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TABLE IV.C.1–6a—CURRENT BASELINE AVERAGE MY 2011 VEHICLE POWER-TO-WEIGHT RATIO—Continued 

[hp/lb] 

Manufacturer PC LT Avg. 

Industry Average .............................................................................................................................. 0.056 0.056 0.056 

TABLE IV.C.1–6b—MY 2011 FINAL RULE AVERAGE PLANNED MY 2011 VEHICLE POWER-TO-WEIGHT RATIO 

[hp/lb] 

PC LT Avg. 

Manufacturer 1 ......................................................................................................................................... 

Manufacturer 2 ......................................................................................................................................... 

Manufacturer 3 ......................................................................................................................................... 

Manufacturer 4 ......................................................................................................................................... 

Manufacturer 5 ......................................................................................................................................... 

Manufacturer 6 ......................................................................................................................................... 

Manufacturer 7 ......................................................................................................................................... 

0.065 

0.061 

0.053 

0.060 

0.060 

0.063 

0.053 

0.058 

0.065 

0.059 

0.058 

0.057 

0.065 

0.055 

0.060 

0.062 

0.056 

0.059 

0.059 

0.065 

0.053 

Industry Average .............................................................................................................................. 0.060 0.059 0.060 

As discussed above, the agencies’ 

market forecast for MY 2012–2016 holds 

the performance and other 

characteristics of individual vehicle 

models constant, adjusting the size and 

composition of the fleet from one model 

year to the next. 

Refresh and redesign schedules (for 

application in NHTSA’s modeling): 

Expected model years in which each 

vehicle model will be redesigned or 

freshened constitute another important 

aspect of NHTSA’s market forecast. As 

discussed in Section IV.C.2.c below, 

NHTSA’s analysis supporting the 

current rulemaking times the addition of 

nearly all technologies to coincide with 

either a vehicle redesign or a vehicle 

freshening. Product plans submitted to 

NHTSA preceding the MY 2011 final 

rule contained manufacturers’ estimates 

of vehicle redesign and freshening 

schedules and NHTSA’s estimates of the 

timing of the five-year redesign cycle 

and the two- to three-year refresh cycle 

were made with reference to those 

plans. In the current baseline, in 

contrast, estimates of the timing of the 

refresh and redesign cycles were based 

on historical dates—i.e., counting 

forward from known redesigns 

occurring in or prior to MY 2008 for 

each vehicle in the fleet and assigning 

refresh and redesign years accordingly. 

After applying these estimates, the 

shares of manufacturers’ passenger car 

and light truck estimated to be 

redesigned in MY 2011 were as 

summarized below for the current 

baseline and the MY 2011 final rule. 

Table IV.C.1–7 below shows the 

percentages of each manufacturer’s 

fleets expected to be redesigned in MY 

2011 for the current baseline. Table 

IV.C.1–8 presents corresponding 

estimates from the market forecast used 

by NHTSA in the analysis supporting 

the MY 2011 final rule (again, to protect 

confidential information, manufacturers 

are not identified by name). 

TABLE IV.C.1–7—CURRENT BASELINE, SHARE OF FLEET REDESIGNED IN MY 2011 

Manufacturer PC LT Avg. 

BMW ........................................................................................................................................................ 

Chrysler .................................................................................................................................................... 

Ford .......................................................................................................................................................... 

Subaru ..................................................................................................................................................... 

General Motors ........................................................................................................................................ 

Honda ...................................................................................................................................................... 

Hyundai .................................................................................................................................................... 

Tata .......................................................................................................................................................... 

Kia ............................................................................................................................................................ 

Mazda ...................................................................................................................................................... 

Daimler ..................................................................................................................................................... 

Mitsubishi ................................................................................................................................................. 

Nissan ...................................................................................................................................................... 

Porsche .................................................................................................................................................... 

Suzuki ...................................................................................................................................................... 

Toyota ...................................................................................................................................................... 

Volkswagen .............................................................................................................................................. 

32% 

0% 

12% 

0% 

20% 

31% 

20% 

28% 

35% 

0% 

0% 

0% 

4% 

0% 

8% 

4% 

23% 

40% 

11% 

7% 

51% 

2% 

33% 

0% 

100% 

87% 

0% 

0% 

56% 

18% 

100% 

21% 

24% 

0% 

34% 

8% 

10% 

22% 

11% 

32% 

16% 

73% 

48% 

0% 

0% 

7% 

9% 

41% 

11% 

12% 

18% 

Industry Average .............................................................................................................................. 15% 17% 15% 

TABLE IV.C.1–8—MY 2011 FINAL RULE, SHARE OF FLEET REDESIGNED IN MY 2011 

PC 

(percent) 

LT 

(percent) 

Avg. 

(percent) 

Manufacturer 1 ......................................................................................................................................... 19 0 11 
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TABLE IV.C.1–8—MY 2011 FINAL RULE, SHARE OF FLEET REDESIGNED IN MY 2011—Continued 

PC 

(percent) 

LT 

(percent) 

Avg. 

(percent) 

Manufacturer 2 ......................................................................................................................................... 

Manufacturer 3 ......................................................................................................................................... 

Manufacturer 4 ......................................................................................................................................... 

Manufacturer 5 ......................................................................................................................................... 

Manufacturer 6 ......................................................................................................................................... 

Manufacturer 7 ......................................................................................................................................... 

34 

5 

7 

19 

34 

27 

27 

0 

0 

0 

28 

28 

29 

3 

5 

11 

33 

28 

Overall .............................................................................................................................................. 20 9 15 

We continue, therefore, to estimate 

that manufacturers’ redesigns will not 

be uniformly distributed across model 

years. This is in keeping with standard 

industry practices, and reflects what 

manufacturers actually do—NHTSA has 

observed that manufacturers in fact do 

redesign more vehicles in some years 

than in others. NHTSA staff have 

closely examined manufacturers’ 

planned redesign schedules, contacting 

some manufacturers for clarification of 

some plans, and confirmed that these 

plans remain unevenly distributed over 

time. For example, although Table 8 

shows that NHTSA expects Company 2 

to redesign 34 percent of its passenger 

car models in MY 2011, current 

information indicates that this company 

will then redesign only (a different) 10 

percent of its passenger cars in MY 

2012. Similarly, although Table 8 shows 

that NHTSA expects four of the largest 

seven light truck manufacturers to 

redesign virtually no light truck models 

in MY 2011, current information also 

indicates that these four manufacturers 

will redesign 21–49 percent of their 

light trucks in MY 2012. 

e. How Does Manufacturer Product Plan 

Data Factor Into the Baseline Used in 

This Proposal? 

As discussed in Section II.B.4 above, 

while the agencies received updated 

product plans in Spring 2009 in 

response to NHTSA’s request, the 

baseline data used in this proposal is 

not informed by these product plans, 

because they contain confidential 

business information the agencies are 

legally required to protect from 

disclosure, and because the agencies 

have concluded that, for purposes of 

this NPRM, a transparent baseline is 

preferable. 

However, as also discussed above, 

NHTSA has conducted a separate 

analysis that does make use of these 

product plans, contained in NHTSA’s 

PRIA. NHTSA performed this separate 

analysis for purposes of comparison 

only. NHTSA used the publicly 

available baseline for all analysis related 

to the development and evaluation of 

the proposed new CAFE standards. 

2. How Were the Technology Inputs 

Developed? 

As discussed above in Section II.E, for 

developing the technology inputs for the 

MY 2012–2016 CAFE and GHG 

standards, the agencies primarily began 

with the technology inputs used in the 

MY 2011 CAFE final rule and in the July 

2008 EPA ANPRM, and then reviewed, 

as requested by President Obama in his 

January 26 memorandum, the 

technology assumptions that NHTSA 

used in setting the MY 2011 standards 

and the comments that NHTSA received 

in response to its May 2008 Notice of 

Proposed Rulemaking. In addition, the 

agencies supplemented their review 

with updated information from more 

current literature, new product plans 

and from EPA certification testing. More 

detail is available regarding how the 

agencies developed the technology 

inputs for this NPRM above in Section 

II.E, in Chapter 3 of the Draft Joint TSD, 

and in Section V of NHTSA’s PRIA. 

a. What Technologies Does NHTSA 

Consider? 

Section II.E.1 above describes the 

fuel-saving technologies considered by 

the agencies that manufacturers could 

use to improve the fuel economy of their 

vehicles during MYs 2012–2016. The 

majority of the technologies described 

in this section are readily available, well 

known, and could be incorporated into 

vehicles once production decisions are 

made. As discussed, the technologies 

considered fall into five broad 

categories: Engine technologies, 

transmission technologies, vehicle 

technologies, electrification/accessory 

technologies, and hybrid technologies. 

Table IV.C.2–1 below lists all the 

technologies considered and provides 

the abbreviations used for them in the 

Volpe model,464 as well as their year of 

availability, which for purposes of 

NHTSA’s analysis means the first model 

year in the rulemaking period that the 

Volpe model is allowed to apply a 

technology to a manufacturer’s fleet.465 

Year of availability recognizes that 

technologies must achieve a level of 

technical viability before they can be 

implemented in the Volpe model, and 

are thus a means of constraining 

technology use until such time as it is 

considered to be technologically 

feasible. For a more detailed description 

of each technology and their costs and 

effectiveness, we refer the reader to 

Chapter 3 of the joint TSD and Section 

V of NHTSA’s PRIA. 

TABLE IV.C.2–1—LIST OF TECHNOLOGIES IN NHTSA’S ANALYSIS 

Technology Model abbreviation Year available 

Low Friction Lubricants ................................................................................................
 LUB ...........................................................
 2011 

Engine Friction Reduction ............................................................................................
 EFR ...........................................................
 2011 

VVT—Coupled Cam Phasing (CCP) on SOHC ...........................................................
 CCPS ........................................................
 2011 

Discrete Variable Valve Lift (DVVL) on SOHC ............................................................
 DVVLS ......................................................
 2011 

Cylinder Deactivation on SOHC ...................................................................................
 DEACS ......................................................
 2011 

464 The abbreviations are used in this section both in Docket No. NHTSA–2009–0059 and on NHTSA’s 465 A date of 2011 means the technology can be 

for brevity and for the reader’s reference if they Web site. applied in all model years, while a date of 2014 

wish to refer to the expanded decision trees and the means the technology can only be applied in model 

model input and output sheets, which are available years 2014 through 2016. 
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TABLE IV.C.2–1—LIST OF TECHNOLOGIES IN NHTSA’S ANALYSIS—Continued 

Technology Model abbreviation Year available 

VVT—Intake Cam Phasing (ICP) .................................................................................
 ICP ............................................................
 2011 

VVT—Dual Cam Phasing (DCP) .................................................................................
 DCP ..........................................................
 2011 

Discrete Variable Valve Lift (DVVL) on DOHC ............................................................
 DVVLD ......................................................
 2011 

Continuously Variable Valve Lift (CVVL) .....................................................................
 CVVL .........................................................
 2011 

Cylinder Deactivation on DOHC ..................................................................................
 DEADD .....................................................
 2011 

Cylinder Deactivation on OHV .....................................................................................
 DEACO .....................................................
 2011 

VVT—Coupled Cam Phasing (CCP) on OHV .............................................................
 CCPO ........................................................
 2011 

Discrete Variable Valve Lift (DVVL) on OHV ...............................................................
 DVVLO ......................................................
 2011 

Conversion to DOHC with DCP ...................................................................................
 CDOHC .....................................................
 2011 

Stoichiometric Gasoline Direct Injection (GDI) ............................................................
 SGDI .........................................................
 2011 

Combustion Restart ......................................................................................................
 CBRST ......................................................
 2014 

Turbocharging and Downsizing ....................................................................................
 TRBDS ......................................................
 2011 

Exhaust Gas Recirculation (EGR) Boost .....................................................................
 EGRB ........................................................
 2013 

Conversion to Diesel following CBRST .......................................................................
 DSLC ........................................................
 2011 

Conversion to Diesel following TRBDS .......................................................................
 DSLT .........................................................
 2011 

6-Speed Manual/Improved Internals ............................................................................
 6MAN ........................................................
 2011 

Improved Auto. Trans. Controls/Externals ...................................................................
 IATC ..........................................................
 2011 

Continuously Variable Transmission ............................................................................
 CVT ...........................................................
 2011 

6/7/8-Speed Auto. Trans with Improved Internals .......................................................
 NAUTO .....................................................
 2011 

Dual Clutch or Automated Manual Transmission ........................................................
 DCTAM .....................................................
 2011 

Electric Power Steering ................................................................................................
 EPS ...........................................................
 2011 

Improved Accessories ..................................................................................................
 IACC .........................................................
 2011 

12V Micro-Hybrid ..........................................................................................................
 MHEV ........................................................
 2011 

Belt Integrated Starter Generator .................................................................................
 BISG .........................................................
 2011 

Crank Integrated Starter Generator .............................................................................
 CISG .........................................................
 2011 

Power Split Hybrid ........................................................................................................
 PSHEV ......................................................
 2011 

2-Mode Hybrid ..............................................................................................................
 2MHEV ......................................................
 2011 

Plug-in Hybrid ...............................................................................................................
 PHEV ........................................................
 2011 

Mass Reduction 1 (1.5%) .............................................................................................
 MS1 ...........................................................
 2011 

Mass Reduction 2 (3.5%–8.5%) ..................................................................................
 MS2 ...........................................................
 2014 

Low Rolling Resistance Tires .......................................................................................
 ROLL .........................................................
 2011 

Low Drag Brakes ..........................................................................................................
 LDB ...........................................................
 2011 

Secondary Axle Disconnect 4WD ................................................................................
 SAX ...........................................................
 2011 

Aero Drag Reduction ....................................................................................................
 AERO ........................................................
 2011 

For purposes of this NPRM and as 

discussed in greater detail in the joint 

TSD, NHTSA and EPA carefully 

reviewed the list of technologies used in 

the agency’s analysis for the MY 2011 

final rule. Given the relatively short 

amount of time, from a technologydevelopment perspective, that has 

elapsed since March 2009 and this 

NPRM, NHTSA and EPA concluded that 

the considerable majority of 

technologies were correctly defined and 

continued to be appropriate for use in 

the analysis supporting the proposed 

standards. However, some refinements 

were made as discussed below. 

Specific to its modeling, NHTSA has 

revised eight of the technologies used in 

the current analysis from those 

considered in the MY 2011 final rule. 

Specifically, two technologies which 

were previously unavailable in the MY 

2011 time frame are now available (in 

the extended MY 2012–2016 period); 

one technology has been combined with 

another; one is newly introduced; three 

have revised names and/or definitions; 

and one has been deleted entirely. 

These changes are discussed further 

below, and NHTSA seeks comment on 

both these changes and the validation of 

the unchanged technology assumptions 

and estimates. 

Availability: In the MY 2011 final 

rule, two of the engine technologies— 

EGR boost and combustion restart— 

were unavailable because they were not 

considered technologically feasible until 

beyond that rulemaking time frame. 

While both were described and 

discussed in the MY 2011 final rule, 

neither was applied in the modeling 

process that supported those 

standards.466 In this analysis, EGR boost 

becomes available in MY 2013, and 

combustion restart in MY 2014, so both 

are being applied by the Volpe model, 

as needed, in this analysis. 

Merging of technologies: In the MY 

2011 final rule, higher voltage and 

improved alternator (HVIA) was used to 

represent changes in the design of the 

alternator, effectively optimizing it for 

higher efficiency (instead of for low cost 

as is typically done). For purposes of 

466 As an additional note, since combustion 

restart was unavailable in the MY 2011 time frame, 

the technology titled diesel following combustion 

restart (DSLC), which as the name indicates was 

only applied after combustion restart, was also 

unavailable. Accordingly, DSLC, which was 

described and discussed in the MY 2011 final rule, 

is now available in the current analysis. 

this analysis, the HVIA technology is no 

longer represented individually, but 

instead has been incorporated into a 

new-to-this-analysis technology called 

belt integrated starter generator, or 

BISG, as discussed next. 

New technology: In the MY 2011 final 

rule, two levels of mild hybrid 

technology were defined: A 12 volt 

micro-hybrid (MHEV) system, which 

utilized a belt-driven starter generator 

operating at 12 volts, and the more 

capable integrated starter generator 

technology (ISG) operating at higher 

voltages (100 volts). ISG envisioned 

both belt and crank configured starter 

generator systems. In the current 

proposal, and in an effort to offer a 

broader spectrum of more diversified 

mild hybrid technologies for the 

modeling process to choose from, 

NHTSA has added the BISG technology 

to the electrification decision tree, and 

redefined the ISG technology to be a 

crank mounted version of ISG, 

accordingly renamed to CISG. 

The BISG technology is a belt-coupled 

system like the 12-volt MHEV, but it 

operates at a higher voltage (e.g., 42 

volts) and thus can make use of 

regenerative braking, as well as 
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potentially adding some limited motive 

power. Since BISG is a higher voltage 

system, optimization of the alternator 

occurs as part of the BISG technology 

application; hence the HVIA technology 

is no longer needed as a separate 

technology. Additionally, the CISG 

technology is now defined as a crank 

mounted system that operates at higher 

voltages (100 volts) than BISG, yet at 

lower voltage than the strong hybrids 

(300 volts) that make greater use of 

regenerative braking and provide greater 

motive power capability. Thus, three 

levels of mild hybrid technology exist in 

the current proposal, as opposed to the 

two levels offered in the MY 2011 final 

rule. 

Revisions and Deletions: The Mass 

Reduction/Material Substitution 

technologies have been revised for the 

current proposal. In the MY 2011 final 

rule, the Volpe model used three levels 

of material substitution technologies, 

referred to as MS1, MS2, and MS5, 

which were progressively applied to 

vehicles with curb weights in excess of 

5,000 pounds (2,268 kg) so as to reduce 

weight by up to a 5 percent maximum. 

In keeping with the agency’s desire to 

limit potential negative impacts to 

safety performance as a result of vehicle 

weight reduction, material substitution 

was not applied to vehicles with curb 

weights below 5,000 pounds. In 

contrast, in the current analysis, and in 

keeping with some manufacturers’ 

stated plans to decrease overall fleet 

weights regardless of subclass or curb 

weight, NHTSA now defines two Mass 

Reduction/Material Substitution 

technologies as follows: 

The Mass Reduction 1.5 percent 

(MS1) represents a 1.5 percent weight 

decrease through material substitution 

applicable to all vehicle subclasses, 

regardless of curb weight, that can be 

applied throughout the rulemaking 

period (and at refresh or redesign cycle 

times). This technology is similar to the 

MS1 technology used in the prior 

analysis in terms of the scale of the 

weight reduction (1 versus 1.5 percent), 

the methods and techniques 

manufacturers are anticipated to use in 

achieving the reductions, and when in 

the product cycle the model applies it 

(at refresh or redesign). 

A second technology, Mass Reduction 

3.5–8.5 percent (MS2), has also been 

defined. The MS2 technology is 

unavailable until MY 2014, and can 

only be applied by the Volpe model at 

a product redesign cycle. MS2 assumes 

a 3.5 to 8.5 percent weight reduction 

dependent on subclass (with the 

smaller/lighter subclasses receiving the 

lowest amounts of reduction, 3.5 

percent, and the larger/heavier vehicles 

the 8.5 percent) via the types of more 

intrusive and complex mass reduction 

associated with a complete vehicle 

redesign.467 MS2 is cumulative to MS1, 

as it is only applied after MS1, therefore 

the maximum weight reduction that can 

occur for smaller subclass vehicles is 5 

percent, while large cars, truck, and 

SUVs could experience 10 percent 

weight reductions. Restricting weight 

reduction on smaller vehicle to lower 

limits, and vice versa for larger vehicles, 

is intended to mitigate or minimize the 

potential safety consequences from the 

modeled weight reductions. Postponing 

the availability of the technology until 

MY 2014 recognizes the lead time 

required to implement platform 

redesigns that would be necessary for 

these levels of weight reduction and 

mass reduction. NHTSA seeks comment 

on the agency’s use of a two-step 

process, with the higher applications of 

MS in MYs 2014 and beyond, and the 

process of applying smaller mass 

reductions to lighter vehicles and higher 

reductions to heavier vehicles for the 

purpose of maintaining safety 

neutrality. 

The MS5 technology used in the MY 

2011 final rule is deleted. 

Additionally, for purposes of this 

NPRM, NHTSA has revised the 

applicability of the diesel technologies 

to restrict it to vehicles with engines of 

6 cylinders or more. NHTSA seeks 

comment on its decision not to apply 

diesel technologies to vehicles with 4-

cylinder engines. NHTSA also seeks 

comment on the revised costing 

methodology for diesel technologies. 

Besides these, all other technologies 

considered in this analysis were also 

considered in the analysis for the MY 

2011 final rule, and although the costs 

and effectiveness estimates may have 

been revised as discussed further below, 

the other technologies remain otherwise 

unchanged for the purposes of this 

analysis in terms of their definition, 

functionality, and configuration. Thus, 

with this catalog of technologies as a 

starting point, NHTSA could then 

review and consider effectiveness and 

cost estimates for each technology, and, 

through the Volpe model analysis, how 

a manufacturer might feasibly apply 

these technologies to their MY 2012– 

2016 vehicles in order to achieve 

compliance with the proposed 

standards. 

467 Examples of such weight savings associated 

with new platform introductions have been 

provided in confidential product plan information 

provided by some manufacturers. 

b. How Did NHTSA Determine the Costs 

and Effectiveness of Each of These 

Technologies for Use in Its Modeling 

Analysis? 

Building on NHTSA’s estimates 

developed for the MY 2011 CAFE final 

rule and EPA’s Advanced Notice of 

Proposed Rulemaking, which relied on 

the 2008 Staff Technical Report,468 the 

agencies took a fresh look at technology 

cost and effectiveness values for 

purposes of the joint proposal under the 

National Program. This joint work is 

reflected in Chapter 3 of the Draft Joint 

TSD and in Section II of this preamble, 

which is summarized below. For more 

detailed information on the 

effectiveness and cost of fuel-saving 

technologies, please refer to Chapter 3 of 

the joint TSD and Section V of NHTSA’s 

PRIA. 

Generally speaking, while NHTSA 

and EPA found that much of the cost 

information used in NHTSA’s MY 2011 

final rule and EPA’s 2008 staff report 

was consistent to a great extent, the 

agencies, in reconsidering information 

from many sources, revised several 

component costs of several major 

technologies: turbocharging/ 

downsizing, mild and strong hybrids, 

diesels, SGDI, and Valve Train Lift 

Technologies. These are discussed at 

length in the joint TSD and in NHTSA’s 

PRIA. Additionally, most effectiveness 

estimates used in both the MY 2011 

final rule and the 2008 EPA staff report 

were determined to be accurate and 

were carried forward without significant 

change into this rulemaking. When 

NHTSA and EPA’s estimates for 

effectiveness diverged slightly due to 

differences in how agencies apply 

technologies to vehicles in their 

respective models, we report the ranges 

for the effectiveness values used in each 

model. For much more information on 

the costs and effectiveness of individual 

technologies, we refer the reader to 

Chapter 3 of the joint TSD and Section 

V of NHTSA’s PRIA. 

NHTSA notes that, in developing 

technology cost and effectiveness 

estimates, the agencies have made every 

effort to hold constant aspects of vehicle 

performance and utility typically valued 

by consumers, such as horsepower, 

carrying capacity, and towing and 

hauling capacity. For example, NHTSA 

includes in its analysis technology cost 

and effectiveness estimates that are 

specific to performance passenger cars 

(i.e., sports cars), as compared to nonperformance passenger cars. When 

468 EPA Staff Technical Report: Cost and 

Effectiveness Estimates of Technologies Used to 

Reduce Light-Duty Vehicle Carbon Dioxide 

Emissions. EPA420–R–08–008, March 2008. 
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commenting on the agencies’ technology 

cost and effectiveness estimates, 

NHTSA urges commenters either to 

place any related comments within the 

same context, or explain any 

assumptions or estimates regarding 

increases or decreases in vehicle 

performance or utility. Additionally, 

NHTSA seeks comment on the extent to 

which commenters believe that the 

agencies have been successful in 

holding constant these elements of 

vehicle performance and utility in 

developing the technology cost and 

effectiveness estimates. 

Additionally, NHTSA notes that the 

technology costs included in this NPRM 

take into account only those associated 

with the initial build of the vehicle. The 

agencies seek comments on the 

additional lifetime costs, if any, 

associated with the implementation of 

advanced technologies, including 

warranty, maintenance and replacement 

costs, such as the replacement costs for 

low rolling resistance tires, low friction 

lubricants, and hybrid batteries, and 

maintenance costs for diesel 

aftertreatment components. 

While the agencies believe that the 

ideal estimates for the final rule would 

be based on tear down studies or BOM 

approach and subjected to a transparent 

peer-reviewed process, NHTSA and 

EPA are confident that the thorough 

review conducted, led to the best 

available conclusion regarding 

technology costs and effectiveness 

estimates for the current rulemaking and 

resulted in excellent consistency 

between the agencies’ respective 

analyses for developing the CAFE and 

CO2 standards. 

NHTSA seeks comment on the 

incremental cost and effectiveness 

estimates employed by the agency in the 

Volpe modeling analysis for this NPRM, 

examples of which are provided in table 

form below. These example Tables 

present effectiveness and cost estimates 

which are incremental in nature, 

according to the decision trees used in 

the Volpe modeling analysis. Thus, the 

effectiveness and cost estimates are not 

absolute to a single baseline vehicle, but 

are incremental to the technology that 

precedes it. 

BILLING CODE 6560–50–C 

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BILLING CODE 6560–50–C 

c. How Does NHTSA Use These 

Assumptions in Its Modeling Analysis? 

NHTSA’s analysis, using the Volpe 

model, relies on several inputs and data 

files to conduct the compliance 

analysis, as discussed further below and 

in Section V of the PRIA. For the 

purposes of applying technologies, the 

Volpe model primarily uses three data 

files, one that contains data on the 

vehicles expected to be manufactured in 

the model years covered by the 

rulemaking, one that identifies the 

appropriate stage within the vehicle’s 

life-cycle for the technology to be 

applied, and one that contains data/ 

parameters regarding the available 

technologies the model can apply. 

These inputs are discussed below. 

As discussed above, the Volpe model 

begins with an initial state of the 

domestic vehicle market, which in this 

case is the market for passenger cars and 

light trucks to be sold during the period 

covered by the proposed standards. The 
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vehicle market is defined on a modelby-model, engine-by-engine, and 

transmission-by-transmission basis, 

such that each defined vehicle model 

refers to a separately defined engine and 

a separately defined transmission. 

For the current proposal, which 

covers MYs 2012–2016, the light vehicle 

(passenger car and light truck) market 

forecast was developed jointly by 

NHTSA and EPA staff using MY 2008 

CAFE compliance data. The MY 2008 

compliance data includes about 1,100 

vehicle models, about 400 specific 

engines, and about 200 specific 

transmissions, which is a somewhat 

lower level of detail in the 

representation of the vehicle market 

than that used by NHTSA in recent 

CAFE analyses.469 However, within the 

limitations of information that can be 

made available to the public, it provides 

the foundation for a realistic analysis of 

manufacturer-specific costs and the 

analysis of attribute-based CAFE 

standards, and is much greater than the 

level of detail used by many other 

models and analyses relevant to light 

vehicle fuel economy.470 

In addition to containing data about 

each vehicle, engine, and transmission, 

this file contains information for each 

technology under consideration as it 

pertains to the specific vehicle (whether 

the vehicle is equipped with it or not), 

the model year the vehicle is 

undergoing redesign, and information 

about the vehicle’s subclass for 

purposes of technology application. In 

essence, the model considers whether it 

is appropriate to apply a technology to 

a vehicle. 

Is a vehicle already equipped, or can 

it not be equipped, with a particular 

technology? 

The market forecast file provides 

NHTSA the ability to identify, on a 

technology by technology basis, which 

technologies may already be present 

(manufactured) on a particular vehicle, 

engine, or transmission, or which 

technologies are not applicable (due to 

technical considerations) to a particular 

vehicle, engine, or transmission. These 

469 The market file for the MY 2011 final rule, 

which included data for MYs 2011–2015, had 5500 

records, or rows, about 5 times what we are using 

in this analysis of the MY 2008 certification data. 

However, both market files had the same number 

of fields, or rows. 

470 Because CAFE standards apply to the average 

performance of each manufacturer’s fleet of cars 

and light trucks, the impact of potential standards 

on individual manufacturers cannot be credibly 

estimated without analysis of fleets manufacturers 

can be expected to produce in the future. 

Furthermore, because required CAFE levels under 

an attribute-based CAFE standard depend on 

manufacturers’ fleet composition, the stringency of 

an attribute-based standard cannot be predicted 

without performing analysis at this level of detail. 

identifications are made on a model-bymodel, engine-by-engine, and 

transmission-by-transmission basis. For 

example, if the market forecast file 

indicates that Manufacturer X’s Vehicle 

Y is manufactured with Technology Z, 

then for this vehicle Technology Z will 

be shown as used. Additionally, NHTSA 

has determined that some technologies 

are only suitable or unsuitable when 

certain vehicle, engine, or transmission 

conditions exist. For example, 

secondary axle disconnect is only 

suitable for 4WD vehicles, and cylinder 

deactivation is unsuitable for any engine 

with fewer than 6 cylinders, while CVTs 

can only be applied to unibody vehicles. 

Similarly, comments received to the 

2008 NPRM indicated that cylinder 

deactivation could not be applied to 

vehicles equipped with manual 

transmissions, due primarily to 

driveability and NVH concerns. The 

Volpe model employs ‘‘engineering 

constraints’’ to address issues like these, 

which are a programmatic method of 

controlling technology application that 

is independent of other constraints. 

Thus, the market forecast file would 

indicate that the technology in question 

should not be applied to the particular 

vehicle/engine/transmission (i.e., is 

unavailable). Since multiple vehicle 

models may be equipped with an engine 

or transmission, this may affect multiple 

models. In using this aspect of the 

market forecast file, NHTSA ensures the 

Volpe model only applies technologies 

in an appropriate manner, since before 

any application of a technology can 

occur, the model checks the market 

forecast to see if it is either already 

present or unavailable. 

NHTSA seeks comment on whether 

this approach is reasonable and ensures 

that technologies are applied in an 

appropriate manner. 

Is a vehicle being redesigned or 

refreshed? 

Manufacturers typically plan vehicle 

changes to coincide with certain stages 

of a vehicle’s life cycle that are 

appropriate for the change, or in this 

case the technology being applied. In 

the automobile industry there are two 

terms that describe when technology 

changes to vehicles occur: redesign and 

refresh (i.e., freshening). Vehicle 

redesign usually refers to significant 

changes to a vehicle’s appearance, 

shape, dimensions, and powertrain. 

Redesign is traditionally associated with 

the introduction of ‘‘new’’ vehicles into 

the market, often characterized as the 

‘‘next generation’’ of a vehicle, or a new 

platform. Vehicle refresh usually refers 

to less extensive vehicle modifications, 

such as minor changes to a vehicle’s 

appearance, a moderate upgrade to a 

powertrain system, or small changes to 

the vehicle’s feature or safety equipment 

content. Refresh is traditionally 

associated with mid-cycle cosmetic 

changes to a vehicle, within its current 

generation, to make it appear ‘‘fresh.’’ 

