Subject: Additional EPA NPRM material regarding sensitivities 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, rebecca.yoon@dot.gov 

Date: 11/09/2011 12:56 PM 

Chandana - 

Included in this email are 2 elements of the EPA proposal which were not included in the October 12, 

2011 submission for the light-duty 2017-2025 proposal. 

Sensitivities: We have included sensitivity assessments for 4 elements of the proposal: mass 

reduction costs, battery pack costs, indirect cost multipliers, and learning curve rates. We also provide a 

discussion of why we have not performed a sensitivity 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 attached 

Feasibility assessment: EPA has included an assessment of MY2011 and 2012 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 more 

detail on the actual data analyzed for the EPA Draft RIA Chapter 3, Section 3.11 (pages 12-16 of the 

attached). 

Thanks 

Bill 

EPA DRIA and Preamble Sections on Uncertainty and Feasiblity, 11.9.2011.docx 
1 

EPA Submission to OMB on 11.9.2011, additional light-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 model to generate 2025MY results for 

each of these sensitivities. We have looked at different 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 0-10 . 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 side 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% confidence 

interval of modified Delphi 

survey results 

High side of 95% 

confidence interval of 

modified Delphi survey 

results 

Learning ratesa 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, hence the low side sensitivity uses the higher learning rates 

while the high side sensitivity uses the lower learning rates. 

3.1.2 Mass Sensitivity 

For the mass reduction cost sensitivity, we adjusted 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 sensitivity. 

 
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 reduction cost sensitivities but 

rather used the same input files used for our primary 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 reduction. 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 the 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 compliance costs of the reference 

case by $31 and the control case by $133, for a net average per-vehicle cost increase of $102 

in MY 2025. The low mass cost inputs decreased the 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 that use more mass reduction technology, 

and less on those that use less. 

3.1.3 Battery Sensitivity 

For the battery pack cost sensitivities, we decreased/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 pack costs. These linear regressions provide 

battery pack DCM as a function of net weight reduction of the vehicle. Table 0-3 and Table 

0-5 show the linear regressions used for our low side and high side sensitivity analyses, 

respectively, while Table 0-4 presents the linear regressions used for our primary analysis (as 

presented in Chapter 3 of the draft joint TSD). 

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

Weight Reduction used for Low Side Sensitivity (2009$) 

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 reduction as a percentage, so a subcompact P2 HEV battery 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% weight 
3 

reduction hit. 

The agencies did not regress PHEV or EV costs for the minivan+towing and large truck vehicle classes since we 

do not believe these vehicle classes would use the technologies.

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

Weight Reduction used for the Primary Analysis (2009$) 

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 reduction as a percentage, so a subcompact P2 HEV battery 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 the minivan+towing and large truck vehicle classes since we 

do not believe these vehicle classes would use the technologies. 

Table 0-5 - Linear Regressions of Battery Pack Direct 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 reduction as a percentage, so a subcompact P2 HEV battery pack with 

a 20% applied weight reduction and, therefore, a 15% net weight reduction would cost (-$194)x(15%)+$788=$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 the minivan+towing and large truck vehicle classes since we do 

not believe these vehicle classes would use the technologies. 

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 package building/ranking process. Using the 

master-sets of packages, we inserted new battery pack 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 cost increase of $61. In the high case, the 
4 

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 reference 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 decreased to 10%. In general, changing the 

battery costs shifted the choice between HEVs and EVs. 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% confidence intervals of the survey 

responses gathered as part of the modified Delphi process used to generate our low, medium 

and high2 complexity ICMs. We discuss this modified 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 presented for each element of the ICM along 

with average responses, standard deviations and other statistical measures. Using these, we 

calculate the ICM elements at the low side of the 95% confidence interval and at the high 

side. Table 0-6 and Table 0-8 show the ICMs used for the low side and high side sensitivity 

analyses, respectively, while Table 0-7 shows the ICMs used for our primary analysis. For 

the High1 ICM, since it was generated using a consensus approach rather than blind surveys, 

we have scaled the ICM elements using the same ratios 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-warranty 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-warranty 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 Sensitivity 

 Near term Long term Summed 

Complexity Warranty Non-warranty Warranty Non-warranty 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 August 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 of 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 master-sets of packages to get the proper 

ordering of packages for each sensitivity case, then ran OMEGA. 

