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Regulatory Impact Analysis of the Waste
Emissions Charge
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EP A-430/R-24-007
November 2024
Regulatory Impact Analysis
of the Waste Emissions Charge
U.S. Environmental Protection Agency
Office of Atmospheric Protection
Climate Change Division
Washington, DC
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CONTACT INFORMATION
This document has been prepared by staff from the Office of Air and Radiation, U.S.
Environmental Protection Agency, and Research Triangle International, Inc. Questions related to
this document should be addressed to the Climate Change Division in the Office of Atmospheric
Protection (email: merp@epa.gov).
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TABLE OF CONTENTS
Table of Contents i
List of Tables iii
List of Figures v
1 Executive Summary 1-1
2 Background and Overview 2-1
2.1 Introduction 2-1
2.2 Statutory Requirements 2-1
2.3 Relationship to Other Requirements Impacting Methane Emissions 2-4
2.4 Economic Basis for the Rulemaking 2-6
2.5 Analysis Overview 2-7
2.6 Economic Significance 2-10
2.7 Transfers 2-10
2.8 Changes Between the Proposal and Final RIA 2-11
2.9 Organization of RIA 2-13
3 Baseline 3-1
3.1 Baseline Projection Approach 3-1
3.1.1 Base Year Emissions by Segment and Source 3-1
3.1.2 Baseline Projection Trends 3-3
3.1.3 Summary of Projections Methodology from NSPS/EG RIA 3-4
3.1.4 Baseline Emissions Results 3-5
4 WEC Scenario 4-1
4.1 Identification of Regulated Sources 4-1
4.1.1 Description of Applicability Standards 4-1
4.1.2 Identification of Applicable Facilities 4-2
4.1.3 Methodology for Projecting WEC-Applicable Emissions 4-4
5 Cost and Emissions Impacts 5-1
5.1 Costs of Methane Mitigation 5-1
5.2 Market Modeling 5-6
5.2.1 Model Description 5-6
5.2.2 Market Impacts 5-10
5.3 Emission Impacts 5-13
5.4 WEC Transfer Payments 5-16
6 Benefits 6-1
6.1 Climate Benefits Resulting from CH4 Emission Reductions 6-1
6.2 Health Effects Associated with Exposure to Non-GHG Pollutants 6-21
6.2.1 Ozone-Related Impacts Due to VOC Emissions 6-21
6.2.2 Ozone-Related Impacts Due to Methane 6-24
6.2.3 PM2 s-Related Impacts Due to VOC Emissions 6-25
6.2.4 Hazardous Air Pollutants (HAP) Impacts 6-27
7 Comparison of Benefits and Costs 7-1
7.1 Comparison of Benefits and Costs 7-1
7.2 Annual Benefits and Costs 7-2
7.3 Transfer Payments 7-5
7.4 Uncertainties and Limitations 7-7
l
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8 Uncertainty Analyses 8-1
8.1 Sensitivity on GHGRP Calculation Methods 8-1
8.1.1 Qualitative Factors in Sensitivity on GHGRP Calculation Methods 8-1
8.1.2 Quantitative Scenario of Sensitivity on GHGRP Calculation Methods 8-4
8.2 Sensitivity on Interaction with NSPS/EG 8-7
8.3 Sensitivity on Netting Scenarios 8-9
9 Distributional and Economic Analyses 9-1
9.1 Small Business Analysis 9-1
9.1.1 Background for Small Entity Impacts 9-1
9.1.2 Methodology for Calculating Small Entity Impacts 9-1
9.1.3 Results and Conclusions of Small Entity Impacts Analysis 9-6
9.2 Employment Impacts 9-8
9.2.1 Background 9-8
9.2.2 Employment Impacts 9-10
9.3 Environmental Justice 9-13
9.3.1 Introduction and Background 9-13
9.3.2 Scope and Limitations 9-15
9.3.3 Summary of Environmental Justice Findings of the NSPS/EG RIA 9-15
9.3.4 Environmental Justice Analysis of the Final WEC Rule 9-16
9.3.5 Aggregate Average Conditions for Potentially Affected Counties 9-20
9.4 The Distribution of Long-Term Climate Impacts 9-23
9.4.1 Environmental Justice Implications of Climate Change 9-23
9.4.2 Avoided U.S. Climate Impacts of the Final Rule 9-27
10 References 10-1
ANNEXES
Illustrative Screening Analysis of Monetized VOC-Related Ozone Health
Benefits A-l
Application of the Framework for Evaluating Damages and Impacts (FrEDI) to
Assess the Distribution of Avoided Climate-Driven Damages B-l
Additional Information on Marginal Abatement Cost (MAC) Modeling for
Analysis of Waste Emissions Charge C-l
11
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LIST OF TABLES
Table 1-1 Emissions Subject to the WEC 1-3
Table 1-2 Projected Emissions Reductions from the Final Waste Emissions Charge, 2024-2035 1-4
Table 1-3 Projected Net WEC Emissions and WEC Obligations in the Policy Scenario 1-5
Table 1-4 Projected Benefits and Costs from the Final Waste Emissions Charge 1-8
Table 1-5 Details of Projected WEC Obligations and Climate Damages from Emissions Subject to WEC 1-10
Table 2-1 Waste Emissions Thresholds by Industry Segment in CAA Section 136(f) 2-2
Table 3-1 Methane Emissions Reported to Subpart W Segments Subject to the WEC, By Source and Unit Type
(RY 2022) 3-2
Table 3-2 Projected CH4 Emissions Baseline of Emissions Reported to Subpart W 3-6
Table 4-1 Numbers of Subpart W Reporting Facilities, WEC Appliable Facilities, and Facilities with WEC
Applicable Emissions Greater than Zero By Industry Segment (Based on RY 2022) 4-3
Table 4-2 Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses 4-6
Table 4-3 Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2024 4-7
Table 4-4 Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2026 4-8
Table 4-5 Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2030 4-8
Table 5-1 Mitigation Costs 5-5
Table 5-2 Mitigation Cost Details 5-5
Table 5-3 Oil and Gas Markets Value and Quantity (2022) 5-7
Table 5-4 PE Model Elasticity Values 5-10
Table 5-5 PE Model Outcomes 5-12
Table 5-6 Cost of Energy Market Impacts 5-13
Table 5-7 Chemical Composition of Natural Gas by Weight by Segment 5-14
Table 5-8 Projected Annual Reductions of Methane, VOC, HAP Emissions from Economic Impacts 5-15
Table 5-9 Methane Mitigation Potential Details 5-16
Table 5-10 Projected WEC Payments in the Policy Scenario, 2024-2035 5-17
Table 6-2 Undiscounted Monetized Climate Benefits from Methane Mitigation under the WEC, 2024-2035 .. 6-14
Table 6-3 Undiscounted Monetized Climate Benefits from Partial Equilibrium Model under the WEC, 2024-2035
6-15
Table 6-4 Undiscounted Total Monetized Climate Benefits under the WEC, 2024-2035 6-15
Table 6-5 Discounted Monetized Climate Benefits under the WEC, 2024-2035 6-16
Table 6-6 Top Annual HAP Emissions as Reported in 2020 NEI for Oil and Natural Gas Sources 6-28
Table 7-1 Projected Emissions Reductions from the Final Waste Emissions Charge, 2024-2035 7-2
Table 7-2 Projected Benefits and Costs from the Final Waste Emissions Charge 7-2
Table 7-3 Projected Annual Emissions Reductions from the Final Waste Emissions Charge 7-4
Table 7-4 Summary of Annual Undiscounted Values, Present Values, and Equivalent Annualized Values for the
2024-2035 Timeframe for Estimated Incremental Abatement Costs, Benefits, and Net Benefits for
Final Rule 7-5
Table 7-5 Details of Projected WEC Obligations and Climate Damages from Emissions Subject to WEC 7-7
Table 8-1 Sensitivity of Emissions Exceeding Facility Waste Emissions Thresholds from GHGRP Revisions
Assuming Fixed Calculation Methods and Select New Sources 8-6
Table 8-2 Comparison of Estimated Emissions Subject to WEC across Netting Scenarios Before Accounting for
Mitigation or Market Responses 8-10
Table 8-3 Comparison of Illustrative Facilities Impacted across Netting Scenarios by Industry Segment 8-10
Table 8-4 Comparison of Emissions Reductions, Costs, and Benefits across Netting Scenarios 8-11
Table 9-1 Small Entity Cost-to-Revenue-Ratio Threshold Analysis Results 9-6
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Table 9-2 Employment in Oil and Gas Sectors (2022) 9-9
Table 9-3 Labor Compensation in the Oil and Gas Sector (2022) 9-10
Table 9-4 Employment Multipliers for Abatement Expenditures 9-12
Table 9-5 Employment Impacts of Compliance Expenditures and Output Changes 9-13
Table 9-6 Categorizing Category Emissions by Intensity 9-19
Table 9-7 Overall Demographic and Health Indicators for All Counties, by Category 9-22
Table A-l Summary of 2017 CAMx MDA8 ozone model performance for all April-September days A-3
Table A-2 Benefit-per-ton Estimates of Ozone-Attributable Premature Mortality and Illnesses for the WEC in
2019 Dollars A-10
Table A-3 Estimated Discounted Economic Value of Ozone-Attributable Premature Mortality and Illnesses under
the Final WEC, 2024-2035 A-11
Table A-4 Stream of Human Health Benefits under the Final WEC, 2024-2035: Monetized Benefits Quantified as
Sum of Avoided Morbidity Health Effects and Avoided Long-term Ozone Mortality A-l 1
Table A-5 Stream of Human Health Benefits under the Final WEC, 2024-2035: Monetized Benefits Quantified as
Sum of Avoided Morbidity Health Effects and Avoided Long-term Ozone Mortality A-12
Table A-6 Stream of Human Health Benefits under theFinal WEC, 2024-2035: Monetized Benefits Quantified as
Sum of Avoided Morbidity Health Effects and Avoided Long-term Ozone Mortality A-12
Table B-l Current FrEDI sectors, including aggregate category group, default adaptation assumptions, and
descriptions. Adapted from the FrEDI Technical Documentation B-7
Table B-2 Four socially vulnerable and reference groups considered here B-12
Table C-1 Calculation of Emission Reductions for a Mitigation Option C-2
Table C-2 Financial Assumptions in Break-Even Price Calculation for Mitigation Options C-5
Table C-3 Mitigation Technologies Included in WEC Analysis by Source Category C-8
Table C-4 Technology and Cost Inputs by Model Facility Size and Type for Zero Emissions Options in
Production; Gathering and Boosting; Transmission and Storage C-ll
Table C-5 Technology and Cost Inputs by Model Facility Size and Type Zero Emissions Options in Production;
Gathering and Boosting; Transmission and Storage C-12
Table C-6 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage C-14
Table C-7 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage C-15
Table C-8 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage C-16
Table C-9 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage C-17
Table C-10 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage C-19
Table C-11 Abatement Potential by Industry Segment and Source Type C-21
Table C-12 Abatement Potential and Mitigation Costs by Segment and Source, 2024 C-25
Table C-13 Abatement Potential and Mitigation Costs by Segment and Source, 2026 C-26
Table C-14 Abatement Potential and Mitigation Costs by Segment and Source, 2030 C-27
iv
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LIST OF FIGURES
Figure 5-1 Oil and Natural Gas MACC with WEC Payment Cost in 2025 5-3
Figure 9-1 Map of the counties identified as having emissions from facilities potentially subject to the Waste
Emissions Charge (2022) 9-17
Figure 9-2 Individual County Emissions Ranked from Lowest to Highest 9-20
Figure A-l Air Quality Modeling Domain A-2
Figure A-2 Climate Regions Used to Summarize 2017 CAMx Model Performance for Ozone A-3
Figure A-3 Map of 2017 CAMx MDA8 Normalized Mean Bias (%) for April-September at all U.S. monitoring
sites in the model domain A-4
Figure A-4 Contributions of 2017 Oil and Natural Gas VOC Emissions across the Contiguous U.S. to the April-
September Average of MDA8 Ozone A-6
Figure B-l Schematic of Analysis Workflow from emissions to damages B-4
Figure B-2 Relative avoided per capita climate driven impacts by sector and US region in 2100 B-10
Figure B-3 State share of annual average avoided U.S. climate-driven impacts in 2100 B-l 1
Figure B-4 Differential reductions in per capita climate-driven impacts in 2090 across socially vulnerable groups,
normalized to the changes in their reference populations B-14
Figure B-5 Per capita reductions in climate-driven impacts for six sectors in 2090, distributed by race and ethnicity.
B-15
Figure C-l Illustrative MAC Curve for Facilities with Emissions Subject to the WEC in the year 2025 C-7
Figure C-2 Total MAC Curve for WEC Applicable Segments of the Oil and Gas Industry in 2024 C-22
Figure C-3 Production Segment MAC Curve in 2024 C-23
Figure C-4 G&B and Processing Segments MAC Curve in 2024 C-23
Figure C-5 Transmission and Storage Segment MAC Curve in 2024 C-24
v
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1 EXECUTIVE SUMMARY
This executive summary presents the results of the U.S. Environmental Protection
Agency's (EPA) regulatory impact analysis (RIA) of the final rule implementing the methane
waste emissions charge (WEC) required under the Inflation Reduction Act (IRA). The RIA is
intended to provide the public with information on the relevant benefits and costs of this final
rulemaking and to comply with executive orders, as well as other potential impacts of the
rulemaking. This rulemaking details how EPA would implement the WEC according to the
specifications in the IRA. Specifically, the rule determines how the WEC will be calculated and
how the exemption and netting provisions will function.
The WEC does not directly require emissions reductions from applicable facilities or
emissions sources. However, by imposing a charge on methane emissions that exceed waste
emissions thresholds, oil and natural gas facilities subject to the WEC are expected to perform
methane mitigation actions and make operational changes where the costs of those changes are
less than the WEC payments that would be avoided by reducing methane emissions. In addition,
because volatile organic compound (VOC) and hazardous air pollutant (HAP) emissions are
emitted along with methane from oil and natural gas industry activities and are simultaneously
reduced by methane mitigation actions, reductions in methane emissions as a result of the WEC
also result in co-reductions of VOC and HAP emissions.
This RIA analyzes potential emissions changes and economic impacts of the WEC that
arise through two pathways: 1) through the application of cost-effective methane mitigation
technologies, and 2) through changes in oil and natural gas production resulting from the WEC
and associated mitigation responses. The analysis of methane mitigation is based on bottom-up
engineering cost and mitigation potential information for a range of methane mitigation
technologies. Application of methane mitigation technologies reduce WEC payments for WEC
obligated parties by reducing methane emissions compared to a baseline without additional
methane mitigation actions. The analysis assumes that methane mitigation is implemented where
the engineering control costs are less than the avoided WEC payments for a particular mitigation
technology.
Additionally, oil and natural gas firms may change their production and operational
decisions in response to the WEC. This potential impact is modeled using a partial equilibrium
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(PE) model of the crude oil and natural gas markets. The total cost of methane mitigation and
WEC payments is added as an increase to production costs, resulting in changes in equilibrium
production of oil and natural gas and associated emissions. Projected WEC payments are
estimated after methane emissions reductions from both methane mitigation and economic
impacts are accounted for.
The number of facilities that will owe WEC obligations, and the amount of those WEC
obligations, will ultimately depend on decisions that are within the control of owners and
operators, among other factors. However, the EPA estimates that only a relatively small
proportion of owner-operators of oil and gas facilities will owe WEC obligations. Using
emissions reported to subpart W for Reporting Year (RY) 2022 as an illustrative example,
approximately 250 companies would owe WEC obligations related to less than 400 facilities,
less than one-fifth of facilities that reported to subpart W. Based on RY2022, Table 1-1 shows
that the WEC would be imposed on less than 15 percent of national methane emissions from
petroleum and natural gas systems. Total methane emissions reported to the Greenhouse Gas
Reporting Program (GHGRP) subpart W are significantly less than national methane emissions
from the U.S. Greenhouse Gas Inventory for petroleum and natural gas systems. WEC-
applicable facilities are the subset of GHGRP facilities that report at least 25 thousand metric
tons CChe to subpart W segments subject to the WEC.
It is also important to note that the WEC would only apply to methane emissions that are
above the emissions threshold, not for all emissions from WEC-applicable facilities. The WEC
has exemptions related to regulatory compliance, emissions from plugged wells, and
unreasonable delay in environmental permitting, although these provisions do not impact the
illustrative results in Table 1-1. Finally, emissions subject to WEC accounts for netting of
emissions between facilities and entities under common ownership and control. Under the final
WEC, facilties with emissions below their emissions threshold may reduce emissions subject to
the WEC at other facilities with emissions above the threshold where those facilities are under
common ownership or control.
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Table 1-1
Emissions Subject to the WEC
CH4 emissions, 2022
(thousand metric
tons)
(MMTCChe with
GWP=28)
Petroleum and Natural Gas Systems National Total (GHGI)
GHGRP Subpart W
From WEC-applicable facilities (>25,000 mtCChe to W)
Facility emissions exceeding emissions threshold
Emissions subject to WEC, after netting
7,900
2,600
1,900
970
730
220
72
54
27
20
The benefit-cost analysis contained in this RIA for the WEC considers the potential
benefits and costs of the WEC arising from cost-effective mitigation actions under the WEC as
well as the potential transfers from affected operators to the government in payments. Costs
include engineering costs for methane mitigation actions and costs resulting from production
changes in oil and natural gas markets under the rule. While EPA expects a range of health and
environmental benefits from reductions in methane, VOC, and HAP emissions under the WEC,
the monetized benefits of the rule are limited to the estimated climate benefits from projected
methane emissions reductions. These benefit estimates are based on the social cost of methane
(SC-CH4). A screening-level analysis of ozone-related benefits from projected VOC reductions
can be found in Appendix A of the RIA. However, these estimates are treated as illustrative and
are not included in the quantified benefit-cost comparisons in the RIA.
The EPA estimates that this action will result in cumulative emissions reductions of 1.2
million metric tons of methane over the 2024 to 2035 period. These reductions represent about
40 percent of methane emissions that would be subject to the WEC before accounting for the
adoption of cost-effective emission reduction technologies. Virtually all the reduced emissions
result from mitigation activities undertaken by industry to reduce WEC payments. Less than one
percent of the estimated reductions is associated with decreased production activity in the oil and
natural gas sector resulting from the final rule. In addition to methane emissions reductions, the
WEC is estimated to result in reductions of 170 thousand metric tons of VOC and 6 thousand
metric tons of HAP over the 2024 to 2035 period.
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Table 1-2 Projected Emissions Reductions from the Final Waste Emissions Charge,
2024-2035
Emission Changes
Methane
Methane
VOC
HAP
(million metric tons
(thousand metric
(thousand metric
(thousand metric
CO2 Eq. using
tons)
tons)
tons)
GWP=28)
Total
1,200
170
6
34
The WEC has important interactions and is designed to work hand-in-hand with the New
Source Performance Standards OOOOb and Emissions Guidelines 0000c for the Oil and
Natural Gas Sector (NSPS/EG) by accelerating the adoption of cost-effective methane mitigation
technologies, including those that would eventually be required under the NSPS OOOOb or EG
0000c. The annual projected emissions reductions, costs, and WEC obligations are
significantly affected by these interactions.
The EPA finalized updates to the Oil and Gas NSPS/EG in March 2024. In addition to
requirements already in place, these rules include standards for many of the major sources of
methane emissions in the oil and natural gas industry. To avoid double counting of benefits and
costs, the baseline for this analysis includes reductions resulting from the 2024 Final NSPS/EG
based on information from the Final RIA for that rule (available in Docket No. EPA-HQ-OAR-
2021-0317). Specifically, that analysis showed gradually increasing reductions in methane
emissions resulting from the NSPS and deep reductions in methane emissions reductions
beginning to take effect in 2028 as a result of the EG 0000c. As facilities implement emission
controls required by the NSPS/EG, emissions subject to the WEC decline.
The second interaction between the WEC and the Oil and Gas NSPS/EG is the regulatory
compliance exemption provision of the WEC. Under this provision, when certain conditions are
met with respect to the implementation of the Oil and Natural Gas NSPS/EG, applicable
facilities in compliance with the NSPS/EG are exempted from the WEC. The analysis in this
RIA assumes that the regulatory compliance exemption takes effect in 2029, such that, in 2029
and later, facilities in the industry segments subject to requirements under the NSPS/EG do not
owe WEC payments. This assumption is based on an assumed timeline under which the
conditions of the regulatory compliance exemption could be met. The timing of the regulatory
compliance exemption availability will vary by state. As timing for any individual state is
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unknown, this RIA analysis assumes that the regulatory compliance exemption becomes
available for all relevant facilities in 2029.
Projected methane emissions subject to WEC after accounting for methane mitigation
and energy market impacts are estimated to be about 600 thousand metric tons in 2024, and then
drop significantly as reductions from the EG OOOOc are implemented in 2028 and the
regulatory compliance exemption takes effect in 2029. Table 1-3 provides projected WEC-
applicable emissions in the baseline and policy scenario.
Table 1-3 Projected Net WEC Emissions and WEC Obligations in the Policy Scenario
Methane Emissions
Reductions from
Methane Mitigation
(thousand metric
tons)
Reductions from
Methane Emissions
Year
Subject to WEC in
Baseline
(thousand metric
tons)
Energy Market
Impacts
(thousand metric
tons)
Subject to WEC in
Policy Scenario
(thousand metric
tons)
2024
710
110
0.1
600
2025
680
220
0.1
460
2026
650
310
1.7
340
2027
630
310
1.6
320
2028
77
42
0.0
35
2029
34
30
0.0
3.2
2030
33
31
0.0
2.9
2031
33
31
0.0
2.7
2032
33
31
0.0
2.4
2033
33
31
0.0
2.0
2034
32
31
0.0
1.7
2035
32
31
0.0
1.4
Total 2024-2035
3,000
1,200
3.7
1,800
Climate benefits associated with this final rule are monetized using estimates of the social
cost of methane (SC-CH4) which calculates the avoided climate related damages from reducing
methane emissions. Methane is the principal component of natural gas. As a potent GHG,
methane absorbs terrestrial infrared radiation once emitted into the atmosphere, which in turn
contributes to increased global warming and continuing climate change. Methane reacts in the
atmosphere to form ozone, which also impacts global temperatures. In addition to other GHG
emissions, methane contributes to warming of the atmosphere, which over time leads to
increased air and ocean temperatures, changes in precipitation patterns, melting and thawing of
global glaciers and ice sheets, increasingly severe weather events, such as hurricanes of greater
intensity, and sea level rise, among other impacts.
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This final rulemaking is projected to reduce VOC emissions, which are a precursor to
ozone. Ozone is not generally emitted directly into the atmosphere but is created when its two
primary precursors, VOC and oxides of nitrogen (NOx), react in the atmosphere in the presence
of sunlight. Emissions reductions under the WEC may decrease ozone formation, human
exposure to ozone, and the incidence of ozone-related health effects. VOC emissions are also a
precursor to fine particulate matter (PM2.5), so VOC reductions may also decrease human
exposure to PM2.5 and the incidence of PM2.5- related health effects.
Available emissions data show that several different HAP are emitted from oil and
natural gas operations. Emissions of eight HAP make up a large percentage of the total HAP
emissions by mass from the oil and natural gas sector: toluene, hexane, benzene, xylenes
(mixed), ethylene glycol, methanol, ethyl benzene, and 2,2,4- trimethylpentane (U.S. EPA,
201 lb). Reductions of HAP emissions under the WEC may reduce exposure to these and other
HAP.
In Section 9.3 of the RIA, EPA identifies existing potential environmental justice issues
for the communities in counties that have emissions sources that are expected to owe the WEC
charge and thus may be positively affected by emissions changes under the rule. Compared to the
national average, these communities include a higher percentage of individuals who identify as
racial and ethnic minorities, have lower average incomes, and have slightly elevated health risks
associated with various air emissions. Reductions in VOC and HAP emissions as a result of the
WEC are expected to benefit communities in these counties. Because the WEC does not directly
require emissions reductions, EPA has not projected specific locations that emissions reductions
might occur. In addition, detailed proximity analysis is infeasible because the emissions affected
by the WEC occur at hundreds of thousands of locations.
The total cost of the final rule includes the engineering costs for methane mitigation
actions implemented by the oil and natural gas industry to reduce WEC obligations. Costs for
methane mitigation are calculated on an annualized basis, with total costs spread over the
expected lifetime. This includes the initial capital costs required to implement and install the
specific mitigation technology. In addition, for mitigation technologies with expected lifetimes
greater than one-year, annual recurring operations and maintenance (O&M) costs which include
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labor, energy and materials are also incorporated. Finally, the total mitigation costs also include
the avoided cost of natural gas losses.
The social cost of energy market impacts is the loss in consumer and producer surplus
value from changes in natural gas market production and prices. The economic impacts analysis
uses a partial equilibrium model and estimates that the impact of the gas market is minimal, with
the largest impact occurring in the first few years with a price increase of less than 0.1% and a
quantity reduction of less than 0.1%.
Table 1-4 presents results of the benefit-cost analysis for the final WEC. The table
presents the present value (PV) and equivalent annual value (EAV), estimated using discount
rates of 2, 3, and 7 percent, of the changes in quantified benefits, costs, and net benefits relative
to the baseline.1 These values reflect an analytical time horizon of 2024 to 2035, are discounted
to 2023, and are presented in 2019 constant dollars. The table includes consideration of the non-
monetized benefits associated with the emissions reductions projected under this rule.2
1 Monetized climate effects are presented under a 2 percent near-term Ramsey discount rate, consistent with EPA's
updated estimates of the SC-GHG. The 2003 version of OMB 's Circular A-4 had generally recommended 3
percent and 7 percent as default discount rates for costs and benefits, though as part of the Interagency Working
Group on the Social Cost of Greenhouse Gases, OMB had also long recognized that climate effects should be
discounted only at appropriate consumption-based discount rates. While this RIA was being drafted, OMB
finalized an update to Circular A-4, in which it recommended the general application of a 2.0 percent discount
rate to costs and benefits (subject to regular updates), as well as the consideration of the shadow price of capital
when costs or benefits are likely to accrue to capital (OMB 2023). Because the SC-GHG estimates reflect net
climate change damages in terms of reduced consumption (or monetary consumption equivalents), the use of the
discount rate estimated using the average return on capital (7 percent in OMB Circular A-4 (2003)) to discount
damages estimated in terms of reduced consumption would inappropriately underestimate the impacts of climate
change for the purposes of estimating the SC-GHG. See Section 6.1 for more discussion.
2 As discussed in Section 6 of this RIA, the monetized benefits estimates provide an incomplete overview of the
beneficial impacts of the rule. In particular, the monetized climate benefits are incomplete and an underestimate
as explained in Section 6.1. In addition, important health and welfare benefits anticipated under these rules are not
quantified or monetized. EPA anticipates that taking non-monetized effects into account would show the rule to
have greater benefit than the tables in this section reflect. Simultaneously, the estimates of costs used in the net
benefits analysis may provide an incomplete characterization of the true costs of the rule. The balance of
unqualified benefits and costs is ambiguous but we believe is unlikely to change the result that the benefits of
the rule exceed the costs.
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Table 1-4 Projected Benefits and Costs from the Final Waste Emissions Charge
(million 2019$)
PV
2 Percent Near-Term Ramsey Discount Rate
EAV
PV
EAV
PV
EAV
Monetized Climate Benefits3
$2,400
$230
$2,400
$230
$2,400
$230
2 Percent
Discount Rate
3 Percent
Discount Rate
7 Percent
Discount Rate
PV
EAV
PV
EAV
PV
EAV
Total Social Costs
$460
$43
$440
$44
$380
$48
Cost of Methane Mitigation
$420
$40
$400
$41
$350
$44
Cost of Energy Market Impacts
$39
$4
$38
$4
$33
$4
Net Benefits'3
$1,900
$190
$2,000
$190
$2,000
$180
Ozone benefits from reducing 1.2 million metric tons of methane from
2024 to 2035
PM2.5 and ozone health benefits from reducing 170 thousand metric
tons of VOC from 2024 to 2035
Non-Monetized Benefits
HAP benefits from reducing 6 metric tons of HAP from 2024 to 2035
Visibility benefits
Reduced vegetation effects
a Monetized climate benefits are based on reductions in methane emissions and are calculated using three different
estimates of the social cost of methane (SC-CH4) (under 1.5 percent, 2.0 percent, and 2.5 percent near-term
Ramsey discount rates). For the presentational purposes of this table, we show the climate benefits associated with
the SC-CH4 at the 2 percent near-term Ramsey discount rate. Please see Table 6-5 for the full range of monetized
climate benefit estimates.
b Several categories of climate, human health, and welfare benefits from methane, VOC, and HAP emissions
reductions remain unmonetized and are thus not directly reflected in the quantified benefit estimates in the table.
See Section 6.1 for a discussion of climate effects that are not yet reflected in the SC-CH4 and thus remain
unmonetized and Section 6.2 for a discussion of other non-monetized benefits. A screening-level analysis of ozone
benefits from VOC reductions can be found in Appendix A of the RIA.
WEC payments are transfers and do not affect total net benefits to society as a whole
because payments by oil and natural gas operators are offset by receipts by the government.
Therefore, from a net-benefit accounting perspective, transfers are considered separately from
costs and benefits (and are therefore not included in Table 1-4). As explained further in Section
2.7, the approach taken here is in line with OMB guidance and the approach taken for RIAs for
other rules impacting payments to the government, such as the Bureau of Land Management
(BLM)'s waste prevention rule.
One of the reasons that transfers are not considered costs is because they represent
payments to the U.S. Treasury that do not affect total resources available to society. Payments to
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the U.S. Treasury can then be used to fund other programs, and the pairing of revenue collection
(e.g., the WEC payments) with commensurate expenditures (e.g., financial assistance programs)
by the federal government can be designed to be revenue neutral. The Methane Emission
Reduction Program created under CAA section 136 includes both collection and expenditure
components. In addition to establishing the WEC, another key purpose of CAA section 136 is to
encourage the transition to available and innovative methane emissions reduction technologies.
See 168 Cong. Rec. E869 (August 23, 2022) (statement of Rep. Frank Pallone). CAA section
136(a) and (b) provides financial and technical assistance to reduce methane emissions from the
oil and gas sector. To implement this program, EPA is partnering with the U.S. Department of
Energy (DOE) to provide up to $1.36 billion in financial and technical assistance. As designed
by Congress, these resources and incentives were intended to complement the regulatory
programs and to help facilitate the transition to a more efficient petroleum and natural gas
industry. These incentives for methane mitigation and monitoring complement the WEC.
The WEC has the effect of better aligning the economic incentives of oil and natural gas
companies with the costs and benefits faced by society from oil and gas activities. In the baseline
scenario the environmental damages resulting from methane emissions from the oil and gas
sector are a negative externality spread across society as a whole. Under the WEC, this negative
externality is internalized, oil and gas companies are required to make WEC payments in
proportion to the climate damages of methane emissions subject to the WEC.3 Alternatively,
firms can avoid making WEC payments by mitigating their emissions generating climate benefits
associated with the amount of mitigation.
Table 1-5 provides details of the calculation steps used to estimate projected WEC
obligations and climate damages based on projected emission subject to WEC. In order to
compare projected WEC payments to climate damages from emissions subject to the WEC,
WEC payments are converted from nominal dollars to 2019 constant dollars using a chain-
weighted GDP price index from the 2023 Annual Energy Outlook (EIA, 2023a).
3 Note that Congress specified that the WEC would rise to $1,500 per metric ton of methane in 2026 and beyond.
This value is consistent with estimates of climate damages associated with emissions of a metric ton of methane
that were available at the time the IRA was passed. The February 2021, 'Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates under Executive Order 13990,' estimated that the
social cost of CH4 under a 3% discount rate for emissions occuring in the year 2020 was $1,500.
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Table 1-5 Details of Projected WEC Obligations and Climate Damages from Emissions
Subject to WEC (million 2019$)
Year
Methane
Emissions
Subject to
WEC in Policy
Scenariob
(thousand
metric tons)
Charge
Specified
by
Congress
(nominal $
per metric
ton)
WEC
Payments
in Policy
Scenario
(million
nominal $)
WEC
Payments
in Policy
Scenario
(million
2019$)
SC-CH4
Values
under 2%
Near-Term
Discount
Rate (2019$
per metric
ton)
Climate
Damages
from
Emissions
Subject to
WEC (million
2019$)a
2024
600
$900
$540
$450
$1,900
$1,200
2025
460
$1,200
$560
$450
$2,000
$930
2026
340
$1,500
$510
$400
$2,100
$700
2027
320
$1,500
$480
$380
$2,200
$690
2028
35
$1,500
$52
$40
$2,200
$77
2029
3
$1,500
$5
$4
$2,300
$7
2030
3
$1,500
$4
$3
$2,400
$7
2031
3
$1,500
$4
$3
$2,500
$7
2032
2
$1,500
$4
$3
$2,500
$6
2033
2
$1,500
$3
$3
$2,600
$5
2034
2
$1,500
$3
$2
$2,700
$5
2035
1
$1,500
$2
$1
$2,800
$4
Total
2024-
1,800
$2,200
$1,700
$3,600
2035
a Climate damages are based on remaining methane emissions subject to WEC after accounting for emissions
reductions and are calculated using three different estimates of the social cost of methane (SC-CH4) (under 1.5
percent, 2.0 percent, and 2.5 percent near-term Ramsey discount rates). For the presentational purposes of this
table, we show the climate benefits associated with the SC-CH4 at the 2 percent near-term Ramsey discount rate.
b The decrease in methane emission subject to WEC in the policy scenario over time is due to combination of
reductions in the baseline including those resulting from the 2024 Final NSPS/EG as well as responses to the
WEC. In particular, the baseline assumes deep reductions in methane emissions beginning to take effect in 2028 as
a result of the EG OOOOc.
Compared to the analysis presented in the RIA for the January 2024 WEC proposal, this
analysis reflects some updates to methodologies used to project impacts reflecting changes in the
final regulations relative to the proposal and updated available data. This analysis incorporates
broader allowance for netting among owner-operators that share a common parent company,
updates to requirements of the regulatory compliance exemption, and updated base year data
from GHGRP for 2022.
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2 BACKGROUND AND OVERVIEW
2.1 Introduction
This document presents the regulatory impact analysis (RIA) for the notice of final
rulemaking titled "Waste Emissions Charge for Petroleum and Natural Gas Systems." The final
rulemaking implements a waste emissions charge (WEC) for methane (CH4) emissions that are
reported by applicable facilities to EPA under Greenhouse Gas Reporting Program (GHGRP)
subpart W and exceed emissions intensity thresholds. The rulemaking responds to requirements
from the Inflation Reduction Act.
2.2 Statutory Requirements
This section describes the legal basis for the final WEC. The Inflation Reduction Act
(IRA), signed into law on August 16, 2022, introduced new requirements for methane emissions
from petroleum and natural gas systems, including a Waste Emission Charge (WEC). EPA
proposed regulations implementing the WEC in January 2024. Section 60113 of the Inflation
Reduction Act added section 136 to the CAA, entitled "Methane Emissions and Waste Reduction
Incentive Program for Petroleum and Natural Gas Systems." Section 136(c) of the CAA, "Waste
Emissions Charge, states, "The Administrator shall impose and collect a charge on methane
emissions that exceed an applicable waste emissions threshold under subsection (f) from an
owner or operator of an applicable facility that reports more than 25,000 metric tons of carbon
dioxide equivalent of greenhouse gases emitted per year pursuant to subpart W of part 98 of title
40, Code of Federal Regulations, regardless of the reporting threshold under that subpart." Other
key sections of the CAA that define the requirements of the methane emissions and waste
reduction incentive program include the following:
• Section 136(d) of the CAA, "Applicable Facility," defines the term applicable facility
for the purposes of section 136.
• CAA section 136(e), "Charge Amount," specifies that the waste emissions charge is
determined by multiplying methane emissions reported to subpart W by specified
charge rates for calendar year 2024, calendar year 2025, and calendar year 2026 and
each year thereafter.
• CAA section 136(f), "Waste Emissions Threshold," establishes the thresholds by
industry segment above which the EPA must impose and collect the CH4 emissions
charge. The subsection also provides that the EPA shall allow for the netting of
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emissions for certain facilities under common ownership or control and provides for
several exemptions from charges.
• CAA section 136(g) mandates that the waste emissions charge shall be imposed and
collected beginning with respect to emissions reported for calendar year 2024 and for
each year thereafter.
The charge per metric ton of methane emitted in excess of the facility waste emissions
threshold increases according to the following schedule, as specified in the IRA: $900 in
calendar year 2024, $1,200 in 2025, and $1,500 in 2026 and beyond. Thresholds are set based on
industry segments and activities conducted at the facility. The waste emissions threshold is a
facility-specific amount of metric tons of methane emissions calculated using the relevant
intensity thresholds specified by Congress and a facility's natural gas throughput (or oil
throughput in certain circumstances); facilities that have methane emissions below the threshold
would not be required to pay the charge. It is also important to note that the WEC only applies to
the subset of methane emissions that are above the emission threshold, not for a facility's total
methane emissions. The emission thresholds for each industry are segment-specific and are
specified in CAA section 136(f), which are shown in Table 2-1
Table 2-1 Waste Emissions Thresholds by Industry Segment in CAA Section 136(f)
Applicable Waste Emissions Threshold, Calculated
Industry Segments as the Metric Tons of Methane Emissions Equal to:
Onshore petroleum and natural gas production 0.20 percent of the natural gas sent to sale from the
Offshore petroleum and natural gas production facility; OR
10 metric tons of methane per million barrels of oil
sent to sale from such facility, if the facility sent no
natural gas to sale
Onshore petroleum and natural gas gathering and 0.05 percent of the natural gas sent to sale from or
boosting through the facility
Onshore natural gas processing
Liquefied natural gas storage
Liquefied natural gas import and export equipment
Onshore natural gas transmission compression 0.11 percent of the natural gas sent to sale from or
Underground natural gas storage through the facility
Onshore natural gas transmission pipeline
The EPA is establishing provisions for the WEC at 40 CFR part 99 consistent with the
authority and directives set forth in CAA section 136(c) through (g). This final rulemaking is
hereafter referred to as the "WEC final rule."
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For petroleum and natural gas systems, the Greenhouse Gas Reporting Program currently
requires that owners or operators of facilities that emit 25,000 metric tons (mt) or more of
greenhouse gases (GHGs) per year in combined emissions from all applicable source categories
(expressed as carbon dioxide equivalents (CChe)) must report GHG data to the GHGRP
according to the requirements of subpart W. Subpart W applies to each of the following ten
industry segments:
• Onshore Petroleum and Natural Gas Production: Production of petroleum and
natural gas associated with onshore production wells and related equipment.
• Offshore Petroleum and Natural Gas Production: Production of petroleum and
natural gas from offshore production platforms.
• Onshore Petroleum and Natural Gas Gathering and Boosting: Gathering
pipelines and other equipment used to collect petroleum/natural gas from onshore
production gas or oil wells and used to compress, dehydrate, sweeten, or transport the
petroleum/natural gas.
• Onshore Natural Gas Processing: Processing of field-quality gas to produce
pipeline-quality natural gas, processing plants that fractionate gas liquids, and
processing plants that do not fractionate gas liquids but have an annual average
throughput of 25 million standard cubic feet per day (MMscf/day) or greater.
• Onshore Natural Gas Transmission Compression: Compressor stations used to
transfer natural gas through transmission pipelines.
• Onshore Natural Gas Transmission Pipeline: All natural gas transmission pipelines
as defined in §98.238 (a rate-regulated interstate or intrastate pipeline, or a pipeline
that falls under the "Hinshaw Exemption" of the Natural Gas Act).
• Underground Natural Gas Storage: Facilities that store natural gas in underground
formations.
• Liquefied Natural Gas (LNG) Storage: LNG storage equipment.
• LNG Import/Export: LNG import and export terminals.
• Natural Gas Distribution: Distribution systems that deliver natural gas to
customers.4
Consistent with Section 136(d) of the CAA, we are defining a "WEC applicable facility"
as a facility within nine of the ten industry segments subject to subpart W, as currently defined in
40 CFR 98.230 and listed above (i.e., all subpart W industry segments except natural gas
distribution) for which the owner or operator of the subpart W reporting facility reports subpart
W emissions of more than 25,000 metric tons CChe. The WEC would be imposed for each WEC
4 The Natural Gas Distribution segment is not included in CAA section 136 and is therefore not discussed further in
this document.
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obligated party, which is defined in the final rule as the owners or operators of one or more WEC
applicable facilities.
2.3 Relationship to Other Requirements Impacting Methane Emissions
In addition to the Waste Emissions Charge, the EPA is currently undertaking several
other actions that impact methane emissions from the oil and natural gas industry, and therefore
influence the results presented in this RIA. In particular, the WEC has important interactions
with revisions to GHGRP subpart W and the Oil and Gas New Source Performance Standards
OOOOb and Emissions Guidelines 0000c (NSPS/EG) for the Oil and Natural Gas Sector.
The Inflation Reduction Act mandates that the WEC calculations be based on methane
emissions reported to GHGRP subpart W. Section 136(h) of the CAA requires that the EPA
revise the requirements of subpart W within two years after the date of enactment of section
60113 of the IRA to ensure that WEC calculations "are based on empirical data, ... accurately
reflect the total methane emissions and waste emissions from the applicable facilities, and allow
owners and operators of applicable facilities to submit empirical emissions data, in manner to
prescribed by the Administrator..." On May 14, 2024, the EPA finalized revisions to the
requirements of subpart W consistent with those directives (88 FR 50282). Those revisions will
be used to report emissions to GHGRP and impact the resulting WEC calculations. However,
reporters will implement the majority of the changes beginning with reports prepared for
Reporting Year (RY) 2025, which are due March 31, 2026. Because CAA section 136(c)
requires the Administrator to impose and collect the WEC beginning with emissions as reported
for calendar year 2024, the first year that the WEC will be collected will be based on the
provisions of subpart W applicable to 2024.5 The analysis in this RIA is based on historical
reported emissions for RY2022 and previous methods and factors rather than the recent
revisions.
The GHGRP subpart W revisions make changes that may significantly affect reported
emissions, but the specific changes are difficult to estimate, particularly at the specificity needed
5 Where the GHGRP revisions include changes in reporting requirements, those requirements generally begin with
RY2025. However, some new calculation methods may optionally be used by reporters for the 2024 reporting
year, so reported methane for 2024 may include a mix of reported emissions using previously existing and
updated calculation methods.
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to estimate WEC payments. For example, the revisions add a new emissions source, "other large
release events." Other large release events are believed to occur sporadically at a minority of
facilities, but with potentially significant emissions when they occur.6 The EPA also has
finalized revisions to add new calculation methods incorporating additional empirical data and
measurements. Calculation methods based on facility- or company-specific measurements may
lead to significantly different emissions reported depending on the particular conditions at each
facility. In order to estimate WEC payments, reported emissions for each facility and WEC
obligated party must be compared against waste emissions thresholds. In lieu of highly uncertain
estimates of how revised GHGRP methods may impact reported emissions, the calculations in
this RIA are mainly based on current reported emissions. Section 8.1 includes a qualitative
discussion of potential sensitivity of this analysis to changes in reported emissions from GHGRP
subpart W revisions.
The WEC also has important interactions and is designed to work hand-in-hand with the
Oil and Gas NSPS/EG. The EPA proposed updates to the Oil and Gas NSPS/EG in 2021,
published a supplemental proposal in 2022, and finalized in March 2024. In addition to
requirements already in place, these rules include standards for many of the major sources of
methane emissions in the oil and natural gas industry. The 2024 Final NSPS/EG includes new
requirements for new and modified facilities and requirements for existing sources, which are to
be implemented by the states via state regulations and state plans. The first way that the WEC
interacts with the NSPS/EG is the significant overlap in the emissions impacted by the two
policies. Some oil and gas operations are subject to emissions reporting under GHGRP subpart
W and are also subject to the requirements of the NSPS/EG. As WEC obligated parties
implement the emissions controls required by the NSPS/EG, the resulting reduced emissions
would also mean reduced WEC payments. This RIA accounts for this interaction by including
the emissions reduction impacts of the 2024 Final Oil and Gas NSPS/EG in the baseline
scenario.
6 EPA does not have an estimate of the quantity of emissions which may be reported under the source category.
Discussion of available information in included in section 8.1. EPA described available information regarding
some event types, such as well blowouts, in section 3 of the technical support document for the GHGRP subpart
W revisions, available here: https://www.reguiations.gov/document/EPA-HO-QAR-2023-0234-0163
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The second interaction between the WEC and NSPS/EG is the regulatory compliance
exemption provision of the WEC. Under this provision, when certain conditions are met with
respect to the implementation of the Oil and Gas NSPS/EG, applicable facilities in compliance
with the NSPS OOOOb and EG 0000c requirements that would otherwise be subject to charge
are exempted from the WEC. The analysis in this RIA assumes that the regulatory compliance
exemption provision takes effect in 2029, such that in 2029 and later, facilities in the industry
segments subject to requirements under the NSPS/EG do not owe WEC payments.7 The 2024
Final Oil and Natural Gas NSPS/EG lays out the timing for state plan submission. Under the EG
0000c, states have 24 months to submit their state plans, and EPA must approve or deny state
plans within 12 months. Requirements under state plans generally phase-in over several years.
For the purpose of this analysis, the EPA has assumed that the regulatory compliance exemption
would be available starting in 2029, reflecting that plans could be effective as early as January
2027, and assuming that requirements phase in over 2027 to 2029. As finalized, the regulatory
compliance exemption applies on a state-by-state basis and the availability of the regulatory
compliance exemption will vary according to plan approval and implementation schedules. As
described in Section 2.8, the timing for individual states is unknown, therefore the RIA assumes
that the regulatory compliance exemption becomes available for all relevant facilities in 2029.
2.4 Economic Basis for the Rulemaking
This section describes the economic rationale for the final WEC. Market failures occur
when free market interactions lead to a suboptimal allocation of resources. The core market
failure addressed by section 136 (c) of the Inflation Reduction Act is the externality of climate
damage from methane emissions. As described in more detail in the Regulatory Impact Analysis
of the Supplemental Proposal for the Standards of Performance for New, Reconstructed, and
Modified Sources and Emissions Guidelines for Existing Sources: Oil and Natural Gas Sector
Climate Review, producers contribute to climate change when extracting, processing, and
transporting petroleum and natural gas products. The producers spread the costs of these actions
7 The analysis in this RIA assumes that all facilities in the industry segments subject to NSPS/EG requirements are
eligible for the regulatory compliance exemption in 2029 and thereafter. We recognize that not all facilities will
be eligible because of compliance issues. However, EPA does not have the capability to predict how many
facilities this situation will affect. Furthermore, the existence of the regulatory compliance provision may have a
beneficial effect on regulatory compliance. The assumption of full compliance is a simplifying assumption for
analysis purposes.
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to society as a whole by lowering the availability of public goods, such as better air quality or
less severe effects of climate change, while reaping the financial benefits themselves.
The WEC attempts to address the market failure by imposing a charge on petroleum and
natural gas producers that emit above a certain threshold of methane. In the absence of the WEC,
the discrepancy in public and private costs means the socially optimal level of methane
emissions is misaligned with the optimal level of methane emissions for petroleum and natural
gas facilities operated by private companies. The final WEC attempts to bring the level of
methane emissions that is optimal for producers in the oil and gas sector closer to the socially
optimal level of methane emissions. Through this policy, oil and natural gas companies subject
to the WEC internalize costs associated with environmental damages of remaining methane
emissions. The WEC properly aligns private incentives: to the extent that companies subject to
the WEC are able to mitigate their emissions, they can both reduce WEC payments and the
environmental damages that result from emissions. In the absence of environmental policies, oil
and natural gas producers may have some economic incentives to mitigate some fugitive
methane emissions because those emissions represent loss of a saleable product, natural gas.
Where mitigation actions cost less than expected revenue from recovered natural gas, a
substantial portion of those actions are likely to be taken up voluntarily. However, this product
revenue incentive does not account for external environmental damages. Where the mitigation
costs exceed expected product revenue, energy market incentives alone would not likely be
sufficient to induce socially optimal mitigation actions. Estimation of breakeven costs for
methane mitigation actions is further discussed in section 5. Furthermore, as described in section
7, total projected WEC payments are less than the total projected damages associated with
emissions subject to the WEC.
