Chairman 

J. MENDEL 

Honda 

President 

M. STANTON 

VEHICLE 

MANUFACTURERS 

Aston Martin 

Ferrari/Maserati 

Honda 

Hyundai 

Isuzu 

Kia 

Mitsubishi 

Nissan 

Peugeot 

Renault 

Subaru 

Suzuki 

Toyota 

AFFILIATES 

ADVICS 

Bosch 

Delphi 

Denso 

JAMA 

ASSOCIATION OF INTERNATIONAL AUTOMOBILE MANUFACTURERS, INC. 

2111 WILSON BOULEVARD - SUITE 1150 - ARLINGTON, VIRGINIA 22201 

703.525.7788 PHONE - 703.525.8817 FAX - WWW.AIAM.ORG

October 3, 2007 

Ms. Deborah Rabin 

Regulations Coordinator 

Air and Radiation Management Administration 

Department of Environment 

1800 Washington Boulevard, Suite 730 

Baltimore, MD 21230-1720 

Re: Comments Regarding Maryland Regulations .01—.14, COMAR 26.11.34, 

Low Emissions Vehicle Program 

Dear Ms. Rabin: 

The Association of International Automobile Manufacturers1

 (AIAM) is a trade 

association representing 14 international motor vehicle manufacturers that account 

for about 40 percent of the passenger cars and 20 percent of light trucks sold 

annually in the United States. In 2006, our member companies represented over 50 

percent of new motor vehicles registered in the State of Maryland. Nationwide, 

AIAM members have invested over $35 billion in U.S.-based production facilities, 

have a combined domestic production capacity of over 4 million vehicles, directly 

employ over 92 thousand Americans, and generate well over half a million U.S. 

jobs in dealerships and suppliers. 2 

Companies represented by AIAM are leaders in bringing advanced fuel-efficient 

technologies to market. Nearly all of the vehicles sold by AIAM member 

companies throughout the United States are “50-state vehicles” that already meet 

both California’s LEV II emissions standards and EPA’s tier 2 emissions standards. 

In addition, our members actively support the federal efforts currently underway to 

improve fuel economy and lower greenhouse gas emissions. Nevertheless, AIAM 

opposed the “Maryland Clean Cars Act of 2007” which adopted California 

emissions and greenhouse gas standards because we do not believe such actions 

will have any significant favorable impact on the local air quality in Maryland. In 

addition, we view a uniform federal greenhouse gas or fuel economy standard as a 

better way to obtain the environmental goals intended by the statute’s greenhouse 

 

1

 AIAM member companies include American Honda Motor Co., American Suzuki Motor Corp., 

Aston Martin Lagonda of North America, Inc., Ferrari North America, Inc., Hyundai Motor 

America, Isuzu Motors America, Inc., Kia Motors America, Maserati North America, Inc., 

Mitsubishi Motors North America, Inc., Nissan North America, Inc. Peugeot Motors of America, 

Renault, SA, Subaru of America and Toyota Motor North America, Inc. AIAM also represents 

original equipment suppliers and other automotive-related trade associations. 

2

 For more information, visit our website at www.aiam.org. 
ASSOCIATION OF INTERNATIONAL AUTOMOBILE MANUFACTURERS, INC. 

2111 WILSON BOULEVARD - SUITE 1150 - ARLINGTON, VIRGINIA 22201 

703.525.7788 PHONE - 703.525.8817 FAX - WWW.AIAM.ORG

gas standards without creating a patchwork of differing state-by-state requirements that will 

harm consumers, dealers and automobile manufacturers. 

AIAM recognizes, however, that adoption of California emissions and greenhouse gas standards 

is now the law in Maryland and that the Maryland Air and Radiation Management 

Administration, Department of the Environment (“ARMA”), is dutifully implementing the 

program as directed by statute. Therefore, these comments will be limited to addressing various 

administrative aspects of the proposed regulations to assist the ARMA in promulgating fair and 

equitable regulations. 

