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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 under Subpart I, docket EPA–HQ–OAR–2011–0028). 69 The 2012 analysis did not take into account the use of abatement. For the industry segment that processed 200 mm wafers, estimates of uncertainties at a 95 percent CI ranged from ±29 percent for C 3F 8 to ±10 percent for CF 4. For the corresponding 300 mm industry segment, estimates of the 95 percent CI ranged from ±36 percent for C 4F 8 to ±16 percent for CF 4. These gas and waferspecific uncertainty estimates are applied to the total emissions of the facilities that did not abate emissions as reported under EPA’s GHGRP. For those facilities reporting abatement of emissions under EPA’s GHGRP, estimates of uncertainties for the no abatement industry segments are modified to reflect the use of full abatement (abatement of all gases from all cleaning and etching equipment) and partial abatement. These assumptions used to develop uncertainties for the partial and full abatement facilities are identical for 200 mm and 300 mm wafer processing facilities. For all facilities reporting gas abatement, a triangular distribution of destruction or removal efficiency is assumed for each gas. The triangular distributions range from an asymmetric and highly uncertain distribution of zero percent minimum to 90 percent maximum with 70 percent most likely value for CF 4 to a symmetric and less uncertain distribution of 85 percent minimum to 95 percent maximum with 90 percent most likely value for C 4F 8, NF 3, and SF 6. For facilities reporting partial abatement, the distribution of fraction of the gas fed through the abatement device, for each gas, is assumed to be triangularly distributed as well. It is assumed that no more than 50 percent of the gases area abated (i.e., the maximum value) and that 50 percent is the most likely value and the minimum is zero percent. Consideration of abatement then resulted in four additional industry segments, two 200-mm waferprocessing segments (one fully and one partially abating each gas) and two 300-mm wafer-processing segment (one fully and the other partially abating each gas). Gas-specific emission uncertainties were estimated by convolving the distributions of unabated emissions with the appropriate distribution of abatement efficiency for fully and partially abated facilities using a Montel Carlo simulation. The uncertainty in E R,F-GHG is obtained by allocating the estimates of uncertainties to the total GHGRP-reported emissions from each of the six industry segments, and then running a Monte Carlo simulation which results in the 95 percent CI for emissions from GHGRP reporting facilities (E R,F-GHG). The uncertainty in E R,N2O is obtained by assuming that the uncertainty in the emissions reported by each of the GHGRP reporting facilities results from the uncertainty in quantity of N 2O consumed and the N 2O emission factor (or utilization). Similar to analyses completed for subpart I (see Technical Support for Modifications to the Fluorinated Greenhouse Gas Emission Estimation Method Option for Semiconductor Facilities under Subpart I, docket EPA–HQ–OAR–2011–0028), the uncertainty of N 2O consumed was assumed to be 20 percent. Consumption of N 2O for GHGRP reporting facilities was estimated by back- calculating from emissions reported and assuming no abatement. The quantity of N 2O utilized (the complement of the emission factor) was assumed to have a triangular distribution with a minimum value of zero percent, mode of 20 percent and maximum value of 84 percent. The minimum was selected based on physical limitations, the mode was set equivalent to the subpart I default N 2O utilization rate for chemical vapor deposition, and the maximum was set equal to the maximum utilization rate found in ISMI Analysis of Nitrous Oxide Survey Data (ISMI, 2009). The inputs were used to simulate emissions for each of the GHGRP reporting, N 2O-emitting facilities. The uncertainty for the total reported N 2O emissions was then estimated by combining the uncertainties of each of the facilities reported emissions using Monte Carlo simulation. The estimate of uncertainty in E NR,F-GHG and E NR,N2O entailed developing estimates of uncertainties for the emissions factors for each non-reporting sub-category and the corresponding estimates of TMLA. The uncertainty in TMLA depends on the uncertainty of two variables—an estimate of the uncertainty in the average annual capacity utilization for each level of production of fabs (e.g., full scale or R&D production) and a 69 On November 13, 2013, EPA published a final rule revising subpart I (Electronics Manufacturing) of the GHGRP (78 FR 68162). The revised rule includes updated default emission factors and updated default destruction and removal efficiencies that are slightly different from those that semiconductor manufacturers were required to use to report their 2012 emissions. The uncertainty analyses that were performed during the development of the revised rule focused on these updated defaults, but are expected to be reasonably representative of the uncertainties associated with the older defaults, particularly for estimates at the country level. (They may somewhat underestimate the uncertainties associated with the older defaults at the facility level.) For simplicity, the 2012 estimates are assumed to be unbiased although in some cases, the updated (and therefore more representative) defaults are higher or lower than the older defaults. Multiple models and sensitivity scenarios were run for the subpart I analysis. The uncertainty analysis presented here made use of the Input gas and wafer size model (Model 1) under the following conditions: Year = 2010, f = 20, n = SIA3. 4-98 DRAFT Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2015

