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Regulatory Impact Analysis of the Proposed
Waste Emissions Charge
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EP A-43 O/R-23-005
January 2024
Regulatory Impact Analysis
of the Proposed 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.eov).
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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 2-9
2.7 Transfers 2-9
2.8 Organization of RIA 2-10
3 Baseline 3-11
3.1 Baseline Projection Approach 3-11
3.1.1 Base Year Emissions by Segment and Source 3-11
3.1.2 Baseline Projection Trends 3-13
3.1.3 Summary of Projections Methodology fromNSPS OOOOb/EG OOOOc RIA 3-14
3.1.4 Baseline Emissions Results 3-15
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 4-3
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 6-23
6.2.3 PM2 s-Related Impacts Due to VOC Emissions 6-24
6.2.4 Hazardous Air Pollutants (HAP) Impacts 6-26
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 7-4
7.4 Uncertainties and Limitations 7-6
8 Uncertainty Analyses 8-1
i
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8.1 Sensitivity on GHGRP Calculation Methods 8-1
8.2 Sensitivity on Interaction with NSPS/EG 8-3
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 9-12
9.3.1 Introduction and Background 9-12
9.3.2 Scope and Limitations 9-14
9.3.3 Summary Environmental Justice Findings of the NSPS OOOOb/EG OOOOc RIA 9-15
9.3.4 Environmental Justice Analysis of the Proposed Rule 9-17
9.3.5 Aggregate Average Conditions for Potentially Affected Counties 9-22
9.4 Distributional Climate Impacts 9-24
9.4.1 Environmental Justice Implications of Climate Change 9-24
9.4.2 Avoided U.S. Climate Impacts of the Proposed Rule 9-28
10 References 10-1
ANNEXES
Appendix A Illustrative Screening Analysis of Monetized VOC-Related Ozone
Health Benefits 1
Appendix B Application of the Framework for Evaluating Damages and Impacts
(FrEDI) to Assess the Distribution of Avoided Climate-Driven Damages 1
Appendix C Additional Information on Marginal Abatement Cost (MAC)
Modeling for Analysis of Waste Emissions Charge 1
it
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LIST OF TABLES
Table
1-1
Table
1-2
Table
1-3
Table
1-4
Table
1-5
Table
2-1
Table
3-1
Table
3-2
Table
4-1
Table
4-2
Table
4-3
Table
4-4
Table
4-5
Table
5-1
Table
5-2
Table
5-3
Table
5-4
Table
5-5
Table
5-6
Table
5-7
Table
5-8
Table
5-9
Table
5-10
Table
6-2
Table
6-3
Table
6-4
Table
6-5
Table
6-6
Table
7-1
Table
7-2
Table
7-3
Table
7-4
Table
7-5
Table
9-1
Table
9-2
Emissions Subject to the WEC 1-2
Projected Emissions Reductions from the Proposed Waste Emissions Charge, 2024-2035 1-3
Projected Net WEC Emissions and WEC Obligations in the Policy Scenario 1-4
Projected Benefits and Costs from the Proposed Waste Emissions Charge (million 2019$) 1-7
Details of Projected WEC Obligations and Climate Damages from Emissions Subject to WEC (million
2019$) 1-9
Waste Emissions Thresholds by Industry Segment in CAA Section 136(f) 2-2
Methane Emissions Reported to Subpart W Segments Subject to the WEC, By Source and Unit Type
(RY 2021) 3-12
Projected CH4 Emissions in Baseline 3-15
Numbers of Subpart W Reporting Facilities, WEC Appliable Facilities, and Facilities with WEC
Applicable Emissions Greater than Zero By Industry Segment (RY 2021) 4-3
Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses 4-6
Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2024, thousand tons 4-7
Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2026, thousand tons 4-7
Projected CH4 Subject to Waste Emissions Charge in Baseline Before Accounting for Mitigation and
Market Responses, by Segment, 2030, thousand tons 4-8
Mitigation Costs 5-5
Mitigation Cost Details (million 2019$) 5-5
Oil and Gas Markets Value and Quantity (2021) 5-7
PE Model Elasticity Values 5-10
PE Model Outcomes 5-12
Market Welfare Losses 5-13
Chemical Composition of Natural Gas by Weight by Segment 5-14
Projected Annual Reductions of Methane, VOC, HAP Emissions from Economic Impacts (kt) 5-15
Methane Mitigation Potential Details 5-15
Projected WEC Payments in the Policy Scenario, 2024-2035 5-16
Undiscounted Monetized Climate Benefits from Methane Mitigation under the WEC Proposal, 2024-
2035 (millions, 2019$) 6-14
Undiscounted Monetized Climate Benefits from Partial Equilibrium Model under the WEC Proposal,
2024-2035 (millions, 2019$) 6-15
Undiscounted Total Monetized Climate Benefits under the WEC Proposal, 2024-2035 (millions,
2019$) 6-15
Discounted Monetized Climate Benefits under the WEC Proposal, 2024-2035 (millions, 2019$).... 6-16
Top Annual HAP Emissions as Reported in 2017 NEI for Oil and Natural Gas Sources 6-27
Projected Emissions Reductions from the Proposed Waste Emissions Charge, 2024-2035 7-2
Projected Benefits and Costs from the Proposed Waste Emissions Charge (million 2019$) 7-2
Projected Annual Emissions Reductions from the Proposed Waste Emissions Charge (thousand metric
tons) 7-3
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 This
Rule (millions of 2019$, discounted to 2023) 7-4
Details of Projected WEC Obligations and Climate Damages from Emissions Subject to WEC (million
2019$) 7-6
Small Entity Cost-to-Revenue-Ratio Threshold Analysis Results 9-6
Employment in Oil and Gas Sectors (2022) 9-8
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Table 9-3 Labor Compensation in the Oil and Gas Sector (2022) 9-9
Table 9-4 Employment Multipliers for Abatement Expenditures 9-11
Table 9-5 Employment Impacts of Compliance Expenditures and Output Changes 9-12
Table 9-6 Categorizing Category Emissions by Intensity 9-20
Table 9-7 Overall Demographic and Health Indicators for All Counties, by Category 9-23
Table A-l Summary of 2017 CAMx MDA8 ozone model performance for all April-September days 3
Table A-2 Benefit-per-ton Estimates of Ozone-Attributable Premature Mortality and Illnesses for the WEC
Proposal in 2019 Dollars 10
Table A-3 Estimated Discounted Economic Value of Ozone-Attributable Premature Mortality and Illnesses under
the Proposed WEC, 2024-2035 (million 2019S) d 11
Table A-4 Stream of Human Health Benefits under the Proposed 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$)a b 11
Table A-5 Stream of Human Health Benefits under the Proposed WEC, 2024-2035: Monetized Benefits
Quantified as Sum of Avoided Morbidity Health Effects and Avoided Long-term Ozone Mortality
(discounted at 7 percent to 2023; million 2019$)ab 12
Table B-l Current FrEDI sectors, including aggregate category group, default adaptation assumptions, and
descriptions. Adapted from the FrEDI Technical Documentation 7
Table B-2 Four socially vulnerable and reference groups considered here 12
Table C-1 Calculation of Emission Reductions for a Mitigation Option 2
Table C-2 Financial Assumptions in Break-Even Price Calculation for Mitigation Options 5
Table C-3 Mitigation Technologies Included in WEC Analysis by Source Category 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 11
Table C-5 Technology and Cost Inputs by Model Facility Size and Type Zero Emissions Options in Production;
Gathering and Boosting; Transmission and Storage 12
Table C-6 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage 14
Table C-7 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage 15
Table C-8 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage 16
Table C-9 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage 17
Table C-10 Technology and Cost Inputs by Mitigation Option in Production; Gathering and Boosting; Transmission
and Storage 19
Table C-l 1 Abatement Potential by Industry Segment and Source Type 21
Table C-12 Abatement Potential and Mitigation Costs by Segment and Source, 2024 26
Table C-13 Abatement Potential and Mitigation Costs by Segment and Source, 2026 27
Table C-14 Abatement Potential and Mitigation Costs by Segment and Source, 2030 28
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 that are expected to owe the Waste
Emissions Charge 9-18
Figure 9-2 Individual County Emissions Ranked from Lowest to Highest 9-21
Figure A-l Air Quality Modeling Domain 2
Figure A-2 Climate Regions Used to Summarize 2017 CAMx Model Performance for Ozone 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 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 6
Figure B-l Schematic of Analysis Workflow from emissions to damages 4
Figure B-2 Relative avoided per capita climate driven impacts by sector and US region 9
Figure B-3 Regional share of annual mean avoided U.S. climate-driven impacts in 2090 10
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 14
Figure B-5 Per capita reductions in climate-driven impacts for six sectors in 2090, distributed by race and ethnicity.
15
Figure C-l Illustrative MAC Curve for Facilities with Emissions Subject to the WEC in the year 2025 6
Figure C-2 Total MAC Curve for WEC Applicable Segments of the Oil and Gas Industry in 2024 23
Figure C-3 Production Segment MAC Curve in 2024 24
Figure C-4 G&B and Processing Segments MAC Curve in 2024 24
Figure C-5 Transmission and Storage Segment MAC Curve in 2024 25
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 proposed 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
proposed rulemaking and to comply with executive orders, as well as other potential impacts of
the rulemaking. This rulemaking proposes how EPA would implement the WEC according to the
specifications in the IRA. Specifically, the rule proposes 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 price
changes under the proposed rule. 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
1-1
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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.
Using emissions reported to Subpart W for Reporting Year (RY) 2021 as an illustrative
example, 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. Under the proposed WEC, facilities with emissions below their
emissions threshold may reduce emissions subject to the WEC at other facilities with emissions
above the emissions threshold where those facilities are under common ownership or control.
Table 1-1 Emissions Subject to the WEC
CH4 emissions, 2021
(thousand metric (MMTCChe with
tons) GWP=28)
Petroleum and Natural Gas Systems National Total (GHGI) 8,600 240
GHGRP Subpart W 2,800 79
From WEC-applicable facilities (>25,000 mtCChe to W) 2,100 60
Facility emissions exceeding emissions threshold 1,200 33
Emissions subject to WEC, after netting 1,000 29
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
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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.
EPA estimates that this action will result in cumulative emissions reductions of 960
thousand metric tons of methane over the 2024 to 2035 period. These reductions represent about
33 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 1
percent of the estimated reductions is associated with decreased production activity in the oil and
natural gas sector estimated under the proposed rule. In addition to methane emissions
reductions, the WEC is estimated to result in reductions of 140 thousand metric tons of VOC and
5 thousand metric tons of HAP over the 2024 to 2035 period.
Table 1-2 Projected Emissions Reductions from the Proposed 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 960 140 5 27
The WEC has important interactions and is designed to work hand-in-hand with the New
Source Performance Standards (NSPS OOOb) and Emissions Guidelines (EG OOOOc) for the
Oil and Natural Gas Sector by accelerating the adoption of cost-effective methane mitigation
technologies, including those that would eventually be required under the NSPS OOOOb or EG
OOOOc. The annual projected emissions reductions, costs, and WEC obligations are
significantly affected by these interactions.
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The EPA proposed updates to the Oil and Gas NSPS OOOOb/EG OOOOc in 2021,
published a supplemental proposal in 2022, and finalized the NSPS OOOOb/EG OOOOc in
December 2023. 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 proposal includes reductions resulting
from the NSPS OOOOb/EG OOOOc based on information from the 2023 Final RIA.
Specifically, that analysis showed methane emissions reductions from the EG OOOOc beginning
to take effect in 2028. As facilities implement emission controls required by the NSPS OOOOb
and EG OOOOc, emissions subject to the WEC decline.
The second interaction between the WEC and NSPS OOOOb/EG OOOOc 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
OOOOb/EG OOOOc, applicable facilities in compliance with the NSPS OOOOb/EG OOOOc
are exempted from the WEC. The analysis in this RIA assumes that the regulatory compliance
exemption takes effect in 2027, such that, in 2027 and later, facilities in the industry segments
subject to requirements under the NSPS OOOOb/EG OOOOc do not owe WEC payments.
Projected methane emissions subject to WEC after accounting for methane mitigation
and energy market impacts are estimated to be about 830 thousand metric tons in 2024, and then
drop significantly the regulatory compliance exemption takes effect in 2027. 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
Year
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)
Methane Emissions
Subject to WEC in
Policy Scenario
(thousand metric
tons)
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
980
940
900
13
13
13
13
13
13
13
150
300
470
5
5
5
5
5
5
5
0.1
0.1
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
830
650
430
8.5
8.4
8.4
8.5
8.5
8.5
8.6
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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)
2034
13
5
0.0
8.4
2035
13
5
0.0
8.3
Total 2024-2035
2,900
960
2.6
2,000
Climate benefits associated with this proposed 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.
This proposed 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 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.
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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 proposal. 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 proposed rule includes the engineering costs for methane mitigation
actions implemented by the oil and natural gas industry to reduce WEC obligations. 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 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 proposed 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
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
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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 proposal. 2
Table 1-4 Projected Benefits and Costs from the Proposed Waste Emissions Charge
(million 2019$)
2 Percent Near-Term Ramsey Discount Rate
PV
EAV
PV
EAV
PV
EAV
Monetized Climate Benefits3
$1,900
$180
$1,900
$180
$1,900
$180
2 Percent
3 Percent
7 Percent
Discount Rate
Discount Rate
Discount Rate
PV
EAV
PV
EAV
PV
EAV
Total Social Costs
$390
$37
$380
$38
$340
$43
Cost of Methane Mitigation
$360
$34
$350
$35
$320
$40
Cost of Energy Market
$30
$3
$29
$3
$26
$3
Impacts
Net Benefits'3
$1,500
$140
$1,500
$140
$1,600
$140
Ozone benefits from reducing 960 thousand metric tons of methane from
2024 to 2035
PM2.5 and ozone health benefits from reducing 140 thousand metric tons of
VOC from 2024 to 2035
Non-Monetized Benefits
HAP benefits from reducing 5 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
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 proposal. 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 proposed rules are not quantified or monetized. EPA anticipates that taking non-monetized effects into
account would show the proposals 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 is unlikely to change the result
that the benefits of the proposal exceed the costs.
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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
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 development of innovative technologies in the detection and mitigation of
methane emissions. See 168 Cong. Rec. E869 (August 23, 2022) (statement of Rep. Frank
Pallone). CAA section 136(a) and (b) provides $1.55 billion to, among other things, help finance
the early adoption of emissions reduction methodologies and technologies and to support
monitoring of methane emissions. 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,
3 Note that Congress specified that the WEC would rise to $1,500 per metric ton of methane in 2026 and beyond.
This value is consistent with estimates of climate damages associated with emissions of a metric ton of methane
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firms can avoid making WEC payments by mitigating their emissions generating climate benefits
associated with the amount of mitigation.
