EPA proposed to revise the definition of ``Footprint'' in 86.1803-01 to
clarify measurement and rounding. The previous definition stated that
track width is ``measured in inches,'' which may inadvertently imply
measuring and recording to the nearest inch. The revised definition
clarifies that measurements should be to the nearest one tenth of an
inch, and average track width should be rounded to the nearest tenth of
an inch. EPA received no comments on this provision, and is finalizing
as proposed.

    We are also finalizing a solution to a situation in which a
manufacturer of a clean alternative fuel conversion is attempting to
comply with the fuel conversion regulations (see 40 CFR part 85 subpart
F) at a point in time before which certain data is available from the
original manufacturer of the vehicle. Clean alternative fuel
conversions are subject to greenhouse gas standards if the vehicle as
originally manufactured was subject to greenhouse gas standards, unless
the conversion manufacturer qualifies for exemption as a small
business. Compliance with light-duty vehicle greenhouse gas emission
standards is demonstrated by complying with the N2O and
CH4 standards and the in-use CO2 exhaust emission
standard set forth in 40 CFR 86.1818-12(d) as determined by the
original manufacturer for the subconfiguration that is identical to the
fuel conversion emission data vehicle (EDV). However, the
subconfiguration data may not be available to the fuel conversion
manufacturer at the time they are seeking EPA certification. Several
compliance options are currently provided to fuel conversion
manufacturers that are consistent with the compliance options for the
original equipment manufacturers. EPA is adding another option that
will be applicable starting with the 2012 model year. The new option
will allow clean alternative fuel conversion manufacturers to satisfy
the greenhouse gas standards if the pre-conversion sum of
CH4 plus N2O plus CREE emissions from the vehicle
is less than the post-conversion emissions, adjusting for the global
warming potential of the constituents.
10. Base Tire Definition
    One of the factors in a manufacturer's calculation of vehicle
footprint is the base tire. Footprint is based on a vehicle's wheel
base and track width, and track width in turn is ``the lateral distance
between the centerlines of the base tires at ground, including the
camber angle.'' \634\ EPA's current definition of base tire is the
``tire specified as standard equipment by the manufacturer.'' \635\
NHTSA proposed a specific change to the base tire definition for the
CAFE program (see Section IV.I.5.g, and proposed 49 CFR 523.2), and EPA
requested comment on whether the base tire definition should be
clarified to ensure a more uniform application across manufacturers (76
FR 75088, December 1, 2011).
---------------------------------------------------------------------------

    \634\ See 40 CFR 86.1803-01
    \635\ See 40 CFR 86.1803-01, and 40 CFR 600.002. Standard
equipment means those features or equipment which are marketed on a
vehicle over which the purchaser can exercise no choice.
---------------------------------------------------------------------------

    Vehicle manufacturers were the only parties providing comments on
this issue, and they were essentially unanimous in stating a desire for
a level playing field, while reiterating that the issue is complex.
Several manufacturers pointed out that the proposed NHTSA definition,
which includes a connection to a vehicle configuration, may not be
workable because the definition of a configuration is independent of
vehicle size, or footprint. Several manufacturers suggested that EPA,
NHTSA, and the auto companies should postpone action on this issue in
this rule and work together to ensure a consistent and complete
understanding of the issue. Others agreed that the definition could
benefit from some clarification. After consideration of the comments,
and a recognition of the importance that the footprint calculation (and
therefore all the elements that comprise the footprint calculation) be
harmonized across EPA and NHTSA, EPA is finalizing a revised definition
in this final rule, which is consistent with the definition being
finalized by NHTSA. The revised definition is as follows:

    Base tire means the tire size specified as standard equipment by
the manufacturer on each unique

combination of a vehicle's footprint and model type. Standard equipment
is defined in 40 CFR 86.1803-01.
    This definition appropriately removes the link to vehicle
configuration that was in NHTSA's proposal, and improves upon EPA's
existing definition with additional specificity that is consistent with
the goal of a footprint-based program, which, as stated by the Alliance
of Automobile Manufacturers, is that ``All vehicles should be included
* * * using a representative footprint based on the physical vehicle *
* *'' EPA agrees with this broadly stated goal, and we believe that the
revised definition offers reasonable clarification that should help
ensure a consistent application of the footprint-based standards across
manufacturers. This new definition, which is harmonized with the
definition being finalized by NHTSA, is also consistent with existing
regulatory language that specifies how EPA intends that footprint-based
standards be implemented. For example, EPA regulations currently state
that ``Each CO2 target value, which represents a unique
combination of model type and footprint value, shall be multiplied by
the total production of that model type/footprint combination for the
appropriate model year'' (see 40 CFR 86.1818-12(c)(2)).
11. Treatment of Driver-Selectable Modes and Conditions
    EPA requested comments on whether there is a need to clarify in the
regulations how EPA treats driver-selectable modes (such as multi-mode
transmissions and other user-selectable buttons or switches) that may
impact fuel economy and GHG emissions in certification testing. See 76
FR 75089; see also section II.F of this preamble for a discussion of
how driver-selectable technologies may be eligible for off-cycle
credits under the case-by-case demonstration provisions in the rule.
New technologies continue to arrive on the market, with increasing
complexity and an increasing array of ways a driver can make choices
that affect the fuel economy and greenhouse gas emissions. For example,
some start-stop systems may offer the driver the option of choosing
whether or not the system is enabled. Similarly, vehicles with ride
height adjustment or grill shutters may allow drivers to override those
features. Note that this discussion pertains specifically to
implementing the testing required on the Federal Test Procedure and the
Highway Fuel Economy Test to generate combined City/Highway GHG and MPG
values for each model type for use in calculating fleet average GHG and
MPG values. For the purpose of assigning off-cycle credit values that
may be based on a driver-selectable technology (see section II.F),
where determination of an accurate real-world benefit of the technology
is a fundamental goal, the policy described here and in current EPA
guidance may not be appropriate.
    Under the current regulations, EPA draws a distinction between
vehicles tested for purposes of CO2 emissions performance
and fuel economy and vehicles tested for non-CO2 emissions
performance. When testing emission data vehicles for certification
under Part 86 for non-CO2 emissions standards, a vehicle
that has multiple operating modes must meet the applicable emission
standards in all modes, and on all fuels. Sometimes testing may occur
in all modes, but more frequently the worst-case mode is selected for
testing to represent the emission test group. For example, a vehicle
that allows the user to disengage the start-stop capability must meet
the standards with and without the start-stop system operating.
Similarly, a plug-in hybrid electric vehicle is tested in charge-
sustaining (i.e., gasoline-only) operation. Current regulations require
the reporting of CO2 emissions from certification tests
conducted under Part 86, but EPA regulations also recognize that these
values, from emission data vehicles that represent a test group, are
ultimately not the values that are used to establish in-use
CO2 standards (which are established on much more detailed
sub-configuration-specific level) or the model type CO2 and
fuel economy values used for fleet averaging under Part 600.
    When EPA tests vehicles for fuel economy and CO2
emissions performance, user-selectable modes are treated somewhat
differently, where the goals are different and where worst-case
operation may not be the appropriate choice for testing. For example,
EPA does not believe that the fuel economy and CO2 emissions
value for a PHEV should ignore the use of grid electricity, or that
other dual fuel vehicles should ignore the real-world use of
alternative fuels that reduce GHG emissions. For PHEVs and dual fuel
CNG vehicles, where the consumer pays an up-front premium for the
vehicle but can recoup that investment by using a less expensive fuel,
the regulations allow the use of utility factors to weight the
CO2 performance on the conventional fuel and the alternative
fuel. Similarly, non-CO2 emission certification testing may
be done in a transmission mode that is not likely to be the predominant
mode used by consumers. Testing under Part 600 must determine a single
fuel economy value for each model type for the CAFE program and a
single CO2 value for each model type for EPA's program. With
respect to transmissions, Part 600 refers to 40 CFR 86.128, which
states the following:
    ``All test conditions, except as noted, shall be run according
to the manufacturer's recommendations to the ultimate purchaser,
Provided, That: Such recommendations are representative of what may
reasonably be expected to be followed by the ultimate purchaser
under in-use conditions.''

    For multi-mode transmissions EPA relies on guidance letter CISD-09-
19 (December 3, 2009) to guide the determination of what is
``representative of what may reasonably be expected to be followed by
the ultimate purchaser under in-use conditions.'' If EPA can make a
determination that a certain mode is the ``predominant'' mode (meaning
nearly total usage), then testing may be done in that mode. However, if
EPA cannot be convinced that a single mode is predominant, then fuel
economy and GHG results from each mode are typically averaged with
equal weighting. There are also detailed provisions that explain how a
manufacturer may conduct surveys to support a statement that a given
mode is predominant. However, CISD-09-19 only addresses transmissions,
and states the following regarding other technologies:

    ``Please contact EPA in advance to request guidance for vehicles
equipped with future technologies not covered by this document,
unusual default strategies or driver selectable features, e.g.,
hybrid electric vehicles where the multimode button or switch
disables or modifies any fuel saving features of the vehicle (such
as the stop-start feature, air conditioning compressor operation,
electric-only operation, etc.).''

    The unique operating characteristics of these technologies often
requires that EPA determine fuel economy and CO2 testing and
calculations on a case-by-case basis. Because the CAFE and
CO2 programs require a single value to represent a model
type, EPA must make a decision regarding how to account for multiple
modes of operation. When a manufacturer brings such a technology to us
for consideration, we will evaluate the technology (including possibly
requiring that the manufacturer give us a vehicle to test) and provide
the manufacturer with instructions on how to determine fuel economy and
CO2 emissions. In general we will evaluate these
technologies in the same way and following the same principles we use
to evaluate transmissions under CISD-09-19, making a determination as
to whether a given operating mode is predominant or not (using the
criteria for predominance described in CISD-

