have lower incomes than the general population. People living near FAF4
truck routes are also more likely to live in metropolitan areas. Even
controlling for region of the country, county characteristics,
population density, and household structure, race, ethnicity, and
income are significant determinants of whether someone lives near a
FAF4 truck route.
---------------------------------------------------------------------------

    \921\ U.S. EPA (2021). Estimation of Population Size and
Demographic Characteristics among People Living Near Truck Routes in
the Conterminous United States. Memorandum to the Docket.
    \922\ FAF4 includes data from the 2012 Commodity Flow Survey
(CFS), the Census Bureau on international trade, as well as data
associated with construction, agriculture, utilities, warehouses,
and other industries. FAF4 estimates the modal choices for moving
goods by trucks, trains, boats, and other types of freight modes. It
includes traffic assignments, including truck flows on a network of
truck routes. https://ops.fhwa.dot.gov/freight/freight_analysis/faf/
.
---------------------------------------------------------------------------

    We additionally analyzed other national databases that allowed us
to evaluate whether homes and schools were located near a major road
and whether disparities in exposure may be occurring in these
environments. Until 2009, the U.S. Census Bureau's American Housing
Survey (AHS) included descriptive statistics of over 70,000 housing
units across the nation and asked about transportation infrastructure
near respondents' homes every two years.923 924 We also
analyzed the U.S. Department of Education's Common Core of Data, which
includes enrollment and location information for schools across the
United States.\925\
---------------------------------------------------------------------------

    \923\ U.S. Department of Housing and Urban Development, & U.S.
Census Bureau. (n.d.). Age of other residential buildings within 300
feet. In American Housing Survey for the United States: 2009 (pp. A-
1). Retrieved from https://www.census.gov/programs-surveys/ahs/data/2009/ahs-2009-summary-tables0/h150-09.html.
    \924\ The 2013 AHS again included the ``etrans'' question about
highways, airports, and railroads within half a block of the housing
unit but has not maintained the question since then.
    \925\ http://nces.ed.gov/ccd/.
---------------------------------------------------------------------------

    In analyzing the 2009 AHS, we focused on whether a housing unit was
located within 300 feet of a ``4-or-more lane highway, railroad, or
airport'' (this distance was used in the AHS analysis).\926\ We
analyzed whether there were differences between households in such
locations compared with those in locations farther from these
transportation facilities.\927\ We included other variables, such as
land use category, region of country, and housing type. We found that
homes with a non-White householder were 22-34 percent more likely to be
located within 300 feet of these large transportation facilities than
homes with White householders. Homes with a Hispanic householder were
17-33 percent more likely to be located within 300 feet of these large
transportation facilities than homes with non-Hispanic householders.
Households near large transportation facilities were, on average, lower
in income and educational attainment and more likely to be a rental
property and located in an urban area compared with households more
distant from transportation facilities.
---------------------------------------------------------------------------

    \926\ This variable primarily represents roadway proximity.
According to the Central Intelligence Agency's World Factbook, in
2010, the United States had 6,506,204 km of roadways, 224,792 km of
railways, and 15,079 airports. Highways thus represent the
overwhelming majority of transportation facilities described by this
factor in the AHS.
    \927\ Bailey, C. (2011) Demographic and Social Patterns in
Housing Units Near Large Highways and other Transportation Sources.
Memorandum to docket.
---------------------------------------------------------------------------

    In examining schools near major roadways, we used the Common Core
of Data (CCD) from the U.S. Department of Education, which includes
information on all public elementary and secondary schools and school
districts nationwide.\928\ To determine school proximities to major
roadways, we used a geographic information system (GIS) to map each
school and roadways based on the U.S. Census's TIGER roadway file.\929\
We estimated that about 10 million students attend schools within 200
meters of major roads, about 20 percent of the total number of public
school students in the United States.\930\ About 800,000 students
attend public schools within 200 meters of primary roads, or about 2
percent of the total. We found that students of color were
overrepresented at schools within 200 meters of primary roadways, and
schools within 200 meters of primary roadways had a disproportionate
population of students eligible for free or reduced-price lunches.\931\
Black

students represent 22 percent of students at schools located within 200
meters of a primary road, compared to 17 percent of students in all
U.S. schools. Hispanic students represent 30 percent of students at
schools located within 200 meters of a primary road, compared to 22
percent of students in all U.S. schools.
---------------------------------------------------------------------------

    \928\ http://nces.ed.gov/ccd/.
    \929\ Pedde, M.; Bailey, C. (2011) Identification of Schools
within 200 Meters of U.S. Primary and Secondary Roads. Memorandum to
the docket.
    \930\ Here, ``major roads'' refer to those TIGER classifies as
either ``Primary'' or ``Secondary.'' The Census Bureau describes
primary roads as ``generally divided limited-access highways within
the Federal interstate system or under state management.'' Secondary
roads are ``main arteries, usually in the U.S. highway, state
highway, or county highway system.''
    \931\ For this analysis we analyzed a 200-meter distance based
on the understanding that roadways generally influence air quality
within a few hundred meters from the vicinity of heavily traveled
roadways or along corridors with significant trucking traffic. See
U.S. EPA, 2014. Near Roadway Air Pollution and Health: Frequently
Asked Questions. EPA-420-F-14-044.
---------------------------------------------------------------------------

    We also reviewed existing scholarly literature examining the
potential for disproportionate exposure among people of color and
people with low socioeconomic status (SES). Numerous studies evaluating
the demographics and socioeconomic status of populations or schools
near roadways have found that they include a greater percentage of
residents of color, as well as lower SES populations (as indicated by
variables such as median household income). Locations in these studies
include Los Angeles, CA; Seattle, WA; Wayne County, MI; Orange County,
FL; and the State of California, and
nationally.932 933 934 935 936 937 938 Such disparities may
be due to multiple factors.939 940 941 942 943
---------------------------------------------------------------------------

    \932\ Marshall, J.D. (2008) Environmental inequality: air
pollution exposures in California's South Coast Air Basin. Atmos
Environ 42: 5499-5503. doi:10.1016/j.atmosenv.2008.02.00.
    \933\ Su, J.G.; Larson, T.; Gould, T.; Cohen, M.; Buzzelli, M.
(2010) Transboundary air pollution and environmental justice:
Vancouver and Seattle compared. GeoJournal 57: 595-608. doi:10.1007/
s10708-009-9269-6.
    \934\ Chakraborty, J.; Zandbergen, P.A. (2007) Children at risk:
measuring racial/ethnic disparities in potential exposure to air
pollution at school and home. J Epidemiol Community Health 61: 1074-
1079. doi:10.1136/jech.2006.054130.
    \935\ Green, R.S.; Smorodinsky, S.; Kim, J.J.; McLaughlin, R.;
Ostro, B. (20042004) Proximity of California public schools to busy
roads. Environ Health Perspect 112: 61-66. doi:10.1289/ehp.6566.
    \936\ Wu, Y; Batterman, S.A. (2006) Proximity of schools in
Detroit, Michigan to automobile and truck traffic. J Exposure Sci &
Environ Epidemiol. doi:10.1038/sj.jes.7500484.
    \937\ Su, J.G.; Jerrett, M.; de Nazelle, A.; Wolch, J. (2011)
Does exposure to air pollution in urban parks have socioeconomic,
racial, or ethnic gradients? Environ Res 111: 319-328.
    \938\ Jones, M.R.; Diez-Roux, A.; Hajat, A.; et al. (2014) Race/
ethnicity, residential segregation, and exposure to ambient air
pollution: The Multi-Ethnic Study of Atherosclerosis (MESA). Am J
Public Health 104: 2130-2137. [Online at: https://doi.org/10.2105/AJPH.2014.302135.].
    \939\ Depro, B.; Timmins, C. (2008) Mobility and environmental
equity: do housing choices determine exposure to air pollution? Duke
University Working Paper.
    \940\ Rothstein, R. The Color of Law: A Forgotten History of How
Our Government Segregated America. New York: Liveright, 2018.
    \941\ Lane, H.J.; Morello-Frosch, R.; Marshall, J.D.; Apte, J.S.
(2022) Historical redlining is associated with present-day air
pollution disparities in US Cities. Environ Sci & Technol Letters 9:
345-350. DOI: [Online at: https://doi.org/10.1021/acs.estlett.1c01012].
    \942\ Ware, L. (2021) Plessy's legacy: the government's role in
the development and perpetuation of segregated neighborhoods. RSF:
The Russel Sage Foundation Journal of the Social Sciences, 7:92-109.
DOI: DOI: 10.7758/RSF.2<IP_ADDRESS>.
    \943\ Archer, D.N. (2020) ``White Men's Roads through Black
Men's Homes'': advancing racial equity through highway
reconstruction. Vanderbilt Law Rev 73: 1259.
---------------------------------------------------------------------------

    Additionally, people with low SES often live in neighborhoods with
multiple stressors and health risk factors, including reduced health
insurance coverage rates, higher smoking and drug use rates, limited
access to fresh food, visible neighborhood violence, and elevated rates
of obesity and some diseases such as asthma, diabetes, and ischemic
heart disease. Although questions remain, several studies find stronger
associations between air pollution and health in locations with such
chronic neighborhood stress, suggesting that populations in these areas
may be more susceptible to the effects of air
pollution.944 945 946 947
---------------------------------------------------------------------------

    \944\ Clougherty, J.E.; Kubzansky, L.D. (2009) A framework for
examining social stress and susceptibility to air pollution in
respiratory health. Environ Health Perspect 117: 1351-1358.
Doi:10.1289/ehp.0900612.
    \945\ Clougherty, J.E.; Levy, J.I.; Kubzansky, L.D.; Ryan, P.B.;
Franco Suglia, S.; Jacobson Canner, M.; Wright, R.J. (2007)
Synergistic effects of traffic-related air pollution and exposure to
violence on urban asthma etiology. Environ Health Perspect 115:
1140-1146. doi:10.1289/ehp.9863.
    \946\ Finkelstein, M.M.; Jerrett, M.; DeLuca, P.; Finkelstein,
N.; Verma, D.K.; Chapman, K.; Sears, M.R. (2003) Relation between
income, air pollution and mortality: a cohort study. Canadian Med
Assn J 169: 397-402.
    \947\ Shankardass, K.; McConnell, R.; Jerrett, M.; Milam, J.;
Richardson, J.; Berhane, K. (2009) Parental stress increases the
effect of traffic-related air pollution on childhood asthma
incidence. Proc Natl Acad Sci 106: 12406-12411. doi:10.1073/
pnas.0812910106.
---------------------------------------------------------------------------

    Several publications report nationwide analyses that compare the
demographic patterns of people who do or do not live near major
roadways.948 949 950 951 952 953 Three of these studies
found that people living near major roadways are more likely to be
people of color or of low SES.954 955 956 They also found
that the outcomes of their analyses varied between regions within the
United States. However, only one such study looked at whether such
conclusions were confounded by living in a location with higher
population density and how demographics differ between locations
nationwide.\957\ In general, it found that higher density areas have
higher proportions of low-income residents and people of color. In
other publications assessing a city, county, or state, the results are
similar.958 959
---------------------------------------------------------------------------