The high ICM inputs increased the average compliance 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 compliance 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 side 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 sensitivity. The reverse is true when 

decreasing the learning rates. For our primary analysis, as described in Chapter 3 of the draft 

joint TSD, we have used a 20% p-value for technologies on the steep portion of the learning 

curve and then have used learning rates of 3% per year for five years, 2% per year for 5 years, 

then 1% per year for 5 years for technologies on the flat portion of the learning curve. Table 

9 shows how we have adjusted these learning rates for both the low and high side sensitivities. 

Table 0-9 - Learning Rates used for our Learning Rate 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 packages using the master-sets of 

packages as described in Chapter 1 of 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 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 compliance costs of the reference case 

by $48 and the control case by $154, for a net average per-vehicle cost increase of $106 in 

MY 2025. The low ICM inputs decreased the average 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 sensitivity case on the 2010 National 

Academy of Science Report “Assessment of Technologies for Improving Light-Duty Vehicle 

Fuel Economy, Assessment for Fuel Economy Technologies for Light-Duty Vehicles” (The 

National Academies Press, June 2010). 

As discussed in detail in Chapter 3 of the draft Joint 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 number 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 effectiveness 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 report as a primary assessment for our cost and 

effectiveness estimates for this proposal, and we have 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 effectiveness estimates. In the Summary of the 

NAS 2010 report (pages S-1 and S-2), the NAS Committee discusses that their costs estimates 

are for the 2010-2015 time frame. They Committee also discusses that there are longer-term 

technologies which are in the 5 to 15 year time horizon which are not the focus of the NAS 

2010 report. There are a number of specific examples where this difference in time frame is 

relevant to any potential comparison between the 2010 NAS report and the EPA & NHTSA 

assessment for this proposal. 
7 

For example, there are a number of technologies that EPA and NHTSA discuss in 

Chapter 3 of the draft Joint TSD which are not a single, discrete piece of hardware, but rather 

a continuum of improvements where the level of improvement can change given the potential 

time horizon. The 2010 NAS Committee considered at least six of these technologies: low 

friction lubricants, engine friction reduction, improved accessories, lower rolling resistance 

tires, aerodynamic drag improvement, and improved internals for automatic transmissions. 

The 2010 NAS report provides cost and effectiveness estimates for one increment of 

improvement for each of these technologies applicable to the 2010-2015 time frame. This is 

similar to the approach utilized by NHTSA and EPA for 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 that 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, without basis, would not consider the further 

projected incremental improvements in these technologies. 

 A second example of the importance of the time frame is evaluation of the 

effectiveness of gasoline direct injection with turbocharging 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 rule. But, for the 2017-2025 proposal, 

based on data in the literature, our discussions with 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 some 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 2010 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 the additional two years EPA and 

NHTSA had available (while the NAS Committee’s report 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 EPA and NHTSA had with auto companies 

and auto suppliers over the past two years. 

The additional publically available studies which EPA and NHTSA utilized included 

new studies on the costs for mass reduction, lithium-ion battery packs, 8 speed automatic 

transmissions, 8 speed dual-clutch transmissions, hybrid electric vehicle, plug-in hybrid 

electric vehicle, and all electric vehicles. EPA and NHTSA also utilized new reports dealing 

with the use of indirect cost multipliers for estimating 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 of 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 draft Joint TSD). 

For the reasons described above, EPA has elected not 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 CO2

Footprint-based Targets with Current Powertrain 

Designs? 

In addition to the analysis discussed above regarding what technologies could be 

added to vehicles in order to achieve the projected CO2 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 today to see how such vehicles compare to the 

proposed MY2017-2025 footprint-based standard curves. 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 for continued refinement of today’s 

technologies and their broader penetration across the fleet for the industry as a whole as well 

as individual companies. In addition, this assessment 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 companies to just produce small passenger 

cars with very low CO2 emissions. 

Using publicly available data, EPA compiled a list of available vehicles and their 2-

cycle CO2 emissions performance (that is, the performance over the city and highway test 

cycles required by this proposal). Data is currently available for all MY2011 vehicles and 

some MY2012 vehicles. EPA gathered vehicle footprint data from EPA reports, 

manufacturer submitted CAFE reports, and manufacturer websites. 