Table 1-5 provides details of the calculation steps used to estimate projected WEC
obligations and climate damages based on projected emission subject to WEC. In order to
compare projected WEC payments to climate damages from emissions subject to the WEC,
WEC payments are converted from nominal dollars to 2019 constant dollars using a chain-
weighted GDP price index from the 2023 Annual Energy Outlook (EIA, 2023).
Table 1-5 Details of Projected WEC Obligations and Climate Damages from Emissions
Subject to WEC (million 2019$)
Year
Methane
Emissions
Subject to
WEC in Policy
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
under 2%
Near-Term
Discount
Rate (2019$
per metric
ton)
Climate
Damages
from
Emissions
Subject to
WEC (million
2019$)a
2024
830
$900
$750
$620
$1,900
$1,600
2025
650
$1,200
$770
$630
$2,000
$1,300
2026
430
$1,500
$640
$510
$2,100
$890
2027
9
$1,500
$13
$10
$2,200
$18
2028
9
$1,500
$13
$10
$2,200
$19
2029
9
$1,500
$13
$10
$2,300
$20
2030
9
$1,500
$13
$9
$2,400
$20
2031
9
$1,500
$13
$9
$2,500
$21
2032
9
$1,500
$13
$9
$2,500
$21
2033
8
$1,500
$13
$9
$2,600
$21
2034
8
$1,500
$13
$8
$2,700
$21
2035
8
$1,500
$13
$8
$2,800
$21
Total
2024-
2035
2,000
-
$2,300
$1,800
-
$4,000
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.
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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2 BACKGROUND AND OVERVIEW
2.1 Introduction
This document presents the regulatory impact analysis (RIA) for the notice of proposed
rulemaking titled "Waste Emissions Charge for Petroleum and Natural Gas Systems." The
proposed rulemaking would implement 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 proposal responds
to requirements from the Inflation Reduction Act.
2.2 Statutory Requirements
This section describes the legal basis for the proposed 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). 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
emissions for certain facilities under common ownership or control and provides for
several exemptions from charges.
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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 industry segment-specific
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 segment-
specific methane intensity thresholds 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 would only apply 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 segment-specific 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
0.05 percent of the natural gas sent to sale from or
through the facility
Onshore petroleum and natural gas gathering and
boosting
Onshore natural gas processing
Liquefied natural gas storage
Liquefied natural gas import and export equipment
Onshore natural gas transmission compression
Underground natural gas storage
Onshore natural gas transmission pipeline
0.11 percent of the natural gas sent to sale from or
through the facility
The EPA is proposing to establish 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 proposed
rulemaking is hereafter referred to as the "WEC proposal" and the proposed provisions under 40
CFR part 99 are hereafter referred to as "proposed WEC regulations."
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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 proposing to define 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 EPA is
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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proposing that WEC would be imposed for each WEC obligated party, which is defined in the
proposed 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 New Source Performance Standards and
Emissions Guidelines (NSPS OOOOb/EG OOOOc) 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." On August 1,
2023, the EPA proposed revisions to the requirements of subpart W consistent with those
directives (88 FR 50282). Those revisions, when finalized, would be used to report emissions to
GHGRP and impact the resulting WEC calculations. However, those amendments would become
effective on January 1, 2025, and reporters would 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 current provisions of subpart W. The analysis in this RIA is based
on current reported emissions and current methods and factors rather than these proposed
amendments.
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
to estimate WEC payments. For example, the proposed revisions add a new emissions source,
"other large release events." Other large release events are believed to occur sporadically at a
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minority of facilities, but with potentially significant emissions when they occur.5 The EPA also
proposed 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
proposed GHGRP Subpart W revisions.
The WEC also has important interactions and is designed to work hand-in-hand with the
Oil and Gas NSPS OOOOb and EG 0000c. The EPA proposed updates to the Oil and Gas
NSPS OOOOb/EG 0000c in 2021, published a supplemental proposal in 2022, and finalized in
December 2023. 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 revised
NSPS OOOOb/EG 0000c 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 implementation plans. The first way that the WEC interacts with the NSPS OOOOb/EG
0000c 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 OOOOb/EG 0000c. As WEC obligated parties implement the
emissions controls required by the NSPS OOOOb/EG 0000c, the resulting reduced emissions
would also mean reduced WEC payments. This RIA accounts for this interaction by including
the emissions reduction impacts of the Oil and Gas NSPS OOOOb/EG 0000c in the baseline
scenario.
The second interaction between the WEC and NSPS OOOOb/EG 0000c is the
regulatory compliance exemption provision of the WEC. Under this provision, when certain
5 EPA does not have an estimate of the number of large release events or quantity of emissions which may be
reported under the proposed source category. 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.regulations.gov/document/EPA-HQ-OAR-2023-0234-0163
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conditions are met with respect to the implementation of the Oil and Gas NSPS OOOOb/EG
OOOOc, applicable facilities in compliance with the NSPS 0000b 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
2027, such that in 2027 and later, facilities in the industry segments subject to requirements
under the NSPS OOOOb/EG OOOOc do not owe WEC payments.6 The Final Oil and Natural
Gas NSPS OOOOb/EG OOOOc lays out the timing for state plan submission. Under the EG
OOOOc, states have 24 months to submit their state implementation plans, and EPA must
approve or deny state plans within 12 months, which means that the regulatory compliance
exemption could be available as early as January 2027, assuming no Federal Implementation
Plan is needed.
2.4 Economic Basis for the Rulemaking
This section describes the economic rationale for the proposed 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 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,
6 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 2027 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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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 proposed 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 already have economic incentives to mitigate 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.
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,
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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.
The regulatory impacts of the proposed WEC are evaluated relative to a baseline that
represents the oil and gas industry in the absence of this proposed action. To avoid double
counting of costs, the baseline for this proposal includes reductions resulting from the NSPS
OOOOb/EG OOOOc for Oil and Gas, as detailed in the Final NSPS OOOOb/EG 0000c RIA.
Only a subset of the baseline emissions is subject to the WEC, as seen in section 4.2.
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 years7. 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 OOOOb/EG OOOOc 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.
7 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.
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2.6 Economic Significance
The proposed 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 1, the emissions reductions projected under the rule are likely to
produce substantial climate benefits, peaking at $780 million to $1.3 billion in 2026, as well as
non-monetized benefits from reductions in VOC and HAP emissions. At the same time, the
proposed WEC is projected to result in substantial transfer payments by the oil and gas industry
to comply with the rule, reaching a maximum of $770 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. (USEPA, 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 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 proposed 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 OOOOb/EG OOOOc.
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
2021 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 2021. Emissions trends are projected
by segment, source, control status, and site types.
The baseline projection includes anticipated impacts from the Oil and Gas NSPS
OOOOb/EG OOOOc. This approach is taken to avoid double-counting of costs and emissions
reductions across the analyses for the NSPS OOOOb/EG OOOOc and WEC. This analysis has
been updated to reflect the 2023 final RIA for the NSPS OOOOb/EG OOOOc.
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
subject to the WEC.8 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" for netting across
facilities). 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.9
8 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.
9 2011-2021 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/2022-
10/subpart_w_202 l_sector_profile .pdf
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Table 3-1 Methane Emissions Reported to Subpart W Segments Subject to the WEC,
By Source and Unit Type (RY 2021)
Source Unit Type CH4 tons
Pneumatic Devices Intermittent Bleed Pneumatic Devices 919,000
Misc Equipment Leaks Equipment Leak Population Counts 396,000
Blowdown Vent Stacks 238,000
Pneumatic Pumps 83,000
Dehydrators 80,000
Liquids Unloading 74,000
Pneumatic Devices High-Bleed Pneumatic Devices 69,000
Reciprocating Compressors Reciprocating Compressors - Rod Packing 59,000
Centrifugal Compressors Wet Seal Centrifugal Compressors - Seals 56,000
Combustion Equipment 55,000
Other Flare Stacks 48,000
Atmospheric Storage Tanks 47,000
Offshore Sources 47,000
Pneumatic Devices Low-Bleed Pneumatic Devices 42,000
Associated Gas Venting and Flaring 41,000
Misc Equipment Leaks Equipment Leak Surveys 34,000
Reciprocating Compressors Reciprocating Compressors - Leaks 33,000
Well Compl. and Work, with HF 11,000
Centrifugal Compressors Dry Seal Centrifugal Compressors - Leaks 8,700
Transmission Tanks 7,000
Centrifugal Compressors Wet Seal Centrifugal Compressors - Leaks 5,200
Gas Well Compl. and Work, without HF 870
Well Testing 7.3
Reporting requirements vary by segment and other facility characteristics. The base year
emissions information is based on data reported for reporting year 2021 (RY 2021). For many
sources, EPA has proposed revisions to reporting that may significantly change methane reported
to Subpart W. Because the most recent data available is from RY 2021, this baseline uses
emissions methods and factors in place in 2021. 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
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population emission factors or engineering calculations, which typically include specified
measurements of process operating parameters (e.g., temperature or pressure). The proposed
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, RY2021 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 RY2021 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 OOOOb/EG OOOOc. Projections by segment,
source (e.g., fugitives, pneumatic controllers, compressors), and unit type (e.g., centrifugal
compressors) were extracted from the projections from the 2023 NSPS OOOOb/EG OOOOc
RIA10. For emissions sources reported to GHGRP Subpart W, but not within the scope of the
NSPS OOOOb/EG OOOOc 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 OOOOb/EG OOOOc 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
10 https://www.epa.gOv/system/files/documents/2023-12/eol2866_oil-and-gas-nsps-eg-climate-review-2060-avl6-
ria-20231130.pdf
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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 NSPS OOOOb/EG
OOOOc 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
OOOOb/EG OOOOc.11 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 OOOOb/EG OOOOc 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 OOOOb/EG OOOOc RIA
Because the emissions baseline incorporates trends from the Final NSPS OOOOb/EG
OOOOc RIA projections, a summary of the projection methodology used in that analysis is
included here. The Final RIA includes further details on the projections methodology.
The Final NSPS OOOOb/EG OOOOc 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 OOOOb/EG OOOOc 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 Final NSPS OOOOb/EG OOOOc RIA summarize the
proposed requirements of those rules. The Final NSPS OOOOb/EG OOOOc RIA did not
quantify regulatory impacts of the super-emitter response program.
The NSPS OOOOb/EG OOOOc activity data projections rely on historical data from the
GHGI, industry data collected by EPA through an information collection request, information on
11 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
3-14
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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)12'13'14. 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 construction 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 proposed
NSPS OOOOb/EG 0000c. 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 in Baseline
Year
CH4 tons projected for Subpart W
(excl. NG dist)
2024
2,300,000
2025
2,300,000
2026
2,200,000
2027
2,200,000
2028
800,000
2029
810,000
2030
810,000
2031
810,000
2032
810,000
2033
810,000
2034
810,000
2035
820,000
12 Annual Energy Outlook 2023, https://www.eia.gov/ontlooks/aeo/.
13 U.S. Greenhouse Gas Emissions and Sinks, https://www.epa.gov/system/files/documents/2023-04/US-GHG-
Inventory-2023-Main-Text.pdf
14 Enverus Energy Analytics, http://www.enverus.com.
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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 EPA is proposing that the facility waste emissions threshold would be
subtracted from facility total methane emissions, as described in the proposed 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.
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
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 OOOOc
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.
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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 proposed
WEC regulations, the EPA is proposing to sum the WEC applicable emissions (positive or
negative) from all WEC applicable facilities under the common ownership or control of a WEC
obligated party to calculate net emissions for that WEC obligated party. To determine the WEC
obligated party's total annual waste emissions charge, or WEC obligation, the EPA is proposing
to multiply its net metric tons of methane exceeding the waste emissions thresholds 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 proposed terms and concepts, Table 4-1
shows the number of total facilities reporting under subpart W in RY 2021, the number of WEC
applicable facilities based on RY 2021 reported data, and the number of facilities with WEC
applicable emissions greater than zero based on RY 2021 emissions and throughputs, by subpart
W industry segment. For this analysis, we used GHGRP data frozen as of August 13, 2022
(available through EPA's Envirofacts website15). To estimate the number of WEC applicable
facilities within the GHGRP, we reviewed RY 2021 GHG emissions to determine which subpart
W facilities reported more than 25,000 mt CChe. For each WEC applicable facility, we
calculated the waste emissions threshold using the RY 2021 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 2021 reported CH4 emissions to determine whether
the WEC applicable emissions for each facility were greater than zero {i.e., positive). To account
for netting among facilities under common ownership or control, for an owner or operator having
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 only changes the
15 https://enviro.epa.gov/
4-2
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count of facilities with emissions subject to WEC in cases where total WEC applicable emissions
for an owner or operator are below 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 (RY 2021)
Number of
Number of
Facilities
Facilities with
Total
Number of
with WEC
Emissions
Number of
WEC
Applicable
Subject to WEC,
Facilities
Applicable
Emissions
After Netting
Industry Segment
Reporting
Facilities
>0a
Onshore petroleum and natural gas production
470
408
269
258
Offshore petroleum and natural gas production
132
16
11
10
Onshore petroleum and natural gas gathering
365
327
209
176
and boosting
Onshore natural gas processing
452
165
-50
-37
Onshore natural gas transmission compression
654
13
~ 3
-2
Onshore natural gas transmission pipeline
50
25
0
0
Underground natural gas storage
49
2
2
1
Liquefied natural gas storage
5
0
0
0
Liquefied natural gas import and export
11
5
0
0
equipment
Total
2,188
961
-544
-484
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.
4.1.3 Methodology for Projecting WEC-Applicable Emissions
To estimate potential impacts of the proposed 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 2021. Methane emissions were projected by segment and source as described
in the baseline section.
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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 appropriate segment-specific
methane intensity threshold 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 segment-specific methane intensity thresholds for each segment
are listed inTable 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 2027 for all facilities reporting to
segments containing facilities subject to the NSPS OOOOb/EG OOOOc 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 OOOOb/EG OOOOc
requirements, and thus receive a regulatory compliance exemption. The assumption that the
regulatory compliance exemption would apply starting in 2027 is based on prompt
implementation of the schedule for state plans outlined in the final Oil and Gas EG OOOOc.