Our primary concern is that the implementation timing of the California programs in Maryland is 

much different from the timing of the programs in California. In the case of the LEV standards, 

the California program has existed for over a decade. For the greenhouse gas standards, 

California plans to adopt the program for the 2009 model year if EPA decides to grant California 

a waiver of preemption under section 209 of the Clean Air Act. Of course, the earliest Maryland 

can adopt the California standards is the 2011 model year as you have proposed. However, these 

timing differences cause problems with other aspects of the program, such as the NMOG 

averaging, ZEV credits averaging, and the greenhouse gas fleet averaging. In order to avoid 

unfair impacts on individual vehicle manufacturers due to these timing and market differences 

between Maryland and California, the Maryland regulations need to contain provisions to 

properly adjust the relevant credits averaging and banking provisions of the program. Other 

states which have recently adopted the California programs have made such adjustments for at 

least the NMOG and ZEV credits programs; therefore, we recommend that you consult and 

coordinate with your colleagues in Connecticut, New Jersey, and Rhode Island, among others to 

address these inequities. 

Thank you for the opportunity to comment on this proposed regulation. Should you have any 

questions about AIAM’s views on this or other matters of interest to the industry, please feel free 

to contact me at (703) 525-7788. We look forward to working constructively with you as this 

regulatory action proceeds. 

Sincerely, 

Michael J. Stanton 

President and CEO 

 
From: "Jennifer T. Cole" <jtcole@autoalliance.org>

To: <drabin@mde.state.md.us>

Date: 10/4/07 4:18PM

Subject: Alliance comments on LEV program

Dear Ms. Rabin,

Attached are the Alliance of Automobile Manufacturers' comments on the

proposal by the Maryland Department of Environment to adopt the Low

Emissions Vehicle Program in MD. I sincerely apologize for the delay in

submitting them however, I was unexpectedly called out of the office

yesterday and was unable to present them at yesterday's public hearing.

The Alliance would greatly appreciate the Department's consideration of

our views. Please let me know if you have any questions or need

additional information. 

Sincerely,

Jennifer Cole

Jennifer Thomas Cole

Manager, State Government Affairs

Alliance of Automobile Manufacturers 

1401 Eye Street, NW, Ste. 900

Washington, DC 20005

P: 202-326-5538

F: 202-326-5589

C: 202-329-7823

jtcole@autoalliance.org
Alliance of Automobile Manufacturers Page i of 33 October 3, 2007

MARYLAND

DEPARTMENT OF THE ENVIRONMENT

Comments of the Alliance of Automobile Manufacturers

On Rulemaking to Adopt California LEV, ZEV and Greenhouse Gas Regulations

October 3, 2007

For More Information Contact:

Steven Douglas Julie C. Becker

Director, Environmental Affairs Assistant General Counsel

Alliance of Automobile Manufacturers Alliance of Automobile Manufacturers

1415 L Street, Suite 1190 1401 Eye Street, N.M., Suite 900

Sacramento, CA 95814 Washington, DC 20005

(916) 266-4532 (202) 326-5511

sdouglas@autoalliance.org jbecker@autoalliance.org
Alliance of Automobile Manufacturers Page i of 33 October 3, 2007

Executive Summary

The Alliance of Automobile Manufacturers is providing comments on the proposal by the 

Maryland Department of the Environment (“the Department”) to adopt the California motor 

vehicle LEV, ZEV and CO2 (or greenhouse gas) regulations in Maryland. As currently proposed 

the adoption of the LEV and ZEV regulations suffer from several faults, namely violations of the 

Clean Air Act and the Commerce Clause. Unfortunately, adopting California’s costly vehicle 

emission program will increase cost to Maryland residents, limit vehicle availability, and degrade 

air quality.

As to the greenhouse gas regulation, some of the principal points about that proposal that 

the Alliance considers important for the Department to consider are as follows:

1. There is no evidence that adoption of the California greenhouse gas rule in Maryland

would have ANY effect on the climate of Maryland. Any claim that the California rule would 

change the climate of Maryland or have any related public-health benefit is unsupportable on a 

scientific basis or even by California’s own admission. If the goal of the regulation is to address 

climate change in Maryland, the only purpose served by adopting the California rule would be 

symbolic.

2. Adopting the California regulation will INCREASE emissions of ozone precursors and 

other pollutants in Maryland. Due to high cost of new vehicles will inhibit fleet turnover, 

increasing the age of the vehicle fleet. By encouraging more driving, the California rule in 

Maryland would increase smog-forming emissions and hinder the state’s efforts to improve air 

quality. The state cannot afford to take symbolic action on the issue of climate change at such a 
Alliance of Automobile Manufacturers Page ii of 33 October 3, 2007

cost to its efforts to reduce smog-forming emissions from motor vehicles, especially when EPA 

has proposed lowering the ozone air quality standards. 

