---------------------------------------------------------------------------

    EPA also examined the relationship between the presence of fuel-
saving technologies and negative evaluations of vehicle operating
characteristics, such as performance and noise, in auto reviews and
found that the presence of the technologies was more often correlated
with positive evaluations than negative ones.\192\ Preliminary work
with data from recent purchasers of new vehicles found similar
results.\193\ While these studies cannot prove that the technologies
pose no problems to other vehicle attributes, they suggest that it is
possible to implement the technologies without imposing hidden costs.
---------------------------------------------------------------------------

    \192\ Helfand, G., et al. (2016). ``Searching for Hidden Costs:
A Technology-Based Approach to the Energy Efficiency Gap in Light-
Duty Vehicles.'' Energy Policy 98: 590-606; Huang, H., et al.
(2018). ``Re-Searching for Hidden Costs: Evidence from the Adoption
of Fuel-Saving Technologies in Light-Duty Vehicles.'' Transportation
Research Part D 65: 194-212.
    \193\ Huang, H., G. Helfand, and K. Bolon (2018a). ``Consumer
Satisfaction with New Vehicles Subject to Greenhouse Gas and Fuel
Economy Standards.'' Presentation at the Society for Benefit-Cost
Analysis annual conference, March. https://benefitcostanalysis.org/docs/G.4_Huang_Slides.pdf, accessed 4/7/2021.
---------------------------------------------------------------------------

    A few public comments addressed perspectives on the issue of
potential tradeoffs among vehicle attributes. The National Automobile
Dealers Association (NADA) raises concerns that vehicle buyers must
give up vehicle attributes, especially performance, to get improved
fuel economy. NYU IPI, on the other hand, finds no evidence of
tradeoffs and notes that some fuel-saving technologies improve other
vehicle attributes, including

performance. In response to these comments, EPA notes that we have
evaluated the relationship between performance and fuel economy, in
light of research arguing that fuel consumption must come at the
expense of other vehicle attributes.\194\ Research in progress from
Watten et al. (2021) \195\ distinguishes between technologies that
improve, or do not adversely affect, both performance and fuel economy
and technologies that reduce engine displacement, which does trade off
improved fuel economy for performance. Thus, EPA does not agree with
NADA that vehicle buyers must give up performance to get better fuel
economy; it is possible to get more of both. Following Moskalik et al.
(2018),\196\ Watten et al. observe that the ``marginal rate of
attribute substitution'' between power and fuel economy has changed
substantially over time. In particular, it has become relatively more
costly to improve efficiency by reducing power, and relatively less
costly to add technologies that improve efficiency. These technology
improvements do not reduce power and in some cases may enhance it. This
research supports the concept that automakers take consumer preferences
into account in identifying where to add technology.
---------------------------------------------------------------------------

    \194\ Knittel, C.R. (2011). ``Automobiles on Steroids: Product
Attribute Trade-Offs and Technological Progress in the Automobile
Sector.'' American Economic Review 101(7): pp. 3368-3399; Klier, T.
and Linn, J. (2016). ``The Effect of Vehicle Fuel Economy Standards
on Technology Adoption.'' Journal of Public Economics 133: 41-63;
McKenzie, D. and Heywood, J.B. (2015). ``Quantifying efficiency
technology improvements in U.S. cars from 1975-2009.'' Applied
Energy 157: 918-928.
    \195\ Watten, A., S. Anderson, and G. Helfand (2021).
``Attribute Production and Technical Change: Rethinking the
Performance and Fuel Economy Trade-off for Light-duty Vehicles.''
Working paper.
    \196\ Moskalik, A., K. Bolon, K. Newman, and J. Cherry (2018).
``Representing GHG Reduction Technologies in the Future Fleet with
Full Vehicle Simulation.'' SAE Technical Paper 2018-01-1273.
doi:10.4271/2018-01-1273.
---------------------------------------------------------------------------

    EPA does not reject the observation that the energy efficiency gap
has existed for light-duty vehicles--that is, it appears that markets
on their own have not led to incorporation by manufacturers, and
purchase by new vehicle buyers, of a number of technologies whose fuel
savings quickly outweigh the costs in the absence of standards. As
discussed in RIA Chapter <IP_ADDRESS>, EPA has previously identified a
number of hypotheses to explain this apparent market failure.\197\ Some
relate to consumer behavior, such as putting little emphasis on future
fuel savings compared to up-front costs (a form of ``myopic loss
aversion''), not having a full understanding of potential cost savings,
or not prioritizing fuel consumption in the complex process of
selecting a vehicle. Explanations of these kinds tend to draw on the
conceptual and empirical literature in behavioral economics, which
emphasizes the importance of limited attention, the relevance of
salience, ``present bias'' or myopia, and loss aversion. (Some of these
are described as contributing to ``behavioral market failures.'') Other
potential explanations relate to automaker behaviors that grow out of
the large fixed costs of investments involved with switching to new
technologies, as well as the complex and uncertain processes involved
in technological innovation and adoption.
---------------------------------------------------------------------------

    \197\ 75 FR 25510-25513; 77 FR 62913-62917; U.S. Environmental
Protection Agency (2016), Proposed Determination on the
Appropriateness of the Model Year 2022-2025 Light-Duty Vehicle
Greenhouse Gas Emissions Standards under the Midterm Evaluation,
EPA-420-R-16-020, Appendix B.1.2; 85 FR 24603-24613.
---------------------------------------------------------------------------

    We note that it is challenging to identify which of these
hypotheses for the efficiency gap explain its apparent existence. On
the consumer side, EPA has explored the evidence on how consumers
evaluate fuel economy in their vehicle purchase decisions.\198\ As
noted, there does not appear to be consensus in that literature on that
behavior; the variation in estimates is very large. Even less research
has been conducted on producer-side behavior. The reason there
continues to be limited adoption of cost-effective fuel-saving
technologies before the implementation of more stringent standards
remains an open question. Yet, more stringent standards have been
adopted without apparent disruption to the vehicle market after they
become effective.\199\ NYU IPI commented that EPA should include
additional potential market failures in its assessment, as well as
additional evidence related to the market failures already mentioned.
The American Enterprise Institute, in contrast, asserts based on
economic theory, but without evidence, that failures in the market for
fuel savings do not exist. EPA agrees with NYU IPI that evidence on
technology costs, fuel savings, and the absence of hidden costs suggest
that there are market failures in the provision of fuel-saving
technologies, though we cannot demonstrate at this time which specific
failures operate in this market. Adding additional possible market
failures to the list of hypotheses is useful for suggesting future
research activities, but does not change the finding that market
failures appear to exist in the provision of fuel economy.
---------------------------------------------------------------------------

    \198\ U.S. Environmental Protection Agency (2010). ``How
Consumers Value Fuel Economy: A Literature Review.'' EPA-420-R-10-
008, https://cfpub.epa.gov/si/si_public_file_download.cfm?p_download_id=499454&Lab=OTAQ (accessed
4/15/2021); U.S. Environmental Protection Agency (2018). ``Consumer
Willingness to Pay for Vehicle Attributes: What is the Current State
of Knowledge?'' EPA-420-R-18-016, https://cfpub.epa.gov/si/si_public_file_download.cfm?p_download_id=536423&Lab=OTAQ (accessed
4/15/2021); Greene, D., A. Hossain, J. Hofmann, G. Helfand, and R.
Beach (2018). ``Consumer Willingness to Pay for Vehicle Attributes:
What Do We Know?'' Transportation Research Part A 118: 258-279.
    \199\ ``The 2020 EPA Automotive Trends Report, Greenhouse Gas
Emissions, Fuel Economy, and Technology since 1975,'' EPA-420-R-21-
003 January 2021. See Table 2-1 for total vehicle production by
model year.
---------------------------------------------------------------------------

B. Vehicle Sales Impacts

    As discussed in Section III.A of this preamble, EPA utilized the
CCEMS model for this analysis. For this final rule as with the proposed
rule, we have continued to estimate vehicle sales impacts through this
model.\200\ First, the model projects future new vehicle sales in the
reference case based on projections of macroeconomic variables. Second,
it applies a demand elasticity (that is, the percent change in quantity
associated with a one percent increase in price) to the change in net
price, where net price is the difference in technology costs less an
estimate of the change in fuel costs over 2.5 years. This approach
assumes that both automakers and vehicle buyers take into consideration
the fuel savings that buyers might expect to accrue over the first 2.5
years of vehicle ownership.
---------------------------------------------------------------------------

    \200\ U.S. Department of Transportation and U.S. Environmental
Protection Agency (2020). Final Regulatory Impact Analysis: The
Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Year
2021-2026 Passenger Cars and Light Trucks.'' https://www.nhtsa.gov/sites/nhtsa.gov/files/documents/final_safe_fria_web_version_200701.pdf, accessed 11/1/2021, p. 871.
---------------------------------------------------------------------------

    As discussed in Section VII.A of this preamble, and in more detail
in RIA Chapter 8.1.2, there does not yet appear to be consensus around
the role of fuel consumption in vehicle purchase decisions, and the
assumption that 2.5 years of fuel consumption is the right number for
both automakers and vehicle buyers deserves further evaluation. As
noted there, Greene et al. (2018) provides a reference value of $1,150
for the value of reducing fuel costs by $0.01/mile over the lifetime of
an average vehicle; for comparison, 2.5 years of fuel savings is only
about 30 percent of that value, or about $334.\201\

This $334 is within the large standard deviation in Greene et al.
(2018) for the willingness to pay to reduce fuel costs, but it is far
lower than both the mean of $1,880 (160 percent of that value) and the
median of $990 (85 percent of that value) per one cent per mile in the
paper. On the other hand, the 2021 NAS report, citing the 2015 NAS
report, observed that automakers ``perceive that typical consumers
would pay upfront for only one to four years of fuel savings'' (pp. 9-
10),\202\ a range of values within that identified in Greene et al.
(2018) for consumer response, but well below the median or mean. Thus,
it appears possible that automakers operate under a different
perception of consumer willingness to pay for additional fuel economy
than how consumers actually behave. Both NYU IPI and Consumer Reports
comment that new vehicle buyers care more about fuel consumption than
the use of 2.5 years suggests. Consumer Reports comments that EPA
should model automaker adoption of fuel-saving technologies based on
historical actions. While EPA considers these concerns as deserving
additional consideration for future actions, the CCEMS model used for
this rulemaking uses 2.5 years for both automaker perception and
consumer perception of the value of additional fuel economy in its
sales modeling. The decision to use the CCEMS model is further
discussed in Section III.A of this preamble.
---------------------------------------------------------------------------

    \201\ See Greene et al. (2018), Footnote 198. Greene et al.
(2018) cite a ballpark value of reducing driving costs by $0.01/mile
as $1150, but does not provide enough detail to replicate their
analysis perfectly. The 30% estimate is calculated by assuming,
following assumptions in Greene et al. (2018), that a vehicle is
driven 15,000 miles per year for 13.5 years, 10% discount rate.
Those figures produce a ``present value of miles'' of 108,600; thus,
a $0.01/mile change in the cost of driving would be worth $1086. In
contrast, saving $0.01/mile for 2.5 years using these assumptions is
worth about $318, or 29% of the value over 13.5 years. Multiplying
Greene et al.'s 29 percent to $1150 = $334.
    \202\ National Research Council (2015). Cost, Effectiveness, and
Deployment of Fuel Economy Technologies for Light-Duty Vehicles.
Washington, DC: The National Academies Press. https://doi.org/10.17226/21744, p. 9-10.
---------------------------------------------------------------------------