Under the EG OOOOc, states have 24 months to submit their state implementation plans, and
EPA must approve or deny state plans within 12 months, which means that the regulatory
exemption could be available as early as January 2027, assuming no Federal Implementation
Plan is needed.
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 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
4-4
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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 CChe 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 a unique definition of facility in 40 CFR
98.238, and facilities in those segments only report emissions as direct emitters 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 report emissions under other GHGRP subparts as
well (e.g., 40 CFR part 98, subpart C, General Stationary Fuel Combustion Sources). 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."
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. For example, a particular facility might
report total methane of 1,000 tons, but the tons of emissions that are above the waste emissions
threshold could be 50 tons. Therefore, 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 at the owner-operator level (column
d in Table 4-2) is a subset of WEC-applicable emissions at the facility level.16 Based on EPA's
16 Calculations of netting are based on facility characteristics in the RY 2021 base year, combined with projected
changes as described in Section 3, and the WEC and netting calculations described in this section. The netting
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initial analysis of the 2021 data, a significant percentage of facilities are relatively efficient and
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
Year
CH4 tons projected
for Subpart W
(excl. NG dist)
(a)
CH4 tons from facilities
with WEC applicable
emissions >0ab
(b)
CH4 tons exceeding
facility waste emissions
thresholdsab
(c)
Net emissions
(tons) subject
to the WEC
(d)
2024
2,300,000
1,600,000
1,100,000
980,000
2025
2,300,000
1,500,000
1,100,000
940,000
2026
2,200,000
1,500,000
1,000,000
900,000
2027
2,200,000
17,000
14,000
13,000
2028
800,000
17,000
14,000
13,000
2029
810,000
17,000
14,000
13,000
2030
810,000
17,000
14,000
13,000
2031
810,000
17,000
14,000
13,000
2032
810,000
17,000
14,000
13,000
2033
810,000
17,000
14,000
13,000
2034
810,000
17,000
14,000
13,000
2035
820,000
17,000
14,000
13,000
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 2021, and thus assume this distribution of facilities and emissions.
The projections assume that starting in 2027, 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.
calculations assume that patterns of WEC facility emissions and ownership are reflective of those in the 2021
GHGRP data but do not attempt to project future changes in the oil and natural gas industry.
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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
1,300
1,000
700
650
Offshore Production
47
17
14
13
Gathering and Boosting
620
500
350
270
Natural Gas Processing
110
59
43
37
Natural Gas Transmission Compression
130
4
3
2
Natural Gas Transmission Pipeline
110
0
0
0
Underground Natural Gas Storage
13
4
2
1
LNG Import/Export
3
0
0
0
LNG Storage
0
0
0
0
Total
2,300
1,600
1,100
980
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
1,200
930
630
580
Offshore Production
47
17
14
13
Gathering and Boosting
620
500
350
270
Natural Gas Processing
110
58
43
37
Natural Gas Transmission
130
4
3
2
Compression
Natural Gas Transmission Pipeline
110
0
0
0
Underground Natural Gas Storage
12
4
1
1
LNG Import/Export
3
0
0
0
LNG Storage
0
0
0
0
Total
2,200
1,500
1,000
900
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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
230
0
0
0
Offshore Production
47
17
14
13
Gathering and Boosting
270
0
0
0
Natural Gas Processing
74
0
0
0
Natural Gas Transmission
73
0
0
0
Compression
Natural Gas Transmission Pipeline
110
0
0
0
Underground Natural Gas Storage
2
0
0
0
LNG Import/Export
3
0
0
0
LNG Storage
0
0
0
0
Total
810
17
14
13
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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. Section 5.1 describes the methods for estimating the expected
cost of methane mitigation. Section 5.2 evaluates the equilibrium impact of increased production
costs borne by oil and natural gas firms on market prices and quantities. In addition, the social
cost of these energy market effects is estimated as the loss in consumer and producer surplus
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).17 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.
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.
17 MAC curves are constructed 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 reflects the average
price and reduction potential if a mitigation technology were applied across the sector.
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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
achievable18 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 OOOOb/EG OOOOc analysis
(U.S. EPA, 2021b, 2022b). Available mitigation data for the offshore segment is limited and
therefore cost estimates in those segments could be overstated. We are requesting comment on
the application of cost effective technologies for the offshore segment (and other segments not
eligible for the regulatory compliance exemption). 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 associated with the
methane emission reductions.
18 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.
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Mitigation Level (ktCH4)
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 OOOOb/EG OOOOc rulemaking was first proposed in 2021 and there is
significant overlap in the mitigation technologies which would be used to satisfy NSPS OOOOb
and EG OOOOc 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.
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
OOOOb/EG OOOOc implementation, costs associated with mitigation resulting from the WEC
decline. Costs associated with NSPS OOOOb/EG OOOOc 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$)
2024
51
2025
110
2026
210
2027
0.1
2028
0.1
2029
0.1
2030
0.1
2031
0.1
2032
0.0
2033
0.0
2034
0.0
2035
0.0
NPV
3%
$350
7%
$320
EAV
3%
$38
7%
$42
Total costs associated with methane mitigation activities include capital costs, recurring
costs, and revenue from avoided losses of natural gas. Table 5-2 presents details of the
composition of mitigation costs among these components including total costs with and without
including revenue from avoided natural gas losses.
Table 5-2 Mitigation Cost Details (million 2019$)
Revenue from
Capital Recurring avoided
costs costs natural gas
losses
2024
$50.6
$69.1
$56.3
$11.3
$17.1
2025
$108.8
$146.2
$106.0
$36.6
$33.7
2026
$214.0
$275.6
$168.3
$102.3
$56.6
2027
$0.1
$0.9
$0.0
$0.9
$0.8
2028
$0.1
$0.9
$0.0
$0.9
$0.8
2029
$0.1
$0.9
$0.0
$0.9
$0.8
2030
$0.1
$0.9
$0.0
$0.9
$0.8
2031
$0.1
$0.9
$0.0
$0.9
$0.8
2032
$0.03
$0.9
$0.0
$0.9
$0.8
2033
$0.02
$0.9
$0.0
$0.9
$0.8
v vi. Mitigation costs
Year costs with .xl x
without revenue
revenue
5-5
-------
2034
2035
$0.01
$0,001
$0.9
$0.9
$0.0
$0.0
$0.9
$0.9
$0.9
$0.9
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 $187.8 billion of gas (34.5 TCF) and $280.2 billion of
crude oil (4.1 billion barrels) in 2021. 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 $161.8 billion in gas (30.7 TCF) and $417.2 billion in crude (6.1 billion
barrels) supplies. Prices in 2021 were $5.44 per MCF of natural gas and $68.13 per barrel of
crude.19 The net present value of total abatement and WEC payments of $1.6 billion (discounted
at 7%, $1.7 billion discounted at 3%) through 2035 are 0.3% (0.3% discounted at 3%) of 2021
domestic oil and gas domestic supply values.
19 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 (2021)
Market / Product
Gas
Crude
$ Billion
BCF
$ Billion
Million Barrels
Output (Y)20
$ 187.8
34,518
$ 280.2
4,113
Imports (M)21
19.0
2,808
210.7
3,093
Exports (X)22
- 45.0
- 6,653
- 73.7
- 1,081
Domestic Supply $ 161.8 30,673 $417.2 6,125
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 _ ( p.. \ay (1)
Y = Y y >
0 + cy)P,
Production: Fuel / pf x^fuel (2)
V _ ~ V I rJ \
Yf = afY
0 + Cf) Vy
Supply: Imports /pM\°^ ^
Mf = M
Demand: Total , c\ °f (4)
Pf
D' = ~D>%
Demand: Exports / (5)
V I "f
Xf Xf V Pr)
Demand: Domestic /nc\(7f
Demand: Imports , c\af 0)
D," = (!-/>,) 5, fe)
KPf
Market clearance: Domestic supply Yf Xf Df = 0 (8)
Market clearance: Imports Mf Df1 = 0 (9)
Zero profit: consumption . 3_ (10)
20 Gas: https://www.eia.gov/inteniational/cbita/world/natural-gas/drv-natural-gas-production
Oil: https://www.eia.gov/dnav/pet/pet_crd_crpdn_adc_mbbl_a.htm
21 Gas: https://www.eia.gov/internationai/cb-ita/world/natnrai-gas/dre-natnral-gas-imports
Oil: https://www.eia.gov/dnav/pet/pet move impcus a2 tins epOO ini() tnbbl a.htm
22 Gas: https://www.eia.gov/international/cb-ita/worlcl/natnral-gas/dre-natnral-gas-exports
Oil: https://www.eia.gov/dnav/pet/pet move exp dc NUS-ZOO tnbbl a.htm
5-7
-------
Zero profit: supply , N-I (11)
Py = (aCRuVCRUFUEL + aGAsPGASFUEL)
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
af. Cost share of fuel / in total production
Cf. Compliance cost applicable to segment / only (gas only)
°fuel '¦ Elasticity of substitution across gas and oil output
Mf\ Imports of fuel f
Of1: Elasticity of import supply for fuel f
pf\ Import price of fuel f
Df. Total demand for fuel f
of: Demand elasticity for fuel f
Xf. Exports of fuel /
a*\ Elasticity of demand for exports of fuel /
\ 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 behavior, 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
-------
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): oFUEL 0.0 0.0
7f
Imports (Foreign): a?1 0.01 0.06 0.19 0.25
Demand
Exports (Foreign): -0.01 -0.01 -0.01 -0.26
Substitution (Dom.-For.): o^ 2.80 7.30 2.80 7.30
Consumption: of -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).
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 OOOOb/EG OOOOc. This
analysis assumes that 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
5-10
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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 0.007%~0.008% 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 order of magnitude -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 0.1% production cost shock for the gas segment results in a 0.007% 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 0.052% and -
0.03%) respectively while crude oil changes by 0.035%> for price and -0.03%> for production in
2026 (not presented here). Given WEC and abatement costs are close in 2024-2026, the
relatively larger impact in 2026 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%>.
5-11
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Table 5-5
PE Model Outcomes
Year
Price: $/MCF
Quantity: BCF
Benchmark
WEC
% Change
Benchmark
WEC
% Change
2024
5.5055
5.5060
0.007%
35,038
35,038
-0.002%
2025
5.5276
5.5280
0.008%
35,214
35,213
-0.002%
2026
5.5497
5.5526
0.052%
35,390
35,379
-0.030%
2027
5.5719
5.5719
0.001%
35,567
35,566
-0.001%
2028
5.5942
5.5942
0.001%
35,744
35,744
-0.001%
2029
5.6165
5.6166
0.001%
35,923
35,923
-0.001%
2030
5.6390
5.6391
0.001%
36,103
36,103
-0.001%
2031
5.6616
5.6616
0.001%
36,283
36,283
-0.001%
2032
5.6842
5.6843
0.001%
36,465
36,464
-0.001%
2033
5.7069
5.7070
0.001%
36,647
36,647
-0.001%
2034
5.7298
5.7298
0.001%
36,830
36,830
-0.001%
2035
5.7527
5.7527
0.001%
37,014
37,014
-0.001%
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 market welfare (consumer and producer surplus) loss
associated with the WEC charge as the change in price times the change in quantity.23 Table 5-6
summarizes the total welfare loss resulting from implementing the WEC in the oil and gas
markets, which totals $0.3 to 0.4 million in 2024-2025, $30.9 in 2026, and $0.01 in the later
years of the analysis period. The NPV of welfare losses are $28.9 million at 3% to $25.8 million
at 7%.
23 This calculation provides an approximate value for the welfare loss that differs depending on the relative value of
the supply and demand elasticities.
5-12
-------
Table 5-6
Market Welfare Losses
Year
Market Welfare Loss
$ Million
2024
$0.28
2025
$0.35
2026
$30.85
2027
$0.01
2028
$0.01
2029
$0.01
2030
$0.01
2031
$0.01
2032
$0.01
2033
$0.01
2034
$0.01
2035
$0.01
NPV
3%
$28.9
7%
$25.8
EAV
3%
$3.1
7%
$3.4
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.
The proposed 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
5-13
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methane. VOC and HAP emissions present adverse health consequences discussed in Section
6.2. This analysis relies on a prior study (Brown, 2011) 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 to 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. 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
Table 5-8 summarizes the annual emissions reductions from abatement activities by
pollutant associated with the proposed 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 2027,
emissions reductions resulting from the WEC decline significantly.24 The remaining reductions
associated with the WEC after 2027 relate to facilities in the offshore production segment, which
is not subject to requirements under the NSPS OOOOb/EG OOOOc. 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.
24 EPA expects that the WEC would incentivize accelerated 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.
5-14
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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
150
0.1
150
23
0.0
23
0.9
0.0
0.9
2025
300
0.1
300
45
0.0
45
1.7
0.0
1.7
2026
470
2.0
480
71
0.3
72
2.6
0.01
2.7
2027
5
0.0
5
0.7
0.0
0.7
0.03
0.0
0.03
2028
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2029
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2030
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2031
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2032
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2033
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2034
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2035
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2024
960
2.6
960
140
0.4
140
5.3
0.0
5.3
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.
Table 5-9 Methane Mitigation Potential Details
Total Technical Cost-Effective Ah t t T 1
Year Abatement Abatement Below Phase-In Factor a emen nc *
Potential (kt) WEC (kt)
Phase-In (kt)
2024
884
445
0.33
148
2025
817
446
0.67
297
2026
765
473
1
473
2027
5
5
1
5
2028
5
5
1
5
2029
5
5
1
5
2030
5
5
1
5
2031
5
5
1
5
5-15
-------
2032
2033
2034
2035
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.
Table 5-10 Projected WEC Payments in the Policy Scenario, 2024-2035
Year
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)
Net Methane
Emissions
Subject to
WEC in Policy
Scenario
(thousand
metric tons)
Charge
Specified by
Congress
(nominal $ per
metric ton)
WEC
Payments in
Policy
Scenario
(million
undiscounted
nominal $)
2024
980
150
0.1
830
$900
$750
2025
940
300
0.14
650
$1,200
$770
2026
900
470
2
430
$1,500
$640
2027
13
5
0.04
9
$1,500
$13
2028
13
5
0.04
9
$1,500
$13
2029
13
5
0.04
9
$1,500
$13
2030
13
5
0.04
9
$1,500
$13
2031
13
5
0.04
9
$1,500
$13
2032
13
5
0.04
9
$1,500
$13
2033
13
5
0.04
9
$1,500
$13
2034
13
5
0.04
9
$1,500
$13
2035
13
5
0.04
9
$1,500
$12
Total
2024-2035
2,900
960
2.6
2,000
$2,300
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6 BENEFITS
The proposed 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 proposed 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
proposed 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
December 2023 Final NSPS OOOOb/EG OOOOc Rulemaking, "Standards of Performance for
New, Reconstructed, and Modified Sources and Emissions Guidelines for Existing Sources: Oil
and Natural Gas Sector Climate Review". The EPA solicited public comment on the
methodology and use of these estimates in the RIA for the agency's December 2022
Supplemental Proposal NSPS OOOOb/EG OOOOc, and has conducted an external peer review
of these estimates, as described further below.