2.5 Analysis Overview
As described in section 2.2, CAA section 136(c) states that a WEC will be levied on
methane emissions that exceed statutorily specified waste emissions thresholds from an owner or
operator of an applicable facility. The waste emissions threshold is a methane intensity metric,
therefore facilities that have methane emissions per unit of throughput below the threshold would
not be required to pay the charge. The WEC only applies to the subset of a facility's emissions
that are above the waste emissions threshold. As explained in section 2.4, the economic effect of
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the WEC is to better align private incentives to reduce emissions that cause external
environmental damages.
For this analysis it is assumed that the applicable facilities facing the WEC on emissions
that exceed the waste emissions threshold will make an economic choice to invest in mitigation
measures that reduce their emissions, thereby reducing the WEC obligation. While many
facilities will likely find it less expensive to reduce their emissions via mitigation technology,
there will be facilities where the cost of reducing emissions is higher than the WEC charges. In
the latter case, it is assumed that the facility will elect to pay the WEC rather than invest in more
costly mitigation technology.
Additionally, oil and natural gas firms may change their production and operational
decisions in response to the WEC. This potential impact is modeled using a partial equilibrium
(PE) model of the crude oil and natural gas markets. The total cost of methane mitigation and
WEC payments is added as an increase to production costs, resulting in changes in equilibrium
production of oil and natural gas and associated emissions. This change in production produces a
loss in consumer and producer surplus in the oil and gas market, referred to as 'costs of energy
market impacts' in this RIA.
Projected WEC payments are estimated after methane emissions reductions from both
methane mitigation by applicable facilities and economic impacts in the oil and gas markets are
accounted for. WEC payments are not social costs. They are transfers that do not affect net
benefits because the payments by oil and natural gas operators are received as benefits by the
government. Total social costs are the sum of two components, the mitigation costs, and the costs
of energy market impacts (loss in consumer and producer surplus). Mitigation costs reflect cost-
effective methane reduction from applicable facilities when the cost per ton of the mitigation
technology is less than the WEC. The energy market impacts reflect the reduction in oil and gas
production from the WEC.
The regulatory impacts of the final WEC are evaluated relative to a baseline that
represents the oil and gas industry in the absence of this finalized action. To avoid double
counting of costs, the baseline for this rule includes reductions resulting from the NSPS/EG for
Oil and Gas, as detailed in the RIA for the 2024 Final NSPS/EG (U.S. EPA, 2023a). Only a
subset of the baseline emissions is subject to the WEC, as seen in section 4.2.
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The impact analysis relies in part on the marginal abatement cost curve (MACC) for the
oil and gas industry, which is further discussed in section 7. The MACC model is a mitigation
cost model that EPA developed to model methane mitigation potential from U.S. oil and natural
gas systems as part of larger analyses of non-C02 GHG emissions projection and mitigation
potential for over 20 years8. The MACC is used to estimate what methane mitigation could be
expected as a result of facilities facing the WEC charges deciding to adopt mitigation measures
earlier than they would have under the NSPS/EG rule. The flat charge per metric ton of methane
suggests that some facilities may find it cheaper to adopt methane emission controls in early
years to reduce or avoid WEC obligations while other facilities will find it cheaper to pay the
WEC. The analysis used EPA's national oil and gas system MACC model to evaluate the
potential emissions reductions likely to occur each year from facilities where mitigation
technology would be cheaper than paying the WEC charges.
For this analysis, EPA updated the mitigation options technologies characterized in the
model to reflect the most recently published best system of emission reduction (BSER) estimates
of emissions reduction performance and costs. Additional information on the mitigation
technologies updated for this analysis is available in Appendix C.
Owners and operators of oil and gas facilities subject to the requirements of the final
Waste Emissions Charge must submit a WEC filing to the EPA. Fulfilling this requirement will
involve calculation, reporting, and recordkeeping activities. The EPA estimated the total cost of
these information collection activities as approximately $1.7 million per year over the 3 years
covered by the Information Collection Request (ICR).9 These reporting and recordkeeping costs
are part of the costs borne by regulated entities as part of the final rulemaking. These costs are
detailed in the ICR and supporting statement and are not included in the analysis in this RIA.
Because these costs are relatively small in comparison to the benefits, costs, and transfers
estimated in the RIA, including them in totals would not meaningfully change overall results.
8 For additional information on the MACC model and its modeling framework see Global Non-C02 Greenhouse
Gas Emissions Projections & Marginal Abatement Cost Analysis: Methodology Documentation. EPA-430-R-19-
012.
9 EPA ICR number 2787.02 (OMB Control No. 2060-0752. A copy of the ICR is available in the docket for this
rulemaking and is briefly summarized in preamble section VLB. Paperwork Reduction Act.
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2.6 Economic Significance
The final Waste Emissions Charge constitutes a "significant regulatory action" as defined
under section 3(f)(1) of Executive Order 12866, as amended by Executive Order 14094.
Executive Order 12866 requires agencies to conduct regulatory analysis for actions that are
significant under Section 3(f)(1) (as amended). Actions that are significant under Section 3(f)(1)
include actions likely to result in annual costs, benefits, or transfers of at least $200 million per
year. As discussion in Section 6, the emissions reductions projected under the rule are likely to
produce substantial climate benefits, peaking at $530 million to $890 million in 2027, as well as
non-monetized benefits from reductions in VOC and HAP emissions. At the same time, the final
WEC is projected to result in substantial transfer payments by the oil and gas industry to comply
with the rule, reaching a maximum of $560 million in 2025.
2.7 Transfers
From the perspective of calculating costs and benefits that accrue to society as a whole,
WEC payments are transfers payments. Transfer payments are a shift in money from one party to
another. On net, transfers do not affect total net benefits because payments by one group are
offset by receipts by another group. In the case of the WEC, payments made by oil and gas
operators are offset by receipts by the government in the societal cost benefit analysis. From
OMB Circular A-4 (2003) and OMB Circular A-4 (2023), transfer payments potentially include
fees to government agencies for goods and services, tax payments from individuals or businesses
to the government (monetary transfers to the government) and tax refunds from the government
(monetary transfers from the government to taxpayers). (OMB, 2003, 2023)
The approach taken here is in line with the approach taken for regulatory impact analyses
for other rules impacting payments to the government. For example, in the BLM's waste
prevention rule, royalty payments were treated as transfers because they are income for the
Federal or Tribal government and costs to the operator or lessee. (BLM, 2022) In an EPA rule
modifying fees related to administration of the Toxic Substance Control Act, the total social cost
did not include the fees incurred by firms and collected by EPA, as those fees represent a transfer
from affected manufacturers and processors to taxpayers. (U.S. EPA, 2018)
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There are two accounting approaches that can be used to quantify transfers in regulatory
impact analyses. (OMB, 2023) First, transfers can be accounted for separately from costs and
benefits. A second approach is to include one side of a transfer as a benefit and the other side of
a transfer as a cost, such that the transfer is treated symmetrically in the estimate of net benefits.
In the comparison of costs and benefits in this RIA, we use the first approach and do not include
the transfer amount in either the benefits or costs.
Although WEC payments are transfers from the perspective of societal costs and benefits,
for the purpose of analyses focused on impacts on oil and gas companies subject to the WEC,
payments are included. In the energy markets analysis, both costs of methane mitigation and
WEC payments impact production and operation costs and result in changes in equilibrium
prices and production. In the small business analysis, WEC payments are the focus of the
analysis of costs for small entities under this program.
2.8 Changes Between the Proposal and Final RIA
Compared to the analysis presented in the RIA for the January 2024 WEC proposal, this
analysis reflects some updates to methodologies used to project impacts reflecting changes in the
final regulations relative to the proposal and updated available data.
This analysis reflects changes to the regulatory requirements for netting for facilities under
common ownership or control and implementation of the regulatory compliance exemption.
Relative to the proposal, the final regulations allow broader netting at the parent company level,
which allows more flexibility for netting, and results in lower anticipated WEC obligations in the
baseline scenario.
The final regulations changed several aspects of the regulatory compliance exemption,
only some of which are captured by the analysis in this RIA. Based on the proposed WEC
regulations, the regulatory compliance exemption would have become available upon
determination that state and other OOOOc-implementing plans met stringency requirements and
were approved and in effect in all states. The final WEC regulations further require that
mitigation requirements are fully implemented before the regulatory compliance exemption is
available. As a result, while the proposal RIA assumed that the regulatory compliance exemption
would be available starting in 2027, this analysis assumes the regulatory compliance exemption
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is available starting in 2029, based on the assumption that plan requirements would phase-in over
several years.
The final WEC regulations include additional changes in requirements for the regulatory
compliance exemption which cannot be captured in this analysis. The WEC proposal anticipated
a national determination that would have made the regulatory compliance exemption available in
all states after state plans were approved and in effect in all states. The final WEC has changed
this approach to state-by-state evaluation. This means that in practice the regulatory compliance
exemption will be available at different times in different states based on a variety of factors
including OOOOc-implementing plan approval and implementation schedules. As timing for any
individual state is unknown, this RIA analysis assumes that the regulatory compliance exemption
becomes available for all relevant facilities in 2029. The final rule also made changes in how the
regulatory compliance exemption is calculated in the case compliance issues. As described in
preamble section II.D.2.f, the EPA is finalizing a definition of compliance which focuses on a
narrower set of compliance activities that directly affect methane emissions. However, these
changes are not reflected in the RIA results because the RIA projections assume all facilities in
segments subject to NSPS/EG requirements are eligible for the regulatory compliance exemption
starting in 2029.
Updated data from the GHGRP has also been incorporated. The baseline analysis has been
updated to reflect reported data for 2022, which was not available at the time that the proposal
RIA analysis was developed. Because reported emissions for RY2022 were approximately 15
percent lower than emissions reported for RY2021, many impacts reported in this document are
somewhat lower due to this update, relative to the proposal RIA estimates.10
EPA notes that for the final rule the RIA assumes that all facilities in the industry segments
subject to NSPS/EG requirements are eligible for the regulatory compliance exemption in 2029
and thereafter. EPA did not consider a scenario with the regulatory compliance exemption
10 The largest decrease in emissions by source was for pneumatic devices (a decrease of 3.3 MMTCChe). Emissions
changes were driven by onshore production, which make up 85% of devices and 81% of C02e emissions. The
number of onshore intermittent-bleed devices decreased 10.5% from RY 2021) to 528,944. Additionally, there
was an 8.7% increase in the number of low-bleed pneumatic devices reported in onshore production, indicating an
overall shift from the use of high- and intermittent-bleeds to low-bleeds. Further information on historical
emissions reported to GHGRP subpart W can be found in: https://www.epa.gov/system/files/documents/2023-
10/subpart_w_2022_sector_profile.pdf
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becoming available in different states at different times over several years. However, EPA
recognizes that not all facilities will be eligible because of compliance issues including delays in
implementation of plan approval and mitigation measures. EPA does not have the capability or
data to predict how many facilities this situation will affect. Furthermore, the existence of the
regulatory compliance provision may have a beneficial effect on regulatory compliance. The
assumption of full compliance is a simplifying assumption for analysis purposes here and
throughout the rest of the RIA.
2.9 Organization of RIA
The remainder of the RIA is organized as follows:
• Section 3, Baseline, describes the baseline projection of CH4 emissions reported to subpart
W for segments subject to the Waste Emissions Charge.
• Section 4, WEC Scenario describes the policy scenario analyzed, WEC applicable facilities,
and the calculation steps for emissions subject to the WEC.
• Section 5, Costs and Emissions Impacts describes the costs and emissions impacts of the
two major responses to the WEC: 1) application of methane mitigation technologies, and 2)
energy market changes in oil and gas production and prices. This section includes
descriptions of the marginal abatement cost analysis, and the partial equilibrium model used
for market modeling.
• Section 6, Benefits, describes the methods used to estimate the climate benefits from
reductions of CH4 emissions. This analysis uses estimates of the social cost of greenhouse
gases to monetize the estimated changes in CH4 emissions expected to occur over 2024
through 2035 for the final rule. Qualitative benefits of VOC and HAP reductions are also
discussed.
• Section 7, Comparison of Benefits and Costs: presents estimates of the net benefits of the
rule.
• Section 8, Uncertainty Analyses: discusses sensitivity of results related to GHGRP
calculation methods and potential interaction with NSPS/EG.
• Section 9, Distributional and Economic Analyses: presents the small business,
employment, environmental justice, and distributional climate impacts analyses.
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3 BASELINE
3.1 Baseline Projection Approach
This section describes the baseline projection of CH4 emissions and throughput reported
to GHGRP subpart W for segments subject to the Waste Emissions Charge, from the base year
2022 through 2035. The baseline is used to estimate facilities and emissions potentially subject
to the Waste Emissions Charge and as an input to the mitigation analysis. The baseline begins
from emissions and activity reported to subpart W in RY 2022, the most recent available
reporting data at the time of this analysis. The base year data has been updated since the proposal
RIA, which used emissions reported for 2021. Emissions trends are projected by segment,
source, control status, and site types. The EPA acknowledges that the regulatory impact analysis
baseline is based on emissions historically reported to Subpart W, and therefore does not reflect
the recently finalized revisions of subpart W. For many sources, EPA has recently finalized
revisions to reporting that may meaningfully change methane reported to subpart W starting in
2025. Section 8 of the RIAs contains a discussion of uncertainty related to this factor. Estimating
WEC obligations requires estimates of reported emissions for particular facilities, which will be
impacted by factors such as reporter choice of calculation method and site-specific
measurements.
The baseline projection includes anticipated impacts from the Oil and Gas NSPS/EG.
This approach is taken to avoid double-counting of costs and emissions reductions across the
analyses for the NSPS/EG and WEC. This analysis reflects the RIA for the 2024 Final
NSPS/EG. The impacts of the WEC are also likely affected by interactions with other policies
affecting emissions and activities of the oil and gas sector, such as the Bureau of Land
Management's waste prevention rule and state policies. These other policies are not explicitly
modeled in the baseline.
3.1.1 Base Year Emissions by Segment and Source
The baseline analysis begins from detailed GHGRP subpart W reported data by facility,
segment, source, and unit type. The baseline scope is CH4 emissions reported under segments
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subject to the WEC.11 Detailed reporting data on throughput and emissions is necessary to
estimate potential WEC amounts and emissions reductions resulting from the WEC, because the
WEC is assessed by facility and owner or operator ("WEC obligated party"). As shown in Table
2-1, emissions reported to subpart W are broken out by source and unit type in order to assess
mitigation potential for each emissions source and equipment type independently. Further detail
on subpart W emissions reported by segment, source, and trends over time can be found in the
GHGRP sector profile for petroleum and natural gas systems.12
Table 3-1 Methane Emissions Reported to Subpart W Segments Subject to the WEC,
By Source and Unit Type (RY 2022)
Source Unit Type CELt tons
Pneumatic Devices Intermittent Bleed Pneumatic Devices 822,000
Misc Equipment Leaks Equipment Leak Population Counts 336,000
Blowdown Vent Stacks 199,000
Pneumatic Pumps 79,000
Combustion Equipment 75,000
Reciprocating Compressors Reciprocating Compressors - Rod Packing 69,000
Liquids Unloading 60,000
Dehydrators 54,000
Other Flare Stacks 53,000
Offshore Sources 52,000
Pneumatic Devices High-Bleed Pneumatic Devices 50,000
Pneumatic Devices Low-Bleed Pneumatic Devices 44,000
Centrifugal Compressors Wet Seal Centrifugal Compressors - Seals 44,000
Associated Gas Venting and Flaring 43,000
Misc Equipment Leaks Equipment Leak Surveys 39,000
Atmospheric Storage Tanks 39,000
Reciprocating Compressors Reciprocating Compressors - Leaks 33,000
Centrifugal Compressors Wet Seal Centrifugal Compressors - Leaks 15,000
Centrifugal Compressors Dry Seal Centrifugal Compressors - Leaks 9,100
Transmission Tanks 8,200
Well Compl. and Work, with HF 7,400
Gas Well Compl. and Work, without HF 1200
Well Testing 38
11 GHGRP subpart W segments subject to the WEC are onshore production, offshore production, gathering and
boosting, gas processing, transmission compression, transmission pipelines, natural gas storage, LNG
import/export, and LNG storage. The NG distribution segment is not subject to the WEC.
12 2011-2022 Greenhouse Gas Reporting Program Industrial Profile: Petroleum and Natural Gas Systems, reflecting
the same data snapshot used in this analysis, available here: https://www.epa.gov/system/files/documents/2023-
10/subpart_w_2022_sector_profile.pdf
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Reporting requirements vary by segment and other facility characteristics. The base year
emissions information is based on data reported for reporting year 2022 (RY 2022). For many
sources, EPA has recently finalized revisions to reporting that may significantly change methane
reported to subpart W starting in 2025. Because the most recent data available is from RY 2022,
this baseline uses emissions methods and factors in place in 2022. The emissions calculation
methods in subpart W can be grouped into categories: (1) direct emissions measurement; (2)
combination of measurement and engineering calculations; (3) engineering calculations; (4) leak
detection and use of a leaker emission factor; and (5) population count and population emission
factors, subpart W emission factors (both population and leaker emission factors) include both
those developed from published empirical data and those developed from site-specific data
collected by the reporting facility. Currently, the majority of emissions reported are quantified
based upon population emission factors or engineering calculations, which typically include
specified measurements of process operating parameters (e.g., temperature or pressure). The
recently finalized revisions to subpart W include new measurement-based calculation
methodologies for several sources, including pneumatic devices and pumps, equipment leaks,
and compressors.
Calculating WEC obligations requires information on the throughput of each facility in
addition to emissions information. All subpart W facilities report information on natural gas
and/or liquids throughput. However, RY2022 throughput for facilities in the natural gas
processing and transmission compression segments is classified as confidential business
information (CBI). For this reason, the RIA analysis uses proxy estimates to substitute for
reported throughput information for facilities in these segments. The proxy throughput estimates
for RY2022 were constructed by allocating total throughput for all subpart W facilities in
processing and transmission compression among the reporting facilities in proportion to carbon
dioxide emissions from combustion reported by these facilities to subpart A.
3.1.2 Baseline Projection Trends
Emissions by segment and source trends are projected by segment and source including
anticipated impacts of the Oil and Gas NSPS/EG. Projections by segment, source (e.g., fugitives,
pneumatic controllers, compressors), and unit type (e.g., centrifugal compressors) were extracted
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from the projections from the RIA for the 2024 Final NSPS/EG13. For emissions sources
reported to GHGRP subpart W, but not within the scope of the NSPS/EG RIA projections,
simplified assumptions based on projected natural gas production activity were used to project
future reported emissions from those sources. The 2023 Annual Energy Outlook projects crude
oil and lease condensate production to grow by 13 percent from 2022 to 2030 (24.6 to 27.7
quads) and for dry natural gas production to increase 2 percent from 2022 to 2030 (37.8 to 38.4
quads). In addition to emissions trends for affected sources and equipment types, the NSPS/EG
RIA projections are used to break out the baseline emissions by control status, vintage, and site.
These categorizations are useful for characterizing mitigation potential and control costs.
Projected throughput was also estimated using the 2023 Annual Energy Outlook projection of
natural gas production, applied to the base year facility throughput (which is either as reported,
or a proxy estimate depending on the segment).
Application of the emissions trends and characteristics from the Final NSPS/EG RIA
projections implicitly assumes that the emissions trends among the subset of oil and gas
operations reporting to the GHGRP subpart W and potentially subject to the WEC are
comparable to the trends for the overall oil and gas industry, which is subject to the NSPS/EG.14
Reporters to the GHGRP represent companies with larger operations than non-reporters.
However, given the various uncertainties involved in constructing the emissions projections, and
the significant coverage of GHGRP of the oil and gas industry, it is reasonable to assume that the
overall projections from the NSPS/EG are relatively representative of the trends that could be
expected from GHGRP reporters potentially subject to the WEC.
3.1.3 Summary of Projections Methodology from NSPS/EG RIA
Because the emissions baseline incorporates trends from the RIA for the 2024 Final
NSPS/EG, a summary of the projection methodology used in that analysis is included here. The
Final NSPS/EG RIA includes further details on the projections methodology (U.S. EPA, 2023a).
13 https://www.epa.gov/system/files/documents/2023-12/eol2866_oil-and-gas-nsps-eg-climate-review-2060-avl6-
ria-20231130.pdf
14 For more information on historical petroleum and natural gas systems emission trends see:
https://www.epa.gov/system/files/documents/2023-10/subpart_w_2022_sector_profile.pdf
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The Final NSPS/EG RIA includes projections of activity data and emissions for the
following sources: fugitive emissions/equipment leaks, pneumatic pumps, pneumatic controllers,
reciprocating compressors, centrifugal compressors, liquids unloading, and storage vessels.
Depending upon the source, the NSPS/EG includes requirements for equipment located at well
sites and centralized production facilities, gathering and boosting stations, natural gas processing
plants, and transmission and storage compressor stations. Tables 2-1 and 2-2 in the RIA for the
2024 Final NSPS/EG summarize the requirements of those rules. The Final NSPS/EG RIA did
not quantify regulatory impacts of the super-emitter response program.
The NSPS/EG RIA activity data projections rely on historical data from the GHGI,
industry data collected by EPA through an information collection request, information on wells
and oil and gas production from the firm Enverus, and projections from the U.S. Energy
Information Administration's (EIA) Annual Energy Outlook (AEO)15'16'17. The projections
construct projected counts of oil and natural gas sites, such as well sites, compressor stations, and
processing plants, that contain or are themselves affected facilities. The Final RIA contains
descriptions of how projections for each site and equipment type are constructed. The projections
used assumed retirement rates and annual new site construction18 to track new and modified
facilities (which would be subject to NSPS OOOOb requirements) and existing facilities (which
would be subject to state requirements based on the emissions guidelines).
3.1.4 Baseline Emissions Results
Methane emissions reported to GHGRP subpart W in the baseline are expected to decline
significantly, in particular with respect to sources subject to requirements under the NSPS/EG.
Emissions decline gradually over time as a result of NSPS OOOOb, while emissions decline
dramatically in 2028 as a result of the EG OOOOc.19 Over the analysis period of 2024 to 2035,
the EIA Annual Energy Outlook reference scenario includes a gradual increase in natural gas
15 Annual Energy Outlook 2023, https://www.eia.gov/ontlooks/aeo/.
16 U.S. Greenhouse Gas Emissions and Sinks, https://www.epa.gov/system/files/documents/2023-04/US-GHG-
Inventory-2023-Main-Text.pdf
17 Enverus Energy Analytics, http://www.enverus.com.
18 See table 2-3 of the RIA for the 2024 Final NSPS/EG
19 The RIA analysis for the 2024 Final NSPS/EG explained that emissions reductions as a result of the EG are
expected to phase in from 2027 to 2029, but that for analytical purposes, all existing source reductions were
assumed to take effect in 2028.
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production, which results in slightly higher baseline emissions in 2035 relative to 2030. Table
3-2 lists results for the projected methane emissions baseline. This baseline does not include the
effects of the Waste Emissions Charge; the policy scenario will be compared against this
baseline scenario.
Table 3-2 Projected CH4 Emissions Baseline of Emissions Reported to Subpart W
Year
CH4 tons projected for subpart W
(excl. NG dist)a
2024
2,100,000
2025
2,100,000
2026
2,000,000
2027
2,000,000
2028
730,000
2029
730,000
2030
730,000
2031
730,000
2032
740,000
2033
740,000
2034
740,000
2035
740,000
aThe baseline projection begins from reported emissions to GHGRP subpart W for RY2022 and incorporates
activity and emissions trends from the EIA AEO 2023 reference case and the RIA for the 2024 Final NSPS/EG.
The baseline here includes all industry segments that report to subpart W except the natural gas distribution
segment because facilities reporting for that segment are not subject to the WEC.
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4 WEC SCENARIO
4.1 Identification of Regulated Sources
As described in section 2.2, CAA section 136(c) states that a WEC will be levied on
applicable waste emissions above the threshold under subsection (f) from an owner or operator
of an applicable facility that reports more than 25,000 metric tons of carbon dioxide equivalent
(tCChe) of greenhouse gases emitted per year pursuant to subpart W of part 98 of title 40.
4.1.1 Description of Applicability Standards
Owners and operators would first determine whether their facility is a WEC applicable
facility and then would determine whether the facility's methane emissions exceed the applicable
waste emissions threshold. To calculate the amount by which a WEC applicable facility is below
or exceeding the waste emissions threshold and thus determine the amount of waste emissions
charge owed, the facility waste emissions threshold is subtracted from facility total methane
emissions, as described in the final regulatory text. This results in a value of metric tons of
methane, referred to as the total facility applicable emissions, that is negative for facilities below
the waste emissions threshold and positive for facilities exceeding the waste emissions threshold.
A facility may report total GHG emissions to subpart W which exceed 25,000 tC02e (and
thus is a WEC applicable facility) and also have negative facility applicable emissions. This can
happen for facilities with relatively low methane emissions and relatively high natural gas
throughput. For example, consider a WEC applicable facility in the onshore production segment
which reports 2,000 tons of methane emissions and 78 million Mscf of natural gas throughput
under subpart W. Accounting for the global warming potential (GWP) of methane, this facility
reports more than 25,000 tC02e of GHG to subpart W. However, applying the segment-specific
methane intensity threshold of 0.2%, this facility would have a facility waste emissions threshold
of approximately 3,000 tons. Because it reported lower methane emissions than this number, its
facility applicable emissions would be approximately negative 1,000 tons.
For a facility that would be subject to charge {i.e., that has a positive value of total facility
applicable emissions), there are three exemptions that may lower the facility's WEC or exempt
the facility entirely from the charge. The first exemption, found in CAA section 136(f)(5),
exempts from the charge emissions occurring at facilities in the onshore or offshore production
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segments that are caused by eligible delays in environmental permitting of gathering or
transmission infrastructure. The second exemption, found in CAA section 136(f)(6), exempts
from the charge facilities subject to and in compliance with the NSPS OOOOb and EG 0000c
if certain conditions are met. The third exemption, found in CAA section 136(f)(7), exempts
from the charge reporting-year emission from wells that are permanently shut in and plugged.
Based upon the applicability of these exemptions, the total facility applicable emissions are
adjusted. The resulting value, also in units of metric tons of methane, is referred to as the WEC
applicable emissions.
When determining the total WEC applicable emissions for a WEC obligated party, CAA
section 136(f)(4) allows for the netting of emissions at facilities under common ownership or
control within and across all applicable segments identified in 136(d). Thus, for the WEC
regulations, the WEC applicable emissions (positive or negative) from all of a WEC obligated
party's WEC applicable facilities are summed to calculate net WEC emissions for that WEC
obligated party. WEC obligated parties with the same parent company can then transfer negative
net WEC emissions to one another. To determine the WEC obligated party's total annual waste
emissions charge, or WEC obligation, its net metric tons of methane exceeding the waste
emissions thresholds after any transfers is multiplied by the annual $/metric ton charge. Any
WEC obligated party with net WEC emissions greater than zero would therefore have a WEC
obligation and be required to pay a waste emissions charge.
4.1.2 Identification of Applicable Facilities
As an illustration of the application of these terms and concepts, Table 4-1 shows the
number of total facilities reporting under subpart W in RY 2022, the number of WEC applicable
facilities based on RY 2022 reported data, and the number of facilities with WEC applicable
emissions greater than zero based on RY 2022 emissions and throughputs, by subpart W industry
segment. For this analysis, we used GHGRP data frozen as of August 18, 2023 (available
through EPA's Envirofacts website20). To estimate the number of WEC applicable facilities
within the GHGRP, we reviewed RY 2022 GHG emissions to determine which facilities reported
more than 25,000 mt C02e to subpart W. For each WEC applicable facility, we calculated the
20 https://enviro.epa.gov/
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waste emissions threshold using the RY 2022 facility-level throughputs and the provisions of
CAA section 136(f) appropriate for that industry segment, and then we subtracted the waste
emissions threshold from the RY 2022 reported CH4 emissions to determine whether the WEC
applicable emissions for each facility were greater than zero {i.e., positive). The final WEC
regulations allow broader netting among owners or operators that share a common parent
company. To account for netting at the parent company level, for netting facilities with both
positive and negative WEC applicable emissions, negative WEC applicable emissions were
proportionally applied to facilities with positive WEC applicable emissions to calculate
emissions subject to WEC after netting. In practice, this approach changes the count of facilities
with emissions subject to WEC in cases where transfers of negative WEC emissions allow
facilities to reduce net WEC emissions to zero.
Table 4-1 Numbers of Subpart W Reporting Facilities, WEC Appliable Facilities, and
Facilities with WEC Applicable Emissions Greater than Zero By Industry
Segment (Based on RY 2022)
Number of
Facilities
with WEC
Applicable
Emissions
>0a
Number of
Industry Segment
Total
Number of
Facilities
Reporting
Number of
WEC
Applicable
Facilities
Facilities with
Emissions Subject
to WEC, After
Netting
Onshore petroleum and natural gas production
459
393
226
202
Offshore petroleum and natural gas production
116
23
17
16
Onshore petroleum and natural gas gathering
and boosting
350
310
201
125
Onshore natural gas processing
444
180
-53
-16
Onshore natural gas transmission compression
659
22
~ 5
-0
Onshore natural gas transmission pipeline
44
20
4
4
Underground natural gas storage
51
1
1
1
Liquefied natural gas storage
5
0
0
0
Liquefied natural gas import and export
equipment
11
7
0
0
Total
2,112b
954b
-507
-364
a Note that the count of facilities with positive WEC applicable emissions is not shown as an exact value for the
Natural Gas Processing and Onshore Natural Gas Transmission Compression industry segments due to the
sensitivity of throughputs in that industry segment and the relatively low number of WEC applicable facilities. For
facilities in these segments, WEC calculations used proxy estimates of throughput to avoid using sensitive data.
bAlso note that for industry segments that use the definition of "facility" as defined in 40 CFR 98.6, a subpart W
reporting facility may include operations from multiple co-located industry segments. The counts presented reflect
each industry segment reported, while the total count includes only unique facilities, and as a result may not match
the sum of industry segment reporting.
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4.1.3 Methodology for Projecting WEC-Applicable Emissions
To estimate potential impacts of the final rule, the EPA projected WEC applicable
facilities and WEC applicable emissions before accounting for potential emissions reductions
from methane mitigation actions.
• Identify WEC applicable facilities. WEC applicable facilities are GHGRP facilities that
report more than 25,000 metric tons CChe to GHGRP subpart W and report emissions under
any of the nine oil and natural gas industry segments subject to the WEC (all segments
except the natural gas distribution segment). Facilities projected to report less than 25,000
metric tons CChe to subpart W in a given year would not be considered subject to the WEC
and are not included in projections of WEC-applicable emissions. Emissions of CO2 and N2O
reported to subpart W were assumed to be fixed for each facility at the same level as reported
in RY 2022. Methane emissions were projected by segment and source as described in the
baseline section.
• Calculate facility waste emissions threshold from segment-specific methane intensity
thresholds. To calculate a facility's projected waste emissions threshold, the facility's
projected natural gas throughput was first multiplied by the relevant intensity threshold
specified by Congress to calculate the volume of gas equivalent to the segment-specific
methane intensity threshold. These values were converted to metric tons by multiplying by
the density of methane (0.0192 mt / Mscf) to calculate the waste emissions threshold in
metric tons of methane The methane intensity thresholds for each segment are listed in Table
2-1.
• Calculate facility tons above or below waste emissions threshold, or total facility
applicable emissions. The facility's projected waste emissions threshold was subtracted
from the facility's projected methane emissions to determine the total facility applicable
emissions. A negative value represented the metric tons of methane emissions a facility was
below the waste emissions threshold while a positive value represented the metric tons of
methane emissions at the facility that exceeded the segment-specific methane intensity
threshold. Facilities with projected subpart W emissions below 25,000 metric tons CChe were
not considered eligible for the purpose of netting and positive or negative tons from these
facilities were excluded.
• Apply regulatory compliance exemption. For this analysis, EPA assumed that the
regulatory compliance exemption would apply starting in 2029 for all facilities reporting to
segments containing facilities subject to the NSPS/EG and that had positive total facility
applicable emissions. These segments are onshore production, natural gas gathering and
boosting, natural gas processing, natural gas transmission compression, and underground
natural gas storage segments. For this analysis, all facilities in these segments were assumed
to have zero violations or deviations related to NSPS/EG requirements, and thus receive a
regulatory compliance exemption. The assumption that the regulatory compliance exemption
would apply starting in 2029 is based on prompt implementation of the schedule for state
plans outlined in 2024 Final Oil and Gas EG OOOOc. Under the EG OOOOc, states have 24
months to submit their state plans, and EPA must approve or deny state plans within 12
months, which means that plans may be in effect as early as 2027, assuming no Federal Plan
is needed. In general plan requirements are assumed to phase in over three years from 2027
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to 2029, meaning that the regulatory compliance exemption would be available starting in
2029.
• Emissions associated with plugged well and unreasonable delay exemptions. To calculate
WEC applicable emissions, emissions associated with wells plugged in the previous year and
unreasonable delay in environmental permitting are subtracted from total facility applicable
methane emissions for the purpose of WEC. This analysis does not include any estimate of
projected facilities or emissions that would receive these exemptions.
• Calculate WEC applicable emissions. For facilities with a regulatory compliance
exemption, the facility's WEC applicable emission are zero. For all others, the facility's
WEC applicable emissions are equal to the previously calculated total facility applicable
emissions.
• Calculate net WEC emissions by WEC Obligated Party. For WEC Obligated Parties with
common ownership or control of multiple facilities, facility tons above or below the waste
emissions thresholds were summed across all facilities to calculate net tons. In addition,
owner-operators under a common parent company may transfer negative WEC emissions to
lower their WEC obligations. Net WEC emissions after transfers for each owner-operator are
estimated assuming netting among WEC obligated parties with a common parent company.
• Calculate potential WEC obligations. WEC Obligated Parties with net tons methane of
zero or below would not be subject to the WEC and have zero WEC obligations. For WEC
Obligated Parties with net tons methane greater than zero, net tons were multiplied by the
WEC. In 2024 the WEC is $900/ton, in 2025 it is $1200/ton, and in 2026 and later years, it is
$1500/ton of methane.
It is important to note that the reporting threshold of 25,000 mt C02e per facility for the
GHGRP is not necessarily the same as the WEC applicable facility threshold in CAA section
136(c). Three of the industry segments included in CAA section 136(c), Onshore Petroleum and
Natural Gas Production, Onshore Petroleum and Natural Gas Gathering and Boosting, and
Onshore Natural Gas Transmission Pipeline, have unique definitions of facility in 40 CFR
98.238, and facilities in those segments only report emissions under subpart W, so the emissions
compared to each of those thresholds would be the same for each facility. However, facilities in
the other six segments use the standard GHGRP facility definition and report emissions under
other GHGRP subparts as well if they are co-located (e.g., 40 CFR part 98, subpart C, General
Stationary Fuel Combustion Sources or subpart Y, Petroleum Refineries). While emissions
reported under these other subparts are included when an owner or operator is considering
whether their facility is required to report to the GHGRP, the emissions from subparts other than
subpart W would not be included when an owner or operator is determining whether their facility
is a "WEC applicable facility."
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Table 4-2 shows how only a portion of the emissions that report under subpart W are
subject to the WEC. It is important to distinguish how each of these subcategories relates to the
overall baseline. As shown in Table 4-1, many facilities have emissions that are below the waste
emission threshold, as defined in the CAA. For those facilities whose emissions per unit of
throughput are below their waste emission threshold, they do not have "WEC applicable
emissions >0" (column b in Table 4-2).
Additionally, total emissions from facilities with WEC-applicable emissions greater than
zero are distinct from methane tons subject to the WEC. The methane tons subject to the WEC at
the facility level (column c in Table 4-2), is a subset of total emissions reported under subpart W.
Lastly, the tons of methane subject to the WEC after accounting for netting among owner-
operators that share a common parent company (column d in Table 4-2) is a subset of WEC-
applicable emissions at the facility level.21 Based on EPA's analysis of the 2022 data, a
significant percentage of facilities are relatively efficient, that is, they have emission rates below
the Congressionally mandated thresholds. Therefore, it is reasonable to expect netting to have a
notable impact on WEC-subject emissions when facilities under common ownership and control
are allowed to net their emissions. Both net WEC emissions and emissions from facilities with
WEC-applicable emissions greater than zero are important inputs to further analyses in this RIA.
Table 4-2 Projected CH4 Subject to Waste Emissions Charge in Baseline Before
Accounting for Mitigation and Market Responses (tons)
CH4 tons projected
CH4 tons from facilities
CH4 tons exceeding
Net emissions
Year
for subpart W
with WEC applicable
facility waste emissions
(tons) subject
(excl. NG dist)
emissions >0a b
thresholdsab
to the WEC
(a)
(b)
(c)
(d)
2024
2,100,000
1,400,000
960,000
710,000
2025
2,100,000
1,300,000
930,000
680,000
2026
2,000,000
1,300,000
900,000
650,000
2027
2,000,000
1,300,000
870,000
630,000
2028
730,000
240,000
140,000
77,000
2029
730,000
55,000
36,000
34,000
2030
730,000
55,000
36,000
33,000
2031
730,000
55,000
36,000
33,000
2032
740,000
55,000
36,000
33,000
2033
740,000
55,000
35,000
33,000
2034
740,000
55,000
35,000
32,000
2035
740,000
55,000
35,000
32,000
21 Calculations of netting are based on facility characteristics in the RY 2022 base year, combined with projected
changes as described in Section 3, and the WEC and netting calculations described in this section. The netting
calculations assume that patterns of WEC facility emissions and ownership are reflective of those in the 2022
GHGRP data but do not attempt to project future changes in the oil and natural gas industry.
4-6
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Notes:
a Estimates of emissions subject to the WEC in this table are based on emissions in the baseline scenario. They do
not include CH4 reductions from application of mitigation technologies or energy market responses.
b Emissions from WEC-applicable facilities are greater than facility emissions exceeding waste emissions thresholds
because a portion of the emissions reported by a WEC-applicable facility are below the waste emissions threshold.
Total emissions from WEC-applicable facilities are included because these reflect emissions potentially targeted
for methane mitigation.
Projected estimates of CH4 tons subject to the WEC in the baseline reflect projections starting from emissions
reported to GHGRP subpart W for RY 2022, and thus assume this distribution of facilities and emissions.
The projections assume that starting in 2029, facilities in onshore production, gathering and boosting, transmission
compression, and natural gas storage are exempted from the WEC as a result of the regulatory compliance
exemption.
Table 4-3, Table 4-4, and Table 4-5 present snapshots of projected methane emissions
subject to the WEC in the baseline by segment in 2024, 2026, and 2030. These results do not
include mitigation or energy market responses to the WEC.
Table 4-3 Projected CH4 Subject to Waste Emissions Charge in Baseline Before
Accounting for Mitigation and Market Responses, by Segment, 2024,
thousand tons
Industry Segment
CH4 projected
for subpart W
(excl. NG dist)
CH4 from
facilities with
WEC applicable
emissions >0
Facility CH4
exceeding
waste emissions
threshold
Net CH4
subject to
WEC
Onshore Production
1,100
850
610
530
Offshore Production
52
27
23
21
Gathering and Boosting
540
420
280
140
Natural Gas Processing
97
43
27
9
Natural Gas Transmission Compression
160
17
7
3
Natural Gas Transmission Pipeline
84
29
14
14
Underground Natural Gas Storage
11
1
0
0
LNG Import/Export
4
0
0
0
LNG Storage
0
0
0
0
Total
2,100
1,400
960
710
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Table 4-4 Projected CH4 Subject to Waste Emissions Charge in Baseline Before
Accounting for Mitigation and Market Responses, by Segment, 2026,
thousand tons
Industry Segment
CH4
projected for
subpart W
(excl. NG dist)
CH4 from
facilities with
WEC applicable
emissions >0
Facility CH4
exceeding
waste
emissions
threshold
Net CH4
subject to
WEC
Onshore Production
1,100
780
550
470
Offshore Production
52
27
23
21
Gathering and Boosting
540
420
280
140
Natural Gas Processing
96
43
26
8
Natural Gas Transmission Compression
160
17
7
3
Natural Gas Transmission Pipeline
84
29
13
13
Underground Natural Gas Storage
10
1
0
0
LNG Import/Export
4
0
0
0
LNG Storage
0
0
0
0
Total
2,000
1,300
900
650
Table 4-5 Projected CH4 Subject to Waste Emissions Charge in Baseline Before
Accounting for Mitigation and Market Responses, by Segment, 2030,
thousand tons
Industry Segment
CH4 projected
for subpart W
(excl. NG dist)
CH4 from
facilities with
WEC
applicable
emissions >0
Facility CH4
exceeding waste
emissions
threshold
Net CH4
subject to
WEC
Onshore Production
200
0
0
0
Offshore Production
52
27
23
20
Gathering and Boosting
240
0
0
0
Natural Gas Processing
61
0
0
0
Natural Gas Transmission Compression
88
0
0
0
Natural Gas Transmission Pipeline
84
29
13
13
Underground Natural Gas Storage
2
0
0
0
LNG Import/Export
4
0
0
0
LNG Storage
0
0
0
0
Total
730
55
36
33
4-8
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5 COST AND EMISSIONS IMPACTS
This section describes cost and emissions impacts of the WEC that arise through two
pathways: 1) through the application of cost-effective methane mitigation technologies, and 2)
through changes in oil and natural gas production and prices resulting from the WEC and
associated mitigation responses. Total social costs include the sum of costs related to each of
these two pathways. Section 5.1 describes the methods for estimating the expected cost of
methane mitigation. The social cost of methane mitigation is estimated total engineering cost.
Section 5.2 evaluates the equilibrium impact of increased production costs borne by oil and
natural gas firms on market prices and quantities. The social cost of these energy market effects
is estimated as the loss in consumer and producer surplus from changes in production resulting
from the WEC. Section 5.3 summarizes the expected total methane abatement and co-abatement
of VOC and HAP. Lastly, WEC obligations are estimated after accounting for methane
mitigation and energy market responses.
5.1 Costs of Methane Mitigation
Mitigation options were used to estimate marginal abatement cost curves (MACCs) in a
reduced form marginal abatement cost (MAC) model for the WEC applicable subsegments of the
Oil and Gas Industry in a manner similar to that presented in the EPA's Global Non-C02
Greenhouse Gas Emission Projections & Mitigation, 2015-2050 report (U.S. EPA, 2019).22 This
analysis builds from the 2019 report and includes updated baseline projections, mitigation option
performance characteristics, and implementation cost assumptions. Section 3 provides more
detail on the baseline projections developed for this analysis. See Appendix C, for additional
details on mitigation options and costs used in this analysis. The marginal abatement cost curve
(MACC) shows the cumulative mitigation potential at incrementally higher costs, where
mitigation is expressed in thousand metric tons of methane, and the costs are expressed in dollars
per metric ton of methane reduced. The MACC represents the aggregation of information on a
wide range of mitigation technologies applied to different types of oil and natural gas operations.
22 MAC curves are constructed by estimating the "break-even" price at which the present-value benefits and costs
for each mitigation option are equal. We then draw a cumulative supply curve of emission reductions by summing
over the reductions at each break-even price in ascending order. The methodology produces a curve where each
step reflects the reduction potential supplied assuming systematic implementation of the mitigation technology
were applied to similar model facilities across the sector.
5-1
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When evaluated against the WEC implementation schedule, we can calculate the cost of
abatement resulting from facilities implementing mitigation technologies where the cost of
mitigation is economic relative to the alterative WEC payment.
Each step of the MACC represents a calculation for a particular mitigation option applied
to a specific type of activity, facility, or type of equipment annual methane emissions
representing the baseline projection of emissions from facilities with WEC-applicable emissions
greater than zero. Each breakeven calculation results in a cost per ton of emissions reduction (the
vertical dimension of the curve) and methane mitigation potential (the horizontal dimension).
The asymptotic limit of the MACC curve represents the mitigation quantity that is technically
achievable23 using mitigation technologies included in the MACC model at facilities with
emissions above the facility-specific waste emissions threshold.
Mitigation technologies used in this analysis were updated based on information gathered
as part of technology assessment for the recent Oil and Gas NSPS/EG analysis (U.S. EPA,
2021b, 2022b). Available mitigation data for the offshore segment is limited and therefore cost
estimates in those segments is more uncertain than in other segments. We requested comment on
the application of cost-effective technologies for the offshore segment (and other segments not
eligible for the regulatory compliance exemption), but did not receive extensive comments. The
mitigation technologies are characterized based on the expected lifetime of equipment, the
emissions reduction efficiency, and the costs of implementation. Costs include the initial capital
costs of implementation, the annual operation and maintenance costs as well as any sources of
expected cost savings for labor, energy or materials associated with the methane emission
reductions.
23 The suite of mitigation measures considered for this analysis reflect the current achievable or demonstrated
technologies considered in NSPS/EG analysis of the Oil and Gas Industry. The MACC model was updated for
this analysis to include currently available information on mitigation measures and costs. However, the MACC
model does not yet include newer emerging technologies such as remote monitoring of fugitive emissions. See
Appendix C for more information on included mitigation measures.
5-2
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5000
4000
Gas&Oil Mitigation in 2025
WEC2025= $1,200
200 400 600 800 1000
Mitigation Level (ktCH4)
1200
1400
1600
Figure 5-1 Oil and Natural Gas MACC with WEC Payment Cost in 2025
In Figure 5-1, the intersection point of the MACC and the horizontal blue line
(representing the WEC payment cost of $1,200 per ton of methane for 2025) is the maximum
mitigation which can be implemented at a lower cost per ton of methane abatement than the
WEC. These cost-effective mitigation technologies (where cost-effective is taken to be those
technologies with cost less than or equal to the WEC), shown as the total area under the MACC
curve shaded in grey, is the total bottom-up engineering costs of implementing these mitigation
technologies. Additional mitigation is technically feasible at higher prices (S/tCFU) but would
not be cost effective relative to the WEC price in 2025. As a result, facilities facing more
expensive mitigation costs would elect to pay the WEC costs rather than implement these more
expensive mitigation measures.
In order to account for practical limitations in the speed of deploying cost-effective
mitigation to oil and gas operations, the analysis assumed a three-year phase-in period for
5-3
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reductions over 2024 to 2026. The phase-in parameter constrains the mitigation potential in 2024
and 2025 to 33% and 67% of total mitigation potential to simulate the assumption that it will
take facilities several years to fully implement mitigation measures. Depending upon a variety of
factors, potential technology deployment speed may be faster or slower than this assumption. Oil
and natural gas companies have been aware of the WEC since the passage of the IRA in 2022. In
addition, the NSPS/EG rulemaking was first proposed in 2021 and there is significant overlap in
the mitigation technologies which would be used to satisfy NSPS/EG requirements and those
which may be adopted to avoid WEC payments. However, widespread deployment of mitigation
technologies may be affected by supply chain, labor, or other constraints that could prevent full
utilization in the short term. Such constraints could include short term availability of skilled
personnel or time needed to increase manufacturing production of necessary equipment.
Table 5-1 presents the total cost of methane mitigation for each year, as calculated by
applying the MACC representing methane mitigation options to the baseline projection in each
year (2024 to 2035). The total mitigation costs over the analysis timeline are then presented in
2023 present values. The year-by-year variation in mitigation costs reflects several factors.
Between 2024 and subsequent years, costs associated with mitigation rise as technology
deployment increases. In addition, as the WEC rises in 2025 and 2026, additional mitigation
becomes cost-effective. Then, as emissions decline in the baseline as a result of NSPS/EG
implementation, costs associated with mitigation resulting from the WEC decline. Costs
associated with NSPS/EG implementation are considered in the RIA for that action and are not
included in this RIA to avoid double-counting. When the regulatory compliance exemption takes
effect, costs (and emissions reductions) resulting from the WEC decline further.
5-4
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Table 5-1 Mitigation Costs
Year
Mitigation costs
(million 2019$)a
2024
$40
2025
$85
2026
$120
2027
$120
2028
$17
2029
$10
2030
$10
2031
$10
2032
$10
2033
$10
2034
$10
2035
$10
NPV
2%
$420
3%
$400
7%
$350
EAV
2%
$43
3%
$44
7%
$47
a Mitigation costs represent a stream of annualized costs based on engineering costs of methane mitigation
technologies including capital costs, recurring costs, and revenue from avoided losses of natural gas. Mitigation
expenditures in a given year serve to reduce WEC obligations in the corresponding year.
