Draft Regulatory Impact Analysis Addendum: Impact
of the Technology Transitions Proposed Rule
December 2022
United States Environmental Protection Agency
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Contents
Executive Summary 4
Introduction 4
Relationship to Allocation Framework Rule and Proposed 2024 Allocation Rule RIA
Results 5
Climate Benefits 8
Compliance Costs 9
Net Costs/Benefits 10
Chapter 1: Introduction and Background 13
1.1 Statutory Requirement 13
1.2 Background 13
1.3 Regulated Community 14
1.4 Summary of Petitions Addressed and Restrictions Proposed 15
Chapter 2: Overview of the Analysis 19
2.1 Introduction 19
2.2 Organization of the Analysis 19
2.3 Years of Analysis 21
2.4 Factors Analyzed 22
2.5 Vintaging Model 22
2.6 Regulatory Option 23
Chapter 3: HFC Allocation Framework Rule Baseline 25
3.1 Introduction 25
3.2 Baseline for Allocation of Consumption Allowances 25
3.3 HFC Consumption under BAU Projection and Allocation Rule Reference Case....26
3.4 Approach to Evaluating Incremental Benefits of the Technology Transitions Rule27
Chapter 4: Compliance Costs 29
4.1 Introduction 29
4.2 Modeling Method for Technology Transition Costs 29
4.3 Abatement Options Modeled 30
4.4 Costs of Transition 32
4.5 Labor Impacts 38
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4.6 Recordkeeping, Reporting, and Labeling Costs 39
Chapter 5: Climate Benefits 41
5.1 Introduction 41
5.2 Consumption and Emission Reductions 41
5.3 The Social Cost of HFC Emissions 47
5.4 Monetized Climate Benefits Results 60
Chapter 6: Comparison of Benefits and Costs 63
Chapter 7: Supplementary Analysis of Alternative GWP Restriction Scenarios 67
7.1 Introduction 67
7.2 Description of scenarios 67
7.3 Results 71
Chapter 8: Environmental Justice Analysis 79
8.1 Introduction and Background 79
8.2 Environmental Justice at EPA 79
8.3 Environmental Justice Analysis for the Proposed HFC Allocation Rule 81
8.4 Aggregate Average Characteristics of Communities Near Potentially Affected
Production Facilities 83
8.5 Characteristics of Communities Near Identified Individual Facilities 88
8.6 Conclusion 97
Chapter 9: Annexes 99
Annex A: Summary of Mitigation Technologies Modeled by End Use 99
Annex B: Annual Emission Reductions by Gas 120
Annex C: Industries Potentially Affected by subsection (i) of the AIM Act 130
Annex D: Imports of Products Containing Hydrofluorocarbons 133
Annex E: Supplemental Approach for Environmental Justice Analysis 160
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Executive Summary
Introduction
This Regulatory Impact Analysis (RIA) addendum provides an assessment of the costs and benefits of the
proposed rule Phasedown of Hydrofluorocarbons: Restrictions on the Use of Certain Hydrofluorocarbons
under Subsection (i) of the American Innovation and Manufacturing Act of 2020 (also referred to in this
document as the Technology Transitions Rule). The proposed rule furthers the implementation of the
American Innovation and Manufacturing (AIM) Act, including through restricting the use of certain
hydrofluorocarbons (HFCs) above a certain global warming potential whether neat or used in a blend,1 or
restricting certain HFCs and certain blends containing HFCs, in specific sectors or subsectors where
HFCs are used. This rule proposes restrictions for the aerosols, foam blowing, and refrigeration, air
conditioning, and heat pumps sectors and would apply to both domestically manufactured and imported
products. This analysis is intended to provide the public with information on the relevant costs and
benefits of this rulemaking and to comply with executive orders. While significant, the estimated benefits
detailed in this document are considered incidental and secondary to the rule's statutory objective of
facilitating the transition to next-generation technologies by restricting use of HFCs in the sectors or
subsectors in which they are used.
The proposed rule follows an already finalized rulemaking issued separately under the AIM Act,
Phasedown of Hydrofluorocarbons: Establishing the Allowance Allocation and Trading Program Under
the American Innovation and Manufacturing Act (Allocation Framework Rule, 86 FR 55116, October 5,
2021), as well as a proposed update to that rule, Phasedown of Hydrofluorocarbons: Allowance
Allocation Methodology for 2024 through 2028.2 The analysis presented in the sections below provides
estimated economic costs and environmental impacts of the provisions of the Technology Transitions
Rule as proposed. The analysis also provides a comparison of these costs and benefits with those assessed
for the Allocation Framework Rules to provide the public with an understanding of any potential changes
1 Under the GWP limit approach, for HFCs used in a blend in the sector or subsector, compliance with the GWP limit would be
determined based on the GWP of the blend. Blends containing an HFC with GWPs at or above the GWP limit would be
prohibited from use in that sector or subsector.
2 Throughout this document, we use "Allocation Framework RIA" and "2024 Allocation Rule RIA" to refer to the analyses of
these rules. We use "Allocation Rules" and "Allocation Rules RIA" to refer to combined or cumulative effect of those two rules;
i.e., the Allocation Framework RIA as updated by the 2024 Allocation Rule RIA.
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in economic and environmental impacts relative to the existing regulation. In addition, for the purposes of
identifying potential environmental justice issues, the analysis presents EPA's assessment of the
characteristics of communities near facilities producing predominant HFC substitutes that are expected to
be affected by the proposed rule.
The methodology used to examine the economic costs and environmental impacts of the proposed rule
closely follows that used in the Allocation Framework RIA3 as well as the addendum to that RIA
prepared for the proposed 2024 Allocation Rule (collectively, "Allocation Rules"). Results and methods
from these analyses are referenced throughout this document. As with the 2024 Allocation Rule analysis,
this document is presented as an addendum to the original Allocation Framework RIA.
The Technology Transitions Rule includes restrictions, summarized below, on the use of a regulated
substance in the sector or subsector in which the regulated substance is used. The intent of the rule is to
facilitate transitions to innovative technologies as HFCs are phased down. This proposed rule responds to
13 petitions covering approximately 40 sectors or subsectors. The proposed restrictions take the form of
GWP limits or a list of prohibited HFCs or HFC blends used in those sectors or subsectors. The additional
benefits anticipated from the Technology Transitions Rule that are presented in this analysis are non-
trivial but also represent a relatively small share of the total benefits already accounted for in the
Allocation Rules RIA.4
Relationship to Allocation Framework Rule and Proposed 2024 Allocation
Rule RIA Results
Results from this analysis indicate that the restrictions in the proposed Technology Transitions Rule will
reduce HFC consumption and emissions at a level on par with that estimated for the Allocation
Framework Rule and the 2024 Allocation Rule for many sectors and subsectors, while requiring more
rapid, deeper transitions in others, resulting in potential additional reductions and associated climate
benefits, although the schedule for the production and consumption phasedown would not be made more
stringent than the schedule under subsection (e)(2)(C) of the AIM Act (i.e., the production and
consumption caps contained in the Allocation Rules would be unchanged). In terms of net compliance
costs, transitions required to meet the restrictions would also result in additional cost savings over time
beyond those projected in the Allocation Rules. These additional savings stem largely from a more rapid
3 Available at www.rezulations.zov under Docket ID EPA-HQ-OAR-2021-0044-0227.
4 The Allocation Rule Reference Case projects the present value of climate-related benefits from 2025 through 2050 to be $253.2
billion (2020$, 3% discount rate, discounted to 2022). The Technology Transitions Rule base case projects incremental climate-
related benefits over the same time period to be $2.7 billion, equivalent to 1% of those projected for the Allocation Rule
Reference Case. (Table 5-14).
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and comprehensive transition to lower-GWP, energy-saving technologies than is otherwise assumed in
the compliance pathway evaluated for the Allocation Rules.
The incremental environmental impact of the proposed Technology Transitions Rule depends in part upon
the specific set of transitions made in order to meet compliance with the proposed rule restrictions
together with the set of transitions projected for the already established Allocation Rules. The proposed
rule contains sector- and subsector-specific restrictions covering a large share of HFC uses. Industry is
already making many of these transitions, and we expect that achieving the allowance cap step-downs
will require many of the same subsector-specific technology transitions that would also be required by
this proposed rule. However, the rule may in some cases require regulated entities to further accelerate
transitions in specific subsectors, relative to what EPA previously assumed in its analysis of the
Allocation Rules. Conversely, for a discrete set of subsectors not covered by the rule, HFC consumption
reductions could conceivably decrease in response to the rule (i.e., consumption would increase compared
to the levels projected in the Allocation Rules analysis). This could occur to the extent that additional
consumption allowances are "freed up" as a result of greater consumption reductions in subsectors
covered by the rule, so long as overall domestic consumption and production remains within the AIM Act
HFC phasedown cap for a given year.
Ultimately, the extent of these potential offsetting effects is uncertain. To account for this uncertainty, this
analysis provides two scenarios to illustrate the range of potential incremental environmental impacts: a
"base case" and a "high additionality case." In our base case scenario for the Technology Transitions
Rule, we conservatively estimate that abatement does not occur in subsectors not covered by the rule—
even if abatement in those same subsectors was previously assumed in the Allocation Rules' RIAs—since
we find that abatement from the Technology Transitions Rule's restrictions would on its own be sufficient
to achieve the AIM Act HFC phasedown cap. In other words, these consumption and emissions reducing
opportunities are assumed to be forgone in the Technology Transitions base case. By contrast, the "high
additionality" case is a less conservative scenario and assumes that HFC consumption reduction activities
not covered by the proposed rule would remain consistent with the Allocation Rule reference scenario
(i.e., neither increase nor decrease in response to this proposed rule).
The two scenarios are meant to provide a lower and upper bound of the incremental benefits from the
proposed rule. Previous regulatory programs to reduce chemical use in the affected industries show that
regulated entities do not limit their response to the required compliance level; rather, regulated entities
may take additional actions that transform industry practices for various reasons, including the
anticipation of future restrictions, strengthening their competitive position, and supporting overall
environmental goals. For example, U.S. production and consumption of ozone-depleting substances
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(ODS) during their phaseout was consistently below the limits established under the Montreal Protocol.
Moreover, the existing HFC phasedown regulation is likely to drive industry transitions in the coming
years regardless of whether they are covered by the restrictions contained in the Technology Transitions
Rule, which as proposed would not have compliance dates until January 1, 2025. These transitions may
occur before the compliance dates of the Technology Transition Rule (e.g., to meet the 2024 reduction in
HFC consumption) and are likely to continue even after the Technology Transitions rule is finalized. For
these reasons, EPA expects that industry transitions will ultimately result in greater reductions than those
projected in the base case, albeit lower than the upper bound high additionality scenario.
Table ES-1 below presents the potential incremental consumption reductions of the proposed rule relative
to the Allocation Rules. Values are presented in both the base case and high additionality case, illustrating
the range in potential incremental impacts. Notably, emissions are generally assumed to lag consumption,
for example as leaks from equipment that can operate for decades. Due to this dynamic, estimated annual
consumption reductions may not correspond to estimates of annual emission reductions and associated
benefits occuring in the same year that are presented elsewhere in this RIA addendum.
Table ES-1 -Incremental Consumption Reductions compared to the Allocation Rule Reference
Case5 for the Technology Transitions Base Case and the Technology Transitions High
Additionality Case
) ear
lech notary Transitions Rule
Hase ( ase Incremental
C 'onsumption
Reductions (MMHI 1 e)
Technology Transitions High
. \dditionality Case Incremental
( onsumption Reductions
(MM 17:1 e)
2025
9
42
2029
27
53
2034
35
49
2036
34
42
2040
21
29
2045
35
44
2050
37
46
Total (cumulative)
735
1121
5 Throughout this document, "Allocation Rule Reference Case" refers to the estimated climate and economic impacts of the
Allocation Framework Rules, specifically as presented in the updated 2024 Allocation Rule RIA addendum. These values
represent the status quo from which incremental impacts of the Technology Transitions Rule are evaluated.
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Climate Benefits
Climate benefits of the proposed rule derive from reducing damages from climate change induced by
reduced emissions of greenhouse gases (GHGs), specifically HFCs. A primary aim of the proposed
Technology Transitions Rule is to facilitate transitions away from HFCs through sector- and subsector-
specific restrictions. These restrictions may in-turn contribute to climate benefits previously quantified by
EPA in relation to the Allocation Rules and may yield additional benefits insofar as transitions progress
beyond those that would occur through implementation of the Allocation Rules alone. Table ES-2 shows
the projected incremental emission reductions by year corresponding to the Technology Transitions Rule
compliance scenario in the base case and high additionally case, relative to the Allocation Rule
Reference Scenario. These benefits of avoided climate damages are monetized using previously
established social cost of HFCs (SC-HFCs) estimates and are presented in Table ES-3.
Both the base case and high additionally case results show a net reduction in consumption and emissions
on a cumulative basis through 2050. Emissions under the proposed rule would decrease compared to
business-as-usual (BAU) estimates (described in more detail in Chapter 3), however they would not
decrease as much as under the Allocation Rule reference scenario for certain model years. For these years,
incremental emission reductions are therefore shown as negative numbers in the table. This reflects
differences in the mix of technological solutions assumed for compliance with each rule and how EPA
accounts for the corresponding changes in emissions overtime. Specifically, the base case excludes
actions not required by this proposed rule, such as improved leak reduction and enhanced recovery of
HFCs, which are assumed to otherwise yield relatively rapid emission reductions. Since the Allocation
Rule reference scenario includes those actions, incremental emission reductions in the base case accrue
more slowly (and therefore are negative in certain years) but are positive on a cumulative basis. Finally,
we note that values in the Technology Transitions base case represent a conservative estimate of
incremental climate benefits from the proposed rule, and there are a range of potential incremental
benefits depending on the ultimate transition pathway chosen by industry.
Table ES-2: Incremental Emission Reductions in the Technology Transitions Compliance Base
Case and High Additionality Case
) ear
lech notary Transitions Rule
fiase ( ase Incremental
Emission Reductions
-------
2040
27
40
2045
27
37
2050
30
38
Total (cumulative)
134
903
Table ES-3 - Annual Incremental Climate Benefits in the Technology Transitions Compliance
Base Case and High Additionality Case a-h-c
) ear
/ eclmolo^y transitions Rule Hase
C Vise Incremental C limate ficnefits
(millions 20JOS)
Technology Transitions High
. idilitioiiality Case Incremental Climate
Benefits (millions 2020S)
2025
$(3,603)
$546
2029
$(1,043)
$2,563
2034
$141
$3,739
2036
$(404)
$3,213
2040
$2,669
$3,928
2045
$2,946
$4,031
2050
$3,606
$4,677
a Incremental climate benefits from the rule in the base case are net negative in the initial model years, but on a
cumulative basis through 2050 are net positive. This is due to differences in the assumed transition pathways and
the timing of corresponding emission reductions. EPA's Vintaging Model is based on stock-turnover, with some
emission reductions occurring faster than others depending on the abatement option. More details on these
assumptions can be found in Chapter 5 of this R1A addendum and the accompanying annexes.
b Benefits include only those related to climate. Climate benefits are based on changes in HFC emissions and are
calculated using four different estimates of the social cost of HFCs (SC-HFCs): model average at 2.5 percent, 3
percent, and 5 percent discount rates; 95th percentile at 3 percent discount rate. For the presentational purposes of
this table, we show the benefits associated with the average SC-HFC at a 3 percent discount rate, but the Agency
does not have a single central SC-HFC point estimate. We emphasize the importance and value of considering the
benefits calculated using all four SC-HFC estimates. Please see Tables 5-3 through 5-12 for the full range of SC-
HFC estimates. As discussed in Chapter 5, a consideration of climate effects calculated using discount rates below 3
percent, including 2 percent and lower, is also warranted when discounting intergenerational impacts.
c These estimates are year-specific estimates.
Compliance Costs
Compliance costs in this analysis stem largely from the assumed industry transitions required to meet the
sector-based and subsector-based restrictions proposed in the rule. This analysis finds that for some
sectors and subsectors, the transitions will result in net positive costs due to required investments in new
lower-GWP technologies and refrigerants. For other cases, these costs are outweighed by assumed energy
savings from the deployment of new technologies, lower-cost refrigerants, and other factors, resulting in
net-negative compliance costs (i.e., cost savings). On the whole, we find that meeting the GWP limits and
HFC restrictions established by the rule as proposed would result in net negative compliance costs.
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There are also costs associated with proposed recordkeeping, reporting, and labeling requirements, as
detailed in the preamble to the proposed rule and section 4.6 of this RIA addendum. Annual incremental
net compliance costs, reflecting these additional costs as well as industry transitions, are shown in table
ES-4 below for select model years.
Table ES-4 -Annual Incremental Net Compliance Costs/Savings* in the Technology Transitions
Compliance Base Case and High Additionality Case
*Note: Values in parenthesis represent net cost savings
) ear
/ echnolo^y transitions Rule liase
C ase Incremental C o/npliance
('lists/Savings (millions 202OS)
Technology Transitions High
. \
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EPA estimates that the range of PV of cumulative net incremental benefits evaluated from 2025 through
2050 is $13.1 billion to $56.3 billion at a 3 percent discount rate for the base case and high additionality
case respectively. The range of incremental EAV over the same period 2025 through 2050 is $803
million and $3.4 billion when using a 3 percent discount rate for the base case and high additionality case
respectively. The comparison of benefits and costs in PV and EAV terms for the base case and high
additionality case can be found in Table ES-5. Estimates in the table are presented as rounded values.
Table ES-5 - Summary of Annual Incremental Climate Benefits, Costs, and Net Benefits of the
Technology Transitions Rule Base Case and High Additionality Case Scenarios for the 2025-
2050 Timeframe (millions of2020$, discounted to 2022)a-b-c-d
lillsc ( list'
High Atltlilionalily (
ll.SC
Year
Incremental
( linmlL'
Hcnc/hs
(.*"'»)
Annual ( o.st.s
(savings)
\i'l licncjils (3"n
licncjils. J",i or
(osisy
Increment
al ( limalc
Hcnc/ils
(.*"»)
Animal ( o.sls
(.stiring*)
\ct licncjils (3"u
licncjils, or
( osls) •
2025
($3,603)
($395)
($3,209)
$546
$31
$515
2026
($3,138)
($462)
($2,676)
$888
($82)
$970
2027
($3,194)
($521)
($2,673)
$1,191
($135)
$1,326
2028
($3,007)
($529)
($2,478)
$1,454
($171)
$1,626
2029
($1,043)
$50
($1,092)
$2,563
$335
$2,227
2030
($963)
($17)
($947)
$2,760
$272
$2,488
2031
($785)
($56)
($729)
$3,004
$237
$2,767
2032
($466)
($77)
($388)
$3,264
$170
$3,094
2033
($118)
($54)
($64)
$3,535
$130
$3,406
2034
$141
($200)
$340
$3,739
($77)
$3,816
2035
$504
($175)
$679
$4,016
($111)
$4,127
2036
($404)
($677)
$273
$3,213
($635)
$3,848
2037
$504
($711)
$1,215
$3,562
($680)
$4,242
2038
$1,320
($710)
$2.031
$3,839
($684)
$4,524
2039
$2,015
($784)
$2,799
$3,970
($685)
$4,654
2040
$2,669
($848)
$3,516
$3,928
($784)
$4,712
2041
$2,602
($754)
$3,357
$3,803
($691)
$4,494
2042
$2,658
($760)
$3,418
$3,846
($697)
$4,543
2043
$2,702
($773)
$3,475
$3,872
($709)
$4,582
2044
$2,775
($782)
$3,557
$3,926
($713)
$4,640
2045
$2,946
($786)
$3,732
$4,031
($717)
$4,748
2046
$3,093
($791)
$3,883
$4,167
($722)
$4,889
2047
$3,240
($795)
$4,035
$4,305
($725)
$5.03 1
2048
$3,384
($801)
$4,185
$4,445
($729)
$5,174
2049
$3,481
($806)
$4,287
$4,543
($733)
$5,276
2050
$3,606
($817)
$4,422
$4,677
($743)
$5,419
Discount
rate
3%
3% 7%
3% 7%
3%
3% 7%
3% 7%
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PV
$5,084
(8,045)
($4,225)
$13,130
$9,309
$51,145
($5,140)
($2,190)
$56,285
$53,335
EAV
$311
($492)
($438)
$803
$748
$3,126
($314)
($227)
$3,440
$3,353
a Benefits include only those related to climate. Climate benefits are based on changes in HFC emissions and are
calculated using four different estimates of the SC-HFCs (model average at 2.5 percent, 3 percent, and 5 percent
discount rates; 95th percentile at 3 percent discount rate). For purposes of this table, we show the effects associated
with the model average at a 3 percent discount rate, but the Agency does not have a single central SC-HFC point
estimate. We emphasize the importance and value of considering the benefits calculated using all four SC-HFC
estimates. As discussed in Chapter 5, a consideration of climate effects calculated using discount rates below 3
percent, including 2 percent and lower, is also warranted when discounting intergenerational impacts.
b Rows may not appear to add correctly due to rounding.
0 The annualized present value of costs and benefits are calculated as if they occur over a 26-year period from 2025
to 2050.
d The costs presented in this table are annual estimates.
e The PV for the 7% net benefits column is found by taking the difference between the PV of climate benefits at 3%
and the PV of costs discounted at 7%. Due to the intergenerational nature of climate impacts the social rate of return
to capital, estimated to be 7 percent in OMB 's Circular A-4, is not appropriate for use in calculating PV of climate
benefits.
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Chapter 1: Introduction and Background
1.1 Statu to ry Requirement
This RIA addendum evaluates the impact associated with the Notice of Proposed Rulemaking referred to
as the "Technology Transitions" rule. Subsection (i) of the AIM Act provides EPA the authority to
"restrict, fully, partially, or on a graduated schedule, the use of a regulated substance in the sector or
subsector in which the regulated substance is used." Persons may petition EPA to act on this authority,
and EPA must make the petition available to the public within 30 days, and grant or deny the petition
within 180 days of receipt. If a petition is granted, EPA must promulgate a final rule no later than two
years after such granting. Any restriction finalized by such a rule may take effect no sooner than one year
after that rule is promulgated. For a complete description of the statutory requirements, see section II.B of
the proposed rule.
Fulfilling a separate statutory requirement of the AIM Act, EPA has previously published the Allocation
Framework Rule establishing a baseline and phasedown schedule for the consumption and production of
HFCs, along with an accompanying RIA detailing the costs and benefits of the HFC phasedown.7 EPA is
also developing an update to that rule to provide the methodology for distributing allowances for the years
2024 through 2028, referred to as the 2024 Allocation Rule. EPA expects that rule to be proposed shortly
before the Technology Transitions Rule is proposed. The Technology Transitions Rule is being
promulgated under a separate statutory requirement but may have a complementary effect on meeting the
HFC phasedown schedule by facilitating necessary transitions to lower-GWP substitutes.
1.2 Background
HFCs are anthropogenic fluorinated chemicals that have no known natural sources. HFCs are used in the
same applications in which ozone depleting substances (ODS) have historically been used, such as
refrigeration and air conditioning, foam-blowing agents, solvents, aerosols, and fire suppression. HFCs
are potent GHGs with 100-year GWPs (a measure of the relative climatic impact of a GHG) that can be
hundreds to thousands of times more potent than carbon dioxide (CO2).
HFC use and emissions have been growing worldwide due to the global phaseout of ODS under the
Montreal Protocol on Substances that Deplete the Ozone Layer (Montreal Protocol), and the increasing
7 Available at www.resulations.sov under Docket ID EPA-HQ-OAR-2021-0044, or see 86 FR 55116 (October 5, 2021).
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use of refrigeration and air conditioning equipment globally.8 HFC emissions had previously been
projected to increase substantially over the next several decades. In 2016, in Kigali, Rwanda, countries
agreed to adopt an amendment to the Montreal Protocol, known as the Kigali Amendment, which
provides for a global phasedown of the production and consumption of HFCs. Global adherence to the
Kigali Amendment would substantially reduce future emissions, leading to a peaking of HFC emissions
before 2040.910
There are hundreds of possible HFC compounds. The 18 HFCs listed as regulated substances by the AIM
Act are some of the most commonly used HFCs and have high impacts as measured by the quantity of
each substance emitted multiplied by their respective GWPs. These 18 HFCs are all saturated, meaning
they have only single bonds between their atoms and therefore have longer atmospheric lifetimes.
For a more detailed background on HFCs, see section III of the Technology Transitions NPRM.
1.3 Regulated Community
The HFC industry is composed of several types of entities. As noted in the RIA for the Allocation
Framework Rule, entities potentially affected by this previous action include those that produce, import,
export, destroy, use as a feedstock, reclaim, package, or otherwise distribute bulk HFCs. This analysis—
which serves as an addendum to the above-mentioned Allocation Framework RIA—addresses a proposed
rule that would restrict the use of HFCs in the following industries: air conditioning, refrigeration, and
heat pumps; foam blowing; and aerosols (including aerosol solvents). In addition to those entities
potentially affected by the phasedown of bulk HFCs, this proposed rule would also affect those who
manufacture, import, sell, or distribute products and equipment that use HFCs in these sectors. Those who
supply HFCs to these manufacturers, such as producers, bulk importers, and reclaimers, could be affected
tangentially because the restrictions would affect subsectors in which they market HFCs restricted by the
rule. However, entities marketing or supplying lower-GWP HFCs or substitutes that meet the criteria
proposed by the rule may be unaffected or actually see increased market share.
8 World Meteorological Organization (WMO), Scientific Assessment of Ozone Depletion: 2018, World Meteorological
Organization, Global Ozone Research and Monitoring Project—Report No. 58, 588 pp., Geneva, Switzerland, 2018. Available at
https://ozone.unep.ors/sites/defaull/files/2019-05/SAP-2018-Assessment-report.vdf.
9 WMO, 2018.
10 Guus J.M. Velders et al. Projections of hydrofluorocarbon (HFC) emissions and the resulting global warming based on recent
trends in observed abundances and current policies. Atmos. Chem. Phys., 22, 6087-6101, 2022. Available at
httvs://doi. ore/10.5194/acv-22-6087-2022.
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1.4 Summary of Petitions Addressed and Restrictions Proposed
In the Technology Transitions Rule, EPA is addressing 13 petitions received pursuant to subsection (i) of
the AIM Act.ll On October 7, 2021, EPA granted a total 10 petitions and partially granted one petition
(86 FR 57141).12 Two additional petitions were submitted in 2022. These 13 petitions are addressed in
the proposed Technology Transitions Rule and are available in the associated docket. For purposes of this
RIA addendum, we also consider all 13 petitions. A table of the petitioner, topic of the petition, and date
received for these 13 petitions is shown here in table 1-1.
Table 1-1 - Summary of Petitions
Petitioner
Receipt Date
Topic
International Institute of Ammonia
Refrigeration (IIAR), et al.
May 23, 2022
Restrict the Use of HFCs in Certain Refrigeration End-
Uses
Air-Conditioning, Heating, and
Refrigeration Institute (AHRI), et al.
March 24, 2022
Restrict the Use of HFCs in Certain Commercial
Refrigeration EauiDinent
California Air Resources Board
(CARB), et al.
July 15, 2021
Replicate HFC Prohibitions from SNAP Rules 20 & 21
and Issue Additional Federal Standards
Household & Commercial Products
Association (HCPA) and National
Aerosol Association (NAA)
July 6, 2021
Replicate SNAP Rules 20 and 21 HFC prohibitions for
Aerosol Propellants
International Institute of Ammonia
Refrigeration (IIAR), et al.
June 3, 2021
Restrict the Use of HFCs in Certain Refrigeration End-
Uses
American Chemistry Council's Center
for the Polyurethanes Industry (CPI)
May 26, 2021
Replicate SNAP Rules 20 and 21 HFC Prohibitions for
the Polvurethane Industry
DuPont
May 10, 2021
Replicate SNAP Rule 20 with Regard to the Phase-out
of HFC-134a in Extruded Polystyrene Boardstock and
Billet (XPS) End-use
DuPont
May 10, 2021
Replicate SNAP Rule 21 with Regard to Rigid
Polvurethane Low-pressure Two-component Sprav
Foam (2K-LP SPF) End-use
Association of Home Appliance
Manufacturers (AHAM)
April 13, 2021
Restrict the Use of HFCs in Certain Air Conditioners
and Dehumidifiers
11 These petitions can be found at https://www.epa.sov/climate-hfcs-reduction/technolosy-transition-petitions-under-aim-act.
12 https://www .fedemlregister.eov/documents/'2021/10/14/2021 -22318/notice-of-determination-to-srant-or-partially-srant-
certain-petitions-submitted-under-subsection-i.
15
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Air-Conditioning, Heating, and
Refrigeration Institute (AHRI), et al.13
April 13, 2021
Restrict the Use of HFCs in Certain Commercial
Refrigeration EauiDinent
Air-Conditioning, Heating, and
Refrigeration Institute (AHRI), et al.
April 13, 2021
Restrict the Use of HFCs in Residential and Light
Commercial Air Conditioners
Environmental Investigation Agency
(EIA), et al.
April 13, 2021
Restrict the Use of HFCs in Certain Stationary
Refrigeration and Air Conditioning End-uses
Natural Resources Defense Council
(NRDC), et al.
April 13, 2021
Replicate HFC Prohibitions from SNAP Rules 20 & 21
The petitions cover approximately 40 sectors and subsectors. Sectors covered are aerosols, foam blowing,
and refrigeration, air conditioning and heat pumps. Within each of these, several subsectors are addressed
in the petitions and the Technology Transitions proposed rule. Table 1-2 provides the sector and
subsectors, GWP limits or prohibited substances, and compliance dates proposed.
Table 1-2 - Proposed restrictions and compliance dates by sector and subsector
Sectors and Subsectors
Proposal (HI P Limit or
Proli ihi ted Su bstan t e
C 'ompliance Date
kcrri<>cr;ilion. Air CoiHlilioiiin<>, :tiul llcnl I'limp
Industrial process refrigeration systems with refrigerant
charge capacities of 200 pounds or greater
150
January 1, 2025
Industrial process refrigeration systems with refrigerant
charge capacities less than 200 pounds
300
January 1, 2025
Industrial process refrigeration, high temperature side
of cascade systems
300
January 1, 2025
Retail food refrigeration - stand-alone units
150
January 1, 2025
Retail food refrigeration - refrigerated food processing
and dispensing equipment
150
January 1, 2025
Retail food refrigeration - supermarket systems with
refrigerant charge capacities of 200 pounds or greater
150
January 1, 2025
Retail food refrigeration - supermarket systems with
refrigerant charge capacities less than 200 pounds
charge
300
January 1, 2025
Retail food refrigeration - supermarket systems, high
temperature side of cascade system
300
January 1, 2025
Retail food refrigeration - remote condensing units
with refrigerant charge capacities of 200 pounds or
greater
150
January 1, 2025
Retail food refrigeration - remote condensing units
with refrigerant charge capacities less than 200 pounds
300
January 1, 2025
13AHRI submitted two additional petitions on August 19, 2021, and October 12, 2021. EPA is treating these two AHRI petitions
as addenda to their October 7, 2021, granted petition, and not as separate petitions, since the subsectors listed in these petitions
are contained in the granted AHRI petition and AHRI refers to these as further steps in the transition for these uses.
16
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Vending machines
150
January 1, 2025
Cold storage warehouse systems with refrigerant
charge capacities of 200 pounds or greater
150
January 1, 2025
Cold storage warehouse systems with refrigerant
charge capacities less than 200 pounds
300
January 1, 2025
Cold storage warehouse - high temperature side of
cascade system
300
January 1, 2025
Ice rinks
150
January 1, 2025
Automatic commercial ice machines - self-contained
with a charge size of 500 grams or less
150
January 1, 2025
Automatic commercial ice machines - self-contained
with a charge size of greater than 500 grams
R-404A, R-507, R-507A, R-
428A, R-422C, R-434A, R-421B,
R-408A, R-422A, R-407B, R-
402A, R-422D, R-421A, R-
125/R-290/R-134a/R-600a
(55/1/42.5/1.5), R-422B, R-424A,
R-402B, GHG-X5, R-417A, R-
438A, R-410B, R-410B, R-407A,
R-410A, R-442A, R-417C,
R407F, R437A, R407C, RS-24
(2004 formulation), HFC-134a
January 1, 2025
Automatic commercial ice machines - remote
R-404A, R-507, R-507A, R-
428A, R-422C, R-434A, R-421B,
R-408A, R-422A, R-407B, R-
402A, R-422D, R-421A, R-
125/R-290/R-134a/R-600a
(55/1/42.5/1.5), R-422B, R-424A,
R-402B, GHG-X5, R-417A, R-
43 8A, R-410B
January 1, 2025
Transport refrigeration - intermodal containers
700
January 1, 2025
Transport refrigeration - road systems
R-404A, R-507, R-507A, R-
428A, R-422C, R-434A, R-421B,
R-408A, R-422A, R-407B, R-
402A, R-422D, R-421A, R-
125/R-290/R-134a/R-600a
(55/1/42.5/1.5), R-422B, R-424A,
R-402B, GHG-X5, R-417A, R-
43 8A, R-410B
January 1, 2025
Transport refrigeration - marine systems
R-404A, R-507, R-507A, R-
428A, R-422C, R-434A, R-421B,
R-408A, R-422A, R-407B, R-
402A, R-422D, R-421A, R-
125/R-290/R-134a/R-600a
(55/1/42.5/1.5), R-422B, R-424A,
R-402B, GHG-X5, R-417A, R-
43 8A, R-410B
January 1, 2025
Residential refrigeration systems
150
January 1, 2025
Chillers - industrial process refrigeration
700
January 1, 2025
Chillers - comfort cooling
700
January 1, 2025
Residential and light commercial air conditioning and
heat pump systems
700
January 1, 2025
Residential and non-residential air conditioning -
variable refrigerant flow systems
700
January 1, 2026
17
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Residential dehumidifiers
700
January 1, 2025
Motor vehicle air conditioning - light-duty Passenger
Vehicles*
150
Model year 2025
Motor vehicle air conditioning - medium-duty
passenger vehicles
150
Model year 2026
Motor vehicle air conditioning - heavy-duty pick-up
trucks
150
Model year 2026
Motor vehicle air conditioning - Complete heavy-duty
vans
150
Model year 2026
Motor vehicle air conditioning - Nonroad vehicles
150
Model year 2026
Foam blowing
Polystyrene - extruded boardstock and billet
150
January I, 2025
Rigid polyurethane and polyisocyanurate laminated
boardstock
0
January 1, 2025
Rigid polyurethane - slabstock and other
150
January 1, 2025
Rigid polyurethane - appliance foam
150
January 1, 2025
Rigid polyurethane - commercial refrigeration and
sandwich panels
150
January 1, 2025
Rigid polyurethane - marine flotation foam
150
January 1, 2025
Rigid polyurethane - low pressure, two-component
spray foam
150
January 1, 2025
Rigid polyurethane - high-pressure two-component
spray foam
150
January 1, 2025
Rigid polyurethane - one-component foam sealants
150
January 1, 2025
Flexible polyurethane
0
January 1, 2025
Integral skin polyurethane
0
January 1, 2025
Polystyrene - extruded sheet
0
January 1, 2025
Polyolefin
0
January 1, 2025
Phenolic insulation board and bunstock
150
January 1, 2025
Aerosols
Aerosol products
150
January 1, 2025
*MY 2025 vehicles manufactured before one year after publication of a final rule would not be restricted.
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Chapter 2: Overview of the Analysis
2.1 Introduction
This analysis identifies the principal costs and benefits of implementing this rulemaking, if finalized as
proposed. Costs and benefits presented in this analysis include compliance costs, climate benefits, and
combined net benefits. While significant, the estimated benefits detailed in this document are considered
incidental and secondary to the rule's statutory objective of facilitating the transition to next-generation
technologies by restricting use of HFCs in the sectors or subsectors in which they are used.
Given that the proposed rules would place restrictions on HFCs, which are subject to the overall
phasedown of production and consumption under the AIM Act, EPA relied on previous analyses
conducted for the Allocation Framework Rule (86 FR 55116; October 5, 2021) and the proposed 2024
Allocation Rule (to be issued shortly before this Technology Transitions Rule) as a starting point for the
assessment of costs and benefits of this rule. We then evaluated how certain sectors and subsectors could
respond to the proposed restrictions in the form of GWP limits while the overall phasedown cap also
remains in place in order to determine potential incremental impacts.
A separate analysis included in this document evaluates the environmental justice impacts of the proposed
rule. As with the costs/benefits analysis, this assessment builds on an initial environmental justice
analysis conducted for the Allocation Framework Rule and expands on the previous approach to provide
additional insight into the demographic characteristics and baseline exposure of the communities near
facilities producing predominant HFC substitutes.
Finally, this analysis includes an assessment of the impact of restrictions on imports of products
containing HFCs. While the Allocation Framework Rule did not include imported products containing
HFCs in calculating the consumption baseline or require consumption allowances for their import, this
rule proposes to restrict imported and domestically manufactured products on an equal basis.
2.2 Organization of the Analysis
The analysis contained in the RIA addendum is organized as follows:
Chapter 3 summarizes the Allocation Framework RIA and specifically the results of the 2024 Allocation
Rule RIA addendum. These values are used as a starting point for this analysis, and effectively serve as
the primary reference case against which potential incremental impacts of the proposed rule are evaluated.
This chapter also discusses the potential for higher or lower incremental benefits from the proposed
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Technology Transitions Rule, depending on whether additional transitions in subsectors covered by the
proposed rule are offset by forgone transitions elsewhere.
Chapter 4 provides an assessment of the net costs of compliance (excluding climate benefits), based on
the GWP limits and specific restrictions proposed in this rule. As with the Allocation Framework RIA,
this assessment follows a Marginal Abatement Cost (MAC) approach, whereby the total costs and savings
associated with abatement options or "transitions" needed to meet compliance are calculated using EPA's
Vintaging Model (described below).14 This chapter also provides details on the general modeling
approach to modeling abatement and costs, as well as the specific market transition assumptions made in
order to estimate the impact of the restrictions in the proposed rule.
Chapter 5 discusses the climate benefits associated with the compliance pathway presented in chapter 4.
The use restrictions in the proposed rule would have an ancillary effect of leading to reduced consumption
of HFCs, which in turn would reduce HFC emissions. The reduction in emissions of these greenhouse
gases (GHGs) would yield social benefits by reducing climate impacts. These climate benefits are
monetized by multiplying the change in emissions of each regulated HFC by estimates of the social cost
of HFCs (SC-HFC) for that chemical. The methodology for calculating the SC-HFCs is described in
detail in Section 4.1 of the Allocation Framework RIA, and the SC-HFC values are given in Section 5.3.2
of this document.
Chapter 6 combines the compliance costs and climate benefit estimates from the preceding chapters in
order to provide an assessment of total net benefits associated with the rule as proposed.
Chapter 7 provides a sensitivity analysis of costs and benefits under alternative compliance scenarios
with either higher or lower subsector-specific GWP limits than those contained in the proposed rule. This
supplementary analysis is provided for illustrative purposes, and we note that economic costs and benefits
are only one factor of several used to determine the limits contained in the proposed rule.
Chapter 8 covers the environmental justice analysis conducted for the proposed rule. This analysis builds
on the environmental justice analysis conducted for the Allocation Framework Rule and evaluates the
demographic characteristics and baseline exposure of the communities near facilities producing
predominant HFC substitutes.
Annex A provides a summary of the mitigation technologies applied to the subsectors affected by this
rule as a means to model the costs and benefits of the proposed restrictions.
14 For additional information on the development and use of MAC curves, see section 3.2 of the Allocation Framework RIA.
20
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Annex B provides annual emission reductions by gas for the proposed Technology Transitions Rule base
case.
Annex C discusses the industries that might be affected by this proposed rule.
Annex D provides an assessment of the impact specifically of import restrictions. The Allocation
Framework Rule and proposed 2024 Allocation Rule do not require expenditure of allowances for
importing products containing HFCs; however, as explained in that annex, the analysis performed for
those rules was agnostic as to where products were manufactured, including both domestic consumption
of HFCs and imports of products containing HFCs. When projecting the U.S. demand for products
containing HFCs, the Vintaging Model and MAC curves do not distinguish between products
manufactured in the U.S. and those that are imported from other countries. Hence, some portion of the
HFC consumption reduction estimated in the RIA for the Allocation Rules reflects the adoption of lower-
GWP alternatives in products imported from other countries, although the adoption of lower-GWP
substances in imported products would not be the direct result of compliance with the Allocation Rules.
The Technology Transitions Rule proposes GWP limits and specific restrictions for both imported and
domestically produced equipment; therefore, a scoping analysis was performed to estimate the effects of
such restrictions on imported products containing HFCs. To the extent that the Allocation Rules' analyses
include reductions due to imported products containing HFCs, those analyses may underestimate the
domestic adoption of abatement options required to meet the AIM Act consumption caps. This, in turn,
may result in an overestimate of the subsequent availability of options for the abatement in domestically
produced equipment to comply with the lower-GWP requirements of this proposed rule.
Annex E provides a demonstration analysis using a geospatially disaggregated "microsimulation" model
to assess communities near facilities identified as producing predominant HFC substitutes. The tool used
is an example of microsimulation approaches using recent advancements in data science, and which can
offer insight into the characteristics of communities by statistically representing "synthetic populations."
These techniques show promise for improving analysis for many issues, including environmental justice.
We include the demonstration analysis, which identifies communities for which further environmental
justice analysis may be warranted, and seek comment on and discussion of the use of microsimulation
techniques for potential future environmental justice analyses.
2.3 Years of Analysis
This analysis estimates the costs for technology transitions that meet the HFC restrictions as proposed.
The earliest required compliance date is January 1, 2025; however, we assume some "early actors" will
21
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begin certain transitions sooner, consistent with assumptions made in the Allocation Framework RIA. We
have assumed here that full compliance would be reached within each subsector no later than the
associated date proposed. For the purpose of evaluating the climate benefits due to emission reductions
that lag the restriction compliance dates, we look at consumption reductions associated with continued
compliance with the proposed Technology Transitions Rule restrictions through 2050. We further assume
that no "backsliding" occurs and that—once established—sector transitions carry on through the entire
2025-2050 period covered by this analysis.