Vehicle refresh generally occurs no 

earlier than two years after a vehicle 

redesign, or at least two years before a 

scheduled redesign. For the majority of 

technologies discussed today, 

manufacturers will only be able to apply 

them at a refresh or redesign, because 

their application would be significant 

enough to involve some level of 

engineering, testing, and calibration 

work.471 

Some technologies (e.g., those that 

require significant revision) are nearly 

always applied only when the vehicle is 

expected to be redesigned, like 

turbocharging and engine downsizing, 

or conversion to diesel or hybridization. 

Other technologies, like cylinder 

deactivation, electric power steering, 

and aerodynamic drag reduction can be 

applied either when the vehicle is 

expected to be refreshed or when it is 

expected to be redesigned, while a few 

others, like low friction lubricants, can 

be applied at any time, regardless of 

whether a refresh or redesign event is 

conducted. Accordingly, the model will 

only apply a technology at the particular 

point deemed suitable. These 

constraints are intended to produce 

results consistent with manufacturers’ 

technology application practices. For 

each technology under consideration, 

NHTSA stipulates whether it can be 

applied any time, at refresh/redesign, or 

only at redesign. The data forms another 

input to the Volpe model. NHTSA 

develops redesign and refresh schedules 

for each of a manufacturer’s vehicles 

included in the analysis, essentially 

based on the last known redesign year 

for each vehicle and projected forward 

in a 5-year redesign and a 2–3 year 

refresh cycle, and this data is also stored 

in the market forecast file. We note that 

this approach is different than NHTSA 

has employed previously for 

determining redesign and refresh 

schedules, where NHTSA included the 

redesign and refresh dates in the market 

forecast file as provided by 

manufacturers in confidential product 

plans. The new approach is necessary 

471 For example, applying material substitution 

through weight reduction, or even something as 

simple as low rolling-resistance tires, to a vehicle 

will likely require some level of validation and 

testing to ensure that the vehicle may continue to 

be certified as compliant with NHTSA’s Federal 

Motor Vehicle Safety Standards (FMVSS). Weight 

reduction might affect a vehicle’s crashworthiness; 

low rolling-resistance tires might change vehicle’s 

braking characteristics or how it performs in crash 

avoidance tests. 
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given the nature of the new baseline 

which as a single year of data does not 

contain its own refresh and redesign 

cycle cues for future model years, and 

to ensure the complete transparency of 

the agency’s analysis. Vehicle redesign/ 

refresh assumptions are discussed in 

more detail in Section V of the PRIA 

and in Chapter 3 of the TSD. NHTSA 

seeks comment on its application for 

this proposal of refresh and redesign 

schedules to manufacturers’ vehicles 

counting from the last known redesign 

in or prior to the baseline fleet, as 

compared to its approach in the MY 

2011 final rule. 

Once the model has concluded that a 

technology should be applied to a 

vehicle, the model must evaluate which 

technology should be applied. This will 

depend on the vehicle subclass to which 

the vehicle is assigned; what 

technologies have already been applied 

to the vehicle (i.e., where in the 

‘‘decision tree’’ the vehicle is); when the 

technology is first available (i.e., year of 

availability); whether the technology is 

still available (i.e., ‘‘phase-in caps’’); and 

the costs and effectiveness of the 

technologies being considered. 

Technology costs may be reduced, in 

turn, by learning effects, while 

technology effectiveness may be 

increased or reduced by synergistic 

effects between technologies. In the 

technology input file, NHTSA has 

developed a separate set of technology 

data variables for each of the twelve 

vehicle subclasses. Each set of variables 

is referred to as an ‘‘input sheet,’’ so for 

example, the subcompact input sheet 

holds the technology data that is 

appropriate for the subcompact 

subclass. Each input sheet contains a 

list of technologies available for 

members of the particular vehicle 

subclass. The following items are 

provided for each technology: the name 

of the technology, its abbreviation, the 

decision tree with which it is 

associated, the (first) year in which it is 

available, the upper and lower cost and 

effectiveness (fuel consumption 

reduction) estimates, the learning type 

and rate, the cost basis, its applicability, 

and the phase-in values. 

To which vehicle subclass is the 

vehicle assigned? 

As part of its consideration of 

technological feasibility, the agency 

evaluates whether each technology 

could be implemented on all types and 

sizes of vehicles, and whether some 

differentiation is necessary in applying 

certain technologies to certain types and 

sizes of vehicles, and with respect to the 

cost incurred and fuel consumption and 

CO2 emissions reduction achieved when 

doing so. The 2002 NAS Report 

differentiated technology application 

using ten vehicle ‘‘classes’’ (4 cars 

classes and 6 truck classes),472 but did 

not determine how cost and 

effectiveness values differ from class to 

class. NAS’s purpose in separating 

vehicles into these classes was to create 

groups of ‘‘like’’ vehicles, i.e., vehicles 

similar in size, powertrain 

configuration, weight, and consumer 

use, and for which similar technologies 

are applicable. NHTSA similarly 

differentiates vehicles by ‘‘subclass’’ for 

the purpose of applying technologies to 

vehicles and assessing their incremental 

costs and effectiveness. NHTSA assigns 

each vehicle manufactured in the 

rulemaking period to one of 12 

subclasses: for passenger cars, 

Subcompact, Subcompact Performance, 

Compact, Compact Performance, 

Midsize, Midsize Performance, Large, 

and Large Performance; and for light 

trucks, Small SUV/Pickup/Van, Midsize 

SUV/Pickup/Van, Large SUV/Pickup/ 

Van, and Minivan. 

For this NPRM as for the MY 2011 

final rule, NHTSA divides the vehicle 

fleet into subclasses based on model 

inputs, and applies subclass-specific 

estimates, also from model inputs, of the 

applicability, cost, and effectiveness of 

each fuel-saving technology. Therefore, 

the model’s estimates of the cost to 

improve the fuel economy of each 

vehicle model depend upon the 

subclass to which the vehicle model is 

assigned. 

Each vehicle’s subclass is stored in 

the market forecast file. When 

conducting a compliance analysis, if the 

Volpe model seeks to apply technology 

to a particular vehicle, it checks the 

market forecast to see if the technology 

is available and if the refresh/redesign 

criteria are met. If these conditions are 

satisfied, the model determines the 

vehicle’s subclass from the market data 

file, which it then uses to reference 

another input called the technology 

input file. NHTSA reviewed its 

methodology for dividing vehicles into 

subclasses for purposes of technology 

application that it used in the MY 2011 

final rule, and concluded that the same 

methodology would be appropriate for 

this NPRM for MYs 2012–2016, but the 

agency invites comments on the method 

of assigning vehicles to subclasses for 

the purposes of technology application 

in the CAFE model, and on the issue of 

technology-application subclasses 

generally. The subclasses and the 

methodology for dividing vehicles 

among them are discussed in more 

detail in Section V of the PRIA and in 

Chapter 3 of the TSD. 

For the reader’s reference, the 

subclasses and example vehicles from 

the market forecast file are provided in 

the tables below. 

PASSENGER CAR SUBCLASSES EXAMPLE (MY 2008) VEHICLES 

Class 

Subcompact ..............................................................................................
 

Subcompact Performance ........................................................................
 

Compact ...................................................................................................
 

Compact Performance ..............................................................................
 

Midsize ......................................................................................................
 

Midsize Performance ................................................................................
 

Large .........................................................................................................
 

Large Performance ...................................................................................
 

Example vehicles 

Chevy Aveo, Honda Civic. 


Mazda Miata, Saturn Sky. 


Chevy Cobalt, Nissan Sentra and Altima. 


Audi S4 Quattro, Mazda RX8. 


Chevy Camaro (V6), Toyota Camry, Honda Accord, Hyundai Azera. 


Chevy Corvette, Ford Mustang (V8), Nissan G37 Coupe. 


Audi A8, Cadillac CTS and DTS. 


Bentley Arnage, Daimler CL600. 


LIGHT TRUCK SUBCLASSES EXAMPLE (MY 2008) VEHICLES 

Class Example vehicles 

Minivans ....................................................................................................
 Dodge Caravan, Toyota Sienna. 

472 The NAS classes included subcompact cars, midsize SUVs, large SUVs, small pickups, large 

compact cars, midsize cars, large cars, small SUVs, pickups, and minivans. 
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LIGHT TRUCK SUBCLASSES EXAMPLE (MY 2008) VEHICLES—Continued 

Class 

Small SUV/Pickup/Van .............................................................................
 

Midsize SUV/Pickup/Van ..........................................................................
 

Large SUV/Pickup/Van .............................................................................
 

Example vehicles 

Ford Escape & Ranger, Nissan Rogue. 


Chevy Colorado, Jeep Wrangler 4-door, Volvo XC70, Toyota Tacoma. 


Chevy Silverado, Ford Econoline, Toyota Sequoia. 


What technologies have already been 

applied to the vehicle (i.e., where in the 

‘‘decision trees’’ is it)? 

NHTSA’s methodology for technology 

application analysis developed out of 

the approach taken by NAS in the 2002 

Report, and evaluates the application of 

individual technologies and their 

incremental costs and effectiveness. 

Incremental costs and effectiveness of 

individual technologies are relative to 

the prior technology state, which means 

that it is crucial to understand what 

technologies are already present on a 

vehicle in order to determine correct 

incremental cost and effectiveness 

values. The benefit of the incremental 

approach is transparency in accounting, 

insofar as when individual technologies 

are added incrementally to individual 

vehicles, it is clear and easy to 

determine how costs and effectiveness 

adds up as technology levels increase. 

To keep track of incremental costs 

and effectiveness and to know which 

technology to apply and in which order, 

the Volpe model’s architecture uses a 

logical sequence, which NHTSA refers 

to as ‘‘decision trees,’’ for applying fuel 

economy-improving technologies to 

individual vehicles. In the MY 2011 

final rule, NHTSA worked with Ricardo 

to modify previously-employed decision 

trees in order to allow for a much more 

accurate application of technologies to 

vehicles. For purposes of the NPRM, 

NHTSA reviewed the technology 

sequencing architecture and updated, as 

appropriate, the decision trees used in 

the analysis reported in the final rule for 

MY 2011. 

In general, and as described in great 

detail in the MY 2011 final rule and in 

Section V of the current PRIA, each 

technology is assigned to one of the five 

following categories based on the 

system it affects or impacts: engine, 

transmission, electrification/accessory, 

hybrid or vehicle. Each of these 

categories has its own decision tree that 

the Volpe model uses to apply 

technologies sequentially during the 

compliance analysis. The decision trees 

were designed and configured to allow 

the Volpe model to apply technologies 

in a cost-effective, logical order that also 

considers ease of implementation. For 

example, software or control logic 

changes are implemented before 

replacing a component or system with a 

completely redesigned one, which is 

typically a much more expensive 

option. In some cases, and as 

appropriate, the model may combine the 

sequential technologies shown on a 

decision tree and apply them 

simultaneously, effectively developing 

dynamic technology packages on an asneeded basis. For example, if 

compliance demands indicate, the 

model may elect to apply LUB, EFR, and 

ICP on a dual overhead cam engine, if 

they are not already present, in one 

single step. An example simplified 

decision tree for engine technologies is 

provided below; the other simplified 

decision trees may be found in Chapter 

3 of the joint TSD and in the PRIA. 

Expanded decision trees are available in 

the docket for this NPRM. 

BILLING CODE 6560–50–C 

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BILLING CODE 6560–50–C 

Each technology within the decision 

trees has an incremental cost and an 

incremental effectiveness estimate 

associated with it, and estimates are 

specific to a particular vehicle subclass 

(see the tables in Section V of the PRIA). 

Each technology’s incremental estimate 

takes into account its position in the 

decision tree path. If a technology is 

located further down the decision tree, 

the estimates for the costs and 

effectiveness values attributed to that 

technology are influenced by the 

incremental estimates of costs and 

effectiveness values for prior technology 

applications. In essence, this approach 

accounts for ‘‘in-path’’ effectiveness 

synergies, as well as cost effects that 

occur between the technologies in the 

same path. When comparing cost and 

effectiveness estimates from various 

sources and those provided by 

commenters in the previous CAFE 
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rulemakings, it is important that the 

estimates evaluated are analyzed in the 

proper context, especially as concerns 

their likely position in the decision trees 

and other technologies that may be 

present or missing. Not all estimates 

available in the public domain or 

offered for the agencies’ consideration 

during the comment period can be 

evaluated in an ‘‘apples-to-apples’’ 

comparison with those used by the 

Volpe model, since in some cases the 

order of application, or included 

technology content, is inconsistent with 

that assumed in the decision tree. 

The MY 2011 final rule discussed in 

detail the revisions and improvements 

made to the Volpe model and decision 

trees during that rulemaking process, 

including the improved handling and 

accuracy of valve train technology 

application and the development and 

implementation of a method for 

accounting path-dependent correction 

factors in order to ensure that 

technologies are evaluated within the 

proper context. The reader should 

consult the MY 2011 final rule 

documents for further information on 

these modeling techniques, all of which 

continued to be utilized in developing 

this proposal.473 To the extent that the 

decision trees have changed for 

purposes of this NPRM, it was due not 

to revisions in the order of technology 

application, but rather to redefinitions 

of technologies or addition or 

subtraction of technologies. NHTSA 

seeks comment on the decision trees 

described here and in the PRIA. 

Is the next technology available in 

this model year? 

As discussed above, the majority of 

technologies considered are available on 

vehicles today, and thus will be 

available for application in the 

rulemaking time frame. Some 

technologies, however, will not become 

available for purposes of NHTSA’s 

analysis until later in the rulemaking 

time frame. When the model is 

considering whether to add a 

technology to a vehicle, it checks its 

year of availability—if the technology is 

available, it may be added; if it is not 

available, the model will consider 

whether to switch to a different decision 

tree to look for another technology, or 

will skip to the next vehicle in a 

manufacturer’s fleet. The year of 

availability for each technology is 

provided above in Table IV.C.2–1. 

Has the technology reached the 

phase-in cap for this model year? 

473 See, e.g., 74 FR 14238–46 (Mar. 30, 2009) for 

a full discussion of the decision trees in NHTSA’s 

MY 2011 final rule, and Docket No. NHTSA–2009– 

0062–0003.1 for an expanded decision tree used in 

that rulemaking. 

Besides the refresh/redesign cycles 

used in the Volpe model, which 

constrain the rate of technology 

application at the vehicle level so as to 

ensure a period of stability following 

any modeled technology applications, 

the other constraint on technology 

application employed in NHTSA’s 

analysis is ‘‘phase-in caps.’’ Unlike 

vehicle-level cycle settings, phase-in 

caps constrain technology application at 

the vehicle manufacturer level.474 They 

are intended to reflect a manufacturer’s 

overall resource capacity available for 

implementing new technologies (such 

as engineering and development 

personnel and financial resources), 

thereby ensuring that resource capacity 

is accounted for in the modeling 

process. At a high level, phase-in caps 

and refresh/redesign cycles work in 

conjunction with one another to avoid 

the modeling process out-pacing an 

OEM’s limited pool of available 

resources during the rulemaking time 

frame, especially in years where many 

models may be scheduled for refresh or 

redesign. This helps to ensure 

technological feasibility and economic 

practicability in determining the 

stringency of the standards. 

NHTSA has been developing the 

concept of phase-in caps over the course 

of the last several CAFE rulemakings, as 

discussed in greater detail in the MY 

2011 final rule,475 and in Section V of 

the PRIA and Chapter 3 of the joint TSD. 

The MY 2011 final rule employed nonlinear phase-in caps (that is, caps that 

varied from year to year) that were 

designed to respond to comments 

raising lead-time concerns in reference 

to the agency’s proposed MY 2011–2015 

standards, but because the final rule 

covered only one model year, many 

phase-in caps for that model year were 

lower than had originally been 

proposed. NHTSA emphasized that the 

MY 2011 phase-in caps were based on 

assumptions for the full five year period 

of the proposal (2011–2015), and stated 

that it would reconsider the phase-in 

474 While phase-in caps are expressed as specific 

percentages of a manufacturer’s fleet to which a 

technology may be applied in a given model year, 

phase-in caps cannot always be applied as precise 

limits, and the Volpe model in fact allows 

‘‘override’’ of a cap in certain circumstances. When 

only a small portion of a phase-in cap limit 

remains, or when the cap is set to a very low value, 

or when a manufacturer has a very limited product 

line, the cap might prevent the technology from 

being applied at all since any application would 

cause the cap to be exceeded. Therefore, the Volpe 

model evaluates and enforces each phase-in cap 

constraint after it has been exceeded by the 

application of the technology (as opposed to 

evaluating it before application), which can result 

in the described overriding of the cap. 

475 74 FR 14268–14271 (Mar. 30, 2009). 

settings for all years beyond 2011 in a 

future rulemaking analysis. 

For purposes of the current proposal 

for MYs 2012–2016, as in the MY 2011 

final rule, NHTSA combines phase-in 

caps for some groups of similar 

technologies, such as valve phasing 

technologies that are applicable to 

different forms of engine design (SOHC, 

DOHC, OHV), since they are very 

similar from an engineering and 

implementation standpoint. When the 

phase-in caps for two technologies are 

combined, the maximum total 

application of either or both to any 

manufacturer’s fleet is limited to the 

value of the cap.476 In contrast to the 

phase-in caps used in the MY 2011 final 

rule, NHTSA has increased the phase-in 

caps for most of the technologies, as 

discussed below. 

In developing phase-in cap values for 

purposes of the current proposal, 

NHTSA initially considered the fact that 

many of the technologies commonly 

applied by the model, those placed near 

the top of the decision trees, such as low 

friction lubes, valve phasing, electric 

power steering, improved automatic 

transmission controls, and others, have 

been commonly available to 

manufacturers for several years now. 

Many technologies, in fact, precede the 

2002 NAS Report, which estimated that 

such technologies would take 4 to 8 

years to penetrate the fleet. Since the 

current proposal would take effect in 

MY 2012, nearly 10 years beyond the 

NAS report, and extends to MY 2016, 

and in the interest of harmonization 

with EPA’s proposal, NHTSA 

tentatively determined that higher 

phase-in caps were likely justified. 

Additionally, NHTSA considered the 

fact that manufacturers, as part of the 

agreements supporting the National 

Program, appear to be anticipating 

higher technology application rates than 

those used in the MY 2011 final rule. 

This also supported higher phase-in 

caps for purposes of the proposal. 

Thus, while phase-in caps for the MY 

2011 final rule reached a maximum of 

50 percent for a couple of technologies 

and generally fell in the range between 

0 and 20 percent, phase-in caps for this 

NPRM for the majority of technologies 

are set to reach 85 or 100 percent by MY 

2016, although more advanced 

technologies like diesels and strong 

hybrids reach only 15 percent by MY 

2016. 

Theoretically, significantly higher 

phase-in caps, such as those used in the 

current proposal as compared to those 

used in the MY 2011 final rule, should 

476 See 74 FR 14270 (Mar 30, 2009) for further 

discussion and examples. 
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result in higher levels of technology 

penetration in the modeling results. 

Reviewing the modeling output does 

not, however, indicate unreasonable 

levels of technology penetration for the 

proposed standards.477 NHTSA believes 

that this is due to the interaction of the 

various changes in methodology for the 

current proposal—changes to phase-in 

caps are but one of a number of 

revisions to the Volpe model and its 

inputs that could potentially impact the 

rate at which technologies are applied 

in this proposal as compared to prior 

rulemakings. Other revisions that could 

impact application rates include the use 

of transparent CAFE certification data in 

baseline fleet formulation and the use of 

other data for projecting it forward,478 or 

the use of a multi-year planning 

programming technique to apply 

technology retroactively to earlier-MY 

vehicles, both of which may have a 

direct impact on the modeling process. 

Conversely the model and inputs 

remain unchanged in other areas that 

also could impact technology 

application, such as in the refresh/ 

redesign cycle settings, estimates used 

for the technologies, both of which 

remain largely unchanged from the MY 

2011 final rule. These changes together 

make it difficult to predict how phasein caps should be expected to function 

in the new modeling process. 

Thus, after reviewing the output files, 

NHTSA tentatively concludes that the 

higher phase-in caps, and the resulting 

technology application rates produced 

by the Volpe model, at both the industry 

and manufacturer level, are appropriate 

for this proposal, achieving a suitable 

level of stringency without requiring 

unrealistic or unachievable penetration 

rates. However, the agency will consider 

comments received on this approach in 

determining what phase-in caps to 

employ in the analysis for the final rule, 

and may change the caps in response to 

comments and/or further analysis. One 

additional question the agency has, 

which may be primarily academic at 

this point, is what impact lower phasein caps, such as those used in earlier 

rulemakings, would have on compliance 

costs (and whether they might counterintuitively increase costs by forcing 

more expensive technologies). NHTSA 

seeks comment on the revised phase-in 

caps as compared to the MY 2011 final 

rule, and particularly on whether, 

477 The modeling output for the analysis 

underlying these proposed standards is available on 

NHTSA’s Web site. 

478 The baseline fleet sets the starting point, from 

a technology point of view, for where the model 

begins the technology application process, so 

changes have a direct impact on the net application 

of technology. 

combined with the refresh and redesign 

assumptions, they help to ensure 

sufficient lead time for manufacturers to 

make the technology changes required 

by the proposed standards. Readers are 

invited to review and assess the phasein caps listed and described more fully 

in Section V of the PRIA, along with the 

application and penetration rates found 

in the Volpe model’s output files, and 

after making their own assessment, 

provide comment and recommendations 

to the agency as appropriate. 

Is the technology less expensive due 

to learning effects? 

Historically, NHTSA did not 

explicitly account for the cost 

reductions a manufacturer might realize 

through learning achieved from 

experience in actually applying a 

technology. Since working with EPA to 

develop the 2008 NPRM for MYs 2011– 

2015, and with Ricardo to refine the 

concept for the March 2009 MY 2011 

final rule, NHTSA has accounted for 

these cost reductions through two kinds 

of mutually exclusive learning, 

‘‘volume-based’’ and ‘‘time-based’’ 

which it continues to use in this 

proposal, as discussed below. 

In the 2008 NPRM, NHTSA applied 

learning factors to technology costs for 

the first time. These learning factors 

were developed using the parameters of 

learning threshold, learning rate, and 

the initial cost, and were based on the 

‘‘experience curve’’ concept which 

describes reductions in production costs 

as a function of accumulated production 

volume. The typical curve shows a 

relatively steep initial decline in cost 

which flattens out to a gentle 

downwardly sloping line as the volume 

increase to large values. In the NPRM, 

NHTSA applied a learning rate discount 

of 20 percent for each successive 

doubling of production volume (on a 

per manufacturer basis), and a learning 

threshold of 25,000 units was assumed 

(thus a technology was viewed as being 

fully learned out at 100,000 units). The 

factor was only applied to certain 

technologies that were considered 

emerging or newly implemented on the 

basis that significant cost improvements 

would be achieved as economies of 

scale were realized (i.e., the 

technologies were on the steep part of 

the curve). 

In the MY 2011 final rule, NHTSA 

continued to use this learning factor, 

referring to it as volume-based learning 

since the cost reductions were 

determined by production volume 

increases, and again only applied it to 

emerging technologies. However, and in 

response to comments, NHTSA revised 

its assumptions on learning threshold, 

basing them instead on an industrywide production basis, and increasing 

the threshold to 300,000 units annually. 

Commenters to the 2008 NPRM also 

described another type of learning factor 

which NHTSA decided to adopt and 

implement in the MY 2011 final rule. 

Commenters described a relatively small 

negotiated cost decrease that occurred 

on an annual basis through contractual 

agreements with first tier component 

and systems suppliers for readily 

available, high volume technologies 

commonly in use by multiple OEMs. 

Based on the same experience curve 

principal, however at production 

volumes that were on the flatter part of 

the curve (and thus the types of volumes 

that represent annual industry 

volumes), NHTSA adopted this type 

learning and referred to it as time-based 

learning. An annual cost reduction of 3 

percent in the second and each 

subsequent year, which was consistent 

with estimates from commenters and 

supported by work Ricardo conducted 

for NHTSA, was used in the final rule. 

In developing this proposal, NHTSA 

and EPA have reviewed both types of 

learning factors, and the thresholds 

(300,000) and reduction rates (20 

percent for volume,479 3 percent for 

time-based) they rely on, and as 

implemented in the MY 2011 final rule, 

and agreed that both factors continue to 

be accurate and appropriate; each 

agency has thus implemented time- and 

volume-based learning in their analyses. 

Noting that only one type of learning 

can be applied to any single technology, 

if any learning is applied at all, the 

agencies reviewed each to determine 

which learning factor was appropriate. 

Volume-based learning is applied to the 

higher complexity hybrid technologies, 

while no learning is applied to 

technologies likely to be affected by 

commodity costs (LUB, ROLL) or that 

have loosely-defined BOMs (EFR, LDB), 

as was the case in the MY 2011 final 

rule. Chapter 3 of the joint TSD shows 

the specific learning factors that NHTSA 

has applied in this analysis for each 

technology, and discusses learning 

factors and each agencies’ use of them 

further. NHTSA seeks comment on its 

use of learning factors, including the 

types, the thresholds, and the reduction 

rates proposed, and particularly on the 

revisions to the learning (time- and 

volume-based) logic as compared to the 

MY 2011 final rule. 

Is the technology more or less 

effective due to synergistic effects? 

When two or more technologies are 

added to a particular vehicle model to 

479 NHTSA will conduct a sensitivity analysis on 

the volume-based learning value of 20 percent for 

the final rule. 
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49666 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

improve its fuel efficiency and reduce 

CO2 emissions, the resultant fuel 

consumption reduction may sometimes 

be higher or lower than the product of 

the individual effectiveness values for 

those items.480 This may occur because 

one or more technologies applied to the 

same vehicle partially address the same 

source (or sources) of engine, drivetrain 

or vehicle losses. Alternately, this effect 

may be seen when one technology shifts 

the engine operating points, and 

therefore increases or reduces the fuel 

consumption reduction achieved by 

another technology or set of 

technologies. The difference between 

the observed fuel consumption 

reduction associated with a set of 

technologies and the product of the 

individual effectiveness values in that 

set is referred to for purposes of this 

rulemaking as a ‘‘synergy.’’ Synergies 

may be positive (increased fuel 

consumption reduction compared to the 

product of the individual effects) or 

negative (decreased fuel consumption 

reduction). An example of a positive 

synergy might be a vehicle technology 

that reduces road loads at highway 

speeds (e.g., lower aerodynamic drag or 

low rolling resistance tires), that could 

extend the vehicle operating range over 

which cylinder deactivation may be 

employed. An example of a negative 

synergy might be a variable valvetrain 

system technology, which reduces 

pumping losses by altering the profile of 

the engine speed/load map, and a sixspeed automatic transmission, which 

shifts the engine operating points to a 

portion of the engine speed/load map 

where pumping losses are less 

significant. As the complexity of the 

technology combinations is increased, 

and the number of interacting 

technologies grows accordingly, it 

becomes increasingly important to 

account for these synergies. 

NHTSA and EPA determined 

synergistic impacts for this rulemaking 

using EPA’s ‘‘lumped parameter’’ 

analysis tool, which EPA described at 

length in its March 2008 Staff Technical 

Report.481 The lumped parameter tool is 

480 More specifically, the products of the 

differences between one and the technologyspecific levels of effectiveness in reducing fuel 

consumption. For example, not accounting for 

interactions, if technologies A and B are estimated 

to reduce fuel consumption by 10% (i.e., 0.1) and 

20% (i.e., 0.2) respectively, the ‘‘product of the 

individual effectiveness values’’ would be 1–0.1 

times 1–0.2, or 0.9 times 0.8, which equals 0.72, 

corresponding to a combined effectiveness of 28% 

rather than the 30% obtained by adding 10% to 

20%. The ‘‘synergy factors’’ discussed in this 

section further adjust these multiplicatively 

combined effectiveness values. 

481 EPA Staff Technical Report: Cost and 

Effectiveness Estimates of Technologies Used to 

a spreadsheet model that represents 

energy consumption in terms of average 

performance over the fuel economy test 

procedure, rather than explicitly 

analyzing specific drive cycles. The tool 

begins with an apportionment of fuel 

consumption across several loss 

mechanisms and accounts for the 

average extent to which different 

technologies affect these loss 

mechanisms using estimates of engine, 

drivetrain and vehicle characteristics 

that are averaged over the EPA fuel 

economy drive cycle. Results of this 

analysis were generally consistent with 

those of full-scale vehicle simulation 

modeling performed in 2007 by Ricardo, 

Inc. 

For the current rulemaking, NHTSA 

used the lumped parameter tool as 

modified in the MY 2011 CAFE final 

rule. NHTSA modified the lumped 

parameter tool from the version 

described in the EPA Staff Technical 

Report in response to public comments 

received in its rulemaking. The 

modifications included updating the list 

of technologies and their associated 

effectiveness values to match the 

updated list of technologies used in the 

final rule. NHTSA also expanded the 

list of synergy pairings based on further 

consideration of the technologies for 

which a competition for losses would be 

expected. These losses are described in 

more detail in Section V of the PRIA. 

NHTSA and EPA incorporate 

synergistic impacts in their analyses in 

slightly different manners. Because 

NHTSA applies technologies 

individually in its modeling analysis, 

NHTSA incorporates synergistic effects 

between pairings of individual 

technologies. The use of discrete 

technology pair incremental synergies is 

similar to that in DOE’s National Energy 

Modeling System (NEMS).482 Inputs to 

the Volpe model incorporate NEMSidentified pairs, as well as additional 

pairs from the set of technologies 

considered in the Volpe model. 

NHTSA notes that synergies that 

occur within a decision tree are already 

addressed within the incremental values 

assigned and therefore do not require a 

synergy pair to address. For example, all 

engine technologies take into account 

incremental synergy factors of preceding 

engine technologies, and all 

Reduce Light-duty Vehicle Carbon Dioxide 

Emissions; EPA420–R–08–008, March 2008. 

482 U.S. Department of Energy, Energy 

Information Administration, Transportation Sector 

Module of the National Energy Modeling System: 

Model Documentation 2007, May 2007, 

Washington, DC, DOE/EIAM070(2007), at 29–30. 

Available at http://tonto.eia.doe.gov/ftproot/ 

modeldoc/m070(2007).pdf (last accessed Jul. 6, 

2009). 

transmission technologies take into 

account incremental synergy factors of 

preceding transmission technologies. 

These factors are expressed in the fuel 

consumption improvement factors in 

the input files used by the Volpe model. 

For applying incremental synergy 

factors in separate path technologies, 

the Volpe model uses an input table (see 

the tables in Chapter 3 of the TSD and 

in the PRIA) which lists technology 

pairings and incremental synergy factors 

associated with those pairings, most of 

which are between engine technologies 

and transmission/electrification/hybrid 

technologies. When a technology is 

applied to a vehicle by the Volpe model, 

all instances of that technology in the 

incremental synergy table which match 

technologies already applied to the 

vehicle (either pre-existing or 

previously applied by the Volpe model) 

are summed and applied to the fuel 

consumption improvement factor of the 

technology being applied. Synergies for 

the strong hybrid technology fuel 

consumption reductions are included in 

the incremental value for the specific 

hybrid technology block since the 

model applies technologies in the order 

of the most effectiveness for least cost 

and also applies all available 

electrification and transmission 

technologies before applying strong 

hybrid technologies. NHTSA seeks 

comment on whether the synergistic 

effects presented are accurate, and 

whether there are other synergies that 

the agency may have overlooked. 

d. Where Can Readers Find More 

Detailed Information About NHTSA’s 

Technology Analysis? 