09-19). These instructions are provided to the manufacturer under the
authority for special test procedures described in 40 CFR 600.111-08.
EPA would apply the same approach to testing for compliance with the
in-use CO2 standard, so testing for the CO2 fleet
average and testing for compliance with the in-use CO2
standard would be consistent.
    EPA requested comment on whether the current approach and
regulatory provisions are sufficient, or whether additional regulations
or guidance should be developed to describe EPA's process.
Manufacturers, who were the only commenters on this issue, commented
that the current case-by-case approach is adequate, and EPA agrees. We
recognize that no regulation can anticipate all options, devices, and
operator controls that may arrive in the future, and adequate
flexibility to address future situations is an important attribute for
fuel economy and CO2 emissions testing. We believe it would
be difficult at this time to construct regulations that adequately and
generically address the use of multiple modes in GHG/MPG testing.
12. Publication of GHG Compliance Information
    As was the case in the MYs 2012-2016 regulation, EPA received
several comments about the need for transparency in its implementation
of the greenhouse gas program and specifically about the need for
public access to information about Agency compliance determinations.
NRDC argued that EPA and NHTSA should publish data on each
manufacturer's credit status and technology penetration on an annual
basis. They suggested specific data that should be disclosed, by car
and truck fleets, including the amount of cumulative credits or debits,
the within-manufacturer credit transfers between car and truck fleets,
air conditioning credits, use of multipliers for EVs, PHEVs, and FCVs,
full size pick-up truck HEV and performance-based credits, and off-
cycle technology credits. They further suggested that the Fuel Economy
Trends Report and the Fuel Economy Guide and associated online database
could be enhanced to include additional vehicle and technology
information, by model and manufacturer. The Union of Concerned
Scientists (UCS) reiterated these comments, noting that EPA should have
a ``clear public accounting of credits and program compliance.'' They
specifically request that data at the ``sub-model level'' be published
regularly, and that such data include the following: model year, make,
model/nameplate, engine family, transmission type, criteria pollutant
certification levels, number of cylinders, fuel type, drive type,
horsepower, footprint, GHG emissions and fuel economy test results,
window label fuel economy, sales volume, sales origin, market
classification, EPA classification, and whether a vehicle is using the
TLAAS program standards. Like NRDC, UCS also requested enhancements to
the Light-Duty Automotive Technology, Carbon Dioxide Emissions, and
Fuel Economy Trends report by adding information on car/truck
designations and vehicle size/footprint.
    EPA remains committed to the principle of transparency and to
disseminating as much information as we are reasonably and legally able
to provide. Not surprisingly, manufacturers have also commented about
the need to protect confidential business information, a practice to
which we also remain committed. As stated in the MYs 2012-2016 final
rule, EPA expects that the dissemination of GHG program data will
possibly take place through the annual Fuel Economy Trends report, the
annual Compliance Report, or through other means, such as online
distribution through fueleconomy.gov or other EPA Web sites, new GHG-
specific reports, or through some combination of all of these. Given
that the data will be released well after the conclusion of a given
model year, certain information is clearly no longer confidential
business information. For example, vehicle production volumes by model
type are unlikely to be treated as confidential given that essentially
the same information can be purchased from sources like WardsAuto. But
production volumes at a finer level of detail, such as at the
subconfiguration or configuration level, could potentially be
considered confidential because those volumes, which are not available
elsewhere, may potentially reveal something about a manufacturer's
long-term strategies. These are issues and questions that EPA expects
to be addressing as we move forward with publishing our compliance
data.
    EPA already releases a considerable amount of information regarding
fuel economy, emissions, and vehicle characteristics, both at the test
level and at the model type level.\636\ The downloadable model type
data available at fueleconomy.gov will soon have CO2
emissions values (adjusted label values and unadjusted values, similar
to the MPG reporting) in addition to the 127 columns of data we already
provide for each model type. However, we plan to expand what we release
publicly such that more information is available regarding GHG program
compliance, For example, EPA intends to publish the applicable fleet
average standards (for cars and for trucks) and the actual fleet
performance for each manufacturer, and the resulting credits or debits
(in Megagrams, or metric tons). In addition, EPA anticipates publishing
the amount of credits generated by each manufacturer (separately for
each of the car and truck fleets) under the optional credit programs,
and the associated volumes of vehicles to which those credits apply.
EPA will also likely publish various credit transactions (transfers
among fleets within a manufacturer and trades between manufacturers),
as well as the total credits or debits accumulated in a model year and
the resulting overall credit or debit balance, taking into account the
credit and debit carry-forward provisions. EPA anticipates that the
data publication will evolve over time, both as the program progresses
and as our data systems adapt to the new requirements and are able to
manage and report data accurately and effectively. For example, our
first public release of information is likely to be a summary of the
early credits generated in the 2009-2011 model years that, at least
initially, may not be as comprehensive as the reporting that follows
the 2012 model year.\637\ EPA is currently assessing how to best
release these data (both the content and the mechanism), but expects
that publication will occur later this year.
---------------------------------------------------------------------------

    \636\ See http://www.epa.gov/otaq/tcldata.htm and http://www.fueleconomy.gov/.
    \637\ Reporting of these credits was due from manufacturers at
the end of March, 2012, and EPA is currently evaluating the data to
ensure compliance with regulatory requirements.
---------------------------------------------------------------------------

F. How will this rule reduce GHG emissions and their associated
effects?

    This action is an important step towards curbing growth of GHG
emissions from cars and light trucks. In the absence of control, GHG
emissions worldwide and in the U.S. are projected to continue steady
growth. Table III-60 shows emissions of carbon dioxide
(CO2), methane (CH4), nitrous oxide
(N2O) and air conditioning refrigerant (HFC-134a) on a
CO2-equivalent basis for calendar years 2010, 2020, 2030,
2040 and 2050. As shown below, in 2010 U.S. GHG emissions made up
roughly 15 percent of total worldwide emissions. The contribution of
direct emissions from cars and light-trucks to this U.S. share is an
estimated 16 percent of U.S. emissions by 2030 in the

absence of control (beyond the control provided by the MY 2016 GHG
standards for these vehicles). As discussed later in this section, this
steady rise in GHG emissions is associated with numerous adverse
impacts on human health, food and agriculture, air quality, and water
and forestry resources.

                 Table III-60--GHG Emissions by Calendar Year Without the MY 2017-2025 Standards
                                                [MMTCO2eq] \638\
----------------------------------------------------------------------------------------------------------------
                                       2010            2020            2030            2040            2050
----------------------------------------------------------------------------------------------------------------
All Sectors (Worldwide) \a\.....          45,000          53,000          61,000          69,000          76,000
All Sectors (U.S. Only) a b.....           6,800           7,300           7,600           8,000           8,100
U.S. Cars/Light Truck Only \c\..           1,100           1,200           1,200           1,400           1,600
----------------------------------------------------------------------------------------------------------------
\a\ Global Change Assessment Model (GCAM).\639\
\b\ 2010 data is from USEPA GHG Inventory,\640\ future year data is from Applied Dynamic Analysis of the Global
  Economy (ADAGE) model.\641\
\c\ 2010 data is from USEPA GHG Inventory, future year data from OMEGA model, Tailpipe CO2 and HFC134a only
  (includes impacts of MYs 2012-2016 standards).

    This rule will result in significant GHG reductions as newer,
cleaner vehicles come into the fleet. EPA estimates the reductions
attributable to the MYs 2017-2025 standards over time assuming the
model year 2025 standards continue indefinitely post-2025, compared to
a reference scenario in which the 2016 model year GHG standards
continue indefinitely beyond 2016.
---------------------------------------------------------------------------

    \638\ ADAGE and GCAM model projections of worldwide and U.S. GHG
emissions are provided for context only. The baseline data in these
models differ in certain assumptions from the baseline used in this
rule. For example, the ADAGE baseline is calibrated to AEO 2010,
which includes the EISA 35 MPG by 2020 provision, but does not
explicitly include the MYs 2012-2016 rule or the 2014-2018 HD GHG
rule. All emissions data were rounded to two significant digits.
    \639\ Based on the Representative Concentration Pathway scenario
in GCAM available at www.globalchange.umd.edu/gcamrcp. See section
III.F.3 and RIA Chapter 6.4 for additional information on GCAM.
---------------------------------------------------------------------------

    For this rule, EPA estimates greenhouse gas impacts from several
sources including: (a) The impact of the standards on tailpipe
CO2 emissions, (b) projected improvements in the efficiency
of vehicle air conditioning systems as a result of the credit program,
(c) reductions in direct emissions of the refrigerant and potent
greenhouse gas HFC-134a from air conditioning systems, (d) ``upstream''
emission reductions from gasoline extraction, production and
distribution processes as a result of reduced gasoline demand
associated with this rule, and (e) ``upstream'' emission increases from
power plants as electric powertrain vehicles increase in the light duty
fleet as a result of this rule. EPA also accounted for the greenhouse
gas impacts of additional vehicle miles travelled (VMT) due to the
``rebound'' effect discussed in Section III.H.
---------------------------------------------------------------------------

    \640\ U.S. EPA (2012) Inventory of U.S. Greenhouse Gas Emissions
and Sinks: 1990-2010. EPA 430-R-12-001. Available at http://epa.gov/climatechange/emissions/downloads12/US-GHG-Inventory-2012-Main-Text.pdf.
    \641\ Based on the ADAGE reference case used in U.S. EPA (2010).
``EPA Analysis of the American Power Act of 2010'' U.S.
Environmental Protection Agency, Washington, DC, USA (www.epa.gov/climatechange/economics/economicanalyses.html).
---------------------------------------------------------------------------

    EPA has updated a number of analytic inputs for this final rule
analysis, as compared to the proposal. The majority of these changes
have small impacts. Two notable changes are a lower VMT projection,
corresponding to a lower projection in Annual Energy Outlook (AEO) 2012
as compared to the AEO 2011 estimates used in the NPRM, and new
emission factors for electricity, discussed later in this section and
in EPA RIA Chapter 4. No significant comments were received on the
general methods used for calculating greenhouse gas impacts, including
the use of the OMEGA model. All tables in this section contain data
from the analysis with the MY 2008 based future fleet projection. For
the analysis containing the MY 2010 alternate future fleet projection,
please see EPA RIA chapter 10.
    Using this approach EPA estimates the standards will reduce annual
fleetwide car and light truck vehicle GHG emissions by approximately
220 million metric tons (MMT) CO2eq or 17 percent by 2030,
when 85 percent of car and light truck miles will be travelled by
vehicles meeting the MY 2017 or later standards. An additional 60
MMTCO2eq of reduced emissions are attributable to reductions
in gasoline production, distribution and transport. 10
MMTCO2eq of additional emissions will be attributable to
increased electricity production. In total, EPA estimates that compared
to a baseline of indefinite 2016 model year standards, net GHG emission
reductions from the program will be approximately 270
MMTCO2-equivalent (MMTCO2eq) annually by 2030,
which represents a reduction of 4% percent of total U.S. GHG emissions
and 0.5% percent of total worldwide GHG emissions projected in that
year. That year, these GHG emission reductions will result in savings
of approximately 23 billion gallons of petroleum-based gasoline.\642\
---------------------------------------------------------------------------

    \642\ All estimates of fuel savings presented here assume that
manufacturers use air conditioning leakage credits as part of their
compliance strategy. If these credits are not used, then
manufacturers would be meeting the standards via adding more fuel
efficient technologies, and thus the fuel savings of the program
would be larger.
---------------------------------------------------------------------------

    EPA projects the total GHG reductions of the program over the full
life of model year 2017-2025 vehicles to be about 1,960
MMTCO2eq, with fuel savings of 160 billion gallons (3.9
billion barrels) of gasoline over the life of these vehicles.
    Section III.F.1 discusses the emission inventory impacts of this
rulemaking, while III.F.2 discusses the climate change impacts of GHGs.
The impacts of this rule on atmospheric CO2 concentrations,
global mean surface temperature, sea level rise, and ocean pH are
discussed in Section III.F.3.
1. Impact on GHG Emissions
    The modeling of fuel savings and greenhouse gas emissions is
substantially similar to the modeling conducted in the proposal as well
as in the MYs 2012-2016 rulemaking and the MYs 2017-2025 Interim Joint
Technical Assessment Report (TAR). As detailed in EPA RIA chapter 4,
EPA estimated calendar year tailpipe CO2 reductions based on
pre- and post-control CO2 gram per mile levels from EPA's
OMEGA model, coupled with VMT schedules derived from AEO 2012 Early
Release. These estimates reflect the real-world CO2
emissions reductions projected for the entire U.S. vehicle fleet in a
specified calendar year. EPA also estimated full lifetime impacts for
model years 2017-2025 using pre- and post-control CO2 levels
projected by the OMEGA model, coupled with projected vehicle sales and
lifetime mileage estimates. These estimates reflect the real-world GHG
emission reductions projected for model years 2017 through

2025 vehicles over their entire life. Upstream impacts from power plant
emissions came from OMEGA estimates of EV/PHEV penetration into the
fleet as a result of the final GHG rule (approximately 2% in MY 2025).
For both calendar year and model year assessments, EPA estimated the
environmental impact of the advanced technology multiplier, pickup
truck hybrid electric vehicle (HEV) incentive credits, intermediate
volume manufacturer provisions, and air conditioning credits. While the
projected usage of off-cycle credits was quantified, their
environmental impacts are not explicitly estimated, as these credits
are assumed to be inherently environmentally neutral (see Section
III.C). EPA also did not assess the impact of the credit banking carry-
forward programs.
    As in the MYs 2012-2016 rulemaking, this rule allows manufacturers
to earn credits for improvements for controls of both direct and
indirect AC emissions. Since these improvements are relatively low
cost, EPA again projects that manufacturers will utilize these
flexibilities widely, leading to additional reductions from GHG
emissions associated with vehicle air conditioning systems. As
explained above, these reductions will come from both direct emissions
of air conditioning refrigerant over the life of the vehicle and
tailpipe CO2 emissions produced by the increased load of the
A/C system on the engine (so called indirect A/C emissions). In
particular, EPA estimates that direct emissions of the refrigerant HFC-
134a, one of the most potent greenhouse gases, will be fully removed
from light-duty vehicles through the phase-in of alternative
refrigerants. More efficient air conditioning systems will also lead to
fuel savings and additional reductions in upstream emissions from fuel
production and distribution. Our estimated reductions from the A/C
credit program assume that manufacturers will fully utilize the program
(i.e. have 100% refrigerant replacement, and obtain the maximum credit
for control of indirect A/C emissions) by MY 2021.
    Upstream greenhouse gas emission reductions associated with the
production and distribution of fuel were estimated using emission
factors from the Department of Energy's (DOE's) GREET1.8c model, with
modifications as detailed in Chapter 4 of the RIA. These estimates
include both international and domestic emission reductions, since
reductions in foreign exports of finished gasoline and/or crude make up
a significant share of the fuel savings resulting from the GHG
standards. Thus, significant portions of the upstream GHG emission
reductions will occur outside of the U.S.; a breakdown of projected
international versus domestic reductions is included in the EPA RIA.
    Electricity emission factors were derived from EPA's Integrated
Planning Model (IPM). EPA uses IPM to analyze the projected impact of
environmental policies on the electric power sector in the 48
contiguous states and the District of Columbia. IPM is a multi-
regional, dynamic, deterministic linear programming model of the U.S.
electric power sector. It provides forecasts of least-cost capacity
expansion, electricity dispatch, and emission control strategies for
meeting energy demand and environmental, transmission, dispatch, and
reliability constraints. For the proposal, we derived average national
GHG emission factors (EFs) from the IPM version 4.10 base case run for
the ``Proposed Transport Rule.\643\ '' The proposal further discussed
the potential consideration of emission factors other than national
power generation, such as marginal power emission factors, or regional
emission factors.
---------------------------------------------------------------------------