2.4 Factors Analyzed
This RIA addendum takes into consideration the costs of technology transition options to meet the
proposed restrictions and the environmental benefits of the consequent reduction in HFC emissions and
the associated avoided global warming. As explained in the Allocation Framework RIA, specific factors
evaluated in this assessment include capital costs, operations and maintenance (O&M) costs, and any
anticipated energy savings resulting from transitions to lower-GWP technologies. This analysis does not
take into account certain factors that could potentially further reduce compliance costs, such as potential
decreases in costs over time resulting from economies of scale or the energy savings from reduced
cooling demand as a result of avoided global warming.
2.5 Vintaging Model
EPA uses the Vintaging Model to forecast the use and emissions of HFCs and other substances, by sector
and subsector, under a BAU scenario and under various policy compliance scenarios. This analysis uses a
version of the model intended to represent compliance with the AIM Act HFC Phasedown as a starting
point and makes adjustments in various sectors as needed to align with the available abatement options
for the proposed GWP limits. The resulting consumption and emissions are compared against the analysis
developed for the Allocation Framework Rules to evaluate incremental impacts.
The model tracks the use and emissions of each of the substances separately for each generation or
"vintage" of equipment. The Vintaging Model is used to produce the estimates of GHG emissions in the
official U.S. GHG Inventory and is updated and enhanced annually. Information on the version of the
model used for this analysis, the various assumptions used, and HFC emissions may be found in EPA's
22
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Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2014,15 A more detailed explanation of the
Vintaging Model may also be found in section 3.2.1 of the Allocation Framework RIA.
As explained in section 3.3.2 of the Allocation Framework RIA, the Vintaging Model assumes some
transition to lower-GWP substances is occurring in the baseline, not as a response to the AIM Act. Some
of these baseline market transitions would meet the requirements proposed in the Technology Transitions
Rule, avoiding the need to model technology transition options to reach compliance.
Due to the nature and limitations of the Vintaging Model, the MAC analysis from the Allocation
Framework RIA, the proposed 2024 Allocation Rule RIA Addendum, and the this RIA addendum cover
the projected impact of compliance for the full U.S. market in aggregate. This includes both domestically
produced and imported products utilizing regulated substances. Since the model on its own does not
distinguish between domestic consumption of regulated HFCs versus imported products containing
regulated HFCs, a separate Annex to this RIA addendum evaluates the impact of the import restrictions
specifically. As mentioned in that Annex, the impacts of the import restrictions are a subset of—rather
than additional to—the benefits presented in this analysis.
2.6 Regulatory Option
As noted in the Technology Transitions proposal, EPA is considering two approaches to restricting
regulated substances under the authority of AIM Act subsection (i). They are: (1) to set GWP limits for
HFCs used within a sector or one or more subsectors, whether neat or used in a blend; and (2) to restrict
specific HFCs or specific blends containing HFCs by sector or one or more subsectors. The Rule as
proposed would use the approach of setting GWP limits for all but three subsectors. These restrictions
have been modeled accordingly, by sector and subsector, in order to estimate the impact of the Rule. For
additional details, see Abatement Options Modeled in the Chapter 4 below.
The primary costs/benefits analysis conducted for this RIA addendum is based on assumed transitions to
HFC substitutes based on the subsector-specific GWP limits in the rule as proposed. As a bounding
exercise, we have also included in this RIA addendum an analysis of potential costs and benefits of this
rule under alternative regulatory scenarios, one where GWP limits are 50% lower than proposed, and one
where they are 50% higher. This supplementary analysis helps illustrate the extent to which costs and
benefits may shift under more or less restrictive limits, while also demonstrating that in many cases
impacts would be essentially unchanged. Importantly, this supplementary analysis is conducted for
15 U.S. EPA. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2014. April 2016. EPA Report EPA-430-R-16-002.
Available at https://www.epa.zov/shzemissions/inventory-iis-zreenhouse-zas-emissions-and-sinks-l 990-2014.
23
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illustrative purposes only. We note that EPA has set the specific GWP limits set for the subsectors
covered by the proposed rule based on a number of factors besides overall economic cost, including best
available data, availability of substitutes (taking into account factors such as technological achievability,
commercial demands, affordability for residential and small business consumers, safety, consumer costs,
building codes, appliance efficiency standards, contractor training costs), and environmental benefits.
More detail on this analysis can be found in Chapter 7 of this RIA addendum.
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Chapter 3: HFC Allocation Framework Rule Baseline
3.1 Introduction
This chapter discusses the HFC consumption baseline established by the Allocation Framework Rule, 40
CFR 84, subpart A, and the estimated costs and benefits of the HFC phasedown as detailed in the
Allocation Framework RIA. These values represent the status quo from which potential incremental costs
and benefits of the proposed Technology Transitions Rule are calculated.
For the purposes of this analysis, we specifically rely on the estimates from the 2024 Allocation Rule RIA
addendum, which are themselves a revision to the estimates from the original Allocation Framework RIA.
The revision reflects updated costs and benefits resulting from a lowered HFC consumption baseline as
well as an adjustment to an abatement option based on information from industry stakeholders. These
estimates are therefore the most up-to-date and relevant reference point from which to quantify additional
impacts. More details on these updates can be found in sections 1.3 and 2.4 of the 2024 Allocation Rule
RIA addendum.
3.2 Baseline for Allocation of Consumption Allowances
Through the Allocation Framework Rule issued under the AIM Act, 40 CFR 84, subpart A, EPA has
established a consumption baseline for the phasedown ofHFCs. The consumption baseline was
established using the average annual quantity of all regulated substances consumed in the United States
from lanuary 1, 2011, through December 31, 2013, and additional quantities of past chlorofluorocarbon
(CFC) and hydrochlorofluorocarbon (HCFC) consumption. More details on the methodology used to
establish this baseline can be found in the Allocation Framework Rule.16 The baseline serves as the
starting point from which statutorily mandated percentage reductions are taken to implement the AIM Act
HFC phasedown.
As detailed in the proposed 2024 Allocation Rule RIA, EPA is proposing to update the consumption
baseline to correct for data that had previously been inaccurately reported. The change would lead to a
revision of the consumption baseline from 303,887,017 MTEVe17 to 300,257,386 MTEVe and associated
revisions to the total consumption cap in each year after the revision takes effect, as the phasedown
schedule is determined as a percentage of the baseline under subsection (e)(2)(C) of the AIM Act, which
16 https://www.federalresister.sov/documents/2021/10/05/2021-21030/phasedown-qf-hydrofluorocarbons-establishins-ihe-
allowance-allocation-and-trudins-prosram-imder-the.
17 As explained in the Allocation Framework Rule, a metric ton of exchange value equivalent (MTEVe) is numerically equal to a
metric ton of carbon dioxide equivalent (MTCC>2e).
25
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EPA codified at 40 CFR 84.7(a). It is this updated consumption baseline that is used as a reference point
in this analysis and the associated revisions to total consumption are shown in figures below.
Table 3-1: Proposed Consumption Caps of the HFC Phasedown
) ear
Proposed Revised Total
Consumption (Mllil e)
Percentage of Starting
liaseline
2024-2028
180,154,432
60%
2029-2033
90,077,216
30%
2034-2035
60,051,477
20%
2036 and thereafter
45,038,608
15%
3.3 HFC Consumption under BAU Projection and Allocation Rule Reference
Case
The Allocation Framework RIA and 2024 Allocation Rule RIA addendum estimate reductions in HFC
consumption and resulting benefits relative to a "Business as Usual" (BAU) scenario of expected
consumption and emissions of HFCs in the absence of regulations promulgated under the AIM Act,
derived from EPA's Vintaging Model. Although many economic analyses will use the term "baseline" to
describe such a forecast, for the purposes of these previous analyses we referred to the projection as a
BAU forecast to distinguish it from the baselines described above from which maximum HFC production
and consumption levels are to be calculated under the AIM Act.
For this analysis, the Allocation Framework Rule with the adjustments in the proposed 2024 Allocation
Rule is the relevant point of comparison and effectively serves as the "BAU" to determine incremental
impacts, given its precedence as existing policy. As a disambiguation, throughout this document we refer
to the Allocation Framework Rule estimates as the "Allocation Rule Reference Case" rather than "BAU,"
to avoid confusion with the BAU scenario included in the Allocation Framework RIA.
Table 3-2 below shows the consumption based BAU originally used to quantify benefits in the Allocation
Framework Rule analysis and the proposed 2024 Allocation Rule analysis, as well as estimated
consumption under the Allocation Rule Reference Case. The latter is used to quantify incremental
benefits in this analysis.
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Table 3-2: HFC Consumption under the OriginalBAUand the Allocation Rule Reference Case
(MMTEVe)
Yeur
/// "(' C o/isu/nprion under
B it (i.e.. no AIM Act)
lll 'C' ( onsumptio/i under
Allocution Rule Reference
( use (i.e., irirh . MM. \ct cup)
2024
324.43
178.43
2029
316.55
86.55
2034
326.44
59.44
2036
326.98
43.98
2045
352.14
66.14
2050
365.93
71.93
The BAU scenario used to quantify benefits under the Allocation Framework Rule does not include
certain transitions that may otherwise have occurred either as a result of separate regulations at the state
or federal level or due to market forces. For a more detailed description of transitions included and not
included in the BAU, as well as a sensitivity analysis including alternative BAUs, see sections 3.3.2 and
Appendix B, respectively, of the Allocation Framework RIA.
3.4 Approach to Evaluating Incremental Benefits of the Technology
Transitions Rule
The cost/benefit analysis contained in this document considers the potential for incremental benefits
resulting from the proposed Technology Transitions Rule. In practice, this means only counting additional
emission reductions from BAU beyond those previously quantified in in the Allocation Framework RIA
and updated 2024 addendum (i.e., incremental to the Allocation Rule Reference Case).
As discussed above, the Allocation Framework Rule establishes a pool of allowances which decrease over
time in accordance with the overall phasedown schedule. These allowances are to a degree
interchangeable, meaning that additional abatement stemming from the restrictions in the proposed
Technology Transitions Rule could conceivably be offset by corresponding increases in HFC
consumption in subsectors not covered by the rule, so long as the overall HFC phasedown compliance
caps are still met. To deal with the inherent uncertainty, we modeled two scenarios.
1) A "base case" where all subsectors covered by restrictions contained in the proposed rule are
assumed to make transitions needed to meet those restrictions, but consumption reduction
27
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activities in subsectors not covered by the proposed Technology Transitions Rule are
excluded, even if previously assumed in the Allocation Rule Reference Case. This scenario
effectively represents a conservative representation of the additionally of this rule.
2) A "high additionality case" where any transitions and resulting abatement assumed in the
Allocation Rule Reference Case is retained in the Technology Transitions scenario, even in
subsectors not technically covered by this rule. This effectively represents an upper bound of
the potential incremental benefits of the proposed rule.
Annex table A-3 provides details on transitions assumed in various subsectors in both the Allocation Rule
Reference Case and the Technology Transitions Base Case. The high additionality case retains abatement
options from the Allocation Rule reference case even if they are not covered by the Technology
Transitions Rule. These include actions take in the fire protection subsector, and improved leak repair,
additional recovery at disposal, and enhanced recovery at servicing for RACHP equipment.
As discussed in the presentation of results later in this document, both the base case and high additionality
case meet compliance with the phasedown cap and yield additional consumption reductions relative to the
Allocation Rule Reference Case. However, the high additionality case ultimately yields the greatest
incremental benefits in terms of reduced consumption and emissions.
Finally, we note that the primary purpose of the Technology Transitions Rule as proposed is not to
capture additional emissions benefits or savings, but to facilitate transitions in certain sectors and
subsectors by restricting the use of HFCs in those sectors and subsectors. To the extent that additional
benefits are captured, these can be considered ancillary.
28
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Chapter 4: Compliance Costs
4.1 Introduction
This RIA addendum estimates the technology transition costs associated with meeting the proposed GWP
limits, as well as the costs associated with the recordkeeping, reporting, and labeling requirements
proposed. While social costs are the most comprehensive measure of costs of a regulation, estimation of
the social costs associated with this rule are beyond the scope of the analysis. The technology transition
costs associated with the rule and the methodology for modeling costs are described in this chapter.
4.2 Modeling Method for Technology Transition Costs
To generate cost estimates for the technology transitions proposed, EPA relied on a methodology
consistent with the approach used in the Allocation Framework RIA (see section 3.2 of the Allocation
Framework RIA). As before, abatement options—or in this case transitions that comply with the
restrictions proposed by the rule—were used to estimate the consumption and emission reductions, the
costs, and the societal benefits associated with compliance. The reductions achieved through
implementing these options are evaluated against both (1) the same "business as usual" (BAU) forecast of
HFC consumption and emissions, generated from EPA's Vintaging Model, used in the Allocation
Framework RIA, and (2) "incremental" benefits beyond those already assessed in the Allocation
Framework RIA as amended by the proposed 2024 Allocation Rule (i.e., the Allocation Rule Reference
Case). An evaluation against the BAU is required because the analytic period for the Allocation Rules and
this Technology Transition Rule overlap. Some of the technology transitions assumed in the Allocation
Rules will no longer be valid given the GWP-limits and subsector-specific restrictions.
Thus, a key methodological distinction between the method applied for this analysis and the Allocation
Rule's RIAs is that only abatement options meeting the proposed Technology Transitions Rule
restrictions for each subsector are modeled. For example, if the proposed restriction for the large retail
food sector requires a transition to technology utilizing substances below a GWP threshold of 150 to 300,
depending on charge size, in year 2025, then only options below this threshold that we have modeled to
date (i.e., transitioning to CCh-based refrigerant systems) are assumed to be viable compliance options
once the restriction kicks in. This differs from the approach taken for the Allocation Framework Rule,
where additional, potentially higher-GWP options (i.e. options exceeding the threshold of the limits in
this proposed rule) may have been assumed to be available as compliance options so long as the overall
cap was still met.
29
-------
As a further point of clarification, many of the transitions required by the Technology Transitions Rule
and included in this analysis are expected to take place regardless of the proposed rule, since they would
be likely to occur given the AIM Act HFC phasedown and other state and local laws and regulations.18
The AIM Act HFC phasedown does not prescribe specific transitions and it is not clear if absent the
Technology Transitions Rule the same transitions would be made at the same time. This analysis
therefore may not accurately predict transition paths but provides an assessment stemming from the
proposed restrictions in the Technology Transitions Rule to more closely evaluate the projected costs and
benefits.
4.3 Abatement Options Modeled
As discussed above, this analysis relies on the version of the Vintaging Model used to evaluate the impact
of the Allocation Framework Rule as updated by the proposed 2024 Allocation Rule. Assumptions for
various sectors and subsectors are then modified, with some additional transitions added or—in cases
where they do not meet the restrictions—removed in order to conform with the Technology Transitions
Rule requirements.
The two regulatory options discussed in section 2.6 of either GWP- or compound-specific restrictions do
not affect the modeling approach. Where a GWP limit is proposed for a subsector, we modeled transitions
to alternatives that comply with that GWP limit. For the few cases where specific HFCs and specific
blends containing HFCs are proposed to be restricted (i.e., prohibited), the GWP of the restricted HFC or
blend with the lowest GWP is modeled as the de facto GWP limit.
Table 4-1 below shows the Technology Transitions Rule requirements by sector/subsector and the
transitions assumed in order to model compliance. The transitions listed in the table represent a "best
guess" of expected technological changes at the time this analysis was conducted and should by no means
be interpreted as a prescriptive list.19
18 For example, several states have already implemented restrictions, or will implement such restrictions before this rule's
proposed January 1,2025, initial compliance date, for stand-alone retail food refrigeration and household refrigerator-freezers;
the states include California, Colorado, Delaware, Maine, Maryland, Massachusetts, New Jersey, New York, Rhode Island,
Virginia, Vermont, and Washington. Additionally, California has adopted, and Washington has proposed, restrictions for
residential and variable refrigerant flow systems in light commercial air conditioning units and heat pumps.
19 Certain restrictions in the proposed Technology Transitions Rule are not shown here and are not assumed to undergo a future
transition, because a transition of the entire market to a substitute compliant with the proposed restrictions was assumed in the
baseline model, and/or because the model used does not break out a specific subsector in the manner addressed in the NPRM.
30
-------
Table 4-1: Proposed Restrictions and Transitions Assumed
Suhsector
(ill 1* Limit
C o/npliaiice
) car
. \ssumed 1 ransirion(s) Included
in Mode!
Centrifugal Chillers
700
2025
HFC-134a replaced w/ R-450A/R-
513 A; HFC-245fa replaced w/ HCFO-
1233zd(E)
Screw Chillers
700
2025
HFO-1234ze(E)
Scroll Chillers
700
2025
HFO-1234ze(E)
Reciprocating Chillers
700
2025
R-452B
Industrial Process
150
2025
NH3/CO2
Refrigeration** (>=200 lb
charge size)
Industrial Process
300
2025
NH3/CO2
Refrigeration** (<200 lb charge
size or high side of a cascade
system)
Cold Storage (>=200 lb charge
150
2025
NH3/CO2
size)
Cold Storage (<200 lb charge
size or high side of a cascade
300
2025
NH3/CO2
system)
Large Retail Food (>=200 lb
150
2025
CO2 Transcritical
charge size)
Large Retail Food (<200 lb
300
2025
CO2 Transcritical
charge size or high side of a
cascade system)
Medium Retail Food (>=200 lb
150
2025
C02
charge size)
Medium Retail Food (<200 lb
300
2025
C02
charge size)
Small Retail Food
150
2025
HCs
Vending Machines
150
2025
R-290
Ice Makers, Self-Contained
700
2025
R-290
Ice Makers, Remote
2200*
2025
R-448A/R-449A
Refrigerated Transport—
Intermodal Containers
700
2025
R-450A/R-513A
Refrigerated Transport—Marine
and -Road
2200*
2025
R-452A
Household Refrigerator-
150
2025
R-600a
Freezers
Residential Dehumidifiers
700
2025
R-32
Window A/C Units
700
2025
R-32
Residential Unitary A/C
700
2025
R-454B
Small Commercial Unitary A/C
700
2025
R-32
Large Commercial Unitary A/C
700
2025
R-32
Water & Ground Source HP
700
2025
R-32/R-452B
PTAC/PTHP
700
2025
R-32/R-452B
31
-------
Non-MDI Aerosols
150
2025
HFC-134a to HFC-152a; HFC-
134a/HFC-152a to Not-in-kind (NIK),
HCs, HFO-1234ze(E)
Aerosol Solvents
150
2025
NIK Aqueous and Semi-aqueous clean
Rigid Polyurethane (PU)
Appliance Foam
150
2025
HCs, HCFO-1233zd(E)
Rigid PU Commercial
Refrigeration Foam
150
2025
HFC-245fa to HCFO-1233zd(E)
Rigid PU Sandwich Panels
150
2025
HFC-134a to HCs; HFC-245fa/C02 to
HCFO-1233ze(E)
Polystyrene Extruded
Boardstock and Billet Foam
150
2025
HFO-1234ze(E)/HCFO-1233zd(E)
Integral Skin PU Foam
0
2025
HCs
Rigid PU and Polyisocyanurate
Laminated Boardstock
0
2025
HCs
Spray Foam
150
2025
HFC-134a to HFO-1234ze(E); HFC-
245fa to HCFO-1233zd(E), HFO-
1234ze(E)
*Subsectors for which EPA is proposing to apply restrictions on specific blends containing HFCs, and are modeled
as having an effective GWP limit of 2200 as a result
** Restrictions on Chillers used for Industrial Process Refrigeration are the same as those for the different types of
chillers (i.e., centrifugal, screw, scroll, and reciprocating chillers with a GWP limit of 700), with the exception that
chillers with a leaving fluid temperature below -58°F (-50°C) used in IPR are not restricted
4.4 Costs of Transition
To quantify compliance costs, EPA used estimates of the assumed cost of each transition (including
capital and operations and maintenance costs), by sector and subsector, calculated on the basis of each ton
of avoided consumption. Costs of a particular transition may be either net positive or net negative in cases
where a particular transition results in savings (e.g., due to energy efficiency) that outweigh expected
costs. The result is an estimate of the costs to U.S. companies to implement changes (i.e., transitions) that
would align with the restrictions contained in the proposed rule.
EPA calculated how much consumption would be reduced in the Technology Transitions scenarios (base
case and high additionally case) by evaluating what options would be needed to achieve compliance
within each sector and subsector, how much of the market those transitions would capture, and how
quickly they would happen. While compliance years for specific restrictions proposed in this rule do not
start until 2025 at the earliest, EPA assumed a ramp-up period for certain transitions in the years leading
up to 2025 in anticipation of the rule.
Table 4-2 below shows a subset of subsectors where there are notable differences between the Allocation
Rule Reference Case and the Technology Transitions base case. The table illustrates how the two analyses
differ in terms of assumed transitions depending on the subsector EPA evaluated. For example, for the
Heat Pumps subsector, both scenarios include the same transition option (conversion to R-452B).
32
-------
However, whereas the market penetration rate of this transition in the base case increases to 100% by
2025 in order to align with restrictions in the Technology Transitions Rule, a similar transition does not
begin until later years (2026 in this example), and impacts a smaller portion of the market (50% in this
example) in the Allocation Rule Reference Case. This leads to higher compliance costs in the Technology
Transitions base case given the earlier and more comprehensive transition required for that subsector. As
another example, in the retail food sector, the set of abatement options from the Allocation Rule
Reference Case is narrowed exclusively to transitions that meet the required GWP limit of the proposed
rule—specifically the conversion to CCh-based refrigeration systems—which have a markedly higher
reduction efficiency (i.e., abatement potential). This conversion is assumed to be net negative in terms of
costs to industry due to energy efficiency gains and the lower cost of the refrigerant being used.
Finally, there are multiple subsectors where no transition or abatement is assumed in the Technology
Transitions base case even though options are included in the Allocation Rule Reference Case, such as the
fire suppression subsectors. These "forgone" abatement options are excluded because they are not
covered by the proposed rule. Despite the forgone abatement, we note that the Technology Transitions
base case would be sufficient to meet the AIM Act HFC phasedown schedule without their inclusion due
to consumption reductions in other subsectors. As discussed in section 3.3 of this document, the
Technology Transition rule may have greater or less incremental abatement and costs in a given sector or
subsector relative to the Allocation Rule Reference Case depending on whether such abatement options
are assumed to be undertaken or not. To deal with this uncertainty, we separately include a "high
additionally" case where these transitions are not assumed to "backslide" in the Technology Transitions
scenario and are included.
Table 4-2: Assumed Transitions in the Allocation Rule Reference Case and Technology
Transitions Base Case
Note: This table provides details on a subset of transition assumptions with notable differences between
the Allocation Rule Reference Case and Technology Transitions base case scenario. A table listing all
transitions assumed for each scenario is included in Annex table A-3.
Allocation Rule Reference C ase technology Transitions (/iase C ase)
transition lieiluctiou MP ( ost liunsitioii. deduction Ml* ('ost
... , . Substitute iljjicicncy (2025) (S ion) Substitute lij/icieucy (2025) (S inn)
Heat Pumps
R-32/R-452B
67%
0%
$5
R-32/R-452B
67%
100%
$5
R-290
100%
19%
$1
R-290
100%
50%
$1
Ice Makers
Not included
R-448A/R-
449A
58%
50%
$6
Large Retail
Food
DX
407A/407F
50%
34%
$(16)
Not included**
33
-------
C02
Transcritical
100%
33%
$(11)
404A/507A
to C02
Transcritical
100%
100%
$(11)
407A/407F
SLS
50%
33%
$(0)
Not included**
Not included
407A to C02
Transcritical
100%
67%
$(20)
Medium Retail
Food
C02
100%
33%
$(3)
CO 2
100%
100%
$(3)
DX
407A/407F
50%
67%
$-
Not included**
PU Rigid: One
Component
Foam
134a to HFO-
1234ze
100%
30%
$8
134a to HFO-
1234ze
100%
100%
$8
Residential
Unitary
R-454B
78%
75%
$6
R-454B
78%
100%
$6
Service
RACHP
subsectors
95%
40%
$23
Not included *
HCs
100%
10%
$(7)
HCs
100%
100%
$(7)
Small Retail
Food
R-448A/R-
449A
65%
70%
$5
Not included**
R-450A/R-
513A
57%
20%
$23
Not included**
Vending
Machines
R-450A/R-
513A
63%
100%
$19
Not included**
R-290
100%
10%
$96
R-290
100%
100%
$96
Window Units/
Dehumidifiers
R-32
68%
27%
$(D
R-32
68%
100%
$(D
XPS:
Boardstock
Foam
134a/C02 to
1234ze(E)/12
33zd(E)
100%
51%
$8
134a/C02 to
1234ze/1233
zdE
100%
100%
$8
NIK Aqueous
100%
5%
$33
NIK Aqueous
100%
2.5%
$33
Electronics
Cleaning
NIK Semi-
aqueous
100%
5%
$70
NIK Semi-
aqueous
100%
2.5%
$70
HFE-7100/
HFE-7200
85%
53%
$0
Not included in base case (alternative not used as
an aerosol solvent)*
HFE-7100/
HFE-7200
85%
73%
$0
Not included in base case (alternative not used as
an aerosol solvent)*
Precision
Not included f
NIK Aqueous
100%
2.5%
CO
m
-to-
Cleaning
Not included +
NIK Semi-
aqueous
100%
2.5%
o
r->
¦CO-
Disposal
RACHP
subsectors
85%
100%
$14
Not included*
Flooding
Agents
Inert Gas
100%
10%
$(7)
Not included*
Water Mist
100%
1%
$(7)
Not included*
FK- 5-1-12
100%
35%
$3
Not included*
Leak Recovery
RACHP
subsectors
40%
100%
$(D
Not included*
"fTransition not assumed in Allocation Rule Reference Case, due to availability of less expensive and/or more
commercially established options
*Transition not assumed in Technology Transitions base case because subsector is not covered by the proposed
rule, despite inclusion in Allocation Rule Reference Case. These subsectors are included in the Technology
Transitions high additionality case (please see section 3.3 of this R1A addendum for discussion of alternative
scenarios of potential incremental benefits).
34
-------
** Transition is not assumed in Technology Transitions Rule base case scenario nor the high additionally case
because it is above the subsector GWP limit in the proposed rule.
After evaluations of the full set of transitions required to meet compliance with the proposed Technology
Transitions Rule, as with the Allocation Framework RIA, total compliance costs were analyzed based on
total abatement associated with each transition for each year, and the assumed cost of each transition.
Costs reflect capital (one-time) cost, revenue, and operating and maintenance costs (annual), and are
calculated on a per MTEVe (in avoided consumption) basis. They are present value in 2020 dollars,
utilizing a 9.8 percent opportunity cost of capital and 0 percent tax rate. Transitions and costs are also
calculated on a year-by-year basis, which accounts for the fact that most options require time for stock
turnover to fully implement options.
Total annual net costs (or savings) associated with both the Allocation Rule Reference Case and
Technology Transitions compliance scenarios are shown in table 4-3 below.
Table 4-3: Costs of Compliance* by Year (billions of2020$) in Allocation Rule Reference Case
and Technology Transitions Scenarios
Allocation Rule
Reference ( use
I echnology / ransitions - liase
( ase
t echnology transitions - High
. \t/(lirionaliry C 'ase
) ear
( osrs,Savings
(billions of
202OS)
C osrs/Savings
-------
certain subsectors are not assumed to transition as rapidly or completely, in some cases resulting in
forgone cost savings (e.g., in the Large Retail Food subsector). All three graphs represent all options
assumed to be undertaken in order to meet compliance, so the right-most data point shows the resulting
consumption and total cost in a given year (i.e., the rightmost points represent final consumption and net
costs in each year after all required options are applied).
Figure 4-1 - Technology Transition Base Case Cost Curve
Residential AC
Transitions (net
positive costs)
Large Retail Food
Transitions (net
negative costs)
Cost Pathway - Technology Transitions Scenario
-$1.5
-$2.0
-•-2025
-•-2030
-•-2035
200 150
Total U.S. HFC Consumption
Figure 4-2 - Technology Transitions High Additionality Case Cost Curve
Residential AC
Transitions (net
positive costs)
Large Retail Food
Transitions (net
negative costs)
-$0.5
Cost Pathway - Technology Transitions Scenario
-$1.0
-$1.5
-$2.0
-•-2025
-•-2030
-•-2035
200 150
Total U.S. HFC Consumption
36
-------
Figure 4-3 - Allocation Rule Reference Case Cost Curve
Cost Pathway - Framework Rule Compliance Case
SO.5
$0.0
§ -$0.5
J3
¦uv
o
IM
O
IN
O
U
-$1.0
-$1.5
-$2.0
-$2.5
-$3.0
large Retail Foo
d
\ nesiaeniiai mi_
Transitions (net
positive costs)
Transitions (net
negative costs)
-2025
-2030
-2035
350
300
250 200 150
Total U.S. HFC Consumption
100
50
Figure Description: Each curve in Figures 4-1 through 4-3 above starts with total costs incurred with the cheapest
(or most cost-effective) transition applied, with more expensive options added on as the curve moves left to right.
Points to the left of the low point on each curve represent transitions with assumed net negative (or cost saving)
costs, while points to the right of the low point on each curve represent transitions with assumed net positive costs.
The rightmost point on each curve for a given year in each figure represents the final total net cost with all required
transitions being applied. Two transitions that result in significant levels of abatement in the Technology Transitions
scenario, one at a net negative cost (large retail food) and one at a net positive cost (residential AC), are highlighted
in the figures.
These results indicate that the proposed Technology Transitions Rule will not result in significant
additional compliance costs relative to the Allocation Rules, and in fact may yield additional abatement
over time. In other words, it would result in additional abatement while reducing compliance costs. In
some respects, this finding could be viewed as counterintuitive. Whereas the Allocation Rules analysis
assumes a "least cost" pathway to compliance based on available abatement options, the Technology
Transitions pathway applies sector-based restrictions regardless of transition costs. It follows then that
such restrictions could be expected to result in added costs.
That the Technology Transitions scenario instead shows additional net savings in both the base case and
high additionally case stems largely from the more rapid and more comprehensive transition to cost-
saving, lower-GWP technologies in particular sectors and subsectors required by the rule. A similarly
comprehensive transition is not assumed to be an "available" abatement option in the Allocation Rules
analysis, since it assumed that the market penetration rates of newer technologies will face more industry
inertia and shift less rapidly without an explicit regulation in place, regardless of potential energy savings
or other benefits over time. While the rate of such industry transitions is ultimately uncertain, a significant
body of literature indicates that in many cases market actors will favor existing technologies and discount
37
-------
energy savings without incentives or regulations, as discussed in section 3.2.2 of the Allocation
Framework RIA.
An example of how these assumptions impact the modeled results is highlighted in the above figures,
where abatement and cost savings in the retail food subsector is assumed to be significantly deeper in the
Technology Transitions scenarios vis-a-vis the Allocation Rule Reference Case. By contrast, the
transitions for the residential AC subsector (also highlighted in the figures above) are similar in both
scenarios, as the GWP limits contained in the proposed rule would not require a substantially different
transition than was previously modeled in the Allocation Rule Reference Case. For a detailed breakdown
of incremental abatement and costs by subsector, please see annex table A-4 of this document.
Since costs are ultimately a reflection of the full suite of transitions assumed in the compliance pathway,
changes in assumed technology costs, rates of adoption, or abatement options assumed to be "available"
in a particular scenario can significantly impact results. The model is sensitive to assumed transition
costs, particularly those which result in high levels of abatement and/or which are high-cost or high-
saving. The Allocation Framework RIA contains a sensitivity analysis showing costs of compliance for
the phasedown rule ranging from a lower bound estimate of $15.7 billion in cumulative savings to an
upper bound estimate of $15.3 billion in cumulative costs through 2036. These sensitivity results are
indicative of the potential uncertainty associated with the Technology Transitions Rule results as well,
given the similar methodology and transition assumptions used for both.
4.5 Labor Impacts
An assessment of potential labor impacts is included in the RIA EPA previously conducted for the
Allocation Framework Rule. That analysis, which includes details on the baseline employment
characteristics for regulated industries, potential employment impacts, and potential impacts on
downstream production processes, can be found in section 3.7 of the Allocation Framework RIA.
Overall, we assess the proposed Technology Transitions Rule as unlikely to have substantial labor
impacts differing from those discussed in this previous analysis. EPA has therefore not endeavored to
conduct an additional assessment of labor impacts. As with the Allocation Framework Rule, we expect
the industry transitions required by the proposed rule to result in small changes to costs, both positive and
negative, for HFC producers, importers, and consumers. We also note that on the whole these regulatory
costs may represent only a small fraction of total costs at regulated firms. Also as noted in the previous
RIA, labor, along with capital and materials, will be required for the conversion activities that will
accommodate production of HFC substitutes. These will likely be transitional, short-run labor costs as
38
-------
production processes are adjusted, and Labor impacts may further be muted due to the low labor intensity
of production in the chemical manufacturing sector in general.
4.6 Recordkeeping, Reporting, and Labeling Costs
As part of the process to implement the recordkeeping, reporting, and labeling requirements of the
proposed Technology Transitions Rule, EPA has prepared an information collection request (ICR), ICR
Number [XXXXXX], and a Supporting Statement Part A for the ICR, all of which can be found in the
docket. The information collection requirements are not enforceable until OMB approves them. Among
other figures, EPA calculated the estimated time and financial burden over a three-year period (ICRs
generally cover three-year time periods) for respondents to implement labeling practices and to
electronically reporting data to the Agency on a quarterly basis using an interactive, web-based tool called
the Electronic Greenhouse Gas Reporting Tool (e-GGRT). A key summary of the respondent burden
estimates follows, and the full methodology for these calculations can be found in the docket.
For the three years covered in the ICR, the total respondent burden associated with information collection
will average 60,798 hours per year and the respondent cost will average $26,019,764 per year.20 This
includes $19,955,215 for capital investment and operation and maintenance (O&M) and $6,064,549 per
year for labor. The breakdown of the burden per year is provided in Table 4-4a in 2022 dollars and in
Table 4-4b in 2020 dollars to align with other analyses in this document.
The ICR will be subject to renewal after the three-year time period is over. For purposes of analysis, we
assume the on-going costs will be equivalent to the year 2 and year 3 costs of $25,475,817 per year.
Table 4-4a: Total Respondent Burden Costs Over the Three-Year ICR Period (2022$s)
) ear
Total
/{espouses
Total
Hours
lor nl
Labor
( osts
(2020S)
Total OAM
( osts
<202OS)
Total C osts
(2020S)
Year 1 (2024)21
199,086,803
69,355
$7,152,443
$19,955,215
$27,107,658
Year 2 (2025)
199,085,861
56,520
$5,520,602
$19,955,215
$25,475,817
Year 3 (2026)
199,085,861
56,520
$5,520,602
$19,955,215
$25,475,817
3yr ICR Annual Average
199,086,175
60,798
$6,604,549
$19,955,215
$26 019,764
Year 4 (2027) and beyond
199,085,861
56,520
$5,520,602
$19,955,215
$25,475,817
20 ICR costs are shown in 2022 dollars. Table 4-4b provides the figures in 2020 dollars.
21 Note: 2024 Recordkeeping, Reporting, and Labeling costs are not included in calculations of incremental
costs of this rule presented elsewhere in this RIA addendum. Estimates of incremental costs presented elsewhere
in this RIA addendum only reflect costs beginning in 2025, the first compliance year associated with the restrictions
in the rule as proposed.
39
-------
Table 4-4b: Total Respondent Burden Costs Over the Three-Year ICR Period (2020$s)
) ear
Total
/{espouses
Total
Hours
Total
Labor
( osts
(20 JOS)
Total (h
-------
Chapter 5: Climate Benefits
5.1 Introduction
The benefits of this rule derive mostly from preventing the emissions of HFCs with high GWPs, thus
reducing the damage from climate change that would have been induced by those emissions. Results from
this analysis indicate that the proposed restrictions on HFC use in the certain sectors and subsectors as a
result of the proposed Technology Transitions Rule will in some cases lead to more rapid and deeper
transitions, which is anticipated to have the ancillary effect of leading to potential additional reductions in
the consumption of HFCs, measured in MTEVe, although the schedule for the production and
consumption phasedown would not be made more stringent than the schedule under subsection (e)(2)(C)
of the AIM Act. These reductions are expected to lead in turn to a reduction in emissions. It is assumed
that all HFCs produced or consumed would be emitted eventually, either from their direct release (e.g., as
propellants), during the lifetime of HFC-containing products (e.g., off-gassing from closed-cell foams or
leaks from refrigeration systems), or during and after servicing or disposal of HFC-containing products.
5.2 Consumption and Emission Reductions
EPA's Vintaging Model is used to estimate both consumption and emissions for each regulated substance
for each generation or "vintage" of equipment in the Technology Transitions compliance scenarios.
Reductions in consumption in units of MMTEVe are calculated for a given year by summing the total
tons avoided resulting from transitions in each sector or subsector. Emission reductions are similarly
calculated by summing total emissions avoided across sectors/subsectors; however, these benefits
typically lag corresponding reductions in consumption since they often occur over the course of
equipment lifetime or during servicing and disposal.
Table 5-1 below shows the consumption reductions by year corresponding to the Technology Transition
Rule compliance scenario in the base case and high additionality case, which are compared to the
Allocation Rule Reference Case to evaluate potential incremental reductions.
41
-------
Table 5-1: Annual Consumption in Allocation Rule Reference Case and Technology Transitions
Compliance Scenarios
. \Hocation Rule
Reference C use
Technology Transitions —
liuse C use
Technology Transitions —
High Adilitioniility Case
) ear
( onsuniption
Reductions
(MMIIJ c)
( onsuniption
Reductions
(MMTi: 1 e)
Incremental
C onsuniption
Reductions
(uun:\ e)
C onsuniption
Reductions
e)
Incremental
C onsuniption
Reductions
(MM It: 1 e)
2025
194
204
9
236
42
2026
217
217
0
247
30
2027
232
230
-2
261
29
2028
246
247
1
276
30
2029
230
256
27
282
53
2030
234
260
26
286
51
203 1
244
271
28
297
54
2032
251
282
31
304
54
2033
254
292
38
310
56
2034
267
302
35
316
49
2035
270
311
41
320
51
2036
283
317
34
325
42
2037
284
317
33
323
39
2038
285
320
34
325
40
2039
288
316
29
327
39
2040
288
308
21
316
29
2041
279
311
32
319
40
2042
281
314
33
322
41
2043
284
318
34
326
42
2044
286
321
34
329
43
2045
286
321
35
329
44
2046
288
324
36
332
44
2047
290
326
36
335
44
2048
292
329
36
337
45
2049
293
330
37
338
45
2050
294
331
37
339
46
Total
6940
7675
735
8060
1121
The mitigation charts below (Figures 5-1 and 5-2) show the estimated avoided consumption resulting
from the Technology Transition Rule restrictions for each year modeled, by sector. As shown, the
anticipated amount of abatement overshoots (dips below) the relevant AIM Act consumption cap (the
maximum annual domestic consumption allowed under the phasedown schedule) from 2025, the first
compliance year for the restrictions, through 2036, the final step-down year of the phasedown schedule.
42
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In the high additionality case, additional reductions stem from the assumption that consumption and
emissions reducing opportunities included in the Allocation Rule Reference Case are retained in the
Technology Transitions case—even if not covered by the Technology Transitions Rule—rather than
assuming these opportunities are forgone. Total consumption reductions from the Allocation Rule
Reference Case are also included as a reference line in both figures. The reductions in both figures reflect
abatement in both domestically manufactured products and imported products.22
Figure 5-1 - Consumption Mitigation by Year under Technology Transitions Scenario (base
case)
400
Phasedown schedule
350 —*— Allocation Rule Reference Case
o i i i i i i i i i i i i
2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036
Year
22 Due to limitations in the tools used for this analysis, consumption reductions as modeled are agnostic as to whether the avoided
HFCs would have been HFC consumption in the United States (i.e., produced in or imported to the United States) or are HFCs
contained in imported products. The AIM Act consumption cap only applies to domestic HFCs consumption. The import of bulk
HFCs placed in domestically manufactured products would therefore require expenditure of allowances under the Allocation
Framework Rule, unless an exemption applies, whereas the import of HFCs contained in imported products do not require such
an expenditure of allowances.
43
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Figure 5-2 - Consumption Mitigation by Year under the Technology Transitions Scenario (high
additionally case)
400
Phased own schedule
350 —*— /ylocation Rule Reference Case
2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036
Year
Table 5-2 below shows the emission reductions by year corresponding to the Technology Transitions
compliance scenarios. Again, these results are compared to the Allocation Rule Reference Case to
determine potential incremental reductions. Notably, these results indicate that in the base case, the
Technology Transitions Rule would only lead to incremental emission reductions in later years (after
2035), despite the more immediate incremental consumption reductions shown above. This is due to the
fact that nearly all subsectors covered by the proposed Technology Transitions Rule are ones where
emission reductions lag behind consumption reductions, and they are modeled as occurring gradually over
the course of equipment lifetime. By contrast, the Allocation Rule Reference Case assumes
implementation of some additional abatement options not covered by the Technology Transitions Rule—
namely leak recovery, disposal, and equipment servicing—which apply immediately rather than
gradually. The exclusion of these abatement options from the Technology Transitions base case
compliance scenario means that emission reductions are more delayed vis-a-vis the Allocation Rule
Reference Case. The one subsector covered by the proposed Technology Transitions Rule that does see
near-immediate emission reductions equal to the consumption reductions is aerosols, based on the
assumed lifetime of one year. However, the restrictions proposed and analyzed here are equivalent to the
abatement options assumed in the Allocation Framework RIA, and hence there are no incremental
benefits from that subsector. These differences in the timing of emission reductions notwithstanding, the
44
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results of this analysis indicate that the Technology Transitions Rule base case would ultimately yield
incremental emission reductions on a cumulative basis.
This dynamic of emission reductions lagging behind consumption reductions is further illustrated by
Figure 5-3 below, which shows annual consumption and emission reductions in the Technology
Transitions Rule base case scenario and Allocation Rule Reference Case overtime. The difference within
each set of reductions (i.e., purple line minus blue line) represents the incremental environmental impacts
from this proposed rule as compared to the Allocation Rule Reference Case.