3. The California greenhouse gas rule would needlessly inject the government into 

consumers’ choices about the types of vehicles that best suit their needs. Some supporters of the 

California rule claim that the rule is beneficial because it will mandate higher fuel economy. 

That claim assumes, contrary to common sense and experience, that a regulatory agency in 

California can better define the private economic interests of Maryland consumers than the 

consumers themselves. Consumers in Maryland or other states interested in buying high-mileage 

vehicles can do so today without the need for specific regulations that require them to do so. 

4. The greenhouse gas regulation under consideration by the Department would conflict 

with state and federal law. The Department has no authority from the Legislature to adopt 

regulations that will increase air pollution levels in Maryland, and for that reason, adoption of the 

California rule would be inconsistent with state law. Such an action would also conflict with 

federal law, which reserves to the national government the sole power to regulate motor vehicle 

fuel economy, as well as other provisions of federal law. 
Alliance of Automobile Manufacturers Page iii of 33 October 3, 2007

Table of Contents

Page

Introduction 1

I. Issues Relating to Maryland’s Adoption of the California LEV II Standards ___________ 2

A. Emission Benefits of California LEV II versus Federal Tier II ____________________________ 2

B. Legal Issues Regarding the Adoption of the LEV and ZEV Standards _____________________ 2

1. Maryland’s Proposed Fleet Average NMOG Requirement Violates Section 177 ___________________ 3

2. Maryland’s Proposed ZEV Credit Bank ____________________________________________________ 4

a. Type III Transfer: ___________________________________________________________________ 5

b. Non-Type III Transfer _______________________________________________________________ 5

II. The California Greenhouse Gas Regulation ____________________________________ 5

A. Regulatory Background_________________________________________________________ 6

B. Issues of Controversy __________________________________________________________ 9

1. Nationwide Deployment of the California Greenhouse Gas Technologies ________________________ 9

2. Reliance on the NESCCAF and CARB Technological Assessments ______________________________ 11

3. Credits and Alternative Compliance Mechanisms __________________________________________ 15

4. Grid-Connected Hybrid Vehicles ________________________________________________________ 16

III. Environmental Assessment of the Greenhouse Gas Rule in Maryland ______________ 18

A. Increases in Air Pollutants _____________________________________________________ 19

B. Safety Issues Related to the Rebound Effect _______________________________________ 20

IV. Economic Issues Raised by the Proposed Regulation __________________________ 20
Alliance of Automobile Manufacturers Page iv of 33 October 3, 2007

A. Consumer Valuation of Future Operating Cost Reductions____________________________ 20

B. Opportunity Costs and Losses in Vehicle Utility ____________________________________ 22

V. Legal Issues Presented by the Greenhouse Gas Regulation _______________________ 22

A. The Energy Policy and Conservation Act.__________________________________________ 23

B. Other Provisions of Federal Law_________________________________________________ 24

Conclusion__________________________________________________________________ 25
Comments of the Alliance of Automobile Manufacturers

On the Proposed Rulemaking to Adopt California Motor Vehicle LEV, ZEV and 

Greenhouse Gas Regulations

Introduction

The Alliance of Automobile Manufacturers1 respectfully submits these comments on the 

proposal by the Department to adopt the California motor vehicle LEV, ZEV and greenhouse gas 

regulations.2 The California LEV program contains three basic elements – emissions 

regulations, a zero emissions vehicles (“ZEV”) mandate, and greenhouse gas regulation. The 

emissions element of the regulatory program, known as the LEV II program, contains 

requirements for exhaust and evaporative emissions as well as on-board diagnostics to monitor 

the emission control system and components. The ZEV mandate requires that automakers power 

a specified percentage of their new vehicle fleet with only battery electricity or hydrogen fuel 

cell power. The last element of California’s regulation calls for the control of greenhouse gases 

from new motor vehicles, commonly known as California’s AB 1493 rule. 

Part I of these comments discusses the proposed adoption of the LEV II standards and 

ZEV mandate and identifies several issues that the Department must consider prior to adoption. 

 

1 The members of the Alliance of Automobile Manufacturers (“the Alliance”) are BMW Group

of North America, Inc., DaimlerChrysler Corporation, Ford Motor Company, General Motors 

Corporation, Mazda North American Operations, Mitsubishi Motors North America, Porsche 

Cars North America, Inc., Toyota Motor North America, Inc., and Volkswagen of America, Inc.

