data gathered in this feasib ility study serve as th e focus of this study. This research was aimed at gaining a greater understanding of landfill settlement in the context of assessing landfill vertical expans ion suitability. The procedures used to determine landfill compressibility are evaluated for utility for determining landfill settlement. Furthermore, specific causes and effects of landfill settlement were examined by looking at various landfill properties and attempting to draw correlations between properties. Specifically, this thesis had the following research objectives:

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4 To compare and evaluate the relation ships between physical waste properties including moisture content, specific we ight (density), composition, degradation, soil content, and compressibility. By analyzing waste samples for various engineering properties, the relationship of each property with respect to waste compressibility helps determine cause s and effects of waste settlement. To compare cone penetration data with physical waste properties and draw correlations between tip resistance, sleev e resistance, friction ratio, pore water pressure, and waste properties. Determ ining the relationships between waste properties and CPT data will allow greater in formation to be gathered using CPT in landfills, one of the few met hods for in situ testing. To evaluate waste compressibility usi ng results from laboratory scale compression testing to predict landfill settlement and compare with the results of field scale conical test load. The comparison of pr edicted settlement with actual measured settlement will help establish the methodology for determining waste settlement. 1.3 Research Approach The area of the old, unlined waste cells unde r consideration for vertical expansion is roughly 100 acres. Because studying the entire area would prove time-consuming and difficult, a smaller test parcel was select ed. Cone penetrati on tests were conducted throughout the test area through the depth of the waste, yielding data for cone and tip resistance and pore water pressure. Then waste was excavated using a large diameter bucket auger rig to obtain samples at various dept hs to be analyzed later in the laboratory. Five borings that coincided with cone pene tration test were performed and a composite waste sample for every five linear feet of boring was obtained. Waste samples were analyzed in the laboratory for waste comp ressibility, composition, and degradation. A custom-built compression-analysis instrument wa s used to evaluate the compressibility of samples removed from landfill borings. Finally, a conical test load was constructed over the test plot to measure comp ressibility of the waste at a field scale. The surcharge, consisting of soil, was placed a maximum of 30 feet deep while resulting settlement was

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5 measured. Compressibility measurements fr om the laboratory scale compression testing and field scale conical te st load are compared. 1.4 Thesis Organization This thesis is organized into five chapte rs. The first chapter introduces the problem and describes the objectives and approach of the research. The second chapter focuses on the compressibility of the waste, measured with a laboratory–scale compression–analysis device, compared to different properties of th e waste. The third chapter examines using the cone penetration testing for predicting la ndfill properties. Chapter 4 examines the results of predicting settlement using laboratory–scale compression–testing data compared with actual settleme nt data from a field scale conical test load. Finally, Chapter 5 summarizes and presents conclusions . Numerous appendices are attached with supporting data and calculations.

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6 CHAPTER 2 RELATION OF LANDFILLED MUNICI PAL WASTE COMPRESSIBILITY, DECOMPOSITION, AND PHYSICAL CHARACTERISTICS 2.1 Introduction When constructing on top of old landfilled refuse, engineers are concerned with the old landfillÂ’s ability to support a new structure. With a land fill vertical expansion where additional waste is placed above closed landf ill cells, the old refuse must be able to support new waste such that the liner for th e new cell will not be compromised and the leachate collection and removal system will continue to drain leachate as the waste settles. To design an effective lined cell, an engineer must be able to estimate the settlement that will result from additiona l overburden pressure. One component of settlement, waste compressibility, is studied in this chapter. Compressibility is compared with other physical characteris tics that affect waste settlem ent, such as composition, soil content, moisture content, and biodegradati on, to evaluate the relationships and draw correlations between waste properties. Studying geotechnical aspects of waste is difficult because of the heterogeneous nature of waste, the difficulty of obtaining a sufficient sample, the er ratic nature of waste particles, and changing propertie s of waste that occur with time (Fassett et al., 1994). Traditionally, soil mechanics theories have b een used to describe waste settlement. According to these theories, waste settlem ent may be broken into three categories: immediate settlement, consolidation settle ment, and secondary compression (creep) as shown in the expression (Qian et al., 2002):

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7 creep. or n, compressio secondary and ; settlement ion consolidat ; settlement immediate ; settlement total : where H H H H H H H Hc i total c i total Primary settlement, or compressibilit y, includes immediate and consolidation settlement. This initial settlement occurs rapidly, typically within the first three months, and has usually been lumped together (B jarngard and Edgers, 1990; Lukas, 1992). Unlike clay consolidation, whic h takes place over a long period of time and is dictated by a decrease in pore water pressure and alignm ent of soil particles, waste consolidation occurs rapidly because of high void space and limited saturation (Lukas, 1992). During primary settlement, mechanical compressi on is the main compression mechanism and includes distortion, bending, crushing, and reorie ntation (Fassett et al., 1994). Secondary settlement is time dependent and is caused by mechanisms including raveling, chemical changes, and biological degrad ation of waste. This study focuses on the compressibility of waste in existing landfill cells . Secondary compression is not considered in this study. The waste is assumed to already be substantiall y degraded so that settlement due to waste compressibility will be much larger than settlement cau sed by degradation. Parameters commonly used to estimate the primary settlement of municipal solid waste (MSW) resulting from an increase in vertical stress include the compression index ( Cc) and the modified compression index (cC '), which are defined as (Fassett et al., 1994):

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8 layer. waste of ss in thickne change and layer; waste of thickness original stress; effective vertical final stress; effective vertical initial ratio; void initial ratio; in void change : where 1 log ' log0 1 0 0 0 0 1 0 0 1 H H e e e C H H C and e Cc c c Both of these compression index parameters are functions of the inverse of the logarithm of change in vertical stress. The compression index (cC ) is related to the void ratio, whereas the modified compression index (cC ') is a function of the waste height. Challenges exist when using either approach. The void ratio is difficult to gauge in field and laboratory experiments as is the initial he ight in field observations. Also, the percent compression-log pressure relationship is not li near. Both issues have been cited as shortcomings of the compression indices cC and cC ' (Edil et al., 1990). Still, waste compressibility and compression indices have been researched numerous times prior to this study using several different field and laboratory methods. Purpose-built compression cells, or oedometers, have been built by Landva and Clark (1990), Pelkey (1997), Hossain et al. (2003), and Beaven (2000 ) to study the compressibility of waste. Numerous other field evaluations of landfill compressibility have been conducted using settlement plates, benchmark surveys, and aerial surveys (Q ian et al., 2002). Because of the complex intermingling of particles under pres sure during waste compression, predicting compression is difficu lt even when using the traditional soil

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9 mechanics approach. Powrie et al., (1999) suggests that because of the compressible nature of some waste particles, certain assumptions of soil mechanics theories, which are based on incompressible partic les, do not hold true. To further understand waste compression properties, previous studies examined individual waste constituents. Landva and Clark (1990) classifi ed waste into four broad cat egories to assign engineering properties (see Table 2-1). A waste constituent, depending on whether organic or inorganic in nature and degradable or inert, will have a different fate in a landfill and thus affect the geotechnical properties of the landfil l as a whole. These categories have been further discussed by Hudson et al. (2004), w ho identified the tendency of particles to crush, bend, or break relative to their void space. For instance, cans and bottles have high void space until crushed or broken. This study also looks at waste components and the need to distinguish between mobile liquid in large drainable pores, liquid in small pores, and liquid trapped or absorbed to a solid co mponent such as textile or paper. The presence of cover soil and various waste la yers of different age further complicates landfill geotechnical study. For this research, waste samples taken fr om old, unlined landfill cells at the Polk County North Central Landfill were characteri zed for typical waste index parameters: specific weight, moisture content, and com position. Further analysis of the samples produced data on the degree of decomposition of the organic fraction of the waste. Samples were also obtained for compre ssion testing. Laboratory compression index testing results are compared a nd correlated with results from waste property analyses in this chapter to determine, among other things, if waste compressibility changes for various degrees of degradation as reported by Hossain et al. (2003). Ultimately, the goal

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10 of this chapter is to gain a better understandi ng of the compressibility as it relates to other waste properties. Table 2-1: Broad Cl assification of Waste Particles from Landva and Clark (1990) Degradable Non-degradable Organic Putrecible: monomers and low-resistance polymers, readily biodegradable Food waste Garden waste Animal waste Material contaminated by such wastes Non-putrecilbe: highly resistant polymers, slowly biodegradable Paper Wood Textiles Leather Plastic, rubber Paint, oil, grease, chemicals, organic sludge Inorganic Metals (corrodible to varying degrees) Inert, stable materials Glass, ceramics Mineral soil, rubble Tailings, slimes Ash Concrete, masonry (construction debris) 2.2 Materials and Methods 2.2.1 Site Description and Sample Collection The Polk County North Central Landfill, located in central Florida, opened in 1976 and today accepts the majority of waste fr om the countyÂ’s 500,000 residents. When the landfill opened (prior to landfill liner regulations in Florida), the site used a trench-andfill method of landfilling that consisted of excav ating 8 to10 feet (2 to 3 meters) of soil, and depositing waste in shallow cells. Afte r the trench was full, the waste was covered, and an additional lift was placed on top of the trench and subsequently covered with soil. This practice took place until 1985. Once landfill regulations were promulgated, waste was deposited in new lined high-rise landfill cells on the property and the trench-and-fill cells were left with soil and grass cover.

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11 The area of the four landfill cells under evaluation for vertical expansion covers approximately 100 acres (40 hectares), and hen ce an in-depth investig ation of the entire landfill was not feasible. Therefore, field i nvestigations focused on one smaller area of the landfill where cone penetration test (CPT) soundings (see Chapter 3), bucket auger borings, and the conical test load (see Chapte r 4) were performed. Figure 2-1 is an aerial photograph of the site with the old cells and te st parcel indicated. A square parcel with sides 120 feet (40 meters) long in center of the northern, middle cell was designated the test area for a number of reasons, most im portantly ease of access. Sampling and analyzing the waste from the landfill genera ted a profile of engi neering properties at various depths in the test parcel. For each bucket auger boring, waste was sampled every 5 feet (1.5 meters) of the boring. The description of each procedure follows. On February 9th and 10th, 2004, a drilling contractor excav ated five large diameter (36-inch, 91-centimeter) bucket auger bori ngs into the waste of the study cell to approximately 30 feet (10 meters) below the landfill surface (see Figure 2-2). Waste samples were collected at various depths al ong the profile of each boring and stored for later waste property and compressibility analys es. All material removed from the borings was unloaded into a small dumpster and weighed before being transferred to a large rolloff container and deposited in the active Class I cells at the landfill. Using the scale data and the drilling log, in-place landfill specifi c weight (density) approximations were calculated. The borings were ultimately back-filled with soil from on-site borrow. During the drilling, as the waste was remove d, a representative sample of waste and soil was compiled for every 5 vertical feet (1.5 meters) of boring (measured with a surveyorÂ’s tape). To obtain a representa tive sample, portions of each bucket removed

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12 from the landfill were grab-sampled in proportions similar to that of the composition the waste removed. This composite sample was divided into two portions. Approximately 20 pounds (9 kilograms) was collected in a 5gallon bucket for later moisture content, composition, and methane yield analysis. Samples for compression testing weighing 60 to 200 pounds (30 to 90 kilograms) were coll ected and stored in 33-gallon trash cans. Figure 2-1: Overall Site Plan for Nort h Central Landfill with Vertical Expansion Feasibility Study and Test Area Shown (USGS 1999) N Approximate Scale 1 inch = 1500 feet Test Parcel ( 40m x 40 m ) Old, unlined waste cells (approx. 40 hectares)

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13 Easting 70620 0 706250 706300 706350 Northing 1338400 13 3 84 5 0 1 33 8 50 0 1338550 13 3 86 0 0 Bucket Auger Boring CENTER (CPT-1, AR2) BORING 6 BORING 7 BORING 12 BORING 13 0 50100 SCALE [FEET] TEST PARCEL BORING 2 Boring 6 Figure 2-2: Locations of Large Diameter Bucket Auger Borings 2.2.2 Measurement of Waste Composition and Moisture Content Before determining methane yield, each sample underwent rigorous preparation and processing including drying and separa tion. Samples were first analyzed for moisture content. This procedure involve d weighing the unprocessed samples and drying the samples in a large metal bin in an oven for 48 to 72 hours at 105°C. The final weight of the sample when compared with the first weight yields the moisture content on a mass basis.

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14 Samples were sorted to determine waste composition. Waste components were classified in eight major cat egories: paper (e.g., newspape r, office paper, cardboard), plastic (e.g., drink containers, film plas tic), yard waste (e.g., tree branches, grass clippings), textile, stone/metal, glass/ceramic , and large and small fine particles. Dried samples were screened to remove fines and then sorted by hand. The material in each category was weighed to determine each fr action by weight. Fi ne particles were classified into two categories by the mass of particles that passed through and that were retained by a number 40 sieve (0.475 mm). 2.2.3 Measurement of Methane Yield, Volatile Solids, and Soil Content Methane yield was measured on the proce ssed samples. The biochemical methane potential (BMP) of each sample was assessed using the Standard Test Method for Determining the Anaerobic Biodegrada tion Potential of Organic Chemicals (ASTM E2170-01) (ASTM, 2001). This procedure has b een used previously to evaluate the level of degradation of organic waste constituents in landfills (Mentha et al., 2002; Townsend et al., 1996). For each sample, BMP assays were conducted on three different fractions: the identified biodegradable co mponents (primarily paper), the small particles retained on the No. 40 sieve (R), and the fine particles passing through the No. 40 sieve (P). Before analysis of the biodegradable components and the retained fraction of the waste, samples were ground using a cutting mill grinder (Fritsch, Germany). Before anaerobic incubation, the volatile solids (VS) content of each fraction was measured on a mass basis. A sub-sample of the three fractions was heated to 550°C for two hours in a muffle furnace, and the remaining sample was weighed. The BMP of each fraction was analyzed in triplicate; 0.2 gram of each samp le (as VS) was measured into a bottle with a prepared microbial media containing 10% an aerobic digested sludge and incubated at

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15 35°C for approximately 45 days (ASTM, 2001). Gas volume and methane concentrations were analyzed periodically during the incubation time. A resulting methane yield was determined for each frac tion measured in volum e of methane per mass of VS (liter CH4/gram VS). An overall methane yield value of each sample was calculated using the relative VS content of each of the three fractions. Methane yield analysis of newspaper and ce llulose was conducted concurren tly to compare with waste sample results. The soils content (SC) of each sample was estimated as a sum of the mass of large soil particles, the mass of nonvolatile component of the retained fr action, and the mass of the nonvolatile component of the passing fraction. This calculation is summarized in the following expression: . M ) VS 1 ( M ) VS 1 ( M M SCsample fines retained fines passing fines passing fines retained particles soil large Since the retained and passing fractions contained some degraded organic waste materials, the soil was assumed to be the nonvolatile portion. 2.2.4 Measurement of Waste Compression To examine the compressibility of landfilled waste, a compression instrument was designed and constructed. The device was de signed to assess the amount of compression a solid waste sample undergoes as a pressure is applied, such as would occur with placement of additional waste overburden. The purpose of the test was to develop a stress-strain relationship of the waste for use in predicting waste compression. The device can exert up to 12,677 pounds per square foot (psf) (600 kilopascals, 88 pounds per square inch) on a sample. In addition to testing samples of waste and soil removed

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16 from the landfill during augering, a sample of shredded cardboard and two samples of compost of different ages were compresse d for the to compare other degraded and undegraded waste media to landfill samples results. The cardboard was shredded to approximately 1 inch (2.5 centimeter) squares. The compost samples were obtained from a MSW composting facility in central Flor ida. One sample was well decomposed, approximately 6 months old, screened with a 3/8-inch (10-millimeter) screen, and fairly low in moisture content. The other compost sample was approximately three weeks old, less degraded, higher in moisture content, a nd screened with a 2-inch (50-millimeters) screen. The description of the devi ce and analysis procedures follows. 2.2.4.1 Compression testing instrument The compression instrument, or oedometer, was a hydraulic press equipped with a steel cylinder for containing the waste sample . The press was equipped with a hydraulic system consisting of a 10-ton cylinder jack and hand pump, connected by a 6-foot (2meter) hydraulic hose with a dial gauge that reads the pressure in the system in pounds per square inch. The stroke of the jack was 6 inches (152 millimeters), and to compress samples to the full capabilities of the system , the press was modified to allow the top carriage to be lowered. After compressing a sa mple at one carriage level to the jack’s full extent, the hydraulic pressure was released, th e carriage was lowered, and the pressure reapplied. See Figure 2-3 for a drawing of th e compression instrument and Figure 2-4 for a photograph of the instrument. The carbon steel cylinder has a 17.1-inch ( 433-millimeter) inside diameter, is 27inches (690-millimeters) long, and has ½-in ch (12.7-millimeter) thick walls; it was manufactured from a section of 18-inch pi pe. The cylinder was constructed with an accompanying circular bottom plate (½-inch (12.7-millimeter) carbon steel) that attaches

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17 to the cylinder with four toggle clamps. Th e bottom plate and the cylinder rest on the base of the press. The compression plate is a 17.05-inch (432-millimeters) diameter, ½inch (12.7-mm) thick steel plate (reinforced w ith steel blades welded perpendicular to the surface) designed with a threaded connecti on to attach to the hydraulic system or extensions. The compression plate threads di rectly to the load cell or to one or a combination of three extensions measuri ng 4, 6, or 8 inches (100, 150, or 200 millimeters). A stainless steel “S” beam load cell manufactured by Omega Engineering (model number LC101-20K) connects the hydraulic jack to the compression plate. The load cell is wired to a digital strain gage meter (Omega [DP41-S]). 2.2.4.2 Procedure Compression analysis began by placing sa mples into the compression cylinder in small lifts and lightly compacting the waste by hand. Once the entire sample—less any ridged, oversized waste components (great er than 6 inches that might compress differentially which would damage the jack)— was in the cylinder, it was mounted on the press and compression analysis began. Pressu re was applied to the waste sample using the hand pump in increments of 2,000 pounds per square foot (100 kilopascals). The linear displacement of the compression plate wa s measured at each pressure increment. Displacement data were used to calculate the specific weight () at each compression point corresponding to an applied vertical stre ss. These data were the basis of waste index analysis. The compression test was continued until a total of 12,000 pounds per square foot (600 kilopascals) of pressure was applied.

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18 Figure 2-3: Compression Anal ysis Instrument Schematic COMPRESSION CYLINDER ID 17.05in (433mm) DIA 17.01in (432mm) COMPRESSION CYLI NDER, BOTTOM PLATE, AND COMPRESSION PLATE MADE OF ½ inch (12.7mm) CARBON STEEL B O TT O M PLATE COMPRESSION PLATE COMPRESSION C ARRIA G E HYDRAULIC JACK LOAD CELL CARRIAGE PI NS 27in (690 mm) DIGITAL STRAIN G A G E METER PRESSURE G A G E PRESS FRAME EXTENSION HYDRAULIC HAND PUMP

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19 Figure 2-4: Compression Anal ysis Instrument Photograph The force read by the load cell lessened with time as the reactive force of the sample diminished as a result waste part icles rearranging. Thus, several force measurements were taken over a short period of time. At each compression data point, the force was measured initially and periodical ly for 15 minutes in or der for the reactive force of the sample to stabilize. Figure 2-5 illustrates the pressure readings over time as compression testing was performed. The re lationship of compression under a constant applied load over time has been documented as a logarithmic relationship (the basis of

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20 secondary compression index, C) (Qian et al., 2002). Similarl y, the change in pressure measurement over time (at constant deflection) in this study was found to diminish at a constant logarithmic rate. Because measur ing the ultimate settlement would have been prohibitive in terms of time and number of sa mples analyzed, the pressure reading at the 15 minute mark was selected to represen t the ultimate pressure measurement. 15 16 17 18 19 20 21 1001,00010,000100,000 Applied Vertical Stress [psf]Vertical Compression Measurement, [in]t1=1 sec. t2=15 sec. t3=30 sec. t4=5 min. t5=10 min. t6=15 min. Figure 2-5: Compression Testing Time Effects 2.2.4.3 Compression instrument design assumptions and wall friction concerns The design of the compression testing in strument and the experimentation were conducted based on certain assumptions. T hough moisture content of some of the samples may have been high, waste was not compressed under satura ted conditions. The cylinder was free-draining and the waste was assumed to be permeable enough that pore water pressure increase did not play a signifi cant role. Hence, effective vertical stress

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21 (Â’v) is considered the same as measured vertical stress (v) (applied load), and the terms are used interchangeably in this chapter. B ecause of the short dura tion of the test, longterm creep and decomposition settlement were not considered. The creep and decomposition portions of settlement were assumed to be small compared to the compressibility. Friction between the waste sample and th e inside wall of the compression cylinder was expected to slightly affect the results of compression analysis. Based on similar waste compression studies, wall friction had a re latively limited effect of 4-8% on refuse density (Beaven, 2000). The th eoretical development of wall friction forces of a portion of a waste sample undergoing compression is presented in Appendix A. To minimize sidewall friction in this experiment, the inside surface was sanded and painted before beginning the study, and spray lubricant was appl ied to the inside surf ace during testing. Wall friction was considered negligible compared to the forces applied to the waste and, hence, pressure data were not corrected for wall friction. 2.2.4.4 Data analysis Compression data obtained during experiment ation consisted of applied force (to determine pressure) and length of compression. Given the dimensions of the cylinder, the compression length, and sample weight, sa mple specific weights were calculated for each applied pressure data point. The da ta were plotted as specific weight (), pounds per cubic foot, versus applied vertical stress (v), pounds per square foo t; the data were fit to a regression line to determine compression indice s to compare different samples. Unlike the compression index (cC) and modified compression index (cC') that are fit to a logarithmic regression line and de pendent on initial conditions 0e or oH, data for this

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22 study were fit to a power law regression line. This model was selected because of the shortcomings of the method for determining cC and cC', namely selection of an initial void ratio (0e) or initial height (oH). This approach was also taken by Beaven (2000). Using the alternative approach, compression data were plotted as specific weight versus applied pressure (Fi gure 2-6). However, applied pressure was adjusted to a convenient pre-determined index. That is, ap plied pressure data are divided by an index pressure such as 50 kPa (1000 psf). In the power law regression: C v' 1000 the coefficient, 1000 (measured in kip per square foot ), corresponds to the density of waste under the index pressure selected, while the exponent, C (unit less), describes the slope of the trend line. Fo r this study data were i ndexed to 1000 psf (50 kPa). = 1000xCR2012345678910 Pressure, v [kpsf]Specific Weight, [pcf] 1000v = 1000ps f Figure 2-6: Example Po wer Law Compression Regression Analysis with 1000 and C

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23 2.3 Results Five large diameter bucket auger (LDA) borings were conducted to approximately 30 feet (9 meters) below the landfill surface. Water was en countered in each boring at approximately 28 to 30 feet below the surface co rresponding to the local surficial aquifer. Twenty-four composite waste samples were excavated and retained for analysis. Samples were named based on their location an d depth. See Figure 2-2 for the layout of the LDA borings. Each LDA boring coincide s with a CPT and are numbered the same. The second number of the sample designation refers to the composite batch sample for each boring. That is, Sample 7-3 refers to the boring at CPT (and LDA) number 7 at the depth of 10 to 15 feet (3 to 4.5 meters) be low landfill surface. Waste samples from the first 5 feet (1.5 meters) of boring were not taken because the segmen t consisted largely of cover soil. However, one cover soil sample , 6-1, was obtained for compression analysis. In LDA number 7, the extent of waste wa s reached and the native soil below the waste was excavated. Sample 7-6 was not obtained. 2.3.1 Waste Properties: Specific Weight, Moisture Content, and Composition The specific weights of waste and soil samples removed by the bucket auger were determined at 5-foot (1.5-meter) interval s below the landfill surface. The average specific weight measured was 68 pounds per cu bic foot (pcf) (1.09 megagrams per cubic meter, Mg/m3) ranging from 39 pcf (0.62 Mg/m3) to 116 pcf (1.86 Mg/m3). The box plot in Figure 2-7 presents the average, median, a nd quartile range of sp ecific weight at each sampling layer in the landfill. Data for the weights of composite samples and waste excavated from borings are presented in A ppendix B. The specific weights of waste samples (which include varying degrees of so il) removed was in th e range of expected MSW and cover soil specific weight values, typically in the range of 40 pcf (0.64 Mg/m3)

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24 to 80 pcf (1.28 Mg/m3) and 100 pcf (1.60 Mg/m3) to 120 pcf (1.92 Mg/m3), respectively (Tchobanoglous et al., 1993). As expected, the top layer was observed to have the highest specific weight and average specific weight due to the high cover so il content. In general, the specific weight of the waste increased with depth. This wa s believed to result from greater overburden pressure, as well as increasing moisture c ontent at lower depths within the cells. Bulk Specific Weight, bulk [lb/ft3] 020406080100120140 Waste Sample Depth [ft] 0 5 10 15 20 25 30 35 Figure 2-7: Average Bulk Specific Wei ght of Waste with Respect to Depth 2.3.1.1 Moisture content Moisture content was measured on 17 of the 24 samples that were obtained during analysis. The average moisture content was 33.7% with the minimum and maximum 24.1% and 43.4%, respectively. The box plot in Figure 2-8 presents the relationship of 75 % Quartile Median Value (solid) Mean (dashed) 25% Quartile

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25 sample moisture content measurements with respect to depth of sample. Typical moisture content values for waste in a la ndfill are in the range of 10-20% under normal landfill operations and 30-40% under bioreact or or leachate reci rculation conditions (Reinhart and Townsend, 1998). Moisture Content [% by mass] 01020304050 Depth of Waste [ft] 0 5 10 15 20 25 30 Figure 2-8: Average Moisture Cont ent at Various Levels in Waste 2.3.1.2 Composition The average composition of the composite samples obtained is presented in Figure 2-9. Waste composition data for individual sa mples are presented in Appendix C. Fines, which included soil, degraded material, and sm all pieces of glass and plastic that were too small to separate by hand, consisted of the largest portion of the samples while paper was the largest single waste component. Yard waste and metal were the next largest

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26 components of the waste. These results are in the ra nge of what is expected from an old landfill. Disregarding fines in the excavated samples, the composition of waste excavated is comparable to MSW compos ition from 2001 (US EPA 2001). The yard waste content, construction and demolition, paper, plastic, and me tal container content would be expected to be highe r in the old landfill as it was filled before mandated source separation and alternate dispos al requirements. Subsequent ly, recycling programs, Class III (construction and demolition) landfills, and yard waste programs have served to divert much of these waste streams from landfills. (a) Paper 18% Plastic 7% Yard Waste 12% Textiles 5% Retained Fines (by No. 40 sieve)34% Passing Fines(through No. 40 sieve)15% Stone/Metal 7% Glass/Ceramic 2% (b) Paper 36% Plastic 13% Yard Waste 24% Textiles 9% Glass/Ceramic 5% Stone/Metal 13% Figure 2-9: Average Waste Composition (a ) with All Landfill Components Including Fines (b) without Fines, Waste Components Only. 2.3.2 Decomposition—Biochemical Methan e Potential and Volatile Solids The methane yield analysis was perfor med on 17 of the composite samples obtained during waste excavation. BMP results are presented in Table 2-2, and data and calculations from the procedure can be found in Appendix D. Methane yield varied from 0.011 to 0.255 L CH4/g VS, with the average being 0.12. The BMP values from the

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27 samples obtained from the old cells represent all the borings and va rious depths within the landfill cell. Table 2-2: Moisture Content, Volatile Solids and Biochemical Methane Potential Sample Moisture Content Volatile Solids (Mass VS/total mass) Biochemical Methane Potential [%] [%] [L CH4/g VS] 2-2 37.6% 54.1 0.096 2-4 34.8% 43.8 0.014 2-5 34.8% 53.5 0.015 2-6 31.9% 38.5 0.011 6-2 43.4% 70.1 0.181 6-3 27.5% 50.9 0.141 6-4 26.7% 75.0 0.035 6-6 42.8% 57.3 0.015 7-2 24.2% 59.9 0.193 7-3 32.1% 69.7 0.200 7-4 38.1% 69.2 0.088 7-5 41.8% 71.2 0.092 12-2 29.4% 58.2 0.228 12-5 40.4% 28.4 0.050 12-61 43.3 0.023 13-3 15.1% 73.8 0.255 Celulose2 0.39 Newspaper2 0.11 1 Moisture content datum for 12-6 was not available 2 Cellulose and newspaper were analyzed as BMP controls and moisture content and volatile solids were not measured. By comparing the methane yield values of the waste samples to BMP values of waste from other studies, a bett er idea of degree of degrad ation can be seen. Typical methane yield of the organic fraction of fresh MSW samples previously studied (Appendix E) range from about 0.20 to 0.24 L CH4/g VS (Chynoweth et al., 1993; Owens and Chynoweth, 1993; Townsend et al., 1996). The data indicat e in Figure 2-10 that the samples at lower depths from 15 to 30 feet (4 .5 to 9 meters) in the landfills have lower methane yield and therefore are more degr aded. Though one could assume that the difference between the degradation results from the different waste ages of the upper and

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28 lower lifts, the time period between placement of lifts was fairly short, and so this is not an adequate explanation for the difference in the level of degradation. The less degraded samples tend to be from the top of the landfill cells where moisture was not as prevalent. Biochemical Methane Potential, BMP [L CH4/g VS] 0.000.050.100.150.200.250.30 Depth of Sample [ft] 0 5 10 15 20 25 30 Figure 2-10: Methane Yield Box Plot with Respect to Sample Depths 2.3.2 Soil Content Soil content data—mass of soil divided by total sample mass—were calculated for 16 of the composite samples that had available volatile solids data. The approximate soil content values are corroborated by observat ions of the compression samples. Soil content ranged from 15.4% to 63.9% and aver aged 32.6%. The soil content tended to be fairly high in the waste samples, indicating th at cover soil was mixed with waste samples

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29 removed from the landfill. The soil conten t appeared higher in the mid–depth range (see Figure 2-11), where the cover soil layer was located according to landfill records. Soil Content [%] 010203040506070 Depth of Sample [ft] 0 5 10 15 20 25 30 Figure 2-11: Soil Content Box Pl ot at Various Sample Depths 2.3.3 Compression Analysis Waste compression testing was performed on the 24 waste samples removed from the landfill and one cover soil sample, and data obtained during compression testing was converted to specific weight-app lied pressure relationship. As an example, data from Sample 6-2 is presented in Figure 2-12 for both raw data (2-11(a)) and specific weight versus applied stress (2-11( b)) at initial time and after 15 minutes. Data for all compression tests can be found in Appendix F.

