2030............................................              18              55              80             170
2035............................................              20              60              86             180
2040............................................              23              66              92             200
2045............................................              25              70              98             220
2050............................................              29              76             100             230
----------------------------------------------------------------------------------------------------------------
Note:
\a\ The SC-CO[ihel2] values are dollar-year and emissions-year specific and have been rounded to two significant
  digits. Unrounded numbers from the current SC-CO[ihel2] TSD were used to calculate the CO[ihel2] benefits.

Table IX-12--Upstream and Downstream Annual CO[ihel2] Benefits for the Given SC-CO[ihel2] Value a Using Method B
                                        and Relative to the Flat Baseline
                                             [Millions of 2013$] \b\
----------------------------------------------------------------------------------------------------------------
                                                                                3% 95th
                  Calendar year                     5% average      3% average     2.5% average     percentile
----------------------------------------------------------------------------------------------------------------
2018............................................              $7             $22             $33             $63
2019............................................              13              46              68             130
2020............................................              21              73             110             210
2021............................................              80             280             420             840
2022............................................             170             550             820           1,700
2023............................................             250             850           1,300           2,600
2024............................................             390           1,300           2,000           4,000
2025............................................             560           1,800           2,700           5,500
2026............................................             700           2,400           3,500           7,100
2027............................................             950           3,000           4,400           9,100
2028............................................           1,100           3,700           5,400          11,000
2029............................................           1,300           4,300           6,400          13,000
2030............................................           1,600           5,000           7,300          15,000
2035............................................           2,700           8,100          11,000          25,000
2040............................................           3,700          11,000          15,000          33,000
2050............................................           5,500          15,000          20,000          45,000
NPV.............................................          24,000         110,000         180,000         340,000
----------------------------------------------------------------------------------------------------------------
Notes:
\a\ The SC-CO[ihel2] values are dollar-year and emissions-year specific.
\b\ For an explanation of analytical Methods A and B, please see Section I.D; for an explanation of the flat
  baseline, 1a, and dynamic baseline, 1b, please see Section X.A.1.

    Table IX-13--Upstream and Downstream Discounted Model Year Lifetime CO[ihel2] Benefits for the Given SC-
                        CO[ihel2] Value Using Method B and Relative to the Flat Baseline
                                             [Millions of 2013$] a b
----------------------------------------------------------------------------------------------------------------
                                                                                3% 95th
                   Model year                       5% average      3% average     2.5% average     percentile
----------------------------------------------------------------------------------------------------------------
2018............................................             $38            $150            $230            $450
2019............................................              36             140             220             430
2020............................................              34             140             220             420
2021............................................             560           2,300           3,600           7,000
2022............................................             590           2,500           3,900           7,500
2023............................................             610           2,600           4,000           7,800
2024............................................             920           4,000           6,200          12,000
2025............................................             940           4,100           6,400          12,000
2026............................................             950           4,200           6,600          13,000
2027............................................           1,200           5,400           8,500          16,000
2028............................................           1,200           5,300           8,400          16,000
2029............................................           1,200           5,300           8,400          16,000
Sum.............................................           8,200          36,000          57,000         110,000
----------------------------------------------------------------------------------------------------------------
Notes:
\a\ The SC-CO[ihel2] values are dollar-year and emissions-year specific.
\b\ For an explanation of analytical Methods A and B, please see Section I.D; for an explanation of the flat
  baseline, 1a, and dynamic baseline, 1b, please see Section X.A.1.

(2) Monetized Non-CO2 GHG Impacts
    EPA calculated the global social benefits of CH4 and
N2O emissions reductions expected from the final rulemaking
using estimates of the social cost of methane (SC-CH4) and
the social cost of nitrous oxide (SC-N2O). Similar to the
SC-CO2, the SC-CH4 and SC-N2O estimate
the monetary value of impacts associated with marginal changes in
CH4 and N2O emissions, respectively, in a given
year. Each metric includes a wide range of anticipated climate impacts,
such as net changes in agricultural productivity and human health,
property damage from increased flood risk, and changes in energy system
costs, such as reduced costs for heating and increased costs for air
conditioning. The SC-CH4 and SC-N2O estimates
applied in this analysis were developed by Marten et al. (2014) and are
discussed in greater detail below. EPA is unaware of analogous
estimates of HFC-134a and has therefore presented a sensitivity
analysis, separate from the main benefit cost analysis, that
approximates the benefits of HFC-134a reductions based on global
warming potential (GWP) gas comparison metrics (``GWP approach'').
Other unquantified non-CO2 benefits are discussed in this
section as well. Additional details are provided in the RIA of these
rules.
(a) Monetized CH4 and N2O Impacts
    As discussed in the proposed rulemaking, a challenge particularly
relevant to the monetization of non-CO2 GHG impacts is that
the IWG did not estimate the social costs of non-CO2 GHG
emissions at the time the SC-CO2 estimates were developed.
While there are other estimates of the social cost of non-
CO2 GHGs in the peer review literature, none of those
estimates are consistent with the SC-CO2 estimates developed
by the IWG and most are likely underestimates due to changes in the
underlying science subsequent to their publication.\838\
---------------------------------------------------------------------------

    \838\ As discussed in the RIA, there is considerable variation
among these published estimates in the models and input assumptions
they employ. These studies differ in the emission perturbation year,
employ a wide range of constant and variable discount rate
specifications, and consider a range of baseline socioeconomic and
emissions scenarios that have been developed over the last 20 years.
See also Reilly and Richards, 1993; Schmalensee, 1993; Fankhauser,
1994; Marten and Newbold, 2012.
---------------------------------------------------------------------------

    However, in the time leading up to the proposal for this
rulemaking, a paper by Marten et al. (2014) provided the first set of
published SC-CH4 and SC-N2O estimates in the
peer-reviewed literature that are consistent with the modeling
assumptions the IWG used to develop the SC-CO2
estimates.\839\ Specifically, the estimation approach of Marten et al.
(2014) used the same set of three IAMs, five socioeconomic-emissions
scenarios, equilibrium climate sensitivity distribution, three constant
discount rates, and aggregation approach used to develop the SC-
CO2 estimates. Marten et al. also used the same rationale as
the IWG to develop global estimates of the SC-CH4 and the
SC-N2O, given that CH4 and N2O are
global pollutants.
---------------------------------------------------------------------------

    \839\ Marten, A.L., E.A. Kopits, C.W. Griffiths, S.C. Newbold &
A. Wolverton (2014). Incremental CH4 and N2O
mitigation benefits consistent with the U.S. Government's SC-
CO2 estimates, Climate Policy, DOI: 10.1080/
14693062.2014.912981.
---------------------------------------------------------------------------

    The resulting SC-CH4 and SC-N2O estimates are
presented in Table IX-14. More detailed discussion of their
methodology, results and a comparison to other published estimates can
be found in the RIA and in Marten et al. (2014).

                                                                   Table IX-14--Social Cost of CH4 and N[ihel2]O, 2012-2050 a
                                                                    [In 2013$ per metric ton] [Source: Marten et al., 2014 b]
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                SC-CH4                                                       SC-N[ihel2]O
                                                                 -------------------------------------------------------------------------------------------------------------------------------
                              Year                                                                                3% 95th                                                         3% 95th
                                                                    5% average      3% average     2.5% average     percentile      5% average      3% average     2.5% average     percentile
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
2012............................................................            $440          $1,000          $1,400          $2,800          $4,000         $14,000         $21,000         $36,000
2015............................................................             490           1,100           1,500           3,100           4,400          14,000          22,000          38,000
2020............................................................             590           1,300           1,800           3,500           5,200          16,000          24,000          43,000
2025............................................................             710           1,500           2,000           4,100           6,000          19,000          26,000          48,000
2030............................................................             830           1,800           2,200           4,600           6,900          21,000          30,000          54,000
2035............................................................             990           2,000           2,500           5,400           8,100          23,000          32,000          60,000

2040............................................................           1,100           2,200           2,900           6,000           9,200          25,000          35,000          66,000
2045............................................................           1,300           2,500           3,100           6,700          10,000          27,000          37,000          73,000
2050............................................................           1,400           2,700           3,400           7,400          12,000          30,000          41,000          79,000
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\a\ The values are emissions-year specific and have been rounded to two significant digits. Unrounded numbers were used to calculate the GHG benefits.
\b\ The estimates in this table have been adjusted to reflect the minor technical corrections to the SC-CO[ihel2] estimates described above. See the Corrigendum to Marten et al. (2014), http://www.tandfonline.com/doi/abs/10.1080/14693062.2015.1070550.

    In addition to requesting comment on these estimates in the
proposed rulemaking, EPA noted that it had initiated a peer review of
the application of the Marten et al (2014) non-CO2 social
cost estimates in regulatory analysis.\840\ EPA also stated that,
pending a favorable peer review, it planned to use the Marten et al
(2014) estimates to monetize benefits of CH4 and
N2O emission reduction in the main benefit-cost analysis of
the final rule.
---------------------------------------------------------------------------

    \840\ For a copy of the peer review and the responses, see
https://cfpub.epa.gov/si/si_public_pra_view.cfm?dirEntryID=291976
(see ``SCCH4 EPA PEER REVIEW FILES.PDF'').
---------------------------------------------------------------------------

    Since then, EPA received responses that supported use of the Marten
et al. estimates. Three reviewers considered seven charge questions
that covered issues such as the EPA's interpretation of the Marten et
al. estimates, the consistency of the estimates with the SC-
CO2 estimates, the EPA's characterization of the limits of
the GWP-approach to value non-CO2 GHG impacts, and the
appropriateness of using the Marten et al. estimates in regulatory
impact analyses. The reviewers agreed with the EPA's interpretation of
Marten et al.'s estimates, generally found the estimates to be
consistent with the SC-CO2 estimates, and concurred with the
limitations of the GWP approach, finding directly modeled estimates to
be more appropriate. While outside of the scope of the review, the
reviewers briefly considered the limitations in the SC-CO2
methodology (e.g., those discussed earlier in this section) and noted
that because the SC-CO2 and SC-CH4 and SC-
N2O methodologies are similar, the limitations also apply to
the resulting SC-CH4 and SC-N2O estimates. Two of
the reviewers concluded that use of the SC-CH4 and SC-
N2O estimates developed by Marten et al. and published in
the peer-reviewed literature is appropriate in RIAs, provided that the
Agency discuss the limitations, similar to the discussion provided for
SC-CO2 and other economic analyses. All three reviewers
encouraged continued improvements in the SC-CO2 estimates
and suggested that as those improvements are realized they should also
be reflected in the SC-CH4 and SC-N2O estimates,
with one reviewer suggesting the SC-CH4 and SC-
N2O estimates lag this process. The EPA supports continued
improvement in the SC-CO2 estimates developed by the U.S.
government and agrees that improvements in the SC-CO2
estimates should also be reflected in the SC-CH4 and SC-
N2O estimates. The fact that the reviewers agree that the
SC-CH4 and SC-N2O estimates are generally
consistent with the SC-CO2 estimates that are recommended by
OMB's guidance on valuing CO2 emissions reductions, leads
the EPA to conclude that use of the SC-CH4 and SC-
N2O estimates is an analytical improvement over excluding
CH4 and N2O emissions from the monetized portion
of the benefit cost analysis.
    The EPA also carefully considered the full range of public comments
and associated technical issues on the Marten et al. estimates received
in this rulemaking and determined that it would continue to use the
estimates in the final rulemaking analysis. Based on the evaluation of
the public comments on this rulemaking, the favorable peer review of
the application of Marten et al. estimates, and past comments urging
EPA to value non-CO2 GHG impacts in its rulemakings, EPA
concluded that the estimates represent the best scientific information
on the impacts of climate change available in a form appropriate for
incorporating the damages from incremental CH4 and
N2O emissions changes into regulatory analysis and has
included those benefits in the main benefits analysis. Please see RTC
Section 11.8 for detailed responses to the comments on non-
CO2 GHG valuation.
    The application of directly modeled estimates from Marten et al.
(2014) to benefit-cost analysis of a regulatory action is analogous to
the use of the SC-CO2 estimates. Specifically, the SC-
CH4 and SC-N2O estimates in Table IX-15 are used
to monetize the benefits of changes in CH4 and
N2O emissions expected as a result of the final rulemaking.
Forecast changes in CH4 and N2O emissions in a
given year resulting from the regulatory action are multiplied by the
SC-CH4 and SC-N2O estimate for that year,
respectively. To obtain a present value estimate, the monetized stream
of future non-CO2 benefits are discounted back to the
analysis year using the same discount rate used to estimate the social
cost of the non-CO2 GHG emission changes.
    The CH4 and N2O benefits based on Marten et
al. (2014) are presented for each calendar year in Table IX-15.

