ORDOT DUMP ORDOT-CHALAN PAGO, GUAM. Estimation of Potential Landfill Gas Yields for the Ordot Dump

Transcription

1 F I N A L ORDOT DUMP ORDOT-CHALAN PAGO, GUAM Estimation of Potential Landfill Gas Yields for the Ordot Dump Prepared for Department of Public Works, Government of Guam 542 North Marine Drive Tamuning, Guam July 2005 Prepared by Dueñas & Associates Project Team (Dueñas & Associates, Inc. and URS Corporation) 155 E.T. Calvo Memorial Parkway, Suite 200 Tamuning, Guam (671)

2 TABLE OF CONTENTS Page 1.0 INTRODUCTION SCOPE OF REPORT SITE HISTORY FACTORS INFLUENCING LANDFILL GAS GENERATION METHODOLOGY LANDFILL GAS GENERATION MODELS MODEL SELECTION ESTIMATION OF METHANE GENERATION POTENTIAL, L O ESTIMATION OF METHANE GENERATION RATE CONSTANT, k GAS CAPTURE EFFICIENCY MODEL PARAMETERS MODEL OUTPUT CONCLUSION...12

3 APPENDICES A Estimated Methane Yield Plot B Estimated Methane Yield Tabulation C Feasibility Study for the Expansion of Ordot Sanitary Landfill, Chapter V TABLES Table 1-1: Variables Influencing Methane Generation and its Modeling...2 Table 1-2: Typical Uncertainties in Variables Affecting Methane Generation and its Modeling...4 Table 2-1: Model Parameters...10 Table 3-1: Projected Power Generation Potential (kw electric)...11

4 1.0 INTRODUCTION 1.1 SCOPE OF REPORT URS Corporation has developed a landfill gas model to predict the future landfill gas production post closure and conducted a preliminary feasibility assessment of future landfill gas-to-energy potential. The models developed for this report have been based on an estimation of waste quantities and an understanding of the history of the Ordot Dump summarized later in this report. 1.2 SITE HISTORY Ordot Dump is located on the central portion of Guam at approximately N and E. Guam is a tropical island and has two distinct seasons, one wet and the other dry. The average annual rainfall at the site is approximately inches, which is high and has resulted in a wet refuse conditions in the Dump. Based on the 2004 field activities performed to delineate the limits of waste, the Dump is estimated to have a plan footprint of 46.8 acres (area contained within the limit of waste). The closure area of the Dump is expected to cover an area of approximately 50 acres. Ordot Dump has been operational since the 1940 s and is currently scheduled to be closed in October 2007, according to the timeline spelled out in the Consent Decree. Information on the exact refuse filling rates is not available however our current estimates are as follows: a) 200 tons per day for approximately 300 days per year from 1950 to 1990; b) 350 tons per day for approximately 300 days per year from 1990 to 2004; and c) 120,000 tons per annum from 2004 to These filling rates have been used in the modeling described in this report. 1.3 FACTORS INFLUENCING LANDFILL GAS GENERATION The basic biological processes leading to the generation of methane from landfills have been well known for many years. Bacterial action leads to the generation of methane from organic substrates by reactions such as the following (simplified) of cellulose to methane. nc 6 H nh 2 0 3nCH 4 + 3nCO 2 (1) The difficulties that are encountered in attempting to develop methane generation models are exemplified by the information shown in Tables 1-1 and 1-2. Table 1-1 shows the operational and other relevant variables that can influence generation and Table 1-2 the uncertainties that can exist in available information. The implications of the tables are briefly discussed. 1

5 Table 1-1: Variables Influencing Methane Generation and its Modeling I. Waste Management and Processing Variables 1. Baling 2. Shredding, crushing/flailing 3. Material separation/removal II. Waste Composition Variables 1. Organic/Inorganic 2. Proportion yard/food/paper/other organic residues 3. Proportion of readily/moderately/slowly decomposable material 4. Whether co-disposal has been done (namely sewage biosolids as well as refuse). III. Biological Factors IV. Design 1. Moisture Content (average value, spatial variation, movement over time) 2. Nutrients (availability/movement) 3. Bacteria (location, density, mobility) 4. ph 5. Temperature 1. Dimensions (area, depth) 2. Gas containment (base, sides, top cover) 3. Gas Extraction System and its effectiveness or efficiency. V. Landfilling Variables 1. Day-to-Day refuse handling Temporary capping characteristics 2