    In addition, setting the elasticity of demand at -1 in the SAFE
FRIA was based on literature more than 25 years old. In the proposed
rule, EPA mentioned that it was sponsoring a review of more recent
estimates of the elasticity of demand for new vehicles and requested
comment on using an elasticity value of -1. As discussed further in RIA
Chapter 8.1.2, EPA recently completed the report reviewing this
literature.\203\ The report also describes a method based in economic
principles to examine the effects of changes in new vehicle prices,
taking into account changes in the used vehicle market and scrappage of
used vehicles. Several commenters (CARB, NYU IPI, and a coalition of
environmental NGOs) provide assessments of the literature. These
commenters all observe that the value of -1 is based on older studies
that focus on short-term changes in the new vehicle market and suggest
using an elasticity no larger (in absolute value) than -0.4. EPA agrees
that more recent evidence incorporating longer-term effects, such as
interactions with the used vehicle market, suggests that -0.4 may be an
upper limit (in absolute value) for this elasticity, and values as low
as -0.15 are plausible. A smaller elasticity does not change the
direction of sales effects, but it does reduce the magnitude of the
effects.
---------------------------------------------------------------------------

    \203\ U.S. Environmental Protection Agency (2021). ``The Effects
of New-Vehicle Price Changes on New- and Used-Vehicle Markets and
Scrappage.'' EPA-420-R-21-019, https://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryId=352754&Lab=OTAQ (accessed 10/
06/2021).
---------------------------------------------------------------------------

    The CCEMS model also makes use of a dynamic fleet share model (SAFE
FRIA p. 877) that estimates, separately, the shares of passenger cars
and light trucks based on vehicle characteristics, and then adjusts
them so that the market shares sum to one. The model also includes the
effects of the standards on vehicle scrappage based on a statistical
analysis (FRIA starting p. 926). The model looks for associations
between vehicle age, change in new vehicle prices, fuel prices, cost
per mile of driving, and macroeconomic measures and the scrappage rate,
with different equations for cars, SUVs/vans, and pickups. EPA's report
to review new vehicle demand elasticities also includes a review of the
literature on the relationship between new and used vehicle markets and
scrappage.
    For this final rule, EPA is maintaining the previous assumptions
for its modeling, with the exception of updating the new-vehicle demand
elasticity to -0.4 based on more recent evidence. As EPA's recently
issued literature review and public commenters have noted, -0.4 appears
to be the largest estimate (in absolute value) for a long-run new
vehicle demand elasticity in recent studies. Further, EPA's report
examining the relationship between new and used vehicle markets shows
that, for plausible values reflecting that interaction, the new vehicle
demand elasticity varies from -0.15 to -0.4. The proposed rule
presented results with -0.4, and for the final rule we are using this
value in our central case, with sensitivities of -0.15 (a lower value
from the report) and -1 (for continuity with the proposed rule). See
Section III.A of this preamble and the Response to Comments document
for further discussion of our updated approach.
    With the modeling assumptions that both automakers and vehicle
buyers consider 2.5 years of future fuel consumption in the purchase
decision and that the demand elasticity is -0.4, vehicle sales are
projected to decrease by roughly one-half to one percent compared to
sales under the SAFE standards, as discussed in more detail in RIA
Chapter 8.1.3. In contrast, when modeled using a demand elasticity of -
0.15, sales decrease by no more than 0.3 percent; and, using a demand
elasticity of -1, sales decrease by about 2 percent. These results show
how the value of the elasticity affects sales impacts. If, however,
automakers underestimate consumers' valuation of fuel economy, then
sales may increase relative to the baseline under the standards. NADA
commented that EPA underestimated adverse sales impacts but does not
provide analytical support for that statement. For reasons noted above,
including the limited consideration of fuel consumption in consumer
vehicle purchase decisions, EPA disagrees that adverse sales impacts
are underestimated.
    How easily new vehicle buyers will be willing to substitute EVs for
internal combustion engine (ICE) vehicles is a matter of some
uncertainty. With up-front costs dropping, the total cost of ownership
for EVs is also dropping and becoming more competitive with ICE
vehicles. Some commenters, including the California Attorney General
Office, Consumer Reports, the National Coalition for Advanced
Technology, Southern Environmental Law Center, Tesla, and some EV
owners, expect EVs to be attractive to many new vehicle buyers as their
costs drop, ranges improve, and more charging infrastructure is
developed. Other commenters, including many automakers, Alliance for
Automotive Innovation, Center for Climate and Energy Solutions,
Environmental Protection Network, and Motor & Equipment Manufacturers
Association, raise the role of complementary policies outside of this
rule, such as purchase subsidies and more development of charging
infrastructure, to facilitate consumer acceptance of EVs. As discussed
in Section III.B.3 of this preamble, our analysis suggests that EV
penetration under these standards is projected to increase from about 7
percent in MY 2023 to about 17 percent in MY 2026. Consistent with the
objectives of E.O. 14037, EPA believes that the transition to zero
emission vehicles is an important pathway in addressing the climate
crisis; in addition, as discussed in Section VII.K

of this preamble, increasing domestic production of EVs will be
important for future leadership and competitiveness of the U.S. auto
industry as other markets also make this transition.

C. Changes in Fuel Consumption

    The final standards will reduce not only GHG emissions but also
fuel consumption. Reducing fuel consumption is a significant means of
reducing GHG emissions from the transportation fleet. EPA received
comments on fuel consumption and savings in the sales and net benefits
analysis as summarized in Sections 13, 17, and 17.1 of the RTC document
for this rulemaking. Table 38 shows the estimated fuel consumption
changes under the final standards relative to the No Action scenario
and include rebound effects, credit usage and advanced technology
multiplier use.
    The largest changes in fuel consumption come from gasoline, which
follows from our projection that improvements to gasoline vehicles will
be the primary way that manufacturers meet the final standards. Through
2050, our rule will reduce gasoline consumption by more than 360,000
million gallons--reaching a 15 percent reduction in annual U.S.
gasoline consumption in 2050. Roughly 17 percent of the fleet is
projected to be either EV or PHEV by MY 2026 to meet the final
standards for which we project smaller percentage changes in the U.S.
electricity consumption to fuel these vehicles.

                         Table 38--Change in Fuel Consumption From the Light-Duty Fleet
----------------------------------------------------------------------------------------------------------------
                                                     Gasoline
                                                    equivalents     Percent of      Electricity     Percent of
                                                     (million        2020 U.S.       (gigawatt       2020 U.S.
                                                     gallons)       consumption       hours)        consumption
----------------------------------------------------------------------------------------------------------------
2023............................................             582               0           3,631               0
2026............................................           3,245              -3          23,196               1
2030............................................           8,680              -7          59,241               2
2035............................................          14,203             -11          95,798               3
2040............................................          17,424             -14         118,225               3
2050............................................          18,860             -15         128,625               3
Sum.............................................        -361,438  ..............       2,457,336  ..............
----------------------------------------------------------------------------------------------------------------
Notes: The CCEMS reports all liquid fuels as gasoline equivalents; according to the Energy Information
  Administration (EIA), U.S. gasoline consumption in 2020 was 123.73 billion gallons, roughly 16 percent less
  (due to the coronavirus pandemic) than the highest consumption on record (2018). According to the Department
  of Energy, there are 33.7 kWh of electricity per gallon gasoline equivalent, the metric reported by CCEMS for
  electricity consumption and used here to convert to kWh. According to EIA, the U.S. consumed 3,800,000
  gigawatt hours of electricity in 2020.

    With changes in fuel consumption come associated changes in the
amount of time spent refueling vehicles. Consistent with the
assumptions used in the proposed rule (and presented in Table 39 and
Table 40), the costs of time spent refueling are calculated as the
total amount of time the driver of a typical vehicle would spend
refueling multiplied by the value of their time. If less time is spent
refueling vehicles under the final standards, then a refueling time
savings would be incurred.

                       Table 39--CCEMS Inputs Used To Estimate Liquid Refueling Time Costs
----------------------------------------------------------------------------------------------------------------
                                                                       Cars          Vans/SUVs        Pickups
----------------------------------------------------------------------------------------------------------------
                       Fixed Component of Average Refueling Time in Minutes (by Fuel Type)
----------------------------------------------------------------------------------------------------------------
Gasoline........................................................             3.5             3.5             3.5
Ethanol-85......................................................             3.5             3.5             3.5
Diesel..........................................................             3.5             3.5             3.5
Electricity.....................................................             3.5             3.5             3.5
Hydrogen........................................................               0               0               0
Compressed Natural Gas..........................................               0               0               0
Average Tank Volume Refueled....................................             65%             65%             65%
Value of Travel Time per Vehicle (2018 $/hour)..................           20.46           20.79           20.79
----------------------------------------------------------------------------------------------------------------

                      Table 40--CCEMS Inputs Used To Estimate Electric Refueling Time Costs
----------------------------------------------------------------------------------------------------------------
                                                                       Cars          Vans/SUVs        Pickups
----------------------------------------------------------------------------------------------------------------
                                  Electric Vehicle Recharge Thresholds (BEV200)
----------------------------------------------------------------------------------------------------------------
Miles until mid-trip charging event.............................           2,000           1,500           1,600
Share of miles charged mid-trip.................................           6.00%           9.00%           8.00%
Charge rate (miles/hour)........................................              67              67              67
----------------------------------------------------------------------------------------------------------------
                                  Electric Vehicle Recharge Thresholds (BEV300)
----------------------------------------------------------------------------------------------------------------
Miles until mid-trip charging event.............................           5,200           3,500           3,800
Share of miles charged mid-trip.................................           3.00%           4.00%           4.00%

Charge rate (miles/hour)........................................             100             100             100
----------------------------------------------------------------------------------------------------------------
Note that the values presented in this table were also used in the August 2021 EPA proposed rule, but this table
  was inadvertently not presented then.

D. Greenhouse Gas Emission Reduction Benefits

    EPA estimated the climate benefits for the final standards using
measures of the social cost of three GHGs: Carbon, methane, and nitrous
oxide. While the program also accounts for reduction in HFCs through
the AC credits program, EPA has not quantified the associated emission
reductions. The social cost of each gas (i.e., the social cost of
carbon (SC-CO2), methane (SC-CH4), and nitrous
oxide (SC-N2O)) is the monetary value of the net harm to
society associated with a marginal increase in emissions in a given
year, or the benefit of avoiding that increase. Collectively, these
values are referenced as the ``social cost of greenhouse gases'' (SC-
GHG). In principle, SC-GHG 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-GHG therefore, reflects the societal value of reducing emissions
of the gas in question by one metric ton.
    We estimate the global social benefits of CO2,
CH4, and N2O emission reductions expected from
the final rule using the SC-GHG estimates presented in the February
2021 Technical Support Document (TSD): Social Cost of Carbon, Methane,
and Nitrous Oxide Interim Estimates under E.O. 13990 (IWG 2021). These
SC-GHG estimates are interim values developed under E.O. 13990 for use
in benefit-cost analyses until an improved estimate of the impacts of
climate change can be developed based on the best available climate
science and economics. We have evaluated the SC-GHG estimates in the
TSD and have determined that these estimates are appropriate for use in
estimating the global social benefits of CO2, CH4, and N2O emission
reductions expected from this final rule. After considering the TSD,
and the issues and studies discussed therein, EPA finds that these
estimates, while likely an underestimate, are the best currently
available SC-GHG estimates. As discussed in Chapter 3.3 of the RIA,
these interim SC-GHG estimates have a number of limitations, including
that the models used to produce them do not include all of the
important physical, ecological, and economic impacts of climate change
recognized in the climate-change literature and that several modeling
input assumptions are outdated. As discussed in the February 2021 TSD,
the Interagency Working Group on the Social Cost of Greenhouse Gases
(IWG) finds that, taken together, the limitations suggest that these
SC-GHG estimates likely underestimate the damages from GHG emissions.
We received comments on the use and application of the interim SC-GHG
estimates as summarized in the RTC document for this rulemaking. The
IWG is currently working on a comprehensive update of the SC-GHG
estimates (to be released by January 2022 under E.O. 13990) taking into
consideration recommendations from the National Academies of Sciences,
Engineering and Medicine, recent scientific literature, public comments
received on the February 2021 TSD and other input from experts and
diverse stakeholder groups. See Section VII.I of this preamble for a
summary of the monetized GHG benefits and Chapter 3.3 of the RIA for
more on the application of SC-GHG estimates.