Total costs associated with methane mitigation activities include capital costs, recurring
costs, and revenue from avoided losses of natural gas. Table 5-2 presents details of the
composition of mitigation costs among these components including total costs with and without
including revenue from avoided natural gas losses.
Table 5-2 Mitigation Cost Details (million 2019$)
Year
Mitigation costs
with revenue
Mitigation costs
without revenue
Capital
costs
Recurring
costs
Revenue from
avoided natural
gas losses
2024
$39.8
$53.6
$48.8
$4.0
$13.1
2025
$85.1
$114.4
$97.4
$14.6
$27.0
2026
$120.8
$163.1
$137.7
$22.2
$39.1
2027
$119.3
$161.0
$133.4
$24.4
$38.5
2028
$17.0
$18.4
$0.5
$17.9
$1.4
2029
$10.0
$11.1
$0.0
$11.1
$1.1
2030
$10.0
$11.1
$0.0
$11.1
$1.2
2031
$10.0
$11.1
$0.0
$11.1
$1.1
5-5
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2032
2033
2034
2035
$9.9
$11.1
$11.1
$11.1
$11.1
$0.0
$0.0
$0.0
$0.0
$11.1
$11.1
$11.1
$11.1
$1.2
$1.2
$1.2
$1.2
$9.93
$9.92
$9,903
5.2 Market Modeling
This section describes estimates of energy market impacts of the WEC. EPA used a
partial equilibrium model to estimate the energy market impacts of costs borne by oil and natural
gas firms because of the WEC. This section presents estimates of the costs of these market
impacts for inclusion in the benefit-cost analysis.
5.2.1 Model Description
The partial equilibrium model represents a single US oil and natural gas extraction sector,
foreign supply and demand for crude oil and natural gas, and domestic demand for a combination
of foreign and domestic sourced products, one for oil and one for gas. The model is calibrated to
reference quantities and prices from the Energy Information Administration and parameterized
with elasticities identified from a search of peer-reviewed literature.
US oil and gas producers supplied $281.0 billion of gas (36.4 TCF) and $412.6 billion of
crude oil (4.3 billion barrels) in 2022. Table 5-3 shows the calculation for the total domestic oil
and gas markets. By subtracting exports and adding imports to domestic production, we arrive at
domestic supply totaling $251.0 billion in gas (32.5 TCF) and $577.2 billion in crude (6.1 billion
barrels) supplies. Prices in 2022 were $7.73 per MCF of natural gas and $77.58 per barrel of
crude.24 The total undiscounted abatement and WEC payments of $2.4 billion over the period
2024 through 2035 are 0.3% of 2022 domestic oil and gas domestic supply values.
24 Gas: https://www.eia.gov/dnav/ng/hist/n3035ns3M.htm
Oil: https://www.eia.gov/dnav/pet/pet pri spt si a.htm
5-6
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Table 5-3 Oil and Gas Markets Value and Quantity (2022)
Market / Product
Gas
Crude
$ Billion
BCF
$ Billion
Million Barrels
Output (Y)25
$281.0
36,353
$412.6
4,347
Imports (M)26
23.4
36,353
288.5
3,040
Exports (X)27
- 53.4
- 6,904
- 123.9
- 1,305
Domestic Supply
$251.09
32,473
$ 577.2
6,082
Production in the model includes elastic supply and demand combined with constant
elasticity of substitution specifications for production of oil versus gas and demand for domestic
versus foreign sources. The following eleven equations define the model, which we solve as a
constrained non-linear system using the Conopt solver in GAMS:
Production: Total _ / py '\^y (1)
0 + cy)P.
Production: Fuel / \°fuel (2)
0 + cf) Py
nk
P_L
Pf
Pf
pf
Yf = afY
Supply: Imports , m\ af (3)
u (Pf
Demand: Total , C\ °/ (4)
n Pf
Df - Df\^C
Demand: Exports / \ of (5)
Xf = Xf i —
T~ TWn
Demand: Domestic / C\
-------
Zero profit: supply * (11)
Py = {ctcRuPcRV + CCgasPgAS ) L
Variable Definitions
Benchmark value of variable under bar
Y: Joint production of oil and gas
py: Unit price of joint output
oy: Elasticity of supply for joint oil-gas production
Yf \ Output of fuel f
cY: Compliance costs for oil and gas segments
Pf \ Unit price of fuel f
a.f : Cost share of fuel / in total production
Cf\ Compliance cost applicable to segment / only (gas only)
(Jfuel '¦ Elasticity of substitution across gas and oil output
Mf \ Imports of fuel f
Of1: Elasticity of import supply for fuel /
pf \ Import price of fuel /
Df\ Total demand for fuel f
of: Demand elasticity for fuel f
Xf\ Exports of fuel f
af\ Elasticity of demand for exports of fuel f
D®: Demand for domestically produced fuel /
Pf\ Cost share of domestic demand in total demand
pj: Armington aggregation consumption price of fuel /
Df1: Demand for imports of fuel /
pf \ Import price of fuel /
oy4: Armington elasticity of substitution among domestic and foreign sources of fuel /
Several elasticity values parameterize the partial equilibrium model. Model elasticities
dictate oil and gas quantities change in response to changes in market prices. In other words, an
elasticity indicates by what percent quantities will change for every percent change in prices.
Elasticities are estimated in the literature by applying statistical techniques to historical price and
quantity data. The PE model includes 10 elasticities each with a short-medium-term and long-
term estimate: 1 for combined oil and gas production activity, 1 for the ability to substitute the
mix of oil and gas production, 2 for the supply of imports (one oil, one gas), 4 for domestic and
foreign (export) demand (one oil, one gas each), and 2 for the substitution of foreign and
domestic sources (one oil, one gas).
We identified long and short-term elasticities from our review of the elasticity literature
for oil and gas markets. The literature includes estimates of both long- and short-term elasticities,
though these terms are not always explicit or well defined in the literature. The model represents
5-8
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a year's worth of production activity, which is generally consistent with the definitions of short-
to medium-run used in the elasticity literature. For later periods in the analysis period, we use
higher elasticity values closer to the long-run estimates, where the literature generally defines
long-run as time periods on the order of multiple years to decades.
Table 5-4 lists the elasticates identified across supply and demand categories. Production
supply elasticities in the literature were disaggregated by fuel source. Substitution elasticities for
fuel competition between the supply of oil and gas were assumed zero (i.e., fixed proportions).
The domestic supply and demand elasticities are for the United States and selected to be
representative of aggregate demand. For example, estimates that cover elasticities from
residential natural gas demand or only several states are excluded. These elasticities are a simple
average of five short-term supply elasticities and three long-term supply elasticities as no supply
elasticities for joint-production were identified in the literature. Import elasticities are taken from
global mean supply elasticities and export demand elasticities from global mean demand
elasticities. Foreign-domestic substitution elasticities were reported in the literature for oil and
gas separately and had either an undefined term-length or were reported as long-term. The PE
model takes the average of these values to parameterize short-term and long-term substitution.
The PE model's own-price elasticity of domestic demand (consumption) is an average of five
literature sources for long-term natural gas elasticities, four sources for long-term oil, seven for
short-term gas, and nine for short-term oil elasticity. The literature sources are cited in the source
in Table 5-4 and in the Reference section. Short-run supply and demand elasticities are small as
it takes time for consumers and producers to adjust their equipment and processes in response to
price changes. Longer-term elasticity estimates are generally higher as they capture the increased
ability of market participants to change production decisions, install new equipment, revise
contract terms, and make other capital and operations adjustments in response to price changes
over time. In this analysis, short-term elasticities were applied to the PE model for periods 2024-
2025 while long-term elasticities were used for periods 2026-2038.
5-9
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Table 5-4 PE Model Elasticity Values
Short-Medium Term Long Term
Gas Oil Gas Oil
Supply
Production: ay 0.02 0.44
Substitution (oil-gas): aFUEL 0.0 0.0
Imports (Foreign): a™ 0.01 0.06 0.19 0.25
Demand
Exports (Foreign): of -0.01 -0.01 -0.01 -0.26
Substitution (Dom.-For.): af 2.80 7.30 2.80 7.30
Consumption:^ -0.30 -0.15 -0.68 -0.47
Source: Elasticities are from: Rubaszek, Szafranek, and Uddin (2021); Newell and Prest (2019); Baumeister and Hamilton
(2019); Marten and Garbaccio (2018); Labandeira et al. (2017); Ponce and Neumann (2014); Krichene (2005).
As reflected in the elasticity values summarized in Table 5-4, oil and gas markets are
relatively inelastic compared to some other markets, particularly in the short-run. With regard to
consumption, oil and gas are often consumed for basic needs including heating, transportation,
and manufacturing processes. With regard to production, the oil and gas production cycle is
relatively long, requiring a number of years to complete lease acquisition, exploration,
development, and production. For this reason oil and gas production responds relatively slowly
to change in long-term price expectations. These factors may point towards the relatively
inelastic nature of oil and gas markets.
5.2.2 Market Impacts
EPA relied on a partial equilibrium simulation model of domestic oil and gas markets
with foreign trade to estimate the market impacts of the WEC. The analysis of methane
mitigation approach (Section 5.1) produced a national estimate of abatement costs, WEC
payments, and emissions reductions over the analysis period. The market analysis conducted
here indicates the scale and direction of estimated price and output changes in oil and gas
markets resulting from the WEC, which support EPA's assessment of EO 13211 "Actions
Concerning Regulations that Significantly Affect Energy Supply, Distribution, or Use."
Together, costs of methane mitigation and WEC payments add to the production costs
borne by oil and natural gas operators for the purpose of energy markets modeling. Over the
analysis period, methane mitigation costs resulting from the WEC and WEC obligations fall as
emissions reductions are required in the baseline by the NSPS/EG. This analysis assumes that
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cost-effective mitigation options are phased in over three years. Assuming faster adoption of
methane mitigation actions would increase costs of methane mitigation and decrease the WEC
obligations borne by oil and natural gas firms in the initial years of the analysis.
EPA's approach is to model the market implications of the production costs borne by oil
and natural gas firms in aggregate as opposed to trying to capture the individual decisions of
each company. However, production cost changes will affect entities in different segments of the
oil and gas market leading to differential impacts on oil and gas prices. For example, oil and gas
producers will face a portion of the costs that impact both crude and gas production costs while
costs faced by natural gas processing facilities, which handle gas but no liquids, will directly
impact only natural gas costs.
Cumulative costs borne by upstream segments are applied via the cy term in Equation (1)
as a fraction of total output. Cumulative costs borne by downstream (gas-only) segments are
applied via the cy term in Equation (2). The key outcomes of interest for this analysis are the
changes in prices and quantities. These model results will be used to calculate the energy market
welfare cost of reduced natural gas production and the change in emissions and WEC payments
resulting from changes in output.
Table 5-5 shows the market model results with WEC and abatement costs having a
negligible impact on natural gas and crude oil prices with 0.006%~0.007% in the first two years
of the analysis period each year of the analysis period. Natural gas and crude oil quantity
percentage impacts (not presented) are an also negligible (-0.002%). Baseline projections for
prices and quantities for production, imports, and exports are based on the Annual Energy
Outlook 2023 reference case. The impact of WEC and abatement cost on natural gas production
and prices is significantly smaller than their share relative to production value. For example, in
2024 the 0.07% production cost shock for the gas segment results in a 0.006% price increase.
Relatively inelastic supply will lead to lower price changes, all else equal. Much of the cost falls
on industry in the short run where elasticities are relatively low and consumer and producer gas
quantities are relatively unresponsive to price changes. Natural gas trade is also a relatively small
component of the domestic market and inelastic in the short term, meaning it displaces relatively
little domestic gas production in response. Gas price and production change by 0.044% and -
0.026%) respectively while crude oil changes by 0.030% for price and -0.026% for production in
5-11
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2026 (not presented here). Given WEC and abatement costs are close in 2024-2026, the
relatively larger impact in 2026-2027 than in 2024-2005 is due to the shift from short-term to
long-term elasticity. With the larger long-term elasticity, oil/gas industry foresees the regulatory
cos and have more flexibility to increase price and reduce production. Between 2027-2035, WEC
and abatement costs becomes smaller, thus has negligible impact on natural gas and crude prices
and quantities, at a level of no more than 0.001% and -0.001%.
Table 5-5 PE Model Outcomes
Year
Price: $/MCF
Quantity: BCF
Benchmark
WEC
% Change
Benchmark
WEC
% Change
2024
5.5055
5.5059
0.006%
35,038
35,038
-0.002%
2025
5.5276
5.5280
0.007%
35,214
35,213
-0.002%
2026
5.5497
5.5521
0.044%
35,390
35,381
-0.026%
2027
5.5719
5.5741
0.041%
35,567
35,558
-0.024%
2028
5.5942
5.5942
0.001%
35,744
35,744
-0.001%
2029
5.6165
5.6166
0.001%
35,923
35,923
0.000%
2030
5.6390
5.6390
0.001%
36,103
36,103
0.000%
2031
5.6616
5.6616
0.001%
36,283
36,283
0.000%
2032
5.6842
5.6842
0.001%
36,465
36,465
0.000%
2033
5.7069
5.7070
0.001%
36,647
36,647
0.000%
2034
5.7298
5.7298
0.001%
36,830
36,830
0.000%
2035
5.7527
5.7527
0.001%
37,014
37,014
0.000%
Output reductions reduce natural gas emissions beyond the methane mitigation actions
taken by producers. This analysis applies a sector-wide emissions factor to output changes from
the emissions model to estimate this market-induced abatement and the value of WEC payments
avoided as a result. These quantities modify the total abatement and WEC payments estimated in
Section 5.1. Last, we estimate the cost of energy market impacts (the loss in consumer and
producer surplus) associated with the WEC charge as the change in price times the change in
quantity.28 Table 5-6 summarizes the costs of energy market impacts from implementing the
WEC in the oil and gas markets, which totals $0.2 to 0.3 million in 2024-2025, $22.00 million in
28 This calculation provides an approximate value for the loss of consumer and producer surplus that differs
depending on the relative value of the supply and demand elasticities.
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2026, $19.08 million in 2027, and less than $0.02 in the later years of the analysis period. The
NPV of costs of energy market impacts are $37.6 million at 3% to $33.0 million at 7%.
Table 5-6 Cost of Energy Market Impacts
Year
Cost of Energy Market
Impacts
$ Million3
2024
$0.21
2025
$0.25
2026
$22.00
2027
$19.08
2028
$0.02
2029
$0.01
2030
$0.01
2031
$0.01
2032
$0.01
2033
$0.01
2034
$0.01
2035
$0.01
NPV
2%
$38.9
3%
$37.6
7%
$33.0
EAV
2%
$4.0
3%
$4.1
7%
$4.4
a Cost of energy market impacts refers to loss in consumer and producer surplus resulting from oil and gas
production changes as estimated in the partial equilibrium energy market modeling.
5.3 Emission Impacts
Estimating total methane mitigation and WEC transfer payments includes accounting for
baseline emissions (Section 3), voluntary mitigation (Section 5.1), and market-induced
mitigation (Section 5.2). The market-induced mitigation estimates in this analysis apply a sector-
wide emissions coefficient of 186 metric tons of methane per billion cubic feet of natural gas
times the change in market output. This calculation implicitly assumes that reductions in natural
gas production occurs at facilities with an average emissions rate equal to the sector average.
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The final WEC rule implements a charge for methane emissions that exceed certain
thresholds. In practice, emissions from the oil and natural gas industry do not occur as pure
methane, but as 'whole gas' or natural gas. Natural gas is composed of methane and certain other
chemicals in quantities that vary depending on the natural gas and petroleum industry segment.
Natural gas in the production and gathering and boosting segments include a higher proportion of
compounds other than methane than gas in the transmission and storage segment. Volatile
organic compounds (VOC) and hazardous air pollutants (HAP) emissions are released alongside
methane. VOC and HAP emissions present adverse health consequences discussed in Section
6.2. This analysis relies on a prior study of the composition of natural gas in different segments
to estimate VOC and HAP abatement likely to occur alongside methane abatement. The prior
study of several emissions sources across the natural gas industry estimated that for every metric
ton of methane emissions, 0.277 metric tons of VOCs and 0.01 tons of HAPs are emitted in the
production sector and 0.028 tons of VOCs and 0.8kg of HAPs are emitted in transmission
(Brown, 2011). Table 5-7 summarizes natural gas composition by weight and segment.
Table 5-7 Chemical Composition of Natural Gas by Weight by Segment
Production
Transmission
Methane
0.695
0.908
VOC
0.193
0.0251
HAP
0.00728
0.00074
Source: Brown, 2011.
Table 5-8 summarizes the annual emissions reductions from abatement activities by
pollutant associated with the final WEC rule between 2024 and 2035. The impacts of these
pollutants accrue at different spatial scales. HAP emissions increase exposure to carcinogens and
other toxic pollutants primarily near the emission source. VOC emissions are precursors to
secondary formation of PM2.5 and ozone on a broader region. Methane reductions are largest in
years 2024 through 2026 as cost-effective mitigation options are phased in prior to EG OOOOc
requirements taking effect. After the regulatory compliance exemption takes effect in 2029,
emissions reductions resulting from the WEC decline significantly.29 The remaining reductions
29 EPA expects that the WEC would incentivize adoption of mitigation technologies required under the NSPS/EG.
The cost analysis uses an annualized cost approach, such that breakeven price calculations involve both operating
costs and capital costs spread over the mitigation technology lifetime. The abatement and costs characterized in
this RIA only relate to the time period before those technologies would have been adopted in the baseline.
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associated with the WEC after 2029 relate to facilities in the offshore production segment, which
is not subject to requirements under the NSPS/EG. For context, total reductions average about
33% of WEC-applicable emissions in the baseline before accounting for responses to the WEC.
The market-induced component is a small fraction (about one one-hundredth to one one-
thousandth) of total abatement.
Table 5-8 Projected Annual Reductions of Methane, VOC, HAP Emissions from
Economic Impacts (kt)
Methane
VOCs
HAPs
Market-
Market-
Market-
Year
Mitigated
Induced
Total
Mitigated
Induced
Total
Mitigated
Induced
Total
2024
110
0.1
110
17
0.0
17
0.6
0.0
0.6
2025
220
0.1
220
34
0.0
34
1.2
0.0
1.2
2026
310
1.7
320
47
0.3
48
1.8
0.01
1.8
2027
310
1.6
310
46
0.2
46
1.7
0.01
1.7
2028
42
0.0
42
4.2
0.0
4.2
0.15
0.0
0.15
2029
30
0.0
30
3.0
0.0
3.0
0.11
0.0
0.11
2030
30
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2031
31
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2032
31
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2033
31
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2034
31
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2035
31
0.0
31
3.0
0.0
3.0
0.11
0.0
0.11
2024
1,200
3.7
1,200
170
0.6
170
6.2
0.0
6.2
Table 5-9 presents details related to the calculation of methane reductions from
mitigation using the MACC, further discussed in Appendix C. Total technical abatement
potential represents all technology options represented in the model regardless of costs. Cost-
effective abatement potential is limited to technology options with breakeven costs less than the
WEC. Finally, a phase-in factor is used to account for practical limits in deployment of cost-
effective mitigation in the short term. For additional details on the MACC calculations, see
section 5.1.
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Table 5-9 Methane Mitigation Potential Details
Year
Total Technical
Abatement
Potential (kt)
Cost-Effective
Abatement Below
WEC (kt)
Phase-In Factor
Abatement Incl.
Phase-In (kt)
2024
632
322
0.33
107
2025
613
330
0.67
220
2026
581
314
1
314
2027
567
309
1
309
2028
42
42
1
42
2029
30
30
1
30
2030
30
30
1
30
2031
31
31
1
31
2032
31
31
1
31
2033
31
31
1
31
2034
31
31
1
31
2035
31
31
1
31
Note: See section 5.1 for details on mitigation modeling and assumptions
5.4 WEC Transfer Payments
This analysis estimates WEC-applicable methane emissions in the policy scenario as
baseline WEC-applicable emissions less total methane mitigation. The mitigation comes from a
combination of application of methane mitigation options and energy market changes (although
the reductions from energy market impacts are quite small relative to methane mitigation). Table
5-10 presents projections of WEC-applicable emissions in the policy scenario as constructed
from these components, and projected WEC payments calculated by applying the appropriate
WEC amount, depending on the year. Because the WEC amounts ($900 in 2024, $1200 in 2025,
and $1500 in 2026 and beyond) are nominal dollar amounts, the WEC obligations in Table 5-10
are expressed in undiscounted nominal dollars.
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ble 5
Year
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
Total
24-20
Projected WEC Payments in the Policy Scenario, 2024-2035
Net Methane
Emissions
Subject to
WEC in
Baseline
(thousand
metric tons)
Reductions
from
Methane
Mitigation
(thousand
metric tons)
Reductions
from Energy
Market
Impacts
(thousand
metric tons)
710
110
0.1
680
220
0.1
650
310
1.7
630
310
1.6
77
42
0.05
34
30
0.03
33
30
0.03
33
31
0.03
33
31
0.03
33
31
0.03
32
31
0.03
32
31
0.03
3,000
1,200
3.7
Net Methane
Emissions
Subject to WEC
in Policy
Scenario
(thousand
metric tons)
Charge
Specified by
Congress
(nominal $ per
metric ton)
600
460
340
320
35
3
3
3
2
2
2
1
1,800
$900
$1,200
$1,500
$1,500
$1,500
$1,500
$1,500
$1,500
$1,500
$1,500
$1,500
$1,500
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6 BENEFITS
The final rule is expected to reduce emissions of methane, VOC, and HAP emissions.
This section reports the estimated monetized climate benefits associated with the estimated
emission reductions. In addition to presenting monetized estimates of impacts from methane
reductions, we also provide a qualitative discussion of potential climate, human health, and
welfare impacts of emissions reductions we are unable to quantify and monetize.
The section describes the methods used to estimate the climate benefits from reductions
of CH4 emissions. This analysis uses estimates of the social cost of methane (SC-CH4) to
monetize the estimated changes in CH4 emissions expected to occur over 2024 through 2035 for
the final rule. In principle, SC-CH4 includes the value of all climate change impacts (both
negative and positive), including (but not limited to) changes in net agricultural productivity,
human health effects, property damage from increased flood risk and natural disasters, disruption
of energy systems, risk of conflict, environmental migration, and the value of ecosystem
services. The SC-CH4 therefore, reflects the societal value of reducing emissions of SC-CH4 by
one metric ton and is the theoretically appropriate value to use in conducting benefit-cost
analyses of policies that affect CH4 emissions.
6.1 Climate Benefits Resulting from CH4 Emission Reductions
We estimate the climate benefits of CH4 emissions reductions expected from the final
rule using estimates of the social cost of methane (SC-CH4) that reflect recent advances in the
scientific literature on climate change and its economic impacts and incorporate
recommendations made by the National Academies of Science, Engineering, and Medicine
(National Academies, 2017). The EPA published and used these estimates in the RIA for the
2024 Final NSPS/EG (U.S. EPA, 2023a). The EPA solicited public comment on the
methodology and use of these estimates in the RIA for the agency's December 2022 NSPS/EG
Supplemental Proposal30 and has conducted an external peer review of these estimates, as
described further below.
30 See https://www.epa.gov/environmental-economics/scghg for a copy of the final report and other related
materials.
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The SC-CH4 is the monetary value of the net harm to society from emitting a metric ton
of CH4 into the atmosphere in a given year, or the benefit of avoiding that increase. In principle,
SC-CH4 is a comprehensive metric that includes the value of all future climate change impacts
(both negative and positive), including changes in net agricultural productivity, human health
effects, property damage from increased flood risk, changes in the frequency and severity of
natural disasters, disruption of energy systems, risk of conflict, environmental migration, and the
value of ecosystem services. The SC-CH4, therefore, reflects the societal value of reducing CH4
emissions by one metric ton and is the theoretically appropriate value to use in conducting
benefit-cost analyses of policies that affect CH4 emissions. In practice, data and modeling
limitations restrain the ability of SC-CH4 estimates to include all physical, ecological, and
economic impacts of climate change, implicitly assigning a value of zero to the omitted climate
damages. The estimates are, therefore, a partial accounting of climate change impacts and likely
underestimate the marginal benefits of abatement.
Since 2008, the EPA has used estimates of the social cost of various greenhouse gases
(i.e., social cost of carbon (SC-CO2), social cost of methane (SC-CH4), and social cost of nitrous
oxide (SC-N2O)), collectively referred to as the "social cost of greenhouse gases" (SC-GHG), in
analyses of actions that affect GHG emissions. The values used by the EPA from 2009 to 2016,
and since 2021 have been consistent with those developed and recommended by the Interagency
Working Group on the SC-GHG (IWG); and the values used from 2017 to 2020 were consistent
with those required by E.O. 13783, which disbanded the IWG. During 2015-2017, the National
Academies conducted a comprehensive review of the SC-CO2 and issued a final report in 2017
recommending specific criteria for future updates to the SC-CO2 estimates, a modeling
framework to satisfy the specified criteria, and both near-term updates and longer-term research
needs pertaining to various components of the estimation process (National Academies, 2017).
The IWG was reconstituted in 2021 and E.O. 13990 directed it to develop a comprehensive
update of its SC-GHG estimates, recommendations regarding areas of decision-making to which
SC-GHG should be applied, and a standardized review and updating process to ensure that the
recommended estimates continue to be based on the best available economics and science going
forward.
The EPA is a member of the IWG and is participating in the IWG's work under E.O.
13990. While that process continues, as noted in previous EPA RIAs, the EPA is continuously
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reviewing developments in the scientific literature on the SC-GHG, including more robust
methodologies for estimating damages from emissions, and looking for opportunities to further
improve SC-GHG estimation going forward.31 In the December 2022 Oil and Gas Supplemental
Proposal NSPS RIA, the Agency included a sensitivity analysis of the climate benefits of the
Supplemental Proposal using a new set of SC-GHG estimates that incorporates recent research
addressing recommendations of the National Academies (2017) in addition to using the interim
SC-GHG estimates presented in the Technical Support Document: Social Cost of Carbon,
Methane, and Nitrous Oxide Interim Estimates under Executive Order 13990 (2021) that the
IWG recommended for use until updated estimates that address the National Academies'
recommendations are available
The EPA solicited public comment on the sensitivity analysis and the accompanying draft
technical report, EPA Report on the Social Cost of Greenhouse Gases: Estimates Incorporating
Recent Scientific Advances, which explains the methodology underlying the new set of estimates,
in the December 2022 Supplemental Oil and Gas Proposal.32 The response to comments
document can be found in the docket for that action.
To ensure that the methodological updates adopted in the technical report are consistent
with economic theory and reflect the latest science, the EPA also initiated an external peer
review panel to conduct a high-quality review of the technical report, completed in May 2023.
See 88 FR at 26075/2 noting this peer review process. The peer reviewers commended the
agency on its development of the draft update, calling it a much-needed improvement in
estimating the SC-GHG and a significant step towards addressing the National Academies'
recommendations with defensible modeling choices based on current science. The peer reviewers
provided numerous recommendations for refining the presentation and for future modeling
improvements, especially with respect to climate change impacts and associated damages that
are not currently included in the analysis. Additional discussion of omitted impacts and other
updates have been incorporated in the technical report to address peer reviewer
recommendations. Complete information about the external peer review, including the peer
31 EPA strives to base its analyses on the best available science and economics, consistent with its responsibilities,
for example, under the Information Quality Act.
32 See https://www.epa.gov/environmental-economics/scghg for a copy of the final report and other related
materials.
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reviewer selection process, the final report with individual recommendations from peer
reviewers, and the EPA's response to each recommendation is available on EPA's website.33
The remainder of this section provides an overview of the methodological updates
incorporated into the SC-GHG estimates used in this RIA. A more detailed explanation of each
input and the modeling process is provided in the technical report, Supplementary Material for
the RIA: EPA Report on the Social Cost of Greenhouse Gases: Estimates Incorporating Recent
Scientific Advances (U.S. EPA, 2023b).
The steps necessary to estimate the SC-GHG with a climate change integrated assessment
model (IAM) can generally be grouped into four modules: socioeconomics and emissions,
climate, damages, and discounting. The emissions trajectories from the socioeconomic module
are used to project future temperatures in the climate module. The damage module then
translates the temperature and other climate endpoints (along with the projections of
socioeconomic variables) into physical impacts and associated monetized economic damages,
where the damages are calculated as the amount of money the individuals experiencing the
climate change impacts would be willing to pay to avoid them. To calculate the marginal effect
of emissions, i.e., the SC-GHG in year t, the entire model is run twice - first as a baseline and
second with an additional pulse of emissions in year t. After recalculating the temperature effects
and damages expected in all years beyond t resulting from the adjusted path of emissions, the
losses are discounted to a present value in the discounting module. Many sources of uncertainty
in the estimation process are incorporated using Monte Carlo techniques by taking draws from
probability distributions that reflect the uncertainty in parameters.
The SC-GHG estimates used by the EPA and many other federal agencies since 2009
have relied on an ensemble of three widely used IAMs: Dynamic Integrated Climate and
Economy (DICE) (Nordhaus, 2010); Climate Framework for Uncertainty, Negotiation, and
Distribution (FUND) (Anthoff & Tol, 2013a, 2013b ); and Policy Analysis of the Greenhouse
Gas Effect (PAGE) (Hope, 2013). In 2010, the IWG harmonized key inputs across the IAMs, but
all other model features were left unchanged, relying on the model developers' best estimates
33 https://www.epa.gov/environmental-economics/scghg-tsd-peer-review
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and judgments. That is, the representation of climate dynamics and damage functions included in
the default version of each IAM as used in the published literature was retained.
The SC-GHG estimates in this RIA no longer rely on the three IAMs (i.e., DICE, FUND,
and PAGE) used in previous SC-GHG estimates. Instead, EPA uses a modular approach to
estimating the SC-GHG, consistent with the National Academies' 2017 near-term
recommendations. That is, the methodology underlying each component, or module, of the SC-
GHG estimation process is developed by drawing on the latest research and expertise from the
scientific disciplines relevant to that component. Under this approach, each step in the SC-GHG
estimation improves consistency with the current state of scientific knowledge, enhances
transparency, and allows for more explicit representation of uncertainty.
The socioeconomic and emissions module relies on a new set of probabilistic projections
for population, income, and GHG emissions developed under the Resources for the Future (RFF)
Social Cost of Carbon Initiative (Rennert, Prest, et al., 2022). These socioeconomic projections
(hereafter collectively referred to as the RFF-SPs) are an internally consistent set of probabilistic
projections of population, GDP, and GHG emissions (CO2, CH4, and N2O) to 2300. Based on a
review of available sources of long-run projections necessary for damage calculations, the RFF-
SPs stand out as being most consistent with the National Academies' recommendations.
Consistent with the National Academies' recommendation, the RFF-SPs were developed using a
mix of statistical and expert elicitation techniques to capture uncertainty in a single probabilistic
approach, taking into account the likelihood of future emissions mitigation policies and
technological developments, and provide the level of disaggregation necessary for damage
calculations. Unlike other sources of projections, they provide inputs for estimation out to 2300
without further extrapolation assumptions. Conditional on the modeling conducted for the SC-
GHG estimates, this time horizon is far enough in the future to capture the majority of
discounted climate damages. Including damages beyond 2300 would increase the estimates of
the SC-GHG. As discussed in (U.S. EPA, 2023b), the use of the RFF-SPs allows for capturing
economic growth uncertainty within the discounting module.
The climate module relies on the Finite Amplitude Impulse Response (FaIR) model
(IPCC, 2021b; Millar et al., 2017; Smith et al., 2018), a widely used Earth system model which
captures the relationships between GHG emissions, atmospheric GHG concentrations, and global
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mean surface temperature. The FaIR model was originally developed by Richard Millar, Zeb
Nicholls, and Myles Allen at Oxford University, as a modification of the approach used in IPCC
AR5 to assess the GWP and GTP (Global Temperature Potential) of different gases. It is open
source, widely used (e.g., IPCC (2018, 2021a)), and was highlighted by the (National
Academies, 2017) as a model that satisfies their recommendations for a near-term update of the
climate module in SC-GHG estimation. Specifically, it translates GHG emissions into mean
surface temperature response and represents the current understanding of the climate and GHG
cycle systems and associated uncertainties within a probabilistic framework. The SC-GHG
estimates used in this RIA rely on FaIR version 1.6.2 as used by the IPCC (2021a). It provides,
with high confidence, an accurate representation of the latest scientific consensus on the
relationship between global emissions and global mean surface temperature, offers a code base
that is fully transparent and available online, and the uncertainty capabilities in FaIR 1.6.2 have
been calibrated to the most recent assessment of the IPCC (which importantly narrowed the
range of likely climate sensitivities relative to prior assessments). See U.S. EPA (2023a) for
more details.
The socioeconomic projections and outputs of the climate module are inputs into the
damage module to estimate monetized future damages from climate change.34 The National
Academies' recommendations for the damage module, scientific literature on climate damages,
updates to models that have been developed since 2010, as well as the public comments received
on individual EPA rulemakings and the IWG's February 2021 TSD, have all helped to identify
available sources of improved damage functions. The IWG (e.g., IWG 2010, 2016a, 2021), the
National Academies (2017), comprehensive studies (e.g., Rose et al. (2014)), and public
comments have all recognized that the damages functions underlying the IWG SC-GHG
estimates used since 2013 (taken from DICE 2010 (Nordhaus, 2010); FUND 3.8 (Anthoff & Tol,
2013a, 2013b); and PAGE 2009 (Hope, 2013)) do not include all the important physical,
ecological, and economic impacts of climate change. The climate change literature and the
34 In addition to temperature change, two of the three damage modules used in the SC-GHG estimation require
global mean sea level (GMSL) projections as an input to estimate coastal damages. Those two damage modules
use different models for generating estimates of GMSL. Both are based off reduced complexity models that can
use the FaIR temperature outputs as inputs to the model and generate projections of GMSL accounting for the
contributions of thermal expansion and glacial and ice sheet melting based on recent scientific research. Absent
clear evidence on a preferred model, the SC-GHG estimates presented in this RIA retain both methods used by
the damage module developers. See U.S. EPA (2023a).for more detail.
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science underlying the economic damage functions have evolved, and DICE 2010, FUND 3.8,
and PAGE 2009 now lag behind the most recent research.
The challenges involved with updating damage functions have been widely recognized.
Functional forms and calibrations are constrained by the available literature and need to
extrapolate beyond warming levels or locations studied in that literature. Research focused on
understanding how these physical changes translate into economic impacts is still developing,
and has received less public resources, relative to the research focused on modeling and
improving our understanding of climate system dynamics and the physical impacts from climate
change (Auffhammer, 2018). Even so, there has been a large increase in research on climate
impacts and damages in the time since DICE 2010, FUND 3.8, and PAGE 2009 were published.
Along with this growth, there continues to be variation in methodologies and scope of studies,
such that care is required when synthesizing the current understanding of impacts or damages.
Based on a review of available studies and approaches to damage function estimation, the EPA
uses three separate damage functions to form the damage module. They are:
A subnational-scale, sectoral damage function (based on the Data-driven Spatial Climate
Impact Model (DSCIM) developed by the Climate Impact Lab (Carleton et al., 2022; Climate
Impact Lab (CIL), 2023; Rode et al., 2021), a country-scale, sectoral damage function (based on
the Greenhouse Gas Impact Value Estimator (GIVE) model developed under RFF's Social Cost
of Carbon Initiative (Rennert, Errickson, et al., 2022), and a meta-analysis-based damage
function (based on Howard and Sterner (2017)). The damage functions in DSCIM and GIVE
represent substantial improvements relative to the damage functions underlying the SC-GHG
estimates used by the EPA to date and reflect the forefront of scientific understanding about how
temperature change and SLR lead to monetized net (market and nonmarket) damages for several
categories of climate impacts. The models' spatially explicit and impact-specific modeling of
relevant processes allows for improved understanding and transparency about mechanisms
through which climate impacts are occurring and how each damage component contributes to the
overall results, consistent with the National Academies' recommendations. DSCIM addresses
common criticisms related to the damage functions underlying current SC-GHG estimates (e.g.,
Pindyck (2017)) by developing multi-sector, empirically grounded damage functions. The
damage functions in the GIVE model offer a direct implementation of the National Academies'
near-term recommendation to develop updated sectoral damage functions that are based on
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recently published work and reflective of the current state of knowledge about damages in each
sector. Specifically, the National Academies noted that "[t]he literature on agriculture, mortality,
coastal damages, and energy demand provide immediate opportunities to update the [models]"
(National Academies 2017, p. 199), which are the four damage categories currently in GIVE. A
limitation of both models is that the sectoral coverage is still limited, and even the categories that
are represented are incomplete. Neither DSCIM nor GIVE yet accommodate estimation of
several categories of temperature driven climate impacts (e.g., morbidity, conflict, migration,
biodiversity loss) and only represent a limited subset of damages from changes in precipitation.
For example, while precipitation is considered in the agriculture sectors in both DSCIM and
GIVE, neither model takes into account impacts of flooding, changes in rainfall from tropical
storms, and other precipitation related impacts. As another example, the coastal damage
estimates in both models do not fully reflect the consequences of SLR-driven salt-water intrusion
and erosion, or SLR damages to coastal tourism and recreation. Other missing elements are
damages that result from other physical impacts (e.g., ocean acidification, non-temperature-
related mortality such as diarrheal disease and malaria) and the many feedbacks and interactions
across sectors and regions that can lead to additional damages.35 See U.S. EPA (2023a) for more
discussion of omitted damage categories and other modeling limitations. DSCIM and GIVE do
account for the most commonly cited benefits associated with CO2 emissions and climate change
— CO2 crop fertilization and declines in cold related mortality. As such, while the GIVE- and
DSCIM-based results provide state-of-the-science assessments of key climate change impacts,
they remain partial estimates of future climate damages resulting from incremental changes in
C02, CH4, and N2O.36
Finally, given the still relatively narrow sectoral scope of the recently developed DSCIM
and GIVE models, the damage module includes a third damage function that reflects a synthesis
of the state of knowledge in other published climate damages literature. Studies that employ
meta-analytic techniques offer a tractable and straightforward way to combine the results of
multiple studies into a single damage function that represents the body of evidence on climate
35 The one exception is that the agricultural damage function in DSCIM and GIVE reflects the ways that trade can
help mitigate damages arising from crop yield impacts.
36 One advantage of the modular approach used by these models is that future research on new or alternative damage
functions can be incorporated in a relatively straightforward way. DSCIM and GIVE developers have work
underway on other impact categories that may be ready for consideration in future updates (e.g., morbidity and
biodiversity loss).
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damages that pre-date CIL and RFF's research initiatives.37 The first use of meta-analysis to
combine multiple climate damage studies was done by Tol (2009) and included 14 studies. The
studies in Tol (2009) served as the basis for the global damage function in DICE starting in
version 2013R (Nordhaus, 2014). The damage function in the most recent published version of
DICE, DICE 2016, is from an updated meta-analysis based on a rereview of existing damage
studies and included 26 studies published over 1994-2013 (Nordhaus & Moffat, 2017). Howard
and Sterner (2017) provide a more recent published peer-reviewed meta-analysis of existing
damage studies (published through 2016) and account for additional features of the underlying
studies. They address differences in measurement across studies by adjusting estimates such that
the data are relative to the same base period. They also eliminate double counting by removing
duplicative estimates. Howard and Sterner's final sample is drawn from 20 studies that were
published through 2015. Howard and Sterner (2017) present results under several specifications,
and their analysis shows that the estimates are somewhat sensitive to defensible alternative
modeling choices. As discussed in detail in U.S. EPA (2023a), the damage module underlying
the SC-GHG estimates in this RIA includes the damage function specification (that excludes
duplicate studies) from Howard and Sterner (2017) that leads to the lowest SC-GHG estimates,
all else equal.
The discounting module discounts the stream of future net climate damages to its present
value in the year when the additional unit of emissions was released. Given the long-time
horizon over which the damages are expected to occur, the discount rate has a large influence on
the present value of future damages. Consistent with the findings of National Academies (2017),
the economic literature, OMB Circular A-4's guidance for regulatory analysis, and IWG
recommendations to date (IWG, 2010, 2013, 2016a, 2016b, 2021), the EPA continues to
conclude that the consumption rate of interest is the theoretically appropriate discount rate to
discount the future benefits of reducing GHG emissions and that discount rate uncertainty should
be accounted for in selecting future discount rates in this intergenerational context. OMB's
Circular A-4 (2003) points out that "the analytically preferred method of handling temporal
differences between benefits and costs is to adjust all the benefits and costs to reflect their value
37 Meta-analysis is a statistical method of pooling data and/or results from a set of comparable studies of a problem.
Pooling in this way provides a larger sample size for evaluation and allows for a stronger conclusion than can be
provided by any single study. Meta-analysis yields a quantitative summary of the combined results and current
state of the literature.
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in equivalent units of consumption and to discount them at the rate consumers and savers would
normally use in discounting future consumption benefits" (OMB, 20 03).38 The damage module
described above calculates future net damages in terms of reduced consumption (or monetary
consumption equivalents), and so an application of this guidance is to use the consumption
discount rate to calculate the SC-GHG. Thus, EPA concludes that the use of the discount rate
estimated using the average return on capital (7 percent in OMB Circular A-4 (2003)), which
does not reflect the consumption rate, to discount damages estimated in terms of reduced
consumption would inappropriately underestimate the impacts of climate change for the
purposes of estimating the SC-GHG.39
For the SC-GHG estimates used in this RIA, EPA relies on a dynamic discounting
approach that more fully captures the role of uncertainty in the discount rate in a manner
consistent with the other modules. Based on a review of the literature and data on consumption
discount rates, the public comments received on individual EPA rulemakings, and the February
2021 TSD (IWG, 2021), and the National Academies (2017) recommendations for updating the
discounting module, the SC-GHG estimates rely on discount rates that reflect more recent data
on the consumption interest rate and uncertainty in future rates. Specifically, rather than using a
constant discount rate, the evolution of the discount rate over time is defined following the latest
empirical evidence on interest rate uncertainty and using a framework originally developed by
Ramsey (1928) that connects economic growth and interest rates. The Ramsey approach
explicitly reflects (1) preferences for utility in one period relative to utility in a later period and
(2) the value of additional consumption as income changes. The dynamic discount rates used to
develop the SC-GHG estimates applied in this RIA have been calibrated following the Newell et
al. (2022) approach, as applied in Rennert, Errickson, et al. (2022); Rennert, Prest, et al. (2022).
This approach uses the Ramsey (1928) discounting formula in which the parameters are
calibrated such that (1) the decline in the certainty-equivalent discount rate matches the latest
empirical evidence on interest rate uncertainty estimated by Bauer and Rudebusch (2020, 2023)
and (2) the average of the certainty-equivalent discount rate over the first decade matches a near-
38 Similarly, OMB's Circular A-4 (2023) points out that "The analytically preferred method of handling temporal
differences between benefits and costs is to adjust all the benefits and costs to reflect their value in equivalent
units of consumption before discounting them" (OMB 2023).
39 See also the discussion of the inappropriateness of discounting consumption-equivalent measures of benefits and
costs using a rate of return on capital in Circular A-4 (OMB 2023).
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term consumption rate of interest. Uncertainty in the starting rate is addressed by using three
near-term target rates (1.5, 2.0, and 2.5 percent) based on multiple lines of evidence on observed
market interest rates.
The resulting dynamic discount rate provides a notable improvement over the constant
discount rate framework used for SC-GHG estimation in previous EPA RIAs. Specifically, it
provides internal consistency within the modeling and a more complete accounting of
uncertainty consistent with economic theory (Arrow et al., 2013; Cropper et al., 2014) and the
National Academies' (2017) recommendation to employ a more structural, Ramsey-like
approach to discounting that explicitly recognizes the relationship between economic growth and
discounting uncertainty. This approach is also consistent with the National Academies (2017)
recommendation to use three sets of Ramsey parameters that reflect a range of near-term
certainty-equivalent discount rates and are consistent with theory and empirical evidence on
consumption rate uncertainty. Finally, the value of aversion to risk associated with net damages
from GHG emissions is explicitly incorporated into the modeling framework following the
economic literature. See U.S. EPA (2023a) for a more detailed discussion of the entire
discounting module and methodology used to value risk aversion in the SC-GHG estimates.
Taken together, the methodologies adopted in this SC-GHG estimation process allow for
a more holistic treatment of uncertainty than in past estimates by the EPA. The updates
incorporate a quantitative consideration of uncertainty into all modules and use a Monte Carlo
approach that captures the compounding of uncertainties across modules. The estimation process
generates nine separate distributions of discounted marginal damages per metric ton - the
product of using three damage modules and three near-term target discount rates - for each gas
in each emissions year. These distributions have long right tails reflecting the extensive evidence
in the scientific and economic literature that shows the potential for lower-probability but higher-
impact outcomes from climate change, which would be particularly harmful to society. The
uncertainty grows over the modeled time horizon. Therefore, under cases with a lower near-term
target discount rate - that give relatively more weight to impacts in the future - the distribution
of results is wider. To produce a range of estimates that reflects the uncertainty in the estimation
exercise while also providing a manageable number of estimates for policy analysis, the EPA
combines the multiple lines of evidence on damage modules by averaging the results across the
three damage module specifications. The full results generated from the updated methodology
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for methane and other greenhouse gases (SC-CO2, SC-CH4, and SC-N2O) for emissions years
2020 through 2080 are provided in U.S. EPA (2023a).
Table 6-1 summarizes the resulting averaged certainty-equivalent SC-CH4 estimates
under each near-term discount rate that are used to estimate the climate benefits of the CH4
emission reductions expected from the final rule. These estimates are reported in 2019 dollars
but are otherwise identical to those presented in U.S. EPA (2023a). The SC-CH4 increases over
time within the models — i.e., the societal harm from one metric ton emitted in 2030 is higher
than the harm caused by one metric ton emitted in 2024 — because future emissions produce
larger incremental damages as physical and economic systems become more stressed in response
to greater climatic change, and because GDP is growing over time and many damage categories
are modeled as proportional to GDP.
Table 6-1 Estimates of the Social Cost of CH4, 2024-2035 (in 2019$ per metric ton CH4)
Near-Term Ramsey Discount Rate
Year
1.5%
2.0%
2.5%
2024
$2,600
$1,900
$1,500
2025
$2,700
$2,000
$1,600
2026
$2,800
$2,100
$1,600
2027
$2,900
$2,200
$1,700
2028
$3,000
$2,200
$1,800
2029
$3,000
$2,300
$1,800
2030
$3,100
$2,400
$1,900
2031
$3,200
$2,500
$2,000
2032
$3,300
$2,500
$2,100
2033
$3,400
$2,600
$2,100
2034
$3,500
$2,700
$2,200
2035
$3,600
$2,800
$2,300
Source: U.S. EPA (2023a).
Note: These SC-CH4 values are identical to those reported in the technical report U.S. EPA (2023a)
adjusted for inflation to 2019 dollars using the annual GDP Implicit Price Deflator values in the U.S.
Bureau of Economic Analysis' (BEA) NIPA Table 1.1.9. The values are stated in $/metric ton CH4 and
vary depending on the year of CH4 emissions. This table displays the values rounded to two significant
figures. The annual unrounded values used in the calculations in this RIA are available in Appendix A.5
of U.S. EPA (2023a) and at: www.epa.gov/environmental-economics/scghg.