   Table IX-15--Annual Upstream and Downstream non-CO[ihel2] GHG Benefits for the Given SC-non-CO[ihel2] Value Using Method B and Relative to the Flat
                                                  Baseline, using the Directly Modeled Approach \a\ \b\
                                                                 [Millions of 2012$] \c\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                          CH4                                              N[ihel2]O
                                                 -------------------------------------------------------------------------------------------------------
                  Calendar year                                                 2.5%       3% 95th                                  2.5%       3% 95th
                                                   5% Average   3% Average    Average     percentile   5% Average   3% Average    Average     percentile
--------------------------------------------------------------------------------------------------------------------------------------------------------
2018............................................           $0           $1           $1           $2           $0           $0           $0           $0
2019............................................            1            1            2            3            0            0            0            0
2020............................................            1            2            3            5            0            0            0            0
2021............................................            4            8           11           22            0            0            1            1
2022............................................            7           16           21           43            0            1            1            2
2023............................................           12           26           33           68            0            1            2            3
2024............................................           19           40           52          110            1            2            3            5
2025............................................           26           56           72          150            1            3            4            7
2026............................................           34           72           92          190            1            3            5            9
2027............................................           44           94          120          250            1            4            6           11
2028............................................           54          120          150          300            2            5            7           13
2029............................................           65          140          170          360            2            6            9           16
2030............................................           76          160          200          420            2            7           10           19
2035............................................          130          260          340          720            4           12           16           31
2040............................................          180          360          460          980            6           16           22           41
2050............................................          280          530          660        1,400            9           22           30           58
NPV.............................................        1,200        3,800        5,400       10,000           37          160          250          430
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\a\ The SC-CH4 and SC-N[ihel2]O values are dollar-year and emissions-year specific.
\b\ Note that net present discounted values of reduced GHG emissions is are calculated differently than other benefits. The same discount rate used to
  discount the value of damages from future emissions (SC-CH4 and SC-N[ihel2]O at 5, 3, and 2.5 percent) is used to calculate net present value
  discounted values of SC-CH4 and SC-N[ihel2]O for internal consistency. Refer to the 2010 SC-CO[ihel2] TSD for more detail.
\c\ For an explanation of analytical Methods A and B, please see Section I.D; for an explanation of the flat baseline, 1a, and dynamic baseline, 1b,
  please see Section X.A.1.

    (b) Sensitivity Analysis--HFC-134a Benefits Based on the GWP
Approximation Approach
    While the rulemaking will result in reductions of HFC-134a, EPA is
unaware of analogous estimates of the social cost of HFC-134a and has
therefore used an alternative valuation approach and presented the
results in this sensitivity analysis, separate from the main benefit
cost analysis. Specifically, EPA has used the global warming potential
(GWP) for HFC-134a to convert the emissions of this gas to
CO2 equivalents, which are then valued using the SC-
CO2 estimates. This approach, henceforth referred to as the
``GWP approach,'' has been used in sensitivity analyses to estimate the
non-CO2 benefits in previous EPA rulemakings (see U.S. EPA
2012, 2013).\841\ EPA has not presented these estimates in a main
benefit-cost analysis due to the limitations associated with using the
GWP approach to value changes in non-CO2 GHG emissions, and
considered the GWP approach as an interim method of analysis until
social cost estimates for non-CO2 GHGs, consistent with the
SC-CO2 estimates, were developed.
---------------------------------------------------------------------------

    \841\ U.S. EPA. (2012). ``Regulatory impact analysis supporting
the 2012 U.S. Environmental Protection Agency final new source
performance standards and amendments to the national emission
standards for hazardous air pollutants for the oil and natural gas
industry.'' Retrieved from http://www3.epa.gov/ttn/ecas/regdata/RIAs/oil_natural_gas_final_neshap_nsps_ria.pdf. U.S. EPA. (2013).
``Regulatory impact analysis: Final rulemaking for 2017-2025 light-
duty vehicle greenhouse gas emission standards and corporate average
fuel economy standards.'' Retrieved from http://www3.epa.gov/otaq/climate/documents/420r12016.pdf.
---------------------------------------------------------------------------

    The GWP is a simple, transparent, and well-established metric for
assessing the relative impacts of non-CO2 emissions compared
to CO2 on a purely physical basis. However, as discussed
both in the 2010 SC-CO2 TSD and previous rulemakings (e.g.,
U.S. EPA 2012, 2013), the GWP approximation approach to measuring non-
CO2 GHG benefits has several well-documented limitations.
These metrics are not ideally suited for use in benefit-cost analyses
to approximate the social cost of non-CO2 GHGs because the
approach would assume all subsequent linkages leading to damages are
linear in radiative forcing, which would be inconsistent with the most
recent scientific literature. Detailed discussion of limitations of the
GWP approach can be found in the RIA.
    EPA applies the GWP approach to estimate the benefits associated
with reductions of HFCs in each calendar year. Under the GWP Approach,
EPA converted HFC-134a to CO2 equivalents using the AR4 100-
year GWP for HFC-134a (1,430).\842\ These CO2-equivalent
emission reductions are multiplied by the SC-CO2 estimate
corresponding to each year of emission reductions. As with the
calculation of annual benefits of CO2 emission reductions,
the annual benefits of non-CO2 emission reductions based on
the GWP approach are discounted back to net present value terms using
the same discount rate as each SC-CO2 estimate. The
estimated HFC-134a benefits using the GWP approach are presented in
Table IX-16.
---------------------------------------------------------------------------

    \842\ Source: Table 2.14 (Errata). Lifetimes, radiative
efficiencies and direct (except for CH4) GWPs relative to
CO2. IPCC Fourth Assessment Report ``Climate Change 2007:
Working Group I: The Physical Science Basis.''

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

Vol. 81

Tuesday,

No. 206

October 25, 2016

Part II--Continued

Book 2 of 2 Books

Pages 73881-74278

Environmental Protection Agency

  Table IX-16--Annual Upstream and Downstream HFC-134a Benefits for the Given SC-CO[ihel2] Value Using Method B
                        and Relative to the Flat Baseline, using the GWP Approach \a\ \b\
                                             [Millions of 2013$] \b\
----------------------------------------------------------------------------------------------------------------
                                                                             HFC-134a
                                                 ---------------------------------------------------------------
                  Calendar year                                                                      3%, 95th
                                                    5% Average      3% Average     2.5% Average     Percentile
----------------------------------------------------------------------------------------------------------------
2018............................................              $0              $0              $0              $0
2019............................................              $0              $0              $0              $0
2020............................................              $0              $0              $0              $0
2021............................................              $0              $1              $1              $3
2022............................................              $1              $2              $3              $5
2023............................................              $1              $3              $4              $8
2024............................................              $1              $4              $5             $11
2025............................................              $1              $5              $7             $14
2026............................................              $2              $6              $9             $18
2027............................................              $2              $7             $10             $21
2028............................................              $3              $8             $12             $25
2029............................................              $3             $10             $14             $29
2030............................................              $4             $11             $16             $33
2035............................................              $5             $15             $22             $47
2040............................................              $6             $18             $25             $54
2050............................................              $9             $23             $31             $70
NPV.............................................             $44            $200            $320            $620
----------------------------------------------------------------------------------------------------------------
Notes:
\a\ The SC-CO[ihel2] values are dollar-year and emissions-year specific.
\b\ For an explanation of analytical Methods A and B, please see Section I.D; for an explanation of the flat
  baseline, 1a, and dynamic baseline, 1b, please see Section X.A.1.

(c) Additional Non-CO2 GHGs Co-Benefits
    In determining the relative social costs of the different gases,
the Marten et al. (2014) analysis accounts for differences in lifetime
and radiative efficiency between the non-CO2 GHGs and
CO2. The analysis also accounts for radiative forcing
resulting from methane's effects on tropospheric ozone and
stratospheric water vapor, and for at least some of the fertilization
effects of elevated carbon dioxide concentrations. However, there exist
several other differences between these gases that have not yet been
captured in this analysis, for example the non-radiative effects of
methane-driven elevated tropospheric ozone levels on human health,
agriculture, and ecosystems, and the effects of carbon dioxide on ocean
acidification. Inclusion of these additional non-radiative effects
would potentially change both the absolute and relative value of the
various gases.
    Of these effects, the human health effect of elevated tropospheric
ozone levels resulting from methane emissions is the closest to being
monetized in a way that would be comparable to the SCC. Premature
ozone-related cardiopulmonary deaths resulting from global increases in
tropospheric ozone concentrations produced by the methane oxidation
process have been the focus of a number of studies over the past decade
(e.g., West et al. 2006; \843\ Anenberg et al. 2012; \844\ Shindell et
al. 2012 \845\). Recently, a paper was published in the peer-reviewed
scientific literature that presented a range of estimates of the
monetized ozone-related mortality benefits of reducing methane
emissions (Sarofim et al. 2015). For example, under their base case
assumptions using a 3 percent discount rate, Sarofim et al. find global
ozone-related mortality benefits of methane emissions reductions to be
$790 per ton of methane in 2020, with 10.6 percent, or $80, of this
amount resulting from mortality reductions in the United States. The
methodology used in this study is consistent in some (but not all)
aspects with the modeling underlying the SC-CO2 and SC-
CH4 estimates discussed above, and required a number of
additional assumptions such as baseline mortality rates and mortality
response to ozone concentrations. While the EPA does consider the
methane impacts on ozone to be important, there remain unresolved
questions regarding several methodological choices involved in applying
the Sarofim et al. (2015) approach in the context of an EPA benefits
analysis, and therefore the EPA is not including a quantitative
analysis of this effect in this rule at this time.
---------------------------------------------------------------------------

    \843\ West JJ, Fiore AM, Horowitz LW, Mauzerall DL (2006) Global
health benefits of mitigating ozone pollution with methane emission
controls. Proc Natl Acad Sci USA 103 (11):3988-3993. doi:10.1073/
pnas.0600201103
    \844\ Anenberg SC, Schwartz J, Shindell D, Amann M, Faluvegi G,
Klimont Z, . . . , Vignati E (2012) Global air quality and health
co-benefits of mitigating near-term climate change through methane
and black carbon emission controls. Environ Health Perspect 120
(6):831. doi:10.1289/ehp.1104301.
    \845\ Shindell D, Kuylenstierna JCI, Vignati E, van Dingenen R,
Amann M, Klimont Z, . . ., Fowler D (2012) Simultaneously Mitigating
Near-Term Climate Change and Improving Human Health and Food
Security. Science 335 (6065):183-189. doi:10.1126/science.1210026.
---------------------------------------------------------------------------