Much more detailed information is 

provided in Section V of the PRIA, and 

a discussion of how NHTSA and EPA 

jointly reviewed and updated 

technology assumptions for purposes of 

this NPRM is available in Chapter 3 of 

the TSD. Additionally, all of NHTSA’s 

model input and output files are now 

public and available for the reader’s 

review and consideration. The 

technology input files can be found in 

the docket for this NPRM, Docket No. 

NHTSA–2009–0059, and on NHTSA’s 

Web site. And finally, because much of 

NHTSA’s technology analysis for 

purposes of this NPRM builds on the 

work that was done for the MY 2011 

final rule, we refer readers to that 

document as well for background 

information concerning how NHTSA’s 

methodology for technology application 

analysis has evolved over the past 

several rulemakings, both in response to 

comments and as a result of the agency’s 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49667 

growing experience with this type of 

analysis.483 

3. How Did NHTSA Develop the 

Economic Assumption Inputs? 

NHTSA’s preliminary analysis of 

alternative CAFE standards for the 

model years covered by this proposed 

rulemaking relies on a range of forecast 

variables, economic assumptions, and 

parameter values. This section describes 

the proposed sources of these forecasts, 

the rationale underlying each 

assumption, and the agency’s 

preliminary choices of specific 

parameter values. These proposed 

economic values play a significant role 

in determining the benefits of 

alternative CAFE standards, as they 

have for the last several CAFE 

rulemakings. Under those alternatives 

where standards would be established 

by reference to their costs and benefits, 

these economic values also affect the 

levels of the CAFE standards 

themselves. Some of these variables 

have more important effects on the level 

of CAFE standards and the benefits from 

requiring alternative increases in fuel 

economy than do others. 

In reviewing these variables and the 

agency’s estimates of their values for 

purposes of this NPRM, NHTSA 

reconsidered previous comments it had 

received and reviewed newly available 

literature. As a consequence, the agency 

elected to revise some of its economic 

assumptions and parameter estimates, 

while retaining others. Some of the most 

important changes, which are discussed 

in greater detail below, as well as in 

Chapter 4 of the joint TSD and in 

Chapter VIII of the PRIA, include 

significant revisions to the markup 

factors for technology costs; reducing 

the rebound effect from 15 to 10 

percent; and revising the value of 

reducing CO2 emissions based on recent 

interagency efforts to develop estimates 

of this value for government-wide use. 

For the reader’s reference, Table IV.C.3– 

1 below summarizes the values used to 

calculate the economic benefits from 

each alternative. The agency seeks 

comment on the economic assumptions 

presented in the table and discussed 

below. 

TABLE IV.C.3–1—ECONOMIC VALUES FOR BENEFITS COMPUTATIONS 

(2007$) 

Fuel Economy Rebound Effect ............................................................................................................................................................ 

‘‘Gap’’ between test and on-road MPG ............................................................................................................................................... 

Value of refueling time per ($ per vehicle-hour) ................................................................................................................................. 

Annual growth in average vehicle use ................................................................................................................................................ 

Fuel Prices (2012–50 average, $/gallon) 

Retail gasoline price ..................................................................................................................................................................... 

Pre-tax gasoline price ................................................................................................................................................................... 

Economic Benefits from Reducing Oil Imports ($/gallon) 

‘‘Monopsony’’ Component ............................................................................................................................................................ 

Price Shock Component ............................................................................................................................................................... 

Military Security Component ........................................................................................................................................................ 

10% 

20% 

$ 24.64 

1.1% 

$3.77 

$3.40 

$ 0.00 

$ 0.17 

$ 0.00 

Total Economic Costs ($/gallon) ........................................................................................................................................... 

Emission Damage Costs (2020, $/ton or $/metric ton) 

$ 0.17 

Carbon monoxide ......................................................................................................................................................................... $ 0 

Volatile organic compounds (VOC) .............................................................................................................................................. $ 1,283 

Nitrogen oxides (NOx)—vehicle use ............................................................................................................................................ $ 5,116 

Nitrogen oxides (NOx)—fuel production and distribution ............................................................................................................. $ 5,339 

Particulate matter (PM2.5)—vehicle use ....................................................................................................................................... $ 238,432 

Particulate matter (PM2.5)—fuel production and distribution ........................................................................................................ $ 292,180 

Sulfur dioxide (SO2) ...................................................................................................................................................................... $ 30,896 

Carbon dioxide (CO2) ................................................................................................................................................................... $ 20 

Annual Increase in CO2 Damage Cost ........................................................................................................................................ 

External Costs from Additional Automobile Use ($/vehicle-mile) 

3% 

Congestion .................................................................................................................................................................................... $ 0.054 

Accidents ...................................................................................................................................................................................... $ 0.023 

Noise ............................................................................................................................................................................................. $ 0.001 

Total External Costs .............................................................................................................................................................. 

External Costs from Additional Light Truck Use ($/vehicle-mile) 

$ 0.078 

Congestion .................................................................................................................................................................................... $0.048 

Accidents ...................................................................................................................................................................................... $0.026 

Noise ............................................................................................................................................................................................. $0.001 

Total External Costs .............................................................................................................................................................. 

Discount Rate Applied to Future Benefits ........................................................................................................................................... 

$0.075 

3% 

a. Costs of Fuel Economy-Improving 

Technologies 

We developed detailed estimates of 

the costs of applying fuel economyimproving technologies to vehicle 

models jointly with EPA for use in 

analyzing the impacts of alternative 

standards considered in this 

483 74 FR 14233–308 (Mar. 30, 2009). 

rulemaking. The estimates were based 

on those reported by the 2002 NAS 

Report analyzing costs for increasing 

fuel economy, but were modified for 

purposes of this analysis as a result of 

extensive consultations among 

engineers from NHTSA, EPA, and the 

Volpe Center. As part of this process, 

the agency also developed varying cost 

estimates for applying certain fuel 

economy technologies to vehicles of 

different sizes and body styles. We may 

adjust these cost estimates based on 

comments received to this NPRM. 

The technology cost estimates used in 

this analysis are intended to represent 
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49668 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

manufacturers’ direct costs for highvolume production of vehicles with 

these technologies and sufficient 

experience with their application so that 

all remaining cost reductions due to 

‘‘learning curve’’ effects have been fully 

realized. However, NHTSA recognizes 

that manufacturers’ actual costs for 

employing these technologies include 

additional outlays for accompanying 

design or engineering changes to models 

that use them, development and testing 

of prototype versions, recalibrating 

engine operating parameters, and 

integrating the technology with other 

attributes of the vehicle. Manufacturers’ 

indirect costs for employing these 

technologies also include expenses for 

product development and integration, 

modifying assembly processes and 

training assembly workers to install 

them, increased expenses for operation 

and maintaining assembly lines, higher 

initial warranty costs for new 

technologies, any added expenses for 

selling and distributing vehicles that use 

these technologies, and manufacturer 

and dealer profit. In previous CAFE 

rulemakings and in NHTSA’s safety 

rulemakings, the agency has accounted 

for these additional costs by using a 

Retail Price Equivalent (RPE) multiplier 

of 1.5. For purposes of this rulemaking, 

based on recent work by EPA, NHTSA 

has applied indirect cost multipliers 

ranging from 1.11 to 1.64 to the 

estimates of vehicle manufacturers’ 

direct costs for producing or acquiring 

each technology to improve fuel 

economy.484 These multipliers vary 

with the complexity of each technology 

and the time frame over which costs are 

estimated. More complex technologies 

are associated with higher multipliers 

because of the larger increases in 

manufacturers’ indirect costs for 

developing, producing (or procuring), 

and deploying these more complex 

technologies. The appropriate 

multipliers decline over time for 

technologies of all complexity levels, 

since increased familiarity and 

experience with their application is 

assumed to reduce manufacturers’ 

indirect costs for employing them. 

NHTSA seeks comment regarding the 

new indirect cost multiplier approach to 

technology costs estimates. We note 

additionally that this issue will be 

addressed in the upcoming revised NAS 

report. 

484 NHTSA notes that in addition to the 

technology cost analysis employing this ‘‘ICM’’ 

approach, the PRIA contains a sensitivity analysis 

using a technology cost multiplier of 1.5. 

b. Potential Opportunity Costs of 

Improved Fuel Economy 

An important concern is whether 

achieving the fuel economy 

improvements required by alternative 

CAFE standards would require 

manufacturers to compromise the 

performance, carrying capacity, safety, 

or comfort of their vehicle models. To 

the extent that it does so, the resulting 

sacrifice in the value of these attributes 

to consumers represents an additional 

cost of achieving the required 

improvements in fuel economy. While 

exact dollar values of these attributes to 

consumers are difficult to infer, 

differences in vehicle purchase prices 

and buyers’ choices among competing 

models that feature different 

combinations of these characteristics 

clearly demonstrate that changing 

vehicle attributes clearly affect the 

utility and economic value that vehicles 

provide to potential buyers.485 

NHTSA and EPA have approached 

this potential problem by developing 

cost estimates for fuel economyimproving technologies that include any 

additional manufacturing costs that 

would be necessary to maintain the 

originally planned levels of 

performance, comfort, carrying capacity, 

and safety of any light-duty vehicle 

model to which those technologies are 

applied. In doing so, the agencies 

followed the precedent established by 

the 2002 NAS Report, which estimated 

‘‘constant performance and utility’’ 

costs for fuel economy technologies. 

NHTSA has used these as the basis for 

its continuing efforts to refine the 

technology costs it uses to analyze 

manufacturer’s costs for complying with 

alternative passenger car and light truck 

CAFE standards for MYs 2012–2016. 

Although the agency has revised its 

estimates of manufacturers’ costs for 

some technologies significantly for use 

in this rulemaking, these revised 

estimates are still intended to represent 

costs that would allow manufacturers to 

maintain the performance, carrying 

capacity, and utility of vehicle models 

while improving their fuel economy. 

Although we believe that our tentative 

cost estimates for fuel economyimproving technologies should be 

generally sufficient to prevent 

485 See, e.g., Kleit A.N., 1990. ‘‘The Effect of 

Annual Changes in Automobile Fuel Economy 

Standards.’’ Journal of Regulatory Economics 2: 

151–172; Berry, Steven, James Levinsohn, and Ariel 

Pakes, 1995. ‘‘Automobile Prices in Market 

Equilibrium,’’ Econometrica 63(4): 841–940; 

McCarthy, Patrick S., 1996. ‘‘Market Price and 

Income Elasticities of New Vehicle Demands.’’ 

Review of Economics and Statistics 78: 543–547; 

and Goldberg, Pinelopi K., 1998. ‘‘The Effects of the 

Corporate Average Fuel Efficiency Standards in the 

US,’’ Journal of Industrial Economics 46(1): 1–33. 

significant reductions in consumer 

welfare provided by vehicle models to 

which manufacturers apply those 

technologies, it is possible that they do 

not include adequate allowance for the 

necessary efforts by manufacturers to 

prevent sacrifices in these attributes on 

all vehicle models. If this is the case, the 

true economic costs of achieving higher 

fuel economy should include the 

opportunity costs to vehicle owners of 

any sacrifices in vehicles’ performance, 

carrying capacity, and utility and the 

agency’s estimated technology costs 

would underestimate the true economic 

costs of improving fuel economy. 

Recognizing this possibility, it may be 

preferable for NHTSA to estimate 

explicitly the changes in vehicle buyers’ 

welfare from the combination of higher 

prices for new vehicle models, increases 

in their fuel economy, and any 

accompanying changes in vehicle 

attributes such as performance, 

passenger- and cargo-carrying capacity, 

or other dimensions of utility. The net 

change in buyer’s welfare that results 

from the combination of these changes 

would provide a more accurate estimate 

of the true economic costs for improving 

fuel economy. The agency seeks 

comment on this or other possible ways 

to deal with this extremely important 

issue. 

c. The On-Road Fuel Economy ‘‘Gap’’ 

Actual fuel economy levels achieved 

by light-duty vehicles in on-road driving 

fall somewhat short of their levels 

measured under the laboratory-like test 

conditions used by EPA to establish its 

published fuel economy ratings for 

different models. In analyzing the fuel 

savings from alternative CAFE 

standards, NHTSA has previously 

adjusted the actual fuel economy 

performance of each light truck model 

downward from its rated value to reflect 

the expected size of this on-road fuel 

economy ‘‘gap.’’ On December 27, 2006, 

EPA adopted changes to its regulations 

on fuel economy labeling, which were 

intended to bring vehicles’ rated fuel 

economy levels closer to their actual onroad fuel economy levels.486 

In its Final Rule, EPA estimated that 

actual on-road fuel economy for lightduty vehicles averages 20 percent lower 

than published fuel economy levels. For 

example, if the overall EPA fuel 

economy rating of a light truck is 20 

mpg, the on-road fuel economy actually 

achieved by a typical driver of that 

vehicle is expected to be 16 mpg 

(20*.80). NHTSA employed EPA’s 

revised estimate of this on-road fuel 

economy gap in its analysis of the fuel 

486 71 FR 77871 (Dec. 27, 2006). 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49669 

savings resulting from alternative CAFE 

standards evaluated in the MY 2011 

final rule. 

For purposes of this NPRM, NHTSA 

conducted additional analysis of this 

issue. The agency used data on the 

number of passenger cars and light 

trucks of each model year that were 

registered for use during calendar years 

2000 through 2006, average fuel 

economy for passenger cars and light 

trucks produced during each model 

year, and estimates of average miles 

driven per year by cars and light trucks 

of different ages. These data were 

combined to develop estimates of the 

average fuel economy that the U.S. 

passenger car and light truck fleets 

would have achieved from 2000 through 

2006 under test conditions. 

NHTSA compared these estimates to 

the Federal Highway Administration’s 

(FHWA) published values of actual onroad fuel economy for passenger cars 

and light trucks during each of those 

years.487 FHWA’s estimates of actual 

fuel economy for passenger cars 

averaged 22 percent lower than 

NHTSA’s estimates of its fleet-wide 

average value under test conditions over 

this period, while FHWA’s estimates for 

light trucks averaged 17 lower than 

NHTSA’s estimates of average light 

truck fuel economy under test 

conditions. These results appear to 

confirm that the 20 percent on-road fuel 

economy discount or gap represents a 

reasonable estimate for use in evaluating 

the fuel savings likely to result from 

alternative CAFE standards for MY 

2012–2016 vehicles. 

d. Fuel Prices and the Value of Saving 

Fuel 

Projected future fuel prices are a 

critical input into the preliminary 

economic analysis of alternative CAFE 

standards, because they determine the 

value of fuel savings both to new 

vehicle buyers and to society. NHTSA 

relied on the most recent fuel price 

projections from the U.S. Energy 

Information Administration’s (EIA) 

Annual Energy Outlook (AEO) for this 

analysis. Specifically, we used the AEO 

2009 (April 2009 release) Reference 

Case forecasts of inflation-adjusted 

(constant-dollar) retail gasoline and 

diesel fuel prices, which represent the 

EIA’s most up-to-date estimate of the 

most likely course of future prices for 

petroleum products.488 

487 Federal Highway Administration, Highway 

Statistics, 2000 through 2006 editions, Table VM– 

1; see http://www.fhwa.dot.gov/policy/ohpi/hss/ 

hsspubs.cfm (last accessed July 27, 2009). 

488 Energy Information Administration, Annual 

Energy Outlook 2009, Revised Updated Reference 

Case (April 2009), Table 12. Available at http:// 

While NHTSA relied on the forecasts 

of fuel prices presented in AEO 2008 

High Price Case in the MY 2011 final 

rule, we noted at the time that we were 

relying on that estimate primarily 

because volatility in the oil market 

appeared to have overtaken the 

Reference Case, and that we anticipated 

that the Reference Case forecast would 

be significantly higher in the next AEO. 

In fact, EIA’s AEO 2009 Reference Case 

forecast projects higher retail fuel prices 

in most future years than those forecast 

in the High Price Case from AEO 2008. 

NHTSA is thus confident that the AEO 

2009 Reference Case is an appropriate 

forecast for projected future fuel prices. 

Measured in constant 2007 dollars, 

the Reference Case forecast of retail 

gasoline prices during calendar year 

2020 is $3.62 per gallon, rising 

gradually to $3.82 by the year 2030 

(these values include Federal, State and 

local taxes). To obtain fuel price 

forecasts for the years 2031 through 

2050, the agency assumes that retail fuel 

prices will continue to increase after 

2030 at the average annual rates 

projected for 2020–2030 in the AEO 

2009 Revised Reference Case.489 This 

assumption results in a projected retail 

price of gasoline that reaches $4.25 in 

2007 dollars by the year 2050. 

The value of fuel savings resulting 

from improved fuel economy to buyers 

of light-duty vehicles is determined by 

the retail price of fuel, which includes 

Federal, State, and any local taxes 

imposed on fuel sales. Total taxes on 

gasoline, including Federal, State, and 

local levies averaged $0.42 per gallon 

during 2006, while those levied on 

diesel averaged $0.50. Because fuel 

taxes represent transfers of resources 

from fuel buyers to government 

agencies, however, rather than real 

resources that are consumed in the 

process of supplying or using fuel, their 

value must be deducted from retail fuel 

prices to determine the value of fuel 

savings resulting from more stringent 

CAFE standards to the U.S. economy as 

a whole. 

NHTSA follows the assumptions used 

by EIA in AEO 2009 that State and local 

gasoline taxes will keep pace with 

www.eia.doe.gov/oiaf/servicerpt/stimulus/excel/ 

aeostimtab_12.xls(last accessed July 26, 2009). 

EIA’s Updated Reference Case reflects the effects of 

the American Reinvestment and Recovery Act of 

2009, as well as the most recent revisions to the 

U.S. and global economic outlook. 

489 This projection uses the rate of increase in fuel 

prices for 2020–2030 rather than that over the 

complete forecast period (2009–2030) because there 

is extreme volatility in the forecasts for the years 

2009 through approximately 2020. Using the 

average rate of change over the complete 2009–2030 

forecast period would result in projections of 

declining fuel prices after 2030. 

inflation in nominal terms, and thus 

remain constant when expressed in 

constant 2007 dollars. In contrast, EIA 

assumes that Federal gasoline taxes will 

remain unchanged in nominal terms, 

and thus decline throughout the forecast 

period when expressed in constant 2007 

dollars. These differing assumptions 

about the likely future behavior of 

Federal and State/local fuel taxes are 

consistent with recent historical 

experience, which reflects the fact that 

Federal as well as most State motor fuel 

taxes are specified on a cents-per-gallon 

basis, and typically require legislation to 

change. 

The projected value of total taxes is 

deducted from each future year’s 

forecast of retail gasoline and diesel 

prices reported in AEO 2009 to 

determine the economic value of each 

gallon of fuel saved during that year as 

a result of improved fuel economy. 

Subtracting fuel taxes results in a 

projected value for saving gasoline of 

$3.22 per gallon during 2020, rising to 

$3.45 per gallon by the year 2030. 

EIA includes ‘‘High Price Case’’ and 

‘‘Low Price Case’’ forecasts in each 

AEO, which reflect uncertainties 

regarding future levels of oil production 

and demand. These alternative 

scenarios project retail gasoline prices 

that range from a low of $2.02 to a high 

of $5.04 per gallon during 2020, and 

from $2.04 to $5.47 per gallon during 

2030. In conjunction with our 

assumption that fuel taxes will remain 

constant in real or inflation-adjusted 

terms over this period, these forecasts 

imply pre-tax values of saving fuel 

ranging from $1.63 to $4.65 per gallon 

during 2020, and from $1.67 to $5.10 

per gallon in 2030. In conducting the 

preliminary analysis of uncertainty in 

benefits and costs from alternative 

CAFE standards required by OMB, 

NHTSA evaluated the sensitivity of its 

benefits estimates to these alternative 

forecasts of future fuel prices. The 

results of this sensitivity analysis can be 

found in the PRIA. 

e. Consumer Valuation of Fuel Economy 

and Payback Period 

In estimating the value of fuel 

economy improvements that would 

result from alternative CAFE standards 

to potential vehicle buyers, NHTSA 

assumes, as in the MY 2011 final rule, 

that buyers value the resulting fuel 

savings over only part of the expected 

lifetime of the vehicles they purchase. 

Specifically, we assume that buyers 

value fuel savings over the first five 

years of a new vehicle’s lifetime, and 

discount the value of these future fuel 

savings at a 3 percent annual rate. The 

five-year figure represents 
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49670 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

approximately the current average term 

of consumer loans to finance the 

purchase of new vehicles. We recognize 

that the period over which individual 

buyers finance new vehicle purchases 

may not correspond exactly to the time 

horizons they apply in valuing fuel 

savings from higher fuel economy. 

The agency deducts the discounted 

present value of fuel savings over the 

first five years of a vehicle model’s 

lifetime from the technology costs 

incurred by its manufacturer to improve 

that model’s fuel economy to determine 

the increase in its ‘‘effective price’’ to 

buyers. The Volpe model uses these 

estimates of effective costs for 

increasing the fuel economy of each 

vehicle model to identify the order in 

which manufacturers would be likely to 

select models for the application of fuel 

economy-improving technologies in 

order to comply with stricter standards. 

The average value of the resulting 

increase in effective cost from each 

manufacturer’s simulated compliance 

strategy is also used to estimate the 

impact of alternative standards on its 

total sales for future model years. 

However, it is important to recognize 

that NHTSA estimates the aggregate 

value to the U.S. economy of fuel 

savings resulting from alternative 

standards—or their ‘‘social’’ value—over 

the entire expected lifetimes of vehicles 

manufactured under those standards, 

rather than over this shorter ‘‘payback 

period’’ we assume for their buyers. The 

procedure the agency uses for doing so 

is discussed in detail in the following 

section. 

f. Vehicle Survival and Use 

Assumptions 

NHTSA’s first step in estimating 

lifetime fuel consumption by vehicles 

produced during a model year is to 

calculate the number expected to 

remain in service during each year 

following their production and sale.490 

This is calculated by multiplying the 

number of vehicles originally produced 

490 Vehicles are defined to be of age 1 during the 

calendar year corresponding to the model year in 

which they are produced; thus for example, model 

year 2000 vehicles are considered to be of age 1 

during calendar year 2000, age 1 during calendar 

year 2001, and to reach their maximum age of 26 

years during calendar year 2025. NHTSA considers 

the maximum lifetime of vehicles to be the age after 

which less than 2 percent of the vehicles originally 

produced during a model year remain in service. 

Applying these conventions to vehicle registration 

data indicates that passenger cars have a maximum 

age of 26 years, while light trucks have a maximum 

lifetime of 36 years. See Lu, S., NHTSA, Regulatory 

Analysis and Evaluation Division, ‘‘Vehicle 

Survivability and Travel Mileage Schedules,’’ DOT 

HS 809 952, 8–11 (January 2006). Available at 

http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf 

(last accessed July 27, 2009). 

during a model year by the proportion 

typically expected to remain in service 

at their age during each later year, often 

referred to as a ‘‘survival rate.’’ 

To estimate production volumes of 

passenger cars and light trucks for 

individual manufacturers, NHTSA 

relied on a baseline market forecast 

constructed by EPA staff beginning with 

MY 2008 CAFE certification data. After 

constructing a MY 2008 baseline, EPA 

used projected car and truck volumes 

for this period from Energy Information 

Administration’s (EIA’s) 2009 Annual 

Energy Outlook (AEO).491 However, 

AEO projects sales only at the car and 

truck level, not at the manufacturer and 

model-specific level, which are needed 

in order to estimate the effects new 

standards will have on individual 

manufacturers.492 Therefore, EPA 

purchased data from CSM–Worldwide 

and used their projections of the 

number of vehicles of each type 

predicted to be sold by manufacturers in 

2011–2015.493 This provided the yearby-year percentages of cars and trucks 

sold by each manufacturer as well as the 

percentages of each vehicle segment. 

Although it was thus necessary to 

assume the same manufacturer and 

segment shares in 2016 as in 2015, 2016 

estimates from CSM should be available 

for the final rule. Using these 

percentages normalized to the AEO 

projected volumes then provided the 

manufacturer-specific market share and 

model-specific sales for model years 

2011–2016. 

To estimate the number of passenger 

cars and light trucks originally 

produced during model years 2012 

through 2016 that will remain in use 

during each subsequent year the agency 

applied age-specific survival rates for 

cars and light trucks to these adjusted 

forecasts of passenger car and light truck 

sales. In 2008, NHTSA updated its 

previous estimates of car and light truck 

survival rates using the most current 

491 Available at http://www.eia.doe.gov/oiaf/aeo/ 

index.html. NHTSA and EPA made the simplifying 

assumption that projected sales of cars and light 

trucks during each calendar year from 2012 through 

2016 represented the likely production volumes for 

the corresponding model year. The agency did not 

attempt to establish the exact correspondence 

between projected sales during individual calendar 

years and production volumes for specific model 

years. 

492 Because AEO 2009’s ‘‘car’’ and ‘‘truck’’ classes 

did not reflect NHTSA’s recent reclassification (in 

March 2009 for enforcement beginning MY 2011) of 

many two wheel drive SUVs from the nonpassenger 

(i.e., light truck) fleet to the passenger car fleet, EPA 

staff made adjustments to account for such vehicles 

in the baseline. 

493 EPA also considered other sources of similar 

information, such as J.D. Powers, and concluded 

that CSM was better able to provide forecasts at the 

requisite level of detail for most of the model years 

of interest. 

registration data for vehicles produced 

during recent model years, in order to 

ensure that they reflected recent 

increases in the durability and expected 

life spans of cars and light trucks.494 

The next step in estimating fuel use 

is to calculate the total number of miles 

that model year 2012–2016 cars and 

light trucks remaining in use will be 

driven each year. To estimate total miles 

driven, the number projected to remain 

in use during each future year is 

multiplied by the average number of 

miles they are expected to be driven at 

the age they will reach in that year. The 

agency estimated annual usage of cars 

and light trucks of each age using data 

from the Federal Highway 

Administration’s 2001 National 

Household Transportation Survey 

(NHTS).495 Because these estimates 

reflect the historically low gasoline 

prices that prevailed at the time the 

2001 NHTS was conducted, however, 

NHTSA adjusted them to account for 

the effect on vehicle use of subsequent 

increases in fuel prices. Details of this 

adjustment are provided in Chapter VIII 

of the PRIA and Chapter of the draft 

joint TSD. 

Increases in average annual use of 

cars and light trucks have been an 

important source of historical growth in 

the total number of miles they are 

driven each year. To estimate future 

growth in their average annual use for 

purposes of this rulemaking, NHTSA 

calculated the rate of growth in the 

adjusted mileage schedules derived 

from the 2001 NHTS necessary for total 

car and light truck travel to increase at 

the rate forecast in the AEO 2009 

Reference Case.496 This rate was 

calculated to be consistent with future 

changes in the overall size and age 

distributions of the U.S. passenger car 

and light truck fleets that result from the 

agency’s forecasts of total car and light 

truck sales and updated survival rates. 

The resulting growth rate in average 

annual car and light truck use of 

approximately 1.1 percent per year was 

494 Lu, S., NHTSA, Regulatory Analysis and 

Evaluation Division, ‘‘Vehicle Survivability and 

Travel Mileage Schedules,’’ DOT HS 809 952, 8–11 

(January 2006). Available at http://wwwnrd.nhtsa.dot.gov/Pubs/809952.pdf (last accessed 

August 9, 2009). These updated survival rates 

suggest that the expected lifetimes of recent-model 

passenger cars and light trucks are 13.8 and 14.5 

years. 

495 For a description of the Survey, see http:// 

nhts.ornl.gov/quickStart.shtml (last accessed 

August 9, 2009). 

496 This approach differs from that used in the 

MY 2011 final rule, where it was assumed that 

future growth in the total number of cars and light 

trucks in use resulting from projected sales of new 

vehicles was adequate by itself to account for 

growth in total vehicle use, without assuming 

continuing growth in average vehicle use. 
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applied to the mileage figures derived 

from the 2001 NHTS to estimate annual 

mileage during each year of the 

expected lifetimes of MY 2012–2016 

cars and light trucks.497 

Finally, the agency estimated total 

fuel consumption by passenger cars and 

light trucks remaining in use each year 

by dividing the total number of miles 

surviving vehicles are driven by the fuel 

economy they are expected to achieve 

under each alternative CAFE standard. 

Each model year’s total lifetime fuel 

consumption is the sum of fuel use by 

the cars or light trucks produced during 

that model year during each year of 

their life spans. In turn, the savings in 

a model year’s lifetime fuel use that will 

result from each alternative CAFE 

standard is the difference between its 

lifetime fuel use at the fuel economy 

level it attains under the Baseline 

alternative, and its lifetime fuel use at 

the higher fuel economy level it is 

projected to achieve under that 

alternative standard.498 

g. Accounting for the Rebound Effect of 

Higher Fuel Economy 

The fuel economy rebound effect 

refers to the fraction of fuel savings 

expected to result from an increase in 

vehicle fuel economy—particularly an 

increase required by the adoption of 

higher CAFE standards—that is offset by 

additional vehicle use. The increase in 

vehicle use occurs because higher fuel 

economy reduces the fuel cost of 

driving, typically the largest single 

component of the monetary cost of 

operating a vehicle, and vehicle owners 

497 While the adjustment for future fuel prices 

reduces average mileage at each age from the values 

derived from the 2001 NHTS, the adjustment for 

expected future growth in average vehicle use 

increases it. The net effect of these two adjustments 

is to increase expected lifetime mileage by about 18 

percent significantly for both passenger cars and 

about 16 percent for light trucks. 

498 To illustrate these calculations, the agency’s 

adjustment of the AEO 2009 Revised Reference Case 

forecast indicates that 9.26 million passenger cars 

will be produced during 2012, and the agency’s 

updated survival rates show that 83 percent of these 

vehicles, or 7.64 million, are projected to remain in 

service during the year 2022, when they will have 

reached an age of 10 years. At that age, passenger 

achieving the fuel economy level they are projected 

to achieve under the Baseline alternative are driven 

an average of about 800 miles, so surviving model 

year 2012 passenger cars will be driven a total of 

82.5 billion miles (= 7.64 million surviving vehicles 

× 10,800 miles per vehicle) during 2022. Summing 

the results of similar calculations for each year of 

their 26-year maximum lifetime, model year 2012 

passenger cars will be driven a total of 1,395 billion 

miles under the Baseline alternative. Under that 

alternative, they are projected to achieve a test fuel 

economy level of 32.4 mpg, which corresponds to 

actual on-road fuel economy of 25.9 mpg (= 32.4 

mpg × 80 percent). Thus their lifetime fuel use 

under the Baseline alternative is projected to be 

53.9 billion gallons (= 1,395 billion miles divided 

by 25.9 miles per gallon). 

respond to this reduction in operating 

costs by driving slightly more. By 

lowering the marginal cost of vehicle 

use, improved fuel economy may lead to 

an increase in the number of miles 

vehicles are driven each year and over 

their lifetimes. Even with their higher 

fuel economy, this additional driving 

consumes some fuel, so the rebound 

effect reduces the net fuel savings that 

result when new CAFE standards 

require manufacturers to improve fuel 

economy. 