    \643\ EPA. IPM. http://www.epa.gov/airmarkt/progsregs/epa-ipm/BaseCasev410.html. ``Proposed Transport Rule/NODA version'' of IPM .
TR--SB--Limited Trading v.4.10.
---------------------------------------------------------------------------

    EPA received several comments on the use of marginal or incremental
emission factors. These comments are discussed extensively in section
III.C.2.a.vi, but generally favored the use of marginal power as
opposed to national average during the impacts analysis. A national
average EF is based on all power in U.S., including existing hydro-
electric, coal, and nuclear. Some of these power sources may not be
available to electric vehicles, as they are at full capacity with
current demands. For this final rulemaking, EPA updated the electricity
emission factor in several ways. The final rulemaking emission factors
include a newer IPM version that incorporates new EPA stationary source
emissions controls (such as the Mercury and Air Toxics Standards and
the Cross-State Air Pollution Rule) \644\ and reflects recent economic
conditions. EPA also changed from a ``national average'' electricity
GHG emissions factor to one that projects the average electricity GHG
emissions factor for the additional electricity demand represented by
the EVs and PHEVs that EPA projects will be on the road in calendar
year 2030 as a result of this final, and bases the locations of these
vehicles on the distribution of hybrid vehicle sales in 2006-2009. The
cumulative effect of the changes is that IPM projects that about 80
percent of the electricity that will be used by EVs and PHEVs in 2030
will come from natural gas, with 15 percent from coal, and 5 percent
from wind and other feedstocks. Details of this analysis can be found
in EPA RIA chapter 4.7.3
---------------------------------------------------------------------------

    \644\ Citations to rules.
---------------------------------------------------------------------------

a. Calendar Year Reductions for Future Years
    Table III-61 shows reductions estimated from these GHG standards
assuming a reference case of 2016 MY standards continuing indefinitely
beyond 2016, and a post-control case in which 2025 MY GHG standards
continue indefinitely beyond 2025. These reductions are broken down by
upstream and downstream components, including air conditioning
improvements, and also account for the offset from a 10 percent ``VMT
rebound effect'' as discussed in Section III.H.
    For selected years, Table III-61 contains the detailed breakdown of
the sources contributing to the GHG reductions. Table III-62 contains
total GHG impacts and fuel savings for all years.

                  Table III-61--Projected Detailed GHG Impacts From the MY 2017-2025 Standards
                                               [MMTCO2eq per year]
----------------------------------------------------------------------------------------------------------------
                 Calendar year:                        2020            2030            2040            2050
----------------------------------------------------------------------------------------------------------------
Net Delta \*\...................................             -27            -271            -455            -569
Net CO2.........................................             -23            -247            -417            -522
Net other GHG...................................              -4             -25             -38             -47
Downstream......................................             -22            -223            -374            -467
CO2 (excluding A/C).............................             -18            -201            -341            -428
A/C--indirect CO2...............................              -1              -3              -4              -5

A/C--direct HFCs................................              -3             -19             -28             -35
CH4 (VMT rebound effect)........................               0               0               0               0
N2O (VMT rebound effect)........................               0               0               0               0
Gasoline Upstream...............................              -5             -57             -96            -121
CO2.............................................              -5             -50             -84            -105
CH4.............................................              -1              -7             -12             -15
N2O.............................................               0               0               0              -1
Electricity Upstream............................               1               9              15              19
CO2.............................................               1               7              13              16
CH4.............................................               0               1               2               3
N2O.............................................               0               0               0               0
----------------------------------------------------------------------------------------------------------------

                     Table III-62--Projected Annual Impacts from the MY 2017-2025 Standards
----------------------------------------------------------------------------------------------------------------
                                                                                Light duty
                                                                                fuel         Light duty
                                                                    GHG impact      consumption        fuel
                          Calendar year                            (MMT CO2 Eq)       impact        consumption
                                                                                (billion       impact (%)
                                                                                gallons)
----------------------------------------------------------------------------------------------------------------
2017............................................................              -2               0               0
2018............................................................              -8              -1               0
2019............................................................             -16              -1               0
2020............................................................             -27              -2               0
2021............................................................             -43              -3               0
2022............................................................             -63              -5               0
2023............................................................             -85              -7               0
2024............................................................            -111              -9               1
2025............................................................            -140             -12               2
2026............................................................            -167             -14               3
2027............................................................            -195             -16               4
2028............................................................            -221             -19               6
2029............................................................            -247             -21               7
2030............................................................            -271             -23               9
2031............................................................            -295             -25              11
2032............................................................            -317             -27              13
2033............................................................            -338             -29              15
2034............................................................            -358             -30              16
2035............................................................            -377             -32              18
2036............................................................            -394             -34              19
2037............................................................            -411             -35              20
2038............................................................            -427             -36              21
2039............................................................            -441             -38              22
2040............................................................            -455             -39              23
2041............................................................            -468             -40              24
2042............................................................            -480             -41              25
2043............................................................            -492             -42              25
2044............................................................            -504             -43              26
2045............................................................            -515             -44              26
2046............................................................            -526             -45              26
2047............................................................            -537             -46              27
2048............................................................            -548             -47              27
2049............................................................            -558             -48              27
2050............................................................            -569             -49              27
                                                                 -----------------------------------------------
    Total 2017-2050.............................................         -10,605            -903  ..............
----------------------------------------------------------------------------------------------------------------

    The total program emission reductions yield significant emission
decreases relative to worldwide and national total emissions.

    Table III-63--Projected GHG Reductions From the MY 2017-2025 Standards as a Percentage of Total Emissions
                                               [MMTCO2eq per year]
----------------------------------------------------------------------------------------------------------------
                                                       2020            2030            2040            2050
         Emission Reduction Relative to:             (percent)       (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
Worldwide reference.............................            -0.1            -0.4            -0.7            -0.8

U.S. reference (all sectors)....................            -0.4            -3.6            -5.7            -7.0
U.S. reference (cars + light trucks)\*\.........            -2.5           -22.6           -32.5           -35.6
----------------------------------------------------------------------------------------------------------------
\*\ Note that total emission reductions include sectors (such as fuel refineries) that are not part of this
  reference.

b. Lifetime Reductions for 2017-2025 Model Years

    EPA also analyzed the emission reductions over the full life of the
2017-2025 model year cars and light trucks that will be affected by
this program.\645\ These results, including both upstream and
downstream GHG contributions, are presented in Table III-64.
---------------------------------------------------------------------------

    \645\ As detailed in RIA Chapter 4 and TSD Chapter 4, for this
analysis the full life of the vehicle is represented by average
lifetime mileages for cars (196,000 miles [MY 2017] and 206,000
miles [MY 2025]) and trucks (213,000 miles [MY 2017] and 224,000
miles [MY 2025]). These estimates are a function of how far vehicles
are driven per year and scrappage rates.

                          Table III-64--Projected net MY 2017-2025 Lifetime GHG Impacts
                                               [MMTCO2eq per year]
----------------------------------------------------------------------------------------------------------------
                                                                     Upstream
                       MY                           Downstream      (Gasoline)      Electricity     Total CO2e
----------------------------------------------------------------------------------------------------------------
2017............................................             -25              -6               1             -30
2018............................................             -58             -14               2             -70
2019............................................             -89             -21               3            -108
2020............................................            -124             -29               4            -149
2021............................................            -178             -43               5            -216
2022............................................            -222             -55               7            -270
2023............................................            -262             -66               9            -320
2024............................................            -304             -78              11            -371
2025............................................            -347             -90              14            -423
                                                 ---------------------------------------------------------------
    Total.......................................          -1,610            -402              57          -1,956
----------------------------------------------------------------------------------------------------------------

c. Impacts of VMT Rebound Effect
    As noted above and discussed more fully in Section III.H., the
effect of a decrease in fuel cost per mile on vehicle use (i.e., the
VMT rebound effect) was accounted for in our assessment of economic and
environmental impacts of this rule. A 10 percent rebound case was used
for this analysis, meaning that VMT for affected model years is modeled
as increasing by 10 percent as much as the decrease in fuel cost per
mile; i.e., a 10 percent decrease in fuel cost per mile from our
standards would result in a 1 percent increase in VMT. Detailed results
are shown in Table III-65. (This increase is accounted for in the GHG
impacts previously presented in this section). The table below compares
the GHG emissions under two different scenarios: One in which the
control scenario VMT estimate is entirely insensitive to the cost of
travel, and one in which the control scenario is affected by the
rebound effect. RIA Chapter 4.5 includes a sensitivity analysis of GHG
emissions impacts from this rule assuming higher and lower values of
the VMT rebound effect.

                       Table III-65--Delta GHG Increase From a 10% VMT Rebound Effect \a\
                                               [MMTCO2eq per year]
----------------------------------------------------------------------------------------------------------------
                                                                     Upstream       Electricity
                       CY                           Downstream       gasoline          \646\        Total CO2e
----------------------------------------------------------------------------------------------------------------
2020............................................               2               1               0               2
2030............................................              16               4               0              21
2040............................................              26               7               0              34
2050............................................              33               9               1              43
----------------------------------------------------------------------------------------------------------------
\a\ These impacts are included in the reductions shown in Table III-61 through Table III-64.

d. Analysis of Alternatives
    EPA analyzed four alternative standard scenarios for this rule
using the MY 2008 based future fleet projection (Table III-66, Table
III-67, Table III-68). EPA assumed that manufacturers would use air
conditioning improvements in identical penetrations as in the primary
scenario. EPA re-estimated the impact of the electric vehicle
multiplier and the HEV pickup incentives under each alternative. Under
these alternatives, EPA projects that the achieved fleetwide average
emission levels would be 156 g/mile CO2 to 176 g/mile
CO2eq in MY 2025. As in the primary scenario, EPA assumed
that the fleet complied with

the standards. For full details on modeling assumptions, please refer
to RIA Chapter 4.2. EPA's assessment of these alternative standards is
discussed in Section III.D.6.
---------------------------------------------------------------------------

    \646\ This assessment assumes that owners of grid-electric
powered vehicles react similarly to changes in the cost of driving
as owners of conventional gasoline vehicles.

