Combined............................................            14.0            24.1            33.7            45.4            58.4           175.6
--------------------------------------------------------------------------------------------------------------------------------------------------------

            Table I.C.1-6b--NHTSA Discounted Benefits ($billion) Under the CAFE Standards (With FFV Credits, Using a 7 Percent Discount Rate)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2012            2013            2014            2015            2016            Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
Passenger Cars..........................................             6.1            11.1            15.5            20.7            27.6            80.9
Light Trucks............................................             5.0             8.2            11.5            15.6            19.3            59.7
                                                         -----------------------------------------------------------------------------------------------

    Combined............................................            11.2            19.3            27.0            36.4            46.9           140.7
--------------------------------------------------------------------------------------------------------------------------------------------------------

    NHTSA attributes most of these benefits--about $143 billion (at a
3% discount rate and excluding consideration of FFV credits), as noted
above--to reductions in fuel consumption, valuing fuel (for societal
purposes) at the future pre-tax prices projected in the Energy
Information Administration's (AEO's) reference case forecast from the
Annual Energy Outlook (AEO) 2010 Early Release. NHTSA's Final
Regulatory Impact Analysis (FRIA) accompanying this rule presents a
detailed analysis of specific benefits of the rule.

Table I.C.1-7--Summary of Benefits Fuel Savings and CO2 Emissions Reduction Due to the Rule (Before FFV Credits)
----------------------------------------------------------------------------------------------------------------
                                                                        Monetized value (discounted)
                                            Amount        ------------------------------------------------------
                                                             3% discount rate            7% discount rate
----------------------------------------------------------------------------------------------------------------
Fuel savings......................  61.0 billion gallons.  $143.0 billion......  $112.0 billion.
CO2 emissions reductions..........  655 mmt..............  $14.5 billion.......  $14.5 billion.
----------------------------------------------------------------------------------------------------------------

    NHTSA estimates that the increases in technology application
necessary to achieve the projected improvements in fuel economy will
entail considerable monetary outlays. The agency estimates that
incremental costs for achieving its standards--that is, outlays by
vehicle manufacturers over and above those required to comply with the
MY 2011 CAFE standards--will total about $52 billion (i.e., during MYs
2012-2016).

                      Table I.C.1-8--NHTSA Incremental Technology Outlays ($billion) Under the CAFE Standards (Before FFV Credits)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2012            2013            2014            2015            2016            Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
Passenger Cars..........................................             4.1             5.4             6.9             8.2             9.5            34.2
Light Trucks............................................             1.8             2.5             3.7             4.3             5.4            17.6
                                                         -----------------------------------------------------------------------------------------------
    Combined............................................             5.9             7.9            10.5            12.5            14.9            51.7
--------------------------------------------------------------------------------------------------------------------------------------------------------

    NHTSA estimates that use of FFV credits could significantly reduce
these outlays:

                         Table I.C.1-9--NHTSA Incremental Technology Outlays ($billion) under CAFE Standards (With FFV Credits)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2012            2013            2014            2015            2016            Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
Passenger Cars..........................................             2.6             3.6             4.8             6.1             7.5            24.6
Light Trucks............................................             1.1             1.5             2.5             3.4             4.4            12.9
                                                         -----------------------------------------------------------------------------------------------
    Combined............................................             3.7             5.1             7.3             9.5            11.9            37.5
--------------------------------------------------------------------------------------------------------------------------------------------------------

    The agency projects that manufacturers will recover most or all of
these additional costs through higher selling prices for new cars and
light trucks. To allow manufacturers to recover these increased outlays
(and, to a much lesser extent, the civil penalties that some companies
are expected to pay for noncompliance), the agency estimates that the
standards would lead to increases in average new vehicle prices ranging
from $457 per vehicle in MY 2012 to $985 per vehicle in MY 2016:

  Table I.C.1-10--NHTSA Incremental Increases in Average New Vehicle Costs ($) Under CAFE Standards (Before FFV
                                                    Credits)
----------------------------------------------------------------------------------------------------------------
                                       2012            2013            2014            2015            2016
----------------------------------------------------------------------------------------------------------------
Passenger Cars..................             505             573             690             799             907
Light Trucks....................             322             416             621             752             961
                                 -------------------------------------------------------------------------------

    Combined....................             434             513             665             782             926
----------------------------------------------------------------------------------------------------------------

    NHTSA estimates that use of FFV credits could significantly reduce
these costs, especially in earlier model years:

   Table I.C.1-11--NHTSA Incremental Increases in Average New Vehicle Costs ($) Under CAFE Standards (With FFV
                                                    Credits)
----------------------------------------------------------------------------------------------------------------
                                       2012            2013            2014            2015            2016
----------------------------------------------------------------------------------------------------------------
Passenger Cars..................             303             378             481             593             713
Light Trucks....................             194             260             419             581             784
                                 -------------------------------------------------------------------------------
    Combined....................             261             333             458             589             737
----------------------------------------------------------------------------------------------------------------

    NHTSA estimates, therefore, that the total benefits of these CAFE
standards will be more than three times the magnitude of the
corresponding costs. As a consequence, its standards would produce net
benefits of $130.7 billion at a 3 percent discount rate (with FFV
credits, $138.2 billion) or $94.5 billion at a 7 percent discount rate
over the useful lives of vehicles sold during MYs 2012-2016.
2. Summary of Costs and Benefits of EPA's GHG Standards
    EPA has analyzed in detail the costs and benefits of the final GHG
standards. Table I.C.2-1 shows EPA's estimated lifetime discounted
cost, benefits and net benefits for all vehicles projected to be sold
in model years 2012-2016. It is important to note that there is
significant overlap in costs and benefits for NHTSA's CAFE program and
EPA's GHG program and therefore combined program costs and benefits are
not a sum of the individual programs.

 Table I.C.2-1--EPA's Estimated 2012-2016 Model Year Lifetime Discounted
Costs, Benefits, and Net Benefits Assuming the $21/Ton SCC Value a b c d
                             [2007 dollars]
------------------------------------------------------------------------
                     3% Discount rate                         $Billions
------------------------------------------------------------------------
Costs.....................................................          51.5
Benefits..................................................         240
Net Benefits..............................................         189
------------------------------------------------------------------------
                     7% Discount rate
------------------------------------------------------------------------
Costs.....................................................          51.5
Benefits..................................................         192
Net Benefits..............................................         140
------------------------------------------------------------------------
\a\ Although EPA estimated the benefits associated with four different
  values of a one ton GHG reduction ($5, $21, $35, $65), for the
  purposes of this overview presentation of estimated costs and benefits
  EPA is showing the benefits associated with the marginal value deemed
  to be central by the interagency working group on this topic: $21 per
  ton of CO2e, in 2007 dollars and 2010 emissions. The $21/ton value
  applies to 2010 CO2 emissions and grows over time.
\b\ As noted in Section III.H, SCC increases over time. The $21/ton
  value applies to 2010 CO2 emissions and grows larger over time.
\c\ Note that net present value of reduced GHG emissions is calculated
  differently than other benefits. The same discount rate used to
  discount the value of damages from future emissions (SCC at 5, 3, and
  2.5 percent) is used to calculate net present value of SCC for
  internal consistency. Refer to Section III.H for more detail.
\d\ Monetized GHG benefits exclude the value of reductions in non-CO2
  GHG emissions (HFC, CH4 and N2O) expected under this final rule.
  Although EPA has not monetized the benefits of reductions in these non-
  CO2 emissions, the value of these reductions should not be interpreted
  as zero. Rather, the reductions in non-CO2 GHGs will contribute to
  this rule's climate benefits, as explained in Section III.F.2. The SCC
  TSD notes the difference between the social cost of non-CO2 emissions
  and CO2 emissions, and specifies a goal to develop methods to value
  non-CO2 emissions in future analyses.

    Table I.C.2-2 shows EPA's estimated lifetime fuel savings and
CO2 equivalent emission reductions for all vehicles sold in
the model years 2012-2016. The values in Table I.C.2-2 are projected
lifetime totals for each model year and are not discounted. As
documented in EPA's Final RIA, the potential credit transfer between
cars and trucks may change the distribution of the fuel savings and GHG
emission impacts between cars and trucks. As discussed above with
respect to NHTSA's CAFE standards, it is important to note that NHTSA's
CAFE standards and EPA's GHG standards will both be in effect, and each
will lead to increases in average fuel economy and reductions in
CO2 emissions. The two agencies' standards together comprise
the National Program, and this discussion of costs and benefits of
EPA's GHG standards does not change the fact that both the CAFE and GHG
standards, jointly, are the source of the benefits and costs of the
National Program.

        Table I.C.2-2--EPA's Estimated 2012-2016 Model Year Lifetime Fuel Saved and GHG Emissions Avoided
----------------------------------------------------------------------------------------------------------------
                                             2012        2013        2014        2015        2016        Total
----------------------------------------------------------------------------------------------------------------
Cars..................  Fuel (billion           4.0         5.5         7.3        10.5        14.3        41.6
                         gallons).
                        Fuel (billion           0.10        0.13        0.17        0.25        0.34        0.99
                         barrels).
                        CO2 EQ (mmt)....       49.3        68.5        92.7       134         177         521

Light Trucks..........  Fuel (billion           3.3         5.0         6.6         9.0        12.2        36.1
                         gallons).
                        Fuel (billion           0.08        0.12        0.16        0.21        0.29        0.86
                         barrels).
                        CO2 EQ (mmt)....       39.6        61.7        81.6       111         147         441
                       -----------------------------------------------------------------------------------------
    Combined..........  Fuel (billion           7.3        10.5        13.9        19.5        26.5        77.7
                         gallons).
                        Fuel (billion           0.17        0.25        0.33        0.46        0.63        1.85
                         barrels).
                        CO2 EQ (mmt)....       88.8       130         174         244         325         962
----------------------------------------------------------------------------------------------------------------

    Table I.C.2-3 shows EPA's estimated lifetime discounted benefits
for all vehicles sold in model years 2012-2016. Although EPA estimated
the benefits associated with four different values of a one ton GHG
reduction ($5, $21, $35, $65), for the purposes of this overview
presentation of estimated benefits EPA is showing the benefits
associated with one of these marginal values, $21 per ton of
CO2, in 2007 dollars and 2010 emissions. Table I.C.2-3
presents benefits based on the $21 value. Section III.H presents the
four marginal values used to estimate monetized benefits of GHG
reductions and Section III.H presents the program benefits using each
of the four marginal values, which represent only a partial accounting
of total benefits due to omitted climate change impacts and other
factors that are not readily monetized. The values in the table are
discounted values for each model year of vehicles throughout their
projected lifetimes. The benefits include all benefits considered by
EPA such as fuel savings, GHG reductions, PM benefits, energy security
and other externalities such as reduced refueling and accidents,
congestion and noise. The lifetime discounted benefits are shown for
one of four different social cost of carbon (SCC) values considered by
EPA. The values in Table I.C.2-3 do not include costs associated with
new technology required to meet the GHG standard.

                  Table I.C.2-3--EPA's Estimated 2012-2016 Model Year Lifetime Discounted Benefits Assuming the $21/Ton SCC Value a b c
                                                               [Billions of 2007 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Model year
                      Discount rate                      -----------------------------------------------------------------------------------------------
                                                               2012            2013            2014            2015            2016            Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
3%......................................................           $21.8           $32.0           $42.8           $60.8           $83.3            $240
7%......................................................            17.4            25.7            34.2            48.6            66.4             192
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ The benefits include all benefits considered by EPA such as the economic value of reduced fuel consumption and accompanying savings in refueling
  time, climate-related economic benefits from reducing emissions of CO2 (but not other GHGs), economic benefits from reducing emissions of PM and other
  air pollutants that contribute to its formation, and reductions in energy security externalities caused by U.S. petroleum consumption and imports. The
  analysis also includes disbenefits stemming from additional vehicle use, such as the economic damages caused by accidents, congestion and noise.
\b\ Note that net present value of reduced GHG emissions is calculated differently than other benefits. The same discount rate used to discount the
  value of damages from future emissions (SCC at 5, 3, and 2.5 percent) is used to calculate net present value of SCC for internal consistency. Refer to
  Section III.H for more detail.
\c\ Monetized GHG benefits exclude the value of reductions in non-CO2 GHG emissions (HFC, CH4 and N2O) expected under this final rule. Although EPA has
  not monetized the benefits of reductions in these non-CO2 emissions, the value of these reductions should not be interpreted as zero. Rather, the
  reductions in non-CO2 GHGs will contribute to this rule's climate benefits, as explained in Section III.F.2. The SCC TSD notes the difference between
  the social cost of non-CO2 emissions and CO2 emissions, and specifies a goal to develop methods to value non-CO2 emissions in future analyses. Also,
  as noted in Section III.H, SCC increases over time. The $21/ton value applies to 2010 emissions and grows larger over time.