The magnitude of the rebound effect 

is an important determinant of the 

actual fuel savings that are likely to 

result from adopting stricter CAFE 

standards. Research on the magnitude of 

the rebound effect in light-duty vehicle 

use dates to the early 1980s, and 

generally concludes that a statistically 

significant rebound effect occurs when 

vehicle fuel efficiency improves.499 The 

agency reviewed studies of the rebound 

effect it had previously relied upon, 

considered more recently published 

estimates, and developed new estimates 

of its magnitude for purposes of this 

NPRM.500 Recent studies provide some 

evidence that the rebound effect has 

been declining over time, and may 

decline further over the immediate 

future if incomes rise faster than 

gasoline prices. This result appears 

plausible, because the responsiveness of 

vehicle use to variation in fuel costs is 

expected to decline as they account for 

a smaller proportion of the total 

monetary cost of driving, which has 

been the case until very recently. At the 

same time, rising personal incomes 

would be expected to reduce the 

sensitivity of vehicle use to fuel costs as 

the time component of driving costs— 

which is likely to be related to income 

levels—accounts for a larger fraction the 

total cost of automobile travel. NHTSA 

developed new estimates of the rebound 

effect by using national data on lightduty vehicle travel over the period from 

1950 through 2006 to estimate various 

econometric models of the relationship 

between vehicle miles-traveled and 

factors likely to influence it, including 

household income, fuel prices, vehicle 

fuel efficiency, road supply, the number 

of vehicles in use, vehicle prices, and 

499 Some studies estimate that the long-run 

rebound effect is significantly larger than the 

immediate response to increased fuel efficiency. 

Although their estimates of the adjustment period 

required for the rebound effect to reach its long-run 

magnitude vary, this long-run effect is most 

appropriate for evaluating the fuel savings and 

emissions reductions resulting from stricter 

standards that would apply to future model years. 

500 For details of the agency’s analysis, see 

Chapter VIII of the PRIA and Chapter 4 of the draft 

joint TSD accompanying this proposed rule. 

other factors.501 The results of NHTSA’s 

analysis are consistent with the findings 

from other recent research: The average 

long-run rebound effect ranged from 16 

percent to 30 percent over the period 

from 1950 through 2007, while 

estimates of the rebound effect in 2007 

range from 8 percent to 14 percent. 

Projected values of the rebound effect 

for the period from 2010 through 2030, 

which the agency developed using 

forecasts of personal income, fuel 

prices, and fuel efficiency from AEO 

2009’s Reference Case, range from 4 

percent to 16 percent, depending on the 

specific model used to generate them. 

In light of these results, the agency’s 

judgment is that the apparent decline 

over time in the magnitude of the 

rebound effect justifies using a value for 

future analysis that is lower than 

historical estimates, which average 15– 

25 percent. Because the lifetimes of 

vehicles affected by the alternative 

CAFE standards considered in this 

rulemaking will extend from 2012 until 

nearly 2050, a value that is significantly 

lower than historical estimates appears 

to be appropriate. Thus NHTSA has 

elected to use a 10 percent rebound 

effect in its analysis of fuel savings and 

other benefits from higher CAFE 

standards for this NPRM. 

NHTSA also invites comment on 

other alternatives for estimating the 

rebound effect. As one illustration, 

variation in the price per gallon of 

gasoline directly affects the per-mile 

cost of driving, and drivers may respond 

just as they would to a change in the 

cost of driving resulting from a change 

in fuel economy, by varying the number 

of miles they drive. Because vehicles’ 

fuel economy is fixed in the short run, 

variation in the number of miles driven 

in response to changes in fuel prices 

will be reflected in changes in gasoline 

consumption. Under the assumption 

that drivers respond similarly to 

changes in the cost of driving whether 

they are caused by variation in fuel 

prices or fuel economy, the short-run 

price elasticity of gasoline—which 

measures the sensitivity of gasoline 

consumption to changes in its price per 

gallon—may provide some indication 

about the magnitude of the rebound 

effect itself. NHTSA invites comment on 

the extent to which the short-run 

elasticity of demand for gasoline with 

respect to its price can provide useful 

information about the size of the 

rebound effect. Specifically, we seek 

comment on whether it would be 

501 The agency used several different model 

specifications and estimation procedures to control 

for the effect of fuel prices on fuel efficiency in 

order to obtain accurate estimates of the rebound 

effect. 
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49672 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

appropriate to use the price elasticity of 

demand for gasoline, or other alternative 

approaches, to guide the choice of a 

value for the rebound effect. 

Additionally, NHTSA recognizes that 

as the world price of oil falls in 

response to lower U.S. demand for oil, 

there is the potential for an increase in 

oil use and, in turn, greenhouse gas 

emissions outside the U.S. This so 

called international oil ‘‘take back’’ 

effect is difficult to estimate. Given that 

oil consumption patterns vary across 

countries, there will be different 

demand responses to a change in the 

world price of crude oil. In addition, 

many countries around the world 

subsidize their oil consumption. It is not 

clear how oil consumption would 

change due to changes in the market 

price of oil given the current pattern of 

demand and subsidies. Further, many 

countries, especially in the developed 

countries/regions (i.e., the European 

Union), already have or anticipate 

implementing policies to limit GHG 

emissions. Further out in the future, it 

is anticipated that developing countries 

would take actions to reduce their GHG 

emissions as well. Any increases in 

petroleum consumption and GHG 

emissions in other nations that occurs in 

response to a decline in world 

petroleum prices would be attributed to 

those nations, and recorded in their 

respective GHG emissions inventories. 

Thus, including the same increase in 

emissions as part of the impact of 

adopting CAFE standards in the U.S. 

would risk double-counting of global 

emissions totals. NHTSA seeks 

comment on how to estimate the 

international ‘‘take back’’ effect and its 

impact on fuel consumption and GHG 

emissions. See the Energy Security 

section of the TSD, 4.2.8, for more 

discussion of the impact of the proposed 

vehicle rule on oil markets. 

h. Benefits From Increased Vehicle Use 

The increase in vehicle use from the 

rebound effect provides additional 

benefits to their owners, who may make 

more frequent trips or travel farther to 

reach more desirable destinations. This 

additional travel provides benefits to 

drivers and their passengers by 

improving their access to social and 

economic opportunities away from 

home. As evidenced by their decisions 

to make more frequent or longer trips 

when improved fuel economy reduces 

their costs for driving, the benefits from 

this additional travel exceed the costs 

drivers and passengers incur in making 

more frequent or longer trips. 

The agency’s analysis estimates the 

economic benefits from increased 

rebound-effect driving as the sum of fuel 

costs drivers incur plus the consumer 

surplus they receive from the additional 

accessibility it provides.502 Because the 

increase in travel depends on the extent 

of improvement in fuel economy, the 

value of benefits it provides differs 

among model years and alternative 

CAFE standards. Under even those 

alternatives that would impose the 

highest standards, however, the 

magnitude of these benefits represents a 

small fraction of total benefits. 

i. The Value of Increased Driving Range 

Improving vehicles’ fuel economy 

may also increase their driving range 

before they require refueling. By 

reducing the frequency with which 

drivers typically refuel, and by 

extending the upper limit of the range 

they can travel before requiring 

refueling, improving fuel economy thus 

provides some additional benefits to 

their owners.503 NHTSA re-examined 

this issue for purposes of this 

rulemaking, and found no information 

in comments or elsewhere that would 

cause the agency to revise its previous 

approach. Since no direct estimates of 

the value of extended vehicle range are 

available, NHTSA calculates directly the 

reduction in the annual number of 

required refueling cycles that results 

from improved fuel economy, and 

applies DOT-recommended values of 

travel time savings to convert the 

resulting time savings to their economic 

value.504 

As an illustration, a typical small light 

truck model has an average fuel tank 

size of approximately 20 gallons. 

Assuming that drivers typically refuel 

when their tanks are 55 percent full (i.e., 

11 gallons in reserve), increasing this 

model’s actual on-road fuel economy 

from 24 to 25 mpg would extend its 

driving range from 216 miles (= 9 

gallons × 24 mpg) to 225 miles (= 9 

gallons × 25 mpg). Assuming that it is 

driven 12,000 miles/year, this reduces 

the number of times it needs to be 

refueled each year from 55.6 (= 12,000 

miles per year/216 miles per refueling) 

to 53.3 (= 12,000 miles per year/225 

502 The consumer surplus provided by added 

travel is estimated as one-half of the product of the 

decline in fuel cost per mile and the resulting 

increase in the annual number of miles driven. 

503 If manufacturers respond to improved fuel 

economy by reducing the size of fuel tanks to 

maintain a constant driving range, the resulting cost 

savings will presumably be reflected in lower 

vehicle sales prices. 

504 See Department of Transportation, Guidance 

Memorandum, ‘‘The Value of Saving Travel Time: 

Departmental Guidance for Conducting Economic 

Evaluations,’’ Apr. 9, 1997. http://ostpxweb.dot.gov/ 

policy/Data/VOT97guid.pdf (last accessed August 

9, 2009); update available at http:// 

ostpxweb.dot.gov/policy/Data/VOTrevision1_2-11-

03.pdf (last accessed August 9, 2009). 

miles per refueling), or by 2.3 refuelings 

per year. 

Weighted by the nationwide mix of 

urban and rural driving, personal and 

business travel in urban and rural areas, 

and average vehicle occupancy for 

driving trips, the DOT-recommended 

values of travel time per vehicle-hour is 

$24.64 (in 2007 dollars).505 Assuming 

that locating a station and filling up 

requires five minutes, the annual value 

of time saved as a result of less frequent 

refueling amounts to $4.72 (calculated 

as 5/60 × 2.3 × $24.64). This calculation 

is repeated for each future year that 

model year 2012–2016 cars and light 

trucks would remain in service. Like 

fuel savings and other benefits, the 

value of this benefit declines over a 

model year’s lifetime, because a smaller 

number of vehicles originally produced 

during that model year remain in 

service each year, and those remaining 

in service are driven fewer miles. 

NHTSA recognizes that many 

assumptions made in its estimate for the 

value of increased driving range are 

subject to uncertainty. Please see 

Chapter 4 of the TSD and Chapter 8 of 

NHTSA’s PRIA for more information 

about the uncertainty regarding these 

assumptions. 

j. Added Costs From Congestion, 

Crashes and Noise 

Increased vehicle use associated with 

the rebound effect also contributes to 

increased traffic congestion, motor 

vehicle accidents, and highway noise. 

NHTSA relies on estimates of per-mile 

congestion, accident, and noise costs 

caused by increased use of automobiles 

and light trucks developed by the 

Federal Highway Administration to 

estimate these increased costs.506 

NHTSA employed these estimates 

previously in its analysis accompanying 

the MY 2011 final rule, and continues 

505 The hourly wage rate during 2008 is estimated 

to average $25.50 when expressed in 2007 dollars. 

Personal travel in urban areas (which represents 94 

percent of urban travel) is valued at 50 percent of 

the hourly wage rate, while business travel (the 

remaining 6 percent of urban travel) is valued at 

100 percent of the hourly wage rate. For intercity 

travel, personal travel (87 percent of total intercity 

travel) is valued at 70 percent of the wage rate, 

while business travel (13 percent) is valued at 100 

percent of the wage rate. The resulting values of 

travel time are $12.67 for urban travel and $17.66 

for intercity travel, and must be multiplied by 

vehicle occupancy (1.6) to obtain the estimated 

values of time per vehicle hour in urban and rural 

driving. Finally, about 66% of driving occurs in 

urban areas, while the remaining 34% takes place 

in rural areas, and these percentages are used to 

calculate a weighted average of the value of time 

in all driving. 

506 These estimates were developed by FHWA for 

use in its 1997 Federal Highway Cost Allocation 

Study; see http://www.fhwa.dot.gov/policy/hcas/ 

final/index.htm (last accessed August 9, 2009). 
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to find them appropriate for this NPRM 

after reviewing the procedures used by 

FHWA to develop them and considering 

other available estimates of these values. 

The agency multiplies FHWA’s 

estimates of per-mile costs by the 

annual increases in automobile and 

light truck use from the rebound effect 

to yield the estimated increases in 

congestion, accident, and noise 

externality costs during each future 

year. 

k. Petroleum Consumption and Import 

Externalities 

U.S. consumption and imports of 

petroleum products also impose costs 

on the domestic economy that are not 

reflected in the market price for crude 

petroleum, or in the prices paid by 

consumers of petroleum products such 

as gasoline. These costs include (1) 

higher prices for petroleum products 

resulting from the effect of U.S. oil 

import demand on the world oil price; 

(2) the risk of disruptions to the U.S. 

economy caused by sudden reductions 

in the supply of imported oil to the U.S.; 

and (3) expenses for maintaining a U.S. 

military presence to secure imported oil 

supplies from unstable regions, and for 

maintaining the strategic petroleum 

reserve (SPR) to cushion against 

resulting price increases.507 

Higher U.S. imports of crude oil or 

refined petroleum products increase the 

magnitude of these external economic 

costs, thus increasing the true economic 

cost of supplying transportation fuels 

above their market prices. Conversely, 

lowering U.S. imports of crude 

petroleum or refined fuels by reducing 

domestic fuel consumption can reduce 

these external costs, and any reduction 

in their total value that results from 

improved fuel economy represents an 

economic benefit of more stringent 

CAFE standards, in addition to the 

value of saving fuel itself. 

NHTSA has carefully reviewed its 

assumptions regarding the appropriate 

value of these benefits for this proposed 

rule. In analyzing benefits from its 

recent actions to increase light truck 

CAFE standards for model years 2005– 

07 and 2008–11, NHTSA relied on a 

1997 study by Oak Ridge National 

Laboratory (ORNL) to estimate the value 

507 See, e.g., Bohi, Douglas R. and W. David 

Montgomery (1982). Oil Prices, Energy Security, 

and Import Policy, Washington, DC: Resources for 

the Future, Johns Hopkins University Press; Bohi, 

D. R., and M. A. Toman (1993). ‘‘Energy and 

Security: Externalities and Policies,’’ Energy Policy 

21:1093–1109; and Toman, M. A. (1993). ‘‘The 

Economics of Energy Security: Theory, Evidence, 

Policy,’’ in A. V. Kneese and J. L. Sweeney, eds. 

(1993). Handbook of Natural Resource and Energy 

Economics, Vol. III. Amsterdam: North-Holland, pp. 

1167–1218. 

of reduced economic externalities from 

petroleum consumption and imports.508 

More recently, ORNL updated its 

estimates of the value of these 

externalities, using the analytic 

framework developed in its original 

1997 study in conjunction with recent 

estimates of the variables and 

parameters that determine their 

value.509 The updated ORNL study was 

subjected to a detailed peer review by 

experts selected by EPA, and its 

estimates of the value of oil import 

externalities were subsequently revised 

to reflect their comments and 

recommendations.510 

At the request of EPA, ORNL further 

revised its 2008 estimates of external 

costs from U.S. oil imports to reflect 

recent changes in the outlook for world 

petroleum prices and continuing 

changes in the structure and 

characteristics of global petroleum 

supply and demand. 

These most recent revisions increase 

ORNL’s estimates of the ‘‘monopsony 

premium’’ associated with U.S. oil 

imports, which measures the reduced 

value of payments from U.S. oil 

purchasers to foreign oil suppliers 

beyond the savings from reduced 

purchases of petroleum itself that 

results when lower U.S. import demand 

reduces the world price of petroleum.511 

Consistency with NHTSA’s use of 

estimates of the global benefits from 

reducing emissions of CO2 and other 

greenhouse gases in this analysis, 

however, requires the use of a global 

perspective for assessing their net value. 

From this perspective, reducing these 

payments simply results in a transfer of 

resources from foreign oil suppliers to 

U.S. purchasers (or more properly, in a 

savings in the value of resources 

previously transferred from U.S. 

purchasers to foreign producers), and 

provides no real savings in resources to 

the global economy. Thus NHTSA’s 

analysis of the benefits from adopting 

higher CAFE standards for MY 2012– 

508 Leiby, Paul N., Donald W. Jones, T. Randall 

Curlee, and Russell Lee, Oil Imports: An 

Assessment of Benefits and Costs, ORNL–6851, Oak 

Ridge National Laboratory, November 1, 1997. 

Available at http://pzl1.ed.ornl.gov/ORNL6851.pdf 

(last accessed August 9, 2009). 

509 Leiby, Paul N. ‘‘Estimating the Energy Security 

Benefits of Reduced U.S. Oil Imports,’’ Oak Ridge 

National Laboratory, ORNL/TM–2007/028, Revised 

July 23, 2007. Available at http://pzl1.ed.ornl.gov/ 

energysecurity.html (click on link below ‘‘Oil 

Imports Costs and Benefits’’) (last accessed August 

9, 2009). 

510 Peer Review Report Summary: Estimating the 

Energy Security Benefits of Reduced U.S. Oil 

Imports, ICF, Inc., September 2007. 

511 The reduction in payments from U.S. oil 

purchasers to domestic petroleum producers is not 

included as a benefit, since it represents a transfer 

that occurs entirely within the U.S. economy. 

2016 cars and light trucks excludes the 

reduced value of monopsony payments 

by U.S. oil consumers that might result 

from lower fuel consumption by these 

vehicles. 

The literature on the energy security 

for the last two decades has routinely 

combined the monopsony and the 

macroeconomic disruption components 

when calculating the total value of the 

energy security premium. However, in 

the context of using a global value for 

the Social Cost of Carbon (SCC) the 

question arises: How should the energy 

security premium be used when some 

benefits from the proposed rule, such as 

the benefits of reducing greenhouse gas 

emissions, are calculated at a global 

level? Monopsony benefits represent 

avoided payments by the U.S. to oil 

producers in foreign countries that 

result from a decrease in the world oil 

price as the U.S. decreases its 

consumption of imported oil. Although 

there is clearly a benefit to the U.S. 

when considered from the domestic 

perspective, the decrease in price due to 

decreased demand in the U.S. also 

represents a loss of income to oilproducing countries. Given the 

redistributive nature of this effect, do 

the negative effects on other countries 

‘‘net out’’ the positive impacts to the 

U.S.? If this is the case, then, the 

monopsony portion of the energy 

security premium should be excluded 

from the net benefits calculation for the 

rule. 

As the preceding discussion has 

indicated, the agencies omitted the 

reduction in monopsony payments that 

occurs when U.S. petroleum 

consumption and imports are reduced 

from their estimates of economic 

benefits for the proposed rules. Since 

the reduction in monopsony payments 

by U.S. oil consumers is exactly offset 

by a decline in income to suppliers of 

imported oil, this omission ensures 

consistency of the agencies’ analysis 

with the inclusion of global benefits 

from reducing emissions of greenhouse 

gas emissions. The agencies seek 

comment on whether, from other 

perspectives, it would be reasonable to 

include both the global value of 

reducing GHG emissions and the 

reduction in monopsony payments by 

U.S. consumers of petroleum products 

in their estimates of total economic 

benefits from reducing U.S. fuel 

consumption. 

ORNL’s most recently revised 

estimates of the increase in the expected 

costs associated with potential 

disruptions in U.S. petroleum imports 

imply that each gallon of imported fuel 

or petroleum saved reduces the 

expected costs of oil supply disruptions 
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49674 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

to the U.S. economy by $0.16 per gallon 

(in 2007$). The reduction in expected 

disruption costs represents a real 

savings in resources, and thus 

contributes economic benefits in 

addition to the savings in fuel 

production costs that result from 

increasing fuel economy. NHTSA 

employs this value in its evaluation of 

the economic benefits from adopting 

higher CAFE standards for MY 2012– 

2016 cars and light trucks. 

NHTSA’s analysis does not include 

savings in budgetary outlays to support 

U.S. military activities among the 

benefits of higher fuel economy and the 

resulting fuel savings.512 NHTSA’s 

analysis of benefits from alternative 

CAFE standards for MY 2012–2016 also 

excludes any cost savings from 

maintaining a smaller SPR from its 

estimates of the external benefits of 

reducing gasoline consumption and 

petroleum imports. This view concurs 

with that of the recent ORNL study of 

economic costs from U.S. oil imports, 

which concludes that savings in 

government outlays for these purposes 

are unlikely to result from reductions in 

consumption of petroleum products and 

oil imports on the scale of those 

resulting from higher CAFE standards. 

Based on a detailed analysis of 

differences in fuel consumption, 

petroleum imports, and imports of 

refined petroleum products among the 

Reference Case, High Economic Growth, 

and Low Economic Growth Scenarios 

presented in AEO 2009, NHTSA 

estimates that approximately 50 percent 

of the reduction in fuel consumption 

resulting from adopting higher CAFE 

standards is likely to be reflected in 

reduced U.S. imports of refined fuel, 

while the remaining 50 percent would 

be reduce domestic fuel refining.513 Of 

this latter figure, 90 percent is 

anticipated to reduce U.S. imports of 

crude petroleum for use as a refinery 

feedstock, while the remaining 10 

percent is expected to reduce U.S. 

domestic production of crude 

petroleum.514 Thus on balance, each 

512 However, the agency conducted a sensitivity 

analysis of the potential effect of assuming that 

some reduction military spending would result 

from fuel savings and reduced petroleum imports 

in order to investigate its impacts on the standards 

and fuel savings. 

513 Differences between forecast annual U.S. 

imports of crude petroleum and refined products 

among these three scenarios range from 24–89 

percent of differences in projected annual gasoline 

and diesel fuel consumption in the U.S. These 

differences average 49 percent over the forecast 

period spanned by AEO 2009. 

514 Differences between forecast annual U.S. 

imports of crude petroleum among these three 

scenarios range from 67–97 percent of differences 

in total U.S. refining of crude petroleum, and 

100 gallons of fuel saved as a 

consequence of higher CAFE standards 

is anticipated to reduce total U.S. 

imports of crude petroleum or refined 

fuel by 95 gallons.515 

l. Air Pollutant Emissions 

i. Impacts on Criteria Air Pollutant 

Emissions 

Criteria air pollutants emitted by 

vehicles and during fuel production 

include carbon monoxide (CO), 

hydrocarbon compounds (usually 

referred to as ‘‘volatile organic 

compounds,’’ or VOC), nitrogen oxides 

(NOX), fine particulate matter (PM2.5), 

and sulfur oxides (SOX). While 

reductions in domestic fuel refining and 

distribution that result from lower fuel 

consumption will reduce U.S. emissions 

of these pollutants, additional vehicle 

use associated with the rebound effect 

from higher fuel economy will increase 

their emissions. Thus the net effect of 

stricter CAFE standards on emissions of 

each criteria pollutant depends on the 

relative magnitudes of its reduced 

emissions in fuel refining and 

distribution, and increases in its 

emissions from vehicle use. Because the 

relationship between emissions in fuel 

refining and vehicle use is different for 

each criteria pollutant, the net effect of 

fuel savings from the proposed 

standards on total emissions of each 

pollutant is likely to differ. We note that 

any benefits in terms of criteria air 

pollutant reductions resulting from this 

rule would not be direct benefits. 

With the exception of SO2, NHTSA 

calculated annual emissions of each 

criteria pollutant resulting from vehicle 

use by multiplying its estimates of car 

and light truck use during each year 

over their expected lifetimes by per-mile 

emission rates appropriate to each 

vehicle type, fuel, model year, and age. 

These emission rates were developed by 

U.S. EPA using its Motor Vehicle 

Emission Simulator (Draft MOVES 

2009).516 Emission rates for SO2 were 

calculated by NHTSA using average fuel 

sulfur content estimates supplied by 

EPA, together with the assumption that 

the entire sulfur content of fuel is 

emitted in the form of SO2.517 Total SO2 

average 85 percent over the forecast period spanned 

by AEO 2009. 

515 This figure is calculated as 50 gallons + 50 

gallons * 90% = 50 gallons + 45 gallons = 95 

gallons. 

516 The MOVES model assumes that the per-mile 

rates at which these pollutants are emitted are 

determined by EPA regulations and the 

effectiveness of catalytic after-treatment of engine 

exhaust emissions, and are thus unaffected by 

changes in car and light truck fuel economy. 

517 These are 30 and 15 parts per million (ppm, 

measured on a mass basis) for gasoline and diesel 

respectively, which produces emission rates of 0.17 

emissions under each alternative CAFE 

standard were calculated by applying 

the resulting emission rates directly to 

estimated annual gasoline and diesel 

fuel use by cars and light trucks. 

As with other impacts, the changes in 

emissions of criteria air pollutants 

resulting from alternative increases in 

CAFE standards for MY 2012–2016 cars 

and light trucks were calculated from 

the differences between emissions 

under each alternative that would 

increase CAFE standards, and emissions 

under the baseline alternative. 

NHTSA estimated the reductions in 

criteria pollutant emissions from 

producing and distributing fuel that 

would occur under alternative CAFE 

standards using emission rates obtained 

by EPA from Argonne National 

Laboratories’ Greenhouse Gases and 

Regulated Emissions in Transportation 

(GREET) model.518 The GREET model 

provides separate estimates of air 

pollutant emissions that occur in 

different phases of fuel production and 

distribution, including crude oil 

extraction, transportation, and storage, 

fuel refining, and fuel distribution and 

storage.519 EPA modified the GREET 

model to change certain assumptions 

about emissions during crude petroleum 

extraction and transportation, as well as 

to update its emission rates to reflect 

adopted and pending EPA emission 

standards. NHTSA converted these 

emission rates from the mass per fuel 

energy content basis on which GREET 

reports them to mass per gallon of fuel 

supplied using estimates of fuel energy 

content supplied by GREET. 

The resulting emission rates were 

applied to the agency’s estimates of fuel 

consumption under each alternative 

CAFE standard to develop estimates of 

total emissions of each criteria pollutant 

during fuel production and distribution. 

The assumptions about the effects of 

changes in fuel consumption on 

domestic and imported sources of fuel 

supply discussed above were then 

employed to calculate the effects of 

grams of SO2 per gallon of gasoline and 0.10 grams 

per gallon of diesel. 

518 Argonne National Laboratories, The 

Greenhouse Gas and Regulated Emissions from 

Transportation (GREET) Model, Version 1.8, June 

2007, available at http:// 

www.transportation.anl.gov/modeling_simulation/ 

GREET/index.html (last accessed August 9, 2009). 

519 Emissions that occur during vehicle refueling 

at retail gasoline stations (primarily evaporative 

emissions of volatile organic compounds, or VOCs) 

are already accounted for in the ‘‘tailpipe’’ emission 

factors used to estimate the emissions generated by 

increased light truck use. GREET estimates 

emissions in each phase of gasoline production and 

distribution in mass per unit of gasoline energy 

content; these factors are then converted to mass 

per gallon of gasoline using the average energy 

content of gasoline. 
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reductions in fuel use from alternative 

CAFE standards on changes in imports 

of refined fuel and domestic refining. 

NHTSA’s analysis assumes that 

reductions in imports of refined fuel 

would reduce criteria pollutant 

emissions during fuel storage and 

distribution only. Reductions in 

domestic fuel refining using imported 

crude oil as a feedstock are assumed to 

reduce emissions during fuel refining, 

storage, and distribution, because each 

of these activities would be reduced. 

Reduced domestic fuel refining using 

domestically-produced crude oil is 

assumed to reduce emissions during all 

four phases of fuel production and 

distribution.520 

Finally, NHTSA calculated the net 

changes in domestic emissions of each 

criteria pollutant by summing the 

increases in emissions projected to 

result from increased vehicle use, and 

the reductions anticipated to result from 

lower domestic fuel refining and 

distribution.521 As indicated previously, 

the effect of adopting higher CAFE 

standards on total emissions of each 

criteria pollutant depends on the 

relative magnitudes of the resulting 

reduction in emissions from fuel 

refining and distribution, and the 

increase in emissions from additional 

vehicle use. Although these net changes 

vary significantly among individual 

criteria pollutants, the agency projects 

that on balance, adopting higher CAFE 

standards would reduce emissions of all 

criteria air pollutants except carbon 

monoxide (CO). 

The net changes in domestic 

emissions of fine particulates (PM2.5) 

and its chemical precursors (such as 

NOX, SOX, and VOCs) are converted to 

economic values using estimates of the 

reductions in health damage costs per 

ton of emissions of each pollutant that 

is avoided, which were developed and 

recently revised by EPA. These savings 

represent the estimated reductions in 

the value of damages to human health 

resulting from lower atmospheric 

concentrations and population exposure 

to air pollution that occur when 

emissions of each pollutant that 

contributes to atmospheric PM2.5 

concentrations are reduced. The value 

of reductions in the risk of premature 

death due to exposure to fine particulate 

520 In effect, this assumes that the distances crude 

oil travels to U.S. refineries are approximately the 

same regardless of whether it travels from domestic 

oilfields or import terminals, and that the distances 

that gasoline travels from refineries to retail stations 

are approximately the same as those from import 

terminals to gasoline stations. 

521 All emissions from increased vehicle use are 

assumed to occur within the U.S., since CAFE 

standards would apply only to vehicles produced 

for sale in the U.S. 

pollution (PM2.5) account for a majority 

of EPA’s estimated values of reducing 

criteria pollutant emissions, although 

the value of avoiding other health 

impacts is also included in these 

estimates. These values do not include 

a number of unquantified benefits, such 

as reduction in the welfare and 

environmental impacts of PM2.5 

pollution, or reductions in health and 

welfare impacts related to other criteria 

pollutants (ozone, NO2, and SO2) and air 

toxics. EPA estimates different PMrelated per-ton values for reducing 

emissions from vehicle use than for 

reductions in emissions of that occur 

during fuel production and 

distribution.522 NHTSA applies these 

separate values to its estimates of 

changes in emissions from vehicle use 

and fuel production and distribution to 

determine the net change in total 

economic damages from emissions of 

these pollutants. 

EPA projects that the per-ton values 

for reducing emissions of criteria 

pollutants from both mobile sources 

(including motor vehicles) and 

stationary sources such as fuel refineries 

and storage facilities will increase over 

time. These projected increases reflect 

rising income levels, which are assumed 

to increase affected individuals’ 

willingness to pay for reduced exposure 

to health threats from air pollution, as 

well as future population growth, which 

increases population exposure to future 

levels of air pollution. 

ii. Reductions in CO2 Emissions 

Emissions of carbon dioxide and other 

greenhouse gases (GHGs) occur 

throughout the process of producing 

and distributing transportation fuels, as 

well as from fuel combustion itself. By 

reducing the volume of fuel consumed 

by passenger cars and light trucks, 

higher CAFE standards will reduce GHG 

emissions generated by fuel use, as well 

as throughout the fuel supply cycle. 

Lowering these emissions is likely to 

slow the projected pace and reduce the 

ultimate extent of future changes in the 

global climate, thus reducing future 

economic damages that changes in the 

global climate are expected to cause. By 

reducing the probability that climate 

changes with potentially catastrophic 

economic or environmental impacts will 

occur, lowering GHG emissions may 

also result in economic benefits that 

exceed the resulting reduction in the 

expected future economic costs caused 

522 These reflect differences in the typical 

geographic distributions of emissions of each 

pollutant, their contributions to ambient PM2.5 

concentrations, pollution levels (predominantly 

those of PM2.5), and resulting changes in population 

exposure. 

by gradual changes in the earth’s 

climatic systems. 

Quantifying and monetizing benefits 

from reducing GHG emissions is thus an 

important step in estimating the total 

economic benefits likely to result from 

establishing higher CAFE standards. 

The agency estimated emissions of CO2 

from passenger car and light truck use 

by multiplying the number of gallons of 

each type of fuel (gasoline and diesel) 

they are projected to consume under 

alternative CAFE standards by the 

quantity or mass of CO2 emissions 

released per gallon of fuel consumed. 

This calculation assumes that the entire 

carbon content of each fuel is converted 

to CO2 emissions during the combustion 

process. Carbon dioxide emissions 

account for nearly 95 percent of total 

GHG emissions that result from fuel 

combustion during vehicle use. 

iii. Economic Value of Reductions in 

CO2 Emissions 

NHTSA has taken the economic 

benefits of reducing CO2 emission into 

account in this rulemaking, both in 

developing proposed CAFE standards 

and in assessing the economic benefits 

of each alternative that was considered. 