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 corresponding estimate of the uncertainty in the number of layers manufactured. For both variables, the distributions of capacity utilizations and number of manufactured layers are assumed triangular for all categories of non-reporting fabs. For production fabs and for facilities that manufacture discrete devices, the most probable utilization is assumed to be 82 percent, with the highest and lowest utilization assumed to be 89 percent, and 70 percent, respectively. The most probable values for utilization for R&D facilities are assumed to be 20 percent, with the highest utilization at 30 percent, and the lowest utilization at 10 percent. For the triangular distributions that govern the number of possible layers manufactured, it is assumed the most probable value is one layer less than reported in the ITRS; the smallest number varied by technology generation between one and two layers less than given in the ITRS and largest number of layers corresponded to the figure given in the ITRS. The uncertainty bounds for the average capacity utilization and the number of layers manufactured are used as inputs in a separate Monte Carlo simulation to estimate the uncertainty around the TMLA of both individual facilities as well as the total non-reporting TMLA of each sub-population. The uncertainty around the emission factors for each non-reporting category of facilities is dependent on the uncertainty of the total emissions (MMT CO 2 Eq. units) and the TMLA of each reporting facility in that category. For each subpopulation of reporting facilities, total emissions were regressed on TMLA (with an intercept forced to zero) for 10,000 emissions and 10,000 TMLA values in a Monte Carlo simulation, which results in 10,000 total regression coefficients (emission factors). The 2.5th and the 97.5th percentile of these emission factors are determined and the bounds are assigned as the percent difference from the estimated emission factor. For simplicity, the results of the Monte Carlo simulations on the bounds of the gas- and wafer size-specific emissions as well as the TMLA and emission factors are assumed to be normally distributed and the uncertainty bounds are assigned at 1.96 standard deviations around the estimated mean. The departures from normality were observed to be small. The final step in estimating the uncertainty in emissions of non-reporting facilities is convolving the distribution of emission factors with the distribution of TMLA using Monte Carlo simulation. The results of the Approach 2 quantitative uncertainty analysis are summarized in Table 4-93, which is also obtained by convolving—using Monte Carlo simulation—the distributions of emissions for each reporting and non-reporting facility. The emissions estimate for total U.S. F-GHG and N 2O emissions from semiconductor manufacturing were estimated to be between 4.8 and 5.3 MMT CO 2 Eq. at a 95 percent confidence level. This range represents 5 percent below to 5 percent above the 2015 emission estimate of 5.0 MMT CO 2 Eq. This range and the associated percentages apply to the estimate of total emissions rather than those of individual gases. Uncertainties associated with individual gases will be somewhat higher than the aggregate, but were not explicitly modeled. Table 4-93: Approach 2 Quantitative Uncertainty Estimates for HFC, PFC, SF6, NF3 and N2O Emissions from Semiconductor Manufacture (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 b Upper Bound b Lower Bound Upper Bound Semiconductor HFC, PFC, SF6, Manufacture NF3, and N2O 5.0 4.8 5.3 -5% 5% a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval. b Absolute lower and upper bounds were calculated using the corresponding lower and upper bounds in percentages. 34 35 36 37 38 The emissions reported under EPA’s GHGRP for 2014 and 2015, which are included in the overall emissions estimated for 2014 and 2015, were based on an updated set of default emission factors. This may have affected the trend seen between 2013 and 2014 (a 13 percent increase), which reversed the trend seen between 2011 and 2013. As discussed in the Planned Improvements section, EPA is considering further analysis to determine how much, if any, of the 2013 to 2014 trend may be attributable to the updated factors. Industrial Processes and Product Use 4-99

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    a Emissions from Wood Biomass and E

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    1 2 Table 2-8: U.S. Greenhouse Gas

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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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    International Bunker Fuels a 0.2 0.

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    Fuel Oil 27.2 45.6 36.7 37.6 37.1 3

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

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    1 Table 3-20: Adjusted Consumption

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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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    2012 13.8 13,785 2013 14.0 14,028 2

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    Other Lands Converted Grassland Min

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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 Table 7-2: Emissions from Waste (

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    1 2 3 4 5 6 7 8 9 10 Table 7-6 pres

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    2013 321 10,536 2014 323 10,613 201

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    1 2 Table 7-16: Approach 2 Quantita

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    1 2 3 4 5 6 7 8 9 10 EF i = emissio

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    a Miscellaneous includes TSDFs (Tre

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    Enteric Fermentation NC NC + NC + (

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