Subject: Additional EPA NPRM material regarding sensitivitie s and technical feasiblity

From: William Charmley/AA/USEPA/US
To: Chandana_L._Achanta@omb.eop.gov
Cc: Robin Moran/AA/USEPA/US@EPA, james.tamm@dot.gov, re becca.yoon@dot.gov
Date: 11/09/2011 12:56 PM

Chandana -

Included in this email are 2 elements of the EPA pr oposal which were not included in the October 12, 2011 submission for the light-duty 2017-2025 propos al.

Sensitivities : We have included sensitivity assessments for 4 e lements of the proposal: mass reduction costs, battery pack costs, indirect cost multipliers, and learning curve rates. We also pro vide a discussion of why we have not performed a sensitivi ty assessment using the 2010 NAS Study. This material will go into a EPA Draft RIA Chapter 3, in a new section 3.13. It is on pages 1-7 of the att ached

Feasibility assessment : EPA has included an assessment of MY2011 and 201 2 vehicles available today and assessed their CO2 performance in relationship to the proposed CO2 standard footprint curves. We have a discussion of this for Preamble III.D (pages 8-11 of the attached), and m ore detail on the actual data analyzed for the EPA Draf t RIA Chapter 3, Section 3.11 (pages 12-16 of the attached).

Thanks

Bill

EPA DRIA and Preamble Sections on Uncertainty and F easiblity, 11.9.2011.docx1



### EPA Submission to OMB on 11.9.2011, additional ligh t-duty 2017-2025

NPRM Draft RIA and Preamble III sub-sections



## EPA Draft RIA Chapter 3

Section 3.12 Cost Sensitivities

3.1.1 Overview

We have conducted several sensitivity analyses on a variety of input parameters. For the analyses presented in and have run the OMEGA mo del to generate 2025MY results for

each of these sensitivities. We have looked at dif ferent levels of mass reduction costs, battery pack costs, indirect cost multipliers, and learning rates. These sensitivities are summarized in Table 0-1, with the summarized results in Table 0-1 0 . Additional sensitivities with regard to benefits are shown in DRIA Chapter 4.

Table 0-1 - Summary of Cost Sensitivities

Sensitivity parameter Low side sensitivity High sid e sensitivity

Mass reduction direct manufacturing costs 40% lower 40% higher

Battery pack direct manufacturing costs 10% lower for P2 HEVs

20% lower for PHEV/EV 10% higher for P2 HEVs 20% higher for PHEV/EV Indirect cost multipliers Low side of 95% confidenc e interval of modified Delphi survey results High side of 95%

confidence interval of modified Delphi survey

results Learning rates a P-value of 30% on steep portion of the curve; cost

reductions of 4%/3%/2% per year for each 5 year increment on the flat portion of the learning curve P-value of 10% on steep portion of the curve; cost

reductions of 2%/1%/0% per year for each 5 year increment on the flat portion of the learning curve

a Higher learning rates results in lower costs, henc e the low side sensitivity uses the higher learning rates while the high side sensitivity uses the lower lear ning rates.

3.1.2 Mass Sensitivity

For the mass reduction cost sensitivity, we adjuste d the mass reduction DMC cost equation by +/-40%. That cost equation is shown in Table 2 along with the cost equation used

for each side of the mass reduction cost sensitivit y.2 Table 0-2 - Mass Reduction Cost Sensitivities

Sensitivity parameter Mass reduction DMC equation used

Low side DMC=$2.60x, where x=% mass reduction Primary case DMC=$4.33x, where x=% mass reduction High side DMC=$6.06x, where x=% mass reduction

We did not re-rank OMEGA packages for the mass redu ction cost sensitivities but rather used the same input files used for our prima ry analysis with new mass costs. Because mass reduction is a cost effective technology, even with higher costs, we believe that OMEGA would still choose a similar degree of mass r eduction. By contrast, even with lower costs, mass reduction would still be limited by the fatality analysis. As a result, the mass reduction sensitivity does not have any impact on t he relative ranking of packages or the engine and hybridization technologies that would be added in response to our proposed

standards.

The high mass cost inputs increased the average com pliance costs of the reference case by $31 and the control case by $133, for a ne t average per-vehicle cost increase of $102 in MY 2025. The low mass cost inputs decreased th e average compliance costs of the reference case by $31 and the control case by $133 for a net average cost decrease of $102 These impacts would be greater on manufacturers tha t use more mass reduction technology,

and less on those that use less.

3.1.3 Battery Sensitivity

For the battery pack cost sensitivities, we decreas ed/increased the battery pack DMCs by the amounts shown in Table 0-3. As presented in Chapter 3 of the draft joint TSD, we have developed linear regressions for our battery p ack costs. These linear regressions provide battery pack DCM as a function of net weight reduct ion of the vehicle. Table 0-3 and Table 0-5 show the linear regressions used for our low si de and high side sensitivity analyses, respectively, while Table 0-4 presents the linear r egressions used for our primary analysis (as presented in Chapter 3 of the draft joint TSD).

Table 0-3 - Linear Regressions of Battery Pack Dire ct Manufacturing Costs vs Net

Weight Reduction used for Low Side Sensitivity (200 9$)

Vehicle Class P2 HEV PHEV20 PHEV40 EV75 EV100 EV150
Subcompact -$159x+$645 -$690x+$2,082 -$694x+$2,919 -$1,080x+$4,339 -$1,651x+$5,088 -$1,615x+$6,633

Small car -$196x+$682 -$798x+$2,197 -$1,675x+$3,229 -$1,626x+$4,710 -$2,279x+$5,603 -$2,480x+$7,350
Large car -$270x+$777 -$1,255x+$2,664 -$2,521x+$4,153 -$2,768x+$5,738 -$3,215x+$6,481 -$3,016x+$8,791

Minivan -$265x+$763 -$1,152x+$2,637 -$1,672x+$4,028 -$2,784x+$5,761 -$2,472x+$6,731 -$3,653x+$9,397

Small truck -$249x+$740 -$1,071x+$2,514 -$1,955x+$3,829 -$2,518x+$5,463 -$2,377x+$6,436 $9,003 Minivan+towing -$265x+$836 Large truck -$285x+$868

Notes: “x” in the equations represents the net weight redu ction as a percentage, so a subcompact P2 HEV batte ry pack with a 20% applied weight reduction and, therefore, a 15% net weight reduction would cost (- $159)x(15%)+$645=$621. The small truck EV150 regression has no slope since the net weight reduction is always 0 due to the 20 % weight3

reduction hit. The agencies did not regress PHEV or EV costs for t he minivan+towing and large truck vehicle classes s ince we

do not believe these vehicle classes would use the technologies.