Since direct estimates of the economic 

benefits from reducing GHG emissions 

are generally not reported in published 

literature on the impacts of climate 

change, these benefits are typically 

assumed to be the ‘‘mirror image’’ of the 

estimated incremental costs resulting 

from an increase in those emissions. 

That is, the benefits from reducing 

emissions are usually measured by the 

savings in estimated economic damages 

that an equivalent increase in emissions 

would otherwise have caused. 

The ‘‘social cost of carbon’’ (SCC) is 

intended to be a monetary measure of 

the incremental damage resulting from 

carbon dioxide (CO2) emissions, 

including (but not limited to) net 

agricultural productivity loss, human 

health effects, property damages from 

sea level rise, and changes in ecosystem 

services. Any effort to quantify and to 

monetize the consequences associated 

with climate change will raise serious 

questions of science, economics, and 

ethics. But with full regard for the limits 

of both quantification and monetization, 

the SCC can be used to provide an 

estimate of the social benefits of 

reductions in GHG emissions. 

For at least four reasons, any 

particular figure will be contestable. 

First, scientific and economic 

knowledge about the impacts of climate 

change continues to grow. With new 

and better information about relevant 

questions, including the cost, burdens, 

and possibility of adaptation, current 
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estimates will inevitably change over 

time. Second, some of the likely and 

potential damages from climate 

change—for example, the loss of 

endangered species—are generally not 

included in current SCC estimates. 

These omissions may turn out to be 

significant; in the sense that they may 

mean that the best current estimates are 

too low. As noted by the IPCC Fourth 

Assessment Report, ‘‘It is very likely that 

globally aggregated figures 

underestimate the damage costs because 

they cannot include many nonquantifiable impacts.’’ Third, it is 

unlikely that the damage estimates 

account for the directed technological 

change that will lead to innovations that 

reduce the costs of responding to 

climate change—for example, it is likely 

that scientists will develop crops that 

are better able to withstand high 

temperatures. In this respect, the current 

estimates may overstate the likely 

damages. Fourth, controversial ethical 

judgments, including those involving 

the treatment of future generations, play 

a role in judgments about the SCC (see 

in particular the discussion of the 

discount rate, below). 

To date, SCC estimates presented in 

recent regulatory documents have 

varied within and among agencies, 

including DOT, DOE, and EPA. For 

example, a regulation proposed by DOT 

in 2008 assumed a value of $7 per ton 

CO2 523 (2006$) for 2011 emission 

reductions (with a range of $0–14 for 

sensitivity analysis). A regulation 

finalized by DOE used a range of $0–$20 

(2007$). Both of these ranges were 

designed to reflect the value of damages 

to the United States resulting from 

carbon emissions, or the ‘‘domestic’’ 

SCC. In the final MY 2011 CAFE EIS, 

DOT used both a domestic SCC value of 

$2/tCO2 and a global SCC value of 

$33/tCO2 (with sensitivity analysis at 

$80/tCO2), increasing at 2.4 percent per 

year thereafter. The final MY 2011 

CAFE rule also presented a range from 

$2 to $80/tCO2. EPA’s Advance Notice 

of Proposed Rulemaking for Greenhouse 

Gases discussed the benefits of reducing 

GHG emissions and identified what it 

described as ‘‘very preliminary’’ SCC 

estimates ‘‘subject to revision’’ that 

spanned three orders of magnitude. 

EPA’s global mean values were $68 and 

$40/tCO2 for discount rates of 2 percent 

523 For the purposes of this discussion, we 

present all values of the SCC as the cost per ton of 

CO2 emissions. Some discussions of the SCC in the 

literature use an alternative presentation of a dollar 

per ton of Carbon. The standard adjustment factor 

is 3.67, which means, for example, that a SCC of 

$10 per ton of CO2 would be equivalent to a cost 

of $36.70 for a ton of carbon emitted. 

and 3 percent respectively (in 2006 real 

dollars for 2007 emissions).524 

The current Administration has 

worked to develop a transparent 

methodology for selecting a set of 

interim SCC estimates to use in 

regulatory analyses until a more 

comprehensive characterization of the 

distribution of SCC is developed. This 

discussion proposes a set of values for 

the interim social cost of carbon. It 

should be emphasized that the analysis 

here is preliminary. Today’s proposed 

joint rulemaking presents SCC estimates 

that reflect the Administration’s current 

understanding of the relevant literature. 

These interim estimates are being used 

for the short-term while an interagency 

group develops a more comprehensive 

characterization of the distribution of 

SCC values for future economic and 

regulatory analyses. The interim values 

should not be viewed as a statement 

about the results of the longer-term 

process. The Administration will be 

evaluating and seeking comment in the 

preamble to today’s proposed rule on all 

of the scientific, economic, and ethical 

issues before establishing final estimates 

for use in future rulemakings. 

The outcomes of the Administration’s 

process to develop interim values are 

judgments in favor of (a) global rather 

than domestic values, (b) an annual 

growth rate of 3%, and (c) interim global 

SCC estimates for 2007 (in 2006 dollars) 

of $55, $33, $19, $10, and $5 per ton of 

CO2. Notably, we have centered our 

current attention on a SCC of $19. The 

proposed figures are based on the 

following judgments. 

1. Global and domestic measures. 

Because of the distinctive nature of the 

climate change problem, we present 

both a global SCC and a fraction of that 

value that represents impacts that may 

occur within the borders of the U.S. 

alone, or a ‘‘domestic’’ SCC, but center 

our current attention on the global 

measure. This approach represents a 

departure from past practices, which 

relied, for the most part, on domestic 

measures. As a matter of law, both 

global and domestic values are 

permissible; the relevant statutory 

provisions are ambiguous and allow 

selection of either measure.525 

524 73 FR 44416 (July 30, 2008). EPA, ‘‘Advance 

Notice of Proposed Rulemaking for Greenhouse 

Gases Under the Clean Air Act, Technical Support 

Document on Benefits of Reducing GHG 

Emissions,’’ June 2008. www.regulations.gov. 

Search for ID ‘‘EPA–HQ–OAR–2008–0318–0078.’’ 

525 It is true that Federal statutes are presumed 

not to have extraterritorial effect, in part to ensure 

that the laws of the United States respect the 

interests of foreign sovereigns. But use of a global 

measure for the SCC does not give extraterritorial 

effect to Federal law and hence does not intrude on 

such interests. 

It is true that under OMB guidance, 

analysis from the domestic perspective 

is required, while analysis from the 

international perspective is optional. 

The domestic decisions of one nation 

are not typically based on a judgment 

about the effects of those decisions on 

other nations. But the climate change 

problem is highly unusual in the sense 

that it involves (a) a global public good 

in which (b) the emissions of one nation 

may inflict significant damages on other 

nations and (c) the United States is 

actively engaged in promoting an 

international agreement to reduce 

worldwide emissions. 

In these circumstances, we believe the 

global measure is preferred. Use of a 

global measure reflects the reality of the 

problem and is expected to contribute to 

the continuing efforts of the United 

States to ensure that emissions 

reductions occur in many nations. 

Domestic SCC values are also 

presented. The development of a 

domestic SCC is greatly complicated by 

the relatively few region- or countryspecific estimates of the SCC in the 

literature. One potential source of 

estimates comes from a recent 

unpublished EPA modeling effort using 

the FUND model. The resulting 

estimates suggest that the ratio of 

domestic to global benefits varies with 

key parameter assumptions. With a 3 

percent discount rate, for example, the 

U.S. benefit is about 6 percent of the 

global benefit for the ‘‘central’’ (mean) 

FUND results, while, for the 

corresponding ‘‘high’’ estimates 

associated with a higher climate 

sensitivity and lower global economic 

growth, the U.S. benefit is less than 4 

percent of the global benefit. With a 2 

percent discount rate, the U.S. share is 

about 2–5 percent of the global estimate. 

Based on this available evidence, an 

interim domestic SCC value equal to 6 

percent of the global damages is 

proposed. This figure is in the middle 

of the range of available estimates from 

the literature. It is recognized that the 6 

percent figure is approximate and 

highly speculative and alternative 

approaches will be explored before 

establishing final values for future 

rulemakings. 

2. Filtering existing analyses. There 

are numerous SCC estimates in the 

existing literature, and it is reasonable 

to make use of those estimates in order 

to produce a figure for current use. A 

starting point is provided by the metaanalysis in Richard Tol, 2008.526 With 

526 Richard Tol, The Social Cost of Carbon: 

Trends, Outliers, and Catastrophes, Economics: The 

Open-Access, Open-Assessment E-Journal, Vol. 2, 

2008–25. http://www.economics-ejournal.org/ 

economics/journalarticles/2008-25 (2008). 
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that starting point, the Administration 

proposes to ‘‘filter’’ existing SCC 

estimates by using those that (1) are 

derived from peer-reviewed studies; (2) 

do not weight the monetized damages to 

one country more than those in other 

countries; (3) use a ‘‘business as usual’’ 

climate scenario; and (4) are based on 

the most recent published version of 

each of the three major integrated 

assessment models (IAMs): FUND, 

PAGE, and DICE. 

Proposal (1) is based on the view that 

those studies that have been subject to 

peer review are more likely to be 

reliable than those that have not been. 

Proposal (2) is based on a principle of 

neutrality and simplicity; it does not 

treat the citizens of one nation (or 

different citizens within the U.S.) 

differently on the basis of speculative or 

controversial considerations. Further, it 

is consistent with the potential 

compensation tests of Kaldor (1939) and 

Hicks (1940), which use unweighted 

sums of willingness to pay. Finally, this 

is the approach used in rulemakings 

across a variety of settings and 

consequently keeps U.S. government 

policy consistent across contexts. 

Proposal (3) stems from the judgment 

that as a general rule, the proper way to 

assess a policy decision is by comparing 

the implementation of the policy against 

a counterfactual state where the policy 

is not implemented. In addition, our 

expectation is that most policies to be 

evaluated using these interim SCC 

estimates will constitute small enough 

changes to the larger economy to safely 

assume that the marginal benefits of 

emissions reductions will not change 

between the baseline and policy 

scenarios. A departure from this 

approach would be to consider a more 

dynamic setting in which other 

countries might implement policies to 

reduce GHG emissions at an unknown 

future date and the U.S. could choose to 

implement such a policy now or at a 

future date. 

Proposal (4) is based on four 

complementary judgments. First, the 

FUND, PAGE, and DICE models now 

stand as the most comprehensive and 

reliable efforts to measure the economic 

damages from climate change. Second, 

the latest versions of the three IAMs are 

likely to reflect the most recent evidence 

and learning, and hence they are 

presumed to be superior to those that 

preceded them. Third, any effort to 

choose among them, or to reject one in 

favor of the others, would be difficult to 

defend at the present time. In the 

absence of a clear reason to choose 

among them, it is reasonable to base the 

SCC on all of them. Fourth, in light of 

the uncertainties associated with the 

SCC, the additional information offered 

by different models is important. 

3. Use a model-weighted average of 

the estimates at each discount rate. At 

this time, a scientifically valid reason to 

prefer any of the three major IAMs 

(FUND, PAGE, and DICE) has not been 

identified. Accordingly, to address the 

concern that certain models not be given 

unequal weight relative to the other 

models, the estimates are based on an 

equal weighting of the means of the 

estimates from each of the models. 

Among estimates that remain after 

applying the filter, we begin by taking 

the average of all estimates within a 

model. The estimated SCC is then 

calculated as the average of the three 

model-specific averages. This approach 

is used to ensure that models with a 

greater number of published results do 

not exert unequal weight on the interim 

SCC estimates. 

4. Apply a 3 percent annual growth 

rate to the chosen SCC values. SCC is 

assumed to increase over time, because 

future emissions are expected to 

produce larger incremental damages as 

physical and economic systems become 

more stressed as the magnitude of 

climate change increases. Indeed, an 

implied growth rate in the SCC can be 

produced by most of the models that 

estimate economic damages caused by 

increased GHG emissions in future 

years. But neither the rate itself nor the 

information necessary to derive its 

implied value is commonly reported. In 

light of the limited amount of debate 

thus far about the appropriate growth 

rate of the SCC, applying a rate of 3 

percent per year seems appropriate at 

this stage. This value is consistent with 

the range recommended by IPCC (2007) 

and close to the latest published 

estimate (Hope 2008). 

(1) Discount Rates 

For estimation of the benefits 

associated with the mitigation of climate 

change, one of the most complex issues 

involves the appropriate discount rate. 

OMB’s current guidance offers a 

detailed discussion of the relevant 

issues and calls for discount rates of 3 

percent and 7 percent. It also permits a 

sensitivity analysis with low rates (1–3 

percent) for intergenerational problems: 

‘‘If your rule will have important 

intergenerational benefits or costs you 

might consider a further sensitivity 

analysis using a lower but positive 

discount rate in addition to calculating 

net benefits using discount rates of 3 

and 7 percent.’’ 527 

527 See OMB Circular A–4, pp. 35–36, citing 

Portney and Weyant, eds. (1999), Discounting and 

The choice of a discount rate, 

especially over long periods of time, 

raises highly contested and exceedingly 

difficult questions of science, 

economics, philosophy, and law. See, 

e.g., William Nordhaus, The Challenge 

of Global Warming (2008); Nicholas 

Stern, The Economics of Climate 

Change (2007); Discounting and 

Intergenerational Equity (Paul Portney 

and John Weyant eds. 1999). It is not 

clear that future generations would be 

willing to trade environmental quality 

for consumption at the same rate as the 

current generations. Under imaginable 

assumptions, decisions based on costbenefit analysis with high discount rates 

might harm future generations—at least 

if investments are not made for the 

benefit of those generations. See Robert 

Lind, Analysis for Intergenerational 

Discounting, id. at 173, 176–177. It is 

also possible that the use of low 

discount rates for particular projects 

might itself harm future generations, by 

ensuring that resources are not used in 

a way that would greatly benefit them. 

In the context of climate change, 

questions of intergenerational equity are 

especially important. 

Reasonable arguments support the use 

of a 3 percent discount rate. First, that 

rate is among the two figures suggested 

by OMB guidance, and hence it fits with 

existing national policy. Second, it is 

standard to base the discount rate on the 

compensation that people receive for 

delaying consumption, and the 3 

percent is close to the risk-free rate of 

return, proxied by the return on long 

term inflation-adjusted U.S. Treasury 

Bonds, as of this writing. Although 

these rates are currently closer to 2.5 

percent, the use of 3 percent provides an 

adjustment for the liquidity premium 

that is reflected in these bonds’ returns. 

At the same time, others would argue 

that a 5 percent discount rate can be 

supported. The argument relies on 

several assumptions. First, that rate can 

also be justified by reference to the level 

of compensation for delaying 

consumption, because it fits with 

market behavior with respect to 

individuals’ willingness to trade-off 

consumption across periods as 

measured by the estimated post-tax 

average real returns to risky private 

investments (e.g., the S&P 500). In the 

climate setting, the 5 percent discount 

rate may be preferable to the riskless 

rate because it is based on risky 

investments and the return to projects to 

mitigate climate change is also risky. In 

contrast, the 3 percent riskless rate may 

be a more appropriate discount rate for 

Intergenerational Equity, Resources for the Future, 

Washington, DC. 
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49678 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

projects where the return is known with 

a high degree of confidence (e.g., 

highway guardrails). In principal, the 

correct discount rate would reflect the 

variance in payoff from climate 

mitigation policy and the correlation 

between the payoffs of the policy and 

the broader economy.528 

Second, 5 percent, and not 3 percent, 

is roughly consistent with estimates 

implied by reasonable inputs to the 

theoretically derived Ramsey equation, 

which specifies the optimal time path 

for consumption. That equation 

specifies the optimal discount rate as 

the sum of two components. The first 

term (the product of the elasticity of the 

marginal utility of consumption and the 

growth rate of consumption) reflects the 

fact that consumption in the future is 

likely to be higher than consumption 

today, so diminishing marginal utility 

implies that the same monetary damage 

will cause a smaller reduction of utility 

in the future. Standard estimates of this 

term from the economics literature are 

in the range of 3 percent–5 percent. The 

second component reflects the 

possibility that a lower weight should 

be placed on utility in the future, to 

account for social impatience or 

extinction risk, which is specified by a 

pure rate of time preference (PRTP). A 

common estimate of the PRTP is 2 

percent, though some observers believe 

that a principle of intergenerational 

equity suggests that the PRTP should be 

close to zero. It follows that discount 

rate of 5 percent is near the middle of 

the range of values that are able to be 

derived from the Ramsey equation. 

It is recognized that the arguments 

above—for use of market behavior and 

the Ramsey equation—face objections in 

the context of climate change, and of 

course there are alternative approaches. 

In light of climate change, it is possible 

that consumption in the future will not 

be higher than consumption today, and 

if so, the Ramsey equation will suggest 

a lower figure. However, the historical 

evidence is consistent with rising 

consumption over time. 

Some critics note that using observed 

interest rates for inter-generational 

decisions imposes current preferences 

on future generations, which some 

economists say may not be appropriate. 

For generational equity, they argue that 

the discount rate should be below 

market rates to correct for market 

distortions and inefficiencies in intergenerational transfers of wealth (which 

are presumed to compensate future 

generations for damage), and to treat 

generations equitably based on ethical 

principles (see Broome 2008).529 

Additionally, some analyses attempt 

to deal with uncertainty with respect to 

interest rates over time. We explore 

below how this might be done.530 

(2) Proposed Interim Estimates 

The application of the methodology 

outlined above yields interim estimates 

of the SCC that are reported in Table 

IV.C.3–2. These estimates are reported 

separately using 3 percent and 5 percent 

discount rates. The cells are empty in 

rows 10 and 11, because these studies 

did not report estimates of the SCC at 

a 3 percent discount rate. The modelweighted means are reported in the final 

or summary row; they are $33 per tCO2 

at a 3 percent discount rate and $5 per 

tCO2 with a 5 percent discount rate. 

TABLE IV.C.3–2—GLOBAL SOCIAL COST OF CARBON (SCC) ESTIMATES ($/tCO2 IN 2007 (2006$)), BASED ON 3% AND 

5% DISCOUNT RATES* 

Model Study Climate scenario 3% 5% 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

FUND ................................................. 

PAGE ................................................. 

PAGE ............................................... 

DICE ................................................. 

Anthoff et al. 2009 ................................... 

Anthoff et al. 2009 ................................... 

Anthoff et al. 2009 ................................... 

Link and Tol 2004 ................................... 

Link and Tol 2004 ................................... 

Guo et al. 2006 ....................................... 

Guo et al. 2006 ....................................... 

Guo et al. 2006 ....................................... 

Wahba & Hope 2006 ............................... 

Hope 2006 ............................................... 

Nordhaus 2008 ........................................ 

FUND default ........................................... 

SRES A1b ............................................... 

SRES A2 ................................................. 

No THC ................................................... 

THC continues ......................................... 

Constant PRTP ....................................... 

Gollier discount 1 .................................... 

Gollier discount 2 .................................... 

FUND Mean ............................................ 

A2-scen ................................................... 

.................................................................. 

.................................................................. 

6 

1 

9 

12 

12 

5 

14 

7 

8.25 

57 

.......... 

.......... 

¥1 

¥1 

¥1 

3 

2 

¥1 

0 

¥1 

0 

7 

7 

8 

528 Specifically, if the benefits of the policy are 

highly correlated with the returns from broader 

economy, then the market rate should be used to 

discount the benefits. If the benefits are 

uncorrelated with the broader economy the long 

term government bond rate should be applied. 

Furthermore, if the benefits are negatively 

correlated with the broader economy a rate less 

than that on long term government bonds should be 

used (Lind, 1982 pp. 89–90). 

529 See Arrow, K.J., W.R. Cline, K-G Maler, M. 

Munasinghe, R. Squiteri, J.E. Stiglitz, 1996. 

‘‘Intertemporal equity, discounting and economic 

efficiency,’’ in Climate Change 1995: Economic and 

Social Dimensions of Climate Change, Contribution 

of Working Group III to the Second Assessment 

Report of the Intergovernmental Panel on Climate 

Change. See also Weitzman, M.L., 1999. In Portney, 

P.R. and Weyant J.P. (eds.), Discounting and 

Intergenerational Equity, Resources for the Future, 

Washington, DC. 

530 Richard Newell and William Pizer, 

Discounting the distant future: how much do 

uncertain rates increase valuations? J. Environ. 

Econ. Manage. 46 (2003) 52–71. 

531 Most of the estimates in Table 1 rely on 

climate scenarios developed by the 

Intergovernmental Panel on Climate Change (IPCC). 

The IPCC published a new set of scenarios in 2000 

for use in the Third Assessment Report (Special 

Report on Emissions Scenarios—SRES). The SRES 

scenarios define four narrative storylines: A1, A2, 

B1 and B2, describing the relationships between the 

forces driving greenhouse gas and aerosol emissions 

and their evolution during the 21st century for large 

world regions and globally. Each storyline 

represents different demographic, social, economic, 

technological, and environmental developments 

that diverge in increasingly irreversible ways. The 

storylines are summarized in Nakicenovic et al., 

2000 (see also http://sedac.ciesin.columbia.edu/ 

ddc/sres/). Because the B1 and B2 storylines 

represent policy cases rather than business-as-usual 

projections, estimates derived from these scenarios 

to be less appropriate for use in benefit-cost 

analysis. They are therefore excluded. 

532 Guo et al. (2006) report estimates based on two 

Gollier discounting schemes. The Gollier 

discounting assumes complex specifications about 

individual utility functions and risk preferences. 

After various conditions are satisfied, declining 

social discount rates emerge. Gollier Discounting 

Scheme 1 employs a certainty-equivalent social rate 

of time preference (SRTP) derived by assuming the 

regional growth rate is equally likely to be 1% 

above or below the original forecast growth rate. 

Gollier Discounting Scheme 2 calculates a certaintyequivalent social rate of time preference (SRTP) 

using five possible growth rates, and applies the 

new SRTP instead of the original. Hope (2008) 

conducts Monte Carlo analysis on the PRTP 

component of the discount rate. The PRTP is 

modeled as a triangular distribution with a min 

value of 1%/yr, a most likely value of 2%/yr, and 

a max value of 3%/yr. 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49679 

TABLE IV.C.3–2—GLOBAL SOCIAL COST OF CARBON (SCC) ESTIMATES ($/tCO2 IN 2007 (2006$)), BASED ON 3% AND 

5% DISCOUNT RATES*—Continued 

Model Study Climate scenario 3% 5% 

Summary ................................................. .................................................................. Model-weighted Mean ............................. 33 5 

* The sample includes all peer reviewed, non-equity-weighted estimates included in Tol (2008), Nordhaus (2008), Hope (2008), and Anthoff et 

al. (2009), that are based on the most recent published version of FUND, PAGE, or DICE and use business-as-usual climate scenarios.531 532 All 

values are based on the best available information from the underlying studies about the base year and year dollars, rather than the Tol (2008) 

assumption that all estimates included in his review are 1995 values in 1995$. All values were updated to 2007 using a 3 percent annual growth 

rate in the SCC, and adjusted for inflation using GDP deflator. 

Analyses have been conducted at $33 

and $5 as these represent the estimates 

associated with the 3 percent and 5 

percent discount rates, respectively.533 

The 3 percent and 5 percent estimates 

have independent appeal, and at this 

time a clear preference for one over the 

other is not warranted. Thus, we have 

also included—and centered our current 

attention on—the average of the 

estimates associated with these discount 

rates, which is $19. (Based on the $19 

global value, the approximate domestic 

fraction of these benefits would be $1.14 

per ton of CO2 assuming that domestic 

benefits are 6 percent of the global 

benefits. 

It is true that there is uncertainty 

about interest rates over long time 

horizons. Recognizing that point, 

Newell and Pizer (2003) have made a 

careful effort to adjust for that 

uncertainty. The Newell-Pizer approach 

models discount rate uncertainty as 

something that evolves over time.534 

This is a relatively recent contribution 

to the literature, and estimates based on 

this method are included with the aim 

of soliciting comment. 

There are several concerns with using 

this approach in this context. First, it 

would be a departure from current OMB 

guidance. Second, an approach that 

would average what emerges from 

discount rates of 3 percent and 5 

percent reflects uncertainty about the 

discount rate, but based on a different 

model of uncertainty. The Newell-Pizer 

approach models discount rate 

uncertainty as something that evolves 

over time; in contrast, the preferred 

approach (outlined above) assumes that 

there is a single discount rate with equal 

probability of 3 percent and 5 percent. 

Table IV.C.3–3 reports on the 

application of the Newell-Pizer 

adjustments. The precise numbers 

depend on the assumptions about the 

data generating process that governs 

interest rates. Columns (1a) and (1b) 

assume that ‘‘random walk’’ model best 

describes the data and uses 3 percent 

and 5 percent discount rates, 

respectively. Columns (2a) and (2b) 

repeat this, except that it assumes a 

‘‘mean-reverting’’ process. While the 

empirical evidence does not rule out a 

mean-reverting model, Newell and Pizer 

find stronger empirical support for the 

random walk model. 

TABLE IV.C.3–3—GLOBAL SOCIAL COST OF CARBON (SCC) ESTIMATES ($/tCO2 IN 2007 (2006$))*, USING NEWELL & 


PIZER (2003) ADJUSTMENT FOR FUTURE DISCOUNT RATE UNCERTAINTY** 


Model Study Climate scenario 

Random-walk 

model 

Meanreverting 

model 

3% 

(1a) 

5% 

(1b) 3% 

(2a) 

5% 

(2b) 

1 FUND ........................... Anthoff et al. 2009 ................................ FUND default ........................................ 10 0 7 ¥1 

2 FUND ........................... Anthoff et al. 2009 ................................ SRES A1b ............................................. 2 0 1 ¥1 

3 FUND ........................... Anthoff et al. 2009 ................................ SRES A2 ............................................... 15 0 10 ¥1 

4 FUND ........................... Link and Tol 2004 ................................. No THC ................................................. 20 6 13 4 

5 FUND ........................... Link and Tol 2004 ................................. THC continues ...................................... 20 4 13 2 

6 FUND ........................... Guo et al. 2006 ..................................... Constant PRTP ..................................... 9 0 6 ¥1 

7 FUND ........................... Guo et al. 2006 ..................................... Gollier discount 1 .................................. 14 0 14 0 

8 FUND ........................... Guo et al. 2006 ..................................... Gollier discount 2 .................................. 

FUND Mean .......................................... 

7 

12 

¥1 

1 

7 

9 

¥1 

0 

9 PAGE ........................... Wahba & Hope 2006 ............................ A2-scen ................................................. 97 13 63 8 

10 PAGE ......................... Hope 2006 ............................................ ............................................................... .......... 13 .......... 8 

11 DICE .......................... Nordhaus 2008 ..................................... ............................................................... .......... 15 .......... 9 

Summary ........................... ............................................................... Model-weighted Mean .......................... 55 10 36 6 

* The sample includes all peer reviewed, non-equity-weighted estimates included in Tol (2008), Nordhaus (2008), Hope (2008), and Anthoff et 

al. (2009), that are based on the most recent published version of FUND, PAGE, or DICE and use business-as-usual climate scenarios. All values are based on the best available information from the underlying studies about the base year and year dollars, rather than the Tol (2008) assumption that all estimates included in his review are 1995 values in 1995$. All values were updated to 2007 using a 3 percent annual growth 

rate in the SCC, and adjusted for inflation using GDP deflator. See the Notes to Table 1 for further details. 

** Assumes a starting discount rate of 3 percent or 5 percent. Newell and Pizer (2003) based adjustment factors are not applied to estimates 

from Guo et al. (2006) that use a different approach to account for discount rate uncertainty (rows 7–8). 

Note that the correction factor from Newell and Pizer is based on the DICE model. The proper adjustment may differ for other integrated assessment models that produce different time schedules of marginal damages. We would expect this difference to be minor. 

533 It should be noted that reported discount rates assumptions about the individual components of represented by a probability distribution. The 

may not be consistently derived across models or the Ramsey equation identified earlier. Newell and Pizer, and Weitzman approaches are 

specific applications of models: While the discount 534 In contrast, an alternative approach based on relatively recent contributions, and we invite 

rate may be identical, it may reflect different Weitzman (2001) would assume that there is a comment on the advantages and disadvantages of 

constant discount rate that is uncertain and each. 
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49680 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

The resulting estimates of the social 

cost of carbon are necessarily greater. 

When the adjustments from the random 

walk model are applied, the estimates of 

the social cost of carbon are $10 and $55 

per ton of CO2, with the 5 percent and 

3 percent discount rates, respectively. 

The application of the mean-reverting 

adjustment yields estimates of $6 and 

$36. Relying on the random walk model, 

analyses are also conducted with the 

value of the SCC set at $10 and $55. 

(3) Caveats 

There are at least four caveats to the 

approach outlined above. 

First, the impacts of climate change 

are expected to be widespread, diverse, 

and heterogeneous. In addition, the 

exact magnitude of these impacts is 

uncertain, because of the inherent 

randomness in the Earth’s atmospheric 

processes, the U.S. and global 

economies, and the behaviors of current 

and future populations. Current IAM do 

not currently individually account for 

and assign value to all of the important 

physical and other impacts of climate 

change that are recognized in the 

climate change literature. Although it is 

likely that our capability to quantify and 

monetize impacts will improve with 

time, it is also likely that even in future 

applications, there are a number of 

potentially significant benefits 

categories that will remain 

unmonetized. 

Second, in the opposite direction, it is 

unlikely that the damage estimates 

adequately account for the directed 

technological change that climate 

change will cause. In particular, climate 

change will increase the return on 

investment to develop technologies that 

allow individuals to better cope with 

climate change. For example, it is likely 

that scientists will develop crops that 

are better able to withstand high 

temperatures. In this respect, the current 

estimates may overstate the likely 

damages. 

Third, there has been considerable 

recent discussion of the risk of 

catastrophic impacts and of how best to 

account for worst-case scenarios. Recent 

research by Weitzman (2009) specifies 

some conditions under which the 

possibility of catastrophe would 

undermine the use of IAMs and 

conventional cost-benefit analysis. This 

research requires further exploration 

before its generality is known and the 

optimal way to incorporate it into 

regulatory reviews is understood. 

Fourth, it is also worth noting that the 

SCC estimates are only relevant for 

incremental policies relative to the 

projected baselines, which capture 

business-as-usual scenarios. To evaluate 

non-marginal changes, such as might 

occur if the U.S. acts in tandem with 

other nations, then it might be necessary 

to go beyond the simple expedient of 

using the SCC along the BAU path. In 

particular, it would be correct to 

calculate the aggregate WTP to move 

from the BAU scenario to the policy 

scenario, without imposing the 

restriction that the marginal benefit 

remains constant over this range. 

All of the values derived from this 

process are expressed in 2006 dollars. 

NHTSA has adjusted them to their 

equivalent values in 2007 dollars for 

consistency with other values used in 

its analysis of benefits from adopting 

higher CAFE standards for MY 2012– 

2016 passenger cars and light trucks. 

The resulting value upon which we 

have centered our analysis, which is 

derived from the figures reported in the 

tables above, is equivalent to $20 per 

metric ton of CO2 emissions avoided 

when expressed in 2007$, and the 

agency has relied on this value in its 

analysis. NHTSA has also analyzed the 

sensitivity of its benefit estimates to 

alternative values of $5, $10, $34, and 

$56 per metric ton of CO2 emissions 

avoided, with all figures again in 2007$. 

