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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 data estimated by the Tier 3 and Tier 1 approaches, the IPCC (2006) default emission factor is used to estimate indirect N 2O emissions that occur in groundwater and waterways (see Table 5-18). Uncertainty and Time-Series Consistency Uncertainty is estimated for each of the following five components of N 2O emissions from agricultural soil management: (1) direct emissions simulated by DAYCENT; (2) the components of indirect emissions (N volatilized and leached or runoff) simulated by DAYCENT; (3) direct emissions calculated with the IPCC (2006) Tier 1 method; (4) the components of indirect emissions (N volatilized and leached or runoff) calculated with the IPCC (2006) Tier 1 method; and (5) indirect emissions estimated with the IPCC (2006) Tier 1 method. Uncertainty in direct emissions, which account for the majority of N 2O emissions from agricultural management, as well as the components of indirect emissions calculated by DAYCENT are estimated with a Monte Carlo Analysis, addressing uncertainties in model inputs and structure (i.e., algorithms and parameterization) (Del Grosso et al. 2010). Uncertainties in direct emissions calculated with the IPCC (2006) Tier 1 method, the proportion of volatilization and leaching or runoff estimated with the IPCC (2006) Tier 1 method, and indirect N 2O emissions are estimated with a simple error propagation approach (IPCC 2006). In addition, uncertainties from the Approach 1 and Approach 3 (i.e., DAYCENT) estimates are combined using simple error propagation (IPCC 2006). Additional details on the uncertainty methods are provided in Annex 3.12. Table 5-19 shows the combined uncertainty for direct soil N 2O emissions ranged from 16 percent below to 26 percent above the 2015 emissions estimate of 213.3 MMT CO 2 Eq., and the combined uncertainty for indirect soil N 2O emissions range from 46 percent below to 155 percent above the 2015 estimate of 38.0 MMT CO 2 Eq. Table 5-19: Quantitative Uncertainty Estimates of N2O Emissions from Agricultural Soil Management in 2015 (MMT CO2 Eq. and Percent) Source Gas 2015 Emission Estimate Uncertainty Range Relative to Emission Estimate (MMT CO2 Eq.) (MMT CO2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Direct Soil N2O Emissions N2O 213.3 179.7 267.9 -16% 26% Indirect Soil N2O Emissions N2O 38.0 20.5 96.8 -46% 155% Notes: Due to lack of data, uncertainties in managed manure N production, PRP manure N production, other organic fertilizer amendments, and sewage sludge amendments to soils are currently treated as certain; these sources of uncertainty will be included in future Inventory reports. 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 Additional uncertainty is associated with an incomplete estimation of N 2O emissions from managed croplands and grasslands in Hawaii and Alaska. The Inventory currently includes the N 2O emissions from mineral fertilizer and PRP N additions in Alaska and Hawaii, and drained organic soils in Hawaii. Land areas used for agriculture in Alaska and Hawaii are small relative to major commodity cropping states in the conterminous United States, so the emissions are likely to be small for the other sources of N (e.g., crop residue inputs), which are not currently included in the Inventory. Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990 through 2015. Details on the emission trends through time are described in more detail in the Methodology section. QA/QC and Verification DAYCENT results for N 2O - emissions and NO 3 leaching are compared with field data representing various cropland and grassland systems, soil types, and climate patterns (Del Grosso et al. 2005; Del Grosso et al. 2008), and further evaluated by comparing the model results to emission estimates produced using the IPCC (2006) Tier 1 method for the same sites. Nitrous oxide measurement data are available for 41 sites, which mostly occur in the United States, with five in Europe and three in Australia, representing over 200 different combinations of fertilizer treatments and cultivation practices. Nitrate leaching data are available for four sites in the United States, representing 10 different combinations of fertilizer amendments/tillage practices. DAYCENT estimates of N 2O emissions are closer to measured values at most sites compared to the IPCC Tier 1 estimate (see Figure 5-8). In general, the IPCC Tier 1 5-32 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2015

