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DRAFT Inventory of U.S Greenhouse Gas Emissions and Sinks

2017_complete_report

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Description of the GHGRP Data for MSW Landfills Directly reported CH 4 emissions, or back-casted emissions based off EPA’s GHGRP dataset were applied for years 2005 to 2015. Under the GHGRP methodology, the first order decay model methodology, adjusted for oxidation is applied to estimate CH 4 generation for landfills without landfill gas collection and control. Landfills with gas collection and control are required to estimate CH 4 emissions two ways; one that is based off of the first order decay methodology, and a second that is based off of directly measured amounts of recovered landfill gas (Equation HH-8 in CFR Part 98.343, as described above). The GHGRP details allowable methodologies for monitoring quantities of recovered CH 4 from the landfill gas, and the EPA verifies all annual greenhouse gas reports. Description of the First Order Decay Methodology for Industrial Waste Landfills Emissions from industrial waste landfills were estimated from industrial production data from 2014 extrapolated to 2015 (ERG 2016), waste disposal factors, and the FOD model. The Inventory methodology assumes over 99 percent of the organic waste placed in industrial waste landfills originates from the food processing (meat, vegetables, fruits) and pulp and paper sectors (EPA 1993), thus estimates of industrial landfill emissions focused on these two sectors. There are currently no data sources that track and report the amount and type of waste disposed of in the universe of industrial waste landfills in the United States. EPA’s GHGRP provides some insight into waste disposal in industrial waste landfills and supports the focus of the Inventory on the two selected sectors, but is not comprehensive. Therefore, the amount of waste landfilled is assumed to be a fraction of production that is held constant over the time series as explained in Annex 3.14. The composition of waste disposed of in industrial waste landfills is expected to be more consistent in terms of composition and quantity than that disposed of in MSW landfills. Data collected through EPA’s GHGRP for industrial waste landfills (Subpart TT) show that only two of the 176 facilities, or 1 percent of facilities, have active gas collection systems (EPA 2015a). EPA’s GHGRP is not a national database and comprehensive data regarding gas collection systems have not been published for industrial waste landfills. Assumptions regarding a percentage of landfill gas collection systems, or a total annual amount of landfill gas collected for the non-reporting industrial waste landfills have not been made for the Inventory methodology. Uncertainty and Time-Series Consistency – TO BE UPDATED FOR FINAL INVENTORY REPORT Several types of uncertainty are associated with the estimates of CH 4 emissions from MSW and industrial waste landfills when the first order decay model is applied. The approach used in the MSW emission estimates assumes that the CH 4 generation potential (L o) and the rate of decay that produces CH 4 from MSW, as determined from several studies of CH 4 recovery at MSW landfills, are representative of conditions at U.S. MSW landfills. When this top-down approach is applied at the nationwide level, the uncertainties are assumed to be less than when applying this approach to individual landfills and then aggregating the results to the national level. In other words, the first order decay methodology as applied in this Inventory is not facility-specific modeling and while this approach may over- or under-estimate CH 4 generation at some landfills if used at the facility-level, the end result is expected to balance out because it is being applied nationwide. There is also a high degree of uncertainty and variability associated with the FOD model, particularly when a homogeneous waste composition and hypothetical decomposition rates are applied to heterogeneous landfills (IPCC 2006). The lack of landfill-specific information regarding the number and type of industrial waste landfills in the United States is a primary uncertainty with respect to the industrial waste generation and emissions estimates. The approach used here assumes that the majority (99 percent) of industrial waste disposed of in industrial waste landfills consists of waste from the pulp and paper and food processing sectors. However, because waste generation and disposal data are not available in an existing data source for all U.S. industrial waste landfills, a straight disposal factor is applied over the entire time series to the amount of waste generated to determine the amounts disposed. Industrial waste facilities reporting under EPA’s GHGRP do report detailed waste stream information, and these data have been used to improve, for example, the DOC value used in the Inventory methodology for the pulp and paper sector. Aside from the uncertainty in estimating landfill CH 4 generation, uncertainty also exists in the estimates of the landfill gas oxidized. A constant oxidation factor of 10 percent as recommended by the IPCC for managed landfills is used for both MSW and industrial waste landfills regardless of climate, the type of cover material, and/or presence Waste 7-9