Each of these values applies to 

emissions during 2007, and are assumed 

to grow in real terms by 3 percent 

annually beginning in 2007. NHTSA 

seeks comments on these values and the 

approach used to derive them. 

m. Discounting Future Benefits and 

Costs 

Discounting future fuel savings and 

other benefits is intended to account for 

the reduction in their value to society 

when they are deferred until some 

future date, rather than received 

immediately. The discount rate 

expresses the percent decline in the 

value of these benefits—as viewed from 

today’s perspective—for each year they 

are deferred into the future. In 

evaluating the benefits from alternative 

increases in CAFE standards for MY 

2012–2016 passenger cars and light 

trucks, NHTSA has employed a 

discount rate of 3 percent per year. The 

agency has also tested the sensitivity of 

these benefit and cost estimates to the 

use of a 7 percent discount rate. 

Although these are the same discount 

rates analyzed in the MY 2011 final 

rule, NHTSA has chosen to use 3 

percent as the basis for the Reference 

Case in this proposed rule rather than 

the 7 percent rate it employed 

previously, for the reasons discussed 

below. 

The primary reason that NHTSA has 

selected 3 percent as the appropriate 

rate for discounting future benefits from 

increased CAFE standards is that most 

or all of vehicle manufacturers’ costs for 

complying with higher CAFE standards 

are likely to be reflected in higher sales 

prices for their new vehicle models. By 

increasing sales prices for new cars and 

light trucks, CAFE regulation will thus 

primarily affect vehicle purchases and 

other private consumption decisions. 

Both economic theory and OMB 

guidance on discounting indicate that 

the future benefits and costs of 

regulations that mainly affect private 

consumption should be discounted at 

the social rate of time preference.535 

OMB guidance also indicates that 

savers appear to discount future 

consumption at an average real (that is, 

adjusted to remove the effect of 

inflation) rate of about 3 percent when 

they face little risk about its likely level. 

Since the real rate that savers use to 

discount future consumption represents 

a reasonable estimate of the social rate 

of time preference, NHTSA has 

employed the 3 percent rate to discount 

projected future benefits and costs 

resulting from higher CAFE standards 

for MY 2012–2016 passenger cars and 

light trucks.536 

Because there is some uncertainty 

about the extent to which vehicle 

manufacturers will be able to recover 

their costs for complying with higher 

CAFE standards by increasing vehicle 

sales prices, however, NHTSA has also 

tested the sensitivity of these benefit 

and cost estimates to the use of a higher 

percent discount rate. OMB guidance 

indicates that the real economy-wide 

opportunity cost of capital is the 

appropriate discount rate to apply to 

future benefits and costs when the 

primary effect of a regulation is ‘‘* * * 

to displace or alter the use of capital in 

the private sector,’’ and estimates that 

this rate currently averages about 7 

percent.537 Thus the agency has also 

tested the sensitivity of its benefit and 

cost estimates for alternative MY 2012– 

2016 CAFE standards to the use of a 7 

percent real discount rate. NHTSA seeks 

comment on whether it should evaluate 

CAFE standards using a discount rate of 

3 percent, 7 percent, or an alternative 

value. 

n. Accounting for Uncertainty in 

Benefits and Costs 

In analyzing the uncertainty 

surrounding its estimates of benefits and 

costs from alternative CAFE standards, 

535 Id. 

536 Office of Management and Budget, Circular A– 

4, ‘‘Regulatory Analysis,’’ September 17, 2003, 33. 

Available at http://www.whitehouse.gov/omb/ 

circulars/a004/a-4.pdf (last accessed August 9, 

2009). 

537 Id. 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49681 

NHTSA has considered alternative 

estimates of those assumptions and 

parameters likely to have the largest 

effect. These include the projected costs 

of fuel economy-improving technologies 

and their expected effectiveness in 

reducing vehicle fuel consumption, 

forecasts of future fuel prices, the 

magnitude of the rebound effect, the 

reduction in external economic costs 

resulting from lower U.S. oil imports, 

the value to the U.S. economy of 

reducing carbon dioxide emissions, and 

the discount rate applied to future 

benefits and costs. The range for each of 

these variables employed in the 

uncertainty analysis is presented in the 

section of this notice discussing each 

variable. 

The uncertainty analysis was 

conducted by assuming independent 

normal probability distributions for 

each of these variables, using the low 

and high estimates for each variable as 

the values below which 5 percent and 

95 percent of observed values are 

believed to fall. Each trial of the 

uncertainty analysis employed a set of 

values randomly drawn from each of 

these probability distributions, 

assuming that the value of each variable 

is independent of the others. Benefits 

and costs of each alternative standard 

were estimated using each combination 

of variables. A total of 1,000 trials were 

used to establish the likely probability 

distributions of estimated benefits and 

costs for each alternative standard. 

o. Where Can Readers Find More 

Information About the Economic 

Assumptions? 

Much more detailed information is 

provided in Chapter VIII of the PRIA, 

and a discussion of how NHTSA and 

EPA jointly reviewed and updated 

economic assumptions for purposes of 

this NPRM is available in Chapter 4 of 

the TSD. In addition, all of NHTSA’s 

model input and output files are now 

public and available for the reader’s 

review and consideration. The 

economic input files can be found in the 

docket for this NPRM, NHTSA–2009– 

0059, and on NHTSA’s Web site. 

Finally, because much of NHTSA’s 

economic analysis for purposes of this 

NPRM builds on the work that was done 

for the MY 2011 final rule, we refer 

readers to that document as well for 

background information concerning 

how NHTSA’s assumptions regarding 

economic inputs for CAFE analysis have 

evolved over the past several 

rulemakings, both in response to 

comments and as a result of the agency’s 

growing experience with this type of 

analysis.538 

4. How Does NHTSA Use the 

Assumptions in Its Modeling Analysis? 

In developing today’s proposed CAFE 

standards, NHTSA has made significant 

use of results produced by the CAFE 

Compliance and Effects Model 

(commonly referred to as ‘‘the CAFE 

model’’ or ‘‘the Volpe model’’), which 

DOT’s Volpe National Transportation 

Systems Center developed specifically 

to support NHTSA’s CAFE rulemakings. 

The model, which has been constructed 

specifically for the purpose of analyzing 

potential CAFE standards, integrates the 

following core capabilities: 

(1) Estimating how manufacturers 

could apply technologies in response to 

new fuel economy standards, 

(2) Estimating the costs that would be 

incurred in applying these technologies, 

(3) Estimating the physical effects 

resulting from the application of these 

technologies, such as changes in travel 

demand, fuel consumption, and 

emissions of carbon dioxide and criteria 

pollutants, and 

(4) Estimating the monetized societal 

benefits of these physical effects. 

An overview of the model follows 

below. Separate model documentation 

provides a detailed explanation of the 

functions the model performs, the 

calculations it performs in doing so, and 

how to install the model, construct 

inputs to the model, and interpret the 

model’s outputs. Documentation of the 

model, along with model installation 

files, source code, and sample inputs are 

available at NHTSA’s web site. The 

model documentation is also available 

in the docket for today’s proposed rule, 

as are inputs for and outputs from 

analysis of today’s proposed CAFE 

standards. 

a. How Does the Model Operate? 

As discussed above, the agency uses 

the Volpe model to estimate the extent 

to which manufacturers could attempt 

to comply with a given CAFE standard 

by adding technology to fleets that the 

agency anticipates they will produce in 

future model years. This exercise 

constitutes a simulation of 

manufacturers’ decisions regarding 

compliance with CAFE standards. 

This compliance simulation begins 

with the following inputs: (a) The 

baseline market forecast discussed 

above in Section IV.C.1, (b) technologyrelated estimates discussed above in 

Section IV.C.2, (c) economic inputs 

discussed above in Section IV.C.3, and 

(d) inputs defining the characteristics of 

538 74 FR 14308–14358 (Mar. 30, 2009). 

potential new CAFE standards. For each 

manufacturer, the model applies 

technologies in a sequence that follows 

a defined engineering logic (‘‘decision 

trees’’ discussed in the MY 2011 final 

rule and in the model documentation) 

and a cost-minimizing strategy in order 

to identify a set of technologies the 

manufacturer could apply in response to 

new CAFE standards. The model 

applies technologies to each of the 

projected individual vehicles in a 

manufacturer’s fleet, until one of three 

things occurs: 

(1) The manufacturer’s fleet achieves 

compliance with the applicable 

standard; 

(2) The manufacturer ‘‘exhausts’’ 539 

available technologies; or 

(3) For manufacturers estimated to be 

willing to pay civil penalties, the 

manufacturer reaches the point at which 

doing so would be more cost-effective 

(from the manufacturer’s perspective) 

than adding further technology.540 

As discussed below, the model has 

also been modified in order to apply 

additional technology in early model 

years if doing so will facilitate 

compliance in later model years. 

The model accounts explicitly for 

each model year, applying most 

technologies when vehicles are 

scheduled to be redesigned or 

freshened, and carrying forward 

technologies between model years. The 

CAFE model accounts explicitly for 

each model year because EPCA requires 

that NHTSA make a year-by-year 

determination of the appropriate level of 

539 In a given model year, the model makes 

additional technologies available to each vehicle 

model within several constraints, including (a) 

whether or not the technology is applicable to the 

vehicle model’s technology class, (b) whether the 

vehicle is undergoing a redesign or freshening in 

the given model year, (c) whether engineering 

aspects of the vehicle make the technology 

unavailable (e.g., secondary axle disconnect cannot 

be applied to two-wheel drive vehicles), and (d) 

whether technology application remains within 

‘‘phase in caps’’ constraining the overall share of a 

manufacturer’s fleet to which the technology can be 

added in a given model year. Once enough 

technology is added to a given manufacturer’s fleet 

in a given model year that these constraints make 

further technology application unavailable, 

technologies are exhausted for that manufacturer in 

that model year. 

540 This possibility was added to the model to 

account for the fact that under EPCA/EISA, 

manufacturers must pay fines if they do not achieve 

compliance with applicable CAFE standards. 49 

U.S.C. 32912(b). NHTSA recognizes that some 

manufacturers will find it more cost-effective to pay 

fines than to achieve compliance, and believes that 

to assume these manufacturers would exhaust 

available technologies before paying fines would 

cause unrealistically high estimates of market 

penetration of expensive technologies such as 

diesel engines and strong hybrid electric vehicles, 

as well as correspondingly inflated estimates of 

both the costs and benefits of any potential CAFE 

standards. 
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49682 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

stringency and then set the standard at 

that level, while ensuring ratable 

increases in average fuel economy.541 

The model also calculates the costs, 

effects, and benefits of technologies that 

it estimates could be added in response 

to a given CAFE standard.542 It 

calculates costs by applying the cost 

estimation techniques discussed above 

in Section IV.C.2, and by accounting for 

the number of affected vehicles. It 

accounts for effects such as changes in 

vehicle travel, changes in fuel 

consumption, and changes in 

greenhouse gas and criteria pollutant 

emissions. It does so by applying the 

fuel consumption estimation techniques 

also discussed in Section IV.C.2, and the 

vehicle survival and mileage 

accumulation forecasts, the rebound 

effect estimate and the fuel properties 

and emission factors discussed in 

Section IV.C.3. Considering changes in 

travel demand and fuel consumption, 

the model estimates the monetized 

value of accompanying benefits to 

society, as discussed in Section IV.C.3. 

The model calculates both the 

undiscounted and discounted value of 

benefits that accrue over time in the 

future. 

The Volpe model has other 

capabilities that facilitate the 

development of a CAFE standard. It can 

be used to fit a mathematical function 

forming the basis for an attribute-based 

CAFE standard, following the steps 

described below. It can also be used to 

evaluate many (e.g., 200 per model year) 

potential levels of stringency 

sequentially, and identify the stringency 

at which specific criteria are met. For 

example, it can identify the stringency 

at which net benefits to society are 

maximized, the stringency at which a 

specified total cost is reached, or the 

stringency at which a given average 

required fuel economy level is attained. 

This allows the agency to compare more 

easily the impacts in terms of fuel 

541 49 U.S.C. 32902(a) states that at least 18 

months before the beginning of each model year, 

the Secretary of Transportation shall prescribe by 

regulation average fuel economy standards for 

automobiles manufactured by a manufacturer in 

that model year, and that each standard shall be the 

maximum feasible average fuel economy level that 

the Secretary decides the manufacturers can 

achieve in that year. NHTSA has long interpreted 

this statutory language to require year-by-year 

assessment of manufacturer capabilities. 49 U.S.C. 

32902(b)(2)(C) also requires that standards increase 

ratably between MY 2011 and MY 2020. 

542 As for all of its other rulemakings, NHTSA is 

required by Executive Order 12866 and DOT 

regulations to analyze the costs and benefits of 

CAFE standards. Executive Order 12866, 58 FR 

51735 (Oct. 4, 1993); DOT Order 2100.5, 

‘‘Regulatory Policies and Procedures,’’ 1979, 

available at http://regs.dot.gov/ 

rulemakingrequirements.htm (last accessed August 

21, 2009). 

savings, emissions reductions, and costs 

and benefits of achieving different levels 

of stringency according to different 

criteria. The model can also be used to 

perform uncertainty analysis (i.e., 

Monte Carlo simulation), in which input 

estimates are varied randomly according 

to specified probability distributions, 

such that the uncertainty of key 

measures (e.g., fuel consumption, costs, 

benefits) can be evaluated. 

b. Has NHTSA Considered Other 

Models? 

Nothing in EPCA requires NHTSA to 

use the Volpe model. In principle, 

NHTSA could perform all of these tasks 

through other means. For example, in 

developing the standards proposed 

today, the agency did not use the Volpe 

model’s curve fitting routines, because 

they could not be modified in time to 

reflect the change in the mathematical 

function defining the proposed CAFE 

standards. The Volpe model may be 

modified to do so for the final rule, 

although the agency can also continue 

to fit the mathematical function outside 

the model. In general, though, these 

model capabilities have greatly 

increased the agency’s ability to rapidly, 

systematically, and reproducibly 

conduct key analyses relevant to the 

formulation and evaluation of new 

CAFE standards. 

During its previous rulemaking, 

which led to the final MY 2011 

standards promulgated earlier this year, 

NHTSA received comments from the 

Alliance and CARB encouraging 

NHTSA to examine the usefulness of 

other models. As discussed in that final 

rule, NHTSA, having undertaken such 

consideration, concluded that the Volpe 

model is a sound and reliable tool for 

the development and evaluation of 

potential CAFE standards.543 

In reconsidering and reaffirming this 

conclusion for purposes of this NPRM, 

NHTSA notes that the Volpe model not 

only has been formally peer-reviewed 

and tested through three rulemakings, 

but also has some features especially 

important for the analysis of CAFE 

standards under EPCA/EISA. Among 

these are the ability to perform year-byyear analysis, and the ability to account 

for engineering differences between 

specific vehicle models. 

EPCA requires that NHTSA set CAFE 

standards for each model year at the 

level appropriate for that year.544 Doing 

so requires the ability to analyze each 

model year and, when developing 

regulations covering multiple model 

years, to account for the 

543 74 FR 14372 (Mar. 30, 2009). 


544 49 U.S.C. 32902(a). 


interdependency of model years in 

terms of the appropriate levels of 

stringency for each one. Also, as part of 

the evaluation of the economic 

practicability of the standards, as 

required by EPCA, NHTSA has 

traditionally assessed the annual costs 

and benefits of the standards as it is 

permitted to do so. The first (2002) 

version of DOT’s model treated each 

model year separately, and did not 

perform this type of explicit accounting. 

Manufacturers took strong exception to 

these shortcomings. For example, GM 

commented in 2002 that ‘‘although the 

table suggests that the proposed 

standard for MY 2007, considered in 

isolation, promises benefits exceeding 

costs, that anomalous outcome is merely 

an artifact of the peculiar Volpe 

methodology, which treats each year 

independently of any other * * *.’’ In 

2002, GM also criticized DOT’s analysis 

for, in some cases, adding a technology 

in MY 2006 and then replacing it with 

another technology in MY 2007. GM 

(and other manufacturers) argued that 

this completely failed to represent true 

manufacturer product-development 

cycles, and therefore could not be 

technologically feasible or economically 

practicable. 

In response to these concerns, and 

related concerns expressed by other 

manufacturers, DOT modified the CAFE 

model in order to account for 

dependencies between model years and 

to better represent manufacturers’ 

planning cycles, in a way that still 

allowed NHTSA to comply with the 

statutory requirement to determine the 

appropriate level of the standards for 

each model year. This was 

accomplished by limiting the 

application of many technologies to 

model years in which vehicle models 

are scheduled to be redesigned (or, for 

some technologies, ‘‘freshened’’), and by 

causing the model to ‘‘carry forward’’ 

applied technologies from one model 

year to the next. 

During the recent rulemaking for MY 

2011 passenger cars and light trucks, 

DOT further modified the CAFE model 

to account for cost reductions 

attributable to ‘‘learning effects’’ related 

to volume (i.e., economies of scale) and 

the passage of time (i.e., time-based 

learning), both of which evolve on yearby-year basis. These changes were 

implemented in response to comments 

by environmental groups and other 

stakeholders. 

The Volpe model is also able to 

account for important engineering 

differences between specific vehicle 

models, and to thereby reduce the risk 

of applying technologies that may be 

incompatible with or already present on 
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a given vehicle model. Some 

commenters have previously suggested 

that manufacturers are most likely to 

broadly apply generic technology 

‘‘packages,’’ and the Volpe model does 

tend to form ‘‘packages’’ dynamically, 

based on vehicle characteristics, 

redesign schedules, and schedules for 

increases in CAFE standards. For 

example, under the proposed CAFE 

standards for passenger cars, the CAFE 

model estimated that manufacturers 

could apply turbocharged SGDI engines 

mated with dual-clutch AMTs to 1.8 

million passenger cars in MY 2016, 

about 16 percent of the MY 2016 

passenger car fleet. Recent 

modifications to the model, discussed 

below, to represent multi-year planning, 

increase the model’s tendency to add 

relatively cost-effective technologies 

when vehicles are estimated to be 

redesigned, and thereby increase the 

model’s tendency to form such 

packages. 

On the other hand, some 

manufacturers have indicated that 

especially when faced with significant 

progressive increases in the stringency 

of new CAFE standards, they are likely 

to also look for narrower opportunities 

to apply specific technologies. By 

progressively applying specific 

technologies to specific vehicle models, 

the CAFE model also produces such 

outcomes. For example, under the 

proposed CAFE standards for passenger 

cars, the CAFE model estimated that in 

MY 2012, some manufacturers could 

find it advantageous to apply SIDI to 

some vehicle models without also 

adding turbochargers. 

By following this approach of 

combining technologies incrementally 

and on a model-by-model basis, the 

CAFE model is able to account for 

important engineering differences 

between vehicle models and avoid 

unlikely technology combinations. For 

example, the model does not apply 

dual-clutch AMTs (or strong hybrid 

systems) to vehicle models with 6-speed 

manual transmissions. Some vehicle 

buyers prefer a manual transmission; 

this preference cannot be assumed 

away. The model’s accounting for 

manual transmissions is also important 

for vehicles with larger engines: For 

example, cylinder deactivation cannot 

be applied to vehicles with manual 

transmissions, because there is no 

reliable means of predicting when the 

driver will change gears. By retaining 

cylinder deactivation as a specific 

technology rather than part of a predetermined package and by retaining 

differentiation between vehicles with 

different transmissions, DOT’s model is 

able to target cylinder deactivation only 

to vehicle models for which it is 

technologically feasible. 

The Volpe model also produces a 

single vehicle-level output file that, for 

each vehicle model, shows which 

technologies were present at the outset 

of modeling, which technologies were 

superseded by other technologies, and 

which technologies were ultimately 

present at the conclusion of modeling. 

For each vehicle, the same file shows 

resultant changes in vehicle weight, fuel 

economy, and cost. This provides for 

efficient identification, analysis, and 

correction of errors, a task with which 

the public can now assist the agency, 

since all inputs and outputs are public. 

Such considerations, as well as those 

related to the efficiency with which the 

Volpe model is able to analyze attributebased CAFE standards and changes in 

vehicle classification, and to perform 

higher-level analysis such as stringency 

estimation (to meet predetermined 

criteria), sensitivity analysis, and 

uncertainty analysis, lead the agency to 

conclude that the model remains the 

best available to the agency for the 

purposes of analyzing potential new 

CAFE standards. 

c. What Changes Has DOT Made to the 

Model? 

Prior to being used for analysis 

supporting today’s proposal, the Volpe 

model was revised to make some minor 

improvements, and to add one 

significant new capability: the ability to 

simulate manufacturers’ ability to 

engage in ‘‘multi-year planning.’’ Multiyear planning refers to the fact that 

when redesigning or freshening 

vehicles, manufacturers can anticipate 

future fuel economy or CO2 standards, 

and add technologies accounting for 

these standards. For example, a 

manufacturer might choose to overcomply in a given model year when 

many vehicle models are scheduled for 

redesign, in order to facilitate 

compliance in a later model year when 

standards will be more stringent yet few 

vehicle models are scheduled for 

redesign.545 Prior comments have 

indicated that the Volpe model, by not 

representing such manufacturer choices, 

tended to overestimate compliance 

costs. However, because of the technical 

complexity involved in representing 

these choices when, as in the Volpe 

model, each model year is accounted for 

separately and explicitly, the model 

could not be modified to add this 

545 Although a manufacturer may, in addition, 

generate CAFE credits in early model years for use 

in later model years (or, less likely, in later years 

for use in early years), EPCA does not allow 

NHTSA, when setting CAFE standards, to account 

for manufacturers’ use of CAFE credits. 

capability prior to the statutory deadline 

for the MY 2011 final standards. 

The model now includes this 

capability, and NHTSA has applied it in 

analyzing the standards proposed today. 

Consequently, this often produces 

results indicating that manufacturers 

could over-comply in some model years 

(with corresponding increases in costs 

and benefits in those model years) and 

thereby ‘‘carry forward’’ technology into 

later model years in order to reduce 

compliance costs in those later model 

years. NHTSA believes this better 

represents how manufacturers would 

actually respond to new CAFE 

standards, and thereby produces more 

realistic estimates of the costs and 

benefits of such standards. 

The Volpe model has also been 

modified to accommodate inputs 

specifying the amount of CAFE credit to 

be applied to each manufacturer’s fleet. 

Although the model is not currently 

capable of estimating manufacturers’ 

decisions regarding the generation and 

use of CAFE credits, and EPCA does not 

allow NHTSA, in setting CAFE 

standards, to take into account 

manufacturers’ potential use of credits, 

this additional capability in the Volpe 

model provides a basis for more 

accurately estimating costs, effects, and 

benefits that may actually result from 

new CAFE standards. Insofar as some 

manufacturers actually do earn and use 

CAFE credits, this provides NHTSA 

with some ability to examine outcomes 

more realistically than EPCA allows for 

purposes of setting new CAFE 

standards. 

In comments on recent NHTSA 

rulemakings, some reviewers have 

suggested that the Volpe model should 

be modified to estimate the extent to 

which new CAFE standards would 

induce changes in the mix of vehicles in 

the new vehicle fleet. NHTSA, like EPA, 

agrees that a ‘‘market shift’’ model, also 

called a consumer vehicle choice model, 

could provide useful information 

regarding the possible effects of 

potential new CAFE standards. An 

earlier experimental version of the 

Volpe model included a multinomial 

logit model that estimated changes in 

sales resulting from CAFE-induced 

increases in new vehicle fuel economy 

and prices. A fuller description of this 

attempt can be found in Section V of the 

PRIA. However, NHTSA has thus far 

been unable to develop credible 

coefficients specifying such a model. In 

addition, as discussed in Section II.H.4, 

such a model is sensitive to the 

coefficients used in it, and there is great 

variation over some key values of these 

coefficients in published studies. 

NHTSA seeks comment on ways to 
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improve on this earlier work and 

develop this capability effectively. If the 

agency is able to do so prior to 

conducting analysis supporting 

decisions regarding final CAFE 

standards, it will attempt to reintegrate 

this capability in the Volpe model and 

include these effects in its analysis of 

final standards. If not, NHTSA will 

continue efforts to develop and make 

use of this capability in future 

rulemakings. 

d. Does the Model Set the Standards? 

Although NHTSA currently uses the 

Volpe model as a tool to inform its 

consideration of potential CAFE 

standards, the Volpe model does not 

determine the CAFE standards that 

NHTSA proposes or promulgates as 

final regulations. The results it produces 

are completely dependent on inputs 

selected by NHTSA, based on the best 

available information and data available 

in the agency’s estimation at the time 

standards are set. Although the model 

has been programmed in previous 

rulemakings to estimate at what 

stringency net benefits are maximized, 

NHTSA has not done so here and has 

instead used the Volpe model to 

estimate stringency levels that produce 

roughly constant rates of increase in the 

combined average required fuel 

economy. Ultimately, NHTSA’s 

selection of a CAFE standard is 

governed and guided by the statutory 

requirements of EPCA, as amended by 

EISA: NHTSA sets the standard at the 

maximum feasible average fuel economy 

level that it determines is achievable 

during a particular model year, 

considering technological feasibility, 

economic practicability, the effect of 

other standards of the Government on 

fuel economy, and the need of the 

nation to conserve energy. 

NHTSA considers the results of 

analyses conducted by the Volpe model 

and analyses conducted outside of the 

Volpe model, including analysis of the 

impacts of carbon dioxide and criteria 

pollutant emissions, analysis of 

technologies that may be available in 

the long term and whether NHTSA 

could expedite their entry into the 

market through these standards, and 

analysis of the extent to which changes 

in vehicle prices and fuel economy 

might affect vehicle production and 

sales. Using all of this information—not 

solely that from the Volpe model—the 

agency considers the governing 

statutory factors, along with 

environmental issues and other relevant 

societal issues such as safety, and 

promulgates the standards based on its 

best judgment on how to balance these 

factors. 

This is why the agency considered 

eight regulatory alternatives, only one of 

which reflects the agency’s proposed 

standards, based on the agency’s 

determinations and assumptions. Others 

assess alternative standards, some of 

which exceed the proposed standards 

and/or the point at which net benefits 

are maximized. These comprehensive 

analyses, which also included scenarios 

with different economic input 

assumptions as presented in the FEIS 

and FRIA, are intended to inform and 

contribute to the agency’s consideration 

of the ‘‘need of the United States to 

conserve energy,’’ as well as the other 

statutory factors. 49 U.S.C. 32902(f). 

Additionally, the agency’s analysis 

considers the need of the nation to 

conserve energy by accounting for 

economic externalities of petroleum 

consumption and monetizing the 

economic costs of incremental CO2 

emissions in the social cost of carbon. 

NHTSA uses information from the 

model when considering what standards 

to propose and finalize, but the model 

does not determine the standards. 

e. How Does NHTSA Make the Model 

Available and Transparent? 

Model documentation, which is 

publicly available in the rulemaking 

docket and on NHTSA’s web site, 

explains how the model is installed, 

how the model inputs (all of which are 

available to the public) 546 and outputs 

are structured, and how the model is 

used. The model can be used on any 

Windows-based personal computer with 

Microsoft Office 2003 and the Microsoft 

.NET framework installed (the latter 

available without charge from 

Microsoft). The executable version of 

the model and the underlying source 

code are also available at NHTSA’s Web 

site. The input files used to conduct the 

core analysis documented in this 

proposed rule are available in the public 

docket. With the model and these input 

files, anyone is capable of 

independently running the model to 

repeat, evaluate, and/or modify the 

agency’s analysis. 

5. How Did NHTSA Develop the Shape 

of the Target Curves for the Proposed 

Standards? 

In developing the shape of the target 

curves for today’s proposed standards, 

NHTSA took a new approach, primarily 

in response to comments received in the 

MY 2011 rulemaking. NHTSA’s 

authority under EISA allows 

546 We note, however, that files from any 

supplemental analysis conducted that relied in part 

on confidential manufacturer product plans cannot 

be made public, as prohibited under 49 CFR part 

512. 

consideration of any ‘‘attribute related 

to fuel economy’’ and any 

‘‘mathematical function.’’ While the 

attribute, footprint, is the same for these 

proposed standards as the attribute used 

for the MY 2011 standards, the 

mathematical function is new. 

Both vehicle manufacturers and 

public interest groups expressed 

concern in the MY 2011 rulemaking 

process that the constrained logistic 

function, particularly the function for 

the passenger car standards, was overly 

steep and could lead, on the one hand, 

to fuel economy targets that were overly 

stringent for small footprint vehicles, 

and on the other hand, to a greater 

incentive for manufacturers to upsize 

vehicles in order to reduce their 

compliance obligation (because largerfootprint vehicles have less stringent 

targets) in ways that could compromise 

energy and environmental benefits. We 

tentatively believe that the constrained 

linear function developed here 

significantly mitigates steepness 

concerns, but we seek comment on 

whether readers agree, and whether 

there are any other issues relating to the 

new approach that NHTSA should 

consider in developing the curves for 

the final rule. 

a. Standards Are Attribute-Based and 

Defined by a Mathematical Function 

EPCA, as amended by EISA, expressly 

requires that CAFE standards for 

passenger cars and light trucks be based 

on one or more vehicle attributes related 

to fuel economy, and be expressed in 

the form of a mathematical function.547 

Like the MY 2011 standards, the MY 

2012–2016 passenger car and light truck 

standards are attribute-based and 

defined by a mathematical function.548 

Also like the MY 2011 standards, the 

MY 2012–2016 standards are based on 

the footprint attribute. However, unlike 

the MY 2011 standards, the MY 2012– 

2016 standards are defined by a 

constrained linear rather than a 

constrained logistic function. The 

reasons for these similarities and 

differences are explained below. 

As discussed above in Section II, 

under attribute-based standards, the 

fleet-wide average fuel economy that a 

particular manufacturer must achieve in 

a given model year depends on the mix 

of vehicles that it produces for sale. 

547 49 U.S.C. 32902(a)(3)(A). 

548 As discussed in Chapter 2 of the TSD, EPA is 

also proposing to set attribute-based CO2 standards 

that are defined by a mathematical function, given 

the advantages of using attribute-based standards 

and given the goal of coordinating and harmonizing 

the CAFE and CO2 standards as expressed by 

President Obama in his announcement of the new 

National Program and in the joint NOI. 
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Until NHTSA began to set ‘‘Reformed’’ 

attribute-based standards for light trucks 

in MYs 2008–2011, and until EISA gave 

NHTSA authority to set attribute-based 

standards for passenger cars beginning 

in MY 2011, NHTSA set ‘‘universal’’ or 

‘‘flat’’ industry-wide average CAFE 

standards. Attribute-based standards are 

preferable to universal industry-wide 

average standards for several reasons. 

First, attribute-based standards increase 

fuel savings and reduce emissions when 

compared to an equivalent universal 

industry-wide standard under which 

each manufacturer is subject to the same 

numerical requirement. Absent a policy 

to require all full-line manufacturers to 

produce and sell essentially the same 

mix of vehicles, the stringency of the 

universal industry-wide standards is 

constrained by the capability of those 

full-line manufacturers whose product 

mix includes a relatively high 

proportion of larger and heavier 

vehicles. In effect, the standards are 

based on the mix of those 

manufacturers. As a result, the 

standards are generally set below the 

capabilities of full-line and limited-line 

manufacturers that sell predominantly 

lighter and smaller vehicles. 

Under an attribute-based system, in 

contrast, every manufacturer is more 

likely to be required to continue adding 

more fuel-saving technology each year 

because the level of the compliance 

obligation of each manufacturer is based 

on its own particular product mix. 