H. Monetized Non-GHG Health Impacts

    This section discusses the economic benefits from reductions in
health and environmental impacts resulting from non-GHG emission
reductions that can be expected to occur as a result of the Phase 2
standards. CO2 emissions are predominantly the byproduct of
fossil fuel combustion processes that also produce criteria and
hazardous air pollutant emissions. The vehicles that are subject to the
Phase 2 standards are also significant sources of mobile source air
pollution such as direct PM, NOX, VOCs and air toxics. The
standards will affect exhaust emissions of these pollutants from
vehicles and will also affect emissions from upstream sources that
occur during the refining and distribution of fuel. Changes in ambient
concentrations of ozone, PM2.5, and air toxics that will
result from the Phase 2 standards are expected to affect human health
by reducing premature deaths and other serious human health effects, as
well as other important improvements in public health and

welfare. Children especially benefit from reduced exposures to criteria
and toxic pollutants, because they tend to be more sensitive to the
effects of these respiratory pollutants. Ozone and particulate matter
have been associated with increased incidence of asthma and other
respiratory effects in children, and particulate matter has been
associated with a decrease in lung maturation. Some minority groups and
children living under the poverty line are even more vulnerable with
higher prevalence of asthma.
    It is important to quantify the health and environmental impacts
associated with the standards because a failure to adequately consider
ancillary impacts could lead to an incorrect assessment of their costs
and benefits. Moreover, the health and other impacts of exposure to
criteria air pollutants and airborne toxics tend to occur in the near
term, while most effects from reduced climate change are likely to
occur only over a time frame of several decades or longer.
    Impacts such as emissions reductions, costs and benefits are
presented in this analysis from two perspectives:
     A ``model year lifetime analysis'' (MY), which shows
impacts of the program that occur over the lifetime of the vehicles
produced during the model years subject to the Phase 2 standards (MYs
2018 through 2029).,
     A ``calendar year analysis'' (CY), which shows annual
costs and benefits of the Phase 2 standards for each year from 2018
through 2050. We assume the standard in the last model year subject to
the standards applies to all subsequent MY fleets developed in the
future.
    In previous light-duty and heavy-duty GHG rulemakings, EPA has
quantified and monetized non-GHG health impacts using two different
methods. For the MY analysis, EPA applies PM-related ``benefits per-
ton'' values to the stream of lifetime estimated emission reductions as
a reduced-form approach to estimating the PM2.5-related
benefits of the rule.846 847 For the CY analysis, EPA
typically conducts full-scale photochemical air quality modeling to
quantify and monetize the PM2.5- and ozone-related health
impacts of a single representative future year. EPA then assumes these
benefits are repeated in subsequent future years when criteria
pollutant emission reductions are equal to or greater than those
modeled in the representative future year.
---------------------------------------------------------------------------

    \846\ Fann, N., Baker, K.R., and Fulcher, C.M. (2012).
Characterizing the PM 2.5-related health benefits of
emission reductions for 17 industrial, area and mobile emission
sectors across the U.S., Environment International, 49, 241-151,
published online September 28, 2012.
    \847\ See also: http://www3.epa.gov/airquality/benmap/sabpt.html. The current values available on the Web page have been
updated since the publication of the Fann et al., 2012 paper. For
more information regarding the updated values, see: http://www3.epa.gov/airquality/benmap/models/Source_Apportionment_BPT_TSD_1_31_13.pdf (accessed September 9,
2014).
---------------------------------------------------------------------------

    This two-pronged approach to estimating non-GHG impacts is
precipitated by the length of time needed to prepare the necessary
emissions inventories and the processing time associated with full-
scale photochemical air quality modeling for a single representative
future year. The timing requirements (along with other resource
limitations) preclude EPA from being able to do the more detailed
photochemical modeling for every year that we include in our benefit
and cost estimates, and require EPA to make air quality modeling input
decisions early in the analytical process. As a result, it was
necessary to use emissions from the proposed program to conduct the air
quality modeling.
    The chief limitation when using air quality inventories based on
emissions from the proposal in the CY modeling analysis is that they
can diverge from the estimated emissions of the final rulemaking. How
much the emissions might diverge and how that difference would impact
the air quality modeling and health benefit results is difficult to
anticipate. For the FRM, EPA concluded that when comparing the proposal
and final rule inventories, the differences were enough to justify the
move of the typical CY benefits analysis (based on air quality
modeling) from the primary estimate of costs and benefits to a
supplemental analysis in an appendix to the RIA (See RIA Appendix
8.A).\848\ While we believe this supplemental analysis is still
illustrative of the standard's potential benefits, EPA has instead
chosen to characterize the CY benefits in a manner consistent with the
MY lifetime analysis. That is, we apply the PM-related ``benefits per-
ton'' values to the CY final rule emission reductions to estimate the
PM-related benefits of the final rule.
---------------------------------------------------------------------------

    \848\ Chapter 5 of the RIA has more detail on the differences
between the air quality and final inventories.
---------------------------------------------------------------------------

    This section presents the benefits-per-ton values used to monetize
the benefits from reducing population exposure to PM associated with
the standards. EPA bases its analyses on peer-reviewed studies of air
quality and health and welfare effects and peer-reviewed studies of the
monetary values of public health and welfare improvements, and is
generally consistent with benefits analyses performed for the analysis
of the final Tier 3 Vehicle Rule,\849\ the final 2012 p.m. NAAQS
Revision,\850\ and the final 2017-2025 Light Duty Vehicle GHG
Rule.\851\
---------------------------------------------------------------------------

    \849\ U.S. Environmental Protection Agency. (2014). Control of
Air Pollution from Motor Vehicles: Tier 3 Motor Vehicle Emission and
Fuel Standards Final Rule: Regulatory Impact Analysis, Assessment
and Standards Division, Office of Transportation and Air Quality,
EPA-420-R-14-005, March 2014. Available on the internet: http://www3.epa.gov/otaq/documents/tier3/420r14005.pdf.
    \850\ U.S. Environmental Protection Agency. (2012). Regulatory
Impact Analysis for the Final Revisions to the National Ambient Air
Quality Standards for Particulate Matter, Health and Environmental
Impacts Division, Office of Air Quality Planning and Standards, EPA-
452-R-12-005, December 2012. Available on the internet: http://www3.epa.gov/ttnecas1/regdata/RIAs/finalria.pdf.
    \851\ U.S. Environmental Protection Agency (U.S. EPA). (2012).
Regulatory Impact Analysis: Final Rulemaking for 2017-2025 Light-
Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average
Fuel Economy Standards, Assessment and Standards Division, Office of
Transportation and Air Quality, EPA-420-R-12-016, August 2012.
Available on the Internet at: http://www3.epa.gov/otaq/climate/documents/420r12016.pdf.
---------------------------------------------------------------------------

    EPA is also requiring that rebuilt engines installed in new
incomplete vehicles (i.e., ``glider kit'' vehicles) meet the emission
standards applicable in the year of assembly of the new vehicle,
including all applicable standards for criteria pollutants (Section
XIII.B). For the final rule, EPA has updated its analysis of the
environmental impacts of these glider kit vehicles (see Section
XIII.B.1). These standards will decrease PM and NOX
emissions dramatically, leading to substantial public health-related
benefits. Although we only present these benefits as a sensitivity
analysis in Section XIII.B, it is clear that removing even a fraction
of glider kit vehicles from the road will yield substantial health-
related benefits that are not captured by the primary estimate of
monetized non-GHG health impacts described in this section.
(1) Economic Value of Reductions in Particulate Matter
    As described in Section VIII, the standards will reduce emissions
of several criteria and toxic pollutants and their precursors. In this
analysis, EPA only estimates the economic value of the human health
benefits associated with the resulting reductions in PM2.5
exposure. Due to analytical limitations with the benefit per ton
method, this analysis does not estimate benefits resulting from
reductions in population exposure to other criteria pollutants such as
ozone.\852\ Furthermore, the

benefits per-ton method, like all air quality impact analyses, does not
monetize all of the potential health and welfare effects associated
with reduced concentrations of PM2.5.
---------------------------------------------------------------------------

    \852\ The air quality modeling that underlies the PM-related
benefit per ton values also produced estimates of ozone levels
attributable to each sector. However, the complex non-linear
chemistry governing ozone formation prevented EPA from developing a
complementary array of ozone benefit per ton values. This limitation
notwithstanding, we anticipate that the ozone-related benefits
associated with reducing emissions of NOX and VOC are
substantial. Refer to RIA Appendix 8.A for the ozone benefits
results from the supplemental CY benefits analysis.
---------------------------------------------------------------------------

    This analysis uses estimates of the benefits from reducing the
incidence of the specific PM2.5-related health impacts
described below. These estimates, which are expressed per ton of
PM2.5-related emissions eliminated by the final program,
represent the monetized value of human health benefits (including
reductions in both premature mortality and premature morbidity) from
reducing each ton of directly emitted PM2.5 or its
precursors (SO2 and NOX), from a specified
source. Ideally, the human health benefits would be estimated based on
changes in ambient PM2.5 as determined by full-scale air
quality modeling. However, the length of time needed to prepare the
necessary emissions inventories, in addition to the processing time
associated with the modeling itself, has precluded us from performing
air quality modeling that reflects the emissions and air quality
impacts associated with the final program.
    EPA received comment regarding the omission of ozone-related
benefits from the non-GHG benefits analysis included in the proposal.
EPA agrees that total benefits are underestimated when ozone-related
benefits are not included in the primary analysis. However, for reasons
described in the introduction to this section, PM- and ozone-related
health benefits based on air quality modeling for the CY analysis are
not included in the primary estimate of costs and benefits. Instead,
they can be found as a supplemental analysis to the RIA in Appendix 8A.
    The PM-related dollar-per-ton benefit estimates used in this
analysis are provided in Table IX-17. As the table indicates, these
values differ among pollutants, and also depend on their original
source, because emissions from different sources can result in
different degrees of population exposure and resulting health impacts.
In the summary of costs and benefits, Section IX.K of this Preamble,
EPA presents the monetized value of PM-related improvements associated
with the final program.

                                                     Table IX-17--PM-Related Benefits-per-Ton Values
                                                                  [Thousands, 2013$] a
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      On-road mobile sources                           Upstream sources \d\
                        Year \c\                         -----------------------------------------------------------------------------------------------
                                                           Direct PM2.5      SO[ihel2]          NOX        Direct PM2.5      SO[ihel2]          NOX
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                      Estimated Using a 3 Percent Discount Rate \b\
--------------------------------------------------------------------------------------------------------------------------------------------------------
2016....................................................       $380-$870         $20-$46        $7.8-$18       $330-$760        $71-$160        $6.9-$16
2020....................................................         410-920           22-50          8.2-18         350-800          76-170          7.5-17
2025....................................................       450-1,000           25-56          9.0-20         400-890          84-190          8.2-18
2030....................................................       490-1,100           28-62          9.7-22         430-960          92-200          8.9-20
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                      Estimated Using a 7 Percent Discount Rate \b\
--------------------------------------------------------------------------------------------------------------------------------------------------------
2016....................................................       $340-$780         $18-$42        $7.1-$16       $300-$680        $64-$140        $6.3-$14
2020....................................................         370-830           20-45          7.5-17         320-730          68-150          6.7-15
2025....................................................         410-920           22-50          8.1-18         350-800          76-170          7.4-17
2030....................................................         440-990           25-56          8.8-20         380-870          82-180          8.0-18
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\a\ The benefit-per-ton estimates presented in this table are based on a range of premature mortality estimates derived from the ACS study (Krewski et
  al., 2009) and the Six-Cities study (Lepeule et al., 2012). See Chapter VIII of the RIA for a description of these studies.
\b\ The benefit-per-ton estimates presented in this table assume either a 3 percent or 7 percent discount rate in the valuation of premature mortality
  to account for a twenty-year segmented premature mortality cessation lag.
\c\ Benefit-per-ton values were estimated for the years 2016, 2020, 2025 and 2030. We hold values constant for intervening years (e.g., the 2016 values
  are assumed to apply to years 2017-2019; 2020 values for years 2021-2024; 2030 values for years 2031 and beyond).
\d\ We assume for the purpose of this analysis that total ``upstream emissions'' are most appropriately monetized using the refinery sector benefit per-
  ton values. The majority of upstream emission reductions associated with the final rule are related to domestic onsite refinery emissions and domestic
  crude production. While total upstream emissions also include storage and transport sources, as well as sources upstream from the refinery, we have
  chosen to simply apply the refinery values.