                                                Table III-66--GHG g/mile targets of Alternative Scenarios
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     2021  CO2 g/mile targets                        2025  CO2 g/mile Targets
                          Title                          -----------------------------------------------------------------------------------------------
                                                               Cars           Trucks           Fleet           Cars           Trucks           Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
Primary.................................................             172             249             199             143             203             163
A--Cars +20 g/mile......................................             192             249             212             163             203             176
B--Cars -20 g/mile......................................             152             249             186             123             203             150
C--Trucks +20 g/mile....................................             172             229             206             143             223             170
D--Trucks -20 g/mile....................................             172             269             192             143             183             156
--------------------------------------------------------------------------------------------------------------------------------------------------------

                                              Table III-67--Calendar Year Impacts of Alternative Scenarios
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                GHG delta  (MMT2 CO2eq)                  Fuel savings  (B. Gallons petroleum gasoline)
                    Scenario                     -------------------------------------------------------------------------------------------------------
                                                      2020         2030         2040         2050         2020         2030         2040         2050
--------------------------------------------------------------------------------------------------------------------------------------------------------
Primary.........................................          -27         -271         -455         -569           -2          -23          -39          -49
A--Cars +20 g/mile..............................          -19         -223         -382         -480           -1          -18          -32          -40
B--Cars -20 g/mile..............................          -34         -311         -514         -641           -3          -28          -46          -58
C--Trucks +20 g/mile............................          -27         -249         -420         -526           -2          -21          -36          -45
D--Trucks -20 g/mile............................          -36         -294         -484         -604           -3          -25          -42          -53
--------------------------------------------------------------------------------------------------------------------------------------------------------

                       Table III-68--Model Year Lifetime Impacts of Alternative Scenarios
                                          [Summary of MY 2017-MY 2025]
----------------------------------------------------------------------------------------------------------------
                                                                                Fuel delta      Fuel delta
                                                                    Total CO2e        (b. gal       (b. barrels
                                                                       (MMT)         petroleum       petroleum
                                                                                gasoline)       gasoline)
----------------------------------------------------------------------------------------------------------------
Primary.........................................................          -1,956            -163            -3.9
A--Cars +20 g/mile..............................................          -1,537            -122            -2.9
B--Cars -20 g/mile..............................................          -2,314            -200            -4.8
C--Trucks +20 g/mile............................................          -1,781            -146            -3.5
D--Trucks -20 g/mile............................................          -2,231            -189            -4.5
----------------------------------------------------------------------------------------------------------------

2. Climate Change Impacts From GHG Emissions
    The impact of GHG emissions on the climate has been reviewed in the
NPRM, as well as in the MYs 2012-2016 light-duty rulemaking and the
heavy-duty GHG rulemaking. See 76 FR 75096; 75 FR 25491; 76 FR 57294.
This section briefly discusses again the issue of climate impacts
noting the context of transportation emissions.
    Once emitted, GHGs that are the subject of this regulation can
remain in the atmosphere for decades to millennia, meaning that (1)
their concentrations become well-mixed throughout the global atmosphere
regardless of emission origin, and (2) their effects on climate are
long lasting. GHG emissions come mainly from the combustion of fossil
fuels (coal, oil, and gas), with additional contributions from the
clearing of forests, agricultural activities, cement production, and
some industrial activities. Transportation activities, in aggregate,
were the second largest contributor to total U.S. GHG emissions in 2010
(27 percent of total domestic emissions).\647\
---------------------------------------------------------------------------

    \647\ U.S. EPA (2012) Inventory of U.S. Greenhouse Gas Emissions
and Sinks: 1990-2010. EPA 430-R-12-001. Available at http://epa.gov/climatechange/emissions/downloads12/US-GHG-Inventory-2012-Main-Text.pdf.
---------------------------------------------------------------------------

    The Administrator relied on thorough and peer-reviewed assessments
of climate change science prepared by the Intergovernmental Panel on
Climate Change (``IPCC''), the United States Global Change Research
Program (``USGCRP''), and the National Research Council of the National
Academies (``NRC'') \648\ as the primary scientific and technical basis
for the Endangerment and Cause or Contribute Findings for Greenhouse
Gases Under Section 202(a) of the Clean Air Act (74 FR 66496, December
15, 2009). These assessments comprehensively address the scientific
issues the Administrator had to examine, providing her both data and
information on a wide range of issues pertinent to the Endangerment
Finding. These assessments have been rigorously reviewed by the expert
community, and also by United States government agencies and
scientists, including by EPA itself.
---------------------------------------------------------------------------

    \648\ For a complete list of core references from IPCC, USGCRP/
CCSP, NRC and others relied upon for development of the TSD for
EPA's Endangerment and Cause or Contribute Findings see section
1(b), specifically, Table 1.1 of the TSD. (Docket EPA-HQ-OAR-2010-
0799).
---------------------------------------------------------------------------

    Based on these assessments, the Administrator determined that
greenhouse gases cause warming; that levels of greenhouse gases are
increasing in the atmosphere due to human activity; the climate is
warming; recent warming has been attributed to the increase in
greenhouse gases; and that warming of the climate threatens human
health and welfare. The Administrator further found that emissions of
well-mixed greenhouse gases from new motor vehicles and engines
contribute to the air pollution that endangers

public health and welfare. Specifically, the Administrator found under
section 202(a) of the Act that six greenhouse gases (carbon dioxide,
methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and
sulfur hexafluoride) taken in combination endanger both the public
health and the public welfare of current and future generations, and
further found that the combined emissions of these greenhouse gases
from new motor vehicles and engines contribute to the greenhouse gas
air pollution that endangers public health and welfare. The D.C.
Circuit recently emphatically upheld the reasonableness of all of these
conclusions. See Coalition for Responsible Regulation v. EPA, (No. 09-
1322, (June 26, 2012) (D.C. Circuit)) slip op. p. 30 (upholding all of
EPA's findings and stating ``EPA had before it substantial record
evidence that anthropogenic emissions of greenhouse gases `very likely'
caused warming of the climate over the last several decades. EPA
further had evidence of current and future effects of this warming on
public health and welfare. Relying again upon substantial scientific
evidence, EPA determined that anthropogenically induced climate change
threatens both public health and public welfare. It found that extreme
weather events, changes in air quality, increases in food- and water-
borne pathogens, and increases in temperatures are likely to have
adverse health effects. The record also supports EPA's conclusion that
climate change endangers human welfare by creating risk to food
production and agriculture, forestry, energy, infrastructure,
ecosystems, and wildlife. Substantial evidence further supported EPA's
conclusion that the warming resulting from the greenhouse gas emissions
could be expected to create risks to water resources and in general to
coastal areas as a result of expected increase in sea level.'')
    More recent assessments have reached similar conclusions to those
of the assessments upon which the Administrator relied. In May 2010,
the NRC published its comprehensive assessment, ``Advancing the Science
of Climate Change.'' \649\ It concluded that ``climate change is
occurring, is caused largely by human activities, and poses significant
risks for--and in many cases is already affecting--a broad range of
human and natural systems.'' Furthermore, the NRC stated that this
conclusion is based on findings that are ``consistent with the
conclusions of recent assessments by the U.S. Global Change Research
Program, the Intergovernmental Panel on Climate Change's Fourth
Assessment Report, and other assessments of the state of scientific
knowledge on climate change.'' These are the same assessments that
served as the primary scientific references underlying the
Administrator's Endangerment Finding. Another NRC assessment, ``Climate
Stabilization Targets: Emissions, Concentrations, and Impacts over
Decades to Millennia'', was published in 2011. This report found that
climate change due to carbon dioxide emissions will persist for many
centuries. The report also estimates a number of specific climate
change impacts, finding that every degree Celsius (C) of warming could
lead to increases in the heaviest 15% of daily rainfalls of 3 to 10%,
decreases of 5 to 15% in yields for a number of crops (absent
adaptation measures that do not presently exist), decreases of Arctic
sea ice extent of 25% in September and 15% annually averaged, along
with changes in precipitation and streamflow of 5 to 10% in many
regions and river basins (increases in some regions, decreases in
others). The assessment also found that for an increase of 4 degrees C
nearly all land areas would experience summers warmer than all but 5%
of summers in the 20th century, that for an increase of 1 to 2 degrees
C the area burnt by wildfires in western North America will likely more
than double, that for an increase of 3 degrees C the sea level will
rise 1.6 to 3.3 feet by 2100, and that coral bleaching and erosion will
increase due both to warming and ocean acidification. The assessment
notes that many important aspects of climate change are difficult to
quantify but that the risk of adverse impacts is likely to increase
with increasing temperature, and that the risk of abrupt climate
changes can be expected to increase with the duration and magnitude of
the warming.
---------------------------------------------------------------------------

    \649\ National Research Council (NRC) (2010). Advancing the
Science of Climate Change. National Academy Press. Washington, DC.
(Docket EPA-HQ-OAR-2010-0799).
---------------------------------------------------------------------------

    In the 2010 report cited above, the NRC stated that some of the
largest potential risks associated with future climate change may come
not from relatively smooth changes that are reasonably well understood,
but from extreme events, abrupt changes, and surprises that might occur
when climate or environmental system thresholds are crossed. Examples
cited as warranting more research include the release of large
quantities of GHGs stored in permafrost (frozen soils) across the
Arctic, rapid disintegration of the major ice sheets, irreversible
drying and desertification in the subtropics, changes in ocean
circulation, and the rapid release of destabilized methane hydrates in
the oceans.
    On ocean acidification, the same report noted the potential for
broad, ``catastrophic'' impacts on marine ecosystems. Ocean acidity has
increased 25 percent since pre-industrial times, and is projected to
continue increasing. By the time atmospheric CO2 content
doubles over its preindustrial value, there would be virtually no place
left in the ocean that can sustain coral reef growth. Ocean
acidification could have dramatic consequences for polar food webs
including salmon, the report said.
    Importantly, these recent NRC assessments represent another
independent and critical inquiry of the state of climate change
science, separate and apart from the previous IPCC and USGCRP
assessments.
3. Changes in Global Climate Indicators Associated With This Rule's GHG
Emissions Reductions
    Although ``EPA need not establish a minimum threshold of risk or
harm before determining whether an air pollutant endangers'', and
similarly need not condition regulation under section 202(a) ``on
evidence of a particular level of mitigation''. see Coalition for
Responsible Regulation v. EPA No. 09-1322, June 26, 2012 (D.C. Circuit)
slip op. pp. 33, 43, EPA examined \650\ the reductions in
CO2 and other GHGs associated with this rulemaking and
analyzed the projected effects on atmospheric CO2
concentrations, global mean surface temperature, sea level rise, and
ocean pH which are common variables used as indicators of climate
change. The analysis projects that the final rule will reduce
atmospheric concentrations of CO2, global climate warming,
ocean acidification, and sea level rise relative to the reference case.
Although the projected reductions and improvements are small in
comparison to the total projected climate change, they are
quantifiable, directionally consistent, and will contribute to reducing
the risks associated with climate change. Climate change is a global
phenomenon and EPA recognizes that this one national action alone will
not prevent it: EPA

notes this would be true for any given GHG mitigation action when taken
alone or when considered in isolation. See Coalition for Responsible
Regulation v. EPA, No. 09-1322, June 26, 2012 (D.C. Circuit)) slip op.
p 43 noting that the GHG emission reductions of the MYs 2012-2016 rule
``result in meaningful mitigation of greenhouse gas emissions''; the
projected emissions reductions of this MYs 2017-2025 rule are projected
to be approximately double those of the MYs 2012-2016 rule so that this
rule obviously results in ``meaningful mitigation of greenhouse gas
emissions'' as well. EPA also repeats that a substantial portion of
CO2 emitted into the atmosphere is not removed by natural
processes for millennia, and therefore each unit of CO2 not
emitted into the atmosphere due to this rule avoids essentially
permanent climate change on centennial time scales.
---------------------------------------------------------------------------

    \650\ Using the Model for the Assessment of Greenhouse Gas
Induced Climate Change (MAGICC) 5.3v2, http://www.cgd.ucar.edu/cas/wigley/magicc/), EPA estimated the effects of this rulemaking's
greenhouse gas emissions reductions on global mean temperature and
sea level. EPA applied the CO2SYS program to estimate the effects of
this rulemaking's greenhouse gas emissions reductions on ocean
acidification. Please refer to Chapter 6.4 of the RIA for additional
information.
---------------------------------------------------------------------------