    Table I.C.2-4 shows EPA's estimated lifetime fuel savings, lifetime
CO2 emission reductions, and the monetized net present
values of those fuel savings and CO2 emission reductions.
The gallons of fuel and CO2 emission reductions are
projected lifetime values for all vehicles sold in the model years
2012-2016. The estimated fuel savings in billions of barrels and the
GHG reductions in million metric tons of CO2 shown in Table
I.C.2-4 are totals for the five model years throughout their projected
lifetime and are not discounted. The monetized values shown in Table
I.C.2-4 are the summed values of the discounted monetized-fuel savings
and monetized-CO2 reductions for the five model years 2012-
2016 throughout their lifetimes. The monetized values in Table I.C.2-4
reflect both a 3 percent and a 7 percent discount rate as noted.

     Table I.C.2-4--EPA's Estimated 2012-2016 Model Year Lifetime Fuel Savings, CO2 Emission Reductions, and
                               Discounted Monetized Benefits at a 3% Discount Rate
                                       [Monetized values in 2007 dollars]
----------------------------------------------------------------------------------------------------------------
                                                     Amount                        $ value (billions)
----------------------------------------------------------------------------------------------------------------
Fuel savings............................  1.8 billion barrels........  $182, 3% discount rate.
                                                                       $142, 7% discount rate.

CO2e emission reductions (CO2 portion     962 MMT CO2e...............  $17 a b.
 valued assuming $21/ton CO2 in 2010).
----------------------------------------------------------------------------------------------------------------
\a\ $17 billion for 858 MMT of reduced CO2 emissions. As noted in Section III.H, the $21/ton value applies to
  2010 emissions and grows larger over time. Monetized GHG benefits exclude the value of reductions in non-CO2
  GHG emissions (HFC, CH4 and N2O) expected under this final rule. Although EPA has not monetized the benefits
  of reductions in these non-CO2 emissions, the value of these reductions should not be interpreted as zero.
  Rather, the reductions in non-CO2 GHGs will contribute to this rule's climate benefits, as explained in
  Section III.F.2. The SCC TSD notes the difference between the social cost of non-CO2 emissions and CO2
  emissions, and specifies a goal to develop methods to value non-CO2 emissions in future analyses.
\b\ Note that net present value of reduced CO2 emissions is calculated differently than other benefits. The same
  discount rate used to discount the value of damages from future emissions (SCC at 5, 3, and 2.5 percent) is
  used to calculate net present value of SCC for internal consistency. Refer to Section III.H for more detail.

    Table I.C.2-5 shows EPA's estimated incremental and total
technology outlays for cars and trucks for each of the model years
2012-2016. The technology outlays shown in Table I.C.2-5 are for the
industry as a whole and do not account for fuel savings associated with
the program.

                                              Table I.C.2-5--EPA's Estimated Incremental Technology Outlays
                                                               [Billions of 2007 dollars]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2012            2013            2014            2015            2016            Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
Cars....................................................            $3.1            $5.0            $6.5            $8.0            $9.4           $31.9
Trucks..................................................             1.8             3.0             3.9             4.8             6.2            19.7
                                                         -----------------------------------------------------------------------------------------------
    Combined............................................             4.9             8.0            10.3            12.7            15.6            51.5
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Table I.C.2-6 shows EPA's estimated incremental cost increase of
the average new vehicle for each model year 2012-2016. The values shown
are incremental to a baseline vehicle and are not cumulative. In other
words, the estimated increase for 2012 model year cars is $342 relative
to a 2012 model year car absent the National Program. The estimated
increase for a 2013 model year car is $507 relative to a 2013 model
year car absent the National Program (not $342 plus $507).

                 Table I.C.2-6--EPA's Estimated Incremental Increase in Average New Vehicle Cost
                                             [2007 dollars per unit]
----------------------------------------------------------------------------------------------------------------
                                       2012            2013            2014            2015            2016
----------------------------------------------------------------------------------------------------------------
Cars............................            $342            $507            $631            $749            $869
Trucks..........................             314             496             652             820           1,098
                                 -------------------------------------------------------------------------------
    Combined....................             331             503             639             774             948
----------------------------------------------------------------------------------------------------------------

D. Background and Comparison of NHTSA and EPA Statutory Authority

    Section I.C of the proposal contained a detailed overview
discussion of the NHTSA and EPA statutory authorities. In addition to
the discussion in the proposal, each agency discusses comments
pertaining to its statutory authority and the agency's responses in
Sections III and IV of this notice, respectively.

II. Joint Technical Work Completed for This Final Rule

A. Introduction

    In this section NHTSA and EPA discuss several aspects of the joint
technical analyses on which the two agencies collaborated. These
analyses are common to the development of each agency's final
standards. Specifically we discuss: the development of the vehicle
market forecast used by each agency for assessing costs, benefits, and
effects, the development of the attribute-based standard curve shapes,
the determination of the relative stringency between the car and truck
fleet standards, the technologies the agencies evaluated and their
costs and effectiveness, and the economic assumptions the agencies
included in their analyses. The Joint Technical Support Document (TSD)
discusses the agencies' joint technical work in more detail.

B. Developing the Future Fleet for Assessing Costs, Benefits, and
Effects

1. Why did the agencies establish a baseline and reference vehicle
fleet?
    In order to calculate the impacts of the EPA and NHTSA regulations,
it is necessary to estimate the composition of the future vehicle fleet
absent these regulations, to provide a reference point relative to
which costs, benefits, and effects of the regulations are assessed. As
in the proposal, EPA and NHTSA have developed this comparison fleet in
two parts. The first step was to develop a baseline fleet based on
model year 2008 data. The second step was to project that fleet into
model years 2011-2016. This is called the reference fleet.

The third step was to modify that MY 2011-2016 reference fleet such
that it had sufficient technology to meet the MY 2011 CAFE standards.
This final version of the reference fleet is the light-duty fleet
estimated to exist in MY 2012-2016 in the absence of today's standards,
based on the assumption that manufacturers would continue to meet the
MY 2011 CAFE standards (or pay civil penalties allowed under EPCA \44\)
in the absence of further increases in the stringency of CAFE
standards. Each agency used this approach to develop a final reference
fleet to use in its modeling. All of the agencies' estimates of
emission reductions, fuel economy improvements, costs, and societal
impacts are developed in relation to the respective reference fleets.
---------------------------------------------------------------------------

    \44\ That is, the manufacturers who have traditionally paid
fines under EPCA instead of complying with the CAFE standards were
``allowed,'' for purposes of the reference fleet, to reach only the
CAFE level at which paying fines became more cost-effective than
adding technology, even if that fell short of the MY 2011 standards.
---------------------------------------------------------------------------

    EPA and NHTSA proposed a transparent approach to developing the
baseline and reference fleets, largely working from publicly available
data. This proposed approach differed from previous CAFE rules, which
relied on confidential manufacturers' product plan information to
develop the baseline. Most of the public comments to the NPRM
addressing this issue supported this methodology for developing the
inputs to the rule's analysis. Because the input sheets can be made
public, stakeholders can verify and check EPA's and NHTSA's modeling,
and perform their own analyses with these datasets. In this final
rulemaking, EPA and NHTSA are using an approach very similar to that
proposed, continuing to rely on publicly available data as the basis
for the baseline and reference fleets.
2. How did the agencies develop the baseline vehicle fleet?
    At proposal, EPA and NHTSA developed a baseline fleet comprised of
model year 2008 data gathered from EPA's emission certification and
fuel economy database. MY 2008 was used as the basis for the baseline
vehicle fleet because it was the most recent model year for which a
complete set of data is publicly available. This remains the case.
Manufacturers are not required to submit final sales and mpg figures
for MY 2009 until April 2010,\45\ after the CAFE standard's mandated
promulgation date. Consequently, in this final rule, EPA and NHTSA made
no changes to the method or the results of the MY 2008 baseline fleet
used at proposal, except for some specific corrections to engineering
inputs for some vehicle models reflected in the market forecast input
to NHTSA's CAFE model. More details about how the agencies constructed
this baseline fleet can be found in Chapter 1.2 of the Joint TSD.
Corrections to engineering inputs for some vehicle models in the market
forecast input to NHTSA's CAFE model are discussed in Chapter 2 of the
Joint TSD.
---------------------------------------------------------------------------

    \45\ 40 CFR 600.512-08, Model Year Report.
---------------------------------------------------------------------------

3. How did the agencies develop the projected MY 2011-2016 vehicle
fleet?
    EPA and NHTSA have based the projection of total car and total
light truck sales for MYs 2011-2016 on projections made by the
Department of Energy's Energy Information Administration (EIA). EIA
publishes a mid-term projection of national energy use called the
Annual Energy Outlook (AEO). This projection utilizes a number of
technical and econometric models which are designed to reflect both
economic and regulatory conditions expected to exist in the future. In
support of its projection of fuel use by light-duty vehicles, EIA
projects sales of new cars and light trucks. In the proposal, the
agencies used the three reports published by EIA as part of the AEO
2009. We also stated that updated versions of these reports could be
used in the final rules should AEO timely issue a new version. EIA
published an early version of its AEO 2010 in December 2009, and the
agencies are making use of it in this final rulemaking. The differences
in projected sales in the 2009 report (used in the NPRM) and the early
2010 report are very small, so NHTSA and EPA have decided to simply
scale the NPRM volumes for cars and trucks (in the aggregate) to match
those in the 2010 report. We thus employ the sales projections from the
scaled updated 2009 Annual Energy Outlook, which is equivalent to AEO
2010 Early Release, for the final rule. The scaling factors for each
model year are presented in Chapter 1 of the Joint TSD for this final
rule.
    The agencies recognize that AEO 2010 Early Release does include
some impacts of future projected increases in CAFE stringency. We have
closely examined the difference between AEO 2009 and AEO 2010 Early
Release and we believe the differences in total sales and the car/truck
split attributed to considerations of the standard in the final rule
are small.\46\
---------------------------------------------------------------------------

    \46\ The agencies have also looked at the impact of the rule in
EIA's projection, and concluded that the impact was small. EPA and
NHTSA have evaluated the differences between the AEO 2010 (early
draft) and AEO 2009 and found little difference in the fleet
projections (or fuel prices). This analysis can be found in the memo
to the docket: Kahan, A. and Pickrell, D. Memo to Docket EPA-HQ-OAR-
2009-0472 and Docket NHTSA-2009-0059. ``Energy Information
Administration's Annual Energy Outlook 2009 and 2010.'' March 24,
2010.
---------------------------------------------------------------------------

    In the AEO 2010 Early Release, EIA projects that total light-duty
vehicle sales will gradually recover from their currently depressed
levels by around 2013. In 2016, car sales are projected to be 9.4
million (57 percent) and truck sales are projected to be 7.1 million
(43 percent). Although the total level of sales of 16.5 million units
is similar to pre-2008 levels, the fraction of car sales is projected
to be higher than that existing in the 2000-2007 timeframe. This
projection reflects the impact of higher fuel prices, as well as EISA's
requirement that the new vehicle fleet average at least 35 mpg by MY
2020. The agencies note that AEO does not represent the fleet at a
level of detail sufficient to explicitly account for the
reclassification--promulgated as part of NHTSA's final rule for MY 2011
CAFE standards--of a number of 2-wheel drive sport utility vehicles
from the truck fleet to the car fleet for MYs 2011 and after. Sales
projections of cars and trucks for future model years can be found in
the Joint TSD for these final rules.
    In addition to a shift towards more car sales, sales of segments
within both the car and truck markets have been changing and are
expected to continue to change. Manufacturers are introducing more
crossover models which offer much of the utility of SUVs but use more
car-like designs. The AEO 2010 report does not, however, distinguish
such changes within the car and truck classes. In order to reflect
these changes in fleet makeup, EPA and NHTSA considered several other
available forecasts. EPA purchased and shared with NHTSA forecasts from
two well-known industry analysts, CSM Worldwide (CSM), and J.D. Powers.
NHTSA and EPA decided to use the forecast from CSM, modified as
described below, for several reasons presented in the NPRM preamble
\47\ and draft Joint TSD. The changes between company market share and
industry market segments were most significant from 2011-2014, while
for 2014-2015 the changes were relatively small. Noting this, and
lacking a credible forecast of company and segment shares after 2015,
the agencies assumed 2016 market share and market segments to be the
same as for 2015.
---------------------------------------------------------------------------

    \47\ See, e.g., 74 FR 49484.