6 Degree of compaction Degree of segregation Degree of material breakdown 2. Liquid addition Managed (liquid additions, leachate recycling) Natural (precipitation, groundwater infiltration) Post-closure changes (infiltration and movement) Table 1-1 shows the kinds of factors that can differ from landfill to landfill, or vary within a landfill and directly or indirectly affect gas production. As examples, cover material may influence water inflow from precipitation, and bottom and side liners, if present, will influence infiltration of groundwater into the waste mass. Consequent varying levels of moisture content may strongly affect gas generation. Shredding, if carried out, is likely to facilitate generation through intermixing of refuse, nutrients and bacteria. If co-disposal has been practiced the additional nutrients can improve gas production. These are only some of the cause and effect relationships that exist between operational parameters and methane generation. Liquid addition such as leachate recirculation can increase the moisture content within the Dump, as well as increasing the available nutrients for microbiological growth. Temperature within the landfill can have an important influence on gas generation rates, as temperature is an important factor in determining the growth of microbes. Typically, the optimum methane generation temperatures are between 27 and 43 degrees Celsius (80 ºF to 109 ºF). Additionally, extremes in ph will also affect methane generation rates as this affects the growth and function of methanogenic bacteria. Most methanogenic bacteria function in a ph range of between 6.7 and 7.4, but the optimal ph is believed to be at 7.0 to 7.2. Rates of methane production may decrease if the ph is lower than 6.3 or higher than ph 7.8. The presence of lime in the Ordot Dump will assist in buffering anaerobic digestion and thereby could increase gas production. 3

7 Table 1-2: Typical Uncertainties in Variables Affecting Methane Generation and its Modeling i) Waste placement/history/location/composition may be difficult to trace, especially for older landfills ii) Biological parameters: nutrients, temperature and ph a) Difficult to measure b) Likely to vary spatially and over time through landfill iii) Collection efficiency a) Believed to range between 40 and 90% b) Depends on vacuum applied, refuse, density, final capping and intermediate cover c) Number and design of gas wells d) Barometric pressure variations e) Type and integrity of final capping provided. iv) Moisture content a) Difficult to measure or estimate b) Likely to vary spatially and over time in the landfill c) Has an important effect on methane generation d) Influenced by capping and rainfall. Table 1-2 indicates the kind of uncertainties that are likely to exist in the data for developing a model. These range from uncertainties in waste placement history, or location, or composition (all quite common in older landfills), to the serious uncertainties regarding extraction efficiency. The importance of a number of factors such as ph, nutrient level, free aqueous phase, and temperature are well established. In controlled systems, the importance of ph and nutrient level to the landfill gas generation process is often emphasized. As it pertains to landfills however, it is difficult to fully convey the complexity of a situation 4

8 where there can be as much variation in the above factors as can occur between different compositions of paper and food wastes in the landfill. The extraction criteria and effectiveness vary, depending on the purpose for which extraction is carried out. The extraction process typically results in various degrees of air infiltration. The infiltrating air inhibits methane generation, and, after consumption of the oxygen in the landfill (largely to produce CO 2 ), the infiltrated air dilutes the recovered gas. Poor management of an extraction system can significantly reduce the methane yield and can increase the risk of underground landfill fires. As stated earlier, the variation in moisture content in the landfill will have a major influence on the rate of landfill gas generation as landfill gas generation increases with moisture content. In Auckland, New Zealand, seasonal differences in landfill gas generation rates are observed between winter and summer as a result of the changes in rainfall experienced between seasons. This is likely to be exacerbated by seasonal typhoons in Guam that cause intense tropical downpours. 5

9 2.0 METHODOLOGY 2.1 LANDFILL GAS GENERATION MODELS A number of landfill gas generation models have been developed in the United States. These are summarized in the US EPA document "Air Emissions from Municipal Solid Waste Landfills - Background Information for Proposed Standards and Guidelines", in March These models include the Palos Verdes Kinetic Model, the Sheldon-Arleta Model and the Scholl Canyon Model. The Palos Verdes Kinetic Model is a two stage first order model. It is assumed that the first stage gas production rate increases exponentially with time and the second stage gas production rate decreases exponentially with time. It is also assumed that the maximum gas production rate and transition from the first stage to the second stage occurs at the time when half of the ultimate gas production has been reached. The Sheldon-Arleta Model is identical to the Palos Verdes Model except for the assumption of half time (that is, the period when half the ultimate gas production is reached). It assumes that the maximum gas production rate occurs at half time, but the half time is equal to 0.35 multiplied by the total production time. The rate of generation of landfill gas used in this study was based on the Scholl Canyon equation, which assumes that the gas production rate is at its highest upon initial waste placement, after a negligible lag time during which anaerobic conditions are established in the landfill (in practice, this is usually 80 to 300 days). The gas production rate is then assumed to decrease exponentially as the organic fraction of the landfill refuse decreases. The total gas generation from the entire landfill is at its peak upon the landfill closure if a constant or increasing annual acceptance rate is assumed. The Scholl Canyon model, as represented by Equation 2, has now been adopted as the preferred model by the US EPA to the extent that they have now issued a computer version of the Scholl Canyon model called LandGEMS (with an update in February 1998 called LANDGEMS version 2). These models are run using metric units. The Scholl Canyon Model equation is: where, Q = Lo R {exp(-kc) - exp(-kt)} (2) Q = methane gas generation at time t, m3.yr-1 refuse Lo = potential methane generation capacity of the refuse, m3 per tonne R = average annual refuse acceptance rate during active life, tonne.yr-1 k = methane generation rate constant, yr-1 c = time since landfill closure, year (c=0 for active landfill) 6