    The benefit-per-ton technique has been used in previous analyses,
including EPA's 2017-2025 Light-Duty Vehicle Greenhouse Gas Rule,\853\
the Reciprocating Internal Combustion Engine rules,854 855
and the Residential Wood Heaters NSPS.\856\ Table IX-18 shows the
quantified PM2.5-related co-benefits captured in those
benefit per-ton estimates, as well as unquantified effects the benefit
per-ton estimates are unable to capture.
---------------------------------------------------------------------------

    \853\ U.S. Environmental Protection Agency (U.S. EPA). (2012).
Regulatory Impact Analysis: Final Rulemaking for 2017-2025 Light-
Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average
Fuel Economy Standards, Assessment and Standards Division, Office of
Transportation and Air Quality, EPA-420-R-12-016, August 2012.
Available on the Internet at: http://www3.epa.gov/otaq/climate/documents/420r12016.pdf.
    \854\ U.S. Environmental Protection Agency (U.S. EPA). (2013).
Regulatory Impact Analysis for the Reconsideration of the Existing
Stationary Compression Ignition (CI) Engines NESHAP, Office of Air
Quality Planning and Standards, Research Triangle Park, NC. January.
EPA-452/R-13-001. Available at http://www3.epa.gov/ttnecas1/regdata/RIAs/RICE_NESHAPreconsideration_Compression_Ignition_Engines_RIA_final2013_EPA.pdf.
    \855\ U.S. Environmental Protection Agency (U.S. EPA). (2013).
Regulatory Impact Analysis for Reconsideration of Existing
Stationary Spark Ignition (SI) RICE NESHAP, Office of Air Quality
Planning and Standards, Research Triangle Park, NC. January. EPA-
452/R-13-002. Available at http://www3.epa.gov/ttnecas1/regdata/RIAs/NESHAP_RICE_Spark_Ignition_RIA_finalreconsideration2013_EPA.pdf.

    \856\ U.S. Environmental Protection Agency (U.S. EPA). (2015).
Regulatory Impact Analysis for Residential Wood Heaters NSPS
Revision. Office of Air Quality Planning and Standards, Research
Triangle Park, NC. February. EPA-452/R-15-001. Available at http://www2.epa.gov/sites/production/files/2015-02/documents/20150204-residential-wood-heaters-ria.pdf.

                             Table IX-18--Human Health and Welfare Effects of PM2.5
----------------------------------------------------------------------------------------------------------------
                                Quantified and monetized in primary
     Pollutant/ effect                       estimates                      Unquantified effects changes in:
----------------------------------------------------------------------------------------------------------------
PM2.5......................  Adult premature mortality................  Chronic and subchronic bronchitis cases.
                             Acute bronchitis.........................  Strokes and cerebrovascular disease.
                             Hospital Admissions: Respiratory and       Low birth weight.
                              cardiovascular.
                             Emergency room visits for asthma.........  Pulmonary function.
                             Nonfatal heart attacks (myocardial         Chronic respiratory diseases other than
                              infarction).                               chronic bronchitis.
                             Lower and upper respiratory illness......  Non-asthma respiratory emergency room
                                                                         visits.
                             Minor restricted-activity days...........  Visibility.
                             Work loss days...........................  Household soiling.
                             Asthma exacerbations (asthmatic
                              population).
                             Infant mortality.........................
----------------------------------------------------------------------------------------------------------------

    A more detailed description of the benefit-per-ton estimates is
provided in Chapter 8 of the RIA that accompanies this rulemaking.
Readers interested in reviewing the complete methodology for creating
the benefit-per-ton estimates used in this analysis can consult EPA's
``Technical Support Document: Estimating the Benefit per Ton of
Reducing PM2.5 Precursors from 17 Sectors.'' \857\ Readers
can also refer to Fann et al. (2012) \858\ for a detailed description
of the benefit-per-ton methodology.
---------------------------------------------------------------------------

    \857\ For more information regarding the updated values, see:
http://www3.epa.gov/airquality/benmap/models/Source_Apportionment_BPT_TSD_1_31_13.pdf (accessed September 9,
2014).
    \858\ Fann, N., Baker, K.R., and Fulcher, C.M. (2012).
Characterizing the PM2.5-related health benefits of emission
reductions for 17 industrial, area and mobile emission sectors
across the U.S., Environment International, 49, 241-151, published
online September 28, 2012.
---------------------------------------------------------------------------

    As Table IX-17 indicates, EPA projects that the per-ton values for
reducing emissions of non-GHG pollutants from both vehicle use and
upstream sources such as fuel refineries will increase over time.\859\
These projected increases reflect rising income levels, which increase
affected individuals' willingness to pay for reduced exposure to health
threats from air pollution.\860\ They also reflect future population
growth and increased life expectancy, which expands the size of the
population exposed to air pollution in both urban and rural areas,
especially among older age groups with the highest mortality risk.\861\
---------------------------------------------------------------------------

    \859\ As we discuss in the emissions chapter of the RIA (Chapter
V), the rule will yield emission reductions from upstream refining
and fuel distribution due to decreased petroleum consumption.
    \860\ The issue is discussed in more detail in the 2012 p.m.
NAAQS RIA. See U.S. Environmental Protection Agency. (2012).
Regulatory Impact Analysis for the Final Revisions to the National
Ambient Air Quality Standards for Particulate Matter, Health and
Environmental Impacts Division, Office of Air Quality Planning and
Standards, EPA-452-R-12-005, December 2012. Available on the
internet: http://www3.epa.gov/ttnecas1/regdata/RIAs/finalria.pdf.
    \861\ For more information about EPA's population projections,
please refer to the following: http://www3.epa.gov/air/benmap/models/BenMAPManualAppendicesAugust2010.pdf (See Appendix K).
---------------------------------------------------------------------------

(2) Unquantified Health and Environmental Impacts
    One commenter supported the inclusion of all quantifiable impacts
of reductions in non-GHG pollutants. Specifically, they suggested the
inclusion of ecosystem benefits from reduced non-GHG pollutants
including those to crops as well as consideration of the impacts on
toxic air contaminants such as diesel PM.
    In addition to the PM-related co-pollutant health impacts EPA
quantifies in this analysis, EPA acknowledges that there are a number
of other health and human welfare endpoints that we are not able to
quantify or monetize because of current limitations in the methods or
available data. These impacts are associated with emissions of air
toxics (including benzene, 1,3-butadiene, formaldehyde, acetaldehyde,
acrolein, naphthalene and ethanol), ambient ozone, and ambient
PM2.5 exposures. Chapter 8 of the RIA lists these
unquantified health and environmental impacts. While there will be
impacts associated with air toxic pollutant emission changes that
result from the final standard, EPA will not attempt to monetize those
impacts. This is primarily because currently available tools and
methods to assess air toxics risk from mobile sources at the national
scale are not adequate for extrapolation to incidence estimations or
benefits assessment. The best suite of tools and methods currently
available for assessment at the national scale are those used in the
National-Scale Air Toxics Assessment (NATA). EPA's Science Advisory
Board specifically commented in their review of the 1996 NATA that
these tools were not yet ready for use in a national-scale benefits
analysis, because they did not consider the full distribution of
exposure and risk, or address sub-chronic health effects.\862\ While
EPA has since improved the tools, there remain critical limitations for
estimating incidence and assessing benefits of reducing mobile source
air toxics.\863\ EPA continues to work to address these limitations;
however, EPA does not have the methods and tools available for
national-scale application in time for the analysis of the final
rules.\864\
---------------------------------------------------------------------------

    \862\ Science Advisory Board. 2001. NATA--Evaluating the
National-Scale Air Toxics Assessment for 1996--an SAB Advisory.
http://www3.epa.gov/ttn/atw/sab/sabrev.html.
    \863\ Examples include gaps in toxicological data, uncertainties
in extrapolating results from high-dose animal experiments to
estimate human effects at lower does, limited ambient and personal
exposure monitoring data, and insufficient economic research to
support valuation of the health impacts often associated with
exposure to individual air toxics. See Gwinn et al., 2011. Meeting
Report: Estimating the Benefits of Reducing Hazardous Air
Pollutants--Summary of 2009 Workshop and Future Considerations.
Environ Health Perspectives, Jan 2011; 119(1): 125-130.
    \864\ In April, 2009, EPA hosted a workshop on estimating the
benefits of reducing hazardous air pollutants. This workshop built
upon the work accomplished in the June 2000 in an earlier (2000)
Science Advisory Board/EPA Workshop on the Benefits of Reductions in
Exposure to Hazardous Air Pollutants, which generated thoughtful
discussion on approaches to estimating human health benefits from
reductions in air toxics exposure, but no consensus was reached on
methods that could be implemented in the near term for a broad
selection of air toxics. Please visit http://epa.gov/air/toxicair/2009workshop.html for more information about the workshop and its
associated materials.
---------------------------------------------------------------------------

I. Energy Security Impacts

    The Phase 2 standards are designed to require improvements in the
fuel efficiency of medium- and heavy-duty vehicles and, thereby, reduce
fuel consumption and GHG emissions. In turn, the Phase 2 standards help
to reduce U.S. petroleum imports. A reduction of U.S. petroleum imports
reduces both financial and strategic risks caused by potential sudden
disruptions in the supply of imported petroleum to the U.S., thus
increasing

U.S. energy security. This section summarizes the agency's estimates of
U.S. oil import reductions and energy security benefits of the Phase 2
final standards. Additional discussion of this issue can be found in
Chapter 8.8 of the RIA.
(1) Implications of Reduced Petroleum Use on U.S. Imports
    U.S. energy security is generally considered as the continued
availability of energy sources at an acceptable price. Most discussion
of U.S. energy security revolves around the topic of the economic costs
of U.S. dependence on oil imports. While the U.S. has reduced its
consumption and increased its production of oil in recent years, it
still relies on oil from potentially unstable sources. In addition, oil
exporters with a large share of global production have the ability to
raise the price of oil by exerting the monopoly power associated with a
cartel, the Organization of Petroleum Exporting Countries (OPEC), to
restrict oil supply relative to demand. These factors contribute to the
vulnerability of the U.S. economy to episodic oil supply shocks and
price spikes.
    In 2014, U.S. expenditures for imports of crude oil and petroleum
products, net of revenues for exports, were $178 billion and
expenditures on both imported oil and domestic petroleum and refined
products totaled $469 billion (in 2013$) (see Figure IX-1).\865\
Recently, as a result of strong growth in domestic oil production
mainly from tight shale formations, U.S. production of oil has
increased while U.S. oil imports have decreased. For example, from 2012
to 2015, domestic oil production increased by 44 percent while net oil
imports and products decreased by 38 percent. While U.S. oil import
costs have declined since 2011, total oil expenditures (domestic and
imported) remained near historical highs through 2014. Post-2015 oil
expenditures are projected (AEO 2015) to remain between double and
triple the inflation-adjusted levels experienced by the U.S. from 1986
to 2002.C
---------------------------------------------------------------------------

    \865\ See EIA Annual Energy Review, various editions. For data
2011-2013, and projected data: EIA Annual Energy Outlook (AEO) 2014
(Reference Case). See Table 11, file ``aeotab_11.xls.''
---------------------------------------------------------------------------