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

    CSM Worldwide provides quarterly sales forecasts for the automotive
industry. In the NPRM, the agencies identified a concern with the 2nd
quarter CSM forecast that was used as a basis for the projection. CSM
projections at that time were based on an industry that was going
through a significant financial transition, and as a result the market
share forecasts for some companies were impacted in surprising ways. As
the industry's situation has settled somewhat over the past year, the
4th quarter projection appears to address this issue--for example, it
shows nearly a two-fold increase in sales for Chrysler compared to
significant loss of market share shown for Chrysler in the 2nd quarter
projection. Additionally, some commenters, such as GM, recognized that
the fleet appeared to include an unusually high number of large pickup
trucks.\48\ In fact, the agencies discovered (independently of the
comments) that CSM's standard forecast included all vehicles below
14,000 GVWR, including class 2b and 3 heavy duty vehicles, which are
not regulated by this final rule.\49\ The commenters were thus correct
that light duty reference fleet projections at proposal had more full
size trucks and vans due to the mistaken inclusion of the heavy duty
versions of those vehicles. The agencies requested a separate data
forecast from CSM that filtered their 4th quarter projection to exclude
these heavy duty vehicles. The agencies then used this filtered 4th
quarter forecast for the final rule. A detailed comparison of the
market by manufacturer can be found in the final TSD. For the public's
reference, copies of the 2nd, 3rd, and 4th quarter CSM forecasts have
been placed in the docket for this rulemaking.\50\
---------------------------------------------------------------------------

    \48\ GM argued that the unusually large volume of large pickups
led to higher overall requirements for those vehicles. As discussed
below, the agencies' analysis for the final rule corrects the number
of large pickups. With this correction and other updates to the
agencies' market forecast and other analytical inputs, the target
functions defining the final standards (and achieving the average
required performance levels defining the national program) are very
similar to those from the NPRM, especially for light trucks, as
illustrated below in Figures II.C-7 and II.C-8.
    \49\ These include the Ford F-250 & F-350, Econoline E-250, & E-
350; Chevy Express, Silverado 2500, & 3500; GMC Savana, Dodge 2500,
& 3500; among others.
    \50\ The CSM Sales Forecast Excel file (``CSM North America
Sales Forecasts 2Q09 3Q09 4Q09 for the Docket'') is available in the
docket (Docket EPA-HQ-OAR-2009-0472).
---------------------------------------------------------------------------

    We then projected the CSM forecasts for relative sales of cars and
trucks by manufacturer and by market segment onto the total sales
estimates of AEO 2010. Tables II.B.3-1 and II.B.3-2 show the resulting
projections for the reference 2016 model year and compare these to
actual sales that occurred in baseline 2008 model year. Both tables
show sales using the traditional definition of cars and light trucks.

       Table II.B.3-1--Annual Sales of Light-Duty Vehicles by Manufacturer in 2008 and Estimated for 2016
----------------------------------------------------------------------------------------------------------------
                                              Cars                  Light trucks                  Total
                                   -----------------------------------------------------------------------------
                                      2008 MY      2016 MY      2008 MY      2016 MY      2008 MY      2016 MY
----------------------------------------------------------------------------------------------------------------
BMW...............................      291,796      424,923       61,324      171,560      353,120      596,482
Chrysler..........................      537,808      340,908    1,119,397      525,128    1,657,205      866,037
Daimler...........................      208,052      272,252       79,135      126,880      287,187      399,133
Ford..............................      709,583    1,118,727    1,158,805    1,363,256    1,868,388    2,481,983
General Motors....................    1,370,280    1,283,937    1,749,227    1,585,828    3,119,507    2,869,766
Honda.............................      899,498      811,214      612,281      671,437    1,511,779    1,482,651
Hyundai...........................      270,293      401,372      120,734      211,996      391,027      613,368
Kia...............................      145,863      455,643      135,589      210,717      281,452      666,360
Mazda.............................      191,326      350,055      111,220      144,992      302,546      495,047
Mitsubishi........................       76,701       49,914       24,028       88,754      100,729      138,668
Porsche...........................       18,909       33,471       18,797       16,749       37,706       50,220
Nissan............................      653,121      876,677      370,294      457,114    1,023,415    1,333,790
Subaru............................      149,370      230,705       49,211       95,054      198,581      325,760
Suzuki............................       68,720       97,466       45,938       26,108      114,658      123,574
Tata..............................        9,596       65,806       55,584       42,695       65,180      108,501
Toyota............................    1,143,696    2,069,283    1,067,804    1,249,719    2,211,500    3,319,002
Volkswagen........................      290,385      586,011       26,999      124,703      317,384      710,011
                                   -----------------------------------------------------------------------------
    Total.........................    7,034,997    9,468,365    6,806,367    7,112,689   13,841,364   16,580,353
----------------------------------------------------------------------------------------------------------------

      Table II.B.3-2--Annual Sales of Light-Duty Vehicles by Market Segment in 2008 and Estimated for 2016
----------------------------------------------------------------------------------------------------------------
                             Cars                                                 Light trucks
----------------------------------------------------------------------------------------------------------------
                                    2008 MY         2016 MY                           2008 MY         2016 MY
----------------------------------------------------------------------------------------------------------------
Full-Size Car.................         829,896         530,945  Full-Size Pickup       1,331,989       1,379,036
Luxury Car....................       1,048,341       1,548,242  Mid-Size Pickup.         452,013         332,082
Mid-Size Car..................       2,166,849       2,550,561  Full-Size Van...          33,384          65,650
Mini Car......................         617,902       1,565,373  Mid-Size Van....         719,529         839,194
Small Car.....................       1,912,736       2,503,566  Mid-Size MAV *..         110,353         116,077
Specialty Car.................         459,273         769,679  Small MAV.......         231,265          62,514
                                                                Full-Size SUV *.         559,160         232,619
                                                                Mid-Size SUV....         436,080         162,502
                                                                Small SUV.......         196,424         108,858
                                                                Full-Size CUV *.         264,717         260,662
                                                                Mid-Size CUV....         923,165       1,372,200
                                                                Small CUV.......       1,548,288       2,181,296
                               ---------------------------------------------------------------------------------

    Total Sales **............       7,034,997       9,468,365  ................       6,806,367       7,079,323
----------------------------------------------------------------------------------------------------------------
* MAV--Multi-Activity Vehicle, SUV--Sport Utility Vehicle, CUV--Crossover Utility Vehicle.
** Total Sales are based on the classic Car/Truck definition.

    Determining which traditionally-defined trucks will be defined as
cars for purposes of this final rule using the revised definition
established by NHTSA for MYs 2011 and beyond requires more detailed
information about each vehicle model. This is described in greater
detail in Chapter 1 of the final TSD.
    The forecasts obtained from CSM provided estimates of car and truck
sales by segment and by manufacturer, but not by manufacturer for each
market segment. Therefore, NHTSA and EPA needed other information on
which to base these more detailed projected market splits. For this
task, the agencies used as a starting point each manufacturer's sales
by market segment from model year 2008, which is the baseline fleet.
Because of the larger number of segments in the truck market, the
agencies used slightly different methodologies for cars and trucks.
    The first step for both cars and trucks was to break down each
manufacturer's 2008 sales according to the market segment definitions
used by CSM. For example, the agencies found that Ford's \51\ cars
sales in 2008 were broken down as shown in Table II.B.3-3:
---------------------------------------------------------------------------

    \51\ Note: In the NPRM, Ford's 2008 sales per segment, and the
total number of cars was different than shown here. The change in
values is due to a correction of vehicle segments for some of Ford's
vehicles.

           Table II.B.3-3--Breakdown of Ford's 2008 Car Sales
------------------------------------------------------------------------

------------------------------------------------------------------------
Full-size cars..........................  160,857 units.
Mid-size Cars...........................  170,399 units.
Small/Compact Cars......................  180,249 units.
Subcompact/Mini Cars....................  None.
Luxury cars.............................  87,272 units.
Specialty cars..........................  110,805 units.
------------------------------------------------------------------------

    EPA and NHTSA then adjusted each manufacturer's sales of each of
its car segments (and truck segments, separately) so that the
manufacturer's total sales of cars (and trucks) matched the total
estimated for each future model year based on AEO and CSM forecasts.
For example, as indicated in Table II.B.3-1, Ford's total car sales in
2008 were 709,583 units, while the agencies project that they will
increase to 1,113,333 units by 2016. This represents an increase of
56.9 percent. Thus, the agencies increased the 2008 sales of each Ford
car segment by 56.9 percent. This produced estimates of future sales
which matched total car and truck sales per AEO and the manufacturer
breakdowns per CSM. However, the sales splits by market segment would
not necessarily match those of CSM (shown for 2016 in Table II.B.3-2).
    In order to adjust the market segment mix for cars, the agencies
first adjusted sales of luxury, specialty and other cars. Since the
total sales of cars for each manufacturer were already set, any changes
in the sales of one car segment had to be compensated by the opposite
change in another segment. For the luxury, specialty and other car
segments, it is not clear how changes in sales would be compensated.
For example, if luxury car sales decreased, would sales of full-size
cars increase, mid-size cars, and so on? The agencies have assumed that
any changes in the sales of cars within these three segments were
compensated for by proportional changes in the sales of the other four
car segments. For example, for 2016, the figures in Table II.B.3-2
indicate that luxury car sales in 2016 are 1,548,242 units. Luxury car
sales are 1,048,341 units in 2008. However, after adjusting 2008 car
sales by the change in total car sales for 2016 projected by EIA and a
change in manufacturer market share per CSM, luxury car sales decreased
to 1,523,171 units. Thus, overall for 2016, luxury car sales had to
increase by 25,071 units or 6 percent. The agencies accordingly
increased the luxury car sales by each manufacturer by this percentage.
The absolute decrease in luxury car sales was spread across sales of
full-size, mid-size, compact and subcompact cars in proportion to each
manufacturer's sales in these segments in 2008. The same adjustment
process was used for specialty cars and the ``other cars'' segment
defined by CSM.
    The agencies used a slightly different approach to adjust for
changing sales of the remaining four car segments. Starting with full-
size cars, the agencies again determined the overall percentage change
that needed to occur in future year full-size car sales after 1)
adjusting for total sales per AEO 2010, 2) adjusting for manufacturer
sales mix per CSM and 3) adjusting the luxury, specialty and other car
segments, in order to meet the segment sales mix per CSM. Sales of each
manufacturer's large cars were adjusted by this percentage. However,
instead of spreading this change over the remaining three segments, the
agencies assigned the entire change to mid-size vehicles. The agencies
did so because the CSM data followed the trend of increasing volumes of
smaller cars while reducing volumes of larger cars. If a consumer had
previously purchased a full-size car, we thought it unlikely that their
next purchase would decrease by two size categories, down to a
subcompact. It seemed more reasonable to project that they would drop
one vehicle size category smaller. Thus, the change in each
manufacturer's sales of full-size cars was matched by an opposite
change (in absolute units sold) in mid-size cars.
    The same process was then applied to mid-size cars, with the change
in mid-size car sales being matched by an opposite change in compact
car sales. This process was repeated one more time for compact car
sales, with changes in sales in this segment being matched by the
opposite change in the sales of subcompacts. The overall result was a
projection of car sales for model years 2012-2016--the reference
fleet--which matched the total sales projections of the AEO forecast
and the manufacturer and segment splits of the CSM forecast. These
sales splits can be found in Chapter 1 of the Joint TSD for this final
rule.
    As mentioned above, the agencies applied a slightly different
process to truck sales, because the agencies could not confidently
project how the change in sales from one segment preferentially went to
or came from another particular segment. Some trend from larger
vehicles to smaller vehicles would have been possible. However, the CSM
forecasts indicated large changes in total sport utility vehicle,
multi-activity vehicle and cross-over sales which could not be
connected. Thus, the