Table 0-4 - Linear Regressions of Battery Pack Dir ect Manufacturing Costs vs Net

Weight Reduction used for the Primary Analysis (200 9$)

Vehicle Class P2 HEV PHEV20 PHEV40 EV75 EV100 EV150
Subcompact -$177x+$716 -$862x+$2,602 -$867x+$3,649 -$1,350x+$5,424 -$2,064x+$6,360 -$2,019x+$8,292

Small car -$218x+$758 -$998x+$2,746 -$2,093x+$4,037 -$2,033x+$5,888 -$2,849x+$7,004 -$3,100x+$9,187
Large car -$300x+$864 -$1,568x+$3,331 -$3,152x+$5,192 -$3,460x+$7,173 -$4,019x+$8,101 -$3,770x+$10,989

Minivan -$294x+$848 -$1,439x+$3,296 -$2,090x+$5,035 -$3,480x+$7,201 -$3,090x+$8,414 -$4,566x+$11,746

Small truck -$277x+$822 -$1,338x+$3,143 -$2,444x+$4,787 -$3,148x+$6,828 -$2,971x+$8,045 $11,253 Minivan+towing -$294x+$929 Large truck -$317x+$964

Notes: “x” in the equations represents the net weight redu ction as a percentage, so a subcompact P2 HEV batte ry pack with a 20% applied weight reduction and, therefore, a 15% net weight reduction would cost (- $177)x(15%)+$716=$689. The small truck EV150 regression has no slope since the net weight reduction is always 0 due to the 20 % weight

reduction hit. The agencies did not regress PHEV or EV costs for t he minivan+towing and large truck vehicle classes s ince we

do not believe these vehicle classes would use the technologies.

Table 0-5 - Linear Regressions of Battery Pack Dire ct Manufacturing Costs vs Net

Weight Reduction used for the High Side Sensitivity (2009$)

Vehicle

Class P2 HEV PHEV20 PHEV40 EV75 EV100 EV150

Subcompact -$194x+$788 - $1,034x+$3,123 -

$1,041x+$4,378 -

$1,620x+$6,509 -$2,477x+$7,632 -$2,423x+$9,950

Small car -$240x+$834 - $1,197x+$3,295 -

$2,512x+$4,844 -

$2,439x+$7,065 -$3,419x+$8,404 - $3,720x+$11,024

Large car -$330x+$950 - $1,882x+$3,997 -

$3,782x+$6,230 -

$4,152x+$8,607 -$4,823x+$9,722 - $4,524x+$13,187

Minivan -$324x+$933 - $1,727x+$3,955 -

$2,508x+$6,042 -

$4,176x+$8,641 -

$3,708x+$10,097 -

$5,479x+$14,096

Small truck -$304x+$904 - $1,606x+$3,771 -

$2,933x+$5,744 -

$3,777x+$8,194 -$3,565x+$9,654 $13,504

Minivan+towing -$324x+$1,022 Large truck -$348x+$1,061

Notes: “x” in the equations represents the net weight redu ction as a percentage, so a subcompact P2 HEV batte ry pack with a 20% applied weight reduction and, therefore, a 15 % net weight reduction would cost (-$194)x(15%)+$78 8=$759. The small truck EV150 regression has no slope since the net weight reduction is always 0 due to the 20 % weight

reduction hit. The agencies did not regress PHEV or EV costs for t he minivan+towing and large truck vehicle classes s ince we do

not believe these vehicle classes would use the tec hnologies.

For the battery pack sensitivities, unlike the mass reduction sensitivities, we did rerank OMEGA packages. However, we started with the master-sets of packages as described in Chapter 1 of this draft RIA for both the 2016MY and 2025MY and did not start with preliminary-sets of packages and conduct a full pac kage building/ranking process. Using the master-sets of packages, we inserted new battery pa ck costs, re-ranked the master-sets of packages to get the proper ordering of packages for each sensitivity case, then ran OMEGA.

The high battery cost inputs increased the average compliance costs of the reference case by $2 and the control case by $63, for a net c ost increase of $61. In the high case, the4

penetration of EVs decreased from 2.8% to 2.2%, as companies chose more cost effective options. MY 2025 HEV penetration increased from 15% to 17%. The low battery cost inputs decreased the average compliance costs of the refer ence case by $2 and the control case by $103 for a net decrease of $101. In the low cost case, the MY 2025 penetration of EVs increased to 3.9%, while the HEV penetration decrea sed to 10%. In general, changing the battery costs shifted the choice between HEVs and E Vs. As both EVs and HEVs are less cost effective (in this set of inputs) than conventional technologies, the penetrations of non-battery dependent technologies was little changed.

3.1.4 ICM Sensitivity

For the ICM sensitivity, we looked at the 95% confi dence intervals of the survey responses gathered as part of the modified Delphi p rocess used to generate our low, medium and high2 complexity ICMs. We discuss this modifie d Delphi process in Chapter 3 of the draft joint TSD and provide details in a memorandum to the docket. A In that memorandum, the survey responses from each respondent are prese nted for each element of the ICM along with average responses, standard deviations and oth er statistical measures. Using these, we

calculate the ICM elements at the low side of the 9 5% confidence interval and at the high

side. Table 0-6 and Table 0-8 show the ICMs used f or the low side and high side sensitivity analyses, respectively, while Table 0-7 shows the I CMs used for our primary analysis. For the High1 ICM, since it was generated using a conse nsus approach rather than blind surveys, we have scaled the ICM elements using the same rati os as resulted from the 95% confidence intervals for the High2 ICM.

Table 0-6 - ICMs used for the Low Side Sensitivity

Near term Long term Summed
Complexity Warranty Non-warranty Warranty Non-warra nty Near term Long term

Low 0.004 0.113 0.001 0.090 1.118 1.091

Medium 0.037 0.225 0.025 0.148 1.262 1.174 High1 0.043 0.361 0.027 0.217 1.404 1.243 High2 0.048 0.479 0.041 0.272 1.528 1.313

Table 0-7 - ICMs used for the Primary Analysis

Near term Long term Summed
Complexity Warranty Non-warranty Warranty Non-warra nty Near term Long term

Low 0.012 0.230 0.005 0.187 1.242 1.193

Medium 0.045 0.343 0.031 0.259 1.387 1.290 High1 0.065 0.499 0.032 0.314 1.564 1.345 High2 0.074 0.696 0.049 0.448 1.770 1.497

Table 0-8 - ICMs used for the High Side Sensitivit y

Near term Long term Summed
Complexity Warranty Non-warranty Warranty Non-warra nty Near term Long term

Low 0.019 0.347 0.010 0.284 1.366 1.294

Medium 0.052 0.461 0.037 0.369 1.513 1.406

A “Documentation of the Development of Indirect Cost Multipliers for Three Automotive Technologies,” Helfand, G., and Sherwood, T., Memorandum dated Aug ust 2009.5 High1 0.087 0.637 0.037 0.411 1.723 1.447 High2 0.099 0.914 0.057 0.623 2.012 1.680

Like done for the battery pack sensitivities, we re -ranked OMEGA packages using the master-sets of packages as described in Chapter 1 o f this draft RIA for the 2016MY and 2025MY. We did not start with preliminary-sets of packages and conduct a full package building/ranking process. Using the master-sets of packages, we inserted new costs calculated using the low/high IMCs, re-ranked the m aster-sets of packages to get the proper ordering of packages for each sensitivity case, the n ran OMEGA.