    \948\ Rowangould, G.M. (2013) A census of the U.S. near-roadway
population: public health and environmental justice considerations.
Transportation Research Part D; 59-67.
    \949\ Tian, N.; Xue, J.; Barzyk. T.M. (2013) Evaluating
socioeconomic and racial differences in traffic-related metrics in
the United States using a GIS approach. J Exposure Sci Environ
Epidemiol 23: 215-222.
    \950\ CDC (2013) Residential proximity to major highways--United
States, 2010. Morbidity and Mortality Weekly Report 62(3): 46-50.
    \951\ Clark, L.P.; Millet, D.B., Marshall, J.D. (2017) Changes
in transportation-related air pollution exposures by race-ethnicity
and socioeconomic status: outdoor nitrogen dioxide in the United
States in 2000 and 2010. Environ Health Perspect https://doi.org/10.1289/EHP959.
    \952\ Mikati, I.; Benson, A.F.; Luben, T.J.; Sacks, J.D.;
Richmond-Bryant, J. (2018) Disparities in distribution of
particulate matter emission sources by race and poverty status. Am J
Pub Health https://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2017.304297?journalCode=ajph.
    \953\ Alotaibi, R.; Bechle, M.; Marshall, J.D.; Ramani, T.;
Zietsman, J.; Nieuwenhuijsen, M.J.; Khreis, H. (2019) Traffic
related air pollution and the burden of childhood asthma in the
continuous United States in 2000 and 2010. Environ International
127: 858-867. https://www.sciencedirect.com/science/article/pii/S0160412018325388.
    \954\ Tian, N.; Xue, J.; Barzyk. T.M. (2013) Evaluating
socioeconomic and racial differences in traffic-related metrics in
the United States using a GIS approach. J Exposure Sci Environ
Epidemiol 23: 215-222.
    \955\ Rowangould, G.M. (2013) A census of the U.S. near-roadway
population: public health and environmental justice considerations.
Transportation Research Part D; 59-67.
    \956\ CDC (2013) Residential proximity to major highways--United
States, 2010. Morbidity and Mortality Weekly Report 62(3): 46-50.
    \957\ Rowangould, G.M. (2013) A census of the U.S. near-roadway
population: public health and environmental justice considerations.
Transportation Research Part D; 59-67.
    \958\ Pratt, G.C.; Vadali, M.L.; Kvale, D.L.; Ellickson, K.M.
(2015) Traffic, air pollution, minority, and socio-economic status:
addressing inequities in exposure and risk. Int J Environ Res Public
Health 12: 5355-5372. http://dx.doi.org/10.3390/ijerph120505355.
    \959\ Sohrabi, S.; Zietsman, J.; Khreis, H. (2020) Burden of
disease assessment of ambient air pollution and premature mortality
in urban areas: the role of socioeconomic status and transportation.
Int J Env Res Public Health doi:10.3390/ijerph17041166.
---------------------------------------------------------------------------

    Two recent studies provide strong evidence that reducing emissions
from heavy-duty vehicles is extremely likely to reduce the disparity in
exposures to traffic-related air pollutants, both using NO2
observations from the recently launched TROPospheric Ozone Monitoring
Instrument (TROPOMI) satellite sensor as a measure of air quality,
which provides the highest-resolution observations heretofore
unavailable from any satellite.\960\
---------------------------------------------------------------------------

    \960\ TROPospheric Ozone Monitoring Instrument (TROPOMI) is part
of the Copernicus Sentinel-5 Precursor satellite.
---------------------------------------------------------------------------

    One study evaluated NO2 concentrations during the COVID-
19 lockdowns in 2020 and compared them to NO2 concentrations
from the same dates in 2019.\961\ That study found that

average NO2 concentrations were highest in areas with the
lowest percentage of white populations, and that the areas with the
greatest percentages of non-white or Hispanic populations experienced
the greatest declines in NO2 concentrations during the
lockdown. These NO2 reductions were associated with the
density of highways in the local area.
---------------------------------------------------------------------------

    \961\ Kerr, G.H.; Goldberg, D.L.; Anenberg, S.C. (2021) COVID-19
pandemic reveals persistent disparities in nitrogen dioxide
pollution. PNAS 118. [Online at https://doi.org/10.1073/pnas.2022409118].
---------------------------------------------------------------------------

    In the second study, NO2 measured from 2018-2020 was
averaged by racial groups and income levels in 52 large U.S.
cities.\962\ Using census tract-level NO2, the study
reported average population-weighted NO2 levels to be 28
percent higher for low-income non-White people compared with high-
income white people. The study also used weekday-weekend differences
and bottom-up emission estimates to estimate that diesel traffic is the
dominant source of NO2 disparities in the studied cities.
---------------------------------------------------------------------------

    \962\ Demetillo, M.A.; Harkins, C.; McDonald, B.C.; et al.
(2021) Space-based observational constraints on NO2 air
pollution inequality from diesel traffic in major US cities. Geophys
Res Lett 48, e2021GL094333. [Online at https://doi.org/10.1029/2021GL094333].
---------------------------------------------------------------------------

    Overall, there is substantial evidence that people who live or
attend school near major roadways are more likely to be of a non-White
race, Hispanic, and/or have a low SES. We expect communities near roads
will benefit from the reduced tailpipe emissions of PM, NOX,
SO2, VOC, CO, and mobile source air toxics from heavy-duty
vehicles in this proposal. EPA is considering how to better estimate
the near-roadway air quality impacts of its regulatory actions and how
those impacts are distributed across populations.
ii. Upstream Source Impacts
    As described in Section V.B.2, we expect some non-GHG emissions
reductions from sources related to refining petroleum fuels and
increases in emissions from EGUs, both of which would lead to changes
in exposure for people living in communities near these facilities. The
EGU emissions increases become smaller over time because of changes in
the projected power generation mix as electricity generation uses less
fossil fuels; in 2055, the reductions in vehicle and refinery-related
emissions of NOX, VOC, PM2.5, and SO2
are larger than the EGU-related increases. Analyses of communities in
close proximity to EGUs have found that a higher percentage of
communities of color and low-income communities live near these sources
when compared to national averages.\963\ Analysis of populations near
refineries also indicates there may be potential disparities in
pollution-related health risk from that source.\964\
---------------------------------------------------------------------------

    \963\ See 80 FR 64662, 64915-64916 (October 23, 2015).
    \964\ U.S. EPA (2014). Risk and Technology Review--Analysis of
Socio-Economic Factors for Populations Living Near Petroleum
Refineries. Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina. January.
---------------------------------------------------------------------------

E. Economic Impacts

1. Impacts on Vehicle Sales, Fleet Turnover, Mode Shift, Class Shift
and Domestic Production
    In this section, we qualitatively discuss the impacts the proposed
regulation may have on HD vehicle sales, including pre-buy and low-buy
decisions, effects on decisions regarding the mode of transportation
used to move goods, possible shifting of purchases between HD vehicle
classes, and possible effects on domestic production of HD vehicles.
Pre-buy occurs when a purchaser pulls ahead a planned future purchase
to make the purchase prior to the implementation of an EPA regulation
in anticipation that a future vehicle may have a higher upfront cost, a
higher operational cost, or have reduced reliability due to the new
regulation. Low-buy occurs when a vehicle that would have been
purchased after the implementation of a regulation is either not
purchased at all, or the purchase is delayed due to the regulation.
Low-buy may occur directly as a function of pre-buy (where a vehicle
was instead purchased prior to implementation of the new regulation),
or due to a vehicle purchaser delaying the purchase of a vehicle due to
cost or uncertainty. Pre- and low-buy are short-term effects, with
research indicating that effects are seen for one year or less before
and after a regulation in implemented.\965\ Pre-buy and low-buy impact
fleet turnover, which can result in a level of emission reduction
attributable to the new emission standards that is different from the
level of emission reduction EPA estimated would be achieved by the new
regulation.
---------------------------------------------------------------------------

    \965\ See the EPA report ``Analysis of Heavy-Duty Vehicle Sales
Impacts Due to New Regulation'' at https://cfpub.epa.gov/si/si_public_pra_view.cfm?dirEntryID=349838&Lab=OTAQ for a literature
review and EPA analysis of pre-buy and low-buy due to HD
regulations.
---------------------------------------------------------------------------

    Additional possible, though unlikely, effects of this proposed
regulation include mode shift, class shift and effects on domestic
production. Mode shift would occur if goods that would normally be
shipped by HD vehicle are instead shipped by another method (e.g.,
rail, boat, air) as a result of this action. Class shift occurs when a
vehicle purchaser decides to purchase a different class of vehicle than
originally intended due to the new regulation. For example, a purchaser
may buy a Class 8 vehicle instead of the Class 7 vehicle they may have
purchased in the absence of a regulation. Domestic production could be
affected if the regulation creates incentives for manufacturers to
shift between domestic and foreign production.
i. Vehicle Sales and Fleet Turnover
    The proposed emission standards may lead to a change in the timing
of planned vehicle purchases, phenomena known as ``pre-buy'' and ``low-
buy.'' Pre-buy occurs when purchasers of HD vehicles pull their planned
future vehicle purchase forward to the months before a regulation is
implemented compared to when they otherwise would have purchased a new
vehicle in the absence of the regulation. Pre-buy may occur due to
expected cost increases of post-regulation vehicles, or in order to
avoid perceived cost, quality, or other changes associated with new
emission standards. Another reason pre-buy might occur is due to
purchaser beliefs about the availability of their vehicle type of
choice in the post-regulation market. For example, if purchasers think
that they might not be able to get the HD ICE vehicle they want after
the proposed regulation is promulgated, they may pre-buy an ICE
vehicle. Pre-buy, to the extent it might occur, could be mitigated in
multiple ways, including by reducing the higher upfront cost of post-
regulation vehicles, by purchasers considering the lower operational
costs of post-regulation vehicles when making their purchase decision,
or through the phasing in of the proposed standards. With respect to
possible purchaser anxiety over being unable to purchase an ICE vehicle
after promulgation of the proposed regulation, we expect that the
federal vehicle and battery tax credits in the IRA, as well as
purchasers' consideration of the lower operational costs of ZEVs, would
mitigate possible pre-buy by reducing the perceived purchase price or
lifetime operational costs difference of a new, post-rule ZEV compared
to a new pre- or post-rule ICE vehicle. Additionally, pre-buy may be
mitigated by educating purchasers on benefits of ZEV ownership (for
example, reduced operational costs) or on charging and hydrogen
refueling infrastructure technology and

availability.\966\ Our proposed standards will increase purchaser
exposure to ZEVs, as well as incentivize manufacturers and dealers to
educate HD vehicle purchasers on ZEVs, including the benefits of ZEVs,
accelerating the reduction of purchaser risk aversion. In addition, we
expect recent congessional actions to support ZEV infrastructure and
supply chain, including the CHIPS Act, BIL and IRA, will reduce
uncertainty related to infrastructure.\967\ We note that the proposed
standards do not mandate the use of a specific technology, and EPA
anticipates that a compliant fleet under the proposed standards would
include a diverse range of technologies, including ICE and ZEV
technologies. The phasing-in of the proposed standards, which do not
eliminate any specific technology from the market, would allow ample
time for purchasers to make decisions about their vehicle of choice.
---------------------------------------------------------------------------

    \966\ For more information on purchaser acceptance of HD ZEVs,
see DRIA Chapter 6.2. For more information on the charging and
hydrogen refueling infrastructure analysis in this proposed rule,
see DRIA Chapter 2.6.
    \967\ The CHIPS Act is the Creating Helpful Incentives to
Produce Semiconductors and Science Act and was signed into lay on
August 9, 2022. It is designed to strengthen supply chains, domestic
manufacturing and national security. More information on how all of
these Acts are expected to support opportunities for growth along
the supply chain can be found in the January 2023 White House
publication ``Building a Clean Energy Economy: A Guidebook to the
Inflation Reduction Act's Investments in Clean Energy and Climate
Action.'' found online at https://www.whitehouse.gov/wp-content/uploads/2022/12/Inflation-Reduction-Act-Guidebook.pdf.
---------------------------------------------------------------------------

    In addition to pre-buy, there is the possibility of ``low-buy''
occurring in response to new regulation. In a low-buy scenario, sales
of HD vehicles would decrease in the months after a regulation becomes
effective, compared to what would have happened in the absence of a
regulation, due to purchasers either pre-buying or delaying a planned
purchase. Low-buy may be directly attributable to pre-buy, where
purchases originally planned for the months following the effective
date of new emission standards are instead purchased in the months
preceding the effective date of the new emission standards. Low-buy may
also be attributable to purchasers delaying the planned purchase of a
new vehicle due to the new emission standards, and may occur for
reasons such as increased costs or uncertainty about the new vehicles.
If pre-buy is smaller than low-buy, to the extent both might occur,
this would lead to a slower fleet turnover, at least in the short
term.\968\ In this scenario, older HD vehicles would remain in use
longer than they would have in the absence of the new emission
standards. This would lead to lower emission reductions than we
estimate would be achieved as a result of the proposed emission
standards. Conversely, if pre-buy is larger than low-buy, short-term
fleet turnover would increase; fleets would, on average, be comprised
of newer model year vehicles. Though these new vehicles are expected to
have lower emissions than the vehicles they are replacing, and emission
reductions would be expected to be larger than under a scenario where
low-buy exceeds pre-buy, emission reductions would still be lower than
we estimated would be achieved as a result of the proposed emission
standards. Under a situation where low-buy matches pre-buy, we would
also expect lower emission reductions than estimated, and emission
reductions would likely be somewhere between the two relative pre-buy/
low-buy scenarios discussed in the previous paragraph. We expect low-
buy, to the extent that it might occur, to be mitigated under the same
circumstances described in this section for pre-buy.
---------------------------------------------------------------------------