    EPA determines that the projected reductions in atmospheric
CO2, global mean temperature, sea level rise, and ocean
acidification are meaningful in the context of this action. The results
of the analysis demonstrate that relative to the reference case, by
2100 projected atmospheric CO2 concentrations are estimated
to be reduced by 3.21 to 3.58 part per million by volume (ppmv), global
mean temperature is estimated to be reduced by 0.0074 to 0.0176[deg]C,
and sea-level rise is projected to be reduced by approximately 0.071-
0.159 cm, based on a range of climate sensitivities (described below).
The analysis also demonstrates that ocean pH will increase by 0.0017 pH
units by 2100 relative to the reference case (ie, reduced
acidification).
a. Estimated Reductions in Atmospheric CO2 Concentration,
Global Mean Surface Temperatures, Sea Level Rise, and Ocean pH
    As in the NPRM, EPA estimated changes in the atmospheric
CO2 concentration, global mean temperature, and sea level
rise out to 2100 resulting from the emissions reductions in this
rulemaking using the Global Change Assessment Model (GCAM, formerly
MiniCAM) \651\ coupled with the Model for the Assessment of Greenhouse
Gas Induced Climate Change (MAGICC, version 5.3v2).\652\ GCAM was used
to create the globally and temporally consistent set of climate
relevant variables required for running MAGICC. MAGICC was then used to
estimate the projected change in these variables over time. Given the
magnitude of the estimated emissions reductions associated with this
action, a simple climate model such as MAGICC is reasonable for
estimating the atmospheric and climate response. This widely-used, peer
reviewed modeling tool was also used to project temperature and sea
level rise under different emissions scenarios in the Third and Fourth
Assessments of the IPCC.
---------------------------------------------------------------------------

    \651\ GCAM is a long-term, global integrated assessment model of
energy, economy, agriculture and land use, that considers the
sources of emissions of a suite of GHG's, emitted in 14 globally
disaggregated regions, the fate of emissions to the atmosphere, and
the consequences of changing concentrations of greenhouse related
gases for climate change. GCAM begins with a representation of
demographic and economic developments in each region and combines
these with assumptions about technology development to describe an
internally consistent representation of energy, agriculture, land-
use, and economic developments that in turn shape global emissions.
Brenkert A, S. Smith, S. Kim, and H. Pitcher, 2003: Model
Documentation for the MiniCAM. PNNL-14337, Pacific Northwest
National Laboratory, Richland, Washington. (Docket EPA-HQ-OAR-2010-
0799)
    \652\ Wigley, T.M.L. 2008. MAGICC 5.3.v2 User Manual. UCAR--
Climate and Global Dynamics Division, Boulder, Colorado. http://www.cgd.ucar.edu/cas/wigley/magicc/ (Docket EPA-HQ-OAR-2010-0799)
---------------------------------------------------------------------------

    The integrated impact of the following non-GHG and GHG emissions
changes are considered: CO2, CH4, N2O,
HFC-134a, NOX, CO, SO2, and volatile organic
compounds (VOC). For these pollutants an annual time-series of
(upstream + downstream) emissions reductions estimated from the
rulemaking were applied as net reductions to a global reference case
(or baseline) emissions scenario in GCAM to generate an emissions
scenario specific to this rule.\653\ The emissions reductions past
calendar year 2050 for all gases were scaled with total U.S. road
transportation fuel consumption from the GCAM reference scenario. Road
transport fuel consumption past 2050 does not change significantly and
thus emissions reductions remain relatively constant from 2050 through
2100. Specific details about the GCAM reference case scenario can be
found in Chapter 6.4 of the RIA that accompanies this final rule.
---------------------------------------------------------------------------

    \653\ Due to timing constraints, this analysis was conducted
with preliminary estimates of the emissions reductions projected
from the final rule, which were highly similar to the final
estimates presented in Chapter 4 of the RIA. For example, the final
projected CO2 emissions reductions for most years in the
2017-2050 time period were roughly one-tenth of a percent smaller
than the preliminary estimates. The preliminary emissions reduction
projections are available in the docket (see ``Emissions for MAGICC
modeling'' in Docket EPA-HQ-OAR-2010-0799), and the files used as
inputs for the MAGICC model are also available (see ``MAGICC Input
File (policy)'' and ``MAGICC Input File (reference)'').
---------------------------------------------------------------------------

    MAGICC calculates the forcing response at the global scale from
changes in atmospheric concentrations of CO2,
CH4, N2O, HFCs, and tropospheric ozone
(O3). It also includes the effects of temperature changes on
stratospheric ozone and the effects of CH4 emissions on
stratospheric water vapor. Changes in CH4, NOX,
VOC, and CO emissions affect both O3 concentrations and
CH4 concentrations. MAGICC includes the relative climate
forcing effects of changes in sulfate concentrations due to changing
SO2 emissions, including both the direct effect of sulfate
particles and the indirect effects related to cloud interactions.
However, MAGICC does not calculate the effect of changes in
concentrations of other aerosols such as nitrates, black carbon, or
organic carbon, making the assumption that the sulfate cooling effect
is a proxy for the sum of all the aerosol effects. Therefore, the
climate effects of changes in PM2.5 emissions and precursors
(besides SO2) that are presented in the RIA Chapter 6 were
not included in the calculations. MAGICC also calculates all climate
effects at the global scale. This global scale captures the climate
effects of the long-lived, well-mixed greenhouse gases, but does not
address the fact that short-lived climate forcers such as aerosols and
ozone can have effects that vary with location and timing of emissions.
Black carbon in particular is known to cause a positive forcing or
warming effect by absorbing incoming solar radiation, but there are
uncertainties about the magnitude of that warming effect and the
interaction of black carbon (and other co-emitted aerosol species) with
clouds. See 77 FR 38890, 38991-993 (June 29, 2012). While black carbon
is likely to be an important contributor to climate change, it would be
premature to include quantification of black carbon climate impacts in
an analysis of these final standards. See generally, EPA, Response to
Comments to the Endangerment Finding Vol. 9 section <IP_ADDRESS> \654\ and
the discussion of black carbon in the endangerment finding at 74 FR
66520 as well as EPA's discussion in the recent proposal to revise the
PM NAAQS (77 FR 38991-993). Additionally, the magnitude of
PM2.5 emissions changes (and therefore, black carbon
emission changes) related to these final standards are small in
comparison to the changes in the pollutants which have been included in
the MAGICC model simulations.
---------------------------------------------------------------------------

    \654\ See http://epa.gov/climatechange/endangerment/comments/volume9.html#1-6-1 (last accessed August 10, 2012) or Docket EPA-HQ-
OAR-2009-0171-11676.

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

    The International Council on Clean Transportation (ICCT) and the
Manufacturers of Emissions Control Association (MECA) mentioned the
benefits of black carbon reductions. Since the proposed rule, EPA has
recently released a Report to Congress addressing black carbon.\655\
EPA continues to recognize that black carbon is an important climate
forcing agent and takes very seriously the emerging science on black
carbon's contribution to global climate change in general and the high
rates of observed climate change in the Arctic in particular. MECA also
mentioned the effects of NOX on climate. As discussed above,
changes in NOX emissions are included as an input into the
MAGICC model. However, the effects due to NOX changes alone
have not been isolated, and because NOX emissions lead to
decreased levels of methane in addition to increased levels of ozone,
the net effect on climate of changes in NOX emissions is
unclear.
---------------------------------------------------------------------------

    \655\ See EPA, March 2012. Report to Congress on Black Carbon
(EPA-450/R-12-001) available at http://epa.gov/blackcarbon/ (last
accessed August 10, 2012).
---------------------------------------------------------------------------

    Changes in atmospheric CO2 concentration, global mean
temperature, and sea level rise for both the reference case and the
emissions scenarios associated with this action were computed using
MAGICC. To calculate the reductions in the atmospheric CO2
concentrations as well as in temperature and sea level resulting from
this final rule, the output from the policy scenario associated with
EPA's final standards was subtracted from an existing Global Change
Assessment Model (GCAM, formerly MiniCAM) reference emission scenario.
To capture some key uncertainties in the climate system with the MAGICC
model, changes in atmospheric CO2, global mean temperature
and sea level rise were projected across the most current IPCC range of
climate sensitivities, from 1.5 [deg]C to 6.0 [deg]C.\656\ This range
reflects the uncertainty for equilibrium climate sensitivity for how
much global mean temperature would rise if the concentration of carbon
dioxide in the atmosphere were to double. The information for this
range come from constraints from past climate change on various time
scales, and the spread of results for climate sensitivity from
ensembles of models.\657\ Details about this modeling analysis can be
found in the RIA Chapter 6.4.
---------------------------------------------------------------------------

    \656\ In IPCC reports, equilibrium climate sensitivity refers to
the equilibrium change in the annual mean global surface temperature
following a doubling of the atmospheric equivalent carbon dioxide
concentration. The IPCC states that climate sensitivity is
``likely'' to be in the range of 2 [deg]C to 4.5 [deg]C, ``very
unlikely'' to be less than 1.5 [deg]C, and ``values substantially
higher than 4.5 [deg]C cannot be excluded.'' IPCC WGI, 2007, Climate
Change 2007--The Physical Science Basis, Contribution of Working
Group I to the Fourth Assessment Report of the IPCC, http://www.ipcc.ch/ (Docket EPA-HQ-OAR-2010-0799).
    \657\ Meehl, G.A. et al. (2007) Global Climate Projections. In:
Climate Change 2007: The Physical Science Basis. Contribution of
Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M.
Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller
(eds.)]. Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA. (Docket EPA-HQ-OAR-2010-0799).
---------------------------------------------------------------------------

    The Institute for Energy Research (IER) argued that the climate
sensitivity is likely to be below or in the low end of the range used
by the EPA. However, this assertion was based on only two recent
studies, while other recent studies have come to different conclusions.
The EPA has relied on assessments like those of the National Academies,
U.S. Global Change Research Program, and IPCC because assessments cover
the full range of the literature and place the individual studies in
context. In addition, one of the two specific studies relied on by IER
to assert that EPA overestimated the climate sensitivity provided
estimates of transient climate sensitivity. Transient sensitivity is a
measure of the temperature change precisely at the time of doubling of
CO2 concentrations, before the climate system has come to
equilibrium. The transient sensitivity is usually about half of the
equilibrium sensitivity. Therefore, it would be premature to conclude
that the range used by the EPA either under or overestimates the likely
equilibrium climate sensitivity.
    The results of this modeling, summarized in Table III-69, show
quantified reductions in atmospheric CO2 concentrations,
projected global mean temperature and sea level resulting from this
action, across all climate sensitivities. As a result of the emission
reductions from the final standards, relative to the reference case the
atmospheric CO2 concentration is projected by 2100 to be
reduced by 3.21-3.58 ppmv, the global mean temperature is projected to
be reduced by approximately 0.0074-0.0176 [deg]C by 2100, and global
mean sea level rise is projected to be reduced by approximately 0.071-
0.159 cm by 2100. The range of reductions in global mean temperature
and sea level rise is larger than that for CO2
concentrations because CO2 concentrations are only weakly
coupled to climate sensitivity through the dependence on temperature of
the rate of ocean absorption of CO2, whereas the magnitude
of temperature change response to CO2 changes (and therefore
sea level rise) is more tightly coupled to climate sensitivity in the
MAGICC model.

  Table III-69--Impact of GHG Emissions Reductions on Projected Changes in Global Climate Associated With EPA's
                                      Final GHG Standards for MYs 2017-2025
                          [Based on a range of climate sensitivities from 1.5-6 [deg]C]
----------------------------------------------------------------------------------------------------------------
                  Variable                               Units                   Year         Projected change
----------------------------------------------------------------------------------------------------------------
Atmospheric CO2 Concentration..............  ppmv.........................            2100        -3.21 to -3.58
Global Mean Surface Temperature............  [deg]C.......................            2100    -0.0074 to -0.0176
Sea Level Rise.............................  cm...........................            2100      -0.071 to -0.159
Ocean pH...................................  pH units.....................            2100           +0.0017 \a\
----------------------------------------------------------------------------------------------------------------
\a\ The value for projected change in ocean pH is based on a climate sensitivity of 3.0.