Thus, the compliance obligation of a 

manufacturer with a higher percentage 

of lighter and smaller vehicles will have 

a higher compliance obligation than a 

manufacturer with a lower percentage of 

such vehicles. As a result, all 

manufacturers must use technologies to 

enhance the fuel economy levels of the 

vehicles they sell. Therefore, fuel 

savings and CO2 emissions reductions 

should be higher under an attributebased system than under a comparable 

industry-wide standard. 

Second, attribute-based standards 

minimize the incentive for 

manufacturers to respond to CAFE in 

ways harmful to safety.549 Because each 

vehicle model has its own target (based 

on the attribute chosen), attribute-based 

standards provide no incentive to build 

smaller vehicles simply to meet a fleetwide average. Since smaller vehicles are 

subject to more stringent fuel economy 

targets, a manufacturer’s increasing its 

proportion of smaller vehicles would 

549 The 2002 NAS Report described at length and 

quantified the potential safety problem with average 

fuel economy standards that specify a single 

numerical requirement for the entire industry. See 

NAS Report at 5, finding 12. 

simply cause its compliance obligation 

to increase. 

Third, attribute-based standards 

provide a more equitable regulatory 

framework for different vehicle 

manufacturers.550 A universal industrywide average standard imposes 

disproportionate cost burdens and 

compliance difficulties on the 

manufacturers that need to change their 

product plans and no obligation on 

those manufacturers that have no need 

to change their plans. Attribute-based 

standards spread the regulatory cost 

burden for fuel economy more broadly 

across all of the vehicle manufacturers 

within the industry. 

And fourth, attribute-based standards 

respect economic conditions and 

consumer choice, instead of having the 

government mandate a certain fleet mix. 

Manufacturers are required to invest in 

technologies that improve the fuel 

economy of their fleets, regardless of 

vehicle mix. Additionally, attributebased standards help to avoid the need 

to conduct rulemakings to amend 

standards if economic conditions 

change, causing a shift in the mix of 

vehicles demanded by the public. 

NHTSA conducted three rulemakings 

during the 1980s to amend passenger 

car standards for MYs 1986–1989 in 

response to unexpected drops in fuel 

prices and resulting shifts in consumer 

demand that made the passenger car 

standard of 27.5 mpg infeasible for 

several years following the change in 

fuel prices. 

As discussed above in Section II, for 

purposes of the CAFE standards 

proposed in this NPRM, NHTSA 

recognizes that the risk, even if small, 

does exist that low fuel prices in MYs 

2012–2016 might lead indirectly to less 

than currently anticipated fuel savings 

and emissions reductions. Thus, we 

seek comment on whether backstop 

standards, or any other method within 

the agencies’ statutory authority, should 

and can be implemented for the import 

and light truck fleets in order to achieve 

the fuel savings that attribute-based 

standards might not absolutely 

guarantee. Commenters are encouraged, 

but not required, to review and respond 

to NHTSA’s discussion of this issue in 

the MY 2011 final rule as a starting 

point.551 

b. What Attribute Does NHTSA Use, and 

Why? 

Consistent with the MY 2011 CAFE 

standards, NHTSA is proposing to use 

footprint as the attribute for the MY 

2012–2016 CAFE standards. There are 

550 Id. at 4–5, finding 10. 


551 74 FR 14409–14412 (Mar. 30, 2009). 


several policy reasons why NHTSA and 

EPA both believe that footprint is the 

most appropriate attribute on which to 

base the standards, as discussed below. 

As discussed in the PRIA, in 

NHTSA’s judgment, from the standpoint 

of vehicle safety, it is important that the 

CAFE standards be set in a way that 

does not encourage manufacturers to 

respond by selling vehicles that are in 

any way less safe. While NHTSA’s 

research also indicates that reductions 

in vehicle mass tend to compromise 

vehicle safety, footprint-based standards 

provide an incentive to use advanced 

lightweight materials and structures that 

would be discouraged by weight-based 

standards, because manufacturers can 

use them to improve a vehicle’s fuel 

economy without their use necessarily 

resulting in a change in the vehicle’s 

target level of fuel economy. 

Further, although we recognize that 

weight is better correlated with fuel 

economy than is footprint, we continue 

to believe that there is less risk of 

‘‘gaming’’ (artificial manipulation of the 

attribute(s) to achieve a more favorable 

target) by increasing footprint under 

footprint-based standards than by 

increasing vehicle mass under weightbased standards—it is relatively easy for 

a manufacturer to add enough weight to 

a vehicle to decrease its applicable fuel 

economy target a significant amount, as 

compared to increasing vehicle 

footprint. We also agree with concerns 

raised in 2008 by some commenters in 

the MY 2011 CAFE rulemaking that 

there would be greater potential for 

gaming under multi-attribute standards, 

such as standards under which targets 

would also depend on attributes such as 

weight, torque, power, towing 

capability, and/or off-road capability. 

Standards that incorporate such 

attributes in conjunction with footprint 

would not only be significantly more 

complex, but by providing degrees of 

freedom with respect to more easilyadjusted attributes, they would make it 

less certain that the future fleet would 

actually achieve the projected average 

fuel economy and CO2 reduction levels. 

However, while NHTSA tentatively 

concludes that footprint is the most 

appropriate attribute upon which to 

base the proposed standards, 

recognizing strong public interest in this 

issue, we seek comment on whether the 

agency should consider setting 

standards for the final rule based on 

another attribute or another 

combination of attributes. If commenters 

suggest that the agency should consider 

another attribute or another 

combination of attributes, the agency 

specifically requests that the 

commenters address the concerns raised 

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49686 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

in the paragraphs above regarding the 

use of other attributes, and explain how 

standards should be developed using 

the other attribute(s) in a way that 

contributes more to fuel savings and 

CO2 reductions than the footprint-based 

Here, TARGET is the fuel economy target 

(in mpg) applicable to vehicles of a given 

footprint (FOOTPRINT, in square feet), b and 

a are the function’s lower and upper 

asymptotes (also in mpg), e is approximately 

equal to 2.718,552 c is the footprint (in square 

feet) at which the inverse of the fuel economy 

target falls halfway between the inverses of 

standards, without compromising 

safety. 

c. What Mathematical Function Did 

NHTSA Use for the RecentlyPromulgated MY 2011 CAFE Standards? 

The MY 2011 CAFE standards are 

defined by a continuous, constrained 

1 TARGET = ( FOOTPRINT −c) d 1 ⎛ 1 1 ⎞ e

+ − ⎜ ⎟ ( FOOTPRINT −c) d a ⎝ b a ⎠1+ e

the lower and upper asymptotes, and d is a 

parameter (in square feet) that determines 

how gradually the fuel economy target 

transitions from the upper toward the lower 

asymptote as the footprint increases. 

After fitting this mathematical form 

(separately) to the passenger car and 

logistic function, which takes the form 

of an S-curve, and is defined according 

to the following formula: 

light truck fleets and determining the 

stringency of the standards (i.e., the 

vertical positions of the curves), NHTSA 

arrived at the following curves to define 

the MY 2011 standards: 

d. What Mathematical Function is 

NHTSA Proposing to Use for New CAFE 

Standards, and Why? 

In finalizing the MY 2011 standards, 

NHTSA noted that the agency is not 

required to use a constrained logistic 

function and indicated that the agency 

may consider defining future CAFE 

standards in terms of a different 

mathematical function. NHTSA has 

done so in preparation for the proposed 

CAFE standards. 

In revisiting this question, NHTSA 

found that the final MY 2011 CAFE 

standard for passenger cars, though less 

552 e is the irrational number for which the slope 

of the function y = numberx is equal to 1 when x 

is equal to zero. The first 8 digits of e are 2.7182818. 

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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49687 

steep than the MY 2011 standard 

NHTSA proposed in 2008, continues to 

concentrate the sloped portion of the 

curve (from a compliance perspective, 

the area in which upsizing results in a 

slightly lower applicable target) within 

a relatively narrow footprint range 

(approximately 47–55 square feet). 

Further, most passenger car models 

have footprints smaller than the curve’s 

51.4 square foot inflection point, and 

many passenger car models have 

footprints at which the curve is 

relatively flat. 

For both passenger cars and light 

trucks, a mathematical function that has 

some slope at most footprints where 

vehicles are produced is advantageous 

in terms of fairly balancing regulatory 

burdens among manufacturers, and in 

terms of providing a disincentive to 

respond to new standards by 

downsizing vehicles in ways that 

compromise vehicle safety. For 

example, a flat standard may be very 

TARGET
 =
 ⎞

⎟

⎠ 

11 , a b

⎤
 

⎥

⎦
 

Here, TARGET is the fuel economy target 

(in mpg) applicable to vehicles of a given 

footprint (FOOTPRINT, in square feet), b and 

a are the function’s lower and upper 

asymptotes (also in mpg), respectively, c is 

the slope (in gpm per square foot) of the 

sloped portion of the function, and d is the 

intercept (in gpm) of the sloped portion of 

the function (that is, the value the sloped 

portion would take if extended to a footprint 

of 0 square feet. The MIN and MAX functions 

take the minimum and maximum, 

respectively of the included values; for 

example, MIN(1,2) = 1, MAX(1,2) = 2, and 

MIN[MAX(1,2),3)]=2. The following chart 

shows an example of a linear target function, 

where a = 0.0241 gpm (41.6 mpg), b = 0.032 

gpm (31.2 mpg), c = 0.000531 gpm per square 

foot, and d = 0.002292 gpm (436 mpg). 

Because the function is linear on a gpm basis, 

not an mpg basis, it is plotted on this basis. 

e. How Did NHTSA Fit the Coefficients 

That Determine the Shape of the 

Proposed Curves? 

For purposes of this NPRM, and for 

EPA’s use in developing new CO2 

emissions standards, the basic curve 

shapes were developed using methods 

similar to those applied by NHTSA in 

fitting the curves defining the MY 2011 

standards. We began with the market 

inputs discussed above, but because the 

baseline fleet is technologically 

heterogeneous, NHTSA used the CAFE 

model to develop a fleet to which nearly 

all the technologies discussed in Section 

V of the PRIA and Chapter 3 of the joint 

difficult for a full-line manufacturer to 

meet, while requiring very little of a 

manufacturer concentrating on small 

vehicles, and a flat standard may 

provide an incentive to manufacturers 

to downsize certain vehicles, in order to 

‘‘balance out’’ other vehicles subject to 

the same standard. 

As a potential alternative to the 

constrained logistic function, NHTSA 

had, in proposing MY 2011 standards, 

presented information regarding a 

constrained linear function. As shown 

in the 2008 NPRM, a constrained linear 

function has the potential to avoid 

creating a localized region (in terms of 

vehicle footprint) over which the slope 

of the function is relatively steep. 

Although NHTSA did not receive public 

comments on this option, the agency 

indicated that it still believed a linear 

function constrained by upper (on a 

gpm basis) and possibly lower limits 

could merit reconsideration in future 

CAFE rulemakings. 

1 

MIN ⎡
 

⎢

⎣
 

MAX ⎛
⎜

⎝
 c×
FOOTPRINT
 +
d,

TSD 553 were applied, by taking the 

following steps: (1) Treating all 

manufacturers as unwilling to pay civil 

penalties rather than applying 

technology, (2) applying any technology 

at any time, irrespective of scheduled 

vehicle redesigns or freshening, and (3) 

ignoring ‘‘phase-in caps’’ that constrain 

the overall amount of technology that 

can be applied by the model to a given 

manufacturer’s fleet. These steps helped 

to increase technological parity among 

vehicle models, thereby providing a 

better basis (than the baseline fleet) for 

estimating the statistical relationship 

between vehicle size and fuel economy. 

More information on the process for 

fitting the passenger car and light truck 

curves for MYs 2012–2016 is available 

above in Section II.C, and NHTSA refers 

the reader to that section and to Chapter 

2 of the joint TSD. NHTSA seeks 

comment on this approach to fitting the 

curves. We note that final decisions on 

this issue will play an important role in 

determining the form and stringency of 

the final CAFE and CO2 standards, the 

553 The agencies excluded diesel engines and 

strong hybrid vehicle technologies from this 

exercise (and only this exercise) because the 

agencies expect that manufacturers would not need 

to rely heavily on these technologies in order to 

comply with the proposed standards. NHTSA and 

EPA did include diesel engines and strong hybrid 

vehicle technologies in all other portions of their 

analyses. 

Having re-examined a constrained 

linear function for purposes of the 

proposed standards, NHTSA tentatively 

concludes that for both passenger cars 

and light trucks, it remains 

meaningfully sloped over a wide 

footprint range, thereby providing a 

well-distributed disincentive to 

downsize vehicles in ways that could 

compromise highway safety. Further, 

the constrained linear function 

proposed today is not so steeply sloped 

that it would provide a strong incentive 

to increase vehicle size in order to 

obtain a lower CAFE requirement and 

higher CO2 limit, thereby compromising 

energy and environmental benefits. 

Therefore, the CAFE standards proposed 

today are defined by constrained linear 

functions. 

The constrained linear function is 

defined according to the following 

formula: 

incentives those standards will provide 

(e.g., with respect to downsizing small 

vehicles), and the relative compliance 

burden faced by each manufacturer. 

D. Statutory Requirements 

1. EPCA, as Amended by EISA 

a. Standard Setting 

NHTSA must establish separate 

standards for MY 2011–2020 passenger 

cars and light trucks, subject to two 

principal requirements.554 First, the 

standards are subject to a minimum 

requirement regarding stringency: They 

must be set at levels high enough to 

ensure that the combined U.S. passenger 

car and light truck fleet achieves an 

average fuel economy level of not less 

than 35 mpg not later than MY 2020.555 

Second, as discussed above and at 

length in the March 2009 final rule 

establishing the MY 2011 CAFE 

standards, EPCA requires that the 

554 EISA added the following additional 

requirements. Standards must be attribute-based 

and expressed in the form of a mathematical 

function. 49 U.S.C. 32902(b)(3)(A). Standards for 

MYs 2011–2020 must ‘‘increase ratably’’ in each 

model year. 49 U.S.C. 32902(b)(2)(C). NHTSA 

interprets this requirement, in combination with the 

requirement to set the standards for each model 

year at the level determined to be the maximum 

feasible level for that model year, to mean that the 

annual increases should not be disproportionately 

large or small in relation to each other. 

555 49 U.S.C. 32902(b)(2)(A). 
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agency establish standards for all new 

passenger cars and light trucks at the 

maximum feasible average fuel economy 

level that the Secretary decides the 

manufacturers can achieve in that 

model year.556 The implication of this 

second requirement is that it calls for 

exceeding the minimum requirement if 

the agency determines that the 

manufacturers can achieve a higher 

level. When determining the level 

achievable by the manufacturers, EPCA 

requires that the agency consider the 

four statutory factors of technological 

feasibility, economic practicability, the 

effect of other motor vehicle standards 

of the Government on fuel economy, 

and the need of the United States to 

conserve energy. In addition, the agency 

has the authority to and traditionally 

does consider other relevant factors, 

such as the effect of the CAFE standards 

on motor vehicle safety. 

i. Statutory Factors Considered in 

Determining the Achievable Level of 

Average Fuel Economy 

As none of the four factors is defined 

in EPCA and each remains interpreted 

only to a limited degree by case law, 

NHTSA has considerable latitude in 

interpreting them. NHTSA interprets the 

four statutory factors as set forth below. 

(1) Technological Feasibility 

‘‘Technological feasibility’’ refers to 

whether a particular technology for 

improving fuel economy is available or 

can become available for commercial 

application in the model year for which 

a standard is being established. Thus, 

the agency is not limited in determining 

the level of new standards to technology 

that is already being commercially 

applied at the time of the rulemaking. It 

can, instead, set technology-forcing 

standards, i.e., ones that make it 

necessary for manufacturers to engage in 

research and development in order to 

bring a new technology to market. 

(2) Economic Practicability 

‘‘Economic practicability’’ refers to 

whether a standard is one ‘‘within the 

financial capability of the industry, but 

not so stringent as to’’ lead to ‘‘adverse 

economic consequences, such as a 

significant loss of jobs or the 

unreasonable elimination of consumer 

choice.’’ 557 In an attempt to ensure the 

economic practicability, the agency 

considers a variety of factors, including 

the annual rate at which manufacturers 

can increase the percentage of its fleet 

that has a particular type of fuel saving 

technology, and cost to consumers. 

556 49 U.S.C. 32902(a). 


557 67 FR 77015, 77021 (Dec. 16, 2002). 


Consumer acceptability is also an 

element of economic practicability. 

At the same time, the law does not 

preclude a CAFE standard that poses 

considerable challenges to any 

individual manufacturer. The 

Conference Report for EPCA, as enacted 

in 1975, makes clear, and the case law 

affirms, ‘‘(A) determination of maximum 

feasible average fuel economy should 

not be keyed to the single manufacturer 

which might have the most difficulty 

achieving a given level of average fuel 

economy.’’ 558 Instead, the agency is 

compelled ‘‘to weigh the benefits to the 

nation of a higher fuel economy 

standard against the difficulties of 

individual automobile manufacturers.’’ 

Id. The law permits CAFE standards 

exceeding the projected capability of 

any particular manufacturer as long as 

the standard is economically practicable 

for the industry as a whole. Thus, while 

a particular CAFE standard may pose 

difficulties for one manufacturer, it may 

also present opportunities for another. 

The CAFE program is not necessarily 

intended to maintain the competitive 

positioning of each particular company. 

Rather, it is intended to enhance fuel 

economy of the vehicle fleet on 

American roads, while protecting motor 

vehicle safety and being mindful of the 

risk of harm to the overall United States 

economy. 

Thus, NHTSA believes that this term 

must be applied in the context of the 

competing concerns associated with 

different levels of standards. Prior to 

switching to attribute-based standards 

in the MY 2008–2011 rulemaking, the 

agency sought to ensure the economy 

practicability of standards in part by 

setting them at or near the capability of 

the ‘‘least capable manufacturer’’ with a 

significant share of the market, i.e., 

typically the manufacturer whose 

vehicles are, on average, the heaviest 

and largest. In the first several 

rulemakings to establish attribute based 

standards, the agency applied marginal 

cost benefit analysis. This ensured that 

the agency’s application of technologies 

was limited to those that would pay for 

themselves and thus would have 

significant appeal to consumers. 

However, the agency can and has 

limited its application of technologies to 

those technologies, with or without the 

use of such analysis. 

(3) The Effect of Other Motor Vehicle 

Standards of the Government on Fuel 

Economy 

‘‘The effect of other motor vehicle 

standards of the Government on fuel 

economy,’’ involves an analysis of the 

558 CEI–I, 793 F.2d 1322, 1352 (D.C. Cir. 1986). 

effects of compliance with emission,559 

safety, noise, or damageability standards 

on fuel economy capability and thus on 

average fuel economy. In previous CAFE 

rulemakings, the agency has said that 

pursuant to this provision, it considers 

the adverse effects of other motor 

vehicle standards on fuel economy. It 

said so because, from the CAFE 

program’s earliest years 560 until 

present, the effects of such compliance 

on fuel economy capability over the 

history of the CAFE program have been 

negative ones. In those instances in 

which the effects are negative, NHTSA 

is called upon to ‘‘mak[e] a 

straightforward adjustment to the fuel 

economy improvement projections to 

account for the impacts of other Federal 

standards, principally those in the areas 

of emission control, occupant safety, 

vehicle damageability, and vehicle 

noise. However, only the unavoidable 

consequences should be accounted for. 

The automobile manufacturers must be 

expected to adopt those feasible 

methods of achieving compliance with 

other Federal standards which minimize 

any adverse fuel economy effects of 

those standards.’’ 561 For example, 

safety standards that have the effect of 

increasing vehicle weight lower vehicle 

fuel economy capability and thus 

decrease the level of average fuel 

economy that the agency can determine 

to be feasible. 

The ‘‘other motor vehicle standards’’ 

consideration has thus in practice 

functioned in a fashion similar to the 

provision in EPCA, as originally 

enacted, for adjusting the statutorilyspecified CAFE standards for MY 1978– 

1980 passengers cars.562 EPCA did not 

permit NHTSA to amend those 

standards based on a finding that the 

maximum feasible level of average fuel 

economy for any of those three years 

was greater or less than the standard 

specified for that year. Instead, it 

provided that the agency could only 

reduce the standards and only on one 

basis: if the agency found that there had 

been a Federal standards fuel economy 

reduction, i.e., a reduction in fuel 

economy due to changes in the Federal 

vehicle standards, e.g., emissions and 

safety, relative to the year of enactment, 

1975. 

559 In the case of emission standards, this 

includes standards adopted by the Federal 

Government and can include standards adopted by 

the States as well, since in certain circumstances 

the Clean Air Act allows States to adopt and enforce 

State standards different from the Federal ones. 

560 42 FR 63184, 63188 (Dec. 15, 1977). See also 

42 FR 33534, 33537 (Jun. 30, 1977). 

561 42 FR 33534, 33537 (Jun. 30, 1977). 

562 That provision was deleted as obsolete when 

EPCA was codified in 1994. 
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The ‘‘other motor vehicle standards’’ 

provision is broader than the Federal 

standards fuel economy reduction 

provision. Although the effects analyzed 

to date under the ‘‘other motor vehicle 

standards’’ provision have been 

negative, there could be circumstances 

in which the effects are positive. In the 

event that the agency encountered such 

circumstances, it would be required to 

consider those positive effects. For 

example, if changes in vehicle safety 

technology led to NHTSA’s amending a 

safety standard in a way that permits 

manufacturers to reduce the weight 

added in complying with that standard, 

that weight reduction would increase 

vehicle fuel economy capability and 

thus increase the level of average fuel 

economy that could be determined to be 

feasible. 

In the wake of Massachusetts v. EPA 

and of EPA’s proposed endangerment 

finding, granting of a waiver to 

California for its motor vehicle GHG 

standards, and its own proposal of GHG 

standards, the agency is confronted with 

the issue of how to treat those standards 

under the ‘‘other motor vehicle 

standards’’ provision. To the extent the 

GHG standards result in increases in 

fuel economy, they would do so almost 

exclusively as a result of inducing 

manufacturers to install the same types 

of technologies used by manufacturers 

in complying with the CAFE standards. 

The primary exception would involve 

increases in the efficiency of air 

conditioners. 

Thus, NHTSA tentatively concludes 

that the effects of the EPA and 

California standards are neither positive 

nor negative because the proposed rule 

results in consistent standards among 

all components of the National Program. 

Comment is requested on whether and 

in what way the effects of the California 

and EPA standards should be 

considered under the ‘‘other motor 

vehicle standards’’ provision or other 

provisions of EPCA in 49 U.S.C. 32902, 

consistent with NHTSA’s independent 

obligation under EPCA/EISA to issue 

CAFE standards? The agency has 

already considered EPA’s proposal and 

the harmonization benefits of the 

National Program in developing its own 

proposal. 

(4) The Need of the United States To 

Conserve Energy 

‘‘The need of the United States to 

conserve energy’’ means ‘‘the consumer 

cost, national balance of payments, 

environmental, and foreign policy 

implications of our need for large 

quantities of petroleum, especially 

imported petroleum.’’ 563 Environmental 

implications principally include those 

associated with reductions in emissions 

of criteria pollutants and CO2. A prime 

example of foreign policy implications 

are energy independence and security 

concerns. 

ii. Other Factors Considered by NHTSA 

The agency historically has 

considered the potential for adverse 

safety consequences in setting CAFE 

standards. This practice is recognized 

approvingly in case law. As the courts 

have recognized, ‘‘NHTSA has always 

examined the safety consequences of the 

CAFE standards in its overall 

consideration of relevant factors since 

its earliest rulemaking under the CAFE 

program.’’ Competitive Enterprise 

Institute v. NHTSA, 901 F.2d 107, 120 

n. 11 (DC Cir. 1990) (‘‘CEI I’’) (citing 42 

Fed. Reg. 33534, 33551 (June 30, 1977)). 

The courts have consistently upheld 

NHTSA’s implementation of EPCA in 

this manner. See, e.g., Competitive 

Enterprise Institute v. NHTSA, 956 F.2d 

321, 322 (D.C. Cir. 1992) (‘‘CEI II’’) (in 

determining the maximum feasible fuel 

economy standard, ‘‘NHTSA has always 

taken passenger safety into account.’’) 

(citing CEI I, 901 F.2d at 120 n. 11); 

Competitive Enterprise Institute v. 

NHTSA, 45 F.3d 481, 482–83 (D.C. Cir. 

1995) (‘‘CEI III’’) (same); Center for 

Biological Diversity v. NHTSA, 538 F.3d 

1172, 1203–04 (9th Cir. 2008) 

(upholding NHTSA’s analysis of vehicle 

safety issues associated with weight in 

connection with the MY 2008–11 light 

truck CAFE rule). Thus, in evaluating 

what levels of stringency would result 

in maximum feasible standards, NHTSA 

assesses the potential safety impacts and 

considers them in balancing the 

statutory considerations and to 

determine the appropriate level of the 

standards. 

Under the universal or ‘‘flat’’ CAFE 

standards that NHTSA was previously 

authorized to establish, the primary risk 

to safety came from the possibility that 

manufacturers would respond to higher 

standards by building smaller, less safe 

vehicles in order to ‘‘balance out’’ the 

larger, safer vehicles that the public 

generally preferred to buy. Under the 

attribute-based standards being 

proposed today, that risk is reduced 

because building smaller vehicles 

would tend to raise a manufacturer’s 

overall CAFE obligation, rather than 

only raising its fleet average CAFE. 

However, even if the manufacturers did 

not engage in any downsizing under 

attribute-based standards, there is still 

the possibility that manufacturers 

563 42 FR 63184, 63188 (1977). 

would rely on downweighting to 

improve their fuel economy (for a given 

vehicle at a given footprint target) in 

ways that may reduce safety to a greater 

or lesser extent. While NHTSA 

recognizes that manufacturers may 

nonetheless choose this option for 

raising their CAFE levels, in prior 

rulemakings we have limited the 

application of downweighting/material 

substitution in our modeling analysis to 

vehicles over 5,000 lbs GVWR.564 

For purposes of today’s proposed 

standards, however, NHTSA has revised 

its modeling analysis to allow some 

application of downweighting/material 

substitution for all vehicles, including 

those under 5,000 lbs GVWR, because 

we believe that this is more consistent 

with how manufacturers will actually 

respond to the standards. However, as 

discussed above, NHTSA does not 

mandate the use of any particular 

technology by manufacturers in meeting 

the standards. More information on the 

new approach to modeling 

manufacturer use of downweighting/ 

material substitution is available in 

Chapter 3 of the draft joint TSD and in 

Section V of the PRIA; and the 

estimated safety impacts that may be 

due to the proposed standards are 

described below. 

iii. Factors That NHTSA Is Prohibited 

From Considering 

EPCA also provides that in 

determining the level at which it should 

set CAFE standards for a particular 

model year, NHTSA may not consider 

the ability of manufacturers to take 

advantage of several EPCA provisions 

that facilitate compliance with the 

CAFE standards and thereby reduce the 

costs of compliance.565 As discussed 

further below, manufacturers can earn 

compliance credits by exceeding the 

CAFE standards and then use those 

credits to achieve compliance in years 

in which their measured average fuel 

economy falls below the standards. 

Manufacturers can also increase their 

CAFE levels through MY 2019 by 

producing alternative fuel vehicles. 

EPCA provides an incentive for 

producing these vehicles by specifying 

that their fuel economy is to be 

determined using a special calculation 

procedure that results in those vehicles 

being assigned a high fuel economy 

level. 

The effect of the prohibitions against 

considering these flexibilities in setting 

the CAFE standards is that the 

flexibilities remain voluntarilyemployed measures. If the agency were 

564 See 74 FR 14396–14407 (Mar. 30, 2009). 


565 49 U.S.C. 32902(h). 

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instead to assume manufacturer use of 

those flexibilities in setting new 

standards, that assumption would result 

in higher standards and thus tend to 

require manufacturers to use those 

flexibilities. 

iv. Determining the Level of the 

Standards by Balancing the Factors 

NHTSA has broad discretion in 

balancing the above factors in 

determining the appropriate levels of 

average fuel economy at which to set the 

CAFE standards for each model year. 

Congress ‘‘specifically delegated the 

process of setting * * * fuel economy 

standards with broad guidelines 

concerning the factors that the agency 

must consider.’’ 566 The breadth of those 

guidelines, the absence of any 

statutorily prescribed formula for 

balancing the factors, the fact that the 

relative weight to be given to the various 

factors may change from rulemaking to 

rulemaking as the underlying facts 

change, and the fact that the factors may 

often be conflicting with respect to 

whether they militate toward higher or 

lower standards give NHTSA discretion 

to decide what weight to give each of 

the competing policies and concerns 

and then determine how to balance 

them. The exercise of that discretion is 

subject to the necessity of ensuring that 

NHTSA’s balancing does not undermine 

the fundamental purpose of the EPCA: 

Energy conservation,567 and as long as 

that balancing reasonably 

accommodates ‘‘conflicting policies that 

were committed to the agency’s care by 

the statute.’’ 568 The balancing of the 

factors in any given rulemaking is 

highly dependent on the factual and 

policy context of that rulemaking. Given 

the changes over time in facts bearing 

on assessment of the various factors, 

such as those relating to the economic 

conditions, fuel prices and the state of 

climate change science, the agency 

recognizes that what was a reasonable 

balancing of competing statutory 

priorities in one rulemaking may not be 

a reasonable balancing of those 

priorities in another rulemaking.569 

Nevertheless, the agency retains 

substantial discretion under EPCA to 

choose among reasonable alternatives. 

EPCA neither requires nor precludes 

the use of any type of cost-benefit 

analysis as a tool to help inform the 

566 Center for Auto Safety v. NHTSA, 793 F.2d 

1322, 1341 (C.A.D.C. 1986). 

567 Center for Biological Diversity v. NHTSA, 538 

F.3d 1172, 1195 (9th Cir. 2008). 

568 CAS, 1338 (quoting Chevron U.S.A., Inc. v. 

Natural Resources Defense Council, Inc., 467 U.S. 

837, 845). 

569 CBD v. NHTSA, 538 F.3d 1172, 1198 (9th Cir. 

2008). 

balancing process. While NHTSA used 

marginal cost-benefit analysis in the 

first two rulemakings to establish 

attribute-based CAFE standards, it was 

not required to do so and is not required 

to continue to do so. Regardless of what 

type of analysis is or is not used, 

considerations relating to costs and 

benefits remain an important part of 

CAFE standard setting. 

Because the relevant considerations 

and factors can reasonably be balanced 

in a variety of ways under EPCA, and 

because of uncertainties associated with 

the many technological and cost inputs, 

NHTSA considers a wide variety of 

alternative sets of standards, each 

reflecting different balancing of those 

policies and concerns, to aid it in 

discerning reasonable outcomes. Among 

the alternatives providing for an 

increase in the standards in this 

rulemaking, the alternatives range in 

stringency from a set of standards that 

increase, on average, 3 percent annually 

to a set of standards that increase, on 

average, 7 percent annually. 

2. Administrative Procedure Act 

To be upheld under the ‘‘arbitrary and 

capricious’’ standard of judicial review 

in the APA, an agency rule must be 

rational, based on consideration of the 

relevant factors, and within the scope of 

the authority delegated to the agency by 

the statute. The agency must examine 

the relevant data and articulate a 

satisfactory explanation for its action 

including a ‘‘rational connection 

between the facts found and the choice 

made.’’ Burlington Truck Lines, Inc. v. 