Figure 5-3 - Consumption and Emission redactions in Technology Transitions Compliance
Scenario and Allocation Ride Reference Scenario
o
4 ^ 4 'o 7 'V ^ 'if 'jp ^ ^ 'S Y V W %
Consumption Reductions - TT Rule (Base case)--- Emissions Recuctions -TT Rule (Base case)
Consumption Reductions - Framework Rule --- Emissions Reductions - Framework Rule
In contrast with the base case, the high additionality case for the Technology Transitions Rule yields
immediate incremental emission reductions, beginning in the first compliance year (2025) and continuing
for all years modeled. This is because the high additionality case assumes that all transitions occurring in
the Allocation Rule Reference Case, if valid under the proposed Technology Transitions Rule, remain
selected even if not covered by the Technology Transitions Rule's restrictions (including those abatement
options that would lead to immediate emission reductions). The high additionality case is representative
of the upper bound of potential incremental benefits of the rule, illustrating the range of incremental
benefits depending on the ultimate transition pathway.
45
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Table 5-2 below shows the emission reductions by year corresponding to the Technology Transition Rule
compliance scenario in the base case and high additionally case, which are compared to the Allocation
Rule Reference Scenario to evaluate potential incremental reductions.
Table 5-2: Annual Emission Reductions in the Allocation Rule Reference Case and Technology
Transitions Compliance Base Case and High Additionality Casea
. Mlocation Rule
Reference C ase
/ ethnology Transitions
liase C ase
Technology Transitions High
. \dditionality C ase
) ear
Emission
Reductions
(MMTUl e)
Emission
Reductions
(MMTUl e)
Incremental
amission
Reductions
(MMTUl e)
amission
Reductions
(uma\ e)
Incremental
amission
Reductions
(MMTUl e)
2025
93
41
-52
101
8
2026
96
52
-44
108
13
2027
106
63
-43
123
17
2028
113
74
-40
133
20
2029
98
85
-13
132
34
2030
108
96
-12
143
35
2031
117
107
-9
154
37
2032
124
119
-5
164
40
2033
132
132
-1
174
42
2034
142
144
2
185
43
2035
150
156
6
195
45
2036
171
167
-3
207
36
2037
176
182
6
215
39
2038
183
197
14
224
40
2039
190
211
21
231
41
2040
197
224
27
237
40
2041
204
230
27
242
38
2042
210
236
27
247
38
2043
215
241
26
252
37
2044
220
246
26
256
37
2045
224
251
27
260
37
2046
227
255
28
264
37
2047
231
259
29
268
37
2048
234
263
29
271
38
2049
236
266
30
274
38
2050
239
269
30
277
38
Total
4435
4568
134
5338
903
"Rows may not appear to add correctly due to rounding.
46
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Annex B further disaggregates the emission reductions by metric tons of each gas abated. It is these
values that are used to calculate the climate-related benefits using the SC-HFC values described in the
remainder of this chapter.
5.3 The Social Cost of HFC Emissions
5.3.1 Methodology overview
This analysis relies on the same methodology for calculating the social cost of HFC emissions as previous
regulatory impact analyses conducted by EPA for AIM Act regulations.23 While CO2 is the most
prevalent GHG emitted by humans, it is not the only GHG with climate impacts. The EPA Endangerment
Finding (2009) recognized a basket of six gases, comprising CO2, methane (CH4), nitrous oxide (N2O),
HFCs, perfluorocarbons (PFCs), and sulfur hexafluoride (SFe). The climate impact of the emission of a
molecule of each of these gases is generally a function of their lifetime in the atmosphere and the
radiative efficiency of that molecule.24 We estimate the climate benefits for this rulemaking using a
measure of the social cost of each HFC (collectively referred to as SC-HFC) that is affected by the rule.
The SC-HFC is the monetary value of the net harm to society associated with a marginal increase in HFC
emissions in a given year or the benefit of avoiding that increase. In principle, SC-HFC includes the value
of all climate change impacts, 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-
HFC, therefore, reflects the societal value of reducing emissions of the gas in question by one metric ton.
The SC-HFC is the theoretically appropriate value to use in conducting benefit-cost analyses of policies
that affect HFC emissions.
The gas specific SC-HFC estimates used in this analysis were developed using methodologies that are
consistent with the methodology underlying estimates of the social cost of other GHGs (carbon dioxide
[SC-CO2], methane [SC-CH4], and nitrous oxide [SC-N2O]), collectively referred to as SC-GHG,
presented in the Technical Support Document: Social Cost of Carbon, Methane, and Nitrous Oxide
Interim Estimates under Executive Order 13990 published in February 2021 by the Interagency Working
23 Available at www. regulations.gov under Docket ID EPA-HQ-OAR-2021-0044.
24 In the case of CH4, the climate effect can encompass the atmospheric reactions of the gas that change the abundance of other
substances with climatic effects, such as ozone (O3) and stratospheric water vapor (H2O).
47
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Group on the Social Cost of Greenhouse Gases (IWG) (IWG 2021). As a member of the IWG involved in
the development of the February 2021 SC-GHG TSD, the EPA agrees that the TSD represents the most
appropriate methodology for estimating the social cost of greenhouse gases until revised estimates have
been developed reflecting the latest, peer-reviewed science. Therefore, EPA views the SC-HFC estimates
used in analysis to be appropriate for use in benefit-cost analysis until improved estimates of the social
cost of other GHGs are developed.
The SC-GHG estimates were developed over many years, using a transparent process, peer-reviewed
methodologies, the best science available at the time of that process, and with input from the public.
Specifically, in 2009, an interagency working group (IWG) that included the EPA and other executive
branch agencies and offices was established to ensure that agencies had access to the best available
information when quantifying the benefits of reducing CO2 emissions in benefit-cost analyses. The IWG
published SC-CO2 estimates in 2010 that were developed from an ensemble of three widely cited
integrated assessment models (IAMs) that estimate climate damages using highly aggregated
representations of climate processes and the global economy combined into a single modeling framework.
The three IAMs were run using a common set of input assumptions in each model for future population,
economic, and CO2 emissions growth, as well as equilibrium climate sensitivity (ECS) — a measure of
the globally averaged temperature response to increased atmospheric CO2 concentrations. These estimates
were updated in 2013 based on new versions of each IAM.25 In August 2016 the IWG published estimates
of the social cost of methane (SC-CH4) and nitrous oxide (SC-N2O) using methodologies that are
consistent with the methodology underlying the SC-CO2 estimates. The modeling approach that extends
the IWG SC-CO2 methodology to non-CCh GHGs has undergone multiple stages of peer review. The SC-
CH4 and SC-N2O estimates were developed by Marten, Kopits, Griffiths, Newbold, and Wolverton (2015)
and underwent a standard double-blind peer review process prior to journal publication. These estimates
were applied in regulatory impact analyses of EPA proposed rulemakings with CH4 and N2O emissions
impacts.26 The EPA also sought additional external peer review of technical issues associated with its
application to regulatory analysis. Following the completion of the independent external peer review of
the application of the Marten et al. (2015) estimates, the EPA began using the estimates in the primary
benefit-cost analysis calculations and tables for a number of proposed rulemakings in 2015 (EPA 2015b,
2015c). The EPA considered and responded to public comments received for the proposed rulemakings
25 Dynamic Integrated Climate and Economy (DICE) 2010 (Nordhaus, 2010), Climate Framework for Uncertainty, Negotiation,
and Distribution (FUND) 3.8 (Anthoff & Tol, 2013a, 2013b), and Policy Analysis of the Greenhouse Gas Effect (PAGE) 2009
(Hope, 2013). Dynamic Integrated Climate and Economy (DICE) 2010 (Nordhaus, 2010), Climate Framework for Uncertainty,
Negotiation, and Distribution (FUND) 3.8 (Anthoff & Tol, 2013a, 2013b), and Policy Analysis of the Greenhouse Gas Effect
(PAGE) 2009 (Hope, 2013).
26 The SC-CH4 and SC-N2O estimates were first used in sensitivity analysis for the Proposed Rulemaking for Greenhouse Gas
Emissions and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles-Phase 2 (U.S. EPA, 2015).
48
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before using the estimates in final regulatory analyses in 2016.27 In 2015, as part of the response to public
comments received to a 2013 solicitation for comments on the SC-CO2 estimates, the IWG announced a
National Academies of Sciences, Engineering, and Medicine review of the SC-CO2 estimates to offer
advice on how to approach future updates to ensure that the estimates continue to reflect the best available
science and methodologies. In January 2017, the National Academies released their final report, Valuing
Climate Damages: Updating Estimation of the Social Cost of Carbon Dioxide, and recommended 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). Shortly thereafter, in March 2017, President Trump
issued EO 13783, which disbanded the IWG, withdrew the previous TSDs, and directed agencies to
ensure SC-GHG estimates used in regulatory analyses are consistent with the guidance contained in
OMB's Circular A-4, "including with respect to the consideration of domestic versus international
impacts and the consideration of appropriate discount rates" (EO 13783, Section 5(c)). Benefit-cost
analyses following EO 13783 used SC-GHG estimates that attempted to focus on the U.S.-specific share
of climate change damages as estimated by the models (and so did not reflect many pathways by which
physical impacts outside the United States affect the welfare of U.S. citizens and residents) and were
calculated using two default discount rates recommended by Circular A-4, 3 percent and 7 percent.28 All
other methodological decisions and model versions used in the SC-GHG calculations remained the same
as those used by the IWG in 2010 and 2013, respectively.
On January 20, 2021, President Biden issued EO 13990, which re-established the IWG and directed it to
develop a comprehensive update of the SC-GHG estimates that reflect the best available science and the
recommendations of National Academies (2017). In February 2021, the IWG recommended the interim
use of the most recent SC-GHG estimates developed by the IWG prior to the group being disbanded in
2017 (IWG, 2021). As discussed in the February 2021 TSD, the IWG's selection of these interim
estimates reflected the immediate need to have SC-GHG estimates available for agencies to use in
regulatory benefit-cost analyses and other applications that were developed using a transparent process,
peer reviewed methodologies, and the science available at the time of that process. The February 2021
27 See IWG (2016b) for more discussion of the SC-CH4 and SC-N2O and the peer review and public comment processes
accompanying their development.
28 EPA regulatory analyses under E.O. 13783 included sensitivity analyses based on global SC-GHG values and using a lower
discount rate of 2.5%. OMB Circular A-4 (OMB, 2003) recognizes that special considerations arise when applying discount rates
if intergenerational effects are important. In the IWG's 2015 Response to Comments, OMB—as a co-chair of the IWG—made
clear that "Circular A-4 is a living document," that "the use of 7 percent is not considered appropriate for intergenerational
discounting," and that "[t]here is wide support for this view in the academic literature, and it is recognized in Circular A-4 itself."
OMB, as part of the IWG, similarly repeatedly confirmed that "a focus on global SCC estimates in [regulatory impact analyses]
is appropriate" (IWG 2015).
49
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update also recognized the limitations of the interim estimates and encouraged agencies to use their best
judgment in, for example, considering sensitivity analyses using lower discount rates. The IWG published
a Federal Register notice on May 7, 2021, soliciting comment on the February 2021 TSD and on how best
to incorporate the latest peer-reviewed scientific literature in order to develop an updated set of SC-GHG
estimates. The EPA has applied the IWG's interim SC-GHG estimates in regulatory analyses published
since the release of the February 2021 TSD.
The SC-HFC estimates used in this analysis were developed using methodologies consistent with the
methodologies underlying the interim estimates of the SC-GHG published in February 2021 by the IWG.
As such, we first summarize the general findings of the IWG review and interim update, and then provide
more discussion of the modeling decisions specific to the estimation of the social cost of non-CC>2 GHGs.
The February 2021 SC-GHG TSD provides a complete discussion of the IWG's initial review conducted
under EO 13990. In particular, the IWG found that the SC-GHG estimates used under EO 13783 fail to
reflect the full impact of GHG emissions in multiple ways. First, the IWG concluded that those estimates
fail to capture many climate impacts that can affect the welfare of U.S. citizens and residents. 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 are better captured within global measures of the social cost of greenhouse gases.
In addition, 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. A wide range of scientific and economic experts have emphasized the issue of reciprocity as
support for considering global damages of GHG emissions. 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 take significant steps to reduce emissions. 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 — is for all countries to base their policies on global estimates of damages.
As a member of the IWG involved in the development of the February 2021 SC-GHG TSD, EPA agrees
with this assessment and, therefore, in this proposed rule the EPA centers attention on a global measure of
SC-HFC. This approach is the same as that taken in EPA regulatory analyses over 2009 through 2016. A
robust estimate of climate damages to U.S. citizens and residents that accounts for the myriad of ways
that global climate change reduces the net welfare of U.S. populations does not currently exist in the
literature. As explained in the February 2021 TSD, existing estimates are both incomplete and an
50
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underestimate of total damages that accrue to the citizens and residents of the U.S. because they do not
fully capture the regional interactions and spillovers discussed above, nor do they include all of the
important physical, ecological, and economic impacts of climate change recognized in the climate change
literature, as discussed further below. The EPA, as a member of the IWG, 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 carbon impacts.
Second, the IWG concluded that the use of the social rate of return on capital (7 percent under current
OMB Circular A-4 guidance) to discount the future benefits of reducing GHG emissions inappropriately
underestimates the impacts of climate change for the purposes of estimating the SC-GHG. Consistent
with the findings of National Academies (2017) and the economic literature, the IWG continued to
conclude that the consumption rate of interest is the theoretically appropriate discount rate in an
intergenerational context (IWG, 2010, 2013, 2016a, 2016b), and recommended that discount rate
uncertainty and relevant aspects of intergenerational ethical considerations be accounted for in selecting
future discount rates.29 Furthermore, the damage estimates developed for use in the SC-GHG are
estimated in consumption-equivalent terms, and so an application of OMB Circular A-4's guidance for
regulatory analysis would then use the consumption discount rate to calculate the SC-GHG. As a member
of the IWG involved in the development of the February 2021 SC-GHG TSD, the EPA agrees with this
assessment and will continue to follow developments in the literature pertaining to this issue. EPA also
notes that while OMB Circular A-4, as published in 2003, recommends using 3 percent and 7 percent
discount rates as "default" values, Circular A-4 also reminds agencies that "different regulations may call
for different emphases in the analysis, depending on the nature and complexity of the regulatory issues
and the sensitivity of the benefit and cost estimates to the key assumptions." On discounting, Circular A-4
recognizes that "special ethical considerations arise when comparing benefits and costs across
generations," and Circular A-4 acknowledges that analyses may appropriately "discount future costs and
consumption benefits... at a lower rate than for intragenerational analysis." In the 2015 Response to
Comments on the Social Cost of Carbon for Regulatory Impact Analysis, OMB, EPA, and the other IWG
members recognized that "Circular A-4 is a living document" and "the use of 7 percent is not considered
29 GHG emissions are stock pollutants, with damages associated with what has accumulated in the atmosphere over time, and
they are long lived such that subsequent damages resulting from emissions today occur over many decades or centuries
depending on the specific greenhouse gas under consideration. In calculating the SC-GHG, the stream of future damages to
agriculture, human health, and other market and non-market sectors from an additional unit of emissions are estimated in terms of
reduced consumption (or consumption equivalents). Then that stream of future damages is discounted 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.
51
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appropriate for intergenerational discounting. There is wide support for this view in the academic
literature, and it is recognized in Circular A-4 itself." Thus, EPA concludes that a 7 percent discount rate
is not appropriate to apply to value the social cost of greenhouse gases in the analysis presented in this
analysis. In this analysis, to calculate the present and annualized values of climate benefits, EPA uses the
same discount rate as the rate used to discount the value of damages from future GHG emissions, for
internal consistency. That approach to discounting follows the same approach that the February 2021 SC-
GHG TSD recommends "to ensure internal consistency—i.e., future damages from climate change using
the SC-GHG at 2.5 percent should be discounted to the base year of the analysis using the same 2.5
percent rate." EPA has also consulted the National Academies' 2017 recommendations on how SC-GHG
estimates can "be combined in RIAs with other cost and benefits estimates that may use different discount
rates." The National Academies reviewed "several options," including "presenting all discount rate
combinations of other costs and benefits with [SC-GHG] estimates."
While the IWG works to assess how best to incorporate the latest, peer reviewed science to develop an
updated set of SC-GHG estimates, it recommended the interim estimates to be the most recent estimates
developed by the IWG prior to the group being disbanded in 2017. The estimates rely on the same models
and harmonized inputs and are calculated using a range of discount rates. As explained in the February
2021 SC-GHG TSD, the IWG has concluded that it is appropriate for agencies to revert to the same set of
four values drawn from the SC-GHG distributions based on three discount rates as were used in
regulatory analyses between 2010 and 2016 and subject to public comment. For each discount rate, the
IWG combined the distributions across models and socioeconomic emissions scenarios (applying equal
weight to each) and then selected a set of four values for use in benefit-cost analyses: an average value
resulting from the model runs for each of three discount rates (2.5 percent, 3 percent, and 5 percent), plus
a fourth value, selected as the 95th percentile of estimates based on a 3 percent discount rate. The fourth
value was included to provide information on potentially higher-than-expected economic impacts from
climate change, conditional on the 3 percent estimate of the discount rate. As explained in the February
2021 SC-GHG TSD, and EPA agrees, this update reflects the immediate need to have an operational SC-
GHG for use in regulatory benefit-cost analyses and other applications that was developed using a
transparent process, peer-reviewed methodologies, and the science available at the time of that process.
Those estimates were subject to public comment in the context of dozens of proposed rulemakings as well
as in a dedicated public comment period in 2013. Since the original 2010 SC-CO2 TSD did not include
direct estimates of the social cost of non-CC>2 GHGs and did not endorse the use of GWP metrics to
52
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approximate the value of non-CCh emission changes in regulatory analysis,30 more work was needed
following 2010 to link non-CC>2 GHG emission changes to economic impacts. The IWG calculated the
SC-CH4 and SC-N2O estimates following the approach used in Marten et al. (2015). In order to develop
SC-CH4 and SC-N2O estimates consistent with the methodology underlying the SC-CO2 estimates,
Marten et al. (2015) needed to minimally augment the IWG modeling framework in two respects: (1)
augment the climate model of two of the IAMs to explicitly consider the path of additional radiative
forcing from a CH4 or N2O perturbation, and (2) add more specificity to the assumptions regarding post-
2100 baseline CH4 and N2O emissions. The August 2016 TSD Addendum (IWG 2016b) provides detailed
discussion of these two modeling modifications and the peer review and public comment processes
accompanying their development. The approach used for developing the SC-HFC estimates mirrors that
of the peer-reviewed SC-CH4 and SC-N2O estimates (Marten et al. 2015, TSD 2016a/b), which require
two modeling modifications specific to HFCs. These two modifications are described below.
Regarding the climate modeling, both the DICE and PAGE models as implemented by the IWG to
estimate SC-CO2 use an exogenous projection of aggregate non-CC>2 radiative forcing, which prevents
one from introducing a direct perturbation of HFC emissions into the models and then observing its
effects.31 Therefore, to estimate the SC-HFC, we applied a one-box atmospheric gas cycle model to
explicitly consider the path of additional radiative forcing from the HFC perturbation, which is then added
to the exogenous non-CC>2 radiative forcing projection to estimate the incremental damages compared
with the baseline. The one-box atmospheric gas cycle model appended to DICE and PAGE used
exponential decay functions to project atmospheric HFC concentrations from the HFC emissions
projections, respectively, in the five socioeconomic emissions scenarios. Consistent with the SC-CH4 and
SC-N2O, the average lifetime of each HFC follow the findings of the Intergovernmental Panel on Climate
Change's (IPCC) Fourth Assessment Report (AR4) (Forster et al. 2007). The direct radiative forcing
30 The potential of non-CC>2 GHGs to change the Earth's climate relative to CO2 is commonly represented by their 100-year
GWP. GWPs measure the contribution to warming of the Earth's atmosphere resulting from emissions of a given gas (i.e.,
radiative forcing per unit of mass) over a particular timeframe relative to C02. As such, GWPs are often used to convert
emissions of non-CC>2 GHGs to CO2 equivalents to facilitate comparison of policies and inventories involving different GHGs.
While GWPs allow for some useful comparisons across gases on a physical basis, using the social cost of carbon dioxide (SC-
CO2) to value the damages associated with changes in CC>2-equivalent emissions is not optimal. This is because non-CC>2 GHGs
differ not just in their potential to absorb infrared radiation over a given time frame, but also in the temporal pathway of their
impact on radiative forcing, which is relevant for estimating their social cost but not reflected in the GWP. Physical impacts other
than temperature change also vary across gases in ways that are not captured by GWP. For instance, CO2 emissions, unlike CH4
and other GHGs, contribute to ocean acidification. Likewise, damages from CH4 emissions are not offset by any positive effect of
C02 fertilization on agriculture. Thus, transforming gases into C02- equivalents using GWP, and then multiplying the C02-
equivalents by the SC-CO2, is not as accurate as a direct calculation of the social costs of non-CC>2 GHGs. For more detailed
discussion of the limitations of using a GWP based approach to valuing non-CC>2 GHG emission changes, see, e.g., Marten et al.
(2012).
31 The FUND model is the only one of the three IAMs that explicitly considers CH4 and N20 using a one-box atmospheric gas
cycle models for these gases, with geometric decay toward pre-industrial levels, based on the IPCC's Third Assessment Report
(TAR) (Ramaswamy et al. 2001). FUND augments the TAR expression for the additional radiative forcing from CH4 to account
for the influences of stratospheric water vapor and tropospheric ozone changes.
53
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associated with the atmospheric HFC concentration was estimated using the functional relationships for
each gas presented in the IPCC's Third Assessment Report (Ramaswamy et al. 2001) and used in AR4.
The second modeling modification was needed because the SC-CO2 modeling exercise assumed that
overall radiative forcing from non-CCh sources remains constant past 2100 without specifying the
projections for individual GHGs that were implicit in that assumption. This broad assumption was
sufficient for the purposes of estimating the SC-CO2; however, estimating SC-HFC requires explicit
projections of baseline emissions of each HFC to determine the atmospheric concentration and radiative
forcing off of which to compare the perturbation. We chose to interpret the SC-CO2 assumption for non-
CO2 radiative forcing past 2100 as applying to each gas individually, such that the emissions of each gas
fall to their respective rate of atmospheric decay. This has the effect of holding global mean radiative
forcing due to atmospheric HFCs constant past 2100.
5.3.2 SC-HFC Estimates
Tables 5-3 through 5-12 summarize the SC-HFC estimates for the years 2020 through 2050 in five-year
increments. The values are stated in $/metric ton of each gas and vary depending on the year of emission
reductions. All estimates are presented in 2020 dollars and are rounded to two significant figures. The full
range of annual unrounded estimates are available in Appendix E of the Allocation Framework Rule
RIA.32 For purposes of capturing uncertainty around the SC-HFC estimates in analyses, we emphasize the
importance of considering all four values for each HFC affected by the rule. The SC-HFC 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 2025—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 5-3: Social Cost ofHFC-32, 2020-2050 (in 2020 dollars per metric ton HFC-32)
Discount Rate and Statistic
Year
5"u. 1 venire
3"i,. 1 venire
. 1 verage
V5th l\t.
2020
18000
38000
50000
100000
2025
22000
45000
58000
120000
2030
27000
53000
67000
140000
2035
33000
62000
77000
170000
32 Available at www. regulations.gov under Docket ID EPA-HQ-OAR-2021-0044.
54
-------
2040
39000
71000
88000
190000
2045
46000
81000
99000
220000
2050
53000
92000
110000
250000
Table 5-4: Social Cost of HFC-125, 2020-2050 (in 2020 dollars per metric ton HFC-125)
Disc/Hint Hate and Statistic
) car
5"«.1rcragc
3",,. 1 rcra^c
15"i>. 1 rcragc
v.v// i\ t.
2020
83000
210000
290000
550000
2025
99000
240000
330000
640000
2030
120000
280000
370000
730000
2035
140000
310000
410000
830000
2040
160000
350000
450000
930000
2045
180000
390000
500000
1000000
2050
210000
430000
550000
1100000
Table 5-5: Social Cost of HFC-134a, 2020-2050 (in 2020 dollars per metric ton HFC-134aj
Discount Rate and Statistic
) car
5"u.1 vcra^c
3"». 1 venire
. 1 vcra^c
3",, V5th l*ct.
2020
38000
87000
12UUUU
23UUUU
2025
46000
100000
130000
270000
2030
55000
120000
150000
310000
2035
65000
130000
170000
360000
2040
76000
150000
190000
410000
2045
88000
170000
210000
460000
2050
100000
190000
230000
510000
55
-------
Table 5-6: Social Cost of HFC-143a, 2020-2050 (in 2020 dollars per metric ton HFC-143a)
Discount Ran• and Statistic
) car
5"«.1 venire
3"i, . 1 vera^e
_\5"» .¦Average
3",, <)5th l\ t.
2020
95000
270000
380000
700000
2025
110000
300000
420000
800000
2030
130000
340000
470000
910000
2035
150000
380000
520000
1000000
2040
180000
430000
570000
1100000
2045
200000
470000
620000
1300000
2050
230000
520000
680000
1400000
Table 5-7: Social Cost ofHFC-152a, 2020-2050 (in 2020 dollars per metric ton HFC-152a)
Discount Rate and Statistic
) car
5"n. 1 rcragc
3"n. 1 rera.!>e
2.5"n. 1 vcra^c
3"„ V5th Ret.
2020
2600
5400
6900
14000
2025
3200
6300
8100
17000
2030
3900
7400
9300
20000
2035
4700
8600
11000
23000
2040
5600
10000
12000
27000
2045
6700
12000
14000
32000
2050
7800
13000
16000
37000
56
-------
Table 5-8: Social Cost ofHFC-227ea, 2020-2050 (in 2020 dollars per metric ton HFC-227ea)
Discount Hate and Statistic
Year
5"«.1rerage
3"n. \ rerage
. iverage
3",, ct.
2020
180000
640000
970000
1700000
2025
210000
710000
1100000
1900000
2030
250000
790000
1200000
2100000
2035
290000
870000
1300000
2300000
2040
330000
960000
1400000
2600000
2045
380000
1000000
1500000
2800000
2050
430000
1100000
1600000
3100000
Table 5-10: Social Cost ofHFC-245fa, 2020-2050 (in 2020 dollars per metric ton HFC-245fa)
Discount Rate and Statistic
Year
5"a . 1 verage
3"n . 1 verage
2.5"ii. 1 verage
3"„
-------
2025
35000
72000
93000
190000
2030
42000
84000
110000
220000
2035
50000
97000
120000
260000
2040
59000
110000
140000
300000
2045
69000
130000
160000
340000
2050
79000
140000
170000
390000
Table 5-11: Social Cost of HFC-43-1 Omee, 2020-2050 (in 2020 dollars per metric ton HFC-43-
lOmee)
Discount Rate and Statistic
) ear
5"u Average
3"». 1 rerage
2.5"n. 1 vcrage
95th l\-t.
2020
43000
100000
130000
260000
2025
52000
120000
150000
310000
2030
62000
130000
170000
360000
2035
73000
150000
200000
410000
2040
86000
170000
220000
470000
2045
99000
190000
240000
520000
2050
110000
220000
270000
570000
Table 5-12: Social Cost ofHFC-23, 2020-2050 (in 2020 dollars per metric ton HFC-23)
Discount Rate and Statistic
Year
5"u .1verage
3"i,. 1 verage
2.5"n. 1 verage
3"„ 95th l\ t.
2020
270000
970000
1500000
2600000
2025
320000
1100000
1600000
2900000
2030
370000
1200000
1800000
3200000
2035
430000
1300000
1900000
3600000
58
-------
2040
490000
1500000
2100000
3900000
2045
570000
1600000
2300000
4400000
2050
640000
1700000
2500000
4800000
Since the SC-HFC estimates presented in Tables 5-3 to 5-12 are based on the same methodology
underlying the SC-GHG estimates presented in the IWG February 2021 TSD, they share a number of
limitations that are common to those SC-GHG estimates. First, the current scientific and economic
understanding of discounting approaches suggests discount rates appropriate for intergenerational analysis
in the context of climate change are likely to be less than 3 percent, near 2 percent or lower (IWG, 2021).
Second, the IAMs used to produce these interim estimates do not include all of the important physical,
ecological, and economic impacts of climate change recognized in the climate change literature and the
science underlying their "damage functions" — i.e., the core parts of the IAMs that map global mean
temperature changes and other physical impacts of climate change into economic (both market and
nonmarket) damages — lags behind the most recent research. For example, limitations include the
incomplete treatment of catastrophic and non-catastrophic impacts in the integrated assessment models,
their incomplete treatment of adaptation and technological change, the incomplete way in which inter-
regional and intersectoral linkages are modeled, uncertainty in the extrapolation of damages to high
temperatures, and inadequate representation of the relationship between the discount rate and uncertainty
in economic growth over long time horizons. Likewise, the socioeconomic and emissions scenarios used
as inputs to the models do not reflect new information from the last decade of scenario generation or the
full range of projections.
The modeling limitations do not all work in the same direction in terms of their influence on the SC-GHG
estimates. However, the IWG has recommended that, taken together, the limitations suggest that the
interim SC-GHG estimates used in this proposed rule likely underestimate the damages from GHG
emissions. In particular, the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment
Report (IPCC, 2007), which was the most current IPCC assessment available at the time when the IWG
decision over the ECS input was made, concluded that SC-C02 estimates "very likely.. .underestimate the
damage costs" due to omitted impacts. Since then, the peer-reviewed literature has continued to support
this conclusion, as noted in the IPCC's Fifth Assessment Report (IPCC, 2014) and other recent scientific
assessments (e.g., IPCC (2018, 2019a, 2019b)); U.S. Global Change Research Program (USGCRP, 2016,
2018); and the National Academies of Sciences, Engineering, and Medicine (National Academies, 2017,
2019).The modeling limitations do not all work in the same direction in terms of their influence on the
59
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SC-GHG estimates. However, the IWG has recommended that, taken together, the limitations suggest that
the interim SC-GHG estimates used in this proposed rule likely underestimate the damages from GHG
emissions. In particular, the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment
Report (IPCC, 2007), which was the most current IPCC assessment available at the time when the IWG
decision over the ECS input was made, concluded that SC-C02 estimates "very likely.. .underestimate the
damage costs" due to omitted impacts. Since then, the peer-reviewed literature has continued to support
this conclusion, as noted in the IPCC's Fifth Assessment Report (IPCC, 2014) and other recent scientific
assessments (e.g., IPCC (2018, 2019a, 2019b)); U.S. Global Change Research Program (USGCRP, 2016,
2018); and the National Academies of Sciences, Engineering, and Medicine (National Academies, 2017,
2019). These assessments confirm and strengthen the science, updating projections of future climate
change and documenting and attributing ongoing changes. For example, sea level rise projections from
the IPCC's Fourth Assessment Report ranged from 18 to 59 centimeters by the 2090s relative to 1980-
1999, while excluding any dynamic changes in ice sheets due to the limited understanding of those
processes at the time (IPCC, 2007). A decade later, the Fourth National Climate Assessment projected a
substantially larger sea level rise of 30 to 130 centimeters by the end of the century relative to 2000, while
not ruling out even more extreme outcomes (USGCRP, 2018). EPA has reviewed and considered the
limitations of the models used to estimate the interim SC-GHG estimates and concurs with the February
2021 SC-GHG TSD's assessment that, taken together, the limitations suggest that the interim SC-GHG
estimates likely underestimate the damages from GHG emissions. The February 2021 SC-GHG TSD
briefly previews some of the recent advances in the scientific and economic literature that the IWG is
actively following and that could provide guidance on, or methodologies for, addressing some of the
limitations with the interim SC-GHG estimates, which also apply to the SC-HFC.
5.4 Monetized Climate Benefits Results
To monetize the climate benefits resulting from the Technology Transitions Rule, the HFC emission
reductions in each year (Table 5-2) are multiplied by the corresponding SC-HFC for that HFC in that year
(Tables 5-3 - 5-12). Table 5-13 presents the undiscounted monetized climate benefits from all regulated
HFCs under the Allocation Rule Reference Case33, the Technology Transitions Rule Base Case and High
Additionality Case, and the incremental climate benefits evaluated from the Allocation Rule Reference
Case. The incremental climate benefits shown here represent the additional benefits (positive numbers)
achieved from the Technology Transitions Rule Base Case and High Additionality Case.
33 This includes the proposed 2024 Allocation Rule including the lower baseline and changes to one of the abatement options.
60
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Table 5-13: Undiscounted Monetized Climate Benefits of the Technology Transitions Rule Base
Case and High Additionality Case 2025-2050 (3% model average SC-GHG estimates, millions
of2020$, discounted to 2022)a
Year
Icchnolo^y Transitions Utile liusc
( use Incrcmcnhil ( limtilc licncfil.s
(millions 2020S)
Technology Transitions High Additionality
( use Incrcmcnhil ( Tannic licnc/il.s (millions
2020.S)
2025
$(3,603)
$546
2029
$ (1,043)
$2,563
2034
$141
$3,739
2036
$(404)
$3,213
2040
$2,669
$3,928
2045
$ 2,946
$4,031
2050
$3,606
$4,677
* Climate benefits are based on changes in HFC emissions and are calculated using four different estimates of the
SC-HFCs (model average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th percentile at 3 percent discount
rate). For purposes of this table, we show the effects associated with the model average at a 3 percent discount rate,
but the Agency does not have a single central SC-HFC point estimate. We emphasize the importance and value of
considering the benefits calculated using all four SC-HFC estimates. A consideration of climate effects calculated
using discount rates below 3 percent, including 2 percent and lower, is also warranted when discounting
intergenerational impacts.
When the base case benefits are discounted to 2022 using a discount rate of 3 percent, the present value of
the incremental benefits of this proposed rule from 2025-2050 are estimated to be $5 billion in 2020
dollars (Table 5-14). This is equivalent to an annual incremental benefit of $311 million per year over that
time frame. Similarly, the present value of the incremental benefits of the High Additionality Case from
2025-2050 are estimated to be $51 billion in 2020 dollars, discounting to 2022 using a discount rate of 3
percent, with an annual incremental benefit of $3.1 billion per year over that time frame.34 Table 5-14
shows discounted monetized incremental climate benefits and the PV and EAV for the 2025 - 2050 time
period using a 3 percent discount rate for the Technology Transitions Rule Base Case and High
Additionality Case. The future benefits in each column are discounted back to 2022 to produce the
present value estimate.
34 The Allocation Rule Reference Case projects the present value of climate-related benefits from 2025 through 2050 to be
$253.2 billion (2020$, 3% discount rate, discounted to 2022). The Technology Transitions Rule base case projects climate-related
benefits over the same time period to be $5 billion, equivalent to 2% of those projected for the Allocation Rule Reference Case.
The high additionality case projects climate-related benefits over the same time period to be $79 billion, equivalent to 31% of
those projected for the Allocation Rule Reference Case. (Table 5-14).
61
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Table 5-14: Discounted Monetized Climate Benefits of the Technology Transitions Rule 2025-
2050 (millions of2020$)abc
Year
iccltnolo'^y litmsilions link' liusc
( use Incremental ( 'limatc licncjils
(millions 2/12 (IS)
h'chiioloxy liansilions High -Itldilionalily
( asc Incremental ( limalc licncjils
(millions 2020S)
2025
($3,603)
$546
2026
($3,138)
$888
2027
($3,194)
$1,191
2028
($3,007)
$1,454
2029
($1,043)
$2,563
2030
($963)
$2,760
2031
($785)
$3,004
2032
($466)
$3,264
2033
($118)
$3,535
2034
$141
$3,739
2035
$504
$4,016
2036
($404)
$3,213
2037
$504
$3,562
2038
$1,320
$3,839
2039
$2,015
$3,970
2040
$2,669
$3,928
2041
$2,602
$3,803
2042
$2,658
$3,846
2043
$2,702
$3,872
2044
$2,775
$3,926
2045
$2,946
$4,031
2046
$3,093
$4,167
2047
$3,240
$4,305
2048
$3,384
$4,445
2049
$3,481
$4,543
2050
$3,606
$4,677
PV (3% d.r.)
$5,084
$51,145
EAV (3% d.r.)
$311
$3,126
" Rows may not appear to add correctly due to rounding.
b The equivalent annual values of benefits are calculated over a 26-year period from 2025 to 2050.
c Climate benefits are based on changes in HFC emissions and are calculated using four different estimates of the
SC-HFCs (model average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th percentile at 3 percent discount
rate). For purposes of this table, we show effects associated with the model average at a 3 percent discount rate, but
the Agency does not have a single central SC-HFC point estimate. We emphasize the importance and value of
considering the benefits calculated using all four SC-HFC estimates. A consideration of climate effects calculated
using discount rates below 3 percent, including 2 percent and lower, is also warranted when discounting
intergenerational impacts.
62
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Chapter 6: Comparison of Benefits and Costs
This section compares the total incremental compliance costs (or savings) with the monetized incremental
environmental benefits detailed in the sections above to provide an assessment of the total net incremental
costs/benefits of the proposed rule. The rule's abatement costs are estimated using the Vintaging Model
and an evaluation of marginal abatement cost curves. This analysis uses abatement costs as a proxy for
social costs. As shown in section 4.4, Table 4-3, the base case estimated that the total annual abatement
costs to implement the proposed Technology Transitions Rule, as described in this document, are
approximately -$0.20 billion in 2025 and -$1.66 billion in 2050 (2020$), while the incremental annual
abatement costs are -$0.42 billion in 2025 and -$0.84 billion in 2025 (2020$). As shown in section 4.6,
Table 4-4, the recordkeeping, reporting, and labeling costs are approximately $23 million in 2025 and $23
million in 2027 and beyond (2020$). The base case total costs inclusive of abatement costs and
recordkeeping, reporting, and labeling costs are approximately -$0.17 billion in 2025 and -$1.64 billion in
2050 (2020$). The base case incremental compliance costs are -$0.39 billion in 2025 and -$0,816 billion
in 2050 (2020$). The high additionally case total costs inclusive of abatement costs and recordkeeping,
reporting, and labeling costs are approximately $0.25 billion in 2025 and $1.6 billion in 2050 (2020$).
The high additionally case incremental compliance costs are $0.31 billion in 2025 and -$0,743 billion in
2050 (2020$). Table 6-1 summarizes the annual abatement, annual recordkeeping, reporting, and labeling,
and total annual costs for selected years for both the base case and high additionally case.
Table 6-1: Summary of Cost Components of Proposed Rule Base Case and High Additionality
Case Scenarios for Selected Years, 2025-2050 (millions of2020$)
le
clmologv t ransitions linle
. 1 Ilium inn
liase < use
High
\dditionality < use
) 'car
Rule
Kejerence
< IISC
( osts
(Saving)
Record
keeping.
Heportin
Labeling
< osts
M IC
Model \el
[but emeu!
( osts
(Saving)
lot a!( osts
(Savings)
( \hntenienl
KXK)
I'otal
Incremental
< osls
(Savings)
MU Model
\et
\hatement
( osts
(Savings)
I'otal ( osts
(Savings)
( Ibatement
KXK)
I'otal
Incremental
< osts
(Savings)
2025
$223
$23
($195)
($172)
($395)
$230
$254
$31
2029
($471)
$23
($445)
($422)
$50
($160)
($136)
$335
2034
($768)
$23
($991)
($967)
($200)
($868)
($845)
($77)
2036
($454)
$23
($1,154)
($1,131)
($677)
($1,112)
($1,089)
($635)
2040
($527)
$23
($1,398)
($1,375)
($848)
($1,335)
($1,312)
($784)
2045
($656)
$23
($1,465)
($1,442)
($786)
($1,397)
($1,373)
($717)
2050
($824)
$23
($1,664)
($1,641)
($817)
($1,591)
($1,567)
($743)
63
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As shown in Chapter 5, the estimated base case monetized incremental climate benefits from
implementation of the rule are approximately $-3.6 billion in 2025 (2020$, using a 3 percent discount
rate). For 2050, the estimated base case monetized incremental climate benefits from implementation of
the rule are approximately $3.6 billion (using a 3 percent discount rate). The estimated high additionality
case monetized incremental climate benefits from implementation of the rule are approximately $.546
billion in 2025 (2020$, using a 3 percent discount rate) and $4.7 billion (using a 3 percent discount rate)
in 2050.
EPA calculates the incremental net benefits of the rule by subtracting the estimated incremental
abatement costs from the estimated incremental benefits. The benefits include those to climate. The
annual base case incremental net benefits of the rule in 2025 (in 2020$) are approximately -$3.2 billion.
The annual high additionality case incremental net benefits of the rule in 2025 (in 2020$) are
approximately $.515 billion. The annual base case incremental net benefits of the rule in 2029 are
approximately -$1 billion, while the high additionality case incremental net benefits are $2.2 billion. The
annual base case incremental net benefits of the rule in 2034 are approximately $340 million, while the
high additionality case incremental net benefits are $3.8 billion. The annual base case incremental net
benefits of the rule in 2036 are approximately $273 million, while the high additionality case incremental
net benefits are $3.8 billion. The annual base case incremental net benefits of the rule in 2045 are
approximately $3.7 billion, while the high additionality case incremental net benefits are $4.7 billion. The
annual base case incremental net benefits of the rule in 2050 are approximately $4.4 billion, while the
high additionality case incremental net benefits are $5.4 billion. Table 6-2 presents annual costs and net
benefits of the rule for the time period of 2025-2050.
As part of fulfilling analytical guidance with respect to Executive Order (E.O.) 12866, EPA presents
estimates of the present value (PV) of the benefits and costs over the 29-year period 2022 to 2050. To
calculate the PV of the net benefits of the proposed rule, annual costs are discounted to 2022 at 3 percent
and 7 percent discount rates as directed by OMB's Circular A-4. Climate benefits are discounted at 3
percent as described in Section 5.3 and consistent with the Final Regulatory Impact Analysis for the
Allocation Framework Rule.35 EPA also presents the equivalent annualized value (EAV), which
represents a flow of constant annual values that, had they occurred in each year from 2025 to 2050, would
yield a sum equivalent to the PV, discounted at 3 percent and 7 percent. The EAV represents the value of
a constant cost or net benefit for each year of the analysis, in contrast to the year-specific estimates
mentioned earlier in this document.
35 Available at www. regulations, gov under Docket ID EPA-HQ-OAR-2021 -0044, or see 86 FR 55116 (October 5, 2021).
64
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EPA estimates that the range of PV of cumulative net incremental benefits evaluated from 2025 through
2050 is $13.1 billion to $56.2 billion at a 3 percent discount rate for the base case and high additionality
case respectively. The range of incremental EAV over the period 2025-2050 is $803 million and $3.4
billion when using a 3 percent discount rate for the base case and high additionality case respectively.