    \968\ Fleet turnover refers to the pace at which new vehicles
are purchased and older vehicles are retired. A slower fleet
turnover means older vehicles are kept on the road longer, and the
fleet is older on average. A faster fleet turnover means that the
fleet is younger, on average.
---------------------------------------------------------------------------

    Analysis of previously promulgated EPA HD emission standards
indicates that where pre-buy or low-buy has been seen, the magnitude of
these phenomena has been small.\969\ Recent analysis conducted by EPA
of pre-buy and low-buy indicates that pre-buy and low-buy effects
typically occur for up to one year before or one year after a
regulation becomes effective, if pre-buy or low-buy occur at all.\970\
EPA contracted with ERG to complete a literature review of research
estimating HD vehicle sales impacts resulting from HD regulations, and
to conduct original research to estimate the existence and magnitude of
pre-buy and low-buy sales impacts of previous EPA HD regulations.\971\
The resulting analysis examined the effect of four HD regulations
(those that became effective in 2004, 2007, 2010 and 2014) on the sales
of Class 6, 7 and 8 vehicles over the twelve months before and after
each standard. For the purposes of this discussion, we will call these
the 2004 rule, 2007 rule, 2010 rule and 2014 rule. The 2004, 2007 and
2010 rules focused on reducing criteria pollutant emissions from HD
vehicles and engines, and the 2014 rule (the HD GHG Phase 1 rule
promulgated in 2014) focused on reducing GHG emissions from HD vehicles
and engines.\972\ The ERG report found little evidence of pre-buy or
low-buy sales impacts on Class 6 and 7 vehicles for any of the rules.
For Class 8 vehicles, evidence of pre-buy was found for up to eight
months before promulgation of the 2010 rule, as well as for up to one
month prior to promulgation of the 2014 rule. Evidence of low-buy was
found after promulgation of the 2002 (up to six months), 2007 (up to 12
months) and 2010 rules (up to five months). The results of the ERG
report also suggest that the range of possible results include a lower
bound of zero, or no pre-buy or low-buy due to EPA rules.
---------------------------------------------------------------------------

    \969\ For example, Lam and Bausell (YEAR), Rittenhouse and
Zaragoza-Watkins (YEAR), and an unpublished report by Harrison and
LeBel (2008). For EPA's summary on these studies, see the EPA peer
review cited in the footnote below, or the recently published EPA
Heavy-Duty 2027 rule at Docket ID EPA-HQ-2019-0555.
    \970\ ``Analysis of Heavy-Duty Vehicle Sales Impacts Due to New
Regulation.'' At https://cfpub.epa.gov/si/si_public_pra_view.cfm?dirEntryID=349838&Lab=OTAQ.
    \971\ ``Analysis of Heavy-Duty Vehicle Sales Impacts Due to New
Regulation.'' At https://cfpub.epa.gov/si/si_public_pra_view.cfm?dirEntryID=349838&Lab=OTAQ.
    \972\ The 2004 rule, `Final Rule for Control of Emission of Air
Pollution From Highway Heavy-Duty Engines', was finalized in 1997.
The 2007 and 2010 rules were finalized as phase-ins in the `Final
Rule for Control of Emissions of Air Pollution from 2004 and Later
Model Year Heavy-Duty Highway Engines and Vehicles; Revision of
Light-Duty On-Board Diagnostics Requirements' in 2000. The 2014 GHG
rule, `Final Rule for Phase 1 Greenhouse House Emissions Standards
and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and
Vehicles,' was finalized in 2011. These rules can be found on the
EPA website https://www.epa.gov/regulations-emissions-vehicles-and-engines/regulations-emissions-commercial-trucks-and-buses-heavy.
---------------------------------------------------------------------------

    While it is instructive that the ERG report found little to no pre-
buy or low-buy effects due to our HD rules, EPA does not believe the
approach to estimate a change in the sales of HD vehicles before and
after the promulgation of a rule due to the cost of that rule (as was
done in the ERG report) should be used to estimate sales effects from
this proposed rule for three main reasons.\973\ First, as outlined in
the previous paragraph, most of the statistically significant sales
effects in the ERG report were estimated using data from criteria
pollutant rules (the 2002, 2004 and 2007 rules), which are not
appropriate for use in estimating effects from HD GHG rules. This is
because differences in how costs are incurred and benefits are accrued
as a result of HD vehicle criteria pollutant regulations versus HD GHG
regulations

may lead to differences in how HD vehicle buyers react to a particular
regulation. For example, the 2014 rule \974\ led to reductions in GHG
emissions and had lower associated technology costs compared to the
criteria pollutant rules, and compliance with the GHG regulation was
associated with fuel savings. We also expect fuel savings effects in
this proposal, as described in Section IV. Second, the pre-buy and low-
buy sales effects were estimated as a function of the average change in
cost of a HD vehicle for each vehicle class due to the specific rule
under consideration (for example, the 2007 rule or 2014 rule). However,
unlike criteria pollutant rules, there were multiple pathways to
compliance with 2014 rule, and therefore uncertainty in the price
change due to the rule, which led to uncertainty in the results
estimated using these price changes. Third, the approach outlined in
the ERG report was estimated only using HD ICE vehicle data (i.e., cost
of compliance due to adding technology to a HD ICE engine). The
research and methodology in the ERG report did not include any data
from the production, sale, or purchase of HD ZEVs. For these reasons,
we are not using the method in the ERG report to estimate sales effects
due to this rule. We request comment on data or methods to estimate the
possible effects of this regulation on the sale of HD ICE vehicles and
HD ZEV sales, including potential impacts associated with pre-buy and
low-buy.
---------------------------------------------------------------------------

    \973\ See the RIA for the HD 2027 rule for an example of how we
might estimate potential impacts of a HD regulation on vehicle
sales, including pre-buy and low-buy using the approach introduced
in the ERG report. 87 FR 17590. March 28, 2022.
    \974\ `Final Rule for Phase 1 Greenhouse House Emissions
Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty
Engines and Vehicles' can be found at https://www.epa.gov/regulations-emissions-vehicles-and-engines/final-rule-phase-1-greenhouse-gas-emissions-standards.
---------------------------------------------------------------------------

    This proposed rulemaking would be expected to lead to reductions in
emissions across the HD vehicle fleet (Section V of this preamble),
though such reductions are expected to happen gradually as the HD fleet
turns over. This is because the fraction of the total HD vehicle fleet
that is new ZEVs would initially be a small portion of the entire HD
market. As more HD ZEVs are sold, and as older HD ICE vehicles are
retired, greater emission reductions are expected to occur. The
emission reductions attributable to each HD segment that would be
affected by this proposed rule would depend on many factors, including
the individual increase in ZEV adoption in each market segment over
time, as well as relative usage, measured in VMT, for a HD ZEV when
compared to a similar HD ICE vehicle. For example, if ZEV uptake occurs
faster than predicted, emission reductions would happen faster than
estimated. If, assuming no change in total fleet VMT, the VMT
attributed to a HD ZEV is less than that of the HD ICE vehicle it is
displacing, emission reductions would happen slower than estimated. In
addition, if pre-buy or low-buy occurs as a result of this proposed
rulemaking, emission reductions would be smaller than anticipated. This
is because, under pre-buy conditions, the pre-bought vehicles will not
be subject to the tighter emission standards, and are less likely to be
ZEVs; however, the pre-bought new vehicles are likely to be less
polluting than the older HD vehicles they are replacing due to more
stringent HD emission standards for new engines and vehicles (if it is
a replacement purchase). Under low-buy, we would expect older, more
polluting, HD vehicles would remain in use longer than they otherwise
would in the absence of new regulation. We expect pre-buy and low-buy
to be very small, if they occur at all. For more information on sales
impacts, see Chapter 6.1.1 of the DRIA. We request comment on data and
methods to estimate possible effects of the proposed emission standards
on fleet turnover and to estimate the VMT of HD ZEVs in comparison to
HD ICE vehicles.
ii. Mode Shift
    Another potential, though unlikely, effect of this proposed
regulation may be mode shift. Mode shift would occur if goods that
would normally be shipped by HD vehicle are instead shipped by another
method (e.g., rail, boat, air) as a result of this action. Whether
shippers switch to a different mode of transportation for freight
depends not only on the cost per mile of the shipment (i.e., freight
rate), but also the value of the shipment, the speed of transport
needed for shipment (for example, for non-durable goods), and the
availability of supporting infrastructure (e.g., rail lines, highways,
waterways). Shifting from HD vehicles to other modes of transportation
may occur if the cost of shipping goods by HD vehicles increases
relative to other modes of transport, and it is feasible to switch the
shipment from truck to another mode of transport. Chapter 3.3 of the
DRIA and Section IV.D of this preamble discuss the estimated decrease
in operational costs of this proposed rule, mainly due to the increase
in the share of ZEVs in the on-road HD fleet. Because the effects of
this proposed action are expected to reduce operational costs for
trucks, we do not think mode shift would be a likely outcome of this
proposed regulation.\975\ We are asking for comment on data and methods
to estimate possible effects of the proposed emission standards on mode
shift. For more information on mode shift, see Chapter 6.1.2 of the
DRIA.
---------------------------------------------------------------------------

    \975\ If manufacturers comply by adding technology to ICE
vehicles, we would also expect to see reduced operational costs
through reduced fuel consumption.
---------------------------------------------------------------------------

iii. Class Shift
    Class shift is also a possible effect of this proposed rule. Class
shift would occur if purchasers shift their purchases from one class of
vehicle to another class of vehicle due to differences in cost among
vehicle types. We expect that class shifting, if it does occur, would
be limited. The proposed emission standards are projected to lead to an
increase in the incremental cost per vehicle for many classes of
vehicles across both vocational vehicles and tractor categories before
accounting for the IRA vehicle and battery tax credits. After
accounting for these credits, our estimates show that this upfront
increase in cost is reduced, and in fact, we estimate that some
vocational vehicles and tractor ZEVs have lower or equivalent upfront
costs compared to comparable ICE vehicles. For more information, see
Preamble Section IV.D or DRIA Chapter 3.4. Furthermore, the upfront
costs for vocational vehicles and tractors would be offset by
operational cost savings.
    Another reason EPA believes class shift would be limited, if it
occurs, is that HD vehicles are typically configured and purchased to
perform a specific function. For example, a concrete mixer is purchased
to transport concrete, or a combination tractor is purchased to move
freight with the use of a trailer. In addition, a purchaser in need of
a specific vocational vehicle, such as a bus, box truck or street
sweeper, would not be able to shift the purchase to a vehicle with a
less stringent emission standard (such as the optional custom chassis
standards for emergency vehicles, recreational vehicles, or mixed use
(nonroad) type vehicles) and still meet their needs. The purchaser
makes decisions based on many attributes of the vehicle, including the
gross vehicle weight rating or gross combined weight rating of the
vehicle, which in part determines the amount of freight or equipment
that can be carried. Due to this, it may not be feasible for purchasers
to switch to other vehicle classes. If a limited amount of shifting
were to occur, we would expect negligible emission impacts (compared