The methodological updates described above represent a major step forward in bringing
SC-GHG estimation closer to the frontier of climate science and economics and address many of
the National Academies' (2017) near-term recommendations. Nevertheless, the resulting SC-
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GHG estimates, including the SC-CH4 estimates presented in Table 6-1, still have several
limitations, as would be expected for any modeling exercise that covers such a broad scope of
scientific and economic issues across a complex global landscape. There are still many
categories of climate impacts and associated damages that are only partially or not reflected yet
in these estimates and sources of uncertainty that have not been fully characterized due to data
and modeling limitations. For example, the modeling omits most of the consequences of changes
in precipitation, damages from extreme weather events, the potential for nongradual damages
from passing critical thresholds (e.g., tipping elements) in natural or socioeconomic systems, and
non-climate mediated effects of GHG emissions. The SC-CH4 estimates do not account for the
direct health and welfare impacts associated with tropospheric ozone produced by methane. As
discussed further in U.S. EPA (2023a), recent studies have found the global ozone-related
respiratory mortality benefits of CH4 emissions reductions, which are not included in the SC-CH4
values presented in Table 6-1, to be, in 2019 dollars, approximately $2,400 per metric ton of
methane emissions in 2030 (McDuffie et al., 2023). In addition, the SC-CH4 estimates do not
reflect that methane emissions lead to a reduction in atmospheric oxidants, like hydroxyl
radicals, nor do they account for impacts associated with CO2 produced from methane oxidizing
in the atmosphere. Importantly, the updated SC-GHG methodology does not yet reflect
interactions and feedback effects within, and across, Earth and human systems. For example, it
does not explicitly reflect potential interactions among damage categories, such as those
stemming from the interdependencies of energy, water, and land use. These, and other,
interactions and feedbacks were highlighted by the National Academies as an important area of
future research for longer-term enhancements in the SC-GHG estimation framework.
Tables 6-2 through 6-4 present the annual, monetized climate benefits under the final
WEC. Projected methane emissions reductions each year are multiplied by the SC-CH4 estimate
for that year from Table 6-1. Table 6-5 shows the annual climate benefits discounted back to
2023 and the PV and the EAV for the 2024-2035 period under each discount rate. In this
analysis, to calculate the present and annualized values of climate benefits, EPA uses the same
discount rate as the near-term target Ramsey rate used to discount the climate benefits from
future CH4 reductions. That is, future climate benefits estimated with the SC-CH4 at the near-
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term 2 percent Ramsey rate are discounted to the base year of the analysis using the same 2
percent rate.40
Table 6-2 Undiscounted Monetized Climate Benefits from Methane Mitigation under
the WEC, 2024-2035 (millions, 2019$)
Near-Term Ramsey Discount Rate (Annual Undiscounted)
Year
1.5%
2%
2.5%
2024
$280
$210
$160
2025
$590
$440
$350
2026
$880
$650
$510
2027
$890
$670
$530
2028
$120
$94
$75
2029
$93
$70
$56
2030
$96
$72
$58
2031
$99
$75
$60
2032
$100
$78
$63
2033
$110
$81
$65
2034
$110
$84
$68
2035
$110
$86
$70
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
40 As discussed in U.S. EPA. (2023a) the error associated with using a constant discount rate rather than the
certainty-equivalent rate path to calculate the present value of a future stream of monetized climate benefits is
small for analyses with moderate time frames (e.g., 30 years or less). EPA (2023a) also provides an illustration of
the amount that climate benefits from reductions in future emissions will be underestimated by using a constant
discount rate relative to the more complicated certainty-equivalent rate path.
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Table 6-3 Undiscounted Monetized Climate Benefits from Partial Equilibrium Model
under the WEC, 2024-2035 (millions, 2019$)
Year
Near-Term Ramsey Discount Rate (Annual Undiscounted)a
1.5%
2%
2.5%
2024
$0.3
$0.2
$0.2
2025
$0.3
$0.2
$0.2
2026
$4.7
$3.5
$2.8
2027
$4.6
$3.4
$2.7
2028
$0.1
$0.1
$0.1
2029
$0.1
$0.1
$0.1
2030
$0.1
$0.1
$0.1
2031
$0.1
$0.1
$0.1
2032
$0.1
$0.1
$0.1
2033
$0.1
$0.1
$0.1
2034
$0.1
$0.1
$0.1
2035
$0.1
$0.1
$0.1
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
Table 6-4 Undiscounted Total Monetized Climate Benefits under the WEC, 2024-2035
(millions, 2019$)
Near-Term Ramsey Discount Rate (Annual Undiscounted)3
Year
1.5%
2%
2.5%
2024
$280
$210
$160
2025
$590
$440
$350
2026
$880
$660
$520
2027
$890
$670
$530
2028
$130
$94
$75
2029
$93
$70
$56
2030
$96
$72
$58
2031
$99
$75
$61
2032
$100
$78
$63
2033
$110
$81
$65
2034
$110
$84
$68
2035
$110
$86
$70
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
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Table 6-5 Discounted Monetized Climate Benefits under the WEC, 2024-2035
(millions, 2019$)
Discounted back to 2023a
Year
1.5%
2%
2.5%
2024
$280
$200
$160
2025
$580
$420
$330
2026
$840
$620
$480
2027
$840
$620
$480
2028
$120
$85
$66
2029
$85
$62
$48
2030
$86
$63
$49
2031
$88
$64
$50
2032
$89
$65
$50
2033
$91
$66
$51
2034
$92
$67
$52
2035
$93
$68
$52
PV
$3,300
$2,400
$1,900
EAV
$300
$230
$180
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
Unlike many environmental problems where the causes and impacts are distributed more
locally, GHG emissions are a global externality making climate change a true global challenge.
GHG emissions contribute to damages around the world regardless of where they are emitted.
Because of the distinctive global nature of climate change, in the RIA for this final rule the EPA
centers attention on a global measure of climate benefits from CH4 reductions. Consistent with
all IWG recommended SC-GHG estimates to date, the SC-CH4 values presented in Table 6-1
provide a global measure of monetized damages from CH4 emissions, and Tables 6-2 through 6-
5 present the monetized global climate benefits of the CH4 emission reductions expected from
the final rule. This approach is the same as that taken in EPA regulatory analyses from 2009
through 2016 and since 2021. It is also consistent with guidance in OMB Circular A-4 (2003,
2023) that recommends reporting of important international effects.41 EPA also notes that EPA's
41 The 2003 version of OMB Circular A-4 states when a regulation is likely to have international effects, "these
effects should be reported"; while OMB Circular A-4 recommends that international effects we reported
separately, the guidance also explains that "[different regulations may call for different emphases in the analysis,
depending on the nature and complexity of the regulatory issues." (OMB, 2003).
The 2023 update to Circular A-4 states that "In certain contexts, it may be particularly appropriate to include effects
experienced by noncitizens residing abroad in your primary analysis. Such contexts include, for example, when:
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cost estimates in RIAs, including the cost estimates contained in this RIA, regularly do not
differentiate between the share of compliance costs expected to accrue to U.S. firms versus
foreign interests, such as to foreign investors in regulated entities.42 A global perspective on
climate effects is therefore consistent with the approach EPA takes on costs. There are many
reasons, as summarized in this section — and as articulated by OMB and in IWG assessments
(IWG2010, 2013, 2016a, 2016b, 2021), the 2015 Response to Comments (IWG 2015), and in
detail in EPA (2023 a) and in Appendix A of the Response to Comments document for the 2024
Final Oil and Gas NSPS/EG — why the EPA focuses on the global value of climate change
impacts when analyzing policies that affect GHG emissions.
International cooperation and reciprocity are essential to successfully addressing climate
change, as the global nature of greenhouse gases means that a ton of GHGs emitted in any other
country harms those in the U.S. just as much as a ton emitted within the territorial U.S.
Assessing the benefits of U.S. GHG mitigation activities requires consideration of how those
actions may affect mitigation activities by other countries, as those international mitigation
actions will provide a benefit to U.S. citizens and residents by mitigating climate impacts that
affect U.S. citizens and residents. This is a classic public goods problem because each country's
reductions benefit everyone else, and no country can be excluded from enjoying the benefits of
other countries' reductions. The only way to achieve an efficient allocation of resources for
• assessing effects on noncitizens residing abroad provides a useful proxy for effects on U.S. citizens and residents
that are difficult to otherwise estimate;
• assessing effects on noncitizens residing abroad provides a useful proxy for effects on U.S. national interests that
are not otherwise fully captured by effects experienced by particular U.S. citizens and residents (e.g., national
security interests, diplomatic interests, etc.);
• regulating an externality on the basis of its global effects supports a cooperative international approach to the
regulation of the externality by potentially inducing other countries to follow suit or maintain existing efforts; or
• international or domestic legal obligations require or support a global calculation of regulatory effects" (OMB
2023). Due to the global nature of the climate change problem, the OMB recommendations of appropriate
contexts for considering international effects are relevant to the CO2 emission reductions expected from the final
rule. For example, as discussed in this RIA, a global focus in evaluating the climate impacts of changes in CO2
emissions supports a cooperative international approach to GHG mitigation by potentially inducing other
countries to follow suit or maintain existing efforts, and the global SC-CO2 estimates better capture effects on
U.S. citizens and residents and U.S. national interests that are difficult to estimate and not otherwise fully
captured.
42 For example, in the RIA for the 2018 Proposed Reconsideration of the Oil and Natural Gas Sector Emission
Standards for New, Reconstructed, and Modified Sources, the EPA acknowledged that some portion of regulatory
costs will likely "accru[e] to entities outside U.S. borders" through foreign ownership, employment, or
consumption (EPA 2018, p. 3-13). In general, a significant share of U.S. corporate debt and equities are foreign-
owned, including in the oil and gas industry.
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emissions reduction on a global basis — and so benefit the U.S. and its citizens and residents —
is for all countries to base their policies on global estimates of damages. A wide range of
scientific and economic experts have emphasized the issue of international cooperation and
reciprocity as support for assessing global damages of GHG emission in domestic policy
analysis. Using a global estimate of damages in U.S. analyses of regulatory actions allows the
U.S. to continue to actively encourage other nations, including emerging major economies, to
also assess global climate damages of their policies and to take steps to reduce emissions. For
example, many countries and international institutions have already explicitly adapted the global
SC-GHG estimates used by EPA in their domestic analyses (e.g., Canada, Israel) or developed
their own estimates of global damages (e.g., Germany), and recently, there has been renewed
interest by other countries to update their estimates since the draft release of the updated SC-
GHG estimates presented in the December 2022 Oil and Gas NSPS/EG Supplemental Proposal
RIA.43 Several recent studies have empirically examined the evidence on international GHG
mitigation reciprocity, through both policy diffusion and technology diffusion effects. See U.S.
EPA (2023a) for more discussion.
For all of these reasons, the EPA believes that a global metric is appropriate for assessing
the climate benefits of avoided methane emissions in this final RIA. In addition, as emphasized
in the National Academies (2017) recommendations, "[i]t is important to consider what
constitutes a domestic impact in the case of a global pollutant that could have international
implications that impact the United States." The global nature of GHG pollution and its impacts
means that U.S. interests are affected by climate change impacts through a multitude of pathways
and these need to be considered when evaluating the benefits of GHG mitigation to U.S. citizens
and residents. The increasing interconnectedness of global economy and populations means that
impacts occurring outside of U.S. borders can have significant impacts on U.S. interests.
Examples of affected interests include direct effects on U.S. citizens and assets located abroad,
international trade, and tourism, and spillover pathways such as economic and political
destabilization and global migration that can lead to adverse impacts on U.S. national security,
43 In April 2023, the government of Canada announced the publication of an interim update to their SC-GHG
guidance, recommending SC-GHG estimates identical to the EPA's updated estimates presented in the December
2022 Supplemental Proposal RIA. The Canadian interim guidance will be used across all federal departments and
agencies, with the values expected to be finalized by the end of the year, https://www.canada.ca/en/environment-
climate-change/services/climate-change/science-research-data/social-cost-ghg.html.
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public health, and humanitarian concerns. Those impacts point to the global nature of the climate
change problem and are better captured within global measures of the social cost of greenhouse
gases.
In the case of this global pollutant, for the reasons articulated in this section, the
assessment of global net damages of GHG emissions allows EPA to fully disclose and
contextualize the net climate benefits of the CH4 emission reductions expected from this final
rule. The EPA disagrees with commenters on the December 2022 Oil and Gas NSPS/EG
Supplemental Proposal that suggested that the EPA can or should use a metric focused on
benefits resulting solely from changes in climate impacts occurring within U.S. borders. The
global models used in the SC-GHG modeling described above do not lend themselves to be
disaggregated in a way that could provide comprehensive information about the distribution of
the rule's climate benefits to citizens and residents of particular countries, or population groups
across the globe and within the U.S. Two of the models used to inform the damage module, the
GIVE and DSCIM models, have spatial resolution that allows for some geographic
disaggregation of a subset of climate impacts across the world. This permits the calculation of a
partial GIVE and DSCIM-based SC-GHG measuring the damages from four or five climate
impact categories (respectively) projected to physically occur within the U.S., subject to caveats.
As discussed at length in U.S. EPA (2023a) these damage modules are only a partial accounting
and do not capture many significant pathways through which climate change affects public
health and welfare. For example, this modeling omits most of the consequences of changes in
precipitation, damages from extreme weather events (e.g., wildfires), the potential for nongradual
damages from passing critical thresholds (e.g., tipping elements) in natural or socioeconomic
systems, and non-climate mediated effects of GHG emissions other than CO2 fertilization (e.g.,
tropospheric ozone formation due to CH4 emissions). Thus, this modeling only cover a subset of
potential climate change impacts. Furthermore, the damage modules do not capture spillover or
indirect effects whereby climate impacts in one country or region can affect the welfare of
residents in other countries or regions — such as how economic and health conditions across
countries will impact U.S. business, investments, and travel abroad.
Additional modeling efforts can and have shed further light on some omitted damage
categories. For example, the Framework for Evaluating Damages and Impacts (FrEDI) is an
open-source modeling framework developed by the EPA to facilitate the characterization of net
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annual climate change impacts in numerous impact categories within the contiguous U.S. and
monetize the associated distribution of modeled damages (Sarofim et al., 2021; U.S. EPA,
2021a).44 The additional impact categories included in FrEDI reflect the availability of U.S.-
specific data and research on climate change effects. As discussed in U.S. EPA (2023a), results
from FrEDI show that annual damages resulting from climate change impacts within the
contiguous U.S. (CONUS) (i.e., excluding Hawaii, Alaska, and U.S. territories) and for impact
categories not represented in GIVE and DSCIM are expected to be substantial. For example,
FrEDI estimates a partial SC-CH4 of $590/mtCH4 for damages physically occurring within
CONUS for 2030 emissions (under a 2 percent near-term Ramsey discount rate) (Hartin et al.,
2023), compared to a GIVE and DSCIM-based U.S.-specific SC-CH4 of $280/mtCH4 and
$75/mtCH4, respectively, for 2030 emissions. While the FrEDI results help to illustrate how
monetized damages physically occurring within CONUS increase as more impacts are reflected
in the modeling framework, they are still subject to many of the same limitations associated with
the DSCIM and GIVE damage modules, including the omission or partial modeling of important
damage categories.45 Finally, none of these modeling efforts — GIVE, DSCIM, and FrEDI —
reflect non-climate mediated effects of GHG emissions experienced by U.S. populations (other
than CO2 fertilization effects on agriculture). As one example of new research on non-climate
mediated effects of methane emissions, McDuffie et al. (2023) estimate the monetized increase
in respiratory-related human mortality risk from the ozone produced from a marginal pulse of
methane emissions. Using the socioeconomics from the RFF-SPs and the 2 percent near-term
44 The FrEDI framework and Technical Documentation have been subject to a public review comment period and an
independent external peer review, following guidance in the EPA Peer-Review Handbook for Influential
Scientific Information (ISI). Information on the FrEDI peer-review is available at the EPA Science Inventory
EPA Science Inventory. (2021). Technical Documentation on The Framework for Evaluating Damages and
Impacts (FrEDI). Retrieved February 16, 2023 from
https://cfpub.epa.gov/si/si_public_record_report. cfm?dirEntryId=351316&Lab=OAP&simplesearch=0&showcrit
eria=2&sortby=pubDate&searchall=fredi&timstype=&datebeginpublishedpresented=02/14/2021.
45 Another method that has produced estimates of the effect of climate change on U.S.-specific outcomes uses a top-
down approach to estimate aggregate damage functions. Published research using this approach include total-
economy empirical studies that econometrically estimate the relationship between GDP and a climate variable,
usually temperature. As discussed in U.S. EPA. (2023a)., the modeling framework used in the existing published
studies using this approach differ in important ways from the inputs underlying the SC-GHG estimates described
above (e.g., discounting, risk aversion, and scenario uncertainty) and focus solely on CO2. Hence, we do not
consider this line of evidence in the analysis for this RIA. Updating the framework of total-economy empirical
damage functions to be consistent with the methods described in this RIA and ibid, would require new analysis.
Finally, because total-economy empirical studies estimate market impacts, they do not include non-market
impacts of climate change (e.g., mortality impacts) and therefore are also only a partial estimate. The EPA will
continue to review developments in the literature and explore ways to better inform the public of the full range of
GHG impacts.
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Ramsey discounting approach, this additional risk to U.S. populations is on the order of
approximately $320/mtCH4 for 2030 emissions (U.S. EPA 2023a).
Applying the U.S.-specific partial SC-CH4 estimates derived from the evidence described
above to the CH4 emissions reduction expected under the WEC final rule would yield substantial
benefits. For example, the present value of the climate benefits of the final rule as measured by
FrEDI using additional U.S.-specific data and research on climate change impacts in CONUS are
estimated to be $620 million (under a 2 percent near-term Ramsey discount rate).46 However,
even with these additional impact categories, the numerous explicitly omitted damage categories
and other modeling limitations discussed above and throughout U.S. EPA (2023a) make it likely
that these estimates underestimate the benefits to U.S. citizens and residents of the CH4
reductions from the final rule; the limitations in developing a U.S.-specific estimate that
accurately captures direct and spillover effects on U.S. citizens and residents further
demonstrates that it is more appropriate to use a global measure of climate benefits from CH4
reductions. The EPA will continue to review developments in the literature, including more
robust methodologies for estimating the magnitude of the various damages to U.S. populations
from climate impacts and reciprocal international mitigation activities, and explore ways to
better inform the public of the full range of GHG impacts.
6.2 Health Effects Associated with Exposure to Non-GHG Pollutants
6.2.1 Ozone-Related Impacts Due to VOC Emissions
This final rulemaking is projected to reduce VOC emissions, which are a precursor to
ozone. Ozone is not generally emitted directly into the atmosphere but is created when its two
primary precursors, VOC and oxides of nitrogen (NOx), react in the atmosphere in the presence
of sunlight. In urban areas, compounds representing all classes of VOC can be important for
ozone formation, but biogenic VOC emitted from vegetation tend to be more important
compounds in non-urban vegetated areas (U.S. EPA 2020a). Recent observational and modeling
46 DCIM and GIVE use global damage functions. Damage functions based on only U.S.-data and research, but not
for other parts of the world, were not included in those models. FrEDI does make use of some of this U.S.-
specific data and research and as a result has a broader coverage of climate impact categories.
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studies have found that VOC emissions can impact ozone levels (U.S. EPA 2020a). Emissions
reductions may decrease ozone formation, human exposure to ozone, and the incidence of ozone-
related health effects.
Calculating ozone impacts from changes in VOC emissions requires information about
the spatial patterns in those emissions changes. In addition, the ozone health effects from the
final rule will depend on the relative proximity of expected VOC and ozone changes to
population. In this analysis, we have not characterized VOC emissions changes at a finer spatial
resolution than the national total due to data and resource constraints. In light of these
limitations, we present an illustrative screening analysis of ozone-related health benefits in
Appendix A based on modeled oil and natural gas VOC contributions to ozone concentrations as
they occurred in 2017 and do not include the results of this screening analysis in the estimate of
benefits (and net benefits) projected from this final rule. To more definitively analyze the
impacts of VOC reductions from this final rule on ozone health benefits, we would need credible
projections of spatial patterns of expected VOC emissions reductions. Similarly, due to the high
degree of variability in the responsiveness of ozone formation to VOC emissions reductions, we
are unable to determine how this rule might affect air quality in downwind ozone nonattainment
areas without modeling air quality changes.
6.2.1.1 Ozone Health Effects
Human exposure to ambient ozone concentrations is associated with adverse health
effects, including premature respiratory mortality and cases of respiratory morbidity (U.S. EPA,
2020a). Researchers have associated ozone exposure with adverse health effects in numerous
toxicological, clinical, and epidemiological studies (U.S. EPA, 2020a). When adequate data and
resources are available, the EPA has generally quantified several health effects associated with
exposure to ozone (U.S. EPA, 2010, 201 la, U.S. EPA, 2021c, 202le, 2024d). EPA quantifies
and monetizes effects the Integrated Science Assessment (ISA) identifies as having either a
causal or likely-to-be-causal relationship with the pollutant. Relative to the 2015 ISA, the 2020
ISA for Ozone reclassified the casual relationship between short-term ozone exposure and total
mortality, changing it from "likely to be causal" to "suggestive of, but not sufficient to infer, a
causal relationship." The 2020 Ozone ISA separately classified short-term ozone exposure and
respiratory outcomes as being "causal" and long-term exposure as being "likely to be causal."
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When determining whether there existed a causal relationship between short- or long-term ozone
exposure and respiratory effects, EPA evaluated the evidence for both morbidity and mortality
effects. The ISA identified evidence in the epidemiologic literature of an association between
ozone exposure and respiratory mortality, finding that the evidence was not entirely consistent
and there remained uncertainties in the evidence base. EPA continues to quantify premature
respiratory mortality attributable to both short- and long-term exposure to ozone because doing
so is consistent with: (1) the evaluation of causality noted above; and (2) EPA's approach for
selecting and quantifying endpoints described in the TSD "Estimating PM2.5- and Ozone
Attributable Health Benefits," which was recently reviewed by the U.S. EPA Science Advisory
Board (U.S. EPA, 2023p; U.S. EPA Science Advisory Board, 2024)
6.2.1.2 Ozone Vegetation Effects
Exposure to ozone has been found to be associated with a wide array of vegetation and
ecosystem effects in the published literature (U.S. EPA, 2020a). Sensitivity to ozone is highly
variable across species, with over 66 vegetation species identified as "ozone-sensitive," many of
which occur in state and national parks and forests. These effects include those that cause
damage to, or impairment of, the intended use of the plant or ecosystem. Such effects are
considered adverse to public welfare and can include reduced growth and/or biomass production
in sensitive trees, reduced yield and quality of crops, visible foliar injury, changed to species
composition, and changes in ecosystems and associated ecosystem services.
6.2.1.3 Ozone Climate Effects
Ozone is a well-known short-lived climate forcing GHG (U.S. EPA, 2013). Stratospheric
ozone (the upper ozone layer) is beneficial because it protects life on Earth from the sun's
harmful ultraviolet (UV) radiation. In contrast, tropospheric ozone (ozone in the lower
atmosphere) is a harmful air pollutant that adversely affects human health and the environment
and contributes significantly to regional and global climate change. Due to its short atmospheric
lifetime, tropospheric ozone concentrations exhibit large spatial and temporal variability (U.S.
EPA, 2009b). The IPCC AR5 estimated that the contribution to current warming levels of
increased tropospheric ozone concentrations resulting from human methane, NOx, and VOC
emissions was 0.5 W/m2, or about 30 percent as large a warming influence as elevated CO2
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concentrations. This quantifiable influence of ground level ozone on climate leads to increases in
global surface temperature and changes in hydrological cycles.
6.2.2 Ozone-Related Impacts Due to Methane
The tropospheric ozone produced by the reaction of methane in the atmosphere has
harmful effects for human health and plant growth in addition to its climate effects (Nolte et al.,
2018). In remote areas, methane is a dominant precursor to tropospheric ozone formation.
Approximately 50 percent of the global annual mean ozone increase since preindustrial times is
believed to be due to anthropogenic methane (Myhre et al., 2013). Projections of future
emissions also indicate that methane is likely to be a key contributor to ozone concentrations in
the future (Myhre et al., 2013). Unlike NOx and VOC, which affect ozone concentrations
regionally and at hourly time scales, methane emissions affect ozone concentrations globally and
on decadal time scales given methane's long atmospheric lifetime when compared to these other
ozone precursors (Myhre et al., 2013). Reducing methane emissions, therefore, will contribute to
efforts to reduce global background ozone concentrations that contribute to the incidence of
ozone-related health effects (Sarofim et al., 2015; USGCRP, 2018). The benefits of such
reductions are global and occur in both urban and rural areas. As discussed in Section 6.1, these
effects are not included in estimates of the social cost of methane. However, a recent analysis by
McDuffie et al. (2023) used a combination of global model simulations from the United Nations
Environment Programme & Climate and Clean Air Coalition (UNEP/CCAC), in combination
with BenMAP, to evaluate the additional risk in respiratory-related human mortality from ozone
produced per ton of methane emissions. This approach is similar to the social cost of methane
and finds that, globally, the monetized increase in respiratory-related human mortality risk from
ozone produced from methane emissions in 2030 is $2,400 per ton of methane per mt CH/iin
2019 US dollars). As discussed in U.S. EPA (2023f), this monetized result is similar to an earlier
study by Sarofim et al. (2017) but smaller than in a 2021 study conducted by the UNEP/CCAC,
which included additional cardiovascular mortality risk due to elevated ozone concentrations
(United Nations Environment Programme and Climate and Clean Air Coalition, 2021).
Collectively, these and other prior studies suggest that there are additional risks to human health
from the methane-ozone mechanism that are not currently accounted for in the social cost of
methane. Applying the ozone-related health benefit per ton estimates from McDuffie et al.
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(2023) would yield a present value of the ozone-related health benefits from the 2024-2035 CH4
emission reductions of the final rule on the order of $2.4 billion (2019 dollars), of which
approximately $340 million are accruing to populations within U.S. borders.47 Because these
benefits are the result of methane, which is a global pollutant, EPA believes it is most
appropriate to focus attention on the global benefits to human health from the methane-ozone
mechanism for the same reasons discuss above with respect to climate benefits. EPA will
continue to look for opportunities to incorporate the ozone related impacts of CH4 emissions in
future updates to the SC-CH4.
6.2.3 PM2.5-RelatedImpacts Due to VOCEmissions
This final rulemaking is expected to result in emissions reductions of VOC, which are a
precursor to PM2.5, thus decreasing human exposure to PM2.5 and the incidence of PIVh.s-related
health effects, although the magnitude of this effect has not been quantified at this time. Most
VOC emitted are oxidized to CO2 rather than to PM, but a portion of VOC emissions contributes
to ambient PM2.5 levels as organic carbon aerosols (U.S. EPA, 2020a). Analysis of organic
carbon measurements suggest only a fraction of secondarily formed organic carbon aerosols are
of anthropogenic origin. The current state of the science of secondary organic carbon aerosol
formation indicates that anthropogenic VOC contribution to secondary organic carbon aerosol is
often lower than the biogenic (natural) contribution (U.S. EPA, 2019a). The potential for an
organic compound to partition into the particle phase is highly dependent on its volatility such
that compounds with lower volatility are more prone to partition into the particle phase and form
secondary organic aerosols (SOA) (Cappa & Wilson, 2012; Donahue, Kroll, Pandis, &
Robinson, 2012; Jimenez et al., 2009). Hydrocarbon emissions from oil and natural gas
operations tend to be dominated by high volatility, low-carbon number compounds that are less
likely to form SOA (Helmig et al., 2014; Koss et al., 2017; Petron et al., 2012). Given that only a
fraction of secondarily formed organic carbon aerosols is from anthropogenic VOC emissions,
47 This estimate relies on benefit per ton numbers that use the socioeconomics from the RFF-SPs and the 2 percent
near-term Ramsey discounting approach. See McDuffie, E. E., Sarofim, M. C., Raich, W., Jackson, M., Roman,
H., Seltzer, K.,. . . Fann, N. (2023). The Social Cost of Ozone-Related Mortality Impacts From Methane
Emissions. Earth's Future, 11(9), e2023EF003853. https://doi.Org/https://doi.org/10.1029/2023EF003853 for
more details.
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and the relatively volatile nature of VOCs emitted from this sector, it is unlikely that the VOC
emissions reductions projected to occur under this proposal would have a large contribution to
ambient secondary organic carbon aerosols. Therefore, we have not quantified the PIVh.s-related
benefits in this analysis. Moreover, without modeling air quality changes, we are unable to
determine how this rule might affect air quality in downwind PM2.5 nonattainment areas.
6.2.3.1 PM2.5 Health Effects
Decreasing exposure to PM2.5 is associated with significant human health benefits,
including reductions in respiratory mortality and respiratory morbidity. Researchers have
associated PM2.5 exposure with adverse health effects in numerous toxicological, clinical, and
epidemiological studies (U.S. EPA, 2020a). These health effects include asthma development
and aggravation, decreased lung function, and increased respiratory symptoms, such as irritation
of the airways, coughing, or difficulty breathing (U.S. EPA, 2019a). These health effects result in
hospital and ER visits, lost workdays, and restricted activity days. When adequate data and
resources are available, the EPA has quantified the health effects associated with exposure to
PM2.5 (U.S. EPA, 202Id, 2024d).
When the EPA quantifies PM2.5-related benefits, the Agency assumes that all fine
particles, regardless of their chemical composition, are equally potent in causing premature
mortality because the scientific evidence is not yet sufficient to allow differentiation of effect
estimates by particle type (U.S. EPA, 2019a). Based on our review of the current body of
scientific literature, the EPA estimates PM-related premature mortality without applying an
assumed concentration threshold. This decision is supported by the data, which are quite
consistent in showing effects down to the lowest measured levels of PM2.5 in the underlying
epidemiology studies. These data are summarized in the Final Report of the Supplement to the
2019 Integrated Science Assessment for Particulate Matter. (U.S. EPA, 2022d).
6.2.3.2 PM Welfare Effects
Suspended particles and gases degrade visibility by scattering and absorbing light.
Decreasing secondary formation of PM2.5 from VOC emissions could improve visibility
throughout the U.S. Visibility impairment has a direct impact on people's enjoyment of daily
activities and their overall sense of wellbeing. Good visibility increases the quality of life where
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individuals live and work, and where they engage in recreational activities. Previous analyses
(U.S. EPA, 2006, 201 lb, 201 lc, 2012) show that visibility benefits are a significant welfare
benefit category. However, without air quality modeling of PM2.5 impacts, we are unable to
estimate visibility related benefits.
Separately, persistent and bioaccumulative HAP reported as emissions from oil and
natural gas operations, including polycyclic organic matter, could lead to PM welfare effects.
Several significant ecological effects are associated with the deposition of organic particles,
including persistent organic pollutants and polycyclic aromatic hydrocarbons (PAHs) (U.S. EPA,
2009a). PAHs can accumulate to high enough concentrations in some coastal environments to
pose an environmental health threat that includes cancer in fish populations, toxicity to
organisms living in the sediment and risks to those (e.g., migratory birds) that consume these
organisms. Atmospheric deposition of particles is thought to be the major source of PAHs to the
sediments of coastal areas of the U.S. (U.S. EPA, 2012).
6.2.4 Hazardous Air Pollutants (HAP) Impacts
Available emissions data show that several different HAP are emitted from oil and
natural gas operations. The HAP emissions from the oil and natural gas sector in the 2020
National Emissions Inventory (NEI) emissions data are summarized in Table 6-6. The table
includes either oil and natural gas nonpoint or oil and natural gas point emissions of at least 10
tons per year, in descending order of annual nonpoint emissions. Emissions of eight HAP make
up a large percentage of the total HAP emissions by mass from the oil and natural gas sector:
toluene, hexane, benzene, xylenes (mixed), ethylene glycol, methanol, ethyl benzene, and 2,2,4-
trimethylpentane (U.S. EPA, 201 Id).
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Table 6-6 Top Annual HAP Emissions as Reported in 2020 NEI for Oil and Natural
Gas Sources
Pollutant
Nonpoint Emissions
(tons/year)
Point Emissions (tons/year)
Benzene
31,117
1,496
Xylenes (Mixed Isomers)
31,439
1,068
Formaldehyde
39,768
326
Toluene
19,306
2,674
Acetaldehyde
4,191
45
Hexane
2,411
1,878
Ethyl Benzene
2,163
305
Acrolein
2,642
29
Methanol
2,841
401
1,3-Butadiene
600
1
2,2,4-Trimethylpentane
189
142
Naphthalene
106
2
Propionaldehyde
90
0
PAH/POM - Unspecified
124
0
1,1,2-Trichloroethane
32
0
Methylene Chloride
34
1
1,1,2,2-Tetrachloroethane
25
0
Ethylene Dibromide
21
0
Methyl Tert-Butyl Ether
0
21
In the subsequent sections, we describe the health effects associated with the main HAP
of concern from the oil and natural gas sector: benzene (Section 6.2.4.1), formaldehyde (Section
6.2.4.2), toluene (Section 6.2.4.3), carbonyl sulfide (Section 6.2.4.4), ethylbenzene (Section
6.2.4.5), mixed xylenes (Section 6.2.4.6), and n-hexane (Section 6.2.4.7), and other air toxics
(Section 6.2.4.8). This proposal is projected to reduce 4,000 tons of HAP emissions over the
2023 through 2035 period. With the data available, it was not possible to estimate the change in
emissions of each individual HAP.
Monetization of the benefits of reductions in cancer incidences requires several important
inputs, including central estimates of cancer risks, estimates of exposure to carcinogenic HAP,
and estimates of the value of an avoided case of cancer (fatal and non-fatal). Due to methodology
and data limitations, we did not attempt to monetize the health benefits of reductions in HAP in
this analysis. Instead, we are providing a qualitative discussion of the health effects associated
with HAP emitted from sources subject to control under the final WEC. The EPA remains
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committed to improving methods for estimating HAP benefits by continuing to explore
additional aspects of HAP-related risk from the oil and natural gas sector, including the
distribution of that risk. This is discussed further in the context of environment justice in Section
9.3.
6.2.4.1 Benzene
The EPA's Integrated Risk Information System (IRIS) database lists benzene as a known
human carcinogen (causing leukemia) by all routes of exposure and concludes that exposure is
associated with additional health effects, including genetic changes in both humans and animals
and increased proliferation of bone marrow cells in mice (IARC, 1982; Irons, Stillman,
Colagiovanni, & Henry, 1992; U.S. EPA, 2003a). The EPA states that data indicate a causal
relationship between benzene exposure and acute lymphocytic leukemia and suggest a
relationship between benzene exposure and chronic non-lymphocytic leukemia and chronic
lymphocytic leukemia. The International Agency for Research on Carcinogens (IARC) has
determined that benzene is a human carcinogen, and the U.S. Department of Health and Human
Services has characterized benzene as a known human carcinogen (IARC, 1987; NTP, 2004).
Several adverse noncancer health effects have been associated with chronic inhalation of
benzene in humans including arrested development of blood cells, anemia, leukopenia,
thrombocytopenia, and aplastic anemia. Respiratory effects have been reported in humans
following acute exposure to benzene vapors, such as nasal irritation, mucous membrane
irritation, dyspnea, and sore throat (ATSDR, 2007a).
6.2.4.2 Formaldehyde
The IARC (2006, 2012) classified formaldehyde as a human carcinogen based upon
sufficient human evidence of nasopharyngeal cancer and strong evidence for leukemia.
Similarly, in 2016, the National Toxicology Program (NTP) classified formaldehyde as known to
be a human carcinogen based on sufficient evidence of cancer from studies in humans supporting
data on mechanisms of carcinogenesis (NTP, 2016). In 2024, EPA updated its classification of
formaldehyde from a probable human carcinogen to carcinogenic to humans via the inhalation
route of exposure based upon evidence that formaldehyde inhalation causes nasopharyngeal
cancer, sinonasal cancer, and myeloid leukemia in humans. (U.S. EPA, 2024e). Formaldehyde
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inhalation exposure causes a range of noncancer health effects including irritation of the nose,
eyes, and throat in humans and animals. Repeated exposures cause respiratory tract irritation,
chronic bronchitis and nasal epithelial lesions such as metaplasia and loss of cilia in humans.
Airway inflammation, including eosinophil infiltration, has been observed in animals exposed to
formaldehyde. In children, there is evidence that formaldehyde may increase the risk of asthma
and chronic bronchitis (ATSDR, 1999; WHO, 2002). Evidence also indicates that inhalation of
formaldehyde may cause reproductive toxicity and decreased pulmonary function in humans
(U.S. EPA, 2024).
6.2.4.3 Toluene48
Under the 2005 Guidelines for Carcinogen Risk Assessment, there is inadequate
information to assess the carcinogenic potential of toluene because studies of humans chronically
exposed to toluene are inconclusive, toluene was not carcinogenic in adequate inhalation cancer
bioassays of rats and mice exposed for life, and increased incidences of mammary cancer and
leukemia were reported in a lifetime rat oral bioassay.
The central nervous system (CNS) is the primary target for toluene toxicity in both
humans and animals for acute and chronic exposures. CNS dysfunction (which is often
reversible) and narcosis have been frequently observed in humans acutely exposed to low or
moderate levels of toluene by inhalation: symptoms include fatigue, sleepiness, headaches, and
nausea. Central nervous system depression has been reported to occur in chronic abusers exposed
to high levels of toluene. Symptoms include ataxia, tremors, cerebral atrophy, nystagmus
(involuntary eye movements), and impaired speech, hearing, and vision. Chronic inhalation
exposure of humans to toluene also causes irritation of the upper respiratory tract, eye irritation,
dizziness, headaches, and difficulty with sleep.
Human studies have also reported developmental effects, such as CNS dysfunction,
attention deficits, and minor craniofacial and limb anomalies, in the children of women who
abused toluene during pregnancy. A substantial database examining the effects of toluene in
subchronic and chronic occupationally exposed humans exists. The weight of evidence from
these studies indicates neurological effects (i.e., impaired color vision, impaired hearing,
48 All health effects language for this section came from: U.S. EPA (2005b).
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decreased performance in neurobehavioral analysis, changes in motor and sensory nerve
conduction velocity, headache, and dizziness) as the most sensitive endpoint.
6.2.4.4 Carbonyl Sulfide
Limited information is available on the health effects of carbonyl sulfide. Acute (short-
term) inhalation of high concentrations of carbonyl sulfide may cause narcotic effects and irritate
the eyes and skin in humans (U.S. National Library of Medicine, 2020). No information is
available on the chronic (long-term), reproductive, developmental, or carcinogenic effects of
carbonyl sulfide in humans. Carbonyl sulfide has not undergone a complete evaluation and
determination under the EPA's IRIS program for evidence of human carcinogenic potential (U.S.
EPA, 1991a).
6.2.4.5 Ethylbenzene
Ethylbenzene is a major industrial chemical produced by alkylation of benzene. The pure
chemical is used almost exclusively for styrene production. It is also a constituent of crude
petroleum and is found in gasoline and diesel fuels. Acute (short-term) exposure to ethylbenzene
in humans results in respiratory effects such as throat and nasal irritation and chest constriction,
and irritation of the eyes, and neurological effects such as dizziness. Chronic (long-term)
exposure of humans to ethylbenzene may cause eye and lung irritation, with possible adverse
effects on the blood. Animal studies have reported effects on the blood, liver, and kidneys and
endocrine system from chronic inhalation exposure to ethylbenzene. No information is available
on the developmental or reproductive effects of ethylbenzene in humans, but animal studies have
reported developmental effects, including birth defects in animals exposed via inhalation. No
association has been found between the occurrence of cancer in humans and ethylbenzene
exposure (ATSDR, 2010). Studies in rodents reported increases in the percentage of animals
with tumors of the nasal and oral cavities in male and female rats exposed to ethylbenzene via
the oral route (Maltoni et al., 1997; Maltoni, Conti, Cotti, & Belpoggi, 1985). The reports of
these studies lacked detailed information on the incidence of specific tumors, statistical analysis,
survival data, and information on historical controls, thus the results of these studies were
considered inconclusive by the International Agency for Research on Cancer (IARC, 2000) and
the National Toxicology Program (NTP, 1999). The NTP (1999) carried out a chronic inhalation
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bioassay in mice and rats and found clear evidence of carcinogenic activity in male rats and some
evidence in female rats, based on increased incidences of renal tubule adenoma or carcinoma in
male rats and renal tubule adenoma in females. NTP (1999) also noted increases in the incidence
of testicular adenoma in male rats. Increased incidences of lung alveolar/bronchiolar adenoma or
carcinoma were observed in male mice and liver hepatocellular adenoma or carcinoma in female
mice, which provided some evidence of carcinogenic activity in male and female mice (NTP,
1999). IARC (2000) classified ethylbenzene as Group 2B, possibly carcinogenic to humans,
based on the NTP studies.
6.2.4.6 Mixed Xylenes
Short-term inhalation of mixed xylenes (a mixture of three closely related compounds) in
humans may cause irritation of the nose and throat, nausea, vomiting, gastric irritation, mild
transient eye irritation, and neurological effects (U.S. EPA, 2003b). Other reported effects
include labored breathing, heart palpitation, impaired function of the lungs, and possible effects
in the liver and kidneys (ATSDR, 2007b). Long-term inhalation exposure to xylenes in humans
has been associated with a number of effects in the nervous system including headaches,
dizziness, fatigue, tremors, and impaired motor coordination (ATSDR, 2007b). The EPA has
classified mixed xylenes in Category D, not classifiable with respect to human carcinogenicity.
6.2.4.7 n-Hexane
The studies available in both humans and animals indicate that the nervous system is the
primary target of toxicity upon exposure of n-hexane via inhalation. There are no data in humans
and very limited information in animals about the potential effects of n-hexane via the oral route.
Acute (short-term) inhalation exposure of humans to high levels of hexane causes mild central
nervous system effects, including dizziness, giddiness, slight nausea, and headache. Chronic
(long-term) exposure to hexane in air causes numbness in the extremities, muscular weakness,
blurred vision, headache, and fatigue. Inhalation studies in rodents have reported behavioral
effects, neurophysiological changes, and neuropathological effects upon inhalation exposure to
n-hexane. Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), the
database for n-hexane is considered inadequate to assess human carcinogenic potential, therefore
the EPA has classified hexane in Group D, not classifiable as to human carcinogenicity.
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6.2.4.8 Other A ir Toxics
In addition to the compounds described above, other toxic compounds might be affected
by this rule, including hydrogen sulfide (H2S). Information regarding the health effects of those
compounds can be found in the EPA's IRIS database.49
49 The U.S. EPA Integrated Risk Information System (IRIS) database is available at
https://www.epa.gov/iris. Accessed April 26, 2020.
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7 COMPARISON OF BENEFITS AND COSTS
7.1 Comparison of Benefits and Costs
This section presents a comparison of quantified benefits and costs. Additionally,
projections of WEC payments are presented separately from costs and benefits as transfers. All
estimates are in 2019 dollars. All costs, emissions changes, and benefits are estimated for the
years 2024 to 2035 relative to a baseline without the final Waste Emissions Charge. The
monetized benefits presented are climate benefits calculated using the social cost of methane.
The costs are the engineering costs of methane mitigation technologies from the marginal
abatement cost (MAC) model, and energy market costs related to the outcomes of the partial
equilibrium modeling.
Table 7-1 summarizes the emissions reductions estimated to result from the WEC over
the 2024 to 2035 period. Table 7-2 presents the present value (PV) and equivalent annual value
(EAV), estimated using discount rates of 2, 3, and 7 percent, of the changes in quantified
benefits, costs, and net benefits 50. These values are discounted to 2023. Note that while the PV
of the costs and net benefits are calculated with discount rates of 2 percent, 3 percent, and 7
percent, the monetized climate benefits are only discounted at 2 percent. Table 7-2 includes
consideration of non-monetized benefits associated with the emissions reductions resulting from
the final rule.
50 Monetized climate effects are presented under a 2 percent near-term Ramsey discount rate, consistent with EPA's
updated estimates of the SC-GHG. The 2003 version of OMB 's Circular A-4 had generally recommended 3
percent and 7 percent as default discount rates for costs and benefits, though as part of the Interagency Working
Group on the Social Cost of Greenhouse Gases, OMB had also long recognized that climate effects should be
discounted only at appropriate consumption-based discount rates. OMB finalized an update to Circular A-4 in
2023, in which it recommended the general application of a 2.0 percent discount rate to costs and benefits (subject
to regular updates), as well as the consideration of the shadow price of capital when costs or benefits are likely to
accrue to capital (OMB 2023). Because the SC-GHG estimates reflect net climate change damages in terms of
reduced consumption (or monetary consumption equivalents), the use of the social rate of return on capital (7
percent under OMB Circular A-4 (2003)) to discount damages estimated in terms of reduced consumption would
inappropriately underestimate the impacts of climate change for the purposes of estimating the SC-GHG. See
Section 6.1 for more discussion.
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Table 7-1 Projected Emissions Reductions from the Final Waste Emissions Charge,
2024-2035
Emission Changes
Methane
(thousand metric
tons)
voc
(thousand metric
tons)
HAP
(thousand metric
tons)
Methane
(million metric tons
C02 Eq. using
GWP=28)
Total
1,200
170
34
Table 7-2 Projected Benefits and Costs from the Final Waste Emissions Charge
(million 2019$)
2 Percent Near-Term Ramsey Discount Rate
PV
EAV
PV
EAV
PV
EAV
Monetized Climate Benefits3
$2,400
$230
$2,400
$230
$2,400
$230
2 Percent
3 Percent
7 Percent
Discount Rate
Discount Rate
Discount Rate
PV
EAV
PV
EAV
PV
EAV
Total Social Costs
$460
$43
$440
$44
$380
$48
Cost of Methane Mitigation
$420
$40
$400
$41
$350
$44
Cost of Energy Market
Impacts
$39
$4
$38
$4
$33
$4
Net Benefits
$1,900
$190
$2,000
$190
$2,000
$180
Ozone benefits from reducing 1.2 million metric tons of methane from 2024
to 2035
PM2.5 and ozone health benefits from reducing 170 thousand metric tons of
VOC from 2024 to 2035
Non-Monetized Benefits
HAP benefits from reducing 6 metric tons of HAP from 2024 to 2035
Visibility benefits
Reduced vegetation effects
a Monetized climate benefits are based on reductions in methane emissions and are calculated using three different
estimates of the social cost of methane (SC-CH4) (under 1.5 percent, 2.0 percent, and 2.5 percent near-term
Ramsey discount rates). For the presentational purposes of this table, we show the climate benefits associated with
the SC-CH4 at the 2 percent near-term Ramsey discount rate. Please see Table 6-5 for the full range of monetized
climate benefit estimates.
b A screening-level analysis of ozone benefits from VOC reductions can be found in Appendix A of the RIA.
7.2 Annual Benefits and Costs
Table 7-3 presents annual emissions reductions of methane, VOC, and HAP emissions
from mitigation actions and energy market impacts.
7-2
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7-3
-------
Table 7-4 provides year-by-year estimates of climate benefits, social costs, and net
benefits, which underlie the summary benefit and cost information presented in Table 7-2. The
present value (PV) and equivalent annualized value (EAV) presented in Table 7-2 and 7-4
summarize the estimates over the 2024 to 2035 analysis period discounted to the year 2023 using
discount rates of 2, 3, and 7 percent.
Table 7-3 Projected Annual Emissions Reductions from the Final Waste Emissions
Charge (thousand metric tons)
Year
Methane
..... . , Market-
Mitigated T , ,
Induced
Total
Mitigated
voc
Market-
Induced
Total
Mitigated
HAP
Market-
Induced
Total
2024
110
0.1
110
17
0.0
17
0.6
0.00
0.6
2025
220
0.1
220
34
0.0
34
1.2
0.00
1.2
2026
310
1.7
320
47
0.3
48
1.8
0.01
1.8
2027
310
1.6
310
46
0.2
46
1.7
0.01
1.7
2028
42
0.0
42
4.2
0.0
4.2
0.15
0.00
0.15
2029
30
0.0
30
3.0
0.0
3.0
0.11
0.00
0.11
2030
30
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
2031
31
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
2032
31
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
2033
31
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
2034
31
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
2035
31
0.0
31
3.0
0.0
3.0
0.11
0.00
0.11
Total
1,200
3.7
1,200
170
0.6
170
6.2
0.0
6.2
7-4
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Table 7-4 Summary of Annual Undiscounted Values, Present Values, and Equivalent
Annualized Values for the 2024-2035 Timeframe for Estimated Incremental
Abatement Costs, Benefits, and Net Benefits for Final Rule (millions of
2019$, discounted to 2023)
Year
Climate
Benefitsf
(2%DR)
Total Social Costs
($MM)
Net Benefits (2% Benefits)
2024
$210
$40
$170
2025
$440
$85
$350
2026
$660
$140
$510
2027
$670
$140
$530
2028
$94
$17
$77
2029
$70
$10
$60
2030
$72
$10
$62
2031
$75
$10
$65
2032
$78
$10
$68
2033
$81
$10
$71
2034
$84
$10
$74
2035
$86
$10
$77
Discount
Rate
2%
2%
3%
7%
2%b
3%b
7%b
PV
$2,400
$460
$440
$380
$1,900
$2,000
$2,000
EAV
$230
$43
$44
$48
$190
$190
$180
a Monetized climate benefits are based on reductions in methane emissions and are calculated using three different
estimates of the social cost of methane (SC-CH4) (under 1.5 percent, 2.0 percent, and 2.5 percent near-term
Ramsey discount rates). For the presentational purposes of this table, we show the climate benefits associated with
the SC-CH4 at the 2 percent near-term Ramsey discount rate. Please see Tables 6.2-6.5 for the full range of
monetized climate benefit estimates.
b Headings denote what percent discount rates are used in calculating different versions of net benefits. In this case,
EPA is using 2% near-term Ramsey discount rate for climate benefits and 2%, 3%, and 7% discount rates for costs
respectively.