EPA evaluated these vehicles against the proposed CO2 footprint-based standard 

curves to determine which vehicles would 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 proposed 2017-2025 greenhouse gas emissions standards, each 

vehicle will have a unique CO2 target based on the vehicle’s footprint. However, it is 

important to note that the proposed CO2 standard is a company-specific sales weighted fleetwide standard for each company’s passenger cars and truck fleets calculate from the proposed 

footprint-based standard curves. No individual vehicle is required to achieve a specific CO2 

target. In this analysis, EPA assumed usage of air conditioner credits because air conditioner 

improvements are considered to be among the cheapest and easiest technologies to reduce 

greenhouse gas emissions, manufacturers are already investing in air conditioner 

improvements, and air conditioner changes do not impact engine, transmission, or 

aerodynamic designs so assuming such credits does not affect consideration of cost and 

leadtime for use of these other technologies. In this analysis, EPA assumed increasing air 

conditioner credits over time with a phase-in of alternative refrigerant for the generation of 

HFC leakage reduction credits consistent with the assumed phase-in schedule discussed in 
9 

Section III.C.I. of this preamble. No adjustments were made to vehicle CO2 performance 

other then this assumption of air conditioning credit generation. Under this analysis, a wide 

range of existing vehicles would meet the MY2017 proposed CO2 targets, and a few meet 

even the proposed MY2025 CO2 targets. The details regarding this assessment are 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 CO2 targets 

with current powertrain designs, assuming air conditioning credit generation consistent with 

our proposal. The list of vehicles includes a full suite of vehicle sizes and classes, including 

midsize cars, minivans, sport utility vehicles, compact cars, small pickup trucks and full size 

pickup trucks – 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 of powertrain technologies (including gasoline engines), and operate on a variety of 

different fuels including gasoline, diesel, electricity, and compressed natural gas. Nearly 

every major manufacturer currently produces vehicles that would meet or exceed the 

proposed MY2017 footprint CO2 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 (or “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 and Sierra’s meet not just the MY2017 

footprint-based CO2 targets with A/C improvements, but their respective targets through 

MY2022). As the CO2 targets become more stringent each model year, fewer MY2011 and 

MY2012 vehicles achieve or surpass the proposed CO2 targets, in particular for gasoline 

powertrains. While approximately 15 unique gasoline 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 CO2 targets with A/C improvements. 

EPA also assessed the subset of these vehicles that have emissions within 5%, of the 

proposed CO2 targets. As detailed in Chapter 3 of the EPA Draft RIA, the analysis shows that 

there are more than twenty additional vehicle models (primarily with gasoline and diesel 

powertrains) that are within 5% of the proposed MY2017 CO2 targets, including compact 

cars, midsize cars, large cars, SUVs, station wagons, minivans, small and standard pickup 

trucks. EPA also receives projected sales data prior 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 targets for those vehicles, requiring only 

improvements in air conditioning systems. In addition, nearly 15% of projected MY2011 

sales would be within 5% of the proposed MY2017 footprint CO2 target with only simple 

improvements to air conditioning systems, a full six 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 proposed footprint-based CO2

targets (assuming improvements in air conditioning) are hybrid-electric, plug-in hybridelectric, and fully electric vehicles. However, the proposed MY 2021 standards, if finalized, 

would not need to be met for another 9 years. Today’s Toyota Prius, Ford Fusion Hybrid, 

Chevrolet Volt, Nissan Leaf, Honda Civic Hybrid, and Hyundai Sonata Hybrid all meet or 
10 

surpass the proposed footprint-based CO2 targets through MY2025. In fact, the current Prius, 

Volt, and Leaf meet the proposed 2025 CO2 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 gasoline 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 vehicles available in the market today 

indicates advanced gasoline vehicles (as well as diesels) 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 increase substantially in order for individual 

manufacturers (and the fleet overall) to achieve the 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 NHTSA describe in detail in Chapter 3 of 

the draft Joint Technical Support Document and which 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 (including in some cases with the application of 

cooled exhaust gas recirculation); continued improvements in engine friction reduction and 

low friction lubricants; transmissions with an increased number of forward gears (e.g., 8 

speeds); improvements in transmission shifting logic; 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’ CO2 benefits can be fully realized and large-scale manufacturing 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 CO2 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 2017-2025 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 important powertrain technologies such as 8-

speed transmissions and second or third generation downsized engines with turbocharging, 