agencies applied an iterative, but straightforward process for
adjusting 2008 truck sales to match the AEO and CSM forecasts.
    The first three steps were exactly the same as for cars. EPA and
NHTSA broke down each manufacturer's truck sales into the truck
segments as defined by CSM. The agencies then adjusted all
manufacturers' truck segment sales by the same factor so that total
truck sales in each model year matched AEO projections for truck sales
by model year. The agencies then adjusted each manufacturer's truck
sales by segment proportionally so that each manufacturer's percentage
of total truck sales matched that forecast by CSM. This again left the
need to adjust truck sales by segment to match the CSM forecast for
each model year.
    In the fourth step, the agencies adjusted the sales of each truck
segment by a common factor so that total sales for that segment matched
the combination of the AEO and CSM forecasts. For example, projected
sales of large pickups across all manufacturers were 1,286,184 units in
2016 after adjusting total sales to match AEO's forecast and adjusting
each manufacturer's truck sales to match CSM's forecast for the
breakdown of sales by manufacturer. Applying CSM's forecast of the
large pickup segment of truck sales to AEO's total sales forecast
indicated total large pickup sales of 1,379,036 units. Thus, we
increased each manufacturer's sales of large pickups by 7 percent.\52\
The agencies applied the same type of adjustment to all the other truck
segments at the same time. The result was a set of sales projections
which matched AEO's total truck sales projection and CSM's market
segment forecast. However, after this step, sales by manufacturer no
longer met CSM's forecast. Thus, we repeated step three and adjusted
each manufacturer's truck sales so that they met CSM's forecast. The
sales of each truck segment (by manufacturer) were adjusted by the same
factor. The resulting sales projection matched AEO's total truck sales
projection and CSM's manufacturer forecast, but sales by market segment
no longer met CSM's forecast. However, the difference between the sales
projections after this fifth step was closer to CSM's market segment
forecast than it was after step three. In other words, the sales
projection was converging to the desired result. The agencies repeated
these adjustments, matching manufacturer sales mix in one step and then
market segment in the next a total of 19 times. At this point, we were
able to match the market segment splits exactly and the manufacturer
splits were within 0.1 percent of our goal, which is well within the
needs of this analysis.
---------------------------------------------------------------------------

    \52\ Note: In the NPRM this example showed 29 percent instead of
7 percent. The significant decrease was due to using the filtered
4th quarter CSM forecast. Commenters, such as GM, had commented that
we had too many full-size trucks and vans, and this change addresses
their comment.
---------------------------------------------------------------------------

    The next step in developing the reference fleets was to
characterize the vehicles within each manufacturer-segment combination.
In large part, this was based on the characterization of the specific
vehicle models sold in 2008--i.e., the vehicles comprising the baseline
fleet. EPA and NHTSA chose to base our estimates of detailed vehicle
characteristics on 2008 sales for several reasons. One, these vehicle
characteristics are not confidential and can thus be published here for
careful review by interested parties. Two, because it is constructed
beginning with actual sales data, this vehicle fleet is limited to
vehicle models known to satisfy consumer demands in light of price,
utility, performance, safety, and other vehicle attributes.
    As noted above, the agencies gathered most of the information about
the 2008 baseline vehicle fleet from EPA's emission certification and
fuel economy database. The data obtained from this source included
vehicle production volume, fuel economy, engine size, number of engine
cylinders, transmission type, fuel type, etc. EPA's certification
database does not include a detailed description of the types of fuel
economy-improving/CO2-reducing technologies considered in
this final rule. Thus, the agencies augmented this description with
publicly available data which includes more complete technology
descriptions from Ward's Automotive Group.\53\ In a few instances when
required vehicle information (such as vehicle footprint) was not
available from these two sources, the agencies obtained this
information from publicly accessible Internet sites such as
Motortrend.com and Edmunds.com.\54\
---------------------------------------------------------------------------

    \53\ Note that WardsAuto.com is a fee-based service, but all
information is public to subscribers.
    \54\ Motortrend.com and Edmunds.com are free, no-fee Internet
sites.
---------------------------------------------------------------------------

    The projections of future car and truck sales described above apply
to each manufacturer's sales by market segment. The EPA emissions
certification sales data are available at a much finer level of detail,
essentially vehicle configuration. As mentioned above, the agencies
placed each vehicle in the EPA certification database into one of the
CSM market segments. The agencies then totaled the sales by each
manufacturer for each market segment. If the combination of AEO and CSM
forecasts indicated an increase in a given manufacturer's sales of a
particular market segment, then the sales of all the individual vehicle
configurations were adjusted by the same factor. For example, if the
Prius represented 30 percent of Toyota's sales of compact cars in 2008
and Toyota's sales of compact cars in 2016 was projected to double by
2016, then the sales of the Prius were doubled, and the Prius sales in
2016 remained 30 percent of Toyota's compact car sales.
    The projection of average footprint for both cars and trucks
remained virtually constant over the years covered by the final
rulemaking. This occurrence is strictly a result of the CSM
projections. There are a number of trends that occur in the CSM
projections that caused the average footprint to remain constant.
First, as the number of subcompacts increases, so do the number of 2-
wheel drive crossover vehicles (that are regulated as cars). Second,
truck volumes have many segment changes during the rulemaking time
frame. There is no specific footprint related trend in any segment that
can be linked to the unchanging footprint, but there is a trend that
non-pickups' volumes will move from truck segments that are ladder
frame to those that are unibody-type vehicles. A table of the footprint
projections is available in the TSD as well as further discussion on
this topic.
4. How was the development of the baseline and reference fleets for
this Final Rule different from NHTSA's historical approach?
    NHTSA has historically based its analysis of potential new CAFE
standards on detailed product plans the agency has requested from
manufacturers planning to produce light vehicles for sale in the United
States. Although the agency has not attempted to compel manufacturers
to submit such information, most major manufacturers and some smaller
manufacturers have voluntarily provided it when requested.
    The proposal discusses many of the advantages and disadvantages of
the market forecast approach used by the agencies, including the
agencies' interest in examining product plans as a check on the
reference fleet developed by the agencies for this rulemaking. One of
the primary reasons for the request for data in 2009 was to obtain
permission from the manufacturers to make public their product plan
information for model years 2010 and 2011. There are a number of
reasons that this could be advantageous in the development of a
reference fleet. First,

some known changes to the fleet may not be captured by the approach of
solely using publicly available information. For example, the agencies'
current market forecast includes some vehicles for which manufacturers
have announced plans for elimination or drastic production cuts such as
the Chevrolet Trailblazer, the Chrysler PT Cruiser, the Chrysler
Pacifica, the Dodge Magnum, the Ford Crown Victoria, the Mercury Sable,
the Pontiac Grand Prix, the Pontiac G5 and the Saturn Vue. These
vehicle models appear explicitly in market inputs to NHTSA's analysis,
and are among those vehicle models included in the aggregated vehicle
types appearing in market inputs to EPA's analysis. However, although
the agencies recognize that these specific vehicles will be
discontinued, we continue to include them in the market forecast
because they are useful as a surrogate for successor vehicles that may
appear in the rulemaking time frame to replace the discontinued
vehicles in that market segment.\55\
---------------------------------------------------------------------------

    \55\ An example of this is in the GM Pontiac line, which is in
the process of being phased out during the course of this
rulemaking. GM has similar vehicles within their other brands (like
Chevy) that will ``presumably'' pick up the loss in Pontiac share.
We model this simply by leaving the Pontiac brand in.
---------------------------------------------------------------------------

    Second, the agencies' market forecast does not include some
forthcoming vehicle models, such as the Chevrolet Volt, the Ford Fiesta
and several publicly announced electric vehicles, including the
announcements from Nissan regarding the Leaf. Nor does it include
several MY 2009 or 2010 vehicles, such as the Honda Insight, the
Hyundai Genesis and the Toyota Venza, as our starting point for
defining specific vehicle models in the reference fleet was Model Year
2008. Additionally, the market forecast does not account for publicly
announced technology introductions, such as Ford's EcoBoost system,
whose product plans specify which vehicles and how many are planned to
have this technology. Chrysler Group LLC has announced plans to offer
small- and medium-sized cars using Fiat powertrains. Were the agencies
to rely on manufacturers' product plans (that were submitted), the
market forecast would account for not only these specific examples, but
also for similar examples that have not yet been announced publicly.
    Some commenters, such as CBD and NESCAUM, suggested that the
agencies' omission of known future vehicles and technologies in the
reference fleet causes inaccuracies, which CBD further suggested could
lead the agencies to set lower standards. On the other hand, CARB
commented that ``the likely impact of this omission is minor.'' Because
the agencies' analysis examines the costs and benefits of progressively
adding technology to manufacturers' fleets, the omission of future
vehicles and technologies primarily affects how much additional
technology (and, therefore, how much incremental cost and benefit) is
available relative to the point at which the agencies' examination of
potential new standards begins. Thus, in fact, the omission only
reflects the reference fleet, rather than the agencies' conclusions
regarding how stringent the standards should be. This is discussed
further below. The agencies believe the above-mentioned comments by
CBD, NESCAUM, and others are based on a misunderstanding of the
agencies' approach to analyzing potential increases in regulatory
stringency. The agencies also note that manufacturers do not always use
technology solely to increase fuel economy, and that use of technology
to increase vehicles' acceleration performance or utility would
probably make that technology unavailable toward more stringent
standards. Considering the incremental nature of the agencies'
analysis, and the counterbalancing aspects of potentially omitted
technology in the reference fleet, the agencies believe their
determination of the stringency of new standards has not been impacted
by any such omissions.
    Moreover, EPA and NHTSA believe that not including such vehicles
after MY 2008 does not significantly impact our estimates of the
technology required to comply with the standards. If included, these
vehicles could increase the extent to which manufacturers are, in the
reference case, expected to over-comply with the MY 2011 CAFE
standards, and could thereby make the new standards appear to cost less
and yield less benefit relative to the reference case. However, in the
agencies' judgment, production of the most advanced technology
vehicles, such as the Chevy Volt or the Nissan Leaf (for example), will
most likely be too limited during MY 2011 through MY 2016 to
significantly impact manufacturers' compliance positions. While we are
projecting the characteristics of the future fleet by extrapolating
from the MY 2008 fleet, the primary difference between the future fleet
and the 2008 fleet in the same vehicle segment is the use of additional
CO2-reducing and fuel-saving technologies. Both the NHTSA
and EPA models add such technologies to evaluate means of complying
with the standards, and the costs of doing so. Thus, our future
projections of the vehicle fleet generally shift vehicle designs
towards those more likely to be typical of newer vehicles. Compared to
using product plans that show continued fuel economy increases planned
based on expectations that CAFE standards will continue to increase,
this approach helps to clarify the costs and benefits of the new
standards, as the costs and benefits of all fuel economy improvements
beyond those required by the MY 2011 CAFE standards are being assigned
to the final rules. In some cases, the ``actual'' (vs. projected or
``modeled'') new vehicles being introduced into the market by
manufacturers are done so in anticipation of this rulemaking. On the
other hand, manufacturers may plan to continue using technologies to
improve vehicle performance and/or utility, not just fuel economy. Our
approach prevents some of these actual technological improvements and
their associated cost and fuel economy improvements from being assumed
in the reference fleet. Thus, the added technology will not be
considered to be free (or having no benefits) for the purposes of this
rule.
    In this regard, the agencies further note that manufacturer
announcements regarding forward models (or future vehicle models) need
not be accepted automatically. Manufacturers tend to limit accurate
production intent information in these releases for reasons such as:
(a) Competitors will closely examine their information for data in
their product planning decisions; (b) the press coverage of forward
model announcements is not uniform, meaning highly anticipated models
have more coverage and materials than models that may be less exciting
to the public and consistency and uniformity cannot be ensured with the
usage of press information; and (c) these market projections are
subject to change (sometimes significant), and manufacturers may not
want to give the appearance of being indecisive, or under/over-
confident to their shareholders and the public with premature release
of information.
    NHTSA has evaluated the use of public manufacturer forward model
press information to update the vehicle fleet inputs to the baseline
and reference fleet. The challenges in this approach are evidenced by
the continuous stream of manufacturer press releases throughout a
defined rulemaking period. Manufacturers' press releases suffer from
the same types of inaccuracies that many commenters believe can affect
product plans.