    Focusing on changes in oil import levels as a source of
vulnerability has been standard practice in assessing energy security
in the past, but given current market trends both from domestic and
international levels, adding changes in consumption of petroleum to
this assessment may provide better information about U.S. energy
security. The major mechanism through which the economy sustains harm
due to fluctuations in the (world) energy market is through price,
which itself is leveraged through both imports and consumption.
However, the United States, may be increasingly insulated from the
physical effects of overseas oil disruptions, though the price impacts
of an oil disruption anywhere will continue to be transmitted to U.S.
markets. As of 2015, Canada accounted for 63 percent of U.S. net oil
imports of crude oil and petroleum products. The implications of the
U.S. becoming a significant petroleum producer have yet to be discerned
in the literature, but it can be anticipated that this will have some
impact on energy security.
    In 2010, just over 40 percent of world oil supply came from OPEC
nations. The AEO 2015 projects that this share will stay high; dipping
slightly from 37 percent by 2020 and then rising gradually to over 40
percent by 2035 and thereafter. Approximately 30 percent of global
supply is from Middle East and North African countries alone, a share
that is also expected to grow. Measured in terms of the share of world
oil resources or the share of global oil export supply, rather than oil
production, the concentration of global petroleum resources in OPEC
nations is even larger. As another measure of concentration, of the 137
countries/principalities that export either crude or refined products,
the top 12 have recently accounted for over 55 percent of exports.\866\
Eight of these countries are members of OPEC, and a ninth is
Russia.\867\ In a market where even a 1-2 percent supply loss can raise
prices noticeably, and where a 10 percent supply loss could lead to an
unprecedented price shock, this regional concentration is of
concern.\868\ Historically, the countries of the Middle East have been
the source of eight of the ten major world oil disruptions,\869\ with
the ninth originating in Venezuela, an OPEC country, and the tenth
being Hurricanes Katrina and Rita.
---------------------------------------------------------------------------

    \866\ Based on data from the CIA, combining various recent
years, https://www.cia.gov/library/publications/the-world-factbook/rankorder/2242rank.html.
    \867\ The other three are Norway, Canada, and the EU, an
exporter of product.
    \868\ For example, the 2005 Hurricanes Katrina/Rita and the 2011
Libyan conflict both led to a 1.8 percent reduction in global crude
supply. While the price impact of the latter is not easily
distinguished given the rapidly rising post-recession prices, the
former event was associated with a 10-15 percent world oil price
increase. There are a range of smaller events with smaller but
noticeable impacts. Somewhat larger events, such as the 2002/3
Venezuelan Strike and the War in Iraq, corresponded to about a 2.9
percent sustained loss of supply, and were associated with a 28
percent world oil price increase.
    Compiled from EIA oil price data, IEA2012 [IEA Response System
for Oil Supply Emergencies (http://www.iea.org/publications/freepublications/publication/EPPD_Brochure_English_2012_02.pdf)
    See table on P. 11.and Hamilton 2011 ``Historical Oil
Shocks,''(http://econweb.ucsd.edu/~jhamilto/oil_history.pdf) in
*Routledge Handbook of Major Events in Economic History*, pp. 239-
265, edited by Randall E. Parker and Robert Whaples, New York:
Routledge Taylor and Francis Group, 2013). Available in bookstores.
    \869\ IEA 2011 ``IEA Response System for Oil Supply
Emergencies.''
    \870\ For historical data: EIA Annual Energy Review, various
editions. For data 2011-2013, and projected data: EIA Annual Energy
Outlook (AEO) 2014 (Reference Case). See Table 11, file
``aeotab_11.xls.''

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

[GRAPHIC] [TIFF OMITTED] TR25OC16.037

    The agencies used EPA's MOVES model to estimate the reductions in
U.S. fuel consumption due to these final rules for vocational vehicles
and tractors. For HD pickups and vans, the agencies used both DOT's
CAFE model and EPA's MOVES model to estimate the fuel consumption
impacts. (Detailed explanations of the MOVES and CAFE models can be
found in Chapter 5 of the RIA. See IX.C of the Preamble for estimates
of reduced fuel consumption from these final rules). Based on a
detailed analysis of differences in U.S. fuel consumption, petroleum
imports, and imports of petroleum products, the agencies estimate that
approximately 90 percent of the reduction in fuel consumption resulting
from adopting improved GHG emission and fuel efficiency standards is
likely to be reflected in reduced U.S. imports of crude oil and net
imported petroleum products.\871\ Thus, on balance, each gallon of fuel
saved as a consequence of the HD GHG and fuel efficiency standards is
anticipated to reduce total U.S. imports of petroleum by 0.90 gallons.
Based upon the fuel savings estimated by the MOVES/CAFE models and the
90 percent oil import factor, the reduction in U.S. oil imports and
exports from these final rules are estimated for the years 2020, 2025,
2030, 2040, and 2050 (in millions of barrels per day (MMBD)) in Table
IX-19 below. For comparison purposes, Table IX-19 also shows U.S.
imports of crude oil in 2020, 2025, 2030 and 2040 as projected by DOE
in the Annual Energy Outlook 2015 Reference Case. U.S. Gross Domestic
Product (GDP) is projected to grow by roughly 48 percent over the same
time frame (e.g., from 2020 to 2040) in the AEO 2015 projections.
---------------------------------------------------------------------------

    \871\ We looked at changes in U.S. crude oil imports and net
petroleum products in the AEO 2015 Reference Case in comparison the
Low (i.e., Economic Growth) Demand Case to undertake this analysis.
See the spreadsheet ``Impact of Fuel Demand on Imports
AEO2015.xlsx.'' We also considered a paper entitled ``Effect of a
U.S. Demand Reduction on Imports and Domestic Supply Levels'' by
Leiby, P., 4/16/2013. This paper suggests that ``Given a particular
reduction in oil demand stemming from a policy or significant
technology change, the fraction of oil use savings that shows up as
reduced U.S. imports, rather than reduced U.S. supply, is actually
quite close to 90 percent, and probably close to 95 percent.''

 Table IX-19--Projected U.S. Imports and Exports of Oil and U.S. Oil Import Reductions Resulting From the Final
        Phase 2 Program in 2020, 2025, 2030, 2040 and 2050 Using Method B and Relative to a Flat Baseline
                                    [Millions of barrels per day (MMBD)] \a\
----------------------------------------------------------------------------------------------------------------
                                                                                U.S. oil
                                                                     U.S. net        U.S. net         import
              Year                   U.S. oil        U.S. oil         product         crude &       reductions
                                      exports         imports        imports *        product     from final  HD
                                                                                imports          Rules
----------------------------------------------------------------------------------------------------------------
2020............................            0.63            6.14           -2.80            2.71           0.007
2025............................            0.63            6.72           -3.24            2.85           0.162
2030............................            0.63            7.07           -3.56            2.88           0.405
2040............................            0.63            8.21           -4.26            3.32           0.721

2050............................            (**)            (**)            (**)            (**)           0.861
----------------------------------------------------------------------------------------------------------------
Notes:
* Negative U.S. Net Product Imports imply positive exports.
** The AEO 2015 only projects energy market and economic trends through 2040.

(2) Energy Security Implications
    In order to understand the energy security implications of reducing
U.S. oil imports, EPA has worked with Oak Ridge National Laboratory
(ORNL), which has developed approaches for evaluating the social costs
and energy security implications of oil use. The energy security
estimates provided below are based upon a methodology developed in a
peer-reviewed study entitled, ``The Energy Security Benefits of Reduced
Oil Use, 2006-2015'', completed in March 2008. This ORNL study is an
updated version of the approach used for estimating the energy security
benefits of U.S. oil import reductions developed in a 1997 ORNL
Report.\872\ For EPA and NHTSA rulemakings, the ORNL methodology is
updated periodically to account for forecasts of future energy market
and economic trends reported in the U.S. Energy Information
Administration's Annual Energy Outlook.
---------------------------------------------------------------------------

    \872\ Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and
Russell Lee, Oil Imports: An Assessment of Benefits and Costs, ORNL-
6851, Oak Ridge National Laboratory, November, 1997.
---------------------------------------------------------------------------

    When conducting this analysis, ORNL considered the full cost of
importing petroleum into the U.S. The full economic cost is defined to
include two components in addition to the purchase price of petroleum
itself. These are: (1) The higher costs for oil imports resulting from
the effect of U.S. demand on the world oil price (i.e., the ``demand''
or ``monopsony'' costs); and (2) the risk of reductions in U.S.
economic output and disruption to the U.S. economy caused by sudden
disruptions in the supply of imported oil to the U.S. (i.e.,
macroeconomic disruption/adjustment costs).
    The literature on energy security for the last two decades has
routinely combined the monopsony and the macroeconomic disruption
components when calculating the total value of the energy security
premium. However, in the context of using a global value for the Social
Cost of Carbon (SCC) the question arises: how should the energy
security premium be used when some benefits from these rules, such as
the benefits of reducing greenhouse gas emissions, are calculated from
a global perspective? Monopsony benefits represent avoided payments by
U.S. consumers to oil producers that result from a decrease in the
world oil price as the U.S. decreases its demand for oil. Although
there is clearly an overall benefit to the U.S. when considered from a
domestic perspective, the decrease in price due to decreased demand in
the U.S. also represents a loss to oil producing countries, one of
which is the U.S. Given the redistributive nature of this monopsony
effect from a global perspective, it is excluded in the energy security
benefits calculations for these final rules.
    In contrast, the other portion of the energy security premium, the
avoided U.S. macroeconomic disruption and adjustment cost that arises
from reductions in U.S. petroleum imports, does not have offsetting
impacts outside of the U.S., and, thus, is included in the energy
security benefits estimated for these final rules. To summarize, the
agencies have included only the avoided macroeconomic disruption
portion of the energy security benefits to estimate the monetary value
of the total energy security benefits of these final rules.
    For this rulemaking, ORNL updated the energy security premiums by
incorporating the most recent oil price forecast and energy market
trends, particularly regional oil supplies and demands, from the AEO
2015 into its model.\873\ ORNL developed energy security premium
estimates for a number of different years. Table IX-20 provides
estimates for energy security premiums for the years 2020, 2025, 2030
and 2040,\874\ as well as a breakdown of the components of the energy
security premiums for each year. The components of the energy security
premiums and their values are discussed below.
---------------------------------------------------------------------------

    \873\ Leiby, P., Factors Influencing Estimate of Energy Security
Premium for Heavy-Duty Phase 2 Final Rule, 11/1/2014, Oak Ridge
National Laboratory.
    \874\ AEO 2015 forecasts energy market trends and values only to
2040. The post-2040 energy security premium values are assumed to be
equal to the 2040 estimate.

                       Table IX-20--Energy Security Premiums in 2020, 2025, 2030 and 2040
                                                [2013$/Barrel] *
----------------------------------------------------------------------------------------------------------------
                                                                 Avoided  macroeconomic
            Year  (range)                 Monopsony (range)      disruption/adjustment       Total mid-point
                                                                     costs  (range)              (range)
----------------------------------------------------------------------------------------------------------------
2020.................................  $2.21 ($0.65-$3.59)....  $5.48 ($2.51-$8.92)....  $7.69 ($4.54-$11.14)
2025.................................  $2.59 ($0.76-$4.14)....  $6.30 ($2.92-$10.22)...  $8.89 ($5.22-$12.83)
2030.................................  $2.83 (0.83-$4.56).....  $7.26 ($3.40-$11.73)...  $10.09 ($5.90-$14.59)

2040.................................  $4.09 ($1.19-$6.67)....  $9.61 ($4.54-$15.39)...  $13.69 ($8.12-$19.64)
----------------------------------------------------------------------------------------------------------------
Note:
* Top values in each cell are the midpoints, the values in parentheses are the 90 percent confidence intervals.