The high ICM inputs increased the average complianc e costs of the reference case by $63 and the control case by $312, for a net average per-vehicle cost increase of $249 in MY 2025. The low ICM inputs decreased the average com pliance costs of the reference case by $105 and the control case by $349 for a net average cost decrease of $244.

3.1.5 Learning Rate Sensitivity

For the learning rate sensitivity, we increased the learning effects for the low side case and decreased the learning effects for the high sid e case. This sounds counterintuitive, but we have done this because the increased learning rates result in lower technology costs so, therefore, are more appropriate for the low side se nsitivity. The reverse is true when decreasing the learning rates. For our primary ana lysis, as described in Chapter 3 of the draft joint TSD, we have used a 20% p-value for technolog ies on the steep portion of the learning curve and then have used learning rates of 3% per y ear for five years, 2% per year for 5 years, then 1% per year for 5 years for technologies on th e flat portion of the learning curve. Table 9 shows how we have adjusted these learning rates f or both the low and high side sensitivities.

Table 0-9 - Learning Rates used for our Learning R ate Sensitivity

Sensitivity Steep learning rate Flat learning rate

Low side 30% 4%, 3%, 2% Primary case 20% 3%, 2%, 1% High side 10% 2%, 1%, 0%

For the learning sensitivity, we re-ranked OMEGA p ackages using the master-sets of packages as described in Chapter 1 of this draft RI A for the 2016MY and 2025MY. We did not start with preliminary-sets of packages and con duct a full package building/ranking process. Using the master-sets of packages, we ins erted new costs calculated using the low/high learning rates, re-ranked the master-sets of packages to get the proper ordering of packages for each sensitivity case, then ran OMEGA.

The high learning inputs increased the average comp liance costs of the reference case by $48 and the control case by $154, for a net ave rage per-vehicle cost increase of $106 in MY 2025. The low ICM inputs decreased the averag e compliance costs of the reference case by $63 and the control case by $158 for a net average cost decrease of $97.6

3.1.6 Summary of Sensitivity Impacts

The average per-vehicle impacts of the sensitivity runs are shown in the following table. Note that the majority of these impacts are less than $100 relative to the primary analysis costs. The ICM impacts are larger.

Table 0-10 – Summary of Per-vehicle Cost Impacts of Sensitivity Analyses in MY 2025 relative to Primary Analysis

Sensitivity Title Low ($) High ($) Primary Case $1946
Mass Cost -$102 $102 Battery Cost $101 $61
ICM $244 $249 Learning Rates $97 $106

3.1.7 NAS report

We note that EPA has decided not to base a sensitiv ity case on the 2010 National Academy of Science Report “ Assessment of Technologies for Improving Light-Duty Vehicle Fuel Economy, Assessment for Fuel Economy Technolog ies for Light-Duty Vehicles” ( The National Academies Press, June 2010).

As discussed in detail in Chapter 3 of the draft Jo int Technical Support Document for this proposal, EPA and NHTSA have utilized the best available information in order to estimate the cost and effectiveness for a large num ber of technologies which can be used to reduce GHG emissions and improve fuel efficiency.

In 2007, NHTSA commissioned the National Academy of Science to perform an assessment of, among other things, the cost and eff ectiveness of technologies for improving the fuel economy of light-duty vehicles. The 2010 NAS Committee published their results of

their assessment in June of 2010. EPA has reviewed this report in detail and for the reasons discussed below, we have not relied upon this repor t as a primary assessment for our cost and effectiveness estimates for this proposal, and we h ave also not used the report to perform a sensitivity assessment for the same reasons.

Our principle reasons are twofold. First, the 2010 NAS Committee focused their report on the near-term, specifically the 2010-2015 time frame, and not on the time frame of this proposal, which is 2017 to 2025. Second, on a range of topics EPA and NHTSA have relied upon newer information for cost and effectiv eness estimates. In the Summary of the NAS 2010 report (pages S-1 and S-2), the NAS Commit tee discusses that their costs estimates are for the 2010-2015 time frame. They Committee a lso discusses that there are longer-term technologies which are in the 5 to 15 year time hor izon which are not the focus of the NAS 2010 report. There are a number of specific exampl es where this difference in time frame is relevant to any potential comparison between the 20 10 NAS report and the EPA & NHTSA assessment for this proposal.7

For example, there are a number of technologies tha t EPA and NHTSA discuss in Chapter 3 of the draft Joint TSD which are not a si ngle, discrete piece of hardware, but rather a continuum of improvements where the level of impr ovement can change given the potential

time horizon. The 2010 NAS Committee considered at least six of these technologies: low friction lubricants, engine friction reduction, imp roved accessories, lower rolling resistance tires, aerodynamic drag improvement, and improved i nternals for automatic transmissions. The 2010 NAS report provides cost and effectiveness estimates for one increment of improvement for each of these technologies applicab le to the 2010-2015 time frame. This is similar to the approach utilized by NHTSA and EPA f or the 2012-2016 rulemaking. However, for the 2017-2025 proposal, where EPA and NHTSA are using a model year 2008 baseline set of vehicles, the agencies estimate tha t for each these technologies two increments of improvement can be implemented across the fleet between 2008 and 2025. Using the NAS Report estimates for these technologies thus, witho ut basis, would not consider the further projected incremental improvements in these technol ogies.

A second example of the importance of the time fra me is evaluation of the effectiveness of gasoline direct injection with tur bocharging and downsizing. The 2010 NAS Committee considered one level of downsizing in the 2010-2015 time frame, and EPA and NHTSA took a similar approach for the 2012-2016 rul e. But, for the 2017-2025 proposal, based on data in the literature, our discussions wi th the auto companies and automotive suppliers, and a 2011 Ricardo study commissioned by EPA, in the longer term additional levels of downsizing are achievable, including in s ome cases with the use of cooled exhaust gas recirculation, that provide additional CO2/fuel consumption reductions. Those additional levels of downsizing were not considered by the 201 0 NAS Committee in their assessment of

near-term costs and effectiveness.