E. Non-Greenhouse Gas Health Impacts

    It is important to quantify the non-GHG health and environmental
impacts associated with the final program because a failure to
adequately consider ancillary impacts could lead to an incorrect
assessment of a program's costs and benefits. Moreover, the health and
other impacts of exposure to criteria air pollutants and airborne
toxics tend to occur in the near term, while most effects from reduced
climate change are likely to occur over a time frame of several decades
or longer. Ideally, human health benefits would be estimated based on
changes in ambient PM2.5 and ozone as determined by full-
scale air quality modeling. However, the projected non-GHG emissions
impacts associated with the final program are expected to contribute to
very small changes in ambient air quality (see Preamble Section V.C of
this preamble for more detail). EPA intends to develop a future rule to
control emissions of GHGs, criteria pollutants, and air toxic
pollutants from light-duty vehicles for model years beyond 2026. We are
considering how to project air quality impacts, and associated health
benefits, from the changes in non-GHG emissions for that future
rulemaking.
    In lieu of air quality modeling, we use a reduced-form benefit-per-
ton (BPT) approach to inform our assessment of PM2.5-related
health impacts, which is conceptually consistent with EPA's use of BPT
estimates in several previous RIAs.204 205 In this approach,
the PM2.5-related BPT values are the total monetized human
health benefits (the sum of the economic value of the reduced risk of
premature death and illness) that are expected from reducing one ton of
directly-emitted PM2.5 or PM2.5 precursor such as
NOX or SO2. We note, however, that the complex,
non-linear photochemical processes that govern ozone formation prevent
us from developing reduced-form ozone BPT values for mobile sources.
This is an important limitation to recognize when using the BPT
approach.
---------------------------------------------------------------------------

    \204\ U.S. Environmental Protection Agency (U.S. EPA). 2015.
Regulatory Impact Analysis for the Final Revisions to the National
Ambient Air Quality Standards for Ground-Level Ozone. EPA452/R-15-
007. Office of Air Quality Planning and Standards, Health and
Environmental Impacts Division, Research Triangle Park, NC.
December. Available at: http://www.epa.gov/ttnecas1/regdata/RIAs/finalria.pdf.
    \205\ U.S. Environmental Protection Agency (U.S. EPA). (2012).
Regulatory Impact Analysis: Final Rulemaking for 2017-2025 Light-
Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average
Fuel Economy Standards, Assessment and Standards Division, Office of
Transportation and Air Quality, EPA-420-R-12-016, August 2012.
Available on the internet at: http://www3.epa.gov/otaq/climate/documents/420r12016.pdf.
---------------------------------------------------------------------------

    EPA received comment about the use of BPT values to estimate the
PM-related health benefits of the program. EPA agrees with commenters
that the use of BPT values to estimate the PM-related health benefits
of the program ``is a well-established approach'' that nonetheless
omits a number of other health and environmental benefits, such as
ozone-related benefits. Commenters expressed concern that because the
BPT approach leaves these benefits unquantified, the analysis
undercounts air quality benefits. EPA believes that using the reduced-
form BPT approach to benefits estimation was reasonable for the
analysis conducted for this

rulemaking though less robust than an analysis based on photochemical
air quality modeling. EPA continues to refine our reduced form methods.
We note that criteria pollutant-related health benefits are typically
driven by reductions in PM-related mortality risk, which are reflected
in the BPT-based analysis of benefits associated with the final rule.
We would expect that monetizing the full suite of health and
environmental benefits associated with the final rule would increase
total benefits, and benefits would increase in proportion to the
criteria pollutant emissions reductions achieved, for both the final
program and the alternatives that were considered. However, as
explained earlier in this section, we are limited to the use of
PM2.5-related BPT values for this analysis. We do not expect
that the omission of unquantified benefits would meaningfully change
how the impacts of the final program compare to the alternatives,
though the rule would be even more beneficial on net (compared to
costs) if all benefits were quantified and monetized.
    For tailpipe emissions, we apply national PM2.5-related
BPT values that were recently derived for the ``Onroad Light Duty
Vehicle'' sector.\206\ The onroad light-duty vehicle BPT values were
derived using detailed mobile sector source-apportionment air quality
modeling, and apply EPA's existing method for using reduced-form tools
to estimate PM2.5-related benefits.207 208
---------------------------------------------------------------------------

    \206\ Wolfe, P.; Davidson, K.; Fulcher, C.; Fann, N.; Zawacki,
M.; Baker, K.R. 2019. Monetized Health Benefits Attributable to
Mobile Source Emission Reductions across the United States in 2025.
Sci. Total Environ. 650, 2490-2498. https://doi.org/10.1016/J.SCITOTENV.2018.09.273. Also see https://www.epa.gov/benmap/mobile-sector-source-apportionment-air-quality-and-benefits-ton.
    \207\ Zawacki, M.; Baker, K.R.; Phillips, S.; Davidson, K.;
Wolfe, P. 2018. Mobile Source Contributions to Ambient Ozone and
Particulate Matter in 2025. Atmos. Environ. 188, 129-141.
    \208\ Fann, N.; Fulcher, C.M.; Baker, K. 2013. The Recent and
Future Health Burden of Air Pollution Apportioned across U.S.
Sectors. Environ. Sci. Technol. 47 (8), 3580-3589. https://doi.org/10.1021/es304831q.
---------------------------------------------------------------------------

    To monetize the PM2.5-related impacts of upstream
emissions, we apply BPT values that were developed for the refinery and
electric generating unit (EGU) sectors.\209\ While upstream emissions
also include petroleum extraction, storage and transport sources, as
well as sources upstream from the refinery, the modeling tool used to
support this analysis only provides estimates of upstream emissions
impacts aggregated across refinery and EGU sources. We believe that for
purposes of this rule the separate accounting of refinery and EGU
impacts adequately monetizes upstream PM-related health impacts.
---------------------------------------------------------------------------

    \209\ U.S. Environmental Protection Agency (U.S. EPA). 2018.
Technical Support Document: Estimating the Benefit per Ton of
Reducing PM2.5 Precursors from 17 Sectors. 2018. Office
of Air Quality Planning and Standards. Research Triangle Park, NC.
---------------------------------------------------------------------------

    EPA received comment about the use of refinery-related BPT values
as a surrogate for the monetization of all upstream emissions impacts.
EPA agrees with the commenters that sector-specific BPT values are
preferable to monetize sector-specific emissions. For the final rule,
upstream emissions have been apportioned to the refinery and EGU
sectors and we apply corresponding BPT values to monetize those
emissions impacts. More information on non-GHG emissions impacts of the
final rule can be found in Preamble Section V.
    EPA bases its benefits analyses on peer-reviewed studies of air
quality and health effects and peer-reviewed studies of the monetary
values of public health and welfare improvements. Recently, EPA updated
its approach to estimating the benefits of changes in PM2.5
and ozone.210 211 These updates were based on information
drawn from the recent 2019 PM2.5 and 2020 Ozone Integrated
Science Assessments (ISAs), which were reviewed by the Clean Air
Science Advisory Committee (CASAC) and the public.212 213 As
part of the update, EPA identified PM2.5-related long-term
premature mortality risk estimates from two studies deemed most
appropriate to inform a benefits analysis: A retrospective analysis of
Medicare beneficiaries (Medicare) and the American Cancer Society
Cancer Prevention II study (ACS CPS-II).214 215 216
---------------------------------------------------------------------------

    \210\ U.S. Environmental Protection Agency (U.S. EPA). 2021.
Regulatory Impact Analysis for the Final Revised Cross-State Air
Pollution Rule (CSAPR) Update for the 2008 Ozone NAAQS. EPA-452/R-
21-002.
    \211\ U.S. Environmental Protection Agency (U.S. EPA). 2021.
Estimating PM2.5- and Ozone-Attributable Health Benefits.
Technical Support Document (TSD) for the Final Revised Cross-State
Air Pollution Rule Update for the 2008 Ozone Season NAAQS. EPA-HQ-
OAR-2020-0272.
    \212\ U.S. Environmental Protection Agency (U.S. EPA). 2019.
Integrated Science Assessment (ISA) for Particulate Matter (Final
Report, 2019). U.S. Environmental Protection Agency, Washington, DC,
EPA/600/R-19/188, 2019.
    \213\ U.S. Environmental Protection Agency (U.S. EPA). 2020.
Integrated Science Assessment (ISA) for Ozone and Related
Photochemical Oxidants (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-20/012, 2020.
    \214\ Di, Q, Wang, Y, Zanobetti, A, Wang, Y, Koutrakis, P,
Choirat, C, Dominici, F and Schwartz, JD (2017). Air pollution and
mortality in the Medicare population. New Engl J Med 376(26): 2513-
2522.
    \215\ Turner, MC, Jerrett, M, Pope, A, III, Krewski, D, Gapstur,
SM, Diver, WR, Beckerman, BS, Marshall, JD, Su, J, Crouse, DL and
Burnett, RT (2016). Long-term ozone exposure and mortality in a
large prospective study. Am J Respir Crit Care Med 193(10): 1134-
1142.
    \216\ The Harvard Six Cities Study (Lepeule et al., 2012), which
had been identified for use in estimating mortality impacts in
previous PM benefits analyses, was not identified as most
appropriate for the benefits update due to geographic limitations.
---------------------------------------------------------------------------

    EPA has not had an opportunity to update its mobile source BPT
estimates to reflect these updates in time for this analysis. Instead,
we use PM2.5 BPT estimates that are based on the review of
the 2009 PM ISA \217\ and 2012 PM ISA Provisional Assessment \218\ and
include a mortality risk estimate derived from the Krewski et al.
(2009) \219\ analysis of the ACS CPS-II cohort and nonfatal illnesses
consistent with benefits analyses performed for the analysis of the
final Tier 3 Vehicle Rule,\220\ the final 2012 PM NAAQS Revision,\221\
and the final 2017-2025 Light-duty Vehicle GHG Rule.\222\ We expect
this lag in updating our BPT estimates to have only a small impact on
total PM benefits, since the underlying mortality risk estimate based
on the Krewski study is identical to the updated PM2.5
mortality risk estimate derived from an expanded analysis of

the same ACS CPS-II cohort.\223\ The Agency is currently working to
update its mobile source BPT estimates to reflect these recent updates
for use in future rulemaking analyses. More information on the BPT
approach to valuing PM-related benefits can be found in RIA Chapter
7.2.
---------------------------------------------------------------------------

    \217\ U.S. Environmental Protection Agency (U.S. EPA). 2009.
Integrated Science Assessment for Particulate Matter (Final Report).
EPA-600-R-08-139F. National Center for Environmental Assessment--RTP
Division, Research Triangle Park, NC. December. Available at:
https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=216546.
    \218\ U.S. Environmental Protection Agency (U.S. EPA). 2012.
Provisional Assessment of Recent Studies on Health Effect of
Particulate Matter Exposure. EPA/600/R-12/056F. National Center for
Environmental Assessment--RTP Division, Research Triangle Park, NC.
December. Available at: https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=247132.
    \219\ Krewski D., M. Jerrett, R.T. Burnett, R. Ma, E. Hughes, Y.
Shi, et al. 2009. Extended Follow-Up and Spatial Analysis of the
American Cancer Society Study Linking Particulate Air Pollution and
Mortality. HEI Research Report, 140, Health Effects Institute,
Boston, MA.
    \220\ U.S. Environmental Protection Agency. (2014). Control of
Air Pollution from Motor Vehicles: Tier 3 Motor Vehicle Emission and
Fuel Standards Final Rule: Regulatory Impact Analysis, Assessment
and Standards Division, Office of Transportation and Air Quality,
EPA-420-R-14-005, March 2014. Available on the internet: http://www3.epa.gov/otaq/documents/tier3/420r14005.pdf.
    \221\ U.S. Environmental Protection Agency. (2012). Regulatory
Impact Analysis for the Final Revisions to the National Ambient Air
Quality Standards for Particulate Matter, Health and Environmental
Impacts Division, Office of Air Quality Planning and Standards, EPA-
452-R-12-005, December 2012. Available on the internet: http://www3.epa.gov/ttnecas1/regdata/RIAs/finalria.pdf.
    \222\ U.S. Environmental Protection Agency (U.S. EPA). (2012).
Regulatory Impact Analysis: Final Rulemaking for 2017-2025 Light-
Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average
Fuel Economy Standards, Assessment and Standards Division, Office of
Transportation and Air Quality, EPA-420-R-12-016, August 2012.
Available on the internet at: http://www3.epa.gov/otaq/climate/documents/420r12016.pdf.
    \223\ Turner, MC, Jerrett, M, Pope, A, III, Krewski, D, Gapstur,
SM, Diver, WR, Beckerman, BS, Marshall, JD, Su, J, Crouse, DL and
Burnett, RT (2016). Long-term ozone exposure and mortality in a
large prospective study. Am J Respir Crit Care Med 193(10): 1134-
1142.
---------------------------------------------------------------------------