(a) Effect of Oil Use on the Long-Run Oil Price
    The first component of the full economic costs of importing
petroleum into the U.S. follows from the effect of U.S. import demand
on the world oil price over the long-run. Because the U.S. is a
sufficiently large purchaser of global oil supplies, its purchases can
affect the world oil price. This monopsony power means that increases
in U.S. petroleum demand can cause the world price of crude oil to
rise, and conversely, that reduced U.S. petroleum demand can reduce the
world price of crude oil. Thus, one benefit of decreasing U.S. oil
purchases, due to improvements in the fuel efficiency of medium- and
heavy-duty vehicles, is the potential decrease in the crude oil price
paid for all crude oil purchased.
    There is disagreement in the literature about the magnitude of the
monopsony component, and its relevance for policy analysis. Brown and
Huntington (2013) \875\ for example, argue that the United States'
refusal to exercise its market power to reduce the world oil price does
not represent a proper externality, and that the monopsony component
should not be considered in calculations of the energy security
externality. However, they also note in their earlier discussion paper
(Brown and Huntington 2010) \876\ that this is a departure from the
traditional energy security literature, which includes sustained wealth
transfers associated with stable but higher-price oil markets. On the
other hand, Greene (2010) \877\ and others in prior literature (e.g.,
Toman 1993) \878\ have emphasized that the monopsony cost component is
policy-relevant because the world oil market is non-competitive and
strongly influenced by cartelized and government-controlled supply
decisions. Thus, while sometimes couched as an externality, Greene
notes that the monopsony component is best viewed as stemming from a
completely different market failure than an externality (Ledyard
2008),\879\ yet still implying marginal social costs to importers.
---------------------------------------------------------------------------

    \875\ Brown, Stephen P.A. and Hillard G. Huntington. 2013.
Assessing the U.S. Oil Security Premium. Energy Economics, vol. 38,
pp 118-127.
    \876\ Reassessing the Oil Security Premium. RFF Discussion Paper
Series, (RFF DP 10-05). doi: RFF DP 10-05
    \877\ Greene, D. L. 2010. Measuring energy security: Can the
United States achieve oil independence?, Energy Policy, 38(4), 1614-
1621. doi:10.1016/j.enpol.2009.01.041.
    \878\ Toman, M., 1993, The economics of energy security: theory,
evidence and policy, Chapter 25, Handbook of Natural Resources and
Energy Economics, Volume 3, pp. 1167-1218.
    \879\ Ledyard, John O. ``Market Failure.'' The New Palgrave
Dictionary of Economics. Second Edition. Eds. Steven N. Durlauf and
Lawrence E. Blume. Palgrave Macmillan, 2008.
---------------------------------------------------------------------------

    Recently, the Council on Foreign Relations (i.e., ``the Council'')
(2015) released a discussion paper that assesses NHTSA's analysis of
the benefits and costs of CAFE in a lower-oil-price world.\880\ In this
paper, the Council notes that while NHTSA cites the monopsony effect of
the CAFE standards for 2017-2025, NHTSA does not include it when
calculating the cost-benefit calculation for the rule. The Council
argues that the monopsony benefit should be included in the CAFE cost-
benefit analysis and that including the monopsony benefit is more
consistent with the legislators' intent in mandating CAFE standards in
the first place.
---------------------------------------------------------------------------

    \880\ Council on Foreign Relations, ``Automobile Fuel Economy
Standards in a Lower-Oil-Price World,'' Sivarm & Levi, November
2015.
---------------------------------------------------------------------------

    The recent National Academy of Science (NAS 2015) Report, ``Cost,
Effectiveness and the Deployment of Fuel Economy Technologies for
Light-Duty Vehicles,'' \881\ suggests that the agencies' logic about
not accounting for monopsony benefits is inaccurate. According to the
NAS, the fallacy lies in treating the two problems, oil dependence and
climate change, similarly. According to the NAS, ``Like national
defense, it [oil dependence] is inherently adversarial (i.e., oil
consumers against producers using monopoly power to raise prices). The
problem of climate change is inherently global and requires global
action. If each nation considered only the benefits to itself in
determining what actions to take to mitigate climate change, an
adequate solution could not be achieved. Likewise, if the U.S.
considers the economic harm its reduced petroleum use will do to
monopolistic oil producers it will not adequately address its oil
dependence problem. Thus, if the United States is to solve both of
these problems it must take full account of the costs and benefits of
each, using the appropriate scope for each problem.'' At this point in
time, we are continuing to exclude monopsony premiums for the cost
benefit analysis of these final rules, but we will be taking comment on
this issue in a near term future rulemaking.
---------------------------------------------------------------------------

    \881\ Transitions to Alternative Vehicles and Fuels,'' Committee
on Transitions to Alternative Vehicles and Fuels, National Research
Council, 2013.
---------------------------------------------------------------------------

    There is also a question about the ability of gradual, long-term
reductions, such as those resulting from these final rules, to reduce
the world oil price in the presence of OPEC's monopoly power. OPEC is
currently the world's marginal petroleum supplier, and could
conceivably respond to gradual reductions in U.S. demand with gradual
reductions in supply over the course of several years as the fuel
savings resulting from these rules grow. However, if OPEC opts for a
long-term strategy to preserve its market share, rather than maintain a
particular price level (as they have done recently in response to
increasing U.S. petroleum production), reduced demand will create
downward pressure on the global price. The Oak Ridge analysis assumes
that OPEC does respond to demand reductions over the long run, but
there is still a price effect in the model. Under the mid-case
behavioral assumption used in the premium calculations, OPEC responds
by gradually reducing supply to maintain market share (consistent with
the long-term self-interested strategy suggested by Gately (2004,
2007)).\882\
---------------------------------------------------------------------------

    \882\ Gately, Dermot, 2004. ``OPEC's Incentives for Faster
Output Growth,'' The Energy Journal, 25 (2):75-96; Gately, Dermot,
2007. ``What Oil Export Levels Should We Expect From OPEC?'', The
Energy Journal, 28(2):151-173.

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

(b) Macroeconomic Disruption Adjustment Costs
    The second component of the oil import premium, ``avoided
macroeconomic disruption/adjustment costs,'' arises from the effect of
oil imports on the expected cost of supply disruptions and accompanying
price increases. A sudden increase in oil prices triggered by a
disruption in world oil supplies has two main effects: (1) It increases
the costs of oil imports in the short-run and (2) it can lead to
macroeconomic contraction, dislocation and Gross Domestic Product (GDP)
losses. For example, ORNL estimates the combined value of these two
factors to be $6.30/barrel (2013$) when U.S. oil imports are reduced in
2025, with a range from $2.92/barrel to $10.22/barrel of imported oil
reduced.
    Since future disruptions in foreign oil supplies are an uncertain
prospect, each of the disruption cost components must be weighted by
the probability that the supply of petroleum to the U.S. will actually
be disrupted. Thus, the ``expected value'' of these costs--the product
of the probability that a supply disruption will occur and the sum of
costs from reduced economic output and the economy's abrupt adjustment
to sharply higher petroleum prices--is the relevant measure of their
magnitude. Further, when assessing the energy security value of a
policy to reduce oil use, it is only the change in the expected costs
of disruption that results from the policy that is relevant. The
expected costs of disruption may change from lowering the normal (i.e.,
pre-disruption) level of domestic petroleum use and imports, from any
induced alteration in the likelihood or size of disruption, or from
altering the short-run flexibility (e.g., elasticity) of petroleum use.
    By late 2015/early 2016, world oil prices were sharply lower than
in 2014. Future prices remain uncertain, but sustained markedly lower
oil prices can have mixed implications for U.S. energy security. Under
lower prices U.S. expenditures on oil consumption are lower, and they
are a less prominent component of the U.S. economy. This would lessen
the issue of imported oil as an energy security problem for the U.S. On
the other hand, sustained lower oil prices encourage greater oil
consumption, and reduce the competitiveness of new U.S. oil supplies
and alternative fuels. The AEO 2015 low oil price outlook, for example,
projects that by 2030 total U.S. petroleum supply would be 10 percent
lower and imports would be 78 percent higher than the AEO Reference
Case. Under the low-price case, 2030 prices are 35 percent lower, so
that import expenditures are 16 percent higher.
    A second potential proposed energy security effect of lower oil
prices is increased instability of supply, due to greater global
reliance on fewer suppling nations,\883\ and because lower prices may
increase economic and geopolitical instability in some supplier
nations.884 885 886 The International Monetary Fund reported
that low oil prices are creating substantial economic tension in the
Middle East oil producers on top of the economic costs of ongoing
conflicts, and noted the risk that Middle East countries including
Saudi Arabia could run out of financial assets without substantial
change in policy.\887\ The concern raised is that oil revenues are
essential for some exporting nations to fund domestic programs and
avoid domestic unrest.
---------------------------------------------------------------------------

    \883\ Fatih Birol, Executive Director of the International
Energy Agency, warns that prolonged lower oil prices would trigger
energy security concerns by increasing reliance on a small number of
low-cost producers ``or risk a sharp rebound in price if investment
falls short.'' ``It would be a grave mistake to index our attention
to energy security to changes in the oil price,'' Birol said. ``Now
is not the time to relax. Quite the opposite: a period of low oil
prices is the moment to reinforce our capacity to deal with future
energy security threats.'' Hussain, Y. (2015). ``Grave mistake'' to
be complacent on energy security, International Energy Agency warns.
Financial Post, (November 10). Retrieved from http://business.financialpost.com/news/energy/grave-mistake-to-be-complacent-on-energy-security-international-energy-agency-warns.
    \884\ Batovic, A. (2015). Low oil prices fuel political and
economic instability. Global Risk Insights, 18-19. Retrieved from
http://globalriskinsights.com/2015/09/low-oil-prices-fuel-political-and-economic-instability/.
    \885\ Monaldi, F. (2015). The Impact of the Decline in Oil
Prices on the Economics, Politics and Oil Industry of Venezuela.
Columbia Center on Global Energy Policy Discussion Papers,
(September). Retrieved from http://energypolicy.columbia.edu/sites/default/files/energy/Impact of the Decline in Oil Prices on
Venezuela, September 2015.pdf.
    \886\ Even, S., & Guzansky, Y. (2015). Falling oil prices and
Saudi stability--Opinion. Jerusalem Post, (September 30). Retrieved
from http://www.jpost.com/Opinion/Falling-oil-prices-and-Saudi-stability-419534.
    \887\ International Monetary Fund (IMF). (2015). IMF Regional
Economic Outlook--Middle East and Central Asia. Regional Economic
Outlook (Vol. 33). Tomkiw, L. (2015). Oil Rich Saudi Arabia Running
Out Of Assets? IMF Report Says It's Possible In Next 5 Years.
International Business Times, October 21, 19-22. Retrieved from
http://www.ibtimes.com/oil-rich-saudi-arabia-running-out-assets-imf-report-says-its-possible-next-5-years-215017.
---------------------------------------------------------------------------

    The Competitive Enterprise Institute (CEI) and others argue that
there are little, if any, energy security benefits associated with
these rules. In large part CEI argues that oil supplies are plentiful
and that current oil prices are low so that reduced consumption of
petroleum products due to these rules would have no effect on energy
security. However, the discussion of current low oil prices (``lowest
Labor Day gasoline prices in a decade'') does not assure the absence of
future oil supply shocks or price shocks, or even speak to their
reduced likelihood. CEI points out that the current low oil prices have
been observed before as recently as a decade ago, as they have in more
than one instance before that. For example, oil prices were even lower
in 1999. But in the intervening periods, oil supply and price shocks
have continued to recur, and the recent price record only amplifies
oil's high historical price volatility.
    Also, sharply lower world oil prices do not clearly imply greater
energy security for the U.S. Current low world oil prices may reduce
the U.S.'s fracking industry's tight oil production (as CEI points
out), or other sources of oil supplies around the world. Some have
hypothesized that reduction in oil production outside of OPEC may be
the objective of some OPEC producers. With low oil prices, U.S.' oil
import share over time might be larger, increasing the U.S.' dependence
on imported oil.
    Securing America's Future Energy (SAFE), Operation Free and the
Investor Network on Climate Risk agree that these rules do improve
America's energy security. SAFE goes on to state that several policy
options should be included in these rules to further enhance energy
security. The agencies agree that these rules enhances America's energy
security, but do not have information to evaluate the policy options
that SAFE proposes.
    The recent economics literature on whether oil shocks are the
threat to economic stability that they once were is mixed. Some of the
current literature asserts that the macroeconomic component of the
energy security externality is small. For example, the National
Research Council (2009) argued that the non-environmental externalities
associated with dependence on foreign oil are small, and potentially
trivial.\888\ Analyses by Nordhaus (2007) and Blanchard and Gali (2010)
question the impact of more recent oil price shocks on the
economy.\889\ They were motivated by

attempts to explain why the economy actually expanded immediately after
the last shocks, and why there was no evidence of higher energy prices
being passed on through higher wage inflation. Using different
methodologies, they conclude that the economy has largely gotten over
its concern with dramatic swings in oil prices.
---------------------------------------------------------------------------