In addition to the difference in time frames being considered by the 2010 NAS report and this proposal, a second significant difference between the two assessments were the

additional studies and information available to EPA and NHTSA which were not reviewed by 2010NAS Committee. In many cases this was due to t he additional two years EPA and NHTSA had available (while the NAS Committee’s repo rt was published in 2010, the bulk of their assessments occurred between 2007 and 2009), and in other areas this new information was the result of the many confidential meetings EP A and NHTSA had with auto companies and auto suppliers over the past two years.

The additional publically available studies which E PA and NHTSA utilized included new studies on the costs for mass reduction, lithi um-ion battery packs, 8 speed automatic transmissions, 8 speed dual-clutch transmissions, h ybrid electric vehicle, plug-in hybrid electric vehicle, and all electric vehicles. EPA a nd NHTSA also utilized new reports dealing with the use of indirect cost multipliers for estim ating indirect manufacturing costs. EPA and NHTSA also are using a number of new studies which were not available to the 2010 NAS

Committee for the estimation of the effectiveness o f a large number of the 2017-2025 technologies; these include peer reviewed papers in the literature as well as the 2011 Ricardo study (discussed in detail in Chapter 3 of the draf t Joint TSD).

For the reasons described above, EPA has elected no t to perform a sensitivity assessment based on the 2010 NAS Report.8



## Preamble Section III.D.7:

To What Extent do Any of Today’s Vehicles Meet or
Surpass the Proposed MY 2017-2025 CO 2 

## Footprint-based Targets with Current Powertrain
Designs?

In addition to the analysis discussed above regardi ng what technologies could be added to vehicles in order to achieve the projected CO 2 obligation for each automotive company under the proposed MY2017 to 2025 standards , EPA performed an assessment of the light-duty vehicles available in the market tod ay to see how such vehicles compare to the proposed MY2017-2025 footprint-based standard curve s. This analysis supports EPA’s overall assessment that there are a broad range of effective and available technologies that could be used to achieve the proposed standards, as well as illustrating the need for the leadtime between today and MY2017 to MY2025 in order fo r continued refinement of today’s technologies and their broader penetration across t he fleet for the industry as a whole as well as individual companies. In addition, this assessm ent supports EPA’s view that the proposed standards would not interfere with consumer utility – footprint-attribute standards provide manufacturers with the ability to offer consumers a full range of vehicles with the utility customers want, and does not require or encourage c ompanies to just produce small passenger cars with very low CO 2 emissions.

Using publicly available data, EPA compiled a list of available vehicles and their 2- cycle CO 2 emissions performance (that is, the performance ov er the city and highway test cycles required by this proposal). Data is current ly available for all MY2011 vehicles and some MY2012 vehicles. EPA gathered vehicle footpri nt data from EPA reports, manufacturer submitted CAFE reports, and manufactur er websites.

EPA evaluated these vehicles against the proposed C O 2 footprint-based standard

curves to determine which vehicles would meet or ex ceed the proposed MY 2017 –MY 2025 footprint-based CO 2 targets assuming air conditioning credit generatio n consistent with today’s proposal. Under the proposed 2017-2025 gre enhouse gas emissions standards, each vehicle will have a unique CO 2 target based on the vehicle’s footprint. However, it is important to note that the proposed CO 2 standard is a company-specific sales weighted flee twide standard for each company’s passenger cars and truck fleets calculate from the proposed footprint-based standard curves. No individual veh icle is required to achieve a specific CO 2 target. In this analysis, EPA assumed usage of air conditioner credits because air conditioner improvements are considered to be among the cheapes t and easiest technologies to reduce greenhouse gas emissions, manufacturers are already investing in air conditioner improvements, and air conditioner changes do not im pact engine, transmission, or aerodynamic designs so assuming such credits does n ot affect consideration of cost and leadtime for use of these other technologies. In t his analysis, EPA assumed increasing air conditioner credits over time with a phase-in of al ternative refrigerant for the generation of HFC leakage reduction credits consistent with the a ssumed phase-in schedule discussed in9

Section III.C.I. of this preamble. No adjustments were made to vehicle CO 2 performance other then this assumption of air conditioning cred it generation. Under this analysis, a wide range of existing vehicles would meet the MY2017 pr oposed CO 2 targets, and a few meet even the proposed MY2025 CO 2 targets. The details regarding this assessment ar e in Chapter

3 of the EPA Draft RIA.

This assessment shows that a significant number of vehicles models sold today (nearly 40 models) would meet or be lower than the proposed MY2017 footprint-based CO 2 targets with current powertrain designs, assuming air condi tioning credit generation consistent with our proposal. The list of vehicles includes a ful l suite of vehicle sizes and classes, including midsize cars, minivans, sport utility vehicles, com pact cars, small pickup trucks and full size pickup trucks – all of which meet the proposed MY 2 017 target values with no technology improvements other then air conditioning system upg rades. These vehicles utilize a wide variety of powertrain technologies (including gasol ine engines), and operate on a variety of different fuels including gasoline, diesel, electri city, and compressed natural gas. Nearly every major manufacturer currently produces vehicle s that would meet or exceed the proposed MY2017 footprint CO 2 target with only improvements in air conditioning systems. For all of these vehicle classes the MY2017 targets are achieved with conventional gasoline powertrains, with the exception of the full size (o r “standard”) pickup trucks. In the case of full size pickups trucks, only HEV versions of the Chevrolet Silverado and the GMC Sierra fall into this category (though the HEV Silverado a nd Sierra’s meet not just the MY2017 footprint-based CO 2 targets with A/C improvements, but their respectiv e targets through MY2022). As the CO 2 targets become more stringent each model year, few er MY2011 and MY2012 vehicles achieve or surpass the proposed CO 2 targets, in particular for gasoline powertrains. While approximately 15 unique gasolin e vehicle models achieve or surpass the MY2017 targets, this number falls to approximately 11 for the MY2018 targets, 9 for the model year 2019 targets, and only 2 unique gasoline vehicle models can achieve the MY2020 proposed CO 2 targets with A/C improvements.