10 t = time since the initial refuse placement, year The difficulty in using this model (or either of the other models mentioned above) is in deciding on values for Lo (the potential methane generation capacity of the refuse) and k (the methane generation rate constant). Some background information on the choice of these values is explained in the following sections. An alternative model developed by the Solid Waste Association of North America (SWANA) is called the Methane Gas Recovery Program (MEGAREP (1997)). This model uses a variety of different modeling scenarios based on zero and first order decay equations. URS has previously used the fourth model contained in MEGAREP, which uses a modified form of the Scholl Canyon equation to allow for separate input for both percentages of readily decomposable and slowly decomposable waste materials. The MEGAREP Model equation is: Q = Lo R {Fr(krexp(-kr(t-tl))) + Fs(ksexp(-ks(t-tl))))} (3) where, Q = methane gas generation at time t, m3.yr-1 Lo = potential methane generation capacity of the refuse, m3 per tonne refuse R = waste in place, tonne Kr = first order decay rate constant for rapidly decomposable waste, yr-1 Ks = first order decay rate constant for slowly decomposable waste, yr-1 Fr = fraction of rapidly decomposable waste; Fs = fraction of slowly decomposable waste t = time since the initial refuse placement, year tl = lag time (between placement and start of generation) The rapidly decomposable wastes (generally including food and green wastes) decompose much quicker than do other decomposable organic wastes, due to a combination of both an optimum nitrogen to carbon ratio and a relatively high moisture content of these wastes. The slowly decomposable wastes (typically paper, cardboard, textiles, wood and wood products) generally have less than optimum nitrogen to carbon ratios or less than optimum moisture contents. These organic wastes also consist of more complex carbon materials that take more energy for the bacteria to break down. 7

11 2.2 MODEL SELECTION For the Ordot Dump study, the US EPA LandGEM model was selected over SWANA MEGAREP or other landfill gas models as the information on the volume and composition of the material being deposited into the Dump is not sufficiently precise to enable more complex modeling. Peer et al (1993) conducted a study to determine which type of model was more accurate in predicting landfill gas generation and concluded that the most important factor in the calculation was the assumed methane potential of the refuse and not the actual mathematical model used to obtain the estimates of methane. Coops et al (1995) validated zero-order, first order, second order and multi-phase first order by comparing predicted values to field data from nine landfills in the Netherlands. They concluded that the first-order, second order and multi-phase models were all similar in describing landfill gas formation although the multiphase models where slightly more accurate than the others in predicting actual methane emissions provided that the input data were accurate. 2.3 ESTIMATION OF METHANE GENERATION POTENTIAL, L O The methane generation potential, L o, is primarily influenced by the refuse composition, moisture content, and permeability of cover material. Generally, estimates of L o are developed based on assessment of the waste stream composition, although other techniques exist. A waste study carried out for Guam in 1993 as part of the Feasibility Study for the Expansion of Ordot Sanitary Landfill, Volume One (Juan C. Tenorio & Associates, Inc., 1993) included a summary of existing data and indicated varying compositions for different residential areas on Guam (See Appendix C). At the time of this report preparation, no other useful data were made available for review. The absence of specific data on waste composition does not allow a theoretical estimate of L o to be calculated. Assuming the waste composition data for different areas obtained in 1980 are generally representative of the waste stream entering Ordot, it appears likely that the L o value will reflect those determined for typical municipal solid waste landfills. Default values for L o of 170 m 3 /tonne and 100 m 3 /tonne are provided in the Clean Air Act (CAA) and the USEPA s AP-42 series, respectively. The CAA default was developed for compliance purposes and is recognized as being conservative in order to protect human health, to encompass a wide range of landfills, and to encourage the use of site-specific data. The AP-42 default was derived from analysis of 21 landfills and is considered to provide a representative best fit estimate for actual methane generation. The AP-42 L o value of 100 m 3 /tonne is generally consistent with URS s experience and other published data, and has therefore been selected as the best estimate at this stage of assessment for the Ordot Dump. The range of published L o estimates varies significantly and for this reason pessimistic and optimistic values have been based on -30% and +20% of the best estimate, respectively. While these values are expected to define the likely envelope of methane generation potential at the site, L o values outside of these have been reported in the literature for some sites. 8