    \888\ National Research Council, 2009. Hidden Costs of Energy:
Unpriced Consequences of Energy Production and Use. National Academy
of Science, Washington, DC.
    \889\ See, William Nordhaus, ``Who's Afraid of a Big Bad Oil
Shock?'', available at http://aida.econ.yale.edu/~nordhaus/homepage/
Big_Bad_Oil_Shock_Meeting.pdf, and Olivier Blanchard and Jordi Gali,
``The macroeconomic Effects of Oil price Shocks: Why are the 2000s
so different from the 1970s?'', pp. 373-421, in The International
Dimensions of Monetary Policy, Jordi Gali and Mark Gertler, editors,
University of Chicago Press, February 2010, available at http://www.nber.org/chapters/c0517.pdf.
---------------------------------------------------------------------------

    One reason, according to Nordhaus, is that monetary policy has
become more accommodating to the price impacts of oil shocks. Another
is that consumers have simply decided that such movements are
temporary, and have noted that price impacts are not passed on as
inflation in other parts of the economy. He also notes that real
changes to productivity due to oil price increases are incredibly
modest, \890\ and that the general direction of the economy matters a
great deal regarding how the economy responds to a shock. Estimates of
the impact of a price shock on aggregate demand are insignificantly
different from zero.
---------------------------------------------------------------------------

    \890\ In fact, ``. . . energy-price changes have no effect on
multifactor productivity and very little effect on labor
productivity.'' Page 19. He calculates the productivity effect of a
doubling of oil prices as a decrease of 0.11 percent for one year
and 0.04 percent a year for ten years. Page 5. (The doubling
reflects the historical experience of the post-war shocks, as
described in Table 7.1 in Blanchard and Gali, p. 380).
---------------------------------------------------------------------------

    Blanchard and Gali (2010) contend that improvements in monetary
policy (as noted above), more flexible labor markets, and lessening of
energy intensity in the economy, combined with an absence of concurrent
shocks, all contributed to lessen the impact of oil shocks after 1980.
They find ``. . . the effects of oil price shocks have changed over
time, with steadily smaller effects on prices and wages, as well as on
output and employment.'' \891\ In a comment at the chapter's end, this
work is summarized as follows: ``The message of this chapter is thus
optimistic in that it suggests a transformation in U.S. institutions
has inoculated the economy against the responses that we saw in the
past.''
---------------------------------------------------------------------------

    \891\ Blanchard and Gali, p. 414.
---------------------------------------------------------------------------

    At the same time, the implications of the ``Shale Oil Revolution''
are now being felt in the international markets, with current prices at
four year lows. Analysts generally attribute this result in part to the
significant increase in supply resulting from U.S. production, which
has put liquid petroleum production roughly on par with Saudi Arabia.
The price decline is also attributed to the sustained reductions in
U.S. consumption and global demand growth from fuel efficiency policies
and previously high oil prices. The resulting decrease in foreign
imports, down to about one-third of domestic consumption (from 60
percent in 2005, for example \892\), effectively permits U.S. supply to
act as a buffer against artificial or other supply restrictions (the
latter due to conflict or a natural disaster, for example).
---------------------------------------------------------------------------

    \892\ See, Oil price Drops on Oversupply, http://www.oil-price.net/en/articles/oil-price-drops-on-oversupply.php, 10/6/2014.
---------------------------------------------------------------------------

    However, other papers suggest that oil shocks, particularly sudden
supply shocks, remain a concern. Both Blanchard and Gali's and Nordhaus
work were based on data and analysis through 2006, ending with a period
of strong global economic growth and growing global oil demand. The
Nordhaus work particularly stressed the effects of the price increase
from 2002-2006 that were comparatively gradual (about half the growth
rate of the 1973 event and one-third that of the 1990 event). The
Nordhaus study emphasizes the robustness of the U.S. economy during a
time period through 2006. This time period was just before rapid
further increases in the price of oil and other commodities with oil
prices more-than-doubling to over $130/barrel by mid-2008, only to drop
after the onset of the largest recession since the Great Depression.
    Hamilton (2012) reviewed the empirical literature on oil shocks and
suggested that the results are mixed, noting that some work (e.g.
Rasmussen and Roitman (2011) finds less evidence for economic effects
of oil shocks, or declining effects of shocks (Blanchard and Gali
2010), while other work continues to find evidence regarding the
economic importance of oil shocks. For example, Baumeister and Peersman
(2011) found that an oil price increase had a decreasing effect over
time. But they note that with a declining price-elasticity of demand
that a given physical oil disruption would have a bigger effect on
price and a similar effect on output as in the earlier data.\893\
Hamilton observes that ``a negative effect of oil prices on real output
has also been reported for a number of other countries, particularly
when nonlinear functional forms have been employed''. Alternatively,
rather than a declining effect, Ramey and Vine (2010) \894\ found
``remarkable stability in the response of aggregate real variables to
oil shocks once we account for the extra costs imposed on the economy
in the 1970s by price controls and a complex system of entitlements
that led to some rationing and shortages.''
---------------------------------------------------------------------------

    \893\ Hamilton, J. D. (2012). Oil Prices, Exhaustible Resources,
and Economic Growth. In Handbook of Energy and Climate Change.
Retrieved from http://econweb.ucsd.edu/~jhamilto/
handbook_climate.pdf.
    \894\ Ramey, V. and Vine, D., 2010, ``Oil, Automobiles, and the
U.S. Economy: How Much have Things Really Changed?'' National Bureau
of Economic Research Working Papers, WP 16067. Retrieved from http://www.nber.org/papers/w16067.pdf [EPA-HQ-OAR-2014-0827-0601].
---------------------------------------------------------------------------

    Some of the recent literature on oil price shocks has emphasized
that economic impacts depend on the nature of the oil shock, with
differences between price increases caused by sudden supply loss and
those caused by rapidly growing demand. Most recent analyses of oil
price shocks have confirmed that ``demand-driven'' oil price shocks
have greater effects on oil prices and tend to have positive effects on
the economy while ``supply-driven'' oil shocks still have negative
economic impacts (Baumeister, Peersman and Van Robays (2010)).\895\ A
recent paper by Kilian and Vigfusson (2014), \896\ for example,
assigned a more prominent role to the effects of price increases that
are unusual, in the sense of being beyond range of recent experience.
Kilian and Vigfusson also conclude that the difference in response to
oil shocks may well stem from the different effects of demand- and
supply-based price increases: ``One explanation is that oil price
shocks are associated with a range of oil demand and oil supply shocks,
some of which stimulate the U.S. economy in the short run and some of
which slow down U.S. growth (see Kilian (2009)). How recessionary the
response to an oil price shock is thus depends on the average
composition of oil demand and oil supply shocks over the sample
period.''
---------------------------------------------------------------------------

    \895\ Baumeister, C., Peersman, G., Van Robays, I., 2010, ``The
Economic Consequences of Oil Shocks: Differences across Countries
and Time'', Workshop and Conference on Inflation Challenges in the
Era of Relative Price Shocks.
    \896\ Kilian, L., Vigfusson, R.J., 2014, ``The Role of Oil Price
Shocks in Causing U.S. Recessions'', Board of Governors of the
Federal Reserve System. International Finance Discussion Papers.
---------------------------------------------------------------------------

    The general conclusion that oil supply-driven shocks reduce
economic output is also reached in a recently published paper by Cashin
et al. (2014) \897\ for 38 countries from 1979-2011. ``The results
indicate that the economic consequences of a supply-driven oil-price
shock are very different from those of an oil-demand shock

driven by global economic activity, and vary for oil-importing
countries compared to energy exporters,'' and ``oil importers
[including the U.S.] typically face a long-lived fall in economic
activity in response to a supply-driven surge in oil prices'' but
almost all countries see an increase in real output for an oil-demand
disturbance. Note that the energy security premium calculation in this
analysis is based on price shocks from potential future supply events
only.
---------------------------------------------------------------------------

    \897\ Cashin, P., Mohaddes, K., Raissi, Maziar, and Raissi, M.,
2014, ``The differential effects of oil demand and supply shocks on
the global economy''. Energy Economics.
---------------------------------------------------------------------------

    Finally, despite continuing uncertainty about oil market behavior
and outcomes and the sensitivity of the U.S. economy to oil shocks, it
is generally agreed that it is beneficial to reduce petroleum fuel
consumption from an energy security standpoint. It is not just imports
alone, but both imports and consumption of petroleum from all sources
and their role in economic activity, that may expose the U.S. to risk
from price shocks in the world oil price. Reducing fuel consumption
reduces the amount of domestic economic activity associated with a
commodity whose price depends on volatile international markets.
(c) Cost of Existing U.S. Energy Security Policies
    The last often-identified component of the full economic costs of
U.S. oil imports are the costs to the U.S. taxpayers of existing U.S.
energy security policies. The two primary examples are maintaining the
Strategic Petroleum Reserve (SPR) and maintaining a military presence
to help secure a stable oil supply from potentially vulnerable regions
of the world. The SPR is the largest stockpile of government-owned
emergency crude oil in the world. Established in the aftermath of the
1973/1974 oil embargo, the SPR provides the U.S. with a response option
should a disruption in commercial oil supplies threaten the U.S.
economy. It also allows the U.S. to meet part of its International
Energy Agency obligation to maintain emergency oil stocks, and it
provides a national defense fuel reserve. While the costs for building
and maintaining the SPR are more clearly related to U.S. oil use and
imports, historically these costs have not varied in response to
changes in U.S. oil import levels. Thus, while the effect of the SPR in
moderating price shocks is factored into the ORNL analysis, the cost of
maintaining the SPR is excluded.
    U.S. military costs are excluded from the analysis performed by
ORNL because their attribution to particular missions or activities is
difficult, and because it is not clear that these outlays would decline
in response to incremental reductions in U.S. oil imports. Most
military forces serve a broad range of security and foreign policy
objectives. The agencies also recognize that attempts to attribute some
share of U.S. military costs to oil imports are further challenged by
the need to estimate how those costs might vary with incremental
variations in U.S. oil imports.
    In the proposal to these rules, the agencies solicited comments on
quantifying the military benefits from reduced U.S. imports of oil. The
California Air Resources Board (CARB) notes that the National Research
Council (NRC) \898\ attempted to estimate the military costs associated
with U.S. imports and consumption of petroleum. The NRC cited estimates
of the national defense costs of oil dependence from the literature
that range from less than $5 to $50 billion per year or more. Assuming
a range of approximate range of $10 to $50 billion per year, the NRC
divided national defense costs by a projected U.S. consumption rate of
approximately 6.4 billion barrels per year (EIA, 2012). This procedure
yielded a range of average national defense cost of $1.50-$8.00 per
barrel (rounded to the nearest $0.50), with a mid-point of $5/barrel
(in 2009$). The agencies acknowledge this NRC study, but have not
included the estimates as part of the cost-benefit analysis for these
rules.
---------------------------------------------------------------------------

    \898\ National Research Council, ``Transitions to alternative
vehicles and fuels,'' 2013.
---------------------------------------------------------------------------

(3) Energy Security Benefits of This Program
    Using the ORNL ``oil premium'' methodology, updating world oil
price values and energy trends using AEO 2015 and using the estimated
fuel savings from these final rules estimated from the MOVES/CAFE
models, the agencies have calculated the annual energy security
benefits of these final rules through 2050.\899\ Since the agencies are
taking a global perspective with respect to valuing greenhouse gas
benefits from the rules, only the avoided macroeconomic adjustment/
disruption portion of the energy security premium is used in the energy
security benefits estimates present below. These results are shown
below in Table IX-21. The agencies have also calculated the net present
value at 3 percent and 7 percent discount rates of model year lifetime
benefits associated with energy security; these values are presented in
Table IX-22.
---------------------------------------------------------------------------

    \899\ In order to determine the energy security benefits beyond
2040, we use the 2040 energy security premium multiplied by the
estimate fuel savings from the final rule. Since the AEO 2015 only
goes to 2040, we only calculate energy security premiums to 2040.