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30 y = 63.453x-0.1953R2 = 0.9992 y = 91.981x-0.2269R2 = 0.9985 0 2 4 6 8 10 12 14 16 -5,00010,00015,00020,00025,000 Force [lb]Sample Thickness, H [in.] Initial Measurement (t=1 sec.) Final Measurement (t=15 min) (a) y = 7.7588x0.2269R2 = 0.9985 y = 11.086x0.1953R2 = 0.9992 0 10 20 30 40 50 60 70 80 -2,0004,0006,0008,00010,00012,00014,000 Vertical Applied Pressure [psf]Specific Weight, g [lb/ft3] Initial Measurement (t=1 sec.) Final Measurement (t=15 min) (b) Figure 2-12: Example Compre ssion Analysis Data for Samp le 6-2 (a) Raw Data Plot Sample Thickness versus Applied Force, (b) Specific Weight versus Pressure

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31 When compared with other compression data from similar studies, these data are within the range of previously reported densities. As a comparison, all compression data points obtained in this research were plotte d with data from similar studies conducted by Beaven (2000). In the Beaven study, a sa mple of aged MSW obtained from a 30-yearold landfill with a mixture of shredded and unprocessed waste (AG1) was compressed at field capacity, and a sample of dry, fresh, crude domestic refuse (DM3) was compressed. These two samples represent the minimum a nd the maximum expected densities of MSW as a function of applied stress. Figure 2-13 presents the data from the previous study and data from this study. The majority of data fall within the expect ed range approximated by the two Beaven datasets. The compost and cardboard samp les were also plotted with the data and the cardboard, as expected, is less dense than the fresh dry waste. The compost is within the range of the waste samples, but the younger sample is denser than the 6–month–old compost, likely because of th e higher moisture content. Two of the waste samples excavated from the old landfill cells exceeded the density of Beaven’s bioreactor waste density. Both Samples 2-3 a nd 12-4 were observed to be denser because the compression samples were observed to cont ain more than 50% clayey soil. The soil sample, as expected, was considerably de nser than all of the waste samples.

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32 0 20 40 60 80 100 120 140 02,0004,0006,0008,00010,00012,000 Applied Pressure, [psf]Specific Weight, [pcf] DM3 dry (Beaven 2000) AG1field cap. (Beaven 2000) Waste (this study) Compost 1 (3 wk. old) Compost 2 (6 mo. old) Cardboard Cover soil (6-1) Sample 2-3 Sample 12-4 Figure 2-13: Specific Weight versus Applied Pressure for all Compression Data Bounded by Dry Fresh Waste and Mature Old Waste at Field Capacity The compression indices used in the data analysis for this study are the coefficient and exponent of the power law regression line fit to compression data for specific weight () – applied vertical stress () relationship. The coefficient, 1000 , corresponds to the theoretical specific weight of the sa mple at 1,000 psf, and the exponent, C, is a constant that describes the slope of the regression lin e. Figures 2-14 through 2-18 present the data and regression lines for each of the borings—2, 6, 7, 12, and 13 respectively. The soil sample (6-1) was taken from Boring 6 and is included in Figure 2-15, while compost and cardboard compression is presen ted in Figure 2-19. The 1000 and C values are summarized in Table 2-3 with the R-squared values of the regression analysis. The average 1000 value was 53.0 pcf, and the minimum was 25.8 pcf for sample 6-3. The

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33 maximum 1000 values for waste samples were 81.9 and 77.0 pcf for Samples 2-3 and 124, respectively, the two samples observed w ith high clayey soil content. The average Cexponent value for waste was 0.18, and values were in the ranged from 0.12 to 0.22. The 1000 and C values for cover soil were 113.8 and 0.07, respectively. Higher 1000 and lower C values indicate less compressible samples, while lower 1000 and higher C values indicate a sample that is more easily compressed. 2-2: = 46.788 0.19722-3: = 81.874 0.1222-4: = 46.7 0.21232-5: = 60.473 0.17152-6: = 51.821 0.21360 20 40 60 80 100 120 0.01.02.03.04.05.06.07.08.09.010.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-14: Specific Weight vers us Applied Pressure for Boring 2

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34 6-1 (soil): = 113.82 0.06576-2: 0.19546-3: 0.21476-4: 966-5: = 60.26 0.16996-6: 0.17640 20 40 60 80 100 120 140 0.01.02.03.04.05.06.07 .08.09.010.011.012.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-15: Specific Weight vers us Applied Pressure for Boring 6 7-2: 0.20197-3: 0.19777-4: 0.16367-5: 0.14740 10 20 30 40 50 60 70 80 90 100 0.01.02.03.04.05.06.07.08.09.010.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-16: Specific Weight vers us Applied Pressure for Boring 7

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35 12-2: 0.219112-3: 0.188912-4 0.118612-5: 0.185512-6: 0.18580 20 40 60 80 100 120 0.01.02.03.04.05.06.07.08.09.010.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-17: Specific Weight vers us Applied Pressure for Boring 12 13-2: = 44.107 0.190113-3: = 33.86 0.184613-4: = 61.519 0.153513-5: 66.732 0.143813-6: = 57.383 0.19330 10 20 30 40 50 60 70 80 90 100 0.01.02.03.04.05.06.07.08.09.010.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-18: Specific Weight vers us Applied Pressure for Boring 13

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36 Cardboard: = 21.496 0.2414Compost (3 wk. old): = 55.294 0.1579Compost (6 mo. Old): = 38.122 0.15770 10 20 30 40 50 60 70 80 90 0.01.02.03.04.05.06.07.08.09.010.0 Pressure, [kpsf]Specific Weight, [pcf] Figure 2-19: Specific Weight versus Applied Pressure for Cardboard and Compost Samples When looking at the compression data a nd assessing the influence of moisture content on the waste compressibility, it is helpful to consider the dry specific weight, dry, of the samples relative to the applied pressu re. Though the effects of pore pressure were assumed not to affect the applied load data in the v relationship, specific weight is increased due to the presence of water. The specific weight of the compression data was adjusted by the moisture conten t percentage to determine a dry relationship. Like the compression indices related to the bulk speci fic weight (including moisture content), regression lines were fit to the data to determine the 1000 and C of relative to the dry data. Because the data were adjusted by a constant value for each sample and compression analyses were not perf ormed on dry waste samples, the C exponent and R2 values did not change—just the 1000 coefficient.

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37 Table 2-3: Compressibility Indices 1000 and C of Compression Samples Sample 1000 f (bulk)1000 f (dry)C R2 2-2 46.79 29.180.197 0.992 2-3 81.87 64.360.122 0.974 2-4 46.70 30.430.213 0.998 2-5 60.47 39.420.172 0.991 2-6 51.82 35.260.214 0.999 6-1 (soil) 113.82102.440.066 0.995 6-2 42.74 24.190.195 0.999 6-3 25.76 18.680.215 0.966 6-4 56.51 41.400.160 1.000 6-5 60.26 36.840.170 0.999 6-6 44.74 25.590.176 0.998 7-2 39.11 29.610.202 1.000 7-3 38.59 26.200.198 1.000 7-4 60.75 37.600.164 0.993 7-5 50.46 29.370.147 0.961 12-2 39.11 27.600.219 0.989 12-3 34.11 24.870.189 0.998 12-4 77.01 55.740.119 1.000 12-5 58.71 35.000.186 0.997 12-6 58.94 36.910.186 0.997 13-2 44.11 29.250.190 0.986 13-3 33.86 25.710.185 0.995 13-4 61.52 41.940.154 0.997 13-5 66.73 40.730.144 1.000 13-6 57.38 35.940.193 0.992 Cardboard 21.50 20.420.241 0.995 Compost (3 wk.) 55.29 38.710.158 0.996 Compost (6 mo.) 38.12 34.310.158 0.989 When compared with other published studies of waste compressibility, these data have similar compression indices. Because of the geotechnical convention for describing waste (initially clay) compressibility in terms of cC and cC', difficulties arise comparing indices from this study. From published da ta from Pelkey (1997) and Beaven (2000), 1000 and C values were determined. Table 2-4 provides waste compression sample details for other studies.

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38 Table 2-4: Summary of Compression Study Data Sample Reference Description Range of Applied Pressure 1000, bulk [psf] C [-] DM3 FC DM3 Dry PV1 FC PV1 Dry AG1 FC AG1 Dry Beaven 2000 Crude, fresh, MSW, field capacity MC=102% Crude, fresh, MSW, MC=51% Pulverized, fresh, MSW mC=141% Pulverized, fresh, MSW MC = 66% Aged MSW (30yr) and soil mixture, field capacity Aged MSW (30yr) and soil mixture 400-10,000 psf (10-500 kPa) 51.2 25.3 41.8 26.9 72.8 41.5 0.16 0.25 0.14 0.26 0.09 0.16 LSR2 LSR3 LSR4 LSR5 LSR7 LSR8 Pelkey 1997 Aged MSW (6yr), i=10.4, CÂ’c=0.17 Aged MSW (3yr), i=8.9, CÂ’c=0.22 Artificial MSW, i=7.9, CÂ’c=0.22 Mixture of above, i=7.6, CÂ’c=0.24 Mixture of above, i=7.6, CÂ’c=0.23 Mixture of above, i=7.9, CÂ’c=0.21 200-40,000 psf (10-2000 kPa) 93.5 91.8 81.5 83.5 80.9 82.1 0.11 0.17 0.17 0.20 0.18 0.15 2.4 Correlations and Discussion This section looks at the re lationships between different waste sample properties to explore the significance of the data gathered and described in the pr evious section. The relation of compressibility parameters and le vel of waste degradati on are of particular interest and are evaluated here. Data points are plotted on vari ous figures in this section,

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39 and statistical t-tests (95% confidence interval) were used to determine statistical differences between sample sets and presente d in Appendix G. Because these data were obtained in field sampling and the aforementioned difficulties of analyzing landfills (heterogeneous waste, difficult obtaining proper sample size, et c.), precise relationships are difficult to draw. Instead qualitative relationshi ps are identified base d on data trends. All waste data are presented in Appendix H with correlations. 2.4.1 Waste Degradation Waste samples excavated from the landfill had varying degrees of degradation. Samples found deeper (15-30 feet below surface) in the landfill were more degraded (and statistically different) than th e samples found less than 15 feet deep. Degraded samples had methane yield measurements less than 0.095 L CH4/g VS and undegraded samples greater that 0.095. This di stinction is maintained th rough the remainder of this discussion. The degraded samples averaged 75% less methane yield than the undegraded samples. The greater degradation at lower levels of the landfill could be caused by a number of factors. The simplest solution is that the waste is older at the bottom. However, landfill records and accounts indi cate that two lifts of wast e were placed over a short period of time—a matter of months—which would not be enough time to reflect the disparity between upper and lower lift me thane yield values. Because the waste compositions for upper and lower waste layers were the same, the differing moisture content values of waste sample are the most likely cause of increasing degradation with depth. Though the data only suggest a 6% difference in average moisture content between the upper and lower samples, field observations of very wet and sometimes saturated waste samples from the lower half of the landfill sugge st the rationale for

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40 greater degradation at greater depths. Becau se the waste has further degraded at the bottom of the landfill over 20 to 30 years, the volatile solids measurements (see Figure 220(a)) are lower than in upper layers where drier conditions do not facilitate anaerobic decomposition. Lastly, percent fines and so il content (see Figure 2-20(b)) averaged 12% and 17% higher, respectively, in the lowe r samples within the landfill. Though the degraded samples are more variable, the two datasets are statistically different. The greater soil content in degraded samples is du e in part to the lower percentage of the biodegradable fraction currently in the wa ste composition. Duri ng degradation in a landfill, readily degradable food waste and pape r are broken down and only fine particles remain and thus the mass of fine particles increases. Additionally, the mass fraction of paper decreases during decomposition that caus es the fraction of so il to increase, though the mass of soil does not change. Higher soil content could also be attributed to the higher composition of cover soil in the samp les obtained from lower depths than those from the upper samples.

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41 UndegradedDegraded Volatile Solids Content [%] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Figure 2-20(a): Waste Degr adation Box Plots (a) Vola tile Solids versus BMP; UndegradedDegraded Soil Content [%] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

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42 Figure 2-20(b): Waste Degradation B ox Plots (b) Soil Content versus BMP 2.4.2 Compressibility and Waste Index Properties The compression coefficient, 1000, and compression exponent, C, describe the compressibility of the waste samples a nd were comparable to previous waste compression studies despite the departure fr om the conventional compression indices. A direct relationship exists between compressibility and the C-exponent. Low C values such as those seen in soils indicate le ss compressibility. Compressibility and 1000 and are inversely proportional. Because 1000 corresponds to the theoreti cal density of a sample under a 1000 psf load, lighter, less dense sa mples such as dry waste or cardboard compress easily yet have a low initial specific weight. Moisture content and soil content affect the specific weight – applied stress relationship. As moisture content increases, the specific weight increases while not adding to the strength propert ies of the sample (assuming the pore water pressure does not increase). Moisture content is directly related to the compression coefficient for bulk specific weight (Figure 2-21(a) ); the specific weight coeffi cient increases as moisture content increases in waste samples. Sim ilarly, the compression exponent is inversely related to moisture content (Figure2-21(b)) in keeping with higher C values being less compressible. Neither 1000 bulk nor C is strongly correlated with moisture content, but a clear relationship is evident.

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43 y = 96.063x + 16.081 R2 = 0.2630 10 20 30 40 50 60 70 80 20%25%30%35%40%45% Moisture Content, MC [%]Compression Coefficient for Bulk Specific Weight, 1000 bulk [pcf] Figure 2-21: Compression Indices versus Mo isture Content: (a) Bulk Specific Weight Compression Coefficient versus Mois ture Content, and (b) Compression Exponent versus Moisture Content

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44 y = -0.1241x + 0.2274 R2 = 0.11140.00 0.05 0.10 0.15 0.20 0.25 20%25%30%35%40%45% Moisture Content, MC [%]Compression Exponent, C [-] (b) Figure 2-21—Continued Soil content is directly related to the compression coefficient for bulk specific weight (Figure 2-22(a)), that is, the specific weight coefficient generally increases as soil content increases in waste samples. Sim ilarly, the compression exponent is inversely related to soil content (Figure 2-22(b)), in keeping with higher C values being less compressible. Neither 1000 bulk nor C is strongly correlated with soil content, but the sample sets are statistically different.

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45 y = 24.761x + 39.115 R2 = 0.1630 10 20 30 40 50 60 70 80 90 0%10%20%30%40%50%60%70% Soil Content, SC [%]Compression Coefficient for Bulk Specific Weight, 1000 bulk [pcf] Low Soil Content High Soil Content ll (a) y = -0.0904x + 0.2187 R2 = 0.51420.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24 0%10%20%30%40%50%60%70% Soil Content, SC [%]Compression Exponent, C [-] Low Soil Content Hi g h Soil Content ll (b) Figure 2-22: Compressibility Indexes versus Soil Content: (a) Bulk Specific Weight Compression Coefficient versus Soil C ontent, and (b) Compression Exponent versus Soil Content

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46 The relationship between compressibility indices and in-place specific weights is not strongly correlated. The bulk specific weight compressibility coefficient (1000, bulk) increases as the in-place bulk specific weight increases (Figure 2-23). The relationship is similar between dry specific weight compressibility coefficient (1000, dry) which increases as the in-place dry specific weight increas es. However, the compression coefficient, C, does not change as a function of in-p lace specific weight for either bulk (bulk) or dry (dry). y = 0.347x + 27.415 R2 = 0.2950 10 20 30 40 50 60 70 80 020406080100120 Bulk Specific Weight, bulk [pcf]Compression Coefficient for Bulk Specific Weight, 1000 bulk [pcf] Figure 2-23: Bulk Specific Weight Compression Coefficient versus In-Place Bulk Specific Weight 2.4.3 Compressibility and Waste Degradation Waste compressibility indexes (1000, bulk, 1000, dry, and C) were compared to the degree of decomposition measured by methan e yield. The box plots in Figure 2-24 present the relationship of the compressibility parameter with respect to the level of

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47 degradation. The compressibility coeffici ents for both bulk and dry specific weights, 1000, bulk and 1000, dry, were greater and statistically di fferent for the degraded samples (Figure 2-24(a) and (b)), meaning degraded samples were less compressible than the undegraded samples. Additionally, the compression exponent, C, was lower for degraded samples with similar variabilities (Figure 2-24(c)). UndegradedDegraded Compression Coefficient for Bulk Specific Weight, 1000, bulk [pcf] 0 10 20 30 40 50 60 70 Figure 2-24: Compressibility Indices for Undegraded and Degraded Samples: (a) Compressibility Coefficient for Bulk Specific Weight versus BMP, (b) Compressibility Coefficient for Dry Specific Weight versus BMP, and (c) Compressibility Exponent versus BMP

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48 UndegradedDegraded Compresion Coefficient for Dry Specific Weight 1000, dry [pcf] 0 10 20 30 40 50 (b) UndegradedDegraded Compression Exponent, C [-] 0.00 0.05 0.10 0.15 0.20 0.25 (c) Figure 2-24—Continued

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49 The relationship of compressibility indexe s and volatile solids is similar to the relationship of compression indi ces and BMP values (Figure 2-25). Low volatile solids samples (also low in methane yield) were le ss compressible, as indicated by the greater compression coefficient for bulk specific weight, 1000, bulk and lower compression exponent, C. y = -43.005x + 59.575 R2 = 0.3110 10 20 30 40 50 60 70 0%10%20%30%40%50%60% Volatile Solids, VS [%]Compression Coefficient for Bulk Specific Weight, 1000 bulk [pcf] Undegraded De g rade d ll Figure 2-25: Compressibility Indices versus Volatile Solids Content (a) Bulk Specific Weight Compressibility Coefficient versus Volatile Solids, and (b) Compression Exponent vers us Volatile Solids

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50 y = 0.0576x + 0.1731 R2 = 0.13330.00 0.05 0.10 0.15 0.20 0.25 0%10%20%30%40%50%60% Volatile Solids, VS [%]Compression Exponent, C [-] Undegraded De g raded (b) Figure 2-25—Continued These findings of lower compressibility of degraded samples than that of less degraded samples corroborate the recent study by Hossain et al. (2003). This study used laboratory oedometer tests to measure compressi bility parameters for waste at different stages of decomposition related to bioreactor and traditional landfill practices. Bioreactor samples were more degraded, with less volat ile solids, and were less compressible than control samples. The Hossain et al. (2003) results indicate a more pronounced difference between degraded and less degraded samples than data from this study. This is likely a reflection of the compression index (Hossa in et al. used compression index, Cc) and the difference between laboratory waste samples and samples obtained from a landfill in this study, which have soil mixed with waste. Th e measure of degradation in the Hossain et al. study ((C+H)/L) is the sum of the measure of ce llulose and hemicellulose

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51 concentration divided by the lignin conten t. Though the methodology and measure of waste decomposition are different, the conclusions are the same. 2.5 Summary and Conclusions Waste was sampled and analyzed at various depths of the 30–foot profile of 20–to 30–year old waste in an unlined landfill. Typical waste index properties—including moisture content, specific weight, and com position—were measured, as were the degree of degradation and the compressibility of waste samples. When properties were compared, no strong correlations were evident because of the great va riability of samples obtained from the landfill, t ypical of field sampling in la ndfills. However, distinct statistical differences were noted based on samples with greater degradation and soil content. Overall, the landfill had higher moisture content and soil cont ent than typically expected in a landfill operati ng today because of different op erating practices. A distinct delineation between the top 15 feet of the la ndfill and the bottom 15 feet was evident. Waste at the bottom, though not appreciably ol der than the top lift, was more degraded, with greater soil content, moisture content, specific weight, and lower volatile solids content. Compressibility parameters were compared with the waste index properties. Waste with higher moisture and soil contents were less compressible than samples with lower values. The compression exponent, C, ranged from 0.196 to 0.214 with an average of 0.20 for dry, undegraded waste; compression ex ponent values for degraded waste ranged from 0.165 to 0.18 and averaged 0.18. Init ial in-place specific weight had no bearing on the compressibility. The compressibility parameters in degraded samples, with lower methane yield and volatile solids, indicate that this waste is less compressible. This

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52 finding can be attributed to a number of fact ors including greater initial soil content or greater relative soil content as a result of th e degraded organic fraction. The degraded, less compressible, samples correspond to waste at the bottom of the landfill.

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53 CHAPTER 3 CONE PENETRATION TESTING FO R CHARACTERIZING LANDFILLED MUNICIPAL SOLID WASTE 3.1 Introduction The cone penetration test (CPT) is an in situ test procedur e commonly used for subsurface soils exploration. In a CPT, or sounding, a steel cone is pushed into the ground at a constant velocity by a hydraulic jack, while the resi stance to the cone tip and friction on a free moving sleeve immediately behind the tip are measured periodically as the cone is advanced. Penetr ation data are compared with empirical relationships to identify soil properties and soil stratification commonly us ed in foundation analysis. Empirical correlations help determine ma ny soil properties including friction angle, relative density, coefficient of earth pressure at rest and modulii for sands, in addition to, undrained shear strength, sensitivity, earth pr essure at rest, overc onsolidation ratio and modulii for clays. Pore water pressure may also be measured in conjunction with the penetration sounding which is known as CPTU or piezocone testing. Because of its relative low cost and the convenience, the CPT is increasingly used for subsurface exploration. Cone penetration testing has only seen limite d use in landfill applications and little data are available. Because of the heteroge neous nature of municipal solid waste (MSW) within a landfill, drawing meaningful conclusions from cone penetration data has been difficult. However, cone penetration testing could be a useful tool for evaluating landfill conditions should meaningful correlations be drawn between cone data and landfill

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54 engineering properties such as moisture cont ent, specific weight (density), degree of degradation, and compressibility. The CPT c ould be used to predict settlement before final cover placement or to assess slope stab ility, and Sillan (1995) has suggested that CPTs can be used to determine the level of decomposition in conjuncti on with bioreactor landfill technology. A number of studies have used CPTs in landfills (Table 3-1), but none have been able to draw correlations between landfill properties and CPT data. The three studies discussed below present more detailed resear ch conducted with CPTs and landfills. Each study was carried out with various objectives including assessing the in situ condition of waste and mechanical properties, finding saturated zones, and drawing correlations between resistance and waste character. At a California landfill, CPTs were performed to help delineate stratification and saturated zones within the landfill, but no useful conclusions were drawn for us ing CPTs to investigate landfills with the exception of identifying cover soil types (Siegel et al., 1990). At another landfill in the midwestern United States, CPT soundings were performed on a chemically stabilized industrial waste fill before installing a cap to determine the in situ condi tion of the materials—namely depth and mechanical characteristics. Data obtained were used to make settlement predictions and compared w ith actual settlemen t measurements (Oakley, 1990). The calculated values of total consolidation sett lement developed using CPT data appeared reasonable compared to original design calcula tions and actual settlement data. Finally, at a Florida landfill, Sillan (1995) tried to correlate CPT results with degree of decomposition by testing fill areas of differing ages. CPTs were performed on different cells at the same site with vary ing waste ages (Sillan, 1995).

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55Table 3-1: Summary of Previous Cone Penetration Test in Landfills Author(s) Year Landfill Location Waste age [years] No. Tests Depth Range [feet] Purpose Tip Resistance, QT [ton/ft2] Friction Ratio Range, FR [%] Trends Soil types Results Belfiore et al. (1990) Central Italy N/A N/A 16 Determine effects of compaction relative to landfilling industrial sludges. Average: 2.5 (corrected) Range: 3 to 15% Average 5% N/A N/A Determined waste partially saturated. Developed undrained strength vs. depth relationship. Duplancic (1990) Panoche Landfill, California 2 to 10 10 N/A Long-term deformation analysis of hazardous waste landfill. N/A N/A N/A N/A Hinkle (1990) Los Angeles Harbor, California 4 to 25 8 50 Test consistency of waste prior to building buildings over capped landfill. 50 tsf 3% N/A Only 40% of soundings reached desired depth. Oakley (1990) Mid-western U.S.A. 2 to 13 11 30 Determine in situ conditions and predict settlement in chemically stabilized landfill. Range: 2 to 100 tsf Average: 20 tsf Range: 0.5 to 10% Average: 5% N/A N/A Calculated values of total settlement using CPT data appear reasonable compared to design and actual settlement. Siegel et al. (1990) Operating Industries, Inc. (OII), California 6 to 40 18 16 to 123 Delineate stratigraphy and saturated zones. Range: 10 to 235 Range: 0 to 8% Average: 4% Increasing QT with depth: 0.25 tsf/ft Sand Clayey silt Could not distinguish cover soil layers. Two tips broke off. Pore pressure transducer system unsuccessful. Sillan (1995) Alachua County Southwest Landfill, Florida 0 to 7 7 to 10 and 10 to 22 35 57 Compare CPT to level of degradation. Range: 54 to 85 Range: 1.37% to 2.89% Increasing QT with 0.4 to 1.8 tsf/ft Sand to Silty sand Silty Sand to Sandy Silt Correlations of QT and FR to biodegradability were not significant. Reinhart et al. (2004) Highlands County Landfill 28 20 to 30 Evaluate differences between landfilled biosolids, bioreactor landfill, and landfilled MSW. Range: 60 to 100 Range: 0.5 to 3% Coarsegrained sandy silty soil No statistical difference between CPT data between studies.