7.3 Transfer Payments
WEC payments are transfers and do not affect total net benefits to society as a whole
because payments by oil and natural gas operators are offset by receipts by the government.
Therefore, from a net-benefit accounting perspective, transfers are considered separately from
costs and benefits (and are therefore not included in Table 7-2). As explained in Section 2.7, the
approach taken here is in line with OMB guidance and the approach taken for RIAs for other
7-5
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rules impacting payments to the government, such as the Bureau of Land Management (BLM)'s
waste prevention rule.
One of the reasons that transfers are not considered costs is because they represent
payments to the U.S. Treasury that do not affect total resources available to society. Payments to
the U.S. Treasury can then be used to fund other programs, and the pairing of revenue collection
(e.g., the WEC payments) with commensurate expenditures (e.g., financial assistance programs)
by the federal government can be designed to be revenue neutral. The Methane Emission
Reduction Program created under CAA section 136 includes both collection and expenditure
components. In addition to establishing the WEC, another key purpose of CAA section 136 is to
encourage the transition to available and innovative methane emissions reduction technologies.
See 168 Cong. Rec. E869 (August 23, 2022) (statement of Rep. Frank Pallone). CAA section
136(a) and (b) provides financial and technical assistance to reduce methane emissions from the
oil and gas sector. To implement this program, EPA is partnering with the U.S. Department of
Energy (DOE) to provide up to $1.36 billion in financial and technical assistance. As designed
by Congress, these resources and incentives were intended to complement the regulatory
programs and to help facilitate the transition to a more efficient petroleum and natural gas
industry. These incentives for methane mitigation and monitoring complement the WEC.
The WEC has the effect of better aligning the economic incentives of oil and natural gas
companies with the costs and benefits faced by society from oil and gas activities. In the baseline
scenario the environmental damages resulting from methane emissions from the oil and gas
sector are a negative externality spread across society as a whole. Under the WEC, this negative
externality is internalized, oil and gas companies are required to make WEC payments in
proportion to the climate damages of methane emissions subject to the WEC.51 Alternatively,
firms can avoid making WEC payments by mitigating their emissions generating climate benefits
associated with the amount of mitigation.
Table 7-5 provides details of the calculation steps used to estimate projected WEC
obligations and climate damages based on projected emission subject to WEC. In order to
51 Note that Congress specified that the WEC would rise to $1,500 per metric ton of methane in 2026 and beyond.
This value is consistent with estimates of climate damages associated with emissions of a metric ton of methane
that were available at the time the IRA was passed. The February 2021, 'Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates under Executive Order 13990,' estimated that the
social cost of CH4 under a 3% discount rate for emissions occuring in the year 2020 was $1,500.
7-6
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compare projected WEC payments to climate damages from emissions subject to the WEC,
WEC payments are converted from nominal dollars to 2019 constant dollars using a chain-
weighted GDP price index from the 2023 Annual Energy Outlook.
Table 7-5 Details of Projected WEC Obligations and Climate Damages from Emissions
Subject to WEC (million 2019$)
Climate
Damages from
Emissions
Subject to
WEC (million
2019$)a
2024
600
$900
$540
$450
$1,900
$1,200
2025
460
$1,200
$560
$450
$2,000
$930
2026
340
$1,500
$510
$400
$2,100
$700
2027
320
$1,500
$480
$380
$2,200
$690
2028
35
$1,500
$52
$40
$2,200
$77
2029
3
$1,500
$5
$4
$2,300
$7
2030
3
$1,500
$4
$3
$2,400
$7
2031
3
$1,500
$4
$3
$2,500
$7
2032
2
$1,500
$4
$3
$2,500
$6
2033
2
$1,500
$3
$2
$2,600
$5
2034
2
$1,500
$3
$2
$2,700
$5
2035
1
$1,500
$2
$1
$2,800
$4
Total
2024-
1,800
-
-
$1,700
-
$3,600
2035
a Climate damages are based on remaining methane emissions subject to WEC after accounting for emissions
reductions and are calculated using three different estimates of the social cost of methane (SC-CH4) (under 1.5
percent, 2.0 percent, and 2.5 percent near-term Ramsey discount rates). For the presentational purposes of this
table, we show the climate benefits associated with the SC-CH4 at the 2 percent near-term Ramsey discount rate.
7.4 Uncertainties and Limitations
Throughout the RIA we considered several sources of uncertainty regarding the
emissions reductions, benefits, costs, and transfer payments estimated for the final rule. We
summarize some of the key elements of our discussions of uncertainty below.
Interactions with other policies impacting methane from the oil and natural gas industry:
In addition to the WEC, the EPA has implemented several other actions that impact methane
emissions from the oil and natural gas industry. In particular, the WEC has important interactions
Methane
Emissions
Subject to WEC
Year in Policy
Scenario
(thousand
metric tons)
Charge
Specified by
Congress
(nominal $
per metric
ton)
WEC
Payments in
Policy
Scenario
(million
nominal $)
WEC
Payments
in Policy
Scenario
(million
2019$)
SC-CH4
Values at 2%
Near-Term
Discount Rate
(2019$ per
metric ton)
7-7
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with recently finalized revisions to GHGRP subpart W and the now finalized NSPS/EG for the
Oil and Natural Gas Sector. Considerations in the interactions of these policies are discussed in
Section 2.3 and in further detail in Section 8. The impacts of the WEC are also likely affected by
interactions with other policies affecting emissions and activities of the oil and gas sector, such
as the Bureau of Land Management's waste prevention rule and state policies. These other
policies are not explicitly modeled in this analysis.
Projection methods and assumptions: because the WEC is assessed by facility and WEC
obligated party, detailed reporting data and projections are needed to estimate potential WEC
obligations and impacts of the rule. However, facility-specific trends may diverge significantly
from overall trends that are used to generate the baseline emissions and throughput projections.
In addition, because the projections begin from RY 2022 subpart W reported data, the
projections reflect details in that data which are likely to shift over time. For example, oil and
natural gas assets are frequently bought and sold by different companies, which could potentially
impact the effects of netting as part of WEC calculations, but it isn't possible to project how
ownership changes may impact WEC obligations. The change to netting does not improve EPA's
ability to project or predict this.
Methane mitigation potential analysis: estimates of methane emissions reductions
resulting from the WEC depend in part on the characterization of mitigation technologies in the
MACC analysis. Section 5.1 discusses important assumptions included in that analysis.
Mitigation technology costs faced by different oil and natural gas companies may vary from the
assumptions used in the MAC model. Mitigation costs vary by segment and may also vary based
on site-specific or operator-specific factors. Where possible, EPA has utilized information
specific to the different segments of the oil and natural gas industry, and reflecting several model
site types. However, various factors that affect cost and emissions reductions are uncertain and
the range of variation cannot be fully captured by the marginal abatement cost analysis. Actual
mitigation activities induced by the WEC may be higher or lower than are estimated here. For
some mitigation technologies, the MAC model has estimated revenue from avoided natural gas
losses. This revenue may be available, for example, in cases where the cost of reducing
emissions exceeds the potential revenue from avoided natural gas losses. The magnitude of
avoided losses may be higher or lower than estimated and may be impacted by factors not
accounted for in the analysis, such as availability of pipeline capacity. The mitigation analysis
may not fully capture various other factors such as unplanned downtime, deferred maintenance,
unplanned capital upgrades, uncertainty about sectoral contracting jobs, or other factors.
Additional information on the mitigation technologies characterized in the analysis is available in
Appendix C to this RIA.
7-8
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Oil and natural gas market impact analysis: the oil and natural gas market impact analysis
presented in this RIA is subject to several caveats and limitations. The market impact analysis
depends on uncertain input parameters and assumptions regarding market structure. A more
detailed discussion of the caveats and limitations of the oil and natural gas market analysis can
be found in Section 5.2.
Monetized methane-related climate benefits: the EPA considered the uncertainty
associated with the social cost of methane (SC-CH4) estimates, which were used to calculate the
monetized climate benefits of the decrease in methane emissions projected because of this action.
Section 6.1 provides a detailed discussion of the limitations and uncertainties associated with the
SC-CH4 estimates used in this analysis and describes ways in which the modeling addresses
quantified sources of uncertainty.
Monetized VOC-related ozone benefits: the illustrative screening analysis described in
Appendix A includes many data sources as inputs that are each subject to uncertainty. Input
parameters include projected emissions inventories, projected mitigation actions, air quality data
from models (with their associated parameters and inputs), population data, population estimates,
health effect estimates from epidemiology studies, economic data, and assumptions regarding the
future state of the world (i.e., regulations, technology, and human behavior). When compounded,
even small uncertainties can greatly influence the size of the total quantified benefits.
7-9
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8 UNCERTAINTY ANALYSES
8.1 Sensitivity on GHGRP Calculation Methods
On May 14, 2024, the EPA finalized revisions to the requirements of subpart W
consistent with directives in the Inflation Reduction Act (referred to in this section as the 2024
subpart W revisions). The 2024 subpart W revisions rule and 2024 GHGRP revisions rule52
include a number of changes that could meaningfully change reported methane emissions and the
resulting potential WEC obligations. The changes can be categorized as:
• new reported emissions sources, such as "other large release events" and crankcase
venting, and existing sources required for more segments;
• changes to emissions factors used in some existing calculation methods, such as changes
in the fugitive emissions factors used in the population method for fugitive emissions in
onshore production and gathering and boosting;
• new calculation methods, especially those involving site- or reporter-specific
measurements or data, such as new measurement methods for equipment leaks and new
leaker factor methods for pneumatic controllers; and
• changes that may result in additional reporters to GHGRP subpart W which have not
reported in past years.
EPA does not currently have a precise quantitative estimate of expected emissions
reporting inclusive of all of these revisions because a broad range of potential outcomes are
plausible. This section first discusses qualitative factors in how the revisions will influence
reported emissions, and then describes one quantitative scenario in how reported emissions may
change below.
8.1.1 Qualitative Factors in Sensitivity on GHGRP Calculation Methods
New emissions sources. The 2024 GHGRP subpart W revisions added new reported
emissions sources such as "other large release events" and crankcase venting. Considered alone,
the addition of new reporting emissions sources will increase overall methane reported to subpart
W and subject to the requirements of the WEC. However, in particular with respect to other large
release events it is difficult to estimate the magnitude of emissions that will be reported and
52 Under the GHGRP, the EPA finalized a separate rule (89 FR 31802, April 25, 2024), which included updates to
the General Provisions of the GHGRP to reflect revised global warming potentials, reporting of GHG data from
additional sectors (i.e., non-subpart W sectors), and revisions to source categories other than subpart W.
8-1
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which facilities will report those emissions. During the development of the 2024 GHGRP subpart
W revisions, the EPA reviewed published studies and data reported to state agencies related to
emission release events in order to understand the frequency and magnitude of other large release
events.53 Additionally, the EPA has reviewed emissions observation data from the Carbon
Mapper data portal.54 During a review of the available data, we identified an average of
approximately 800 events that exceed the 100 kg/hr threshold per year from 2016-2023 that have
been attributed to oil and gas. However, there is not sufficient data to estimate event duration or
attribute to particular sources to understand whether these emissions may already be captured
under reporting for other sources. We note that although subpart W provides a default duration of
91 days under the other large release events source category, we do not think it would be
appropriate for purposes of this sensitivity analysis to assign this default to all of these events
identified in the Carbon Mapper data set, as we expect facilities will in many cases be able to use
surveys or monitored data to bound events and some of these events may be appropriately
captured under other sources in subpart W (e.g., if any these events were blowdowns). We note
that the default duration is only required under subpart W when survey data or other monitored
data is not available.
Changes to emissions factors. Changes to emissions factors have several potential effects.
For example, the 2024 Subpart W revisions increase the emissions factors used for the
population method for equipment leaks in onshore production and gathering and boosting. In RY
2022, most facilities' equipment leak emissions were calculated using the population method.55
If we assume that these reporters continue to use the population method, then their reported
emissions would increase. However, the population method is not the only available method for
reporting equipment leak emissions, and higher fugitive emissions factors that more accurately
reflect potential emissions in the absence of fugitive monitoring also increase the economic
incentive to perform equipment leak monitoring and repair and to report using other calculation
methods for fugitives that are able to reflect emissions reductions from monitoring and repair
53 The details of this review are included in the "Greenhouse Gas Reporting Rule: Technical Support for Revisions
and Confidentiality Determinations for Data Elements Under the Greenhouse Gas Reporting Rule; Final Rule -
Petroleum and Natural Gas Systems" (see Docket Item No EPA-HQ-OAR-2023-0234-0453).
54 Carbon Mapper data [2016-2023], Retrieved from https://data.carbonmapper.org [April 2024]
55 The population method consists of multiplying default population emission factors by counts of all applicable
major equipment or equipment component types that exist at the facility, and by the equipment or component type
total annual operating time.
8-2
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programs. In addition, as more oil and natural gas operations become subject to fugitive
monitoring requirements under the NSPS/EG, those facilities will be required to switch to other
calculation methods for equipment leaks.56 Because of the possibility that reporters will switch
reporting methods, an increase in emissions factors may not lead to a proportionate increase in
reported emissions. For other emissions source types, switching between methods may be
optional and therefore potentially less likely. For example, switching between methods is
optional in the case of liquids unloading emissions.
New reporting methods. It is particularly uncertain what emissions will be reported using
new required or optional calculation methods in subpart W that utilize site- or reporter-specific
measurements.57 Measurements or reporter-specific data might lead to higher or lower reported
emissions than would have been calculated under other methods. When choosing whether to
report using an optional reporter-specific measurement or using a default emissions factor,
reporters are expected to choose calculation approaches that they expect will minimize WEC
obligations and measurement and reporting costs. Thus, holding other calculation methods
constant, the addition of optional measurement methods is likely to reduce reported emissions
and WEC obligations. However, in most cases GHGRP reporters are required to report based on
measurements or surveys that they have conducted. For example, where reporters have
performed fugitive emissions surveys pursuant to NSPS requirements or have elected to
complete a voluntary survey consistent with subpart W requirements, they are required to report
leaks found through those surveys. To estimate WEC obligations, EPA would further need to
make assumptions about how incorporation of measurement data would affect the distribution of
reported emissions by individual facilities. Results of measurements may vary significantly
between different oil and natural gas operators, and EPA does not yet have sufficient data to
56 These other methods consist of conducting leak surveys to identify leaking components and multiplying default
leaker emission factors by the number of components found to be leaking during the surveys and an estimated
leak duration. Starting with reporting year 2024, facilities may also optionally elect to measure emissions from
components found to be leaking during surveys and use the measured emission rates as an alternative to applying
default leaker emission factors. Furthermore, once a minimum number of leak measurements are conducted as
prescribed under 40 CFR 98 Subpart W, facilities may develop facility-specific leaker factors to apply to leaking
components instead of the default leaker factors provided in the rule.
57 The subpart W revisions introduced several new measurement-based methods to estimate emissions from different
source types (e.g., equipment leaks, pneumatic devices, associated gas venting and flaring). In many cases, these
new measurement-based methods are optional and, therefore, it is unknow to what extent they will be adopted by
reporters in lieu of existing methods.
8-3
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quantitatively estimate whether facilities will choose to adopt these new optional measurement
methods and the corresponding impact of these methods on potential WEC obligations.
New reporters. Several changes in the 2024 Subpart W revisions and the 2024 GHGRP
revisions to general provisions may result in additional reporters who have not been required to
report to GHGRP in the past. For example, the revised GHGRP general provisions includes an
increase in GWP of methane from 25 to 28, which may lead more oil and natural gas facilities to
exceed the 25,000 CChe reporting threshold beginning with the 2025 reporting year. EPA
estimated that approximately 200 additional facilities would report to subpart W as a result of
this change to GWP starting with reporting year 2025.58 However, not all oil and gas facilities
newly subject to the GHGRP and reporting under subpart W would likely be subject to the WEC,
as some of these facilities may have emissions below 25,000 metric tons CChe reported to
subpart W (i.e. they may report emissions under other subparts that in total put them over the
reporting threshold to the GHGRP even if their emissions to subpart W remain below metric tons
CChe). Similarly, the addition of new reporting source categories may bring facilities that were
previously below the reporting threshold above 25,000 metric tons CChe starting with reporting
year 2025. New reporting facilities would increase the overall baseline used in this RIA, but
information on the emissions intensity of these new reporters is unavailable. Even if new
reporters cause the total reported methane to subpart W to increase, total WEC-applicable
emissions may not be increased significantly. For example, emissions reported by new reporters
may fall above or below the relevant methane intensity thresholds specified by Congress.
8.1.2 Quantitative Scenario of Sensitivity on GHGRP Calculation Methods
Quantitative estimation of future emissions reported under subpart W is complicated by
multiple layers of uncertainty. These layers include uncertainty in what calculation methods will
be used where options are available, uncertainty in the outcome of new measurements, and
uncertainty in the occurrence of certain conditions such as other large release events. Some
aspects of the revisions will lead to increases in emissions, while other aspects could lead to
either increases or decreases in reported emissions. Despite the relatively broad range of
plausible outcomes described above, some indication of potential outcomes can be discerned
58 https://www.regulations.gov/document/EPA-HQ-OAR-2023-0234-0166
8-4
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through estimation of changes which are amenable to calculation, such as changes in emissions
factors.
Table 8-1 provides the results of a sensitivity analysis on potential emissions reported to
GHGRP subpart W and subject to WEC under an assumption of fixed calculation methods
accounting for changes in GHGRP emissions factors that are effective starting with reporting
year 2025. It also includes estimates for reporting of select new emissions sources by existing
reporters: crankcase venting, equipment leaks for stations and farm taps, and blowdowns from
underground natural gas storage facilities. This assessment starts from emissions reporting for
RY2022 to subpart W. It assumes that facilities which used default emissions factors to calculate
emissions for an emissions source continue to use the same calculation methods (i.e., fixed
calculation methods), but re-estimates emissions as if the revised factors had been used. Sources
for which changes were estimated include pneumatic devices, equipment leaks, flare stacks,
combustion slip, and dehydrators. This particular approach is used not because it is necessarily
the most likely, but because it is the only alternative for which we have sufficient data available
at this time. In addition, this scenario represents the least-cost approach for GHGRP reporters
with respect to emissions measurement and reporting burden. Performing additional
measurements or implementing alternative calculation methods might entail additional reporting
burden but lower WEC obligations.
8-5
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Table 8-1 Sensitivity of Emissions Exceeding Facility Waste Emissions Thresholds
from GHGRP Revisions Assuming Fixed Calculation Methods and Select
New Sources (tons methane)
Facility CH4 exceeding waste
emissions threshold (tons)
Industry Segment
Current
Subpart W
Reporting
(RY2022)
Final Revision
(Estimated)3
Percent
Change
(Estimated)3
Onshore Production
640,000
1,200,000
+90%
Offshore Production
21,000
23,000
+9%
Gathering and Boosting
270,000
690,000
+160%
Natural Gas Processing
n/ab
n/ab
n/ab
Natural Gas Transmission Compression
n/ab
n/ab
n/ab
Natural Gas Transmission Pipeline
13,000
19,000
+42%
Underground Natural Gas Storage
150
990
+550%
LNG Import/Export
0
0
0%
LNG Storage
0
0
0%
Total
940,000
1,950,000
+107%
a Estimated changes resulting from GHGRP subpart W revisions only account for select aspects of the revisions for
which data are available to estimate. The estimated change assumes that reporters continue to use the same
calculation methods as in RY2022. The estimates account for reporting of several new emissions sources by
existing reporters: crankcase venting, equipment leaks for stations and farm taps, and blowdowns from
underground natural gas storage facilities. The estimates related to the revisions do not account for the addition of
other large release events, the addition of new calculation methods, new reporting facilities, netting, or switching
between calculation methods,
b The estimates of emissions changes related to GHGRP subpart W revisions exclude Natural Gas Processing and
Natural Gas Transmission Compression, due to CBI data considerations.
The result of the fixed calculation method and select new sources scenario is
approximately a 80 percent increase in reported methane emissions to subpart W resulting in
approximately 110 percent increase in emissions which exceed facility waste emissions
thresholds. Please note that this analysis does not account for a variety of factors including use of
site-specific measurements, other new reporting sources such as other large release events,
emissions reported by new reporting facilities or other factors described qualitatively above. It
represents one potential scenario in how emissions may change within a relatively broad range of
plausible outcomes. Again, EPA does not expect that the results presented here are the most
likely scenario. There are both reasons that future reporting under the revised GHGRP subpart W
may be higher than estimated here (such as because this estimate does not include new sources
like other large release events) or lower than estimated here (such as if incorporated
measurement data result in lower reported emissions, or due to reductions in emissions from
8-6
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NSPS/EG compliance, as discussed below, or other mitigation activities). The estimate for this
scenario is broadly consistent with at least one estimate from an outside group. Enverus
Intelligence Research (EIR) conducted an analysis using a similar approach based upon the 2023
proposed GHGRP subpart W revisions and RY2021 reported data. In addition to emissions
factor changes, the EIR analysis included an estimate for other large release events. That analysis
found a 130% increase in methane reported by the upstream and gathering sectors.59
8.2 Sensitivity on Interaction with NSPS/EG
The WEC has important interactions and is designed to complement the Oil and Gas
NSPS/EG. Because of these interactions, the requirements and implementation of the NSPS/EG
influence the reductions and impacts of the WEC. To the extent that oil and natural gas
companies implement strong emissions controls because of requirements in the NSPS/EG,
emissions reductions resulting from the WEC and WEC obligations would be lower than if less
stringent emissions controls were required under the NSPS /EG. To the extent that NSPS/EG
implementation is delayed relative to the planned schedule, the WEC may serve as a partial
backstop to ensure that cost-effective mitigation actions are implemented promptly.
The EPA proposed updates to the Oil and Gas NSPS/EG in 2021, published a
supplemental proposal in 2022, and finalized rules in March 2024. In addition to requirements
already in place, these proposals include standards for many of the major sources of methane
emissions in the oil and natural gas industry. The revised NSPS includes new requirements for
new and modified facilities, while the EG OOOOc includes requirements for existing sources,
which are to be implemented by the states via state regulations and state plans.
There is significant overlap in both the oil and natural gas operations subject to the WEC
and the NSPS/EG and the emissions reduction measures that could be taken to avoid WEC
obligations and those potentially required under the NSPS/EG. On the one hand, the scope of
operations impacted by the WEC is a subset of those affected by the NSPS OOOOb and EG
OOOOc because the WEC must be collected from owners or operators of applicable facilities
that report more than 25,000 metric tons of carbon dioxide equivalent of greenhouse gases per
year pursuant to the petroleum and natural gas systems source category requirements of the
59 https://www.enverus.com/newsroom/epas-emission-revision-more-rules-double-the-methane-triple-the-tax/
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Greenhouse Gas Reporting Rule, and that exceed methane emissions intensity thresholds set
forth in CAA section 136 for different types of applicable facilities. On the other hand, the scope
of equipment and emissions sources affected by the 2024 Final NSPS/EG is a subset of the
reported emissions sources and equipment for which GHGRP facilities report methane
emissions.
With respect to overlap in oil and natural gas operations, the scope or coverage of
GHGRP subpart W reporting coverage varies by segment. For example, in RY 2022 emissions
were reported to GHGRP related to approximately 500,000 oil and natural gas onshore
production wells, out of over 900,000 producing wells in 2022 (EIA, 2023b). Because GHGRP
reporters skew towards higher-production wells, the proportion of total oil and natural gas
production covered by GHGRP subpart W reports is significantly higher than the proportion of
producing wells. By contrast, because the ownership structure and operations of natural gas
gathering and boosting tends to be more concentrated than onshore production, more than 95%
of gathering and boosting facilities are estimated to report to GHGRP. Regardless, in both the
onshore production and gathering and boosting segments of the oil and natural gas industry,
many operators are subject to both the requirements of the WEC and the NSPS/EG.
With respect to overlap in emissions sources and mitigation actions relevant to both the
WEC and the NSPS/EG, emissions sources with requirements under the NSPS/EG make up a
majority of methane emission reported to subpart W. Many of the most cost-effective methane
mitigation options estimated in the MACC correspond to sources and requirements under the
NSPS/EG. The Final NSPS/EG RIA estimated methane emissions reductions associated with
fugitive emission, natural gas driven pneumatic controllers, pneumatic pumps, reciprocating
compressors, centrifugal compressors, liquids unloading, storage vessels, and associated gas.
These sources make up about 80% of methane emissions currently reported to subpart W.
Because the WEC and Oil and Gas NSPS/EG apply to overlapping facilities and
emissions sources, the emissions reduction and mitigation costs of the two policies can be
thought of as complementary. To the extent that more emissions reductions (and costs) result
from the NSPS/EG, the expected emissions reductions (and costs) resulting from the WEC
would be expected to be lower.
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8.3 Sensitivity on Netting Scenarios
One important feature of the statutory provisions of the waste emissions charge program
is the allowance for netting of WEC obligations among facilities under common ownership or
control; this section evaluates the sensitivity of RIA results to the alternative interpretations of
the netting provision, or netting scenarios.
EPA's final interpretation of the netting provisions differs from the proposed
interpretation. The EPA proposed that the WEC obligated party and the scope of netting facilities
would be among facilities owned or operated by the same owner-operator organization. EPA is
finalizing a broader interpretation of netting that allows transfers of negative WEC emissions
among owner-operators that share a common parent company. The final interpretation of the
netting provisions was informed by public comments received and statutory interpretation
reflecting Congress' support for broad application of netting. Below we evaluate the implications
for RIA results of these differing approaches to netting. The EPA did not base its interpretation
of the netting provisions on these scenario results.
The broader allowance for netting in the common parent netting scenario results in lower
WEC obligations before accounting for methane mitigation and market responses because
broader netting allows broader opportunities for WEC obligated parties to net negative WEC
emissions to reduce their WEC obligations. This lower initial exposure to potential WEC
obligations leads to lower impacts generally, across WEC obligations, emissions reductions,
costs, and benefits. This RIA has a limited capability to capture the extent to which differences in
the netting scenarios may drive different incentives for facilities to pursue mitigation because the
MACC analysis (which drives the emissions reduction estimates) cannot capture the full
heterogeneity of oil and gas facilities and thus their differing opportunities for mitigation
activities.
Table 8-2 compares emissions subject to WEC under the proposal owner-operator netting
scenario to the emissions subject to WEC under the final rule, which allows netting among
owner-operators with a common parent company. The illustrative analysis based on reporting for
RY2022 indicates that the broader netting scenario results in approximately 15 percent less
emissions subject to WEC before mitigation actions or market responses are incorporated. Please
8-9
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note that these results are based on emissions reported in RY2022, not the sensitivity results
discussed in Section 8.1.
Table 8-2 Comparison of Estimated Emissions Subject to WEC across Netting
Scenarios Before Accounting for Mitigation or Market Responses
CH4 emissions, 2022
(thousand metric tons)
„ , Final
Proposal Netti f
Owner- 0/0wi(h
Operator „
' Common
Ne,t,ng Parent
(MMTC02e with
GWP=28)
„ , Final
Proposa! Neta f
Owner- ()/(J
Operator „
' Common
Ne,t,ng Parent
Petroleum and Natural Gas Systems Total (GHGI)
7,900
220
GHGRP subpart W
2,600
72
From WEC-applicable facilities
1,900
54
Facility emissions exceeding emissions threshold
970
27
Emissions subject to WEC, after netting
840 730
24
20
Note: calculation steps for estimating emissions subject to WEC are described in section 4.1.3.
While Table 8-2 focuses on overall emissions subject to WEC across netting scenarios,
Table 8-3 compares facilities potentially subject to WEC by segment, based on illustrative
analysis of RY2022 emissions reporting. Broader opportunities for netting particularly affect the
counts of facilities with WEC obligations in the gathering and boosting and processing segments
of the industry. This indicates that corporate organization in these segments more often allows
for opportunities to transfer negative net WEC emissions between owner-operators with a
common parent than in other industry segments.
Table 8-3 Comparison of Illustrative Facilities Impacted across Netting Scenarios by
Industry Segment (RY2022)
Total
Number
Number of
Proposal
Owner-
Final
Netting of
O/O with
Common
Parent
of
Number of
Facilities
Operator
Industry Segment
Facilities
Reporting
under
subpart
W
WEC
Applicable
Facilities
with WEC
Applicable
Emissions
>0a
Netting
Number of Facilities
with Emissions
Subject to WEC,
After Netting
Onshore Production
459
393
226
213
202
Offshore Production
116
23
17
15
16
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Gathering and Boosting
350
310
201
163
125
Natural Gas Processing
444
180
-53
-36
-16
Natural Gas Transmission Compression
659
22
~ 5
-3
-0
Natural Gas Transmission Pipeline
44
20
4
4
4
Underground Natural Gas Storage
51
1
1
1
1
LNG Storage
5
0
0
0
0
LNG Import/Export
11
7
0
0
0
Total
2,112
954
-507
-435
-364
Note: calculation steps for estimating emissions subject to WEC are described in section 4.1.3.
Lastly, Table 8-4 presents summary estimates of emissions reductions, costs, benefits,
and net benefits for the owner-operator versus common parent netting scenarios. The broader
netting allowed in the common parent netting scenario results in lower emissions reductions,
costs, benefits and net benefits than the owner-operator scenario. However, this result is limited
by the analysis's limited ability to capture the effect of broader netting incentivizing emissions
reductions at a broader range of facilities.
Table 8-4 Comparison of Emissions Reductions, Costs, and Benefits across Netting
Scenarios
Proposal
Owner-Operator
Netting
Final
Netting of O/O
with Common
Parent
(thousand tons)
Emissions Subject to WEC in Baseline
3400 3000
Emissions Reductions
Methane
1,400 1,200
voc
200 170
2 Percent Near-Term Ramsey Discount
Rate
(million 2019$)
Monetized Climate Benefits (PV)a
$2,900 $2,400
Total Social Costs $540 $460
Cost of Methane Mitigation $500 $420
Cost of Energy Market Impacts $44 $39
Net Benefits $2,400 $1,900
a Monetized climate benefits are based on reductions in methane emissions and are calculated using three different
estimates of the social cost of methane (SC-CH4) (under 1.5 percent, 2.0 percent, and 2.5 percent near-term
Ramsey discount rates). For the presentational purposes of this table, we show the climate benefits associated with
the SC-CH4 at the 2 percent near-term Ramsey discount rate. Please see Tables 6.2-6.5 for the full range of
monetized climate benefit estimates
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9 DISTRIBUTIONAL AND ECONOMIC ANALYSES
9.1 Small Business Analysis
9.1.1 Background for Small Entity Impacts
The EPA evaluated the impacts of this action where it identified small entities could
potentially be affected and considered whether additional measures to minimize impacts were
needed. In evaluating the impacts of this action, the EPA assessed the costs and impacts to small
entities from the WEC. Because the WEC is a charge on emissions exceeding specific methane
intensity thresholds and does not impose emissions standards or require implementation of
technologies or work practices, estimated costs for the purposes of the small entity impact
analysis were based only on the WEC and do not include costs associated with reducing
emissions below the specified methane intensity thresholds. An assessment of costs for
individual facilities to achieve the methane intensity thresholds is also inappropriate for the small
entity analysis due to the impact of netting across multiple facilities. For many WEC Obligated
Parties (i.e., reported facility owners or operators), total WEC is based on the methane intensity
performance of multiple facilities, and reduction of methane intensity at an individual facility
may or may not impact total WEC. These costs were therefore evaluated at the owner or operator
level and account for netting of emissions from facilities under common ownership or control.
Estimated WEC obligations include netting among owner-operators that share a common parent
company. Costs are based on the WEC impact in 2024, applying a charge of $900 per metric ton
of methane.
9.1.2 Methodology for Calculating Small Entity Impacts
To evaluate whether this rule would have a significant economic impact on a substantial
number of small entities, the EPA evaluated the costs of the rule on small entities identified in
the RY 2022 subpart W dataset. The EPA used reported facility-to-parent company and facility-
to-owner or operator data to link facilities to WEC obligated parties. While the EPA recognizes
there have been mergers and acquisitions since the end of 2022 that impact facility ownership,
there are no available data that track these changes at the subpart W facility level, nor is there
any means to project any additional ownership changes that may occur through the end of 2024.
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Reported 2022 ownership structures were therefore held constant for the small entity impact
analysis. Revisions were made to the RY 2022 data to project RY 2024 methane intensity at the
facility level. These include:
• Methane emissions data were projected forward from 2022 to 2024 using the 2017-2022
annual segment-specific rate of change in reported methane emissions for each segment of
subpart W applicable to WEC
• Total facility CChe in 2024 was recalculated using the projected methane emissions data and
application of AR5 GWPs for methane and N2O (no changes to actual N2O or CH4 emissions
were made). Projected CChe was used to determine if facilities would exceed the WEC
applicability threshold of reported subpart W emissions equal to or greater than 25,000
metric tons CChe
• Throughput volumes were projected forward from 2022 to 2024 using the 2022-2030 annual
rate of change for dry natural gas production in the Energy Information Administration's
2023 Annual Energy Outlook. The dry gas production rate of change was to project forward
throughput for all subpart W segments; the rate of change for crude oil and lease condensate
production was applied to onshore and offshore production facilities that report zero gas
sales.
In order to analyze the impacts on the entities subject to the WEC, the EPA employed a
survey-like approach. The survey approach consists of review of available or reported data from
a sample of facilities that are representative of the total population of affected facilities, in order
to estimate the likelihood of impacts on small entities in the total population. However, instead
of drawing a small, representative sample, the EPA sampled every unit in the universe of parent
entities in a current reporting facility. Business information was available for a large proportion
of parent entities, and those with no available information were treated as non-responders.
The survey approach is based on a survey of the full population of current subpart W
reporters and their parent entities. The survey estimates the business size distribution and the
annual revenues for each parent company, which are compared to the estimated WEC costs of
each parent company's associated facility owner or operator. For the survey approach, the EPA
reviewed the available RY 2022 data for owners or operators of subpart W facilities to determine
whether the reporters were part of a small entity and whether the annualized costs of the rule
would have a significant impact on a substantial number of small entities. The survey approach
included the following steps:
1. Soliciting business information from each parent entity for the survey, including a listing
of all facilities that the parent entity has an ownership stake in.
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2. Classifying parent entities with available employment and revenue data as small or "not
small."
3. Mapping facility parent entities to facility owners or operators.
4. Classifying facility owners or operators as small or "not small" based on the
classification of their parent entities.
5. Analyzing expected costs and assigning cost-to-revenue ratios for facility owners or
operators.
Soliciting business information. To obtain the employment and revenue data for each of
the RY 2022 subpart W parent entities, the EPA reviewed information from Zoomlnfo, Experian,
and D&B Hoovers business databases in a three-step process. Using an approximate string-
matching algorithm, the list of operators was first merged with business information from
Zoomlnfo for approximately 86% of subpart W parent entities. The remaining unmatched
operators were matched to the Experian business database when possible. Additionally, a small
number of operators were matched with the D&B Hoovers database information that was
collected as part of the Regulatory Impact Analysis (RIA) for the supplemental notice of
proposed rulemaking titled "Standards of Performance for New, Reconstructed, and Modified
Sources and Emissions Guidelines for Existing Sources: Oil and Natural Gas Sector Climate
Review." This matching process added information on the ultimate parent entities, number of
employees, and annual revenues of the operators. The matches were examined and, when
necessary, manual adjustments were made to the matched list of ultimate parent entities to
standardize company names, revenue, and employment information. Revenue and employment
data were identified for 453 of 468 subpart W parent entities.
Classifying small businesses. Each subpart W parent company's NAICS codes that were
reported to subpart A (40 CFR 98.3(c)(10)) for RY 2021 were used in conjunction with revenue
and/or employment data to classify the company as either "small business" or "not small
business." NAICS codes are reported at the facility level under subpart A. Therefore, the
company's employment and revenue data were evaluated against the Small Business Association
(SB A) size classification threshold associated with the relevant NAICS code(s) for the facilities
owned by the company. If a company reported emissions to subpart W from facilities with
different NAICS codes, then the NAICS code for each of their owned facilities was evaluated
against the SBA size classification thresholds. For example, if a company reported one facility
under onshore petroleum and natural gas production (NAICS code 211130) and another facility
under onshore natural gas transmission compression (NAICS code 486210), then the company's
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employment and revenue data was compared to the small business thresholds for both NAICS
codes (211130 and 486210). If either NAICS code threshold comparison indicated that the
company was a small business, then the company was designated as a small business for the
purposes of this analysis. This approach was taken to conservatively identify all potential small
entities that may be subject to subpart W; therefore, it is likely that some entities identified as
"Small" may not reflect true small entities. Additionally, the classification also reflects only U.S.
reported revenues. The entities for which revenue and employee data were not identified were
assumed to be small businesses.
Mapping parents to WEC Obligated Parties. Because the final rule uses facility owners
or operators as the WEC Obligated Party, parent companies must be mapped to owners or
operators. For facilities with a single parent company and a single owner or operator, the
reported owner or operator was mapped to the reported parent company. The final rule also uses
a Designated Company approach under which all tons of methane from a facility with multiple
parent companies are allocated to a single WEC Obligated Party. For these facilities, the
assigned WEC Obligated Party was the owner or operator that mapped to the parent company
with the largest equity share in the facility. For facilities with parent companies that had equal
equity share in the facility but a single owner or operator, the WEC Entity was mapped to the
parent company associated with that owner or operator (e.g., an owner or operator whose name
indicated it was a subsidiary of one of the parent companies). For facilities with parent
companies that had equal equity share in the facility and an owner or operator associated with
each parent company, the WEC Entity was mapped to the parent company with operational
control of the facility (based on an internet search). For facilities with multiple parent companies
but a single owner or operator that could not be linked to any of the parent companies, the owner
or operator was mapped to the parent company with the largest equity share in the facility. For
all facilities, the assigned WEC Entity (i.e., owner or operator) was classified as a small business
or not small business based on the classification of its parent company.
Analyzing expected costs to WEC obligated parties and assigning cost-to-revenue ratios.
To estimate expected costs to reported owners or operators, the EPA calculated the facility-level
tons of methane emissions above or below the waste emissions thresholds, summed facility-level
tons across facilities under common ownership or control of each WEC Obligated Party to
calculate net tons of methane, and multiplied any positive value by $900 to calculate total cost.
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There would be no costs for WEC Obligated Parties with netted tons of methane equal to or
below zero. WEC costs for 2024 were estimated using the emissions and throughput projections
described in section 9.1.1 and the WEC calculation steps described below.
• Identify WEC applicable facilities. WEC applicable facilities are GHGRP facilities that
report more than 25,000 metric tons CChe to GHGRP subpart W and report emissions under
any of the nine oil and natural gas industry segments subject to the WEC (all segments
except the natural gas distribution segment). Facilities projected to report less than 25,000
metric tons CChe to subpart W in a given year would not be considered subject to the WEC
and are not included in projections of WEC-applicable emissions. Emissions of CO2 and N2O
reported to subpart W were assumed to be fixed for each facility at the same level as reported
in RY 2021. Methane emissions were projected by segment and source as described section
9.1.1.
• Calculate facility waste emissions threshold from segment-specific methane intensity
thresholds. To calculate a facility's projected waste emissions threshold, the facility's
projected natural gas throughput was first multiplied by the relevant methane intensity
threshold specified by Congress to calculate the volume of gas equivalent to the segment-
specific methane intensity threshold. These values were converted to metric tons by
multiplying by the density of methane (0.0192 mt / Mscf) to calculate the waste emissions
threshold in metric tons of methane. The methane intensity thresholds for each segment are
listed in Table 1-1.
• Calculate facility tons above or below waste emissions threshold, or WEC applicable
emissions. A facility's projected waste emissions threshold was subtracted from the facility's
projected methane emissions to determine the total facility applicable emissions. This
analysis conservatively did not consider the impact of exemptions, so the total facility
applicable emissions are equal to the WEC applicable emissions. A negative value
represented the metric tons of methane emissions a facility was below the waste emissions
threshold while a positive value represented the metric tons of methane emissions at the
facility that exceeded the methane intensity threshold. Facilities with projected subpart W
emissions below 25,000 metric tons CChe were not considered eligible for the purpose of
netting and positive or negative tons from these facilities were excluded.
• Calculate net WEC emissions by owner-operator. For WEC Obligated Parties with
common ownership or control of multiple facilities, facility tons above or below the waste
emissions thresholds were summed across all facilities to calculate net tons.
• Calculate potential WEC obligations. WEC Obligated Parties with net tons methane of
zero or below would not be subject to the WEC and have zero WEC obligations. For WEC
Obligated Parties with net tons methane greater than zero, net tons were multiplied by the
WEC, which for 2024 is $900/ton of methane.
To estimate small business impacts, the EPA conducted an analysis to estimate the cost-
to-revenue ratio (CRR) based on the total 2024 WEC costs and the reported revenues. Because
revenue data were available for the majority of parent companies but only a small number of
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owners or operators, parent company revenue was used to calculate CRR for each WEC
Obligated Party. Estimated CRR were calculated for each WEC Obligated Parties by dividing
total WEC costs by reported revenue data.
Revenue data were not found for seven WEC Obligated Parties with estimated WEC
obligations. For these entities, a proxy for revenue was used by calculating the value equal to the
first quartile of revenue for all small entities with revenue data.
9.1.3 Results and Conclusions of Small Entity Impacts Analysis
The number of small entities potentially affected by the final WEC regulation were
estimated based on the information collected for 590 owners or operators associated with a
facility within one or more of the industry segments identified in CAA section 136(d) reporting
at least 25,000 metric tons C02e under subpart W in RY2022. Of these, 371 were identified as
small entities. Table 9-1 below shows the percent of small entities estimated to have a cost-to-
revenue ratio that exceeds 1% or 3%. Since this analysis relied, in part, upon confidential
business information (CBI) reported under subpart W to estimate these impacts, we present only
aggregated data and will not provide economic impact estimates by firm.
Table 9-1 Small Entity Cost-to-Revenue-Ratio Threshold Analysis Results
WEC Obligated Parties
590
Small Entity WEC Obligated Parties
371
Number of Small Entities with a CRR >1%
101
Percent of Small Entities with a CRR >1%
27%
Number of Small Entities with a CRR >3%
70
Percent of Small Entities with a CRR >3%
19%
After considering the economic impact of the final rule on small entities, EPA has
concluded that the final rule costs would not likely have a significant impact on a substantial
number of small entities. EPA's evaluation of the impacts to small entities relied on several
methodologies involving conservative assumptions. Therefore, this evaluation likely
overestimates the potential impacts on small entities. First, the analysis calculates WEC
obligations at the owner or operator level but does not take into account netting of emissions,
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which the final rule allows among owners or operators with the same parent company. For many
owners or operators, netting will reduce the total charge owed. The analysis therefore projects
the maximum amounts owed by owners or operators under the estimated 2024 emissions levels;
actual charges will be lower if parent company netting is applied. This analysis does not apply
netting at the parent company level because there is no meaningful way to estimate how tons will
be transferred from an owner or operator with net negative tons to one or multiple owners or
operators with positive net negative tons that shares the same parent company. Additionally, the
identification and classification of subpart W parent entities reporting under more than one
NAICS code resulted in a designation of "small" based on whether the business information
available met the SBA size classification threshold for a single NAICS code. The classification
also reflects only U.S. reported revenues. The Agency is aware that there some WEC obligated
parties classified as "small" that are subsidiaries to international corporations, but we are unable
to identify the total number of these entities and associated revenues. If such information was
known, those WEC obligated parties would likely not be considered as affected small entities.
The Agency is also aware that some WEC obligated parties classified as "small" are subsidiaries
to private equity firms or banks that would not meet the SBA definition of a small business.
Additionally, the individual costs imposed on a facility may be distributed across multiple WEC
obligated parties. As a result, the CRRs estimated by WEC obligated party may be overstated.
In addition to the conservative assumptions listed above, there are further mitigating
factors not included in this screening analysis that will likely significantly reduce compliance
costs, and, as a result, cost-to-revenue-ratios. As discussed in Section 5.1, the compliance cost
estimate using only the defined WEC obligations does not account for early adoption of
mitigation measures that, when implemented, can lower an entity's emissions below the
threshold and therefore result in no WEC. Some facilities may find that it is less expensive to
invest in mitigation technologies than to pay the WEC. EPA notes it does not have sufficient
information to estimate which individual facilities will undertake mitigation actions. As result,
the total cost to a small entity could be greatly reduced. We estimate that the avoided WEC
payments in 2024 resulting from methane mitigation is hundreds of millions of dollars
cumulatively across all WEC entities. Over the analysis period, total compliance costs fall as
economic abatement options are taken and residual emissions facing WEC payments fall. The
cumulative result of this additional analysis that the CRRs estimated here are likely overstated.
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Further mitigating factors not included in this screening analysis are evident from the
market model analysis described in Section 5.2. Estimates of price elasticities of demand and
supply are needed to assess cost pass through. The price elasticity of demand is a measure of the
responsiveness of product demand to a change in price of a product. Likewise, the price elasticity
of supply is a measure of the responsiveness of supply of a product to a change in its price.
Elasticity estimates are used when they are available to provide an indication of how much of the
control costs borne directly by firms in affected industries can be passed on to consumers. For
example, WEC obligations shift supply curves upward. As evidenced by the price elasticities
shown in Table 5-4, demand for product from affected producers is inelastic (i.e., the price
elasticity of demand is less than 1), indicating there will be a price increase that allows cost pass
through to consumers.
The cumulative effect of the above mitigating factors and conservative assumptions used in
the screening analysis indicates that, overall, the final rule would not likely have a significant
impact on a substantial number of small entities.
9.2 Employment Impacts
This section provides background information on employment in natural gas extraction,
transmission, and distribution sectors as well as an estimate of the likely employment impacts of
the WEC. For the latter, we consider employment impacts in other sectors that will provide
installation and manufacturing services to support expected methane abatement activity.
9.2.1 Background
Table 9-2 shows employment in three sectors related to the oil and gas industry based on
data provided by the Bureau of Labor Statistics (BLS): oil and gas extraction (NAICS 2111),
pipeline transportation of natural gas (NAICS 486210), and natural gas distribution (NAICS
221210).60 In total, about 263,000 people were employed by the three sectors in 2022, with oil
and gas extraction employing the largest number and natural gas distribution only slightly fewer.
Please note that the employment discussion and analysis in this section does not account for
60 Retrieved from FRED: IPUCN221210W200000000 (221210), IPUIN486210W200000000 (486210),
IPUBN2111W200000000 (2111) on July 19,2024, not seasonally adjusted
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employment in related sectors such as support activities for oil and gas extraction (NAICS
213112).61
Table 9-2 Employment in Oil and Gas Sectors (2022)
NAICS
Sector
Employment (thousands)
2111
Oil and gas extraction
118.9
486210
Pipeline transportation of natural gas
31.7
221210
Natural gas distribution
112.7
Total
263.3
Federal Reserve employment data report annual sectoral employment. Employment in oil
and gas extraction has declined 39% since 2015, dropping from 195 thousand employees in 2015
to 119 thousand employees in 2022. Employment has remained steady in pipeline transportation
and natural gas distribution, with consistent levels over the past decade. Collectively,
employment across the three sectors has declined 22% from 338 thousand in 2015 to 263
thousand in 2022.