The comparison of benefits and costs in PV and EAV terms for the base case and high additionality case
can be found in Table 6-2. Estimates in the table are presented as rounded values.
Table 6-2 - Summary of Annual Incremental Climate Benefits, Costs, and Net Benefits of the
Technology Transitions Rule Base Case and High Additionality Case Scenarios for the 2025-
2050 Timeframe (millions of2020$, discounted to 2022)a-b-c-d
lltlsc (
lli'fili Atldilionalily (
a.sc
Year
Incremental
( limalc
licncfils
(3"',')
Annual ( osls
(saving)
\cl licncjlls (J"n
licncjlls, 3",, or
( OSls)'
Incremental
(limalc
licncjlls
(J"»)
Annual ( osls
(savings)
Vi7 licncjlls (3"n
licncjlls, .?"» or
( osls) •
2025
($3,603)
-$395
-$3,209
$546
$31
$515
2026
($3,138)
-$462
-$2,676
$888
($82)
$970
2027
($3,194)
-$521
-$2,673
$1,191
($135)
$1,326
2028
($3,007)
-$529
-$2,478
$1,454
($171)
$1,626
2029
($1,043)
$50
-$1,092
$2,563
$335
$2,227
2030
($963)
-$17
-$947
$2,760
$272
$2,488
2031
($785)
-$56
-$729
$3,004
$237
$2,767
2032
($466)
-$77
-$388
$3,264
$170
$3,094
2033
($118)
-$54
-$64
$3,535
$130
$3,406
2034
$141
-$200
$340
$3,739
($77)
$3,816
2035
$504
-$175
$679
$4,016
($111)
$4,127
2036
($404)
-$677
$273
$3,213
($635)
$3,848
2037
$504
-$711
$1,215
$3,562
($680)
$4,242
2038
$1,320
-$710
$2.03 1
$3,839
($684)
$4,524
2039
$2,015
-$784
$2,799
$3,970
($685)
$4,654
2040
$2,669
-$848
$3,516
$3,928
($784)
$4,712
2041
$2,602
-$754
$3,357
$3,803
($691)
$4,494
2042
$2,658
-$760
$3,418
$3,846
($697)
$4,543
2043
$2,702
-$773
$3,475
$3,872
($709)
$4,582
2044
$2,775
-$782
$3,557
$3,926
($713)
$4,640
2045
$2,946
-$786
$3,732
$4,031
($717)
$4,748
2046
$3,093
-$791
$3,883
$4,167
($722)
$4,889
2047
$3,240
-$795
$4,035
$4,305
($725)
$5.03 1
2048
$3,384
-$801
$4,185
$4,445
($729)
$5,174
2049
$3,481
-$806
$4,287
$4,543
($733)
$5,276
2050
$3,606
-$817
$4,422
$4,677
($743)
$5,419
Discount
rate
3%
3% 7%
3% 7%
3%
3% 7%
3% 7%
65
-------
PV
$5,084
-$8,045
-$4,225
$13,130
$9,309
$79,204
-$4,241
-$1,693
$83,446
$80,898
EAV
$311
-$492
-$438
$803
$748
$4,841
-$259
-$175
$5,101
$5,017
a Benefits include only those related to climate. Climate benefits are based on changes in HFC emissions and are
calculated using four different estimates of the SC-HFCs (model average at 2.5 percent, 3 percent, and 5 percent
discount rates; 95th percentile at 3 percent discount rate). For purposes of this table, we show the effects associated
with the model average at a 3 percent discount rate, but the Agency does not have a single central SC-HFC point
estimate. We emphasize the importance and value of considering the benefits calculated using all four SC-HFC
estimates. A consideration of climate effects calculated using discount rates below 3 percent, including 2 percent
and lower, is also warranted when discounting intergenerational impacts, discount rate.
b Rows may not appear to add correctly due to rounding.
0 The annualized present value of costs and benefits are calculated as if they occur over a 26-year period from 2025
to 2050.
d The costs presented in this table are annual estimates.
e The PV for the 7% net benefits column is found by taking the difference between the PV of climate benefits at 3%
and the PV of costs discounted at 7%. Due to the intergenerational nature of climate impacts the social rate of return
to capital, estimated to be 7 percent in OMB 's Circular A-4, is not appropriate for use in calculating PV of climate
benefits.
66
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Chapter 7: Supplementary Analysis of Alternative
GWP Restriction Scenarios
7.1 Introduction
This chapter contains a supplementary assessment of economic costs and benefits under alternative
compliance scenarios with either higher or lower GWP limits than those contained in the proposed rule.
This supplementary analysis helps illustrate the extent to which costs and benefits may shift under more
or less restrictive limits, while also demonstrating that in many cases impacts would be essentially
unchanged. Importantly, this supplementary analysis is conducted for illustrative purposes only.
7.2 Description of scenarios
We modeled two alternative scenarios in order to evaluate potential differences in costs and benefits
compared to the proposed rule base case: one with GWP limits for all subsectors set 50% higher, and one
with GWP limits for all subsectors set 50% lower. In making assumptions about the HFC substitutes and
technologies that would be used in the base case for the rule as well as the higher and lower bound
scenarios, our approach relies on industry data of already commercially established or near-commercially
established substitutes for HFCs. We acknowledge this as a modeling limitation, since ultimately industry
is expected to innovate and develop new lower-GWP substitutes that are as yet undeveloped or for which
data on expected costs do not exist. This means these scenarios are indicative of potential future costs and
benefits, but not meant as prescriptive or fully predictive.
Table 7-1 below details the GWP limits assumed for the base, upper, and lower bound scenarios as well
as the corresponding assumed technological transitions for each subsector. As shown in the table, even
under the higher and lower GWP limit scenarios, for many subsectors the assumed transitions remain
unchanged. This stems from fact that there are a finite number of known substitutes for any given
subsector. Therefore, additional options may not necessarily be available even if the GWP limits are
loosened, and by the same token many GWP transitions made in the base case scenario—particularly
those that are already zero or near-zero GWP substances—would still be in compliance even if the GWP
is lowered further.
67
-------
Table 7-1: GWP Limits and Transition Assumption for the Technology Transitions Base Case,
Lower Scenario, and Higher Scenario
Hase ( asi¦ I'echnology
transitions Scenario
5H"n l.otnr Scenario
50"o Higher Scenario
Suhsector
<,ur
Li mil
Transition
Assumptions
(,\ir
l.imi!
Iran si lion
¦I ssnmptions
(,\ir
Limit
liansilion
Assumptions
Centrifugal Chillers
700
HFC-134a replaced
w/ R-450A/R-513A.
HFC-245fa replaced
w/ HCFO-
1233/,d(E)
'5ii
Subsecliir iraiisiikiiis
in NCR)-12 ' vdi 1!)
1050
No change (no
known alternative
even at this higher
GWP)
Screw Chillers
700
R-410A & R-407C
replaced w/ HFO-
1234ze(E)
350
No change (base
case scenario
already complies
with limit)
1050
No change (no
known alternative
even at this higher
GWP)
Scroll Chillers
700
R-410A & R-407C
replaced w/ HFO-
1234/.e(E)
350
No change (base
case scenario
already complies
with limit)
1050
No change(no
known alternative
even at this higher
GWP)
Reciprocating Chillers
700
R-410A & R-407C
replaced w/ R-452B
'5u
Subsecliir iraiisiiiiins
in MR )-l2'4/c
1050
No change(no
known alternative
even at this higher
GWP)
Industrial Process
Refrigeration (<200 lb
charge size)
300
NH3/C02
150
No change (base
case scenario
already complies
with limit)
45(1
R-454 \ is an
;i\ ailahlc imnsiiion
iipiiiiu
Industrial Process
Refrigeration (>=200 lb
charge size)
150
NH3/C02
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
Cold Storage (<200 lb
charge)
300
NH3/C02
150
No change (base
case scenario
already complies
with limit)
45(1
R-454 \ is an
a\ ailahlc imnsiiion
option
Cold Storage (>=200 lb
charge)
150
NH3/C02
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
Large Retail Food
(<200 lb charge)
300
R-407A to C02
Transcritical: R-
404A/R-507A to
C02 Transcritical
150
No change (base
case scenario
already complies
with limit)
45(1
R-454 \ is an
a\ ailahlc imnsiiion
opiion
68
-------
Large Retail Food
(>=200 lb charge)
150
R-407A to C02
Transcritical; R-
404A/R-507A to
C02 Transcritical
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
Medium Retail Food
(<200 lb charge)
300
C02
150
No change (base
case scenario
already complies
with limit)
45(1
R-454 \ is an
a\ ailahlc imnsiiion
iipiiiiu
Medium Retail Food
(>=200 lb charge)
150
C02
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
Small Retail Food
150
HCs
75
No change (base
case scenario
already complies
with limit)
225
No change(no
known alternative
even at this higher
GWP)
Vending Machines
150
R-290
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
Ice Makers. Self-
contained
700
R-290
350
No change (base
case scenario
already complies
with limit)
1050
R-32 or R-454B are
available transition
options
Ice Makers. Remote
2200*
R-448A/R-449A
1100
Subsector transitions
to R-290
3300
R-452A is an
available transition
option
Refrigerated
Transport—Inlcrmodal
Containers
700
R-450A/R-513 A
350
Subsector transitions
to R-454 \
1050
No change (no
known alternative
even at this higher
GWP)
Refrigerated
Transport—Marine and
-Road
2200*
R-452A
1 loo
Suhscclur iraiisiikHis
in R-45D \ R-5M \
3300
No change(no
known alternative
even at this higher
GWP)
Household
Rcfrigcrator-Frcc/crs
150
HFC-134a to R-
600a
"5
\n change i.hase
case scenario
already complies
with limit)
225
No change(no
known alternative
even at this higher
GWP)
Residential
Dehumidifiers
700
R-32
"o<)
Suhsecliir iraiisiiiiius
in !<-:•«)
1050
No change (no
known alternative
even at this higher
GWP)
69
-------
Window A/C Units
700
R-32
'5(>
Suhsecliir iraiisiiiiius
in k-:^(i
1050
No change(no
known alternative
even at this higher
GWP)
Residential Unitarv
A/C
700
R-454B
'5(>
Suhsecliir iraiiMiiiius
to k-454 \
1050
No change(no
known alternative
even at this higher
GWP)
Small Commercial
Unitary A/C
700
R-32
'5(>
Suhsecliir iraiisiiiiius
tn k-454 \
1050
No change(no
known alternative
even at this higher
GWP)
Large Commercial
Unitary A/C
700
R-32
'5ii
Suhsecliir iraiisiiiiius
ln k-454 \
1050
No change(no
known alternative
even at this higher
GWP)
Water & Ground
Source HP
700
R-32/R-452B
'5u
Suhsecliir iraiisiiiiius
ln k-454 \
1050
No change(no
known alternative
even at this higher
GWP)
PTAC/PTHP
700
R-32/R-452B
'5u
Suhsecliir iraiisiiiiius
to k-454 \
1050
No change(no
known alternative
even at this higher
GWP)
Non-MDI Aerosols
150
HFC-134a to HFC-
152a: HFC-
134a/HFC-152a to
Not-in-kind (NIK).
HCs. HFO-
1234/,e(E)
Suhsecliir iraiisiiuius
in NIK. IIC. III'O-
i:'4a.'
-------
Polystyrene Extruded
Boardstock and Billet
Foam
150
HFC-134a/C02 to
HFO-
1234zc(E)/HCFO-
1233/.d(E)
75
No change (base
case scenario
already complies
with limit)
225
No change(no
known alternative
even at this higher
GWP)
Integral Skin PU Foam
0
HCs
0
No change (base
case scenario
already complies
with limit)
0
No change (no
known alternative
even at this higher
GWP)
Rigid PU and
Polyisocvanuratc
La m i na I cd B oa rds I ock
0
HCs
0
No change (base
case scenario
already complies
with limit)
0
No change(no
known alternative
even at this higher
GWP)
Spray Foam
150
HFC-134a to HFO-
1234ze(E); HFC-
245fa to HCFO-
1233zd(E), HFO-
1234ze(E)
75
No change (base
case scenario
already complies
with limit)
225
No change (no
known alternative
even at this higher
GWP)
* No specific GWP limit is set for remote ice makers, refrigerated transport—road, and refrigerated transport—
marine. Based on the specific HFCs and specific blends containing HFCs prohibited, these subsectors are modeled
as a GWP limit of 2,200.
7.3 Results
Results of this exercise are shown in tables 7-2 and 7-3 below. In terms of avoided HFC consumption, the
results are generally aligned with expectations and indicate that a raising or lowering of the GWP limits in
the proposed rule would have the effect of producing corresponding increases or decreases, respectively,
in HFC consumption and emissions. However, it is notable that the change is modest in both cases. In the
high-GWP case, with limits 50% higher than those in the currently proposed rule, annual HFC
consumption reductions are approximately 1.4% lower on average relative to the base case, for a
cumulative difference of approximately -105 MMTEVe through 2050. In the low-GWP case, with limits
set 50% lower, annual HFC consumption reductions are approximately 4% higher on average relative to
the base case, for a cumulative difference of approximately +310 MMTEVe through 2050. While modest
relative to total consumption reductions resulting from this rule and the Allocation Rules, it is notable that
these increases are more significant relative to the incremental impact of the Technology Transitions Rule
alone. In the low-GWP case, the change would more than double the average annual incremental
consumption reductions, relative to the Allocation Rules. In the high-GWP case, the change would
represent a roughly 40% decrease in average annual incremental consumption reductions.
Several factors contribute to the somewhat muted HFC consumption impacts stemming from alternative
GWP limits in these scenarios. The first being that, as shown in table 7-1 above, many of the subsectors
retain their base case transition assumptions and thus are unchanged in this analysis even with the higher
71
-------
or lower assumed GWP limits in place. In addition, many of the subsectors where we do assume a change
in transitions are relatively small in terms of their HFC consumption relative to the total affected by this
rule. Finally, even for subsectors that represent a relatively large share of consumption, the difference
between the GWP of the transition assumed in the base case versus that assumed in the high- or low-GWP
case may be relatively small. For example, we assume that in the residential AC subsector, units would
transition to a lower-GWP HFC blend, R-454A (GWP of 236, or 88.7% below the original HFC blend R-
41 OA used in this subsector), in the low-GWP case as opposed to the base case transition to R-454B
(GWP of 465, or 77.7% below the original HFC blend). This yields additional average annual
consumption reductions of approximately 2.2 MMTEVe through 2050 which—while not trivial—are
small in comparison to total annual consumption reductions across all subsectors relative to business as
usual.
In contrast with the HFC consumption results, in both the high- and low-GWP case, the changes to
compliance costs are significant. In the high-GWP case, average annual abatement costs are $1.2 billion
higher than in the base case, and cumulative abatement costs come to approximately $1.8 billion through
2050. In the low-GWP case, average annual abatement costs are $2.7 billion higher than in the base case,
and cumulative abatement costs come to approximately $42.6 billion through 2050. By contrast,
cumulative costs in the base case come to a net savings of -$28 billion through 2050.
The higher abatement costs in both the high- and low-GWP case stem from differences in assumed
transition costs in a small subset of subsectors with relatively large shares of HFC consumption and
available abatement. For example, in the high-GWP case, the large retail food subsector transitions
partially to an HFC blend (R-454A) that would be available under the revised GWP limit, and which has
an assumed net positive transition cost of approximately $10-20 per ton of abatement as opposed to the
base case transition to CO2- and ammonia-based systems that are assumed to yield a net savings due to
their superior efficiency and the lower cost of refrigerants. In the low-GWP case, the transition to a lower
GWP blend in the residential AC subsector yields a modest improvement in avoided consumption, as
mentioned above, but a much steeper increase in costs to approximately $28 per ton of abatement as
opposed to $5.60 in the base case. Each of these subsectors represents a substantial share of the HFC
market (e.g., Residential AC accounts for over 100 MMTEVe in annual HFC consumption, or roughly
one-third of the total market across all sectors in the model's BAU), meaning that changes to assumed
transitions costs will have significant impacts on results.
These findings further illustrate the decoupled nature of abatement and costs in the model; a transition to
a lower-GWP substitute may yield additional abatement at a lower cost if the transition is assumed have a
net cost savings, and transitions to higher-GWP substitute do not necessarily reduce costs if these
72
-------
substitutes are more expensive to produce and use. Results of this exercise also underscore that the model
is sensitive to the cost assumptions of transitions, particularly for subsectors that consume a large share of
HFCs. Tables 7-2, 7-3, and 7-4 show the annual consumption reductions, emission reductions, and costs,
respectively, from these two scenarios and incremental changes relative to the Technology Transitions
Rule base case.
Table 7-2 - Annual Consumption Reductions in Technology Transitions Rule Base Case and
High/Low GWP Scenarios
lecliiwloiiy
ii iinsilions linlc -
Hasc ( use
Technology Transitions link- - Low
(ill I'Casc
h'clmolo^y Transitions link• - lli^h
(illPCusc
Year
( oiiMiinj'lion
licilncliiins
(MMTI.I W
( onsnmpfion
lictlnclions
( M M TI. I c)
( limine in
( oiisnniption
lictlnclions
(MM I I. I c)
( oiiMimptioii
licdncliiins
(MM TI. I c)
( litin^f in
( (tnsuniplion
lii'tlnclioii.s
( M M TI. I c)
2025
204
213
10
201
-2
2026
217
227
10
215
-2
2027
230
241
10
228
-3
2028
247
257
10
244
-3
2029
256
265
8
253
-4
2030
260
266
7
256
-4
203 1
271
278
7
267
-4
2032
282
289
7
277
-5
2033
292
300
8
287
-5
2034
302
310
8
297
-5
2035
311
318
7
305
-6
2036
317
322
5
311
-6
2037
317
324
8
311
-6
2038
320
329
10
315
-4
2039
316
331
14
314
-3
2040
308
325
16
307
-1
2041
311
329
18
312
1
2042
314
331
17
314
0
2043
318
331
13
314
-4
2044
321
334
14
317
-4
2045
321
336
15
315
-6
2046
324
339
15
318
-6
2047
326
342
16
320
-6
2048
329
345
17
323
-6
2049
330
348
18
325
-5
2050
331
350
19
325
-6
73
-------
Table 7-3: Annual Emission Reductions in Technology Transitions Rule Base Case and
High/Low GWP Scenarios a
Technology
Transitions Utile
- fiase C use
Technology Transitions
Rule-Low (Ml* Case
Technology Transitions Rule -
High (iti l'Case
) ear
Emission
Reductions
(UUTi:\ e)
Emission
Reductions
(MMTi:\ e)
( hange in
amission
Reductions
-------
Table 7-4 - Costs of Compliance * by Year (billions of2020$) in Technology Transitions Base
Case and High/Low GWP Scenarios
Technology
I'mnsilions link- -
HtlSl' ( (ISC
Technology lituisilioiis link' - Tow
(ill P ( Use
leclinoloxy Transitions link- - High
(,li P(
-------
Technology Transitions Rule High Additionality Case, the low GWP scenario, and the high GWP
scenario. The incremental climate benefits shown here represent the additional benefits (positive
numbers) achieved from these four scenarios over the Framework Allocation Rule reference case.
Table 7-5: Undiscounted Monetized Climate Benefits of the Technology Transitions Rule Low
and High GWP Case Scenarios 2025-2050 (3% model average SC-GHG estimates, millions of
2020$, discounted to 2022)a
Year
Technology Transitions
Rule Base ( ase
Incremental ( limale
Benefits (millions
2020S)
Technology Transitions
High .Atltlilionalily ( ase
Incremental ( limale
Benefits (millions
2020S)
Technology Transitions
Low (ill l>( ase
Incremental ( limale
Benefits (millions
2020.S>
'/ ei ¦// nolofii • '/ ians ilions
llifih
-------
of benefits and costs in PV and EAV terms for the base case and high additionally case can be found in
Table 7-6. Estimates in the table are presented as rounded values.
Table 7-6 - Summary of Annual Incremental Climate Benefits, Costs, and Net Benefits of the
Technology Transitions Rule Low and High GWP Case Scenarios for the 2025-2050 Timeframe
(millions of2020$, discounted to 2022)a-b-c-d
l.ou-
-------
estimate. We emphasize the importance and value of considering the benefits calculated using all four SC-HFC
estimates. A consideration of climate effects calculated using discount rates below 3 percent, including 2 percent
and lower, is also warranted when discounting intergenerational impacts.
b Rows may not appear to add correctly due to rounding.
0 The annualized present value of costs and benefits are calculated as if they occur over a 26-year period from 2025
to 2050.
d The costs presented in this table are annual estimates.
e The PV for the 7% net benefits column is found by taking the difference between the PV of climate benefits at 3%
and the PV of costs discounted at 7%. Due to the intergenerational nature of climate impacts the social rate of return
to capital, estimated to be 7 percent in OMB 's Circular A-4, is not appropriate for use in calculating PV of climate
benefits.
78
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Chapter 8: Environmental Justice Analysis
8.1 Introduction and Background
This environmental justice analysis was developed to support the proposed Technology Transitions Rule.
The environmental justice analysis that was conducted as part of the Allocation Framework RIA
addressed issues associated with the impacts of changes in the production of HFCs on communities near
facilities identified as producers of these chemicals. EPA could not identify specific effects of the
phasedown on individual communities, but the Agency did identify eight facilities with emissions likely
to be affected by the Allocation Framework Rule. EPA was also able to analyze demographic
characteristics of the fence-line communities in the Census Block Groups within 1-, 3-, 5-, and 10-mile
radii of the affected facilities. Chapter 6 - the environmental justice analysis - of the Allocation
Framework RIA concluded, in part, that:
• Higher percentages of low income and Black or African American individuals live near
HFC production facilities compared to the overall or rural average at the national level;
• Multiple HFC alternatives are available, some of which have toxic profiles for the
chemicals used as feedstocks in their production.
• Given limited information regarding which substitutes will be produced where, it is
unclear to what extent this rule will impact baseline risks from hazardous air toxics for
communities living near HFC and HFC substitute production facilities.
Many of the environmental justice implications of the proposed Technology Transitions Rule are similar
to those addressed at length in the Allocation Framework RIA. This proposed rule has the effect of
providing incremental additional reductions in HFC consumption beyond those specified in the
Allocation Framework Rule itself. These reductions in emissions are expected to further improve future
climate conditions to the benefit, particularly, of vulnerable populations. The Agency is not quantifying
these benefits at this time.
8.2 Environmental Justice at EPA
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 minority populations and low-income populations 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
79
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of environmental laws, regulations, and policies.38 Executive Order 14008 (86 FR 7619; January 27,
2021) also 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.
As noted in the Allocation Framework RIA, the production and consumption of HFCs is expected to
result in changes in the emissions of chemicals which burden communities surrounding the production
facilities. Because of the limited information regarding where substitutes will be produced and what other
factors might affect production and emissions at those locations, it's unclear to what extent this rule may
affect baseline risks from hazardous air toxics for communities living near facilities producing HFC
substitutes. We do understand that communities neighboring facilities that currently produce HFCs and
those that are likely to produce HFC substitutes are often overburdened and disadvantaged. The Agency
has a strong interest in mitigating undue burden on these overburdened communities.
EPA stated its intention in the Allocation Framework Rule to "continue to monitor the impacts of this
program on HFC and substitute production, and emissions in neighboring communities, as we move
forward to implement this rule," (see 86 FR 55129). EPA will continue to work to address environmental
justice and equity concerns for the communities near the facilities identified in this analysis. For example,
the requirements for emissions data in the forthcoming proposed 2024 Allocation Rule will give EPA
tools to continue to address these concerns. EPA is proposing in that rule to build on the one-time
reporting requirement and require annual reporting of the emission quantities from each facility's HFC
production line emissions units. In order to track the environmental justice impacts of HFC production,
38 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 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 minority populations, low-income populations,
tribes, and indigenous peoples in the development, implementation and enforcement of environmental laws, regulations and
policies" (U.S. EPA, 2015). See also https://www.epa.gov/environmentaljustice.
80
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EPA would establish a baseline for each facility and monitor and track trends of feedstock, byproduct,
and coproduct emissions related to HFC production on a more detailed and annual basis, in addition to the
quantity of HFCs produced and the location of HFC production facilities.
In addition to the proposed Technology Transitions Rule and other rules which address emissions under
the Clean Air Act, the Agency continues to evaluate chemicals under the Toxic Substances Control Act
(TSCA). For certain chemicals for which risk evaluations are complete that are used in the manufacture of
HFCs and HFC substitutes, including carbon tetrachloride, methylene chloride, tetrachloroethylene
(perchloroethylene), and trichloroethylene, EPA under section 6 of TSCA will be addressing the
unreasonable risks identified. If EPA finalizes its forthcoming proposed 2024 Allocation Rule, data on
emissions obtained through that proposed rule may inform future rulemakings affecting HFC and HFC
substitute production facilities.
8.3 Environmental Justice Analysis for the Proposed HFC Allocation Rule
In the Allocation Framework Rule, EPA summarized the public health and welfare effects of GHG
emissions (including HFCs), including findings that certain parts of the population may be especially
vulnerable to climate change risks based on their characteristics or circumstances, including the poor, the
elderly, the very young, those already in poor health, the disabled, those living alone, and/or indigenous
populations dependent on one or limited resources due to factors including but not limited to geography,
access, and mobility (86 FR 55124 - 55125). Potential impacts of climate change raise environmental
justice issues. Low-income communities can be especially vulnerable to climate change impacts because
they tend to have more limited capacity to bear the costs of adaptation and are more dependent on
climate-sensitive resources such as local water and food supplies. In corollary, some communities of
color, specifically populations defined jointly by both ethnic/racial characteristics and geographic
location, may be uniquely vulnerable to climate change health impacts in the United States.
As discussed in more detail in the Allocation Framework RIA, the environmental justice benefits of
reducing climate change are significant. The HFCs themselves are not a local pollutant and have low
toxicity to humans. However, chemicals used as feedstocks or catalysts in the production of HFCs or
produced as byproducts may have localized effects if released into the environment, and these may have
environmental justice implications. The HFCs regulated under the HFC Allocation Program use a wide
array of chemicals as feedstocks or catalysts for production or produce them as byproducts, some of
which are hazardous when released into the environment or when workers or other occupational non-
users are exposed to them. More information on these chemicals, their toxicities, and their health effects
can be found in the Allocation Framework RIA.
81
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Similar to the Allocation Framework Rule, EPA expects that this proposed rule would reduce GHG
emissions, which would benefit populations that may be especially vulnerable to damages associated with
climate change. We also expect that the restriction on use of certain HFCs would increase the production
of HFC substitutes. For the purposes of the proposed Technology Transitions Rule, EPA assessed the
characteristics of communities near facilities we expect to be affected by this rule (i.e., facilities
producing predominant HFC substitutes). EPA used data from the Toxics Release Inventory (TRI),39
Greenhouse Gas Reporting Program (GHGRP),40 Chemical Data Reporting (CDR) Program,41 and
information provided by industry stakeholders to identify the facilities producing HFC substitutes. Once
production locations were identified, EPA retrieved the Facility Registry Service (FRS) IDs for each
production facility using the Agency's FRS national dataset42 This step was conducted to facilitate
extracting 1) an environmental profile and 2) demographic information within 1,3,5 and 10 miles for
each facility using EPA's Enforcement and Compliance History Online (ECHO) database.43
In considering potential additional analysis for a final rule based on this proposal, EPA is also considering
assessing the estimated exposure of the communities near the identified facilities to toxics using the Risk
Screening Environmental Index Geographic Microdata (RSEI-GM).44
EPA identified 12 facilities producing predominant non-fluorinated substitutes for HFCs such as
hydrocarbons, ammonia (R-717), and CO2 (R-744), and two additional facilities producing
hydrofluoroolefin (HFOs), for a total of 14 sites that may be impacted by this rule and where production
changes may impact nearby communities.
As discussed in the Allocation Framework RIA, there are many toxic and potentially toxic chemicals
involved in the manufacturing processes that may be impacted by this rule, and fenceline communities are
impacted by emissions from facilities of the type identified here. That analysis details the reported
39 TRI tracks the management of certain toxic chemicals that may pose a threat to human health and the environment. U.S.
facilities in different industry sectors must report annually how much of each chemical is released to the environment and/or
managed through recycling, energy recovery and treatment. Facilities submit a TRI Form R for each TRI-listed chemical it
manufactures, processes, or otherwise uses in quantities above the reporting threshold.
40 The GHGRP requires reporting of greenhouse gas data and other relevant information from large GHG emission sources, fuel
and industrial gas suppliers, and CO2 injection sites in the United States. The program generally requires reporting when
emissions from covered sources are greater than 25,000 pounds of CC>2e per year.40 Publicly available information40 includes
facility names, addresses, and lat/long information.
41 The CDR program, under the Toxic Substances Control Act, requires manufacturers (including importers) to provide EPA with
information on the production and use of chemicals in commerce. Under the CDR rule, EPA collects information on the types,
quantities, and uses of chemical substances produced domestically and imported into the United States. The information is
collected every four years from manufacturers of certain chemicals in commerce generally when production volumes are 25,000
pounds or greater for a specific reporting year.41 Publicly available information41 includes facility name, addresses, lat/long
information on production facilities, and additional information about the chemicals and downstream uses.
42 FRS National Data Set available at https://www.epa.zov/irs/eva-irs-facilities-state-sinzle-file-csv-dawnload
43 https://echo.epa.zov/.
44 The Risk-Screening Environmental Indicators Geographic Microdata is available at https://www.epa.zov/rsei/rsei-zeozraphic-
microdata-rsei-gm. The RSEI model uses reported emissions from the Toxic Release Inventory to model exposure to
environmental risk at a very granular level.
82
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emissions and assessments of the risks that some of the substances may pose, but it also notes several
limits to our ability to assess the impact this rule on the exposure that specific communities may face:
• These facilities generally produce several chemical products, individual facilities use
different production methods with differing emissions characteristics, and processes and
feedstocks may change. It is unknown how emissions and risks may change as a result of
the Allocation Framework Rule, and this uncertainty extends to the potential emission
impacts of this rule
• Many of the emissions resulting from production are poorly understood given a lack of
data on the choices that producers of impacted chemicals will make in the future in
response to the Allocation Framework Rule and this proposed rule.
• Many of the communities near the facilities expected to be affected by the Allocation
Framework Rule and this proposed rule are also near other sources of toxic emissions
which contribute to environmental justice concerns.
• Some companies with multiple production facilities may choose to consolidate
production of regulated substances at a subset of facilities as the phasedown continues,
which could lead to an increase in regulated substance production at a single facility,
despite the overall phasedown.
Due to the limitations of the current data, we cannot make conclusions about the impact of this proposed
rule on individuals or specific communities. For the purposes of identifying environmental justice issues,
however, it is important to understand the characteristics of the communities surrounding these facilities
to better ensure that future actions, as more information becomes available, can improve outcomes.
Following the format used for the Allocation Framework RIA, this analysis focuses on information that is
available on the demographics and baseline exposure of the communities near these facilities.
8.4 Aggregate Average Characteristics of Communities Near Potentially
Affected Production Facilities
The RIA for the Allocation Framework Rule notes that a key issue for evaluating potential for
environmental justice concerns is the extent to which an individual might be exposed to feedstock,
catalyst, or byproduct emissions from production of HFCs or HFC substitutes. As described earlier, as
part of risk evaluations conducted under section 6 of TSCA, EPA has evaluated risks to workers and
occupational non-users for several chemicals used as feedstocks for HFCs or HFC substitutes (e.g.,
carbon tetrachloride, methylene chloride, tetrachloroethylene (perchloroethylene), and trichloroethylene).
83
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These risks are characterized in the 2020 risk evaluations for each chemical.45 The rulemakings under
TSCA to address unreasonable risks for each chemical aim to incorporate reasonably available
information on demographics of workers at these facilities in order to identify potential environmental
justice concerns.
EPA has not undertaken an analysis of how the emissions of various HFC or HFC substitute feedstocks,
catalysts, and byproducts affect nearby communities (e.g., through use of a fate and transport model or the
modeling of main exposure pathways). However, a proximity-based approach can identify correlations
between the location of these identified production facilities and potential effects on nearby communities.
Specifically, this approach assumes that individuals living within a specific distance of an HFC
production facility are more likely to be exposed to releases from feedstocks, catalysts, or byproducts.
Those living further away are less likely to be exposed to these releases. Census block groups that are
located within 1, 3, 5 and 10 miles of the facility are selected as potentially relevant distances to proxy for
exposure. Socioeconomic and demographic data from the American Community Survey 5-year data
release for 2019 (the most recent year available) are used to examine whether a greater percentage of
population groups of concern live within a specific distance from a production facility compared to the
national average. The national average for rural areas is also presented since nine of the 14 production
facilities expected to be impacted by the proposed rule are classified as rural.46
In addition, Air Toxics Screening Assessment (AirToxScreen, formerly National Air Toxic Assessment
(NATA)) data from 2017 (the most recent year available) for census tracts within and outside of a 1-, 3-,
5- and 10-mile distance are used to approximate the cumulative baseline cancer and respiratory risk due to
air toxics exposure for communities near these production facilities. The total cancer risk is reported as
the risk per million people if exposed continuously to the specific concentration over an assumed lifetime.
The total respiratory risk is reported as a hazard quotient, which is the exposure to a substance divided by
the level at which no adverse effects are expected. Both total risk measures are the sum of the individual
risk values for all the chemicals evaluated in the AirToxScreen database. Note that these risks are not
necessarily only associated with a specific HFC substitute production facility. Industrial activity is often
concentrated (i.e., multiple plants located within the same geographic area).
45 The risks evaluations for these chemicals can be found in the following dockets: EPA-HQ-OPPT-2019-0499 (carbon
tetrachloride); EPA-HQ-OPPT-2019-0437 and EPA-HQ-OPPT-2016-0742 (methylene chloride); EPA-HQ-OPPT-2019-0502
andEPA-HQ-OPPT-2016-0732 (tetrachloroethylene (perchloroethylene)); EPA-HQ-OPPT-2016-0737 andEPA-HQ-OPPT-
2019-0500E (trichloroethylene).
46 The US Census definition of "rural" is used. The term rural is applied to census areas that are not classified as urbanized areas
or urban clusters and have a population density below 2,500 people per square mile. Census also looks at other factors before
classifying an area as rural including adjacency to an urban area. For the 1-mile radius, population density near an HFC
production facility ranges from 40 people per square mile to 306 people per square mile for each of the seven facilities in rural
areas. For the 3-mile radius, population density near a facility ranges from 46 people per square mile to 1,262 people per square
mile. Elowever, if the majority of census blocks within our buffer are urban-adjacent, we continue to use the overall national or
state level average as a basis of comparison.
84
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Table 8-1 presents the density of TRI facilities (nearby facilities that could contribute to the cumulative
AirToxScreen cancer and respiratory risk in communities) located within 1-, 3-, 5-, and 10-mile radii of
the nine facilities. 11 of the 14 facilities have fewer than five neighboring TRI facilities within a 1-mile
radius. Expanding the radius to 3 miles increases the number of neighboring TRI facilities substantially
for seven of the facilities. Expanding the radii to 5 and 10 miles generally increases the number of
neighboring facilities even further. There are only three facilities within ten miles of the KSP plant in
Tad, WV, and analysis shows there are no TRI facilities within ten miles of the Aeropress facility in
Sibley, LA.
Table 8-1: Total Number of Neighboring TRI Facilities within 1, 3, 5 and 10 miles of Identified
Facilities
I'dcilily
Locution
llil
llil
T1H
llil
I'dcililics
I'dcililics
i'dcililics
I'dcililics
1
fill/ill u 1-
within ti
with in a 5-
n-illiin ti Ill-
Mill' lititlins
Mile Radius
Milc Hudius
Mile lidtlius
Chemours-
Corpus Christi
Gregory, TX
2
4
6
6
Chemours El Dorado
El Dorado, AR
2
2
2
12
Honeywell-Geismar
Geismar, LA
4
21
31
36
Aeropress Corp.
San Dimas Plant
San Dimas, CA
1
1
4
34
CF Industries Nitrogen
LLC-Port Neal
Sergeant Bluff,
IA
2
6
7
21
Linde, Inc - Whiting
East Chicago,
IN
5
27
35
71
Air Products and
Geismar, LA
13
18
42
Chemicals Geismar SMR
J
Haltermann Carless
Manvel Inc
Manvel, TX
1
1
2
10
Air Products and
Chemicals Port Arthur
Port Arthur, TX
2
15
15
31
Diversified Gas and Oil
Tad, WV
KSP C02 Plant
J
Linde, Inc - Decatur
Decatur, AL
3
11
23
29
CALAMCO
Stockton, CA
5
7
14
22
Diversified
CPC International
Channahon, IL
5
6
9
24
Aeropres Corp -Sibley
Sibley, LA
Source: Toxic Releases Inventory (2019)
Summary statistics presented in the Allocation Framework RIA describe other types of TRI emissions
associated with feedstocks, catalysts, or byproducts of HFC substitute production (i.e., water and land
emissions, offsite disposal, and non-production releases). These may be affected by the current rule, but
these aspects of risk have not been explicitly incorporated into this proximity analysis, though they may
be worthy of further investigation.
Table 8-2 presents summary information for the demographic data and AirToxScreen risks averaged
85
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across the 14 communities near the identified production facilities compared to the overall and rural
national average. This table is analogous to one presented in the Allocation Framework RIA for these
facilities, but it uses the updated AirToxScreen data.
The values in the last four columns reflect population-weighted averages across the Census block groups
within the specified distance of the facility. While it is not possible to disaggregate the risk information
from AirToxScreen by race, ethnicity or income, the overall cancer and respiratory risk in communities
within 1, 3, 5 or 10 miles of an identified production facility is markedly greater than either the overall or
rural national average.
Table 8-2: Overall Community Profile and AirToxScreen Risks for Communities Near Identified
Facilities
Overall
\ational
¦ivera^e
Rural Areas
\ational
.1 rm/ji'
II iill in 1
mile
".1
production
facility
H ithin 3
mill's
"J
production
facility
H illiin 5
miles
1
production
facility
Hit hi it 10
miles
"J
production
facility
% White (race)
72
84
61
60
58
54
% Black or
African American
(race)
13
7.6
19
15
15
19
% Other (race)
15
8.2
20
25
26
27
% Hispanic
(ethnic origin)
18
10
32
37
39
34
Median
Household Income
(lk 2019$)
71
67
63
66
65
70
% Below Poverty
Line
7.3
6.8
8.2
8.5
8.5
7.6
% Below Half the
Poverty Line
5.8
5.1
8.0
7.0
6.8
6.1
Total Cancer Risk
(per million)
29
26
43
38
37
36
Total Respiratory
Risk (hazard
quotient)
0.37
0.32
0.43
0.43
0.42
0.42
Notes: Demographic definitions are as described in the 2019 American Community Survey (US Census 2021). The
"hazard quotient" is defined as the ratio of the potential exposure to a substance and the level at which no adverse
effects are expected (calculated as the exposure divided by the appropriate chronic or acute value). A hazard
quotient of 1 or lower means adverse noncancer effects are unlikely and, thus, can be considered to have negligible
hazard. For HQs greater than one, the potential for adverse effects increases, but we do not know by how much.
Total cancer and respiratory risk are drawn from the Air Toxics Screening Assessment (AirToxScreen, formerly
National Air Toxic Assessment (AirToxScreen, 2021).
Results by race and ethnicity are often sensitive to how the comparison group (i.e., overall, versus rural
national average) and the distance to an HFC substitute production facility are defined. Looking across all
86
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14 facilities (Table 8-2), a higher percentage of Black or African American individuals live in the
communities near HFC substitute production facilities compared to the national average or the rural areas
national average. In these communities, the percentage of White residents is lower than either the national
average or the rural national average at all distances analyzed. There is a higher percentage of Black or
African American individuals near these locations, compared to the averages, and higher percentages of
people of other racial minorities or persons of Hispanic Ethnicity. Median income is lower for the
communities near these facilities compared to the national average or rural national average, except that
within 10 miles, the median income of $70,000 is higher than the rural national average of $67,000. There
is a higher percentage of households with low and very low incomes at all analyzed distances from these
facilities. The national percentage of rural households with incomes less than half of the poverty line is
5.1%, and the overall national average is 5.8%. Within 1 mile of these specific facilities, the average
percentage of rural households with incomes less than half of the poverty line is 8.0%. The percentage of
households with incomes less than half of the poverty level declines with distance from the facilities, but,
at 6.1%, the number at the 10-mile radius is still higher than the national or rural national average.
For this analysis, we use the most recent 2017 AirToxScreen data for total cancer risk and total
respiratory risk. Comparing the data for the whole country to the 2014 data (that were available at the
time the Allocation Framework RIA was written) it is important to note that total cancer and total
respiratory risk have dropped for both rural and national average areas. The overall national average and
rural areas average total cancer risk using the newest data are shown to have dropped to 29 and 26 per
million, respectively, from 32 and 29 per million, compared to the 2014 data averages. A similar drop for
total respiratory risk to 0.37 and 0.32 per million for the overall national average and rural areas national
average respectively, from 0.44 and 0.38 per million.
Proximity analysis to the identified facilities generally shows higher risks at all analyzed distances, on
average, for these 14 facilities. The analysis shows that the risks are higher for those within the 1-mile
average radius and generally decrease at the 3-, 5-, and 10-mile radii. It is worth noting that the averages
reported in Table 8-2 may obfuscate potentially large differences in the community characteristics
surrounding individual production facilities. It is important, therefore, to examine the socioeconomic and
demographic community characteristics for each facility separately, using the appropriate applicable
national- and state-level averages for comparison.47
47 The relatively small number of facilities directly affected by this rule enabled EPA to assemble a uniquely granular assessment
of the characteristics of these facilities and the communities where they are located.
87
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8.5 Characteristics of Communities Near Identified Individual Facilities
For three of the 14 facilities identified here, the demographic data is identical to that published in the
Allocation Framework RIA in September of 2021. The racial, ethnic, and income figures for these eight
communities within 1,3,5, and 10 miles of the respective facilities are drawn from the most recent
American Communities Survey data, which is the 2019 dataset. The facility-by-facility discussion in the
Allocation Framework RIA used the 2014 NATA Database. This analysis uses the newest (2017)
AirToxScreen Database. For the Chemours Corpus Christi, Chemours El Dorado, and Honeywell
Geismar facilities, the AirToxScreen 2017 analysis indicates that total cancer risk and total respiratory
risk declined since the 2014 report, and two of these facilities are in communities identified as having
higher risks than either their respective state or national averages. (The analysis shows that risks are
substantially higher for the Geismar community).