to those emission reductions estimated to occur as a result of the
proposed emission standards) because the vehicle classes that would be
feasibly `switched' are all subject to this proposed rule. We request
comment on data or methods to estimate the effect the proposed emission
standards might have on class shifting.
iv. Domestic Production
    The proposed emission standards are not expected to provide
incentives for manufacturers to shift between domestic and foreign
production. This is because the emission standards apply to vehicles
sold in the United States regardless of where such vehicles are
produced. If foreign manufacturers already have increased expertise in
satisfying the requirements of the emission standards, there may be
some initial incentive for foreign production. However, given
increasing global interest in reducing vehicle emissions, specifically
through the use of ZEVs, as domestic manufacturers produce vehicles
with reduced emissions, including ZEVs, the opportunity for domestic
manufacturers to sell in other markets might increase. To the extent
that the proposed emission standards might lead to application and use
of technologies that other countries may seek now or in the future,
developing this capacity for domestic producers now may provide some
additional ability to serve those markets.
    As discussed in Preamble Section 1.C, and DRIA Chapter 1, the IRA
contains tax credit incentives that are impacted by the location of
production and may encourage domestic production of ZEV vehicles or
components. A portion of these tax incentives are included in our cost
analysis for the proposed rule, as describe in Section IV, and DRIA
Chapter 3. We request comment on whether our standards would impact the
domestic production of HD vehicle components.
2. Purchaser Acceptance
    We expect this proposed rule to lead to an increase in the adoption
of HD BEVs and FCEVs for most HD vehicle types beginning in MY 2027
(see Section II of this preamble or DRIA Chapter 2 for details).
Businesses that operate HD vehicles are under competitive pressure to
reduce operating costs, which should encourage purchasers to identify
and rapidly adopt new vehicle technologies that reduce operating costs.
As outlays for labor and fuel generally constitute the two largest
shares of HD vehicle operating costs, depending on the price of fuel,
distance traveled, type of HD vehicle, and commodity transported (if
any), businesses that operate HDVs face strong incentives to reduce
these costs.976 977 As explained in Section IV and Chapter 3
of the DRIA, though HD ZEVs in general have higher upfront costs than
comparable ICE vehicles, our costs analysis shows that the incremental
upfront cost difference between a ZEV and a comparable ICE vehicle
would be partially or fully offset by a combination of the federal
vehicle tax credit and battery tax credit for HD ZEVs that are
available through MY 2032 and operational savings.\978\ For the vehicle
types for which we propose new CO2 emission standards, we
expect that the ZEVs will have a lower total cost of ownership when
compared to a comparable ICE vehicle (even after considering the
upfront cost of purchasing the associated EVSE for a BEV), due to the
expected cost savings in fuel, maintenance, and repair over the life of
the HD ZEV when compared to comparable ICE vehicle. See Section IV of
this preamble and Chapter 3 of the DRIA for more information on the
estimated costs of this proposed rule.
---------------------------------------------------------------------------

    \976\ American Transportation Research Institute, An Analysis of
the Operational Costs of Trucking, September 2013. Docket ID: EPA-
HQ-OAR-2014-0827-0512.
    \977\ Transport Canada, Operating Cost of Trucks, 2005. Docket
ID: EPA-HQ-OAR-2014-0827-0070.
    \978\ For more information on the Federal tax credits, see
Section I.C.
---------------------------------------------------------------------------

    In DRIA Chapter 6.2, we discuss the possibility that an ``energy
efficiency gap'' or ``energy paradox'' has existed, where available
technologies that would reduce the total cost of ownership for the
vehicle (when evaluated over their expected lifetimes using
conventional discount rates) have not been widely adopted, or the
adoption is relatively slow, despite their potential to repay buyers'
initial investments rapidly. We recognize that there are factors that
may impact adoption of HD ZEVs, including uncertainty related to the
technology and supporting infrastructure, as well as incentives created
by this proposed rule for manufacturers to develop ZEV technology and
educate purchasers.
    We expect that adoption rates of HD ZEVs will be impacted by buyers
taking advantage of existing incentives, specifically the IRA vehicle
tax credit and battery tax credit, as well as the extent to which
buyers consider the cost savings of purchasing a ZEV over a HD ICE
vehicle in their purchase decision, mainly observed through operational
cost savings. We expect purchasing decisions would also be affected by
purchasers' impressions of charging infrastructure support and
availability, perceptions of the comparisons of quality and durability
of the different HD powertrains, and resale value of the vehicle.
    The availability of existing incentives, specifically the Federal
purchaser and battery manufacturing tax credits in the IRA, is expected
to lead to lower upfront costs for purchasers of HD ZEVs than would
otherwise occur.\979\ We expect this will result in a higher ZEV
adoption rate than would otherwise exist absent such incentives. In
addition, as purchasers consider more of the operational cost savings
of a ZEV over a comparable ICE vehicle in their purchase decision, the
smaller the impact of the higher upfront costs for purchasers of a ZEV
compared to an ICE vehicle has on that decision, and purchasers are
more likely to purchase a ZEV. We note that ZEVs may not be purchased
at the rates estimated in the analysis for this proposed rule. They may
be smaller if purchasers do not consider the full, or even a portion
of, value of operational cost savings, which may happen due to
uncertainty, e.g., uncertainty about future fuel prices. Additionally,
this may occur if a principal-agent problem exists, causing split
incentives.\980\ A principal-agent problem would exist if truck
operators (agents) and truck purchasers who are not also operators
(principals) value operational cost savings differently (split
incentives), which could lead to differences in purchase decisions
between truck operators and truck purchasers. For example, a HD vehicle
purchaser may not be directly responsible for the future fuel costs of
the vehicle they purchase, or the person who would be responsible for
those fuel costs may not be involved in the purchase decision. In this
case, truck operators may place a higher value on the potential savings
in operational costs over the lifetime of a vehicle and give less
weight to the increase in upfront cost that may be associated with a
ZEV purchase, whereas a truck purchaser may weigh higher upfront costs
more heavily than possible operational cost savings. Such potential
split incentives, or market failures, could lead to lower ZEV adoption
rates than we are estimating in this proposal, which may reduce the
non-GHG environmental benefits of the proposed emission standards due
to lower non-

GHG emission reductions than estimated in this proposal. Other examples
of this might include if a purchaser values charging or fueling
infrastructure, either the cost of installation or the availability,
differently than the operator. The direction of the effect in this case
would depend on who was responsible for the cost of the infrastructure
installation, or who places more value on the availability of
widespread infrastructure.
---------------------------------------------------------------------------

    \979\ Note that the incentives exist in the baseline and under
the scenario with our proposed standards.
    \980\ A principal-agent problem happens when there is a conflict
in priorities (split incentives) between a ``principal,'' or the
owner of an asset, and an ``agent,'' or the the person to whom
control of the asset has been delegated, such as a manager or HD
vehicle operator.
---------------------------------------------------------------------------

    Uncertainty about ZEV technology, charging infrastructure
technology and availability for BEVs, or hydrogen refueling
infrastructure for FCEVs, may affect ZEV adoption rates. As ZEVs become
increasingly more affordable and ubiquitous, we expect uncertainty
related to these technologies will diminish over time. As uncertainty
related to these technologies decreases, it may lead to higher rates of
ZEV adoption that estimated. In addition, ZEVs may be purchased at
higher rates than estimated in the analysis if, for example, ZEV costs
decrease faster than expected, or due to increasing commitments from
fleet owners or operators to purchase ZEVs.
    We expect that the Federal vehicle and battery tax credits in the
IRA, as well as purchasers' consideration of the lower operational
costs of ZEVs, would mitigate any possible pre-buy by reducing the
perceived purchase price or lifetime operational costs difference of a
new, post-rule ZEV compared to a new pre- or post-rule ICE vehicle. We
expect this would increase purchaser willingness to purchase a new ZEV.
When purchasers are educated on charging or refueling infrastructure
technology and availability, both as it stands at the time of possible
purchase, as well as plans for future availability, uncertainty related
to operating a new ZEV decreases.
    EPA recognizes that there is uncertainty related to ZEVs that may
impact the adoption of this technology even though it reduces operating
costs. Markets for both new and used HD vehicles may face these
problems, although it is difficult to assess empirically the degree to
which they do. We expect the proposed Phase 3 standards, if finalized,
will help overcome such barriers by incentivizing the development of
ZEV technologies and the education of HD vehicle purchasers on ZEV
benefits and infrastructure.
    We request comment and data on acceptance of HD ZEVs.
3. VMT Rebound
    Historically, the ``rebound effect'' has been interpreted as more
intensive vehicle use, resulting in an increase in liquid fuel in
response to increased ICE vehicle fuel efficiency. Although much of
this possible vehicle use increase is likely to take the form of an
increase in the number of miles vehicles are driven, it can also take
the form of an increase in the loaded operating weight of a vehicle or
altering routes and schedules in response to improved fuel efficiency.
More intensive use of those HD ICE vehicles consumes fuel and generates
emissions, which reduces the fuel savings and avoided emissions that
would otherwise be expected to result from increasing fuel efficiency
of HD ICE vehicles.
    Unlike the LD vehicle rebound effect, there is little published
literature on the HD vehicle rebound effect, and all of it focuses on
the rebound effect due to increased ICE fuel efficiency. Winebrake et
al. (2015) suggests that vocational trucks and tractor trailers have a
rebound effect of essentially zero. Leard et al. (2015) estimate that
tractor trailers have a rebound effect of 30 percent, while vocational
vehicles have a 10 percent rebound rate.\981\ Patwary et al. (2021)
estimated that the average rebound effect of the U.S. road freight
sector is between about 7 to 9 percent, although their study indicated
that rebound has increased over time.\982\ This is slightly smaller
than the value found by Leard et al. (2015) for the similar sector of
tractors. We do not have data that operational cost savings of
switching from an ICE vehicle to a ZEV will affect the VMT driven of
that vehicle, nor do we have data on how changing fuel prices might
affect VMT of ZEVs over time. Given the increasing penetration of ZEVs
in the HD fleet, and the estimated increase over the time frame of this
proposed rule, we do not believe the rebound estimates in literature
cited here are appropriate for use in our analysis. Therefore, we are
not estimating any VMT rebound due to this rule. We request comment on
the VMT response of HD ICE vehicles and HD ZEVs due to this rule,
including the response of increasing efficiency within ICE vehicles, as
well as the response to switching from an ICE vehicle to a ZEV. We
request comment and data on the rebound assumptions for HD ICE vehicles
and HD ZEVs.
---------------------------------------------------------------------------

    \981\ Leard, B., Linn, J., McConnell, V., and Raich, W. (2015).
Fuel Costs, Economic Activity, and the Rebound Effect for Heavy-Duty
Trucks. Resources For the Future Discussion Paper, 14-43.
    \982\ Patwary, A. L., Yu, T. E., English, B.C., Hughes, D. W.,
and Cho, S. H. (2021). Estimating the rebound effect of the US road
freight transport. Transportation Research Record, 2675(6), 165-174.
---------------------------------------------------------------------------

4. Employment Impacts
    Economic theories of labor demand indicate that employers affected
by environmental regulation may change their demand for different types
of labor in different ways, increasing demand for some types,
decreasing demand for other types, or not changing it at all for still
other types. A variety of conditions can affect employment impacts of
environmental regulation, including baseline labor market conditions
and employer and worker characteristics such as industry and region. A
growing body of literature has examined employment effects of
environmental regulation. Morgenstern et al. decompose the labor
consequences in a regulated industry facing increased abatement
costs.\983\ This study identifies three separate components of labor
demand effects. First, there is a demand effect caused by higher
production costs, which in turn, results in increased market prices.
Increased market prices reduce consumption (and production), thereby
reducing demand for labor within the regulated industry. Second, there
is a cost effect. As production costs increase, manufacturing plants
use more of all inputs, including labor, to produce the same level of
output. Third, there is a factor-shift effect, which occurs when post-
regulation production technologies may have different labor intensities
than pre-regulation production technologies.\984\
---------------------------------------------------------------------------

    \983\ Morgenstern, R.D.; Pizer, W.A.; and Shih, J.-S. ``Jobs
Versus the Environment: An Industry-Level Perspective.'' Journal of
Environmental Economics and Management 43: 412-436. 2002.
    \984\ Additional literature using similar frameworks include
Berman and Bui (2001) and Desch[ecirc]nes (2018). For more
information on this literature, see the Chapter 10 of the RIA for
the HD2027 rule, found at Docket ID EPA-HQ-OAR-2019-0055.
---------------------------------------------------------------------------