12 2.4 ESTIMATION OF METHANE GENERATION RATE CONSTANT, k The methane generation rate constant, called k, is influenced by a number of factors, including: refuse type, moisture, ph, temperature, and landfill operating conditions. The decomposable fraction of the waste stream, based on analysis of different residential areas in 1980, appears to have a relatively high component of slowly degradable material (paper, textiles, wood) compared with typical compositions in other developed countries. The component of slowly degradable material will act to reduce the k value slightly, although any such reductions are expected to be more than offset by the wet nature of the site, as described below. For dry sites, k values of 0.02/year or lower may be appropriate. Alternatively, where a site is predominantly wet, k values in excess of 0.3/year have been recorded. The high annual precipitation at Ordot Dump (approximately 94 inches) is likely to result in a high average moisture content in the Dump. Furthermore, leachate seepages have been observed discharging from the sides of the Dump. Giving consideration to the indicative waste composition and the wet condition of the site, it is likely that a high overall k value will be applicable for modeling purposes. A best estimate value of 0.3 per year has been selected, based on URS experience at other highly saturated sites. However the elevated temperatures and high rainfall could result in k values nearer to 0.4/year. Given the likely high k value, the gas generation from refuse placed prior to around 1980 is likely to be too low to collect economically. This may impact the layout of any collection system and implies that the accurate determination of refuse volumes placed subsequent to 1980 is of more importance for gas modeling purposes than refuse placed prior to that time. 2.5 GAS CAPTURE EFFICIENCY If landfill gas from the Ordot Dump is to be utilized, it will be necessary to install a collection system comprising extraction wells and reticulation. The capture efficiency for gas collection will be dependent on the design and operation of the system, capping permeability, condensate management, capping integrity, refuse depth, and many other factors. It is assumed that the gas extraction system at the Ordot Dump will be designed to provide good gas capture and an appropriate capping system. Although actual capture efficiencies are difficult to determine, it is expected that the gas capture efficiency at the site will be around 70% to 80% of the theoretical modelled gas generation values and these percentage values have been used for the Pessimistic and Optimistic Scenarios, respectively. 2.6 MODEL PARAMETERS Following the design basis outlined in Sections 2.3 and 2.4, the following parameters were used in the models to estimate the potential landfill gas generation and recovery models. 9

13 Table 2-1: Model Parameters Pessimistic Scenario Best Estimate Scenario Optimistic Scenario Methane Generation Potential, L o 70 m 3 /tonne 100 m 3 /tonne 120 m 3 /tonne Methane Generation Rate, k 0.4/year 0.3/year 0.2/year Capture Efficiency 70% 75% 80% 10

14 3.0 MODEL OUTPUT The predicted methane yield from the Ordot Dump is shown in Figure 1, Appendix A. The yield is the expected rate at which methane could be extracted and is calculated by applying the extraction efficiency value to the modeled methane generation. Figure 1 indicates the likely envelope of methane yield from the Ordot Dump, namely defined between the pessimistic and optimistic plots. The plots are based on average annual yields and do not indicate the seasonal variations in gas production and capture which are likely to occur as a result of moisture changes in the Dump. It should be noted that while the plot shows the total methane yield, the landfill gas yield (i.e., including carbon dioxide and other constituents) would be approximately twice that for methane. The presence of other constituents in the landfill gas would naturally impact the sizing and design of any gas extraction and utilization equipment. As expected with the use of a high k value, the methane generation rate is predicted to fall relatively quickly with time. Based on the best estimate parameters, the methane yield is predicted to peak at around 324 million cubic feet per year at the completion of filling in 2007 and reduce to around 16 million cubic feet per year over the subsequent 10 years to Methane generation at 2007 for the pessimistic and optimistic scenarios is predicted to be 225 to 384 million cubic feet per year, respectively, reducing to 4 and 52 million cubic feet per year, respectively, by It is understood that a gas to electric energy project is being considered. Such schemes are usually planned to have at least a 15-year and preferably 25-year life. An estimate of the equivalent electricity generation potential has been tabulated against projected methane yields in Appendix B and summarized for selected years in Table 3-1 below. The power generation potential has been calculated based on 9.15 kw e of potential electricity for each million cubic feet of methane per year. As shown in Table 3-1, the best estimate parameters indicate sufficient methane yield to potentially support around 3,000 kw e power generation at 2007 reducing to around 150 kw e by Over a shorter term of say five years from closure, a sustainable yield to support a maximum 700 kw e plant may be available. These estimates are indicative only and the pessimistic and optimistic model scenarios also need to be considered. Table 3-1: Projected Power Generation Potential (kw electric) Pessimistic Best Estimate Optimistic ,060 2,970 3, ,