EPA also assessed the subset of these vehicles that have emissions within 5%, of the proposed CO 2 targets. As detailed in Chapter 3 of the EPA Draf t RIA, the analysis shows that there are more than twenty additional vehicle model s (primarily with gasoline and diesel powertrains) that are within 5% of the proposed MY 2017 CO 2 targets, including compact cars, midsize cars, large cars, SUVs, station wagon s, minivans, small and standard pickup trucks. EPA also receives projected sales data pri or to each model year from each manufacturer. Based on this data, approximately 7% of MY2011 sales will be vehicles that would meet or be better than the proposed MY 2017 t argets for those vehicles, requiring only improvements in air conditioning systems. In addit ion, nearly 15% of projected MY2011 sales would be within 5% of the proposed MY2017 foo tprint CO 2 target with only simple improvements to air conditioning systems, a full si x model years before the proposed standard takes effect. With improvements to air conditionin g systems, the most efficient gasoline internal combustion engines would meet the MY 2020 proposed footprint targets. After MY2020, the only current vehicles that continue to meet the proposed footprint-based CO 2 targets (assuming improvements in air conditioning) are hybrid-electric, plug-in hybridelectric, and fully electric vehicles. However, th e proposed MY 2021 standards, if finalized, would not need to be met for another 9 years. Toda y’s Toyota Prius, Ford Fusion Hybrid, Chevrolet Volt, Nissan Leaf, Honda Civic Hybrid, an d Hyundai Sonata Hybrid all meet or10

surpass the proposed footprint-based CO 2 targets through MY2025. In fact, the current Priu s, Volt, and Leaf meet the proposed 2025 CO 2 targets without air conditioning credits.

This assessment of MY2011 and MY2012 vehicles makes it clear that HEV technology (and of course EVs and PHEVs) is capable of achieving the MY2025 standards. However, as discussed earlier in this section, EPA’ s modeling projects that the MY2017-2025 standards can primarily be achieved by advanced gas oline vehicles – for example, in MY2025, we project more than 80 percent of the new vehicles could be advanced gasoline powertrains. The assessment of MY2011 and MY2012 v ehicles available in the market today indicates advanced gasoline vehicles (as well as di esels) can achieve the targets for the early model years of the proposed standards (i.e., model years 2017-2020) with only improvements in air conditioning systems. However, significant improvements in technologies are needed and penetrations of those technologies must increas e substantially in order for individual manufacturers (and the fleet overall) to achieve th e proposed standards for the early years of the program, and certainly for the later years (i.e ., model years 2021-2025). These technology improvements are the very technologies EPA and NHTS A describe in detail in Chapter 3 of the draft Joint Technical Support Document and whic h we forecasted penetration rates earlier in this section III.D, and they include for example : gasoline direct injection fuel systems; downsized and turbocharged gasoline engines (includ ing in some cases with the application of cooled exhaust gas recirculation); continued improv ements in engine friction reduction and low friction lubricants; transmissions with an incr eased number of forward gears (e.g., 8 speeds); improvements in transmission shifting logi c; improvements in transmission gear box efficiency; vehicle mass reduction; lower rolling resistance tires, and improved vehicle aerodynamics. In many (though not all) cases these technologies are beginning to penetrate the U.S. light-duty vehicle market.

In general, these technologies must go through the automotive product development cycle in order to be introduced into a vehicle. In some cases additional research is needed before the technologies’ CO 2 benefits can be fully realized and large-scale man ufacturing can be achieved. The subject of technology penetration phase-in rates is discussed in more detail in Chapter 3.5 of the draft Joint Technical Support Document. In that Chapter, we explain that why many CO 2 reducing technologies should be able to penetrate the new vehicle market at high levels between now and MY2016. There are also many of the key technologies we project as being needed to achieve the proposed 201 7-2025 standards which will only be able to penetrate the market at relatively low levels (e .g., a maximum level of 30% or less) by MY2016, and even by MY2021. These include importan t powertrain technologies such as 8- speed transmissions and second or third generation downsized engines with turbocharging,

The majority of these technologies must be integrat ed into vehicles during the product redesign schedule, which is typically on a 5-year c ycle. EPA discussed in the MY2012-2016 rule the significant costs and potential risks asso ciated with requiring major technologies to be added in-between the typical 5-year vehicle redesig n schedule, (see 75 FR at 25467-68, May 7, 2010). In addition, engines and transmissions generally have longer lifetimes then 5 years, typically on the order of 10 years. Thus major pow ertrain technologies generally take longer to penetrate the new vehicle fleet then can be done in a 5-year redesign cycle. As detailed in Chapter 3.5 of the draft Joint TSD, EPA projects th at 8-speed transmissions could increase their maximum penetration in the fleet from 30% in MY2016 to 80% in 2021 and to 100% in11

MY2025. Similarly, we project that second generati on downsized and turbocharged engines (represented in our assessment as engines with a br ake-mean effective pressure of 24 bars) could penetrate the new vehicle fleet at a maximum level of 15% in MY2016, 30% in MY2021, and 75% in MY2025. When coupled with the t ypical 5 year vehicle redesign schedule, EPA project that is not possible for all of the advanced gasoline vehicle technologies we have assessed to penetrate the flee t in a single 5 year vehicle redesign

schedule.

Given the status of the technologies we project to be used to achieve the proposed MY2017-2025 standards and the product development a nd introduction process which is fairly standard in the automotive industry today, o ur assessment of the MY2011 and MY2012 vehicles in comparison to the proposed standards su pports our overall feasibility assessment,

and reinforces our assessment of the lead time need ed for the industry to achieve the proposed

standards.12



## EPA Draft RIA Chapter 3

Section 3.11 How Many of Today’s Vehicles Can Meet orSurpass the Proposed MY 2017-2025 CO2 Footprintbased Targets with Current Powertrain Designs?

As part of its evaluation of the feasibility of the proposed program, EPA evaluated all MY2011 and MY2012 vehicles sold in the U.S. today a gainst the proposed CO2 footprintbased standard curves to determine which vehicles w ould meet or exceed the proposed MY 2017 –MY 2025 footprint-based CO2 targets assuming air conditioning credit generation consistent with today’s proposal. Under the propos ed 2017-2025 greenhouse gas emissions standards, each vehicle will have a unique CO2 targ et based on the vehicle’s footprint (with each manufacturer having its own unique fleetwide standard )) . In this analysis, EPA

assumed air conditioner credits because air condit ioner improvements are considered to be among the cheapest and easiest technologies to redu ce greenhouse gas emissions, manufacturers are already investing in air conditio ner improvements, and air conditioner changes do not impact engine, transmission, or aero dynamic designs so assuming such credits

does not affect consideration of cost and leadtime for use of these other technologies. EPA applied increasing air conditioner credits over tim e with a phase-in of alternative refrigerant for the generation of HFC leakage reduction credits consistent with the assumed phase-in

schedule discussed in Preamble Section III.C. No a djustments were made to vehicle CO 2 performance other then this assumption of air condi tioning credit generation. Under this analysis, a wide range of these existing vehicles w ould meet the MY2017 proposed CO2 targets, and a few meet even the proposed MY2025 CO 2 targets.