The majority of these technologies must be integrated into vehicles during the product 

redesign schedule, which is typically on a 5-year cycle. EPA discussed in the MY2012-2016 

rule the significant costs and potential risks associated with requiring major technologies to be 

added in-between the typical 5-year vehicle redesign 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 powertrain 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 that 8-speed transmissions could increase 

their maximum penetration in the fleet from 30% in MY2016 to 80% in 2021 and to 100% in 
11 

MY2025. Similarly, we project that second generation downsized and turbocharged engines 

(represented in our assessment as engines with a brake-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 typical 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 fleet 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 and introduction process which is 

fairly standard in the automotive industry today, our assessment of the MY2011 and MY2012 

vehicles in comparison to the proposed standards supports our overall feasibility assessment, 

and reinforces our assessment of the lead time needed 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 or 

Surpass 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 against the proposed CO2 footprintbased standard curves to determine which vehicles would 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 proposed 2017-2025 greenhouse gas emissions 

standards, each vehicle will have a unique CO2 target 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 conditioner improvements are considered to be 

among the cheapest and easiest technologies to reduce greenhouse gas emissions, 

manufacturers are already investing in air conditioner improvements, and air conditioner 

changes do not impact engine, transmission, or aerodynamic 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 time 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 adjustments were made to vehicle CO2 

performance other then this assumption of air conditioning credit generation. Under this 

analysis, a wide range of these existing vehicles would meet the MY2017 proposed CO2 

targets, and a few meet even the proposed MY2025 CO2 targets. 

Using publicly available dataB, EPA compiled a list of all available vehicles and their 

2-cycle CO2 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 0-1Error! 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 conditioning credit generation consistent with 

our proposal. The table highlights the vehicles that meet or are lower than the proposed 

footprint targets from MY 2017 to 2025 in green, and shows the percentage below the 

proposed target for each year. The list of vehicles includes midsize cars, minivans, sport 

utility vehicles, compact cars, and small pickup trucks – 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 of powertrain technologies, including internal 

combustion, hybrid-electric, plug-in hybrid-electric, and full electric, and operate on a variety 

of different fuels including gasoline, diesel, electricity, and compressed natural gas. Nearly 

 

B www.fueleconomy.gov 
13 

every major manufacturer produces vehicles that would meet or exceed the proposed 

MY2017 footprint CO2 target with only simple improvements in air conditioning systems. 

Vehicles that are above, but within 5%, of the proposed 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 trucks. 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 wheelbase optionsC

. 

EPA also receives projected sales data prior 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 targets for those vehicles, requiring only 

improvements in air conditioning systems. In addition, nearly 30% of projected MY2011 

sales would be within 10% of the proposed MY2017 footprint CO2 target with only simple 

improvements to air conditioning systems, a full six 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 proposed footprint-based CO2 targets 

(assuming improvements in air conditioning) are hybrid-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 vehicles will continue to improve in that 

timeframe and will be able to meet the standard (using the technologies discussed in Chapter 

3 of the draft Joint TSD and as discussed in Preamble Section III.D) assuming air conditioner 

improvements . Today’s Toyota Prius, Ford Fusion Hybrid, Chevrolet Volt, Nissan Leaf, 

Honda Civic Hybrid, and Hyundai Sonata Hybrid all meet or surpass the proposed footprintbased CO2 targets through MY2025. In fact, the current 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 currently 

available. Not all possible engine and wheelbase combinations are produced. 
Table 0-1 - Vehicles that Meet or Exceed Proposed Targets With Current Powertrain Des