Manufacturers can often be overly optimistic in their press releases,
both on projected date of release of new models and on sales volumes.
    More generally and more critically, as discussed in the proposal
and as endorsed by many of the public comments, there are several
advantages to the approach used by the agencies in this final rule.
Most importantly, today's market forecast is much more transparent. The
information sources used to develop today's market forecast are all
either in the public domain or available commercially. Another
significant advantage of today's market forecast is the agencies'
ability to assess more fully the incremental costs and benefits of the
proposed standards. In addition, by developing baseline and reference
fleets from common sources, the agencies have been able to avoid some
errors--perhaps related to interpretation of requests--that have been
observed in past responses to NHTSA's requests. An additional advantage
of the approach used for this rule is a consistent projection of the
change in fuel economy and CO2 emissions across the various
vehicles from the application of new technology. With the approach used
for this final rule, the baseline market data comes from actual
vehicles (on the road today) which have actual fuel economy test data
(in contrast to manufacturer estimates of future product fuel
economy)--so there is no question what is the basis for the fuel
economy or CO2 performance of the baseline market data as it
is.
5. How does manufacturer product plan data factor into the baseline
used in this Final Rule?
    In the spring and fall of 2009, many manufacturers submitted
product plans in response to NHTSA's recent requests that they do so.
NHTSA and EPA both have access to these plans, and both agencies have
reviewed them in detail. A small amount of product plan data was used
in the development of the baseline. The specific pieces of data are:
     Wheelbase.
     Track Width Front.
     Track Width Rear.
     EPS (Electric Power Steering).
     ROLL (Reduced Rolling Resistance).
     LUB (Advance Lubrication i.e. low weight oil).
     IACC (Improved Electrical Accessories).
     Curb Weight.
     GVWR (Gross Vehicle Weight Rating).
    The track widths, wheelbase, curb weight, and GVWR for vehicles
could have been looked up on the Internet (159 were), but were taken
from the product plans when available for convenience. To ensure
accuracy, a sample from each product plan was used as a check against
the numbers available from Motortrend.com. These numbers will be
published in the baseline file since they can be easily looked up on
the internet. On the other hand, EPS, ROLL, LUB, and IACC are difficult
to determine without using manufacturer's product plans. These items
will not be published in the baseline file, but the data has been
aggregated into the agencies' baseline in the technology effectiveness
and cost effectiveness for each vehicle in a way that allows the
baseline for the model to be published without revealing the
manufacturer's data.
    Also, some technical information that manufacturers have provided
in product plans regarding specific vehicle models is, at least insofar
as NHTSA and EPA have been able to determine, not available from public
or commercial sources. While such gaps do not bear significantly on the
agencies' analysis, the diversity of pickup configurations necessitated
utilizing a sales-weighted average footprint value \56\ for many
manufacturers' pickups. Since our modeling only utilizes footprint in
order to estimate each manufacturer's CO2 or fuel economy
standard and all the other vehicle characteristics are available for
each pickup configuration, this approximation has no practical impact
on the projected technology or cost associated with compliance with the
various standards evaluated. The only impact which could arise would be
if the relative sales of the various pickup configurations changed, or
if the agencies were to explore standards with a different shape. This
would necessitate recalculating the average footprint value in order to
maintain accuracy.
---------------------------------------------------------------------------

    \56\ A full-size pickup might be offered with various
combinations of cab style (e.g., regular, extended, crew) and box
length (e.g., 5\1/2\', 6\1/2\', 8') and, therefore, multiple
footprint sizes. CAFE compliance data for MY 2008 data does not
contain footprint information, and does not contain information that
can be used to reliably identify which pickup entries correspond to
footprint values estimable from public or commercial sources.
Therefore, the agencies have used the known production levels of
average values to represent all variants of a given pickup line
(e.g., all variants of the F-150 and the Sierra/Silverado) in order
to calculate the sales-weighted average footprint value for each
pickup family. Again, this has no impact on the results of our
modeling effort, although it would require re-estimation if we were
to examine light truck standards of a different shape. In the
extreme, one single footprint value could be used for every vehicle
sold by a single manufacturer as long as the fuel economy standard
associated with this footprint value represented the sales-weighted,
harmonic average of the fuel economy standards associated with each
vehicle's footprint values.
---------------------------------------------------------------------------

    Additionally, as discussed in the NPRM, in an effort to update the
2008 baseline to account for the expected changes in the fleet in the
near-term model years 2009-2011 described above, NHTSA requested
permission from the manufacturers to make this limited product plan
information public. Unfortunately, virtually no manufacturers agreed to
allow the use of their data after 2009 model year. A few manufacturers,
such as GM and Ford, stated we could use their 2009 product plan data
after the end of production (December 31), but this would not have
afforded us sufficient time to do the analysis for the final rule.
Since the agencies were unable to obtain consistent updates, the
baseline and reference fleets were not updated beyond 2008 model year
for the final rule. The 2008 baseline fleet and projections were
instead updated using the latest AEO and CSM data as discussed earlier.
    NHTSA and EPA recognize that the approach applied for the current
rule gives transparency and openness of the vehicle market forecast
high priority, and accommodates minor inaccuracies that may be
introduced by not accounting for future product mix changes anticipated
in manufacturers' confidential product plans. For any future fleet
analysis that the agencies are required to perform, NHTSA and EPA plan
to request that manufacturers submit product plans and allow some
public release of information. In performing this analysis, the
agencies plan to reexamine potential tradeoffs between transparency and
technical reasonableness, and to explain resultant choices.

C. Development of Attribute-Based Curve Shapes

    In the NPRM, NHTSA and EPA proposed to set attribute-based CAFE and
CO2 standards that are defined by a mathematical function
for MYs 2012-2016 passenger cars and light trucks. EPCA, as amended by
EISA, expressly requires that CAFE standards for passenger cars and
light trucks be based on one or more vehicle attributes related to fuel
economy, and be expressed in the form of a mathematical function.\57\
The CAA has no such requirement, though in past rules, EPA has relied
on both universal and attribute-based standards (e.g., for nonroad
engines, EPA uses the attribute of horsepower). However, given the
advantages of using attribute-based standards and given the

goal of coordinating and harmonizing CO2 standards
promulgated under the CAA and CAFE standards promulgated under EPCA,
EPA also proposed to issue standards that are attribute-based and
defined by mathematical functions. There was consensus in the public
comments that EPA should develop attribute-based CO2
standards.
---------------------------------------------------------------------------

    \57\ 49 U.S.C. 32902(a)(3)(A).
---------------------------------------------------------------------------

    Comments received in response to the agencies' decision to base
standards on vehicle footprint were largely supportive. Several
commenters (BMW, NADA, NESCAUM) expressed support for attribute-based
(as opposed to flat or universal) standards generally, and agreed with
EPA's decision to harmonize with NHTSA in this respect. Many commenters
(Aluminum Association, BMW, ICCT, NESCAUM, NY DEC, Schade, Toyota) also
supported the agencies' decision to continue setting CAFE standards,
and begin setting GHG standards, on the basis of vehicle footprint,
although one commenter (NJ DEP) opposed the use of footprint due to
concern that it encourages manufacturers to upsize vehicles and
undercut the gains of the standard. Of the commenters supporting the
use of footprint, several focused on the benefits of harmonization--
both between EPA and NHTSA, and between the U.S. and the rest of the
world. BMW commented, for example, that many other countries use
weight-based standards rather than footprint-based. While BMW did not
object to NHTSA's and EPA's use of footprint-based standards, it
emphasized the impact of this non-harmonization on manufacturers who
sell vehicles globally, and asked the agencies to consider these
effects. NADA supported the use of footprint, but cautioned that the
agencies must be careful in setting the footprint curve for light
trucks to ensure that manufacturers can continue to provide
functionality like 4WD and towing/hauling capacity.
    Some commenters requested that the agencies consider other or more
attributes in addition to footprint, largely reiterating comments
submitted to the MYs 2011-2015 CAFE NPRM. Cummins supported the
agencies using a secondary attribute to account for towing and hauling
capacity in large trucks, for example, while Ferrari asked the agencies
to consider a multi-attribute approach incorporating curb weight,
maximum engine power or torque, and/or engine displacement, as it had
requested in the previous round of CAFE rulemaking. An individual, Mr.
Kenneth Johnson, commented that weight-based standards would be
preferable to footprint-based ones, because weight correlates better
with fuel economy than footprint, because the use of footprint does not
necessarily guarantee safety the way the agencies say it does, and
because weight-based standards would be fairer to manufacturers.
    In response, EPA and NHTSA continue to believe that the benefits of
footprint-attribute-based standards outweigh any potential drawbacks
raised by commenters, and that harmonization between the two agencies
should be the overriding goal on this issue. As discussed by NHTSA in
the MY 2011 CAFE final rule,\58\ the agencies believe that the
possibility of gaming is lowest with footprint-based standards, as
opposed to weight-based or multi-attribute-based standards.
Specifically, standards that incorporate weight, torque, power, towing
capability, and/or off-road capability in addition to footprint would
not only be significantly more complex, but by providing degrees of
freedom with respect to more easily-adjusted attributes, they would
make it less certain that the future fleet would actually achieve the
average fuel economy and CO2 levels projected by the
agencies. The agencies recognize that based on economic and consumer
demand factors that are external to this rule, the distribution of
footprints in the future may be different (either smaller or larger)
than what is projected in this rule. However, the agencies continue to
believe that there will not be significant shifts in this distribution
as a direct consequence of this rule. The agencies are therefore
finalizing MYs 2012-2016 CAFE and GHG standards based on footprint.
---------------------------------------------------------------------------

    \58\ See 74 FR 14359 (Mar. 30, 2009).
---------------------------------------------------------------------------

    The agencies also recognize that there could be benefits for a
number of manufacturers if there was greater international
harmonization of fuel economy and GHG standards, but this is largely a
question of how stringent standards are and how they are enforced. It
is entirely possible that footprint-based and weight-based systems can
coexist internationally and not present an undue burden for
manufacturers if they are carefully crafted. Different countries or
regions may find different attributes appropriate for basing standards,
depending on the particular challenges they face--from fuel prices, to
family size and land use, to safety concerns, to fleet composition and
consumer preference, to other environmental challenges besides climate
change. The agencies anticipate working more closely with other
countries and regions in the future to consider how to mitigate these
issues in a way that least burdens manufacturers while respecting each
country's need to meet its own particular challenges.
    Under an attribute-based standard, every vehicle model has a
performance target (fuel economy and CO2 emissions for CAFE
and CO2 emissions standards, respectively), the level of
which depends on the vehicle's attribute (for the proposal, footprint).
The manufacturers' fleet average performance is determined by the
production-weighted \59\ average (for CAFE, harmonic average) of those
targets. NHTSA and EPA are promulgating CAFE and CO2
emissions standards defined by constrained linear functions and,
equivalently, piecewise linear functions.\60\ As a possible option for
future rulemakings, the constrained linear form was introduced by NHTSA
in the 2007 NPRM proposing CAFE standards for MY 2011-2015. Described
mathematically, the proposed constrained linear function was defined
according to the following formula: \61\
---------------------------------------------------------------------------

    \59\ Production for sale in the United States.
    \60\ The equations are equivalent but are specified differently
due to differences in the agencies' respective models.
    \61\ This function is linear in fuel consumption but not in fuel
economy.
[GRAPHIC] [TIFF OMITTED] TR07MY10.004

---------------------------------------------------------------------------
Where

TARGET = the fuel economy target (in mpg) applicable to vehicles of
a given footprint (FOOTPRINT, in square feet),
a = the function's upper limit (in mpg),
b = the function's lower limit (in mpg),

c = the slope (in gpm per square foot) of the sloped portion of the
function,
d = the intercept (in gpm) of the sloped portion of the function
(that is, the value the sloped portion would take if extended to a
footprint of 0 square feet, and the MIN and MAX functions take the
minimum and maximum, respectively, of the included values; for
example, MIN(1,2) = 1, MAX(1,2) = 2, and
MIN[MAX(1,2),3)]=2.