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56 The following research was conducted to st udy the use of cone penetration testing for landfill applications in conj unction with a vertical expa nsion feasibility study at the Polk County North Central Landfill in central Florida. The objective of the research presented in this chapter is to draw correla tions between cone penetration tip and sleeve resistance and pore pressure measurements with landfill properties such as moisture content, soil content, degree of degradation, and specific weight. To reach this objective, CPT data were compared with data obtained from analyses conducted on waste excavated while boring into the waste in the same location as some of the CPTs. Waste samples were analyzed for waste composition, methane yield, moisture content, and volatile solids (VS). 3.2 Materials and Methods 3.2.1 Site Description At the Polk County North Central Landfill, cone penetration testing was conducted as part of the vertical expa nsion feasibility study described in Chapter 2. Geotechnical studies of the landfill waste were conducted to determine if siting a new, lined landfill atop the existing shallow cells is feasible. The site is described in details and figures in Chapter 2. Rather than investigating the en tire landfill, a small test parcel measuring 120 feet by 120 feet was selected for in-depth investigation in which CPT soundings were performed. The landfill cells were constructed by excavating trenches in native soil approximately 8 to 10 feet (2.5 to 3 meters) be low the surface and filling with waste. The trenches were then covered with excavated so il, and a second lift of waste placed on top. The original permit application indicated th at waste was filled in 100 by 600–foot (30 by 180–meter) trenches; however, no evidence of this was found in the CPTs or auger

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57 borings. The second lift appears to have b een an area fill; that is, it contains no soil divisions. The site is underlain by approximately 30 feet of overconsolidated cohesive soils with sand lenses. Clays, silts, sandy clays, cl ayey sands, and silty sands are the soil types found. The soil is underlain by weathered li mestone or siltstone (Jones, Edmunds & Associates, 2004). 3.2.2 Cone Penetration Testing The cone penetration test cons ists of pushing a steel cone tip attached to a series of push rods into the waste at a constant rate while measuring the resi stance on the tip and on the friction sleeve. The electric piezocone penetrometer used in this study measured tip resistance, sleeve friction, and dynami c pore pressure with transducers. The transducers in the penetrometer tip transmitted data to acquisition equipment via cables inside the push rods. Specific details of the procedure and equipment specifications can be found in the Standard Test Method for Mechanical Cone Penetration Tests of Soil (ASTM D3441-98) (ASTM, 1998) and the Standard Test Method for Performing Electronic Friction Cone and Piezoc one Penetration Testing of Soils (ASTM D5778-95) (ASTM 2000b). CPT soundings we re performed on January 27th and 28th, 2004 by Ardaman & Associates, Inc. (Orlando , Florida) using a proprietary, 10–cm2 penetration tip manufactured in-house. The locations of the CPTs and the large diameter auger borings discussed later are presented in Figure 3-1. 3.2.2.1 CPT equipment The components of the piezocone penetromet er consist of a cone tip, a free moving friction sleeve, numerous soil and water seals, and an orifice with a saturated filter where pore water pressure is measured. A schematic of a typical piezocone tip is included in

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58 Figure 3-2. Strain gauge load cell transducer s inside the instrument measured forces as the instrument penetrated the waste and soil. The cone instrument was threaded into 1– meter rods and pushed into the ground by a 20-ton hydraulic jack mounted in a ballasted truck. Inside the climate controlled truck are the hydrau lic ram and data acquisition equipment. Easting 7 0 6200 706 2 50 7 06 3 0 0 7 0 6350 Northing 1338 4 00 1338 4 50 1 3 38 5 00 1 3 38 5 50 1 3 38 6 00 Cone Penetration Sounding Cone Penetration Sounding and Large Diameter Borings CPT-1 CPT-6 CPT-8 CPT-7 CPT-15 CPT-12 CPT-13 CPT-11 0 50100 SCALE [FEET] TEST PARCEL CPT-9 CPT-10 CPT-2 CPT-3 CPT-4 CPT-5 CPT-19 CPT-1 CPT-14(approx.) CPT-6 Figure 3-1: Layout of Test Parcel, Cone Penetration Test s, and Bucket Auger Borings 3.2.2.2. CPT procedure and data The piezocone tip was pushed into the ground at a constant rate of 2 cm/sec. Pressure readings were meas ured approximately 5 times per second and recorded by a personal computer with data acquisition software in the truck. The electric signal readings from the strain gauges were conve rted into engineering units based on the

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59 calibration of the cone tip. Penetration pro ceeded 1–meter rod at a time until the test was ceased when tip resistance or inclinometer readings became excessive as a result of buried obstructions encountered. Figure 3-2: Typical Pi ezocone Tip Schematic The parameters measured and recorded with respect to depth were tip resistance (QT), sleeve friction (FS), and pore pressure (U), and fr om these data the friction ratio (FR) was calculated. The following relationships describe the derivation of these values: Adapted from Lunne et al. (1997) Inclinomete r Shaf t Push rod connector Soil seal Water seal Signal cable Water seal Soil seal Cone Filte r Cone sensor Friction sleeve 60° Pressure senso r 37.5mm A=10cm2 133.7mm A=15c m 2

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60 Tip Resistance: area. projected horizontal force; axial ultimate ; resistance tip cone : where c c T c c TA Q Q A Q Q Sleeve Friction: sleeve. of area surface sleeve; on force friction ultimate ; resistance friction : where s s s s s sA Q F A Q F Friction Ratio: . resistance tip cone friction; Sleeve ratio; friction : where T S R T s RQ F F Q F F Using the data obtained from tip resistan ce, sleeve friction, and pore pressure, soil classifications are made by the data acquisiti on software based on empirical relationships. The media penetrated are classified based on the observed piezocone data: tip resistance, sleeve friction, friction ratio, and pore pressu re. Generally, sandy soils exhibit high tip resistance and low sleeve friction and pore pressure, while clay exhibits lower tip resistance but higher sleeve friction and pore pressure. Th e soil classification system used is from Robertson et al. (1986), which assigns so il index numbers based on CPT data, which correspond with Unified Soil Clas sification System (U SCS) (ASTM D2487) (ASTM 2000a) soil classes. The soil classi fication numbers along w ith description and corresponding USCS classification are presented in Table 3-2.

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61 Table 3-2: Soil Classification Numbers, Descriptions and USCS Class for Cone Penetration Testing (R obertson et al., 1986) Soil Classification Number Description USCS 1 Sensitive Fine Grained OH/CH 2 Organic Material OH 3 Clay CH 4 Silty clay to clay CL/MH 5 Clayey silt to silty clay MH/CL 6 Silty sand to sandy silt SC 7 Sand to sandy silt SP/SC 8 Sand to silty sand SP 9 Sand SP/SW 10 Gravelly sand to sand SP/GW 11 Very stiff finedgrained OC Clay 12 Sand to Clayey Sand Cemented 3.2.2.3 CPT statistical analysis and summary Cone data vary a great deal necessitati ng parametric statistical analysis to summarize the wide range of data over a desi red depth range. To reduce and summarize the data, the arithmetic mean, geometric m ean, median, mode, and standard deviation were used to measure central tendencies and variability of each sounding for depth ranges of interest. To compare CPT data, depth ranges of interest were selected to include only waste and only soil in one analysis, as well as various depth ranges within the waste in another analysis. Cone penetration data typical ly follow a lognormal distribution, as is the case with cone tip resistance through the waste portion of CPT 7 presented in Figure 3-3; therefore, the geometric mean (i.e. the most frequent occurrence of the lognor mal distribution) was selected to singularly represen t the tip resistance, sleeve frict ion, friction ratio, and pore pressure over a given depth (Lunne et al., 1997). The lognormality of several samples was evaluated and compared with the normality using the statistical software package

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62 MINITAB, Version 14 (www.minitab.com, State College, Pennsylvania), using an Anderson-Darling normality test. In all cases tested for lognormality versus normality, the data fit better to the lognormal probabi lity distribution (Appe ndix I). Negative values of cone penetration data, while not often encountered, were discarded when calculating the geometric mean. Figure 3-3: Lognormal Distribution of Tip Resistance of Waste in CPT 7 (Depth: 3-30ft) 3.2.3 Waste Boring, Sample Collection, and Characterization After the CPTs were performed in the landfill test area, large diameter bucket auger borings were performed in the same locations as five of the CPTs. Waste removed from the borings was sampled and analyzed in the laboratory for moisture content, composition, volatile solids, and biochemical methane potential. The details and results of each of these procedures are presented in Chapter 2. Because the large volume of Tip Resistance, QT [tsf]Frequency 180 150 120 90 60 30 0 90 80 70 60 50 40 30 20 10 0 Lognormal distribution Geometric Mean

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63 waste removed from the bucket could not all be analyzed, a composite, 20-pound (9kilogram) representative sample of waste was taken for every 5-foot (1.5-meter) interval in each of the borings. Material removed fr om the borings was weighed, and volume was approximated by measuring boring depth with a surveyors tape to determine specific weight. The compressibility of waste from each composite sample point was evaluated using laboratory scale compression analyzer, or oedometer. The information gathered while boring into the landfill was the basis for comparison to CPT data. 3.2.4 Statistical Comparison of Wa ste Properties and CPT Data Waste properties were compared with CPT data, and correlations were examined between various properties and depths. Simila r to the work in Chapter 2, the CPT data were divided into 5-foot (1.5 -meter) intervals in the waste, and the geometric means of CPT data—(tip resistance (QT), sleeve friction (FS), friction ratio (FR), and pore pressure (U))—were compared with other waste index properties—(specific weight (bulk and dry), moisture content (MC), methane yield (BMP ), soil content (SC), and compressibility parameters (1000 and C))—using statistical correlation in an Excel spreadsheet. As discussed in Chapter 2, waste samples were segregated based on the level of degradation and soil content. These distinctions were ma intained when looking at CPT data and were the bases for determining statistical difference (95% confidence interval) using the t-test. 3.3 Results 3.3.1 Piezocone Penetration Test Results Sixteen piezocone penetration tests were performed in the test parcel area to depths ranging from 13 to 54 feet (4 to 16.5 meters) below the surface of the landfill. The tests were ceased when tip resistance or inclinati on values became excessive as hard material in the waste or soil below landfill was encount ered. Of the sixteen CPT soundings, four

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64 were stopped in the waste because of high tip resistance, five penetrated through the waste layers before encountering hard soil below the landfill waste, and seven reached the bedrock below the soil. The locations of the soundings are indicated in Figure 3-1. CPT data through the waste portions of th e tests are summarized in Table 3-3 by presenting the geometric means of the tip and sleeve resistance, friction ratio, and pore pressure. As an example of CPT data, the tip resi stance, sleeve friction, friction ratio, and pore pressure are plotted with respect to depth for CPT-7 in Figure 3-4. The plots indicate the delineation of soil a nd waste especially for tip resi stance. The first 3 feet of the sounding reflects the cove r soil layer. The waste be tween 3 feet (1 meter) and approximately 29 feet (9 meters) deep is evident by the higher va riability of the tip resistance, sleeve friction, and friction ratio in this interval. Below 29 feet (9 meters) in the native soil the data are not as variable as in the waste layer. The increase in pore pressure around 29 feet (9 meters) deep i ndicates where the cone tip encountered the surficial water table. This clear stratifi cation was not always ev ident with other CPT soundings, however. Piezocone penetration results for all CP T soundings can be found in Appendix J. The geometric means of the tip resistances, QT, for all the CPTs ranged from 28 tsf to 77.5 tsf, and the average of the geometri c means was 46 tsf. Sleeve friction, FS, ranged from 0.26 tsf to 1.45 tsf and averaged 1.10 tsf. Friction ratio, FR, varied from 0.72% to 4.54% and averaged 2.66%. Finally, pore pr essure geometric mean values ranged from 0.07 tsf up to 0.90 tsf and averaged 0.25 tsf.

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65 Table 3-3: Summary of Cone Penetration Testing Data in Waste Geometric Mean Sounding Max. Depth Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FRPore pressure, U Soil Type Most frequent [ft] [tsf] [tsf] [%] [tsf] CPT 1 14 40.9 1.31 3.21 0.26 Clay CPT 2* 54 28.0 0.84 3.02 0.10 Clay CPT 3 32 39.5 1.17 2.96 0.90 Clay CPT 4 53 36.9 1.68 4.54 0.13 Clay CPT-5 13 53.4 0.80 1.60 0.15 Sand to Sandy silt CPT-6* 48 35.3 1.25 3.55 0.06 Clay CPT-7* 54 33.4 1.22 3.66 0.07 Clay CPT-8 30 45.4 1.45 3.11 0.16 Clay CPT-9 29 53.1 1.35 2.61 0.08 Sand to Sandy silt CPT-10 52 45.2 1.01 2.26 0.10 Silty sand to Sandy silt CPT-11 27 44.0 1.14 2.68 0.27 Clay CPT-12* 53 36.6 1.01 2.77 0.25 Clay CPT-13* 23 77.5 0.94 1.22 0.17 Gravelly sand to Sand CPT-14 39 51.8 1.06 2.05 0.71 Sand to Silty Sand CPT-15 34 48.3 0.26 0.72 0.23 Sand to Silty Sand CPT-19 46 69.5 ** ** 0.29 Very stiff finegrained Average 35.5 46.2 1.10 2.66 0.25 Std. Dev. 14.8 13.0 0.33 0.98 0.23 *Location of bucket auger boring. **Unreliable data for CPT-19 because of broken tip.

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66 Figure 3-4: Cone Penetra tion Data Plots for CPT 7 0 5 10 15 20 25 30 35 40 45 50 55 60 0200400 Tip Resistance, QT [tsf]Depth [ft] 0 5 10 15 20 25 30 35 40 45 50 55 60 051015 Sleeve Friction, FS [tsf]Depth [ft] 0 5 10 15 20 25 30 35 40 45 50 55 60 050100 Friction Ratio, FR [%]Depth [ft] 0 5 10 15 20 25 30 35 40 45 50 55 60 0123 Pore Pressure, U [tsf]Depth [ft] Cover Soil Waste Native Subgrade Soil Water Table Saturated

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67 3.3.2 Large Diameter Boring Results The results for the waste characterization are summarized in this section and Table 3-4. The waste index properties were determ ined in the laboratory for the five large diameter borings into the landfill. The bori ng locations coincided with the locations of the cone penetration soundings with the same number. Each boring was divided into six sections representing 5-foot (1.5-meter) inte rvals of the boring. The top samples were composed largely of cover soil, so they are not included in th e discussion of waste properties. Complete descrip tions of analysis procedures and discussion of results are found in Chapter 2. 3.4 Discussion 3.4.1 Landfill Stratification 3.4.1.1Comparison of CPT data between soil and waste layers Cone penetration data between known layers of soil and waste at various sounding depths were compared. CPT data wa s divided into depth categories based on known delineation of cover soil, waste, and na tive soil below the landfill observed while conducting the large diameter borings and evid ent in some CPT plots (See Figure 3-4 and Appendix K). Figure 3-5 presents a schematic representation of the landfill stratigraphy. At a depth ranging from 28 to 30 feet below the landfill surface, the surficial aquifer was reached and waste and soil encountered below was saturated. Typically, the first 3 feet of borings were cover soil composed of Sand to Silty sand (Soil clas sification number 8) and Sand to Sandy silt (Soil classificati on number 7) (Robertson et al., 1986). The geometric means of cover soil layer CPT data were tip resi stance of 34 tons per square foot (tsf), sleeve friction of 0.4 tsf, friction ratio of 1.4%, and pore water pressure of 0.16 tsf.

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68 Table 3-4: Summar y of Waste Index Data for Samples Sample Depth Specific Weight Moisture Content Total Fines (R+P) Soil Content Volatile Solids Methane Yield Compression Indices Up. [ft] Low. [ft] bulk [pcf] dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk)1000 (dry) C 2-2 5 10 38.9 24.3 37.63% 47.4% 36.2% 29.6% 0.095 46.8 29.2 0.20 2-3 10 15 62.9 47.1 25.05% 85.0% 81.9 64.4 0.12 2-4 15 20 92.1 60.0 34.84% 40.0% 29.6% 23.0% 0.014 46.7 30.4 0.21 2-5 20 25 88.2 57.5 34.82% 57.1% 45.5% 22.9% 0.015 60.5 39.4 0.17 2-6 25 30 73.7 50.2 31.93% 27.3% 17.0% 25.7% 0.010 51.8 35.3 0.21 6-2 5 10 52.5 29.7 43.40% 22.4% 15.4% 53.5% 0.181 42.7 24.2 0.20 6-3 10 15 54.5 39.5 27.49% 31.7% 19.8% 30.6% 0.141 25.8 18.7 0.21 6-4 15 20 44.9 32.9 26.74% 72.9% 63.9% 14.6% 0.035 56.5 41.4 0.16 6-5 20 25 54.8 33.5 38.87% 69.1% 60.3 36.8 0.17 6-6 25 30 60.6 34.7 42.80% 65.5% 60.3% 6.0% 0.015 44.7 25.6 0.18 7-2 5 10 44.3 33.6 24.28% 35.2% 20.9% 41.0% 0.193 39.1 39.1 0.20 7-3 10 15 59.0 40.0 32.12% 30.1% 20.5% 49.5% 0.200 38.6 26.2 0.20 7-4 15 20 64.4 39.9 38.10% 68.6% 59.0% 18.1% 0.088 60.7 37.6 0.16 7-5 20 25 49.9 29.0 41.80% 55.7% 45.6% 25.7% 0.092 50.5 29.4 0.15 7-6 25 30 64.7 12-2 5 10 44.6 31.5 29.43% 32.6% 26.1% 29.9% 0.228 39.1 27.6 0.22 12-3 10 15 41.0 29.9 27.18% 34.1 24.9 0.19 12-4 15 20 73.0 52.8 27.62% 89.5% 77.0 55.7 0.12 12-5 20 25 74.6 44.5 40.38% 24.8% 16.1% 14.5% 0.050 58.7 35.0 0.19 12-6 25 30 97.2 60.9 37.37% 25.1% 19.6% 16.7% 0.023 58.9 36.9 0.19 13-2 5 10 54.0 35.8 33.68% 44.1 29.3 0.19 13-3 10 15 55.4 42.1 24.06% 30.4% 26.4% 46.0% 0.255 33.9 25.7 0.18 13-4 15 20 61.1 41.7 31.83% 61.5 41.9 0.15 13-5 20 25 83.6 51.0 38.96% 66.7 40.7 0.14 13-6 25 30 81.4 51.0 37.37% 57.4 35.9 0.19 (No sample was taken for 7-6 at 25-30 feet deep. Waste composition and methane yield data (including volatile solids and soil content) were not performed fo r samples 12-3, 12-4, 13-2, 13-4, 13-5, and 13-6. Methane yield data were not available for Samples 2-3 and 6-5. Moisture content values in italic font are approximates based on the average values of other samples at the same depth.) The second layer of CPT data comparison was the MSW, which was in the range of 3 to 30 feet (1 to 9 meters) deep. Based on documented landfill operations, an intermediate cover soil layer was placed between two lifts; however, clear delineation of this layer was not discernable from either buc ket auger borings or CPT data. Soil content increased in the mid range of the landfill depth, which was evident in boring observations and soil content calculations. The geometric means of the waste layer CPT data were tip resistance of 46 tsf, sleeve friction of 1.1 tsf, friction ratio of 2.7%, and pore pressure of

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69 0.25 tsf. The most frequently observed soil classification was Clay (No. 3, USCS – CH) which reflects lower tip resistance and higher friction ratio. Finally, the third layer was saturate d native soil below the landfilled waste ranging from 30 to 56 feet (9 to 16.5 meters) below the surface. Seven CPTs succeeded in penetrating to the bedroc k located approximately 48 to 54 feet (14.5 to 16.5 meters) below the landfill surface. The geometric means of the waste layer CPT data were tip resistance of 75 tsf, sleeve friction of 1.6 tsf, friction ratio of 3.0%, and pore pressure of 1.3 tsf. The most frequently seen soil cla ssification was Clay (No. 3), but a variety of classifications were also observed: Sand to Sandy silt (7), Sand to Silty sand (8), Very stiff fine grained (11), and Gravelly sand to Sand (10). Figure 3-5: Landfill Stratification 3.4.1.2 Intermediate soil cove r layer within waste The cover soil layer within the waste was not readily discernable from the cone penetration data due to a numb er of factors in both the wa ste and in the CPT method. The soil layer, as noted from the field bori ng evaluations, was not clearly delineated, and actually was quite interspersed among waste ove r approximately 10 vertical feet in the landfill. This is a result of landfill operations and differential settlement of the waste. Perhaps landfill operators were not as concerned with maximizing landfill volume use Cone Penetration Test Auger Borings Final soil cove r Second waste lif t Intermediate soil cove r Water Table First waste Soil sub g rade Roc k EL Friction Sleeve Ti p

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70 and a large cover soil layer (2 to 3 feet ) was placed on top of the first lift and subsequently mixed with waste as the landfill settled. The second reason for the CPT not being able to identify cover soil stratum in the landfill is a documented shortcoming of the CPT. Because of the natu re of the test, the transition from one layer to another does not register as a sharp change (Lunne et al., 1997). Studies have shown that cone resist ance is influenced by material properties ahead of and behind the cone. The cone can sense and interface over a distance of approximately 2 to 3 cone diameters (100-135 mm in this case) in soft material, but stiffer materials are affected by the material properties up to 20 to 30 cone diameters (Schmertmann, 1978). This compounded with th e variability of tip and sleeve resistance as the tip encounters hard objects in the la ndfill, makes discerning cover soil layers within the waste difficult. 3.4.1.3 Statistical differences Comparing the cover soil layer to the waste layer, the tip resistance, sleeve friction, and friction ratio are greater a nd statistically different (t-test, 95% confidence interval) in the waste than in the cover soil layer (Fi gure 3-6 to 3-8). However, the pore water pressure is not statistically different (Fi gure 3-9), which is due to the unsaturated conditions of both profiles. Tip resistance, friction ratio, and pore pre ssure are greater in the native soil layer than in the waste, but only pore pressure is st atistically different. This is a reflection of the difference between the saturated soil laye r and unsaturated waste. Comparing the intermediate soil cover to the native subgrade soil, each of the CPT parameters is greater in the lower soil layer. The sleeve fricti on, friction ratio, and pore pressure are statistically different; however, the tip resistance is not (w ith 95% confidence).

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71 Cover SoilWasteSubgrade Soil Tip Resistance, Q T [tsf] 0 20 40 60 80 100 120 140 Figure 3-6: Tip Resistance a nd Penetration Media Box Plot Cover SoilWasteSubgrade Soil Sleeve Friction, F S [tsf] 0.0 0.5 1.0 1.5 2.0 2.5 Figure 3-7: Sleeve Friction a nd Penetration Media Box Plot

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72 Cover SoilWasteSubgrade Soil Friction Ratio, FR [%] 0 1 2 3 4 5 6 Figure 3-8: Friction Ratio a nd Penetration Media Box Plot Cover SoilWasteSubgrade Soil Pore Pressure, U [tsf] 0 1 2 3 4 5 Figure 3-9: Pore Pressure an d Penetration Media Box Plot

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73 3.4.2 CPT Data and Waste Properties The CPT data were compared with data obtained from analysis of waste sampled from the bucket auger borings. A complete table of waste properties was presented in Table 3-4, and a summary of CPT data is pr esented in Table 3-5. A distinction in samples was noted between samples that ha d high methane yield (less degraded) and those with lower methane yield. Another distinction was made between samples with high soil content (> 25% by mass) and samples with lower soil fraction. To examine the connections between wast e parameters and cone penetration data, the correlation coefficient was computed as follows: 2 2) ( ) ( ) )( ( ) , (y y x x y y x x Y X n Correlatio . Correlation factors are presen ted in Table 3-6. Among the stronger relationships (correlation coefficient closer to 1 or -1) are friction ratio a nd soil content, volatile solids content, and BMP values. Some of the more significant relationships are further explored in following sections.

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74Table 3-5: Summary Data for CPT Soundings Compared to Auger Boring Sample Depths Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Soil Description Sample Depth [ft] Mean Geo. Mean Std. Dev. Mean Geo. Mean Std. Dev. Mean Geo. Mean Std. Dev. Mean Geo. Mean Std. Dev. Mode Lower Upper. QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] 2-1 0 5 55.8 45.2 40.5 0.61 0.46 0.44 1.75 1. 02 3.00 0.308 0.231 0.195 Sand to Silty Sand 2-2 5 10 31.7 20.3 30.2 1.15 0.94 0.71 7.70 4.65 8.65 0.115 0.086 0.073 Clay 2-3 10 14.1 42.8 31.5 35.7 0.74 0.68 0.28 3.07 2.16 2.16 0.138 0.126 0.046 Clay 6-1 0 5 44.1 34.9 29.9 1.28 0.79 1.57 6.39 2.26 17.17 0.072 0.055 0.049 Sand to Sandy silt 6-2 5 10 34.0 29.2 22.1 0.51 0.45 0.25 2.12 1.54 1.95 0.065 0.055 0.032 Sand to Sandy silt 6-3 10 15 67.4 52.8 48.9 2.12 1.83 1.35 4.13 3.48 2.93 0.140 0.103 0.098 Silty sand to Sandy silt 6-4 15 20 50.1 44.5 28.4 1.94 1.75 0.91 4.70 3.93 3.11 0.022 0.020 0.069 Clay 6-5 20 25 32.7 27.1 16.4 1.35 1.28 0.44 5.89 4.71 6.72 0.047 0.046 0.012 Clay 6-6 25 30 39.4 31.2 28.0 1.95 1.56 1.43 5.51 5.01 2.56 0.122 0.108 0.045 Clay 7-1 0 5 36.9 31.8 19.6 0.58 0.42 0.36 2.30 1. 32 3.46 0.063 0.043 0.056 Sand to Silty Sand 7-2 5 10 50.3 41.5 30.7 1.23 1.02 0.75 2.77 2.45 1.42 0.122 0.108 0.055 Sand to Sandy silt 7-3 5 10 50.3 41.5 30.7 1.23 1.02 0.75 2.77 2.45 1.42 0.122 0.108 0.055 Sand to Sandy silt 7-4 15 20 61.5 47.5 42.9 2.43 2.20 1.10 6.42 4.68 6.01 0.094 0.078 0.052 Clay 7-5 20 25 34.9 25.8 23.9 1.15 1.03 0.46 10.48 4.04 28.53 0.037 0.027 0.022 Clay 7-6 25 30 25.2 16.1 18.7 0.99 0.87 0.47 11.61 4.99 23.96 0.134 0.063 0.176 Clay 12-1 0 5 35.4 30.7 17.1 1.04 0.91 0.46 4.41 2.97 7.02 0.693 0.467 0.403 Silty sand to Sandy silt 12-2 5 10 65.1 52.4 50.8 1.66 1.57 0.55 3.77 3.01 2.45 0.226 0.204 0.155 Clay 12-3 10 15 55.8 42.1 36.4 1.12 0.96 0.76 3.33 2.28 2.76 0.202 0.173 0.101 Sand 12-4 15 20 49.6 40.0 32.5 1.13 1.02 0.47 3.41 2.56 2.37 0.176 0.156 0.066 Clay 12-5 20 25 30.1 23.1 23.4 0.98 0.89 0.48 4.96 3.86 3.79 0.311 0.308 0.050 Clay 12-6 25 30 39.9 33.1 24.9 0. 96 0.78 0.59 3.21 2. 36 1.94 0.320 0.315 0.055 Clayey silt to Silty clay 13-1 0 5 32.6 30.9 9.6 0.47 0.41 0.21 1.53 1.30 0.87 0.069 0.067 0.011 Sand to Sandy silt 13-2 5 10 44.8 38.5 26.7 0.69 0.62 0.29 2.07 1.61 1.56 0.136 0.131 0.037 Sand to Sandy silt 13-3 10 15 56.6 50.8 29.7 1.25 0.94 0.94 2.61 1. 85 2.24 0.280 0.273 0.058 Sand to Silty Sand 13-4 15 20 114.2 93.5 65.0 1.50 1.22 0.87 2.59 1.31 4.00 0.200 0.198 0.021 Sand 13-5 20 24.5 279.0 267.6 63.3 1.74 1.32 1.24 0.58 0.49 0.34 0.169 0.169 0.007 Gravelly sand to Sand Average 56.2 47.1 31.8 1.22 1.04 0.70 4.23 2.78 5.48 0.169 0.143 0.077 St. Dev 48.8 47.4 13.6 0.51 0.46 0.38 2.63 1.35 7.01 0.137 0.107 0.082

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75Table 3-6: Correlation Factors of Waste Properties and CPT Data Depth [ft] bulk [pcf] dry [pcf] Moisture [%] Soil [%] Volatile Solids [%] BMP [L CH4/g VS] 1000 bulk [pcf] 1000 dry [pcf] C [-] Geometric Mean Tip Resistance, QT [tsf] Geometric Mean Sleeve Friction, FS [tsf] Geometric Mean Friction Ratio, FR [%] Geometric Mean Pore Pressure, U [tsf] Depth [ft] 1.00 0.03 0.54 0.45 0.23 -0.72 -0.80 0.02 -0.22 0.09 0.17 0.40 0.50 -0.04 bulk [pcf] 0.03 1.00 0.95 0.28 -0.15 -0.37 -0.60 0.46 0.31 -0.20 0.14 -0.33 -0.33 0.57 dry [pcf] 0.54 0.95 1.00 -0.03 -0.21 -0.27 -0.49 0.47 0.41 -0.14 0.35 -0.08 -0.40 0.62 Moisture [%] 0.45 0.28 -0.03 1.00 0.17 -0.31 -0.44 0.13 -0.26 0.01 0.05 -0.06 0.30 -0.14 Soil [%] 0.23 -0.17 -0.22 0.13 0.99 -0.56 -0.41 0.40 0.35 -0.69 -0.05 0.58 0.76 -0.61 Volatile Solids [%] -0.72 -0.37 -0.27 -0.31 -0.57 1.00 0.81 -0.61 -0.42 0.37 0.32 -0.34 -0.73 -0.09 BMP [L CH4/g VS] -0.80 -0.60 -0.49 -0.44 -0.39 0.81 1.00 -0.71 -0.48 0.29 0.56 -0.10 -0.64 0.07 1000 bulk [pcf] 0.02 0.46 0.47 0.13 0.40 -0.61 -0.71 1.00 0.94 -0.88 0.09 -0.23 -0.13 -0.13 1000 dry [pcf] -0.22 0.31 0.41 -0.26 0.31 -0.42 -0.48 0.94 1.00 -0.86 0.01 -0.25 -0.20 -0.16 C [-] 0.09 -0.20 -0.14 0.01 -0.72 0.37 0.29 -0.88 -0.86 1.00 -0.14 0.19 0.17 0.24 Geometric Mean Tip Resistance, QT [tsf] 0.17 0.14 0.35 0.05 -0.05 0.32 0.56 0.09 0.01 -0.14 1.00 0.23 -0.45 0.09 Geometric Mean Sleeve Friction, FS [tsf] 0.40 -0.33 -0.08 -0.06 0.55 -0.34 -0.10 -0.23 -0.25 0.19 0.23 1.00 0.53 -0.13 Geometric Mean Friction Ratio, FR [%] 0.50 -0.33 -0.40 0.30 0.72 -0.73 -0.64 -0.13 -0.20 0.17 -0.45 0.53 1.00 -0.22 Geometric Mean Pore Pressure, U [tsf] -0.04 0.57 0.62 -0.14 -0.53 -0.09 0.07 -0.13 -0.16 0.24 0.09 -0.13 -0.22 1.00 Strong correlations in bold

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76 3.4.2.1 CPT data and depth of waste In Chapter 2, several trends were found among samples obtained at different depths in the landfill. The deeper waste tended to have higher bulk specifi c weight and moisture content while having lower volatile solids and me thane yield. In this section, CPT data are plotted with respect to depth in the landf ill to determine if changes in measured CPT data are significant with re spect to variability . Figures 3-10 through 3-13 present tip resistance, sleeve friction, friction ratio, and po re water pressure, respectively. Due to the high variability of each sample, no differen ce between CPT depth and each of the CPT data parameters is noticeable. Tip Resistance, QT [tsf] 0100200300400 Depth [ft] 0 5 10 15 20 25 30 Figure 3-10: Box Plot of Tip Resist ance with respect to Depth in Waste

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77 Sleeve Friction, FS [tsf] 0246810 Depth [ft] 0 5 10 15 20 25 30 Figure 3-11: Box Plot of Sleeve Fric tion with respect to Depth in Waste

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78 Friction Ratio, FR [%] 05101520 Depth [ft] 0 5 10 15 20 25 30 Figure 3-12: Box Plot of Friction Ra tio with respect to Depth in Waste Pore Pressure, U [tsf] 0.00.20.40.60.81.0 Depth [ft] 0 5 10 15 20 25 30 Figure 3-13: Box Plot of Pore Pressu re with respect to Depth in Waste

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79 3.4.2.2 CPT data compared to degree of degradation In Chapter 2 a distinction was made between samples with higher measured methane yield and those with lower methan e yield. Assuming high methane yield correlates to less degraded waste as low yield corresponds to more degraded waste samples were compared based on the other pr operties associated with each. Several significant trends relating to moisture conten t, specific weight, and volatile solids content were noted. This section compares CPT data with the same sample distinctions made in Chapter 2 for degree of degradation. Plotting the tip resistance and friction ratio for both degraded and less degraded samples shows that tip resistance is higher for less degraded samples (Figure 3-14) and friction ratio is higher for degraded samples (Figure 3-15). The geometric means of the tip resistances of the less degraded sample s averaged 30% greater than the degraded samples. The average of friction ratio of less degraded samples was 2.6%, while it increased to 3.5% for degraded samples. Based on the distinction in degree of degradation, however, the CPT data were not statistically different between degraded and less degraded samples with 95% confidence.