2017 2018 2019 

2011 Mercedes-Benz Smart fortwo (cabriolet) 123.9 0.0 26.8 EV A1 n/a Two Seaters C 100% 100% 100% 

2011 Mercedes-Benz Smart fortwo (coupe) 123.9 0.0 26.8 EV A1 n/a Two Seaters C 100% 100% 100% 2011 Nissan LEAF 141.7 0.0 44.7 EV A1 n/a Midsize Cars C 100% 100% 100% 2011 Chevrolet VOLT 48.4 56.0 45.3 PHEV CVT 1.4 Compact Cars C 76% 76% 75% 2011 Toyota PRIUS 70.8 125.6 44.2 HEV CVT 1.8 Midsize Cars C 46% 44% 42% 2012 Honda CIVIC HYBRID 63.1 140.9 43.5 HEV A5 1.5 Compact Cars C 38% 35% 33% 2011 Hyundai SONATA HYBRID 52.2 170.3 48.0 HEV A6 2.4 Midsize Cars C 30% 28% 24% 2012 Ford FUSION HYBRID FWD 54.2 164.0 45.6 HEV CVT 2.5 Midsize Cars C 30% 27% 24% 2012 Lincoln MKZ HYBRID FWD 54.2 164.0 45.6 HEV CVT 2.5 Midsize Cars C 30% 27% 24% 2011 Lexus CT 200h 57.5 154.6 42.6 HEV CVT 1.8 Compact Cars C 30% 27% 24% 2011 Honda INSIGHT 57.3 155.1 40.8 HEV CVT 1.3 Compact Cars C 27% 24% 21% 2011 Toyota HIGHLANDER HYBRID 4WD 38.7 229.7 48.8 HEV CVT 3.5 Sport Utility Vehicle T 21% 20% 18% 2011 Lexus RX 450h AWD 38.6 230.4 48.6 HEV CVT 3.5 Sport Utility Vehicle T 21% 19% 18% 2011 Honda CIVIC CNG 37.5 175.7 43.4 CNG A5 1.8 Subcompact Cars C 21% 17% 14% 2011 Chevrolet SILVERADO 2WD HYBRID 28.5 311.4 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 14% 14% 14% 2011 GMC SIERRA 2WD HYBRID 28.5 311.4 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 14% 14% 14% 2011 Chevrolet SILVERADO 4WD HYBRID 28.4 313.2 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 13% 13% 14% 2011 GMC SIERRA 4WD HYBRID 28.4 313.2 67.3 HEV CVT 6.0 Standard Pick-up Trucks T 13% 13% 14% 2011 Nissan ALTIMA HYBRID 46.7 190.3 46.3 HEV CVT 2.5 Midsize Cars C 19% 15% 12% 2011 Toyota CAMRY HYBRID 45.9 193.4 46.9 HEV CVT 2.4 Midsize Cars C 18% 15% 11% 2011 Lexus HS 250h 47.3 188.0 44.5 HEV CVT 2.4 Compact Cars C 17% 13% 9% 2012 Ford ESCAPE HYBRID AWD 39.0 227.6 43.3 HEV CVT 2.5 Sport Utility Vehicle T 13% 12% 10% 2011 Honda CR-Z 50.1 177.3 39.5 HEV CVT 1.5 Two Seaters C 15% 12% 8% 2011 Mercedes-Benz Smart fortwo (cabriolet) 49.5 179.5 26.8 Gasoline A5 1.0 Two Seaters C 14% 11% 7% 2011 Mercedes-Benz Smart fortwo (coupe) 49.5 179.5 26.8 Gasoline A5 1.0 Two Seaters C 14% 11% 7% 2012 Hyundai ELANTRA 44.7 198.7 45.2 Gasoline M6 1.8 Midsize Cars C 13% 9% 5% 2012 Hyundai ELANTRA 44.4 200.2 45.2 Gasoline A6 1.8 Midsize Cars C 12% 9% 4% 2011 Toyota TACOMA 2WD 30.2 294.5 55.9 Gasoline M5 2.7 Small Pick-up Trucks T 9% 7% 5% 2011 Toyota SIENNA 29.4 302.0 56.1 Gasoline A6 2.7 Minivan T 7% 5% 3% 2012 Chevrolet CRUZE ECO 44.4 200.3 44.8 Gasoline M6 1.4 Midsize Cars C 11% 8% 3% 2011 Lexus RX 450h 40.4 220.2 48.6 HEV CVT 3.5 Sport Utility Vehicle C 9% 6% 1% 2012 Ford Focus SFE FWD 43.6 203.7 44.2 Gasoline A6 2.0 Compact Cars C 9% 5% 0% 2012 Honda CIVIC HF 44.3 200.6 43.4 Gasoline A5 1.8 Compact Cars C 9% 5% 0% 2011 Honda ODYSSEY 2WD 29.0 306.7 55.9 Gasoline A6 3.5 Minivan T 5% 3% 1% 2011 Ford RANGER 2WD 31.2 284.5 50.6 Gasoline M5 2.3 Small Pick-up Trucks T 4% 2% 0% 2012 Ford ESCAPE HYBRID FWD 44.1 201.4 43.3 HEV CVT 2.5 Sport Utility Vehicle C 8% 4% 0% 2011 Toyota TACOMA 2WD 28.3 313.6 55.9 Gasoline A4 2.7 Small Pick-up Trucks T 3% 1% -1% 2012 Hyundai ACCENT 45.5 195.1 41.7 Gasoline A6 1.6 Compact Cars C 8% 4% -1% 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 Compact Cars 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% 2011 Chevrolet TAHOE 2WD HYBRID 28.5 311.4 54.8 HEV CVT 6.0 Sport Utility Vehicle T 2% -1% -2% 2011 GMC YUKON 2WD HYBRID 28.5 311.4 54.8 HEV CVT 6.0 Sport Utility Vehicle T 2% -1% -2% 2011 Chevrolet TAHOE 4WD HYBRID 28.4 313.2 54.8 HEV CVT 6.0 Sport Utility Vehicle T 1% -1% -3%2011 GMC YUKON 4WD HYBRID 28.4 313.2 54.8 HEV CVT 6.0 Sport Utility 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 Midsize Cars 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 Compact Cars C 3% -2%