Table 8-3: Community Profiles and AirToxScreen Risks for Chemours Corpus Christi - Gregory,
TX
II it hin 1
II ilhin.?
II illiin 5
II ithin III
Overall
Overall
mile
miles
miles
miles
\ational
State
"J
"J
"J
"J
Average
Average
production
facility
production
facility
production
facility
production
facility
% White (race)
72
74
95
91
92
91
% Black or
African American
13
12
1.6
2.3
2.2
2.1
(race)
% Other (race)
15
14
3.6
6.3
6.2
7.1
% Hispanic
(ethnic origin)
18
39
40
41
44
40
Median
Household Income
71
69
78
79
69
61
(lk 2019$)
% Below Poverty
Line
7.3
8.2
1.4
4.1
3.4
6
% Below Half the
Poverty Line
5.8
6.2
1.0
2.8
3.7
4.9
Total Cancer Risk
(per million)
29
31
20
20
20
20
Total Respiratory
Risk (hazard
0.37
0.36
0.20
0.20
0.21
0.21
quotient)
88
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Table 8-4: Community Profiles and AirToxScreen Risks for Chemours El Dorado - El Dorado,
AR
Rural Areas
\alional
.Ii'ito;1!'
Rural Areas
State
¦ 1 verage
II it liin 1
mile
".1
l>n>
-------
Total Respiratory
Risk (hazard 0.32 0.43 0.52 0.53 0.53 0.51
quotient)
Of the other 11 facilities, nine are in communities in which either the AirToxScreen 2017 data show
elevated Total Cancer Risk and/or Total Respiratory Risk are generally above the national and state
averages. The Air Products and Chemicals Geismar, LA facility (near the Honeywell Geismar Complex
noted above) has substantially higher risks than the state or national averages. The CF Industries facility
in Sergeant Bluff, IA and the Diversified CPC International facility in Channahon, IL are located in areas
where the Total Cancer Risk and Total Respiratory Risk are generally lower than the state and national
average risks (although the Total Cancer Risk within one mile of the Diversified CPC facility is 30 per
million - slightly higher than the 29 per million risks for the overall national average and Illinois overall
average risk).
Ten of the 14 facilities are situated in communities that are generally more diverse than the national or
state average. Four of the facilities are in communities (San Dimas, CA; Stockton, CA; East Chicago, IL;
and Decatur, AL) are home to more residents who identify as having Hispanic Ethnicity than the state or
national averages. Five communities (East Chicago, IL; Geismar, LA; Port Arthur, TX; Decatur, AL, and
Sibley, LA) have higher proportions of residents who identify as Black or African American than the
averages. For some facilities, such as the Chemours El Dorado, HC Manvel, Aeropress-Sibley and CF
Industries Port Neal plants, there are relatively high percentages of households that identify as White in
close proximity, but become more diverse at the 5 and 10 mile distances.
For six of the 14 facilities, median household incomes in surrounding communities are consistently lower
the state or national averages and percentages of low and very low-income households are high. In many
cases, the incomes are lowest and poverty rates highest close to the plants. On the other hand, for
Chemours Corpus Christi, Chemours El Dorado, Diversified CPC Channahon, and Aeropress San Dimas,
median income is relatively high close to the facility, and percentages of households below the poverty
line and half the poverty line are low. In these communities, analysis shows that median incomes decrease
and poverty rates increase with distance from the facilities. Finally, the communities near the Honeywell
and Aeropress facilities in Geismar, LA , the Diversified CPC facility in Channahon, IL. and the
Haltermann Carless facility in Manvel, TX have higher median incomes and lower percentages of
households with low incomes than the averages.
90
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Table 8-6: Community Profiles and AirToxScreen Risks for Aeropress Inc. - San Dimas, CA
Overall
\ational
Average
Overall
State
Average
II it hin 1
mile
"J
production
facility
II it hin.?
miles
"J
production
facility
II itliin 5
miles
"J
production
facility
II it hin III
miles
"J
production
facility
% White (race)
72
60
73
65
58
49
% Black or
African American
(race)
13
5.8
2.1
3
3.9
3.6
% Other (race)
15
35
25
32
39
47
% Hispanic
(ethnic origin)
18
39
36
44
50
55
Median
Household Income
(lk 2019$)
71
83
88
88
83
80
% Below Poverty
Line
7.3
7.3
3.5
4.8
6
6.5
% Below Half the
Poverty Line
5.8
5.8
5.6
4.1
5
4.6
Total Cancer Risk
(per million)
29
31
40
38
38
37
Total Respiratory
Risk (hazard
quotient)
0.37
0.43
0.44
0.45
0.44
0.46
Table 8-7: Community Profiles and AirToxScreen Risks for CF Industries Inc - Nitrogen Port
Neal, Sergeant Bluff IA
liurul Areas
\ntioiHil
A verii^e
Rural Areas
Stale
¦ 1 verage
II it hin 1
mile
»1
production
facility
II it hin.?
miles
"J
production
facility
II itliin 5
miles
"J
production
facility
II ithin lit
miles
"J
production
facility
% White (race)
84
94
94
90
79
79
% Black or
African American
(race)
7.6
1.6
0.13
0.07
0.25
3.0
% Other (race)
8.2
4.4
5.7
9.9
20
18
% Hispanic
(ethnic origin)
10
4.2
2.1
4.0
6.9
18
Median
Household Income
(lk 2019$)
67
68
67
70
82
68
% Below Poverty
Line
6.8
5.0
3.0
4.9
6.4
6.0
% Below Half the
Poverty Line
5.1
3.6
1.5
2.9
4.3
6.6
Total Cancer Risk
(per million) 26 _ 20 _ 20 _ 20 _ 20 _ 20
91
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Total Respiratory
Risk (hazard
quotient)
0.32
0.22
0.2
0.2
0.2
0.21
Table 8-8: Community Profiles and AirToxScreen Risks for Linde Inc. Whiting - East Chicago,
IN
Overall
\atioiial
Overall
Slate
.Average
11 i th in 1
mile
"J
production
facility
11 ithin.?
miles
"J
production
facility
11 ithin 5
miles
"J
production
facility
11 ithin lit
miles
"J
production
facility
% White (race)
72
83
23
35
46
33
% Black or
African American
(race)
13
9.4
35
29
32
57
% Other (race)
15
7.3
43
36
22
11
% Hispanic
(ethnic origin)
18
6.9
61
49
38
20
Median
Household Income
(lk 2019$)
71
62
34
39
45
47
% Below Poverty
Line
7.3
7.0
17
14
12
11
% Below Half the
Poverty Line
5.8
6.0
13
13
11
10
Total Cancer Risk
(per million)
29
23
30
30
30
30
Total Respiratory
Risk (hazard
quotient)
0.37
0.30
0.4
0.37
0.37
0.37
Table 8-9: Community Profiles and AirToxScreen Risks for Air Products Geismar -
Geismar, LA
linral .1 reas
\alional
A verage
linral Areas
St at e
Average
11 ith in 1
mile
"./
production
/acilily
11 ithin
miles
"./
production
facility
II ithin 5
miles
".f
production
facility
11 ithin HI
miles
"J
production
facility
% White (race)
84
70
63
70
56
68
% Black or
African American
(race)
7.6
25
30
26
39
27
% Other (race)
8.2
4.7
6.6
4.0
5.3
5.7
% Hispanic
(ethnic origin)
10
3.6
1.2
3.3
4.7
5.0
Median
Household Income
(lk 2019$)
67
53
86
83
79
80
% Below Poverty
Line
6.8
9.8
2.2
3.8
6.3
5.3
92
-------
% Below Half the
Poverty Line
5.1
7.8
6.5
5.3
8.3
5.4
Total Cancer Risk
(per million)
26
39
93
95
93
81
Total Respiratory
Risk (hazard
quotient)
0.32
0.43
0.50
0.50
0.51
0.50
Table 8-10: Community Profiles and AirToxScreen Risks for Haltermann Carless Manvel -
Manvel, TX
liural .1 reas
\alional
A verage
liurul Im/s
Si trie
Average
11 iIII in 1
mile
"./
I'roiluclion
/aeilily
U it hin J
miles
"./
production
facility
II it hin 5
miles
".f
production
facility
11 it hin 10
miles
"J
production
facility
% White (race)
84
82
88
83
70
64
% Black or
African American
(race)
7.6
7.9
4.9
8.4
17
19
% Other (race)
8.2
9.8
6.7
9.0
12
18
% Hispanic
(ethnic origin)
10
32
27
32
34
27
Median
Household Income
(lk 2019$)
67
70
71
80
82
99
% Below Poverty
Line
6.8
7.1
4.6
4.5
5.1
3.5
% Below Half the
Poverty Line
5.1
5.4
1.9
2.4
3.7
3.0
Total Cancer Risk
(per million)
26
28
30
30
30
31
Total Respiratory
Risk (hazard
quotient)
0.32
0.33
0.35
0.36
0.37
0.37
Table 8-11: Community Profiles and AirToxScreen Risks for Air Products and Chemicals Inc. -
Port Arthur, TX
Overall
\ational
Average
Overall
Slate
.Average
H iIII in 1
mile
"J
production
facility
11 illiin.?
miles
"J
production
facility
11 illiin 5
miles
"J
production
facility
11 it hin 10
miles
"J
production
facility
% White (race)
72
74
33
32
51
69
% Black or
African American
(race)
13
12
61
63
37
22
% Other (race)
15
14
6.6
5.4
12
8.9
% Hispanic
(ethnic origin)
18
39
5.4
18
35
25
93
-------
Median
Household Income
(lk 2019$)
71
69
43
35
38
50
% Below Poverty
Line
7.3
8.2
9.5
13
13
8.3
% Below Half the
Poverty Line
5.8
6.2
14
14
11
7.4
Total Cancer Risk
(per million)
29
31
41
43
51
59
Total Respiratory
Risk (hazard
quotient)
0.37
0.36
0.4
0.4
0.4
0.4
Table 8-12: Community Profiles and AirToxScreen Risks for Diversified Gas and Oil
- Tad, WV
liural .1 reas
\alional
.¦ 1 vernal'
liurul Areas
Slulc
Average
11 illiin 1
mile
»./
I'roilnclion
/ticilily
U it hin J
miles
<>(
production
facility
II it hin 5
miles
"f
production
facility
Wit hin HI
miles
"J
production
facility
% White (race)
84
95
99
97
96
90
% Black or
African American
(race)
7.6
2.4
0
0.29
0.96
6.2
% Other (race)
8.2
2.5
0.89
2.7
2.9
3.9
% Hispanic
(ethnic origin)
10
1.4
0.45
0.91
0.9
0.89
Median
Household Income
(lk 2019$)
67
50
48
47
44
49
% Below Poverty
Line
6.8
9.3
10
11
11
9
% Below Half the
Poverty Line
5.1
6.6
5.5
7.4
5.9
9.1
Total Cancer Risk
(per million)
26
27
30
30
30
31
Total Respiratory
Risk (hazard
quotient)
0.32
0.32
0.40
0.40
0.40
0.39
Table 8-13: Community Profiles and AirToxScreen Risks for Linde Inc. Decatur - Decatur, AL
Overall
\alional
Average
Overall
Slate
.Average
II iIhin 1
mile
production
/ticilily
11 illiin J
miles
"J
production
facility
H illiin 5
miles
"J
production
facility
llil hin 10
miles
"J
production
facility
% White (race)
72
68
44
60
67
74
% Black or
African American
(race)
13
27
52
32
23
17
94
-------
% Other (race)
15
5.3
4.0
8.1
9.5
8.3
% Hispanic
(ethnic origin)
18
4.3
13
14
14
9.1
Median
Household Income
(lk 2019$)
71
55
35
50
52
59
% Below Poverty
Line
7.3
9.1
16
13
12
9.5
% Below Half the
Poverty Line
5.8
7.2
9.0
6.8
6.1
5.5
Total Cancer Risk
(per million)
29
34
47
40
40
35
Total Respiratory
Risk (hazard
quotient)
0.37
0.47
0.57
0.50
0.49
0.44
Table 8-14: Community Profiles and AirToxScreen Risks for CALAMCO
- Stockton, CA
Overall
\ational
Average
Overall
State
Average
11 itliin 1
mile
"J
production
facility
11 itliin.?
miles
"J
production
facility
11 itliin 5
miles
"J
production
facility
11 it hi n lit
miles
"J
production
facility
% White (race)
72
60
58
54
52
51
% Black or
African American
(racej
13
5.8
9.5
9.9
10
9.4
% Other (race)
15
35
33
36
38
40
% Hispanic
(ethnic origin)
18
39
67
50
50
45
Median
Household Income
(lk 2019$)
71
83
49
55
55
62
% Below Poverty
Line
7.3
7.3
12
11
11
9.9
% Below Half the
Poverty Line
5.8
5.8
9.9
8.5
8
7
Total Cancer Risk
(per million)
29
31
30
30
30
30
Total Respiratory
Risk (hazard
quotient)
0.37
0.43
0.49
0.5
0.47
0.45
95
-------
Table 8-15: Community Profiles and AirToxScreen Risks for Diversified CPC International Inc.
- Channahon, IL
Overall
\alional
Average
Overall
Stale
Average
II iill in 1
mile
"./
production
facility
H illiin 3
miles
"J
production
facility
II illiin 5
miles
1
production
facility
11 illiin 10
miles
"J
production
facility
% White (race)
72
72
95
92
86
79
% Black or
African American
(race)
13
14
0.88
2
7.4
12
% Other (race)
15
14
4.2
6.3
6.4
9.6
% Hispanic
(ethnic origin)
18
17
10
13
16
19
Median
Household Income
(lk 2019$)
71
74
110
97
93
81
% Below Poverty
Line
7.3
6.6
1.0
3.1
3.1
4.7
% Below Half the
Poverty Line
5.8
5.6
2.6
1.5
2.6
3.7
Total Cancer Risk
(per million)
29
29
30
27
26
27
Total Respiratory
Risk (hazard
quotient)
0.37
0.38
0.30
0.31
0.32
0.34
Table 8-16: Community Profiles and AirToxScreen Risks for Aeropress, Inc. - Sibley, LA
Overall
\alional
Average
Overall
Stale
Average
H iIII in 1
mile
"J
production
facility
11 illiin 3
miles
"J
production
facility
11 illiin 5
miles
"J
production
facility
11 it hi n 10
miles
"J
production
facility
% White (race)
72
62
71
51
56
64
% Black or
African American
(race)
13
32
26
47
41
33
% Other (race)
15
5.8
2.7
1.3
2.5
2.5
% Hispanic
(ethnic origin)
18
5.1
1.6
1.8
1.1
1.7
Median
Household Income
(lk 2019$)
71
54
27
27
33
38
% Below Poverty
Line
7.3
10
11
18
20
18
% Below Half the
Poverty Line
5.8
8.3
9.8
8.3
7.5
7.7
Total Cancer Risk
(per million)
29
41
40
40
40
40
96
-------
Total Respiratory
Risk (hazard
quotient) 0.37 0.45 0.50 0.50 0.50 0.50
8.6 Conclusion
This proposed rule is expected to reduce GHG emissions, which would benefit populations that may be
especially vulnerable to damages associated with climate change. We also expect that the restriction on
use of certain HFCs will increase the production of HFC substitutes. How producers transition from high-
GWP HFCs could drive changes in potential risk for communities living near HFC and HFC substitute
production facilities due to the use of feedstock chemicals that could have local effects if released into the
environment. EPA finds evidence of environmental justice concerns near HFC production facilities from
cumulative exposure to existing environmental hazards in these communities, and that further
investigation is warranted. The proximity analysis of these communities demonstrates that:
• The characteristics of the communities near facilities are heterogeneous;
• Total baseline cancer risk and total respiratory risk from air toxics (not all of which stem
from HFC substitute production) varies, but is generally higher, and in some cases much
higher, within 1-3 miles of an HFC substitute production facility;
• In general, higher percentages of low income and people of color individuals live near
HFC substitute production facilities compared to the overall or rural average at the
national level;
• It is not clear the extent to which these baseline risks are directly related to HFC
substitute production, but some feedstocks and byproducts are toxic; and
• Since multiple HFC substitutes are available, some of which have toxic profiles for the
chemicals used as feedstocks in their production, continued analysis of HFC and HFC
substitute production facilities and associated environmental justice concerns is
appropriate.
Given the uncertainty about how the transition to lower-GWP substitutes and market trends independent
of this proposed rulemaking could affect production of predominant HFC substitutes at individual
facilities, and how those changes in production could affect associated air pollutant emissions,
particularly in communities that are disproportionately burdened by air pollution, EPA is seeking
information to help better characterize these changes and their implications for nearby communities for
analysis of the final rule.48 See the proposed rule for more information on the questions on which EPA is
48 Statements made in this chapter on the environmental justice concerns of the AIM Act draw support from the following
citations: Banzhaf, Spencer, Lala Ma, and Christopher Timmins. 2019. Environmental justice: The economics of race, place, and
97
-------
seeking input. The Agency will continue to evaluate the impacts of this program on communities with
environmental justice concerns and consider further action, as appropriate, to protect health in
communities affected by HFC substitute production.
pollution. Journal of Economic Perspectives; Hernandez-Cortes, D., and Meng, K.C., 2020. Do environmental markets cause
environmental injustice? Evidence from California's carbon market (No. w27205). NBER; Hu, L., Montzka, S.A., Miller, B.R.,
Andrews, A.E., Miller, J.B., Lehman, S.J., Sweeney, C., Miller, S.M., Thoning, K., Siso, C. and Atlas, E.L., 2016. Continued
emissions of carbon tetrachloride from the United States nearly two decades after its phaseout for dispersive uses. Proceedings of
the National Academy of Sciences; Mansur, E. and Sheriff, G., 2021. On the measurement of environmental inequality: Ranking
emissions distributions generated by different policy instruments.; U.S. EPA. 2011. Plan EJ 2014. Washington, DC: U.S. EPA,
Office of Environmental Justice.; U.S. EPA. 2015. Guidance on Considering Environmental Justice During the Development of
Regulatory Actions. May 2015.; USGCRP. 2016. The Impacts of Climate Change on Human Health in the United States: A
Scientific Assessment. U.S. Global Change Research Program, Washington, DC.
98
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Chapter 9: Annexes
Annex A: Summary of Mitigation Technologies Modeled by End Use
Table A-l Market Penetration in 2025, by transition technology, in Technology Transitions Base Case Compliance Scenario "•b¦c
Sector
Subset-tor
'/ in ii.\ it inn 1 ei ¦// nolog;i ¦
Market Penetration in 2(125
Aerosols
Non-MDI Aerosols
non-MDI Aerosols 11FC-152a lo Nol-in-Kind (NIK)
40%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato NIK
25%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato HFC-152a
13%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato HC
25%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-152ato HC
20'! i,
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato HFO-1234ze(E)
25%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-152ato HFO-1234ze(E)
14%
Foam
Commercial Refrigeration Foam
Rigid PU: Commercial Refrigeration (Commercial Refrigeration
Foam) - HFC-245fato HCFO-1233zd(E)
100%
Foam
Extruded Polystyrene (XPS):
Boardstock Foam
Polystyrene: Extruded Boardstock and Billet (XPS: Boardstock Foam)
- HFC-134a/C02 to HFO-1234ze(E)/HCFO-1233zd(E)
100%
Foam
Flexible Polyurethane (PU) Foam:
Integral Skin Foam
Integral Skin Polyurethane (Flexible PU Foam: Integral Skin Foam) -
HFC-134a to HCs
100%
Foam
PU and PIR Rigid: Boardstock
PU and PIR Rigid: Boardstock - HFC-245fa Blend to HC
100%
Foam
PU Rigid: Domestic Refrigerator and
Freezer Insulation
Rigid PU: Appliance (PU Rigid: Domestic Refrigerator and Freezer
Insulation) - HFC-245fato hydrocarbons (HCs)
50%
Foam
PU Rigid: Domestic Refrigerator and
Freezer Insulation
Rigid PU: Appliance (PU Rigid: Domestic Refrigerator and Freezer
Insulation) - HFC-245fato HCFO-1233zd(E)
50%
Foam
PU Rigid: One Component Foam
PU Rigid: One Component Foam - HFC-134ato HFO-1234ze(E)
100%
Foam
Foam
PU Rigid: Sandwich Panels:
Continuous and Discontinuous
PU Rigid: Sandwich Panels:
Continuous and Discontinuous
Rigid PU: Sandwich Panels (PU Rigid: Sandwich Panels: Continuous
and Discontinuous) - HFC-134ato HCs
Rigid PU: Sandwich Panels (PU Rigid: Sandwich Panels: Continuous
and Discontinuous) - HFC-245fa/C02 to HCFO-1233zd(E)
100%
100%
99
-------
Sector
Snb.\ector
ir an sit ion Technology
Market Penetration in 2025
Foam
PU Rigid: Spray Foam (High-
Pressure)
PU Rigid: Spray Foam (High-Pressure) - HFC-245fa and HFC-
245fa/C02 blend to HCFO- 1233zd(E)
70%
Foam
PU Rigid: Spray Foam (Low-
Pressure)
PU Rigid: Spray Foam (Low-Pressure) - HFC-245fa and HFC-
245fa/C02 to HFO-1234ze(E)
30%
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
CFC-114 Chillers - HFC-134ato R-450A/R-513A
o
o
©^
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
CFC-11 Centrifugal Chillers - HFC-134ato R-450A/R-513A
O
O
©^
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
CFC-12 Centrifugal Chillers - HFC-134ato R-450A/R-513A
O
O
V©
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
R-500 Chillers - HFC-134ato R-450A/R-513A
i o
©
1 xo
!
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
CFC-12 Centrifugal Chillers - HFC-245fato HCFO-1233zd(E)
100%
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
R-500 Chillers - HFC-245fato HCFO-1233zd(E)
O
O
©^
Refrigeration, A/C, & Heat
Pumps
Centrifugal Chillers
CFC-11 Centrifugal Chillers - HFC-245fato HCFO-1233zd(E)
O
O
V©
©^
Refrigeration, A/C, & Heat
Pumps
Cold Storage
CFC-12 Cold Storage - R-404A/R-507Ato NH3/C02
i ©
©
1 V©
! ©^
Refrigeration, A/C, & Heat
Pumps
Cold Storage
HCFC-22 Cold Storage - R-404A/R-507Ato NH3/C02
100%
Refrigeration, A/C, & Heat
Pumps
Cold Storage
R-502 Cold Storage - R-404A/R-507Ato NH3/C02
100%
Refrigeration, A/C, & Heat
Pumps
Dehumidifiers
HCFC-22 Dehumidifiers - R-410Ato HFC-32
O
O
^©
©^
Refrigeration, A/C, & Heat
Pumps
Ice Makers
CFC-12 Ice Makers - R-404A/HFC-134ato R-290
50%
Refrigeration, A/C, & Heat
Pumps
Ice Makers
CFC-12 Ice Makers - R-404Ato R-448A/R-449A
50%
Refrigeration, A/C, & Heat
Pumps
Industrial Process Refrigeration
CFC-11 Industrial Process Refrigeration - HFCsto NH3/C02
100%
Refrigeration, A/C, & Heat
Pumps
Industrial Process Refrigeration
CFC-12 Industrial Process Refrigeration - HFCs to NH3/C02
o
O
^©
©^
Refrigeration, A/C, & Heat
Pumps
Industrial Process Refrigeration
HCFC-22 Industrial Process Refrigeration - HFCs to NH3/C02
100%
Refrigeration, A/C, & Heat
Pumps
Large Commercial Unitary A/C
HCFC-22 Large Commercial Unitary A/C - R-410A to HFC-32 and
MCI IE
100%
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
CFC-12 Large Retail Food - R-407Ato C02 Transcritical
100%
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
R-502 Large Retail Food - R-407A to C02 Transcritical
100%
100
-------
Sector
Snb.\ector
ir an sit ion Technology
Market Penetration in 2025
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
CFC-12 Large Retail Food - R-404A/R-507A to C02 Transcritical
100%
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
R-502 Large Retail Food - R-404A/R-507Ato C02 Transcritical
100%
Refrigeration, A/C, & Heat
Pumps
Medium Retail Food (Large
Condensing Units)
HCFC-22 Large Condensing Units (Medium Retail Food) - R-
404A/R-507Ato C02
100%
Refrigeration, A/C, & Heat
Pumps
Medium Retail Food (Small
Condensing Units}
HCFC-22 Small Condensing Units (Medium Retail Food) - R-
404A/HFC-134ato C02
100%
Refrigeration, A/C, & Heat
Pumps
PD Chillers: Reciprocating
Reciprocating Chillers - R-410A/R-407C to HFO-1234ze(E)
100%
Refrigeration, A/C, & Heat
Pumps
PD Chillers: Screw
Screw Chillers - R-410A/R-407Cto HFO-1234ze(E)
o
o
V©
Refrigeration, A/C, & Heat
Pumps
PD Chillers: Scroll
Scroll Chillers - R-410A/R-407C to R-452B
i o
©
1 xo
!
Refrigeration, A/C, & Heat
Pumps
PTAC/PTHP
HCFC-22 PTAC/PTHP - R-410A to HFC-32/R-452B
! ©
©
1 n©
!
Refrigeration, A/C, & Heat
Pumps
Refrigerated Appliances
CFC-12 Refrigerated Appliances - HFC-134a to R-600a
O
O
©^
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport: Intermodal
Containers
Intermodal Containers - R-404A/HFC- 134a to R-450A/R-513A
O
O
V©
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport: Marine
Merchant Fishing Transport - R-404A/R-507Ato R-452A
o
o
©^
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport: Marine
: Reefer Ships - R-404A/R-507Ato R-452A
100%
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport: Road
Road Transport - R-404Ato R-452A
O
o
©^
Refrigeration, A/C, & Heat
Pumps
Residential Unitary A/C
HCFC-22 Residential Unitary A/C - R-410A to R-454B and MCHE
o
o
^©
©^
Refrigeration, A/C, & Heat
Pumps
Small Commercial Unitary A/C
HCFC-22 Small Commercial Unitary A/C - R-410Ato HFC-32 and
microchannel heat exchanger (MCHE_)
o
o
©^
Refrigeration, A/C, & Heat
Pumps
Small Retail Food
R-12 Small Retail Food (Low Temperature) - R-404Ato HCs
o
o
^©
©^
Refrigeration, A/C, & Heat
Pumps
Small Retail Food (Medium
Temperature)
R-12 Small Retail Food (Medium Temperature) - HFC-134a to HCs
i ©
©
1 V©
! ©^
Refrigeration, A/C, & Heat
Pumps
Vending Machines
CFC-12 Vending Machines - HFC-134ato R-290
O
o
^©
©^
Refrigeration, A/C, & Heat
Pumps
Water & Ground Source HP
HCFC-22 Water & Ground Source HP - R-410A to HFC-32/R-452B
o
o
©^
101
-------
Sector
Snhsector
Transition Technology
Market Penetration in 2025
Refrigeration, A/C, & Heat
Pumgs
Window Units
HCFC-22 Window Units - R-410A to HFC-32
100%
Solvents
Electronics Cleaning
Aerosol Solvent Electronics Cleaning - retrofitted Not-in-kind
Aqueous
3%
Solvents
Electronics Cleaning
Aerosol Solvent Electronics Cleaning - retrofitted Not-in-kind Semi-
aqueous
3%
Solvents
Precision Cleaning
Aerosol Solvent Precision Cleaning - retrofitted Not-in-kind Aqueous
3%
Solvents Precision Cleaning Aerosol Solvent Precision Cleaning - retrofitted Not-in-kind Semi- 3%
aqueous
a. 50% market penetration for icemakers is based on the assumption that half (in terms of amount of refrigerant) are self-contained units and the other half are
remote systems.
b. Market penetration for aerosols is given as the percent in the original chemical (i.e., HFC-134a or HFC-152a).
c. Market penetrations for HFC-134a do not reach 100% to account for a portion that is used in defense sprays and not subject to this rule.
Table A-2 Percent reduction off baseline
Percent Reduction off Baseline (i.e.. Technical
l://ectiveness) ("») Relative to ( onsmnption from Model
T'acility Type
Sector Snhsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Hjjiciency
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-152ato
NIK
100%
15%
15%
15%
15%
15%
15%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato
NIK
100%
13%
13%
13%
13%
13%
13%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato
HFC-152a
91%
6%
6%
6%
6%
6%
6%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134a to
HC
100%
13%
13%
13%
13%
13%
13%
102
-------
Per cent Reduction off liaselinc (i.e.. Technical
EJJectireness) ("») Relative to ( on.smnption from Model
i'ticilily Type
Sector Snbsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Efficiency
Aerosols
Non-MDI Aerosols
: non-MDI Aerosols HFC-152a to
: HC
95%
7%
7%
7%
7%
7%
7%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-134ato
HFO-1234ze(E)
100%
9%
13%
13%
13%
13%
13%
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-152ato
HFO-1234ze(E)
95%
5%
7%
7%
7%
7%
7%
Foam
Commercial
Refrigeration Foam
Rigid PU: Commercial Refrigeration
(Commercial Refrigeration Foam) -
HFC-245fato HCFO-1233zd(E)
99%
99%
99%
99%
99%
99%
99%
Foam
Flexible PU Foam:
Integral Skin Foam
Integral Skin Polyurethane (Flexible
PU Foam: Integral Skin Foam) -
HFC-134a to HCs
100%
100%
o
o
100%
100%
100%
100%
Foam
PU and PIR Rigid:
Boardstock
PU and PIR Rigid: Boardstock -
HFC-245fa Blend to HC
99%
100%
100%
100%
100%
100%
100%
Foam
PU Rigid: Domestic
Refrigerator and
Freezer Insulation
Rigid PU: Appliance (PU Rigid:
Domestic Refrigerator and Freezer
Insulation) - HFC-245fa to HCs
99%
0%
0%
0%
0%
0%
0%
Foam
PU Rigid: Domestic
Refrigerator and
Freezer Insulation
Rigid PU: Appliance (PU Rigid:
Domestic Refrigerator and Freezer
Insulation) - HFC-245fato HCFO-
1233zd(E)
99%
0%
0%
0%
0%
0%
0%
Foam
PU Rigid: One
Component Foam
PU Rigid: One Component Foam -
HFC-134ato HFO-1234ze(E)
100%
94%
94%
94%
94%
94%
94%
Foam
PU Rigid: Sandwich
Panels: Continuous
and Discontinuous
Rigid PU: Sandwich Panels (PU
Rigid: Sandwich Panels: Continuous
and Discontinuous) - HFC-134ato
I It's
100%
59%
59%
59%
59%
59%
59%
Foam
PU Rigid: Sandwich
Panels: Continuous
and Discontinuous
Rigid PU: Sandwich Panels (PU
Rigid: Sandwich Panels: Continuous
and Discontinuous) - HFC-
245fa/C02to HCFO-1233zd(E)
99%
41%
41%
41%
41%
41%
41%
103
-------
Per cent Reduction off liaselinc (i.e.. Technical
EJJectireness) ("») Relative to ( on.smnption from Model
i'ticilily Type
Sector Snbsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Efficiency
Foam
PL' Rigid: Spray Foam
PI' Rigid: Spray Foam (High-
Pressure) - HFC-245fa and HFC-
245fa/C02 blend to HCFO-
1233zd(E)
99" 0
69" 0
69" 0
69"..