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80 UndegradedDegraded Tip Resistance, Q T [tsf] 0 10 20 30 40 50 60 Figure 3-14: Box Plot of Tip Resistance for Degraded and Less Degraded Samples UndegradedDegraded Friction Ratio, F R [%] 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Figure 3-15: Box Plot of Friction Ratio for Degraded and Less Degraded Samples

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81 3.4.2.3 CPT data and soil content The difference with high (>25%) and low (<25%) soil content was among the distinctions made between waste samples. Low soil content samples tended to have higher tip resistance (Figure 316) and lower friction ratio (Figure 3-17). Though the difference between the averages of the geomet ric means of tip resistance is 20%, the difference is not statistically significant. However, the friction ratio is statistically different between samples with low and high soil content. Low Soil ContentHigh Soil Content Tip Resistance, Q T [tsf] 0 10 20 30 40 50 60 Figure 3-16: Box Plot of Tip Resistance for High and Low Soil Content in Waste

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82 Low Soil ContentHigh Soil Content Friction Ratio, F R [%] 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Figure 3-17: Box Plot of Friction Ratio for High and Low Soil Content in Waste 3.4.3 Correlation of Cone Penetration Tests with Compressibility The compressibility parameters evaluated in Chapter 2 are compared with tip resistance and friction ratio to distinguish any correlations. The waste compressibility (determined by lower 1000 and higher C being more compressible) tended to decrease with an increase of tip resistan ce (Figure 3-18) and decrease as C increased (Figure 3-19). Comparing friction ratio to compressibility rev ealed that higher friction ratio corresponds to less compressible material (Figures 3-19 a nd 3-20). That is, highe r tip resistance and friction ratio values were measured in denser, less compressible materials.

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83 y = -0.4855x + 64.622 R2 = 0.2772 20 25 30 35 40 45 50 55 60 65 202530354045505560 Tip Resistance, QT [tsf]Compression Coefficient forBulk Specific Weight, bulk [pcf] Figure 3-18: Compression Coefficient (1000 bulk) versus Tip Resistance y = 0.0006x + 0.1631 R2 = 0.1303 0.10 0.15 0.20 0.25 202530354045505560 Tip Resistance, QT [tsf]Compression Exponent, C [-] Figure 3-19: Compression Expone nt versus Tip Resistance Increasing Compressibility Increasing Compressibility

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84 y = 4.3051x + 31.801 R2 = 0.2213 0 10 20 30 40 50 60 70 0123456 Friction Ratio, FR [%]Compression Coefficient forBulk Specific Weight, bulk [pcf] Figure 3-20: Compression Coefficient (1000 bulk) versus Friction Ratio y = -0.007x + 0.2092 R2 = 0.1851 0.00 0.05 0.10 0.15 0.20 0.25 0123456 Friction Ratio, FR [%]Compression Exponent, C [-] Figure 3-21: Compression Expone nt versus Friction Ratio Increasing Compressibility Increasing Compressibility

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85 3.4.4 Comparison of CPT Data with Other Studies Table 3-7 compares CPT data from waste pr ofile only with data from other studies. Because other studies did not often report complete CPT data and the methods are sometimes unclear making comparing these resu lts to other studies difficult. However, the Reinhart et al. (2004) study used the same equipment as this study, but CPTs were conducted in newer waste (1-year old). Intere stingly, the values for tip resistance and friction ratio are slight ly higher, which is the opposite fr om the findings of this study: tip resistance and friction ratio increase with wa ste age, degradation, and compressibility. However, this is explained by increased initia l compaction effort applied to the waste at a modern landfill, which focuses on attaining gr eater compaction compared to the test cells in this study. CPT data are comparable to th e ranges seen in the Sillan (1995) study. In the Sillan study degraded, older waste ( unknown compaction effort), demonstrated a higher friction ratio than the newer waste. Friction ratio in this study was greater than friction ratio of newest biorea cted waste in the Sillan study and slightly more than the degraded waste from Sillan. 3.4.5 Cone Penetration Data and Soil Classification CPT data from this study were transposed on the soil classification chart from Robertson et al. (1986) in Fi gure 3-22. The degraded wast e layers exhibited lower tip resistance and higher friction ra tio, evident in the figure. The less degraded waste layers generally had greater tip resistance and lowe r friction ratio similar to cohseionless soils (sand and gravel). This figure also indicat es lower tip resistance and greater sleeve friction in the degraded waste layers similar to cohesive soils (silts and clay). The waste classifications do not correspond to USCS soil classifications.

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86 Table 3-7: CPT Data Compared to Waste CPTs from Other Studies Author(s) Year Description Average1 Tip Resistance (QT) Average Sleeve Friction (FS) Average Friction Ratio (FR) Average Pore Pressure (U) [tsf] [tsf] [%] [tsf] This study1 Waste (3 to 30 feet deep) 62.0 1.29 3.52 0.35 Reinhart et al. (2004) Biosolids Area Bioreactor Control 77.7 81.9 70.5 1.52 1.65 1.61 2.65 2.70 3.15 0.13 0.14 0.12 Oakley (1990) Chemically stabilized landfill 202 1.022 5.02 Not Reported (N/R) Sillan (1995) 30-acre cell (10-17yrs) 11-acre cell (6-10yrs) Active Bioreactor (0-6yrs) 56.0-72.2 85.9 54.0-60.9 N/R 1.82-2.89 2.15 1.37-1.93 0.09-0.14 -0.10 0.07-0.16 Siegel et al. (1990) 602 2.02 3.52 N/R Hinkle (1990) 50 0.75 N/R N/R 1 Average values are used in this comparison for da ta from this study rather than geometric mean in previous discussions. 2 Approximations based on figure of typical CPT data.

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87 Friction Ratio, FR [%] 0123456 Cone Tip Resistance, QT [tsf] 10 100 Soil classification chart from Robertson et al. (1986)3 4 5 6 7 8 11 Figure 3-22: Cone Penetration Da ta and Soil Classification Plot 3.5 Summary and Conclusions The piezocone penetration test was useful for evaluating landfilled waste in some respects and less so in others. Unlike using CP Ts in soils, using CPTs in landfills yields highly variable data, making st rong correlations difficult. A good deal of information can be garnered about the stratigraphy of waste in the landfill. The pore pressure from the piezocone identifies saturated and unsaturated zones, while the resistance parameters can be used to delineate the difference between waste and large layers of soil based on the variability differences. However, distingui shing between waste a nd cover soil layers within the waste proved difficult; this was at tributed to the difficulty of delineating stratigraphic boundaries of thin layers in the highly variable waste. Less Degraded (lower soils, lower moisture content, higher volatile solids) Degraded (high moisture content, higher soil content, lower soils content)

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88 The relation of cone penetration data to other waste properties were noted, though statistically most were not di fferent. Friction ratio tended to be higher for samples with a high soil content and a higher leve l of degradation. Tip resist ance tended to be higher for samples with low soil content and exhibiti ng less degradation. Compressibility parameters tended to exhibit a more compre ssible nature for higher tip resistance and lower friction ratio. This study adds to the knowledge and e xperience using the CPT in MSW landfills and draws some meaningful connections betw een CPT parameters and waste character. For CPTs to be more useful for definining waste character, additional tests would have to be performed in several other landfills of varying ages, mois ture content, degradation, soil content, and initial compaction effort. Ultimately, the research goal would be to develop a waste classification algorithm or char t similar to soil classification charts that have been presented by several researchers. Meaningful correlations can be drawn for the CPT in MSW landfills over layers of wast e by looking at average (geometric mean) value of CPT data, but further research is needed before useful waste classification systems can be created.

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89 CHAPTER 4 PREDICTION OF MSW LANDFILL SETTLEMNT AND COMPARISON TO CONICAL TEST LOAD FOR MEASUR ING WASTE COMPRESSIBILITY 4.1 Introduction Engineers need the ability to predict municipal solid waste (MSW) landfill settlement for a number of reasons, including building structures on top of old landfill cells, vertically expanding closed landfill cells, and designing adequate pollution control systems such as cap and gas collection syst em. Landfills typically settle 30% from the initial height over the duration of degradati on of the organic fraction of waste—typically 30 years. In Florida, closed landfills have often been converted to parks. Gaining a better understanding of settlement as it relate s to other waste engineering properties will help in predicting settlement and perhaps mitigating settlement for landfill redevelopment. Studying geotechnical aspects of landfills is a difficult endeavor. Numerous researchers have studied landfill geotechnical aspects to develop better means to predict landfill settlement. Settlement has often been broken down into two components— primary and secondary. Primary settlement occurs rapidly as a result of immediate settlement in which waste particles are co mpressed and rearranged, typically taking place over a period of a few months (Lukas, 1992). Secondary settlement is the effect of chemical and biological decomposition mechan isms and takes place over long periods of time (20 to 30 years). Traditionally, soil mechan ics theories of compressibility have been applied to municipal solid waste (MSW) landfills (Fassett et al., 1994). However, due to

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90 the compressible nature of some waste particle s and that properties change with time, soil mechanics properties have shortcomings in predicting settlement in MSW landfills (Powrie et al., 1999). Laboratory–scale experiments in compressi on cells, also know as consolidometers or oedometers, have been conducted by vari ous researchers (Beaven, 2000; Hossain et al., 2003; Hudson et al., 2004; Landva and Clar k, 1990; Pelkey, 1997) and in conjunction with this study (presented in Chapter 2). Because of the heterogeneity of waste, laboratory–scale compressibility testing is lim ited by challenges presented in obtaining a representative sample. Field evaluations of compressibility and settlement are often difficult to conduct but have been performed and have included aerial survey comparison, benchmark surveys on the landfill surface, and settlement plates below an earth embankment, similar to the procedure discus sed in this chapter (Qian et al., 2002). This chapter uses results of laborat ory–scale compression testing to predict settlement of the landfill test parcel. Pr edicted settlement results are compared with settlement measurements obtained as a resu lt of a cone–shaped earthen surcharge or conical test load (CTL) that was constructed above the test area of the landfill cells undergoing the vertical expansion feasibility study. This procedure, consisting of constructing a CTL over the closed, unlined ce lls containing 20 to 30–year old waste for measuring settlement, is similar to that desc ribed by Schmertmann (1993). Settlement of the waste was monitored as the load was constr ucted in stages. Similar studies have been conducted in which surcharges were built over old waste and settlement was monitored to assess landfill compression prio r to highway construction a nd before and after dynamic deep compaction (Sheurs and Khera, 1980; Welsh, 1983).

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91 The objective of this chapter is to evaluate waste compressibility using results from laboratory–scale compression testing to pr edict landfill settlement and compare with the results of field–scale loading test. This will be useful for predicting the settlement anticipated as a result of constructing a ne w, lined, Class I landfill above the existing waste cells. 4.2 Methods The methodology in this chapter consis ts of two independent analyses and comparison. The conical test load was constr ucted over the designated test parcel of the landfill, and settlement was measured. These data were compared with predicted settlement based on compressibility index values determined in laboratory scale compression testing conducted on samples obtai ned from waste in the same area as the CTL. To this end, this section first presents a brief site description, followed by brief waste analysis methodology that refers to th e compression testing. Then, the CTL and settlement measurement methodology is explai ned. Finally, the components of the settlement analysis methodology are presented. 4.2.1 Site Description The Polk County North Central Landf ill opened in December 1975, and accepts waste from the greater Lakeland, Florid a, area. Between 1976 and 1985 waste was deposited in shallow cells (30 foot thickness ) using a trench-and-fill method. The site and filling methods are presented in detail in Chapter 2. A feasibility study was conducted by Jone s, Edmunds & Associates (2004) to determine if siting a lined MSW landfill on top of these old cells was possible from an environmental and geotechnical standpoint. A thorough investigation of the entire landfill was not in the scope of this project, but a smaller test parcel was selected (Figure

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92 2-1 in Chapter 2) as the location for cone penetration test soundings (see Chapter 3), bucket auger borings (Chapter 2), and the coni cal test load described in this chapter. 4.2.2 Waste Properties Analysis and Laboratory Compression Testing Landfill waste properties were determined through numerous analyses described in Chapter 2. Representative waste samples were obtained for every 5–foot (1.5–meter) section of a boring by excavating waste soil a nd waste using a 36–inch bucket auger rig. For each representative sample, an in-place specific weight was determined and analyses for moisture contents, soils co ntents, volatile solids, and me thane yield were conducted in the laboratory. Further detail of the procedures and results for each analysis are presented in Chapter 2. Waste compressibility for each represen tative sample was obtained using a laboratory compression–analysis device described in Chapter 2. The stress-strain data obtained from the analysis were used to de termine a density (specific weight) – applied vertical pressure relationship. Data points were plotted and a pow er law regression line was fit to the data. The exponent of the function of the regres sion line was used to describe the compressibility of each sample as shown here: C 1000 where the vrelationship is defined by the theoretical initial specific weight condition, 1000 [pcf] and the compression exponent, C [unitless]. 4.2.3 Conical Test Load A conical test load was cons tructed over the test parcel located in the center of the northern central landfill cell of the proposed vertical expans ion area. The test load surcharge was constructed of sandy soil obtai ned from off-site borrow. The soil was

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93 stockpiled on site, away from the test area un til time of construction. The soil was moved into location by off-road arti culated trucks and then moved into place by an excavator. Final grading and compaction were performed with a track dozer. The average in-place density of the test load was determined by Ardaman and Associates, Inc. (Orlando, Florida) to be 102.2 pounds per cubic foot (pcf ) using a nuclear density gage. Test load construction was conducted by landfill staff a nd equipment on site. Construction of the conical test load proceeded in three phases over two months. Each phase load except the first was cone shape with 3:1 side slopes, measuring 9, 18, and 29 feet (3, 6, and 9 meters) in height. The Phase I load was a modified pyramid measuring 90 by 60 feet at the base with 3:1 slopes coming to a crest at 10 feet. A topographical survey using Trimble (Sunnyvale, California) differential GPS equipment was taken by the author after each phase was complete and before beginning lo ad test construction to estimate volume. The details of the load test volumes and dimensions are summarized in Table 4-1. Table 4-1: Conical Test Lo ad Dimensions and Volumes Stage Construction Date Height Total Volume [ft] [yd3] Phase I March 8-10, 2004 9 828 Phase II March 4-29, 2004 18 2,762 Phase III April 8-16, 2004 29 8,685 Adapted from Jones, Edmunds & Associates (2004) Settlement plates were used to measur e the compression effects of the additional load on the waste. Before constructing the first phase of the test load, twelve settlement plates were installed in the test load area, as well as six additional benchmarks adjacent to the test load. Settlement plates were st eel sheet metal measur ing 1/2 inch (12.7 millimeter) thick by 2 foot (60 centimeter) squa re with a steel coupling welded to the center of the plate (Figure 4-1) . One of the settlement plat es was constructed of treated wood measuring 4 foot (120 cm) square made of 2 by 8–inch lumber and bolted together

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94 with galvanized hardware. Plate inst allation consisted of removing grass and approximately 6 inches (15 cm) of soil, replac ing with clean sand or fine crushed glass, and leveling the plate. The arrangement of sett lement plates is displayed in Figure 4-2. One primary plate was located at the center of the cone (AR 2), and other plates were located in duplicate at radii of 10, 17, 30, 40, 54, and 70 feet (3, 5, 9, 12, 16, and 21 meters) to obtain a settlement profile under various points beneath the test load. The additional six settlement measurement points were 4 foot (1.2 meter) iron pipe driven into the landfill. Four of the pipes were located at the toe of the slope of the final Phase III load (i.e., 90 foot radius), and two were 10 feet beyond that at 100 feet from center. Settlement was measured by surveying iron pipe extensions that extended through the test load. Iron pipe lengths (typically 4 to 6 feet) were threaded into the settlement plate coupling and secured with a pipe wren ch. Before constructing each phase of the test load, iron pipe extensions were added to each plate so that they extended beyond the depth of the soil at that location for the ne xt phase. Each pipe extension and coupling was measured with a tape measure. In a ddition to the iron pipe extensions, 2–inch PVC pipe was installed around the iron pipe extens ion, and a cap was placed on the top of the outer PVC pipe to protect the pipe from the el ements and friction eff ects of the soil load.

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95 Figure 4-1: Settlement Plate When each of the three phases was complete , the settlement plates were surveyed using total station survey equipment opera ted by professional surv eyors (Pickett and Associates, Inc., Bartow, Florida). Survey da ta were compared with extension lengths to obtain total settlement. Four months after the Phase III was complete, another survey of the settlement plate extensions was taken to determine if additional settlement occurred over time. The settlement points were left in place for approximately five months before the test load was deconstructed. PVC Cap PVC Casing (2in.diameter) Iron pipe extension (1 in. diameter) with cou p lin g s as needed Settlement Plate (½ in. thick ) 2FT Welded steel cou p lin g Survey Point Load Test Fill

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96 Easting 7 06200 7 06250 7 06300 706350 Northing 1 33 8 40 0 1338450 13 3 85 0 0 1 338550 13 3 86 0 0 Settlement Plates Settlement Pipes AR 2 AR1 AR3 UF 1 UF2 UF3 UF4 UF5 UF6 UF7 UF8 UF11 UF9 UF15 UF10 UF14 PHASE 3 PHASE 2 PHASE 1 UF12 UF13 0 50100 SCALE [FEET] TEST PARCEL Figure 4-2: Conical Test Load Settlement Plate Arrangement 4.2.4 Settlement Analysis and Comparison To analyze the settlement, a m odel was generated based upon waste compressibility properties, waste stratification, and change in vertical pressure. This model is explained in depth in Appendix L, but the methodology is outlined here. First, waste stratification and layer properties mu st be identified, in cluding the number of layers, initial height or thickness, density-pressure relationship, initial density, and historic waste compression effort. Then the in itial pressure must be determined at the midpoint of each layer based on initial density . The additional overburden pressure is

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97 then calculated and added to initial pressure to get final pressure. If the final pressure is greater than the historic loading, the new de nsity is calculated using the density-pressure relationship. Finally, the cha nge in height for each layer is determined base on the new density, and the sum of all layer height change equa ls the total settlement. Several assumptions must be made to calculate predicted settlement based on this methodology. Historic wa ste compression effort, qo, i, is typically estimated based on compaction machinery; however, 1,000 pounds per s quare foot (psf) has been reported to be an appropriate assumption in the ab sence of compaction information based on published values for compaction effort applie d to the waste layer during placement (Qian et al., 2002). For this study a range of hist oric waste compaction effort values (1,000 to 2,500 psf) were used to model settlement and compared. Several methods exist for determining the change in vertical pressure due to surface loads including Boussinesq charts. For this analysis the change in vertical pressure was determined using geotechnical finite element software describe d below. The relationship of specific weight to vertical pressure may be determined using field or laboratory set tlement analysis. In this research, the relationship was de termined using laboratory–scale compression analysis (Chapter 2) and was re presented by the compression exponent, C, the exponent of the power law regression line fit to the data using Excel. Typical C values and ranges are presented in Table 4-2 based on waste anal ysis for level of degradation, moisture content, and density.

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98 Table 4-2: Wast e Layer Compressibility Parameters Waste Character Average C Range of C Less degraded, lower moisture content and lower initial specific weight; More compressible. 0.20 0.196 to 0.214 Greater degradation, moisture content, and specific weight; Less compressible. 0.18 0.165 to 0.186 The landfill stratigraphy assigned to the mode l for settlement analysis was similar to the approaches taken in Chapters 2 and 3. Landfill layers were divided into six layers with thicknesses of 5 feet. The top layer was a ssumed to be 3 feet of soil cover and 2 feet of waste (Figure 4-3). Waste properties for layers were di fferentiated based on depth in the landfill from observations made while boring into the landfill (Chapter 2) and in the CPT soundings (Chapter 3). Waste less than 15 feet below the surface tended to have lower moisture content and specific weight and have greater compressibility than the waste found from 15 to 30 feet below the la ndfill surface. For th is reason, the upper waste layers were modeled with o = 50 pounds per cubic foot (p cf) specific weight and compression exponent C = 0.20, while the lower layers were modeled with o = 70 pcf and compression exponent C = 0.18.

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99 Figure 4-3: Waste Settlement Model Parameters Regardless of the method for determining the settlement effects of the additional overburden pressure, the cha nge in vertical stress (v) must be known. The vertical stress increase (v) at various locations and depths below the conical test load was determined using a finite element model to determine the pressure distribution under a cone. Finite element software, SIGMA/W, made by GeoSlope Inte rnational (Calgary, Alberta, Canada), was used to determine the change in vertical stress for the axissymmetrical design at various radii corres ponding to settlement plate locations and depths below surface. Each phase of the te st load was modeled, and the change in vertical stress, v, was determined for element nodes at points below settlement plates 1: H0, 1=3ft; 0, 1=110pcf, qo 2: H0, 2=2ft; 0, 2=50pcf, qo 3: H0, 3=5ft; 0, 3=50pcf, qo 4: H0, 4=5ft; 0, 4=50pcf, qo 5: H0, 5=5ft; 0, 5=70pcf, qo 1( v): C=0.07 2( v): C=0.20 3( v): C=0.20 4( v): C=0.20 5( v): C=0.18 6: H0, 6=5ft; 0, 6=70pcf, qo 6( v): C=0.18 7: H0, 7=5ft; 0, 7=70pcf, qo 7( v): C =0.18 Conical Test Load Cover Soil Layer Subgrade Soil Layer

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100 corresponding to the midpoints of waste layers . Methodology and vert ical stress values are presented in Appendix M. To compare measured settlement for the coni cal test load with predicted settlement using this methodology, the settlement was calcu lated at points where settlement plates were located. Settlement was calculated for each phase of the CTL at each of the plate locations for typical compression exponent, C, values and for a range of historic loading effort, qo (preconsolidation pressure). 4.3 Results 4.3.1 Conical Test Load Settlement Settlement data show that the maximum settlement of 2.2 feet occurred at the center settlement plate (AR-2) under the Phase III load. Figure 4-4 shows the settlement profile from all the settlemen t plates for all phases (also seen in Appendix N). Though the figure indicates settl ement plates were in one plane, they were located throughout the conical test load (see Figure 4-1) and are pr esented this way for simplicity. Once again, the Phase I load was not a cone but rather a modified pyramid, and the end view is depicted in the figure. Settlement increas ed with additional placement of load and over time, measured after construc tion of the Phase III load. As expected, the settlement plates closest to the center saw greater settlement than points farther from the center. Plates were installed at duplicate radii, and settlements measured at duplicate plates were consistent. An additional 25 to 30% of settlement was measured four months after Phase III was construction at points near the center; more settlement occurred at some of the plates farther from center over time. Though additional settlement was seen over time, this was considered primary rather than sec ondary settlement. The standard error of the

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101 settlement measurement was determined to be ±0.03 feet and settle ment readings less than the standard error were not reported. Figure 4-4: Measured Settlement for Three Phases of Test Load and Additional Settlement 4.3.2 Waste Properties The characteristics of the waste excavated from the five large diameter auger borings is summarized in Table 3-4 (Chapter 3). Generally, the following distinctions about the waste sampled in the test parcel were made: 1. Waste in the lower portion of the landfill exhibited higher moisture contents and densities, lower methane yield and volatile solids contents, and greater soil contents than in shallower waste samples. 2. The compression indices indicate wast e with lower methane yield was less compressible. 3. Waste with higher soils contents and mois ture contents were less compressible. 0 0.5 1 1.5 2 2.5 3Settlement [ft] Phase I Phase II Phase III Phase III (4mo.) UF 1(70) UF 3 ( 54 ) UF 4(40) UF 2 ( 30 ) AR1(16) UF 9(10) AR2(rad = 0 ft) AR3(17) UF 5(30) UF 8(40) UF 7(54) UF 6(70) UF-15 (102) UF-10, UF-12 (90) UF-11 , UF-13 (90) UF-14 (102)

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102 4.3.3 Finite Element Modeling This section summarizes the added vertical stress from each phase of the conical test load determined using geotechnical finite element software. Data obtained in this analysis were applied to the landfill settlement analysis for the change in vertical stress at various points under the test load. The maximum increase in vertical pressure observed on the axis of the cone immediately below the ground surface for Phase I, Phase II, and Phase III were 648 psf, 1,446 psf, and 2,330 psf, respectively. Figures 4-5 to 4-7 present the load distributions for the added vertical pr essure as a result of each phase of the test load. Phase I is approximated as a cone rather than the modified pyramid that was actually constructed. POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE I H = 9 FT R = 30 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load Phase 1.gsz 0 0 200 4 0 0 400 6 0 0 Radius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 Figure 4-5: Cross Section of Vertical Stress Distribution for Added Stress from CTL Phase I using Finite Element Software SIGMA/W from GeoSlope International

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103 POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE II H = 19 FT R = 60 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load Phase 2.gsz 0 0 2 0 0 4 0 0 6 0 0 8 0 0 8 0 0 1000 1 2 0 0 1 4 0 0 Radius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 Figure 4-6: Cross Section of Vertical Stress Distribution for Added Stress from CTL Phase II using Finite Element Software SIGMA/W from GeoSlope International POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE III H = 29 FT R = 90 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load 3.gsz 0 2 0 0 400 6 0 0 8 0 0 1000 1 0 0 0 1 2 0 0 1 4 0 0 1600 1 8 0 0 2 0 0 0 2200 Radius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 40 Figure 4-7: Cross Section of Vertical Stress Distribution for Added Stress from CTL Phase III using Finite Element Software SIGMA/W from GeoSlope International

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104 4.3.4 Settlement Analysis Settlement was predicted using the met hodology discussed, and the results are presented in this section. Table 4-3 presents a typical settlement calculation for the center settlement plate (AR-2) under the Phase III load. Figures 48 through 4-11 present settlement predictions compared with measured settlement. In all cases, settlement was over–predicted based on laborat ory compression parameters. For Phase I the maximum measured settlement was 0.4 foot whereas the average predicted settlement ranged from 0.0 to 0.9 foot. The settlement predicted using qo = 1,500 psf was the closest prediction to the measured data. The shape of the Phase I load was a modified pyramid which was 9–feet thick at AR-1, AR-2, and AR-3 settle ment plates and less above UF-9, which is the reason for the UF-9 plate irregularity where less settlement was observed than plates AR-1 and AR-2, farther from the center. For Phase II the maximum settlement measured was 1.2 feet, but the predicted settlement ra nged from 0.15 to 3.1 feet. The predicted settlement most closely matche d measured settlement when qo = 1,750 psf. The initial Phase III survey measured a maximum of 2.2 f eet of cumulative settlement in the center; however, the model predicted 1.2 to 4.6 feet of settlement. The Phase III measured data matches well with the qo = 2,000 psf. Finally, for the Ph ase III load after 4 months of primary settlement, the measured settlement was 2.8 feet, yet the model predicts 1.2 to 4.6 feet. The measured data, again, would match qo = 1,750 psf best.