 Table IX-21--Annual U.S. Energy Security Benefits of the Final Program
  and Net Present Values at 3% and 7% Discount Rates Using Method B and
             Relative to a Flat Baseline for Final HDV Rules
                       [In Millions of 2013$] \a\
------------------------------------------------------------------------
                                                                Benefits
                             Year                               (2013$)
------------------------------------------------------------------------
2018.........................................................         $4
2019.........................................................          9
2020.........................................................         14
2021.........................................................         55
2022.........................................................        109
2023.........................................................        171
2024.........................................................        268
2025.........................................................        372
2026.........................................................        482
2027.........................................................        627
2028.........................................................        775
2029.........................................................        923
2030.........................................................      1,074
2035.........................................................      1,847
2040.........................................................      2,533
2050.........................................................      3,025
NPV, 3%......................................................     24,716
NPV, 7%......................................................     10,050
------------------------------------------------------------------------

Table IX-22--Discounted Model Year Lifetime Energy Security Benefits Due
   to the Final Program at 3% and 7% Discount Rates Using Method B and
             Relative to a Flat Baseline for Final HDV Rules
                         [Millions of 2013$] \a\
------------------------------------------------------------------------
                                                        3%         7%
                   Calendar year                     Discount   Discount
                                                       rate       rate
------------------------------------------------------------------------
2018..............................................        $30        $21
2019..............................................         29         20
2020..............................................         28         18
2021..............................................        485        294
2022..............................................        520        304
2023..............................................        552        311
2024..............................................        849        461
2025..............................................        886        464
2026..............................................        917        463
2027..............................................      1,183        577
2028..............................................      1,182        555
2029..............................................      1,184        536
------------------------------------------------------------------------
    Sum...........................................      7,844      4,026
------------------------------------------------------------------------

J. Other Impacts

(1) Costs of Noise, Congestion and Crashes Associated With Additional
(Rebound) Driving
    Although it provides benefits to drivers as described above,
increased vehicle use associated with the rebound effect also
contributes to increased

traffic congestion, motor vehicle crashes, and highway noise. Depending
on how the additional travel is distributed over the day and where it
takes place, additional vehicle use can contribute to traffic
congestion and delays by increasing the number of vehicles using
facilities that are already heavily traveled. These added delays impose
higher costs on drivers and other vehicle occupants in the form of
increased travel time and operating expenses. At the same time, this
additional travel also increases costs associated with traffic crashes
and vehicle noise.
    The agencies estimate these costs using the same methodology as
used in the two light-duty and the HD Phase 1 rule analyses, which
relies on estimates of congestion, crash, and noise costs imposed by
automobiles and light trucks developed by the Federal Highway
Administration to estimate these increased external costs caused by
added driving.\900\ We provide the details behind the estimates in
Chapter 8.7 of the RIA. Table IX-23 presents the estimated annual
impacts associated with crash, congestion and noise along with net
present values at both 3 percent and 7 percent discount rates. Table
IX-24 presents the estimated discounted model year lifetime impacts
associated with crashes, congestion and noise. The methodology used in
this final rule is the same as that used in the proposal, except that
costs were updated to 2013 dollars.
---------------------------------------------------------------------------

    \900\ These estimates were developed by FHWA for use in its 1997
Federal Highway Cost Allocation Study; http://www.fhwa.dot.gov/policy/hcas/final/index.htm (last accessed July 8, 2012).

 Table IX-23--Annual Costs Associated With Crashes, Congestion and Noise
  and Net Present Values at 3% and 7% Discount Rates Using Method B and
                      Relative to the Flat Baseline
                         [Millions of 2013$] \a\
------------------------------------------------------------------------
                                                              Costs of
                                                              crashes,
                       Calendar year                         congestion,
                                                              and noise
------------------------------------------------------------------------
2018......................................................            $0
2019......................................................             0
2020......................................................             0
2021......................................................            99
2022......................................................           139
2023......................................................           178
2024......................................................           216
2025......................................................           252
2026......................................................           285
2027......................................................           317
2028......................................................           345
2029......................................................           372
2030......................................................           396
2035......................................................           487
2040......................................................           541
2050......................................................           604
NPV, 3%...................................................         6,755
NPV, 7%...................................................         3,070
------------------------------------------------------------------------
Note:
\a\ For an explanation of analytical Methods A and B, please see Section
  I.D; for an explanation of the flat baseline, 1a, and dynamic
  baseline, 1b, please see Section X.A.1.

Table IX-24--Discounted Model Year Lifetime Costs of Crashes, Congestion
and Noise at 3% and 7% Discount Rates Using Method B and Relative to the
                              Flat Baseline
                         [Millions of 2013$] \a\
------------------------------------------------------------------------
                                                        3%         7%
                   Calendar year                     discount   Discount
                                                       rate       rate
------------------------------------------------------------------------
2018..............................................       $124        $80
2019..............................................        140         89
2020..............................................        158        100
2021..............................................        343        215
2022..............................................        333        201
2023..............................................        323        187
2024..............................................        319        178
2025..............................................        313        168
2026..............................................        305        158
2027..............................................        297        148
2028..............................................        289        139
2029..............................................        283        131
                                                   ---------------------
    Sum...........................................      3,227      1,793
------------------------------------------------------------------------
Note:
\a\ For an explanation of analytical Methods A and B, please see Section
  I.D; for an explanation of the flat baseline, 1a, and dynamic
  baseline, 1b, please see Section X.A.1.

(2) Benefits Associated With Reduced Refueling Time
    By reducing the frequency with which drivers typically refuel their
vehicles and by extending the upper limit of the range that can be
traveled before requiring refueling (i.e., future fuel tank sizes
remain constant), savings will be realized associated with less time
spent refueling vehicles. Alternatively, refill intervals may remain
the same (i.e., future fuel tank sizes get smaller), resulting in the
same number of refills as today but less time spent per refill because
there will be less fuel to refill. The agencies have estimated this
impact using the former approach--by assuming that future tank sizes
remain constant.
    The savings in refueling time are calculated as the total amount of
time the driver of a typical truck in each class will save each year as
a consequence of pumping less fuel into the vehicle's tank. The
calculation does not include any reduction in time spent searching for
a fueling station or other time spent at the station; it is assumed
that time savings occur only when truck operators are actually
refueling their vehicles.
    The calculation uses the reduced number of gallons consumed by
truck type and divides that value by the tank volume and refill amount
to get the number of refills, then multiplies that by the time per
refill to determine the number of hours saved in a given year. The
calculation then applies DOT-recommended values of travel time savings
to convert the resulting time savings to their economic value,
including a 1.2 percent growth rate in those time savings going
forward.\901\ The input metrics used in the analysis are presented in
greater detail in RIA Chapter 9.7. The annual benefits associated with
reduced refueling time are shown in Table IX-25 along with net present
values at both 3 percent and 7 percent discount rates. The discounted
model year lifetime benefits are shown in Table IX-26. The methodology
used in this final rule is the same as that used in the proposal,
except that costs have been updated to 2013 dollars.
---------------------------------------------------------------------------

    \901\ U.S. Department of Transportation, Valuation of Travel
Guidance, July 9, 2014, at page 14.

 Table IX-25--Annual Refueling Benefits and Net Present Values at 3% and
   7% Discount Rates Using Method B and Relative to the Flat Baseline
                          [Millions of 2013$] a
------------------------------------------------------------------------
                                                              Refueling
                       Calendar year                           benefits
------------------------------------------------------------------------
2018.......................................................           $1
2019.......................................................            3
2020.......................................................            5
2021.......................................................           27
2022.......................................................           56
2023.......................................................           91
2024.......................................................          144
2025.......................................................          202
2026.......................................................          264
2027.......................................................          342
2028.......................................................          420
2029.......................................................          495
2030.......................................................          570
2035.......................................................          895
2040.......................................................        1,141

2050.......................................................        1,497
NPV, 3%....................................................       11,985
NPV, 7%....................................................        4,925
------------------------------------------------------------------------
Note:
\a\ For an explanation of analytical Methods A and B, please see Section
  I.D; for an explanation of the flat baseline, 1a, and dynamic
  baseline, 1b, please see Section X.A.1.

  Table IX-26--Discounted Model Year Lifetime Refueling Benefits Using
               Method B and Relative to the Flat Baseline
                          [Millions of 2013$] a
------------------------------------------------------------------------
                                                        3%         7%
                    Model year                       discount   discount
                                                       rate       rate
------------------------------------------------------------------------
2018..............................................         $9         $7
2019..............................................          9          6
2020..............................................          8          6
2021..............................................        218        135
2022..............................................        255        152
2023..............................................        290        166
2024..............................................        428        236
2025..............................................        461        245
2026..............................................        491        251
2027..............................................        609        300
2028..............................................        601        285
2029..............................................        594        272
                                                   ---------------------
Sum...............................................      3,976      2,061
------------------------------------------------------------------------
Note:
\a\ For an explanation of analytical Methods A and B, please see Section
  I.D; for an explanation of the flat baseline, 1a, and dynamic
  baseline, 1b, please see Section X.A.1.

(3) Benefits of Increased Travel Associated With Rebound Driving
    The increase in travel associated with the rebound effect produces
additional benefits to vehicle owners and operators, which reflect the
value of the added (or more desirable) social and economic
opportunities that become accessible with additional travel. The
analysis estimates the economic benefits from increased rebound-effect
driving as the sum of fuel expenditures incurred plus the consumer
surplus from the additional accessibility it provides. As evidenced by
the fact that vehicles make more frequent or longer trips when the cost
of driving declines, the benefits from this added travel exceed added
expenditures for the fuel consumed. The amount by which the benefits
from this increased driving exceed its increased fuel costs measures
the net benefits from the additional travel, usually referred to as
increased consumer surplus.
    The agencies' analysis estimates the economic value of the
increased consumer surplus provided by added driving using the
conventional approximation, which is one half of the product of the
decline in vehicle operating costs per vehicle-mile and the resulting
increase in the annual number of miles driven. Because it depends on
the extent of improvement in fuel economy, the value of benefits from
increased vehicle use changes by model year and varies among
alternative standards. Under even those alternatives that will impose
the highest standards, however, the magnitude of the consumer surplus
from additional vehicle use represents a small fraction of this
benefit.
    The annual benefits associated with increased travel are shown in
Table IX-27 along with net present values at both 3 percent and 7
percent discount rates. The discounted model year lifetime benefits are
shown in Table IX-28. The methodology used in this final rule is the
same as that used in the proposal, except that costs have been updated
to 2013 dollars.

 Table IX-27--Annual Value of Increased Travel and Net Present Values at
    3% and 7% Discount Rates Using Method B and Relative to the Flat
                                Baseline
                          [Millions of 2013$] a
------------------------------------------------------------------------
                                                             Benefits of
                       Calendar year                          increased
                                                               travel
------------------------------------------------------------------------
2018......................................................            $0
2019......................................................             0
2020......................................................             0
2021......................................................           298
2022......................................................           417
2023......................................................           534