    The projected reductions are small relative to the change in
temperature (1.8-4.8 [deg]C), sea level rise (23-55 cm), and ocean
acidity (-0.30 pH units) from 1990 to 2100 from the MAGICC simulations
for the GCAM reference case. However, this is to be expected given the
magnitude of emissions reductions expected from the program in the
context of global emissions. This uncertainty range does not include
the effects of uncertainty in future emissions. It should also be noted
that the calculations in MAGICC do not include the possible effects of

accelerated ice flow in Greenland and/or Antarctica: the recent NRC
report estimated a likely sea level increase for a business-as-usual
scenario of 0.5 to 1.0 meters.\658\ Further discussion of EPA's
modeling analysis is found in the RIA, Chapter 6.
---------------------------------------------------------------------------

    \658\ National Research Council (NRC), 2011. Climate
Stabilization Targets: Emissions, Concentrations, and Impacts over
Decades to Millennia. Washington, DC: National Academies Press.
(Docket EPA-HQ-OAR-2010-0799)
---------------------------------------------------------------------------

    IER and a number of private citizens asserted that the reductions
in temperature and other climate factors are too small to be
meaningful. However, as has been stated, no one rule will prevent
climate change by itself. As stated in the Endangerment and Cause or
Contribute Findings for Greenhouse Gases Under Section 202(a) of the
Clean Air Act; final rule (74 FR at 66543), ``The commenters' approach,
if used globally, would effectively lead to a tragedy of the commons,
whereby no country or source category would be accountable for
contributing to the global problem of climate change, and nobody would
take action as the problem persists and worsens.'' \659\ While this
rule does not single-handedly eliminate climate change, it is an
important contribution to reducing the rate of change, and this
reduction in rate is global and long-lived. EPA appropriately placed
the benefits of reductions in context in the rule, by calculating the
likely reductions in temperature and comparing them to total projected
changes in temperature over the same time period. In addition, EPA used
the social cost of carbon methodology in order to estimate a
monetization of the benefits of these reductions (see section III.H.6),
and the net present value resulting from the CO2 reductions
due to this rule (between years 2017 and 2050) was calculated to be
between tens to hundreds of billions of dollars. As noted above, the
D.C. Circuit pointedly rejected the argument that EPA should refrain
from issuing GHG standards under section 202(a) due to claimed lack of
mitigating effect on the endangerment, and further held that ``the
emission standards would result in meaningful mitigation of greenhouse
gas emissions'' in the form of ``960 million metric tons of
CO2e over the lifetime of the model year 2012-2016
vehicles''. Coalition for Responsible Regulation v. EPA, No. 09-1322,
(June 26, 2012) (D.C. Circuit)) slip op. p 43; projected emissions
reductions of this MYs 2017-2025 rule are projected to be approximately
double those of the MYs 2012-2016 rule and thus, in the D.C. Circuit's
language, ``result in meaningful mitigation of greenhouse gas
emissions.''
---------------------------------------------------------------------------

    \659\ The Supreme Court likewise spoke to this issue, stating
that ``[a]gencies, like legislatures, do not generally resolve
massive problems'' like climate change ``in one fell regulatory
swoop.'' Massachusetts v. EPA, 549 U.S. at 524. They ``whittle away
at them over time.'' Id. The Supreme Court additionally emphasized
that ``reducing domestic automobile [greenhouse gas] emissions is
hardly a tentative step'' toward addressing climate change, inasmuch
as ``the United States transportation sector emits an enormous
quantity of carbon dioxide into the atmosphere.'' Id. Thus,
``[j]udged by any standard, U.S. motor-vehicle emissions make a
meaningful contribution to greenhouse gas concentrations.'' Id. at
525.
---------------------------------------------------------------------------

    The National Wildlife Federation (NWF), Union of Concerned
Scientists, American Medical Association of California, Ceres,
Environmental Defense Fund, and several private citizens also discussed
the importance of these standards in terms of mitigating climate risks,
noting impacts to heat, ozone, extreme events, wildfires, floods,
agriculture, coastal regions, droughts, and vulnerable populations. The
EPA agrees that the reductions enacted in this rule are an important
step towards reducing climate risks over the coming decades and
centuries.
    A summary of comments on climate change impacts from GHG emissions
and other climate-forcing agents as well as changes in global
indicators associated with GHG emissions reductions from this rule is
available in sections 16.2 and 16.3 of EPA's Response to Comments
document. These sections also contain EPA's more detailed responses to
these comments.
    EPA used the computer program CO2SYS,\660\ version 1.05, to
estimate projected changes in ocean pH for tropical waters based on the
atmospheric CO2 concentration change (reduction) resulting
from this final rule.\661\ The program performs calculations relating
parameters of the CO2 system in seawater. EPA used the
program to calculate ocean pH as a function of atmospheric
CO2 concentrations, among other specified input conditions.
Based on the projected atmospheric CO2 concentration
reductions resulting from this final rule, the program calculates an
increase in ocean pH of 0.0017 pH units in 2100 relative to the
reference case (compared to a decrease of 0.3 pH units from 1990 to
2100 in the reference case). Thus, this analysis indicates the
projected decrease in atmospheric CO2 concentrations from
EPA's final standards will result in an increase in ocean pH. For
additional validation, results were generated using different known
constants from the literature. A comprehensive discussion of the
modeling analysis associated with ocean pH is provided in the RIA,
Chapter 6.
---------------------------------------------------------------------------

    \660\ Lewis, E., and D.W.R. Wallace. 1998. Program Developed for
CO2 System Calculations. ORNL/CDIAC-105. Carbon Dioxide
Information Analysis Center, Oak Ridge National Laboratory, U.S.
Department of Energy, Oak Ridge, Tennessee. (Docket EPA-HQ-OAR-2010-
0799)
    \661\ Due to timing constraints, this analysis was conducted
with preliminary estimates of the CO2 emissions
reductions projected from the final rule, which were highly similar
to the final estimates presented in Chapter 4 of this RIA. The final
projected CO2 emissions reductions for most years in the
2017-2050 time period were roughly one-tenth of a percent smaller
than the preliminary estimates. The preliminary CO2
emissions reduction projections are available in the docket (see
``Emissions for MAGICC modeling'' in Docket EPA-HQ-OAR-2010-0799).
---------------------------------------------------------------------------

    As discussed in III.F.2, the 2011 NRC assessment on ``Climate
Stabilization Targets: Emissions, Concentrations, and Impacts over
Decades to Millennia'' determined how a number of climate impacts--such
as heaviest daily rainfalls, crop yields, and Arctic sea ice extent--
would change with a temperature change of 1 degree Celsius (C) of
warming. These relationships of impacts with temperature change could
be combined with the calculated reductions in warming in Table II-63 to
estimate changes in these impacts associated with this rulemaking.
b. Program's Effect on Climate
    As a substantial portion of CO2 emitted into the
atmosphere is not removed by natural processes for millennia, each unit
of CO2 not emitted into the atmosphere avoids some degree of
permanent climate change. Therefore, reductions in emissions in the
near-term are important in determining climate impacts experienced not
just over the next decades but over thousands of years.\662\ Though the
magnitude, in isolation, of the avoided climate change projected here
is small in comparison to the total projected changes, these reductions
represent a reduction in the adverse risks associated with climate
change (though these risks were not formally estimated for this action)
across a range of equilibrium climate sensitivities.
---------------------------------------------------------------------------

    \662\ National Research Council (NRC) (2011). Climate
Stabilization Targets: Emissions, Concentrations, and Impacts over
Decades to Millennia. National Academy Press. Washington, DC.
(Docket EPA-HQ-OAR-2010-0799)
---------------------------------------------------------------------------

    EPA's analysis of this rule's impact on global climate conditions
is intended to quantify these potential reductions using the best
available science. EPA's modeling results show repeatable, consistent
reductions relative to the reference case in changes of CO2
concentration, temperature, sea-level rise, and ocean pH over the next
century.

G. How will the rule impact non-GHG emissions and their associated
effects?

    Although this rule focuses on GHGs, it will also have an impact on
the emissions of non-GHG pollutants. Section III.G.1 of this preamble
details the criteria pollutant and air toxic inventory impacts of this
rule. The subsequent sections, III.G.2 and III.G.3, discuss the health
and environmental effects associated with the criteria and toxic air
pollutants that are being impacted by this rule. In Section III.G.4, we
discuss the potential impact of this rule on concentrations of criteria
and air toxic pollutants in the ambient air. The tools and
methodologies used in this analysis are substantially similar to those
used in the proposal and in the MYs 2012-2016 light duty rulemaking.
1. Inventory
a. Impacts
    In addition to reducing the emissions of greenhouse gases, this
rule will influence ``non-GHG'' pollutants, i.e., ``criteria'' air
pollutants and their precursors, and air toxics. The rule will affect
emissions of carbon monoxide (CO), fine particulate matter
(PM2.5), sulfur dioxide (SOX), volatile organic
compounds (VOC), nitrogen oxides (NOX), benzene, 1,3-
butadiene, formaldehyde, acetaldehyde, and acrolein. Our estimates of
these non-GHG emission impacts from the GHG program are shown by
pollutant in Table III-70 and Table III-71 both in total and broken
down by the three drivers of these changes: (a) ``Downstream'' emission
changes, reflecting the estimated effects of VMT rebound (discussed in
Sections III.F and III.H) and decreased consumption of fuel; (b)
``upstream'' emission reductions due to decreased extraction,
production and distribution of motor vehicle gasoline; (c) ``upstream''
emission increases from power plants as electric powertrain vehicles
increase in the light duty fleet as a result of this rule. The GHG
rule's impacts on criteria and toxics emissions are discussed below,
followed by individual discussions of the methodology used to calculate
each of these three sources of impacts.
    As shown in Table III-70, EPA estimates that the light duty vehicle
program will result in reductions of NOX, VOC,
PM2.5 and SOX, but will increase CO emissions.
For NOx, VOC, and PM2.5, we estimate net
reductions because the net emissions reductions from reduced fuel
refining, distribution and transport is larger than the emission
increases due to increased VMT and increased electricity production. In
the case of CO, we estimate slight emission increases, because there
are relatively small reductions in upstream emissions, and thus the
projected emission increases due to VMT rebound and electricity
production are greater than the projected emission decreases due to
reduced fuel production. For SOX, downstream emissions are
roughly proportional to fuel consumption, therefore a decrease is seen
in both downstream and fuel refining sources.
    We received several comments on the methods used to quantify
emissions from advanced technology vehicles. Growth Energy commented
that ``There is substantial evidence that GDI increases PM mass and PM
number emissions compared to the conventional port fuel injection (PFI)
technology now in widespread use * * *. Therefore, the final rule
should evaluate and consider both the increased PM due to GDI use and
the potential for more widespread ethanol use to decrease PM mass and
number emissions.'' The Clean Fuels Development Coalition submitted
similar comments. EPA agrees with the commenter that testing on initial
GDI technology, primarily wall-guided systems, has shown an increase in
PM emissions over the FTP as compared to conventional PFI gasoline
engines. However, the technology is still evolving, making it difficult
to predict future PM emission performance of GDI vehicles. Testing on
initial spray-guided GDI systems has shown less of a PM increase over
the FTP, and even reduced PM emissions over the USO6 compared to PFI
vehicles.\663\ Due to the improved fuel economy and reduced emissions
offered by spray-guided GDI technology, it is anticipated that spray-
guided GDI will replace wall-guided systems in the 2017 to 2025
timeframe.\664\ As a result, in the technical assessment conducted by
the agencies as part of this rulemaking, the agencies assessed the
emissions and fuel consumption improvements associated with spray-
guided GDI systems and assumed that their overall in-use PM emission
performance was comparable to that of PFI vehicles.
---------------------------------------------------------------------------

    \663\ ``Test Program to evaluate PM emissions from GDI
vehicles,'' Memo from Michael Olechiw to EPA docket EPA-HQ-OAR-2010-
0799
    \664\ The technology modeling for this rule includes a spray
guided GDI system. See Joint TSD Section 3.3
---------------------------------------------------------------------------

    For all criteria pollutants the overall impact of the program will
be small compared to total U.S. inventories across all sectors. In
2030, EPA estimates that the program will reduce total NOX,
PM2.5, VOC and SOX inventories by 0.1 to 1.0
percent, while increasing the total national CO inventory by 0.4
percent.
    As shown in Table III-71, EPA estimates that the program will
result in similarly small changes for air toxic emissions compared to
total U.S. inventories across all sectors. In 2030, EPA estimates the
program will increase total 1,3-butadiene and acetaldehyde emissions by
0.1 to 0.2 percent. Total acrolein, benzene and formaldehyde emissions
will decrease by similarly small amounts.