Table 9-3 shows total labor compensation in NAICS 2111 and 221210 based on data
provided from the Bureau of Labor Statistics (BLS).62 Labor compensation is defined as payroll
plus supplemental payments, and includes salaries, wages, commissions, dismissal pay, bonuses,
vacation and sick leave pay, and compensation in kind. In total, the two sectors provided $48.7
billion in labor compensation. Per worker, the oil and gas extraction sector provided $253.3
thousand, while natural gas distribution provided $163.4 thousand. The Economic Census
provides wage data for additional 6-digitNAICs codes every five years, with 2012 and 2017
being the latest available.63
61 Over the past two decades, firms in the oil and gas industry have increasingly relied on contractors relative to
hiring employees directly. These contractors are not counted as employees within the sectors, so labor
productivity for oil and gas extraction for oil and gas extraction appears to be greater than it otherwise would be if
these contract workers were included.
62 Retrieved from FRED: IPUBN2111L020000000 (2111), IPUCN221210L020000000 (221210)
63 https://data.census.gov/table?q=aH+sectors:+summarv+statistics&v=2012&n=N0600.00
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Table 9-3 Labor Compensation in the Oil and Gas Sector (2022)64
NAICS Sector
Total Labor Compensation
(billions)
Total Compensation
per Worker
(thousands)
2111 Oil and gas extraction
221210 Natural gas di stributi on
$30.2
$18.4
$253.3
$163.4
While total labor compensation in the oil and gas extraction sector has declined in the last
decade due to fewer employees, total compensation per employee has risen from $195.5
thousand in 2012 to $253.3 thousand in 2022. Total labor compensation in natural gas
distribution has risen from $14.5 billion in 2012 to $18.4 billion in 2022, and compensation per
worker has risen from $132.7 thousand in 2012 to $163.4 thousand in 2022.
The BLS Office of Productivity and Technology (OPT) also measures sectoral output per
worker, a measure of labor productivity, for select sectors.65 In oil and gas extraction (2111),
output-per-worker has nearly tripled over the past decade. In natural gas distribution (221210),
labor productivity has increased 23% from 2022 to 2023. Output has risen sharply in 2021 and
2022, from an average of approximately $100 billion per year for distribution over the period
2012-2020 to $175 billion in 2022. Similarly, oil and gas extraction, while varying more over
2012-2020 from $200-400 billion, was $650 billion in 2022.
9.2.2 Employment Impacts
This section presents an analysis of potential employment impacts of the final WEC. The
analysis is focused on employment within the oil and natural gas industry and does not attempt to
model economy-wide employment changes. Oil and natural gas industry employment is
potentially affected through each of the cost and emissions impact pathways analyzed in this
RIA. Increased expenditures on methane mitigation technologies lead to potential increases in
64 Data accessed in July 2024. The information has since been updated; however, these figures were used as inputs
into other parts of this analysis. The updated numbers were not available in time to produce new results elsewhere
in this analysis. As of July 2024, total labor compensation for oil and gas extraction was $30.2 billion in 2022,
and $18.4 billion in 2022 for natural gas distribution. Total worker compensation per worker in 2022 was $253.3
thousand for oil and gas extraction, and $163.4 thousand for natural gas distribution.
65 https://www.bls.gov/prodnctivitv/tables/ see labor productivity and costs measures, detailed industries.
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employment because of the labor-intensive nature of some mitigation actions, such as
performing fugitive leak detection and repair activities. The energy market impacts lead to
reduced employment through reduced production of natural gas. However, based on the analyses
in section 5, the costs of methane mitigation are dominant when compared to production
changes.
Facilities expecting to pay the WEC will take on abatement activities that allow them to
avoid paying the WEC where they can abate for less money. The cost of these activities is
represented by the costs of methane mitigation, characterized in Section 5.1 as the height of the
MACC. These costs represent expenditures on capital equipment and labor to install and maintain
natural gas handling and emissions abatement. As these expenditures are already accounted for
within the costs of methane mitigation, they are not additive to societal welfare that has already
been characterized. However, given the importance of employment as an economic issue, we
identify the value of certain employment supported by abatement expenditures.
This analysis estimates the employment induced by the WEC by disaggregating total
abatement expenditures, equal to the area under the MACC curve up to total abatement, into
capital and operations-and-maintenance. Total capital expenditures represent a mix of capital
equipment, labor for construction and installation, and other materials. EPA considers the
magnitude of wages paid to construct, operate, and maintain the control equipment (direct
employment) and to manufacture control equipment (indirect employment). For oil and natural
gas firms that pay the WEC this analysis assumes no associated increased employment, though
there may be additional labor demand associated with WEC compliance, reporting, and payment
processing for WEC-applicable facilities.
This analysis bases job and wage benefits associated with abatement expenditures on the
ratio of employment and wages to total output within sectors that provide emissions abatement
services. These ratios are calculated from economic survey data conducted under the Economic
Census for a range of North American Industrial Classification System (NAICS) codes. This
analysis associates expenditures with an appropriate NAICS codes for capital equipment,
installation, and operations and maintenance with NAICS to assign an employment multiplier for
each. Table 9-4 presents the multipliers, which range from 0.4 jobs per million dollars of
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expenditure in natural gas extraction (NAICS code 211130) to 4.3 jobs per million dollars
expenditure on capital installation.
Table 9-4 Employment Multipliers for Abatement Expenditures
Expenditure
Type / Segment
NAICS
Employment /
$MM Output
Segment Group
Average
Employment /
$MM
Capital
Equipment
Installation
333132
237120
2.72
4.25
O&M
Oil Extraction
Natural Gas Extraction
211120
211130
0.60
0.44
Production
0.5
Pipeline Transportation
486210
1.11
Gathering,
1.0
Natural Gas Distribution
221210
0.91
Boosting,
Transmission, &
Storage (GBTS)
Production
Natural Gas (all segments)
Multiple
0.5
Direct job impacts of the WEC come from a mix of compliance expenditures (positive)
and changes in output (negative). The largest jobs impact comes from capital equipment
manufacturing and installation, which support about 155 jobs in 2024 up to about 438 jobs in
2026. Capital and O&M expenditures from the MACC analysis and output changes estimated
from the PE Model form the basis of the jobs impacts estimates. The split of capital expenditures
between equipment and installation expenditures is assumed to be 70/30. Job losses from
reduced output are 2 jobs in 2024 and 28 jobs in 2026 and with none in the remainder of the
analysis period. Total jobs supported are about 162 in 2024, rising to about 443 in 2026, and
dropping to zero in the later years of the analysis period.
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Table 9-5 Employment Impacts of Compliance Expenditures and Output Changes
Capital O&M Output Total
Equipment Installation Production GETS"
Multiplier:
2.7
4.3
0.5
1.0
0.5
Year
Exp.
Jobs
Exp.
Jobs
Exp.
Jobs
Exp.
Jobs
Rev.
Jobs
Jobs
2024
$34.2
93
$14.6
62
-$9.9
-5
$14.0
14
-$3.3
-2
162
2025
$68.2
186
$29.2
124
-$16.2
-8
$30.9
31
-$3.6
-2
331
2026
$96.4
262
$41.3
176
-$22.0
-11
$44.2
45
-$50.2
-28
443
2027
$93.4
254
$40.0
170
-$19.6
-10
$43.9
44.4
-$46.9
-26
433
2028
$0.3
1
$0.1
1
$15.5
8
$2.5
2
-$1.4
-1
11
2029
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$1.0
-1
5
2030
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
-1
5
2031
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
-1
5
2032
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
-1
5
2033
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
0
5
2034
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
0
5
2035
$0.0
0
$0.0
0
$11.1
6
$0.0
0
-$0.9
0
5
a GBTS stands for Gathering, Boosting, Transmission, & Storage.
9.3 Environmental Justice
9.3.1 Introduction and Background
Executive Order 14906, signed April 21, 2023, builds on the prior executive orders to
further advance environmental justice (88 FR 25251), including Executive Order 12898 (59 FR
7629, February 16, 1994) and Executive Order 14008 (86 FR 7619, January 27, 2021) which
establish federal executive policy on environmental justice. EPA defines66 environmental justice
as the "just treatment and meaningful involvement of all people, regardless of income, race,
color, national origin, Tribal affiliation, or disability, in agency decision-making and other
Federal activities that affect human health and the environment so that people: (i) are fully
protected from disproportionate and adverse human health and environmental effects (including
risks) and hazards, including those related to climate change, the cumulative impacts of
environmental and other burdens, and the legacy of racism or other structural or systemic
66 EPA recognizes that Executive Order 14096 (88 FR 25251, April 21, 2023) provides a new terminology and a
new definition for environmental justice. For additional information, see
https://www.federalregister.gov/documents/2023/04/26/2023-08955/revitalizing-our-nations-commitment-to-
environmental-justice-for-all.
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barriers; and (ii) have equitable access to a healthy, sustainable, and resilient environment in
which to live, play, work, learn, grow, worship, and engage in cultural and subsistence
practices."67
Executive Order 12898 (59 FR 7629; February 16, 1994) establishes federal executive
policy on environmental justice. Its main provision directs federal agencies, to the greatest extent
practicable and permitted by law, to make environmental justice part of their mission by
identifying and addressing, as appropriate, disproportionately high and adverse human health or
environmental effects of their programs, policies, and activities on communities with
environmental justice concerns in the United States. EPA defines environmental justice as the
fair treatment and meaningful involvement of all people regardless of race, color, national origin,
or income with respect to the development, implementation, and enforcement of environmental
laws, regulations, and policies. EPA's "Technical Guidance for Assessing Environmental Justice
in Regulatory Analysis" (U.S. EPA, 2016) provides recommendations that encourage analysts to
conduct the highest quality analysis feasible, recognizing that data limitations, time and resource
constraints, and analytic challenges will vary by media and circumstance.
A reasonable starting point for assessing the need for a more detailed EJ analysis is to
review the available evidence from the published literature and from community input on what
factors may make population groups of concern more vulnerable to adverse effects (e.g.,
underlying risk factors that may contribute to higher exposures and/or impacts). It is also
important to evaluate the data and methods available for conducting an EJ analysis. EJ analyses
can be grouped into two types, both of which are informative, but not always feasible for a given
rulemaking:
1. Baseline: Describes the current (pre-control) distribution of exposures and risk,
identifying potential disparities.
2. Policy: Describes the distribution of exposures and risk after the regulatory option(s)
have been applied (post-control), identifying how potential disparities change in response
to the rulemaking.
EPA's 2016 Technical Guidance does not prescribe or recommend a specific approach or
methodology for conducting EJ analyses, though a key consideration is consistency with the
67 See, e.g., Environmental Protection Agency. "Environmental Justice." Available at:
https://www.epa.gov/environmentaljustice.
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assumptions underlying other parts of the regulatory analysis when evaluating the baseline and
regulatory options.
9.3.2 Scope and Limitations
The EJ analysis described in this section evaluates only a "baseline" set of environmental
justice indicators of 559 counties determined to have methane emissions expected to be affected
by the WEC, using the most recent available data. This analysis uses historical data, which
enables us to characterize communities that in these counties prior to implementation of the final
rule, and identify potential environmental justice concerns - on aggregate - across the
populations of the 559 counties. We lack key information that would be needed to assess post-
control risks (the "policy" scenario as described above) under the WEC or the regulatory
alternatives analyzed in this RIA. Therefore, the extent to which this rule will affect potential EJ
outcomes is not quantitatively evaluated.
This action chronologically follows the Oil and Gas NSPS/EG RIA which presents a
detailed environmental justice analysis of health risks and economic activity associated with the
oil and gas industry. Because the sources potentially affected by the WEC are a subset of those
affected by the 2024 Final NSPS/EG rule and the populations overlap, EPA expects the WEC
implications for environmental justice to be directionally similar to those of the NSPS/EG rule.
Because the magnitude of emissions reductions is larger for the NSPS/EG rule than for the WEC,
the magnitude of environmental justice implications is also smaller for the WEC.
In updating the analysis for this final rule, EPA has used the most recent data for county
level emissions that are expected to be affected by the rule. Time and resource constraints
prevent the replication of the full series of analyses conducted for the NSPS/EG RIA.
9.3.3 Summary of Environmental Justice Findings of the NSPS/EG RIA
The RIA for the 2024 Final NSPS/EG conducted detailed analyses of impacts the rule
across several areas of concern for environmental justice.
The NSPS/EG RIA presented an evaluation of the EJ implications of ozone from VOC
emissions from the oil and natural gas sector. The RIA for the 2024 Final NSPS/EG concluded
that because of expected reductions in methane emissions, the NSPS/EG would also contribute to
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the slight reductions in formation of ground level ozone, with attendant benefits for human
health. Similarly, the Air Toxics exposure analysis showed that there are many sources of air
toxics from a number of sectors, but populations currently over-represented in exposure to
emissions from the oil and gas sector include environmental justice communities, and that
emissions reductions from the Rule will benefit those communities.
The RIA for the 2024 Final NSPS/EG also considered the economic impacts of
regulation on employment among overburdened or marginalized communities. The RIA notes
that a reduction in employment in the oil and natural gas sector may be associated with loss of
income for workers in the oil and gas industry, and for oil and gas communities. With respect to
energy expenditures, the RIA notes that low income, and, to some extent, racial and ethnic
minorities are more likely to be negatively impacted by energy price increases. However, the
RIA notes that the NSPS/EG rule is unlikely to have a significant impact on oil and gas
employment or on energy prices among overburdened and marginalized communities, and,
therefore, that it is unlikely to exacerbate existing inequality. Please note that Section 9.2 of this
RIA estimates employment impacts of the WEC, and finds net increase in employment in oil and
gas industries.
As mentioned above, EPA expects that the findings of the environmental justice analysis
included in the RIA for the 2024 Final NSPS/EG are generally relevant for the WEC as well
because of the overlap in affected sources and populations.
9.3.4 Environmental Justice Analysis of the Final WEC Rule
EPA constructed an analysis of reported methane emissions - by county - in the United
States for the facilities in the Onshore Petroleum and Natural Gas Production and Onshore
Petroleum and Natural Gas Gathering and Boosting industry segments with methane emissions
that exceed their waste emissions threshold (i.e., their WEC applicable emissions are greater than
zero) based on reported RY 2022 emissions and throughputs. We allocated the reported methane
emissions for facilities in the Onshore Petroleum and Natural Gas Production industry segment
to counties proportional to the number of producing wells the facility reported for each county
(which is part of the reported sub-basin identifier). We determined the counties in which each
facility in the Onshore Petroleum and Natural Gas Gathering and Boosting industry segment
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operated based on the reported location of acid gas removal units, dehydrators, flare stacks, and
atmospheric storage tanks. We then allocated the reported methane emissions evenly across the
counties identified.
We used this analysis to identify 559 counties where Onshore Petroleum and Natural Gas
Production and/or Onshore Petroleum and Natural Gas Gathering and Boosting facilities with
reported emissions for 2022 that would exceed facility waste emissions thresholds (see Section
4). See Figure 9-1.
I I State boundaries
Counties with CH4 emissions above
the WEC intensity threshold
I I Low
I I Medium
Very High
A
Figure 9-1 Map of the counties identified as having emissions from facilities potentially
subject to the Waste Emissions Charge (2022)
As noted above, the analysis in this section is focused on baseline conditions using
historical data. Again, we are not able to assess how the rule may affect emissions from specific
counties - emissions changes will depend on decisions taken by regulated entities in response to
specific local conditions. Consequently, we do not quantify any environmental justice impact of
the WEC following its implementation. Importantly, we note that this final rule may not impact
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all locations with oil and natural gas emissions equally, in part due to differences in existing state
regulations in locations like Colorado and California, which have more stringent requirements.
For the 559 counties described above, we can identify certain demographic characteristics
of the communities, the incidence of some chronic disease conditions among the populations,
and Total Cancer Risk and Total Respiratory Risk for the people in these counties. We compare
the data on these characteristics for counties likely to be affected by the WEC to data on the
characteristics to national averages. Note that this comparison does not isolate the correlation
between environmental justice concerns and oil and gas production -counties may have oil and
gas activity and associated emissions but may not be subject to the WEC and there are other
sources of emissions that contribute to health risks. Additionally, emissions from the oil and gas
sector may affect populations downwind of the source county, but for this analysis we are not
conducting air transport modeling and limiting analysis to the populations living in the source
counties.
Demographic data, including income, race and ethnicity are taken from the most recent
(2018-2022) American Communities Survey (ACS) published by the Census Bureau (2023a).
This data was gathered from 2018-2022. We use the 2022 "PLACES Dataset," published by the
Centers for Disease Control, to gather county-level incidence of asthma and heart disease
(specifically "Chronic Asthma Prevalence Among Adults >18 years," and "Chronic Heart
Disease Prevalence Among Adults >18 years"). We provide county level cancer risk and
respiratory risk at the county level by analyzing the EPA dataset on risks from atmospheric
pollution called AirToxScreen (U.S. EPA, 2024b). "Total Cancer Risk" is presented as cancers
per one million people from a lifetime exposure to a certain level of air pollution, over and above
other cancer risks. "Total Respiratory Risk" is a non-cancer hazard quotient, which is exposure
to a substance divided by the level of exposure at which no adverse effects are expected - both
risk measures are the sum of all individual risk values for the chemicals evaluated in the
AirToxScreen database (U.S. EPA, 2024c).
Emissions from the 559 counties described above range from under one metric ton per
year of methane, to more than 50,000 tons per year. We've divided the counties into groups
based on their respective annual emissions and compare the average demographic and risk
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indicators for each category with the averages for the entire group, and with the averages for all
U.S. counties. The categories are "low, medium, high, and very high." (see Table 9-6)
Table 9-6 Categorizing Category Emissions by Intensity
Category Label
County emissions
(mt/year)
Percentile
Total Counties
Percent of Total
Emissions
Low
<1-585
<60*
334
6%
Medium
585 - 1,292
OS
0
s-
1
00
o
B-
113
12%
High
1,292-6,818
82
32%
Very High
6,818-50,543
>95*
30
50%
These results show that the emissions vary widely, and that the highest emitting counties
account for a disproportionate fraction of the total. The top 30 counties, less than 5% of the of
the group, contribute over 50% of the methane emissions. Emissions from the 334 low emissions
counties contributes 6 percent of the total. Figure 9-2 shows emissions from all 559 counties
ranked from lowest total annual emissions to highest.
The categorization gives an opportunity to investigate any relationship between county
emissions quantity and health risk for communities in these counties. Clearly, there are many
potential reasons that emissions identified here may not be directly correlated with risks, even
though these emissions are associated with emissions of hazardous air pollution and are
precursors to ground level ozone. First, counties are large areas, and populations in counties may
not be near oil and gas emissions sources. Second, there are other sources of emissions risks in
these counties. Moreover, many of these counties include emissions from the oil and gas sector
that are not affected by the proposal, and therefore not quantified in these results. Additionally,
many communities in these counties face risks from atmospheric emissions from outside of their
county boundaries.
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40,OC
30,000
20,000
10,0(1)
0 • '
° »s R»» s 8 s s a s I 3 S 3 IS 3 s 1 11 5 ; s s s K 8 I fi S51 R 3 g 5 s 5 S s =; £ 1 j I 5 5 3 I s 1 £ 11 I 5 s 5 I I
Figure 9-2 Individual County Emissions Ranked from Lowest to Highest
It is important to note, however, that these results are averages, and circumstances for
communities and households in individual counties can be very different from the average risks
we can show with this data.
9.3.5 Aggregate Average Conditions for Potentially Affected Counties
The data shown in Table 9-7 are taken for each county from the most recent government
datasets. The demographic data is from the 2018-2022 American Communities Survey (US
Census, 2023). The Total Cancer Risk and Total Respiratory Risk data are from the EPA
AirToxScreen 2020 database (EPA, 2024b). Chronic Asthma Prevalence among Adults Age >
18 years and Chronic Heart Disease Prevalence among Adults Age >18 years are from the
Center for Disease Control "2022 PLACES" Dataset (CDC, 2023). For each indicator, the
national average for the indicator is in the first column (note that national average of 3,143
counties includes the counties in this dataset). The second column includes the averages for all
559 counties identified as having emissions potentially subject to the WEC. The Low Emissions
column averages are for the 334 counties with annual methane emissions less than 585 metric
tons. The Medium Emissions column shows the indicator averages for the 118 counties with
emissions between 585 and 1,292 metric tons. The82 counties represented in the High Emissions
column have emissions between 1,292 and 6,818 metric tons, and the Very High Emission
column represents the 30 counties with reported emissions above 6,818 tons (the county with the
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highest emissions potentially subject to the WEC has reported emissions of 50,544 metric tons of
methane).
Looking at all of the potential WEC counties, this analysis shows results that are
generally consistent with the main results from the NSPS/EG RIA analysis. The communities in
these counties are generally more diverse than the national average. These counties are home to
higher percentages of individuals who identify as being Native American, or who identify as
members of race "other" than White, Black or African American, or Native American. There are
generally more people who identify as having Hispanic or Latino ethnicity - who are
substantially over-represented in the High and Very High Emissions counties. There are
generally fewer individuals who identify as Black or African Americans in these counties, with
progressively fewer moving from Low to Medium to High emissions counties, but a high
percentage (10.4) again in the 30 "Very High Emissions" counties. Native Americans
populations are disproportionately represented in these counties with High Emissions and Very
High Emissions. While the median household income for these counties is generally lower than
the national average, it is higher than the national average in the 30 counties with the highest
emissions. Similarly, the households with low incomes (below the Poverty line) and very low
incomes (below 50% of the poverty line) are over-represented compared to the national average,
but in the counties with the highest emissions there are fewer households with low and very low
incomes.
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Table 9-7 Overall Demographic and Health Indicators for All Counties, by Category
All
Low
Medium
High
Very High
Potential
Emissions
Emissions
Emissions
Emissions
National
\\l(
(<60th
(60th - 80th
(80th-95th
(>95th
Average
( tunnies
percentile)
percentile)
percentile)
percentile)
% White (race)
65.9
(.1 "
62.4
57.5
66.5
62.9
% Black or African
12.5
lu "
11.2
10.7
4.7
10.4
American (Race)
% Native American
(Race)
0.84
1.0
1.0
0.8
1.6
1.8
% Other (Race)
21.7
"
26.4
31.8
21.5
27.8
% Hispanic (Ethnicity)
18.7
2" (.
23.2
36.3
31.0
32.4
Median Household
78.6
- 1 £
75.7
71..5
62.5
83.8
Income (lk 2019$)
4
% Below Poverty Line
6.5
~ 5
7.3
7.8
9.9
5.7
% Below Half the
Poverty Line
5.7
(.4
6.4
6.8
6.4
5.4
Total Cancer Risk (per
million)
25.4
2" (.
26.9
30.8
23.3
28.5
Total Respiratory Risk
(hazard quotient)
0.31
o ^2
0.31
0.35
0.25
0.30
Chronic Asthma
9.7
1>.X
9.9
9.5
9.9
9.6
Prevalence (> 18yrs)
Chronic Heart Disease
^ A
f (i
5.9
6.0
6.4
5.7
Prevalence (> 18yrs)
With regard to the health indicators from the AirToxScreen and PLACES datasets, there
appears to be a general elevation across all health categories for the 559 counties compared to the
national averages68. However, there does not appear to be a significant trend in health risks for
counties with higher emissions potentially subject to the WEC.
These health indicators are consistent with the findings from the NSPS/EG RIA: that
while ozone and hazardous pollutants from the oil and gas industry are known to present health
risks, data at the county level is too aggregated and across too large an area to show the impacts
of the emissions on entire county populations.
68 The statistical significance of the cancer risk factors from the AirToxScreen Data cannot be quantitatively
characterized since the dose-response function is modeled. The general observation from the analysis is not that
affected sources are uniquely responsible for elevated risk to communities, as there are other sources of risk.
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It is possible, however, that some households in these 559 counties are located in close
proximity to sources of emissions and may face higher than average health risks. This analysis
indicates that these risks appear to be higher for communities with environmental justice
concerns. With currently available data, the quantitative assessments of existing environmental
justice indicators are subject to various types of uncertainty, but these results suggest additional and
continuing analysis of environmental justice concerns for these communities is warranted.
Due to lack of resources, time, and data, it is not possible to conduct a more thorough
investigation of the very localized conditions of communities that may be subject to
disproportionate risk, which include environmental justice communities of concern, and that may
be affected by the rule.
Because the impacts of the rule will depend on decisions about emissions sources that
will be made in response to local economic and regulatory conditions, it is not possible to project
the impact of the rule on specific communities. EPA believes, however, that in aggregate the
final action will result in reduction of methane, hazardous air pollutants, and volatile organic
compounds, and, generally, this result will improve environmental justice outcomes.
9.4 The Distribution of Long-Term Climate Impacts
9.4.1 Environmental Justice Implications of Climate Change
Methane emissions represent a significant share of total GHG emissions and hence are a
major contributor to climate change. In 2009, under the Endangerment and Cause or Contribute
Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act ("Endangerment
Finding"), the Administrator considered how climate change threatens the health and welfare of
the U.S. population. As part of that consideration, the EPA Administrator also considered risks to
communities with environmental justice concerns, finding that certain parts of the U.S.
population may be especially vulnerable based on their characteristics or circumstances. These
groups include economically and socially vulnerable communities; individuals at vulnerable life
stages, such as the elderly, the very young, and pregnant or nursing women; those already in
poor health or with comorbidities; the disabled; those experiencing homelessness, mental illness,
or substance abuse; and/or Indigenous or people of color dependent on one or limited resources
for subsistence due to factors including but not limited to geography, access, and mobility.
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Scientific assessment reports produced over the past decade by the U.S. Global Change
Research Program (USGCRP), the IPCC, and the National Academies of Science, Engineering,
and Medicine add more evidence that the impacts of climate change raise potential EJ concerns
(IPCC, 2018; Oppenheimer et al., 2014; Porter et al., 2014; Smith et al., 2014; USGCRP, 2016,
2018).
These reports conclude that poorer or predominantly non-White communities can be
especially vulnerable to climate change impacts because they tend to have limited adaptive
capacities and are more dependent on climate-sensitive resources such as local water and food
supplies or have less access to social and information resources. Some communities of color,
specifically populations defined jointly by ethnic/racial characteristics and geographic location,
may be uniquely vulnerable to climate change health impacts in the U.S. In particular, the 2016
scientific assessment on the Impacts of Climate Change on Human Health found with high
confidence that vulnerabilities are place- and time-specific, life stages and ages are linked to
immediate and future health impacts, and social determinants of health are linked to greater
extent and severity of climate change-related health impacts. The GHG emission reductions
associated with this proposal would contribute to efforts to reduce the probability of severe
impacts related to climate change. Individuals living in socially and economically disadvantaged
communities, such as those living at or below the poverty line or who are experiencing
homelessness or social isolation, are at greater risk of health effects from climate change. This is
also true with respect to people at vulnerable life stages, specifically women who are pre- and
perinatal, or are nursing; in utero fetuses; children at all stages of development; and the elderly.
Per the Fifth National Climate Assessment (NCA5), "Health risks from a changing climate
include higher rates of heat-related morbidity and mortality; increases in the geographic range of
some infectious diseases; greater exposure to poor air quality; increases in some adverse
pregnancy outcomes; higher rates of pulmonary, neurological, and cardiovascular diseases; and
worsening mental health." Many of these exacerbated health conditions occur at higher rates
within vulnerable communities. Importantly, negative public health outcomes include those that
are physical in nature, as well as mental, emotional, social, and economic.
The scientific assessment literature demonstrates that there are myriad ways these
populations may be affected at the individual and community levels. Individuals face differential
exposure to criteria pollutants, in part due to the proximities of highways, trains, factories, and
9-24
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other major sources of pollutant-emitting sources to less-affluent residential areas. Outdoor
workers, such as construction or utility crews and agricultural laborers, who frequently are
comprised of already at-risk groups, are exposed to poor air quality and extreme temperatures
without relief. Furthermore, individuals within EJ populations of concern face greater housing,
clean water, and food insecurity and bear disproportionate economic impacts and health burdens
associated with climate change effects. They have less or limited access to healthcare and
affordable, adequate health or homeowner insurance. Resiliency and adaptation are more
difficult for economically disadvantaged communities: They have less liquidity, individually and
collectively, to move or to make the types of infrastructure or policy changes to limit or reduce
the hazards they face. They frequently are less able to self-advocate for resources that would
otherwise aid in building resilience and hazard reduction and mitigation.
In a 2021 report, Climate Change and Social Vulnerability in the United States: A Focus
on Six Impacts, EPA considered the degree to which four socially vulnerable populations—
defined based on income, educational attainment, race and ethnicity, and age— may be more
exposed to the highest impacts of climate change (U.S. EPA, 2021c). The report found that
Blacks and African American populations are approximately 40 percent more likely to currently
live in these areas of the U.S. projected to experience the highest increases in mortality rates due
to changes in temperature. Additionally, Hispanic and Latino individuals in weather exposed
industries were found to be 43 percent more likely to currently live in areas with the highest
projected labor hour losses due to temperature changes. American Indian and Alaska Native
individuals are projected to be 48 percent more likely to currently live in areas where the highest
percentage of land may be inundated by sea level rise. Overall, the report confirmed findings of
broader climate science assessments that Americans identifying as people of color, those with
low-income, and those without a high school diploma face higher differential risks of
experiencing the most damaging impacts of climate change.
The assessment literature cited in EPA's 2009 and 2016 Endangerment and Cause or
Contribute Findings, as well as Impacts of Climate Change on Human Health (2016) and the
NCA4 (2018), also concluded that certain populations and life stages, including children, are
especially sensitive to climate-related health effects. In a more recent 2023 report, Climate
Change Impacts on Children's Health and Weil-Being in the U.S., EPA considered the degree to
which children's health and well-being may be impacted by five climate-related environmental
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hazards - extreme heat, poor air quality, changes in seasonality, flooding, and different types of
infectious diseases (U.S. EPA, 2023c). The report found that children's academic achievement is
projected to be reduced by 4-7% per child, as a result of moderate and higher levels of warming,
impacting future income levels. The report also projects increases to the numbers of annual
emergency department visits associated with asthma and a four to eleven percent increase in new
asthma diagnoses due to climate-driven increases in air pollution. In addition, more than 1
million children in coastal regions are projected to be temporarily displaced from their homes
annually due to climate-driven flooding, and infectious disease rates are similarly anticipated to
rise, with the number of new Lyme disease cases in children living in 22 states in the eastern and
midwestern U.S. increasing by approximately 3,000-23,000 per year compared to current levels.
Overall, the report confirmed findings of broader climate science assessments that children are
uniquely vulnerable to climate-related impacts and that in many situations, children in the U.S.
who identify as Black, Indigenous, and People of Color, are limited English-speaking, do not
have health insurance, or live in low-income communities may be disproportionately exposed to
the most severe impacts of climate change.
Native American Tribal communities possess unique vulnerabilities to climate change,
particularly those impacted by degradation of natural and cultural resources within established
reservation boundaries and threats to traditional subsistence lifestyles. Tribal communities whose
health, economic well-being, and cultural traditions depend upon the natural environment will
likely be affected by the degradation of ecosystem goods and services associated with climate
change. The IPCC indicates that losses of customs and historical knowledge may cause
communities to be less resilient or adaptable. The NCA4 noted that while Indigenous peoples are
diverse and will be impacted by the climate changes universal to all Americans, there are several
ways in which climate change uniquely threatens Indigenous peoples' livelihoods and
economies. In addition, there can institutional barriers to their management of water, land, and
other natural resources that could impede adaptive measures.
For example, Indigenous agriculture in the Southwest is already being adversely affected
by changing patterns of flooding, drought, dust storms, and rising temperatures leading to
increased soil erosion, irrigation water demand, and decreased crop quality and herd sizes. The
Confederated Tribes of the Umatilla Indian Reservation in the Northwest have identified climate
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risks to salmon, elk, deer, roots, and huckleberry habitat. Housing and sanitary water supply
infrastructure are vulnerable to disruption from extreme precipitation events.
NCA4 noted that Indigenous peoples often have disproportionately higher rates of
asthma, cardiovascular disease, Alzheimer's, diabetes, and obesity, which can all contribute to
increased vulnerability to climate-driven extreme heat and air pollution events. These factors
also may be exacerbated by stressful situations, such as extreme weather events, wildfires, and
other circumstances.
NCA4 and IPCC Fifth Assessment Report also highlighted several impacts specific to
Alaskan Indigenous Peoples. Coastal erosion and permafrost thaw will lead to more coastal
erosion, exacerbated risks of winter travel, and damage to buildings, roads, and other
infrastructure - these impacts on archaeological sites, structures, and objects that will lead to a
loss of cultural heritage for Alaska's Indigenous people. In terms of food security, the NCA4
discussed reductions in suitable ice conditions for hunting, warmer temperatures impairing the
use of traditional ice cellars for food storage, and declining shellfish populations due to warming
and acidification. While the NCA also noted that climate change provided more opportunity to
hunt from boats later in the fall season or earlier in the spring, the assessment found that the net
impact was an overall decrease in food security.
In addition, the U.S. Pacific Islands and the indigenous communities that live there are
also uniquely vulnerable to the effects of climate change due to their remote location and
geographic isolation. They rely on the land, ocean, and natural resources for their livelihoods, but
face challenges in obtaining energy and food supplies that need to be shipped in at high costs. As
a result, they face higher energy costs than the rest of the nation and depend on imported fossil
fuels for electricity generation and diesel. These challenges exacerbate the climate impacts that
the Pacific Islands are experiencing. NCA4 notes that Indigenous peoples of the Pacific are
threatened by rising sea levels, diminishing freshwater availability, and negative effects to
ecosystem services that threaten these individuals' health and well-being.
9.4.2 Avoided U.S. Climate Impacts of the Final Rule
As discussed in the previous section, large-scale impacts resulting from GHG-driven
long-term climate change may be experienced differently across populations and regions. This
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section presents an analysis of the distribution of avoided long-term climate impacts associated
with the CH4 emission reductions from the final rule to better understand how the WEC rule may
mitigate climate change impacts, and how these changes may be experienced differently by
residents across the U.S. This analysis uses the Framework for Evaluating Damages and Impacts
(FrEDI)69 (U.S. EPA, 2024a) to illustrate how climate-driven impacts at the end of the century
(2100) may be distributed across different sectors, regions, and populations within contiguous
U.S. borders. While the impact categories included in this analysis cover a large range across the
U.S. economy, FrEDI does not include a comprehensive list of all climate-driven impacts and
only explores those effects that directly occur within contiguous U.S. borders. Therefore, FrEDI
only provides a subset of the impacts expected to accrue to U.S. citizens and their interests. See
Appendix B for additional information on the FrEDI analysis.
Summary of Changes Across Sectors, Regions, and Populations
Annual net70 climate-driven impacts across all modeled sectors of the U.S. are projected
to decrease as a result of methane emission reductions from the rule. These avoided damages are
associated with reductions in climate-driven impacts on human health, such as changes in
temperature-related mortality, climate-driven air quality (ozone and ambient fine particulate
matter (PM2.5)) related mortality71, suicide, violent crime, and exposure to wildfire smoke,
ambient dust in the Southwest, Vibriosis, and Valley fever; infrastructure-related impacts such as
effects on transportation from high-tide flooding, property damage from hurricane winds, and
damages to roads and rail; and labor hours lost when temperatures are too hot for workers to
work outdoors or in unconditioned workplaces.
Of these analyzed sectors, reductions in climate-driven impacts associated with the final
rule will not be distributed evenly across different geographic U.S. regions. However, all states
69 This analysis uses v4.1 of the Framework for Evaluating Damages and Impacts (U.S. EPA, 2024a). The FrEDI
Technical Documentation and associated R package have been subject to both a public review comment period
and an independent expert peer review, following EPA peer-review guidelines. The original FrEDI Technical
Documentation was published in October 2021 (U.S. EPA, 2021a). www.epa.gov/cira/fredi
70 FrEDI evaluates both negative and positive effects of climate change across its sectors, which can geographically
vary in sign and magnitude (e.g., warming can lead to decreases in health effects in the Midwest from climate-
driven changes in PM2 5). At the national level, the net impacts are reduced in all sectors in response to changes in
methane emissions from the final rule.
71 The air quality benefits described here are a result of changes in concentrations of ozone and fine particulate
matter (PM2 5) that are the result of climate-driven changes in meteorology, atmospheric chemistry, and other
biogeochemical factors and not from direct changes in PM2 5 and ozone precursor emissions.
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are projected to benefit. Regional and sectoral differences are driven in part by geographic
variations in where climate change damages are projected to occur, the sector being considered,
and the current demographic patterns of where populations currently live. Figure 9-3 shows the
distribution of the climate impacts per capita that are projected to be avoided under the final rule
in the year 2100, across 48 U.S. states plus the District of Columbia. Virginia is projected to
have the largest avoided impacts per capita, with Massachusetts, and North Carolina projected to
experience the second and third largest avoided per capita impacts. When further considering the
detailed sector-specific impacts avoided under the final WEC, there are also important
differences in the distribution of the relative avoided impacts across each U.S. state. For
example, while temperature-related mortality is projected to be the largest sector (e.g., the sector
experiencing the largest per capita avoided damages) in each state in 2100, avoided damages
from climate-driven changes in air quality are projected to be the second largest in 27 states,
avoided damages to transportation infrastructure (e.g., rail and roads) are projected to be the
second largest in seven states throughout the Midwest and Northern Plains (Kansas, Minnesota,
Montana, North Dakota, Nebraska, South Dakota, Wyoming), avoided damages to agriculture
are projected to be the second largest in Iowa and Illinois, and avoided damages from wildfire
are projected to be either the second or third largest in eight states within the Northwest,
Northern Plains, and Southwest regions (Colorado, Idaho, Montana, Nevada, Oregon, Utah,
Washington, Wyoming). In addition, avoided impacts from some sectors are only expected to be
experienced in select regions. For example, avoided damages from climate-driven changes in
dust and Valley Fever will primarily be experienced by populations living in states in the
Southwest region (second or third largest sectors in Arizona, Colorado, New Mexico, and Utah),
while reductions in tropical wind damage and transportation impacts from high-tide flooding will
largely occur along coastlines of states in the Southeast, Southern Plains, and Northeast regions
(second or third largest sectors in 18 states, including DC, Louisiana, New Hampshire,
Massachusetts, New Jersey, and Texas).
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¦
higher
lower
Figure 9-3 Annual Avoided Climate Driven Damages Per Capita, by State in the Year
210072
Lastly, while all populations are also projected to experience a reduction in net climate-
driven impacts from the rule, these avoided impacts will not be evenly distributed across
populations. Understanding the comparative risks to different populations is critical for
developing effective and equitable strategies for responding to climate change. Of the four
dimensions of social vulnerability considered in this analysis (age, income, education level, and
race and ethnicity73), BIPOC (Black, Indigenous, and People of Color) individuals aged 65 and
older are more likely to live in regions that are projected to see the largest reductions in climate-
driven air quality mortality, while those with low-incomes74 are more likely to see larger
reductions in avoided lost labor hours due to extreme temperatures. When further considering
differences across different races and ethnicities included in this analysis, Black or African
Americans over the age of 65 are more likely to see greater reductions in climate-driven changes
in air quality mortality and transportation impacts from high tide flooding, largely driven by the
regional differences in where different populations currently live and where avoided climate
driven changes are projected to occur due to emission reductions in the final rule.
72 Figure 9-3 includes avoided damages from all sectors modeled within FrEDI v4.1, which is not a comprehensive
accounting of all the ways in which climate will impact American interests.
73 Based on the data and methodology presented in a recent EPA report on Climate Change and Social Vulnerability
in the United States (U.S. Enviromnental Protection Agency: Climate Change and Social Vulnerability in the
United States: A Focus on Six Impacts, Washington, DC, EPA/430/R-21/003, 2021.).
74 Individuals living in households with income that is 200% of the poverty level or lower
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This analysis advances the detailed understanding of the distribution of climate change
impacts within U.S. borders (excluding Alaska, Hawaii, and the U.S. territories), and is intended
to provide a snapshot of the different ways U.S. residents are projected to experience fewer
climate-driven damages as a result of the methane reductions from the WEC. See Appendix B
for detailed discussion of avoided damages across all 22 impact sectors, 7 regions, 48 states (plus
the District of Columbia), and 4 dimensions of social vulnerability included within FrEDI. This
assessment is the most detailed and complete to date but is not comprehensive and should
therefore be considered a preliminary accounting of climate impacts relevant to U.S. interests.
9-31
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ANNEXES
APPENDIX A
ILLUSTRATIVE SCREENING ANALYSIS OF MONETIZED VOC-RELATED OZONE
HEALTH BENEFITS
In this appendix, we present a supplementary screening analysis to estimate potential
health benefits from the changes in ozone concentrations resulting from VOC emissions
reductions under the final rule. As described in detail below, the distribution of the projected
change in VOC emissions are subject to significant uncertainties; for this reason, the estimated
benefits reported below should not be interpreted as a central estimate and thus are not reflected
in the calculated net benefits above. For this analysis, we apply a national benefit-per-ton
approach based on photochemical modeling with source apportionment paired with the
Environmental Benefits Mapping and Analysis Program (BenMAP) for years between 2024 and
2035 using an April-September average of 8-hr daily maximum (MDA8) ozone metric.
A.l Air Quality Modeling Simulations
The photochemical model simulations are described in detail in U.S. EPA (2021a) and
are summarized briefly in this section. The air quality modeling used in this analysis included
annual model simulations for the year 2017. The photochemical modeling results for 2017, in
conjunction with modeling to characterize the air quality impacts from groups of emissions
sources (i.e., source apportionment modeling) and expected emissions changes due to this rule,
were used to estimate ozone benefits expected from this rule in the years 2024-2035.
The air quality model simulations (i.e., model runs) were performed using the
Comprehensive Air Quality Model with Extensions (CAMx version 7.00) (Ramboll Environ,
2016). The CAMx nationwide modeling domain (i.e., the geographic area included in the
modeling) covers all lower 48 states plus adjacent portions of Canada and Mexico using a
horizontal grid resolution of 12x12 km shown in Figure A-l.
A-l
-------
' -
_ \ fry
_J" S 1
/ \
( ) \m.
1 K
V « /
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m \
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1—V"1
.
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r
<
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col m ro* 2M I ly V
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Figure A-l Air Quality Modeling Domain
A.2 Ozone Model Performance
While U.S. EPA (2021a) provides an overview of model performance, we provide a more
detailed assessment here specifically focusing on ozone model performance relevant to the
metrics used in this analysis. In this section, we report CAMx model performance for the MDA8
ozone across all days in April-September. While regulatory analyses often focus on model
performance on high ozone days relevant to the NAAQS (U.S. EPA, 2018a), here we focus on
all days in April-September since the relevant ozone metrics used as inputs into BenMAP use
summertime seasonal averages. Model performance information is provided for each of the nine
National Oceanic and Atmospheric Administration (NOAA) climate regions in the contiguous
US, as shown in Figure A-2 and first described by Karl and Koss (1984).
Table A-l provides a summary of model performance statistics by region. Normalized
Mean Bias was within ±10 percent in eveiy region and within ±5 percent in the Northeast, Ohio
Valley, South, Southwest, and West regions. Across all monitoring sites, normalized mean bias
was -0.2 percent. Normalized mean error for modeled MDA8 ozone was less than ±20 percent in
every region except the Northwest where it was 21 percent. Correlation between the modeled
and observed MDA8 ozone values was 0.7 or greater in five of the nine regions (Northeast,
Upper Midwest, Southeast, South, and West). In the remaining four regions correlation was 0.69
in the Ohio Valley, 0.64 in the Northern Rockies and Plains, 0.46 in the Southwest, and 0.69 in
A-2
-------
the Northwest. Across the contiguous U.S. as a whole, the correlation between modeled and
measured MDA8 ozone was 0.72.
U.S. Climate Regions
Figure A-2 Climate Regions Used to Summarize 2017 CAMx Model Performance for
Ozone
Table A-l Summary of 2017 CAMx MDA8 ozone model performance for all April-
September days
Region
Number of
Monitoring
Sites
Mean
observed
MDA8
(ppb)
Mean
modeled
MDA8
(ppb)
Corr
elati
on
Mean
bias
(ppb)
RMS
E
(ppb
)
Normalize
d mean
bias (%)
Normalized
mean error
(%)
Northeast
189
42.4
42.5
0.71
0.1
9.1
0.3
17.2
Upper
Midwest
107
42.5
39.1
0.70
-3.4
9.1
-8.0
17.2
Ohio
Valley
236
45.4
45.8
0.69
0.4
8.3
0.8
14.7
Southeast
177
40.2
43.4
0.76
3.3
00
00
8.2
17.7
South
145
42.0
43.5
0.73
1.5
00
00
3.6
16.7
Northern
Rockies
55
46.8
43.1
0.64
-3.7
9.3
-7.9
16.4
and Plains
Southwest
117
54.3
52.5
0.46
-1.8
10.2
-3.4
15.5
Northwest
28
41.4
44.0
0.69
2.7
12.4
6.4
21.0
West
200
51.6
50.1
0.74
-1.5
10.3
-2.9
16.1
All
1258
45.4
45.3
0.72
-0.1
9.3
-0.2
16.4
A-3
-------
Figure A-3 displays modeled MDA8 normalized mean bias at individual monitoring sites.
This figure reveals that the model has slight overpredictions of mean April-September MDA8
ozone in the southeastern portion of the country and along the Pacific coast and slight
underpredictions in the northern and western portions of the country. Time series plots of the
modeled and observed MDA8 ozone and model performance statistics across the nine regions
were developed. Overall, the model closely captures day to day fluctuations in ozone
concentrations, although the model had a tendency to underpredict ozone in the earlier portion of
the ozone season (April and May) and overpredict in the later portion of the ozone season (July-
September) with mixed results in June. This model performance is within the range of other
ozone model applications, as reported in scientific studies (Emery et al., 2017; Simon, Baker, &
Phillips, 2012). Thus, the model performance results demonstrate the scientific credibility of our
2017 modeling platform. These results provide confidence in the ability of the modeling platform
to provide a reasonable projection of expected future year ozone concentrations and
contributions.
Figure A-3 Map of 2017 CAMx MDA8 Normalized Mean Bias (%) for April-September
at all U.S. monitoring sites in the model domain
A.3 Source Apportionment Modeling
The contribution of specific emissions sources to ozone in the 2017 modeled case were
tracked using a tool called "source apportionment." In general, source apportionment modeling
03 8hrmax NMB (%) for run CAMx_2017icenginesSO4PRI_12US2 for 20170401 to 20170930
• AQS Daily
A-4
-------
quantifies the air quality concentrations formed from individual, user-defined groups of
emissions sources or "tags." These source tags are tracked through the transport, dispersion,
chemical transformation, and deposition processes within the model to obtain hourly gridded
contributions from the emissions in each individual tag to hourly modeled concentrations of
ozone.
For this analysis ozone contributions were modeled using the Ozone Source
Apportionment Technique (OSAT) tool. In this modeling, VOC emissions from oil and natural
gas operations were tagged separately for three regions of the U.S. regions. The model-produced
gridded hourly ozone contributions from emissions from each of the source tags which we
aggregated up to an ozone metric relevant to recent health studies (i.e., the April-September
average of the MDA8 ozone concentration). The April-September average of the MDA8 ozone
contributions from each regional oil and natural gas tag were summed to produce a spatial field
representing national oil and natural gas VOC contributions to ozone across the United States
(Figure A-4).
A-5
-------
Apr-Sep MDA8 03
159 239 318
Min = 0.00E+0 at (1,1), Max = 1.885 at (145,139)
n
i
Figure A-4 Contributions of 2017 Oil and Natural Gas VOC Emissions across the
Contiguous U.S. to the April-September Average of MDA8 Ozone.
A.4 Applying Modeling Outputs to Quantify a National VOC-Ozone Benefit Per-Ton
Value
Following an approach detailed in the RIA and TSD for the Revised Cross-State Update,
we estimated the number and value of ozone-attributable premature deaths and illnesses for the
purposes of calculating a national ozone VOC benefit per-ton value for the policy scenario (U.S.
EPA, 202If, 202lg).