Using publicly available data B , EPA compiled a list of all available vehicles and their 2-cycle CO 2 g/mile performance (that is, the performance over the city and highway compliance tests). Data is currently available for all MY2011 vehicles and some MY2012 vehicles. EPA gathered vehicle footprint data from EPA reports, 1 manufacturer submitted CAFE reports, and manufacturer websites. .

Table 0-1 Error! Reference source not found. shows that a significant number of vehicles sold today would meet or be lower than the proposed footprint-based CO2 targets with current powertrain designs, assuming air condi tioning credit generation consistent with our proposal. The table highlights the vehicles t hat meet or are lower than the proposed footprint targets from MY 2017 to 2025 in green, an d shows the percentage below the proposed target for each year. The list of vehic les includes midsize cars, minivans, sport utility vehicles, compact cars, and small pickup tr ucks – all of which meet the proposed MY 2017 target values with no technology improvements other then air conditioning system upgrades. These vehicles utilize a wide variety o f powertrain technologies, including internal combustion, hybrid-electric, plug-in hybrid-electri c, and full electric, and operate on a variety of different fuels including gasoline, diesel, ele ctricity, and compressed natural gas. Nearly

B www.fueleconomy.gov13

every major manufacturer produces vehicles that wou ld meet or exceed the proposed MY2017 footprint CO2 target with only simple improv ements in air conditioning systems.

Vehicles that are above, but within 5%, of the prop osed targets are highlighted in

Error! Reference source not found. in yellow. This list also includes vehicles from multiple classes, including large cars and standard pickup t rucks. Four versions of the F-150 pickup truck are within 5% of the proposed targets through at least 2021. This includes two engine options (the 3.7L V6 and the 3.5L V6), and three wh eelbase options C

.

EPA also receives projected sales data prior to eac h model year from each manufacturer. Based on this data, approximately 7% of MY2011 sales will be vehicles that would meet or be better than the proposed MY 2017 t argets for those vehicles, requiring only improvements in air conditioning systems. In addit ion, nearly 30% of projected MY2011 sales would be within 10% of the proposed MY2017 fo otprint CO2 target with only simple improvements to air conditioning systems, a full si x model years before the proposed standard

takes effect.

With improvements to air conditioning systems, the most efficient gasoline internal combustion engines would meet the MY 2020 proposed footprint targets. After MY2020, the only current vehicles that continue to meet the pro posed footprint-based CO2 targets (assuming improvements in air conditioning) are hyb rid-electric, plug-in hybrid-electric, and fully electric vehicles. However, the proposed MY 2020 standards will not be in effect for another 9 years. EPA expects that gasoline vehicle s will continue to improve in that timeframe and will be able to meet the standard (us ing the technologies discussed in Chapter

3 of the draft Joint TSD and as discussed in Preamb le Section III.D) assuming air conditioner improvements . Today’s Toyota Prius, Ford Fusion H ybrid, Chevrolet Volt, Nissan Leaf, Honda Civic Hybrid, and Hyundai Sonata Hybrid all m eet or surpass the proposed footprintbased CO2 targets through MY2025. In fact, the cur rent Prius, Volt, and Leaf meet the proposed 2025 CO2 targets without air conditioning credits.