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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.25 In the December 2022 Supplemental Proposal
NSPS OOOOb/EG OOOOc 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 estimates26 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 Proposal NSPS OOOOb/EG OOOOc RIA.27 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
25 EPA strives to base its analyses on the best available science and economics, consistent with its responsibilities,
for example, under the Information Quality Act.
26 Technical Support Document: Social Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates under
Executive Order 13990 (IWG, 2021)
27 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.28
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, 2023a).
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)29; Climate Framework for Uncertainty, Negotiation, and Distribution
(FUND)30; and Policy Analysis of the Greenhouse Gas Effect (PAGE)31. 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 and judgments. That is, the representation of
28 https://www.epa.gov/environmental-economics/scghg-tsd-peer-review
29 Nordhaus, 2010
30 Anthoff & Tol, 2013a, 2013b
31 Hope, 2013
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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, 2023a), 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.32 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., IWG2010, 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,
32 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). Supplementary Material for the Regulatory Impact
Analysis for the Final Rulemaking, "Standards of Performance for New, Reconstructed, and Modified Sources
and Emissions Guidelines for Existing Sources: Oil and Natural Gas Sector Climate Review": EPA Report on the
Social Cost of Greenhouse Gases: Estimates Incorporating Recent Scientific Advances. Washington, DC: U.S.
EPA for more details.
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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
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:
1. 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),
2. 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
3. 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
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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 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.33 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 CO2, CH4, and
N2O.34
33 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.
34 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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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
damages that pre-date CIL and RFF's research initiatives.35 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
35 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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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
in equivalent units of consumption and to discount them at the rate consumers and savers would
normally use in discounting future consumption benefits" (OMB, 2003).36 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.37
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
36 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).
37 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 (2023) (OMB 2023).
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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-
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 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
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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
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 proposed 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
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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-
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 $2,400 per metric ton of
methane emissions in 2030 (McDuffie et al., 2023). In addition, the SC-CH4 estimates do not
reflect that methane emissions lead to a reduction in atmospheric oxidants, like hydroxyl
radicals, nor do they account for impacts associated with CO2 produced from methane oxidizing
in the atmosphere. Importantly, the updated SC-GHG methodology does not yet reflect
interactions and feedback effects within, and across, Earth and human systems. For example, it
does not explicitly reflect potential interactions among damage categories, such as those
stemming from the interdependences of energy, water, and land use. These, and other,
interactions and feedbacks were highlighted by the National Academies as an important area of
future research for longer-term enhancements in the SC-GHG estimation framework.
Tables 6-2 through 6-4 present the undiscounted annual monetized climate benefits under
the WEC proposal. Projected methane emissions reductions each year are multiplied by the SC-
CH4 estimate for that year. Table 6-5 shows the annual climate benefits discounted back to 2023
and the PV and the EAV for the 2024-2035 period under each discount rate. In this analysis, to
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calculate the present and annualized values of climate benefits, EPA uses the same discount rate
as the near-term target Ramsey rate used to discount the climate benefits from future CH4
reductions. That is, future climate benefits estimated with the SC-CH4 at the near-term 2 percent
Ramsey rate are discounted to the base year of the analysis using the same 2 percent rate.38
Table 6-1 Undiscounted Monetized Climate Benefits from Methane Mitigation under
the WEC Proposal, 2024-2035 (millions, 2019$)
Near-Term Ramsey Discount Rate (Annual Undiscounted)
Year
1.5%
2%
2.5%
2024
$390
$290
$220
2025
$800
$590
$470
2026
$1,300
$980
$770
2027
$14
$10
$8
2028
$14
$11
$8
2029
$15
$11
$9
2030
$15
$11
$9
2031
$15
$12
$9
2032
$16
$12
$10
2033
$16
$13
$10
2034
$17
$13
$11
2035
$17
$13
$11
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
38 As discussed in U.S. EPA. (2023a). Supplementary Material for the Regulatory Impact Analysis for the Final
Rulemaking, "Standards of Performance for New, Reconstructed, and Modified Sources and Emissions
Guidelines for Existing Sources: Oil and Natural Gas Sector Climate Review EPA Report on the Social Cost of
Greenhouse Gases: Estimates Incorporating Recent Scientific Advances. Washington, DC: U.S. EPA, the error
associated with using a constant discount rate rather than the certainty-equivalent rate path to calculate the present
value of a future stream of monetized climate benefits is small for analyses with moderate time frames (e.g., 30
years or less). Ibid, also provides an illustration of the amount that climate benefits from reductions in future
emissions will be underestimated by using a constant discount rate relative to the more complicated certainty-
equivalent rate path.
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Table 6-2 Undiscounted Monetized Climate Benefits from Partial Equilibrium Model
under the WEC Proposal, 2024-2035 (millions, 2019$)
Year
Near-Term Ramsey Discount Rate (Annual Undiscounted)a
1.5%
2%
2.5%
2024
$0.3
$0.3
$0.2
2025
$0.4
$0.3
$0.2
2026
$5.6
$4.2
$3.3
2027
$0.1
$0.1
$0.1
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
$0.1
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
Table 6-3 Undiscounted Total Monetized Climate Benefits under the WEC Proposal,
2024-2035 (millions, 2019$)
Near-Term Ramsey Discount Rate (Annual Undiscounted)3
Year
1.5%
2%
2.5%
2024
$390
$290
$220
2025
$800
$590
$470
2026
$1,300
$990
$780
2027
$14
$10
$8
2028
$14
$11
$9
2029
$15
$11
$9
2030
$15
$11
$9
2031
$16
$12
$10
2032
$16
$12
$10
2033
$17
$13
$10
2034
$17
$13
$11
2035
$17
$14
$11
Note: Estimates may not sum due to independent rounding.
a Climate benefits are based on changes (reductions) in CH4 emissions and are calculated using updated estimates of
the SC-CH4 from U.S. EPA (2023a).
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Table 6-4 Discounted Monetized Climate Benefits under the WEC Proposal, 2024-2035
(millions, 2019$)
Discounted back to 2023a
Year
1.5%
2%
2.5%
2024
$380
$280
$220
2025
$780
$570
$440
2026
$1,300
$930
$720
2027
$13
$10
$7
2028
$13
$10
$8
2029
$13
$10
$8
2030
$14
$10
$8
2031
$14
$10
$8
2032
$14
$10
$8
2033
$14
$10
$8
2034
$14
$11
$8
2035
$15
$11
$8
PV
$2,600
$1,900
$1,500
EAV
$230
$180
$140
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 proposed 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 proposed 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)
that states when a regulation is likely to have international effects, "these effects should be
reported".39 EPA also notes that EPA's cost estimates in RIAs, including the cost estimates
39 While OMB Circular A-4 (2003) recommends that international effects be reported separately, the guidance also
explains that "[d]ifferent regulations may call for different emphases in the analysis, depending on the nature and
complexity of the regulatory issues." (OMB 2003). Circular A-4 (2023) states that "In certain contexts, it may be
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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.40 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 (IWG 2010, 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 Final Oil and Gas NSPS OOOOb/EG OOOOc 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
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
particularly appropriate to include effects experienced by noncitizens residing abroad in your primary analysis.
Such contexts include, for example, when:
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).
40 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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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 Supplemental Proposal NSPS
OOOOb/EG OOOOc RIA 41 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,
public health, and humanitarian concerns. Those impacts point to the global nature of the climate
41 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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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
proposed rule. The EPA disagrees with commenters on the 2022 Supplemental NSPS
OOOOb/EG OOOOc proposal who suggest 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 for example through the movement of refugees.
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
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,
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2021a).42 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.43 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
42 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.
43 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). Supplementary Material for the Regulatory Impact
Analysis for the Final Rulemaking, "Standards of Performance for New, Reconstructed, and Modified Sources
and Emissions Guidelines for Existing Sources: Oil and Natural Gas Sector Climate Review": EPA Report on the
Social Cost of Greenhouse Gases: Estimates Incorporating Recent Scientific Advances. Washington, DC: U.S.
EPA, 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).
Taken together, applying the U.S.-specific partial SC-CH4 estimates derived from the
evidence described above to the CH4 emissions reduction expected under the WEC proposal
would yield substantial benefits. For example, the present value of the climate benefits of the
proposed rule as measured by FrEDI using additional U.S.-specific data and research on climate
change impacts in CONUS are estimated to be $510 million (under a 2 percent near-term
Ramsey discount rate).44 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 proposed 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 proposed 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, 2013). Recent observational and modeling
44 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 from oil and natural gas operations can impact ozone
levels. 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
proposed 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 proposal. To more definitively analyze the impacts
of VOC reductions from this proposed 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). These health effects include
respiratory morbidity, such as asthma attacks, hospital and emergency department visits, lost
school days, and premature respiratory mortality. The scientific literature is also suggestive that
exposure to ozone is associated with chronic respiratory damage and premature aging of the
lungs.
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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
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
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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.
6.2.3 PM2.5-RelatedImpacts Due to VOC Emissions
This proposed 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 PM2.5-
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, 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
PM2.5-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.
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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).
When the EPA quantifies PIVh.s-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.
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
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.
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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 2017
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).
6-26
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Table 6-5 Top Annual HAP Emissions as Reported in 2017 NEI for Oil and Natural
Gas Sources
Pollutant
Nonpoint Emissions
(tons/year)
Point Emissions (tons/year)
Benzene
26,869
502
Xylenes (Mixed Isomers)
25,410
506
Formaldehyde
23,413
222
Toluene
18,054
823
Acetaldehyde
2,722
26
Hexane
2,675
886
Ethyl Benzene
2,021
113
Acrolein
1,602
18
Methanol
1,578
342
1,3-Butadiene
337
5.80E-01
2,2,4-Trimethylpentane
252
46
Naphthalene
104
1.10E+00
Propionaldehyde
102
0.00E+00
PAH/POM - Unspecified
68
2.50E-02
1,1,2-Trichloroethane
25
1.40E-03
Methylene Chloride
22
8.70E-02
1,1,2,2-Tetrachloroethane
14
1.90E-03
Ethylene Dibromide
13
1.90E-03
Methyl Tert-Butyl Ether
0
17.30
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 proposed WEC. The EPA remains
committed to improving methods for estimating HAP benefits by continuing to explore
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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
In 1989, the EPA classified formaldehyde as a probable human carcinogen based on
limited evidence of cancer in humans and sufficient evidence in animals (U.S. EPA, 1991b).
Later 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). Formaldehyde 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
6-28
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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).
6.2.4.3 Toluene45
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,
decreased performance in neurobehavioral analysis, changes in motor and sensory nerve
conduction velocity, headache, and dizziness) as the most sensitive endpoint.
45 All health effects language for this section came from: U.S. EPA (2005b).
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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 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. 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 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
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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 Air 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.46
46 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 proposed Waste Emissions Charge. The
monetized benefits presented are climate benefits calculated using the social cost of methane.
The costs presented are engineering costs of methane mitigation technologies 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 47 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
this proposal.
47 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.
7-1
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Table 7-1 Projected Emissions Reductions from the Proposed Waste Emissions Charge,
2024-2035
Proposal
Total
Emission Changes
Methane
(thousand metric
tons)
960
voc
(thousand metric
tons)
140
HAP
(thousand metric
tons)
Methane
(million metric tons
C02 Eq. using
GWP=28)
27
Table 7-2 Projected Benefits and Costs from the Proposed Waste Emissions Charge
(million 2019$)
2 Percent Near-Term Ramsey Discount Rate
PV EAV PV EAV PV EAV
Monetized Climate Benefits3
$1,900
$180
$1,900
$180
$1,900
$180
2 Percent
3 Percent
7 Percent
Discount Rate
Discount Rate
Discount Rate
PV
EAV
PV
EAV
PV
EAV
Total Social Costs
$390
$37
$380
$38
$340
$43
Cost of Methane Mitigation
$360
$34
$350
$35
$320
$40
Cost of Energy Market
$30
$3
$29
$3
$26
$3
Impacts
Net Benefits
$1,500
$140
$1,500
$140
$1,600
$140
Ozone benefits from reducing 960 thousand metric tons of methane from
2024 to 2035
PM2.5 and ozone health benefits from reducing 140 thousand metric tons of
VOC from 2024 to 2035
Non-Monetized Benefits
HAP benefits from reducing 5 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. Table 7-4 provides the net benefits
7-2
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calculated from this rule and the corresponding present value and equivalent annualized value
(EAV) discounted to the year 2023 using discount rates of 2, 3, and 7 percent.
Table 7-3 Projected Annual Emissions Reductions from the Proposed Waste Emissions
Charge (thousand metric tons)
Methane
voc
HAP
Year
Mitigated
Market-
Induced
Total
Mitigated
Market-
Induced
Total
Mitigated
Market-
Induced
Total
2024
150
0.1
150
23
0.0
23
0.9
0.0
0.9
2025
300
0.1
300
45
0.0
45
1.7
0.0
1.7
2026
470
2.0
480
71
0.3
72
2.6
0.0
2.7
2027
5
0.0
5
0.7
0.0
0.7
0.03
0.0
0.03
2028
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2029
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2030
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2031
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2032
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2033
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2034
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
2035
5
0.0
5
0.5
0.0
0.5
0.0
0.0
0.0
Total
960
2.6
960
140
0.4
140
5.3
0.0
5.3
7-3
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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 This Rule (millions of 2019$,
discounted to 2023)
Year
Climate
Benefitsa
(2%DR)
Total Social Costs
($MM)
Net Benefits (2% Benefits)
2024
$290
$51
$240
2025
$590
$110
$490
2026
$990
$240
$740
2027
$10
$0
$10
2028
$11
$0
$11
2029
$11
$0
$11
2030
$11
$0
$11
2031
$12
$0
$12
2032
$12
$0
$12
2033
$13
$0
$13
2034
$13
$0
$13
2035
$14
$0
$14
Discount
Rate
2%
2%
3%
7%
2%b
3%b
7%b
PV
$1,900
$390
$380
$340
$1,500
$1,500
$1,600
EAV
$180
$37
$38
$43
$140
$140
$140
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
7-4
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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 development of innovative technologies in the detection and mitigation of
methane emissions. See 168 Cong. Rec. E869 (August 23, 2022) (statement of Rep. Frank
Pallone). CAA section 136(a) and (b) provides $1.55 billion to, among other things, help finance
the early adoption of emissions reduction methodologies and technologies and to support
monitoring of methane emissions. 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.48 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
compare projected WEC payments to climate damages from emissions subject to the WEC,
48 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 $1,500.