69" 0
69" 0
69%
Foam
PU Rigid: Spray Foam
PU Rigid: Spray Foam (Low-
Pressure) - HFC-245fa and HFC-
245fa/CCh to HFO-1234ze(E)
99%
30%
30%
30%
30%
30%
30%
Foam
XPS: Boardstock
Foam
Polystyrene: Extruded Boardstock
and Billet (XPS: Boardstock Foam)
- HFC-134a/C02 to HFO-
1234ze(E)/HCFO- 1233zd(E)
100%
99%
99%
99%
99%
99%
99%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
CFC-114 Chillers - HFC-134ato R-
450A/R-513A
57%
0%
100%
100%
100%
57%
57%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
CFC-11 Centrifugal Chillers - HFC-
134ato R-450A/R-513A
57%
48%
55" 0
64%
67%
93%
45%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
CFC-12 Centrifugal Chillers - HFC-
ma to R-450A/R-513 A
57%
54%
61%
70%
77%
85%
74%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
R-500 Chillers - HFC-134a to R-
450A/R-513A
57%
54%
61%
71%
77%
85%
74%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
CFC-12 Centrifugal Chillers - HFC-
245fa to HCFO-1233zd(E)
99%
19%
20%
23%
24%
26%
15%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
R-500 Chillers - HFC-245fato
HCFO- 1233zd(E)
99%
19%
20%
23%
24%
26%
15%
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
CFC-11 Centrifugal Chillers - HFC-
245fa to HCFO-1233zd(E)
99%
31%
34%
38%
38%
45%
20%
Refrigeration, A/C, &
Heat Pumps
Cold Storage
CFC-12 Cold Storage - R-404A/R-
507A to NH5/CO2
100%
55%
81%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Cold Storage
HCFC-22 Cold Storage - R-404A/R-
507A to NH3/CO2
100%
54%
65%
87%
100%
100%
ox
O
O
Refrigeration, A/C, &
Heat Pumps
Cold Storage
R-502 Cold Storage - R-404A/R-
507A to NH3/CO2
100%
49%
69%
88%
100%
100%
100%
104
-------
Per cent Reduction off liaselinc (i.e.. Technical
EJJectireness) ("») Relative to ( on.smnption from Model
i'ticilily Type
Sector Snbsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Efficiency
Refrigeration, A/C, &
Heat Pumps
Dehumidifiers
: HCFC-22 Dehumidifiers - R-410A
to HFC-32
68%
98%
100%
90%
55%
55%
55%
Refrigeration, A/C, &
Heat Pumps
Ice Makers
CFC-12 Ice Makers - R-404A/HFC-
134a to R-290
100%
67%
76%
50%
50%
50%
50%
Refrigeration, A/C, &
Heat Pumps
Ice Makers
CFC-12 Ice Makers - R-404A to R-
448A/R-449A
58%
39%
44%
29%
29%
29%
29%
Refrigeration, A/C, &
Heat Pumps
Industrial Process
Refrigeration
CFC-11 Industrial Process
Refrigeration - HFCs to NH3/CO2
100%
74%
91%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Industrial Process
Refrigeration
CFC-12 Industrial Process
Refrigeration - HFCs to NH3/CO2
100%
87%
100%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Industrial Process
Refrigeration
HCFC-22 Industrial Process
Refrigeration - HFCs to NH3/CO2
100%
58%
68%
93%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Large Commercial
Unitary A/C
HCFC-22 Large Commercial
Unitary A/C - R-410A to HFC-32
and MCHE
68%
51%
76%
97%
80%
80%
80%
Refrigeration, A/C, &
Heat Pumps
Large Retail Food
CFC-12 Large Retail Food - R-
407Ato CO2 Transcritical
100%
19%
42%
57%
59%
61%
61%
Refrigeration, A/C, &
Heat Pumps
Large Retail Food
R-502 Large Retail Food - R-407A
to CO2 Transcritical
100%
19%
42%
57%
59%
61%
61%
Refrigeration, A/C, &
Heat Pumps
Large Retail Food
CFC-12 Large Retail Food - R-
404A/R-507A to CO2 Transcritical
100%
16%
30%
35" 0
41%
39%
39%
Refrigeration, A/C, &
Heat Pumps
Large Retail Food
R-502 Large Retail Food - R-
404A/R-507A to CO2 Transcritical
100%
16%
30%
35%
41%
39%
39%
Refrigeration, A/C, &
Heat Pumps
Medium Retail Food
HCFC-22 Large Condensing Units
(Medium Retail Food) - R-404A/R-
507Ato CO2
100%
49%
76%
97%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Medium Retail Food
HCFC-22 Small Condensing Units
(Medium Retail Food) - R-
404A/HFC-134ato CO2
100%
54%
78%
93%
95%
80%
80%
105
-------
Per cent Reduction off liaselinc (i.e.. Technical
EJJectireness) ("») Relative to ( on.smnption from Model
i'ticilily Type
Sector Snbsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Efficiency
Refrigeration, A/C, &
Heat Pumps
PD Chillers
Screw Chillers - R-410A/R-407C to
HFO-1234ze(E)
100%
92%
100%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
PD Chillers
Reciprocating Chillers - R-410A/R-
407CtoHFO-1234ze(E)
100%
87%
100%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
PD Chillers
Scroll Chillers - R-410A/R-407C to
R-452B
64%
62%
100%
100%
100%
63%
63%
Refrigeration, A/C, &
Heat Pumps
PTAC/PTHP
HCFC-22 PTAC/PTHP - R-410Ato
HFC-32/R-452B
67%
72%
85%
99%
67%
67%
67%
Refrigeration, A/C, &
Heat Pumps
Refrigerated
Appliances
CFC-12 Refrigerated Appliances -
HFC-134a to R-600a
100%
100%
100%
100%
100%
100%
100%
Refrigeration, A/C, &
Heat Pumps
Residential Unitary
A/C
HCFC-22 Residential Unitary A/C -
R-410Ato R-454B and MCHE
78%
51%
75%
98%
86%
86%
86%
Refrigeration, A/C, &
Heat Pumps
Small Commercial
Unitary A/C
HCFC-22 Small Commercial
Unitary A/C - R-410Ato HFC-32
and MCHE
68%
49%
71%
92%
80%
80%
80%
Refrigeration, A/C, &
Heat Pumps
Small Retail Food
R-12 Small Retail Food (Low
Temperature) - R-404A to HCs
100%
57%
43%
33%
33%
33%
33%
Refrigeration, A/C, &
Heat Pumps
Small Retail Food
R-12 Small Retail Food (Medium
Temperature) - HFC-134ato HCs
100%
100%
100%
67%
67%
67%
67%
Refrigeration, A/C, &
Heat Pumps
Transport
Intermodal Containers — R-
404A/HFC-134a to R-450A/R-513A
77%
2%
4%
6%
5%
5° o
5%
Refrigeration, A/C, &
Heat Pumps
Transport
Merchant Fishing Transport - R-
404A/R-507A to R-452A
46%
7%
14%
20%
26%
32%
34%
Refrigeration, A/C, &
Heat Pumps
Transport
Reefer Ships - R-404A/R-507Ato
R-452A
31%
8%
13%
19%
25%
30%
30%
Refrigeration, A/C, &
Heat Pumps
Transport
Road Transport - R-404A to R-452A
20%
13%
30%
45%
42%
42%
42%
106
-------
Per cent Reduction off liaselinc (i.e.. Technical
EJJectireness) ("») Relative to ( on.smnption from Model
i'ticilily Type
Sector Snbsector Transition Technology Reduction 2025 2030 2035 20-10 20-15 2050
Efficiency
Refrigeration, A/C, & Vending Machines : CFC-12 Vending Machines - HFC- 100% 100% 100% 99% 99% 99% 99%
Heat Pumps 134ato R-290
Refrigeration, A/C, & Water & Ground HCFC-22 Water & Ground Source 67% 42% 61% 74% 84% 63% 63%
Heat Pumps Source HP HP - R-410A to HFC-32/R-452B
Refrigeration, A/C, &
Heat Pumps
Window Units
HCFC-22 Window Units - R-410A
to HFC-32
96% 100% 100%
Solvents
Electronics Cleaning
Aerosol Solvent Electronics
Cleaning - retrofitted Not-in-kind
Aqueous
100% 3% 3% 3% 3% 3% 3%
Solvents
Electronics Cleaning
Aerosol Solvent Electronics
Cleaning - retrofitted Not-in-kind
Semi-aqueous
100% 3% 3% 3% 3% 3% 3%
Solvents
Precision Cleaning
Aerosol Solvent Precision Cleaning -
retrofitted Not-in-kind Aqueous
100% 3%
3% 3% 3% 3% 3%
Solvents
Precision Cleaning
Aerosol Solvent Precision Cleaning -
retrofitted Not-in-kind Semi-aqueous
100% 3% 3% 3% 3% 3% 3%
107
-------
Table A-3 - Transitions Modeled in Allocation Rule Reference Case and Technology Transitions Compliance Case
Sector
Snhsector
litiiisilioiis in Allocution link• Kejerence ( use
I'runsilions Modeled in Technology liuiisilions
Utile liuse ( use
• non-MDI Aerosols HFC-152a to NIK
• non-MDI Aerosols HFC-152a to NIK
• non-MDI Aerosols HFC-134a to NIK
• non-MDI Aerosols HFC-134a to NIK
• non-MDI Aerosols HFC-134a to HFC-152a
• non-MDI Aerosols HFC-134a to HFC-152a
Aerosols
Non-Metered Dose
Inhaler Aerosols
• non-MDI Aerosols HFC-134a to HC
• non-MDI Aerosols HFC-152a to HC
• non-MDI Aerosols HFC-134ato HFO-1234ze
• non-MDI Aerosols HFC-152a to HFO-1234ze
• non-MDI Aerosols HFC-134a to HC
• non-MDI Aerosols HFC-152a to HC
• non-MDI Aerosols HFC-134a to HFO-1234ze
• non-MDI Aerosols HFC-152a to HFO-1234ze
• Flooding Agents - Inert Gas
Fire
Flooding Agents
• Flooding Agents - Water Mist
• Flooding Agents - Fluoroketone (FK) 5-1-12
not modeled in base case
Foam Blowing
Commercial
Refrigeration Foam
• Rigid PU: Commercial Refrigeration (Commercial
Refrigeration Foam) - HFC-245fa to HCFO-1233zd(E)
• Rigid PU: Commercial Refrigeration (Commercial
Refrigeration Foam) - HFC-245fa to HCFO-1233zd(E)
Foam Blowing
Flexible Polyurethane
(PU) Foam: Integral Skin
Foam
• Integral Skin Polyurethane (Flexible PU Foam:
Integral Skin Foam) - HFC-134a to HCs
• Integral Skin Polyurethane (Flexible PU Foam:
Integral Skin Foam) - HFC-134a to HCs
Foam Blowing
PU and
Polyisocyanurate (PIR)
Rigid: Boardstock
• PU and PIR Rigid: Boardstock- HFC-245fa Blend to
HC
• PU and PIR Rigid: Boardstock - HFC-245fa Blend to
HC
• Rigid PU: Appliance (PU Rigid: Domestic Refrigerator
and Freezer Insulation) - HFC-245fa to HCs
• Rigid PU: Appliance (PU Rigid: Domestic Refrigerator
and Freezer Insulation) - HFC-245fa to HCs
Foam Blowing
PU Rigid: Domestic
Refrigerator and
Freezer Insulation
• Rigid PU: Appliance (PU Rigid: Domestic Refrigerator
and Freezer Insulation) - HFC-245fa to HCFO-
1233zd(E)
• Rigid PU: Appliance (PU Rigid: Domestic Refrigerator
and Freezer Insulation) - HFC-245fa to HCFO-
1233zd(E)
Foam Blowing
PU Rigid: One
Component Foam
• PU Rigid: One Component Foam - HFC-134a to HFO-
1234ze(E)
• PU Rigid: One Component Foam - HFC-134a to HFO-
1234ze(E)
Foam Blowing
PU Rigid: Sandwich
Panels: Continuous and
Discontinuous
• Rigid PU: Sandwich Panels (PU Rigid: Sandwich
Panels: Continuous and Discontinuous) - HFC-134a to
HCs
• Rigid PU: Sandwich Panels (PU Rigid: Sandwich
Panels: Continuous and Discontinuous) - HFC-134a to
HCs
108
-------
Sector
Snhseclor
litiiisilioiis in Allocution link• Kejerence ( use
irunsitions Modeled in Technology Irunsitions
linle liuse ( use
• Rigid PU: Sandwich Panels (PU Rigid: Sandwich
Panels: Continuous and Discontinuous) - HFC-
245fa/C02 to HCFO-1233zd(E)
• Rigid PU: Sandwich Panels (PU Rigid: Sandwich
Panels: Continuous and Discontinuous) - HFC-
245fa/C02 to HCFO-1233zd(E)
Foam Blowing
PU Rigid: Spray Foam
• PU Rigid: Spray Foam (High-Pressure) - HFC-245fa
and HFC-245fa/C02 blend to HCFO-1233zd(E)
• PU Rigid: Spray Foam (Low-Pressure) - HFC-245fa
and HFC-245fa/C02 to HFO-1234ze(E)
• PU Rigid: Spray Foam (High-Pressure) - HFC-245fa
and HFC-245fa/C02 blend to HCFO-1233zd(E)
• PU Rigid: Spray Foam (Low-Pressure) - HFC-245fa
and HFC-245fa/C02 to HFO-1234ze(E)
Foam Blowing
Extruded Polystyrene
(XPS): Boardstock Foam
• Polystyrene: Extruded Boardstock and Billet (XPS:
Boardstock Foam) - HFC-134a/C02 to HFO-
1234ze(E)/HCFO-1233zd(E)
• Polystyrene: Extruded Boardstock and Billet (XPS:
Boardstock Foam) - HFC-134a/C02 to HFO-
1234ze(E)/1233zd(E)
• CFC-114 Chillers - HFC-134a to R-450A/R-513A
• CFC-114 Chillers - HFC-134a to R-450A/R-513A
• CFC-11 Centrifugal Chillers - HFC-134a to R-450A/R-
513A
• CFC-11 Centrifugal Chillers - HFC-134a to R-450A/R-
513A
• CFC-12 Centrifugal Chillers - HFC-134a to R-450A/R-
513A
• CFC-12 Centrifugal Chillers - HFC-134a to R-450A/R-
513A
Refrigeration, A/C, &
Heat Pumps
Centrifugal Chillers
• R-500 Chillers - HFC-134a to R-450A/R-513A
• CFC-12 Centrifugal Chillers - HFC-245fa to HCFO-
1233zd(E)
• R-500 Chillers - HFC-245fa to HCFO-1233zd(E)
• CFC-11 Centrifugal Chillers - HFC-245fa to HCFO-
1233zd(E)
• R-500 Chillers - HFC-134a to R-450A/R-513A
• CFC-12 Centrifugal Chillers - HFC-245fa to HCFO-
1233zd(E)
• R-500 Chillers - HFC-245fa to HCFO-1233zd(E)
• CFC-11 Centrifugal Chillers - HFC-245fa to HCFO-
1233zd(E)
• Commercial Unitary A/C - R-410A to HFC-32 and
MCHE
• HCFC-22 Small Commercial Unitary A/C - R-410A to
HFC-32 and MCHE
Refrigeration, A/C, &
Heat Pumps
Commercial Unitary
• Commercial Unitary A/C - R-410A to R-410A and
MCHE
• Commercial Unitary A/C - R-410A to HFC-32
• HCFC-22 Large Commercial Unitary A/C - R-410A to
HFC-32 and MCHE
Refrigeration, A/C, &
Heat Pumps
Disposal
• Recovery at Disposal for ALL Equipment
not modeled in base case
Heat Pumps (HP)
• HP - R-410A to HFC-32/R-452B
• HCFC-22 PTAC/PTHP - R-410A to HFC-32/R-452B
109
-------
Sector
Snhseclor
litiiisilioiis in Allocution link• Kejerence ( use
irunsitions Modeled in Technology Irunsitions
linle liuse ( use
Refrigeration, A/C, &
Heat Pumps
• HCFC-22 Water & Ground Source HP - R-410A to
HFC-32/R-452B
Refrigeration, A/C, &
Heat Pumps
Ice Makers
• Ice Makers - R-404A/HFC-134a to R-290
• CFC-12 Ice Makers - R-404A/HFC-134a to R-290
• CFC-12 Ice Makers - R-404A to R-448A/R-449A
Refrigeration, A/C, &
Heat Pumps
Industrial Process
Refrigeration (IPR), Cold
Storage (CS)
• IPR and Cold Storage - HFCs to NH3/C02
• IPR and Cold Storage - HFCs to NH3/CO2
• Large Retail Food - R-404A/R-507A to Direct
• CFC-12 Large Retail Food - R-407A to C02
Expansion (DX) R-407A/R-407F
Transcritical
• Large Retail Food - R-404A/R-507A to C02
• R-502 Large Retail Food - R-407A to C02 Transcritical
Refrigeration, A/C, &
Heat Pumps
Large Retail Food
Transcritical
• Large Retail Food - R-404A/R-507A to R-407A/R-
407F Secondary Loop Systems (SLS)
• CFC-12 Large Retail Food - R-404A/R-507A to C02
Transcritical
• R-502 Large Retail Food - R-404A/R-507A to C02
Transcritical
Refrigeration, A/C, &
Heat Pumps
Leak Repair
• Leak Repair for Large Equipment
not modeled in base case
• Medium Retail Food - R-404A/R-507A/HFC-134a to
• HCFC-22 Large Condensing Units (Medium Retail
Refrigeration, A/C, &
Heat Pumps
Medium Retail Food
C02
• Medium Retail Food - R-404A/R-507A/HFC-134a to
DX R-407A/R-407F
Food) - R-404A/R-507A to C02
• HCFC-22 Small Condensing Units (Medium Retail
Food) - R-404A/HFC-134a to C02
• Screw Chillers - R-410A/R-407C to HFO-1234ze(E)
• Screw Chillers - R-410A/R-407C to HFO-1234ze(E)
Refrigeration, A/C, &
Heat Pumps
Positive Displacement
Chillers
• Reciprocating Chillers - R-410A/R-407C to HFO-
1234ze(E)
• Scroll Chillers - R-410A/R-407C to R-452B
• Reciprocating Chillers - R-410A/R-407C to HFO-
1234ze(E)
• Scroll Chillers - R-410A/R-407C to R-452B
Refrigeration, A/C, &
Heat Pumps
Refrigerated Appliances
• CFC-12 Refrigerated Appliances - HFC-134a to R-
600a
• CFC-12 Refrigerated Appliances - HFC-134a to R-
600a
Refrigeration, A/C, &
Heat Pumps
Residential Unitary
• Residential Unitary A/C - R-410A to R-454B and
MCHE
• HCFC-22 Residential Unitary A/C - R-410A to R-454B
and MCHE
Refrigeration, A/C, &
Heat Pumps
Service
• Recovery at Service for Small Equipment
not modeled in base case
110
-------
Sector
Snhseclor
litiiisilioiis in Allocution link• Kejerence ( use
irunsitions Modeled in Technology Irunsitions
linle liuse ( use
• R-12 Small Retail Food (Low Temperature) - R-404A
• R-12 Small Retail Food (Low Temperature) - R-404A
to HCs
to HCs
• R-12 Small Retail Food (Low Temperature) - R-404A
• R-12 Small Retail Food (Medium Temperature) -
Refrigeration, A/C, &
Heat Pumps
Small Retail Food
to R-448A/R-449A
• R-12 Small Retail Food (Low Temperature) - R-404A
to R-450A/R-513A
• R-12 Small Retail Food (Medium Temperature) -
HFC-134a to R-448A/R-449A
HFC-134a to HCs
• Transport - R-404A to R-452A
• Intermodal Containers - R-404A/HFC-134a to R-
450A/R-513A
Refrigeration, A/C, &
Heat Pumps
Transport
• Merchant Fishing Transport - R-404A/R-507A to R-
452A
• Reefer Ships - R-404A/R-507A to R-452A
• Road Transport - R-404A to R-452A
Refrigeration, A/C, &
Heat Pumps
Vending Machines
• Vending Machines - HFC-134a to R-450A/R-513A
• Vending Machines - HFC-134a to R-290
• CFC-12 Vending Machines - HFC-134a to R-290
Refrigeration, A/C, &
Heat Pumps
Window AC,
Dehumidifiers
• Window AC, Dehumidifiers - R-410A to HFC-32
• HCFC-22 Dehumidifiers - R-410A to HFC-32
• HCFC-22 Window Units - R-410A to HFC-32
• Precision Cleaning applications - retrofitted HFC to
• Aerosol Solvent Electronics Cleaning - retrofitted
Hydrofluoroether (HFE)
Not-in-kind Aqueous
• Electronic Cleaning applications - retrofitted HFC to
• Aerosol Solvent Electronics Cleaning - retrofitted
HFE
Not-in-kind Semi-aqueous
Solvents
Electronics Cleaning
• Electronic Cleaning applications - retrofitted Not-in-
kind Aqueous
• Electronic Cleaning applications - retrofitted Not-in-
kind Semi-aqueous
• Aerosol Solvent Precision Cleaning - retrofitted Not-
in-kind Aqueous
• Aerosol Solvent Precision Cleaning - retrofitted Not-
in-kind Semi-aqueous
Ill
-------
Table A-4 Incremental Costs and Abatement by Subsector for Technology Transitions base case relative to Allocation Rule Reference
Case
Snb.secfor
Incremental ¦ 1 luilemenl
(MM II.1 e)
21125
2030
Increinenlul ( osls (S millions)
2025 2030
Chillers
0.71
9.18
$64.45
$398.31
Commercial Refrigeration Foam
0
0
$-
$-
Commercial Unitary
1.85
0.41
($11.33) i
($6.25)
Disposal
-20.76
-22.08
($298.30)
($317.15)
Electronics Cleaning
-0.56
-0.65
($2.75) !
$3.50
Flexible PU Foam: Integral Skin Foam
0
0
$-
$-
Flooding Agents
-1.3
-1.96
($0.42) I
$2.37
Heat Pumps
0.72
0.24
$3.64
$1.19
Ice Makers
1.21
0.81
($1.70) I
($2.72)
IPR/Cold Storage
0
0
$-
$-
Large Retail Food
11.3
22.24
($200.97) !
($395.31)
Leak Reduction
-4.49
-4.08
$6.70
$6.09
Medium Retail Food
0.09 |
1.19
($10.49) r
($18.19)
Non-MDI Aerosols
0.4
0.65
$44.54 |
$72.47
I'D Chillers
0
7.54
$-
$117.26
Precision Cleaning
-0.48
-0.64
$4.15 ,
$4.59
PU and PIR Rigid: Boardstock
0
0
$-
$-
PU Rigid: Domestic Refrigerator and Freezer Insulation
0
0
$-
$-
PU Rigid: One Component Foam
0
0
$-
$-
PU Rigid: Sandwich Panels: Continuous and Discontinuous
0
0
$-
$-
PU Rigid: Spray Foam
0
0
$-
$-
Refrigerated Appliances
0
0
$-
$-
112
-------
Snb.\ector
Increment u!. 1 luilement
(MMTI.1 e)
21125
20.W
Incremental ( o.\f\ (S millions)
2025 2i)M)
Residential Unitary
13.61
2.4
$76.66
$13.50
Service
-7.35
0
($171.18)
$-
Small Retail Food
0.16
0.32
($2.80) |
($2.59)
Transport
0.81
2.08
$17.83 |
$45.80
Vending Machines
0
0
$0.00 !
$0.00
Window ACs & DehumidifiersWindow Dehumids
5.88
4.41
($5.30)
($3.97)
XPS: BoardstockFoam I 6.99 i 2.42 j $57.64) $19.97
113
-------
Table AS Summary of Costs and Revenue of Transition Technologies
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
134a to HC
$325,000
$2,551,500
$0
807,124.5
($3.10)
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
134a to HFC-152a
$500,000
$2,551,500
$0
740,502.0
($3.34)
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
134a to HFO-1234ze(f)
$500,000
$0
$4,252,500
807,408.0
$5.37
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
134a to NIK
$250,000
$4,536,000
$500,000
810,810.0
($4.93)
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
152a to HC
$325,000
$0
$0
66,622.5
$0.79
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
152a to HFO-1234ze(f)
$500,000
$0
$6,804,000
66,906.0
$102.90
Aerosols
Non-MDI Aerosols
non-MDI Aerosols HFC-
152a to NIK
$250,000
$1,984,500
$500,000
70,308.0
($20.54)
Foam
Commercial Refrigeration Foam
Rigid PU: Commercial
Refrigeration (Commercial
Refrigeration Foam) - HFC-
245fa to HCFO-1233zd(£)
$0
$0
$280,000
71,610.0
$3.91
Foam
Flexible PU Foam: Integral Skin Foam
Integral Skin Polyurethane
(Flexible PU Foam: Integral
Skin Foam) - HFC-134a to
HCs
$405,000
$135,000
$0
42,705.0
($2.13)
114
-------
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
Foam
PU and PIR Rigid; Boardstock
PU and PIR Rigid:
Boardstock - HFC-245fa
Blend to HC
$695,500
$520,000
$0
66,527.5
($6.68)
Foam
PU Rigid: Domestic Refrigerator and Freezer
Insulation
Rigid PU: Appliance (PU
Rigid: Domestic
Refrigerator and Freezer
Insulation) - HFC-245fa to
HCFO-1233zd(F)
$0
$0
$2,147,162
549,136.6
$3.91
Foam
PU Rigid: Domestic Refrigerator and Freezer
Insulation
Rigid PU: Appliance (PU
Rigid: Domestic
Refrigerator and Freezer
Insulation) - HFC-245fa to
HCs
$5,610,000
$4,351,836
$0
549,405.0
($6.81)
Foam
PU Rigid: One Component Foam
PU Rigid: One Component
Foam - HFC-134a to HFO-
1234ze(F)
$399,000
$0
$1,320,480
185,780.7
$7.34
Foam
PU Rigid: Sandwich Panels: Continuous &
Discontinuous
Rigid PU: Sandwich Panels
(PU Rigid: Sandwich
Panels: Continuous &
Discontinuous) - HFC-134a
to HCs
$201,500
$2,038,500
$2,490,000
644,845.5
$0.73
Foam
PU Rigid: Sandwich Panels: Continuous &
Discontinuous
Rigid PU: Sandwich Panels
(PU Rigid: Sandwich
Panels: Continuous &
Discontinuous) - HFC-
245fa/C02 to HCFO-
1233zd(F)
$0
$0
$1,812,000
463,419.0
$3.91
Foam
PU Rigid: Spray Foam
PU Rigid: Spray Foam
(High-Pressure) — HFC-
$250,000
$0
$230,124
58,854.2
$4.37
115
-------
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
245fa and HFC-245fa/C02
blend to HCFO-1233zd(£)
Foam
PU Rigid: Spray Foam
PU Rigid: Spray Foam (Low-
Pressure) - HFC-245fa and
HFC-245fa/C02 to HFO-
1234ze(f)
$550,000
$0
$230,124
58,911.7
$4.92
Foam
XPS: Boardstock Foam
Polystyrene: Extruded
Boardstock and Billet (XPS:
Boardstock Foam) - HFC-
134a/C02to HFO-
1234ze(£j/HCFO-1233zd(£)
$19,300,000
$0
$5,529,000
1,003, 852.2
$7.59
Refrigeration, A/C, & Heat
Pumps
Chillers
CFC-11 Centrifugal Chillers
— HFC-134a to R-450A/R-
513A
$12,695
$0
$762
74.2
$28.84
Refrigeration, A/C, &
Heat Pumps
Chillers
CFC-11 Centrifugal Chillers
- HFC-245fa to HCFO-
1233zd(£)
$53,800
$0
$168
71.8
$83.62
Refrigeration, A/C, & Heat
Pumps
Chillers
CFC-114 Chillers-HFC-
134a to R-450A/R-513A
$16,793
$0
$1,008
111.3
$26.53
Refrigeration, A/C, & Heat
Pumps
Chillers
CFC-12 Centrifugal Chillers
- HFC-134a to R-450A/R-
513A
$13,057
$0
$783
73.2
$29.70
Refrigeration, A/C, & Heat
Pumps
Chillers
CFC-12 Centrifugal Chillers
— HFC-245fa to HCFO-
1233zd(f)
$53,880
$0
$173
71.7
$82.51
Refrigeration, A/C, & Heat
Pumps
Chillers
R-500 Chillers - HFC-134a
to R-450A/R-513A
$13,057
$0
$783
73.2
$29.70
116
-------
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
Refrigeration, A/C, & Heat
Pumps
Chillers
R-500 Chillers - HFC-245fa
to HCFO-1233zd(f)
$53,880
$0
$173
71.7
$82.51
Refrigeration, A/C, & Heat
Pumps
Commercial Unitary AC
Commercial Unitary A/C -
R-410A to HFC-32
($46)
$4
$0
2.1
($4.72)
Refrigeration, A/C, & Heat
Pumps
Heat Pumps
Heat Pumps - R-410Ato
HFC-32/R-452B
$4
$0
$1
0.3
$4.64
Refrigeration, A/C, & Heat
Pumps
Ice Makers (seld-contained)
Ice Makers - R-404A/HFC-
134a to R-290
$107,125
$9,587
$0
14,213.1
$0.73
Refrigeration, A/C, & Heat
Pumps
Ice Makers (remote)
Ice Makers - R-404Ato R-
448A/R-449A
($190,985)
$8,403
$0
12,656.8
($3.47)
Refrigeration, A/C, & Heat
Pumps
Industrial Process
IPR-HFCs to NH3/CO2
$193,000
$50,180
$0
711.6
($41.09)
Refrigeration, A/C, & Heat
Pumps
Cold Storage
Cold Storage - HFCs to
nh3/co2
$193,000
$50,180
$0
711.6
($41.09)
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
Large Retail Food - R-
404A/R-507A to C02
Transcritical
$19,610
$13,445
$0
1,096.4
($10.11)
Refrigeration, A/C, & Heat
Pumps
Large Retail Food
Large Retail Food - R-407A
to C02 Transcritical
$19,610
$13,445
$0
1,096.4
($10.11)
Refrigeration, A/C, & Heat
Pumps
Medium Retail Food
Medium Retail Food - R-
404A/R-507A to C02
($108)
$13
$0
8.1
($3.16)
Refrigeration, A/C, & Heat
Pumps
PD Chillers
Reciprocating Chillers —R-
410A/R-407C to HFO-
1234ze(F)
$2,048
$0
$123
66.8
$5.39
Refrigeration, A/C, & Heat
Pumps
PD Chillers
Screw Chillers - R-410A/R-
407Cto HFO-1234ze(£)
$1,950
$0
$117
63.6
$5.39
117
-------
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
Refrigeration, A/C, & Heat
Pumps
PD Chillers
Scroll Chillers - R-410A/R-
407C to R-452B
$3,334
$0
$200
40.9
$14.33
Refrigeration, A/C, & Heat
Pumps
Refrigerated Appliances
CFC-12 Refrigerated
Appliances -HFC-134a to
R-600a
($201,075)
$3,156
$0
8,798.0
($3.43)
Refrigeration, A/C, & Heat
Pumps
Residential Unitary AC
Residential Unitary A/C —
R-410A to R-454B
$28
$0
$2
1.2
$5.18
Refrigeration, A/C, & Heat
Pumps
Small Retail Food
R-12 Small Retail Food
(Low Temperature) - HCs
($4)
$0.3
$0
0.1
($6.54)
Refrigeration, A/C, & Heat
Pumps
Small Retail Food
R-12 Small Retail Food
(Medium Temperature) -
R-404A to HCs
($2)
$0.2
$0
0.1
($4.22)
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport—Road
Road Refrigerated
Transport - R-404A to R-
452A
$86
$0
$28
2.0
$20.44
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport—Intermodal Containers
Intermodal Containers - R-
404A/HFC-134a to R-
450A/R-513A
$88
$0
$29
4.5
$9.29
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport—Marine
Merchant Fishing
Refrigerated Transport - R-
404A/R-507A to R-452A
$6,426
$0
$643
130.7
$10.25
Refrigeration, A/C, & Heat
Pumps
Refrigerated Transport—Marine
Reefer Ships Refrigerated
Transport - R-404A/R-507A
to R-452A
$42,775
$0
$4,278
543.3
$16.41
Refrigeration, A/C, & Heat
Pumps
Vending Machines
Vending Machines - HFC-
134a to R-290
$305,950
$191
$0
554.0
$88.76
118
-------
Sector
Subsector
Abatement Option
Capital
Cost
(2015
USD)
Annual
Revenue
(2015
USD)
Annual
O&M
Costs
(2015
USD)
Abatement
Amount
(mtC02e)
Break-
even
Cost
(2015
USD/
mtC02e)
Refrigeration, A/C, & Heat
Pumps
Residential AC
Window AC - R-410A to
HFC-32
($0.5)
$0
$0
0.1
($0.83)
Refrigeration, A/C, & Heat
Pumps
Residential Dehumidifiers
Residential Dehumidifiers -
R-410A to HFC-32
($0.5)
$0,003
$0
0.1
($0.83)
Aerosol Solvents
Electronics Cleaning
Electronic Cleaning
applications - retrofitted
Not-in-kind Aqueous
$50,000
$1,000
$700
186.0
$33.33
Aerosol Solvents
Electronics Cleaning
Electronic Cleaning
applications - retrofitted
Not-in-kind Semi-aqueous
$55,000
$0
$5,900
186.0
$70.16
Aerosol Solvents
Precision Cleaning
Electronic Cleaning
applications - retrofitted
Not-in-kind Aqueous
$50,000
$1,000
$700
186.0
$33.33
Aerosol Solvents
Precision Cleaning
Electronic Cleaning
applications - retrofitted
Not-in-kind Semi-aqueous
$55,000
$0
$5,900
186.0
$70.16
119
-------
Annex B: Annual Emission Reductions by Gas
Tables B-l through B-10 provide the emission reductions by year for the ten HFCs that are addressed by
either the proposed Technology Transitions Rule or in the Allocation Rule Reference Case.
Table B-l - HFC-32 Emission Reductions by Year from the Technology Transitions Rule and the
Allocation Rule Reference Case
Year
iccliiwluxy Transitions liasc
( use ///¦'( -.->J amission
lii'tlmiions (MMII.'I c)
Mlocdlion liulc licjcrcncc ( use
///¦'( -32 Emission lii'tlmiions
(MM II.1 c)
DiJJcrcmv (MMTill c)
2022
0.027064
0.149306
-0.12224
2023
0.089718
0.248403
-0.15869
2024
0.225457
5.476462
-5.25101
2025
0.433194
7.098892
-6.6657
2026
0.642552
6.763833
-6.12128
2027
0.852574
7.43397
-6.5814
2028
1.063068
7.287905
-6.22484
2029
1.274131
4.784301
-3.51017
2030
1.486678
5.012834
-3.52616
2031
1.689036
5.207339
-3.5183
2032
1.855508
5.313906
-3.4584
2033
2.022838
5.384956
-3.36212
2034
2.198541
5.383358
-3.18482
2035
2.374942
5.4303
-3.05536
2036
2.474194
27.40027
-24.9261
2037
1.970909
12.48527
-10.5144
2038
2.317256
11.18038
-8.86312
2039
2.624145
11.61263
-8.98849
2040
2.845912
13.89957
-11.0537
2041
2.918619
22.03156
-19.1129
2042
2.997757
18.70938
-15.7116
2043
3.073831
15.57646
-12.5026
2044
3.142134
12.60967
-9.46753
2045
3.173567
9.817435
-6.64387
2046
3.228789
9.913521
-6.68473
2047
3.279759
10.0071
-6.72734
2048
3.32603
10.09812
-6.77209
2049
3.367459
10.18649
-6.81903
2050 3.403709 10.27232 -6.86861
120
-------
Table B-2 - HFC-125 Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Year
Technology Transitions liase
( u.\f ///'( -125 Umissiun
Red net ions (M Ml 1 e)
Allocation Utile Reference ( use
///¦'( -125 Umission licilnclions
(MMTL1 c)
Di/Jcrcncc
2022
1.598784
5.711603
-4.11282
2023
3.748394
7.780165
-4.03177
2024
7.927573
37.56324
-29.6357
2025
14.92651
48.20376
-33.2773
2026
21.97851
50.28277
-28.3043
2027
29.03365
57.10351
-28.0699
2028
36.08065
59.76146
-23.6808
2029
43.12536
47.39895
-4.27359
2030
50.20801
53.75278
-3.54477
2031
57.41416
60.02412
-2.60995
2032
64.87328
66.30937
-1.43609
2033
72.39482
72.48318
-0.08836
2034
79.75855
78.39186
1.366685
2035
87.40973
84.52413
2.885601
2036
94.97999
79.61881
15.36117
2037
106.1732
99.6375
6.535707
2038
117.9416
105.842
12.09956
2039
128.2236
110.3954
17.82813
2040
138.0807
113.2453
24.83538
2041
140.9198
110.0355
30.88424
2042
143.8883
117.5929
26.29539
2043
146.1011
124.1339
21.96719
2044
148.0015
129.8506
18.15093
2045
150.1686
134.8486
15.31994
2046
151.9571
136.3546
15.60257
2047
153.6602
137.7968
15.86335
2048
155.2736
139.1731
16.10042
2049
156.797
140.4806
16.31638
2050
158.2288
141.7183
16.51055
Table B-3 - HFC-134a Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Year
Technology Transitions liase
( tisc ///¦'( -13-la amission
Reductions (MM'iai c)
Allocation Unle Hcjerence ( use
///¦'( -13-In amission
Reductions (MM'iai e)
DiJJcrcncc (MM'iai c)
2022
3.669394
2.190366
1.479028
2023
5.084643
2.765359
2.319285
2024 6.726568 14.12936 -7.40279
121
-------
2025
9.6472
13.71806
-4.07086
2026
10.35921
13.32921
-2.96999
2027
11.36764
15.62647
-4.25884
2028
12.42865
17.34761
-4.91895
2029
13.52356
15.82696
-2.3034
2030
14.70179
17.35208
-2.65029
2031
15.67112
17.81007
-2.13894
2032
16.80103
17.14651
-0.34548
2033
17.92933
16.5166
1.412733
2034
19.42186
16.03767
3.384187
2035
20.33009
15.39826
4.931829
2036
21.62142
16.45899
5.162439
2037
22.75326
14.75932
7.993935
2038
23.72431
15.1901
8.53421
2039
24.70329
15.62188
9.081417
2040
25.69001
16.05046
9.639553
2041
26.676
16.47971
10.1963
2042
27.49399
16.9337
10.56029
2043
28.31749
17.38035
10.93714
2044
29.10206
17.82127
11.28079
2045
29.96523
18.25933
11.70589
2046
30.53858
18.66339
11.8752
2047
31.09951
19.05785
12.04166
2048
31.63251
19.42809
12.20442
2049
32.14586
19.77567
12.37019
2050
32.62982
20.09643
12.53339
Table B-4 - HFC-143a Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Year
Teclmolo&v liunsitions liusc
( tisc ///¦'( -N3u amission
Reductions (MMU.'l c)
Mloculion liulc licjcrcncc ( use
///¦'( '-l-IJtu Umission
Reductions (MMU.'l c)
nijjcrcncc (M.Ml 1:1 c)
2022
2.099635
6.523559
-4.42392
2023
2.794035
8.389586
-5.59555
2024
3.77587
11.19305
-7.41718
2025
5.524597
13.16049
-7.63589
2026
7.334428
13.97219
-6.63776
2027
9.181275
13.92634
-4.74506
2028
11.06614
16.29642
-5.23028
2029
12.99036
16.93567
-3.94532
2030
14.9557
17.99047
-3.03477
2031
17.09103
19.08887
-1.99784
2032
19.24129
20.24872
-1.00742
122
-------
2033
21.40488
21.46957
-0.06469
2034
23.18815
24.01805
-0.8299
2035
25.3234
25.41089
-0.08749
2036
27.21788
26.62126
0.596622
2037
29.09486
27.72543
1.369435
2038
30.6436
28.73448
1.909115
2039
32.19872
29.70195
2.496768
2040
33.75781
30.63549
3.122323
2041
35.3156
31.53108
3.784515
2042
36.78176
32.38733
4.394433
2043
38.09175
33.22205
4.8697
2044
39.33895
34.05003
5.288915
2045
40.54274
34.84875
5.693993
2046
41.49432
35.57749
5.916833
2047
42.35033
36.23388
6.116442
2048
43.10604
36.81445
6.291586
2049
43.75785
37.31595
6.441896
2050 44.3014 37.73528 6.56612
Table B-5 -HFC-152a Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Year
Icchnolo^y transitions liase
( tisc ///¦'( -I52u amission
Reductions (MMIJ.'I c)
Allocution liulc licjcrcncc ( use
///¦'( -I52(i Emission
Reductions (MMII.'I c)
nijjcrcncc (M.Ml 1:1 c)
2022
1.802037
0 699964
1.102073
2023
1.925979
0.741384
1.184595
2024
2.054157
0.784227
1.26993
2025
2.186692
0.828434
1.358258
2026
2.262519
0.874065
1.388453
2027
2.340504
0.891546
1.448958
2028
2.420703
0.909379
1.511325
2029
2.503174
0.927565
1.575609
2030
2.622714
0.946117
1.676598
2031
2.643696
0.953686
1.690009
2032
2.664846
0.961315
1.703531
2033
2.686165
0.969006
1.717159
2034
2.707654
0.976759
1.730895
2035
2.729315
0.984572
1.744743
2036
2.751149
0.992448
1.758701
2037
2.773157
1.000388
1.772769
2038
2.795342
1.008391
1.786951
2039
2.817706
1.016458
1.801248
2040
2.840248
1.02459
1.815659
123
-------
2041
2.862971
1.032787
1.830184
2042
2.885873
1.041049
1.844824
2043
2.908959
1.049377
1.859582
2044
2.932231
1.057772
1.874459
2045
2.955688
1.066234
1.889454
2046
2.979335
1.074764
1.904571
2047
3.00317
1.083363
1.919807
2048
3.027196
1.092029
1.935166
2049
3.051413
1.100766
1.950647
2050
3.075823
1.109572
1.966251
Table B-6 - HFC-227ea Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Technology Transitions linse
Year ( use ///¦'( -22 ~eu amission
Reductions (\I\Ili:\ c)
Allocution liulc Reference ( use
///¦'( -22~eu amission
Reductions (MMII.'l e)
Difference e)
2022
Q
0 03977
-0 03977
2023
0
0.049008
-0.04901
2024
0
0.059699
-0.0597
2025
0
0.071677
-0.07168
2026
0
0.084654
-0.08465
2027
0
0.098886
-0.09889
2028
0
0.114342
-0.11434
2029
0
0.131022
-0.13102
2030
0
0.149086
-0.14909
2031
0
0.168245
-0.16825
2032
0
0.188595
-0.1886
2033
0
0.210073
-0.21007
2034
0
0.232709
-0.23271
2035
0
0.255507
-0.25551
2036
0
0.277435
-0.27744
2037
0
0.29843
-0.29843
2038
0
0.31849
-0.31849
2039
0
0.337649
-0.33765
2040
0
0.355649
-0.35565
2041
0
0.372844
-0.37284
2042
0
0.389395
-0.38939
2043
0
0.405044
-0.40504
2044
0
0.419856
-0.41986
2045
0
0.433831
-0.43383
2046
0
0.446839
-0.44684
2047
0
0.458786
-0.45879
2048
0
0.469766
-0.46977
124
-------
2049
0
0.479683
-0.47968
2050 0 0.488474 -0.48847
Table B-7 - HFC-236fa Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case (2020 dollars per metric ton ofHFC-236fa)
Year
Teclmolo&v liunsitions liuse
( use /// '( -2JO/U Umission
Reductions (MMI/.'l e)
Allocution liulc liejerence ( use
///¦'( -230/u Emission
Reductions (MMl'l:l e)
Difference (MM'iil\ c)
2022
Q
0 0? 1
-0 0?197
2023
0
0.020896
-0.0209
2024
0
0.062295
-0.0623
2025
0
0.048464
-0.04846
2026
0
0.033356
-0.03336
2027
0
0.020112
-0.02011
2028
0
0.009025
-0.00903
2029
0
0
0
2030
0
0
0
2031
0
0
0
2032
0
0
0
2033
0
0
0
2034
0
0
0
2035
0
0
0
2036
0
0
0
2037
0
0
0
2038
0
0
0
2039
0
0
0
2040
0
0
0
2041
0
0
0
2042
0
0
0
2043
0
0
0
2044
0
0
0
2045
0
0
0
2046
0
0
0
2047
0
0
0
2048
0
0
0
2049
0
0
0
2050 0 0 0
125
-------
Table B-8 - HFC-245fa Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
Year
Technology Transitions Rase
( ase ///¦'( -2-l.yu Umission
Reductions (MMII.'I e)
Allocation linlc Reference ( ase
///'( -2-l.ya Emission
Reductions (MMII.'I e)
Difference (MM'iai e)
2022
2.014679
1.994119
0 020%
2023
2.840971
2.754947
0.086025
2024
3.824917
3.637922
0.186995
2025
4.099066
4.655283
-0.55622
2026
4.978231
5.207886
-0.22966
2027
5.613549
5.793071
-0.17952
2028
6.251291
6.412993
-0.1617
2029
6.861425
7.015437
-0.15401
2030
7.580261
7.731115
-0.15085
2031
8.078753
8.228937
-0.15018
2032
8.782718
8.933689
-0.15097
2033
10.08003
10.23279
-0.15276
2034
11.42002
11.57519
-0.15517
2035
12.201
12.3591
-0.1581
2036
13.02174
13.33733
-0.3156
2037
13.88636
14.21642
-0.33006
2038
14.33673
14.68157
-0.34485
2039
14.78578
15.1457
-0.35992
2040
15.23388
15.60911
-0.37523
2041
15.68116
16.0719
-0.39074
2042
16.12793
16.53446
-0.40653
2043
16.49862
17.01404
-0.51542
2044
17.07603
17.70076
-0.62474
2045
17.67693
18.40582
-0.72889
2046
18.28768
18.99455
-0.70688
2047
18.91833
19.58725
-0.66892
2048
19.54687
20.18074
-0.63387
2049
19.84212
20.7773
-0.93518
2050
20.44572
21.3714
-0.92568
Table B-9 - HFC-43-10mee Emission Reductions by Year from the Technology Transitions Rule
and the Allocation Rule Reference Case
Year
Technology Transitions Base
( use ///'( '--IJ-IOmee amission
Reductions (MMII.'I e)
Allocation Rule Reference ( ase
///¦'( —M-IOmee amission
Reductions (MM'iai e)
Difference (MM'iai e)
2022
0.05
0.757503
-0.7075
2023
0.066667
0.810636
-0.74397
2024 0.083333 1.141338 -1.058
126
-------
2025
0.1
1.23997
-1.13997
2026
0.1
1.342087
-1.24209
2027
0.1
1.447801
-1.3478
2028
0.1
1.557206
-1.45721
2029
0.1
1.169546
-1.06955
2030
0.1
1.236567
-1.13657
2031
0.1
1.29044
-1.19044
2032
0.1
1.345083
-1.24508
2033
0.1
1.400537
-1.30054
2034
0.1
1.456786
-1.35679
2035
0.1
1.513836
-1.41384
2036
0.1
2.314032
-2.21403
2037
0.1
2.332546
-2.23255
2038
0.1
2.351207
-2.25121
2039
0.1
2.370014
-2.27001
2040
0.1
2.388979
-2.28898
2041
0.1
2.408083
-2.30808
2042
0.1
2.427353
-2.32735
2043
0.1
2.44677
-2.34677
2044
0.1
2.466349
-2.36635
2045
0.1
2.486076
-2.38608
2046
0.1
2.505962
-2.40596
2047
0.1
2.526017
-2.42602
2048
0.1
2.546217
-2.44622
2049
0.1
2.566591
-2.46659
2050
0.1
2.587121
-2.48712
Table B-10 - HFC-23 Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
:)
Year
'cchiwluxy liunsitions liusc
( use ///¦'( --?.¦> amission
Reductions (MMU.'l c)
Mloculion liulc licjcrcncc ( use
11I X Emission Herfuclions
(MM I I. I c)
nijjcrcncc (MM'iil\ c)
2022
3.847906
3.847906
0
2023
3.843997
3.843997
0
2024
3.740918
3.740918
0
2025
3.707044
3.707044
0
2026
3.824169
3.824169
0
2027
3.704811
3.704811
0
2028
3.770625
3.770625
0
2029
3.798208
3.798208
0
2030
3.779526
3.779526
0
2031
3.779689
3.779689
0
2032
3.77211
3.77211
0
127
-------
2033
3.764122
3.764122
0
2034
3.766701
3.766701
0
2035
3.773329
3.773329
0
2036
3.76768
3.76768
0
2037
3.774666
3.774666
0
2038
3.775115
3.775115
0
2039
3.772549
3.772549
0
2040
3.771773
3.771773
0
2041
3.770894
3.770894
0
2042
3.770759
3.770759
0
2043
3.771496
3.771496
0
2044
3.772029
3.772029
0
2045
3.771884
3.771884
0
2046
3.772352
3.772352
0
2047
3.772094
3.772094
0
2048
3.771759
3.771759
0
2049
3.771671
3.771671
0
2050
3.77166
3.77166
0
Table B-l 1 sums the above ten HFC-specific tables for total emission reductions.
Table B-l 1 - Total HFC Emission Reductions by Year from the Technology Transitions Rule and
the Allocation Rule Reference Case
i
Year
'cchnolo^y Transitions liusc
( 'use Total /// '( ' amission
lictliiclions (MMII.'I c)
Allocution liulc lic/crcncc ( use
Total ///¦'( 1 amission DiJJcrcncc
lictliiclions (MMII.'I c)
(MM II.1 c)
2022
15.1095
21.93552
-6.82602
2023
20.3944
27.40438
-7.00998
2024
28.35879
77.78851
-49.4297
2025
40.6243
92.73207
-52.1078
2026
51.47962
95.71422
-44.2346
2027
62.194
106.0465
-43.8525
2028
73.18113
113.467
-40.2858
2029
84.17621
97.98766
-13.8114
2030
95.43468
107.9506
-12.5159
2031
106.4675
116.5514
-10.0839
2032
118.0908
124.2193
-6.12851
2033
130.3822
132.4308
-2.04865
2034
142.5615
141.8391
0.722386
2035
154.2418
149.6499
4.591883
2036
165.934
170.7883
-4.85421
2037
180.5264
176.23
4.296447
2038
195.6339
183.0818
12.55218
128
-------
2039
209.2258
189.9743
19.25149
2040
222.3204
196.981
25.3394
2041
228.245
203.7344
24.51063
2042
234.0464
209.7864
24.26003
2043
238.8632
214.9995
23.86376
2044
243.4649
219.7483
23.71662
2045
248.3546
223.938
24.41662
2046
252.3582
227.3034
25.05476
2047
256.1834
230.5232
25.6602
2048
259.784
233.5743
26.20966
2049
262.8333
236.4547
26.37863
2050 265.957 239.1506 26.80643
129
-------
Annex C: Industries Potentially Affected by subsection
(i) of the AIM Act
Companies that may be potentially affected by this rule include those that use HFCs to
manufacture products, such as refrigeration and air conditioning systems, foams, and aerosols. Industries
that may be potentially affected tangentially by this rule are those that produce, import, export, destroy,
use as a feedstock, reclaim, or otherwise distribute HFCs. Potentially affected categories, NAICS codes,
and examples of potentially regulated entities are included in Table C-l.