                            Table III-70--Annual Criteria Emission Impacts of Program
                                                  [Short tons]
----------------------------------------------------------------------------------------------------------------
                                                              CY 2020                         CY 2030
                                                 ---------------------------------------------------------------
                                    Pollutant         Impacts       % of total        Impacts       % of total
                                                   (short tons)   U.S. inventory   (short tons)   U.S. inventory
----------------------------------------------------------------------------------------------------------------
Total.........................  VOC.............         -11,712            -0.1        -123,070            -1.0
                                CO..............          14,164             0.0         224,875             0.4
                                NOX.............            -904             0.0          -6,509            -0.1
                                PM2.5...........            -136             0.0          -1,254             0.0
                                SOX.............          -1,270             0.0         -13,377            -0.2
Downstream....................  VOC.............             249             0.0           4,835             0.0
                                CO..............          14,414             0.0         227,250             0.4
                                NOX.............             498             0.0           8,281             0.1
                                PM2.5...........              40             0.0             568             0.0

                                SOX.............            -420             0.0          -4,498            -0.1
Fuel Production and             VOC.............         -12,043            -0.1        -128,823            -1.0
 Distribution.
                                CO..............            -749             0.0          -8,009             0.0
                                NOX.............          -1,757             0.0         -18,795            -0.2
                                PM2.5...........            -280             0.0          -3,000            -0.1
                                SOX.............          -1,198             0.0         -12,813            -0.2
Electricity...................  VOC.............              81             0.0             917             0.0
                                CO..............             499             0.0           5,634             0.0
                                NOX.............             355             0.0           4,005             0.0
                                PM2.5...........             104             0.0           1,179             0.0
                                SOX.............             348             0.0           3,933             0.0
----------------------------------------------------------------------------------------------------------------

                           Table III-71--Annual Air Toxic Emission Impacts of Program
                                                  [Short tons]
----------------------------------------------------------------------------------------------------------------
                                                              CY 2020                         CY 2030
                                                 ---------------------------------------------------------------
                                    Pollutant         Impacts       % of total        Impacts       % of total
                                                   (short tons)   U.S. inventory   (short tons)   U.S. inventory
----------------------------------------------------------------------------------------------------------------
Total.........................  1,3-Butadiene...               1             0.0              25             0.2
                                Acetaldehyde....               3             0.0              57             0.1
                                Acrolein........               0             0.0               2             0.0
                                Benzene.........             -16             0.0            -101             0.0
                                Formaldehyde....              -7             0.0             -43             0.0
Downstream....................  1,3-Butadiene...               1             0.0              28             0.2
                                Acetaldehyde....               4             0.0              70             0.1
                                Acrolein........               0             0.0               3             0.0
                                Benzene.........               8             0.0             160             0.1
                                Formaldehyde....               3             0.0              66             0.0
Fuel Production and             1,3-Butadiene...               0             0.0              -2             0.0
 Distribution.
                                Acetaldehyde....              -1             0.0             -14             0.0
                                Acrolein........               0             0.0              -2             0.0
                                Benzene.........             -24             0.0            -261            -0.1
                                Formaldehyde....             -10             0.0            -110            -0.1
Electricity...................  1,3-Butadiene...               0             0.0               0             0.0
                                Acetaldehyde....               0             0.0               1             0.0
                                Acrolein........               0             0.0               1             0.0
                                Benzene.........               0             0.0               0             0.0
                                Formaldehyde....               0             0.0               1             0.0
----------------------------------------------------------------------------------------------------------------

b. Methodology
    As in the MYs 2012-2016 rulemaking and in the proposal, for the
downstream analysis, the current version of the EPA motor vehicle
emission simulator (MOVES2010a) was used to estimate VOC, CO,
NOX, PM and air toxics emission rates. Additional emissions
from light duty cars and trucks attributable to the rebound effect were
then calculated using the OMEGA model post-processor. A more complete
discussion of the inputs, methodology, and results is contained in RIA
Chapter 4.
    This rule assumes that MY 2017 and later vehicles are compliant
with the agency's Tier 2 emission standards. This rule does not model
any future Tier 3 emission standards, because these standards have not
yet been proposed (see Section III.A).
    As in the MYs 2012-2016 GHG rulemaking, for this analysis we
attribute decreased fuel consumption from this program to petroleum-
based fuels only, while assuming no effect on volumes of ethanol and
other renewable fuels because they are mandated under the Renewable
Fuel Standard (RFS2). For the purposes of this emission analysis, we
assume that all gasoline in the timeframe of the analysis is blended
with 10 percent ethanol (E10). However, as a consequence of the fixed
volume of renewable fuels mandated in the RFS2 rulemaking and the
decreasing petroleum consumption predicted here, we anticipate that
this rulemaking would in fact increase the fraction of the U.S. fuel
supply that is made up by renewable fuels. The impacts of this increase
are difficult to project at the present time. Since it is not centrally
relevant to the analysis for this rulemaking, we have not included
renewable fuel volumes in this analysis beyond the assumption that all
gasoline is E10.
    In this rulemaking EPA modeled the three impacts on criteria
pollutant emissions (VMT rebound driving, changes in fuel production,
and changes in electricity production) discussed above.
    While electric vehicles have zero tailpipe emissions, EPA assumes
that manufacturers will plan for these vehicles in their regulatory
compliance strategy for non-GHG emissions standards, and will not over-
comply with those standards. Since the Tier 2 emissions standards are
fleet-average

standards, we assume that if a manufacturer introduces EVs into its
fleet, that it would correspondingly compensate through changes to
vehicles elsewhere in its fleet, rather than meet an overall lower
fleet-average emissions level.\665\ Consequently, EPA assumes neither
tailpipe pollutant benefit (other than CO2) nor an
evaporative emission benefit from the introduction of electric vehicles
into the fleet. Other factors which may impact downstream non-GHG
emissions, but which are not estimated in the final rulemaking
inventory analysis, include: the potential for decreased criteria
pollutant emissions due to increased air conditioner efficiency;
reduced refueling emissions due to less frequent refueling events and
reduced annual refueling volumes resulting from the GHG standards; and
increased hot soak evaporative emissions due to the likely increase in
number of trips associated with VMT rebound modeled in this rule. In
all, these additional analyses would likely result only in small
changes relative to the national inventory.
---------------------------------------------------------------------------

    \665\ Historically, manufacturers have reduced precious metal
loading in catalysts in order to reduce costs. See http://www.platinum.matthey.com/media-room/our-view-on-.-.-./thrifting-of-precious-metals-in-autocatalysts/ Accessed 11/08/2011.
Alternatively, manufacturers could also modify vehicle calibration.
---------------------------------------------------------------------------

    To determine the upstream fuel production impacts, EPA estimated
the impact of reduced petroleum volumes on the extraction and
transportation of crude oil as well as the production and distribution
of finished gasoline. For the purpose of assessing domestic-only
emission reductions it was necessary to estimate the fraction of fuel
savings attributable to domestic finished gasoline, and of this
gasoline what fraction is produced from domestic crude. For this
analysis EPA estimated that 50 percent of fuel savings is attributable
to domestic finished gasoline and that 90 percent of this gasoline
originated from imported crude. Emission factors for most upstream
emission sources are based on the GREET1.8 model, developed by DOE's
Argonne National Laboratory,\666\ but in some cases the GREET values
were modified or updated by EPA to be consistent with the National
Emission Inventory (NEI) or other relevant data.\667\ EPA made several
additional updates between proposal and final rulemaking to the non-GHG
emission rates as discussed in chapter 4 of the RIA. The primary
updates for this analysis were to incorporate newer information on
gasoline distribution emissions for VOC from the NEI, which were
significantly higher than GREET estimates; newer information on on-site
refinery emissions from the NEI, which were significantly lower than
GREET estimates; new mobile source emission factors; and the
incorporation of upstream emission factors for the air toxics estimated
in this analysis: benzene, 1,3-butadiene, acetaldehyde, acrolein, and
formaldehyde. The development of these emission factors is detailed in
a memo to the docket and in RIA Chapter 4. These emission factors were
incorporated into the OMEGA post-processor.
---------------------------------------------------------------------------

    \666\ Greenhouse Gas, Regulated Emissions, and Energy Use in
Transportation model (GREET), U.S. Department of Energy, Argonne
National Laboratory, http://www.transportation.anl.gov/modeling_simulation/GREET/.
    \667\ U.S. EPA. 2002 National Emissions Inventory (NEI) Data and
Documentation, http://www.epa.gov/ttn/chief/net/2002inventory.html.
---------------------------------------------------------------------------

    As with the GHG emission analysis discussed in section III.F,
electricity emission factors were derived from EPA's Integrated
Planning Model (IPM). EPA uses IPM to analyze the projected impact of
environmental policies on the electric power sector in the 48
contiguous states and the District of Columbia. IPM is a multi-
regional, dynamic, deterministic linear programming model of the U.S.
electric power sector. It provides forecasts of least-cost capacity
expansion, electricity dispatch, and emission control strategies for
meeting energy demand and environmental, transmission, dispatch, and
reliability constraints. EPA discusses revisions to these emission
factors in Section III.F and in RIA chapter 4.
2. Health Effects of Non-GHG Pollutants
    In this section we discuss health effects associated with exposure
to some of the criteria and air toxic pollutants impacted by the
vehicle standards.
a. Particulate Matter
    Particulate matter (PM) is a highly complex mixture of solid
particles and liquid droplets distributed among numerous atmospheric
gases which interact with solid and liquid phases. Particles range in
size from those smaller than 1 nanometer (10-9 meter) to
over 100 micrometer ([micro]m, or 10-6 meter) in diameter
(for reference, a typical strand of human hair is 70 um in diameter and
a grain of salt is about 100 [micro]m). Atmospheric particles can be
grouped into several classes according to their aerodynamic and
physical sizes, including ultrafine particles (<0.1 [micro]m),
accumulation mode or `fine' particles (< 1 to 3 [micro]m), and coarse
particles (>1 to 3 [micro]m). For regulatory purposes, fine particles
are measured as PM2.5 and inhalable or thoracic coarse
particles are measured as PM10-2.5, corresponding to their
size (diameter) range in micrometers and referring to total particle
mass under 2.5 and between 2.5 and 10 micrometers, respectively. The
EPA currently has standards that measure PM2.5 and
PM10.\668\
---------------------------------------------------------------------------

    \668\ Regulatory definitions of PM size fractions, and
information on reference and equivalent methods for measuring PM in
ambient air, are provided in 40 CFR Parts 50, 53, and 58.
---------------------------------------------------------------------------

    Particles span many sizes and shapes and consist of hundreds of
different chemicals. Particles are emitted directly from sources and
are also formed through atmospheric chemical reactions; the former are
often referred to as ``primary'' particles, and the latter as
``secondary'' particles. Particle pollution also varies by time of year
and location and is affected by several weather-related factors, such
as temperature, clouds, humidity, and wind. A further layer of
complexity comes from particles' ability to shift between solid/liquid
and gaseous phases, which is influenced by concentration and
meteorology, especially temperature.
    Fine particles are produced primarily by combustion processes and
by transformations of gaseous emissions (e.g., sulfur oxides
(SOX), nitrogen oxides (NOX), and volatile
organic compounds (VOC)) in the atmosphere. The chemical and physical
properties of PM2.5 may vary greatly with time, region,
meteorology, and source category. Thus, PM2.5 may include a
complex mixture of different components including sulfates, nitrates,
organic compounds, elemental carbon and metal compounds. These
particles can remain in the atmosphere for days to weeks and travel
hundreds to thousands of kilometers.
i. Health Effects of Particulate Matter
    Scientific studies show ambient PM is associated with a series of
adverse health effects. These health effects are discussed in detail in
EPA's Integrated Science Assessment (ISA) for Particulate Matter.\669\
Further discussion of health effects associated with PM can also be
found in the RIA for this final rule. The ISA summarizes health effects
evidence associated with both short-term and long-term exposures to
PM2.5, PM10-2.5, and ultrafine particles.\670\
---------------------------------------------------------------------------

    \669\ U.S. EPA (2009) Integrated Science Assessment for
Particulate Matter (Final Report). U.S. Environmental Protection
Agency, Washington, DC, EPA/600/R-08/139F, Docket EPA-HQ-OAR-2010-
0799.
    \670\ See also 77 FR 38906-909 (proposing revisions to the
primary PM NAAQS and summarizing evidence on health effects related
to exposure to fine particulate matter).