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105 Table 4-3: Phase III Settlement Calcul ation for Center Settlement Plate (AR-2) Initial Conditions Load Conditions Compression Density Layer Depth Specific Initial Surcharge Sum Exponent Ratio Settlement Low. Up. H0/2 H0 Weight,0 v, 0v(v, 0v) C 2/1H [ft] [ft] [ft] [ft] [pcf] [psf] [psf] v, 1[psf][-] [-] [ft] 1 0 3 1.5 3 110.0 165 2330 2495 0.07 1.016 0.046 2 3 5 4 2 50.0 380 2292 2672 0.200 1.060 0.113 3 5 10 7.5 5 50.0 555 2239 2794 0.200 1.069 0.324 4 10 15 12.5 5 50.0 805 2166 2971 0.200 1.082 0.380 5 15 20 17.5 5 70.0 1105 2094 3199 0.180 1.088 0.405 6 20 25 22.5 5 70.0 1455 1925 3380 0.180 1.099 0.451 7 25 30 27.5 5 70.0 1805 1891 3696 0.180 1.117 0.523 30 Total Settlement: 2.242 Figure 4-8: Settlement Analysis Results for Phase I of the Conical Test Load 0 0.2 0.4 0.6 0.8 1Settlement [ft] Measured Settlement qo = 1000psf qo = 1500psf qo = 2000psf qo = 2500psf UF 1 (70) UF 3 (54) UF 4 (40) UF 2 (30) AR1 (16) UF 9 (10) AR2 (rad = 0 ft) AR3 (17) UF 5 (30) UF 8 (40) UF 7 (54) UF 6 (70) UF-15 (102) UF-10, UF-12 (90) UF-11 , UF-13 (90) UF-14 (102)

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106 Figure 4-9: Settlement Analysis Results for Phase II of the Conical Test Load Figure 4-10: Settlement Analysis Results for Phase III of the Conical Test Load -0.5 0 0.5 1 1.5 2 2.5 3 3.5Settlement [ft] Measured Settlement qo = 1000psf qo = 1500psf qo = 2000psf qo = 2500psf UF 1 (70) UF 3 (54) UF 4 (40) UF 2 (30) AR1 (16) UF 9 (10) AR2 (rad = 0 ft) AR3 (17) UF 5 (30) UF 8 (40) UF 7 (54) UF 6 (70) UF-15 (102) UF-10, UF-12 (90) UF-11 , UF-13 (90) UF-14 (102) 0 1 2 3 4 5Settlement [ft] Measured Settlement qo = 1000psf qo = 1500psf qo = 2000psf qo = 2500psf UF 1 (70) UF 3 (54) UF 4 (40) UF 2 (30) AR1 (16) UF 9 (10) AR2 (rad = 0 ft) AR3 (17) UF 5 (30) UF 8 (40) UF 7 (54) UF 6 (70) UF-15 (102) UF-10, UF-12 (90) UF-11 , UF-13 (90) UF-14 (102)

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107 Figure 4-11: Settlement Analysis Results for Phase III after 4 Months of the Conical Test Load 4.4 Discussion The settlement model tended to predict a wide range of settlement for all of the phases of the test load depending larg ely upon the historic load applied, qo. The range of waste settlements based on varying comp ressibility indices in the ranges C values in Table 4-1 was only 10% of the predicted se ttlement at each point. The settlement prediction was much more sensitive to qo than C. The settlement method with qo = 1,000 psf over–predicte d waste settlement by twice as much, making it a conservative predicti on of true settlement. The prediction is not unreasonable because geotechnical engin eering often use fact ors of safety in designing based on settlement calculations. 0 1 2 3 4 5Settlement [ft] Measured Settlement qo = 1000psf qo = 1500psf qo = 2000psf qo = 2500psf UF 1 (70) UF 3 (54) UF 4 (40) UF 2 (30) AR1 (16) UF 9 (10) AR2 (rad = 0 ft) AR3 (17) UF 5 (30) UF 8 (40) UF 7 (54) UF 6 (70) UF-15 (102) UF-10, UF-12 (90) UF-11 , UF-13 (90) UF-14 (102)

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108 4.4.1 Historical load The historical load has a substantial effect on the prediction of the waste settlement. In Figures 4-8 through 4-11 the predicted settle ment lines are plotte d with the measured settlement for Phase III assuming four different historic loading effort, qo, values: 1,000 psf, 1,500 psf, 2,000 psf, and 2,500 psf. For th e four different scenarios, the appropriate qo value to best model the settlement da ta ranged between 1,500 psf to 2,000 psf. 4.4.2 Waste rebound and compression under loads less than historic load The settlement prediction model used in this study assumes that the once historic load is applied to the waste and unloaded th e density remains the same (i.e. total elastic deformation). Actually, the el asticity/plasticity of the wast e is more complicated. The result of simplifying the model and assuming unloaded waste retains the density of the greatest historic applied load is an under–prediction of the actual settlement. Similarly, as Sheurs and Khera (1980) report, stress hist ory plays an important role. When the ratio of stress history and existing st ress was less than 1, measured strain was only 5 to 7%. When the ratio was 1.4 or greater, the meas ured strain was between 11 and 17%. Thus, this under prediction could be estimated to a ffect only predicted settlement values 5 to 7%. 4.5 Conclusions This study shows that excavating waste samples from a landfill and evaluating compressibility in a laboratory setting will yi eld meaningful settlement prediction results. The testing procedure, though rather involved, c ould be applied to virtually any landfill to determine primary settlement, or compression—the immediate effect of additional overburden pressure on waste. Waste indicies for waste with various characters presented in Chapter 2 were incorporated in the model; and while the range of C values

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109 used in the analysis did not play as great of a role for predicting settlement, the historic load using this methodology did. The historic loading values, or qo, best predicted landfill settlement when qo was in the range of 1,500 to 2,000 psf. Further research at this location c ould confirm the methodology under greater pressures by measuring the addi tional vertical pressure and settlement of the old waste under the new landfill, should it be constructed over the old waste.

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110 CHAPTER 5 SUMMARY AND CONCLUSIONS 5.1 Summary Landfill settlement is an important engineering challenge with significant environmental and economic implications in th e field of waste management. This study was performed to gain a greater understand ing of landfill geotechnical engineering and gain greater utility for using cone penetration testing (CPT) in landfills. The research presented in this thesis was performed as part of a larger study to evaluate the feasibility of constructing a new, lined landfill on top of an unlined, old municipal waste landfill. This thesis was organized into three sepa rate, yet related, studies. The first study looked at various waste engine ering properties compared to compressibility of discrete samples taken from the old landfill at different depths in the landfill. A great difference existed between the upper and lower halves of the waste. The lower waste had higher moisture content, lower volatile solids, and lower methane yield. Several relationships were found between engineering properties in the landfill (in itial density, soils content, moisture content, volatile solids conten t, and level of degradation) and waste compressibility. Samples that had lower meth ane yield and volatile solids content (more degraded) were less compressible than less de graded samples indicating that as waste decomposes the compressibility diminishes. In the next chapter, the CPT was us ed in landfilled waste to determine relationships between CPT data and waste prope rties. The CPT, commonly used in soil foundation analysis, is valuable for id entifying soil engineering properties and

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111 stratification using empirical relationships a nd could be valuable for evaluating landfill conditions should meaningful empirical relations hips be drawn for waste. CPT data for known stratigraphic layers below the surface— 3–foot cover soil layer, 27–foot waste layer with intermittent soil, and the soil beneath the waste down to the bedrock—were first compared and distinct differences between layers were found. Then CPT data were further broken down into ranges corresponding to waste samples taken in Chapter 2 and compared with other waste properties. Fric tion ratio provided mean ingful results among different waste properties, and similar observations were made with the tip resistance. In the final study, waste compressibility da ta from Chapter 2 were used to predict primary landfill settlement under an applie d load that was compared to observed settlement from a conical test load made of soil. Predicting landfill settlement is a difficult, yet important, engineering undert aking with many applications for landfill redevelopment. Waste settlement was dete rmined using a model that related waste compressibility to specific weight. Then set tlement data, observed at several points under the conical test load, were compared to pr edicted data. The results of the comparison helped determine the utility of evaluating wa ste compressibility in a laboratory setting and applying compression indices to accurately predict settlement. 5.2 Conclusions The findings of these thr ee studies relate to the geotechnical and environmental aspects of what happens in landfills as they age with respect to predicting settlement. Generally speaking, waste compressibility is influenced by several other landfill engineering properties, the CP T can be used to gain a greater understanding of waste properties, and using the compression data obtained in a laboratory on a small waste

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112 sample can produce accurate settlement pred ictions. More specifica lly, the findings of this study include the following: Waste with higher moisture content, f ound deeper in the landfill, was more degraded than drier waste found at shallowe r depths, though not significantly older. As waste degrades and the engineeri ng properties change (specific weight increases, soil content increases, volatil e solids decrease, and methane yield decreases), waste becomes less compressibl e. Waste compression exponents used in this study were C = 0.20 for less degraded waste and C = 0.18 for more degraded samples. Piezocone penetration tes ting can be used to dist inguish waste engineering properties and degree of waste decomposition with confidence in a landfill if data are divided into layers and average (o r geometric mean) values are compared between layers (to account for the high variability of CPT data in waste). Waste layers with greater degradation, which also exhibited higher moisture content, lower volatile solids, higher sp ecific weight, and higher soil content exhibited greater cone tip resistance, QT, and higher friction ration (FR). Higher waste compressibility (determined by lower 1000 and higher C being more compressible) tended to increase with incr ease of tip resistance and decrease with increasing friction ratio. When used to estimate landfill settlement, the waste compressibility data provided a relatively accurate prediction when compar ed to field data. This prediction was dependent on the assumption of a historic waste load, with qo in the range of 1,500 to 2,000 psf providing the best results. 5.3 Implications The greater implications of these fi ndings may affect the manner in which landfills are designed, operated, and studi ed. Confirming that waste engineering properties and compressibility change with the level of degradation and over time, engineers can account for the changes in vol ume and capacity calculations, approximate settlement, and understand landfill geotechnical behavior better. The CPT can be developed into a more meaningful tool for de termining waste characteristics. However, additional tests need to be perf ormed in several other landfills with different conditions to

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113 develop empirical relationshi ps with confidence and perh aps determine algorithms or waste classification charts for determine wa ste properties from CPT data. A waste classification algorithm or waste classification chart, much li ke Robertson et al. (1986) created for soil classification, could be crea ted for waste based on a dditional experiences and CPT data. Also CPT data could be useful in drawing correlati ons with friction angle in order to be able to predict slope stabil ity. Finally, a new method for predicting waste primary settlement or compressibility usi ng laboratory compression data from samples obtained from the landfill was suggested. This method was performed and compared well with actual settlement data. This method could be used in the future to evaluate compressibility on a small scale, using la boratory compression instruments, and then applied with confidence to large-scale landfill engin eering design where primary settlement is a concern.

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114 APPENDIX A COMPRESSION–ANALYSIS WA LL FRICTION DISCUSSION AND CALCULATION Wall friction within the compression cylinder used in laboratory–scale compression–analysis affects force measur ements (Figure B-1). Beaven (2000) conducted similar waste compression studies a nd concluded that the sidewall friction had only a 4 to 8% effect on refuse density. Th e following equation was derived to determine the vertical effective stress due to wall friction for any depth in the compression cylinder (Beaven 2000): [psf]. load Applied ]; [ cell n compressio of wall and ste between wa angle friction ]; [ waste the of angle friction internal ' [ft]; cylinder the of diameter inside [ft]; cell in the depth [pcf]; weight specific tan ' sin 1 4 : where 1 ' P d z d B Pe e BBz Bz vo o Assumptions about the intern al friction of the waste, , and the friction angle between waste and compression cylinder wall, , were made. Internal friction angle of the waste has been reported to range from 20° and 40°, and 30° was selected for this calculation. The friction angle between wast e and side wall was measured by Beaven (2000) to be 27°, but is approximated for this calculations to be 25°.

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115 Figure B-1: Theoretical Comp ression Cylinder Sidewall Model Typical compression circumstances we re assumed where specific weight, , was equal to 60.0 pcf and applied pressure was 3, 500 psf. The resulting vertical effective stress as a result of wall friction in the middle of the cylinder (z = 1 foot) was 427 psf, which is 12.2% of the measured load. Alternativ ely, under the maximum load applied to a waste sample (12,677 psf), the wall friction in the middle of the cylinder was 1,481 psf, 11.7% of the total applied pressure. A adapted from Beaven (2000) d P z z Â’v Â’h Â’v+ Â’v P = Applied Load A = Cross section area = Shear stress in sidewall = Specific Weight = angle of friction between waste and sidewall Pore pressure assumed zero and not reflected in diagram

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APPENDIX B LARGE DIAMETER BUCKET AUGER BO RING LOG AND SPE CIFIC WEIGHT CALCULATIONS

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117Table B-1: Boring Waste Removal Wei ghts and Specific Weight Calculations Gross Container Net Trash Bucket Bucket Total Segment Specific Sample Weight Weight Weight Can1 12 23 Weight Depth Length Volume Weight [lbs.] [lbs.] [lbs.] [lbs.] [lbs.] [lbs.] [lbs.] [ft] [ft] [ft3] [pcf] 2-1 4,096 1,046 3,050 3050 4.5 4.5 31.8 95.9 2-2 2,453 1,050 1,403 82 12 17 1514 10.0 5.5 38.9 38.9 2-3 2,964 750 2,214 132 28 33 2407 15.4 5.4 38.3 62.9 2-4 4,110 1,045 3,065 98 20 17 3200 20.3 4.9 34.8 92.1 2-5 4,412 1,046 3,366 123 20 22 3531 26.0 5.7 40.1 88.2 2-6 4,934 1,077 3,857 131 24 26 4038 33.8 7.8 54.8 73.7 6-1 3,394 750 2,644 217 2861 5.3 5.3 37.1 77.1 6-2 2,674 1,046 1,628 97 20 19 1764 10.0 4.8 33.6 52.5 6-3 2,383 1,050 1,333 56 12 11 1412 13.7 3.7 25.9 54.5 6-4 2,673 1,045 1,628 134 32 31 1825 19.4 5.8 40.6 44.9 6-5 3,160 1,046 2,114 123 28 26 2291 25.3 5.9 41.8 54.8 6-6 2,835 1,050 1,785 134 41 39 1999 30.0 4.7 33.0 60.6 7-1 3,180 750 2,430 2430 5.4 5.4 38.3 63.5 7-2 2,606 1,046 1,560 97 22 19 1698 10.8 5.4 38.3 44.3 7-3 2,481 1,035 1,446 88 17 13 1564 14.6 3.8 26.5 59.0 7-4 2,814 750 2,064 148 33 31 2276 19.6 5.0 35.3 64.4 7-5 3,326 1,046 2,280 113 24 23 2440 26.5 6.9 48.9 49.9 7-6 2,636 1,035 1,601 1601 30.0 3.5 24.7 64.7 Radius = 36 in Area = 7.1 ft2

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118Table B-1—Continued Gross Container Net Trash Bucket Bucket Total Segment Specific Sample Weight Weight Weight Can1 12 23 Weight Depth Length Volume Weight [lbs.] [lbs.] [lbs.] [lbs.] [lbs.] [lbs.] [l bs.] [ft] [ft] [ft3] [pcf] 12-1 4,583 750 3,833 3833 4.7 4.7 33.0 116.2 12-2 2,638 1,046 1,592 66 13 11 1682 10.0 5.3 37.7 44.6 12-3 2,373 1,050 1,323 72 15 15 1425 14.9 4.9 34.8 41.0 12-4 3,412 1,035 2,377 182 31 33 2623 20.0 5.1 35.9 73.0 12-5 2,961 750 2,211 117 23 22 2373 24.5 4.5 31.8 74.6 12-6 4,280 1,050 3,230 152 28 26 3436 29.5 5.0 35.3 97.2 12-7 2,439 1,046 1,393 1393 31.0 1.5 10.6 131.4 13-1 4,486 1,046 3,440 3440 5.0 5.0 35.3 97.3 13-2 2,833 1,045 1,788 79 21 22 1910 10.0 5.0 35.3 54.0 13-3 2,681 750 1,931 66 13 13 2023 15.2 5.2 36.5 55.4 13-4 2,945 1,046 1,899 138 26 26 2089 20.0 4.8 34.2 61.1 13-5 4,363 1,045 3,318 171 27 30 3546 26.0 6.0 42.4 83.6 13-6 3,562 750 2,812 115 24 23 2974 31.2 5.2 36.5 81.4 1 Trash Can sample used in compression analysis 2 Bucket 1 used in moisture content, methane yield, volatile solids, and soil content analysis 3 Bucket 2 used in leaching tests not discussed in this thesis

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APPENDIX C WASTE SAMPLE COMPOSITION DATA

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120Table C-1: Waste Sample Composition Data Sample Sample Weight Moisture Content Paper Plastic Yard Waste Textiles Stone/ Metal Glass/ Ceramic Retained Fines Passing Fines Total mass [g] 2121 798 856 423 136 179.1 663 131.2 1717 437 4542 2-2 fraction [%] 37.63% 18.8% 9.3% 3.0% 3.9% 14.6% 2.9% 37.8% 9.6% 100.0% mass [g] 12250 3068.7 176 120 251 25 1166 15 7934 1975 11663 2-3 fraction [%] 25.05% 1.5% 1.0% 2.2% 0.2% 10.0% 0.1% 68.0% 16.9% 100.0% mass [g] 6835 2381 510 261 471 567 266 194 1212 302 3782 2-4 fraction [%] 34.84% 13.5% 6.9% 12.4% 15.0% 7.0% 5.1% 32.0% 8.0% 100.0% mass [g] 8258 2875 594 381 279 253 344 129 1960 677 4617 2-5 fraction [%] 34.82% 12.9% 8.3% 6.1% 5.5% 7.5% 2.8% 42.4% 14.7% 100.0% mass [g] 10325 3297 863 545 1210 295 443 362 1280 120 5119 2-6 fraction [%] 31.93% 16.9% 10.7% 23.6% 5.8% 8.7% 7.1% 25.0% 2.3% 100.0% mass [g] 7590 3293.8 1850 431 376 21 227 108 505 364 3880 6-2 fraction [%] 43.40% 47.7% 11.1% 9.7% 0.5% 5.8% 2.8% 13.0% 9.4% 100.0% mass [g] 4202 1155.2 525 170 862 127 113 55 460 398 2711 6-3 fraction [%] 27.49% 19.4% 6.3% 31.8% 4.7% 4.2% 2.0% 17.0% 14.7% 100.0% mass [g] 13230.3 3538.4 572.325 527.6875 498.5 257.5125 145.65 172.25 4075.7 1762.8 8012 6-4 fraction [%] 26.74% 7.1% 6.6% 6.2% 3.2% 1.8% 2.1% 50.9% 22.0% 100.0% mass [g] 10989 4270.9 605.61 328.94 276.52 75.44 623.9 44.15 3198.97 1175.2 6329 6-5 fraction [%] 38.87% 9.6% 5.2% 4.4% 1.2% 9.9% 0.7% 50.5% 18.6% 100.0% mass [g] 16895.5 7231.8 142.51 460.71 914.65 285.86 813.9 193.92 2973.13 2354.7 8139 6-6 fraction [%] 42.80% 1.8% 5.7% 11.2% 3.5% 10.0% 2.4% 36.5% 28.9% 100.0% mass [g] 7738.8 1878.6 1349.2 456.8625 628.975 186.575 398.225 130.8 1168.2 542.6 4861 7-2 fraction [%] 24.28% 27.8% 9.4% 12.9% 3.8% 8.2% 2.7% 24.0% 11.2% 100.0% mass [g] 4964.3 1594.7 1203 91 535 125 53 78 571 325 2981 7-3 fraction [%] 32.12% 40.3% 3.0% 18.0% 4.2% 1.8% 2.6% 19.1% 10.9% 100.0% mass [g] 7977.8 3039.4 664 458 1087 29 187 80 4383 1089 7976 7-4 fraction [%] 38.10% 8.3% 5.7% 13.6% 0.4% 2.3% 1.0% 55.0% 13.6% 100.0% mass [g] 9415.1 3935.7 770.375 279.275 729.8125 78.425 175.375 51.1125 1413.26 1210.9 4709 7-5 fraction [%] 41.80% 16.4% 5.9% 15.5% 1.7% 3.7% 1.1% 30.0% 25.7% 100.0%

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121Table C-1—Continued Sample Sample Weight MC Paper Plastic Yard Waste Textiles Stone/ Metal Glass/ Ceramic Retained Fines Passing Fines Total mass [g] 4099.8 1206.6 677.375 425.525 240.65 90.525 262.8 41.4 430 411.5 2580 12-2 fraction [%] 29.43% 26.3% 16.5% 9.3% 3.5% 10.2% 1.6% 16.7% 16.0% 100.0% mass [g] 3865.144 13993 588 110 204 1.9 60 4.0 6451 1793 9211 12-4 fraction [%] 27.62% 6.4% 1.2% 2.2% 0.0% 0.7% 0.0% 70.0% 19.5% 100% mass [g] 8818.8 3560.8 251.0875 304.55 1021.725 1107.5125 297.6 133.85 842.075 183.5 4142 12-5 fraction [%] 40.38% 6.1% 7.4% 24.7% 26.7% 7.2% 3.2% 20.3% 4.4% 100.0% mass [g] N/A N/A 762 588 666 410 594 115 680 368 4183 12-6 fraction [%] N/A 18.2% 14.0% 15.9% 9.8% 14.2% 2.8% 16.3% 8.8% 100.0% mass [g] 3185 766.4 1676.62 80.15 435.41 16.52 370.37 107.89 402.9 772.3 3862.16 13-3 fraction [%] 24.06% 43.4% 2.1% 11.3% 0.4% 9.6% 2.8% 10.4% 20.0% 100.0%

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APPENDIX D BIOCHEMICAL METHANE POTENTIAL, MOISTURE CONTENT, VOLATILE SOLIDS, AND SOIL CONTENT DATA; BMP CUMULATIVE VOLUME PLOTS

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123 Table D-1: Biochemical Methane Po tential Raw Data and Calcluation Raw Data from BMP Assay BMP Standard Deviation Total Solids Volatile Solids Mass Fraction Total Degradable Fraction Vol. Solid Fraction (MF/TDF) Ultimate BMP Sample Component [L CH4/ g vs] [-] [mass] [mass] [% of total] [% of total] [% of VS] [L CH4/ g vs] 2-2 2-2 B 0.1308 0.0080 0.8846 0.8623 18.8% 66.3% 28.4% 0.0955 2-2 P 0.0504 0.0042 0.9684 0.1054 9.6% 66.3% 14.5% 2-2 R 0.0399 0.0021 0.9349 0.2509 37.8% 66.3% 57.0% 2-4 2-4 B 0.0187 0.0037 0.8059 0.7503 13.5% 53.5% 25.2% 0.0144 2-4 P 0.0000 0.0066 0.9575 0.1122 8.0% 53.5% 14.9% 2-4 R 0.0110 0.0022 0.9175 0.2725 32.0% 53.5% 59.9% 2-5 2-5 B 0.0293 0.0009 0.9565 0.8442 12.9% 70.0% 18.4% 0.0150 2-5 P 0.0113 0.0002 0.9909 0.0944 14.7% 70.0% 21.0% 2-5 R 0.0000 0.0067 0.9830 0.2363 42.4% 70.0% 60.7% 2-6 2-6 B 0.0138 0.0016 0.5638 0.5109 16.9% 44.2% 38.1% 0.0105 2-6 P 0.0000 0.0041 1.0285 0.1416 2.3% 44.2% 5.3% 2-6 R 0.0072 0.0021 0.7462 0.2999 25.0% 44.2% 56.6% 6-2 6-2 B 0.2012 0.0133 0.9384 0.9159 47.7% 70.1% 68.0% 0.1808 6-2 P 0.0408 0.0024 0.9773 0.2143 9.4% 70.1% 13.4% 6-2 R 0.0502 0.0063 0.9528 0.3603 13.0% 70.1% 18.6% 6-3 6-3 B 0.1155 0.0037 0.9679 0.9327 19.4% 51.0% 38.0% 0.1409 6-3 P 0.1946 0.0021 0.9858 0.1531 14.7% 51.0% 28.8% 6-3 R 0.1779 0.0656 0.9525 0.5400 17.0% 51.0% 33.2% 6-4 6-4 B 0.0533 0.0065 0.9276 0.7213 7.1% 80.0% 8.9% 0.0349 6-4 P 0.0223 0.0037 0.9820 0.0758 22.0% 80.0% 27.5% 6-4 R 0.0245 0.0084 0.9776 0.1403 50.9% 80.0% 63.6% 6-6 6-6 B 0.0205 0.0042 0.9759 0.4732 1.8% 67.2% 2.6% 0.0151 6-6 P 0.0264 0.0317 0.9946 0.0304 28.9% 67.2% 43.0% 6-6 R 0.0116 0.0111 0.9892 0.1147 36.5% 67.2% 54.4% 7-2 7-2 B 0.2497 0.0047 0.8889 0.8541 27.8% 62.9% 44.1% 0.1933 7-2 P 0.0808 0.0131 0.9669 0.1192 11.2% 62.9% 17.7% 7-2 R 0.0938 0.0106 0.9201 0.4956 24.0% 62.9% 38.2% 7-3 7-3 B 0.2318 0.0156 0.9222 0.9112 40.3% 70.4% 57.3% 0.2002 7-3 P 0.0793 0.0019 0.9818 0.1968 10.9% 70.4% 15.5% 7-3 R 0.0748 0.0186 0.9738 0.3768 19.1% 70.4% 27.2% 7-4 7-4 B 0.1982 0.0036 0.7755 0.7920 8.3% 76.9% 10.8% 0.0876 7-4 P 0.0001 0.0013 0.9463 0.0867 13.6% 76.9% 17.7% 7-4 R 0.0063 0.0250 0.9229 0.1399 55.0% 76.9% 71.4% 7-5 7-5 B 0.1584 0.0094 0.8790 0.8329 16.4% 72.1% 22.7% 0.0917 7-5 P 0.0030 0.0051 0.9865 0.1157 25.7% 72.1% 35.7% 7-5 R 0.0000 0.0019 0.9805 0.2340 30.0% 72.1% 41.6% B Biodegradable portion (i.e. paper) P Fines passing No. 40 sieve R Fines retained by No. 40 sieve