    EPA received comments asserting that quantifying and monetizing the
health benefits of reduced emissions of particulate matter is not
consistent with the available scientific evidence and that EPA did not
consider the advice made by some members of CASAC that reviewed the
2019 PM ISA. We disagree that our estimates are not consistent with the
available scientific evidence and the advice of the Clean Air Science
Advisory Committee. In determining which health outcomes to quantify
and monetize, EPA relies on the weight-of-evidence evaluation of
relationships between PM2.5 exposure and health effects
conducted within the ISAs, which are the scientific basis of the NAAQS
review process. ISAs represent thorough evaluations and syntheses of
the most policy-relevant science. EPA uses a structured and transparent
process for evaluating scientific information and determining the
causal nature of relationships between air pollution exposures and
health effects. The ISA development process is detailed in the Preamble
of the Integrated Science Assessments,\224\ which describes approaches
for literature searches, criteria for selecting and evaluating relevant
studies, and a framework for evaluating the weight of evidence and
forming causality determinations. EPA quantifies and monetizes health
effects that the ISA determines are ``causal'' or ``likely to be
causal.'' The focus on categories identified as having a ``causal'' or
``likely to be causal'' relationship with the pollutant of interest
allows for the estimation of pollutant-attributable human health
benefits in which the Agency is most confident.
---------------------------------------------------------------------------

    \224\ See https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=310244.
---------------------------------------------------------------------------

    As part of the process of developing an ISA, the Clean Air
Scientific Advisory Committee (CASAC) is statutorily required to review
the science underlying decisions about the NAAQS. CASAC provides
independent review of draft ISA documents for scientific quality and
sound implementation of the causal framework that informs the ISA
before it is finalized. The 2020 PM NAAQS review was completed without
the benefit of a PM-specific panel supporting the CASAC, as had been
done in prior reviews. However, CASAC did have access to a pool of
consultants who were available to respond in writing to questions from
CASAC members. With limited access to relevant expertise, CASAC did not
reach consensus on the determination that there is a causal
relationship for PM2.5 exposure (i.e., both short- and long-
term) and mortality presented within the draft PM ISA. After the
disbandment of the 20-member CASAC PM panel, CASAC noted that
``Additional expertise is needed for [CASAC] to provide a thorough
review of the [PM NAAQS] documents'' and recommended the Administrator
reappoint ``the previous CASAC PM panel or panel with similar
expertise.'' \225\ In his final decision to retain the PM standards,
after considering CASAC's advice, the EPA Administrator, ``placing the
greatest weight on evidence of effects for which the ISA determined
there is a causal or likely causal relationship with long- and short-
term PM2.5 exposures,'' \226\ concluded that the current PM
NAAQS are necessary to protect public health. Thus, the Administrator
fully considered CASAC's recommendations with respect to assessing the
health risks of PM in the review of the PM NAAQS and EPA is being
consistent with the conclusions of the PM NAAQS review in this action.
---------------------------------------------------------------------------

    \225\ In the time since the previously chartered CASAC, EPA has
recognized the significant accumulation of new scientific studies
since the cutoff date of the 2019 PM ISA (January 2018) and
published a draft supplement to the 2019 PM ISA. The Supplement
found that recent studies further support, and in some instances
extend, the evidence that formed the basis of the causality
determinations presented within the 2019 PM ISA that characterizes
relationships between PM exposure and health, including mortality.
    \226\ 85 FR 82715. The effects for which the 2019 ISA determined
there is a causal or likely causal relationship with long- and
short-term PM2.5 exposures include respiratory effects,
cardiovascular effects, and mortality.
---------------------------------------------------------------------------

    Commenters also asserted that health benefits from reductions in
human exposure to ambient concentrations of PM2.5 only occur
above the level of the primary health-based NAAQS, and that accounting
for the health benefits of PM2.5 at all represents double
counting given other regulatory measures promulgated under the Clean
Air Act to reduce ambient concentrations of PM2.5. The EPA
disagrees with this assertion. First, it is important to recognize that
the NAAQS ``shall be ambient air quality standards . . . which in the
judgment of the Administrator'' are ``requisite'' to protect public
health with an ``adequate margin of safety'' (CAA Section 109).
``Requisite'' means sufficient but not more than necessary while an
``adequate margin of safety'' is intended to address uncertainties
associated with inconclusive evidence and to provide a reasonable
degree of protection against hazards that research has not yet
identified. The CAA does not require eliminating all risk, and
therefore, the NAAQS does not represent a zero-risk standard.
Additionally, EPA is reconsidering the 2020 decision to retain the PM
standards because available scientific evidence and technical
information suggests that the current standards may not be adequate to
protect public health and welfare, as required by the Clean Air Act.
    As detailed in the 2019 PM ISA and previous assessments in support
of the PM NAAQS, EPA's review of the science has consistently found no
evidence of a threshold below which exposure to PM2.5 yields
no health response. Specifically, the 2019 p.m. ISA found that
``extensive analyses across health effects continues to support a
linear, no-threshold concentration-response (C-R) relationship.'' This
conclusion in the 2019 PM ISA is supported by the more recent
evaluation of the health effects evidence detailed in the recently
released Draft Supplement to the PM ISA which found ``continued
evidence of a linear, no-threshold concentration-response (C-R)
relationship.''
    Regarding double-counting, the emissions attributed to this final
rulemaking are incremental to all other currently promulgated air
pollution regulations and can therefore be monetized without double-
counting previously achieved benefits from mobile source emissions
reductions.
    The PM-related BPT estimates used in this analysis are provided in
Table 41. We multiply these BPT values by projected national changes in
NOX, SO2 and directly-emitted PM2.5,
in tons, to estimate the total PM2.5-related monetized human
health benefits associated with the final program. As the table
indicates, these values differ among pollutants and depend on their
original source, because emissions from different sources can result in
different degrees of population exposure and resulting health impacts.
The BPT values for emissions of non-GHG pollutants from both onroad
light-duty vehicle use and upstream sources such as fuel refineries
will increase over time. These projected increases reflect rising
income levels, which increase affected individuals' willingness to pay
for

reduced exposure to health threats from air pollution. The BPT values
also reflect future population growth and increased life expectancy,
which expands the size of the population exposed to air pollution in
both urban and rural areas, especially among older age groups with the
highest mortality risk.\227\
---------------------------------------------------------------------------

    \227\ For more information about income growth adjustment
factors and EPA's population projections, please refer to the
following: https://www.epa.gov/sites/production/files/2015-04/documents/benmap-ce_user_manual_march_2015.pdf.

                                                     Table 41--PM2.5-Related Benefit-Per-Ton Values
                                                                       [2018$] \a\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                      Onroad light duty vehicles \b\           Upstream sources--refineries \c\          Upstream sources--EGUs \c\
                              --------------------------------------------------------------------------------------------------------------------------
             Year               Direct PM2.5                                   Direct                                 Direct
                                                     SO2           NOX         PM2.5         SO2          NOX         PM2.5         SO2          NOX
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                        Estimated Using a 3 Percent Discount Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
2020.........................        $600,000        $150,000       $6,400     $380,000      $81,000       $8,100     $160,000      $44,000       $6,600
2025.........................         660,000         170,000        6,900      420,000       90,000        8,800      180,000       49,000        7,100
2030.........................         740,000         190,000        7,600      450,000       98,000        9,600      190,000       52,000        7,600
2035.........................         830,000         210,000        8,400  ...........  ...........  ...........  ...........  ...........  ...........
2040.........................         920,000         230,000        9,000  ...........  ...........  ...........  ...........  ...........  ...........
2045.........................       1,000,000         250,000        9,600  ...........  ...........  ...........  ...........  ...........  ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                        Estimated Using a 7 Percent Discount Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
2020.........................         540,000         140,000        5,800      350,000       74,000        7,300      150,000       40,000        5,900
2025.........................         600,000         150,000        6,200      380,000       80,000        7,900      160,000       43,000        6,400
2030.........................         660,000         170,000        6,800      410,000       88,000        8,600      170,000       48,000        6,900
2035.........................         750,000         190,000        7,500  ...........  ...........  ...........  ...........  ...........  ...........
2040.........................         830,000         210,000        8,200  ...........  ...........  ...........  ...........  ...........  ...........
2045.........................         900,000         230,000        8,600  ...........  ...........  ...........  ...........  ...........  ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\a\ The benefit-per-ton estimates presented in this table are based on estimates derived from the American Cancer Society cohort study (Krewski et al.,
  2009). They also assume either a 3 percent or 7 percent discount rate in the valuation of premature mortality to account for a twenty-year segmented
  premature mortality cessation lag.
\b\ Benefit-per-ton values for onroad light duty vehicles were estimated for the years 2020, 2025, 2030, 2035, 2040, and 2045. We hold values constant
  for intervening years (e.g., the 2020 values are assumed to apply to years 2021-2024; 2025 values for years 2026-2029; and 2045 values for years 2046
  and beyond).
\c\ Benefit-per-ton values for upstream sources were estimated only for the years 2020, 2025 and 2030. We hold values constant for intervening years and
  2030 values are applied to years 2031 and beyond.

    The monetized PM2.5 health impacts of the final
standards are presented in Table 46. Using PM2.5-related BPT
values to monetize the non-GHG impacts of the final standards omits
ozone-related impacts, unquantified PM-related health impacts, as well
as other impacts associated with reductions in exposure to air toxics,
ecosystem benefits, and visibility improvement. Section V of this
preamble provides a qualitative description of both the health and
environmental effects of the non-GHG pollutants impacted by the final
program.

F. Energy Security Impacts

    This final rule will require reductions in the GHG emissions from
light-duty vehicles and, thereby, reduce fuel consumption. In turn,
this final rule will help to reduce U.S. petroleum imports. A reduction
of U.S. petroleum imports reduces both financial and strategic risks
caused by potential sudden disruptions in the supply of imported
petroleum to the U.S., thus increasing U.S. energy security. In other
words, reduced U.S. oil imports act as a ``shock absorber'' when there
is a supply disruption in world oil markets.
    Given that the U.S. is projected to be a net exporter of crude oil
and product over the time frame of the analysis of this final rule
(2023-2050), one could surmise that the U.S. no longer has a
significant energy security problem. However, U.S. refineries still
rely on significant imports of heavy crude oil from potentially
unstable regions of the world. Also, oil exporters with a large share
of global production have the ability to raise or lower the price of
oil by exerting market power through the Organization of Petroleum
Exporting Countries (OPEC) to alter oil supply relative to demand.
These factors contribute to the vulnerability of the U.S. economy to
episodic oil supply shocks and price spikes, even when the U.S. is
projected to be an overall net exporter of crude oil and product.
    In order to understand the energy security implications of reducing
U.S. oil imports, EPA has worked with Oak Ridge National Laboratory
(ORNL), which has developed approaches for evaluating the social costs
and energy security implications of oil use. When conducting this
analysis, ORNL considers the full cost of importing petroleum into the
U.S. The full economic cost (i.e., oil security premiums, as labeled
below) is defined to include two components in addition to the purchase
price of petroleum itself. These are: (1) The higher costs/benefits for
oil imports resulting from the effect of changes in U.S. demand on the
world oil price (i.e., the ``demand'' or ``monopsony'' costs/benefits);
and (2) the risk of reductions in U.S. economic output and disruption
to the U.S. economy caused by sudden disruptions in the supply of
imported oil to the U.S. (i.e., the avoided macroeconomic disruption/
adjustment costs). One commenter (American Enterprise Institute)
suggests that there are no energy security benefits associated with
this rule, since there is only one price in the international petroleum
market, confronted equally by economies importing all or none of their
oil. We disagree and believe that there are energy security benefits to
the U.S. from decreased exposure to volatile world oil prices. We
respond to this comment in more detail in the RTC.
    For this final rule, EPA is using oil security premiums estimated
using ORNL's methodology, which incorporates oil price projections and
energy market and economic trends from the EIA's Annual Energy Outlook
(AEO). Specifically, we are using oil security premiums based on AEO
2021, updating the oil security premiums from the AEO 2018 used in the
proposed rule. In addition, for this final rule, EPA and ORNL have
worked together to revise the oil security premiums based