C The F-150 engine and wheelbase combinations listed in Table 0-1 correspond to models that are current ly available. Not all possible engine and wheelbase c ombinations are produced.14Table 0-1 - Vehicles that Meet or Exceed Proposed Targets With Current Powertrain Designs2017 2018 2019 2020 2021 2022 2023 2024 20252011 Mercedes-Benz Smart fortwo (cabriolet) 123.9 0.0 26.8 EV A1 n/a Two Seaters C 100% 100% 100% 100% 100% 100% 100% 100% 100%2011 Mercedes-Benz Smart fortwo (coupe) 123.9 0.0 26.8 EVA1 n/a Two Seaters C 100% 100% 100% 100% 100% 100% 100% 100% 100%2011 Nissan LEAF 141.7 0.0 44.7 EV A1 n/a Midsize Cars C 100% 100% 100% 100% 100% 100% 100% 100% 100%2011 Chevrolet VOLT 48.4 56.0 45.3 PHEV CVT 1.4 Compact CarsC 76% 76% 75% 73% 72% 71% 69% 68% 66%2011 Toyota PRIUS 70.8 125.6 44.2 HEV CVT 1.8 Midsize Cars C 46% 44% 42% 40% 37% 34% 31% 28% 24%2012 Honda CIVIC HYBRID 63.1 140.9 43.5 HEV A5 1.5 Compact Cars C 38% 35% 33% 30% 27% 23% 20% 16% 12%2011 Hyundai SONATA HYBRID 52.2 170.3 48.0 HEV A6 2.4 Midsize Cars C 30% 28% 24% 21% 18% 14% 10% 6% 1%2012 Ford FUSION HYBRID FWD 54.2 164.0 45.6 HEV CVT 2.5 Midsize Cars C 30% 27% 24% 21% 17% 13% 9% 5% 0%2012 Lincoln MKZ HYBRID FWD 54.2 164.0 45.6 HEV CVT 2.5 Midsize Cars C 30% 27% 24% 21% 17% 13% 9% 5% 0%2011 Lexus CT 200h 57.5 154.6 42.6 HEV CVT 1.8 Compact Cars C30% 27% 24% 21% 17% 13% 9% 5% 0%2011 Honda INSIGHT 57.3 155.1 40.8 HEV CVT 1.3 Compact Cars C27% 24% 21% 17% 13% 9% 5% 0% -4%2011 Toyota HIGHLANDER HYBRID 4WD 38.7 229.7 48.8 HEV CVT 3.5 Sport Utility Vehicle T 21% 20% 18% 16% 10% 6% 1% -4%2011 Lexus RX 450h AWD 38.6 230.4 48.6 HEV CVT 3.5 Sport Utility Vehicle T 21% 19% 18% 16% 10% 5% 0% -5%2011 Honda CIVIC CNG 37.5 175.7 43.4 CNG A5 1.8 Subcompact Cars C 21% 17% 14% 10% 6% 1% -3%2011 Chevrolet SILVERADO 2WD HYBRID 28.5 311.4 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 14% 14% 14% 13% 7% 2% -3%2011 GMC SIERRA 2WD HYBRID 28.5 311.4 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 14% 14% 14% 13% 7% 2% -3%2011 Chevrolet SILVERADO 4WD HYBRID 28.4 313.2 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 13% 13% 14% 12% 6% 1% -3%2011 GMC SIERRA 4WD HYBRID 28.4 313.2 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 13% 13% 14% 12% 6% 1% -3%2011 Nissan ALTIMA HYBRID 46.7 190.3 46.3 HEV CVT 2.5 Midsize Cars C 19% 15% 12% 8% 3% -1%2011 Toyota CAMRY HYBRID 45.9 193.4 46.9 HEV CVT 2.4 MidsizeCars C 18% 15% 11% 7% 3% -2%2011 Lexus HS 250h 47.3 188.0 44.5 HEV CVT 2.4 Compact Cars C17% 13% 9% 5% 1% -4%2012 Ford ESCAPE HYBRID AWD 39.0 227.6 43.3 HEV CVT 2.5 Sport Utility Vehicle T 13% 12% 10% 8% 1% -4%2011 Honda CR-Z 50.1 177.3 39.5 HEV CVT 1.5 Two Seaters C 15% 12% 8% 4% -1%2011 Mercedes-Benz Smart fortwo (cabriolet) 49.5 179.5 26.8 Gasoline A5 1.0 Two Seaters C 14% 11% 7% 2% -2%2011 Mercedes-Benz Smart fortwo (coupe) 49.5 179.5 26.8 Gasoline A5 1.0 Two Seaters C 14% 11% 7% 2% -2%2012 Hyundai ELANTRA 44.7 198.7 45.2 Gasoline M6 1.8 MidsizeCars C 13% 9% 5% 1% -4%2012 Hyundai ELANTRA 44.4 200.2 45.2 Gasoline A6 1.8 MidsizeCars C 12% 9% 4% 0% -5%2011 Toyota TACOMA 2WD 30.2 294.5 55.9 Gasoline M5 2.7 SmallPick-up Trucks T 9% 7% 5% 3% -4%2011 Toyota SIENNA 29.4 302.0 56.1 Gasoline A6 2.7 Minivan T 7% 5% 3% 1%2012 Chevrolet CRUZE ECO 44.4 200.3 44.8 Gasoline M6 1.4 Midsize Cars C 11% 8% 3% -1%2011 Lexus RX 450h 40.4 220.2 48.6 HEV CVT 3.5 Sport UtilityVehicle C 9% 6% 1% -3%2012 Ford Focus SFE FWD 43.6 203.7 44.2 Gasoline A6 2.0 Compact Cars C 9% 5% 0% -4%2012 Honda CIVIC HF 44.3 200.6 43.4 Gasoline A5 1.8 CompactCars C 9% 5% 0% -4%2011 Honda ODYSSEY 2WD 29.0 306.7 55.9 Gasoline A6 3.5 Minivan T 5% 3% 1% -1%2011 Ford RANGER 2WD 31.2 284.5 50.6 Gasoline M5 2.3 Small Pick-up Trucks T 4% 2% 0% -2%2012 Ford ESCAPE HYBRID FWD 44.1 201.4 43.3 HEV CVT 2.5 Sport Utility Vehicle C 8% 4% 0% -5%2011 Toyota TACOMA 2WD 28.3 313.6 55.9 Gasoline A4 2.7 SmallPick-up Trucks T 3% 1% -1% -4%2012 Hyundai ACCENT 45.5 195.1 41.7 Gasoline A6 1.6 CompactCars C 8% 4% -1% -5%2012 Infiniti M35h 38.8 229.1 49.1 HEV A7 3.5 Midsize Cars C 6% 2% -2%2012 Honda CIVIC 43.0 206.7 43.4 Gasoline A5 1.8 Compact Cars C 6% 2% -3%2012 Ford FOCUS FWD 42.1 211.0 44.2 Gasoline A6 2.0 CompactCars C 5% 1% -4%2011 Honda CR-Z 44.9 197.9 39.5 HEV M6 1.5 Two Seaters C 5% 1% -4%2011 Ford Fiesta SFE FWD 44.9 198.0 39.3 Gasoline A6 1.6 Subcompact Cars C 5% 1% -4%2012 Fiat 500 44.5 199.6 34.7 Gasoline M5 1.4 Minicompact Cars C 4% 0% -5%2011 Cadillac ESCALADE 2WD HYBRID 28.5 311.4 54.8 HEV CVT 6.0 Sport Utility Vehicle T 2% -1% -2% -5%2011 Chevrolet TAHOE 2WD HYBRID 28.5 311.4 54.8 HEV CVT 6.0Sport Utility Vehicle T 2% -1% -2% -5%2011 GMC YUKON 2WD HYBRID 28.5 311.4 54.8 HEV CVT 6.0 SportUtility Vehicle T 2% -1% -2% -5%2011 Chevrolet TAHOE 4WD HYBRID 28.4 313.2 54.8 HEV CVT 6.0Sport Utility Vehicle T 1% -1% -3%2011 GMC YUKON 4WD HYBRID 28.4 313.2 54.8 HEV CVT 6.0 SportUtility Vehicle T 1% -1% -3%2012 Chevrolet CRUZE ECO 40.9 