1 2 3 4 5 6 7 8 9 10 methodology tends to over-estimate emissions when observed values are low and under-estimate emissions when observed values are high, while DAYCENT estimates have less bias. DAYCENT accounts for key site-level factors (i.e., weather, soil characteristics, and management) that are not addressed in the IPCC Tier 1 method, and thus the model is better able to represent the variability in N 2O emissions. DAYCENT does have a tendency to underestimate very high N 2O emission rates; and estimates are adjusted using the statistical model derived from the comparison of model estimates to measurements (see Annex 3.12 for more information). Regardless, the comparison demonstrates that DAYCENT provides relatively high predictive capability for N 2O emissions, and is an improvement over the IPCC Tier 1 method. Figure 5-8: Comparison of Measured Emissions at Field Sites and Modeled Emissions Using the DAYCENT Simulation Model and IPCC Tier 1 Approach (kg N2O per ha per year) 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Spreadsheets containing input data and probability distribution functions required for DAYCENT simulations of croplands and grasslands and unit conversion factors have been checked, in addition to the program scripts that are used to run the Monte Carlo uncertainty analysis. Links between spreadsheets have been checked, updated, and corrected when necessary. Spreadsheets containing input data, emission factors, and calculations required for the Tier 1 method have been checked and updated as needed. Recalculations Discussion Methodological recalculations in the current Inventory are associated with the following improvements: (1) driving the DAYCENT simulations with updated input data for land management from the National Resources Inventory extending the time series through 2012; (2) modifying the number of experimental study sites used to quantify model uncertainty for direct N 2O emissions; (3) DAYCENT model development to improve the simulation of soil temperature; (4) improvements in the cropping and land use histories that are simulated in DAYCENT between 1950 and 1979 that generate initial values for the model state variables, such as initial soil organic C stock values; and (5) implementing a more robust set of model output variables that enabled a more accurate and detailed accounting of N from synthetic fertilizers, managed manure, and PRP manure applied to grasslands. These changes resulted in a decrease in emissions of approximately 14.4 percent on average relative to the previous Inventory and an increase in the upper bound of the 95 percent confidence interval for direct N 2O emissions from 24 to 31 percent. The differences in emissions and uncertainty are mainly due to modifying the number of study sites used to quantify model uncertainty. Agriculture 5-33

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    1 2 3 4 5 6 irreversible accumulati

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    a Emission estimates reported in th

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    a Emissions from Wood Biomass and E

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    1 2 3 4 Overall, in 2015, waste act

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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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    N2O 1.0 1.2 1.1 1.0 1.1 1.1 1.1 Oth

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    Coal b 1,653.7 1,596.3 1,809.1 -3%

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    Gas/Waste Product 1990 2005 2011 20

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    Activity 1990 2005 2011 2012 2013 2

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    Previous Estimated Emissions from S

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    Emissions (w/o Plunger) (MT) 372,28

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    Reciprocating Compressors 64,413 64

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    CO2 206.8 189.9 172.9 169.6 171.5 1

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    1 Table 4-89: CO2 Emissions from Zi

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    New Mexico 70,608 52,250 12.0 0.263

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    C Storage Factor, Proportion of Ini

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    1 2 Table 7-16: Approach 2 Quantita

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    Enteric Fermentation NC NC + NC + (

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Quality manual for the greenhouse gas inventory. Version 1.
Greenhouse Gas Emissions from U.S. Heavy-Duty Trucks
D - Inventory of Greenhouse Gas Emissions - Abengoa
Building trust in greenhouse gas inventories from the United ... - WWF
2009 Corporate Greenhouse Gas Emissions Inventory - the Town of ...
Use of Models and Facility-Level Data in Greenhouse Gas Inventories
City of Richmond 2008 Greenhouse Gas Emissions Inventory
Inventory of New York City Greenhouse Gas Emissions - NYC.gov
Expert Meeting on Uncertainty and Validation of Emission Inventories
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County of San Diego 2005/2006 Greenhouse Gas Emissions Inventory
international maritime transport and greenhouse gas emissions - IMO
Greenhouse Gas Emissions from U.S. Agriculture and Forestry: A ...
Greenhouse Gas Emissions Inventory Report - Cal Poly Pomona
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GREENHOUSE GAS EMISSIONS - The Sallan Foundation
Reducing U.S. Greenhouse Gas Emissions - Center for Climate and ...
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Greenhouse Gas Emissions from U.S. Transportation - Center for ...
Greenhouse Gas Emission Policies Is There a Way ... - Castalia
Evaluation of Greenhouse Gas Emissions from Septic ... - Geoflow
RE-CALCULATING THE GREENHOUSE GAS EMISSIONS ... - Inra
National Greenhouse Gas Inventories - US Environmental ...
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