Model 

Year Manufacturer Vehicle

Unadjusted 

Fuel Economy

(mpg)

Footprint

(ft

2

)

Tailpipe CO2

(ft

2

)

Powertrain 

Type Vehicle Class Car/ Truck 

Transmission Engine Displacement (L)
2017 2018 2019 

2011 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 Midsize Cars 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 Midsize Cars 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 Midsize Cars 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% 2011 Ford F150 PICKUP 2WD 23.9 372.3 72.8 Gasoline A6 3.5 Standard Pick-up Trucks T -4% -4% -4% 2011 Ford F150 PICKUP 2WD 23.9 372.3 67.2 Gasoline A6 3.5 Standard Pick-up Trucks T -4% -4% -4% 2011 Ford F150 PICKUP 2WD 24.4 363.8 67.2 Gasoline A6 3.7 Standard Pick-up Trucks T -2% -1% -1% 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 Gasoline M6 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 Compact Cars C 0% -5%2011 Toyota VENZA AWD 30.2 294.3 48.8 Gasoline A4 2.0 Sport Utility 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 Sport Utility 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 Subcompact Cars C -1%2012 Volkswagen Passat 44.6 228.2 45.3 Diesel A6 2.0 Midsize Cars C -1%2011 Honda FIT 42.5 208.9 39.9 Gasoline A5 1.5 Small Station Wagons C -1%2012 Nissan SENTRA 39.5 224.9 44.3 Gasoline CVT 2.0 Midsize Cars C -1%2011 Toyota COROLLA 41.0 217.0 42.5 Gasoline M5 1.8 Compact Cars C -1%2012 Ford FOCUS FWD 39.4 225.4 44.2 Gasoline M5 2.0 Compact Cars 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 Cars C -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 Subcompact Cars C -2%2011 Kia OPTIMA 36.3 245.1 48.1 Gasoline A6 2.4 Midsize Cars C -2%2012 Chevrolet CRUZE 38.5 230.5 44.8 Gasoline M6 1.8 Midsize Cars 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 M6 2.0 Small Station Wagons C -4%2011 Kia FORTE KOUP 38.3 232.1 44.6 Gasoline A6 2.0 Compact Cars 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/

Truck

Footprint

(ft2)

Powertrain 

Type Transmission

Engine 

Displacement

(L)

Vehicle Class Model Year Manufacturer Vehicle Unadjusted Fuel Economy (mpg) Tailpipe CO2 (ft2)
16 

 

1

 EPA’s “Light Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy 

Trends Report, 1975 through 2010”