upon recent energy security literature (see Chapter 3.2.5 of the RIA
accompanying this rule for how the macroeconomic oil security premiums
have been updated based upon a review of recent energy security
literature on this topic). These revisions have lowered the estimated
oil security premiums since the proposal of this rule. However, this
modest decrease in oil security premiums is offset by an increase in
fuel savings since the proposal, resulting in an overall increase in
energy security benefits for this final rule compared to the proposal.
    In our analysis, we only consider the avoided macroeconomic
disruption/adjustment costs in the oil security premiums (i.e., labeled
macroeconomic oil security premiums below), since the monopsony impacts
are considered transfer payments. Two commenters (Center for Biological
Diversity et al., CARB) suggest that EPA is underestimating the energy
security benefits of the final rule by not accounting for the monopsony
oil security impacts. EPA continues to believe that the monopsony
impacts of this rule are transfer payments. Therefore, EPA disagrees
that the energy security benefits of this final rule are underestimated
for this reason. See more discussion of the monopsony oil security
premiums in the RIA and RTC.
    Three commenters (Center for Biological Diversity et al., CARB,
SAFE) suggest that EPA understates the energy security benefits of the
final rule by not considering military cost impacts. One commenter
(American Enterprise Institute) suggests that reductions in military
costs from the rule would be imperceptible. While EPA believes that
military costs are important considerations, we continue to believe
that there are methodological limitations in our ability to quantify
these impacts (e.g., how a reduction of U.S. oil imports would
incrementally reduce oil supply protection forces). As a result, we do
not quantify military cost impacts for this final rule. (See Chapter
3.2.3 of the RIA for a review of the literature on the military costs
impacts of U.S. oil import reductions). In addition, some commenters
(Attorney General of Missouri, et al., SAFE, Alliance for Automotive
Innovation, an energy company, private citizens) express concern that
these standards would reduce U.S. security by increasing the U.S.'s
reliance on foreign countries (i.e., China) for electric vehicle
components such as electric batteries. We respond to both sets of
comments, military cost impacts and U.S. security implications of this
final rule, in more detail in the RTC.
    To calculate the energy security benefits of this final rule, EPA
is using the ORNL oil security premium methodology with: (1) Estimated
oil savings calculated by EPA and (2) an oil import reduction factor of
91 percent, which represents how much U.S. oil imports are reduced
resulting from changes in U.S. oil consumption. One commenter (Center
for Biological Diversity et al.) requests more explanation of how EPA
estimates the oil import reduction factor. The Alliance for Automotive
Innovation believes that U.S. refiners and oil producers may see a
greater reduction in fuel demand than EPA is estimating as a result of
this final rule. We continue to believe that EPA's use of the most
recent AEO 2021 provides a reasonable estimate of the oil import
reduction factor being used in this rule and also the impacts of this
rule on U.S. oil producers and refineries. We respond to both of these
comments in more detail in the RTC. Each of the assumptions used to
calculate the energy security benefits of this final rule, oil savings
and the oil import reduction factor, are discussed in more detail in
Chapter 3.2 of the RIA. EPA presents the macroeconomic oil security
premiums used for the final standards for selected years from 2023-2050
in Table 42.

  Table 42--Macroeconomic Oil Security Premiums for Selected Years From
                                2023-2050
                            [2018$/Barrel] *
------------------------------------------------------------------------
                                             Macroeconomic oil security
               Year (range)                       premiums (range)
------------------------------------------------------------------------
2023......................................  $3.15 ($0.92-$5.71).
2026......................................  $3.23 ($0.74-$6.00).
2030......................................  $3.41 ($0.62-$6.41).
2035......................................  $3.76 ($0.70-$7.05).
2040......................................  $4.21 ($1.04-$7.77).
2050......................................  $4.94 ($1.46-$8.91).
------------------------------------------------------------------------
* Top values in each cell are the midpoints, the values in parentheses
  are the 90 percent confidence intervals.

G. Impacts of Additional Driving

    As discussed in Chapter 3.1 of the RIA, the assumed rebound effect
might occur when an increase in vehicle fuel efficiency encourages
people to drive more as a result of the lower cost per mile of driving.
Along with the safety considerations associated with increased vehicle
miles traveled (described in Section VII.H of this preamble),
additional driving can lead to other costs and benefits that can be
monetized. For a discussion of these impacts--Drive Value, Congestion,
Noise--all of which are calculated in the same way as done in the
proposed rule, see RIA Chapter 3.4. EPA did not receive any comments on
these elements of our proposal.

H. Safety Considerations in Establishing GHG Standards

    Consistent with previous light-duty GHG analyses, EPA has assessed
the potential of the final MY 2023-2026 standards to affect vehicle
safety. EPA applied the same historical relationships between mass,
size, and fatality risk that were established and documented in the
SAFE rulemaking. These relationships are based on the statistical
analysis of historical crash data, which included an analysis performed
by using the most recently available crash studies based on data for
model years 2007 to 2011. EPA used the findings of this analysis to
estimate safety impacts of the modeled mass reductions over the
lifetimes of new vehicles in response to MY 2023-2026 standards. As in
the initial promulgation of the GHG standards and the MTE Proposed
Determination, EPA's assessment in this rulemaking is that
manufacturers can achieve the MY 2023-2026 standards while using modest
levels of mass reduction as one technology option among many. On the
whole, EPA considers safety impacts in the context of all projected
health impacts from the rule including public health benefits from the
projected reductions in air pollution. Based on the findings of our
safety analysis, we concluded there are no changes to the vehicles
themselves, nor the combined effects of fleet composition and vehicle
design, that will have a statistically significant impact on safety.
All fatalities that are statistically significant are due to changes in
use (VMT) rather than changes to the vehicles themselves.
    The projected change in risk of fatal and non-fatal injuries is
influenced by changes in fleet mix (car/truck share), vehicle scrappage
rates, distribution of VMT among vehicles in the fleet and vehicle
mass. Because the empirical analysis described previously did not
produce any mass-safety coefficients with a statistically significant
difference from zero, we analyzed safety results over the range of
coefficient values. We project that the effect of the final standards
on annual fatalities per billion miles driven ranges from a decrease of
0.25 percent to an increase of 0.36 percent, with a central estimate of
a 0.06 percent increase.\228\
---------------------------------------------------------------------------

    \228\ These fatality risk values are the average of changes in
annual risk through 2050. The range of values is based on the 5% to
95% confidence interval of mass-safety coefficients presented in the
SAFE FRM.

---------------------------------------------------------------------------

    In addition to changes in risk, EPA also considered the projected
impact of the standards on the absolute number of fatal and non-fatal
injuries. The majority of the fatalities projected would result from
the projected increased driving--i.e., people choosing to drive more
due to the lower operating costs of more efficient vehicles. Our cost-
benefit analysis accounts for both the value of this additional driving
and its associated risk, which we assume are considerations in the
decision to drive. The risk valuation associated with this increase in
driving partially offsets the associated increase in societal costs due
to increased fatalities and non-fatal injuries.
    This analysis projects that there will be an increase in VMT under
the standards of 304 billion miles compared to the No Action scenario
through 2050 (an increase of about 0.3 percent). EPA estimates that
vehicle safety, in terms of risk measured as the total fatalities per
the total distance traveled over this period, will remain almost
unchanged at 5.012 fatalities per billion miles under the final rule,
compared to 5.010 fatalities per billion miles for the no-action
scenario. EPA has also estimated, over the same 30 year period, that
total fatalities will increase by 1,780, with 1,348 deaths attributed
to increased driving and 432 deaths attributed to the increase in
fatality risk. In other words, approximately 75 percent of the change
in fatalities under these standards is due to projected increases in
VMT and mobility (i.e., people driving more). Our analysis also
considered the increase in non-fatal injuries. Consistent with the SAFE
FRM, EPA assumed that non-fatal injuries scale with fatal injuries.
    EPA also estimated the societal costs of these safety impacts using
assumptions consistent with the SAFE FRM (see Table 43.) Specifically,
we are continuing to use the cost associated with each fatality of
$10.4 million (2018 dollars). We have also continued to use a scalar of
approximately 1.6 applied to fatality costs to estimate non-fatal
injury costs. In addition, we have accounted for the driver's inherent
valuation of risk when making the decision to drive more due to
rebound. This risk valuation partially offsets the fatal and non-fatal
injury costs described previously, and, consistent with the SAFE FRM,
is calculated as 90 percent of the fatal and non-fatal injury costs due
to rebound to reflect the fact that consumers do not fully evaluate the
risks associated with this additional driving.

I. Summary of Costs and Benefits

    This section presents a summary of costs, benefits, and net
benefits of the program. Table 43 shows the estimated annual monetized
costs of the program for the indicated calendar years. The table also
shows the present-values (PV) of those costs and the annualized costs
for the calendar years 2021-2050 using both 3 percent and 7 percent
discount rates.\229\ The table includes an estimate of foregone
consumer sales surplus, which measures the loss in benefits attributed
to consumers who would have purchased a new vehicle in the absence of
the final standards.
---------------------------------------------------------------------------

    \229\ For the estimation of the stream of costs and benefits, we
assume that after implementation of the MY 2023-2026 standards, the
2026 standards apply to each year thereafter.

                                                    Table 43--Costs Associated With the Final Program
                                                               [Billions of 2018 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                             Foregone
              Calendar year               consumer sales    Technology      Congestion         Noise      Fatality costs     Non-fatal      Total costs
                                            surplus \a\        costs                                                        crash costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
2023....................................          $0.029            $5.6           $0.03        $0.00045           $0.13           $0.23            $6.1
2026....................................            0.11              16            0.12           0.002            0.42             0.7              17
2030....................................           0.093              17             0.4          0.0067            0.44            0.73              19
2035....................................           0.078              17            0.68           0.011            0.27            0.44              19
2040....................................           0.063              16            0.84           0.014            0.15            0.25              17
2050....................................           0.052              15             0.9           0.015            0.16            0.25              16
PV, 3%..................................             1.3             280             9.6            0.16             4.9             8.1             300
PV, 7%..................................            0.84             160             4.8            0.08             3.2             5.3             180
Annualized, 3%..........................           0.069              14            0.49          0.0082            0.25            0.42              15
Annualized, 7%..........................           0.068              13            0.39          0.0065            0.26            0.43              14
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ ``Foregone Consumer Sales Surplus'' refers to the difference between a vehicle's price and the buyer's willingness to pay for the new vehicle; the
  impact reflects the reduction in new vehicle sales described in Section VII.B of this preamble. See Section 8 of CAFE_Model_Documentation_FR_2020.pdf
  in the docket for more information.

    Table 44 shows the undiscounted annual monetized fuel savings of
the program. The table also shows the present- and annualized-values of
those fuel savings for the same calendar years using both 3 percent and
7 percent discount rates. The net benefits calculations use the
aggregate value of fuel savings (calculated using pre-tax fuel prices)
since savings in fuel taxes do not represent a reduction in the value
of economic resources utilized in producing and consuming fuel. Note
that the fuel savings shown in Table 44 result from reductions in
fleet-wide fuel use (including rebound effects, credit usage and
advanced technology multiplier use). Thus, fuel savings grow over time
as an increasing fraction of the fleet is projected to meet the
standards.