The EPA historically has used evidence reported in the Integrated Science Assessment
(ISA) for the most recent NAAQS review to inform its approach for quantifying air pollution-
attributable health, welfare, and environmental impacts associated with that pollutant. The ISA
synthesizes the toxicological, clinical and epidemiological evidence to determine whether each
A-6
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pollutant is causally related to an array of adverse human health outcomes associated with either
short-term (hours to less than one month) or long-term (one month to years) exposure; for each
outcome, the ISA reports this relationship to be causal, likely to be causal, suggestive of a causal
relationship, inadequate to infer a causal relationship, or not likely to be a causal. We estimate
the incidence of air pollution-attributable premature deaths and illnesses using methods
reflecting evidence reported in the 2020 Ozone ISA (U.S. EPA, 2020a) and accounting for
recommendations from the Science Advisory Board. When updating each health endpoint the
EPA considered: (1) the extent to which there exists a causal relationship between that pollutant
and the adverse effect; (2) whether suitable epidemiologic studies exist to support quantifying
health impacts; (3) and whether robust economic approaches are available for estimating the
value of the impact of reducing human exposure to the pollutant. EPA calculated and monetized
the incidence change of mortality, respiratory hospital admissions, respiratory ED visits, asthma
symptoms / exacerbation, allergic rhinitis symptoms, minor restricted activity days, and school
absence days. For a detailed description, see (U.S. EPA, 2021e, 2024d).
In brief, we used the environmental Benefits Mapping and Analysis Program—
Community Edition (BenMAP-CE) to quantify estimated counts of premature deaths and
illnesses attributable to summer season average ozone concentrations using the modeled surface
described above (Section A. 1.2). We calculate effects using a health impact function, which
combines information regarding the: concentration-response relationship between air quality
changes and the risk of a given adverse outcome; population exposed to the air quality change;
baseline rate of death or disease in that population; and air pollution concentration to which the
population is exposed. These quantified health impacts were then used to estimate the economic
value of these ozone-attributable effects as described below. For this supplemental proposal, we
quantified counts of premature deaths and illnesses by multiplying an incidence per ton against
an updated estimate of emissions described in Section 2.3. Modeled air quality changes were not
available.
We performed BenMAP-CE analyses for 2025, 2030, and 2035 using the single model
surface described above, but accounting for the change in population size, baseline death rates
and income growth in each future year. We next divided the sum of the monetized ozone benefits
in each year the April-September VOC emissions associated with the oil and natural gas source
apportionment tags in the 2017 CAMx modeling to determine a benefit per ton value for each
A-7
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year from 2024-2035.75 Emissions totals for the oil and natural gas sector used in the
contribution modeling are reported in U.S. EPA (2023). Finally, the benefit per ton values were
multiplied by the expected national VOC emissions changes in each year, as reported in Section
5.3. Since values reported in Section 5 were annual totals, we assume the emissions changes are
distributed evenly across months of the year and divide emissions changes by two to estimate the
April-September VOC changes expected from this final rule. Dividing by two is used to
calculate the emissions during the six month ozone season from April through September.
A.5 Uncertainties and Limitations of Air Quality Methodology
The approach applied in this screening analysis is consistent with how air quality impacts
have been estimated in past regulatory actions (U.S. EPA, 2019b, 2021f). However, in this
section we acknowledge and discuss several limitations.
First, the 2017 modeled ozone concentrations are subject to uncertainty. While all models
have some level of inherent uncertainty in their formulation and inputs, evaluation of the model
outputs against ambient measurements shows that ozone model performance is within the range
of model performance reported from photochemical modeling studies in the literature (Emery et
al., 2017; Simon et al., 2012) and is adequate for estimating ozone impacts of VOC emissions for
the purpose of this rulemaking.
In any complex analysis using estimated parameters and inputs from a variety of models,
there are likely to be many sources of uncertainty. This analysis is no exception. This analysis
includes many data sources as inputs, including emissions inventories, air quality data from
models (with their associated parameters and inputs), population data, population estimates,
health effect estimates from epidemiology studies, economic data for monetizing benefits, and
assumptions regarding the future state of the world (i.e., regulations, technology, and human
behavior). Each of these inputs are uncertain and generate uncertainty in the benefits estimate.
When the uncertainties from each stage of the analysis are compounded, even small uncertainties
can have large effects on the total quantified benefits. Therefore, the estimates of annual benefits
should be viewed as representative of the magnitude of benefits expected, rather than the actual
benefits that would occur every year.
75 The monetized benefit-per-ton values are listed in Table A-2.
A-8
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Because regulatory health impacts are distributed based on the degree to which housing
and work locations overlap geographically with areas where atmospheric concentrations of
pollutants change, it is difficult to fully know the distributional impacts of a rule. Air quality
models provide some information on changes in air pollution concentrations induced by
regulation, but it may be difficult to identify the characteristics of populations in those affected
areas, as well as to perform high-resolution air quality modeling nationwide. Furthermore, the
overall distribution of health benefits will depend on whether and how households engage in
averting behaviors in response to changes in air quality, e.g., by moving or changing the amount
of time spent outside (Sieg, Smith, Banzhaf, & Walsh, 2004).
Another limitation of the methodology is that it treats the response of ozone benefits to
changes in emissions from the tagged sources as linear. For instance, the benefits associated with
a 10 percent national change in oil and natural gas VOC emissions would be estimated to be
twice as large as the benefits associated with a 5 percent change in nation oil and natural gas
VOC emissions. The methodology therefore does not account for 1) any potential nonlinear
responses of ozone atmospheric chemistry to emissions changes and 2) any departure from
linearity that may occur in the estimated ozone-attributable health effects resulting from large
changes in ozone exposures.
We note that the emissions changes are relatively small compared to 2017 emissions
totals from all sources. Previous studies have shown that air pollutant concentrations generally
respond linearly to small emissions changes of up to 30 percent (Cohan, Hakami, Hu, & Russell,
2005; Cohan & Napelenok, 2011; Dunker, Yarwood, Ortmann, & Wilson, 2002; Koo, Dunker, &
Yarwood, 2007; Napelenok, Cohan, Hu, & Russell, 2006; Zavala, Lei, Molina, & Molina, 2009)
and that linear scaling from source apportionment can do a reasonable job of representing
impacts of 100 percent of emissions from individual sources (Baker & Kelly, 2014).
Additionally, past studies have shown that ozone responds more linearly to changes in VOC
emissions than changes in NOx emissions (Hakami, Odman, & Russell, 2003; Hakami, Odman,
& Russell, 2004). Therefore, it is reasonable to expect that the ozone benefits from expected
VOC emissions changes from this rule can be adequately represented using this this linear
assumption.
A-9
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A final limitation is that the source apportionment ozone contributions reflect the spatial
and temporal distribution of the emissions from each source tag in the 2017 modeled case. The
representation of the spatial patterns of ozone contributions are important because benefits
calculations depend on the spatial patterns of ozone changes in relationship to spatial distribution
of population and health incidence values. While we accounted for changes the size of the
population, baseline rates of death and income, we assume the spatial pattern of oil and natural
gas VOC contributions to ozone remain constant at 2017 levels. Thus, the current methodology
does not allow us to represent any expected changes in the spatial patterns of ozone that could
result from changes in oil and natural gas emissions patterns in future years or from spatially
heterogeneous emissions changes resulting from this final rule. For instance, the method does not
account for the possibility that new sources would change the spatial distribution of oil and
natural gas VOC emissions.
Table A-2 Benefit-per-ton Estimates of Ozone-Attributable Premature Mortality and
Illnesses for the WEC in 2019 Dollars
Benefit-per-ton of Reducing VOC Emissions from the Oil and Natural Gas Sector
Short-term
mortality
and
morbidity
(discounted
at 2%)
Short-term
mortality
and
morbidity
(discounted
at 3%)
Short-term
mortality
and
morbidity
(discounted
at 7%)
Long-term
mortality
and
morbidity
(discounted
at 2%)
Long-term
mortality
and
morbidity
(discounted
at 3%)
Long-term
mortality
and
morbidity
(discounted
at 7%)
2025
2030
2035
$244
$262
$278
$229
$247
$262
$204
$221
$236
$1,840
$2,050
$2,280
$1,780
$1,980
$2,200
$1,590
$1,780
$1,970
A-10
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Table A-3 Estimated Discounted Economic Value of Ozone-Attributable Premature
Mortality and Illnesses under the Final WEC, 2024-2035 (million 2019$)a'd
Year
Final WEC
2% Discount Rate
3% Discount Rate
7% Discount Rate
2024
$2.0b and $15°
$1.8b and $14°
$1.6b and $12°
2025
$3.9b and $30°
$3.6b and $28°
$3.0b and $23°
2026
$5.5b and $41°
$5.0b and $39°
$4.0b and $31°
2027
$5.2b and $39°
$4.7b and $37c
$3.6b and $28°
2028
$0.50b and $3.9°
$0.45b and $3.6°
$0.33b and $2.7C
2029
$0.35b and $2.8C
$0.3 lb and $2.5°
$0.22b and $1.8°
2030
$0.34b and $2.7C
$0.30b and $2.4C
$0.2lb and $1.7°
2031
$0.34b and $2.6C
$0.29b and $2.3C
$0.19 and $1.6C
2032
$0.33b and $2.6C
$0.28b and $2.3C
$0.18b and $1.4°
2033
$0.34b and 2.8°
$0.29b and $2.4C
$0.18b and $1.5°
2034
$0.33b and $2.7C
$0.28b and $2.4C
$0.17b and $1.4°
2035
$0.32b and $2.7C
$0.27b and $2.3C
$0.16b and $1.3°
a Values rounded to two significant figures.
b Includes ozone mortality estimated using the pooled Katsouyanni et al. (2009) and Zanobetti and Schwartz (2008)
short-term risk estimates.
0 Includes ozone mortality estimated using the Turner et al. (2016) long-term risk estimate.
d The WEC regulates emissions of methane. Additional benefits to the regulation may result from associated
reductions in VOC emissions.
Table A-4 Stream of Human Health Benefits under the Final WEC, 2024-2035:
Monetized Benefits Quantified as Sum of Avoided Morbidity Health Effects
and Avoided Long-term Ozone Mortality (discounted at 2 percent to 2023;
million 2019$)a'b
Year
Final WEC Option
2024
$15
2025
$30
2026
$41
2027
$39
2028
$3.9
2029
$2.8
2030
$2.7
2031
$2.6
2032
$2.6
2033
$2.8
2034
$2.7
2035
$2.7
Present Value (PV)
$150
Equivalent Annualized Value (EAV)
$14
a Benefits calculation includes ozone-related morbidity effects and avoided ozone-attributable deaths quantified
using the Turner et al. (2016) long-term risk estimate.
A-ll
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b The WEC is expected to result in emissions reductions of methane. Additional benefits to the regulation may result
from associated reductions in VOC emissions.
Table A-5 Stream of Human Health Benefits under the Final WEC, 2024-2035:
Monetized Benefits Quantified as Sum of Avoided Morbidity Health Effects
and Avoided Long-term Ozone Mortality (discounted at 3 percent to 2023;
million 2019$)a b
Year
Final WEC Option
2024
$14
2025
$28
2026
$39
2027
$37
2028
$3.6
2029
$2.5
2030
$2.4
2031
$2.3
2032
$2.3
2033
$2.4
2034
$2.4
2035
$2.3
Present Value (PV)
$140
Equivalent Annualized Value (EAV)
$14
a Benefits calculation includes ozone-related morbidity effects and avoided ozone-attributable deaths quantified
using the Turner et al. (2016) long-term risk estimate.
b The WEC regulates emissions of methane. Additional benefits to the regulation may result from associated
reductions in VOC emissions.
Table A-6 Stream of Human Health Benefits under theFinal WEC, 2024-2035:
Monetized Benefits Quantified as Sum of Avoided Morbidity Health Effects
and Avoided Long-term Ozone Mortality (discounted at 7 percent to 2023;
million 2019$)a b
Year
Final WEC Option
2024
$12
2025
$23
2026
$31
2027
$28
2028
$2.7
2029
$1.8
2030
$1.7
2031
$1.6
2032
$1.4
2033
$1.5
A-12
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2034
2035
$1.4
$1.3
Present Value (PV)
Equivalent Annualized Value (EAV)
$110
$14
a Benefits calculated as value of avoided ozone-attributable deaths (quantified using a concentration-response
relationship from the Turner et al. (2016) study and ozone-related morbidity effects).
b The WEC regulates emissions of methane. Additional benefits to the regulation may result from associated
reductions in VOC emissions.
A.6 References
Baker, K. R., & Kelly, J. T. (2014). Single source impacts estimated with photochemical model
source sensitivity and apportionment approaches. Atmospheric Environment, 96, 266-274.
Cohan, D. S., Hakami, A., Hu, Y., & Russell, A. G. (2005). Nonlinear response of ozone to
emissions: Source apportionment and sensitivity analysis. Environmental Science & Technology,
39(17), 6739-6748.
Cohan, D. S., & Napelenok, S. L. (2011). Air quality response modeling for decision support.
Atmosphere, 2(3), 407-425.
Dunker, A. M., Yarvvood, G., Ortmann, J. P., & Wilson, G. M. (2002). The decoupled direct
method for sensitivity analysis in a three-dimensional air quality model implementation,
accuracy, and efficiency. Environmental Science & Technology, 36(13), 2965-2976.
Emery, C., Liu, Z., Russell, A. G., Odman, M. T., Yarvvood, G., & Kumar, N. (2017).
Recommendations on statistics and benchmarks to assess photochemical model performance.
Journal of the Air & Waste Management Association, 67(5), 582-598.
Hakami, A., Odman, M. T., & Russell, A. G. (2003). High-order, direct sensitivity analysis of
multidimensional air quality models. Environmental Science & Technology, 37(11), 2442-2452.
Hakami, A., Odman, M. T., & Russell, A. G. (2004). Nonlinearity in atmospheric response: A
direct sensitivity analysis approach. Journal of Geophysical Research: Atmospheres, I09(DI5).
Karl, T., & Koss, W. J. (1984). Regional and national monthly, seasonal, and annual temperature
weighted by area, 1895-1983.
Katsouyanni, K., Samet, J. M., Anderson, H. R., Atkinson, R., Le Tertre. A., Medina, S., . . .
Committee, H. E. 1. H. R. (2009). Air pollution and health: a European and North American
approach (APHENA). Res Rep Health Eff lnst( 142), 5-90. Retrieved from
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Koo, B., Dunker, A. M., & Yarvvood, G. (2007). Implementing the decoupled direct method for
sensitivity analysis in a particulate matter air quality model. Environmental Science &
Technology, 41(8), 2847-2854.
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Napelenok, S. L., Cohan, D. S., Hu, Y., & Russell, A. G. (2006). Decoupled direct 3D sensitivity
analysis for particulate matter (DDM-3D/PM). Atmospheric Environment, 40(32), 61 12-6121.
Ramboll Environ. (2016). Comprehensive Air Quality Model with Extensions Version 6.40.
Retrieved from Novato, CA: https://camx-
vvp. azureweb si tes. n et/Fil es/C A M \ U sersGui de_v6.40. pdf
Si eg, H., Smith, V. K., Banzhaf, H. S., & Walsh, R. (2004). Estimating the general equilibrium
benefits of large changes in spatially delineated public goods. International Economic Review,
45(4), 1047-1077.
Simon, H., Baker, K. R., & Phillips, S. (2012). Compilation and interpretation of photochemical
model performance statistics published between 2006 and 2012. Atmospheric Environment, 61,
124-139.
Turner, M. C., Jerrett, M., Pope, A., Ill, Krewski, D., Gapstur, S. M., Diver, W. R., . . . Burnett,
R. T. (2016). Long-term ozone exposure and mortality in a large prospective study. American
Journal of Respiratory and Critical Care Medicine, 193(10), 1134-1142.
doi 10.1 164/rccm.201508-16330C.
U.S. EPA. (2018). Modeling Guidance for Demonstrating Attainment of Air Quality Goals for
Ozone, PM2.5, and Regional Haze. (EPA 454/R-18-009). Research Triangle Park, NC: Office of
Air Quality Planning and Standards. Available at:
https://www3.epa.gov/ttn/scram/guidance/guide/O3-PM-RH-Modeling_Guidance-20l 8.pdf.
U.S. EPA. (2019). Regulatory Impact Analysis for the Repeal of the Clean Power Plan, and the
Emission Guidelines for Greenhouse Gas Emissions from Existing Electric Utility Generating
Units. (EPA-452/R-19-003). Research Triangle Park, NC: U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, Health and Environmental Impact
Division. Available at: https://www.epa.gov/sites/production/files/20l9-
06/documents/utilities_ria_final_cpp_repeal_and_ace_2019-06.pdf.
U.S. EPA. (2020). Integrated Science Assessment for Ozone and Related Photochemical
Oxidants (Final Report). (EPA/600/R-20/012). Washington, DC: U.S. Environmental Protection
Agency. Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-
rel ated-photochemi cal-oxi dants.
U.S. EPA. (2021 a). 2017 National Emission Inventory Based Photochemical Modeling for
Sector Specific Air Quality Assessments (EPA-454-R-21 -005). Retrieved from Research
Triangle Park, NC: https://www.epa.gov/system/files/documents/2021-08/epa-454-r-21-005.pdf.
U.S. EPA. (2021b). Regulatory Impact Analysis for the Final Revised Cross-State Air Pollution
Rule (CSAPR) Update for the 2008 Ozone NAAQS (EPA-452-R-21 -002). Retrieved from
Research Triangle Park, NC: https://www.epa.gov/csapr/revised-cross-state-air-pollution-rule-
update.
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U.S. EPA. (2021 c). Technical Support Document (TSD) for the Final Revised Cross-State Air
Pollution Rule Update for the 2008 Ozone Season NAAQS: Estimating PM2.5- and Ozone-
Attributable Health Benefits (Docket ID No. EPA-HQ-OAR-2020-0272). Retrieved from
Research Triangle Park, NC: https://www.epa.gov/csapr/revised-cross-state-air-pollution-rule-
update.
U.S. EPA. (2021 d). Technical Support Document (TSD) for the Final Revised Cross-State Air
Pollution Rule Update for the 2008 Ozone Season NAAQS: Estimating PM2.5- and Ozone-
Attributable Health Benefits. (EPA-HQ-OAR-2020-0272). Durham, NC: U.S. Environmental
Protection Agency. Available at: https://www.epa.gov/sites/default/files/:]
03/documents/estimatingpm2.5~and ozone-attributable health benefits tsd.pdf.
U.S. EPA. (202 le). Technical Support Document, "Estimating the Benefit per Ton of Reducing
Directly-Emitted PM2.5, PM2.5 Precursors and Ozone Precursors from 21 Sectors."
https://www.epa.gov/system/files/documents/2021 -10/source-apportionment-tsd-oct-2021 _0.pdf
U.S. EPA (2023). Technical Support Document Estimating the Benefit per Ton of Reducing
Directly-Emitted PM2.5, PM2.5 Precursors and Ozone Precursors from 21 Sectors. Research
Triangle Park, NC: U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, Health and Environmental Impact Division. Available at:
https://www.epa.eov/sYStem/files/documents/20 iource-apportionment-tsd-oct-2021 O.pdf
U.S. EPA. (2024d). Estimating PM2.5- and Ozone-Attributable Health Benefits: 2024 Update.
https://www.epa.gOv/system/files/documents/2024-06/estimating-pm2.5-and-ozone-attributable-
health-benefits-tsd-2024. pdf
Zanobetti, A., & Schwartz, J. (2008). Mortality displacement in the association of ozone with
mortality: an analysis of 48 cities in the United States. American Journal of Respiratory and
Critical Care Medicine, 177(2), 184-189. doi: 10.1 164/rccm.200706-8230C.
Zavala, M., Lei, W., Molina, M., & Molina, L. (2009). Modeled and observed ozone sensitivity
to mobile-source emissions in Mexico City. Atmospheric Chemistry and Physics, 9(1), 39-55.
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APPENDIX B
APPLICATION OF THE FRAMEWORK FOR EVALUATING DAMAGES AND
IMPACTS (FREDI) TO ASSESS THE DISTRIBUTION OF AVOIDED CLIMATE-
DRIVEN DAMAGES
In this Appendix, we provide further detail on the distribution of climate-driven impacts
avoided as a result of the methane (CH4) emission reductions from the final WEC, using the
Framework for Evaluating Damages and Impacts (FrEDI) (U.S. EPA, 2024).
B.l What is the Framework for Evaluating Damages and Impacts (FrEDI)?
The EPA developed FrEDI to better understand and communicate the detailed impacts
and risks from climate change in the United States. FrEDI is a reduced complexity model that
quantifies annual physical and economic impacts within contiguous U.S. (CONUS) borders
through the end of the 21st century resulting from future climate change under any user-defined
temperature trajectory. FrEDI draws upon over 30 existing peer-reviewed studies and climate
change impact models, including from the Climate Change Impacts and Risk Analysis (CIRA)
project76, to estimate the relationship between future degrees of warming and damages across
more than 20 impact sectors. The temperature-impact relationships are then used to rapidly
estimate climate change damages under any custom policy scenario. Recent FrEDI applications77
have advanced the collective understanding of how future impacts from climate change are
expected to be differentially experienced in different sectors across U.S. regions. The FrEDI
framework and its Technical Documentations (U.S. EPA, 2024) have been subject to a public
review and an independent external peer review78, following guidance in the EPA Peer-Review
76 EPA Climate Change Impacts and Risk Analysis (CIRA). https://www.epa.gov/cira
77 (1) Supplementary Material for the Regulatory Impact Analysis for the Supplemental Proposed Rulemaking,
"Standards of Performance for New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing
Sources: Oil and Natural Gas Sector Climate Review", Docket ID No. EPA-HQ-OAR-2021-0317 2022; (2) The
Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050. United
States Department of State and the United States Executive Office of the President, Washington DC. 2021; (3)
Climate Risk Exposure: An Assessment of the Federal Government's Financial Risks to Climate Change, White
Paper, Office of Management and budget, April 2022; (4) Hartin et al., Advancing the estimation of future
climate impacts within the United States. EGUspJiere, https://doi.org/10.5194/egusphere-2023-114.
78 Information on the peer-review is available at the EPA Science Inventory:
https://cfpnb.epa.gov/si/si public record Report.cfm?Lab=OAP&dirEntrvId=36Q384
B-l
-------
Handbook for Influential Scientific Information (ISI)79. FrEDI documentation and source code
are available at: https://www.epa.eov/cira/fredi.
B.2 Why are Distributional Climate Impacts Important to Consider?
The impacts of climate change occurring in a particular area or to a particular community
are determined by the physical climate stressors (e.g., heat, and precipitation) unique to that
location, the sensitivity to adverse effects, and the ability or capacity to adapt. This means that
understanding the risks of climate change to the U.S., and the damages avoided due to
greenhouse gas (GHG) emission reductions, is improved with detailed information regarding
where impacts may occur, to what sectors, and how populations may be differentially affected.
By leveraging the unique capabilities of FrEDI, EPA thereby offers additional context for this
specific rulemaking to help the public better understand the environmental impacts and potential
benefits from policies that reduce national GHG emissions, such as methane. The inclusion of
this analysis also directly aligns with general recommendations from EPA's Science Advisory
Board on a recent Agency rule80: "Given that exposure and vulnerability to climate risks vary,
the benefits of reducing emissions vary as well. The differential benefits of reduced greenhouse
gas emissions are not captured by the average social cost of carbon value and therefore
additional consideration of the distributional effects of reducing greenhouse gas emissions is
warranted. [...] The EPA should utilize ... the EPA CIRA program for information on the
disproportionate health impacts of climate change and consider greenhouse gas implications
from the proposed rule." By following these recommendations, the distributional application of
FrEDI presented in this RIA complements, but does not replace, existing global climate impact
and benefit assessments that use the social cost of greenhouse gases (SC-GHG). While global
impacts from the WEC are captured by the SC-GHG (in Chapter 6), FrEDI provides
complementary illustrative information about how reductions in long-term climate-driven
impacts may be differentially experienced within U.S. borders. Therefore, these results should
not be compared to global SC-GHG estimates.
79 EPA Science and Technology Policy Council Peer Review Handbook.
https://www.epa.gov/sites/defauit/files/2020-Q8/documents/epa peer review handbook 4th edition.pdf
80 EPA Science Advisory Board Letter to Administrator Regan, Final Science Advisory Board Regulatory Review
Report of Science Supporting EPA Decisions for the Proposed Rule: Control of Air Pollution from New Motor
Vehicles: Heavy-Duty Engine and Vehicle Standards (RIN 2060-AU41), EPA-SAB-23-001, December 2022.
B-2
-------
B.3 How is FrEDI Applied in the Final WEC RIA?
For this RIA, FrEDI is applied within a broader modeling workflow shown in Figure B-l
to analyze the distribution of avoided climate-driven impacts associated with final WEC CH4
emission changes. While this application of FrEDI may be considered the most detailed and
complete analysis of its kind, these estimates do not account for all damage categories, do not
include damages outside U.S. borders, and do not consider damages that occur due to
interactions between different sectors. Therefore, these estimates should be considered a
preliminary accounting of net avoided climate driven impacts relevant to U.S. interests.
B.3.1 Methodological Overview
Future global emission scenarios (Figure B-l, Input 1) are first passed to a climate
emulator (model information provided in Section B.3.5) to develop projections of global mean
temperature (Figure B-l, Output 1). These mean temperature changes (Figure B-l, Input 2) are
then passed to FrEDI81, which quantifies the climate-driven damages in 22 sectors within U.S.
borders that are associated with these temperature changes (Figure B-l, Output 2). In this
analysis, the two global emission scenarios include: 1) a global time series of emissions with no
additional mitigation (used to quantify projected 'reference' climate-driven damages) and 2) the
same global scenario, with each year starting in 2024 (first year of the WEC CH4 reductions)
adjusted for CH4 emission changes resulting from the final WEC. Details and results are
presented in the following sections.
81 https://github.com/USEPA/FrEDI/releases/tag/v4.1
B-3
-------
Figure B-l Schematic of Analysis Workflow from emissions to damages82
PUT1 iini in i
GLOBAL MEAN
TEMPERATURE
CHANGE J0gm*L
\A W © W
B.3.2 How are Avoided Climate Impacts Calculated?
This analysis presents the distribution of annual net avoided climate-driven impacts in the
year 2100 that are associated with WEC CH4 emission reductions. Reductions of CH4 emissions
are taken from RIA Table 5-8, which presents the total annual CH4 emission reductions from
abatement activities associated with the final WEC (hereafter called the WEC scenario). The
avoided climate-driven impacts in 2100 are calculated by comparing the distribution of long-
term climate-driven damages across multiple populations, regions, and sectors in the WEC
scenario compared to the reference scenario. The metric of annual net impacts captures both
positive and negative impacts from climate change and is consistent with the approach used in
the climate impacts literature, including the U.S. National Climate Assessment (USGCRP, 2018)
and United Nations' Intergovernmental Panel on Climate Change (IPCC) (IPCC, 2022)
assessments. Given the way that climate impacts accumulate over time, results here focus on the
year 2100 to capture the impacts from avoided long-term climate-driven changes83. Recognizing
that "climate change creates new risks and exacerbates existing vulnerabilities in communities
across the United States" (USGCRP, 2018), we use this approach to examine how the final WEC
may mitigate projected monetized climate impacts across different regions, sectors, and
populations.
82 Global emission scenarios (through 2100) are passed to the Finite amplitude Impulse Response (FaIR vl.6.4)
climate emulator to develop global temperature projections associated with global emission changes. Global
temperature changes are then passed to FrEDI, which applies sector and state-specific damage functions to project
the domestic annual climate-driven damages across sectors associated with the emissions-driven global mean
temperature changes.
83 FrEDI is capable to quantifying impacts for any year through 2100. The snapshot of avoided impacts here
represents the projected impacts in the year 2100 that are projected as a result of annual changes in emissions,
each year, from the first policy year through 2100. This is a different approach than a net present damage
analysis, which aggregates all impacts that result from a single emissions change in a particular year, through the
year 2300.
OUTPUT 2
Sectoral impacts
+ & +
+
+ m +g
+ many more-
^ Damages
B-4
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B. 3.3 Global Emissions Scenario
Global 'reference scenario' emissions of greenhouse gases (GHGs) (CO2, CH4, N2O,
HFCs, PFCs), primary aerosol components (black carbon, organic carbon), pollutant precursors
(CO, NOx, SOx, VOCs, NH3), and other halogenated species (CFCs, CH3CI, CH3Br, etc.)
through the year 2100 are from the 'current policy scenario' developed by Ou et al., 2021.
Projected temperature changes and climate-driven damages associated with these emissions
represent projected damages in the absence of additional emissions mitigation policies.
B. 3.4 Policy Emissions Scenario
To account for annual CH4 emission reductions from abatement activities associated with
the final WEC, the second 'policy scenario' is calculated by subtracting the expected rule-
specific reductions from the global reference emissions scenario. In this analysis, reductions of
CH4 are held constant between the final WEC emission year and the year 2100. Results are
minimally sensitive to this assumption. For all other compounds, emissions through the end of
the century are from the global reference scenario.
B.3.5 Climate Emulator & Projected Temperature Change
To convert global emissions to global temperature projections, we use the Finite
amplitude Impulse Response (FaIR vl.6.4) climate emulator (Smith et al., 2018a; Smith et al.,
2018b), which captures the relationships between GHG emissions, atmospheric GHG
concentrations, and global mean surface temperature. FaIR is a widely used reduced-complexity
Earth system model recommended by the National Academies, calibrated to and extensively
used within the Sixth Assessment Report (AR6) of the United Nations' IPCC, and applied in the
December 2023 Final Oil and Gas NSPS/EG Rulemaking, "Standards of Performance for New,
Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil and
Natural Gas Sector Climate Review" (U.S. EPA, 2023). The mean results presented in this
analysis are derived by running FaIR with an ensemble of 2237 sets of uncertain climate
B-5
-------
parameters84 that have been previously calibrated to the IPCC AR6 Working Group 1 assessment
(Smith, 2021).
B.4 Calculation of Avoided U.S. Climate-Driven Impacts
As described in the Technical Documentation (U.S. EPA, 2024), FrEDI uses projections
of global temperature and socioeconomic conditions (U.S. Gross Domestic Product [U.S. GDP]
and regional population85) with underlying damage functions86 to project economic damage end
points for 22 impact sectors, listed in Table B-l.
While these sectors represent a large range of impacts across the U.S. economy, FrEDI
does not include a comprehensive list of all impacts and only explores a subset of those that
directly occur within CONUS borders. Therefore, FrEDI only provides a partial estimate of
avoided climate impacts expected to accrue to U.S. citizens and their interests. In addition, not
all anticipated impacts are quantified within the represented sectors - for example the coastal
property analysis addresses direct flood damage to structures but omits indirect impacts such as
business interruptions that result from that damage. This approach also incorporates climate
uncertainty from the FaIR model but does not fully account for uncertainty in the underlying
temperature-impact relationships for each sector. For a more detailed accounting of uncertainties,
please see the FrEDI Technical Documentation (U.S. EPA, 2024). Lastly, FrEDI also does not
account for impacts of the final WEC resulting from factors outside of the direct impact of CH4
emission reductions on climate change, such as direct air quality improvements from reductions
in co-emissions of air pollutants.
84 Uncertainties in climate model parameters considered in FaIR, include but are not limited to the sensitivity of
climate to increases in atmospheric CO2 concentrations, forcing from aerosol components, forcing from black
carbon on snow, and carbon cycle parameters.
85 Population scenarios are based on UN Median Population projection (United Nations, Department of Economic
and Social Affairs, Population Division, 2015. World Population Prospects: The 2015 Revision, Key Findings,
and Advance Tables. No. Working Paper No. ESA/P/WP.241) and EPA's ICLUSv2 model (Bierwagen, et al.,
National housing and impervious surface scenarios for integrated climate impact assessments. Proc. Natl. Acad.
Sci. 107, 2010; U.S. EPA, 2017), and GDP from the EPPA version 6 model (Chen, et al., Long-term economic
modeling for climate change assessment. Economic Modelling, 52 (Part B): 867-883, 2015,
http://www.sciencedirect.com/science/article/pii/S0264999315003193)).
86 A temperature binning approach is used to develop relationships between climate-driven changes in CONUS
surface temperature or sea level rise (calculated from temperature), socioeconomic conditions (e.g., U.S. Gross
Domestic Product [GDP] and state population), and the resulting physical and economic damages across 22
sectors and 48 states and the District of Columbia. These temperature-impact relationships are synthesized from
over 30 underlying peer-reviewed studies on climate change impact and form a key basis of FrEDI's calculations.
B-6
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Table B-l Current FrEDI sectors, including aggregate category group, default
adaptation assumptions, and descriptions. Adapted from the FrEDI
Technical Documentation
Sector
Aggregate
Category
Default Adaptation or
Variant Option
Impact Description
Agriculture
Agriculture
With CO2 fertilization
Revenue lost from changes in wheat, cotton,
soybean, and maize crop yields
Coastal Property
Infrastructure
Reactive Adaptation
Costs related to armoring, elevation,
nourishment, structure repair, and
abandonment (including storm surge
impacts)
Electricity Demand and
Supply
Electricity
No Additional
Adaptation*
Changes in power sector costs for heating
and cooling (demand) and required capacity
expansion (supply)
Electricity
Transmission and
Electricity
Reactive Adaptation
Repair of replacement of transmission &
distribution infrastructure
Distribution
T emperature -Related
Health
No Additional
Damages from the net of heat- and cold-
Mortality^
Adaptation*
related mortality
Transportation Impacts
from High Tide
Flooding
Infrastructure
Reasonably
Anticipated Adaptation
Damages from coastal flooding related
traffic delays, rerouting, infrastructure
improvements, and other transport impacts.
Inland Flooding
Infrastructure
No Additional
Adaptation*
Residential property damages from riverine
flooding
Labor
Labor
No Additional
Adaptation*
Damages from work hours lost and lost
wages in high-risk industries due to
temperature
Marine Fisheries
Ecosystems +
No Additional
Lost value of marine fisheries landings from
Recreation
Adaptation*
changes in thermally available habitat for
commercial fish species
Climate-Driven
Changes in Air Quality
Health
2011 precursor
Emissions
Damages from climate-driven changes in
temperature and weather on ozone and fine
particulate matter exposure and attributable
mortality
Crime
Health
No Additional
Adaptation*
Damages from the change in the number of
Property and Violent crimes and crime
valuation
Rail
Infrastructure
Reactive Adaptation
Infrastructure repair and delay costs
associated with temperature-induced track
buckling
Roads
Infrastructure
Reactive Adaptation
Cost of road repair, user costs (vehicle
damage), and road delays due to changes in
road surface quality
Southwest Dust
Health
No Additional
Adaptation*
Damages from mortality and hospitalization
costs from changes in fine and coarse dust
particle exposure
Suicided
Health
No Additional
Adaptation*
Damages from climate-driven changes in
temperature and weather on suicide
Wind Damage from
Tropical Storms
Infrastructure
No Additional
Adaptation*
Cost of property damage from hurricane
winds to coastal properties
Urban Drainage
Infrastructure
Proactive Adaptation
Costs of upgrading urban stormwater
infrastructure
Water Quality
Ecosystems +
Recreation
No Additional
Adaptation*
Willingness to pay to avoid water quality
changes for recreation
B-7
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Wildfire
Health
No Additional
Adaptation*
Damages from mortality and morbidity
from wildfire-driven air pollution exposure
and response cost for fire suppression
Winter Recreation
Ecosystems +
Recreation
Adaptation
Revenue lost from suppliers of alpine,
cross-country skiing, and snowmobiling
Valley Fever
Health
No Additional
Adaptation*
Damages from mortality, morbidity, and
lost wages
Vibriosis
Health
No Additional
Adaptation*
Damages from hospitalization costs, lost
wages, and mortality from Vibriosis
*'No additional adaptation' classification is sector specific and does not imply that there is no adaptation in the
underlying study. Rather, adaptive measures and strategies are included to the extent that these actions were taken in
recent history in response to climate hazards. However, no alternative adaptation options are modeled in FrEDI for
these sectors. For more information, please see the FrEDI technical documentation (U.S. EPA, 2024). * As described
in the 2024 FrEDI Technical Documentation, default temperature-related mortality damages have been adjusted to
account for the fraction of heat related deaths that are attributable to suicide, which are explicitly represented by the
'suicide' sector.
B.5 Results: Distributional Changes in Avoided U.S. Climate-Driven Impacts
Results in this section represent the expected reduction in annual climate-driven impacts
in 2100, or the economic impacts avoided, when implementing the WEC CH4 emission
reductions (e.g., avoided impacts = reference scenario damages - policy scenario damages)87.
Considering the 22 sectors included in FrEDI, net avoided climate-driven damages from the
WEC at the national level are projected to occur across all sectors and regions within the
CONUS. The majority of these improvements are projected to occur within sectors that impact
human health, including reductions in mortality from avoided warming, mortality from climate-
driven changes in air pollution (ozone and ambient fine particulate matter)88, suicide incidence,
exposure to wildfire smoke, Southwest dust, Vibriosis, and Valley fever, as well as reduced
impacts to labor hours in high-risk industries and reductions in infrastructure-related damages
such as avoided transportation impacts from high-tide flooding, reduced property damage from
hurricane winds, and avoided damages to roads and rail.
At the regional level, Figure B-2 provides a more detailed breakdown, by sector, of how
changes in avoided climate-driven sectoral impacts per capita are expected to vary across seven
regions89 within the CONUS by 2100. While all regions are expected to see reductions in net
87 This metric differs from the net present benefits that are presented in RIA Chapter 6, which account for the
discounted sum of climate-driven damages from the each WEC reduction year through 2300. Changes in annual
impacts from FrEDI focus on 2100 to capture long-term climate-driven changes.
88 The air quality impacts described here are a result of changes in concentrations of ozone and fine particulate
matter (PM2 5) that are the result of climate-driven changes in meteorology, atmospheric chemistry, and other
biogeochemical factors. This is in contrast and in addition to the direct air quality changes resulting from changes
in pollutant emissions from smokestacks, as discussed in other sections of this RIA.
89 Corresponding to regions of the 4th U.S. National Climate Assessment.
B-8
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impacts under the final WEC scenario (column 1), which will increase overtime (column 2), the
right panel of Figure B-2 also lists the five sectors (of the 22 analyzed) that will accrue the
largest annual impact reductions per capita in each region. For example, while the largest
improvements in all regions are projected to be from reduced mortality from avoided
temperature changes, improvements related to climate-driven changes in air quality mortality
(2nd largest sector at the national level) are expected to be most pronounced in the Southwest,
Southeast, Northeast, and Northwest regions. In addition, avoided damages to transportation
infrastructure (e.g., rail and roads) and agriculture are relatively more important in the Midwest
and Northern Plains, while reduction in transportation impacts from high-tide flooding and
avoided coastal property flood and wind damage are relatively more important in coastal regions.
B-9
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Figure B-2 Relative avoided per capita climate driven impacts by sector and US region
in 2100.90
impacts Per capita Relative Avoided Climate-Driven Impacts in Analyzed Sectors, Across 7 U.S. Regions
2100
2030-2100
Trend
Southeast
Northeast
Southern
Plains
Northwest
Southwest
Northern
Plains
Midwest
r
p «
r
gat
r
<&
cfi>
¦«?'
/A\
/A\
m /a\
...+17 more
Temperature-Related
Mortality
Transportation Impacts ZttX
from High Tide Flooding /ll\
C±l
Suicide
Climate-Driven Air
Quality Mortality
t§>
Rail
Coastal Properties
briol
!.'Southwest Dust ^ Agficultufi,
Figure B-3 provides a more detailed breakdown of the distribution of avoided climate-
driven impacts per capita across each state under the final WEC. Overall, Virginia is projected to
have the largest avoided impacts per capita, with Massachusetts, and North Carolina projected to
experience the second and third largest avoided per capita impacts. For illustrative purposes,
Figure B-3 includes a call-out to the state in each region that is projected to experience the
largest avoided damages per capita, as well as the top five sectors in those states that are
projected to have the largest avoided impacts. Combined, Figures B-2 and B-3 show that while
the Southeast region is projected to experience the largest avoided damages, the distribution of
these improvements varies across states within this region. These figures also highlight the
regional differences in avoided impacts across sectors. For example, avoided impacts from
90 Left bars) relative per capita improvements in each region in 2100 as well as the per capita improvements in the
years 2030, 2050, 2070, 2090, and 2100. Right green tiles and icons) avoided climate-driven impacts experienced
in the top 5 sectors within FrEDI in each region, in order of decreasing per capita impact changes (from left to
right). Green shading illustrates the relative changes in each sector, normalized to the temperature-related
mortality impacts in that region. Results are not a comprehensive accounting of all the ways climate-change is
projected to impact the American public.
B-10
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climate-driven changes in wildfire and dust will primarily impact populations living in the
western U.S., and reductions in tropical wind damage and transportation impacts from high-tide
flooding will largely occurring in states along the eastern U.S. coastline.
Figure B-3 State share of annual average avoided U.S. climate-driven impacts in 210091
Northern Plains:
Wyoming
Northwest:
Idaho
f ¦ 6 •* C: /a\
Oklahoma
Midwest:
Missouri
Northeast:
Massachusetts
Southeast:
Virginia
Lastly, understanding the comparative risks to different populations living in different
areas is also critical for developing effective and equitable strategies for responding to climate
change. Analysis from a recent independently peer-reviewed EPA report on Climate Change and
Social Vulnerability in the United States (U.S. EPA, 2021) (hereafter referred to as the SV
Report), provides a framework within FrEDI for better understanding the degree to which
socially vulnerable populations are disproportionately exposed to the impacts from climate
change in six impact categories.
As described in the SV Report, differential climate change risks are a function of
exposure to where physical climate change impacts are projected to occur and vulnerability, in
terms of an individual's capacity to prepare for, cope with, and recover from these impacts. This
91 Map insert shows the relative avoided climate-driven damages per capita in each CONUS state in the year 2100.
For each NCA region, the state with the largest avoided damages per capita is called-out, with icons indicating the
top five sectors in FrEDI that are projected to experience the largest avoided damages in those states. Icons are
the same as in Figure B-2. Results are not a comprehensive accounting of all the ways climate-change is projected
to impact the American public.
B-ll
-------
framework uses data on where populations live as an indicator of exposure and for vulnerability,
considers four categories for which there is evidence of differential vulnerability (Table B-2),
including low income (individuals living in households with income at or below 200% of the
poverty level), ethnicity and race (individuals identifying as BIPOC92), educational attainment
(individuals ages 25 and older with less than a high school diploma or equivalent), and age
(individuals ages 65 and older). These categories are consistent with population groups of
concern highlighted in EPA's Technical EJ Guidance (U.S. EPA, 2016).
Table B-2 Four socially vulnerable and reference groups considered here
Categories
Group Name
Description
Reference Group
Income
Low income
Individuals living in households with
income that is 200% of the poverty
level or lower
Individuals living in households with
income greater than 200% of the
poverty level.
Age
65 and Older
Ages 65 and older
Under age 65
Race and
BIPOC
Individuals identifying as one or
Individuals identifying as White and/or
ethnicity
more of the following: Black or
African American, American Indian
or Alaska Native, Asian, Native
Hawaiian or Other Pacific Islander,
and/or Hispanic or Latino
non-Hispanic
Education
No High School
individuals aged 25 and older with
Individuals aged 25 or older with
Diploma
less than a high school diploma or
equivalent
educational attainment of a high school
diploma (or equivalent) or higher.
As described in the FrEDI Technical Documentation (Appendix E) (U.S. EPA, 2024),
differential impacts in each group are calculated in FrEDI at the Census tract level as a function
of current population demographic patterns (i.e., percent of each group living in each census
tract), projections of CONUS population (from ICLUS, U.S. EPA, 2017), and projections of
where climate-driven impacts are projected to occur (i.e., using FrEDI temperature-impact
relationships) at the Census tract level. The relative percent of each socially vulnerable group in
each Census tract are from the 2014-2018 U.S. Census American Community Survey dataset
92 This analysis uses the term BIPOC to refer to individuals identifying as Black or African American; American
Indian or Alaska Native; Asian; Native Hawaiian or Other Pacific Islander; and/or Hispanic or Latino. It is
acknowledged that there is no 'one size fits all' language when it comes to talking about race and ethnicity, and
that no one term is going to be embraced by every member of a population or community. The use of BIPOC is
intended to reinforce the fact that not all people of color have the same experience and cultural identity. This
analysis therefore also includes results for individual racial and ethnic groups.
B-12
-------
(U.S. Census) and are held constant overtime because robust and long-term projections of local
changes in demographics are not readily available.
Figure B-4 shows how reductions in annual climate-driven impacts within the six impact
categories93, under the final WEC, are expected to be distributed across different populations,
according to age, income, education level, and race and ethnicity. Those populations with greater
than 100% differential improvements (right of the dashed lines) are projected to experience
relatively larger reductions in long-term climate-driven impacts due to the WEC, compared to
their reference populations (Table B-2). These are the same populations that are projected to
experience relatively larger damages under the reference scenario. Those socially vulnerable
groups with changes of less than 100% (left of the dashed lines) are still expected to see
improvements but are projected to experience relatively smaller impact reductions than their
reference populations. For example, Figure B-4 shows that BIPOC individuals age 65 and older
are 13% more likely to see larger reductions in air quality attributable mortality relative to their
white and/or non-Hispanic reference population. In addition, those in the low-income group are
more likely (5%) to see larger reductions in lost labor hours than then those outside the low-
income group. As most bars are to the right of the dashed lines, Figure B-4 shows that nearly all
socially vulnerable groups are projected to experience larger reductions in climate change
impacts, compared to their reference populations.
93 The six impact categories include premature mortality (ages 65+) and new childhood (ages 0-17) asthma cases
attributable climate-driven changes in air quality (ambient fine particulate matter), temperature mortality, labor
hours lost due to high-temperature days, people impacted by coastal property inundation due to sea level rise, and
transportation impacts from high tide flooding.
B-13
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Figure B-4 Differential reductions in per capita climate-driven impacts in 2090 across
socially vulnerable groups, normalized to the changes in their reference
populations.94
Climate-Driven Air Quality -
Age 65+ Mortality
Over age 65
No High-School
Diploma
Low Income
BIPOC
Over age 65
No High-School
Diploma
Low Income
BIPOC
40
Lost Labor
Hours
Climate-Driven Air Quality -
Childhood Asthma
II
Temperature-Related
Mortality
Coastal Flooding
Property Damage
Transportation Impacts from
High Tide Flooding
80
120 0
40 80
Percent (%)
120 0
40
80
120
Impacts to the BIPOC individuals in Figure B-4 can also be distributed across different
races and ethnicities as shown in Figure B-595. These are normalized to the per capita changes
experienced by the national impacted population instead of a reference population. Therefore,
bars to the right on the dashed lines in Figure B-5 indicate where specific groups of individuals
will experience greater reductions in climate driven impacts compared to the national average
and those to the left will experience smaller impact reductions than the national average.
94 Dashed gray lines represent 100% of the annual avoided impacts that are experienced by the reference population
for that sector (Table B-2). Bars greater than 100% indicate that a group is projected to experience more impact
reductions from WEC reductions than the reference population. Bars less than 100% indicate that a group is
projected to experience fewer impact reductions than the reference population. No bars indicate there are no
impacts considered in that group. This is not a complete accounting of all climate impacts to the U.S. Coastal
property damage and transportation impacts from high tide flooding are included considering no additional
adaptation.
95 Impact results as a function of racial and ethnic group were also presented in EPA's SV Report.
B-14
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Figure B-5 Per capita reductions in climate-driven impacts for six sectors in 2090,
distributed by race and ethnicity.96
White, non-Hispanic
Two or more races
Pacific Islander
Other Race
Hispanic or Latino
Black or African American
Asian
American Indian
or Alaska Native
White, non-Hispanic
Two or more races
Pacific Islander
Other Race
Hispanic or Latino
Black or African American
Asian
American Indian
or Alaska Native
When considering the six impact categories analyzed here, Figure B-5 shows that all
groups are projected to see fewer climate change impacts under the WEC (all bars are greater
than zero), but that some specific populations may see more benefits than others. For example,
by 2100, Black or African Americans over the age of 65 are 47% more likely to see more
reductions in climate-driven changes in air quality mortality than the national average, which is
largely because of regional differences in where these populations currently live and where
future climate-driven air quality changes are projected to occur. As another example, Asian
Americans are 44% more likely to see larger reductions in transportation impacts from high tide
flooding than the national average. Typically, the populations projected to be impacted the most
by climate change under the reference scenario are the same groups that are projected to
experience the greatest impact reductions under the WEC.