15 4.0 CONCLUSION URS has estimated the gas generation and expected gas capture rates (gas yield) for the Ordot Dump for a filling period ending in The quality of the input data into the model on refuse volumes and refuse composition is very limited; therefore gas estimates can only be approximated. Based on actual known gas decay rates from moderately wet landfills in New Zealand with rainfalls of 43.3 inches (1100 mm) and over 59 inches (1500 mm) per annum, and where gas extraction is practiced, we have calibrated models to estimate methane die off following completion of filling. The parameters established as part of this calibration have been used to develop the model parameters for the Ordot Dump. Our conclusion is that the higher tropical temperatures and high rainfall are likely to result in a very rapid reduction in gas generation after closure. Any gas to electrical power scheme would most likely be 500 KW e or less if the power plant was to be run for any length of time (over approximately 5 years). The use of very low permeability capping with good stormwater drainage will significantly reduce the rate of water ingress and may reduce refuse degradation rates. Such an option would be of particular use in extending the gas production curve particularly in areas of more recent filling. Reducing the rate of gas generation extends the period over which a fixed gasto-energy system can be used. The magnitude of this extended gas production period is, however, difficult to assess. 12

16 APPENDIX A ESTIMATED METHANE YIELD PLOT

17 Figure 1 - Ordot Dump Estimated Methane Yield 450 Pessimistic: Lo=70m3/tonne, k=0.4/yr, 70% capture 400 Best Estimate: Lo=100m3/tonne, k=0.3/yr, 75% capture Optimistic: Lo=120m3/tonne, k=0.2/yr, 80% capture 350 million cubic feet / year Year 24 November 2004 LFG Generation Report Appendix A & B - Draft 2 November 24

18 APPENDIX B ESTIMATED METHANE YIELD TABULATION

19 Ordot Dump Estimated Methane Yield Year Refuse in Place (Tons) Pessimistic: L o =70m 3 /tonne, k=0.4/yr, 70% capture Methane Yield (million cubic feet per year) Best Estimate: L o =100m 3 /tonne, k=0.3/yr, 75% capture Optimistic: L o =120m 3 /tonne, k=0.2/yr, 80% capture Pessimistic: L o =70m 3 /tonne, k=0.4/yr, 70% capture Power (kw electric) Best Estimate: L o =100m 3 /tonne, k=0.3/yr, 75% capture Optimistic: L o =120m 3 /tonne, k=0.2/yr, 80% capture ,800, ,046 1,526 1, ,859, ,046 1,526 1, ,920, ,046 1,526 1, ,979, ,046 1,527 1, ,039, ,046 1,527 1, ,099, ,046 1,527 1, ,159, ,046 1,527 1, ,220, ,046 1,527 1, ,279, ,046 1,527 1, ,340, ,046 1,527 1, ,399, ,046 1,527 1, ,504, ,304 1,823 2, ,610, ,477 2,043 2, ,714, ,594 2,206 2, ,819, ,672 2,327 2, ,924, ,724 2,416 2, ,030, ,758 2,483 2, ,134, ,782 2,532 2, ,239, ,798 2,568 2, ,344, ,808 2,595 3, ,450, ,815 2,615 3, ,554, ,820 2,630 3, ,659, ,823 2,641 3, ,779, ,913 2,749 3, ,899, ,972 2,829 3, ,020, ,012 2,888 3, ,140, ,039 2,932 3, ,260, ,057 2,964 3, ,260, ,379 2,196 2, ,260, ,627 2, ,260, ,205 1, ,260, , ,260, , ,260, , ,260, ,260, ,260, ,260, ,260, ,260, ,260, November 2004 LFG Generation Report Appendix A & B - Draft 2 November 24

20 APPENDIX C FEASIBILITY STUDY FOR THE EXPANSION OF ORDOT SANITARY LANDFILL, CHAPTER V

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