Table C-l: NAICS Classification of Potentially Regulated Entities
V I/( .V ( ixh
Y I/( S Industry Ih-scriplion
211120
Crude Petroleum Extraction
221210
Natural Gas Distribution
236118
Residential Remodelers
236220
Commercial and Institutional Building Construction
238220
Plumbing, Heating, and Air-Conditioning Contractors
238990
All Other Specialty Trade Contractors
311351
Chocolate and Confectionery Manufacturing from Cacao Beans
322299
All Other Converted Paper Product Manufacturing
325120
Industrial Gas Manufacturing
325180
Other Basic Inorganic Chemical Manufacturing
325199
All Other Basic Organic Chemical Manufacturing
325211
Plastics Material and Resin Manufacturing
325320
Pesticide and Other Agricultural Chemical Manufacturing
325992
Photographic Film, Paper, Plate and Chemical Manufacturing
325998
All Other Miscellaneous Chemical Product and Preparation Manufacturing
326150
Urethane and Other Foam Product
331420
Copper Rolling, Drawing, Extruding, and Alloying
332312
Fabricated Structural Metal Manufacturing
332313
Plate Work Manufacturing
333132
Oil and Gas Field Machinery and Equipment Manufacturing
333314
Optical Instrument and Lens Manufacturing
333316
Photographic and Photocopying Equipment Manufacturing
333413
Industrial and Commercial Fan and Blower and Air Purification Equipment Manufacturing
Air-Conditioning and Warm Air Heating Equipment and Commercial and Industrial Refrigeration
Equipment Manufacturing
333611
Turbine and Turbine Generator Set Unit Manufacturing
130
-------
Y l/( .V ( ode
\l/( S Industry Description
333996
Fluid Pow or Pump and Motor ManufacHiring
334419
Other Electronic Component Manufacturing
334515
Instrument Manufacturing for Measuring and Testing Electricity and Electrical Signals
334516
Analytical Laboratory Instrument Manufacturing
334613
Blank Magnetic and Optical Recording Media Manufacturing
336510
Railroad Rolling Stock Manufacturing
336611
Ship Building and Repairing
336612
Boat Building
339999
All Other Miscellaneous Manufacturing
423120
Motor Vehicle Supplies and New Parts Merchant Wholesalers
423450
Medical, Dental, and Hospital Equipment and Supplies Merchant Wholesalers
423460
Ophthalmic Goods Merchant Wholesalers
423730
Warm Air Heating and Air-Conditioning Equipment and Supplies Merchant Wholesalers
423740
Refrigeration Equipment and Supplies Merchant Wholesalers
423830
Industrial Machinery and Equipment Merchant Wholesalers
423860
Transportation Equipment and Supplies (except Motor Vehicle) Merchant Wholesalers
423990
Other Miscellaneous Durable Goods Merchant Wholesalers
424210
Drugs and Druggists' Sundries Merchant Wholesalers
424410
General Line Grocery Merchant Wholesalers
424610
Plastics Materials and Basic Forms and Shapes Merchant Wholesalers
424690
Other Chemical and Allied Products Merchant Wholesalers
424910
Farm Supplies Merchant Wholesalers
441310
Automotive Parts and Accessories Stores
443141
Household Appliance Stores
443142
Electronics Stores
444130
Hardware Stores
446191
Food (Health) Supplement Stores
452311
Warehouse Clubs and Supercenters
453998
All Other Miscellaneous Store Retailers (except Tobacco Stores)
454110
Electronic Shopping and Mail-Order Houses
481111
Scheduled Passenger Air Transportation
482111
Line-Haul Railroads
488510
Freight Transportation Arrangement
493110
General Warehousing and Storage
522293
International Trade Financing
523130
Commodity Contracts Dealing
531110
Lessors of Residential Buildings and Dwellings
531120
Lessors of Nonresidential Buildings (except Miniwarehouses)
532420
Office Machinery and Equipment Rental and Leasing
541330
Engineering Services
541519
Other Computer Related Services
131
-------
V I/( .V ( ode
Y I/( S Industry Ih-scriplion
541715
Research and Development in the Physical, Engineering, and Life Sciences (except
Nanotechnology and Biotechnology)
561210
Facilities Support Services
561910
Packaging and Labeling Services
561990
All Other Support Services
562920
Recovery and Reclamation
722511
Full-Service Restaurants
811219
Other Electronic and Precision Equipment Repair and Maintenance
811412
Appliance Repair and Maintenance
132
-------
Annex D: Imports of Products Containing
Hydrofluorocarbons
D.l Introduction and Background
This Annex analyzes the historical and projected import of products containing hydrofluorocarbons
(HFCs) listed as regulated substances under the American Innovation and Manufacturing Act of 2020
("AIM Act").
As noted earlier, EPA prepared a Regulatory Impact Analysis (RIA) for the Allocation Framework Rule
(86 FR 55116, October 5, 2021) establishing the framework for allocating HFC production and
consumption allowances for the years 2022 and 2023 49 In the Allocation Framework RIA accompanying
that rule (EPA-HQ-OAR-2021-0044-0227), EPA estimated the potential consumption reductions from
2022 through 2036 and emission reductions from 2022 to 2050 achieved by codifying the AIM Act HFC
phasedown consumption limits. Because EPA's analytic approach using the Vintaging Model and MAC
curves does not distinguish between products manufactured in the United States and those that are
imported from other countries, the Allocation Framework RIA did not specifically examine the impacts of
the import of products containing HFCs ("products") in terms of the amount of HFCs supplied to the U.S.
market or potentially abated therefrom vis-a-vis the reductions achieved under the phasedown. Under the
Allocation Framework Rule such imports do not require the expenditure of allowances; therefore, the
adoption of lower-GWP substances in imported products would not be the direct result of compliance
with the Allocation Framework Rule.
The same analytic limitations regarding differentiating between domestic and imported products applies
to the analysis of the Technology Transitions Rule. This Annex uses other techniques and information
sources to analyze the market for imported products containing HFCs. It is important to provide analysis
of the consumption and emissions impacts of the Technology Transitions Rule's provisions affecting
imported products. Domestic manufacturers must operate under the proposed constraints of the
Technology Transitions Rule regarding sector and subsector GWP limits and specific restrictions, as well
as the overall AIM Act production and consumption caps. Imported products will only be subject to the
proposed constraints of the Technology Transitions Rule regarding sector and subsector GWP limits and
specific restrictions. To the extent that the Allocation Rules' analyses include reductions due to imported
products containing HFCs, those analyses may underestimate the domestic adoption of abatement options
49 As noted previously, we use "Allocation Framework RIA" to refer to the analysis of the Allocation Framework Rule as
promulgated on October 5, 2021. This Annex provides supplementary analysis to address additional aspects of that RIA.
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required to meet the AIM Act consumption caps. This, in turn, may result in an overestimate of the
subsequent availability of options for the abatement in domestically produced equipment to comply with
the lower-GWP requirements of this proposed rule.
D. 1.1 Imported Products Containing HFCs
Several types of products containing HFCs are imported to the United States. Under EPA's Greenhouse
Gas Reporting Program (GHGRP), codified at 40 CFR Part 98, the net supply of HFCs in a subset of
imported products, i.e., appliances and closed-cell foam, has risen from 7.4 MMTCChe in 2011 to 35.2
MMTCC^e in 2020. These totals are the amount of all reported imports minus all reported exports. The
total amount of imports is greater than these totals.
The data reported under the GHGRP represents less than the total amount of HFCs contained in products
imported into the United States due to two limitations. First, the scope of the GHGRP excludes certain
product types that contain HFCs. For instance, aerosol cans and fire extinguishers are not reported.
Second, reporting is not required for those who import and export less than 25,000 MTCC^e annually.
Even so, the reported 2020 net import of saturated HFCs in products and foams equates to 11.4% of the
net supply of HFCs in bulk.50
To conduct the analysis in this Annex, we examined the categories of products typically containing HFCs
when imported to the United States. Product categories included in this Annex include closed-cell foams
and aerosol cans that contain HFCs. The term "closed-cell" is used to describe many types of foam
products and indicates that unlike for "open-cell" foams the intent is for the blowing agent, in this case an
HFC, to be contained within the cells of the foam. An aerosol can is another example. In this case, the
useful product is not the metal can itself, but the material within the can that is to be distributed
(aerosolized) from the can. An HFC may be used as the propellant to create the aerosolized product (e.g.,
hairspray or body deodorant), may be both the propellant and the useful product itself (e.g., as a duster),
or may be the solvent carrier (e.g., HFC-134a as the propellant carrying HFC-43-10mee as a solvent, for
instance for removal of grease, flux and other soils from electrical equipment or electronics).
In other types of products, the HFC is required for the equipment to work, and is often pre-charged when
the product is manufactured as a convenience to the ultimate consumer. For example, a self-contained
room air conditioner (e.g., a "window AC") would typically be pre-charged with the refrigerant, and the
cooling circuit would be closed at the factory. This avoids the need for a homeowner or technician to
provide the refrigerant and seal the system before it can be plugged in and used. Several other types of
products come fully charged with the appropriate amount of a refrigerant, including household
50 https://www.epa.zov/zhzreportins/suppliers-industrial-zhzs-and-products-containinz-ghzs, viewed on August 2, 2022.
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dehumidifiers, portable air conditioners, packaged terminal air conditioners and heat pumps, beverage and
food coolers, and vending machines. Walk-in cold storage "rooms" and chillers could also be pre-
charged, although in some instances—typically when the product is too large to fit in a standard sized
shipping truck—the individual components for these types of products would be manufactured separately
and the system would be installed and charged with a refrigerant on-site.
Another type of pre-charged product includes those that typically contain a "holding charge." A common
example is the "condensing unit" for a residential air conditioner. The condensing unit typically contains
the compressor, the condenser, and often other parts of the air conditioner. It would be placed outside, and
the refrigerant lines would be connected to the indoor unit, which contains the evaporator. Condensing
units, especially those of smaller capacity and intended primarily for residential applications, generally
contain a holding charge of the refrigerant. The amount is meant to be close to the full charge required in
applications with a defined length of refrigerant lines. As each application of such units vary, notably in
the length of refrigerant lines required to reach the indoor unit, the system is typically "balanced" by the
installer to provide the correct amount of refrigerant needed for the application.
D.1.2 Allocation Framework Rule Coverage of Imports
The Allocation Framework Rule provided the methodology for allocating allowances for the production
and import of bulk substances. Apart from allocations for the discreet and statutorily required applications
listed in (e)(4)(B)(iv) of the AIM Act, the Allocation Framework Rule did not provide for the allocation
of allowances based on a company's manufacture or import of products that use HFCs.
Furthermore, in defining the terms "consumption" and establishing the baseline based on the formula
provided in the AIM Act, EPA did not include the quantity of HFCs contained in imported products.
There were several reasons for this approach as discussed in the Allocation Framework Rule (see 86 FR
55130-55132; 86 FR 55137-55140). The Agency surmised that subsection (i) of the AIM Act provided
clearer authority to address imported products while achieving the goals of the AIM Act and noted that at
that time already more than a dozen petitions under subsection (i) had been received to address both
imported and domestically manufactured products. EPA is proposing a rule under the authority of
subsection (i), referred to as the "Technology Transitions Rule," to address manufacture and import of
products containing HFCs.
D.1.3 Allocation Framework RIA Coverage of Imports
As mentioned above, the Allocation Framework RIA estimated the potential consumption and associated
emission reductions possible while complying with the HFC phasedown requirements in the AIM Act.
The Allocation Framework RIA describes EPA's process for such estimates. EPA used a Marginal
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Abatement Cost (MAC) analysis based on previous work to develop a cost scenario that would reduce
consumption to the amount required under the AIM Act. The MAC analysis required the use of abatement
options that provided the cost and consumption reductions possible in the U.S. market. EPA relied on its
Vintaging Model to calculate a "business as usual" (BAU) projection of HFC consumption and to
determine the reduction in consumption, and the associated reduction in emissions, achieved under the
individual abatement options.
The Allocation Framework RIA is agnostic as to whether products under each abatement option are
imported or manufactured domestically. In other words, if an abatement option assumed that a certain
HFC was replaced by a lower-GWP substance, such change was assumed for all products equally. Several
abatement options included in the analysis needed to reduce domestic consumption of HFCs to reach the
AIM Act consumption caps involve an equipment market that is at least in part imported to the United
States. In the Allocation Framework RIA, if a specific HFC subsector was assumed to fully convert to a
lower-GWP substance, the analysis included HFC consumption reduction for all products - both those
products produced domestically and those imported. If only a portion of a subsector was assumed to
convert, the percentage assumed as not transitioning was based on information and conclusions on the
particular subsector and the viability of the alternative substance; that portion not converting was not
meant to represent the percentage of the subsector that is imported.
D.2 Imports of Products Containing HFCs
Because of the limitations in the Allocation Framework RIA discussed above, EPA undertook a scoping
analysis to estimate the amount of HFCs historically contained in imported products and to project such
HFC supply in the future. This scoping analysis was conducted using supplementary data from the U.S.
Census, previous EPA rulemakings, EPA's Vintaging Model, and other sources. A table summarizing the
types of products analyzed and the related assumptions, explained below, is provided in Section D.3 of
this Annex. In addition, EPA estimated the potential reductions in such supply and in the associated
emissions based on exercising the authority in subsection (i) of the AIM Act as proposed in the
Technology Transitions Rule.
D. 2.1 Historical Information on Imported Products
Import data were available from the United States International Trade Commission, with divisions by the
U.S. Census Bureau's 6-digit North American Industry Classification System (NAICS), the 10-digit
Harmonized Tariff Schedule (HTS), and 5-digit Standard International Trade Classification (SITC).51
EPA first used expert judgement to gather the product types that were likely to be imported containing
51 https.V/dataweb. usitc. gov/
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HFCs, which included one aerosols subsector, one polyurethane foams subsector, and nine subsectors in
the Refrigeration, Air Conditioning, and Heat Pump sector. Based on feedback from the National Aerosol
Association (NAA) and the Household and Commercial Production Association (HCPA), EPA gathered
aerosol import data from 27 import categories represented by 35 separate HTS codes. For the other types
of products, EPA used the SITC codes, as these offered greater differentiation than other methods such as
HTS codes. In this way, EPA gathered the imports of products (by number of units) for the years 2016-
2021.
D. 2.2 Current HFCs Contained in Imported Products
EPA then determined the likely HFC contained in these products and the amount or charge size to
calculate the quantity, in metric tons and CChe, contained in such products. Product lifetimes were also
gathered so that emissions could be calculated while accounting for the time lag between product
manufacture and emissions. In terms of the HFC contained in the imported products, EPA evaluated two
scenarios:
A. Mix. We assumed that the products being imported included some products using traditional,
high-GWP HFCs and others using lower-GWP alternative substances. Using previous work under
EPA's Significant New Alternatives Policy (SNAP) program, Small Business Regulatory
Enforcement Fairness Act (SBREFA) analysis, the Vintaging Model, and other sources, we
estimated the market share amongst the imports between the baseline high-GWP HFC(s) and the
likely alternative substance(s). This is considered conservative (lower reductions on a CChe
basis), as we would expect the imported products to be reliant more on the older, higher-GWP
options whereas the overall market may be a mix with some newer lower-GWP options.
B. High-GWP. As a bounding exercise, we assumed the imported products contained the high-GWP
HFC(s) that have historically been used in the individual subsectors. However, where it was
reasonably concluded that the transition in imported products was already occurring, we did not
make such an adjustment to that subsector. For instance, information from the GHGRP shows us
that some light-duty passenger cars are imported with HFO-1234yf, and others with HFC-134a,
so the imports were divided between these two options as before.
The following graphs display the total imports for each year 2016 through 2021 by subsector in CChe
terms.52
52 Blank items in the legend of the right (high-GWP) graph represent subsectors wherein lower-GWP alternative substances were
removed from the historical imports, and which were instead assumed to have contained only high-GWP HFCs.
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Figure D-l: Historical HFCs in Imported Products under Two Scenarios (MA fTCOje)
Historical Imports (Mixscenario) Historical Imports (High-GWP scenario)
¦ Hi
2016 2017 2018 2019 2020 2021
¦ SA1 ¦ SA2 ¦ VM1 ¦ VM2 «VM3 RFPD bTRI
¦ TR2 ¦ HRF1 IMRF2 1SAC1 ¦ SAC 2 ¦ UAC1 ¦ UAC2
¦ Aer ¦ PU1 ¦ PU2 ¦ MVACC1 ¦ MVACC2 ¦ MVACT1 ¦ MVACT2
I I
2019
¦ SA1
¦ TR2
¦ Aer
2017 2018
l ¦VM1 ¦
¦ HRF1 ¦ HRF2 ¦ SAC1 BSAC2
2020 2021
RFPD BTRI
¦UAC1 ¦
¦ PU1
MVACC1 ¦ MVACC2 ¦ MVACT1 ¦ MVACT2
These estimates of historical HFC in imported products seem reasonable when compared to the available
data from GHGRP (Part 98). The values here range from 28 MMTCChe to 35 MMTCC^e (Mix scenario)
or 33 MMTCC^e to 40 MMTCChe (High-GWP scenario) for the years 2016-2020.53 Values from the
GHGRP, which are net supply, not imports only, and are limited in scope and coverage as explained
above, range from 28 MMTCChe to 35 MMTCChe over the same time period.
D.2.3 Projecting Future Imports of Products
Although the market fluctuates from year to year, there is a general growth in imports in CC^e terms, with
an annual linear increase of 1.7 to 2.0 MMTCChe. The GHGRP data, which dates back to 2011, shows an
even steeper linear growth of 2.7 MMTCC^e per annum, although the increase is only 1.14 MMTCChe
per year for the 2016-2020 timeframe. Given this increasing trend, it is important to estimate what the
import of products containing HFCs could be in the future, if no restrictions were placed on them. For this
factor, we also used two scenarios to bound the analysis:
1. BAU-linked. We assumed the imports grow or decline at the same rates as the business-as-usual
(BAU) consumption curve presented in the Allocation Framework RIA. This assumption would
imply the portion of the overall market supplied by imports remains the same.
2. Linear trend. We used a linear regression of the historical import data. Each subsector was
trended separately. These projections were higher than the BAU-linked estimates for most years.
These projections can be considered as "business as usual" projections; that is, they show how imported
products would grow without the proposed Technology Transitions Rule in place. As discussed above in
sections D.1.2 and D.1.3 of this Annex, the Allocation Framework Rule, and the related proposed 2024
53 GHGRP data for 2021 are not yet available and thus not included in this comparison.
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Allocation Rule, do not constrain the import of products containing HFCs. Thus, these "business as
usual" projections apply irrespective of those rules.
There is much uncertainty in such estimates and this fact is the reason why we offer two scenarios that we
feel would bound the most likely outcomes. However, in the absence of the Technology Transitions Rule,
it might be expected that as the production and consumption of HFCs are phased down under the
Allocation Rules, the available HFC might be directed towards those applications that could not be
imported (e.g., field-erected refrigeration systems). This could mean that imported products containing
HFCs could grow even faster than the projection scenarios analyzed, and domestic manufacture of such
products would decline. This might in turn cause economic harm to domestic manufacturers, or a shift by
those manufacturers to open production lines outside of the United States. Many U.S.-headquartered
businesses already have overseas facilities, and so for them it might be simply a redistribution of where
products containing HFCs are made, if their production is not already 100% outside the United States.
As discussed below in section D.5.2 of this Annex, the redistribution of production, even in absence of
this proposed Technology Transitions Rule, would be constrained by several factors. We note that
currently, major U.S. trading partners are parties to the Kigali Amendment to the Montreal Protocol, so
the availability of HFCs would also be constrained in those countries. Further, the U.S. is a large market
for HFC-containing products, which would lead manufacturers to offer only products that comply with
our regulations. Also, other countries are adopting similar restrictions, and many States have or would do
so in the absence of the proposed Technology Transitions Rule, again leading manufacturers to offer a
limited selection of products, specifically ones that comply with the proposed restrictions in this rule.
For these reasons, we feel the projections are reasonable bounds on the "business as usual" imports of
products containing HFCs. The following graph shows the annual projected imports in CChe terms
without restrictions using the two projection methods discussed above, with each shown under the two
scenarios regarding the types of chemicals contained in the imported products.
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Figure D-2: Projected HFC Imports in Products in absence of the Technology Transitions Rule (AfKlTCO je)
120
100
80
a>
rsl
O
fd 60
40
20
0
2022 2026 2030 2034 2038 2042 2046 2050
Four estimates each under the GWP Limits and Compliance Path scenarios are shown. Each of the lines is color-
coded to match the estimated annual HFCs in imported products without restrictions (solid lines). For brevity, only
one entry is shown in the legend to indicate the format of the four GWP Limits estimates (dotted lines) and the four
Compliance Path estimates (dashed lines).
D.2.4 Future Alternative Substances Contained in Imported Products
The Technology Transitions Rule proposes GWP limits on several types of products, including most all
those assumed to be imported with HFCs contained in them, and proposes that such limits apply equally
to imported products and domestically manufactured products.54 These proposed restrictions, if enacted,
will require imported products that do not already comply with the restrictions to transition to alternative
substances. Such restrictions could affect multinational companies" decisions regarding where to
manufacture products and hence change the dynamics of the import market. Such decisions are difficult to
predict, so here we assume the trends as discussed above continue while the Technology Transitions Rule
takes effect, if enacted as proposed.
Importers of products, like the domestic manufacturers, have a variety of alternative substances to choose
from while complying with the proposed Technology Transitions Rule restrictions. Multiple choices for
each product subsector exist as discussed in the preamble to the proposed Technology Transitions Rule
and the Technical Support Documents referenced therein. We made two assumptions regarding what
substance products would transition to under this rule:
I. GWP limits. We assumed products with imported HFCs above the GWP limit would change to a
substance or blend with the exact GWP limit proposed. Few alternative substances currently exist
54 The exception is road transport refrigeration, wherein EPA proposes to restrict specific HFCs and blends containing HFCs . As
explained in the text above, for this analysis we apply a GWP limit of 2,200 to model this subsector.
Annual Projected Imports without Restrictions
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at the exact GWP limits proposed, so this approach would require such hypothetical blends to be
developed. To attribute emissions by chemical (so that individual social costs of HFCs could be
applied), we assumed the current high-GWP HFC would be "blended down" with another non-
HFC chemical (e.g., an HFO or a hydrocarbon) to reach the exact GWP limit. This would result
in the highest level (in CChe terms) of imports allowed under the restrictions and hence lower
reductions in both the amount imported and the resulting emissions than the following approach.
II. Compliance Path. Because the alternative substances contained in imported products would not
necessarily have GWPs at the exact limit, and instead would likely be other existing or
developing alternative substances that are below that limit, we developed a compliance path of
most likely alternative substances based on the abatement options analyzed previously in the
Allocation Framework RIA and our knowledge of the subsectors.
With the various projections estimated above and the two possible approaches in the alternative
substances chosen, we can estimate the resulting supply of HFCs in imported products with restrictions.
The projected import of HFCs with and without restrictions is shown in the following graph.
Figure D-3: Projected Imports of HFCs in Products with and without the Technology Transitions Rule (AlAITCOje)
Annual HFCs in Imported in Products
with and without Restrictions
o
2025 2030 2035 2040 2045 2050
BAU-linked (High GWP) Linear trend (High GWP)
BAU-linked (Mix) Linear trend (Mix)
GWP Limits — — Compliance Path
The difference between the with and without restriction scenarios indicates how much supply of HFCs is
avoided by restricting imports as proposed. We do not consider these additional benefits beyond the MAC
approach used to analyze this rule and the Allocation Rules, because as discussed above the model used
for the MAC approach assumes compliance for the entire U.S. market and remains agnostic as to whether
the affected subsector includes products that are imported with HFCs or not.
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The following graphs display the annual reductions in HFCs imported in products over time. Reductions
start in 2025, the first proposed compliance period in the Technology Transitions Rule.
Figure D-4: Reductions of HFCs in Imported Products with the Technology Transitions Rule (MAITCOje)
Annual Reductions of HFCs Imported in Products
(GWP Limits)
Annual Reductions of HFCs Imported in Products
(Compliance Path)
70 -
a> 60
8 50 -—¦
^ 40 _
20
BAU-linked (High GWP) Linear trend (High GWP)
BAU-linked (Mix) Linear trend (Mix)
5 30 -2—
20
BAU-linked (High GWP) Linear trend (High GWP)
BAU-linked (Mix) Linear trend (Mix)
2025 2030 2035 2040 2045 2050
2025 2030 2035 2040 2045 2050
D.2.5 Emissions
Once imported to the United States, emissions from products containing HFCs would occur. To
estimate the emissions from the imported products, EPA applied a simplified emission profile to
each subsector, assuming that the full charge imported would be emitted at the product's end-of-
life. For aerosols, this is the same emission profile used in Vintaging Model and conforms with
guidelines from the Intergovernmental Panel on Climate Change. The estimate is conservative
(i.e., modeled emissions occur later than actual) for foam products, which would typically have
diffusive emissions from the foam during product use, and full emissions either at disposal (e.g.,
from crushing the foams) or possibly thereafter (e.g., remaining HFCs emitted after the foam has
been put in a landfill). For many of the air conditioning and refrigeration appliances, the
emission profile is similar to real-life use. For example, window air-conditioners, domestic
refrigerators, and other types of self-contained products generally maintain their refrigerant
charge throughout the lifetime, with no service or "topping-off' of the refrigerant required.
Regulations under section 608 of the CAA require recovering the refrigerant before the
equipment is disposed; however, we have not modeled the fate of any refrigerant so recovered,
and hence these emissions may lead to less conservative (i.e., modeled emissions occurring
earlier than actual) results. Finally, some imported air conditioning and refrigeration products
(e.g., condensing units used in residential AC) are typically serviced throughout their useful life.
Here the modeled emissions are again conservative, as this analysis did not account for any
additional refrigerant needed for service. Using this emission profile, annual emissions from
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imported products with and without the restrictions in the Technology Transitions Rule are
generated, as shown in the graph below.
Figure D-5: HFC Emissions from Imported Products with and without Technology Transitions Rule (AlAITCOje)
Annual HFC Emissions from Imported Products
with and without Restrictions
— BAU-linked (High GWP)
— Linear trend (High GWP)
BAU-linked (Mix)
Lineartrend (Mix)
— — Compliance Path
Four estimates each under the GWP Limits and Compliance Path scenarios are shown. Each of the lines is color-
coded to match the estimated annual HFC emissions from imported products without restrictions (solid lines). For
bre\>itv, only one entry is shown in the legend to indicate the format of the four GWP Limits estimates (dotted lines)
and the four Compliance Path estimates (dashed lines).
Annual emission reductions due to the restrictions on imported products are shown in the graphs
below. In general, the linear trend scenarios achieve higher reductions than the BAU-linked
scenarios because the amount imported in products is higher under that growth scenario. All
scenarios see certain years where emission reductions increase significantly. This is due to the
emission profile assumption that emissions occur at the product end-of-life, and that different
product types have different lifetimes. For example, a final increase in 2050 is seen arising from
the polyurethane foam products, which have a 25-year lifetime and a compliance date beginning
in 2025.
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Figure D-6: HFC Emission Reductions from Imported Products with the Technology Transitions Rule (MAlTCOje)
Annual HFC Emission Reductions from Imported Annual HFC Emission Reductions from Imported
Products (GWP Limits) 50 Products (Compliance Path)
a) 40
O
£ 30
^ 20
10
0
-BAU-linked (High GWP)
-Linear trend (High GWP)
-BAU-linked (Mix)
Linear trend (Mix)
-BAU-linked (High GWP)
-Linear trend (High GWP)
-BAU-linked (Mix)
-Linear trend (Mix)
D. 2.6 Climate Benefits
The emission projections as discussed above were compiled for each HFC regulated, both with
and without the restrictions. The differences in these results were then used to monetize the
incremental climate benefits of emission reductions from imported products. To do this, the
change in emissions for each HFC in each year is multiplied by the corresponding SC-HFC for
that HFC in that year.
The monetization of climate benefits in this analysis uses the same HFC-specific SC-HFC
estimates as the estimation of the benefits of the full HFC phasedown in the Allocation
Framework RIA. The complete listing of these values can be found in Appendix D of the Costs
and Benefits Addendum for the proposed 2024 Allocation Rule. Section 4.2 of that document
discusses other aspects of the SC-HFC estimates, including discounting. The SC-HFC values are
listed in 2020 dollars per metric ton of HFC emitted by year. The SC-HFC 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 2025—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. A more complete discussion of the development of these SC-
HFC estimates can be found in section 4.1 of the Allocation Framework RIA.
I). 2. 7 Costs
There are expected to be costs or savings to transition imported products from HFCs to lower-GWP
alternatives. The costs to convert factory lines would occur outside the United States, as would any costs
or savings from making the product with the alternative in lieu of the HFC, and the costs or savings
associated with the equipment itself. For instance, in the proposed rule, EPA notes that if an alternative is
more efficient than the HFC, less materials (e.g., copper, aluminum) may be needed to provide the
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necessary heat transfer surfaces in an air conditioner. This would lower the material cost to produce that
air conditioner, a savings that would go to the overseas producer.
It is unknown whether or how a manufacturer might recoup any such costs or pass through any such
savings. For instance, if a manufacturer already planned and financed a transition for other reasons (such
as increasing energy efficiency of their products to compete within all markets), the additional costs of
adopting an alternative refrigerant might be minimal compared to the overall increased costs. Likewise, a
manufacturer might have already planned to adopt an alternative chemical so that their products could be
sold in markets with similar restrictions, such as the European Union. Manufacturers that are in countries
who are parties to the Kigali Amendment to the Montreal Protocol might likewise be compelled to adopt
lower-GWP alternatives or at least see the financial advantage to do so. Also, several manufacturers have
internal policies and goals related to climate change and sustainability, and so might transition for those
reasons.
Costs or savings from using a less or more efficient product would occur in the United States, as
customers would be paying for the energy (electricity) to operate such products. However, manufacturers,
knowing the potential energy efficiency aspects of a new product, might price more efficient equipment at
a premium or might lower prices for less efficient equipment. Again, what such decisions would be made
by foreign manufacturers, or even domestic manufacturers, are difficult to predict with any degree of
certainty.
As discussed above, the GWP Limits scenarios assumed an alternative existed at the exact GWP limit set.
While one could determine the reductions associated with such an alternative, assessing the costs would
be difficult. A specific GWP limit could be satisfied in a theoretically infinite set of possible options, but
it is reasonable that costs of each such options would be different. For instance, blends that would have a
GWP of exactly the limit are blends of one HFC and an inert gas or other substance with a GWP of zero.
For example, 22.2% (by weight) HFC-32 or 4.3% HFC-125 or 10.5% HFC-134a could be blended with
an inert gas and yield a GWP of exactly 150. Likewise, a 4.7%/95.3% blend of HFC-32 and HFC-152a
would have a GWP of 150, as would a 2.0%/98.0% blend of HFC-134a and HFC-152a. The absolute
price of these different blends would be very different, as would the social costs.
For the Compliance Path scenarios, EPA assumed a particular substitute for each subsector. In part the
substitute was determined by looking at the MAC abatement options as discussed in Chapter 4. For those
subsectors, we do determine an abatement cost, in terms of dollars per metric ton of CC^e abated. To get
an estimate of the costs—which again are not necessarily the costs to the United States economy—we can
simply multiply this factor by the total reductions of HFCs in imported products (see section D.2.4 of this
Annex). Annual costs for the four Compliance Path scenarios are shown below in section D.4 of this
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Annex, and range from approximately $200 million to $700 million, depending on the scenario and year.
Cumulative costs through 2050 range from $5.4 billion to $12.8 billion. These costs are rather large
compared to the overall cost of the proposed Technology Transitions Rule for a few reasons. First, the
analysis in this RIA addendum looks at the incremental costs of the proposed rule as compared to the
Allocation Framework Rule and the proposed 2024 Allocation Rule. Thus, this analysis is only covering a
portion of the market change whereas the costs in this Annex are estimated for the entire market change.
Second, the proposed Technology Transitions Rule cost analysis includes a larger mix of transitions, and
significant savings were found in some subsectors which are not imported with pre-charged HFCs,
reducing the overall costs. Third, as explained in section D.5.1 of this Annex, under some assumptions the
import of HFCs in products could, in absence of this proposed rule, exceed the consumption limits
established by the HFC phasedown. In that sense, this Annex is estimating a larger import of such
products that are otherwise implicit in the scenarios used in evaluating the overall costs of the Allocation
Rules and the incremental costs of the proposed Technology Transition Rule.
We note that this methodology to estimate costs cannot be applied to the "retail food refrigeration—
refrigerated food processing and dispensing equipment" (RFPD) subsector nor the motor vehicle air
conditioning (MVAC) options. For the RFPD equipment, the medium-duty (MD) vehicles, and the
heavy-duty (HD) pick-up trucks, abatement options were not applied because the Vintaging Model used
for the MAC analysis, in this RIA addendum as well as the Allocation Framework RIA and the proposed
2024 Allocation Rule RIA addendum, did not model such equipment. For the light-duty (LD) passenger
vehicles and trucks subsector, the Vintaging Model already assumed a complete transition to HFO-1234yf
in the baseline before the 2025 compliance date proposed; therefore, no abatement option was assumed in
the MAC analyses. Therefore, the costs calculated do not include those associated with these subsectors.
D.3 Data and Assumptions
The following table provides a summary of the subsectors of products assumed to be imported
with HFCs, Customs codes, assumed HFC type and quantity contained, and assumed product
lifetime.
146
-------
Table D-l: Assumptions Applied to Imported Products Containing HFCs
Subsector
SITC
//i(Substitutes(s)
C barge
Size (hif)
Lifetime
(years)
Stand-alone/Self-contained Refrigeration Systems
74143
HFC-134a, R-450A, R-513A, R-290
0.29
10
Vending Machines
74595
HFC-134a, R-404A, R-450A, R-
513A, HC-290
0.29
10
Retail Food Refrigeration - Refrigerated Food
Processing and Dispensing Equipment
74597
HFC-134a, R-404A, R-450A, R-
513A, HC-290
0.29
10
Transport Refrigeration
78629
R-404A. R-452A. R-507A
6.4
12
Household Refrigerators and Freezers
77521,
77522
HFC-13 4a. HC-600a
0.16
14
Window/Room/Portable AC & Dehumidifiers
74151
HFC-32. R-410A
0.5
12
Residential and Non-residential A/C, Excluding Small
AC Appliances
74155
HFC-32. R-410A. R-454B
1.0
15
Aerosol Products
HTS
Codes2
HFC-134a, HFC-152a, NIK, HCs,
HFO-1234zc(E). DME. Compressed
Gas
0.13
1
Polyurethane Products
57545
HFC-13 4a. HFC-245fa. HCFO-
1233zd(E), HFO-1234ze(E), HC.
CO7. H20
0.16
25
LD Passenger Vehicles and Trucks
78120
HFC-134a. HFC-152a. HFO-1234vf.
C02
0.6
16
MD Passenger Vehicles and HD Pick-up Trucks
78219
HFC-134a. HFC-152a. HFO-1234vf.
C02
0.8
15
1 Substitutes in italics are those that are assumed to not be used in the High-GWP scenarios. Alternatives underlined are the
assumed substitute in the Compliance Path scenarios.
2 Based on NAA and HCPA feedback, in lieu of SITC codes, aerosol products were analyzed based on the following HTS codes
(up to three ending zeros removed for brevity): 3307.30.5, 3307.49.0, 3303.00.3, 3402.90.503, 3307.20.0, 3808.59.4, 3808.94.1,
3305.10.0, 2903.39.2045, 2903.39.202, 3824.99.55, 3403.19.1, 3824.79.9079, 3403.99.0, 3824.99.9297, 3402.13.5, 3402.20.51,
3305.90.0,3305.30.0, 3305.20.0,3808.91.2501,3808.59.1,3808.91.5001,2710.19.308,2710.19.4, 2710.19.459,2710.19.9,
3208.90.0, 3910.00.0, 3814.00.1, 3814.00.509, 9503.00.0073, 9304.00.6, 3340.99.5, 3506.99.0
The following table presents the number of products historically imported.
147
-------
Table D-2: Historical Imports of Products Containing HFCs
Subset-tor
Historical Imports (number of units)
20 If,
20!"
20 IS
20IV
2020
2021
Stand-alone/Self-contained
Refrigeration Systems
1,262,726
1,282,473
1,570,103
1,501,740
1,949,071
2,369,816
Vending Machines
118,937
177,623
377,538
225,755
176,358
366,746
Retail Food Refrigeration -
Refrigerated Food
Processing and Dispensing
Equipment
0
0
0
0
3,380
4,602
Transport Refrigeration
34,288
34,595
37,490
32,692
26,268
33,231
Household Refrigerators and
Freezers
10,805,746
11,759,748
13,691,610
10,504,055
16,712,049
17,885,268
Window/Room/Portable AC
& Dehumidifiers
7,601,183
8,901,440
10,572,457
7,216,190
8,877,754
11,572,778
Residential and Non-
residential A/C, Excluding
Small AC Appliances
5,038,993
5,712,015
6,425,533
5,300,644
5,487,311
10,060,600
Aerosol Products1
265,119,336
302,612,257
412,503,772
435,655,906
584,041,797
553,443,114
Polyurethane Products1
44,517,187
45,301,179
51,055,137
46,933,601
41,996,017
57,765,298
LD Passenger Vehicles and
Trucks
10,276,390
10,264,987
9,834,511
9,571,266
8,111,633
7,847,343
MD Passenger Vehicles and
HD Pick-up Trucks
979,498
992,042
1,029,316
1,089,792
861,911
974,658
1 Aerosol Products and Polyurethane Products are shown in kilograms.
148
-------
D.4 Results
The following table shows the estimated import of HFCs in products in absence of the
restrictions proposed in the Technology Transitions Rule. Four BAU scenarios are provided as
described above in section D.2.3 of this Annex, depending on both the future growth of HFCs
from the historical trends (termed "BAU-linked" and "Linear trend") and assumptions regarding
the mix of chemicals in those imported products (termed "Mix" and "High-GWP").
Table D-3: Annual Quantity of HFCs in Imported Products in absence of the Technology
Transitions Rule
Historical and Future. \nnual Imports without Restrictions (MMT('();e)
Mix
High-tillV
) ear
n 11 -linked
Linear trend
11 11 '-linked
Linear trend
2016
28
28
33
33
2017
31
31
36
36
2018
35
35
40
40
2019
29
29
34
34
2020
30
30
34
34
2021
42
42
49
49
2022
43
38
50
45
2023
44
40
51
47
2024
45
42
53
49
2025
45
44
52
51
2026
45
45
52
53
2027
45
47
52
55
2028
44
49
52
57
2029
44
51
51
58
2030
44
52
52
60
203 1
45
54
52
62
2032
45
56
52
64
2033
45
57
53
66
2034
46
59
53
68
2035
46
61
53
70
2036
46
63
53
72
2037
46
65
54
75
2038
46
67
54
77
2039
47
69
54
79
2040
47
71
55
82
2041
48
73
55
84
2042
48
75
56
86
149
-------
2043
48
77
56
88
2044
49
79
57
91
2045
49
81
57
93
2046
50
83
58
95
2047
50
85
58
97
2048
50
87
59
100
2049
51
89
59
102
2050
51
91
60
104
Total1
1,548
2,040
1,799
2,356
1 Totals may not sum due to independent rounding.
Two possible scenarios to comply with the restrictions in the proposed Technology Transitions
Rule were explored (termed "GWP Limits" and "Compliance Path") for each of the four
scenarios above, as explained in section D.2.4 of this Annex. The following table displays the
reductions in the supply of HFCs under these scenarios.
Table D-4: Annual Reductions of the Quantity of HFCs in Imported Products under the
Technology Transitions Rule
. \nniitil Reductions of III 'C \ in Imported Products (MMiC (>:c)
(ill'P Limits
C ompliance Path
Mix
High-tiM P
Mix
Ui»h-
-------
2043
33
50
40
60
37
57
46
70
2044
33
51
40
61
37
58
46
71
2045
33
52
41
63
38
60
46
73
2046
34
53
41
64
38
61
47
75
2047
34
55
41
66
38
63
47
77
2048
34
56
41
68
39
64
47
78
2049
35
57
42
69
39
66
48
80
2050
35
58
42
71
39
67
48
82
Total1
829
1,121
1,002
1,357
935
1,284
1,147
1,572
1 Totals may not sum due to independent rounding.
As discussed above in section D.2.5 of this Annex, a simplified emission profile was applied to
the products imported with HFCs. The next two tables display the estimated emissions under the
case without and with the proposed Technology Transitions Rule, respectively. The third table
below shows the emission reductions achieved under the eight scenarios described should the
rule be finalized as proposed.
Table D-5: Annual HFC Emissions from Imported Products in absence of the Technology
Transitions Rule
.\nniKil Emissions from Products Imported with Hi'C 's without Restrictions
(MMKO.e)
Mix
m^h-an p
) ear
HA I -linked
Linear trend
li. \ l -Unhed
Linear trend
2025
1
1
1
1
2026
1
2
1
2
2027
1
2
1
2
2028
10
11
8
8
2029
11
12
9
9
2030
14
15
11
11
203 1
20
21
20
21
2032
29
29
28
29
2033
33
34
31
32
2034
31
31
29
30
2035
32
32
30
30
2036
39
40
39
40
2037
40
38
39
37
2038
40
40
40
39
2039
41
41
40
41
2040
41
43
40
42
2041
44
48
49
53
151
-------
2042
44
49
49
55
2043
44
51
50
57
2044
44
53
49
58
2045
44
54
48
59
2046
45
57
52
64
2047
45
58
52
65
2048
45
60
53
67
2049
46
61
53
69
2050
46
63
53
71
Total1
829
945
874
989
1 Totals may not sum due to independent rounding.
Table D-6: Annual HFC Emissions from Imported Products under the Technology Transitions
Rule
Aniiiiiil Emissions from Products Imported with lll'C's (MMT('();c)
CW l> l imits
C ompliiince I'iitli
Mix
1 li»h-(;\\ I*
M
i\
1 li«h-(;\\ P
liAl -
Lineiir
ISA ( -
1. incur
liAl -
1. incur
ISA I -
l.ineiir
^ Oil 1"
linked
trend
linked
trend
linked
trend
linked
trend
2025
1
1
1
1
1
1
1
1
2026
1
2
1
2
1
1
1
1
2027
1
2
1
2
1
1
1
1
2028
10
11
8
8
10
10
7
8
2029
11
12
9
9
11
11
8
8
2030
14
15
11
11
14
14
10
11
203 1
20
21
20
21
20
20
19
20
2032
29
29
28
29
28
28
27
28
2033
33
34
31
32
32
33
31
31
2034
31
31
29
30
31
30
29
29
2035
31
31
28
29
30
30
28
28
2036
39
39
38
38
38
38
37
37
2037
30
28
33
31
29
27
33
30
2038
31
30
34
33
30
28
33
31
2039
30
29
33
33
29
28
32
31
2040
18
19
18
19
16
15
15
15
2041
17
19
22
25
13
15
19
20
2042
17
20
23
26
13
15
19
21
2043
17
21
24
28
14
16
20
22
2044
17
22
23
27
14
17
19
22
2045
17
22
22
27
13
17
18
21
2046
18
24
25
31
14
18
21
25
2047
18
24
26
31
15
19
22
25
152
-------
2048
18
25
26
32
15
19
22
25
2049
18
26
26
33
15
20
22
26
2050
15
23
16
24
11
17
10
16
Total1
503
558
556
609
457
487
504
530
1 Totals may not sum due to independent rounding.
Table D-7: Annual HFC Emission Reductions from Imported Products under the Technology
Transitions Rule
. iiiiiiidl Emission Reductions from Products Imported with I/l'Cs (MM IX ():c)
-------
As discussed in section D.2.7 of this Annex, costs can be estimated under the Compliance Path
abatement options. We stressed in the discussion above that these costs are not necessarily those
that would be experienced by the U.S. economy. Furthermore, as this is a scoping analysis and
the Allocation Framework RIA, the 2024 Allocation Rule RIA, and the proposed Technology
Transitions Rule RIA addendum are considered whole market analyses, accounting for the
transition in both domestically produced and imported products, these costs are not considered
additive to the costs of those rules.