96 Results for each sector are normalized to the average per capita impact avoided by the total impacted population
in that sector. See Figure 4 caption for more details. This analysis does not consider effects on populations living
in Hawai'i, Alaska, or U.S. territories but does use demographic data from the U.S. Census which includes
individuals living in the CONUS who identify as "American Indian or Alaska Native" and "Native Hawaiian or
Other Pacific Islander." This is not a complete accounting of all climate impacts to the U.S. Coastal property
damage and transportation impacts from high tide flooding are included considering no additional adaptation.
Climate-Driven Air Quality -
Age 65+ Mortality
m
i
Lost Labor
Hours
Climate-Driven Air Quality -
Childhood Asthma
¦
Temperature-Related
Mortality
I
i
4
:
!
Coastal Flooding
Property Damage
Transportation Impacts from
High Tide Flooding
rr
!
0 50 100 150
B-15
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There are many impacts of climate change and additional dimensions of vulnerability that
are not incorporated into this analysis, and therefore these results only reveal a portion of the
potential unequal risks to socially vulnerable populations. In addition, this analysis does not
consider how changes in future demographic patterns in the U.S. could affect risks to these
populations, nor how climate change may affect socially vulnerable populations living outside
the CONUS.
Overall, the FrEDI analysis presented here is intended to produce estimates of annual net
climate-driven impacts within U.S. borders using the best available data and methods. FrEDI was
developed using a transparent process, peer-reviewed methodologies, and is designed as a
flexible framework that is continually refined to reflect the current state of climate change impact
science. While FrEDI does not provide a complete and comprehensive accounting of all potential
climate change impacts relevant to U.S. interests and is subject to uncertainties (such as future
levels of adaptation), this analysis provides the most detailed and complete illustration to date of
the distribution of climate change impacts within U.S. borders.
B.6 References
IPCC: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working
Group 11 to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H -
O. Portner, D C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegria, M. Craig, S.
Langsdorf, S. Loschke, V. M oiler, A. Okem, B. Rama (eds.)]., Cambridge University Press.
Cambridge University Press, Cambridge, UK and New York, NY, US A, 3056,
10.1017/9781009325844, 2022.
Ou, Y., Iyer, G., Clarke, L., Edmonds, J., Fawcett, A. A., Hultman, N., McFarland, J. R.,
Binsted, M., Cui, R., Fvson, C., Geiges, A., Gonzales-Zuniga, S., Gidden, M. J., Hohne, N.,
Jeffery, L., Kuramochi, T., Lewis, J., Meinshausen, M., Nicholls, Z., Patel, P., Ragnauth, S.,
Rogelj, J., Waldhoff, S., Yu, S., and McJeon, H.: Can updated climate pledges limit warming
well below 2°C?, Science, 374, 693-695, 10.1 l26/science.abl8976, 2021.
Smith, C.: FalR vl .6.2 calibrated and constrained parameter set (vl.0) [dataset], 2021.
Smith, C. J., Forster, P. M., Allen, M., Leach, N., Millar, R. J., Passerello, G. A., and Regayre, L.
A.: FAIR vl .3: a simple emissions-based impulse response and carbon cycle model, Geosci.
Model Dev., I I, 2273-2297, 10.5 194/gmd-1 1-2273-2018, 2018a.
Smith, C. J., Millar, R., Nicholls, Z., Allen, M., Forster, P., Leach, N., Passerello, G., Regayre,
L.: FAIR - Finite Amplitude Impulse Response Model (multi-forcing version),
10.528 l/zenodo. 1247898, 2018b.
B-16
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U.S. Census: American Community Survey 2014-2018 [https://www.census.gov/programs-
surveys/acs/data.html]
U.S. Environmental Protection Agency: Technical Guidance for Assessing Environmental
Justice in Regulatory Analysis, 2016.
U.S. Environmental Protection Agency: Updates to The Demographic and Spatial Allocation
Models to Produce Integrated Climate And Land Use Scenarios (1CLUS) (Version 2),
Washington, DC, EPA/600/R-16/366F, 2017.
U.S. Environmental Protection Agency: Climate Change and Social Vulnerability in the United
States: A Focus on Six Impacts, Washington, DC, EPA/430/R-21 /003, 2021.
U.S. Environmental Protection Agency (EPA): Supplementary Material for the Regulatory
Impact Analysis for the Supplemental Proposed Rulemaking, "Standards of Performance for
New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review", 2023.
U.S. Environmental Protection Agency: Technical Documentation for the Framework for
Evaluating Damages and Impacts. U.S. Environmental Protection Agency, EPA. 430-R-24-001.
www. epa. go v/ci ra/Fr E DI, 2024.
USGCRP: Impacts, Risks, and Adaptation in the United States: Fourth National Climate
Assessment, Volume 11 Washington, DC, USA, 1515, 10.7930/NCA4.2018., 2018.
B-17
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APPENDIX C
ADDITIONAL INFORMATION ON MARGINAL ABATEMENT COST (MAC)
MODELING FOR ANALYSIS OF WASTE EMISSIONS CHARGE
C.l MAC Model Overview
Marginal abatement cost (MAC) model is a bottom-up, engineering cost analysis using the
most current information on mitigation options available to the United States oil and gas
industry. The modeling approach and many of the key assumptions are consistent with the
methodology described in the EPA's Global Non-C02 Greenhouse Gas Emission Projections &
Mitigation, 2015-2050 report. The MAC curves were constructed for each region and sector by
estimating the carbon price at which the present-value benefits and costs for each mitigation
option equilibrate. The methodology produces a stepwise curve, where each point reflects the
average price and reduction potential if a mitigation technology were applied across the sector.
In conjunction with the projected GHG emissions for from facilities subject to the WEC, we
express the resulting annual reductions in metric tons of methane (tCH4).
C.2 MAC Model Description
The MAC model considers a suite of mitigation technologies applicable to facilities
subject to the WEC. Each mitigation technology is characterized with respect to variables
related to technical effectiveness in reducing emissions and cost for the purpose of calculating a
breakeven price. The MACC is constructed by aggregating mitigation potential from all
technologies as applied to the emissions baseline.
C.3 Mitigation Technology Emissions Reduction Characteristics
The mitigation potential associated with each mitigation is based on a number of factors
that include technical applicability, market penetration, and reduction efficiency. The technical
effectiveness of each mitigation option is calculated as shown in Table C-l. Technical
effectiveness is the percent mitigation potential of a specific mitigation technology or control
option that considers technical appropriateness of the option, the market penetration or uptake of
the mitigation measure within the oil and gas industry combined with the emissions reduction
efficiency of the mitigation technology when implemented/installed.
C-l
-------
Table C-l Calculation of Emission Reductions for a Mitigation Option
Technical
Market
Reduction
Technical
Applicability
X Share3
X Efficiency
= Effectiveness
(%)
(%)
(%)
(%)
Technical
Baseline
Emissions
Effectiveness
X Emissions
= Reductions
(%)
(tCH4)
(tCH4)
Percentage of
Percentage of
Percentage of
Percentage of
Emission
Unit
total baseline
technically
technically
baseline
stream to
emission
emissions
applicable
achievable
emissions that
which the
reductions.
from a
baseline
emission
can be reduced
option is
particular
emissions to
mitigation
at the national
applied.
emission
which a
for an option
or regional
source to
given option
after it is
level by a
which a given
is applied;
applied to a
given option.
option can be
avoids
given
potentially
double
emission
applied.
counting
among
competing
options.
stream.
a Implied market shares for noncompeting mitigation options (i.e., only one option is applicable for an emission streams) sums
to 100%.
where:
TA = technical applicability (%)
MS = market share (%)
RE = reduction efficiency (%)
TE = technical efficiency (%)
BE = baseline emissions (tCH4)
Technical applicability accounts for the portion of emissions from a facility or region that
a mitigation option could feasibly reduce based on its application. For example, if an option
applies only to the underground portion of emissions from coal mining, then the technical
applicability for the option would be the percentage of emissions from underground mining
relative to total emissions from coal mining.
The implied market share of an option is a mathematical adjustment for other qualitative
factors that may influence the effectiveness or adoption of a mitigation option. EPA does not
imply that effectiveness and adoption are interchangeable. We used market shares for each
mitigation option within every sector. The market shares, determined by various sector-specific
C-2
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methods, must sum to one for each sector and were assumed constant over time. This assumption
avoids cumulative reductions of greater than 100% across options.
When nonoverlapping options are applied, they affect 100% of baseline emissions from
the relevant source. Examples of two nonoverlapping options in the natural gas system are
replacement of high-bleed pneumatic devices and leak detection and repair of compressors in the
transmission segment. These options were applied independently to different parts of the sector
and do not compete for the same emission stream.
The reduction efficiency of a mitigation option is the percentage reduction achieved with
adoption. The reduction efficiency was applied to the relevant baseline emissions as defined by
technical applicability and adoption effectiveness. Most abatement options, when adopted,
reduce an emission stream less than 100%. If multiple options are available for the same
component, the total reduction for that component is less than 100%.
Once the technical effectiveness of an option was calculated as described above, this
percentage was multiplied by the baseline emissions for each sector and region to calculate the
absolute amount of emissions reduced by employing the option. The absolute amount of baseline
emissions reduced by an option in a given year is expressed in metric tons of methane.
If the options were assumed to be technically feasible in a given region, they were
assumed to be implemented systematically for all applicable components in the industry.
Furthermore, once options are adopted, they were assumed to remain in place for the duration of
the analysis, and an option's parameters do not change over its lifetime.
C.4 Mitigation Technology Economic Characteristics
Each abatement option is characterized in terms of its costs and benefits per abated unit
of gas (tons of emitted CH4). The carbon price at which an option's benefits equal the costs is
referred to as the option's break-even price expressed in $/tCH4 reduced.
For each mitigation option, the carbon price (P) at which that option becomes
economically viable was calculated using the equation below (i.e., where the present value of the
benefits of the option equals the present value of the costs of implementing the option). A
present value analysis of each option was used to determine break-even mitigation costs. Break-
even calculations are independent of the year the mitigation option is implemented but are
C-3
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contingent on the life expectancy of the option. The net present value calculation solves for
break-even price P by equating the present value of the benefits with the present value of the
costs of the mitigation option. More specifically,
i
I
t=i
(1 - TR)(P ¦ER + R) + TB
(1 +DR)1
y\(l-TR)RC]
1 I
= CC +
Z_i| (1 + DR)f
t=lL
T r(l - TR)RC]
(1 + DRY
I
t=l
v
Net Present Benefits
1
t=l
(1 -TR)(P-ER + R) + TB
(1 +DR)1
(D.l)
y
Net Present Costs
where:
P = the break-even price of the option ($/tCH4)
ER = the emission reduction achieved by the technology (tCH4)
R = the revenue generated from energy production (scaled based energy prices)
T = the option lifetime (years)
DR = the discount rate (5%)
CC = the one-time capital cost of the option ($)
RC = the recurring (O&M) cost of the option (portions of which may be scaled based on regional labor and
materials costs) ($/year)
TR = the tax rate (0%)
Assuming that the emission reduction ER, the recurring costs RC, and the revenue R do
not change on an annual basis, then we can rearrange this equation to solve for the break-even
price P of the option for a given year:
CC RC R CC TR
P=Z\ TP^ rP y r 1 + ER ~ ER ~ ER ¦ T ' (1 - TR) (D.2)
(1-77?) ER Lt=i(1+DR)t
Costs include capital or one-time costs and O&M or recurring costs. Most of the
agricultural sector options, such as changes in management practices, do not have applicable
capital costs, with the exception of anaerobic digesters for manure management.
Benefits or revenues from employing an abatement option can include (1) the intrinsic
value of the recovered gas (e.g., the value of CH4 either as natural gas or as electricity/heat),
C-4
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(2) non-GHG benefits of abatement options (e.g., non-energy savings for labor or equipment). In
most cases, the abatement of CH4 has two price signals: one price based on CH4's value as
energy (because natural gas is between 90% and 98% CH4) and one price based on CH4's value
as a GHG. All cost and benefit values are expressed in constant-year 2019 dollars. The analysis
applied a 5% discount rate and assumed a 0% tax rate. Table C-2 lists the basic financial
assumptions used in the analysis.
Table C-2 Financial Assumptions in Break-Even Price Calculation for Mitigation
Options
Economic Parameter
Assumption
Discount rate
5%
Tax rate
0%
Constant-year dollars
2019$
Finally, the MACC model also includes assumptions regarding the quantitative impacts
of learning over time, with a learning rate of 15%. The learning rate defines the rate of decrease
in the implementation costs overtime as industry gains more experience. The cost reduction
curve initially drives costs down rapidly in the early years but decreases its year-on-year
reductions in later years as potential cost reduction opportunities are exhausted. The results of
learning overtime reduce the costs of implement the mitigation measures while also improving
the reduction efficiency of mitigation measures over time. This element of the MACC model
means costs of mitigation in future years will be lower compared to the present. As a result,
some mitigation measures not cost-effective in 2024 (S/tCFU <= WEC S/tCFU) may be costs-
effective in later years.
C.5 WEC Facility MAC Curves Construction
The mitigation option analysis throughout this report was conducted using a common
methodology and framework. MAC curves were constructed for each region and sector in the
United States by estimating the "break-even" price at which the present-value benefits and costs
for each mitigation option equilibrate. The methodology produces a curve where each point
C-5
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reflects the average price and reduction potential if a mitigation technology were systematically
adopted by all similar facilities across the oil or gas segment. When combined with the projected
baseline emissions for the specific facility type, results are expressed in absolute annual
reductions (tCH4) at specific average mitigation costs or prices. For example, in the illustrative
MAC shown in Figure C-l below shows the quantity of mitigation technical achievable at prices
below the WEC rate ($/tCH4). The quantity of mitigation (Qmacc) expected from WEC
facilities in the 2025 is -460 ktCH4, where the MAC curve crosses the WEC.
The Q MACC represents the full technically available mitigation potential at mitigations
costs below the WEC charge. In order to account for practical limitations in the speed of
deploying cost-effective mitigation to oil and gas operations, the analysis assumed a three-year
phase-in period for reductions over 2024 to 2026. The phase-in parameter constrains the
mitigation potential in 2024 and 2025 to 33% and 67% of total mitigation potential to simulate
the assumption that it will take facilities several years to fully implement mitigation measures.
Depending upon a variety of factors, potential technology deployment speed may be faster or
slower than this assumption. Because many of the mitigation technologies estimated in the
MACC model correspond to mitigation technologies considered as part of the Oil and Gas
NSPS/EG rulemaking process, oil and gas operators have been aware of potential requirements
since 2021. However, widespread deployment of mitigation technologies may be affected by
supply chain, labor, or other constraints that could prevent full utilization in the short term.
C-6
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Figure C-l Illustrative MAC Curve for Facilities with Emissions Subject to the WEC in
the year 2025
Mitigation Level (ktCH4)
C.6 Mitigation Options Modeled
This mitigation analysis utilized information on mitigation measures cost and
performance gathered as part of technology analysis process from the Oil and Natural Gas
NSPS/EG rulemaking process. Data on technologies was derived from both the analysis related
to the 2021 proposal and the 2022 supplemental proposal. In particular, updated technology cost
and performance data was drawn from spreadsheets published in the docket underlying the
NSPS/EG Technical Support Documents (EPA, 2022 and 2021). Mitigation option information
address methane emissions from the following emissions sources:
Table C-3 lists the mitigation technologies included in the MACC analysis for the WEC
rule.
C-l
-------
Table C-3 Mitigation Technologies Included in WEC Analysis by Source Category
Emissions Source
Mitigation Options
Pneumatic controllers
• Replace Continuous High-Bleed Controllers with
Low-Bleed Controllers
• Electric Powered Controllers (where a grid
connection, on-site power exists)
• Solar Powered Electronic Controllers
Fugitive emissions from well sites
• Fugitive Emissions Leak Detection and Repair at
Well Sites
Fugitive emissions from natural gas processing plants
• Fugitive Emissions Leak Detection and Repair at
NG Processing Plants
Fugitive emissions from compressor stations
• Fugitive Emissions Leak Detection and Repair at
compressor stations
Fugitive emissions from offshore facilities
• Fugitive Emissions Leak Detection and Repair at
offshore facilities
Pneumatic pumps
• Install a New Combustion Device or Process
• Route Emissions to an Existing Combustion Device
or Process
• Replace a gas-driven pump with an electric pump -
Processing
Liquids Unloading
• Non-Venting Liquids Unloading Techniques
Reciprocating compressors
• Replacement of rod packing every 3 years
• Fugitive Emissions Leak Detection and Repair
• Routing of Emission Through a Closed Vent
System Under Negative Pressure to a Combustion
Device
Centrifugal compressors
• Converting Wet Seals to Dry Seals System
• Routing emissions to a New Control Device
• Routing emissions to an Enclosed Combustion
Device or Process.
The balance of this section briefly defines the sources and mitigation technologies
considered for the WEC analysis. Much of the definitions are terms are borrowed directly from
the EPA 2021 Background Technical Support Document for the NSPS/EG analysis of the Oil
and Natural Gas Sectors (EPA,2021).
C-8
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C.6.1 Pneumatic Controllers
Pneumatic controllers are devices used to regulate a variety of physical parameters, or
process variables, using air or gas pressure to control the operation of mechanical devices, such
as valves. The valve control process conditions such as levels, temperatures and pressures. When
a pneumatic controller identifies the need to alter a process condition, it will open or close a
control valve. In many situations across all segments of the oil and natural gas industry,
pneumatic controllers make use of the available high-pressure natural gas to operate or control
the valve. In these "gas-driven" pneumatic controllers, natural gas may be released with every
valve movement and/or continuously from the valve control.
Pneumatic controllers can be categorized based on the emissions pattern of the controller.
Some controllers are designed to have the supply-gas provide the required pressure to power the
end-device, and the excess amount of gas is emitted. The emissions of this excess gas are
referred to as "bleed," and this bleed occurs continuously. Also referred to as "continuous bleed"
pneumatic controllers, these controllers can be further categorized based on the bleed volume.
Controllers with bleed rate less than or equal to 6 standard cubic feet per hour (scfh) are referred
to as "low bleed," and those with a higher bleed rate are referred to as "high bleed." Another type
of controller is designed to release gas only when the process parameter needs to be adjusted by
opening or closing the valve, and there is no vent or bleed of gas to the atmosphere when the
valve is stationary. These types of controllers are referred to as "intermittent vent" pneumatic
controllers. EPA (2021) cites that while emissions from individual pneumatic controllers are
small, there are an estimated 1.7 million controllers utilized across oil and gas production
facilities and natural gas transmission and storage facilities. Combined emissions from all these
pneumatic controllers represents approximately 50% of the baseline emissions from WEC
applicable facilities.
Emissions from natural gas-powered pneumatic controllers occur as a function of their
design. Continuous bleed controllers using natural gas as the power source emit a portion of that
gas at a constant rate. Intermittent vent controllers using natural gas as the power source emit
natural gas only when the controller sends a signal to open or close the valve.
The mitigation options for pneumatic controllers are summarized below these include: (1)
replacing high-bleed controllers with low-bleed controllers; (2) electric powered controllers; and
C-9
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(3) solar powered controller systems. Additionally, the analysis categorizes facilities based on
the controller site type (new vs. existing) and facility size (large, medium, and small), these site
configurations were assumed to change over from existing to new sites over a 15-year time
frame.
Under the baseline projections developed for this analysis there are no emissions from the
new facility in the baseline in 2021. All the CH4 distribution are from existing facilities.
Zero Emissions Options in Production, Gathering and Boosting, Transmission
Compression, and Underground Natural Gas Storage
Low-bleed controllers provide the same operational function as high-bleed controllers but
have lower continuous bleed emissions. This analysis adopts the technology costs assumptions
presented in EPA, 2022. The technical lifetime of equipment was assumed to be 15 years. The
reduction efficiency is assumed to be 100% for all zero emissions mitigation options. Table C-4
below summarizes the reduction efficiency and costs by pneumatic controller type.
C-10
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Table C-4 Technology and Cost Inputs by Model Facility Size and Type for Zero
Emissions Options in Production; Gathering and Boosting; Transmission
and Storage97
Facility
Site
Mitigation
Reduction
Capital Costs
O&M Costs
Size
Type
Option
Efficiency
($2019)
($2019)
Small
New
Electric controllers -grid
100%
$15,287
-$916
Small
New
Electric controllers - solar
100%
$16,831
-$726
Small
New
Compressed air - grid
100%
$47,512
$4,068
Small
New
Compressed air - generator
100%
$95,115
$2,161
Medium
New
Electric controllers -grid
100%
$25,426
-$1,832
Medium
New
Electric controllers - solar
100%
$28,515
-$1,452
Medium
New
Compressed air - grid
100%
$71,426
$2,816
Medium
New
Compressed air - generator
100%
$100,231
$909
Large
New
Electric controllers -grid
100%
$55,842
-$4,582
Large
New
Electric controllers - solar
100%
$63,049
-$3,665
Large
New
Compressed air - grid
100%
$113,277
$2,454
Large
New
Compressed air - generator
100%
$190,577
-$1,360
Small
Existing
Electric controllers -grid
100%
$20,593
-$916
Small
Existing
Electric controllers - solar
100%
$22,653
-$726
Small
Existing
Compressed air - grid
100%
$58,636
$4,068
Small
Existing
Compressed air - generator
100%
$120,000
$2,161
Medium
Existing
Electric controllers -grid
100%
$34,322
-$1,832
Medium
Existing
Electric controllers - solar
100%
$38,441
-$1,452
Medium
Existing
Compressed air - grid
100%
$76,481
$2,816
Medium
Existing
Compressed air - generator
100%
$120,000
$909
Large
Existing
Electric controllers -grid
100%
$75,508
-$4,582
Large
Existing
Electric controllers - solar
100%
$85,119
-$3,665
Large
Existing
Compressed air - grid
100%
$127,469
$2,454
Large
Existing
Compressed air - generator
100%
$220,000
-$1,360
Options If Zero-Emission Options are Technically Infeasible
As described in EPA, 2022, the primary costs associated with electronic controller
systems are the initial capital expenditures for the equipment (i.e., controllers and control panel),
the engineering and installation costs, and the operating costs for electrical energy. Electrical
supply is assumed to be available at the facility irrespective of the electronic controllers at the
97 Capital and annual costs of controller systems are discussed in Chapter 3.2.3 of EPA, 2022.
C-ll
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site, the costs of the power supply were not included in the mitigation option costs for electronic
controllers. Table C-5 presents the costs for electronic controllers across production,
transmission and storage segments at facilities based on the number of controllers at each site.
The technical lifetime of equipment was assumed to be 15 years.
Table C-5 Technology and Cost Inputs by Model Facility Size and Type Zero Emissions
Options in Production; Gathering and Boosting; Transmission and Storage98
Facility
Size
Site
Type
Mitigation
Option
Reduction
Efficiency
Capital Costs
($2019)
O&M Costs
($2019)
Small
New
Route to existing
combustion device
95.0%
$15,256
$497
Small
New
Route to new combustion
device
95.0%
$53,725
$20,846
Small
New
Install low or intermittent
controllers with inspection
27.3%
$0
$600
Medium
New
Route to existing
combustion device
95.0%
$27,461
$1,329
Medium
New
Route to new combustion
device
95.0%
$65,930
$21,244
Medium
New
Install low or intermittent
controllers with inspection
38.4%
$0
$600
Large
New
Route to existing
combustion device
95.0%
$64,075
$2,088
Large
New
Route to new combustion
device
95.0%
$102,544
$22,437
Large
New
Install low or intermittent
controllers with inspection
38.4%
$0
$600
Small
Existing
Route to existing
combustion device
95.0%
$15,256
$497
Small
Existing
Route to new combustion
device
95.0%
$53,725
$20,846
Small
Existing
Install low or intermittent
controllers with inspection
27.3%
$0
$600
Medium
Existing
Route to existing
combustion device
95.0%
$27,461
$1,329
Medium
Existing
Route to new combustion
device
95.0%
$65,930
$21,244
Medium
Existing
Install low or intermittent
controllers with inspection
38.4%
$0
$600
98 As discussed in EPA, 2022, electronic controller costs reflect information in the 2022 Carbon Limits report, as
well as estimates of installation costs used in the November 2021 analyses and considered operation and
maintenance costs for all types of pneumatic controller systems not driven by natural gas.
C-12
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Large
Existing
Route to existing
combustion device
95.0%
$64,075
$2,088
Large
Existing
Route to new combustion
device
95.0%
$102,544
$22,437
Large
Existing
Install low or intermittent
controllers with inspection*
38.4%
$0
$600
C. 6.2 Fugitive Emissions from Well Sites, Gas Processing Plants, Compressor Stations and
Offshore Facilities
There are several potential sources of fugitive emissions throughout the oil and natural
gas industry. Fugitive emissions occur when connection points are not fitted properly or when
seals and gaskets start to deteriorate. Changes in pressure and mechanical stresses can also cause
components or equipment to emit fugitive emissions. Poor maintenance or operating practices,
such as improperly reseated pressure relief valves (PRVs) or worn gaskets on thief hatches on
controlled storage vessels are also potential causes of fugitive emissions. Additional sources of
fugitive emissions include agitator seals, connectors, pump diaphragms, flanges, instruments,
meters, open-ended lines (OELs), pressure relief devices such as PRVs, pump seals, valves or
controlled liquid storage tanks. EPA 2022 analysis provided a breakdown of model facilities for
the production well sites categorized by the types of equipment in operation at the site.
Table C-6 below presents the reduction efficiency and costs for the various mitigation
options models to address fugitive emissions across the segments of the oil and natural gas
industry. For production wellhead sites this analysis simplified the number of options to only
include the options that assumed 0.5% leak rates. A discussion of how 0.5% leak rates are
determined and used can be found in in EPA 2022. For offshore production facilities this
analysis applies the directed inspection and maintenance option reported in EPA 2019, as there
was no clear updated cost information for this type of facility in earlier cited NSPS/EG analysis.
C-13
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Table C-6 Technology and Cost Inputs by Mitigation Option in Production; Gathering
and Boosting; Transmission and Storage
Segment
Site Type
Mitigation Option
Reduction
Efficiency
Capital Costs
($2019)
O&M Costs
($2019)
Producti
on
Single Wellhead
Only
Equipment Leak Monitoring at Well
Site (0.5% leak rate, 30 day repair)a
48%
1,027
1,889
Producti
on
Wellhead, tank,
and other
Equipment Leak Monitoring at Well
Site (0.5% leak rate, 30 day repair)a
47%
1,027
2,160
Producti
on
Multi-Wellhead
Only
Equipment Leak Monitoring at Well
Site (0.5% leak rate, 30 day repair)a
44%
1,027
1,858
Producti
on
Offshore
Direct Inspection & Maintenance 0
95%
-
33,333
G&B
Compressor
Station
Equipment Leak Monitoring Program
at a Compressor Station (G&B) w/o
Recovery Credits b
43%
1,027
10,134
Processi
ng
Processing Plant
Equipment Leak Monitoring Program
at Processing Plantb
40%
3,087
6,353
Transmi
ssion
Compressor
Station
Equipment Leak Monitoring Program
at a Compressor Station
(Transmission) w/o Recovery Credits'3
40%
23,883
12,903
Storage
Compressor
Station
Equipment Leak Monitoring Program
at a Compressor Station (Storage) w/o
Recovery Credits b
40%
23,883
17,000
Source: a)EPA, 2022; b) EPA, 2021, and c) EPA, 2019.
C. 6.3 Pneumatic Pumps
A pneumatic pump is a positive displacement reciprocating unit generally used by the Oil
and Natural Gas Industry for one of four purposes: (1) hot oil circulation for heat tracing/freeze
protection, (2) chemical injection, (3) moving bulk liquids, and (4) glycol circulation in
dehydrators. There are two basic types of pneumatic pumps used in the Oil and Natural Gas
Industry — diaphragm pumps and piston pumps. Natural gas-driven pneumatic pumps emit
methane and volatile organic compounds (VOC) as part of their normal operation. However,
pneumatic pumps may also be powered by electricity or compressed air, and these types of
controllers do not use or emit natural gas.
Two types of control options were evaluated in the revised technology analysis related to
the 2022 Supplemental proposal (EPA, 2022). The first type utilizes pneumatic pumps that are
not driven by natural gas, thus eliminating methane emissions. The other option is to reduce
emissions when natural gas-driven pneumatic pumps are used. Table C-7 summarizes the base
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mitigation technology and cost assumptions for pneumatic pumps. These options are applied
across to emissions from production and G&B, transmission, and storage segments.
Table C-7 Technology and Cost Inputs by Mitigation Option in Production; Gathering
and Boosting; Transmission and Storage
Pump Type
Mitigation Option
Reduction
Efficiency
Capital
Costs
($2019)
O&M
Costs
($2019)
Zero Emissions (Non NG-Driven)
One Diaphragm
Electric Pump
100%
$5,219
$329
One Diaphragm
Solar Powered Electric Pump
100%
$2,246
$0
One Diaphragm
Compressed Air-Driven Pump
100%
$6,742
$10,335
One Piston
Electric Pump
100%
$2,043
$329
One Piston
Solar Powered Electric Pump
100%
$2,246
$0
One Piston
Compressed Air-Driven Pump
100%
$6,742
$0
Routing to Combustion if Zero Emissions is Technically Infeasible
One Diaphragm
Route Emissions to an Existing Process
95%
$6,102
$0
One Piston
Route Emissions to an Existing Process
95%
$6,102
$0
One Diaphragm
Route Emissions to an Existing Combustion Device
95%
$6,102
$0
One Piston
Route Emissions to an Existing Combustion Device
95%
$6,102
$0
One Diaphragm
Route Emissions to a New Combustion Device
95%
$38,469
$19,095
One Piston
Route Emissions to a New Combustion Device
95%
$38,469
$19,095
Source: EPA, 2022.
C.6.4 Liquids Unloading
As described in EPA, 2021, the accumulation of liquids in new or mature wells" can
impede and sometimes halt gas production. When the accumulation of liquid results in the
slowing or cessation of gas production (i.e., liquids loading), removal of fluids (i.e., liquids
unloading) is required in order to maintain production. Gas wells therefore often need to remove
or "unload" accumulated liquids to maintain gas production.
This analysis models two liquid unloading techniques (i.e.; with and without the use of a
plunger lift). For liquids unloading that do not employ plunger lift, emissions occur when there is
99 In new gas wells, there is generally sufficient reservoir pressure/gas velocity to facilitate the flow of water and
hydrocarbon liquids through the well head and to the separator to the surface along with produced gas. In mature
gas wells, the accumulation of liquids in the wellbore can occur when the bottom well pressure/ gas velocity
approaches average pressure.
C-15
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venting of a well, typically to an atmospheric tank. For example, a common unloading method
manually diverts the well's flow from a production separator to an atmospheric pressure tank.
Under this scenario, venting to the atmospheric tank occurs because the separator operates at a
higher pressure than the atmospheric tank and the well will temporarily flow to the atmospheric
tank (which has a lower pressure than the pressurized separator). Natural gas is released through
the tank vent to the atmosphere until liquids are unloaded.
For liquids unloading performed using a plunger lift, liquids may be removed manually
or by automation. This method closes (shuts in) the well by lowering the plunger below the
accumulated liquids in the well bore, which increases the reservoir pressure. Liquid is removed
by the plunger when the well is reopened and the gas in the well pushes the plunger and the
liquid back up the well bore (based on pressure differential). Emissions occur if the plunger does
not return to the surface as expected, or when the plunger controller bypasses the separator and
directs the flow to a lower pressure atmospheric pressure vent.
Table C-8 summarizes the mitigation technology and costs assumptions obtained from
the Oil and Gas NSPS/EG technical analysis (EPA,2021). For costs, the analysis assumes 25
percent of the average duration of a liquids unloading event would be the additional time
required to implement BMP (i.e., monitoring and following steps to minimize/eliminate venting
of emissions). It is assumed that persons implementing BMPs are already onsite, and no travel
costs would be required. An average duration of a liquids unloading venting event (1.9 hours)
was obtained from the API/ANGA Report (API ANGA 2012). Thus, the time assumed to be
needed to implement the BMP per unloading event was 0.475 hours per event. The reported cost
per event assumes technical hour rate for plant and system operators, gas plant operators
($71.47/hr).
Table C-8 Technology and Cost Inputs by Mitigation Option in Production; Gathering
and Boosting; Transmission and Storage
O&M
Mitigation Option Reduction Capital Costs Costs3
Segment Efficiency ($2019) ($2019)
Production Liquids Unloading - Without Plunger Lift -10% Control 10% - $65
Production Liquids Unloading - Without Plunger Lift - 25% Control 25% - $65
Production Liquids Unloading - Without Plunger Lift - 50% Control 50% - $65
Production Liquids Unloading - With Plunger Lift - 10% Control 10% - $65
C-16
-------
Production Liquids Unloading - With Plunger Lift - 25% Control 25%
Production Liquids Unloading - With Plunger Lift - 50% Control 50%
$65
$65
a[l.9-hour event X 0.475 hour] X $71.74 hour = $64.75/event
Source: EPA, 2022.
C. 6.5 Centrifugal Compressors
Table C-9 summarizes the technology costs and reduction efficiency assumptions
obtained from the analysis update (EPA, 2022 and 2021). For wet seal centrifugal compressors,
the technologies included: (1) routing emissions to a control device that achieves an emission
reduction of 95.0 percent, (2) routing emissions to a process, and (3) implementing maintenance
and repair activities to meet a numerical emission limit. For dry seal compressors, the mitigation
technology was (1) direct inspection and maintenance/repair and routing to an enclosed
combustor.
Table C-9 Technology and Cost Inputs by Mitigation Option in Production; Gathering
and Boosting; Transmission and Storage
Segment
Site
Type
Mitigation
Option
Reduction
Efficiency
Capital Costs
($2019)
O&M Costs
($2019)
Production
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
Production
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
Production
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
89%
$0
$25,000
Production
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
89%
$0
$25,000
Production
New
Emissions Routed to a New
Combustion Device - Wet Seal
Centrifugal Comp
95%
$80,926
$128,683
C-17
-------
Production
Existing
Emissions Routed to a Existing
Combustion Device - Wet Seal
Centrifugal Comp
95%
$26,214
$3,732
G&B
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
G&B
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
G&B
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
89%
$0
$25,000
G&B
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
89%
$0
$25,000
G&B
New
Emissions Routed to a New
Combustion Device - Wet Seal
Centrifugal Comp
95%
$80,926
$128,683
G&B
Existing
Emissions Routed to a Existing
Combustion Device - Wet Seal
Centrifugal Comp
95%
$26,214
$3,732
T&S
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
T&S
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Dry Seal
Centrifugal Comp
37%
$0
$15,000
T&S
New
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
54%
$0
$25,000
T&S
Existing
Direct Inspection and
Maintenance/Repair Option and
Routing to An Enclosed
Combustor Option - Wet Seal
Centrifugal Comp
54%
$0
$25,000
C-18
-------
T&S
New
Emissions Routed to a New
Combustion Device - Wet Seal
Centrifugal Comp
95%
$80,926
$128,683
T&S
Existing
Emissions Routed to a Existing
Combustion Device - Wet Seal
Centrifugal Comp
95%
$26,214
$3,732
C. 6.6 Reciprocating Compressors
In a reciprocating compressor, natural gas enters the suction manifold, and then flows
into a compression cylinder where it is compressed by a piston driven in a reciprocating motion
by the crankshaft powered by an internal combustion engine. Emissions occur when natural gas
leaks around the piston rod when pressurized natural gas is in the cylinder. The compressor rod
packing system consists of a series of flexible rings that create a seal around the piston rod to
prevent gas from escaping between the rod and the inboard cylinder head. However, over time,
during operation of the compressor, the rings become worn, and the packaging system needs to
be replaced to prevent excessive leaking from the compression cylinder.
For this analysis, the projected baseline emissions are estimates for two types of emission
(1) emissions from rod packing system, and (2) fugitive leaks from reciprocating compressors.
We applied the Rod Packing Change Out option to the first emissions stream. The annual
monitoring option applied to the fugitive emissions.
Options to reduce emissions from reciprocating compressors include limiting leaks of
natural gas past the piston rod packing unit. Two alternative approaches are analyzed in this
analysis, these include: (1) specifying a frequency for the replacement of the compressor rod
packing, (2) monitoring the emissions from the compressor and replacing the rod packing when
the results exceed a specified threshold. Table C-10 summarizes the technologies used in the
analysis by segment and compressor type.
Table C-10 Technology and Cost Inputs by Mitigation Option in Production; Gathering
and Boosting; Transmission and Storage
Segment
Site
Type
Mitigation
Option
Reduction
Efficiency
Capital Costs
($2019)
O&M Costs
($2019)
Production
New
Rod Packing Change Out
56%
$6,345
$1,963
Production
New
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$6,345
$2,560
Production
Existing
Rod Packing Change Out
56%
$6,345
$1,963
C-19
-------
Production
Existing
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$6,345
$2,560
G&B
New
Rod Packing Change Out
56%
$6,345
$1,963
G&B
New
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$6,345
$2,560
G&B
Existing
Rod Packing Change Out
56%
$6,345
$1,963
G&B
Existing
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$6,345
$2,560
Processing
New
Rod Packing Change Out
80%
$4,807
$1,682
Processing
New
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$4,807
$2,279
Processing
Existing
Rod Packing Change Out
80%
$4,807
$1,682
Processing
Existing
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$4,807
$2,279
T&S
New
Rod Packing Change Out -
Transmission
80%
$6,345
$1,963
T&S
New
Annual Monitoring to Evaluate
Need for Packing Replacement -
Transmission
92%
$6,345
$2,560
T&S
Existing
Rod Packing Change Out -
Transmission
80%
$6,345
$1,963
T&S
Existing
Annual Monitoring to Evaluate
Need for Packing Replacement -
Transmission
92%
$6,345
$2,560
T&S
New
Rod Packing Change Out -
Storage
77%
$8,653
$2,332
T&S
New
Annual Monitoring to Evaluate
Need for Packing Replacement -
Storage
92%
$8,653
$2,929
T&S
Existing
Rod Packing Change Out -
Storage
77%
$8,653
$2,332
T&S
Existing
Annual Monitoring to Evaluate
Need for Packing Replacement -
Storage
92%
$8,653
$2,929
Source: EPA, 2022.
C.7 Emission Reductions and Mitigation Costs
The abatement potential achievable under the WEC analysis is summarized by segment
and source in Table C-l 1. In 2024, our analysis estimates cost effective mitigation potential to
be approximately 150 kilotonnes methane (ktCH4). This potential increases in the following year
to over 300 ktCTU and then drops to 47 ktCTU for years 2026 through 2035.
C-20
-------
Table C-ll Abatement Potential by Industry Segment and Source Type (ktCELt)
Segment/Source"
2024
2025
2026
2027
Onshore Production
75.45
143
.00
247
.41
-
Offshore Production
1.59
3
.17
4
.76
4.76
Gathering and Boosting
63.33
134
.79
196
.99
-
Natural Gas Processing
6.43
12
.80
18
.83
-
Natural Gas Transmission Compression
1 fiQ
3
30
5
06
-
Vilural (ias Transmission Pipeline - ...
I iklergrouikl Villi ml (ias Slorage - ...
I.\(i Imporl l\porl - ...
I.\(i Storage - ...
Total Abatement Potential 148.48 297.15 473.06 4.76
Author's Calculations. a NG pipeline transmission and storage, LNG import/export and storage are not included in the analysis
because emissions from these sources did not exceed the WEC threshold criteria. As a result, no abatement is reported for
these segments.
It is important to note several key assumptions and data limitations associated with these
estimates.
First, the analysis presented in the RIA and the resulting mitigation potentials reflect the
baseline projections of emissions developed specifically for this rule making effort. See section
3 of the RIA for additional description of the baseline projections and what assumptions and
caveats are included in the final projection values. As shown in Table C-l 1 there are no
applicable emissions subject to WEC in the transmission pipeline, gas storage and LNG
segments.
Additionally, the mitigation potential reported is the quantity of abatement available at
mitigation costs ($/tCH4) less than the WEC price ($/tCH4) in a given year. There is significant
additional abatement available at prices above the WEC, but we assume that facilities where the
cost of implementing mitigation technologies is more expensive that the WEC fee, these
facilities would choose to pay the fee as it would be the more economical option.
Finally, the abatement potential reported in Table C-ll reflects an exogenous assumption
of adoption "phase in", where only one third of the full abatement potential estimated is assumed
to be achievable in 2024. This assumption increases to two thirds in 2025 and then increases to
full mitigation potential by 2026. These "phase in" constraints are intended to reflect the fact that
facilities need time to assess the mitigation options and costs before implementing them. As a
C-21
-------
result, the amount of mitigation observed in the first two years would be some fraction of the full
economical (e.g. Mit Cost < WEC) mitigation potential.
The MAC curve is a composite and the corresponding mitigation options available to the
applicable segments of the Oil and Natural Gas Industry subject to the WEC rule. Figure C-2
below shows the aggregate MAC curve for the industry, which shows cost-effective mitigation
potential of-445 tCH4 in 2024. Figure C-3 through Figure C-5 below, show the disaggregated
MAC curves by segment (i.e. production, G&B, T&S) illustrating the differences in mitigation
potential across the industry segments. The largest share of cost-effective mitigation potential is
available in the production segment (Figure C-3), accounting for approximately 252 2 tCFU in
2024 or -52% of the total abatement potential. Gathering and boosting and processing (Figure
C-4) offers the next largest potential of cost-effective reductions, approximately 209 tCFU
accounting for another -47% of 2024 abatement potential. Finally, Transmission and Storage
(Figure C-5) provides the remaining 5 tCFU of cost-effective abatement.
Figure C-2 Total MAC Curve for WEC Applicable Segments of the Oil and Gas
Industry in 2024
Mitigation Level (ktCH4)
C-22
-------
Figure C-3
Production Segment MAC Curve in 2024
-500
0
Figure C-4
100
200 300
Mitigation Level(ktCH4)
400
500
G&B and Processing Segments MAC Curve in 2024
100
200 300
Mitigation Level(ktCH4)
400
500
C-23
-------
Figure C-5 Transmission and Storage Segment MAC Curve in 2024
2-500
J.Q00
< 1.500
x
£ 1.000
CP
E 500
¦500
WECmm - $900
100
200 300
Mitigation Level(ktCH4)
400
500
Table C-12 to Table C-14 provide snapshots of the mitigation results in years 2024, 2026
and 2030. In each table we report the full mitigation potential, the cost-effective abatement
potential, potential after applying the "phase in" constraint. In addition, each table share the
breakdown of cost to achieve the "phase in" abatement potential both with and without the
inclusion of offsets of revenue from gas and non-gas savings.
C-24
-------
Table C-12 Abatement Potential and Mitigation Costs by Segment and Source, 2024
Total
Cost-
Effective
Abatement
Below WEC
(kt)
MACC
MACC
Total Cost
Total Cost
Industry Segment /
Technical
Abatement
with
without
Source
Abatement
Incl. Phase-
Revenue
Revenue
Potential
(kt)
In (kt)
(million $)
(million $)
Onshore Production
480
187
62
$21.7
$30.9
Pneumatic Controllers
462
175
58
$20.5
$29.2
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
9
4
1
$0.2
$0.3
Pneumatic Pumps
0
0
0
$0.0
$0.0
Liquids Unloading
8
8
3
$1.0
$1.4
Offshore Production
7
7
2
$0.1
$0.4
Fugitive Emissions
0
0
0
$0.0
$0.0
Gathering and Boosting
113
96
32
$13.6
$17.8
Pneumatic Controllers
67
54
18
$3.7
$5.9
Fugitive Emissions
38
38
13
$9.7
$11.6
Compressors
8
4
1
$0.3
$0.4
Pneumatic Pumps
0
0
0
$0.0
$0.0
Natural Gas Processing
4
4
1
$0.3
$0.4
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
4
4
1
$0.3
$0.4
Transmission and
28
28
9
$4.1
$4.1
Storage
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
23
23
8
$3.3
$3.3
Compressors
4
4
1
$0.8
$0.8
Total
632
322
107
$39.8
$53.6
C-25
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Table C-13 Abatement Potential and Mitigation Costs by Segment and Source, 2026
Total
Cost-
Effective
Abatement
Below WEC
(kt)
MACC
MACC
Total Cost
Total Cost
Industry Segment /
Technical
Abatement
with
without
Source
Abatement
Incl. Phase-
Revenue
Revenue
Potential
(kt)
In (kt)
(million $)
(million $)
Onshore Production
436
176
176
$61.6
$88.9
Pneumatic Controllers
419
159
159
$53.4
$79.3
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
9
9
9
$5.5
$5.7
Pneumatic Pumps
0
0
0
$0.0
$0.0
Liquids Unloading
8
8
8
$2.7
$3.9
Offshore Production
7
7
7
$0.1
$1.2
Fugitive Emissions
0
0
0
$0.0
$0.0
Gathering and Boosting
106
99
99
$46.0
$59.5
Pneumatic Controllers
61
54
54
$14.4
$21.5
Fugitive Emissions
37
37
37
$26.8
$32.8
Compressors
8
8
8
$4.9
$5.2
Pneumatic Pumps
0
0
0
$0.0
$0.0
Natural Gas Processing
4
4
4
$0.7
$1.1
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
4
4
4
$0.7
$1.1
Transmission and
28
28
28
$12.3
$12.4
Storage
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
24
24
24
$9.9
$9.9
Compressors
4
4
4
$2.4
$2.5
Total
581
314
314
$120.8
$163.1
C-26
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Table C-14 Abatement Potential and Mitigation Costs by Segment and Source, 2030
Total
Cost-
Effective
Abatement
Below WEC
(kt)
MACC
MACC
Total Cost
Total Cost
Industry Segment /
Technical
Abatement
with
without
Source
Abatement
Incl. Phase-
Revenue
Revenue
Potential
(kt)
In (kt)
(million $)
(million $)
Onshore Production
0
0
0
$0.0
$0.0
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
0
0
0
$0.0
$0.0
Pneumatic Pumps
0
0
0
$0.0
$0.0
Liquids Unloading
0
0
0
$0.0
$0.0
Offshore Production
7
7
7
$0.1
$1.2
Fugitive Emissions
0
0
0
$0.0
$0.0
Gathering and Boosting
0
0
0
$0.0
$0.0
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
0
0
0
$0.0
$0.0
Pneumatic Pumps
0
0
0
$0.0
$0.0
Natural Gas Processing
0
0
0
$0.0
$0.0
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
0
0
0
$0.0
$0.0
Transmission and
24
24
24
$9.9
$9.9
Storage
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
24
24
24
$9.9
$9.9
Compressors
0
0
0
$0.0
$0.0
Total
30
30
30
$10.0
$11.1
C.8 References
EPA. 2019. Global Non-CO 2 Greenhouse Gas Emission Projections & Marginal Abatement
Cost Analysis: Methodology Documentation. EPA-430-R-19-012. Available at:
https://www.epa.gov/sites/production/flles/2019-
09/documents/nonco2_methodology _report.pdf.
EPA. 2022. Oil and Natural Gas Sector: Emission Standards for New, Reconstructed, and
Modified Sources and Emissions Guidelines for Existing Sources: Oil and Natural Gas
Sector Climate Review; Supplemental Background Technical Support Document for the
Proposed New Source Performance Standards (NSPS) and Emissions Guidelines (EG).
C-27
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EPA. 2021. Oil and Natural Gas Sector: Emission Standards for New, Reconstructed, and
Modified Sources and Emissions Guidelines for Existing Sources: Oil and Natural Gas
Sector Climate Review; Supplemental Background Technical Support Document for the
Proposed New Source Performance Standards (NSPS) and Emissions Guidelines (EG).
API ANGA. 2012. Characterizing Pivotal Sources of Methane Emissions from Natural Gas
Production. Summary and Analysis of API and ANGA Survey Responses. Available at:
https://www.api.Org/-/media/files/news/2 tober/api-anga-survev-report.pdf
Carbon Limits. 2022. Zero emission technologies for pneumatic controllers in the USA Updated
applicability and cost effectiveness. Available at https://cdn.catf.us/wp-
content/uploads/2022/01/31114844/Zero-EmissionsTechnologoes-for-Pneumatic-Controllers-
2022.pdf.
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