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

    The ISA concludes that health effects associated with short-term
exposures (hours to days) to ambient PM2.5 include
mortality, cardiovascular effects, such as altered vasomotor function
and hospital admissions and emergency department visits for ischemic
heart disease and congestive heart failure, and respiratory effects,
such as exacerbation of asthma symptoms in children and hospital
admissions and emergency department visits for chronic obstructive
pulmonary disease and respiratory infections.\671\ The ISA notes that
long-term exposure (months to years) to PM2.5 is associated
with the development/progression of cardiovascular disease, premature
mortality, and respiratory effects, including reduced lung function
growth, increased respiratory symptoms, and asthma development.\672\
The ISA concludes that the currently available scientific evidence from
epidemiologic, controlled human exposure, and toxicological studies
supports a causal association between short- and long-term exposures to
PM2.5 and cardiovascular effects and mortality. Furthermore,
the ISA concludes that the collective evidence supports likely causal
associations between short- and long-term PM2.5 exposures
and respiratory effects. The ISA also concludes that the scientific
evidence is suggestive of a causal association for reproductive and
developmental effects and cancer, mutagenicity, and genotoxicity and
long-term exposure to PM2.5.\673\
---------------------------------------------------------------------------

    \671\ See U.S. EPA, 2009 Final PM ISA, Note 669, at Section
<IP_ADDRESS>.
    \672\ See U.S. EPA 2009 Final PM ISA, Note 669, at page 2-12,
Sections <IP_ADDRESS> and <IP_ADDRESS>.
    \673\ See U.S. EPA 2009 Final PM ISA, Note 669, at Section
2.3.2.
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    For PM10-2.5, the ISA concludes that the current
evidence is suggestive of a causal relationship between short-term
exposures and cardiovascular effects. There is also suggestive evidence
of a causal relationship between short-term PM10-2.5
exposure and mortality and respiratory effects. Data are inadequate to
draw conclusions regarding the health effects associated with long-term
exposure to PM10-2.5.674,675
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    \674\ See U.S. EPA 2009 Final PM ISA, Note 669, at Section
2.3.4, Table 2-6.
    \675\ See also 77 FR 38947-948 (discussing health effects
related to exposure to PM10-2.5).
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    For ultrafine particles, the ISA concludes that there is suggestive
evidence of a causal relationship between short-term exposures and
cardiovascular effects, such as changes in heart rhythm and blood
vessel function. It also concludes that there is suggestive evidence of
association between short-term exposure to ultrafine particles and
respiratory effects. Data are inadequate to draw conclusions regarding
the health effects associated with long-term exposure to ultrafine
particles.\676\
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    \676\ See U.S. EPA 2009 Final PM ISA, Note 669, at Section
2.3.5, Table 2-6.
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b. Ozone
    Ground-level ozone pollution is typically formed by the reaction of
VOC and NOX in the lower atmosphere in the presence of
sunlight. These pollutants, often referred to as ozone precursors, are
emitted by many types of pollution sources, such as highway and nonroad
motor vehicles and engines, power plants, chemical plants, refineries,
makers of consumer and commercial products, industrial facilities, and
smaller area sources.
    The science of ozone formation, transport, and accumulation is
complex. Ground-level ozone is produced and destroyed in a cyclical set
of chemical reactions, many of which are sensitive to temperature and
sunlight. When ambient temperatures and sunlight levels remain high for
several days and the air is relatively stagnant, ozone and its
precursors can build up and result in more ozone than typically occurs
on a single high-temperature day. Ozone can be transported hundreds of
miles downwind from precursor emissions, resulting in elevated ozone
levels even in areas with low local VOC or NOX emissions.
i. Health Effects of Ozone
    The health and welfare effects of ozone are well documented and are
assessed in EPA's 2006 Air Quality Criteria Document and 2007 Staff
Paper.677,678 People who are more susceptible to effects
associated with exposure to ozone can include children, the elderly,
and individuals with respiratory disease such as asthma. Those with
greater exposures to ozone, for instance due to time spent outdoors
(e.g., children and outdoor workers), are of particular concern. Ozone
can irritate the respiratory system, causing coughing, throat
irritation, and breathing discomfort. Ozone can reduce lung function
and cause pulmonary inflammation in healthy individuals. Ozone can also
aggravate asthma, leading to more asthma attacks that require medical
attention and/or the use of additional medication. Thus, ambient ozone
may cause both healthy and asthmatic individuals to limit their outdoor
activities. In addition, there is suggestive evidence of a contribution
of ozone to cardiovascular-related morbidity and highly suggestive
evidence that short-term ozone exposure directly or indirectly
contributes to non-accidental and cardiopulmonary-related mortality,
but additional research is needed to clarify the underlying mechanisms
causing these effects. In a report on the estimation of ozone-related
premature mortality published by NRC, a panel of experts and reviewers
concluded that short-term exposure to ambient ozone is likely to
contribute to premature deaths and that ozone-related mortality should
be included in estimates of the health benefits of reducing ozone
exposure.\679\ Animal toxicological evidence indicates that with
repeated exposure, ozone can inflame and damage the lining of the
lungs, which may lead to permanent changes in lung tissue and
irreversible reductions in lung function. The respiratory effects
observed in controlled human exposure studies and animal studies are
coherent with the evidence from epidemiologic studies supporting a
causal relationship between acute ambient ozone exposures and increased
respiratory-related emergency room visits and hospitalizations in the
warm season. In addition, there is suggestive evidence of a
contribution of ozone to cardiovascular-related morbidity and non-
accidental and cardiopulmonary mortality.
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    \677\ U.S. EPA. (2006). Air Quality Criteria for Ozone and
Related Photochemical Oxidants (Final). EPA/600/R-05/004aF-cF.
Washington, DC: U.S. EPA. Docket EPA-HQ-OAR-2010-0799.
    \678\ U.S. EPA. (2007). Review of the National Ambient Air
Quality Standards for Ozone: Policy Assessment of Scientific and
Technical Information, OAQPS Staff Paper. EPA-452/R-07-003.
Washington, DC, U.S. EPA. Docket EPA-HQ-OAR-2010-0799.
    \679\ National Research Council (NRC), 2008. Estimating
Mortality Risk Reduction and Economic Benefits from Controlling
Ozone Air Pollution. The National Academies Press: Washington, DC
Docket EPA-HQ-OAR-2010-0799.
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c. Nitrogen Oxides and Sulfur Oxides
    Nitrogen dioxide (NO2) is a member of the NOX
family of gases. Most NO2 is formed in the air through the
oxidation of nitric oxide (NO) emitted when fuel is burned at a high
temperature. Sulfur dioxide (SO2) a member of the sulfur
oxide (SOX) family of gases, is formed from burning fuels
containing sulfur (e.g., coal or oil derived), extracting gasoline from
oil, or extracting metals from ore.
    SO2 and NO2 can dissolve in water droplets
and further oxidize to form sulfuric and nitric acid which react with
ammonia to form sulfates and nitrates, both of which are important
components of ambient PM. The health

effects of ambient PM are discussed in Section III.G.2.a of this
preamble. NOX and NMHC are the two major precursors of
ozone. The health effects of ozone are covered in Section III.G.2.b.i.
i. Health Effects of NO2
    Information on the health effects of NO2 can be found in
the EPA Integrated Science Assessment (ISA) for Nitrogen Oxides.\680\
The EPA has concluded that the findings of epidemiologic, controlled
human exposure, and animal toxicological studies provide evidence that
is sufficient to infer a likely causal relationship between respiratory
effects and short-term NO2 exposure. The ISA concludes that
the strongest evidence for such a relationship comes from epidemiologic
studies of respiratory effects including symptoms, emergency department
visits, and hospital admissions. Based on both short- and long-term
studies, the ISA concludes that associations of NO2 with
respiratory health effects are stronger among a number of groups; these
include individuals with preexisting pulmonary conditions (e.g., asthma
or COPD), children and older adults. The ISA also draws two broad
conclusions regarding airway responsiveness following NO2
exposure. First, the ISA concludes that NO2 exposure may
enhance the sensitivity to allergen-induced decrements in lung function
and increase the allergen-induced airway inflammatory response
following 30-minute exposures of asthmatics to NO2
concentrations as low as 0.26 ppm. Second, exposure to NO2
has been found to enhance the inherent responsiveness of the airway to
subsequent nonspecific challenges in controlled human exposure studies
of asthmatic subjects. Small but significant increases in non-specific
airway hyperresponsiveness were reported following 1-hour exposures of
asthmatics to 0.1 ppm NO2. Enhanced airway responsiveness
could have important clinical implications for asthmatics since
transient increases in airway responsiveness following NO2
exposure have the potential to increase symptoms and worsen asthma
control. Together, the epidemiologic and experimental data sets form a
plausible, consistent, and coherent description of a relationship
between NO2 exposures and an array of adverse health effects
that range from the onset of respiratory symptoms to hospital
admission.
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    \680\ U.S. EPA (2008). Integrated Science Assessment for Oxides
of Nitrogen--Health Criteria (Final Report). EPA/600/R-08/071.
Washington, DC: U.S.EPA. Docket EPA-HQ-OAR-2010-0799.
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    Although the weight of evidence supporting a causal relationship is
somewhat less certain than that associated with respiratory morbidity,
NO2 has also been linked to other health endpoints. These
include all-cause (nonaccidental) mortality, hospital admissions or
emergency department visits for cardiovascular disease, and decrements
in lung function growth associated with chronic exposure.
ii. Health Effects of SO2
    Information on the health effects of SO2 can be found in
the EPA Integrated Science Assessment for Sulfur Oxides.\681\
SO2 has long been known to cause adverse respiratory health
effects, particularly among individuals with asthma. Other potentially
sensitive groups include children and the elderly. During periods of
elevated ventilation, asthmatics may experience symptomatic
bronchoconstriction within minutes of exposure. Following an extensive
evaluation of health evidence from epidemiologic and laboratory
studies, the EPA has concluded that there is a causal relationship
between respiratory health effects and short-term exposure to
SO2. Separately, based on an evaluation of the epidemiologic
evidence of associations between short-term exposure to SO2
and mortality, the EPA has concluded that the overall evidence is
suggestive of a causal relationship between short-term exposure to
SO2 and mortality.
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    \681\ U.S. EPA. (2008). Integrated Science Assessment (ISA) for
Sulfur Oxides--Health Criteria (Final Report). EPA/600/R-08/047F.
Washington, DC: U.S. Environmental Protection Agency. Docket EPA-HQ-
OAR-2010-0799.
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d. Carbon Monoxide
    Carbon monoxide (CO) is a colorless, odorless gas emitted from
combustion processes. Nationally and, particularly in urban areas, the
majority of CO emissions to ambient air come from mobile sources.
i. Health Effects of CO
    Information on the health effects of CO can be found in the EPA
Integrated Science Assessment (ISA) for Carbon Monoxide.\682\ The ISA
concludes that ambient concentrations of CO are associated with a
number of adverse health effects.\683\ This section provides a summary
of the health effects associated with exposure to ambient
concentrations of CO.\684\
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    \682\ U.S. EPA, 2010. Integrated Science Assessment for Carbon
Monoxide (Final Report). U.S. Environmental Protection Agency,
Washington, DC, EPA/600/R-09/019F, 2010. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686. Docket EPA-HQ-
OAR-2010-0799
    \683\ The ISA evaluates the health evidence associated with
different health effects, assigning one of five ``weight of
evidence'' determinations: causal relationship, likely to be a
causal relationship, suggestive of a causal relationship, inadequate
to infer a causal relationship, and not likely to be a causal
relationship. For definitions of these levels of evidence, please
refer to Section 1.6 of the ISA.
    \684\ Personal exposure includes contributions from many
sources, and in many different environments. Total personal exposure