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124 Table D-1—Continued Raw Data from BMP Assay BMP Standard Deviation Total Solids Volatile Solids Mass Fraction Total Degradable Fraction Vol. Solid Fraction (MF/TDF) Ultimate BMP Sample Component [L CH4/ g vs] [-] [mass] [mass] [% of total] [% of total] [% of VS] [L CH4/ g vs] 12-2 12-2 B 0.2400 0.0127 0.9462 0.8404 26.3% 58.9% 44.6% 0.2282 12-2 P 0.1715 0.0087 0.9929 0.0951 16.0% 58.9% 27.1% 12-2 R 0.1933 0.0534 0.9848 0.2970 16.7% 58.9% 28.3% 12-5 12-5 B 0.0951 0.0098 0.7892 0.7651 6.1% 30.8% 19.7% 0.0502 12-5 P 0.0151 0.0027 0.9452 0.1458 4.4% 30.8% 14.4% 12-5 R 0.0220 0.0016 0.8286 0.3239 20.3% 30.8% 66.0% 12-6 12-6 B 0.0255 0.0034 0.9616 0.5941 18.2% 43.3% 42.1% 0.0225 12-6 P 0.0096 0.0050 0.9824 0.1426 8.8% 43.3% 20.3% 12-6 R 0.0186 0.0025 0.9724 0.2481 16.3% 43.3% 37.6% 13-3 13-3 B 0.2660 0.0062 0.9376 0.9066 43.4% 73.8% 58.8% 0.2553 13-3 P 0.1505 0.0112 0.9864 0.0701 20.0% 73.8% 27.1% 13-3 R 0.1494 0.0069 0.9695 0.2459 10.4% 73.8% 14.1% B Biodegradable portion (i.e. paper) P Fines passing No. 40 sieve R Fines retained by No. 40 sieve

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125 Table D-2: Fines, Volatile Solids, and Soil Content Data and Calculations BMP St. Dev. Total Percent Fines Component Volatile Solids Volatile Solids Fraction Total Volatile Solids Component Soil Content Total Soil Content Sample Component (%R+%P) [% of comp] [% of to tal] [% of total] [% of comp] [% of total] 2-2 2-2 B 0.0058 47.4% 97.5% 18.4% 29.6% 36.2% 2-2 P 10.9% 1.0% 8.6% 2-2 R 26.8% 10.1% 27.7% 2-4 2-4 B 0.0031 40.0% 93.1% 12.5% 23.0% 29.6% 2-4 P 11.7% 0.9% 7.0% 2-4 R 29.7% 9.5% 22.5% 2-5 2-5 B 0.0035 57.1% 88.3% 11.3% 22.9% 45.5% 2-5 P 9.5% 1.4% 13.3% 2-5 R 24.0% 10.2% 32.2% 2-6 2-6 B 0.0019 27.3% 90.6% 15.3% 25.7% 17.0% 2-6 P 13.8% 0.3% 2.0% 2-6 R 40.2% 10.0% 15.0% 6-2 6-2 B 0.0122 22.4% 97.6% 46.5% 53.5% 15.4% 6-2 P 21.9% 2.1% 7.3% 6-2 R 37.8% 4.9% 8.1% 6-3 6-3 B 0.0228 31.7% 96.4% 18.7% 30.6% 19.8% 6-3 P 15.5% 2.3% 12.4% 6-3 R 56.7% 9.6% 7.3% 6-4 6-4 B 0.0071 72.9% 77.8% 5.6% 14.6% 63.9% 6-4 P 7.7% 1.7% 20.3% 6-4 R 14.4% 7.3% 43.6% 6-6 6-6 B 0.0132 65.5% 48.5% 0.8% 6.0% 60.3% 6-6 P 3.1% 0.9% 28.0% 6-6 R 11.6% 4.2% 32.3% 7-2 7-2 B 0.0069 35.2% 96.1% 26.7% 41.0% 20.9% 7-2 P 12.3% 1.4% 9.8% 7-2 R 53.9% 12.9% 11.1% 7-3 7-3 B 0.0154 30.1% 98.8% 39.9% 49.5% 20.5% 7-3 P 20.0% 2.2% 8.7% 7-3 R 38.7% 7.4% 11.7% 7-4 7-4 B 0.0141 68.6% 102.1% 8.5% 18.1% 59.0% 7-4 P 9.2% 1.2% 12.4% 7-4 R 15.2% 8.3% 46.6% 7-5 7-5 B 0.0066 55.7% 94.8% 15.5% 25.7% 45.6% 7-5 P 11.7% 3.0% 22.7% 7-5 R 23.9% 7.2% 22.9%

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126 Table D-2—Continued BMP St. Dev. Total Percent Fines Component Volatile Solids Volatile Solids Fraction Total Volatile Solids Component Soil Content Total Soil Content Sample Component (%R+%P) [% of comp] [% of to tal] [% of total] [% of comp] [% of total] 12-2 12-2 B 0.0196 32.6% 88.8% 23.3% 29.9% 26.1% 12-2 P 9.6% 1.5% 14.4% 12-2 R 30.2% 5.0% 11.6% 12-5 12-5 B 0.0049 24.8% 96.9% 5.9% 14.5% 16.1% 12-5 P 15.4% 0.7% 3.7% 12-5 R 39.1% 7.9% 12.4% 12-6 12-6 B 0.0033 25.1% 61.8% 11.3% 16.7% 19.6% 12-6 P 14.5% 1.3% 7.5% 12-6 R 25.5% 4.1% 12.1% 13-3 13-3 B 0.0064 30.4% 96.7% 42.0% 46.0% 26.4% 13-3 P 7.1% 1.4% 18.6% 13-3 R 25.4% 2.6% 7.8% B Biodegradable portion (i.e. paper) P Fines passing No. 40 sieve R Fines retained by No. 40 sieve

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127 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-2 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-4 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-2 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-4 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-2 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-4 P Cellulose Newspaper Blank Figure D-1: BM P Cumulative Methane Volume for Sample 2-2 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-2: BMP Cu mulative Methane Volume for Sample 2-4 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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128 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-5 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-6 Paper Cellulose Newspaper Blank Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-5 R Cellulose Newspaper Col 1 vs Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-6 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-5 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 2-6 P Cellulose Newspaper Blank Figure D-3: BM P Cumulative Methane Volume for Sample 2-5 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-4: BMP Cu mulative Methane Volume for Sample 2-6 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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129 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-2 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-3 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-2 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-3 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-2 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-3 P Cellulose Newspaper Blank Figure D-5: BM P Cumulative Methane Volume for Sample 6-2 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-6: BMP Cu mulative Methane Volume for Sample 6-3 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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130 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-4 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-6 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-4 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-6 R Cellulose Newspaper Blank Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-4 P Cellulose Newspaper Col 1 vs Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 6-6 P Cellulose Newspaper Blank Figure D-7: BM P Cumulative Methane Volume for Sample 6-4 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-8: BMP Cu mulative Methane Volume for Sample 6-5 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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131 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-2 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-3 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-2 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-3 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-2 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-3 P Cellulose Newspaper Blank Figure D-9: BM P Cumulative Methane Volume for Sample 7-2 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-10: BMP Cumulative Methane Volume for Sample 7-3 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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132 Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 74 Paper Cellulose Newspaper Col 1 vs Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-5 Paper Cellulose Newspaper Blank Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-4 R Cellulose Newspaper Col 1 vs Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-5 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-4 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 7-5 P Cellulose Newspaper Blank Figure D-11: BMP Cumulative Methane Volume for Sample 7-4 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-12: BMP Cumulative Methane Volume for Sample 7-5 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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133 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-2 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-5 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-2 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-5 R Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-2 P Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-5 P Cellulose Newspaper Blank Figure D-13: BMP Cumulative Methane Volume for Sample 12-2 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-14: BMP Cumulative Methane Volume for Sample 12-5 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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134 Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-6 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 13-3 Paper Cellulose Newspaper Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-6 R Cellulose Newspaper Blank Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 13-3 R Cellulose Newspaper Col 1 vs Blank Days 01020304050 Cumulative Methane Volume (mL) 0 20 40 60 80 100 12-6 P Cellulose Newspaper Col 1 vs Blank Days 0102030405060 Cumulative Methane Volume (mL) 0 20 40 60 80 100 13-3 P Cellulose Newspaper Blank Figure D-15: BMP Cumulative Methane Volume for Sample 12-6 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines Figure D-16: BMP Cumulative Methane Volume for Sample 13-3 (a) Biodegradable Paper, (b) Retained Fines, and (c) Passing Fines

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135 APPENDIX E MSW BIOCHEMCIAL METHANE POTENTI AL VALUES FROM PREVIOUS STUDIES Table E-1: Biochemical Methane Potentia l Values for Waste and Waste Components from Previous Studies Sample Description Volatile Solid [%] Ultimate Methane yield [L CH4 / g VS] Mechanically Sorted Organic Fraction of MSW Sumter County, FL1 Fresh Dried 79.7 84.1 0.222 (±0.014)* 0.215 (±0.013)* Hand Sorted Organic Fraction of MSW – Levy County, FL1 92.5 0.205 (±0.011)* Yard waste Samples1 Grass Leaves Branches Blend 88.1 95.0 93.9 92.0 0.209 (±0.005)* 0.123 (±0.005)* 0.134 (±0.006)* 0.143 (±0.004)* Paper Samples1 Office Corrugated Printed newspaper Unprinted newspaper Magazine 92.7 97.7 97.6 97.9 78.1 0.369 (±0.014)* 0.278 (±0.012)* 0.100 (±0.003)* 0.084 (±0.003)* 0.203 (±0.008)* Food packing samples1 Cellophane Uncoated food board Coated food board Milk carton Wax paper 99.4 98.6 93.3 99.4 98.4 0.349 (±0.023)* 0.343 (±0.020)* 0.334 (±0.017)* 0.318 (±0.014)* 0.341 (±0.022)* MSW non-classified2 0.210 (±0.012)** MSW non-classified2 0.220 (±0.009)** MSW feed 429-ETU2 0.292 (±0.018)** MSW 0.0381cm (0.03”) 2 0.206 (±0.014)** MSW 0.0762cm (0.06”) 2 0.212 (±0.010)** MSW 0.3175cm (0.125”) 2 0.224 (±0.002)** MSW 1.27cm (0.5”) 2 0.216 (±0.015)** * Standard Deviation **80% confidence interval 1 Owens and Chynoweth (1993) 2 Chynoweth et al. (1993)

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APPENDIX F LABORATORY SCALE WASTE COMPRESSION–ANALYSIS DATA

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137Table F-1: Wa ste Compression Analysis Data Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry /1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 2-2 73 391.5 3209 2152 1364 9.5 65 286 11.2 1.49 49.1 1,327 0.787 37.6% 30.6 1.36 46.8 0.197 0.992 29.2 2-2 73 428.5 6344 4013 2544 17.7 122 249 9.8 1.29 56.4 1,524 0.904 37.6% 35.2 2.54 2-2 73 449.0 9607 5867 3719 25.8 178 228 9.0 1.19 61.5 1,661 0.985 37.6% 38.4 3.72 2-2 73 465.5 12795 8813 5586 38.8 267 212 8.3 1.10 66.3 1,790 1.062 37.6% 41.4 5.59 2-2 73 473.8 15911 11197 7097 49.3 340 203 8.0 1.06 69.0 1,863 1.105 37.6% 43.0 7.10 2-2 73 481.0 18223 14843 9408 65.3 450 196 7.7 1.02 71.5 1,932 1.146 37.6% 44.6 9.41 2-2 73 485.5 20215 37.6% 2-3 121 400.0 3156 2103 1333 9.3 64 277 10.9 1.44 83.9 2,266 1.345 25.1% 62.9 1.33 81.8 0.122 0.974 64. 4 2-3 121 426.0 6341 4443 2816 19.6 135 251 9.9 1.31 92.6 2,501 1.484 25.1% 69.4 2.82 2-3 121 445.3 9410 6663 4223 29.3 202 232 9.1 1.21 100.3 2,709 1.607 25.1% 75.2 4.22 2-3 121 449.8 12809 9563 6061 42.1 290 227 9.0 1.18 102.3 2,762 1.639 25.1% 76.7 6.06 2-3 121 455.5 15821 12447 7889 54.8 378 222 8.7 1.15 105.0 2,834 1.681 25.1% 78.7 7.89 2-3 121 459.0 19299 15436 9784 67.9 468 218 8.6 1.13 106.6 2,879 1.708 25.1% 79.9 9.78 2-3 121 461.3 20222 25.1% 2-4 87 343.25 34.8% 2-4 87 385.5 4103 2601 18.1 125 292 11.5 1.52 57.4 1,549 0.919 34.8% 37.4 2.60 46.7 0.213 0.998 30.4 2-4 87 406.75 6083 3856 26.8 185 270 10.6 1.41 61.9 1,670 0.991 34.8% 40.3 3.86 2-4 87 424.5 8168 5177 36.0 248 253 9.9 1.31 66.2 1,788 1.061 34.8% 43.1 5.18 2-4 87 440 10717 6793 47.2 325 237 9.3 1.23 70.5 1,904 1.130 34.8% 46.0 6.79 2-4 87 450 13640 8645 60.0 414 227 8.9 1.18 73.6 1,988 1.180 34.8% 48.0 8.65 2-5 106 351 3708 34.8% 2-5 106 384.75 6413 3807 2413 16.8 116 292 11.5 1.52 69.7 1,882 1.116 34.8% 45.4 2.41 60.5 0.172 0.991 39.4 2-5 106 412.75 9530 6019 3815 26.5 183 264 10.4 1.38 77.1 2,081 1.235 34.8% 50.2 3.82 2-5 106 426.5 12648 8718 5526 38.4 265 251 9.9 1.30 81.3 2,195 1.302 34.8% 53.0 5.53 2-5 106 436 15872 11197 7097 49.3 340 241 9.5 1.25 84.5 2,282 1.354 34.8% 55.1 7.10 2-5 106 443.25 19021 13675 8668 60.2 415 234 9.2 1.22 87.1 2,352 1.396 34.8% 56.8 8.67 2-5 106 447.5 19991 34.8%

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138Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry /1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 2-6 115 235 1750 31.9% 2-6 115 260.75 3132 1784 1131 7.9 54 416 16.4 2.17 53.1 1,434 0.851 31.9% 36.1 1.13 0.214 0.999 2-6 115 318.25 6331 3511 2225 15.5 107 359 14.1 1.87 61.6 1,663 0.987 31.9% 41.9 2.23 2-6 115 348.5 9318 5436 3445 23.9 165 329 12.9 1.71 67.3 1,817 1.078 31.9% 45.8 3.45 2-6 115 374 12588 7620 4830 33.5 231 303 11.9 1.58 72.9 1,969 1.168 31.9% 49.6 4.83 2-6 115 389.5 16123 9826 6228 43.3 298 288 11.3 1.50 76.9 2,075 1.231 31.9% 52.3 6.23 2-6 115 401 18882 12445 7888 54.8 378 276 10.9 1.44 80.1 2,162 1.283 31.9% 54.5 7.89 2-6 115 385.25 19952 31.9% 6-2 85 304.25 3214 1804 1143 7.9 55 373 14.7 1.94 43.8 1,183 0.702 43.4% 24.8 1.14 42.7 0.195 0.999 24.2 6-2 85 357.25 6528 3983 2525 17.5 121 320 12.6 1.66 51.1 1,379 0.818 43.4% 28.9 2.52 6-2 85 384 9225 5914 3748 26.0 179 293 11.5 1.52 55.7 1,505 0.893 43.4% 31.6 3.75 6-2 85 403 12804 8648 5481 38.1 262 274 10.8 1.43 59.6 1,610 0.955 43.4% 33.7 5.48 6-2 85 413.75 15740 10973 6955 48.3 333 263 10.4 1.37 62.0 1,675 0.994 43.4% 35.1 6.96 6-2 85 428.25 18883 14062 8913 61.9 427 249 9.8 1.29 65.7 1,773 1.052 43.4% 37.2 8.91 6-2 85 432.25 20315 15461 245 9.6 1.27 66.7 1,802 1.069 43.4% 37.8 6-3 41.5 373.75 3186 1835 1163 8.1 56 303 11.9 1.58 26.3 710 0.421 27.5% 19.1 1.16 25.8 0.215 0.966 18.7 6-3 41.5 424 6486 3698 2344 16.3 112 253 10.0 1.32 31.5 851 0.505 27.5% 22.9 2.34 6-3 41.5 452 9574 6264 3970 27.6 190 225 8.9 1.17 35.4 957 0.568 27.5% 25.7 3.97 6-3 41.5 455.5 12718 8558 5424 37.7 260 222 8.7 1.15 36.0 972 0.577 27.5% 26.1 5.42 6-3 41.5 467 15970 11532 7309 50.8 350 210 8.3 1.09 38.0 1,025 0.608 27.5% 27.5 7.31 6-3 41.5 489 18573 13560 8595 59.7 412 188 7.4 0.98 42.4 1,145 0.679 27.5% 30.7 8.59

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139Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry /1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 6-4 105 283.5 1640 26.7% 6-4 105 328.25 3188 1775 1125 7.8 54 349 13.7 1.81 57.6 1,555 0.922 26.7% 42.2 1.13 56.5 0.160 0.999 41.4 6-4 105 366.75 6595 3692 2340 16.3 112 310 12.2 1.61 64.7 1,748 1.037 26.7% 47.4 2.34 6-4 105 388 9513 5754 3647 25.3 175 289 11.4 1.50 69.5 1,876 1.113 26.7% 50.9 3.65 6-4 105 402.5 12619 8094 5130 35.6 246 275 10.8 1.43 73.2 1,975 1.172 26.7% 53.6 5.13 6-4 105 419.75 16089 11645 7381 51.3 353 257 10.1 1.34 78.1 2,107 1.250 26.7% 57.2 7.38 6-4 105 426.25 19530 14177 8986 62.4 430 251 9.9 1.30 80.1 2,162 1.283 26.7% 58.7 8.99 6-4 105 431 20500 26.7% 6-5 111 276.5 1574 38.9% 6-5 111 327.5 3547 1667 1057 7.3 51 350 13.8 1.82 60.8 1,641 0.973 38.9% 37.1 1.06 60.3 0.170 0.999 36.8 6-5 111 367.25 6584 3376 2140 14.9 102 310 12.2 1.61 68.6 1,851 1.098 38.9% 41.9 2.14 6-5 111 394.25 9721 5857 3712 25.8 178 283 11.1 1.47 75.1 2,028 1.203 38.9% 45.9 3.71 6-5 111 406 12784 7075 4484 31.1 215 271 10.7 1.41 78.4 2,116 1.255 38.9% 47.9 4.48 6-5 111 415.75 15886 9130 5787 40.2 277 261 10.3 1.36 81.3 2,194 1.302 38.9% 49.7 5.79 6-5 111 427 19700 12200 7733 53.7 370 250 9.9 1.30 84.9 2,293 1.360 38.9% 51.9 7.73 6-5 111 431.75 19798 38.9% 6-6 54.5 393.75 488 309 2.1 15 283 11.2 1.47 37.0 998 0.592 42.8% 21.1 0.31 44.7 0.176 0.998 25.6 6-6 54.5 421.5 1010 640 4.4 31 256 10.1 1.33 41.0 1,107 0.657 42.8% 23.4 0.64 6-6 54.5 455.5 2284 1448 10.1 69 222 8.7 1.15 47.3 1,276 0.757 42.8% 27.0 1.45 6-6 54.5 479 4316 2736 19.0 131 198 7.8 1.03 52.9 1,428 0.847 42.8% 30.2 2.74 6-6 54.5 494.5 6464 4097 28.5 196 183 7.2 0.95 57.4 1,549 0.919 42.8% 32.8 4.10 6-6 54.5 505 9091 5762 40.0 276 172 6.8 0.90 60.9 1,643 0.975 42.8% 34.8 5.76 6-6 54.5 512.75 11724 7431 51.6 356 164 6.5 0.86 63.7 1,721 1.021 42.8% 36.5 7.43 6-6 54.5 520 14344 9092 63.1 435 157 6.2 0.82 66.7 1,800 1.068 42.8% 38.1 9.09 6-6 54.5 523 16505 10461 72.6 501 154 6.1 0.80 68.0 1,835 1.089 42.8% 38.9 10.46

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140Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 7-2 85 234.75 1583 24.3% 7-2 85 276.75 3133 1949 1235 8.6 59 400 15.8 2.08 40.8 1102 0.654 24.3% 30.9 1.24 39.1 0.202 1.000 29.6 7-2 85 332 6567 4089 2592 18.0 124 345 13.6 1.80 47.4 1278 0.758 24.3% 35.9 2.59 7-2 85 359.5 9474 6084 3856 26.8 185 318 12.5 1.65 51.4 1389 0.824 24.3% 39.0 3.86 7-2 85 380.5 12850 8604 5453 37.9 261 297 11.7 1.54 55.1 1487 0.882 24.3% 41.7 5.45 7-2 85 395.25 15825 11327 7179 49.9 344 282 11.1 1.47 58.0 1565 0.929 24.3% 43.9 7.18 7-2 85 407.5 18675 13609 8626 59.9 413 270 10.6 1.40 60.6 1636 0.971 24.3% 45.9 8.63 7-3 78.5 216.75 1033 32.1% 7-3 78.5 302.5 3199 1968 1247 8.7 60 375 14.8 1.95 40.3 1088 0.645 32.1% 27.3 1.25 38.6 0.198 1.000 26.2 7-3 78.5 380 9431 6246 3959 27.5 190 297 11.7 1.55 50.8 1371 0.814 32.1% 34.5 3.96 7-3 78.5 399.25 12831 8903 5643 39.2 270 278 10.9 1.45 54.3 1466 0.870 32.1% 36.9 5.64 7-3 78.5 414.5 15861 11947 7572 52.6 363 263 10.3 1.37 57.5 1552 0.920 32.1% 39.0 7.57 7-3 78.5 425.25 18977 14535 9213 64.0 441 252 9.9 1.31 59.9 1618 0.960 32.1% 40.7 9.21 7-3 78.5 428.25 19983 32.1% 7-4 125 285.75 1751 38.1% 7-4 125 303.75 3250 2095 1328 9.2 64 373 14.7 1.94 64.1 1731 1.027 38.1% 39.7 1.33 60.7 0.164 0.993 37.6 7-4 125 339.5 6581 4328 2743 19.1 131 338 13.3 1.76 70.9 1914 1.136 38.1% 43.9 2.74 7-4 125 361.25 9402 6518 4131 28.7 198 316 12.4 1.64 75.8 2046 1.214 38.1% 46.9 4.13 7-4 125 382.5 12683 8625 5467 38.0 262 295 11.6 1.53 81.2 2193 1.301 38.1% 50.3 5.47 7-4 125 391.75 15794 11211 7106 49.3 340 285 11.2 1.48 83.9 2265 1.344 38.1% 51.9 7.11 7-4 125 401.25 18733 13989 8867 61.6 425 276 10.9 1.43 86.8 2343 1.390 38.1% 53.7 8.87 7-4 125 403 20300 38.1%

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141Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 7-5 98.5 248.75 1592 41.8% 7-5 98.5 324.75 3132 2050 1299 9.0 62 352 13.9 1.83 53.7 1451 0.861 41.8% 31.3 1.30 50.5 0.147 0.961 29.4 7-5 98.5 345.25 6573 4408 2794 19.4 134 332 13.1 1.73 57.1 1541 0.914 41.8% 33.2 2.79 7-5 98.5 366 9622 6318 4005 27.8 192 311 12.3 1.62 60.9 1643 0.975 41.8% 35.4 4.00 7-5 98.5 385.5 12704 9122 5782 40.2 277 292 11.5 1.52 64.9 1753 1.040 41.8% 37.8 5.78 7-5 98.5 397.75 15715 11086 7027 48.8 336 279 11.0 1.45 67.8 1830 1.086 41.8% 39.4 7.03 7-5 98.5 410 19082 13896 8808 61.2 422 267 10.5 1.39 70.9 1914 1.136 41.8% 41.3 8.81 7-5 98.5 414.5 20100 41.8% 12-2 53 405.25 1831 29.4% 12-2 53 441.75 3652 2320 1470 10.2 70 235 9.3 1.22 43.3 1169 0.693 29.4% 30.5 1.47 39.1 0.219 0.98 9 27.6 12-2 53 463.75 6531 4472 2834 19.7 136 213 8.4 1.11 47.7 1289 0.765 29.4% 33.7 2.83 12-2 53 486 9513 6660 4221 29.3 202 191 7.5 0.99 53.3 1439 0.854 29.4% 37.6 4.22 12-2 53 500.5 12687 8849 5609 38.9 269 177 7.0 0.92 57.7 1557 0.924 29.4% 40.7 5.61 12-2 53 510.5 15833 11800 7479 51.9 358 167 6.6 0.87 61.1 1651 0.979 29.4% 43.1 7.48 12-2 53 518.25 18766 15073 9554 66.3 457 159 6.3 0.83 64.1 1731 1.027 29.4% 45.2 9.55 12-2 53 522.5 19568 29.4% 12-3 57 307.5 1047 27.2% 12-3 57 377 3172 2188 1387 9.6 66 300 11.8 1.56 36.5 986 0.585 27.2% 26.6 1.39 34.1 0.189 0.99 8 24.8 12-3 57 412.25 6526 4583 2905 20.2 139 265 10.4 1.38 41.4 1117 0.663 27.2% 30.1 2.90 12-3 57 433.5 9351 6906 4377 30.4 210 244 9.6 1.27 45.0 1214 0.720 27.2% 32.8 4.38 12-3 57 446 12811 9210 5838 40.5 280 231 9.1 1.20 47.4 1280 0.759 27.2% 34.5 5.84 12-3 57 460.75 15979 12153 7703 53.5 369 216 8.5 1.13 50.6 1367 0.811 27.2% 36.9 7.70 12-3 57 467.5 18946 15148 9601 66.7 460 210 8.3 1.09 52.3 1411 0.837 27.2% 38.1 9.60 12-3 57 472.25 20486 27.2%

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142Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 12-4 173 233.75 2616 27.6% 12-4 173 291 6360 3978 2521 17.5 121 386 15.2 2.01 85.9 2319 1.376 27.6% 62.2 2.52 77.0 0.119 1.000 55.7 12-4 173 312.25 9525 6357 4029 28.0 193 365 14.4 1.90 90.9 2454 1.456 27.6% 65.8 4.03 12-4 173 326.75 12857 8902 5642 39.2 270 350 13.8 1.82 94.7 2556 1.516 27.6% 68.5 5.64 12-4 173 338.25 15747 11900 7543 52.4 361 339 13.3 1.76 97.9 2642 1.568 27.6% 70.8 7.54 12-4 173 346.5 19100 14717 9328 64.8 447 331 13.0 1.72 100.3 2708 1.607 27.6% 72.6 9.33 12-4 173 350.25 19942 27.6% 12-5 108 338.5 3116 1997 1266 8.8 61 339 13.3 1.76 61.0 1648 0.978 40.4% 36.4 1.27 58.7 0.186 0.997 35.0 12-5 108 379.5 6504 3944 2500 17.4 120 298 11.7 1.55 69.4 1875 1.112 40.4% 41.4 2.50 12-5 108 399.8 9169 5403 3425 23.8 164 277 10.9 1.44 74.5 2012 1.194 40.4% 44.4 3.42 12-5 108 418.5 12915 8012 5078 35.3 243 259 10.2 1.35 79.9 2158 1.280 40.4% 47.6 5.08 12-5 108 430.5 15701 10921 6922 48.1 331 247 9.7 1.28 83.8 2262 1.342 40.4% 50.0 6.92 12-5 108 439.5 18874 13585 8611 59.8 412 238 9.4 1.24 87.0 2348 1.393 40.4% 51.9 8.61 12-5 108 444.5 20221 40.4% 12-6 129 267.75 3287 0 0 0.0 0 409 16.1 2.13 60.6 1636 0.970 37.4% 37.9 12-6 129 319 6372 3806 2412 16.8 116 358 14.1 1.86 69.3 1870 1.109 37.4% 43.4 2.41 58.9 0.186 0.997 36.9 12-6 129 341.25 9402 5340 3385 23.5 162 336 13.2 1.75 73.8 1994 1.183 37.4% 46.2 3.38 12-6 129 361.5 12963 7096 4498 31.2 215 316 12.4 1.64 78.6 2122 1.259 37.4% 49.2 4.50 12-6 129 375.75 15742 9690 6142 42.7 294 301 11.9 1.57 82.3 2222 1.318 37.4% 51.5 6.14 12-6 129 389 18696 12196 7730 53.7 370 288 11.3 1.50 86.1 2324 1.379 37.4% 53.9 7.73 12-6 129 397.5 20410 37.4% 13-2 64 416.3 3610 2348 1488 10.3 71 261 10.3 1.36 47.2 1273 0.755 33.7% 31.3 1.49 44.1 0.190 0.986 29.3 13-2 64 447.0 6363 4580 2903 20.2 139 230 9.1 1.20 53.5 1444 0.856 33.7% 35.5 2.90 13-2 64 466.3 9424 5866 3718 25.8 178 211 8.3 1.10 58.3 1575 0.935 33.7% 38.7 3.72 13-2 64 480.8 12832 9814 6220 43.2 298 196 7.7 1.02 62.6 1691 1.004 33.7% 41.5 6.22 13-2 64 486.3 15967 12122 7683 53.4 368 191 7.5 0.99 64.5 1740 1.032 33.7% 42.7 7.68 13-2 64 494.0 18935 14948 9474 65.8 454 183 7.2 0.95 67.2 1814 1.076 33.7% 44.5 9.47 13-2 64 497.0 20178 33.7%