    Due to a lack of data, we are not able to estimate employment
effects from this proposed rule. The overall effect of the proposed
rule on employment in the heavy-duty vehicle manufacturing sector
depends on the relative magnitude of factor-shift, cost, and demand
effects, as well as possible differences in employment related to HD
ICE and ZEV manufacturing. As markets shift to HD ZEVs, employment
needs will shift as well. In Chapter 6.4.2 of the DRIA, we show that
the amount of labor per million dollars in sales in motor vehicle
manufacturing sectors has generally declined over time, indicating that
fewer people have been needed to produce the same value of goods. For
example, in 1997, motor vehicle body and trailer manufacturing employed

almost 3.4 employees per million dollars in sales. This fell to almost
2.7 in 2021. In the electrical equipment manufacturing sector, which is
involved in the production of EVs, employment has increased from almost
2.3 to almost 2.7 per million dollars from 2007 to 2021. The
International Union, United Automobile, Aerospace and Agricultural
Implement Workers of America (UAW) states that re-training programs
will be needed to support auto workers in a market with an increasing
share of electric vehicles in order to prepare workers that might be
displaced by the shift to the new technology.\985\ Volkswagen states
that labor requirements for ICE vehicles are about 70 percent higher
than their electric counterpart, but these changes in employment
intensities in the manufacturing of the vehicles can be offset by
shifting to the production of new components, for example batteries or
battery cells.\986\ Climate Nexus indicates that transitioning to
electric vehicles will lead to a net increase in jobs, a claim that is
partially supported by the rising investment in batteries, vehicle
manufacturing and charging stations.\987\ Though most of these
statements are specifically referring to light-duty vehicles, they hold
true for the HD market as well. The expected investment mentioned by
Climate Nexus is also supported by recent Federal investment which will
allow for increased investment along the vehicle supply chain,
including domestic battery manufacturing, charging infrastructure, and
vehicle manufacturing, both in the LD and HD markets.\988\ This
investment includes the BIL, the CHIPS Act,\989\ and the IRA, which are
expected to create domestic employment opportunities along the full
automotive sector supply chain, from components and equipment
manufacturing and processing to final assembly, as well as incentivize
the development of reliable EV battery supply chains.\990\ For example,
the IRA is expected to impact domestic employment through conditions on
eligibility for purchase incentives and battery manufacturing
incentives. These conditions include contingencies for domestic
assembly, domestic critical materials production, and domestic battery
manufacturing. The BlueGreen Alliance and the Political Economy
Research Institute estimate that IRA will create over 9 million jobs
over the next decade, with about 400,000 of those jobs being attributed
directly to the battery and fuel cell vehicle provisions in the
act.\991\ In addition, the IRA is expected to lead to increased demand
in ZEVs through tax credits for purchasers of ZEVs.
---------------------------------------------------------------------------

    \985\ More information on UAW's comments can be found in the
white paper ``Making EVs work for American workers'' found at
https://uaw.org/wp-content/uploads/2019/07/190416-EV-White-Paper-REVISED-January-2020-Final.pdf.
    \986\ Herrmann, F., Beinhauer, W., Borrmann, D., Hertwig, M.,
Mack, J., Potinecke, T., Praeg, C., Rally, P. 2020. Effects of
Electric Mobility and Digitlaisation on the Quality and Quantity of
Employment at Volkswagen. Fraunhofer Institute for Industrial
Engineering IAO. Study on behalf of the Sustainability Council of
the Volkswagen Group. https://www.volkswagenag.com/presence/stories/2020/12/frauenhofer-studie/6095_EMDI_VW_Summary_um.pdf.
    \987\ See the report from Climate Nexus at https://climatenexus.org/climate-issues/energy/ev-job-impacts/.
    \988\ See Preamble Section I for information on the BIL and IRA
provisions relevant to vehicle electrification, and the associated
infrastructure.
    \989\ The CHIPS Act is the Creating Helpful Incentives to
Produce Semiconductors and Science Act and was signed into lay on
August 9, 2022. It is designed to strengthen supply chains, domestic
manufacturing and national security. More information can be found
at https://www.whitehouse.gov/briefing-room/statements-releases/2022/08/09/fact-sheet-chips-and-science-act-will-lower-costs-create-jobs-strengthen-supply-chains-and-counter-china/.
    \990\ More information on how these acts are expected to aid
employment growth and create opportunities for growth along the
supply chain can be found in the January, 2023 White House
publication ``Building a Clean Energy Economy: A Guidebook to the
Inflation Reduction Act's Investments in Clean Energy and Climate
Action.'' found online at https://www.whitehouse.gov/wp-content/uploads/2022/12/Inflation-Reduction-Act-Guidebook.pdf.
    \991\ Political Economy Research Institute. (2022). Job Creation
Estimates Through Proposed Inflation Reduction Act. University of
Massachusetts Amherst. Retrieved from https://www.bluegreenalliance.org/site/9-million-good-jobs-from-climate-action-the-inflation-reduction-act.
---------------------------------------------------------------------------

    The factor-shift effect on employment reflects potential employment
changes due to changes in labor intensity of production resulting from
compliance activities. The proposed standards do not mandate the use of
a specific technology, and EPA anticipates that a compliant fleet under
the proposed standards would include a diverse range of technologies
including ICE and ZEV technologies. In our assessment that supports the
appropriateness and feasibility of the proposed standards, we developed
a technology pathway that could be used to meet each of the standards,
which project the increased ZEV adoption rates. ZEVs and ICE vehicles
require different inputs and have different costs of production, though
there are some common parts as well. There is little research on the
relative labor intensity needs of producing a HD ICE vehicle versus
producing an equivalent HD ZEV. Though there are some news articles and
research from the light-duty motor vehicle market, they do not provide
a clear indication of the relationship between employment needs for
ZEVs and ICE vehicles. Some studies find that LD BEVs are less complex,
requiring fewer person-hours to assemble than an equivalent ICE
vehicle.\992\ Others find that there is not a significant difference in
the employment needed to produce ICE vehicles when compared to
ZEVs.\993\ We do not have data on employment differences in traditional
ICE manufacturing sectors and ZEV manufacturing sectors, especially for
expected effects in the future, nor do we have data on the employment
needed for the level of battery production we anticipate will be
required to meet future HD ZEV demand. We request comment on data
concerning the potential employment impacts of HD component and vehicle
manufacturing of ZEVs, including batteries.
---------------------------------------------------------------------------

    \992\ Barret, J. and Bivens, J. (2021). The stakes for workers
in how policymakers manage the coming shift to all-electric
vehicles. Economic Policy Institute. https://www.epi.org/publication/ev-policy-workers.
    \993\ Kupper, D., Kuhlmann, K., Tominaga, K., Arora, A.,
Schlageter, J.. (2020). Shifting Gears in Auto Manufacturing.
https://www.bcg.com/publications/2020/transformative-impact-of-electric-vehicles-on-auto-manufacturing.
---------------------------------------------------------------------------

    The demand effect reflects potential employment changes due to
changes in new HD vehicle sales. If HD ICE vehicle sales decrease,
fewer people would be needed to assemble trucks and the components used
to manufacture them. On the other hand, if HD ZEV sales increase, more
people would be needed to assemble HD ZEVs and their components,
including batteries. Additional, short-term, effects might be seen if
pre-buy or low-buy were to occur. If pre-buy occurs, HD vehicle sales
may increase temporarily, leading to temporary increases in employment
in the related manufacturing sectors. If low-buy occurs, there may be
temporary decreases in employment in the manufacturing sectors related
to HD vehicles.
    The cost effect reflects the potential impact on employment due to
increased costs from adopting technologies needed for vehicles to meet
the new emission standards. In the HD ICE vehicle manufacturing sector,
if firms invest in lower emitting HD ICE vehicles, we would expect
labor to be used to implement those technologies. We do not expect the
rule to require compliance activities in the production of ZEVs, as
these vehicles, by definition, emit zero emissions. In addition, though
the proposed standards do not mandate the use of a specific technology,
and EPA anticipates that a compliant fleet

under the proposed standards would include a diverse range of
technologies including ICE and ZEV technologies, in our assessment that
supports the appropriateness and feasibility of the proposed standards,
we developed a technology pathway that could be used to meet each of
the standards, which project increased ZEV adoption rates. Therefore,
we expect little cost effect on employment due to this rule.
    We request comment on data and methods that could be used to
estimate the potential effects of this action on employment in HD
vehicle manufacturing sectors, and on how increasing electrification in
the HD market in general, might impact employment in HD manufacturing
sectors, both for ICE powertrains as well as electrified powertrains.
We request comment on data and methods to estimate possible effects of
the proposed emission standards on employment in the HD ICE and ZEVs
manufacturing markets.
    As the share of ZEVs in the HD market increases, there may also be
effects on employment in the associated BEV charging and hydrogen
refueling infrastructure industries. These impacts may occur in several
ways, including through greater demand for charging and fueling
infrastructure to support more ZEVs, leading to more private and public
charging and fueling facilities being constructed, or through greater
use of existing facilities, which can lead to increased maintenance
needs for those facilities. We request comment on data and methods that
could be used to estimate the effect of this action on the HD BEV
vehicle charging infrastructure industry.
    Because of the diversity of the HD vehicle market, we expect that
entities from a wide range of transportation sectors would purchase
vehicles subject to the proposed emission standards. HD vehicles are
typically commercial in nature, and typically provide an ``intermediate
good,'' meaning that such vehicles are used to provide a commercial
service (transporting goods, municipal service vehicles, etc.), rather
than serving as final consumer goods themselves (as most light-duty
vehicles do). As a result, the purchase price of a new HD vehicle
likely impacts the price of the service provided by that vehicle. If
lifetime operational cost savings, or purchase incentives (as might be
available for a new ZEV), are not accounted for in the prices for
services provided by the new vehicles, this may result in higher prices
for the services provided by these vehicles compared to the same
services provided by a pre-regulation vehicle, and potentially reduce
demand for the services such vehicles provide. In turn, there may be
less employment in the sectors providing such services. On the other
hand, if these cost savings are passed on to consumers through lower
prices for services provided, it may lead to an increase in demand for
those services, and therefore may lead to an increase in employment in
those sectors providing those services. We expect that the actual
effects on demand for the services provided by these vehicles and
related employment would depend on cost pass-through, as well as
responsiveness of demand to increases in transportation cost, should
such increases occur.\994\
---------------------------------------------------------------------------

    \994\ Cost pass-through refers to the amount of increase in up-
front cost incurred by the HD vehicle owner that is then passed on
to their customers in the form of higher prices for services
provided by the HD vehicle owner.
---------------------------------------------------------------------------

    This action may also produce employment effects in other sectors,
for example, in firms providing fuel. While reduced fuel consumption
represents cost savings for purchasers of fuel, it could also represent
a loss in value of output for the petroleum refining industry, which
could result in reduced employment in that sector. Because the
petroleum refining industry is material-intensive, and EPA estimates
the reduction in fuel consumption will be mainly met by reductions in
oil imports (see Section VI.F), the employment effect is not expected
to be large.
    This proposed action could also provide some positive impacts on
driver employment in the heavy-duty trucking industry. As discussed in
Section IV, the reduction in fuel costs from purchasing a ZEV instead
of an ICE vehicle would be expected to not only reduce operational
costs for ZEV owners and operators, compared to an ICE vehicle, but may
also provide additional incentives to purchase a HD ZEV over a HD ICE
vehicle. For example, in comments submitted as part of the recent HD
2027 proposal, the Zero Emission Transportation Association stated that
driver satisfaction due to ``a smoother ride with minimal vibrations,
less noise pollution, and a high-tech driving experience free from the
fumes of diesel exhaust'' has the possibility of decreasing truck
driver shortages and increasing driver retention.