217.1 44.8 Gasoline A6 1.4 Midsize Cars C 4% -1% -5%2012 Volkswagen Passat 46.4 219.5 45.3 Diesel M6 2.0 MidsizeCars C 3% -1%2012 Honda CIVIC 41.8 212.4 43.4 Gasoline M5 1.8 Compact Cars C 3% -1%2012 Ford FOCUS FWD 41.1 216.1 44.2 Gasoline A6 2.0 CompactCars C 3% -2%ModelYearManufacturer VehicleUnadjustedFuel Economy(mpg)Footprint(ft2)Tailpipe CO2(ft2)PowertrainTypeVehicle ClassCar/TruckComplianceTransmissionEngineDisplacement(L)152017 2018 2019 2020 2021 2022 2023 2024 20252011 Ford Fiesta FWD 44.0 202.2 39.3 Gasoline A6 1.6 Subcompact Cars C 3% -2%2012 Buick LACROSSE 38.1 233.3 48.0 Gasoline A6 2.4 MidsizeCars C 3% -2%2011 Kia FORTE ECO 40.7 218.3 44.5 Gasoline A6 2.0 Midsize Cars C 2% -2%2012 Chevrolet CRUZE 40.4 219.8 44.8 Gasoline M6 1.4 MidsizeCars C 2% -2%2011 Mini Mini Cooper 43.6 203.9 38.8 Gasoline M6 1.6 Minicompact Cars C 2% -3%2012 Chevrolet CRUZE 40.1 221.7 44.8 Gasoline A6 1.4 MidsizeCars C 1% -3%2012 Buick REGAL 38.1 233.3 46.8 Gasoline A6 2.4 Midsize Cars C 0% -4%2011 Ford F150 PICKUP 2WD 23.9 372.3 75.9 Gasoline A6 3.5 Standard Pick-up Trucks T -4% -4% -4% -4% -4% -4%2011 Ford F150 PICKUP 2WD 23.9 372.3 72.8 Gasoline A6 3.5 Standard Pick-up Trucks T -4% -4% -4% -4% -4% -5%2011 Ford F150 PICKUP 2WD 23.9 372.3 67.2 Gasoline A6 3.5 Standard Pick-up Trucks T -4% -4% -4% -4% -5%2011 Ford F150 PICKUP 2WD 24.4 363.8 67.2 Gasoline A6 3.7 Standard Pick-up Trucks T -2% -1% -1% -1% -3%2011 Cadillac ESCALADE 4WD HYBRID 28.0 317.4 54.8 HEV CVT 6.0 Sport Utility Vehicle T 0% -3% -4%2011 GMC YUKON DENALI HYBRID 4WD 28.0 317.4 54.8 HEV CVT 6.0 Sport Utility Vehicle T 0% -3% -4%2011 Mercedes-Benz ML450 HYBRID 4MATIC 29.6 300.4 51.0 HEV CVT 3.5 Sport Utility Vehicle T -1% -3% -5%2012 Ford TRANSIT CONNECT FWD 31.1 286.0 47.9 Gasoline M5 1.6 Special Purpose Vehicle T -1% -3% -5%2011 Mini Mini Cooper Countryman 41.0 216.8 43.0 GasolineM6 1.6 Compact Cars C 0% -5%2012 Volkswagen Jetta 46.1 220.7 43.8 Gasoline A6 2.0 Compact Cars C 0% -5%2011 Ford Fiesta FWD 42.7 208.1 39.3 Gasoline A6 2.7 Subcompact Cars C 0% -5%2012 Volkswagen Jetta 46.1 220.9 43.8 Diesel CVT 3.5 CompactCars C 0% -5%2011 Toyota VENZA AWD 30.2 294.3 48.8 Gasoline A4 2.0 SportUtility Vehicle T -2% -5%2011 Nissan QUEST 27.2 326.7 55.9 Gasoline M6 2.0 Minivan T -1% -4%2011 Nissan FRONTIER 2WD 27.4 324.8 54.8 Gasoline M5 2.5 Small Pick-up Trucks T -3% -5%2011 Mazda MAZDA2 42.6 208.6 39.4 Gasoline M5 1.5 Compact Cars C -1% -5%2012 Ford Transit Connect Van 30.5 291.8 47.9 Gasoline A4 2.0 Vans, Cargo Types T -3%2011 Toyota SIENNA 26.7 333.0 56.1 Gasoline A6 3.5 Minivan T -3%2012 Kia SORENTO 4WD 30.6 290.8 47.1 Gasoline A6 2.4 Sport Utility Vehicle T -4%2012 Kia SPORTAGE 4WD 31.0 286.9 46.0 Gasoline A6 2.4 SportUtility Vehicle T -5%2011 Suzuki EQUATOR 2WD 27.3 325.3 54.0 Gasoline M5 2.5 Small Pick-up Trucks T -4%2011 Toyota YARIS 42.6 208.7 39.9 Gasoline M5 1.5 SubcompactCars C -1%2012 Volkswagen Passat 44.6 228.2 45.3 Diesel A6 2.0 MidsizeCars C -1%2011 Honda FIT 42.5 208.9 39.9 Gasoline A5 1.5 Small StationWagons C -1%2012 Nissan SENTRA 39.5 224.9 44.3 Gasoline CVT 2.0 MidsizeCars C -1%2011 Toyota COROLLA 41.0 217.0 42.5 Gasoline M5 1.8 CompactCars C -1%2012 Ford FOCUS FWD 39.4 225.4 44.2 Gasoline M5 2.0 CompactCars C -2%2012 Hyundai SONATA 36.5 243.3 48.0 Gasoline A6 2.4 Large Cars C -2%2011 Kia OPTIMA 36.5 243.8 48.1 Gasoline M6 2.4 Midsize CarsC -2%2012 Hyundai SONATA 36.5 243.6 48.0 Gasoline M6 2.4 Large Cars C -2%2011 Kia FORTE 38.9 228.4 44.5 Gasoline A6 2.0 Midsize Cars C-2%2011 Toyota YARIS 41.9 212.2 39.9 Gasoline A4 1.5 SubcompactCars C -2%2011 Kia OPTIMA 36.3 245.1 48.1 Gasoline A6 2.4 Midsize CarsC -2%2012 Chevrolet CRUZE 38.5 230.5 44.8 Gasoline M6 1.8 MidsizeCars C -3%2011 Mini Mini Cooper 41.7 213.3 38.8 Gasoline A6 1.6 Minicompact Cars C -3%2012 Volkswagen GOLF 46.1 220.7 42.4 Diesel A6 2.0 Compact Cars C -3%2012 Volkswagen GOLF 46.1 220.9 42.4 Diesel M6 2.0 Compact Cars C -4%2011 Kia RIO 41.1 216.0 41.3 Gasoline M5 1.6 Compact Cars C -4%2012 Volkswagen JETTA SPORTWAGEN 46.1 220.9 42.3 Diesel M62.0 Small Station Wagons C -4%2011 Kia FORTE KOUP 38.3 232.1 44.6 Gasoline A6 2.0 CompactCars C -4%2012 Audi A6 35.4 251.0 48.6 Gasoline CVT 2.0 Midsize Cars C -4%2011 Nissan VERSA 40.8 217.9 41.4 Gasoline CVT 1.8 Midsize Cars C -4%2011 Hyundai ENTOURAGE 26.8 331.6 54.8 Gasoline A6 3.5 Minivan T -5%2012 Kia SEDONA 26.8 331.6 54.7 Gasoline A6 3.5 Minivan T -5%2011 Mini Mini Clubman 41.0 216.8 40.1 Gasoline M6 1.6 Subcompact Cars C -5%2011 Mini Mini Convertible 41.0 216.8 38.8 Gasoline M6 1.6 Minicompact Cars C -5%2012 Audi A3 46.1 220.7 41.8 Diesel A6 2.0 Small Station Wagons C -5%Car/TruckComplianceFootprint(ft2)PowertrainTypeTransmissionEngineDisplacement(L)Vehicle ClassModelYearManufacturer VehicleUnadjustedFuel Economy(mpg)Tailpipe CO2(ft2)16

1 EPA’s “Light Duty Automotive Technology, Carbon Di oxide Emissions, and Fuel Economy Trends Report, 1975 through 2010”