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143Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 13-3 53 388.75 3313 24.1% 13-3 53 427.5 6399 4223 2677 18.6 128 250 9.8 1.30 40.8 1102 0.654 24.1% 31.0 2.68 33.9 0.185 0.995 25.7 13-3 53 444.5 9511 6478 4106 28.5 197 233 9.2 1.21 43.8 1183 0.702 24.1% 33.3 4.11 13-3 53 458.25 12897 9081 5756 40.0 276 219 8.6 1.14 46.5 1257 0.746 24.1% 35.3 5.76 13-3 53 469 15838 11988 7598 52.8 364 208 8.2 1.08 49.0 1322 0.784 24.1% 37.2 7.60 13-3 53 480.25 19065 14978 9494 65.9 455 197 7.8 1.02 51.7 1397 0.829 24.1% 39.3 9.49 13-4 115 289.75 1725 31.8% 13-4 115 331 3185 2122 1345 9.3 64 346 13.6 1.80 63.9 1725 1.023 31.8% 43.5 1.34 61.5 0.154 0.997 41.9 13-4 115 369.5 6371 4114 2608 18.1 125 308 12.1 1.60 71.9 1940 1.151 31.8% 49.0 2.61 13-4 115 391.5 9712 6814 4319 30.0 207 286 11.2 1.49 77.4 2090 1.240 31.8% 52.8 4.32 13-4 115 403.5 12804 9269 5875 40.8 281 274 10.8 1.42 80.8 2182 1.294 31.8% 55.1 5.87 13-4 115 413.5 16024 11913 7551 52.4 362 264 10.4 1.37 83.9 2264 1.343 31.8% 57.2 7.55 13-4 115 423.25 19501 15761 9990 69.4 478 254 10.0 1.32 87.1 2351 1.395 31.8% 59.4 9.99 13-4 115 425.5 20580 31.8% 13-5 163 167.25 1591 39.0% 13-5 163 223 3177 1946 1233 8.6 59 454 17.9 2.36 68.8 1858 1.102 39.0% 42.0 1.23 66.7 0.144 1.000 40.7 13-5 163 263.5 6459 3772 2391 16.6 114 414 16.3 2.15 75.5 2039 1.210 39.0% 46.1 2.39 13-5 163 288.25 9566 5611 3556 24.7 170 389 15.3 2.02 80.3 2169 1.287 39.0% 49.0 3.56 13-5 163 306.5 12774 8139 5159 35.8 247 371 14.6 1.93 84.3 2276 1.350 39.0% 51.4 5.16 13-5 163 320.75 15850 10678 6768 47.0 324 356 14.0 1.85 87.7 2367 1.404 39.0% 53.5 6.77 13-5 163 335.75 20093 13982 8862 61.5 424 341 13.4 1.78 91.5 2471 1.466 39.0% 55.9 8.86

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144Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) 13-6 104 348.5 3582 37.4% 13-6 104 374 5009 3015 1911 13.3 92 303 11.9 1.58 65.6 1772 1.052 37.4% 41.1 1.91 57.4 0.193 0.99 2 35.9 13-6 104 386.75 6404 4125 2615 18.2 125 290 11.4 1.51 68.5 1850 1.098 37.4% 42.9 2.61 13-6 104 408.5 9694 6015 3812 26.5 183 269 10.6 1.40 74.1 2000 1.187 37.4% 46.4 3.81 13-6 104 424 12620 8062 5110 35.5 245 253 10.0 1.32 78.6 2122 1.259 37.4% 49.2 5.11 13-6 104 434.5 15772 10522 6669 46.3 319 243 9.6 1.26 82.0 2214 1.314 37.4% 51.4 6.67 13-6 104 445.75 18982 11955 7577 52.6 363 231 9.1 1.20 86.0 2322 1.377 37.4% 53.9 7.58 13-6 104 448.5 20032 37.4% Cmp 1 135 223 3220 1992 1263 8.8 60 454 17.9 2.36 57.2 1543 0.916 30.0% 40.0 1.26 55.3 0.158 0.996 38.7 Comp 1 135 269.25 6363 3915 2481 17.2 119 408 16.1 2.12 63.6 1718 1.019 30.0% 44.5 2.48 Cmp 1 135 300.5 9371 5846 3705 25.7 177 377 14.8 1.96 68.9 1861 1.104 30.0% 48.2 3.71 Cmp 1 135 316.5 12536 8387 5316 36.9 255 361 14.2 1.88 72.0 1943 1.153 30.0% 50.4 5.32 Cmp 1 135 330 15982 10737 6805 47.3 326 347 13.7 1.81 74.8 2019 1.198 30.0% 52.3 6.81 Cmp 1 135 340.5 19006 13400 8493 59.0 407 337 13.3 1.75 77.1 2082 1.235 30.0% 54.0 8.49 Cmp 1 135 347 20670 Crdb 39.8 333.5 1915 1214 8.4 58 344 13.5 1.79 22.3 601 0.357 5.0% 21.2 1.21 21.5 0.241 0.995 20.4 Crdb 39.8 397.75 4153 2632 18.3 126 279 11.0 1.45 27.4 739 0.439 5.0% 26.0 2.63 Crdb 39.8 421.75 6068 3846 26.7 184 255 10.1 1.33 30.0 809 0.480 5.0% 28.5 3.85 Crdb 39.8 437.25 7761 4919 34.2 236 240 9.4 1.25 31.9 861 0.511 5.0% 30.3 4.92 Crdb 39.8 454 10760 6820 47.4 327 223 8.8 1.16 34.3 926 0.549 5.0% 32.6 6.82 Crdb 39.8 462.5 13802 8748 60.8 419 215 8.5 1.12 35.6 962 0.571 5.0% 33.9 8.75 Crdb 39.8 468.5 20500

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145Table F-1—Continued Average Sample Wt. Deform. Force [lbs] Pre ssure Cyl. Length Vol. Density MC dry/1000Regression analysis [lbs] [mm] Initial Final [psf] [psi] [kPa] (mm) (in) (ft3) (lb/ft3) (lb/yd3) Mg/m3 [%] (lb/ft3) [kpsf] 1000 (bulk)C R2 1000 (dry) Soil 224 284.0 1604 Soil 224 307.5 3399 2332 1478 10.3 71 370 14.6 1.92 116.5 3146 1.866 10.0% 104.9 1.48 113. 8 0.066 0.995 102.4 Soil 224 324.8 6315 4602 2917 20.3 140 352 13.9 1.83 122.2 3300 1.958 10.0% 110.0 2.92 Soil 224 335.8 9414 7247 4593 31.9 220 341 13.4 1.78 126.2 3406 2.021 10.0% 113.5 4.59 Soil 224 342.5 12801 10405 6595 45.8 316 335 13.2 1.74 128.7 3475 2.062 10.0% 115.8 6.59 Soil 224 347.0 15832 11717 7427 51.6 356 330 13.0 1.72 130.5 3522 2.090 10.0% 117.4 7.43 Soil 224 351.8 19323 16874 1069 5 74.3 512 325 12.8 1.69 132.4 3574 2.120 10.0% 119.1 10.70 Soil 224 353.0 21000 Cmp 2 78.8 216.25 509 323 2.2 15 461 18.1 2.40 32.9 888 0.527 10.0% 29.6 0.32 38.1 0.158 0.989 34.3 Cmp 2 78.8 243.25 919 582 4.0 28 434 17.1 2.26 34.9 943 0.559 10.0% 31.4 0.58 Cmp 2 78.8 287.75 2143 1358 9.4 65 389 15.3 2.03 38.9 1051 0.623 10.0% 35.0 1.36 Cmp 2 78.8 328 4268 2705 18.8 130 349 13.7 1.82 43.4 1172 0.695 10.0% 39.1 2.71 Cmp 2 78.8 349.25 5746 3642 25.3 174 328 12.9 1.71 46.2 1248 0.740 10.0% 41.6 3.64 Cmp 2 78.8 369 8018 5082 35.3 243 308 12.1 1.60 49.2 1328 0.788 10.0% 44.3 5.08 Cmp 2 78.8 385 10554 6689 46.5 320 292 11.5 1.52 51.9 1400 0.831 10.0% 46.7 6.69 Cmp 2 78.8 396.5 12978 8226 57.1 394 281 11.1 1.46 54.0 1458 0.865 10.0% 48.6 8.23 Cmp 2 78.8 402.5 14708 9322 64.7 446 275 10.8 1.43 55.2 1489 0.884 10.0% 49.6 9.32 Cmp1 – Fresh, 3 week old compost Cmp2 – Degraded, mature 6 month old compost Crdb Cardboard

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APPENDIX G STATISTICAL ANALYSIS OF LEVEL OF DEGRADATION AND SOIL CONTENT RELATED TO OTHER WASTE PROPERTIES

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147Table G-1: Summary of Waste Property Data for Less-Degraded Samples (BMP > 0.90 L CH4/g VS) Sample Avg. Depth Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices [ft] bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C 2-2 7.5 38.9 24.3 37.63% 47.4% 36.2% 29.6% 0.0955 46.79 29.181 0.20 6-2 7.5 52.5 29.7 43.40% 22.4% 15.4% 53.5% 0.1808 42.74 24.188 0.20 6-3 12.5 54.5 39.5 27.49% 31.7% 19.8% 30.6% 0.1409 25.76 18.676 0.21 7-2 7.5 44.3 33.6 24.28% 35.2% 20.9% 41.0% 0.1933 39.11 29.61 0.20 7-3 12.5 59.0 40.0 32.12% 30.1% 20.5% 49.5% 0.2002 38.59 26.198 0.20 12-2 7.5 44.6 31.5 29.43% 32.6% 26.1% 29.9% 0.2282 39.11 27.597 0.22 13-3 12.5 55.4 42.1 24.06% 30.4% 26.4% 46.0% 0.2553 33.86 25.713 0.18 Table G-2: Summary of Waste Property Data for Degr aded Samples (BMP < 0.90 L CH4/g VS) Sample Avg. Depth Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices [ft] bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C 2-4 17.5 92.1 60.0 34.84% 40.0% 29.6% 23.0% 0.0144 46.70 30.430 0.21 2-5 22.5 88.2 57.5 34.82% 57.1% 45.5% 22.9% 0.0150 60.47 39.417 0.17 2-6 27.5 73.7 50.2 31.93% 27.3% 17.0% 25.7% 0.0105 51.82 35.257 0.21 6-4 17.5 44.9 32.9 26.74% 72.9% 63.9% 14.6% 0.0349 56.51 41.397 0.16 6-6 27.5 60.6 34.7 42.80% 65.5% 60.3% 6.0% 0.0151 44.74 25.589 0.18 7-4 17.5 64.4 39.9 38.10% 68.6% 59.0% 18.1% 0.0876 60.75 37.602 0.16 7-5 22.5 49.9 29.0 41.80% 55.7% 45.6% 25.7% 0.0917 50.46 29.366 0.15 12-5 22.5 74.6 44.5 40.38% 24.8% 16.1% 14.5% 0.0502 58.71 35.003 0.19 12-6 27.5 97.2 60.9 37.37% 25.1% 19.6% 16.7% 0.0225 58.94 36.913 0.19

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148Table G-3: Statistical T-test Comparis on between Less-Degraded and Degraded Sample Sets (95% Confidence Interval) Sample Set Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C Less degraded Average 49.9 34.4 31.2% 32.8% 23.6% 40.0% 0.185 38.0 25.9 0.20 Variance 53.3 41.6 0.5% 0.6% 0.5% 1.0% 0.003 44.9 13.8 0.000 Std Dev 7.3 6.5 7.2% 7.6% 6.7% 10.1% 0.053 6.7 3.7 0.012 Degraded Average 70.0 44.3 36.8% 50.6% 39.6% 18.6% 0.038 54.9 34.8 0.18 Variance 330.9 146.9 0.2% 3.8% 3.8% 0.4% 0.001 36.3 23.9 0.000 Std Dev 18.2 12.1 4.9% 19.5% 19.5% 6.5% 0.032 6.0 4.9 0.022 % Difference 29% 22% 15% 35% 40% 115% 3.87 31% 26% 13% TTEST Statistic1 0.0078 0.0464 0.1045 0.0220 0.0435 0.0007 0.0001 0.0002 0.0007 0.0140 Probability2 99.22% 95.36% 89.55% 97.80% 95.7% 99.93% 99.99% 99.98% 99.93% 98.6% 1 Type3 T-test with 2 tails performed using Microsoft Excel 2 Probabilities greater than 95% confid ence are statistically different.

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149Table G-4: Summary of Waste Property Data for Low Soil Cont ent Samples (Soils Content < 30%) Sample Avg. Depth Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices [ft] bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C 2-6 27.5 73.7 50.2 31.93% 27.3% 17.0% 25.7% 0.0105 51.82 35.257 0.21 6-2 7.5 52.5 29.7 43.40% 22.4% 15.4% 53.5% 0.1808 42.74 24.188 0.20 6-3 12.5 54.5 39.5 27.49% 31.7% 19.8% 30.6% 0.1409 25.76 18.676 0.21 7-2 7.5 44.3 33.6 24.28% 35.2% 20.9% 41.0% 0.1933 39.11 29.61 0.20 7-3 12.5 59.0 40.0 32.12% 30.1% 20.5% 49.5% 0.2002 38.59 26.198 0.20 12-2 7.5 44.6 31.5 29.43% 32.6% 26.1% 29.9% 0.2282 39.11 27.597 0.22 12-5 22.5 74.6 44.5 40.38% 24.8% 16.1% 14.5% 0.0502 58.71 35.003 0.19 12-6 27.5 97.2 60.9 37.37% 25.1% 19.6% 16.7% 0.0225 58.94 36.913 0.19 13-3 12.5 55.4 42.1 24.06% 30.4% 26.4% 46.0% 0.2553 33.86 25.713 0.18 Table G-5: Summary of Waste Property Data for High Soil Cont ent Samples (Soils Content > 30%) Sample Avg. Depth Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices [ft] bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C 2-2 7.5 38.9 24.3 37.63%47.4% 36.2% 29.6% 0.0955 46.79 29.181 0.20 2-4 17.5 92.1 60.0 34.84%40.0% 29.6% 23.0% 0.0144 46.70 30.43 0.21 2-5 22.5 88.2 57.5 34.82%57.1% 45.5% 22.9% 0.0150 60.47 39.417 0.17 6-4 17.5 44.9 32.9 26.74%72.9% 63.9% 14.6% 0.0349 56.51 41.397 0.16 6-6 27.5 60.6 34.7 42.80%65.5% 60.3% 6.0% 0.0151 44.74 25.589 0.18 7-4 17.5 64.4 39.9 38.10%68.6% 59.0% 18.1% 0.0876 60.75 37.602 0.16 7-5 22.5 49.9 29.0 41.80%55.7% 45.6% 25.7% 0.0917 50.46 29.366 0.15

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150Table G-6: Statistical T-test Compar ison between High and Low Soils Content Sa mple Sets (95% Confidence Interval) Sample Set Specific Weight Moisture Content Fines Content Soils Content Volatile Solids BMP Compression Indices bulk [pcf]dry [pcf][%] [%] [%] [%] [L CH4/g VS] 1000 (bulk) 1000 (dry) C Low Soil Average 61.8 41.3 32.3% 28.8% 20.2% 34.1% 0.142 43.2 28.8 0.20 Variance 293.5 95.9 0.5% 0.2% 0.2% 2.0% 0.008 126.1 36.0 0.000 Std Dev 17.1 9.8 6.9% 4.2% 3.9% 14.1% 0.092 11.2 6.0 0.013 High Soil Average 63.0 41.2 34.8% 65.1% 48.6% 20.0% 0.051 58.6 39.0 0.16 Variance 303.5 155.0 0.4% 2.4% 1.7% 0.6% 0.002 159.5 153.2 0.001 Std Dev 17.4 12.5 6.3% 15.5% 13.0% 7.9% 0.039 12.6 12.4 0.030 % Difference 2% 0% 7% 56% 58% 71% 1.82 26% 26% 22% TTEST Statistic1 0.8821 0.9748 0.4132 0.00003 0.0009 0.0244 0.0203 0.0121 0.0369 0.0044 Probability2 11.79% 2.52% 58.68% 99.997% 99.91% 97.56% 97.97% 98.79% 96.31% 99.6% 1 Type3 T-test with 2 tails performed using Microsoft Excel 2 Probabilities greater than 95% confid ence are statistically different. Excel T-test Function for Statistical difference =TTEST(array1, array2, tails, type) Returns the probability associated with a Student's t-Test tails: specifies the number of distribution tails. If tails = 1, TTEST uses the one-tailed distribution. If tails = 2, TTEST uses the two tailed distribution. type: 1 Paired 2 Two-sample equal variance (homoscedastic) 3 Two-sample unequal variance (heteroscedastic) TTEST uses the data in array1 and array2 to compute a non-negative t-statistic. If tails=1, TTEST returns the probability of a higher value of the t-statistic under the assumption that array1 and array2 are samples from populations with the same mean. The value returned by TTEST when tails=2 is double that returned when tails=1 and corresponds to the pr obability of a higher absolute value of the t-statistic under the “same population means” assumption.

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APPENDIX H SUMMARY OF WASTE DATA

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152Table H-1: Comple te Summary of Wa ste Property Data Sample Depth Specific Weight MC Waste Compos ition [%] Fines Soil VS BMP Compression Indexes Up [ft] Lo [ft] Avg [ft] bulk [pcf] dry [pcf] bulk [pcy] [%] Paper Plastic Yard Waste Textile Stone/ Metal Glass/ Ceramic Fines Retained Fines: Passing [%] [%] [%] [L CH4/ g VS] 1000 ( bulk) 1000 ( dry) C 2-1 0 5 2.5 95.9 2589 No Sample Taken 2-2 5 10 7.5 38.9 24.3 1051 37.63% 18.8% 9.3% 3.0% 3.9% 14.6% 2.9% 37.8% 9.6% 47.4% 36.2% 29.6% 0.0955 46.79 29.181 0.20 2-3 10 15 12.5 62.9 47.1 1697 25.05% 1.5% 1.0% 2.2% 0.2% 10.0% 0.1% 68.0% 16.9% 85.0% ?? 81.87 64.364 2-4 15 20 17.5 92.1 60.0 2486 34.84% 13.5% 6.9% 12.4% 15.0% 7.0% 5.1% 32.0% 8.0% 40.0% 29.6% 23.0% 0.0144 46.70 30.43 0.21 2-5 20 25 22.5 88.2 57.5 2380 34.82% 12.9% 8.3% 6.1% 5.5% 7.5% 2.8% 42.4% 14.7% 57.1% 45.5% 22.9% 0.0150 60.47 39.417 0.17 2-6 25 30 27.5 73.7 50.2 1990 31.93% 16.9% 10.7% 23.6% 5.8% 8.7% 7.1% 25.0% 2.3% 27.3% 17.0% 25.7% 0.0105 51.82 35.257 0.21 6-1 0 5 2.5 77.1 2082 No Sample Taken 113.82 102.44 0.07 6-2 5 10 7.5 52.5 29.7 1419 43.40% 47.7% 11.1% 9.7% 0.5% 5.8% 2.8% 13.0% 9.4% 22.4% 15.4% 53.5% 0.1808 42.74 24.188 0.20 6-3 10 15 12.5 54.5 39.5 1471 27.49% 19.4% 6.3% 31.8% 4.7% 4.2% 2.0% 17.0% 14.7% 31.7% 19.8% 30.6% 0.1409 25.76 18.676 0.21 6-4 15 20 17.5 44.9 32.9 1212 26.74% 7.1% 6.6% 6.2% 3.2% 1.8% 2.1% 50.9% 22.0% 72.9% 63.9% 14.6% 0.0349 56.51 41.397 0.16 6-5 20 25 22.5 54.8 33.5 1479 38.87% 9.6% 5.2% 4.4% 1.2% 9.9% 0.7% 50.5% 18.6% 69.1% ?? 60.26 36.837 0.17 6-6 25 30 27.5 60.6 34.7 1636 42.80% 1.8% 5.7% 11.2% 3.5% 10.0% 2.4% 36.5% 28.9% 65.5% 60.3% 6.0% 0.0151 44.74 25.589 0.18 7-1 0 5 2.5 63.5 1714 No Sample Taken 7-2 5 10 7.5 44.3 33.6 1197 24.28% 27.8% 9.4% 12.9% 3.8% 8.2% 2.7% 24.0% 11.2% 35.2% 20.9% 41.0% 0.1933 39.11 29.61 0.20 7-3 10 15 12.5 59.0 40.0 1593 32.12% 40.3% 3.0% 18.0% 4.2% 1.8% 2.6% 19.1% 10.9% 30.1% 20.5% 49.5% 0.2002 38.59 26.198 0.20 7-4 15 20 17.5 64.4 39.9 1739 38.10% 8.3% 5.7% 13.6% 0.4% 2.3% 1.0% 55.0% 13.6% 68.6% 59.0% 18.1% 0.0876 60.75 37.602 0.16 7-5 20 25 22.5 49.9 29.0 1347 41.80% 16.4% 5.9% 15.5% 1.7% 3.7% 1.1% 30.0% 25.7% 55.7% 45.6% 25.7% 0.0917 50.46 29.366 0.15 7-6 25 30 27.5 64.7 1747 No Sample Taken 12-1 0 5 2.5 116.2 3137 No Sample Taken 12-2 5 10 7.5 44.6 31.5 1205 29.43% 26.3% 16.5% 9.3% 3.5% 10.2% 1.6% 16.7% 16.0% 32.6% 26.1% 29.9% 0.2282 39.11 27.597 0.22 12-3 10 15 12.5 41.0 29.6 1107 27.89% 34.11 24.866 0.19 12-4 15 20 17.5 73.0 52.8 1971 27.62% 6.4% 1.2% 2.2% 0.0% 0.7% 0.0% 70.0% 19.5% 89.5% 77.01 55.743 0.12 12-5 20 25 22.5 74.6 44.5 2014 40.38% 6.1% 7.4% 24.7% 26.7% 7.2% 3.2% 20.3% 4.4% 24.8% 16.1% 14.5% 0.0502 58.71 35.003 0.19 12-6 25 30 27.5 97.2 60.9 2625 37.37% 18.2% 14.0% 15.9% 9.8% 14.2% 2.8% 16.3% 8.8% 25.1% 19.6% 16.7% 0.0225 58.94 36.913 0.19 13-1 0 5 2.5 97.3 2628 No Sample Taken 13-2 5 10 7.5 54.0 35.8 1459 33.68% Sample Unavailable 44.11 29.25 0.19 13-3 10 15 12.5 55.4 42.1 1496 24.06% 43.4% 2.1% 11.3% 0.4% 9.6% 2.8% 10.4% 20.0% 30.4% 26.4% 46.0% 0.2553 33.86 25.713 0.18 13-4 15 20 17.5 61.1 40.8 1651 33.23% Sample Unavailable 61.519 41.937 0.1535 13-5 20 25 22.5 83.6 51.0 2257 38.96% Sample Unavailable 66.732 40.728 0.1438 13-6 25 30 27.5 81.4 51.0 2199 37.37% Sample Unavailable 57.383 35.939 0.1933 Cardboard 34.4% 0.1023 21.496 20.422 0.2414 Compost 1 24.06% 0.0105 55.294 38.706 0.1579 Compost 2 43.40% 0.2553 38.122 34.31 0.1577

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APPENDIX I LOGNORMALITY OF CONE PENETRATION DATA

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154 Percent 600 400 200 0 99.9 99 95 90 80 70 60 50 40 30 20 10 5 1 0.1 2.5 2.0 1.5 1.0 0.5 QT Log(QT) QT P-Value<0.005 Log(QT) Mean1.612 StDev0.3368 N399 AD Mean 1.556 P-Value<0.005 55.98 StDev58.49 N399 AD35.281CPT-1 (Depth 3-13.7 feet) Figure I-1: Normality – Lognormality Test fo r Tip Resistance for CPT-1 (3-13.7 feet) Percent 120 90 60 30 0 99.9 99 95 90 80 70 60 50 40 30 20 10 5 1 0.1 2 1 0 -1 FR Log(FR) FR P-Value<0.005 Log(FR) Mean0.5072 StDev0.3692 N399 AD Mean 9.908 P-Value<0.005 4.627 StDev7.304 N399 AD63.179CPT-1 (Depth 3-13.7 feet) Figure I-2: Normality – Lognormality Test for Friction Ratio for CPT 1, (3 to 13.7 feet)

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155 Percent 300 200 100 0 -100 99.99 99 95 80 50 20 5 1 0.01 3 2 1 0 QT log(QT) QT P-Value<0.005 log(QT) Mean1.597 StDev0.3430 N986 AD Mean 2.429 P-Value<0.005 52.41 StDev39.96 N986 AD33.594CPT-3 (Depth 3-30 feet) Figure I-3: Normality – Lognormality Test for Tip Resistance for CPT-3 (3-30 feet) Percent 120 90 60 30 0 99.9 99 95 90 80 70 60 50 40 30 20 10 5 1 0.1 2 1 0 -1 FR Log(FR) FR P-Value<0.005 Log(FR) Mean0.5072 StDev0.3692 N399 AD Mean 9.908 P-Value<0.005 4.627 StDev7.304 N399 AD63.179CPT-3 (Depth 3-30 feet) Figure I-4: Normality – Lognormality Test for Friction Ratio for CPT-3 (3-30 feet)

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156 Percent 200 100 0 -100 99.99 99 95 80 50 20 5 1 0.01 2.5 2.0 1.5 1.0 0.5 99.99 99 95 80 50 20 5 1 0.01 QT log(QT) QT P-Value<0.005 log(QT) Mean1.548 StDev0.3062 N997 AD Mean 5.819 P-Value<0.005 44.77 StDev33.94 N997 AD59.387 C PT-6 (Depth 3-30 feet) Figure I-5: Normality – Lognormality Test fo r Tip Resistance for CPT-6 (3 to 30 feet) Percent 120 80 40 0 99.99 99 95 80 50 20 5 1 0.01 1.0 0.5 0.0 -0.5 -1.0 FS log(FS) FS P-Value<0.005 log(FS) Mean0.09320 StDev0.3175 N1967 AD Mean 18.451 P-Value<0.005 5.149 StDev8.271 N997 AD156.091CPT-6 Depth 3-30 feet Figure I-6: Normality – Lognormality Test for Sleeve Friction for CPT-6 (3-30 feet)

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157 Percent 120 80 40 0 99.99 99 95 80 50 20 5 1 0.01 2 1 0 -1 99.99 99 95 80 50 20 5 1 0.01 FR log(FR) FR P-Value<0.005 log(FR) Mean0.5501 StDev0.3452 N997 AD Mean 4.998 P-Value<0.005 5.149 StDev8.271 N997 AD156.091CPT-6 Depth 3-30 feet Figure I-7: Normality – Lognormality Test fo r Friction Ratio for CPT-6 (3 to 30 feet) Percent 0.4 0.2 0.0 -0.2 99.99 99 95 80 50 20 5 1 0.01 0 -1 -2 -3 U log(U) U P-Value<0.005 log(U) Mean-1.225 StDev0.3877 N927 AD Mean 4.369 P-Value<0.005 0.07755 StDev0.07329 N997 AD44.839CPT 6 Depth 3-30 feet Figure I-8: Normality – Lognormality Test for Pore Pressure for CPT-6 (3-30 feet)