                            Table 44--Fuel Savings Associated With the Final Program
                                           [Billions of 2018 dollars]
----------------------------------------------------------------------------------------------------------------
                                                                    Retail fuel      Fuel tax      Pre-tax fuel
                          Calendar year                               savings         savings         savings
----------------------------------------------------------------------------------------------------------------
2023............................................................           $0.94           $0.31           $0.62
2026............................................................             5.1             1.7             3.3
2030............................................................              16             4.5              12

2035............................................................              28             7.1              21
2040............................................................              37             8.5              29
2050............................................................              42             8.6              33
PV, 3%..........................................................             420             100             320
PV, 7%..........................................................             210              51             150
Annualized, 3%..................................................              21             5.1              16
Annualized, 7%..................................................              17             4.1              12
----------------------------------------------------------------------------------------------------------------
Note: Electricity expenditure increases are included.

    Table 45 presents estimated annual monetized benefits from non-
emission sources for the indicated calendar years. The table also shows
the present- and annualized-value of those benefits for the calendar
years 2021-2050 using both 3 percent and 7 percent discount rates.

                                  Table 45--Benefits From Non-Emission Sources
                                           [Billions of 2018 dollars]
----------------------------------------------------------------------------------------------------------------
                                                                                Energy        Total non-
                  Calendar year                     Drive value   Refueling time     security        emission
                                                                      savings        benefits        benefits
----------------------------------------------------------------------------------------------------------------
2023............................................          $0.035        -$0.0052          $0.031          $0.061
2026............................................            0.14           -0.12            0.18             0.2
2030............................................            0.55           -0.27            0.51            0.79
2035............................................               1           -0.47            0.92             1.5
2040............................................             1.3           -0.67             1.3             1.9
2050............................................             1.5           -0.83             1.6             2.3
PV, 3%..........................................              15            -7.4              14              21
PV, 7%..........................................             7.2            -3.6               7              11
Annualized, 3%..................................            0.75           -0.38            0.73             1.1
Annualized, 7%..................................            0.58           -0.29            0.56            0.85
----------------------------------------------------------------------------------------------------------------
* See Section VII.G, Section VII.C and Section VII.F of this preamble for more on drive value, refueling time
  and energy security, respectively.

    Table 46 presents estimated annual monetized benefits from non-GHG
emission sources for the indicated calendar years. The table also shows
the present- and annualized-values of those benefits for the calendar
years 2021-2050 using both 3 percent and 7 percent discount rates.

                                                   Table 46--PM2.5-Related Emission Reduction Benefits
                                                           [Billions of 2018 dollars] \a\ \b\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                 Tailpipe benefits               Upstream benefits         Total PM2.5-related benefits
                                                         ----------------------------------------------------------------
                      Calendar year                                                                                -------------------------------
                                                               3% DR           7% DR           3% DR           7% DR           3% DR           7% DR
--------------------------------------------------------------------------------------------------------------------------------------------------------
2023....................................................        -$0.0034        -$0.0031           $0.02          $0.018          $0.016          $0.015
2026....................................................           0.018           0.016           0.097           0.088            0.11             0.1
2030....................................................            0.15            0.13            0.45            0.41             0.6            0.54
2035....................................................            0.44             0.4            0.79            0.72             1.2             1.1
2040....................................................            0.68            0.62               1            0.95             1.7             1.6
2050....................................................            0.89             0.8             1.4             1.3             2.3             2.1
PV......................................................             6.7             2.8              12             5.3              19             8.1
Annualized..............................................            0.34            0.22            0.61            0.43            0.96            0.65
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\a\ Note that the non-GHG impacts associated with the standards presented here do not include the full complement of health and environmental effects
  that, if quantified and monetized, would increase the total monetized benefits. Instead, the non-GHG benefits are based on benefit-per-ton values that
  reflect only human health impacts associated with reductions in PM2.5 exposure.
\b\ Calendar year non-GHG benefits presented in this table assume either a 3 percent or 7 percent discount rate in the valuation of PM-related premature
  mortality to account for a twenty-year segmented cessation lag. Note that annual benefits estimated using a 3 percent discount rate were used to
  calculate the present and annualized values using a 3 percent discount rate and the annual benefits estimated using a 7 percent discount rate were
  used to calculate the present and annualized values using a 7 percent discount rate.

    Table 47 shows the benefits of reduced GHG emissions, and
consequently the annual quantified benefits (i.e., total GHG benefits),
for each of the four interim social cost of GHG (SC-GHG) values
estimated by the interagency working group. As discussed in the RIA
Chapter 3.3, there are some limitations to the SC-GHG analysis,
including the incomplete way in which the integrated assessment models
capture catastrophic and non-

catastrophic impacts, their incomplete treatment of adaptation and
technological change, uncertainty in the extrapolation of damages to
high temperatures, and assumptions regarding risk aversion.

                           Table 47--Climate Benefits From Reductions in GHG Emissions
                                           [Billions of 2018 dollars]
----------------------------------------------------------------------------------------------------------------
                                                                    Discount rate and statistic
                                                 ---------------------------------------------------------------
                  Calendar year                                                                       3% 95th
                                                    5% average      3% average     2.5% average     percentile
----------------------------------------------------------------------------------------------------------------
2023............................................          $0.081           $0.27            $0.4            $0.8
2026............................................            0.48             1.6             2.3             4.7
2030............................................             1.5             4.6             6.7              14
2035............................................             2.8             8.4              12              25
2040............................................             3.9              11              16              34
2050............................................             5.5              14              20              44
PV..............................................              31             130             200             390
Annualized......................................               2             6.6             9.5              20
----------------------------------------------------------------------------------------------------------------
Notes: The present value of reduced GHG emissions is calculated differently than other benefits. The same
  discount rate used to discount the value of damages from future emissions (SC-GHGs at 5, 3, 2.5 percent) is
  used to calculate the present value of SC-GHGs for internal consistency. Annual benefits shown are
  undiscounted values.

    Table 48 presents estimated annual net benefits for the indicated
calendar years. The table also shows the present and annualized value
of those net benefits for the calendar years 2021-2050 using both 3
percent and 7 percent discount rates. The table includes the benefits
of reduced GHG emissions (and consequently the annual net benefits) for
each of the four SC-GHG values considered by EPA. We estimate that the
total benefits of the program far exceed the costs and would result in
a net present value of benefits that ranges between $27-$450 billion,
depending on which SC-GHG and discount rate is assumed.

   Table 48--Net Benefits (Emission Benefits + Non-Emission Benefits + Fuel Savings-Costs) Associated With the
                                                  Final Program
                                       [Billions of 2018 dollars] \a\ \b\
----------------------------------------------------------------------------------------------------------------
                                                                                Net benefits,
                                                   Net benefits,   Net benefits,   Net benefits,   with climate
                                                   with climate    with climate    with climate   benefits based
                  Calendar year                   benefits based  benefits based  benefits based  on 3% discount
                                                  on 5% discount  on 3% discount      on 2.5%       rate, 95th
                                                       rate            rate        discount rate  percentile SC-
                                                                                GHG
----------------------------------------------------------------------------------------------------------------
2023............................................           -$5.3           -$5.1             -$5           -$4.6
2026............................................             -13             -12             -11            -9.1
2030............................................            -4.6            -1.4            0.63             7.9
2035............................................             7.8              13              17              30
2040............................................              19              26              31              49
2050............................................              27              36              41              66
PV, 3%..........................................              88             190             260             450
PV, 7%..........................................              27             120             190             390
Annualized, 3%..................................             4.9             9.5              12              23
Annualized, 7%..................................             1.7             6.2             9.2              20
----------------------------------------------------------------------------------------------------------------
Notes:
\a\ The present value of reduced GHG emissions is calculated differently than other benefits. The same discount
  rate used to discount the value of damages from future emissions (SC-GHG at 5, 3, 2.5 percent) is used to
  calculate present value of SC-GHGs for internal consistency, while all other costs and benefits are discounted
  at either 3% or 7%. Annual costs and benefits shown are undiscounted values.
\b\ Note that the non-GHG impacts associated with the standards presented here do not include the full
  complement of health and environmental effects that, if quantified and monetized, would increase the total
  monetized benefits. Instead, the non-GHG benefits are based on benefit-per-ton values that reflect only human
  health impacts associated with reductions in PM2.5 exposure.

J. Impacts on Consumers of Vehicle Costs and Fuel Savings

    Although the primary purpose of this regulatory action is to reduce
GHG emissions, the impact of EPA's standards on consumers is an
important consideration for EPA. This section discusses the impact of
the standards on consumer net costs for purchasing and fueling
vehicles. For further discussion of impacts on vehicle sales, see
Section VII.B of this preamble and for impacts on affordability, see
Section VII.M of this preamble.
    EPA estimates that the average cost of a new MY 2026 vehicle will
increase by $1,000 due to the final standards, while we estimate that
the average per-mile fuel cost in the first year will decrease by 0.73
cents.\230\ Over time, reductions

in fuel consumption will offset the increase in upfront costs. For
instance, EPA estimates that, over the lifetime of a MY 2026
vehicle,\231\ the reduction in fuel costs will exceed the increase in
vehicle costs by $1,083, using a 3 percent discount rate.\232\
---------------------------------------------------------------------------

    \230\ See U.S. Environmental Protection Agency, ``Fuel Savings
Offset to Vehicle Costs_20211031.xlsx,'' in the docket for this and
the other calculations in this section. Fuel prices are based on
AEO2021 and change over time; for the Reference Case, the average
retail fuel price for years 2026-2036 ranged from $2.53 to $2.98/
gallon (2020$) for gasoline and $0.118 to $0.119/kWh of electricity
(2020$). U.S. Energy Information Administration (EIA), U.S.
Department of Energy (DOE), Annual Energy Outlook, 2021. For the
analysis involving 5-year ownership periods, we use the fuel costs
associated with the initial year of purchase for each owner, i.e.,
2026, 2031, 2036. The analysis includes the program flexibilities of
credit banking, fleet averaging, advanced technology multipliers,
and air conditioning and off-cycle credits.
    \231\ The CCEMS models vehicles over a 30 year lifetime;
however, it includes scrappage rates such that fewer and fewer
vehicles of any vintage remain on the road year after year, and
those vehicles that remain are driven fewer and fewer miles year
after year.
    \232\ EPA Guidelines for Preparing Economic Analysis, Chapter
6.4, suggests that a 3 percent discount rate is appropriate for
calculations involving consumption, instead of the opportunity cost
of capital. Here, the discount rate is applied, beginning in 2026
when the vehicle is purchased new, to the stream of fuel costs over
the vehicle lifetime. U.S. Environmental Protection Agency (2010).
``Guidelines for Preparing Economic Analysis,'' Chapter 6. https://www.epa.gov/sites/production/files/2017-09/documents/ee-0568-06.pdf,
accessed 6/14/2021.
---------------------------------------------------------------------------

    Another way to look at the effects on vehicle buyers is to examine
how the costs are distributed among new and used vehicle owners.
Because depreciation occurs over the lifetime of the vehicle, the net
purchase cost to an owner will depend on the vehicle age when it was
bought, and, if sold, the length of time that the vehicle was owned. A
study from Argonne National Laboratory provides estimates for the
depreciation of light-duty vehicles by age, as summarized in Table
49.\233\ If the additional cost of fuel-saving technology depreciates
at the same rates, then a person who buys a new vehicle and sells it
after 5 years would incur 60 percent of the upfront costs (100 percent
of the original value, less 40 percent paid back). Analogously, the
person who buys the vehicle at age 5 would incur 20 percent of those
costs (40 percent, less 20 percent paid back), and the purchaser of the
10-year-old vehicle would face a net 10 percent of the cost of the
technology after it is sold five years later at vehicle age 15. A
person purchasing a new vehicle, driving the average fleetwide VMT for
the given age and facing the fuel prices used in this analysis, would
face an estimated net cost of $60, shown in Table 50, which reflects
fuel savings that offset 91 percent of the depreciation cost. The buyer
of that 5-year-old used vehicle would see an estimated reduction in net
cost--that is, a net saving--of $357, while the buyer of that same 10-
year-old used vehicle would see an estimated reduction of net cost of
$430. In general, the purchasers of older vehicles will see a greater
portion of their depreciation costs offset by fuel savings.
---------------------------------------------------------------------------

    \233\ Argonne National Laboratory (2021). ``Comprehensive Total
Cost of Ownership Quantification for Vehicles with Different Size
Classes and Powertrains.'' ANL/ESD-21/4, Figure ES-2. https://publications.anl.gov/anlpubs/2021/05/167399.pdf, accessed 6/8/2021.