    Because the format is linear on a gallons-per-mile basis, not on a
miles-per-gallon basis, it is plotted as fuel consumption below.
Graphically, the constrained linear form appears as shown in Figure
II.C-1.
BILLING CODE 6560-50-P
[GRAPHIC] [TIFF OMITTED] TR07MY10.005

    The specific form and stringency for each fleet (passenger car and
light trucks) and model year are defined through specific values for
the four coefficients shown above.
    EPA proposed the equivalent equation below for assigning
CO2 targets to an individual vehicle's footprint value.
Although the general model of the equation is the same for each vehicle
category and each year, the parameters of the equation differ for cars
and trucks and for each model year. Described mathematically, EPA's
proposed piecewise linear function was as follows:

Target = a, if x <= l
Target = cx + d, if l < x <= h
Target = b, if x > h

In the constrained linear form similar in form to the fuel economy
equation above, this equation takes the simplified form:

Target = MIN [ MAX (c * x + d, a), b]

Where

Target = the CO2 target value for a given footprint (in
g/mi)
a = the minimum target value (in g/mi CO2) \62\
---------------------------------------------------------------------------

    \62\ These a, b, d coefficients differ from the a, b, d
coefficients in the constrained linear fuel economy equation
primarily by a factor of 8887 (plus an additive factor for air
conditioning).
---------------------------------------------------------------------------

b = the maximum target value (in g/mi CO2)
c = the slope of the linear function (in g/mi per sq ft
CO2)
d = is the intercept or zero-offset for the line (in g/mi
CO2)
x = footprint of the vehicle model (in square feet, rounded to the
nearest tenth)
l & h are the lower and higher footprint limits or constraints or
(``kinks'') or the boundary between the flat regions and the
intermediate sloped line (in sq ft)

    Graphically, piecewise linear form, like the constrained linear
form, appears as shown in Figure II.C-2.

[GRAPHIC] [TIFF OMITTED] TR07MY10.006

BILLING CODE 6560-50-C

    As for the constrained linear form, the specific form and
stringency of the piecewise linear function for each fleet (passenger
car and light trucks) and model year are defined through specific
values for the four coefficients shown above.
    For purposes of the proposed rules, NHTSA and EPA developed the
basic curve shapes using methods similar to those applied by NHTSA in
fitting the curves defining the MY 2011 standards. The first step
involved defining the relevant vehicle characteristics in the form used
by NHTSA's CAFE model (e.g., fuel economy, footprint, vehicle class,
technology) described in Section II.B of this preamble and in Chapter 1
of the Joint TSD. However, because the baseline fleet utilizes a wide
range of available fuel saving technologies, NHTSA used the CAFE model
to develop a fleet to which all of the technologies discussed in
Chapter 3 of the Joint TSD \63\ were applied, except dieselization and
strong hybridization. This was accomplished by taking the following
steps: (1) Treating all manufacturers as unwilling to pay civil
penalties rather than applying technology, (2) applying any technology
at any time, irrespective of scheduled vehicle redesigns or freshening,
and (3) ignoring ``phase-in caps'' that constrain the overall amount of
technology that can be applied by the model to a given manufacturer's
fleet. These steps helped to increase technological parity among
vehicle models, thereby providing a better basis (than the baseline or
reference fleets) for estimating the statistical relationship between
vehicle size and fuel economy.
---------------------------------------------------------------------------

    \63\ The agencies excluded diesel engines and strong hybrid
vehicle technologies from this exercise (and only this exercise)
because the agencies expect that manufacturers would not need to
rely heavily on these technologies in order to comply with the
proposed standards. NHTSA and EPA did include diesel engines and
strong hybrid vehicle technologies in all other portions of their
analyses.
---------------------------------------------------------------------------

    In fitting the curves, NHTSA and EPA also continued to fit the
sloped portion of the function to vehicle models between the footprint
values at which the agencies continued to apply constraints to limit
the function's value for both the smallest and largest vehicles.
Without a limit at the smallest footprints, the function--whether
logistic or linear--can reach values that would be unfairly burdensome
for a manufacturer that elects to focus on the market for small
vehicles; depending on the underlying data, an unconstrained form,
could result in stringency levels that are technologically infeasible
and/or economically impracticable for those manufacturers that may
elect to focus on the smallest vehicles. On the other side of the
function, without a limit at the largest footprints, the function may
provide no floor on required fuel economy. Also, the safety
considerations that support the provision of a disincentive for
downsizing as a compliance strategy apply weakly, if at all, to the
very largest vehicles. Limiting the function's value for the largest
vehicles leads to a function with an inherent absolute minimum level of
performance, while remaining consistent with safety considerations.
    Before fitting the sloped portion of the constrained linear form,
NHTSA and EPA selected footprints above and below which to apply
constraints (i.e., minimum and maximum values) on the function. The
agencies believe that the linear form performs well in describing the
observed relationship between footprint and fuel consumption or
CO2 emissions for vehicle models within the footprint ranges
covering most vehicle models, but that the single (as opposed to
piecewise) linear form does not perform well in describing this
relationship for the smallest and largest vehicle models. For passenger
cars, the agency noted that several manufacturers offer small, sporty
coupes below 41 square feet, such as the BMW Z4 and Mini, Honda S2000,
Mazda MX-5 Miata, Porsche Carrera and 911, and Volkswagen New Beetle.
Because such vehicles represent a small portion (less than 10 percent)
of the passenger car market, yet often have performance, utility, and/
or structural characteristics that could make it technologically
infeasible and/or economically impracticable for manufacturers focusing
on such vehicles to achieve the very challenging average requirements
that could apply in the absence of a constraint, EPA and NHTSA proposed
to ``cut off'' the linear portion of the passenger car function at 41
square feet. The agencies recognize that for manufacturers who make
small vehicles in this size range, this cut off creates some incentive
to downsize (i.e., further reduce the size, and/or increase the
production of models currently smaller than 41 square feet) to make it
easier to meet the target. The cut off may also create the incentive
for manufacturers who do not currently offer such models to do so in
the future. However, at the same time, the agencies believe that there
is a limit to the market for cars smaller than 41 square feet--most
consumers likely have some minimum expectation about interior volume,
among other things. The agencies thus believe that the number of
consumers who will want vehicles smaller than 41 square feet
(regardless of how they are priced) is small, and that the incentive to
downsize in response to this final rule, if present, will be minimal.
For consistency, the agency proposed to ``cut off'' the light truck
function at the same footprint, although no light trucks are currently
offered below 41 square feet. The agencies further noted that above 56
square feet, the only passenger car model present in the MY 2008 fleet
were four luxury vehicles with extremely low sales volumes--the Bentley
Arnage and three versions of the Rolls Royce Phantom. NHTSA and EPA
therefore also proposed to ``cut off'' the linear portion of the
passenger car function at 56 square feet. Finally, the agencies noted
that although public information is limited regarding the sales volumes
of the many different configurations (cab designs and bed sizes) of
pickup trucks, most of the largest pickups (e.g., the Ford F-150, GM
Sierra/Silverado, Nissan Titan, and Toyota Tundra) appear to fall just
above 66 square feet in footprint. EPA and NHTSA therefore proposed to
``cut off'' the linear portion of the light truck function at 66 square
feet.
    Having developed a set of vehicle emissions and footprint data
which represent the benefit of all non-diesel, non-hybrid technologies,
we determined the initial values for parameters c and d were determined
for cars and trucks separately. c and d were initially set at the
values for which the average (equivalently, sum) of the absolute values
of the differences was minimized between the ``maximum technology''
fleet fuel consumption (within the footprints between the upper and
lower limits) and the straight line of the function defined above at
the same corresponding vehicle footprints. That is, c and d were
determined by minimizing the average absolute residual, commonly known
as the MAD (Mean Absolute Deviation) approach, of the corresponding
straight line.
    Finally, NHTSA calculated the values of the upper and lower
parameters (a and b) based on the corresponding footprints discussed
above (41 and 56 square feet for passenger cars, and 41 and 66 square
feet for light trucks).
    The result of this methodology is shown below in Figures II.C-3 and
II.C-4 for passenger cars and light trucks, respectively. The fitted
curves are shown with the underlying ``maximum technology'' passenger
car and light truck fleets. For passenger cars, the mean absolute
deviation of the sloped portion of the function was 14 percent.

For trucks, the corresponding MAD was 10 percent.
BILLING CODE 6560-50-P
[GRAPHIC] [TIFF OMITTED] TR07MY10.007

[GRAPHIC] [TIFF OMITTED] TR07MY10.008

BILLING CODE 6560-50-C

    The agencies used these functional forms as a starting point to
develop mathematical functions defining the actual proposed standards
as discussed above. The agencies then transposed these functions
vertically (i.e., on a gpm or CO2 basis, uniformly downward)
to produce the same fleetwide fuel economy (and CO2 emission
levels) for cars and light trucks described in the NPRM.
    A number of public comments generally supported the agencies'
choice of attribute-based mathematical functions, as well as the
methods applied to fit the function. Ferrari indicated support for the
use of a constrained linear form rather than a constrained logistic
form, support for the application of limits on the functions' values,
support for a generally less steep passenger car curve compared to MY
2011, and support for the inclusion of all manufacturers in the
analysis used to fit the curves. ICCT also supported the use of a
constrained linear form. Toyota expressed general support for the
methods and outcome, including a less-steep passenger car curve, and
the application of limits on fuel economy targets applicable to the
smallest vehicles. The UAW commented that the shapes and levels of the
curves are reasonable.
    Other commenters suggested that changes to the agencies' methods
and results would yield better outcomes. GM suggested that steeper
curves would provide a greater incentive for limited-line manufacturers
to apply technology to smaller vehicles. GM argued that steeper and, in
their view, fairer curves could be obtained by using sales-weighted
least-squares regression rather than minimization of the unweighted
mean absolute deviation. Conversely, students from UC Santa Barbara
commented that the passenger car and light truck curves should be
flatter and should converge over time in order to encourage the market
to turn, as the agencies' analysis assumes it will, away from light
trucks and toward passenger cars.
    NADA commented that there should be no ``cut-off'' points (i.e.,
lower limits or floors), because these de facto ``backstops'' might
limit consumer choice, especially for light trucks--a possibility also
suggested by the Alliance. The Alliance and several individual
manufacturers also commented that the cut-off point for light trucks
should be shifted to 72 square feet (from the proposed 66 square feet),
arguing that the preponderance of high-volume light truck models with
footprints greater than 66 square feet is such that a 72 square foot
cut-off point makes it unduly challenging for manufacturers serving the
large pickup market and thereby constitutes a de facto backstop. Also,
with respect to the smallest light truck models, Honda commented that
the cut-off point should be set at the point defining the smallest 10
percent of the fleet, both for consistency with the passenger car cut-
off point, and to provide a greater incentive for manufacturers to
downsize the smallest light truck models (which provide greater
functionality than passenger cars).
    Other commenters focused on whether the agencies should have
separate curves for different fleets or whether they should have a
single curve that applied to both passenger cars and light trucks. This
issue is related, to some extent, to commenters who discussed whether
car and truck definitions should change. CARB, Ford, and Toyota
supported separate curves for cars and trucks, generally stating that
different fleets have different functional characteristics and these
characteristics are appropriately addressed by separate curves.
Likewise, AIAM, Chrysler, and NADA supported leaving the current
definitions of car and truck the same. CBD, ICCT, and NESCAUM supported
a single curve, based on concerns about manufacturers gaming the system
and reclassifying passenger cars as light trucks in order to obtain the
often-less stringent light truck standard, which could lead to lower
benefits than anticipated by the agencies.
    In addition, the students from UC Santa Barbara reported being
unable to reproduce the agencies' analysis to fit curves to the
passenger car and light truck fleets, even when using the model,
inputs, and external analysis files posted to NHTSA's Web site when the
NPRM was issued.
    Having considered public comments, NHTSA and EPA have re-examined
the development of curves underlying the standards proposed in the
NPRM, and are promulgating standards based on the same underlying
curves. The agencies have made this decision considering that, while
EISA mandates that CAFE standards be defined by a mathematical function
in terms of one or more attributes related to fuel economy, neither
EISA nor the CAA require that the mathematical function be limited to
the observed or theoretical dependence of fuel economy on the selected
attribute or attributes. As a means by which CAFE and GHG standards are
specified, the mathematical function can and does properly play a
normative role. Therefore, NHTSA and EPA have concluded that, as
supported by comments, the mathematical function can reasonably be
based on a blend of analytical and policy considerations, as discussed
below and in the Joint Technical Support Document.
    With respect to GM's recommendation that NHTSA and EPA use weighted
least-squares analysis, the agencies find that the market forecast used
for analysis supporting both the NPRM and the final rule exhibits the
two key characteristics that previously led NHTSA to use minimization
of the unweighted Mean Absolute Deviation (MAD) rather than weighted
least-squares analysis. First, projected model-specific sales volumes
in the agencies' market forecast cover an extremely wide range, such
that, as discussed in NHTSA's rulemaking for MY 2011, while unweighted
regression gives low-selling vehicle models and high-selling vehicle
models equal emphasis, sales-weighted regression would give some
vehicle models considerably more emphasis than other vehicle
models.\64\ The agencies' intention is to fit a curve that describes a
technical relationship between fuel economy and footprint, given
comparable levels of technology, and this supports weighting discrete
vehicle models equally. On the other hand, sales weighted regression
would allow the difference between other vehicle attributes to be
reflected in the analysis, and also would reflect consumer demand.
---------------------------------------------------------------------------