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158 Percent 300 200 100 0 -100 99.99 99 95 80 50 20 5 1 0.01 2.5 2.0 1.5 1.0 0.5 qt (tsf) LOG(qt) qt (tsf) P-Value<0.005 LOG(qt) Mean1.563 StDev0.3169 N973 AD Mean 1.438 P-Value<0.005 47.17 StDev35.94 N973 AD36.085 Figure I-9: Normality–Lognormality Test for Ti p Resistance for CPT 12, (10 to 15 feet)

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APPENDIX J CONE PENETRATION TEST DATA PLOTS

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APPENDIX K CONE PENETRATION SUMMARY DATA AND STATISTICAL COMPARISON

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177Table K-1: CPT Summar y Statistics for Cover Soil Layers (0-3 feet) Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Modal Soil Depth [ft] Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Description Sample Low High QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] CPT-1 0.0 3.0 42.0 38.9 15.8 0.62 0.57 0.23 1.58 1.45 0.71 0.1 0.1 0.1 Sand to Sandy silt CPT-2 0.0 3.0 48.8 42.8 25.2 0.33 0.28 0.15 0.73 0.66 0.35 0.4 0.4 0.2 Sand to Silty Sand CPT-3 0.0 3.0 29.4 27.9 9.5 0.53 0.44 0.26 1.80 1.59 0.93 0.1 0.0 0.0 Sand to Sandy silt CPT-4 0.0 3.0 32.5 30.6 10.1 0.93 0.45 0.84 2.84 1.45 2.59 0.4 0.4 0.1 Clay CPT-5 0.0 3.0 42.2 37.7 18.6 0.42 0.31 0.25 1.11 0.81 1.02 0.0 0.0 0.0 Sand to Silty Sand CPT-6 0.0 3.0 44.2 39.2 20.4 0.67 0.52 0.50 1.43 1.32 0.56 0.1 0.1 0.0 Sand to Sandy silt CPT-7 0.0 3.0 44.4 38.9 21.2 0.44 0.28 0.31 0.96 0.73 0.62 0.1 0.0 0.0 Sand to Silty Sand CPT-8 0.0 3.0 28.2 26.9 9.2 0.43 0.37 0.17 1.59 1.37 0.70 0.4 0.4 0.2 Sand to Sandy silt CPT-9 0.0 3.0 39.9 27.4 58.8 0.32 0.25 0.18 1.40 1.07 0.88 0.1 0.0 0.1 Silty sand to Sandy silt CPT-10 0.0 3.0 20.4 19.1 7.2 0.35 0.27 0.19 1.85 1.39 0.96 0.0 0.0 0.0 Sand to Sandy silt CPT-11 0.0 3.0 13.6 8.9 10.7 0.28 0.21 0.21 2.66 2.36 1.22 0.2 0.0 0.3 Clay CPT-12 0.0 3.0 36.4 29.4 21.0 1.08 0.88 0.56 5.37 3.00 8.97 0.5 0.3 0.4 Sand to Sandy silt CPT-13 0.0 3.0 36.4 29.4 21.0 1.08 0.88 0.56 5.37 3.00 8.97 0.5 0.3 0.4 Sand to Sandy silt CPT-14 0.0 3.0 29.7 28.1 8.9 0.34 0.24 0.21 1.01 0.80 0.53 0.3 0.3 0.1 Sand to Sandy silt CPT-15 0.0 3.0 71.2 40.9 69.8 0.83 0.34 1.08 2.89 1.36 3.40 0.1 0.0 0.1 Sand to Sandy silt CPT-19 0.0 3.0 95.3 81.9 40.6 -* 0.14 0.58 -* 0.21 0.42 0.2 0.2 0.0 Sand

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178Table K-2: CPT Summ ary Statistics for Waste Layers (3-30 feet) Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Modal Soil Depth [ft] Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Description Sample Low High QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] CPT-1 3.0 13.6 56.0 40.9 58.5 1.53 1.31 0.81 4.63 3.21 7.30 0.34 0.26 0.28 Clay CPT-2 3.0 14.1 42.0 28.0 39.5 0.98 0.84 0.56 5.22 3.02 6.63 0.13 0.10 0.08 Clay CPT-3 3.0 30.0 52.4 39.5 40.0 1.37 1.17 0.79 4.23 2.96 4.22 1.56 0.90 1.78 Clay CPT-4 3.0 30.0 54.7 36.9 70.8 2.73 1.68 3.52 5.42 4.54 3.41 0.18 0.13 0.17 Clay CPT-5 3.0 12.8 75.9 53.4 71.8 1.18 0.80 0.98 2.74 1.60 3.39 0.20 0.15 0.17 Sand to Sandy silt CPT-6 3.0 30.0 44.8 35.3 33.9 1.62 1.25 1.26 5.15 3.55 8.27 0.08 0.06 0.07 Clay CPT-7 3.0 30.0 45.6 33.4 32.7 1.48 1.22 0.91 -* -* -* 0.10 0.07 0.10 Clay CPT-8 3.0 29.9 60.2 45.4 53.5 1.88 1.45 1.47 5.02 3.11 -* 0.34 0.16 0.39 Clay CPT-9 3.0 29.3 66.2 53.1 48.4 1.63 1.35 0.97 3.92 2.61 7.03 0.15 0.08 0.14 Sand to Sandy silt CPT-10 3.0 30.0 58.3 45.2 43.2 1.28 1.01 0.83 3.23 2.26 3.11 0.11 0.10 0.04 Silty sand to Sandy silt CPT-11 3.0 27.7 65.1 44.0 67.6 1.44 1.14 0.94 4.03 2.68 3.72 0.35 0.27 0.27 Clay CPT-12 3.0 30.0 47.2 36.6 35.9 1.16 1.01 0.61 3.69 2.77 2.70 0.30 0.25 0.22 Clay CPT-13 3.0 24.5 117.5 77.5 105.8 1.24 0.94 0.97 1.97 1.22 2.45 0.19 0.17 0.07 Gravelly sand to Sand CPT-14 3.0 30.0 62.8 51.8 45.4 1.25 1.06 0.85 2.57 2.05 1.66 0.77 0.71 0.27 Sand to Silty Sand CPT-15 3.0 30.0 60.4 48.3 45.5 0.47 0.26 0.47 1.39 0.72 1.61 0.43 0.23 0.56 Sand to Silty Sand CPT-19 3.0 30.0 82.2 69.5 49.7 -* -* -* -* -* -* 0.30 0.29 0.06 Very stiff fine-grained

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179Table K-3: CPT Summar y Statistics for Subgrade Soil Layers (30-54 feet) Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Modal Soil Depth [ft] Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Description Sample Low High QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] CPT-3 30.0 32.3 89.7 73.3 69.7 1.58 1.36 0.77 2.23 1.85 1.29 5.10 4.29 4.26 Sand to Sandy silt CPT-4 30.0 53.2 53.9 44.0 35.5 2.85 2.17 2.00 5.50 4.93 2.85 2.38 1.70 1.48 Very stiff fine grained CPT-6 30.0 48.5 55.2 42.8 47.7 2.96 2.27 2.16 5.53 5.30 1.65 0.75 0.47 0.64 Clay CPT-7 30.0 53.8 77.1 50.7 71.3 3.10 2.35 2.46 5.45 4.63 3.06 0.96 0.94 0.23 Clay CPT-10 30.0 51.7 50.2 36.8 38.1 2.44 1.71 2.02 7.18 4.67 23.76 0.22 0.17 0.15 Clay CPT-12 30.0 53.2 61.1 44.3 45.6 2.21 1.60 1.84 3.75 3.48 1.49 7.78 2.00 10.94 Clayey silt to Silty clay CPT-14 30.0 43.3 292.7 233.5 129.9 1.31 -* 0.80 1.44 0.41 7.79 0.55 0.54 0.10 Gravelly sand to Sand CPT-15 30.0 33.5 104.2 91.1 52.6 1.22 0.87 0.74 1.73 1.08 1.52 0.89 0.88 0.14 Sand CPT-19 30.0 46.0 74.7 59.4 54.9 0.75 0.50 0.81 1.27 0.87 1.60 0.41 0.41 0.04 Sand to Silty Sand

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180Table K-4: Statistical Analysis for Difference of Population Means CP T Data between Known Waste Layers Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Sample QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] 0-3 Avg: 40.9 34.2 23.0 0.51 0.40 0.39 2.17 1.41 2.05 0.22 0.16 0.12 St. Dev. 19.4 15.4 18.3 0.38 0.22 0.27 1.46 0.79 2.82 0.18 0.14 0.12 3-30 Avg: 61.96 46.18 52.65 1.42 1.10 1.06 3.80 2.59 4.27 0.35 0.25 0.29 St. Dev. 18.4 13.0 18.9 0.49 0.33 0.72 1.27 0.98 2.26 0.37 0.23 0.42 30-55 Avg: 95.42 75.10 60.60 2.05 1.60 1.51 3.79 3.02 5.00 2.11 1.27 2.00 St. Dev. 76.1 61.9 28.8 0.86 0.67 0.71 2.20 1.97 7.32 2.62 1.29 3.62 TTEST: 0-3 and Waste 0.00375 0.0 2488 9.19E-05 4. 515E-06 3.58E-07 0.0 0341 0.00344 0.001 36 0.02619 0.23564 0.223931 0.14432 99.63% 97.5% 99.99% 99.94% 100.00 99.66% 99.98 99.86% 97.38% 76.44% 77.61% 85.57% TTEST: Waste and 30-55 0.2284 0.20158 0.471 0. 067 0.076716 0.15761 0. 98641 0.55405 0.77813 0. 07777 0.045065 0.19586 77.16% 79.84% 52.81% 93.20% 92.33% 84.24% 1.36% 44.60% 22.19% 92.22% 95.49% 80.41% TTEST: 0-3 and 30-55 0.0655 0. 08494 0.00422 0.00 0 0.001242 0.00129 0.0 7364 0.04147 0.27436 0.0 6187 0.032774 0.15901 93.45% 91.51% 99.58% 99.95% 99.88% 99.87% 92.64% 95.85% 72.56% 93.81% 96.72% 84.10%

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181Table K-5: CPT Summ ary Statistics for Waste Sampling Layers (5 foot intervals) Tip Resistance, QT Sleeve Friction, FS Friction Ratio, FR Pore Pressure, U Modal Soil Depth [ft] Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Avg. Geo. Mean Std. Dev. Description Sample Low High QT [tsf] QT [tsf] QT [tsf] FS [tsf] FS [tsf] FS [tsf] FR [%] FR [%] FR [%] U [tsf] U [tsf] U [tsf] 2-1 0 5 55.8 45.2 40.5 0.61 0.46 0.44 1.75 1. 02 3.00 0.308 0.231 0.195 Sand to Silty Sand 2-2 5 10 31.7 20.3 30.2 1.15 0.94 0.71 7.70 4.65 8.65 0.115 0.086 0.073 Clay 2-3 10 14.1 42.8 31.5 35.7 0.74 0.68 0.28 3.07 2.16 2.16 0.138 0.126 0.046 Clay 6-1 0 5 44.1 34.9 29.9 1.28 0.79 1.57 6.39 2.26 17.17 0.072 0.055 0.049 Sand to Sandy silt 6-2 5 10 34.0 29.2 22.1 0.51 0.45 0.25 2.12 1.54 1.95 0.065 0.055 0.032 Sand to Sandy silt 6-3 10 15 67.4 52.8 48.9 2.12 1.83 1.35 4.13 3.48 2.93 0.140 0.103 0.098 Silty sand to Sandy silt 6-4 15 20 50.1 44.5 28.4 1.94 1.75 0.91 4.70 3.93 3.11 0.022 0.020 0.069 Clay 6-5 20 25 32.7 27.1 16.4 1.35 1.28 0.44 5.89 4.71 6.72 0.047 0.046 0.012 Clay 6-6 25 30 39.4 31.2 28.0 1.95 1.56 1.43 5.51 5.01 2.56 0.122 0.108 0.045 Clay 7-1 0 5 36.9 31.8 19.6 0.58 0.42 0.36 2.30 1. 32 3.46 0.063 0.043 0.056 Sand to Silty Sand 7-2 5 10 50.3 41.5 30.7 1.23 1.02 0.75 2.77 2.45 1.42 0.122 0.108 0.055 Sand to Sandy silt 7-3 10 15 62.8 56.8 28.2 1.85 1.68 0.72 3.46 2.96 2.08 0.145 0.124 0.085 Silty sand to Sandy silt 7-4 15 20 61.5 47.5 42.9 2.43 2.20 1.10 6.42 4.68 6.01 0.094 0.078 0.052 Clay 7-5 20 25 34.9 25.8 23.9 1.15 1.03 0.46 10.48 4.04 28.53 0.037 0.027 0.022 Clay 7-6 25 30 25.2 16.1 18.7 0.99 0.87 0.47 11.61 4.99 23.96 0.134 0.063 0.176 Clay 12-1 0 5 35.4 30.7 17.1 1.04 0.91 0.46 4.41 2.97 7.02 0.693 0.467 0.403 Silty sand to Sandy silt 12-2 5 10 65.1 52.4 50.8 1.66 1.57 0.55 3.77 3.01 2.45 0.226 0.204 0.155 Clay 12-3 10 15 55.8 42.1 36.4 1.12 0.96 0.76 3.33 2.28 2.76 0.202 0.173 0.101 Sand 12-4 15 20 49.6 40.0 32.5 1.13 1.02 0.47 3.41 2.56 2.37 0.176 0.156 0.066 Clay 12-5 20 25 30.1 23.1 23.4 0.98 0.89 0.48 4.96 3.86 3.79 0.311 0.308 0.050 Clay 12-6 25 30 39.9 33.1 24.9 0.96 0.78 0.59 3.21 2.36 1.94 0.320 0.315 0.055 Clayey silt to Silty clay 13-1 0 5 32.6 30.9 9.6 0.47 0.41 0.21 1.53 1.30 0.87 0.069 0.067 0.011 Sand to Sandy silt 13-2 5 10 44.8 38.5 26.7 0.69 0.62 0.29 2.07 1.61 1.56 0.136 0.131 0.037 Sand to Sandy silt 13-3 10 15 56.6 50.8 29.7 1.25 0.94 0.94 2.61 1. 85 2.24 0.280 0.273 0.058 Sand to Silty Sand 13-4 15 20 114.2 93.5 65.0 1.50 1.22 0.87 2.59 1.31 4.00 0.200 0.198 0.021 Sand 13-5 20 24.5 279.0 267.6 63.3 1.74 1.32 1.24 0.58 0.49 0.34 0.169 0.169 0.007 Gravelly sand to Sand Average 56.6 47.7 31.7 1.25 1.06 0.70 4.26 2.80 5.50 0.169 0.144 0.078 St. Dev 48.8 47.4 13.6 0.52 0.47 0.38 2.62 1.35 7.00 0.137 0.106 0.082

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182 APPENDIX L SETTLEMENT PREDICTION METHODOLOGY 1. Identify waste layers and properties and initial conditions: n = number of layers; Ho, i = initial height of each layer [ft]; o, i = initial specific weight [pcf]; i(v) = relationship of specific weight a nd vertical pressure for each layer: C = Compression Exponent [-] exponent of power law regression of settlement; qo, i = historic waste compression effort [psf]. 2. Calculate for each layer: v, o = existing overburden pressure acting at the midlevel of the waste layer; 1 , 1 1 , 1 , ,... 2o i o i i o i o vH H H v = overburden pressure due to extern al load at midlevel of each level; I qi o v, Where: I = influence v, 2 = total vertical stress from ex isting overburden and external load; v o v v , 2 , 3. Determine the relationship between historic waste compaction effort and total vertical stress and calculate density ratio:

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183 a. If v, 2 < qo, i, then 11 2 ; b. If v, 2 > qo, i, then C Vq 0 2 , 1 2 if v, o < qo, i, and C v V 0 , 2 , 1 2 if v, o >qo, i; 4. Calculate the change in height of each layer, Hi: i i i o iH H, 2 , 1 ,1 5. Sum the Hi for each layer to dete rmine total settlement

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184 APPENDIX M FINITE ELEMENT MODEL PARAMETERS AND CHANGE IN VERTICAL STRESS OUTPUT USING SIGMA/W This appendix explains the finite element modeling methodology using SIGMA/W from GeoSlope International (Calgary, Albe rta, Canada) that used to determine the vertical change in stress for various points under the conical te st load (CTL). Loads were modeled for each phase of CTL construction corresponding to each settlement measurement (Figures M-1 through M-3). This software provided the capability of creating an axis-symmetrical load (cone) to determine the vertical stress distribution below the surcharge. The vertical stress cha nges from the model were recorded at radii that corresponded to locations (radii) of settlement plates under the field CTL. The vertical stress change was recorded for node s at various depths below the surface (for each settlement plate radius) that corresponde d to midpoints of layers used in the settlement prediction methodology. The result of the finite element modeli ng are presented in Figures 4-5 through 4-7 with a contour plots of change in vertical e ffective stress. This appendix presents model input parameters, element meshes (Figures M1 to M-3), and tabulated results (Tables M2 to M-4).

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185 Table M-1: Finite Element Model Parameters Summarized Analysis Settings Type Analysis Settings Load/Deformation Control View Axisymmetrical Material Properties # Model Color E Modulus PoissonÂ’s Ratio Regions 1Linear-Elastic Yellow 4000 0 1, 2, 3, 4 2Linear-Elastic Green 4000 0 5 Region and Element Definitions Region DimensionsNo. of Elements Element Dimensions Secondary Nodes Hor. Vert. Hor. Vert. Hor. Vert. 1 110 30 110 60 1 0.5 2 90 30 9 60 10 0.5 3 110 30 110 3 1 10 4 90 30 9 3 10 10 5 (Ph I) 30 9 30 1 1 0-9 (Ph II) 60 19 60 3 1 0-6.3 (Ph-III) 90 29 90 6 1 0-4.8 Body Load Matl. # Vertical Horizontal Ko 10 0 0 2102.20 0 0 (Region 5 only)

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186 1 2 3 4 5 POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE I H = 9 FT R = 30 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load Phase 1.gsz Radius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 Figure M-1: Phase I CTL Finite Element Mesh Table Table M-2: Summar y of Change in Vertical Stress (v) [psf] for Phase I Settlement Plate and Corresponding Radius [ft] Depth Layer AR-1, AR-2, AR-3 UF-9 UF-2, UF-5 UF-4, UF-8 UF-3, UF-7 UF-1, UF-6 UF 10 to 13 UF-14, UF-15 0 10 30 40 54 70 90 102 0 494.1 429.6 4.6 0.0 0.0 0.0 0.0 0.0 1.5 1 648.0 549.8 26.5 0.3 0.0 0.0 0.0 0.0 4 2 608.6 520.8 52.7 2.4 0.3 0.0 0.0 0.0 7.5 3 549.3 475.1 76.9 9.5 1.2 0.0 0.0 0.0 12.5 4 467.0 408.3 96.9 23.4 3.9 0.0 0.0 0.0 17.5 5 393.8 347.7 106.6 36.7 8.0 0.0 0.0 0.0 22.5 6 332.4 296.8 110.2 47.1 12.6 0.0 0.0 0.0 27.5 7 282.6 255.4 110.3 54.5 17.1 0.0 0.0 0.0

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187 1 2 3 4 5 POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE II H = 19 FT R = 60 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load Phase 2.gsz Radius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 Figure M-2: Phase II CTL Finite Element Mesh Table M-3: Summar y of Change in Vertical Stress (v) [psf] for Phase II Settlement Plate and Corresponding Radius [ft] Depth Layer AR-1 UF-9 AR-2 AR-3 UF-2, UF-5 UF-4, UF-8 UF-3, UF-7 UF1, UF-6 UF 10 to 13 UF-14, UF-15 0 10 16 17 30 40 54 70 90 102 0 1353.4 1280.0 1175.0 1154.5 823.9 513.7 174.3 0.0 0.0 0.0 1.5 1 1445.9 1397.9 1304.5 1286.3 967.7 675.6 229.6 33.7 0.0 0.0 4 2 1419.8 1359.7 1273.1 1255.7 954.8 671.8 236.5 32.8 -0.1 -0.2 7.5 3 1360.0 1306.0 1226.4 1210.1 929.2 660.1 24.3 13.2 -0.1 -4.8 12.5 4 1227.6 1229.8 1158.0 1143.1 887.5 63.5 264.8 34.9 1.1 -1.0 17.5 5 1199.1 1155.9 1090.5 1076.9 843.3 613.1 280.2 58.4 3.8 -1.1 22.5 6 1125.6 1086.1 1026.2 1013.8 799.8 589.4 291.8 79.7 7.8 -0.6 27.5 7 1057.6 1021.3 966.3 954.9 758.7 567.1 299.5 97.5 12.6 0.6

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188 POLK COUNTY VERTICAL EXPANSION FEASIBILITY STUDY CONICAL TEST LOAD PHASE III H = 29 FT R = 90 FT SPEC. WEIGHT SOIL = 102.2 PCFPolk VE Conical Test Load 3.gszRadius [ft]0102030405060708090100110120130140150160170180190200 Elevation [ft]-60 -50 -40 -30 -20 -10 0 10 20 30 40 Figure M-3: Phase III CTL Finite Element Mesh Table M-4: Summar y of Change in Vertical Stress (v) [psf] for Phase III Settlement Plate and Corresponding Radius [ft] Depth Layer AR-1, AR-2, AR-3 UF-9 UF-2, UF-5 UF-4, UF-8 UF-3, UF-7 UF-1, UF-6 UF 10 to 13 UF14, UF15 0 10 30 40 54 70 90 102 0 494.1 429.6 4.6 0.0 0.0 0.0 0.0 0.0 1.5 1 648.0 549.8 26.5 0.3 0.0 0.0 0.0 0.0 4 2 608.6 520.8 52.7 2.4 0.3 0.0 0.0 0.0 7.5 3 549.3 475.1 76.9 9.5 1.2 0.0 0.0 0.0 12.5 4 467.0 408.3 96.9 23.4 3.9 0.0 0.0 0.0 17.5 5 393.8 347.7 106.6 36.7 8.0 0.0 0.0 0.0 22.5 6 332.4 296.8 110.2 47.1 12.6 0.0 0.0 0.0 27.5 7 282.6 255.4 110.3 54.5 17.1 0.0 0.0 0.0

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189 APPENDIX N CONICAL TEST LOAD SETTLEMENT MEASUREMENT Table N-1: Conical Test Load Settlement Data Total Settlement Additional Settlement Settlement Radius Phase I Phase II Phase III Phase III (4 months) Plate [ft] [ft] [ft] [ft] [ft] AR-1 16.3 0.29 0.90 1.83 0.56 AR-2 0.0 Center 0.39 1.20 2.22 0.61 AR-3 17.5 0.32 0.90 1.87 0.61 UF-1 69.4 0.27 0.16 UF-2 29.6 0.15 0.68 1.54 0.50 UF-3 53.6 0.08 0.75 0.29 UF-4 39.9 0.39 1.24 0.45 UF-5 30.1 0.20 0.82 1.86 0.66 UF-6 70.8 0.60 0.47 UF-7 53.8 0.15 0.98 0.44 UF-8 40.0 0.06 0.59 1.43 0.51 UF-9 10.1 0.28 0.98 1.98 0.53 UF-10 90.1 0.10 UF-11 90.1 UF-12 88.9 UF-13 89.3 0.19 UF-14 102.3 UF-15 102.4 UF-16 (Control) 159.2

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190 LIST OF REFERENCES American Society for Testing and Materials (A STM). (1998). “Standard test method for mechanical cone penetration tests of soil.” ASTM D3441-98, Sampling and Related Field Testing for Soil Evaluations , Vol 4.08, West Conshohocken, Pa. American Society for Testing and Materials (A STM). (2000a). “Standard classification of soils for engineering purposes (U nified Soil Classification System).” ASTM D2487-00, Identification and Classification of Soils , Vol 4.08, West Conshohocken, Pa. American Society for Testing and Materials (ASTM). (2000b). “Standard test method for performing electronic friction cone and pi ezocone penetration testing of soils.” ASTM D5778-95(2000), Sampling and Relate d Field Testing for Soil Evaluations Vol 4.09, West Conshohocken, Pa. American Society for Testing and Materials (A STM). (2001). “Standard test method for determining anaerobic bi odegradation potential of organic chemicals under methanogenic conditions.” ASTM E2170-01 , Terminology and Technical Services , Vol 11.05, West Conshohocken, Pa. Beaven, R. P. (2000). “The hydrogeologi cal and geotechnical properties of household waste in relation to sustainable landfilling.” PhD. dissertation, Department of Civil and Environmental Engineering, Qu een Mary and Westfield College, Southhampton, England. Belfiore, F., Manassero, M., and Viola, C. (1990). “Geotechnical analysis of some industrial sludges.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohocken, Pa., 317-330. Bjarngard, A., and Edgers, L. (1990). “Settlement of municipal solid waste landfills.” Proc., 13th Annual Madison Waste Conference , Madison, Wis., 192-205. Chynoweth, D. P., Turick, C. E., Owens, J. M ., Jerger, D. E., and Peck, M. W. (1993). “Biochemical methane potential of biomass and waste feedstocks.” Biomass and Bioenergy , 5(1), 95-111. Duplancic, N. (1990). “Landfill deforma tion monitoring and stability analysis.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohocken, Pa., 303-314.

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191 Edil, T. B., Ranguette, V. J., and Wuellner, W. W. (1990). “Settlement of municipal refuse.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohoken, Pa., 225-239. Fassett, J. B., Leonards, G. A., and Repetto, P. C. (1994). “Geotechnical properties of municipal solid wastes and th eir use in landfill design.” Proceedings from Waste Tech '94 Conference , National Solid Waste Manageme nt Association, Charleston, S.C. Hinkle, R. D. (1990). “Landfill site reclai med for commercial use as container storage facility.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohoken, Pa., 331-344. Hossain, M. S., Gabr, M. A., and Barlaz, M. A. (2003). “Relationship of compressibility parameters to municipal solid waste decomposition.” Journal of Geotechnical and Geoenvironmental Engineering, ASCE , 129(12), 1151-1158. Hudson, A. P., White, J. K., Beaven, R. P ., and Powrie, W. (2004). “Modeling the compression behavior of landfilled domestic waste.” Waste Management , 24, 259269. Jones, Edmunds & Associates, Inc. (2004). Polk County North Central Landfill (Site 201) Closed MSW Landfill Vertic al Expansion Feasibility Study , Gainesville, Fla. Landva, A. O., and Clark, J. I. (1990). “Geotechnics of waste fill.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohoken, Pa., 86-103. Lukas, R. G. (1992). “Dynamic compaction of sanitary land Fills.” Geotechnical News , September, 10(9). Lunne, T., Robertson, P. K., and Powell, J. J. M. (1997). Cone Penetration in Geotechnical Practice , Blackie Academic & Professional, London. Mehta, R., Barlaz, M. A., Y azdani, R., Augenstein, D., Bryars, M., and Sinderson, L. (2002). “Refuse decomposition in th e presence and absence of leachate recirculation.” Journal of Environmental Engineering , 128(3), 228-236. Oakley, R. E. (1990). “Case history: use of the cone penetrometer to calculate the settlement of a chemically stabilized landfill.” Geotechnics of Waste Fills—Theory and Practice ; ASTM STP 1070 , A. O. Landva and G. D. Knowles, eds., West Conshohoken, Pa., 345-357. Owens, J. M., and Chynoweth, D. P. (1993). “Biochemical methane potential of municipal solid waste (MSW) components.” Water Science Technology , 27(2), 114.

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194 BIOGRAPHICAL SKETCH Tobin Scott McKnight was born in Merced , California, on August 2, 1978. After living most of his life in south Florida, he graduated from Miami Killian Senior High in 1996 and enrolled in the University of Florid a. In December 2001 he graduated with a Bachelor of Science in Environmental Engi neering. In spring 2002 he enrolled in the University of Florida graduate school, ag ain in the Department of Environmental Engineering Sciences in the Solid and Hazardous Waste Management Group. Upon commencement with a Master of Engineering degree, Mr. McKnight will begin his career as an environmental consultant for Jones, Edmunds & Associates in Gainesville, Florida.