F. Oil Imports and Electricity and Hydrogen Consumption

    The proposed standards would reduce not only GHG emissions but also
liquid fuel consumption (i.e., oil consumption) while simultaneously
increasing electricity and hydrogen consumption. Reducing liquid fuel
consumption is a significant means of reducing GHG emissions from the
transportation sector. As discussed in Section V and DRIA Chapter 4, we
used an updated version of EPA's MOVES model to estimate the impact of
the proposed standards on heavy-duty vehicle emissions, fuel
consumption, and electricity consumption. In Chapter 6.5 of the DRIA,
we present fossil fuel--diesel, gasoline, CNG--consumption impacts.
Table 6-1 in Chapter 6 of the DRIA shows the estimated reduction in
U.S. oil imports under the proposed standards relative to the reference
case scenario. This proposal is projected to reduce U.S. oil imports
4.3 billion gallons through 2055. The oil import reductions are the
result of reduced consumption (i.e., reduced liquid fuel demand) of
both diesel fuel and gasoline and our estimate that 86.4 percent of
reduced liquid fuel demand results in reduced imports.\995\ DRIA Table
6-1 also includes the projected increase in electricity and hydrogen
consumption due to the proposed rule.
---------------------------------------------------------------------------

    \995\ To estimate the 86.4 percent import reduction factor, we
look at changes in U.S. crude oil imports/exports and net refined
petroleum products in the AEO 2022 Reference Case, Table 11.
Petroleum and Other Liquids Supply and Disposition, in comparison to
the Low Economic Growth Case from the AEO 2022. See the spreadsheet,
``Low vs Reference case impact on Imports 2022 AEO.xlsx''.
---------------------------------------------------------------------------

VII. Benefits of the Proposed Program

A. Social Cost of GHGs

    EPA estimated the climate benefits for the proposed standards using
measures of the social cost of three GHGs: Carbon, Methane, and Nitrous
oxide. 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 such an 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 and is the
theoretically appropriate value to use in conducting benefit-cost
analyses of policies that affect GHG emissions. EPA and other Federal
agencies began regularly incorporating SC-GHG estimates in their
benefit-cost analyses conducted under Executive

Order (E.O.) 12866 \996\ since 2008, following a Ninth Circuit Court of
Appeals remand of a rule for failing to monetize the benefits of
reducing CO2 emissions in a rulemaking process.
---------------------------------------------------------------------------

    \996\ Benefit-cost analyses have been an integral part of
executive branch rulemaking for decades. Presidents since the 1970s
have issued executive orders requiring agencies to conduct analysis
of the economic consequences of regulations as part of the
rulemaking development process. E.O. 12866, released in 1993 and
still in effect today, requires that for all regulatory actions that
are significant under 3(f)(1), an agency provide an assessment of
the potential costs and benefits of the regulatory action, and that
this assessment include a quantification of benefits and costs to
the extent feasible.''
---------------------------------------------------------------------------

    We estimate the global social benefits of CO2,
CH4, and N2O emission reductions expected from
the proposed 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 updated estimates 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 proposed 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. These SC-GHG estimates were developed over
many years using a transparent process, peer-reviewed methodologies,
the best science available at the time of that process, and with input
from the public. As discussed in Chapter 7 of the DRIA, 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. The IWG
is currently working on a comprehensive update of the SC-GHG estimates
(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. The
EPA is participating in the IWG's work. In addition, while that process
continues, EPA is continuously reviewing developments in the scientific
literature on the SC-GHG, including more robust methodologies for
estimating damages from emissions, and looking for opportunities to
further improve SC-GHG estimation going forward. Most recently, EPA has
developed a draft updated SC-GHG methodology within a sensitivity
analysis in the regulatory impact analysis of EPA's November 2022
supplemental proposal for oil and gas standards that is currently
undergoing external peer review and a public comment process. See
Chapter 7 of the DRIA for more discussion of this effort.
    We monetize benefits of the proposed standards and evaluate other
costs in part to better enable a comparison of costs and benefits
pursuant to E.O. 12866, but we recognize that there are benefits that
we are currently unable to fully quantify. EPA's consistent practice
has been to set standards to achieve improved air quality consistent
with CAA section 202 and not to rely on cost-benefit calculations, with
their uncertainties and limitations, in identifying the appropriate
standards. Nonetheless, our conclusion that the estimated benefits
considerably exceed the estimated costs of the proposed program
reinforces our view that the proposed standards represent an
appropriate weighing of the statutory factors and other relevant
considerations.
    Table VII-1 presents the estimated annual, undiscounted climate
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 for the stream of years beginning with the first year of
rule implementation, 2027, through 2055 for the proposed program. Also
shown are the present values (PV) and equivalent annualized values
(EAV) associated with each of the four interim SC-GHG values. As
discussed in the DRIA Chapter 7, 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. Our analysis includes
CO2 emission increases from EGUs that would result from our
proposal (see Section V) but we have not quantified upstream emissions
impacts associated with liquid fuel refining.

           Table VII-1--Climate Benefits From Reduction in GHG Emissions Associated With the Proposal
                                           [Millions of 2021 Dollars]
----------------------------------------------------------------------------------------------------------------
                                                                             Proposal
                                                 ---------------------------------------------------------------
                  Calendar Year                                                                       3% 95th
                                                    5% Average      3% Average     2.5% Average     Percentile
----------------------------------------------------------------------------------------------------------------
2027............................................             $33            $110            $160            $320
2028............................................              74             240             350             710
2029............................................             120             400             580           1,200
2030............................................             190             610             880           1,800
2031............................................             290             900           1,300           2,700
2032............................................             410           1,300           1,800           3,800
2033............................................             530           1,600           2,300           4,900
2034............................................             660           2,000           2,800           6,000
2035............................................             780           2,300           3,300           7,100
2036............................................             940           2,800           4,000           8,500
2037............................................           1,100           3,300           4,700           9,900

2038............................................           1,300           3,800           5,400          12,000
2039............................................           1,500           4,300           6,100          13,000
2040............................................           1,700           4,900           6,900          15,000
2041............................................           1,900           5,400           7,600          16,000
2042............................................           2,100           5,900           8,300          18,000
2043............................................           2,300           6,500           9,000          20,000
2044............................................           2,500           7,000           9,800          21,000
2045............................................           2,700           7,500          10,000          23,000
2046............................................           2,900           8,000          11,000          24,000
2047............................................           3,100           8,400          12,000          26,000
2048............................................           3,300           8,800          12,000          27,000
2049............................................           3,500           9,200          13,000          28,000
2050............................................           3,700           9,700          13,000          30,000
2051............................................           3,800          10,000          14,000          30,000
2052............................................           4,000          10,000          14,000          31,000
2053............................................           4,100          11,000          15,000          32,000
2054............................................           4,300          11,000          15,000          32,000
2055............................................           4,400          11,000          15,000          33,000
Present Value...................................          22,000          87,000         130,000         260,000
Equivalent Annualized Value.....................           1,400           4,600           6,500          14,000
----------------------------------------------------------------------------------------------------------------
Note: Climate benefits include changes in vehicle GHGs and EGU CO2 emissions, but do not include changes in
  other EGU GHGs or refinery GHGs.

B. Criteria Pollutant Health Benefits

    This section discusses the economic benefits from reductions in
adverse health impacts resulting from non-GHG emission reductions that
can be expected to occur as a result of the proposed CO2
emission standards. GHG emissions are predominantly the byproduct of
fossil fuel combustion processes that also produce criteria and
hazardous air pollutant emissions. The heavy-duty vehicles that are
subject to the proposed CO2 emission standards are also
significant sources of mobile source air pollution such as directly-
emitted PM, NOX, VOCs, CO, SO2 and air toxics. We
expect the proposed CO2 emission standards would lead to an
increase in HD ZEVs and a decrease in HD ICE vehicles, which would
result in reductions of these non-GHG pollutants (see Section V). Zero-
emission technologies would also affect emissions from upstream sources
that occur during, for example, electricity generation and from the
refining and distribution of liquid fuel (see Section V). This
proposal's benefits analysis includes added emissions due to increased
electricity generation but does not include emissions reductions from
reduced petroleum refining.
    Changes in ambient concentrations of ozone, PM2.5, and
air toxics that would result from the proposed CO2 emission
standards are expected to affect human health by reducing premature
deaths and other serious human health effects, and they are also
expected to result in other important improvements in public health and
welfare (see Section VI). Children, especially, benefit from reduced
exposures to criteria and toxic pollutants because they tend to be more
sensitive to the effects of these respiratory pollutants. Ozone and
particulate matter have been associated with increased incidence of
asthma and other respiratory effects in children, and particulate
matter has been associated with a decrease in lung maturation.
    When feasible, EPA conducts full-scale photochemical air quality
modeling to demonstrate how its national mobile source regulatory
actions affect ambient concentrations of regional pollutants throughout
the United States. The estimation of the human health impacts of a
regulatory action requires national-scale photochemical air quality
modeling to conduct a full-scale assessment of PM2.5 and
ozone-related health benefits. Air quality modeling and associated
analyses are not available for this document.
    For the analysis of the proposed CO2 emission standards
(and analysis of the alternative standards in Section IX), we instead
use a reduced-form ``benefit-per-ton'' (BPT) approach to estimate the
monetized PM2.5-related health benefits of this proposal.
The BPT approach estimates the monetized economic value of
PM2.5-related emission reductions (such as direct PM,
(NOX, and SO2) due to implementation of the
proposed program. Similar to the SC-GHG approach for monetizing
reductions in GHGs, the BPT approach estimates monetized health
benefits of avoiding one ton of PM2.5-related emissions from
a particular source sector. The value of health benefits from
reductions (or increases) in PM2.5 emissions associated with
this proposal were estimated by multiplying PM2.5-related
BPT values by the corresponding annual reduction in tons of directly-
emitted PM2.5 and PM2.5 precursor emissions
(NOX and SO2). As explained in Chapter 7.2 in the
DRIA, the PM2.5 BPT values represent the monetized value of
human health benefits, including reductions in both premature mortality
and nonfatal illnesses.
    The mobile sector BPT estimates used in this proposal were
published in 2019, but were recently updated using the suite of
premature mortality and morbidity studies in use by EPA for the 2023
p.m. NAAQS Reconsideration Proposal.997 998 The EGU BPT
estimates used in this proposal were also recently updated.\999\ The
health benefits

Technical Support Document (Benefits TSD) that accompanied the PM NAAQS
Reconsideration Proposal details the approach used to estimate the
PM2.5-related benefits reflected in the mobile source
BPTs.\1000\ For more detailed information about the benefits analysis
conducted for this proposal, including the BPT unit values used in this
analysis, please refer to Chapter 7 of the DRIA.
---------------------------------------------------------------------------

    \997\ 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. Available at: https://doi.org/10.1016/J.SCITOTENV.2018.09.273.
    \998\ U.S. Environmental Protection Agency (U.S. EPA). 2023. PM
NAAQS Reconsideration Proposal RIA. EPA-HQ-OAR-2019-0587. January.
    \999\ U.S. Environmental Protection Agency (U.S. EPA). 2023.
Technical Support Document: Estimating the Benefit per Ton of
Reducing Directly-Emitted PM2.5, PM2.5
Precursors and Ozone Precursors from 21 Sectors. January.
    \1000\ U.S. Environmental Protection Agency (U.S. EPA). 2023.
Estimating PM2.5- and Ozone-Attributable Health Benefits.
Technical Support Document (TSD) for the PM NAAQS Reconsideration
Proposal RIA. EPA-HQ-OAR-2019-0587. January.
---------------------------------------------------------------------------

    A chief limitation to using PM2.5-related BPT values is
that they do not reflect benefits associated with reducing ambient
concentrations of ozone. The PM2.5-related BPT values also
do not capture the benefits associated with reductions in direct
exposure to NO2 and mobile source air toxics, nor do they
account for improved ecosystem effects or visibility. The estimated
benefits of this proposal would be larger if we were able to monetize
these unquantified benefits at this time.
    Table VII-2 presents the annual, undiscounted PM2.5-
related health benefits estimated for the stream of years beginning
with the first year of rule implementation, 2027, through calendar year
2055 for the proposed standards. Benefits are presented by Source:
Onroad heavy-duty vehicles and EGUs. Because premature mortality
typically constitutes the vast majority of monetized benefits in a
PM2.5 benefits assessment, we present benefits based on risk
estimates reported from two different long-term exposure studies using
different cohorts to account for uncertainty in the benefits associated
with avoiding PM-related premature deaths.1001 1002 Although
annual benefits presented in the table are not discounted for the
purposes of present value or annualized value calculations, annual
benefits do reflect the use of 3-percent and 7-percent discount rates
to account for avoided health outcomes that are expected to accrue over
more than a single year (the ``cessation lag'' between the change in PM
exposures and the total realization of changes in health effects).
Table VII-2 also displays the present and annualized values of
estimated benefits that occur from 2027 to 2055, discounted using both
3-percent and 7-percent discount rates and reported in 2021 dollars. We
estimate that the present value of benefits for the proposed program is
$15 to $29 billion at a 3-percent discount rate and $5.8 to $11 billion
at a 7-percent discount rate (2021 dollars).
---------------------------------------------------------------------------

    \1001\ Wu, X, Braun, D, Schwartz, J, Kioumourtzoglou, M and
Dominici, F (2020). Evaluating the impact of long-term exposure to
fine particulate matter on mortality among the elderly. Science
advances 6(29): eaba5692.
    \1002\ Pope III, CA, Lefler, JS, Ezzati, M, Higbee, JD,
Marshall, JD, Kim, S-Y, Bechle, M, Gilliat, KS, Vernon, SE and
Robinson, AL (2019). Mortality risk and fine particulate air
pollution in a large, representative cohort of US adults.
Environmental health perspectives 127(7): 077007.