                                                Table 49--Depreciation Estimates for Light Duty Vehicles
--------------------------------------------------------------------------------------------------------------------------------------------------------
                      Vehicle age                             1             2             3             4             5            10            15
--------------------------------------------------------------------------------------------------------------------------------------------------------
Fraction of original value retained...................         0.70          0.61          0.53         0.475          0.40          0.20          0.10
--------------------------------------------------------------------------------------------------------------------------------------------------------
Estimated by Argonne National Laboratory using Edmunds data for MYs 2013-2019 vehicles (see figure ES-2).\233\

Table 50--Impact of Standards on Depreciation and Fuel Costs for MY 2026
                    Vehicle Over 5 Years of Ownership
------------------------------------------------------------------------
                                                            Portion of
                                              Vehicle      depreciation
                                           depreciation    costs offset
                                             plus fuel        by fuel
                                               costs        savings (%)
------------------------------------------------------------------------
Vehicle Purchased New...................             $60              91
Vehicle Purchased at Age 5..............          ($357)             257
Vehicle Purchased at Age 10.............          ($430)             478
------------------------------------------------------------------------
Calculated using analysis VMT assumptions for standards, using a 3%
  discount rate from year of purchase.

    Because the use of vehicles varies widely across vehicle owners,
another way to estimate the effects of the standards is to examine the
``break even'' number of miles--that is, the number of miles driven
that would result in fuel savings matching the increase in up-front
costs. For example, if operating costs of a MY 2026 vehicle decrease by
0.73 cents per mile due to reduced fuel consumption, the upfront costs
(when purchased new) would be recovered after 137,000 miles of driving,
excluding discounting.\234\ As this measure makes clear, the financial
effect on a new vehicle owner depends on the amount that the vehicle is
driven. Mobility service providers, such as taxis or ride-sharing
services, are likely to accumulate miles more quickly than most people
who use their vehicles for personal use. As discussed in Section VII.M
of this preamble, the lower per-mile cost for these vehicles may reduce
the importance of up-front costs in the charge for mobility as a
service, and thus further enable use of that service.
---------------------------------------------------------------------------

    \234\ This estimate is calculated as the increase in cost,
$1,000, divided by the reduced per-mile cost, $0.0073, to get miles
until cost is recovered.
---------------------------------------------------------------------------

    Table 51 shows, for purchasers of different-age MY 2026 vehicles,
how the degree to which fuel savings offset depreciation costs will
depend on vehicle use levels.\235\ Cost recovery is again higher for
older vehicles, and faster for vehicles that accumulate VMT more
quickly. For example, a consumer who purchases a 5-year old used MY
2026 vehicle would recover their vehicle costs through fuel savings
after only 23,000 miles of driving.
---------------------------------------------------------------------------

    \235\ The up-front costs for each purchaser are based on the
cost to the owner based on the depreciated price for the vehicle's
age, with recovery of some further depreciated cost after 5 years of
ownership. Cost recovery per mile is $0.0073, and is multiplied by
the number of miles in the second column. The remaining columns are
cost recovery divided by the relevant cost. Discounting is not used
to abstract from the VMT occurring during a specified timeframe.

Table 51--Proportion of Depreciation Costs Offset by Fuel Savings, for New and Used Vehicle Purchasers, for a MY
                                                  2026 Vehicle
----------------------------------------------------------------------------------------------------------------
                                                                                When vehicle    When vehicle
                                                                   When vehicle   purchased at 5   purchased at
                                                                   purchased new     years old     10 years old
----------------------------------------------------------------------------------------------------------------
Portion of vehicle depreciation      At 10,000 miles............             12%             43%             93%
 cost offset by fuel savings (own
 vehicle for 5 years).
                                     At 50,000 miles............             61%            214%            467%
                                     At 100,000 miles...........            122%            428%            933%
Miles where fuel savings fully       Owned vehicle for 5 years..          82,000          23,000          11,000
 offset the vehicle owner's
 depreciation cost.
                                     Owned vehicle for full              137,000          47,000          21,000
                                      remaining lifetime.
----------------------------------------------------------------------------------------------------------------

    Thus, the financial effects on a vehicle buyer depend on how much
that person drives, as well as whether the vehicle is bought new or
used. Importantly, all people receive the benefits of reduced GHG
emissions, the primary focus of this rule.

K. Employment Impacts

    Several commenters, including the Alliance, Blue-Green Alliance,
International Union, United Automobile, Aerospace & Agricultural
Implement Workers of America (UAW), SAFE (Securing America's Future
Energy), and a coalition of 25 Great Lakes and Midwest environmental
organizations, indicated that domestic employment effects, especially
in the auto industry, are an important impact of the standards. The
Blue-Green Alliance, Ceres, Environmental Entrepreneurs, EDF,
Environmental Law and Policy Center, EOS at Federated Hermes, New
Mexico Environment Department, New York State Department of
Environmental Conservation, and the coalition of organizations argue
that strong standards contribute to job-supporting domestic
manufacturing. CBD et al. considers EPA's employment estimates to be
too low, by not considering impacts in the broader economy. National
Coalition for Advanced Transportation, SAFE and Alliance discuss the
role of domestic supply chains for electric vehicles in promoting
domestic employment. The UAW notes their involvement in building these
``vehicles of the future.'' Volkswagen describes its partnership with
Chattanooga State Community College to train workers in next-generation
auto manufacturing skills. EPA acknowledges these comments and
recognizes employment impacts as an important impact to be assessed,
and thus we present an assessment of impacts of these standards on
employment.
    If the U.S. economy is at full employment, even a large-scale
environmental regulation is unlikely to have a noticeable impact on
aggregate net employment.\236\ Instead, labor would primarily be
reallocated from one productive use to another, and net national
employment effects from environmental regulation would be small and
transitory (e.g., as workers move from one job to another).\237\
Affected sectors may nevertheless experience transitory effects as
workers change jobs. Some workers may retrain or relocate in
anticipation of new requirements or require time to search for new
jobs, while shortages in some sectors or regions could bid up wages to
attract workers. These adjustment costs can lead to local labor
disruptions. Even if the net change in the national workforce is small,
localized reductions in employment may adversely impact individuals and
communities just as localized increases may have positive impacts.
---------------------------------------------------------------------------

    \236\ Full employment is a conceptual target for the economy
where everyone who wants to work and is available to do so at
prevailing wages is actively employed. The unemployment rate at full
employment is not zero.
    \237\ Arrow et al. (1996). ``Benefit-Cost Analysis in
Environmental, Health, and Safety Regulation: A Statement of
Principles.'' American Enterprise Institute, The Annapolis Center,
and Resources for the Future. See discussion on bottom of p. 6. In
practice, distributional impacts on individual workers can be
important, as discussed later in this section.
---------------------------------------------------------------------------

    If the economy is operating at less than full employment, economic
theory does not clearly indicate the direction or magnitude of the net
impact of environmental regulation on employment; it could cause either
a short-run net increase or short-run net decrease.\238\ At the level
of individual companies, employers affected by environmental regulation
may increase their demand for some types of labor, decrease demand for
other types of labor, or for still other types, not change it at all.
The uncertain direction of labor impacts is due to the different
channels by which regulations affect labor demand.
---------------------------------------------------------------------------

    \238\ Schmalensee, Richard, and Stavins, Robert N. ``A Guide to
Economic and Policy Analysis of EPA's Transport Rule.'' White paper
commissioned by Excelon Corporation, March 2011.
---------------------------------------------------------------------------

    Morgenstern et al. (2002) \239\ decompose the labor consequences in
a regulated industry facing increased abatement costs into three
separate components. First, there is a demand effect caused by higher
production costs raising market prices. Higher prices reduce
consumption (and production), reducing demand for labor within the
regulated industry. Second, there is a cost effect where, as production
costs increase, plants use more of all inputs, including labor, to
produce the same level of output. Third, there is a factor-shift effect
where post-regulation production technologies may have different labor
intensities. Other researchers use different frameworks along a similar
vein.\240\
---------------------------------------------------------------------------

    \239\ Morgenstern, R.D.; Pizer, W.A.; and Shih, J.-S. (2002).
``Jobs Versus the Environment: An Industry-Level Perspective.''
Journal of Environmental Economics and Management 43: 412-436. 2002.
    \240\ Berman, E. and Bui, L. T. M. (2001). ``Environmental
Regulation and Labor Demand: Evidence from the South Coast Air
Basin.'' Journal of Public Economics 79(2): 265-295;
Desch[ecirc]nes, O. (2018). ``Balancing the Benefits of
Environmental Regulations for Everyone and the Costs to Workers and
Firms.'' IZA World of Labor 22v2. https://wol.iza.org/uploads/articles/458/pdfs/environmental-regulations-and-labor-markets.pdf,
accessed 4/19/2021.
---------------------------------------------------------------------------

    RIA Chapter 8.2 discusses the calculation of employment impacts in
the model used for this analysis. The estimates include effects on
three sectors: Automotive dealers, final assembly labor and parts
production, and fuel economy technology labor. The first two of these
are examples of Morgenstern et al.'s (2002) demand-effect employment,
while the third reflects cost-effect employment. For automotive
dealers, the model estimates the hours involved in each new vehicle
sale. To estimate the labor involved in final assembly, the model used
average labor hours per vehicle at a sample of U.S. assembly plants,
adjusted by the ratio of vehicle assembly manufacturing employment to
employment for total

vehicle and equipment manufacturing for new vehicles. Finally, for fuel
economy technology labor, DOT calculated the average revenue per job-
year for automakers.
    The new-vehicle demand elasticity, among other factors, affects
employment impacts because it affects the estimated changes in new
vehicle sales due to the standards. In the proposed rule, EPA's central
analysis used a new-vehicle demand elasticity of -1, with a sensitivity
analysis using -0.4 as the demand elasticity. As discussed in Section
VII.B of this preamble, in this FRM, EPA's central case uses a new-
vehicle demand elasticity of -0.4, with sensitivities of -0.15 and -1,
due to evidence that the value of -1 used in the proposed rule, from
older studies, is no longer supported by recent studies. EPA's
assessment of employment impacts, in RIA Chapter 8.2.3, using the sales
assumptions of both automakers and consumers using 2.5 years of fuel
consumption in vehicle decisions and a demand elasticity of -0.4, shows
an increase in employment of between about 1 and 2.4 percent due to the
labor involved in producing the technologies needed to meet the
standards. If, instead, we use the sensitivity analysis with a demand
elasticity of -0.15, employment is higher for both the no-action
alternative and the standards, but the percent change is almost the
same. In contrast, in our sensitivity analysis using the -1 demand
elasticity, which EPA now believes is outdated, employment increases by
between 0 and 0.7 percent. If automakers underestimate consumers'
valuation of fuel economy, as noted in Section VII.B of this preamble,
then demand-effect employment is likely to be higher, and employment
impacts are likely to be more positive.
    Note that these are employment impacts in the directly regulated
sector, plus the impacts for automotive dealers. These do not include
economy-wide labor impacts. As discussed earlier, economy-wide impacts
on employment are generally driven by broad macroeconomic effects. It
also does not reflect employment effects due to reduced spending on
fuel consumption. Those changes may lead to some reductions in
employment in gas stations, and some increases in other sectors to
which people reallocate those expenditures.
    Electrification of the vehicle fleet is likely to affect both the
number and the nature of employment in the auto and parts sectors and
related sectors, such as providers of charging infrastructure. The
kinds of jobs in auto manufacturing are expected to change: For
instance, there will be no need for engine and exhaust system assembly
for EVs, while many assembly tasks will involve electrical rather than
mechanical fitting. Batteries represent a significant portion of the
manufacturing content of an electrified vehicle, and some automakers
are likely to purchase the cells, if not pre-assembled modules or
packs, from suppliers. The effect on total employment for auto
manufacturing is uncertain: Some suggest that fewer workers will be
needed because BEVs have fewer moving parts,\241\ while others estimate
that the labor-hours involved in BEVs are almost identical to that for
ICE vehicles.\242\ Effects in the supply chain, as Securing America's
Energy Future (SAFE) and Alliance noted, depend on where goods in the
supply chain are developed. Blue-Green Alliance, BICEP, Ceres,
Environmental Entrepreneurs, Elders Climate Action, SAFE, and the UAW
all argue that developing EVs in the U.S. is critical for domestic
employment and for the global competitiveness of the U.S. in the future
auto industry. EPA agrees that these concerns are important and will
continue to assess changes in employment associated with
electrification of the auto industry.
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    \241\ Krisher, T., and Seewer, J. (2021). ``Autoworkers face
uncertain future in an era of electric cars.'' https://abcnews.go.com/US/wireStory/autoworkers-face-dimmer-future-era-electric-cars-75828610, accessed 10/20/2021.
    \242\ Kupper, D., K. Kuhlmann, K. Tominaga, A. Arora, and J.
Schlageter (2020). ``Shifting Gears in Auto Manufacturing.'' https://www.bcg.com/publications/2020/transformative-impact-of-electric-vehicles-on-auto-manufacturing, accessed 10/20/2021.
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L. Environmental Justice