United States, 371 U.S. 156, 168 (1962). 

Statutory interpretations included in 

an agency’s rule are subjected to the 

two-step analysis of Chevron, U.S.A., 

Inc. v. Natural Resources Defense 

Council, 467 U.S. 837, 104 S.Ct. 2778, 

81 L.Ed.2d 694 (1984). Under step one, 

where a statute ‘‘has directly spoken to 

the precise question at issue,’’ id. at 842, 

104 S.Ct. 2778, the court and the agency 

‘‘must give effect to the unambiguously 

expressed intent of Congress,’’ id. at 

843, 104 S.Ct. 2778. If the statute is 

silent or ambiguous regarding the 

specific question, the court proceeds to 

step two and asks ‘‘whether the agency’s 

answer is based on a permissible 

construction of the statute.’’ Id. 

If an agency’s interpretation differs 

from the one that it has previously 

adopted, the agency need not 

demonstrate that the prior position was 

wrong or even less desirable. Rather, the 

agency would need only to demonstrate 

that its new position is consistent with 

the statute and supported by the record, 

and acknowledge that this is a departure 

from past positions. The Supreme Court 

emphasized this recently in FCC v. Fox 

Television, 129 S.Ct. 1800 (2009). When 

an agency changes course from earlier 

regulations, ‘‘the requirement that an 

agency provide reasoned explanation for 

its action would ordinarily demand that 

it display awareness that it is changing 

position,’’ but ‘‘need not demonstrate to 

a court’s satisfaction that the reasons for 

the new policy are better than the 

reasons for the old one; it suffices that 

the new policy is permissible under the 

statute, that there are good reasons for 

it, and that the agency believes it to be 

better, which the conscious change of 

course adequately indicates.’’ 570 

3. National Environmental Policy Act 

As discussed above, EPCA requires 

the agency to determine what level at 

which to set the CAFE standards for 

each model year by considering the four 

factors of technological feasibility, 

economic practicability, the effect of 

other motor vehicle standards of the 

Government on fuel economy, and the 

need of the United States to conserve 

energy. NEPA directs that 

environmental considerations be 

integrated into that process. To 

accomplish that purpose, NEPA requires 

an agency to compare the potential 

environmental impacts of its proposed 

action to those of a reasonable range of 

alternatives. 

To explore the environmental 

consequences in depth, NHTSA has 

prepared a draft environmental impact 

statement. The purpose of an EIS is to 

‘‘provide full and fair discussion of 

significant environmental impacts and 

[to] inform decisionmakers and the 

public of the reasonable alternatives 

which would avoid or minimize adverse 

impacts or enhance the quality of the 

human environment.’’ 40 CFR 1502.1. 

NEPA is ‘‘a procedural statute that 

mandates a process rather than a 

particular result.’’ Stewart Park & 

Reserve Coal., Inc. v. Slater, 352 F.3d at 

557. The agency’s overall EIS-related 

obligation is to ‘‘take a ‘hard look’ at the 

environmental consequences before 

taking a major action.’’ Baltimore Gas & 

Elec. Co. v. Natural Res. Def. Council, 

Inc., 462 U.S. 87, 97, 103 S.Ct. 2246, 76 

L.Ed.2d 437 (1983). Significantly, ‘‘[i]f 

the adverse environmental effects of the 

proposed action are adequately 

identified and evaluated, the agency is 

not constrained by NEPA from deciding 

that other values outweigh the 

environmental costs.’’ Robertson v. 

Methow Valley Citizens Council, 490 

U.S. 332, 350, 109 S.Ct. 1835, 104 

L.Ed.2d 351 (1989). 

570 Ibid., 1181. 

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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49691 

The agency must identify the not command the agency to favor an passenger cars and light trucks is 

‘‘environmentally preferable’’ environmentally preferable course of expressed as a mathematical function 

alternative, but need not adopt it. action, only that it make its decision to that defines a fuel economy target 

‘‘Congress in enacting NEPA * * * did proceed with the action after taking a applicable to each vehicle model and, 

not require agencies to elevate hard look at environmental for each fleet, establishes a required 

environmental concerns over other consequences. CAFE level determined by computing 

appropriate considerations.’’ Baltimore the sales-weighted harmonic average of

Gas and Elec. Co. E. What Are the Proposed CAFE v. Natural Resources those targets.571 

Defense Council, Inc., Standards? 462 U.S. 87, 97 As discussed above in Section II.C, 

(1983). Instead, NEPA requires an NHTSA is proposing to determine fuel 1. Form of the Standards 

agency to develop alternatives to the economy targets using a constrained 

proposed action in preparing an EIS. 42 Each of the CAFE standards that linear function defined according to the 

U.S.C. 4332(2)(C)(iii). The statute does NHTSA is proposing today for following formula: 

1 TARGET =
 

MIN ⎡
 

⎢

⎣
 

MAX ⎛
⎜

⎝
 c×
FOOTPRINT
 +
d, ⎞

⎟

⎠ 

11 , a b

⎤
 

⎥

⎦
 

Here, TARGET is the fuel economy target production-weighted harmonic average The proposed standards are, therefore, (in mpg) applicable to vehicles of a given of the fuel economy targets applicable to specified by the four coefficients footprint (FOOTPRINT, in square feet), b and each vehicle model: defining fuel economy targets: a are the function’s lower and upper 

asymptotes (also in mpg), respectively, c a = upper limit (mpg) is 

the slope (in gpm per square foot) of the ∑ = 

i

i

SALESi
 

TARGETi
 

SALES
 b = lower limit (mpg) 

c = slope (gpm per square foot) 

d = intercept (gpm) 

The values of the coefficients are 

sloped portion of the function, and d is the CAFE

intercept (in gpm) of the sloped portion of required

the function (that is, the value the sloped ∑


portion would take if extended to a footprint i

of 0 square feet). The MIN and MAX Here, CAFErequired is the required level for different for the passenger car standards 

functions take the minimum and maximum, a given fleet, SALESi is the number of units and the light truck standards. respectively of the included values. of model i produced for sale in the United 

States, TARGETi is the fuel economy target 2. Passenger Car Standards for MYs As also discussed in Section II.C, applicable to model i (according to the 2012–2016 under the proposed standards (as under equation shown in Chapter II and based on the recently-promulgated MY 2011 For passenger cars, NHTSA is the footprint of model i), and the summations standards), the CAFE level required of in the numerator and denominator are both proposing CAFE standards defined by 

any given manufacturer will be performed over all models in the fleet in the following coefficients during MY 

determined by calculating the question. 2012–2016: 

TABLE IV.E.2–1—COEFFICIENTS DEFINING PROPOSED MY 2012–2016 FUEL ECONOMY TARGETS FOR PASSENGER CARS 

Coefficient 2012 2013 2014 2015 2016 

a (mpg) ....................................................................... 

b (mpg) ....................................................................... 

c (gpm/sf) ................................................................... 

d (gpm) ....................................................................... 

36 .23 

28 .12 

0 .0005308 

0 .005842 

37 .15 

28 .67 

0 .0005308 

0 .005153 

38 .08 

29 .22 

0 .0005308 

0 .004498 

39 .55 

30 .08 

0 .0005308 

0 .003520 

41 .38 

31 .12 

0 .0005308 

0 .002406 

These coefficients result in footprint- standard, which is specified by a a constrained linear function, is shown 

dependent target curves shown constrained logistic function rather than for comparison. 

graphically below. The MY 2011 final 

571 Required CAFE levels shown here are determined until the end of each model year, when target curves, as defined by the constrained linear 

estimated required levels based on NHTSA’s all of the vehicles produced by a manufacturer in function, and as embedded in the function for the 

current projection of manufacturers’ vehicle fleets that model year are known and their compliance sales-weighted harmonic average, are the real 

in MYs 2012–2016. Actual required levels are not obligation can be determined with certainty. The ‘‘standards’’ being proposed today. 

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49692 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

As discussed, the CAFE levels sales that NHTSA has used to examine individual manufacturers during MYs 

required of individual manufacturers today’s proposed CAFE standards, the 2012–2016 (an updated estimate of the 

will depend on the mix of vehicles they agency estimates that the targets shown average required fuel economy level 

produce for sale in the United States. above will result in the following under the final MY 2011 standard is 

Based on the market forecast of future average required fuel economy levels for shown for comparison): 572 

TABLE IV.E.2–2—ESTIMATED AVERAGE FUEL ECONOMY REQUIRED UNDER FINAL MY 2011 AND PROPOSED MY 2012– 

2016 CAFE STANDARDS FOR PASSENGER CARS 

Manufacturer MY 2011 MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 

BMW ........................................................ 30.2 33.2 34.0 34.8 36.0 37.5 

Chrysler .................................................... 29.6 33.0 33.7 34.5 35.3 36.8 

Daimler ..................................................... 29.4 32.6 33.1 33.8 35.0 36.4 

Ford .......................................................... 29.8 33.0 33.7 34.5 35.8 37.3 

General Motors ........................................ 30.3 33.0 33.8 34.6 35.8 37.3 

Honda ....................................................... 30.8 33.9 34.7 35.5 36.8 38.4 

Hyundai .................................................... 30.8 33.8 34.6 35.5 36.8 38.3 

Kia ............................................................ 30.6 33.6 34.4 35.2 36.5 38.0 

Mazda ...................................................... 30.7 34.1 34.8 35.7 37.0 38.6 

Mitsubishi ................................................. 31.0 34.4 35.3 36.1 37.4 39.2 

Nissan ...................................................... 30.7 33.5 34.2 35.0 36.2 37.8 

Porsche .................................................... 31.2 36.2 37.2 38.1 39.6 41.4 

Subaru ...................................................... 31.0 34.8 35.7 36.5 37.9 39.6 

Suzuki ...................................................... 31.2 35.9 36.8 37.7 39.2 41.0 

Tata .......................................................... 27.8 30.7 31.4 32.1 33.1 34.4 

Toyota ...................................................... 30.8 34.1 34.9 35.7 37.0 38.6 

Volkswagen .............................................. 30.8 34.6 35.4 36.2 37.5 39.1 

Average ............................................. 30.5 33.6 34.4 35.2 36.4 38.0 

572 In the March 2009 final rule establishing MY under the MY 2011 passenger car standard. Based the MY 2011 final rule, NHTSA now estimates that 

2011 standards for passenger cars and light trucks, on the agency’s current forecast of the MY 2011 the average required fuel economy level for NHTSA estimated that the required fuel economy passenger car market, which anticipates greater passenger cars will be 30.5 mpg in MY 2011. levels for passenger cars would average 30.2 mpg numbers of passenger cars than the forecast used in 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49693 

We note that a manufacturer’s 

required average fuel economy level for 

a model year under the proposed 

standards would be based on its actual 

production numbers in that model year. 

Therefore, its official required fuel 

economy level would not be known 

until the end of that model year. 

However, because the targets for each 

vehicle footprint would be established 

in advance of the model year, a 

manufacturer should be able to estimate 

its required level accurately. 

3. Minimum Domestic Passenger Car 

Standards 

EISA expressly requires each 

manufacturer to meet a minimum fuel 

economy standard for domestically 

manufactured passenger cars in addition 

to meeting the standards set by NHTSA. 

According to the statute (49 U.S.C. 

32902(b)(4)) the minimum standard 

shall be the greater of (A) 27.5 miles per 

gallon; or (B) 92 percent of the average 

fuel economy projected by the Secretary 

for the combined domestic and nondomestic passenger automobile fleets 

manufactured for sale in the United 

States by all manufacturers in the model 

year. The agency must publish the 

projected minimum standards in the 

Federal Register when the passenger car 

standards for the model year in question 

are promulgated. 

Based on NHTSA’s current market 

forecast, the agency’s estimates of these 

minimum standards under the proposed 

MY 2012–2016 CAFE standards (and, 

for comparison, the final MY 2011 

standard) are summarized below in 

Table IV.E.2–1.573 For eventual 

compliance calculations, the final 

calculated minimum standards will be 

updated to reflect any changes in the 

average fuel economy level required 

under the final standards. 

TABLE IV.E.3–1—ESTIMATED MINIMUM STANDARD FOR DOMESTICALLY MANUFACTURED PASSENGER CARS UNDER FINAL
 

MY 2011 AND PROPOSED MY 2012–2016 CAFE STANDARDS FOR PASSENGER CARS
 

2011 2012 2013 2014 2015 2016 

28.0 30.9 31.6 32.4 33.5 34.9 

4. Light Truck Standards 

For light trucks, NHTSA is proposing CAFE standards defined by the following coefficients during MYs 2012–2016: 

TABLE IV.E.4–1—COEFFICIENTS DEFINING PROPOSED MY 2012–2016 FUEL ECONOMY TARGETS FOR LIGHT TRUCKS 

Coefficient 2012 2013 2014 2015 2016 

a (mpg) ....................................................................... 

b (mpg) ....................................................................... 

c (gpm/sf) ................................................................... 

d (gpm) ....................................................................... 

29 .44 

22 .06 

0 .0004546 

0 .01533 

30 .32 

22 .55 

0 .0004546 

0 .01434 

31 .30 

23 .09 

0 .0004546 

0 .01331 

32 .70 

23 .84 

0 .0004546 

0 .01194 

34 .38 

24 .72 

0 .0004546 

0 .01045 

These coefficients result in footprint- which is specified by a constrained constrained linear function, is shown 

dependent targets shown graphically logistic function rather than a for comparison. 

below. The MY 2011 final standard, 

573 In the March 2009 final rule establishing MY passenger cars would be 27.8 mpg under the MY required CAFE standard will be 28.0 mpg in MY 

2011 standards for passenger cars and light trucks, 2011 passenger car standard. Based on the agency’s 2011. 

NHTSA estimated that the minimum required current forecast of the MY 2011 passenger car 

CAFE standard for domestically manufactured market, NHTSA now estimates that the minimum 

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49694 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

Given these targets, the CAFE levels has used to examine today’s proposed manufacturers during MYs 2012–2016 

required of individual manufacturers CAFE standards, the agency estimates (an updated estimate of the average 

will depend on the mix of vehicles they that the targets shown above will result required fuel economy level under the 

produce for sale in the United States. in the following average required fuel final MY 2011 standard is shown for 

Based on the market forecast NHTSA economy levels for individual comparison): 574 

TABLE IV.E.4–2—ESTIMATED AVERAGE FUEL ECONOMY REQUIRED UNDER FINAL MY 2011 AND PROPOSED MY 2012– 

2016 CAFE STANDARDS FOR LIGHT TRUCKS 

Manufacturer MY 2011 MY 2012 MY 2013 MY 2014 MY 2015 MY 2016 

BMW ........................................................ 25.7 26.3 27.0 27.7 28.8 30.1 

Chrysler .................................................... 24.2 25.2 25.8 26.4 27.3 28.5 

Daimler ..................................................... 24.7 25.4 26.1 26.9 27.9 29.1 

Ford .......................................................... 23.3 24.3 24.9 25.3 26.2 27.3 

General Motors ........................................ 22.9 23.6 24.2 24.8 25.6 26.6 

Honda ....................................................... 25.6 26.4 27.1 27.9 29.0 30.4 

Hyundai .................................................... 25.9 26.6 27.3 28.1 29.3 30.6 

Kia ............................................................ 25.1 25.8 26.4 27.2 28.3 29.6 

Mazda ...................................................... 26.3 27.4 28.1 28.8 29.9 31.4 

Mitsubishi ................................................. 26.4 27.4 28.1 28.9 30.1 31.6 

Nissan ...................................................... 24.1 25.0 25.6 26.1 27.0 28.2 

Porsche .................................................... 25.5 26.0 26.7 27.4 28.5 29.8 

Subaru ...................................................... 26.5 27.5 28.3 29.2 30.4 31.8 

Suzuki ...................................................... 26.3 27.2 27.9 28.7 29.9 31.3 

Tata .......................................................... 26.1 26.9 27.6 28.4 29.6 31.0 

Toyota ...................................................... 25.2 25.7 26.3 27.1 28.1 29.3 

Volkswagen .............................................. 25.0 25.6 26.2 26.9 27.9 29.2 

Average ............................................. 24.2 25.0 25.6 26.2 27.1 28.3 

574 In the March 2009 final rule establishing MY under the MY 2011 light truck standard. Based on in MY 2011. The increase in the estimate reflects 

2011 standards for passenger cars and light trucks, the agency’s current forecast of the MY 2011 light a slight decrease in the size of the average light NHTSA estimated that the required fuel economy truck market, NHTSA now estimates that the truck. 

levels for light trucks would average 24.1 mpg required fuel economy levels will average 24.2 mpg 
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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49695 

As discussed above with respect to 

the proposed passenger cars standards, 

we note that a manufacturer’s required 

fuel economy level for a model year 

under the proposed standards would be 

based on its actual production numbers 

in that model year. 

F. How Do the Proposed Standards 

Fulfill NHTSA’s Statutory Obligations? 

In developing the proposed MY 2012– 

16 standards, the agency developed and 

considered a wide variety of 

alternatives. NHTSA took a new 

approach to defining alternatives as 

compared to the most recent prior CAFE 

rulemaking. In response to comments 

received in the last round of 

rulemaking, in our March 2009 notice of 

intent to prepare an environmental 

impact statement, the agency selected a 

range of candidate stringencies that 

increased annually, on average, 3% to 

7%.575 That same approach has been 

carried over to this NPRM and to the 

accompanying DEIS and PRIA. The 

majority of the alternatives considered 

in this rulemaking are defined as 

average percentage increases in 

stringency—3 percent per year, 4 

percent per year, 5 percent per year, and 

so on. NHTSA believes that this 

approach more clearly communicates 

the level of stringency of each 

alternative and is more intuitive than 

alternatives defined in terms of different 

cost-benefit ratios, and still allows us to 

identify alternatives that represent 

different ways to balance NHTSA’s 

statutory requirements under EPCA/ 

EISA. 

In the notice of intent, we noted that 

each of the listed alternatives 

represents, in part, a different way in 

which NHTSA could conceivably 

balance conflicting policies and 

575 Notice of intent to prepare an EIS, 74 FR 

14857, 14859–60, April 1, 2009. 

considerations in setting the standards. 

We were mindful that the agency would 

need to weigh and balance many factors, 

such as the technological feasibility, 

economic practicability, including 

leadtime considerations for the 

introduction of technologies and 

impacts on the auto industry, the 

impacts of the standards on fuel savings 

and CO2 emissions, fuel savings by 

consumers; as well as other relevant 

factors such as safety. For example, the 

7% Alternative, the most stringent 

alternative, weighs energy conservation 

and climate change considerations more 

heavily and technological feasibility and 

economic practicability less heavily. In 

contrast, the 3% Alternative, the least 

stringent alternative, places more weight 

on technological feasibility and 

economic practicability. We recognized 

that the ‘‘feasibility’’ of the alternatives 

also may reflect differences and 

uncertainties in the way in which key 

economic (e.g., the price of fuel and the 

social cost of carbon) and technological 

inputs could be assessed and estimated 

or valued. 

In subsequently developing the NPRM 

and the associated analytical 

documents, the agency expanded the 

list of alternatives to provide a degree of 

analytical continuity between the old 

and new approach to defining 

alternatives in an effort help the agency 

and the public understand the 

similarities and dissimilarities between 

the two approaches and to make the 

transition to the new approach. To that 

end, we included and analyzed two 

additional alternatives, one that sets 

standards at the point where net 

benefits are maximized, and another 

that sets standards at the point at which 

total costs are equal to total benefits.576 

576 The stringency indicated by each of these 

alternatives depends on the value of inputs to 

NHTSA’s analysis. Results presented here for these 

With respect to the first of those 

alternatives, we note that Executive 

Order 12866 focuses attention on an 

approach that maximizes net benefits. 

Further, since NHTSA has thus far set 

attribute-based CAFE standards at the 

point at which net benefits are 

maximized, we believed it would be 

useful and informative to consider the 

potential impacts of that approach as 

compared to the new approach for MYs 

2012–2016. 

After working with EPA in thoroughly 

reviewing and in some cases reassessing 

the effectiveness and costs of 

technologies, most of which are already 

being incorporated in at least some 

vehicles, market forecasts and economic 

assumptions, we used the Volpe model 

extensively to assess the technologies 

that the manufacturers could apply in 

order to comply with each of the 

alternatives. This permitted us to assess 

the variety, amount and cost of the 

technologies that could be needed to 

enable the manufacturers to comply 

with each of the alternatives. NHTSA 

estimated how the application of these 

and other technologies could increase 

vehicle costs. The following five figures 

show industry-wide average 

incremental (i.e., relative to the 

reference fleet) per-vehicle costs, for 

each model year, each fleet, and the 

combined fleet. Estimates specific to 

each manufacturer are shown in the 

accompanying PRIA. 

two alternatives are based on NHTSA’s reference 

case inputs, which underlie the central analysis of 

the proposed standards. In the accompanying PRIA, 

the agency presents the results of that analysis to 

explore the sensitivity of results to changes in key 

economic inputs. Because of numerous changes in 

model inputs (e.g., discount rate, rebound effect, 

CO2 value, technology cost estimates), our analysis 

often exhausts all available technologies before 

reaching the point at which total costs equal total 

benefits. In these cases, the stringency that exhausts 

all available technologies is considered. 

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49698 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

Corresponding to these per-vehicle results for MY 2012–2016 for industry large U.S.-headquartered and three large 

cost increases, NHTSA estimated total and Chrysler, Ford, General Motors, foreign-headquartered full-line 

incremental outlays for additional Honda, Nissan, and Toyota. This figure manufacturers. 

technology in each model year. The focuses on these manufacturers as they 

following figure shows cumulative currently (in MY 2008) represent three 

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Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 49699 

For each alternative, NHTSA has also each model year, including fuel savings, well as the estimated societal benefits of 

estimated all corresponding effects for CO2 reductions, and other effects, as these effects. 

TABLE IV.F.1—FUEL SAVINGS, CO2 REDUCTIONS, AND TECHNOLOGY COSTS FOR REGULATORY ALTERNATIVES 

Regulatory alternative Fuel savings 

(b. gal) 

CO2 

reductions 

(mmt) 

Cost 

($b) 

3% per Year ................................................................................................................................. 

4% per Year ................................................................................................................................. 

5% per Year ................................................................................................................................. 

6% per Year ................................................................................................................................. 

Maximum Net Benefit .................................................................................................................. 

7% per Year ................................................................................................................................. 

37 

54 

69 

83 

90 

91 

404 

582 

718 

846 

923 

934 

29 

46 

74 

103 

111 

116 

Total Cost = Total Benefit .................................................................................................... 95 977 122 

The accompanying PRIA presents a economic practicability and the need of presented above to the corresponding 

detailed analysis of these results. the nation to conserve energy, the cumulative fuel savings. 

Relevant to EPCA’s requirement that following figure compares the 

NHTSA consider, among other factors, incremental technology outlays 

The agency then assessed which 

alternative would represent a reasonable 

balancing of the statutory criteria, given 

the difficulties confronting the industry 

and the economy, and the priorities and 

policy goals of the President. Those 

priorities and goals include achieving 

nationally harmonized and coordinated 

program for regulating fuel economy 

and GHG emissions. 

Part of that assessment entailed an 

evaluation of the stringencies necessary 

to achieve both Federal and State GHG 

emission reduction goals, especially 

those of California and the States that 

have adopted its GHG emission 

standard for motor vehicles. Given that 

EPCA requires attribute-based 

standards, NHTSA and EPA determined 

the level at which an attribute-based 

GHG emissions standard would need to 

be set to achieve the goals of California. 

This was done by evaluating a 

nationwide CAA standard for MY 2016 

that would require the levels of 

technology upgrade, across the country, 

which California standards would 

require for the subset of vehicles sold in 

California under the California 

standards for MY 2009–2016 (known as 

‘‘Pavley 1’’). In essence, the stringency 

of the California Pavley 1 program was 

evaluated, but for a national standard. 

For a number of reasons discussed in 

section III.D, an assessment was 

developed of an equivalent national 

new vehicle fleet-wide CO2 performance 

standards for model year 2016 which 

would result in the new vehicle fleet in 

the State of California having CO2 

performance equal to the performance 

from the California Pavley 1 standards. 

That level, 250 g/mi, is equivalent to 

35.5 mpg if the GHG standard is met 
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49700 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules 

exclusively by fuel economy 

improvements. 

To obtain the counterpart CAFE 

standard, we then adjusted that level 

downward to account for differences 

between the more prescriptive EPCA 

and the more flexible CAA. These 

differences give EPA greater ability 

under the CAA to provide compliance 

flexibilities that would enable 

manufacturers to achieve compliance 

with a given level of requirement under 

the CAA at less cost than with the same 

level of requirement under EPCA. 

Principal among those greater 

flexibilities are the credits that EPA can 

provide for improving the efficiency of 

air conditioners and reducing the 

leakage of refrigerants from them. The 

adjustments result in a figure of 34.1 

mpg as the appropriate counterpart 

CAFE standard. This differential gives 

manufacturers the opportunity to reach 

35.5 mpg under the CAA in ways that 

would significantly reduce their costs. 

Were NHTSA instead to establish its 

standard at the same level, 

manufacturers would need to make 

substantially greater expenditures on 

fuel-saving technologies to reach 35.5 

mpg under EPCA. 

Given the importance to this 

rulemaking of achieving a harmonized 

National Program, we created a new 

alternative whose annual percentage 

increases would achieve 34.1 mpg by 

MY 2016. That alternative is one which 

increases on average at 4.3% annually. 

This new alternative, like the seven 

alternative presented above, represents a 

unique balancing of the statutory factors 

and other relevant considerations. We 

have added that alternative to the table 

below. 

Regulatory 

alternative 

Fuel 

savings 

(b. gal) 

CO2 

reductions 

(mmt) 

Cost 

($b) 

3% per Year ..... 37 404 29 

4% per Year ..... 54 582 46 

Regulatory 

alternative 

Fuel 

savings 

(b. gal) 

CO2 

reductions 

(mmt) 

Cost 

($b) 

Proposed (4.3% 

per Year) ....... 62 656 60 

5% per Year ..... 69 718 74 

6% per Year ..... 83 846 103 

Maximum Net 

Benefit ........... 90 923 111 

7% per Year ..... 91 934 116 

Total Cost = 

Total 

Benefit .... 95 977 122 

As noted earlier, NHTSA has used the 

Volpe model to analyze each of these 

alternatives based on analytical inputs 

determined jointly with EPA. For a 

given regulatory alternative, the Volpe 

model estimates how each manufacturer 

could apply technology in response to 

the MY 2012 standard (separately for 

cars and trucks), carries technologies 

applied in MY 2012 forward to MY 

2013, and then estimates how each 

manufacturer could apply technology in 

response to the MY 2013 standard. 

When analyzing MY 2013, the model 

considers the potential to add ‘‘extra’’ 

technology in MY 2012 in order to carry 

that technology into MY 2013, thereby 

avoiding the use of more expensive 

technologies in MY 2013. The model 

continues in this fashion through MY 

2016, and then performs calculations to 

estimate the costs, effects, and benefits 

of the applied technologies, and to 

estimate any civil penalties owed based 

on projected noncompliance. For each 

regulatory alternative, the model 

calculates incremental costs, effects, and 

benefits relative to the regulatory 

baseline (i.e., the no-action alternative), 

under which the MY 2011 CAFE 

standards continue through MY 2016. 

The model calculates results for each 

model year, because EPCA requires that 

NHTSA set its standards for each model 

year at the ‘‘maximum feasible average 

fuel economy level that the Secretary 

decides the manufacturers can achieve 

in that model year’’ considering four 

statutory factors. Pursuant to EPCA’s 

directive notice not to consider statutory 

credits in establishing CAFE standards, 

NHTSA did not FFV credits, credits 

carried forward and backward, and 

transferred credit.577 578 In addition, the 

analysis reflects the ability of 

manufacturers to pay fines in lieu of 

compliance. 

Because it entails year-by-year 

examination of eight regulatory 

alternatives for, separately, passenger 

cars and light trucks, NHTSA’s analysis 

involves a large amount of information. 

Detailed results of this analysis are 

presented separately in the PRIA 

accompanying today’s notice. The 

remainder of this section discusses a 

combination of aggregated and 

illustrative results of this analysis. 

The following figure compares 

average fuel economy levels required of 

manufacturers under the eight 

regulatory alternatives in MYs 2012, 

2014, and 2016. Required levels for MY 

2013 and MY 2015 fall between those 

for MYs 2012 and 2014 and MYs 2014 

and 2016, respectively. Although 

required levels for these interim years 

are not presented in the following figure 

to limit the complexity of the figure, 

they do appear in the accompanying 

PRIA.579 

577 Separately, NHTSA has conducted analysis 

that accounts for EPCA’s provisions regarding FFVs. 

578 Because NHTSA’s modeling represents every 

model year explicitly, accounts for estimates of 

when vehicle model redesigns will occur, and sets 

aside these compliance flexibilities, the agency’s 

modeling produces results that differ varyingly 

from EPA’s for specific manufacturers, fleets, and 

model years. 

579 Also, the ‘‘Max NB’’ and the ‘‘TC = TB’’ 

alternatives depend on the inputs to the agencies’ 

analysis. The sensitivity analysis presented in the 

PRIA documents the response of these alternatives 

to changes in key economic inputs. For example, 

the combined average required fuel economy under 

the ‘‘Max NB’’ alternative is 36.8 mpg under the 

reference case economic inputs presented here, and 

ranges from 32.8 mpg to 37.2 mpg under the 

alternative economic inputs presented in the PRIA. 

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As this figure illustrates, the proposed 

standards involve a ‘‘faster start’’ toward 

increased stringency than do any of the 

alternatives that increase steadily (i.e., 

the 3%/y, 4%/y, 5%/y, 6%/y, and 7%/ 

y alternatives). However, by MY 2016, 

the stringency of the proposed standards 

reflects an average annual increase of 

4.3%/y. The proposed standards, 

therefore, represent an alternative that 

could be referred to as ‘‘4.3% per year 

with a fast start’’ or a ‘‘front-loaded 

4.3% average annual increase.’’ 

In NHTSA’s analysis, these achieved 

average fuel economy levels result from 

the application of technology rather 

than changes in the mix of vehicles 

produced for sale in the U.S. The 

accompanying PRIA presents detailed 

estimates of additional technology 

penetration into the NHTSA reference 

fleet associated with each regulatory 

alternative. The following four charts 

illustrate the results of this analysis, 

considering the application of four 

technologies by six manufacturers and 

the industry as a whole. Technologies 

include gasoline direct injection (GDI), 

engine turbocharging and downsizing, 

diesel engines, and strong HEV systems 

(including CISG systems). GDI and 

turbocharging are among the 

technologies that play an important role 

in achieving the fuel economy 

improvements shown in NHTSA’s 

analysis, and diesels and strong HEVs 

represent technologies involving 

significant challenges for widespread 

use through MY 2016. These figures 

focus on Chrysler, Ford, General Motors, 

Honda, Nissan, and Toyota, as these 

manufacturers currently (in MY 2008) 

represent three large U.S.-headquartered 

and three large foreign-headquartered 

full-line manufacturers. For each 

alternative, the figures show additional 

application of technology by MY 2016. 

The PRIA presents results for all model 

years, technologies, and manufacturers, 

and NHTSA has considered these 

broader results when considering the 

eight regulatory alternatives. 

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49702 Federal Register / Vol. 74, No. 186 / Monday, September 28, 2009 / Proposed Rules