7-5
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WEC payments are converted from nominal dollars to 2019 constant dollars using a chain-
weighted GDP price index from the 2023 Annual Energy Outlook.
Table 7-5 Details of Projected WEC Obligations and Climate Damages from Emissions
Subject to WEC (million 2019$)
Year
Methane
Emissions
Subject to
WEC 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)
Climate
Damages
from
Emissions
Subject to
WEC (million
2019$)a
2024
830
$900
$750
$620
$1,900
$1,600
2025
650
$1,200
$770
$630
$2,000
$1,300
2026
430
$1,500
$640
$510
$2,100
$890
2027
9
$1,500
$13
$10
$2,200
$18
2028
9
$1,500
$13
$10
$2,200
$19
2029
9
$1,500
$13
$10
$2,300
$20
2030
9
$1,500
$13
$9
$2,400
$20
2031
9
$1,500
$13
$9
$2,500
$21
2032
9
$1,500
$13
$9
$2,500
$21
2033
9
$1,500
$13
$9
$2,600
$21
2034
9
$1,500
$13
$8
$2,700
$21
2035
9
$1,500
$13
$8
$2,800
$21
Total
2024-
2035
2,000
-
$2,300
$1,800
-
$4,000
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 proposed 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 is currently undertaking several other actions that impact
methane emissions from the oil and natural gas industry. In particular, the WEC has important
interactions with revisions to GHGRP Subpart W and the NSPS OOOOb and EG OOOOc for the
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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.
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 proposal. 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 2021 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.
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.
Additional information on the mitigation technologies characterized in the analysis is available in
Appendix C to this RIA.
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.
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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.
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8 UNCERTAINTY ANALYSES
8.1 Sensitivity on GHGRP Calculation Methods
On August 1, 2023, the EPA proposed revisions to the requirements of Subpart W
consistent with directives in the Inflation Reduction Act (referred to in this section as the 2023
Subpart W proposal). The 2023 Subpart W proposal includes a number of proposed changes that
could significantly 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 may result in additional reporters to GHGRP Subpart W which have not reported
in past years.
EPA does not currently have a quantitative estimate of expected emissions reporting
inclusive of all of these proposed revisions. Some qualitative factors in how they will influence
reported emissions and the results of this RIA are discussed below.
New emissions sources. 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 which facilities will report those emissions.
Changes to emissions factors. Changes to emissions factors have complicated potential
effects. For example, the 2023 Subpart W proposal significantly increases the emissions factors
used for the population method for equipment leaks in onshore production and gathering and
boosting. In RY 2021, most facilities and equipment leak emissions were calculated using the
population method. If we assume that these reporters continue to use the population method, then
their reported emissions would increase significantly. 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
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increase the economic incentive to perform equipment leak monitoring and repair and to report
using other calculation methods for fugitives. In addition, EPA expects that as more oil and
natural gas operations become subject to fugitive monitoring requirements under the NSPS
OOOOb/EG OOOOc that more facilities will switch to other calculation methods for equipment
leaks. For other source categories, switching between methods may be less important. For
example, switching between methods is less likely in the case of combustion slip emissions, and
so the proposed increase in emissions factors related to combustion slip is likely to lead to higher
reported methane emissions.
New reporting methods. It is particularly uncertain what emissions will be reported using
new calculation methods utilizing site- or reporter-specific measurements. Measurements or
reporter-specific data might lead to significantly higher or lower emissions than would have been
calculated under other methods. When choosing whether to report using a reporter-specific
measurement or using a default emissions factor, reporters are expected to choose calculation
approaches that minimize WEC obligations. Thus, holding other calculation methods constant,
the addition of optional measurement methods is likely to reduce reported emissions and WEC
obligations. However, in some 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, they are required to report
leaks found through those surveys. For the purpose of estimating WEC obligations, EPA would
further need to make assumptions about how measurements would affect the distribution of
reported emissions by individual facilities in relation to throughput. Measurements may vary
significantly between different oil and natural gas operators, making it infeasible to estimate the
impact of these methods on potential WEC obligations.
New reporters. Several proposed changes in 2023 Subpart W proposal and the 2023
GHGRP supplemental proposal which included revisions to general provisions may result in
additional reporters who have not been required to report to GHGRP in the past. For example,
the GHGRP supplemental proposal includes an increase in GWP of methane from 25 to 28, and
may lead more oil and natural gas facilities to exceed the 25,000 C02e reporting threshold.
Similarly, the addition of new reporting source categories may bring facilities that were
previously below the reporting threshold above 25,000 metric tons C02e. New reporting
facilities would increase the overall baseline used in this RIA, but information on the emissions
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intensity of these new reporters is unavailable. Even if total reported methane to Subpart W
increases, total WEC-applicable emissions may not be increased significantly.
8.2 Sensitivity on Interaction with NSPS/EG
The WEC has important interactions and is designed to complement the Oil and Gas
NSPS OOOOb and EG 0000c. Because of these interactions, the requirements and
implementation of the NSPS OOOOb/EG 0000c influence the reductions and impacts of the
proposed WEC. To the extent that oil and natural gas companies implement strong emissions
controls because of requirements in the NSPS OOOOb/EG 0000c, emissions reductions
resulting from the WEC and WEC obligations would be lower than if less stringent emissions
controls were required under the NSPS OOOOb/EG 0000c. To the extent that NSPS
OOOOb/EG 0000c 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 December 2023. 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 0000c includes requirements for
existing sources, which are to be implemented by the states via state regulations and state
implementation plans.
There is significant overlap in both the oil and natural gas operations subject to the WEC
and the NSPS OOOOb/EG 0000c and the emissions reduction measures that could be taken to
avoid WEC obligations and those potentially required under the NSPS OOOOb/EG 0000c. On
the one hand, the scope of operations impacted by the WEC is a subset of those affected by the
NSPS OOOOb and EG 0000c because the WEC applies only to facilities reporting more than
25,000 tons C02e to Subpart W and which exceed waste emissions threshold levels with respect
to intensity. On the other hand, the scope of equipment and emissions sources affected by the
NSPS OOOOb and EG 0000c is a subset of the reported emissions sources and equipment for
which GHGRP facilities report methane emissions.
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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 2021 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 2021 (EIA, 2022). Because GHGRP
reporters skew towards higher-production wells, the proportion of total emissions or 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 proposed WEC and the
NSPS OOOOb/EG OOOOc.
With respect to overlap in emissions sources and mitigation actions relevant to both the
WEC and the NSPS OOOOb/EG OOOOc, 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 OOOOb/EG OOOOc 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
reported to Subpart W.
Because the WEC and Oil and Gas NSPS OOOOb/EG OOOOc 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 OOOOb/EG OOOOc, the expected emissions reductions (and costs)
resulting from the WEC would be expected to be lower.
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9 DISTRIBUTIONAL AND ECONOMIC ANALYSES
9.1 Small Business Analysis
9.1.1 Backgroundfor Small Entity Impacts
The EPA evaluated the impacts of the proposed revisions where it identified small
entities could potentially be affected and considered whether additional measures to minimize
impacts were needed. In evaluating the impacts of the proposed revisions, 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 WEC
Entity level to account for netting of emissions from facilities under common ownership or
control. 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 proposed rule would have a significant economic impact on a
substantial number of small entities, the EPA evaluated the costs of the proposed rule on small
entities identified in the RY 2021 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 2021 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. Reported 2021 ownership structures were therefore held constant for
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the small entity impact analysis. Revisions were made to the RY 2021 data to project RY 2024
methane intensity at the facility level. These include:
Methane emissions data were projected forward from 2021 to 2024 using the 2016-2021
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 2021 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 reported or solicited
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 2021 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 proposal
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 2021 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 468 of 472 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
(SBA) 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 proposed 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 proposed 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 appropriate segment-specific
methane intensity threshold 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 segment-specific 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 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.
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 Parties. Estimated CRR were calculated for each WEC Obligated Parties by dividing
total WEC costs by reported revenue data.
Revenue data were not found for two WEC Obligated Parties. These entities had net
methane tons of less than zero tons, and thus would not be subject to the WEC and would have
CRR of zero; revenue data were therefore not needed for these WEC Obligated Parties.
9.1.3 Results and Conclusions of Small Entity Impacts Analysis
The number of small entities potentially affected by the proposed WEC regulation were
estimated based on the information collected for 785 WEC Obligated Parties. Of these, 439 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
785
Small Entity WEC Obligated Parties
439
Number of Small Entities with a CRR >1%
101
Percent of Small Entities with a CRR >1%
21%
Number of Small Entities with a CRR >3%
76
Percent of Small Entities with a CRR >3%
17%
After considering the economic impact of the proposed rule on small entities, EPA has
concluded that the proposed rule costs would not likely have a significant impact on a substantial
number of small entities. Although the screening analysis suggests that some small entities may
have cost-to-revenue ratios that exceed 3%, the 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. For example, 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 SB A size
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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 cost 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. As result, the total compliance cost 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.
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 compliance costs 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
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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 proposed 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).49 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.
Table 9-2 Employment in Oil and Gas Sectors (2022)
NAICS
Sector
Employment (thousands)
2111
Oil and gas extraction
119.3
486210
Pipeline transportation of natural gas
31.1
221210
Natural gas distribution
112.8
Total
263.2
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
49 Retrieved from FRED: IPUCN221210W200000000 (221210), IPUIN486210W200000000 (486210),
IPUBN2111U121000000 (2111)
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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).50 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.51
Table 9-3 Labor Compensation in the Oil and Gas Sector (2022)
NAICS
Sector
Total Labor Compensation
Total Compensation
(billions)
per Worker
(thousands)
2111
Oil and gas extraction
$30.2
$253.3
221210
Natural gas distribution
$18.4
$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 $195.6
thousand in 2012 to $253.3 thousand in 2022. Total labor compensation in natural gas
distribution has risen from $13.4 billion in 2012 to $18.4 billion in 2022, and compensation per
worker has risen from $122.6 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.52 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%. Output has risen sharply in 2021 and 2022, from an
50 Retrieved from FRED: IPUBN2111L020000000 (2111), IPUCN221210L020000000 (221210)
51 https://data.census.gov/table?q=aH+sectors:+summarv+statistics&v=2012&n=N0600.00
52 https://www.bls.gov/prodnctlvitv/tables/ see labor productivity and costs measures, detailed industries.
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average of approximately $100 billion per year for distribution over the period 2012-2020 to
$200 billion in 2022. Similarly, oil and gas extraction, while varying more over 2012-202 from
$200-400 billion, was $650 billion in 2022.
9.2.2 Employment Impacts
This section presents preliminary analysis of potential employment impacts of the
proposed 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 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 ise
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, because employment is an important economic issue, we identify
the value of certain employment supported by abatement expenditures.
This analysis estimates the value of 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
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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
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
Natural Gas Distribution
486210
221210
1.11
0.91
Gathering,
Boosting,
Transmission, &
Storage (GBTS)
1.0
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 200 jobs in 2024 up to about 500 jobs in
2026. Capital and O&M expenditures from the MACC analysis and output changes 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 33 jobs in 2026 and with none in the remainder of the analysis period.
Total jobs supported are about 200 in 2024, rising to about 600 in 2026, and dropping to zero in
9-11
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the later years of the analysis period. Note that job impact estimates are based on employment
(i.e., the number of people working in an industry), not full-time equivalent jobs.
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
$39.4
107
$16.9
72
-$13.3
-7
$24.6
25
-$3.8
-2
195
2025
$74.2
202
$31.8
135
-$19.2
-10
$55.7
56
-$4.2
-2
381
2026
$117.8
320
$50.5
215
$19.4
10
$82.9
84
-$59.5
-33
596
2027
$0.0
0
$0.0
0
$0.9
0
$0.0
0.0
-$1.3
-1
0
2028
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.3
-1
0
2029
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.2
-1
0
2030
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.2
-1
0
2031
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.2
-1
0
2032
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.2
-1
0
2033
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.1
-1
0
2034
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.1
-1
0
2035
$0.0
0
$0.0
0
$0.9
0
$0.0
0
-$1.1
-1
0
9.3 Environmental Justice
9.3.1 Introduction and Background
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.53 Executive Order 14008 (86 FR 7619; January 27, 2021) also
53 Fair treatment occurs when "no group of people should bear a disproportionate burden of environmental harms and risks,
including those resulting from the negative environmental consequences of industrial, governmental, and commercial
9-12
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calls on Agencies to make achieving environmental justice part of their missions "by developing
programs, policies, and activities to address the disproportionately high and adverse human
health, environmental, climate-related and other cumulative impacts on disadvantaged
communities, as well as the accompanying economic challenges of such impacts." It also
declares a policy "to secure environmental justice and spur economic opportunity for
disadvantaged communities that have been historically marginalized and overburdened by
pollution and under-investment in housing, transportation, water and wastewater infrastructure
and health care." EPA also released its "Technical Guidance for Assessing Environmental
Justice in Regulatory Analysis" (U.S. EPA, 2016) to provide 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
operations or programs and policies" (U.S. EPA, 2011). Meaningful involvement occurs when " 1) potentially affected
populations have an appropriate opportunity to participate in decisions about a proposed activity [i.e., rulemaking] that will
affect their environment and/or health; 2) the population's contribution can influence [the EPA's] rulemaking decisions; 3) the
concerns of all participants involved will be considered in the decision-making process; and 4) [the EPA will] seek out and
facilitate the involvement of population's potentially affected by EPA's rulemaking process" (U.S. EPA, 2015). A potential
environmental justice concern is defined as "actual or potential lack of fair treatment or meaningful involvement of
communities with environmental justice concerns in the development, implementation and enforcement of environmental
laws, regulations and policies" (U.S. EPA, 2015). See also https://www.epa.gov/environmentaljustice.
9-13
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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 563 counties with methane emissions expected to be affected by the WEC,
using the most recent available data. This enables us to characterize communities that in these
counties prior to implementation of the proposed rule. We lack key information that we would be
needed to assess post-control risks (the "policy" scenario as described above) under the proposed
WEC or the regulatory alternatives analyzed in this RIA. Therefore, the extent to which this
proposed rule will affect potential EJ outcomes is not quantitatively evaluated.