                               Table VII-2--Year-Over-Year Monetized PM2.5-Related Health Benefits of the Proposed Program
                                                                    [Millions, 2021$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                    Onroad heavy-duty vehicles                     EGUs                           Total benefits
                                                 -------------------------------------------------------------------------------------------------------
                                                    3% Discount     7% Discount                                             3% Discount     7% Discount
                                                       rate            rate        3% Discount rate    7% Discount rate        rate            rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
2027............................................          $23-49          $21-44          $(17)-(35)          $(15)-(32)         $6.4-13         $5.7-12
2028............................................          51-110           46-97           (37)-(76)           (33)-(69)           15-31           13-28
2029............................................          87-180          78-160          (61)-(130)          (55)-(110)           26-53           23-48
2030............................................         140-290         130-260         (120)-(260)         (110)-(230)           16-33           14-30
2031............................................         220-460         200-410         (240)-(500)         (220)-(450)       (22)-(45)       (20)-(40)
2032............................................         330-670         290-610         (400)-(820)         (360)-(730)      (70)-(140)      (64)-(130)
2033............................................         440-900         400-810        (560)-(1100)        (500)-(1000)     (120)-(240)     (110)-(210)
2034............................................       560-1,100       500-1,000        (720)-(1500)        (650)-(1300)     (160)-(330)     (150)-(300)
2035............................................       690-1,400       620-1,200        (890)-(1800)        (800)-(1600)     (210)-(410)     (190)-(370)
2036............................................       820-1,700       740-1,500        (930)-(1900)        (840)-(1700)     (110)-(220)     (100)-(200)
2037............................................       970-1,900       870-1,700        (930)-(1900)        (840)-(1700)           31-62           27-57
2038............................................     1,100-2,200     1,000-2,000        (890)-(1800)        (800)-(1600)         220-440         200-400
2039............................................     1,300-2,500     1,100-2,200        (810)-(1600)        (730)-(1500)         440-880         400-790
2040............................................     1,400-2,800     1,300-2,500        (700)-(1400)        (630)-(1200)       700-1,400       630-1,300
2041............................................     1,500-3,000     1,400-2,700        (660)-(1300)        (590)-(1200)       870-1,700       780-1,500
2042............................................     1,700-3,300     1,500-2,900        (610)-(1200)        (550)-(1100)     1,000-2,100       940-1,900
2043............................................     1,800-3,500     1,600-3,100        (540)-(1100)         (490)-(970)     1,200-2,400     1,100-2,200
2044............................................     1,900-3,700     1,700-3,300         (470)-(930)         (420)-(830)     1,400-2,800     1,300-2,500
2045............................................     2,000-3,900     1,800-3,500         (380)-(760)         (340)-(680)     1,600-3,100     1,400-2,800
2046............................................     2,100-4,100     1,900-3,700         (350)-(690)         (310)-(620)     1,700-3,400     1,600-3,100
2047............................................     2,200-4,300     2,000-3,800         (310)-(620)         (280)-(550)     1,900-3,600     1,700-3,300
2048............................................     2,300-4,400     2,000-4,000         (270)-(540)         (240)-(480)     2,000-3,900     1,800-3,500
2049............................................     2,300-4,600     2,100-4,100         (230)-(450)         (200)-(410)     2,100-4,100     1,900-3,700
2050............................................     2,400-4,700     2,200-4,300         (180)-(370)         (170)-(330)     2,300-4,400     2,000-3,900
2051............................................     2,500-4,900     2,300-4,400         (190)-(370)         (170)-(330)     2,300-4,500     2,100-4,100
2052............................................     2,600-5,100     2,400-4,600         (190)-(380)         (170)-(340)     2,400-4,700     2,200-4,200
2053............................................     2,700-5,200     2,400-4,700         (190)-(380)         (170)-(340)     2,500-4,800     2,300-4,400
2054............................................     2,800-5,400     2,500-4,800         (190)-(390)         (170)-(350)     2,600-5,000     2,300-4,500
2055............................................     2,900-5,500     2,600-5,000         (200)-(390)         (180)-(350)     2,700-5,200     2,400-4,600
Present Value...................................   23,000-46,000   10,000-20,000    (8,200)-(17,000)     (4,600)-(9,300)   15,000-29,000    5,800-11,000

Equivalent Annualized Value.....................     1,200-2,400       840-1,700         (430)-(860)         (380)-(760)       780-1,500         470-910
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes: The range of benefits in this table reflect the range of premature mortality estimates derived from the Medicare study (Wu et al., 2020) and the
  NHIS study (Pope et al., 2019). All benefits estimates are rounded to two significant figures. Annual benefit values presented here are not
  discounted. Negative values in parentheses are health disbenefits related to increases in estimated emissions. The present value of benefits is the
  total aggregated value of the series of discounted annual benefits that occur between 2027-2055 (in 2021 dollars) using either a 3% or 7% discount
  rate. The benefits associated with the standards presented here do not include health benefits associated with reduced criteria pollutant emissions
  from refineries. The benefits in this table also do not include the full complement of health and environmental benefits that, if quantified and
  monetized, would increase the total monetized benefits.

    This analysis includes many data sources that are each subject to
uncertainty, including projected emission inventories, air quality data
from models, population data, population estimates, health effect
estimates from epidemiology studies, economic data, and assumptions
regarding the future state of the world (i.e., regulations, technology,
and human behavior). When compounded, even small uncertainties can
greatly influence the size of the total quantified benefits. There are
also inherent limitations associated with using the BPT approach.
Despite these uncertainties, we believe the criteria pollutant benefits
presented here are our best estimate of benefits absent air quality
modeling and we have confidence in the BPT approach and the
appropriateness of relying on BPT health estimates for this rulemaking.
Please refer to DRIA Chapter 7 for more information on the uncertainty
associated with the benefits presented here.

C. Energy Security

    The proposed CO2 emission standards are designed to
require reductions in GHG emissions from HD vehicles in the 2027-2032
and beyond timeframe and, thereby, reduce liquid fuel consumption. We
expect the standards will be met through a combination of zero-emission
technologies and improvements in ICE vehicle technologies, which would,
in turn, reduce the demand for liquid fuels and enable the United
States to reduce 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 United
States, thus increasing U.S. energy security.
    Energy security is broadly defined as the uninterrupted
availability of energy sources at affordable prices.\1003\ Energy
independence and energy security are distinct but related concepts. The
goal of U.S. energy independence is the elimination of all U.S. imports
of petroleum and other foreign sources of energy, but more broadly it
is the elimination of U.S. sensitivity to the variations in the price
and supply of foreign sources of energy.\1004\ See Chapter 7 of the
DRIA for a more detailed assessment of energy security and energy
independence impacts of this proposed rule and Section II.D.2.ii for a
discussion on battery critical materials and supply.
---------------------------------------------------------------------------

    \1003\ International Energy Agency. ``Energy security: Ensuring
the uninterrupted availability of energy sources at an affordable
price''. Last updated December 2, 2019.
    \1004\ Greene, D. 2010. Measuring energy security: Can the
United States achieve oil independence? Energy Policy 38, pp. 1614-
1621.
---------------------------------------------------------------------------

    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 estimates the risk of reductions in U.S. economic output
and disruption to the U.S. economy caused by sudden disruptions in
world oil supply and associated price shocks (i.e., labeled the avoided
macroeconomic disruption/adjustment costs). These risks are quantified
as ``macroeconomic oil security premiums,'' i.e., the extra costs of
oil use besides its market price.
    For this proposed rule, EPA is using macroeconomic oil security
premiums estimated using ORNL's methodology, which incorporates updated
oil price projections and energy market and economic trends from the
U.S. Department of Energy's Energy Information Administration's (EIA)
Annual Energy Outlook (AEO) 2022. EPA and ORNL have worked together to
revise the macroeconomic oil security premiums based upon recent energy
security literature. We do not consider military cost impacts as a
result of reductions in U.S. oil imports from this proposed rule due to
methodological issues in quantifying these impacts.
    To calculate the oil security benefits of this proposed rule, EPA
is using the ORNL macroeconomic oil security premium methodology with:
(1) Estimated oil savings calculated by EPA and (2) An oil import
reduction factor of 86.4 percent, which shows how much U.S. oil imports
are reduced from changes in U.S. oil consumption. In Table VII-3, EPA
presents the macroeconomic oil security premiums and the energy
security benefits for the proposed HDV standards for the years from
2027-2055.

 Table VII-3--Macroeconomic Oil Security Premiums (2021$/Barrel) and Energy Security Benefits With the Proposal
                                             [In millions of 2021$]
----------------------------------------------------------------------------------------------------------------
                                                                                Energy
                           Calendar year                             Macroeconomic oil security      security
                                                                          premiums (range)           benefits
----------------------------------------------------------------------------------------------------------------
2027..............................................................           $3.57 ($0.79-$6.65)             $15
2028..............................................................           $3.65 ($0.80-$6.79)              33
2029..............................................................           $3.72 ($0.80-$6.92)              55
2030..............................................................           $3.79 ($0.81-$7.06)              91
2031..............................................................           $3.87 ($0.85-$7.22)             140
2032..............................................................           $3.96 ($0.89-$7.38)             210
2033..............................................................           $4.04 ($0.92-$7.53)             280
2034..............................................................           $4.13 ($0.96-$7.69)             350
2035..............................................................           $4.21 ($1.00-$7.85)             420
2036..............................................................           $4.29 ($1.03-$7.98)             490
2037..............................................................           $4.36 ($1.06-$8.11)             560
2038..............................................................           $4.44 ($1.10-$8.24)             620
2039..............................................................           $4.51 ($1.13-$8.37)             690
2040..............................................................           $4.59 ($1.16-$8.50)             750
2041..............................................................           $4.65 ($1.19-$8.62)             800
2042..............................................................           $4.71 ($1.21-$8.73)             850
2043..............................................................           $4.76 ($1.24-$8.85)             900
2044..............................................................           $4.82 ($1.26-$8.96)             940
2045..............................................................           $4.88 ($1.29-$9.08)             990
2046..............................................................           $4.94 ($1.32-$9.18)           1,000
2047..............................................................           $5.00 ($1.35-$9.28)           1,100
2048..............................................................           $5.06 ($1.37-$9.37)           1,100
2049..............................................................           $5.12 ($1.40-$9.46)           1,100
2050..............................................................           $5.18 ($1.43-$9.56)           1,200
2051..............................................................           $5.18 ($1.43-$9.56)           1,200
2052..............................................................           $5.18 ($1.43-$9.56)           1,200
2053..............................................................           $5.18 ($1.43-$9.56)           1,200
2054..............................................................           $5.18 ($1.43-$9.56)           1,300
2055..............................................................           $5.18 ($1.43-$9.56)           1,300
PV, 3%............................................................  ............................          12,000
PV, 7%............................................................  ............................           6,000
EAV, 3%...........................................................  ............................             620
EAV, 7%...........................................................  ............................             490
----------------------------------------------------------------------------------------------------------------

VIII. Comparison of Benefits and Costs

    This section compares the estimated range of benefits associated
with reductions of GHGs, monetized health benefits from reductions in
PM2.5, energy security benefits, fuel savings, and vehicle-
related operating savings to total costs associated with the proposal
and the alternative. Estimated costs are detailed and presented in
Section IV of this preamble. Those costs include costs for both the new
technology in our technology package and the operating costs associated
with that new technology. Importantly, as detailed in Section IV of
this preamble, the vehicle costs presented here exclude both the IRA
battery tax credit and vehicle tax credit while the fuel savings
exclude fuel taxes; as such, these costs, along with other operating
costs, represent the social costs and/or savings associated with the
proposed standards. Benefits from the reduction of GHG emissions and
criteria pollutant emissions, and energy security benefits associated
with reductions of imported oil, are presented in Section VII.