    \64\ For example, the agencies' market forecast shows MY 2016
sales of 187,000 units for Toyota's 2WD Sienna, and shows 27 model
configurations with MY 2016 sales of fewer than 100 units.
Similarly, the agencies' market forecast shows MY 2016 sales of
268,000 for the Toyota Prius, and shows 29 model configurations with
MY 2016 sales of fewer than 100 units. Sales-weighted analysis would
give the Toyota Sienna and Prius more than a thousand times the
consideration of many vehicle model configurations. Sales-weighted
analysis would, therefore, cause a large number of vehicle model
configurations to be virtually ignored. See discussion in NHTSA's
final rule for MY 2011 passenger car and light truck CAFE standards,
74 FR 14368 (Mar. 30, 2009), and in NHTSA's NPRM for that
rulemaking, 73 FR 24423-24429 (May 2, 2008).
---------------------------------------------------------------------------

    Second, even after NHTSA's ``maximum technology'' analysis to
increase technological parity of vehicle models before fitting curves,
the agencies' market forecast contains many significant outliers. As
discussed in NHTSA's rulemaking for MY 2011, MAD is a statistical
procedure that has been demonstrated to produce more efficient
parameter estimates than least-squares analysis in the presence of
significant outliers.\65\ In addition, the

agencies remain concerned that the steeper curves resulting from
weighted least-squares analysis would increase the risk that energy
savings and environmental benefits would be lower than projected,
because the steeper curves would provide a greater incentive to
increase sales of larger vehicles with lower fuel economy levels. Based
on these technical considerations and these concerns regarding
potential outcomes, the agencies have decided not to re-fit curves
using weighted least-squares analysis, but note that they may
reconsider using least-squares regression in future analysis.
---------------------------------------------------------------------------

    \65\ Id. In the case of a dataset not drawn from a sample with a
Gaussian, or normal, distribution, there is often a need to employ
robust estimation methods rather than rely on least-squares approach
to curve fitting. The least-squares approach has as an underlying
assumption that the data are drawn from a normal distribution, and
hence fits a curve using a sum-of-squares method to minimize errors.
This approach will, in a sample drawn from a non-normal
distribution, give excessive weight to outliers by making their
presence felt in proportion to the square of their distance from the
fitted curve, and, hence, distort the resulting fit. With outliers
in the sample, the typical solution is to use a robust method such
as a minimum absolute deviation, rather than a squared term, to
estimate the fit (see, e.g., ``AI Access: Your Access to Data
Modeling,'' at http://www.aiaccess.net/English/Glossaries/GlosMod/
e_gm_O_Pa.htm#Outlier). The effect on the estimation is to let
the presence of each observation be felt more uniformly, resulting
in a curve more representative of the data (see, e.g., Peter
Kennedy, A Guide to Econometrics, 3rd edition, 1992, MIT Press,
Cambridge, MA).
---------------------------------------------------------------------------

    NHTSA and EPA have considered GM's comment that steeper curves
would provide a greater incentive for limited-line manufacturers to
apply technology to smaller vehicles. While the agencies agree that a
steeper curve would, absent any changes in fleet mix, tend to shift
average compliance burdens away from GM and toward companies that make
smaller vehicles, the agencies are concerned, as stated above, that
steeper curves would increase the risk that induced increases in
vehicle size could erode projected energy and environmental benefits.
    NHTSA and EPA have also considered the comments by the students
from UC Santa Barbara indicating that the passenger car and light truck
curves should be flatter and should converge over time. The agencies
conclude that flatter curves would reduce the incentives intended in
shifting from ``flat'' CAFE standards to attribute-based CAFE and GHG
standards--those being the incentive to respond to attribute-based
standards in ways that minimize compromises in vehicle safety, and the
incentive for more manufacturers (than primarily those selling a wider
range of vehicles) across the range of the attribute to have to
increase the application of fuel-saving technologies. With regard to
whether the agencies should set separate curves or a single one, NHTSA
also notes that EPCA requires NHTSA to establish standards separately
for passenger cars and light trucks, and thus concludes that the
standards for each fleet should be based on the characteristics of
vehicles in each fleet. In other words, the passenger car curve should
be based on the characteristics of passenger cars, and the light truck
curve should be based on the characteristics of light trucks--thus to
the extent that those characteristics are different, an artificially-
forced convergence would not accurately reflect those differences.
However, such convergence could be appropriate depending on future
trends in the light vehicle market, specifically further reduction in
the differences between passenger car and light truck characteristics.
While that trend was more apparent when car-like 2WD SUVs were
classified as light trucks, it seems likely to diminish for the model
year vehicles subject to these rules as the truck fleet will be more
purely ``truck-like'' than has been the case in recent years.
    NHTSA and EPA have also considered comments on the maxima and
minima that the agencies have applied to ``cut off'' the linear
function underlying the proposed curves for passenger cars and light
trucks. Contrary to NADA's suggestion that there should be no such cut-
off points, the agencies conclude that curves lacking maximum fuel
economy targets (i.e., minimum CO2 targets) would result in
average fuel economy and GHG requirements that would not be
technologically feasible or economically practicable for manufacturers
concentrating on those market segments. In addition, minimum fuel
economy targets (i.e., maximum CO2 targets) are important to
mitigate the risk to energy and environmental benefits of potential
market shifts toward large vehicles. The agencies also disagree with
comments by the Alliance and several individual manufacturers that the
cut-off point for light trucks should be shifted to 72 square feet
(from the proposed 66 square feet) to ease compliance burdens facing
manufacturers serving the large pickup market. Such a shift would
increase the risk that energy and environmental benefits of the
standards would be compromised by induced increases in the sales of
large pickups, in situations where the increased compliance burden is
feasible and appropriate. Also, the agencies' market forecast suggests
that most of the light trucks models with footprints larger than 66
square feet have curb weights near or above 5,000 pounds. This
suggests, in turn, that in terms of highway safety, there is little or
no need to discourage downsizing of light trucks with footprints larger
than 66 square feet. Based on these energy, environmental,
technological feasibility, economic practicability, and safety
considerations, the agencies conclude that the light truck curve should
be cut off at 66 square feet, as proposed, rather than at 72 square
feet. The agencies also disagree with Honda's suggestion that the cut-
off point for the smallest trucks be shifted to a larger footprint
value, because doing so could potentially increase the incentive to
reclassify vehicles in that size range as light trucks, and could
thereby increase the possibility that energy and environmental benefits
of the rule would be less than projected.
    Finally, considering comments by the UC Santa Barbara students
regarding difficulties reproducing NHTSA's analysis, NHTSA reexamined
its analysis, and discovered some erroneous entries in model inputs
underlying the analysis used to develop the curves proposed in the
NPRM. These errors are discussed in NHTSA's final Regulatory Impact
Analysis (FRIA) and have since been corrected. They include the
following: Incorrect valvetrain phasing and lift inputs for many BMW
engines, incorrect indexing for some Daimler models, incorrectly
enabled valvetrain technologies for rotary engines and Atkinson cycle
engines, omitted baseline applications of cylinder deactivation in some
Honda and GM engines, incorrect valve phasing codes for some 4-cylinder
Chrysler engines, omitted baseline applications of advanced
transmissions in some VW models, incorrectly enabled advanced
electrification technologies for several hybrid vehicle models, and
incorrect DCT effectiveness estimates for subcompact passenger cars.
These errors, while not significant enough to impact the overall
analysis of stringency, did affect the fitted slope for the passenger
car curve and would have prevented precise replication of NHTSA's NPRM
analysis by outside parties.
    After correcting these errors and repeating the curve development
analysis presented in the NPRM, NHTSA obtained the curves shown below
in Figures II.C-5 and II.C-6 for passenger cars and light trucks,
respectively. The fitted curves are shown with the underlying ``maximum
technology'' passenger car and light truck fleets. For passenger cars,
the mean absolute deviation of the sloped portion of the function was
14 percent. For trucks, the corresponding MAD was 10 percent.
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[GRAPHIC] [TIFF OMITTED] TR07MY10.009

[GRAPHIC] [TIFF OMITTED] TR07MY10.010

    This refitted passenger car curve is similar to that presented in
the NPRM, and the refitted light truck curve is nearly identical to the
corresponding curve in the NPRM. However, the slope of the refitted
passenger car curve is about 27 percent steeper (on a gpm per sf basis)
than the curve presented in the NPRM. For passenger cars and light
trucks, respectively, Figures II.C-7 and II.C-8 show the results of
adjustment--discussed in the next section--of the above curves to yield
the average required fuel economy levels corresponding to the final
standards.
[GRAPHIC] [TIFF OMITTED] TR07MY10.011