Table D-8: Annual Costs from Reductions in HFCs Imported in Products under the Compliance
Path Scenarios
. \nniial Costs from Reductions of lll'C in Imported Products, Compliance Path
Scenarios (S2020 millions)
Mix
lh\'h-(,IIV
) ear
n 11 -linked
Linear trend
li 11 -linhed
Linear trend
2025
200
193
306
298
2026
199
204
304
314
2027
198
214
303
329
2028
197
225
301
345
2029
196
235
300
361
2030
197
246
302
376
203 1
198
257
304
392
2032
200
267
306
407
2033
201
278
307
423
2034
202
288
309
439
2035
202
299
310
454
2036
203
309
310
470
2037
204
320
313
486
2038
206
330
315
501
2039
208
341
318
517
2040
210
352
321
533
2041
211
362
323
548
2042
213
373
326
564
2043
215
383
329
579
2044
217
394
332
595
2045
219
404
335
611
2046
220
415
337
626
2047
222
425
340
642
2048
224
436
343
658
2049
226
446
345
673
154
-------
2050
227
457
348
689
Emissions by gas were analyzed to estimate social benefits from the above emission reductions.
The sum of the monetized benefits from all of the regulated HFCs from each year and scenario
are shown in Table E-9. When the benefits are discounted to 2022 using a discount rate of 3
percent, the present value of the benefits of this provision from 2025-2050 are estimated to range
from $18 to $24.8 billion in 2020 dollars. This is equivalent to an annual benefit ranging from
$1.1 to $1.5 billion per year over that time frame. As with the costs discussed above, these
climate benefits are not considered additional to the Allocation Rules or the proposed
Technology Transition Rule.
Table D-9: Social Cost of HFC Emission Reductions for the 2025-2050 Timeframe from
Imported Products under the Technology Transitions Rule (3% discount rate) (billions of 2020$,
discounted to 2022)a'b'c
) ear
/. n. 11 -
linked
(lh\'h
(HIP)
aup
Limits
2 n 11 -
linked (High
am*)'
C ompliance
Path
C limate
H 11 -
linked
(Mix)
(/IIP
Limits
Hen efirs (3"„ /
4. H 11 -
linked (Mix)
C ompliance
Path
)/{)' by Scenai
5. Linear
Trend
(Uii-h
(ill P)
(/II P
Limits
•in (Million 2020S)
(>. Linear
Trend (High
(illP)
( ompliance
Path
Linear
Trend
(Mix)
(HIP
Limits
-------
2044
2.9
3.3
3
3.3
2.9
3.3
3.5
3.9
2045
3
3.4
3.1
3.4
3
3.4
3.7
4.1
2046
3.1
3.5
3.2
3.5
3.1
3.5
3.8
4.3
2047
3.2
3.6
3.2
3.5
3.2
3.6
4
4.5
2048
3.3
3.6
3.3
3.6
3.3
3.6
4.2
4.7
2049
3.4
3.7
3.4
3.7
3.4
3.7
4.4
5
2050
4.9
5.4
4
4.4
4.9
6.6
5.1
5.7
PV
19.7
20.3
18.5
20.4
18
20.8
21.8
24.8
EAV
1.2
1.2
1.1
1.2
1.1
1.3
1.3
1.5
aThe annualized present value of costs and benefits are calculated as if they occur over a 26-year period
from 2025 to 2050.
b Climate benefits are based on changes in HFC emissions and are calculated using four different estimates
of the SC-HFCs (model average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th percentile at 3 percent
discount rate). For purposes of this table, we show the effects associated with the model average at a 3 percent
discount rate, but the Agency does not have a single central SC-HFC point estimate. We emphasize the importance
and value of considering the benefits calculated using all four SC-HFC estimates. As discussed in Chapter 4, a
consideration of climate effects calculated using discount rates below 3 percent, including 2 percent and lower, is
also warranted when discounting intergenerational impacts.
0 These estimates are year-specific estimates.
D.5 Discussion
D.5.1 Summary
In addition to providing a level playing field for domestic manufacturers, restrictions on
imported products consistent with the proposed Technology Transitions Rule would reduce the
supply of HFCs in products, reduce emissions occurring in the United States, and help achieve
the climate benefits calculated in the Allocation Framework Rule and the proposed Technology
Transitions Rule.
The supply of HFCs in imported products is growing and without applying restrictions this
growth would likely continue at the same time that the United States is phasing down bulk
consumption. The amount contained in imported products, compared to the bulk supply, could
become more significant as the phasedown of bulk HFC consumption continues. The projections
shown above indicate the supply of HFCs in imported products are approximately 38 to 50
MMTCChe currently, or equal to about 14% to 19% compared to the allowable consumption in
2022, assuming a baseline of approximately 300 MMTEVe. Under the scenarios analyzed,
growth in imported products could be significant, at the same time that the consumption of bulk
HFCs will be phased down. For instance, in 2029, the amount in imports could be 49% to 65%
156
-------
compared to allowable bulk consumption of approximately 90 MMTEVe. Under one scenario
the growth in imported products would exceed the 2034 allowable bulk consumption, and by
2036 all four projections would exceed bulk consumption.
Although restricting the HFCs allowed in imported products is not expected to eliminate that
supply of HFCs, it would curtail it. For several products, lower-GWP HFCs could replace the
high-GWP HFCs currently used. For others, non-fluorinated alternative substances could be
used. We analyzed two possible ways in which importers could comply with the restrictions.
Because emissions lag consumption, the full scope of emission reductions would not be seen
immediately. Emission reductions from aerosols (1-year lifetime) would start in 2026 while most
other products would show emission reductions in the mid-2030's to early-2040's (10- to 16-
year lifetimes). Finally, emission reductions from polyurethane foam products (25-year lifetime)
would not be seen until 2050. In 2050, the annual emissions of HFCs reduced from imported
products range from 31 to 55 MMTCChe, and total emission reductions from 2025, when the
Technology Transitions Rule proposed restrictions take effect, range from 318 to 459
MMTC02e.
As shown above, the emission reductions provide significant climate benefits. Using the social
cost of HFCs methodology from the Allocation Framework Rule, we calculate the climate
benefits. When the benefits are discounted to 2022 using a discount rate of 3 percent, the present
value of the benefits of this provision from 2025-2050 are estimated to range from $18 to $24.8
billion in 2020 dollars. This is equivalent to an annual benefit ranging from $1.1 to $1.5 billion
per year over that time frame
D. 5.2 Leakage and Market Spillover
The concept of leakage is an uncertainty that is important to consider. See for instance the
discussion in section 4.3 of Appendix B of the Allocation Framework RIA. Under the proposed
Technology Transitions Rule, restrictions are placed on products imported with HFCs. The
scoping analysis in this Annex quantifies the possible trends in future imports of such products
both with and without the proposed rule in effect. The reductions in the supply of HFCs
contained in imported products as well as the emissions from those products is estimated under
several scenarios.
157
-------
Leakage could occur if by these restrictions the HFCs that would have been used in such
products are instead used in other sectors, including the same products destined for markets other
than the United States or other countries with similar restrictions. For instance, if a factory in
another country currently manufactures air conditioners using R-410A and based on this
proposed rule such products are restricted, that manufacturer could still sell those R-410A air
conditioners to other customers outside the United States. Likewise, the manufacturer could
choose to run the production line for a certain amount of time using a refrigerant that is allowed
under the proposed rule, and sell those products into the U.S. market, while running the
production line the remaining time using R-410A and selling those products elsewhere.
We do not have the information to know exactly how foreign manufacturers would respond to
the restrictions proposed in this rule. Most, we expect, would still want to profit by selling
products to the United States, and would modify their products to be acceptable under this
proposed rule. Whether such production would consume the total capacity of a given production
line is unknown. However, it does not seem likely that the amount of product sold to other
markets would increase solely due to this rule. If there were such a demand for those products,
presumably the manufacturer would have already responded by increasing production capacity,
for instance by adding night shifts or building another production line. Future changes in demand
are hard to predict, but the socio-economic factors that would increase (or decrease) the demand
for HFC-containing products is not likely to be directly affected by this proposed rule.
We did not analyze in detail the countries from which imported products come; however, it is
clear that there are a few major trading countries or regions to consider, including, for instance,
Canada, China, the European Union, Japan, and Mexico. All of these countries are parties to the
Kigali Amendment to the Montreal Protocol, meaning they must reduce their own consumption
of HFCs, including the HFCs they place in products exported to the United States or elsewhere.
Hence, by requiring those products shipped to the United States to use lower-GWP substances,
this proposed rule could provide some extra room under their individual HFC consumption
limits. It may be the case that this extra room, if it does exist, could make HFCs less expensive
and available to more customers in those countries. To the extent that such reactions cause an
increase in the use and emissions of HFCs in those countries, there would be effects to the
United States, as emissions of greenhouses anywhere affects the entire world.
158
-------
That said, given the Kigali Amendment reduces the allowed HFC consumption, and does so in a
fairly quick timeframe, we would expect such a phenomenon to be short-lived, if it does arise at
all. For instance, Canada, the EU, and Japan must reduce HFC consumption to 15% of their
respective baselines by 2036, and China and Mexico must reduce HFC consumption to 20% of
their baselines by 2045.55 Furthermore, in some countries, exports are restricted. For instance,
Canada restricts the use of high-GWP HFCs in some product types addressed by this rule, and
these bans apply to both domestically-produced equipment and products exported to any other
country. In the EU and Canada, GWP limits are placed on certain products and manufacturers
would have to expend allowances to make HFC-containing products, irrespective of the market
for which they are destined.
The proposed rule could also have market spillover effects. While the restrictions are affecting
products containing HFCs imported to the United States, the size of the U.S. market is quite
large and is likely to have a spillover effect on other markets. For instance, using the R-410A air
conditioner example above, a manufacturer may decide to change its entire production line to a
lower-GWP substitute compliant with the U.S. proposed rule. The portion of that manufacturer's
products sold outside the United States would lead to lower GHG emissions in other countries,
which would be a societal benefit to all countries.
55 Internal EU regulations also establish a phasedown of HFC consumption; however, they will not ensure compliance with the
Kigali Amendment notably beyond 2030 (see https://eur-lex.europa.eu/resource.html?uri=cellar:ecf2b875-b59f-llec-b6f4-
01 cm 75ed71 al. POOL 02/DQC l&format=PDF).
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Annex E: Supplemental Approach for Environmental
Justice Analysis
Background
As described in Chapter 8 "Environmental Justice Analysis" of this RIA addendum, EPA seeks
to better quantify the impacts of these rule on vulnerable and burdened communities. In seeking
to reduce disproportionate negative environmental consequences on overburdened communities,
and in our efforts to "conduct the highest quality analysis feasible,"56 EPA is considering the use
of additional analytical tools to understand burdens facing communities.
Section 8.4 "Aggregate Average Characteristics of Communities Near Potentially Affected
Production Facilities" provides an analysis of the environmental justice aspects of this proposed
rule by discussing the characteristics of Census block groups near the nine identified facilities, as
described by the American Community Survey (ACS).
In this supplemental analysis, EPA is providing a demonstration of analysis using a statistical
technique called "microsimulation" to assess these communities in more detail. EPA is seeking
comment on the use of microsimulation analyses generally for future application to
environmental justice analyses.
Microsimulation techniques have been used for various analyses for decades. By combining data
from different surveys with geospatial information, microsimulation provides analytical utility
beyond that possible with the respective individual datasets, surveys, and maps. Increases in
computing power and the advances in software development have made microsimulation
approaches faster and more flexible.57 Data science has advanced to allow for the identification
of populations with multiple characteristics - for the case of environmental justice analysis, for
example, it is possible to identify communities facing multiple burdens and multiple
vulnerabilities.
56 EPA. Technical Guidance for Assessing Environmental Justice in Regulatory Analysis. 2016. Available at:
https://www.epa.gov/environmentaljustice/technical-guidance-assessing-environmental-justice-regulatory-analysis.
57 Lovelace, R., Dumont, M., 2016. Spatial microsimulation with R. CRC Press.
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The technique employed for this demonstration analysis was used originally by the National
Institutes of Health for the National Infectious Disease Study.58 The method involves using
statistics to combine two databases59 to create a population of anonymous "synthetic
households." Using the 2010 decennial census, the 2007 - 2011 ACS, and a very fine-scale
model of the geographic density of U.S. population,60 analysts can generate a "synthetic
population" of approximately 116 million households. The synthetic households are assigned
demographic characteristics according to the population characteristics of their respective Census
block group. This microsimulation has additional analytical capability because each of the
simulated households are mapped to a 90x90 meter grid of actual physical locations of
residences in 2010. In other words, maps using this dataset can show dots on a map representing
every known residence in 2010 with an accuracy of 45 meters. (Maps presented in Figures F-l
through F-14 show distributions of household locations near the facilities of interest - the points
are accurate for residences in 2010 within the dimensions of the printed dots). The techniques
employed are reproducible using current data, which while beyond the scope of current efforts,
would offer much more detailed proximity analysis of communities near specific facilities.
The dataset used for this supplementary analysis is publicly available.61 Because it is not up to
date, EPA does not represent information in this appendix to be descriptive of current
demographic features of communities near the facilities potentially affected by the proposed rule,
but rather as a potential tool to identify locations that may merit additional consideration due to
population patterns in the recent past. EPA is investigating the utility of microsimulation for
environmental justice analysis of atmospheric pollution by combining various geospatial
information with the demographic specificity and large sample size of the ACS.
In addition to the synthetic dataset mentioned above, EPA is exploring novel methods to
combine the spatial and socio-demographic information of the ACS with estimates of household
characteristics from smaller surveys. Whereas the previous method provides a precise location
estimate, the novel method provides greater detail on household characteristics. Example surveys
58 Wheaton WD, Cajka JC, Chasteen BM, Wagener D, Cooley PC, Ganapathi L, et al. Synthesized population databases: a US
geospatial database for agent-based models. Research Triangle Park, NC: RTI Press; 2009.
59 Wheaton, W.D. (May 2014) 2010 U.S. Synthetic Population Ver. 1. RTI International.
60ICLUSE Tools and Datasets (VI.3 and 1.3.1) U.S. EPA. ICLUS Tools andDatasets (Version 1.3 & 1.3.1). U.S. Environmental
Protection Agency, Washington, DC, EPA/600/R-09/143F, 2010. Current and previous version available at
https://www.epa.gov/gcx/about-iclus.
61 The dataset is available on request from https://www.rti.org/synthpop-synthetic-population-data-analysis. The Synthpop
viewer is accessible at https://synthpopviewer.rti.org/.
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include the Consumer Expenditure Survey, the EIA Residential Energy Consumption Survey, the
American Housing Survey, and the National Household Transportation Survey. While these
surveys provide useful analytical insight that can inform environmental justice analysis, they are
smaller surveys compiled of responses from fewer individuals and they are not as spatially
disaggregated as the ACS. Using microsimulation approaches to combine the ACS with other
surveys can allow analysis of synthetic populations at finer geographic scale that statistically
represent the detail of the smaller, specialized surveys.
Many different surveys and datasets can be incorporated within microsimulation. Existing
microsimulation models featuring different datasets provide insight into healthcare availability
and inform tax policy.62 Potential uses of microsimulation by EPA includes identification of
communities facing burdens ranging from proximity to manufacturing facilities, environmental
hazards such as air quality, and other vulnerabilities including poverty, natural hazard risk, food
insecurity, energy insecurity, and inadequate access to medical care. By combining data from
surveys, it is likely to be possible in the future, for example, to characterize the demographics of
communities not just by their residents, but also considering locations where individuals are
likely to work and go to school. It may be that residents of a community, for example, do not live
close to specific hazardous facilities, but many work in areas with such facilities. Additionally,
by combining data from surveys on employment and jobs, future microsimulation analysis may
be able to identify communities at risk of adverse economic impacts both of environmental
hazards and, potentially, the unintended impacts of different kinds of policies.
In the past, the approach to analyzing environmental justice for many atmospheric emissions
rules has typically been conducted at higher levels of geographic aggregation. With advances in
data availability, data science, and computational power, more local detail may be available for
actions with regional or national environmental implications. While the utility of
microsimulations may be limited by the statistical representation represented by the sample size
of the datasets used, the ability to combine different surveys to address novel questions may help
identify communities facing multiple, cumulative burdens. This capability may be extremely
important in analyses of proximity exposure to certain risks, such as toxics or HAPs in which the
atmospheric concentration of a pollutant is important. Of course, these methodologies can apply
62 Including: Cronin, Julie-Anne. 1999. U.S. Treasury Distributional Analysis Methodology. OTA Paper 85. Washington, DC:
U.S. Department of the Treasury.
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to other wide-scale risks with locally vulnerable populations (e.g., clean water, wildfire, and
flooding63).
The method used in this supplementary analysis has been used by EPA before, in the context of
analysis by the Office of Water. In 2011, EPA was able to identify households potentially
affected by leaking underground storage tanks.64 The method identified, with a high degree of
statistical likelihood, the number of households using well water potentially affected within the
probably plume of contaminants from known underground storage tanks. In addition to
estimating the number of affected households, the technique estimated the number of households
with certain characteristics relevant to environmental justice, including the number of affected
vulnerable households, and the number of households with young children.
It is important to note, however, that while the microsimulation methods described in this
analysis provide more refined measures of the number of households nearby a facility, evaluating
the characteristics of these households relies on a strong assumption that key demographics are
uniformly distributed across the number of households in a census block group and, therefore,
uniformly distributed within the resulting simulated population. Evaluating exposure and risk
using the simulated population across dimensions such as race, ethnicity, and income would, by
necessity, assume that these groups are no more or less likely to live in households on the fence
line side of a block group than they are to live on the opposite side of that same block group.
Comparing Microsimulation and the ACS/AirToxScreen Analyses
The Allocation Framework RIA and Chapter 8 of this RIA addendum use the ACS to estimate
the percentage of communities that identify as members of specific races/ethnicities and to
provide information on income. However, these analyses are based on the "average"
characteristics of Census block groups within a specific distance from identified facilities. The
analyses include Total Cancer Risk data and Total Respiratory Risk data as reported in the
AirToxScreen data as well, and these are also based on the "average" risk characteristics across
these Census tracts.
63 Brouwers, L. 2005. "Microsimulation Models for Disaster Policy Making." Stockholm University.
64 "Risk Analysis to Support Potential Revisions to Underground Storage Tank (UST) Regulations" prepared by RTI
International, December 22,2010.
163
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Because the demographic characteristics and the risk quantifications are averaged across the
geographic area of the Census blocks groups, the ACS and AirToxScreen data cannot identify
the distribution of household locations within the boundaries of the block groups. The Census
Bureau data divides communities into separate geographic areas called blocks, and the ACS
reports data for "block groups" each with populations of a few thousand individuals.65 While
urban Census block groups may be relatively small geographically, more rural blocks may
represent many square miles. Consider, for example, a case in which a specific facility is located
near one boundary of its Census block, but the actual residences of households within the block
are clustered in a town that is miles from the facility. In a case like this, the ACS/AirToxScreen
analysis may overstate the actual risks to nearby residents. Conversely, a community may be "at
the fence line" of a facility, and these specific households may face higher risks than the
averages that are estimated across the Census block group.
As stated above, EPA used the publicly available version of the dataset for this analysis, The
dataset allows for detailed maps to be created, showing the (2010) location of households within
as mapped to a 90x90 meter grid, and it can assign each household with statistically likely racial,
income, age, and education characteristics based on the probabilities of these characteristics as
reported for their respective Census block in the ACS.
This analysis shows that there are circumstances in which the use of this specific
microsimulation tool can show differences in the number of households estimated to be close to
a specific facility. In cases for which the 2010 individual households are distributed very
differently from the average population density for their respective Census block groups (for
example, a town in a relatively rural block group), the tool can show that the ACS/AirToxScreen
average calculations are likely to either overstate or understate proximity of populations to the
facility. These cases appear to involve geographically large Census block groups. The
differences appear most dramatic in the one-mile radius analyses - differences between the
Census block group averages and the household location analyses are reduced as the distance
from the facility increases.
65 See https://www2.census.gov/geo/pdfs/reference/GAKMyChllGAKM.
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Comparison of Demographic Analysis for Each Identified Facility
Following the approach taken in Chapter 8, this analysis assesses the communities within 1-, 3-,
5-, and 10-mile distances of each of the nine affected facilities. For each community, the
technique identifies modeled "actual" locations of households Household locations are modeled
using the ICLUS database based on the location of actual residences identified by the 2010
Census, anonymized, and assigned to a grid of 90x90 meter squares, based on actual residences
in the 2010 Census. We report the number of households identified in this manner within 1-, 3-,
5-, and 10-miles distances of each facility, and offer tables comparing the results of the
microsimulation analysis with the estimates calculated using the ACS data.
This supplemental analysis then, will have different results in cases where a concentration of
households - in a town for example - may be within the proximity buffers. For each facility, we
present a map showing the communities surrounding the site. The maps show concentric circles
centered on the facility location representing the 1-, 3-, 5-, and 10-mile distances used for
analysis. The modeled household locations using the 2010 synthetic population are presented as
dark grey dots. The dots do not represent current household locations: they merely show
locations of residences in 2010 as determined by Census, ACS, and population density modeling.
While some residential structures may have changed use since 2010, many locations that were
household residences in 2010 are likely to be locations of current households. These recent
residential patterns may help identify communities where more detailed assessments may be
helpful to address environmental justice issues in these communities.
In the data table accompanying each map, each column represents the analysis for the
communities within the specified distance of the facility. The number in bold is our calculation
using the current ACS as presented in Chapter 8. The simulated population numbers based on the
modeled households for 2010 are presented for comparison in (italics). While potentially helpful
for presenting patterns of recent residential locations as a way of identifying communities of
concern, the specific numbers are out of date. The percentages of population by race or by
relative income, for example, can change rapidly in some communities. In many cases, estimates
of the percentage of people living below the federal poverty line, and separately, the percentage
living below 50 percent of the poverty line, are different from the assessments of the current
ACS.
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One example of how the analysis of modeled 2010 household locations differs from that using
the current ACS is the community near the Chemours Corpus Christi Facility, located near
Gregory, Texas. To understand differences between the microsimulation tool based on modeled
2010 household locations and the ACS analysis for this facility, we present two maps. In Figure
F-l(a), the modeled 2010 simulated household locations are represented. The facility is at the
center of the "bull's eye" of the 1-, 3-, 5-, and 10-mile distance. The dots are the modeled
locations of households in 2010 within the 90x90 meter squares of the population density model.
Within the one-mile circle, there are a very small number of dots representing residences in
2010. The microsimulation result shows that there were just 3 households within the one-mile
radius circle.
Figure F-l(b) is a map of the same location showing the boundaries of the relevant ACS Census
block groups. (This map is from ArcGIS Hub.66) The colored polygons in the map are individual
Census block groups mapped from the ACS. The facility is located in the large, medium shaded,
block group bounded on the south by Corpus Christi Bay, extending west off the map, with
northern boundary the diagonal line running from Taft southeast to Gregory and then to the
northeastern corner near Ingleside. (This is block group as 484090107002, showing a 2019
population of 3,220, and a population density of 38.4 per square mile. In 2010, the population
was 2666, with a population density of 3 1.8). Comparing the maps, one notes that the dots
representing the locations of residences in 2010 were clustered to the west side of this region, in
Portland, and to the east, near Ingleside. The facility is near the center of the rectangle. In 2010
the area was a large industrial area with essentially no residences. Analysis at the level of the
block group, as done in Chapter 8 and in many other demographic studies using survey data,
geometrically calculates the area at a given distance from the given coordinates (in this case, of
the Chemours facility) and assumes that the population of the block group is distributed evenly.
In this case, the one-mile circle represents a fraction of the area of the block group, and with a
population density of 38.4 per square mile, that calculation yields an estimate of 120 people
living within one mile of the site. Since the AirToxScreen database associates risk disaggregated
to the Census tract level, the risk is assumed to be constant across the area of the polygon. Note
66 ArcGIS Hub data referenced for GEOID 484090107002 https://hub.arcgis.com/datasets/TEA-Texas::census-block-group-
map/explore ? location =27.906983%2C-97.233085%2C11.43.
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in Table F-l, the discrepancy between the bold numbers estimated using the previous ACS
methodology, and the (italicized) numbers from the 2010 microsimulation.
In this case, household location model suggests that the ACS Census block group average
approach overestimates the number of individuals living within the one-mile distance. EPA is not
modeling the transport nor does the Agency have sufficient information on emissions to measure
the health impacts at specific distances, but the modeling shows that, as of 2010, fewer
households were likely within a one-mile radius of the facility than are estimated using the
averaging method.
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Chemours Corpus Christi - Gregory, TX
Figure F- 1(a) Chemours Corpus Christi: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
@ Identified Facility
+ Adjacent Facilities
• Modeled Households
' ' County lines
I—i—i—i—I—i—i—i—i
0 2 4 8 Miles
Figure
Portland, and Ingleside
F-l(b). San Patricio and Aransas Counties, IX. showing Gregory,
rpus
irlsti
yr
j.
-------
T;ihlc I'-1 (\'iiip;iiisnn AC'S Census Block ;nnJ iy>/<> Si nilh iii //"Hm'/m/i/v ("licnmiii\ Corpus (liristi
II illiiii I mile
oj production
Jucilily
II illiiii miles
"J production
Jucility
II illiiii 5 mill's
oj production
facility
II ithin 10
mill's
oj production
/ticilily
% White (race)
95 (100)
91 (91.9)
92 (91.0)
91 (91.0)
% Black or African
American (race)
1.6 (0)
2.3 (2.5)
2.2 (1.9)
2.1 (2.2)
% Other (race)
3.6 (0)
6.3 (5.6)
6.2 (7.1)
7.1 (6.8)
% Below Poverty Line
1.4 (0)
4.1 (7.3)
3.4 (7.4)
6.0 (9.4)
% Below Half the
Poverty Line
1 (0)
2.8 (3.3)
3.7 (4.1)
4.9 (4.1)
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Chemours El Dorado - El Dorado AR
Figure F-2. Chemours EI Dorado: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
Table F-2. Comparison ACS Census Block and (2010 Synthetic Households): Chemours El Dorado
Within 1 mile
ofproduction
facility
Within 3 miles
Within 5 miles
Within 10
ofproduction
facility
ofproduction
facility
miles
ofproduction
facility
% White (race)
94 (92.7)
94 (96.8)
82 (93.9)
62 (62.1)
% Black or African
American (race)
1.4 (4.9)
1.4 (2.9)
15 (4.5)
35 (36.4)
% Other (race)
4.7 (2.4)
4.7 (0.3)
2.9 (1.6)
3.4 (1.5)
% Below Poverty Line
8.0 (9.8)
8.0 (6.4)
11 (5.6)
13 (15.0)
% Below Half the
Poverty Line
5.2 (0)
5.2 (1.9)
4.2 (2.3)
7.7 (8.0)
170
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@ Identified Facility
+ Adjacent Facilities
• Modeled Households
County lines
Honeywell Geismar Complex - Geismar, LA
The Honeywell Geismar Complex, in Ascension Parish, LA, near the border with Iberville
Parish, is one of three facilities EPA has analyzed in connection with the AIM Act, the other two
being the Mexichem Flour Plant to the west in San Gabriel, Iberville, and the Air Products
facility to the west in Geismar. The overlapping concentric rings of the analyses are shown in
Figure F-3. The 2010 synthetic household analysis shows no residences within one mile of the
Honeywell Complex, as indicated in the comparison between the ACS calculations and the 2010
household model in the first column of Table F-3.
Figure F-3. Honeywell Geismar Complex: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
i—i—i—i—i—i—'—i—i
0 2 4 8 Miles
Table F-3. Comparison ACS Census Block and (2010 Synthetic Households): Honeywell Geismar
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
ofproduction
ofproduction
ofproduction
ofproduction
facility
facility
facility
facility
% White (race) 57 ^ 63 (52.8) 62 (62.8) 66 (69.8)
% Black or African
American (race)
38 (n/a)
34 (33.4)
36 (33.4)
27 (26.6)
% Other (race)
5.4 (n/a)
2.5 (3.9)
3.0 (3.9)
7,1 (3.6)
% Below Poverty Line
2.3 (n/a)
2.5 (10.6)
2.8 (8,1)
5.7 (6.2)
% Below Half the
Poverty Line
7.2 (n/a)
5.0 (4.7)
5.5 (4.9)
4.9 (3.8)
171
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@ Identified Facility
+ Adjacent Facilities
• Modeled Households
County lines
Aero press Corporation San Dimas - San Dimas, CA
Figure F-4, Aeropress San Dimas: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
i—i—i—i—i—i—i—i—i
0 2 4 8 Miles
Table F-4. Comparison ACS Census Block and {2010 Synthetic Households): Aeropress San Dimas
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
of production
ofproduction
ofproduction
of production
facility
facility
facility
facility
% White (race)
73 (71.3)
65 (73.8)
58 (67.1)
49 (56.4)
% Black or African
American (race)
2.1 (4.1)
3.0 (4.1)
3.9 (5.5)
3.6 (4.9)
% Other (race)
25 (24.2)
32 (22.1)
39 (27.4)
47 (38.7)
% Below Poverty Line
3.5 (7.1)
4.8 (8.0)
6.0 (10.0)
6.5 (11.0)
% Below Half the
Poverty Line
5.6 (3.7)
4.1 (3.1)
5.0 (3.4)
4.6 (3.7)
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CF Industries Holdings Inc. Port Neal Nitrogen Complex - Sergeant Bluff, IA
The Sergeant Bluff facility is on the Nebraska border with western Iowa. There were no
households modeled in the 2010 population density data within a one-mile radius of the facility,
and no synthetic households represented on the map in Figure F-5. The ACS analysis of the area,
as indicated of the first column of Table F-5, shows the figures in bold for the "average" of the
block groups, compared to the microsimulation result for the 2010 synthetic households shown
as (n/a) because the calculation is not applicable.
Figure F-5. CF Industries Holdings Port Neal: Modeled Household Locations {in 2010) within 1, 3, 5, 10 miles
© Identified Facility
+ Adjacent Facilities
Modeled Households
County lines
i—l—r-
4
8 Miles
Within 1 mile
ofproduction
facility
With in 3 miles
ofproduction
facility
Within 5 miles
ofproduction
facility
Within 10 miles
of production
facility
% White (race)
94 (n/a)
90 (100)
79 (99.4)
79 (87.7)
% Black or African
American (race)
0.13 (n/a)
0.07 (0)
0.25 (0)
3.0 (2.4)
% Other (race)
5.7 (h/a)
9.9 (0)
20 (0.50)
18 (9.8)
% Below Poverty Line
3.0 (n/a)
4.9 (4.2)
6.4 (3.0)
6.0 (11.2)
% Below Half the
Poverty Line
1.5 (n/a)
2.9 (0)
4.3 (0.50)
6.6 (3.5)
173
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@ Identified Facility
+ Adjacent Facilities
Modeled Households
County lines
Linde, Inc. Whiting - East Chicago, IN
Figure F-6. Linde Inc. Whiting: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
i—"—"—i—i—i—i—i—i
0 2 4 8 Miles
Table F-6. Comparison ACS Census Block and (2010 Synthetic Households): Linde Inc. Whiting
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
ofproduction
ofproduction
ofproduction
ofproduction
facility
facility
facility
facility
% White (race) 23 (20.1) 35 (38.5) 46 (50.0) 33 (41.3)
% Black or African
American (race)
35 (48.1)
29 (33.9)
32 (31.1)
57 (49.3)
% Other (race)
43 (31.1)
36 (27.5)
22 (18.8)
11 (9.4)
% Below Poverty Line
17 (28.7)
14 (30.5)
12 (22.5)
11 (20.2)
% Below Half the
Poverty Line
13 (13.0)
13 (14.2)
11 (10.0)
10 (9.2)
174
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Air Products and Chemicals, Inc. Geismar - Geisinar, LA
© Identified Facility
+ Adjacent Facilities
• Modeled Households
CD County lines
The Air Products and Chemicals SMR Facility in Ascension Parish is another of three facilities
EPA has analyzed in these communities in connection with the AIM Act. The Honeywell
Geismar Complex, also in Geismar, and the Mexichem Flour facility to the west in San Gabriel
are the other two. The overlapping concentric rings of the analyses are shown in Figure F-7. The
2010 synthetic household analysis shows a community within the 1 mile radius the facility. A
small number of households appear to be within the 3 mile radius of the Air Products and
Chemicals Facility and within 5 miles of the Ftoneywell Complex.
Figure F-7. Air Products and Chemicals: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
i—i—i—i—i—'—i—i—i
0 2 4 8 Miles
Table F-7. Comparison ACS Census Block and (2010 Synthetic Households): Air Products Geismar
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
ofproduction
of production
ofproduction
ofproduction
facility
facility
facility
facility
% White (race) 63 {BM) 70 (60.8) 56 (57.5) 68 (71.4)
% Black or African
American (race)
30 (28.0)
26 (36.5)
39 (39.0)
27 (25.8)
% Other (race)
6.6 (0)
4.0 (2.7)
5.3 (3.5)
5.7 (2.7)
% Below Poverty Line
2.2 (8.0)
3.8 (12.2)
6.3 (12.4)
5.3 (11.5)
% Below Half the
Poverty Line
6.5 (0)
5.3 (3.5)
8.3 (4.9)
5.4 (4.3)
175
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Haltermann Carless Inc. - Manvel, TX
Figure F-8. HCManvel: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
@ Identified Facility
+ Adjacent Facilities
¦ Modeled Households
I I County lines
~i—i—i—<—i—i
4 8 Miles
Table F-8. Comparison ACS Census Block and (2010 Synthetic Households) : HC Manvel
Within 1 mile
of production
facility
Within 3 miles
ofproduction
facility
Within 5 miles
of production
facility
Within 10 miles
ofproduction
facility
% White (race)
88 (91.1)
83 (91.7)
70 (86.4)
64 (72.9)
% Black or African
American (race)
4.9 (028)
8.4 (1.2)
17 (3.1)
19 (13.5)
% Other (race)
6.7 (8.5)
9.0 (7.1)
12 (10.5)
18 (13.6)
% Below Poverty Line
4.6 (6.6)
4.5 (8.8)
5.1 (13.9)
3.5 (8.0)
% Below Half the
Poverty Line
1.9 (2.7)
2.4 (3.0)
3.7 (5.5)
3.0 (3.1)
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Air Products and Chemicals Inc Port Arthur Facility - Port Arthur, TX
Air Products and Chemicals' Port Arthur facility is very near the eastern Texas border with
Louisiana. The Census block groups closest to the plant are very diverse. To the south and west,
extends group 48245011600. It is very large (nearly 400 square miles) extending off the map in
Figure F-9. It is predominantly open space including wildlife management areas, state parks, oil
fields, and the Texas Point National Wildlife Refuge. The population density is 2.6 per square
mile, mainly in communities near Winnie and Stowell that are some 20 miles west of the facility.
Approximately 95 percent of the population of this block group identifies as White. In the Port
Arthur communities immediately east of the center the map, there are Census Block Groups
482450051002, 482450059002, and 482450059001. These are much smaller, denser, and
between 90 and 99 percent Black or African American.
Figure F-9. Air Products and Chemicals Port Arthur: Modeled Household Locations (in 2010) within 1, 3, 5, 10
miles
Table F-9. Comparison ACS Census Block and (2010 Synthetic Households): APC Port Arthur
Within 1 mile
ofproduction
facility
Within 3 miles
ofproduction
facility
Within 5 miles
ofproduction
facility
Within 10 miles
ofproduction
facility
% White (race)
33 (1.4)
32 (9.7)
51 (39.4)
69 (66.8)
% Black or African
American (race)
61 (98.5)
63 (88.9)
37 (46.1)
22 (22.5)
% Other (race)
6.6 (0)
5.4 (1.4)
12 (14.4)
8.9 (10.7)
% Below Poverty Line
9.5 (51.7)
13 (30.7)
13 (25.2)
8.3 (17.0)
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% Below Half the
Poverty Line
14 (25.6) 14 (12.8) 11 (10.5) 7.4 (6.8)
Table F-10. Comparison ACS Census Block and (2010 Synthetic Households): Diversified KSP Plant
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
ofproduction
ofproduction
ofproduction
ofproduction
facility
facility
facility
facility
® Identified Facility
+ Adjacent Facilities
Modeled Households
County lines
Diversified Gas and Oil Corp. KSP COi Plant - Tad, WV
Figure F-10. Diversified KSP Plant: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
1—1—1—1—1—1—1—1—1
0 2 4 8 Miles
% White (race)
99 di a,
97 (91.8)
96 (94.0)
90 (88.2)
% Black or African
American (race)
0 (n/a)
0.29 (0)
0.96 (0)
6.2 (4.6)
% Other (race)
0.89 (n/a)
2.7 (8.2)
2.9 (5.9)
3.9 (7.2)
% Below Poverty Line
10 j'n/a)
11 (13.1)
11 (12.3)
9.0 (14.7)
% Below Half the
Poverty Line
5.5 (n/a)
7.4 (3.7)
5.9 (3.5)
2A.J5J)
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@ Identified Facility
+ Adjacent Facilities
~ Modeled Households
I I County lines
Linde, Inc. Decatur - Decatur, AL
The Linde Decatur facility is near another facility EPA has analyzed in connection with the AIM
Act. The other is the Daikin America facility to the west of the Linde site. The overlapping
concentric rings of the analyses are shown in Figure I'-l 1. The synthetic household analysis
identified 68 households within 1 mile of the Linde facility in 2010, clustered to the south as
indicated on the map. The 1 mile radii of the two facilities overlap, and there are many
households within 3 miles of both facilities.
Figure F-l I. Linde Decatur: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
i—i—i—'—i—i—i—i—i
0 2 4 8 Miles
Table F-l 1. Comparison ACS Census Block and (2010 Synthetic Households): Linde Decatur
Within 1 mile
Within 3 wiles
Within 5 miles
Within 10 miles
of production
ofproduction
ofproduction
ofproduction
facility
facility
facility
facility
% White (race) 44 j_30.9)_ 60 (46.6) 67 (68.9) 74 (74.8)
% Black or African
American (race)
52 (64.7)
32 (45.9)
23 (24.6)
17 (19.7)
% Other (race)
4.0 (4.4)
8.1 (7.4)
9.5 (6.5)
8.3 (5.4)
% Below Poverty Line
16 (32,4)
13 (23.4)
12 (16.4)
9.5 (15.2)
% Below Half the
Poverty Line
9.0 (16.2)
6.8 (7.5)
6.1 (5.3)
5.5 (4.9)
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CALAMCQ - Stockton, CA
Figure F-12. CALAMCO: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
Table F-12. Comparison ACS Census Block and (2010 Synthetic Households): CALAMCQ
Within 1 mile
ofproduction
facility
Within 3 wiles
of production
facility
Within 5 miles
of production
facility
Within 10 miles
of production
facility
% White (race)
58 (67.0)
54 (57.2)
52 (56.6)
51 (53.4)
% Black or African
American (race)
9.5 (11.3)
9.9 (12.8)
10 (13.0)
9.4 (11.3)
% Other (race)
33 (21.7)
36 (30.0)
38 (30.5)
40 (32.3)
% Below Poverty Line
12 (2 7.1)
11 (19.9)
11 (20.6)
9.9 (17.2)
% Below Half the
Poverty Line
9.9 (6.3)
8.5 (6.9)
8.0 (6.8)
7.0 (5.5)
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Diversified CPC International - Channahon, IL
within 1, 3, 5, 10 miles
@ Identified Facility
+ Adjacent Facilities
• Modeled Households
County lines
i r
4
8 Miles
Table F-13. Comparison ACS Census Block and (20/0 Synthetic Households): Diversified CPC
Within 1 mile
Within 3 miles
Within 5 miles
Within 10 miles
of production
ofproduction
of production
ofproduction
facility
facility
facility
facility
% White (race)
95 (100)
92 (95.5)
86 (95.3)
79 (83.7)
% Black or African
American (race)
0.88 (0)
2.0 (2.2)
7.4 (2.5)
12 (10.3)
% Other (race)
4.2 (0)
6.3 (2.3)
6.4 (2.1)
9.6 (5.9)
% Below Poverty Line
1.0 (12.5)
3.1 (2.2)
3.1 (4.3)
4.7 (8.1)
% Below Half the
Poverty Line
2.6 (0)
1.5 (0.7)
2.6 (1.5)
3.7 (2.9)
Figure F-13. Diversified CPC: Modeled Household Locations (in 2010)
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Aeropress Corporation Sibley - Sibley, LA
Figure F-14. Aeropress Sibley: Modeled Household Locations (in 2010) within 1, 3, 5, 10 miles
Table F-14. Comparison ACS Census Block and (2010 Synthetic Households): Aeropress Sibley
Within 1 mile
ofproduction
facility
Within 3 miles
ofproduction
facility
Within 5 miles
ofproduction
facility
Within 10 miles
ofproduction
facility
% White (race)
71 (46.7)
51 (58.0)
56 (43.5)
64 (62.4)
% Black or African
American (race)
26 (48.7)
47 (39.1)
41 (55.1)
33 (36.2)
% Other (race)
2.7 (4.5)
1.3 (2.9)
2.5 (1.4)
2.5 (1.3)
% Below Poverty Line
11 (14.7)
18 (23.3)
20 (30.2)
18 (21.9)
% Below Half the
Poverty Line
9.8 (2.5)
8.3 (6.9)
7.5 (9.7)
7.7 (7.2)
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Conclusion
Using microsimulation techniques can provide additional analytical information by using
advanced data science and statistics to combine data from different surveys and geospatial
datasets. The dataset used here, with a synthetic population featuring modeled locations of
residences in 2010 combined with information from the 2010 Decennial Census and the ACS can
show statistically representative demographic information for household locations in 2010. We
are not presenting the demographic results as these are considered to be more out-of-date than
the location of residences. The current version of the database used here is not publicly available.
The publicly available data results presented here may, by showing patterns of residence in the
recent past, show communities that merit more environmental justice analysis. In the time
available, EPA is not pursuing additional analysis of communities for this proposed rule. Other
synthetic datasets are available and being developed. These have additional analytic capabilities
and may be useful in identifying overburdened communities.
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