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 of a gas collection system. The number of published field studies measuring the rate of oxidation has increased substantially since the 2006 IPCC Guidelines were published and, as discussed in the Potential Improvements section, efforts are being made to review the literature and revise this value based on recent, peer-reviewed studies. Another significant source of uncertainty lies with the estimates of CH 4 recovered by flaring and gas-to-energy projects at MSW landfills. The GHGRP MSW landfills database was added as a fourth recovery database starting with the 1990 through 2013 Inventory report. Relying on multiple databases for a complete picture introduces uncertainty because the coverage and characteristics of each database differs, which increases the chance of double counting avoided emissions. Additionally, the methodology and assumptions that go into each database differ. For example, the flare database assumes the midpoint of each flare capacity at the time it is sold and installed at a landfill; in reality, the flare may be achieving a higher capacity, in which case the flare database would underestimate the amount of CH 4 recovered. The LFGTE database is updated annually. The flare database is populated by the voluntary sharing of flare sales data by select vendors and is not able to be obtained annually, which likely underestimates recovery for landfills not included in the three other recovery databases used by the Inventory. The EIA database has not been updated since 2006 and has, for the most part, been replaced by the GHGRP MSW landfills database. To avoid double counting and to use the most relevant estimate of CH 4 recovery for a given landfill, a hierarchical approach is used among the four databases. GHGRP data are given precedence because CH 4 recovery is directly reported by landfills and undergoes a rigorous verification process; the EIA data are given second priority because facility data were directly reported; the LFGTE data are given third priority because CH 4 recovery is estimated from facility-reported LFGTE system characteristics; and the flare data are given fourth priority because this database contains minimal information about the flare, no site-specific operating characteristics, and includes smaller landfills not included in the other three databases (Bronstein et al. 2012). The coverage provided across the databases most likely represents the complete universe of landfill CH 4 gas recovery; however, the number of unique landfills between the four databases does differ. The IPCC default value of 10 percent for uncertainty in recovery estimates was used for two of the four recovery databases in the uncertainty analysis where metering of landfill gas was in place (for about 64 percent of the CH 4 estimated to be recovered). This 10 percent uncertainty factor applies to the LFGTE database; 12 percent to the EIA database; and 1 percent for the GHGRP MSW landfills dataset because of the supporting information provided and rigorous verification process. For flaring without metered recovery data (the flare database), a much higher uncertainty value of 50 percent is used. The compounding uncertainties associated with the four databases in addition to the uncertainties associated with the FOD model and annual waste disposal quantities leads to the large upper and lower bounds for MSW landfills presented in Table 7-5. Industrial waste landfills are shown with a lower range of uncertainty due to the smaller number of data sources and associated uncertainty involved. For example, three data sources are used to generate the annual quantities of MSW waste disposed over the 1940 to current year timeframe, while industrial waste landfills rely on two data sources. There is less uncertainty in the GHGRP data because this methodology is facility-specific, uses directly measured CH 4 recovery data (when applicable), and allows for a variety of landfill gas collection efficiencies, destruction efficiencies, and/or oxidation factors to be used. The results of the 2006 IPCC Guidelines Approach 2 quantitative uncertainty analysis are summarized in Table 7-5. Table 7-5: Approach 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (MMT CO2 Eq. and Percent) Source Gas 2015 Emission Estimate Uncertainty Range Relative to Emission Estimate a (MMT CO2 Eq.) (MMT CO2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Landfills CH4 MSW CH4 Industrial CH4 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval. 7-10 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2015

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    Cement Production 33.3 45.9 32.0 35

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    Total 1,862.5 2,441.6 2,197.3 2,059

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    Total Emissions 6,366.7 7,315.6 6,7

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    Activity 1990 2005 2011 2012 2013 2

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    Previous Estimated Emissions from S

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    1 Table 4-89: CO2 Emissions from Zi

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    Other Lands Converted Grassland Min

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  • Page 481 and 482: C Storage Factor, Proportion of Ini
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  • Page 489 and 490: 1 Table 7-2: Emissions from Waste (
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  • Page 509 and 510: 2013 321 10,536 2014 323 10,613 201
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  • Page 529 and 530: Enteric Fermentation NC NC + NC + (
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