This proposed action chronologically follows the Supplemental Proposal for the
Standards of Performance for New, Reconstructed, and Modified Sources and Emissions
Guidelines for Existing Sources: Oil and Gas Sector (NSPS OOOOb/EG OOOOc, hereafter;
(U.S. EPA, 2022c). The RIA for the 2022 Supplemental NSPS OOOOb/EG OOOOc proposal
presented a detailed environmental justice analysis of health risks and economic activity
associated with the oil and gas industry. EPA expects the WEC implications for environmental
justice to be similar to that of the NSPS OOOOb/EG OOOOc rule, as the sources potentially
affected by the proposed rule are a subset of those affected by the NSPS OOOOb/EG OOOOc
rule, but the projected methane emissions reduction is smaller in magnitude. Time and resource
constraints prevent the replication of the series of analyses conducted for the NSPS OOOOb/EG
OOOOc. This chapter presents a summary of the NSPS OOOOb/EG OOOOc findings that are
expected to be relevant to the current proposal, in addition to presenting a baseline analysis of
communities proximate to potentially affected sources. In addition to demographic and health
risk indicators addressed by the NSPS OOOOb/EG OOOOc RIA, this analysis shows results for
two additional health indicators. This chapter does not address the full range of issues analyzed
in the 2022 Supplemental NSPS OOOOb/EG OOOOc RIA. The final NSPS OOOOb/EG
OOOOc RIA uses an approach different from the analysis of these issues from the supplemental
RIA.
9-14
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The scope of this analysis is to present a "snapshot" of the characteristics of the
communities in these counties and the quantified risks these communities currently face,
compared to the national average.
9.3.3 Summary Environmental Justice Findings of the NSPS OOOOb/EG OOOOc RIA
9.3.3.1 Ozone from Oil and Natural Gas VOC Emission Impacts
The 2022 Supplemental NSPS OOOOb/EG OOOOc RIA presented an evaluation of the
EJ implications of ozone from VOC emissions from the oil and natural gas sector. Analysis of a
baseline (pre-control) air quality scenario comparing exposures to ozone formed from VOC
emissions from the oil and natural gas sector across races/ethnicities, ages, and sexes. The NSPS
OOOOb/EG OOOOc RIA analysis focused comparing exposure differences to determine if risks
unequally distributed among population subgroups of interest.
The NSPS OOOOb/EG OOOOc RIA baseline ozone concentration results showed that
Native American populations on average may be exposed to a slightly higher concentration of
ozone from oil and natural gas VOC emissions than White populations, who, in turn, may on
average be exposed to a higher concentration than the overall average for adults of all
races/ethnicities and sexes aged 30-99. Similarly, the analysis suggests that Hispanic populations
on average are exposed to a slightly higher concentration of ozone from oil and natural gas VOC
emissions than both non-Hispanic individuals and the overall average for adults of all
races/ethni cities and sexes aged 30-99.
The NSPS OOOOb/EG OOOOc RIA concluded that because of expected reductions in
methane emissions, the rule would also contribute to the slight reductions in formation of ground
level ozone, with attendant benefits for human health.
For the present proposed Rule, we are not updating the NSPS OOOOb/EG OOOOc RIA
analysis, and do not quantify the benefit of this reduction in risk for individual communities.
However, we expect this Rule to contribute further reductions in emissions and additional
improvements to outcomes for environmental justice communities.
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9.3.3.2 Air Toxics Analysis
For the analysis of the environmental justice impacts of the NSPS OOOOb/EG OOOOc
Rule on air toxics exposure, the RIA assessed cancer risks from EPA emissions inventories and
air modeling. The emissions identified were primarily (97%) non-point sources, and these were
modeled essentially as evenly geographically dispersed in across the area of the source county,
the RIA provided the caveat that this assumption about the location of these emissions may not
be accurate. Additionally, the National Emissions Inventory database for emissions for the oil
and gas sector included both sources that would be affected by the regulation, and sources that
would not be affected.
The RIA conducted modeling at the level of census block groups and the EPA
AEROMOD 4km2 grid (9km2 grid for Alaska) for the non-point sources and the 3% of sources
(approximately 400 individual point sources) and found the incremental risk due to oil and gas
emissions was less than 1 in 1 million for 90 percent of the census blocks with oil and gas
emissions. The modeling identified 122 census blocks (with approximately 140,000 people)
exposed to risks greater than 50 in 1 million, and 36 census blocks (with approximately 36,000
people) with risks higher than 100 in 1 million.
Of the racial and ethnic minority population identified to be exposed to elevated risks
from oil and gas air toxics emissions, Native Americans and those over 64 years old were over-
represented (compared to the national average population) but not at the highest exposure levels.
People identifying as Hispanic or Latino and ages 0-17 were over-represented in census blocks
exposed to the highest risk.
9.3.3.3 Summary of Employment Analysis
In assessing the environmental justice impacts of the NSPS OOOOb/EG OOOOc
proposal, the RIA considered the impacts of potential 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. Oil and gas workers disproportionately identify as
White, and have higher income than the national average, but racial and ethnic minorities, are
9-16
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disproportionately represented in oil and gas communities. The RIA also notes large historical
swings in oil and gas employment.
9.3.3.4 Summary of Household Expenditures Analysis
The 2022 Supplemental NSPS OOOOb/EG OOOOc RIA analyzes energy expenditures
by income quintile and by marginalized groups. 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 OOOOb/EG OOOOc rule is unlikely to have a
significant impact on energy prices, and, therefore, that it was unlikely to exacerbate pre-existing
energy burden inequality.
The proposed WEC is expected to be similarly unlikely to affect energy prices, and,
therefore, is not likely to exacerbate energy burden inequality.
9.3.4 Environmental Justice Analysis of the Proposed 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 2021 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
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 563 counties where Onshore Petroleum and Natural Gas
Production and/or Onshore Petroleum and Natural Gas Gathering and Boosting facilities with
emissions that may be above the waste emissions threshold and therefore subject to the WEC
9-17
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(see Section 4) operated in 2021. These are the counties where emissions might change due to
the WEC. See Figure 9-1.
I I State boundaries
Counties with 2021 CH4 emissions
above the WEC intensity threshold
I I Low
~ Medium
High
Very High
Alaska
Hawaii
"o
<3
&
Figure 9-1 Map of the counties identified as having emissions from facilities that are
expected to owe the Waste Emissions Charge
As noted above, the analysis in this section is focused on baseline conditions prior to
implementation of the proposed rule. Again, we are not able to assess how the proposed 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 proposal may not impact all locations with oil and natural gas emissions equally, in part
9-18
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due to differences in existing state regulations in locations like Colorado and California, which
have more stringent requirements.
For these counties, we are able to 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
baseline data for counties with the emissions to data for counties likely to be affected by the
WEC to national averages for the demographic and risk categories. Note that this comparison
does not perfectly 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. 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
(2021) American Communities Survey (ACS) published by the Census Bureau. This data was
gathered from 2017-2021. We use the 2021 "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. "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, 2023b).
Emissions from the 563 counties 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 indicators for each category
9-19
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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
<1-643
<60*
339
6%
Medium
643 - 2,329
OS
0
s-
1
00
o
B-
109
13%
High
2,329 - 7,863
80^-95^
83
32%
Very High
7,863 - 50,540
>95*
29
49%
These results show that the emissions vary widely, and that the highest emitting counties
account for a disproportionate fraction of the total. The top 29 counties, representing 5% of the
of the group, contribute nearly 50% of the methane emissions. Emissions from the 339 low
emissions counties contributes 6 percent of the total. Figure 9-2 shows emissions from all 563
counties ranked from lowest total annual emissions to highest.
9-20
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50,000
40,000
c
.2 30,000
i 20,000
<
10,000
ooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
*Hr\im^i-Lr»i£)r,sooaio*HrMro'd-LOU3r^cx)CTio*H(NrO'^-Lnu3rvoocTio*HrMro'^-LOiDr^oocT)OTH(Nro'd-i-ou3rs.ooCTio*HrMro'^-LOU3
TH*H*HTHTHTH*HrHTHTHr«jrMrsirsirMfNrsiLnLOLnLn
Individual County Emissions by Rank
Figure 9-2 Individual County Emissions Ranked from Lowest 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. Additionally, 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.
Moreover, many communities in these counties face risks from atmospheric emissions from
outside of their county boundaries. It is important to note that these results are averages, and
circumstances for communities in individual counties can be very different from the average
risks we can show with this data.
9-21
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9.3.5 Aggregate Average Conditions for Potentially Affected Counties
The data shown in Table 9-7 are taken for each country from the most recent government
datasets. The demographic data is from the 2021 American Communities Survey (US Census,
2023). The Total Cancer Risk and Total Respiratory Risk are from the EPA AirToxScreen 2019
database (EPA, 2022d). 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
"PLACES" Dataset (CDC, 2022). 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 563 counties identified as having
emissions potentially subject to the WEC. The Low Emissions column averages are for the 339
counties with annual methan emissions less than 643 metric tons. The Medium Emissions
column shows the indicator averages for the 109 counties with emissions between 643 and 2,329
metric tons. The 83 counties represented in the High Emissions column have emissions between
2,329 and 7,863 metric tons, and the Very High Emission column represents the 29 counties with
reported emissions above 7,863 tons (the county with the highest emissions potentially subject to
the WEC has reported emissions of 50,540 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 OOOOb/EG OOOOc 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 (10.6) again in the 29 "Very High Emissions" counties. Native Americans
populations are disproportionately represented in these counties - increasingly more so in
counties in the higher the emissions category.
While the median household income for these counties is generally lower than the
national average, it is higher than the national average in the 29 counties with the highest
9-22
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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,
there are fewer households with low and very low incomes in the counties with the highest
emissions.
Table 9-7 Overall Demographic and Health Indicators for All Counties, by Category
All
Low
Medium
High
Very High
Polenlial
Emissions
Emissions
Emissions
Emissions
National
\\l(
(<60th
(60th - 80th
(80th-95th
(>95th
Average
( on ill ios
percentile)
percentile)
percentile)
percentile)
% White (race)
68.1
(>5 1
62.5
76.9
73.3
66.6
% Black or African
American (Race)
12.6
1 1 1
12.1
9.0
4.3
10.6
% Native American
0.80
0 K)~
0.88
0.83
1.3
1.8
(Race)
% Other (Race)
19.3
2' "
25.4
14.2
22.3
22.8
% Hispanic (Ethnicity)
18.4
5
26.3
14.5
42.5
31.7
Median Household
72.3
/ V ¦)
68.6
67.0
57.7
76.5
Income (lk 2019$)
(»«V _
% Below Poverty Line
6.7
7.7
7.1
9.7
6.2
% Below Half the
Poverty Line
5.6
(t i
6.4
5.8
7.7
5.1
Total Cancer Risk (per
million)
25.6
:_4
27.8
26.1
22.4
28.8
Total Respiratory Risk
(hazard quotient)
0.3 1
(I ^2
0.33
0.29
0.25
0.30
Chronic Asthma
9.8
')
9.9
O Q
O Q
9.4
Prevalence (> 18 yrs)
y.o
y.o
Chronic Heart Disease
5.7
c 11
5.7
6.2
6.6
5.6
Prevalence (> 18 yrs)
With regard to the health indicators from the AirToxScreen and PLACES datasets, there
appears to be a slight elevation across all health categories for the 563 counties compared to the
national averages. However, there does not appear to be a discernable 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 OOOOb/EG
OOOOc RIA: that while ozone and hazardous pollutants from the oil and gas industry are known
9-23
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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.
It is possible, however, that some households in these 563 counties are located in close
proximity to sources of emissions and may face higher than average health risks. This analysis
indicates that these risks are experienced by communities with environmental justice concerns at
a higher percentage. 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, which include environmental
justice communities of concern, that may be affected by the proposed 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 proposed
rule on specific communities. EPA believes, however, that in aggregate the proposed 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 Distributional 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, she 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 Fourth National Climate Assessment (NCA4), "Climate change affects human health by
altering exposures to heat waves, floods, droughts, and other extreme events; vector-, food- and
waterborne infectious diseases; changes in the quality and safety of air, food, and water; and
stresses to mental health and well-being." Many health conditions such as cardiopulmonary or
respiratory illness and other health impacts are associated with and exacerbated by an increase in
GHGs and climate change outcomes, which is problematic as these diseases 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
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exposure to criteria pollutants, in part due to the proximities of highways, trains, factories, and
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
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which children's health and well-being may be impacted by five climate-related environmental
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 Proposed 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 proposed 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. Specifically, this analysis uses the Framework for Evaluating Damages
and Impacts (FrEDI) (U.S. EPA, 2021a) to illustrate how climate-driven impacts at the end of the
century (2090) 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 C for additional information on the FrEDI analysis.
Summary of Changes Across Sectors, Regions, and Populations
Annual net54 climate-driven impacts across all modeled sectors of the U.S. are projected
to decrease as a result of methane emission reductions from the proposed rule. These avoided
damages are associated with national level 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) related mortality55, 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
proposed rule will not be distributed evenly across different geographic regions. 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
54 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 proposed rule.
55 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.
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where different populations currently live. For example, while the largest avoided climate
impacts in each region are associated with reductions in mortality rates from avoided
temperature change, the relative reductions in other sectors are projected to vary by region. For
example, avoided damages from climate-driven air quality related mortality are second largest in
4 of the 7 FrEDI U.S. regions, avoided damages to transportation infrastructure (e.g., rail and
roads) and agriculture are comparatively larger in the Midwest and Northern Plains, and avoided
wildfire damages are comparatively larger in the Northwest and Southwest regions. For other
sectors, impacts are only expected to occur in select regions, such as climate-driven changes in
dust and Valley fever primarily impacting populations living in the Southwest region, and
reductions in tropical wind damage and transportation impacts from high-tide flooding largely
occurring along coastlines of the Southeast, Southern Plains, and Northeast regions.
Lastly, while all populations are also projected to experience a reduction in net climate-
driven impacts from the proposed rule, these avoided impacts will not be evenly distributed
across different 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 ethnicity56), 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 living with low-income 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, Blacks and
African Americans over the age of 65 are more likely to see greater reductions in climate-driven
changes in air quality, while Hispanics and Latinos are more likely to see reductions in lost labor
hours, largely driven by the regional differences in where these populations currently live and
where avoided climate driven changes are projected to occur due to emission reductions in the
proposed rule.