A. Methods

    EPA presents three different benefit-cost comparisons for the
proposal and the alternative:
    1. A future-year snapshot comparison of annual benefits and costs
in the year 2055, chosen to approximate the annual health benefits that
would occur in a year when the program would be fully implemented and
when most of the regulated fleet would have turned over. Benefits,
costs, and net benefits are presented in year 2021 dollars and are not
discounted. However, 3-percent and 7-percent discount rates were
applied to account for avoided health outcomes that are expected to
accrue over more than a single year (the ``cessation lag'' between the
change in PM exposures and the total realization of changes in health
effects).
    2. The present value (PV) of the stream of benefits, costs, and net
benefits calculated for the years 2027 through 2055, discounted back to
the first year of implementation of the proposed rule (2027) using both
3-percent and 7-percent discount rates, and presented in year 2021
dollars. Note that year-over-year costs are presented in Section IV and
year-over-year benefits may be found in Section VII.
    3. The equivalent annualized value (EAV) of benefits, costs, and
net benefits representing a flow of constant annual values that, had
they occurred in each year from 2027 through 2055, would yield an
equivalent present value to those estimated in method 2 (using either a
3-percent or 7-percent discount rate). Each EAV represents a typical
benefit, cost, or net benefit for each year of the analysis and is
presented in year 2021 dollars.

B. Results

    Table VIII-1 shows the undiscounted annual monetized vehicle-
related technology package RPE costs of the proposal and alternative in
calendar year 2055. The table also shows the PV and EAV of those costs
for the calendar years 2027 through 2055 using both 3-percent and 7-
percent discount rates. The table includes an estimate of the vehicle
technology package RPE costs and the costs associated with EVSE.

    Note that all costs, savings, and benefits estimates presented in
the tables that follow are rounded to two significant figures; numbers
may not sum due to independent rounding.

                               Table VIII-1--Vehicle-Related Technology Costs Associated With the Proposal and Alternative
                                                               [Millions of 2021 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                Proposal                                               Alternative
                                       -----------------------------------------------------------------------------------------------------------------
                                             Vehicle                                                  Vehicle
                                            technology          EVSE RPE             Sum             technology          EVSE RPE             Sum
                                           package RPE                                              package RPE
--------------------------------------------------------------------------------------------------------------------------------------------------------
2055..................................            -$1,500             $2,900             $1,400            -$1,200             $2,100               $880
PV, 3%................................              9,000             47,000             56,000              4,000             33,000             37,000
PV, 7%................................             10,000             29,000             39,000              5,400             20,000             25,000
EAV, 3%...............................                470              2,500              2,900                210              1,700              1,900
EAV, 7%...............................                820              2,300              3,200                440              1,600              2,100
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Table VIII-2 shows the undiscounted annual monetized vehicle-
related operating savings of the proposal and alternative in calendar
year 2055. The table also shows the PV and EAV of those savings for
calendar years 2027 through 2055 using both 3-percent and 7-percent
discount rates. The savings in diesel exhaust fluid (DEF) consumption
arise from the electrification of the HD fleet and the corresponding
decrease in diesel engine equipped vehicles which require DEF to
maintain compliance with NOX emission standards. The
maintenance and repair savings are substantial due again to
electrification of the HD fleet, with HD BEVs and FCEVs projected to
require 71 percent and 75 percent, respectively, of the maintenance and
repair costs required of HD vehicles equipped with internal combustion
engines.

                                                  Table VIII-2--Vehicle-Related Operating Savings Associated With the Proposal and Alternative
                                                                                [Millions of 2021 dollars *]
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Proposal                                                       Alternative
                                                                 -------------------------------------------------------------------------------------------------------------------------------
                                                                   Pre-tax fuel                    Maintenance &                   Pre-tax fuel                    Maintenance &
                                                                      savings       DEF savings   repair savings  Sum of savings      savings       DEF savings   repair savings  Sum of savings
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2055............................................................          $4,300          $2,300         $24,000         $31,000          $2,800          $1,700         $17,000         $22,000
PV, 3%..........................................................          28,000          22,000         200,000         250,000          18,000          15,000         140,000         180,000
PV, 7%..........................................................          14,000          11,000          99,000         120,000           8,900           7,900          71,000          87,000
EAV, 3%.........................................................           1,400           1,100          10,000          13,000             920             810           7,400           9,100
EAV, 7%.........................................................           1,100             900           8,100          10,000             720             640           5,800           7,100
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
* Fuel savings are net of savings in diesel, gasoline, and CNG consumption with increased electricity and hydrogen consumption; DEF savings accrue only to diesel vehicles; maintenance and
  repair savings include impacts associated with all fuels.

    Table VIII-3 shows the undiscounted annual monetized energy
security benefits of the proposal and alternative in calendar year
2055. The table also shows the PV and EAV of those benefits for
calendar years 2027 through 2055 using both 3-percent and 7-percent
discount rates.

 Table VIII-3--Energy Security Benefits Associated With the Proposal and
                               Alternative
                       [Millions of 2021 dollars]
------------------------------------------------------------------------
                                             Proposal       Alternative
------------------------------------------------------------------------
2055....................................          $1,300            $910
PV, 3%..................................          12,000           8,500
PV, 7%..................................           6,000           4,300
EAV, 3%.................................             620             440
EAV, 7%.................................             490             350
------------------------------------------------------------------------

    Table VIII-4 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 (IWG). As discussed in DRIA
Chapter 7, 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. These climate benefits include benefits
associated with reduced vehicle GHGs and increased EGU CO2
emissions, but do not include any impacts associated with petroleum
extraction, petroleum transportation, or liquid fuel refining.
    Table VIII-5 shows the undiscounted annual monetized
PM2.5-related health benefits of the proposal and
alternative in calendar year 2055. The table also shows the PV and EAV
of those benefits for calendar years 2027 through 2055 using both 3-
percent and 7-percent discount rates. The range of benefits in this
table reflect the two premature mortality estimates derived from the
Medicare study (Wu et al., 2020) and the NHIS study (Pope et al.,
2019).1005 1006
---------------------------------------------------------------------------

    \1005\ Wu, X, Braun, D, Schwartz, J, Kioumourtzoglou, M and
Dominici, F (2020). Evaluating the impact of long-term exposure to
fine particulate matter on mortality among the elderly. Science
advances 6(29): eaba5692.
    \1006\ Pope III, CA, Lefler, JS, Ezzati, M, Higbee, JD,
Marshall, JD, Kim, S-Y, Bechle, M, Gilliat, KS, Vernon, SE and
Robinson, AL (2019). Mortality risk and fine particulate air
pollution in a large, representative cohort of U.S. adults.
Environmental health perspectives 127(7): 077007.

                       Table VIII-4--Climate Benefits From Reduction in GHG Emissions Associated With the Proposal and Alternative
                                                               [Millions of 2021 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Proposal                                     Alternative
                                                             -------------------------------------------------------------------------------------------
                                                                  5%         3%        2.5%      3% 95th        5%         3%        2.5%      3% 95th
                                                               Average    Average    Average    Percentile   Average    Average    Average    Percentile
--------------------------------------------------------------------------------------------------------------------------------------------------------
2055........................................................     $4,400    $11,000    $15,000      $33,000     $3,200     $8,000    $11,000      $24,000
PV..........................................................     22,000     87,000    130,000      260,000     16,000     62,000     96,000      190,000
EAV.........................................................      1,400      4,600      6,500       14,000      1,000      3,300      4,700        9,900
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes: Climate benefits are based on changes (reductions) in CO2, CH4, and N2O emissions and are calculated using four different estimates of the social
  cost of carbon (SC-CO2), the social cost of methane (SC-CH4), and the social cost of nitrous oxide (SC-N2O) (model average at 2.5-percent, 3-percent,
  and 5-percent discount rates; 95th percentile at 3-percent discount rate). The 95th perncentile estimate was included to provide information on
  potentially higher-than-expected economic impacts from climate change, conditional on the 3 percent estimate of the discount rate. We emphasize the
  importance and value of considering the benefits calculated using all four SC-CO2, SC-CH4, and SC-N2O estimates. As discussed in the Technical Support
  Document: Social Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates under Executive Order 13990 (IWG 2021), a consideration of climate
  benefits calculated using discount rates below 3 percent, including 2 percent and lower, are also warranted when discounting intergenerational
  impacts.
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 VIII-5--PM2.5-Related Emission Reduction Benefits Associated With the Proposal and Alternative
                                           [Millions of 2021 dollars]
----------------------------------------------------------------------------------------------------------------
                                                    Proposal                             Alternative
                                     ---------------------------------------------------------------------------
                                              3%                 7%                 3%                 7%
----------------------------------------------------------------------------------------------------------------
2055................................      $2,700-$5,200      $2,400-$4,600      $1,900-$3,700      $1,700-$3,300
PV..................................      15,000-29,000       5,800-11,000      11,000-21,000        4,200-8,200
EAV.................................          780-1,500            470-910          570-1,100            340-670
----------------------------------------------------------------------------------------------------------------
Notes: The range of benefits in this table reflects the range of premature mortality estimates derived from the
  Medicare study (Wu et al., 2020) and the NHIS study (Pope III et al., 2019). All benefits estimates are
  rounded to two significant figures. The present value of benefits is the total aggregated value of the series
  of discounted annual benefits that occur between 2027-2055 (in 2021 dollars) using either a 3-percent or 7-
  percent discount rate. The benefits associated with the standards presented here do not include health
  benefits associated with reduced criteria pollutant emissions from refineries. The benefits in this table also
  do not include the full complement of health and environmental benefits that, if quantified and monetized,
  would increase the total monetized benefits.

    Table VIII-6 shows the undiscounted annual net benefits of the
proposal and alternative in calendar year 2055 using each of the four
social cost of GHG valuations. The table also shows the PV and EAV of
the net benefits for calendar years 2027 through 2055 using both 3-
percent and 7-percent discount rates. For presentational simplicity, we
use the mid-point of the range of PM2.5 benefits in the
annual 2055 net benefit calculation. For the calculation of PV and EAV
net benefits, we use the high-end estimate of PM2.5 benefits
assuming a 3-percent discount rate and the low-end estimate of benefits
assuming a 7-percent discount rate in the corresponding 3- and 7-
percent PV and EAV estimates. These choices do not fundamentally alter
the net benefit calculations since differences between the chosen
PM2.5 benefit estimates are not reflected when net benefits
are rounded to two significant figures. These net benefits include
benefits associated with reduced vehicle GHGs and increased EGU
CO2 emissions, but do not include any impacts associated
with petroleum extraction, petroleum transportation or liquid fuel
refining.

                                         Table VIII-6--Net Benefits Associated With the Proposal and Alternative
                                                               [Millions of 2021 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                            Proposal  Average                                Alternative
                                                             -------------------------------------------------------------------------------------------
                                                                  5%         3%        2.5%      3% 95th        5%         3%        2.5%      3% 95th