    Executive Order 12898 (59 FR 7629, February 16, 1994) establishes
federal executive policy on environmental justice. It directs federal
agencies, to the greatest extent practicable and permitted by law, to
make achieving 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 U.S. EPA defines environmental justice as the fair
treatment and meaningful involvement of all people regardless of race,
color, national origin, or income with respect to the development,
implementation, and enforcement of environmental laws, regulations, and
policies.\243\
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    \243\ Fair treatment means that ``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.'' Meaningful involvement occurs when ``(1)
potentially affected populations have an appropriate opportunity to
participate in decisions about a proposed activity [e.g.,
rulemaking] that will affect their environment and/or health; (2)
the public's contribution can influence [EPA's rulemaking] decision;
(3) the concerns of all participants involved will be considered in
the decision-making process; and (4) [EPA will] seek out and
facilitate the involvement of those potentially affected'' A
potential EJ concern is defined as ``the 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.'' See ``Guidance on Considering
Environmental Justice During the Development of an Action.''
Environmental Protection Agency, www.epa.gov/environmentaljustice/guidanceconsidering-environmental-justice-duringdevelopment-action.
See also https://www.epa.gov/environmentaljustice.
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    Executive Order 14008 (86 FR 7619, February 1, 2021) also calls on
federal agencies to make achieving environmental justice part of their
respective 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.''
    Under Executive Order 13563 (76 FR 3821, January 21, 2011), federal
agencies may consider equity, human dignity, fairness, and
distributional considerations in their regulatory analyses, where
appropriate and permitted by law.
    EPA's 2016 ``Technical Guidance for Assessing Environmental Justice
in Regulatory Analysis'' provides recommendations on conducting the
highest quality analysis feasible, recognizing that data limitations,
time and resource constraints, and analytic challenges will vary by
media and regulatory context.\244\
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    \244\ ``Technical Guidance for Assessing Environmental Justice
in Regulatory Analysis.'' Epa.gov, Environmental Protection Agency,
https://www.epa.gov/sites/production/files/2016-06/documents/ejtg_5_6_16_v5.1.pdf.
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    When assessing the potential for disproportionately high and
adverse health or environmental impacts of regulatory actions on
populations of color, low-income populations, tribes, and/or indigenous
peoples, EPA strives

to answer three broad questions: (1) Is there evidence of potential EJ
concerns in the baseline (the state of the world absent the regulatory
action)? Assessing the baseline will allow EPA to determine whether
pre-existing disparities are associated with the pollutant(s) under
consideration (e.g., if the effects of the pollutant(s) are more
concentrated in some population groups). (2) Is there evidence of
potential EJ concerns for the regulatory option(s) under consideration?
Specifically, how are the pollutant(s) and its effects distributed for
the regulatory options under consideration? (3) Do the regulatory
option(s) under consideration exacerbate or mitigate EJ concerns
relative to the baseline? It is not always possible to quantitatively
assess these questions.
    EPA's 2016 Technical Guidance does not prescribe or recommend a
specific approach or methodology for conducting an environmental
justice analysis, though a key consideration is consistency with the
assumptions underlying other parts of the regulatory analysis when
evaluating the baseline and regulatory options. Where applicable and
practicable, the Agency endeavors to conduct such an analysis. Going
forward, EPA is committed to conducting environmental justice analysis
for rulemakings based on a framework similar to what is outlined in
EPA's Technical Guidance, in addition to investigating ways to further
weave environmental justice into the fabric of the rulemaking process.
EPA greatly values input from EJ stakeholders and communities and looks
forward to engagement as we consider the impacts of light-duty vehicle
emissions.
1. GHG Impacts
    In 2009, under the Endangerment and Cause or Contribute Findings
for Greenhouse Gases Under Section 202(a) of the Clean Air Act
(``Endangerment Finding''), the Administrator considered how climate
change threatens the health and welfare of the U.S. population. As part
of that consideration, she also considered risks to minority and low-
income individuals and communities, finding that certain parts of the
U.S. population may be especially vulnerable based on their
characteristics or circumstances. These groups include economically and
socially disadvantaged communities; individuals at vulnerable
lifestages, such as the elderly, the very young, and pregnant or
nursing women; those already in poor health or with comorbidities; the
disabled; those experiencing homelessness, mental illness, or substance
abuse; and/or Indigenous or minority populations dependent on one or
limited resources for subsistence due to factors including but not
limited to geography, access, and mobility.
    Scientific assessment reports produced over the past decade by the
U.S. Global Change Research Program (USGCRP),\245\ \246\ the
Intergovernmental Panel on Climate Change (IPCC),\247\ \248\ \249\
\250\ and the National Academies of Science, Engineering, and Medicine
\251\ \252\ add more evidence that the impacts of climate change raise
potential environmental justice concerns. These reports conclude that
poorer or predominantly non-White communities can be especially
vulnerable to climate change impacts because they tend to have limited
adaptive capacities and are more dependent on climate-sensitive
resources such as local water and food supplies, or have less access to
social and information resources. Some communities of color,
specifically populations defined jointly by ethnic/racial
characteristics and geographic location, may be uniquely vulnerable to
climate change health impacts in the U.S. In particular, the 2016
scientific assessment on the Impacts of Climate Change on Human Health
\253\ found with high confidence that vulnerabilities are place- and
time-specific, lifestages and ages are linked to immediate and future
health impacts, and social determinants of health are linked to greater
extent and severity of climate change-related health impacts.
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    \245\ USGCRP, 2018: Impacts, Risks, and Adaptation in the United
States: Fourth National Climate Assessment, Volume II [Reidmiller,
D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K.
Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research
Program, Washington, DC, USA, 1515 pp. doi: 10.7930/NCA4.2018.
    \246\ USGCRP, 2016: The Impacts of Climate Change on Human
Health in the United States: A Scientific Assessment. Crimmins, A.,
J. Balbus, J.L. Gamble, C.B. Beard, J.E. Bell, D. Dodgen, R.J.
Eisen, N. Fann, M.D. Hawkins, S.C. Herring, L. Jantarasami, D.M.
Mills, S. Saha, M.C. Sarofim, J. Trtanj, and L. Ziska, Eds. U.S.
Global Change Research Program, Washington, DC, 312 pp. http://dx.doi.org/10.7930/J0R49NQX.
    \247\ Oppenheimer, M., M. Campos, R.Warren, J. Birkmann, G.
Luber, B. O'Neill, and K. Takahashi, 2014: Emergent risks and key
vulnerabilities. In: Climate Change 2014: Impacts, Adaptation, and
Vulnerability. Part A: Global and Sectoral Aspects. Contribution of
Working Group II to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros,
D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee,
K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N.
Levy, S. MacCracken, P.R. Mastrandrea, and L.L.White (eds.)].
Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, pp. 1039-1099.
    \248\ Porter, J.R., L. Xie, A.J. Challinor, K. Cochrane, S.M.
Howden, M.M. Iqbal, D.B. Lobell, and M.I. Travasso, 2014: Food
security and food production systems. In: Climate Change 2014:
Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral
Aspects. Contribution of Working Group II to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change [Field,
C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E.
Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma,
E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and
L.L.White (eds.)]. Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, pp. 485-533.
    \249\ Smith, K.R., A.Woodward, D. Campbell-Lendrum, D.D. Chadee,
Y. Honda, Q. Liu, J.M. Olwoch, B. Revich, and R. Sauerborn, 2014:
Human health: Impacts, adaptation, and co-benefits. In: Climate
Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global
and Sectoral Aspects. Contribution of Working Group II to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change
[Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea,
T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B.
Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and
L.L. White (eds.)]. Cambridge University Press, Cambridge, United
Kingdom and New York, NY, USA, pp. 709-754.
    \250\ IPCC, 2018: Global Warming of 1.5 [deg]C. An IPCC Special
Report on the impacts of global warming of 1.5 [deg]C above pre-
industrial levels and related global greenhouse gas emission
pathways, in the context of strengthening the global response to the
threat of climate change, sustainable development, and efforts to
eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. P[ouml]rtner,
D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C.
P[eacute]an, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X.
Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T.
Waterfield (eds.)]. In Press.
    \251\ National Research Council. 2011. America's Climate
Choices. Washington, DC: The National Academies Press. https://doi.org/10.17226/12781.
    \252\ National Academies of Sciences, Engineering, and Medicine.
2017. Communities in Action: Pathways to Health Equity. Washington,
DC: The National Academies Press. https://doi.org/10.17226/24624.
    \253\ USGCRP, 2016: The Impacts of Climate Change on Human
Health in the United States: A Scientific Assessment.
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i. Effects on Specific Populations of Concern
    Individuals living in socially and economically disadvantaged
communities, such as those living at or below the poverty line or who
are experiencing homelessness or social isolation, are at greater risk
of health effects from climate change. This is also true with respect
to people at vulnerable lifestages, specifically women who are pre- and
perinatal, or are nursing; in utero fetuses; children at all stages of
development; and the elderly. Per the Fourth National Climate
Assessment, ``Climate change affects human health by altering exposures
to heat waves, floods, droughts, and other extreme events; vector-,
food- and waterborne infectious diseases; changes in the quality and
safety of air, food, and water; and stresses to mental health and well-
being.'' \254\ Many health conditions

such as cardiopulmonary or respiratory illness and other health impacts
are associated with and exacerbated by an increase in GHGs and climate
change outcomes, which is problematic as these diseases occur at higher
rates within vulnerable communities. Importantly, negative public
health outcomes include those that are physical in nature, as well as
mental, emotional, social, and economic.
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    \254\ Ebi, K.L., J.M. Balbus, G. Luber, A. Bole, A. Crimmins, G.
Glass, S. Saha, M.M. Shimamoto, J. Trtanj, and J.L. White-Newsome,
2018: Human Health. In Impacts, Risks, and Adaptation in the United
States: Fourth National Climate Assessment, Volume II [Reidmiller,
D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K.
Maycock, and B.C. Stewart (eds.)]. U.S. Global Change Research
Program, Washington, DC, USA, pp. 539-571. doi: 10.7930/
NCA4.2018.CH14.
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    To this end, the scientific assessment literature, including the
aforementioned reports, demonstrates that there are myriad ways in
which these populations may be affected at the individual and community
levels. Individuals face differential exposure to criteria pollutants,
in part due to the proximities of highways, trains, factories, and
other major sources of pollutant-emitting sources to less-affluent
residential areas. Outdoor workers, such as construction or utility
crews and agricultural laborers, who frequently are comprised of
already at-risk groups, are exposed to poor air quality and extreme
temperatures without relief. Furthermore, individuals within EJ
populations of concern face greater housing, clean water, and food
insecurity and bear disproportionate economic impacts and health
burdens associated with climate change effects. They have less or