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
56 Based on the data and methodology presented in a recent EPA report on Climate Change and Social Vulnerability
in the United States (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.).
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to provide a snapshot of the different ways U.S. residents are projected to experience fewer
climate-driven impacts as a result of the methane reductions from the proposed WEC. See
Appendix C for detailed discussion of avoided damages across the 22 impact sectors, 7 regions,
and 4 dimensions of social vulnerability included within FrEDI. This distributional 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.
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ANNEXES
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 proposed 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.
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
proposed rule, were used to estimate ozone benefits expected from this proposed 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.
1
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s
Figure A-l Air Quality Modeling Domain
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 every 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
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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
8.8
8.2
17.7
South
145
42.0
43.5
0.73
1.5
8.8
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
3
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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
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
AQS Daily
03 8hrmax NMB (%) for run CAMx_2017icenginesSQ4PRM2US2 for 20170401 to 20170930
4
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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).
5
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Apr-Sep MDA8 03
1 80 159 239 318 397
Min = 0.00E+0 at (1,1), Max = 1.885 at (145,139)
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.
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 proposed policy
scenario (U.S. EPA, 202If, 202lg).
The EPA hi storically 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
pollutant is causally related to an array of adverse human health outcomes associated with either
6
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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. Detailed descriptions of these
updates are available in the TSD for the Final Revised Cross-State Air Pollution Rule for the
2008 Ozone NAAQS Update titled Estimating PM2.5- and Ozone-Attributable Health Benefits
(U.S. EPA, 202lh).
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 each year between 2024 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 year from 2024-2035. Emissions totals for the oil and natural gas sector used
7
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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 2.3. Since values reported in Section 2 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 supplemental proposed rule.
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.
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
8
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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 proposed rule can be adequately represented using this this
linear assumption.
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
9
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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 supplemental proposed 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 Proposal in 2019 Dollars
Benefit-per-ton of Reducing VOC Emissions from the Oil and Natural Gas Sector
Short-term Short-term Long-term Long-term
mortality and mortality and mortality and mortality and
morbidity morbidity morbidity morbidity
(discounted at 3%) (discounted at 7%) (discounted at 3%) (discounted at 7%)
2025 $252 $225 $1,962 $1,753
2030 $272 $244 $2,183 $1,962
2035 $289 $260 $2,425 $2,172
10
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Table A-3 Estimated Discounted Economic Value of Ozone-Attributable Premature
Mortality and Illnesses under the Proposed WEC, 2024-2035 (million
2019$)ad
Proposed WEC
Year
3% Discount Rate
7% Discount Rate
2024
$2.8b to $22°
$2.4b to $19°
2025
$5.4b to $42°
$4.5b to $35°
2026
$8.3b to $64°
$0.6.6b to $51°
2027
$0.080b to $0.62°
$0.06lb to $0.48°
2028
$0.056b to $0.45°
$0.042b to $0.34°
2029
$0.055b to $0.44°
$0.039b to $0.31°
2030
$0.053b to $0.42°
$0.036b to $0.29°
2031
$0.051b to $0.41°
$0.034b to $0.27°
2032
$0.049b to $0.39°
$0.03 lb to $0.25°
2033
$0.050b to $0.42°
$0.03 lb to $0.26°
2034
$0.049b to $0.41°
$0.029b to $0.24°
2035
$0.047b to $0.39°
$0.027b to $ 0.22°
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 Proposed 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
Proposed WEC Option
2024
$22
2025
$42
2026
$64
2027
$0.62
2028
$0.45
2029
$0.44
2030
$0.42
2031
$0.41
2032
$0.39
2033
$0.42
2034
$0.41
2035
$0.39
Present Value (PV)
Equivalent Annualized Value (EAV)
$139
$13
a Benefits calculation includes ozone-related morbidity effects and avoided ozone-attributable deaths quantified
using the Turner et al. (2016) long-term risk estimate.
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b The WEC regulates emissions of methane. Additional benefits to the regulation may result from associated
reductions in VOC emissions.
Table A-5 Stream of Human Health Benefits under the Proposed WEC, 2024-2035:
Monetized Benefits Quantified as Sum of Avoided Morbidity Health Effects
and Avoided Long-term Ozone Mortality (discounted at 7 percent to 2023;
million 2019$)a'b
Year
Proposed WEC Option
2024
$19
2025
$35
2026
$51
2027
$0.48
2028
$0.34
2029
$0.31
2030
$0.29
2031
$0.27
2032
$0.25
2033
$0.26
2034
$0.24
2035
$0.22
Present Value (PV)
Equivalent Annualized Value (EAV)
$108
$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.
References
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source sensitivity and apportionment approaches. Atmospheric Environment, 96, 266-274.
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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
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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:
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Zanobetti, A., & Schwartz, J. (2008). Mortality displacement in the association of ozone with
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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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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 proposed WEC, using the
Framework for Evaluating Damages and Impacts (FrEDI) (U.S. EPA, 2021a).
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. 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) project57, to
estimate the relationship between future degrees of warming and damages across more than 20
impact sectors. FrEDI then uses these temperature-impact relationships to rapidly estimate
climate change damages under any custom policy pathway. Recent FrEDI applications58 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 Documentation (U.S. EPA, 2021a) have been subject to a public review and an
independent external peer review59, following guidance in the EPA Peer-Review Handbook for
57 EPA Climate Change Impacts and Risk Analysis (CIRA). https://www.epa.gov/eira
58 (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. EGUsphere, https://doi.org/10_5194/egusphere-2023-l 14.
59 Information on the peer-review is available at the EPA Science Inventory:
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.
1
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Influential Scientific Information (ISI)60. FrEDI documentation and source code are available at:
https://www.epa. eov/cira/fredi.
Why are Distributional Climate Impacts Important to Consider?
The impacts of climate change occuring in a particular area or to a particular community
are determined by the physical climate stressors (e.g., heat, wildfire, flooding) 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
the analysis also directly aligns with general recommendations from EPA's Science Advisory
Board on a recent Agency rule61: "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 the RIA complements, but does not replace, existing global climate impact
and benefits assessments that use the social cost of greenhouse gases (SC-GHG). While global
impacts from the proposed 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.
60 EPA Science and Technology Policy Council Peer Review Handbook.
https://www.epa.gov/sites/defanit/files/2020-08/docnments/epa peer review handbook 4th edition.pdf
61 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.
2
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How is FrEDI Applied in the Proposed 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 proposed 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 (only those that can have implications on the U.S.
economy), and do not consider damages that occur due to interactions between different sectors.
Therefore, these estimates should be considered a preliminary accounting of net climate driven
impacts relevant to U.S. interests.
Methodological Overview
Future global emission scenarios (Figure B-l, Input 1) are first passed to a climate
emulator (model information provided in Section 4) 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 FrEDI62, 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 baseline climate-driven damages) and 2) the
same global baseline, with each year starting in 2024 (first year of the proposed WEC CH4
reductions) adjusted for CH4 emission changes resulting from the proposed WEC. Details and
results are presented in the following sections.
62 https://github.eom/USEPA/FrEDI/releases/tag/v3.4
3
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Figure B-l Schematic of Analysis Workflow from emissions to damages63
GLOBAL MEAN
TEMPERATURE
CHANGE
u w © w
How are Avoided Climate Impacts Calculated?
This analysis presents the distribution of net avoided climate-driven impacts in the year
2090 that are associated with proposed 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 proposed WEC (hereafter called the
proposed WEC scenario). The avoided climate-driven impacts in 2090 are then calculated by
comparing the distribution of long-term climate-driven damages across multiple populations,
regions, and sectors in the proposed WEC scenario compared to the baseline 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.
NCA (USGCRP, 2018) and IPCC (IPCC, 2022) assessments. Given the way that climate impacts
accumulate over time, results here focus on the year 2090 to better capture the impacts from
avoided long-term climate-driven changes64. 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 proposed WEC may mitigate projected
monetized climate impacts across different regions, sectors, and populations.
OUTPUT 2
Sectoral impacts
+ *4°
+ W + §
+ many more- ,
^ Damages
63 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 region-specific damage functions to
project the domestic annual climate-driven damages across sectors associated with the emissions-driven global
mean temperature changes.
64 FrEDI is capable to quantifying impacts for any year through 2100. The snapshot of avoided impacts here
represents the projected impacts in the year 2090 that are projected as a result of annual changes in emissions,
each year, from the first policy year through 2090. 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.
4
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Global Emissions Scenario
Global baseline 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, CHaBr, 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.
Policy Emissions Scenario
To account for annual CH4 emission reductions from abatement activities associated with
the proposed WEC, the expected rule-specific reductions are subtracted from the global baseline
emissions scenario (from Ou et al., 2021). In this analysis, reductions of CH4 are held constant
between the final emissions year and the year 2090. Results are minimally sensitive to this
assumption. For all other compounds, emissions through the end of the century are taken from
the global baseline scenario.
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., 2018; Smith 2018),
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' Intergovernmental Panel on Climate Change
(IPCC), and applied in EPA's November 2022 supplemental proposal for oil and gas standards
(U.S. EPA, 2022). The mean results presented in this analysis are derived by running FaIR with
an ensemble of 2237 sets of uncertain climate parameters65 that have been previously calibrated
to the IPCC AR6 Working Group 1 assessment (Smith, 2021).
65 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.
5
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Calculation of Avoided U.S. Climate-Driven Impacts
As described in the Technical Documentation (U.S. EPA, 2021a), FrEDI uses projections
of global temperature and socioeconomic conditions (U.S. Gross Domestic Product [U.S. GDP]
and regional population66) with underlying damage functions67 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 those that directly occur
within contiguous U.S. borders. Therefore, FrEDI only provides a subset of the 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, 2021a). Lastly, FrEDI also does not account for
impacts of the proposed 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.
66 Population scenarios are based on UN Median Population projection (United Nations, 2015) and EPA's ICLUSv2
model (Bierwagen et al., 2010; EPA 2017), and GDP from the EPPA version 6 model (Chen et al., 2015).
67 A temperature binning approach is used to develop relationships between climate-driven changes in contiguous
U.S. (CONUS) surface temperature or sea level rise (calculated from temperature), socioeconomic conditions
(e.g., U.S. Gross Domestic Product [GDP] and regional population), and the resulting physical and economic
damages across 22 sectors and seven CONUS regions. 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.
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
Damage to coastal property value
Electricity Demand and
Supply
Electricity
No Additional
Adaptation*
Increases in power sector costs (e.g., capital,
fuel, variable and fixed operations and
maintenance cost
Electricity
Transmission and
Electricity
Reactive Adaptation
Damages to transmission & distribution
infrastructure
Distribution
T emperature-Related
Mortality
Health
No Additional
Adaptation*
Mortality from changes in hot and cold
temperatures
Transportation Impacts
from High Tide
Flooding
Infrastructure
Reasonably
Anticipated Adaptation
Coastal flooding related traffic delays,
rerouting, infrastructure improvements, and
other transport impacts.
Inland Flooding
Infrastructure
No Additional
Adaptation*
Residential damages from riverine flooding
Labor
Labor
No Additional
Adaptation*
Damages from work hours lost in high-risk
industries due to temperature
Marine Fisheries
Ecosystems +
Recreation
No Additional
Adaptation*
Changes in thermally available habitat for
commercial fish species
Climate-Driven Air
Health
2011 Precursor
Mortality from ozone and fine particulate
Quality Mortality
Emissions
matter exposure
Crime
Health
No Additional
Adaptation*
Change in the number of Property and
Violent crimes
Rail
Infrastructure
Reactive Adaptation
Infrastructure 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*
Mortality from changes in fine and coarse
dust particle exposure
Suicide
Health
No Additional
Adaptation*
Impact of climate-driven changes in
temperature and weather on suicide
incidence
Wind Damage from
Tropical Storms
Infrastructure
No Additional
Adaptation*
Cost of changes in hurricane wind damage
to coastal properties
Urban Drainage
Infrastructure
Proactive Adaptation
Costs of proactive urban drainage
infrastructure adaptation
Water Quality
Ecosystems +
Recreation
No Additional
Adaptation*
Willingness to pay to avoid water quality
changes
Wildfire
Health
No Additional
Adaptation*
Mortality from wildfire emission 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*
Mortality, morbidity, and lost wages
Vibriosis
Health
No Additional
Adaptation*
Direct medical costs, lost days, and
mortality from changes in Vibriosis cases
*'No additional adaptation' classification is sector specific and does not imply that there is no adaptation in the
underlying study, only that there are no additional adaptation options in FrEDI. For more information please see the
FrEDI technical documentation (U.S. EPA, 2021a).
7
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Results: Distributional Changes in Avoided U.S. Climate-Driven Impacts
Results in this section represent the expected reduction in annual climate-driven impacts
in 2090, or the economic impacts avoided, when implementing the proposed WEC CH4 emission
reductions (e.g., improvements = scenario #1 damages - scenario #2 damages)68. Considering the
22 sectors included in FrEDI, net avoided climate-driven damages from the proposed WEC at
the national level are projected to occur across all sectors and regions within the contiguous
United States. The majority of these improvements are projected to occur within sectors that are
also projected to have the greatest baseline damages, including those that impact human health,
such as reductions in mortality from temperature changes, mortality from climate-driven changes
in air pollution (ozone and ambient fine particulate matter)69, suicide incidence, exposure to
wildfire smoke, Southwest dust, Vibriosis, and Valley fever, as well as reductions in lost labor
hours and infrastructure-related impacts 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 mean avoided climate-driven sectoral impacts are expected to vary across seven
regions70 within the contiguous U.S. by 2090. While all regions are expected to see reductions in
net impacts under the proposed WEC scenario (column 1), that 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 reductions in impacts 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 air quality mortality (3rd largest sectors at the national level) are
expected to be most pronounced in the Southwest, Southeast, 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
68 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 2090 to capture long-term climate-driven changes.
69 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.
70 Corresponding to regions of the 4th U.S. National Climate Assessment.
8
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damage are relatively more important in coastal regions. Lastly, relatively larger reductions in
wildfire damages are projected in the Northwest, Southwest, and Northern Plains.