[GRAPHIC] [TIFF OMITTED] TR07MY10.012

BILLING CODE 6560-50-C
    While the resultant light truck curves are visually
indistinguishable from one another, the refitted curve for passenger
cars would increase stringency for the smallest cars, decrease
stringency for the largest cars, and provide a greater incentive to
increase vehicle size throughout the range of footprints within which
NHTSA and EPA project most passenger car models will be sold through MY
2016. The agencies are concerned that these changes would make it
unduly difficult for manufacturers to introduce new small passenger
cars in the United States, and unduly risk losses in energy and
environmental benefits by increasing incentives for the passenger car
market to shift toward larger vehicles.
    Also, the agencies note that the refitted passenger car curve
produces only a slightly closer fit to the corrected fleet than would
the curve estimated in

the NPRM; with respect to the corrected fleet (between the ``cut off''
footprint values, and after the ``maximum technology'' analysis
discussed above), the mean absolute deviation for the refitted curve is
13.887 percent, and that of a refitted curve held to the original slope
is 13.933 percent. In other words, the data support the original slope
very nearly as well as they support the refitted slope.
    Considering NHTSA's and EPA's concerns regarding the change in
incentives that would result from a refitted curve for passenger cars,
and considering that the data support the original curves about as well
as they would support refitted curves, the agencies are finalizing CAFE
and GHG standards based on the curves presented in the NPRM.
    Finally, regarding some commenters' inability to reproduce the
agencies' NPRM analysis, NHTSA believes that its correction of the
errors discussed above and its release (on NHTSA's Web site) of the
updated Volpe model and all accompanying inputs and external analysis
files should enable outside parties to independently reproduce the
agencies' analysis. If outside parties continue to experience
difficulty in doing so, we encourage them to contact NHTSA, and the
agency will do its best to provide assistance.
    Thus, in summary, the agencies' approach to developing the
attribute-based mathematical functions for MY 2012-2016 CAFE and
CO2 standards represents the agencies' best technical
judgment and consideration of potential outcomes at this time, and we
are confident that the conclusions have resulted in appropriate and
reasonable standards. The agencies recognize, however, that aspects of
these decisions may merit updating or revision in future analysis to
support CAFE and CO2 standards or for other purposes.
Consistent with best rulemaking practices, the agencies will take a
fresh look at all assumptions and approaches to curve fitting,
appropriate attributes, and mathematical functions in the context of
future rulemakings.
    The agencies also recognized in the NPRM the possibility that lower
fuel prices could lead to lower fleetwide fuel economy (and higher
CO2 emissions) than projected in this rule. One way of
addressing that concern is through the use of a universal standard--
that is, an average standard set at a (single) absolute level. This is
often described as a ``backstop standard.'' The agencies explained that
under the CAFE program, EISA requires such a minimum average fuel
economy standard for domestic passenger cars, but is silent with regard
to similar backstops for imported passenger cars and light trucks,
while under the CAA, a backstop could be adopted under section 202(a)
assuming it could be justified under the relevant statutory criteria.
NHTSA and EPA also noted that the flattened portions of the curves at
the largest footprints directionally address the issue of a backstop
(i.e., the mpg ``floor'' or gpm ``ceiling'' applied to the curves
provides a universal and absolute value for that range of footprints).
The agencies sought comment on whether backstop standards, or any other
method within the agencies' statutory authority, should and can be
implemented in order to guarantee a level of CO2 emissions
reductions and fuel savings under the attribute-based standards.
    The agencies received a number of comments regarding the need for a
backstop beyond NHTSA's alternative minimum standard. Comments were
divided fairly evenly between support for and opposition to additional
backstop standards. The following organizations supported the need for
EPA and NHTSA to have explicit backstop standards: American Council for
an Energy Efficient Economy (ACEEE), American Lung Association,
California Air Resources Board (CARB), Environment America, Environment
Defense Fund, Massachusetts Department of Environmental Protection,
Natural Resources Defense Council (NRDC), Northeast States for
Coordinated Air Use Management (NESCAUM), Public Citizen and Safe
Climate Campaign, Sierra Club, State of Washington Department of
Ecology, Union of Concerned Scientists, and a number of private
citizens. Commenters in favor of additional backstop standards for all
fleets for both NHTSA and EPA \66\ generally stated that the emissions
reductions and fuel savings expected to be achieved by MY 2016 depended
on assumptions about fleet mix that might not come to pass, and that
various kinds of backstop standards or ``ratchet mechanisms'' \67\ were
necessary to ensure that those reductions were achieved in fact. In
addition, some commenters \68\ stated that manufacturers might build
larger vehicles or more trucks during MYs 2012-2016 than the agencies
project, for example, because (1) any amount of slope in target curves
encourages manufacturers to upsize, and (2) lower targets for light
trucks than for passenger cars encourage manufacturers to find ways to
reclassify vehicles as light trucks, such as by dropping 2WD versions
of SUVs and offering only 4WD versions, perhaps spurred by NHTSA's
reclassification of 2WD SUVs as passenger cars. Both of these
mechanisms will be addressed further below. Some commenters also
discussed EPA authority under the CAA to set backstops,\69\ agreeing
with EPA's analysis that section 202(a) allows such standards since EPA
has wide discretion under that section to craft standards.
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    \66\ ACEEE, American Lung Association, CARB, Christopher Lish,
Environment America, EDF, MA DEP, NRDC, NESCAUM, Public Citizen,
Sierra Club et al., SCAQMD, UCS, WA DE.
    \67\ Commenters generally defined a ``ratchet mechanism'' as an
automatic re-calculation of stringency to ensure cumulative goals
are reached by 2016, even if emissions reductions and fuel savings
fall short in the earlier years covered by the rulemaking.
    \68\ CBD, MA DEP, NJ DEP, Public Citizen, Sierra Club et al.,
UCS.
    \69\ CARB, Public Citizen, Sierra Club et al.
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    The following organizations opposed a backstop: Alliance of
Automobile Manufacturers (AAM), Association of International Automobile
Manufacturers (AIAM), Ford Motor Company, National Automobile Dealers
Association (NADA), Toyota Motor Company, and the United Auto Workers
Union. Commenters stating that additional backstops would not be
necessary disagreed that upsizing was likely,\70\ and emphasized the
anti-backsliding characteristics of the target curves. Others argued
that universal absolute standards as backstops could restrict consumer
choice of vehicles. Commenters making legal arguments under EPCA/
EISA\71\ stated that Congress' silence regarding backstops for imported
passenger cars and light trucks should be construed as a lack of
authority for NHTSA to create further backstops. Commenters making
legal arguments under the CAA\72\ focused on the lack of clear
authority under the CAA to create multiple GHG emissions standards for
the same fleets of vehicles based on the same statutory criteria, and
opposed EPA taking steps that would reduce harmonization with NHTSA in
standard setting. Furthermore, AIAM indicated that EISA's requirement
that the combined (car and truck) fuel economy level reach at least 35
mpg by

2020 itself constitutes a backstop.\73\ One individual \74\ commented
that while additional backstop standards might be necessary given
optimism of fleet mix assumptions, both agencies' authorities would
probably need to be revised by Congress to clarify that backstop
standards (whether for individual fleets or for the national fleet as a
whole) were permissible.
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    \70\ For example, the Alliance and Toyota said that upsizing
would not be likely because (1) it would not necessarily make
compliance with applicable standards easier, since larger vehicles
tend to be heavier and heavier vehicles tend to achieve worse fuel
economy/emissions levels; (2) it may require expensive platform
changes; (3) target curves become increasingly more stringent from
year to year, which reduces the benefits of upsizing; and (4) the
mpg floor and gpm ceiling for the largest vehicles (the point at
which the curve is ``cut off'') discourages manufacturers from
continuing to upsize beyond a point because doing so makes it
increasingly difficult to meet the flat standard at that part of the
curve.
    \71\ AIAM, Alliance, Ford, NADA, Toyota.
    \72\ Alliance, Ford, NADA, UAW.
    \73\ NHTSA and EPA agree with AIAM that the EISA 35 mpg
requirement in MY 2020 has a backstop-like function, in that it
requires a certain level of achieved fleetwide fuel economy by a
certain date, although it is not literally a backstop standard.
Considering that NHTSA's MY 2011 CAFE standards increased projected
average fuel economy requirements (relative to the MY 2010
standards) at a significantly faster rate than would be required to
achieve the 35-in-2020 requirement, and considering that the
standards being finalized today would increase projected average
combined fuel economy requirements to 34.1 mpg in MY 2016, four
years before MY 2020, the agencies believe that the U.S. vehicle
market would have to shift in highly unexpected ways in order to put
the 35-in-2020 requirement at risk, even despite the fact that due
to the attribute-based standards, average fuel economy requirements
will vary depending on the mix of vehicles produced for sale in the
U.S. in each model year. The agencies further emphasize that both
NHTSA and EPA plan to conduct and document retrospective analyses to
evaluate how the market's evolution during the rulemaking timeframe
compares with the agencies' forecasts employed for this rulemaking.
Additionally, we emphasize that both agencies have the authority,
given sufficient lead time, to revise their standards upwards if
necessary to avoid missing the 35-in-2020 requirement.
    \74\ Schade.
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    In response, EPA and NHTSA remain confident that their projections
of the future fleet mix are reliable, and that future changes in the
fleet mix of footprints and sales are not likely to lead to more than
modest changes in projected emissions reductions or fuel savings.\75\
Both agencies thus remain confident in these fleet projections and the
resulting emissions reductions and fuel savings from the standards. As
explained in Section II.B above, the agencies' projections of the
future fleet are based on the most transparent information currently
available to the agencies. In addition, there are only a relatively few
model years at issue. Moreover, market trends today are consistent with
the agencies' estimates, showing shifts from light trucks to passenger
cars and increased emphasis on fuel economy from all vehicles.
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    \75\ For reference, NHTSA's March 2009 final rule establishing
MY 2011 CAFE standards was based on a forecast that passenger cars
would represent 57.6 percent of the MY 2011 fleet, and that MY 2011
passenger cars and light trucks would average 45.6 square feet (sf)
and 55.1 sf, respectively, such that average required CAFE levels
would be 30.2 mpg, 24.1 mpg, and 27.3 mpg, respectively, for
passenger cars, light trucks, and the overall light-duty fleet.
Based on the agencies' current market forecast, even as soon as MY
2011, passenger cars will comprise a larger share (59.2 percent) of
the light vehicle market; passenger cars and light trucks will, on
average, be smaller by 0.5 sf and 1.3 sf, respectively; and average
required CAFE levels will be higher by 0.2 mpg, 0.3 mpg, and 0.3
mpg, respectively, for passenger cars, light trucks, and the overall
light-duty fleet.
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    Finally, the shapes of the curves, including the ``flattening'' at
the largest footprint values, tend to avoid or minimize regulatory
incentives for manufacturers to upsize their fleet to change their
compliance burden. Given the way the curves are fit to the data points
(which represent vehicle models' fuel economy mapped against their
footprint), the agencies believe that there is little real benefit to
be gained by a manufacturer upsizing their vehicles. As discussed
above, the agencies' analysis indicates that, for passenger car models
with footprints falling between the two flattened portions of the
corresponding curve, the actual slope of fuel economy with respect to
footprint, if fit to that data by itself, is about 27 percent steeper
than the curve the agencies are promulgating today. This difference
suggests that manufacturers would, if anything, have more to gain by
reducing vehicle footprint than by increasing vehicle footprint. For
light trucks, the agencies' analysis indicates that, for models with
footprints falling between the two flatted portions of the
corresponding curve, the slope of fuel economy with respect to
footprint is nearly identical to the curve the agencies are
promulgating today. This suggests that, within this range,
manufacturers would typically have little incentive to either
incrementally increase or reduce vehicle footprint. The agencies
recognize that based on economic and consumer demand factors that are
external to this rule, the distribution of footprints in the future may
be different (either smaller or larger) than what is projected in this
rule. However, the agencies continue to believe that there will not be
significant shifts in this distribution as a direct consequence of this
rule.
    At the same time, adding another backstop standard would have
virtually no effect if the standard was weak, but a more stringent
backstop could compromise the objectives served by attribute-based
standards--that they distribute compliance burdens more equally among
manufacturers, and at the same time encourage manufacturers to apply
fuel-saving technologies rather than simply downsizing their vehicles,
as they did in past decades under flat standards. This is why Congress
mandated attribute-based CAFE standards in EISA. This compromise in
objectives could occur for any manufacturer whose fleet average was
above the backstop, irrespective of why they were above the backstop
and irrespective of whether the industry as a whole was achieving the
emissions and fuel economy benefits projected for the final standards,
the problem the backstop is supposed to address. For example, the
projected industry wide level of 250 gm/mile for MY 2016 is based on a
mix of manufacturer levels, ranging from approximately 205 to 315 gram/
mile \76\ but resulting in an industry wide basis in a fleet average of
250 gm/mile. Unless the backstop was at a very weak level, above the
high end of this range, then some percentage of manufacturers would be
above the backstop even if the performance of the entire industry
remains fully consistent with the emissions and fuel economy levels
projected for the final standards. For these manufacturers and any
other manufacturers who were above the backstop, the objectives of an
attribute based standard would be compromised and unnecessary costs
would be imposed. This could directionally impose increased costs for
some manufacturers. It would be difficult if not impossible to
establish the level of a backstop standard such that costs are likely
to be imposed on manufacturers only when there is a failure to achieve
the projected reductions across the industry as a whole. An example of
this kind of industry wide situation could be when there is a
significant shift to larger vehicles across the industry as a whole, or
if there is a general market shift from cars to trucks. The problem the
agencies are concerned about in those circumstances is not with respect
to any single manufacturer, but rather is based on concerns over shifts
across the fleet as a whole, as compared to shifts in one
manufacturer's fleet that may be more than offset by shifts the other
way in another manufacturer's fleet. However, in this respect, a
traditional backstop acts as a manufacturer specific standard.