Figure B-2 Relative avoided per capita climate driven impacts by sector and US region.71
impacts Per capita Relative Avoided Climate-Driven Impacts in Analyzed Sectors, Across 7 U.S. Regions
2090
Southeast
Northeast
Northern
Plains
Northwest
Southern
Plains
Southwest
Midwest
NW
SW
2030-2090
Trend
ml
.nl
ml
nil
.Hi
ill
ml
JS, "fi
ft
/A\
<8>
/A\
m
i
m
&
&
r
Temperature-Related
Mortality
£^5V) Transportation Impacts
from High Tide Rooding
£& 1 Suicide
Climate-Driven Air
Quality Mortality
/A\
Rail
/A\
C3
-ft
Wind Damage
Coastal Properties
p Southwest Dust ^ Agriculture
Figure B-3 provides a more detailed breakdown of the regional distribution across each
sector and shows that for some sectors, reductions are only expected to occur in select regions,
such as climate-driven changes in dust and Valley fever primarily impacting populations living
in the Southwest, and reductions in tropical wind damage and transportation impacts from high-
tide flooding largely occurring along coastlines of the Southeast, Southern Plains, and Northeast.
71 Left bars) relative per capita improvements in each region in 2090 as well as the per capita improvements in the
years 2030, 2050, 2070, and 2090. Right green tiles and icons) avoided climate driven impacts experienced in
each sector, in order of decreasing per capita impact changes (from left to right) in each region. Green shading
illustrates the relative changes in each sector, normalized to the temperature mortality impacts in that region.
9
-------
Figure B-3 Regional share of annual mean avoided U.S. climate-driven impacts in 209072
Temp.-Related Transportation Impacts Climate-Driven , .
Mortality from HTF Air Quality Mortality*
Suicide Coastal Properties Wildfire Wind Damage
Roads Rail Elec. Demand & Supply Southwest Dust
Agriculture Valley Fever Elec. Trans. & Dist. Vibrio
Water Quality Winter Recreation Crime Inland Flooding
Urban Drainage* Marine Fisheries*
%
| Midwest
J Northeast
Southeast
Midwest Northwest Northern
Plains
Northeast Southwest
Southeast Southern Plains
12 Pie charts are ordered (left-to-right, top-to-bottom) by decreasing national impacts avoided within U.S. borders,
such that premature mortality from temperature change has the largest and marine fisheries have the smallest.
Sectors marked with an (*) have impacts increase in some regions, which are not shown in the pie charts.
10
-------
Temp.-Related Transportation Impacts Climate-Driven
Mortality from HTF Air Quality Mortality*
Suicide Coastal Properties Wildfire Wind Damage
Roads Rail Elec. Demand & Supply Southwest Dust
Agriculture Valley Fever Elec. Trans. & Dist. Vibrio
Water Quality Winter Recreation Crime Inland Flooding
Urban Drainage* Marine Fisheries*
%
Midwest Northwest Northern
Northeast ¦¦ Southwest
Southeast Southern Plains
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, 2021b) (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
11
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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 BIPOC73), 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).
As described in the FrEDI Technical Documentation (Appendix G) (U.S. EPA, 2021a),
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
(U.S. Census) and are held constant overtime because robust and long-term projections of local
changes in demographics are not readily available.
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.
73 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.
12
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Figure B-4 shows how reductions in annual climate-driven impacts within the six impact
categories74, under the proposed 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 under the proposed
WEC scenario, compared to their reference populations (Table B-2). These are the same
populations that are projected to experience relatively larger damages under the baseline
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 the white and/or non-Hispanic reference population. In addition,
those in the low-income group are more likely (6%) to see larger reductions in lost labor hours
than then those outside the low-income group. As nearly all bars in each category are to the right
of the dashed lines, Figure B-4 also shows that nearly all socially vulnerable groups are projected
to experience larger reductions in climate change impacts, compared to the reference
populations.
74 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.
13
-------
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.75
Climate-Driven Air Quality -
Age 65+ Mortality
Over age 65
No High-School
Diploma
Over age 65
No High-School
Diploma
Low Income
BIPOC
Lost Labor
Hours
Climate-Driven Air Quality -
Childhood Asthma
Temperature-Related
Mortality
Coastal Flooding
Property Damage
Transportation Impacts from
High Tide Flooding
____1
120 0
40 80
Percent {%)
120
Impacts to the BIPOC individuals in Figure B-4 can also be distributed across different
races and ethnicities as shown in Figure B-576. 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.
75 Dashed gray lines represent 100% of the annual avoided impacts that are experienced by the reference population
for that sector (Table C-2). Bars greater than 100% indicate that a group is projected to experience more impact
reductions from proposed 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.
76 Impact results as a function of racial and ethnic group were also presented in EPA's SV Report.
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.77
Climate-Driven Air Quality
Age 65+ Mortality
Climate-Driven Air Quality ¦
Childhood Asthma
Coastal Flooding
Property Damage
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
Lost Labor
Hours
Temperature-Related
Mortality
¦l
Transportation Impacts from
High Tide Flooding
150
50 100 150
Percent (%)
When considering current demographic patterns of different populations and the
projected exposure to the six impact categories analyzed here, Figure B-5 shows that all groups
are projected to see fewer climate change impacts under the proposed WEC scenario (all bars are
greater than zero), but that some specific populations may see more benefits than others. For
example, by 2090, Blacks and African Americans over the age of 65 are 46% more likely to see
more reductions in climate-driven changes in air quality than the national average, which is
largely because of regional differences in where these populations currently live and where
future air quality changes are projected to occur. As another example, considering the effects of
temperature on laborers working in exposed industries, Hispanics and Latinos are 12% more
likely to see larger reductions in lost labor hours than the national average. Typically, the
77 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 contiguous U.S. who identify as "American Indian or Alaska Native" and "Native
Hawaiian or Other Pacific Islander."
15
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populations projected to be impacted the most by climate change under the baseline scenario are
the same groups that will experience the greatest reductions in impacts under the proposed WEC.
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 contiguous United States.
Overall, the FrEDI analyses 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.
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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.
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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, 2018.
U.S. Census: American Community Survey 2014-2018 [https://www.census.gov/programs-
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U.S. Environmental Protection Agency: Technical Guidance for Assessing Environmental
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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: Technical Documentation for the Framework for
Evaluating Damages and Impacts (Updated). , U.S. Environmental Protection Agency, EPA.
430-R-21 -004. www.epa.gov/cira/FrED1, 2021 a.
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, 202lb.
U.S. Environmental Protection Agency (EPA): Supplementary Material for the Regulatory
Impact Analysis for the Supplemental Proposed Rulemaking, "Standards of Performance for
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17
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ADDITIONAL INFORMATION ON MARGINAL ABATEMENT COST (MAC)
MODELING FOR ANALYSIS OF WASTE EMISSIONS CHARGE
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 curve is constructed 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).
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.
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.
1
-------
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. We used market
shares for each mitigation option within every sector. The market shares, determined by various
2
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sector-specific 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 immediately. 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.
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.
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
3
-------
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
t=i
(1 TR)(P ¦ER + R) + TB
(1 + DRY
1
Net Present Benefits
= CC +
J L
I
t=i
(1 - TR)RC
(1 + DRY
*
Net Present Costs
(D.l)
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 =
(* TP\ pp yT ^ ER ER ER ¦ T (1 TR)
(1 -77?) ER Lt=i(1 + DRy
(D.2)
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),
(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. 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
($/tCH4 <= WEC S/tCFU) may be costs-effective in later years.
WEC Facility MAC Curves Construction
The mitigation option analysis throughout this report was conducted using a common
methodology and framework. MAC curves were constructed for each region and sector by
estimating the "break-even" price at which the present-value benefits and costs for each
mitigation option equilibrate. The methodology produces a curve where each point reflects the
average price and reduction potential if a mitigation technology were systematically adopted by
all similar facilities across the oil or gas segment. When combined with the projected baseline
emissions for the specific facility type, results are expressed in absolute annual reductions
(tCH4) at specific average mitigation costs or prices. For example, in the illustrative MAC
shown in Figure C-l below shows the quantity of mitigation technical achievable at prices below
the WEC rate ($/tCH4). The quantity of mitigation (Qmacc) expected from WEC facilities in
the 2025 is -460 ktCH4, where the MAC curve crosses the WEC.
5
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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 NSPS OOOOb/EG
OOOOc 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.
Figure C-l Illustrative MAC Curve for Facilities with Emissions Subject to the WEC in
the year 2025
Mitigation Level (ktCH4)
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
OOOOb and EG 0000c 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 OOOOb and EG 0000c 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.
7
-------
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 OOOOb and EG 0000c
analysis of the Oil and Natural Gas Sectors (EPA,2021).
8
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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
9
-------
(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.
10
-------
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
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
site, the costs of the power supply were not included in the mitigation option costs for electronic
11
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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 Storage
Facility
Site
Mitigation
Reduction
Capital Costs
O&M Costs
Size
Type
Option
Efficiency
($2019)
($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
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
12
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. . Install low or intermittent 38.4%
controllers with inspection*
$0
$600
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. 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 OOOOb/EG OOOOc
analysis.
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 b
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.
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
14
-------
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.
Liquids Unloading
As described in EPA, 2021, the accumulation of liquids in new or mature wells78 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
78 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.
15
-------
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 NSPS OOOOb/EG OOOOc 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. 189 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
Production
Liquids Unloading - With Plunger Lift - 25% Control
25%
-
$65
16
-------
Production Liquids Unloading - With Plunger Lift - 50% Control 50%
$65
a[l.9-hour event X 0.475 hour] X $71.74 hour = $64.75/event
Source: EPA, 2022.
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)
Producti
on
New
Direct Inspection and
Maintenance/Repair Option
and Routing to An Enclosed
Combustor Option - Dry
Seal Centrifugal Comp
37%
$0
$15,000
Producti
on
Existing
Direct Inspection and
Maintenance/Repair Option
and Routing to An Enclosed
Combustor Option - Dry
Seal Centrifugal Comp
37%
$0
$15,000
Producti
on
New
Direct Inspection and
Maintenance/Repair Option
and Routing to An Enclosed
Combustor Option - Wet
Seal Centrifugal Comp
89%
$0
$25,000
Producti
on
Existing
Direct Inspection and
Maintenance/Repair Option
and Routing to An Enclosed
Combustor Option - Wet
Seal Centrifugal Comp
89%
$0
$25,000
Producti
on
New
Emissions Routed to a New
Combustion Device - Wet
Seal Centrifugal Comp
95%
$80,926
$128,683
Producti
on
Existing
Emissions Routed to a
Existing Combustion
95%
$26,214
$3,732
17
-------
Device - Wet Seal
Centrifugal Comp
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
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
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
Site
Mitigation
Reduction
Capital Costs
O&M Costs
Segment
Type
Option
Efficiency
($2019)
($2019)
Producti
New
Rod Packing Change Out
56%
$6,345
$1,963
on
19
-------
Producti
on
New
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$6,345
$2,560
Producti
on
Existing
Rod Packing Change Out
56%
$6,345
$1,963
Producti
on
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
Processin
g
New
Rod Packing Change Out
80%
$4,807
$1,682
Processin
g
New
Annual Monitoring to Evaluate
Need for Packing Replacement
92%
$4,807
$2,279
Processin
g
Existing
Rod Packing Change Out
80%
$4,807
$1,682
Processin
g
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.
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
20
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be approximately 150 ktCH4. This potential increases in the following year to over 300 ktCH4
and then drops to 47 ktCH4 for years 2026 through 2035.
Table C-ll Abatement Potential by Industry Segment and Source Type
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
1.69
3.
.39
5
.06
-
Vilural (ias Transmission Pi pel i no - ...
I iklcr^rouikl Vilural (ias Storage - ...
I.\(i I ill poll Lxporl - ...
I.\(i Slorage - ...
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-ll 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
addition 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
21
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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
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 tCFU in 2024. Figure C-3 through 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.
22
-------
Figure C-2 Total MAC Curve for WEC Applicable Segments of the Oil and Gas
Industry in 2024
Mitigation Level (ktCH4)
23
-------
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
24
-------
Figure C-5 Transmission and Storage Segment MAC Curve in 2024
2-500
J.Q00
< 1.500
x
5 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.
25
-------
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
623
226
75
$23.5
$33.7
Pneumatic Controllers
475
181
60
$19.9
$28.9
Fugitive Emissions
66
0
0
$0.0
$0.0
Compressors
24
15
5
$0.4
$0.4
Pneumatic Pumps
43
17
6
$1.5
$2.0
Liquids Unloading
14
13
4
$1.7
$2.4
Offshore Production
5
5
2
$0.1
$0.3
Fugitive Emissions
5
5
2
$0.1
$0.3
Gathering and Boosting
231
190
63
$25.4
$32.9
Pneumatic Controllers
111
93
31
$6.4
$10.1
Fugitive Emissions
70
70
23
$17.6
$21.1
Compressors
32
20
7
$0.7
$0.8
Pneumatic Pumps
18
7
2
$0.6
$0.8
Natural Gas Processing
19
19
6
$1.1
$1.6
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
19
19
6
$1.1
$1.6
Transmission and
5
5
2
$0.6
$0.7
Storage
Pneumatic Controllers
0
0
0
$0.0
$0.0
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
5
5
2
$0.6
$0.6
Total
884
445
148
$50.6
$69.1
26
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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
519
247
247
$121.4
$156.6
Pneumatic Controllers
381
145
145
$44.2
$67.8
Fugitive Emissions
61
47
47
$56.4
$64.0
Compressors
24
24
24
$9.5
$9.7
Pneumatic Pumps
39
18
18
$6.8
$8.4
Liquids Unloading
14
13
13
$4.5
$6.6
Offshore Production
5
5
5
$0.1
$0.9
Fugitive Emissions
5
5
5
$0.1
$0.9
Gathering and Boosting
217
197
197
$87.6
$111.5
Pneumatic Controllers
97
87
87
$21.3
$32.6
Fugitive Emissions
70
70
70
$50.7
$62.1
Compressors
32
32
32
$12.5
$13.0
Pneumatic Pumps
18
8
8
$3.1
$3.9
Natural Gas Processing
19
19
19
$3.1
$4.6
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
19
19
19
$3.1
$4.6
Transmission and
5
5
5
$1.8
$2.0
Storage
Pneumatic Controllers
0
0
0
$0.0
$0.1
Fugitive Emissions
0
0
0
$0.0
$0.0
Compressors
5
5
5
$1.8
$1.9
Total
765
473
473
$214.0
$275.6
27
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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
5
5
5
$0.1
$0.9
Fugitive Emissions
5
5
5
$0.1
$0.9
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
0
0
0
$0.0
$0.0
Storage
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
Total
5
5
5
$0.1
$0.9
References
EPA. 2019. Global Non-CO2 Greenhouse Gas Emission Projections & Marginal Abatement
Cost Analysis: Methodology Documentation. EPA-430-R-19-012. Available at:
https://www.epa.gov/sites/production/files/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).
28
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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).
29
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