2 The Department’s proposal is contained in: Notice of Proposed Action Title 26, Subtitle 11, 

Air Quality, 26.11.34, Low Emissions Vehicle Program. Maryland Register, Vol. 34, Issue 18, 

Friday, August 31, 2007, page 1609.
Alliance of Automobile Manufacturers Page 2 of 33 October 3, 2007

Part II provides an overview of the proposed greenhouse gas regulation. Parts III and IV 

examine the environmental effects of the proposed greenhouse gas regulation in Maryland and 

the impact of the rule on Maryland consumers. Part V evaluates the legal issues presented by the 

greenhouse gas proposal. Several attachments accompany these comments.

I. Issues Relating to Maryland’s Adoption of the California LEV II Standards

A. Emission Benefits of California LEV II versus Federal Tier II 

The Department should decline to adopt the California standards for reasons of good 

public policy. Recently, the Alliance asked a team of experts from Sierra Research, Air 

Improvement Resource, Inc., and NERA Economic Consulting to evaluate the emissions impacts 

of the entire California vehicle emissions program, including the greenhouse gas standards, on 

emissions from new light-duty vehicles in California, relative to those that would occur in 

California under the federal vehicle emissions standards. To our knowledge, this is the first and 

only study of this kind. The study – a copy of which is enclosed as Attachment 1 - concludes 

that the California standards result in higher levels of a variety of pollutants, including exhaust 

PM2.5, NOx, hydrocarbons (HCs), carbon monoxide, and air toxics. We believe this is critical 

information for the Department to consider, particularly in light of the fact that individuals who 

wrote the California regulation have, in sworn testimony, admitted that it will not measurably 

impact global climate.

B. Legal Issues Regarding the Adoption of the LEV and ZEV Standards

Section 177 of the Clean Air Act, 42 U.S.C. § 7507, allows for states to adopt alternative

emissions standards that would otherwise be preempted by Section 209 of the Act. For a state to 
Alliance of Automobile Manufacturers Page 3 of 33 October 3, 2007

promulgate a standard under Section 177 it (1) must “adopt such standards at least two years 

before commencement of such model year”; and (2) must adopt standards that “are identical to 

the California standards for which a waiver has been granted for such model year.” The 

identicality requirement means that no state may modify the California regulations. Section 177 

goes on to specify that no state may “prohibit or limit, directly or indirectly, the manufacture or 

sale of a new motor vehicle or motor vehicle engine that is certified in California as meeting 

California standards.” Id. Furthermore, no state may “take any action of any kind to create, or 

have the effect of creating, a motor vehicle or motor vehicle engine different than a motor 

vehicle or engine certified in California under California standards (a ‘third vehicle’).” Id.

1. Maryland’s Proposed Fleet Average NMOG Requirement Violates 

Section 177

Both California and the Federal Government control motor vehicle emissions using a 

sales-weighted average that each manufacturer is required to meet for its new vehicle fleet. By 

virtue of this fleet average scheme, a manufacturer can sell some vehicles with emissions that are 

higher than the required average provided that such sales are offset by the sale of vehicles with 

emissions that are lower than the required average. The regulations as currently proposed adopt 

California’s fleet NMOG average, see Department’s proposal §.06, Fleet NMOG Requirements. 

However, by adopting and attempting to enforce the California fleet NMOG average Maryland

will likely violate the Clean Air Act. This potential violation could be corrected if the 

Department simply required reporting rather than compliance with, the fleet average NMOG. 

The Alliance recommends this approach. Without knowing or attempting to speculate on future 

product placement in Maryland, it is equally possible that this approach could result in fleet 
Alliance of Automobile Manufacturers Page 4 of 33 October 3, 2007

average NMOG slightly higher than California or slightly lower, but in either case, the difference 

is likely small and would certainly not result in any measureable air quality difference. The 

following summarizes how mandatory compliance with the fleet NMOG requirement could 

violate the Clean Air Act.

A manufacturer’s fleet NMOG average in Maryland will depend on its particular sales 

mix in Maryland, as determined by Maryland consumers. By virtue of the differences between 

the Maryland and California markets, it is highly unlikely that a manufacturer will sell exactly 

the same products in exactly the same proportions in Maryland as it will in California. If 

Maryland consumers demand a particular manufacturer’s sales mix in Maryland that results in a 

higher fleet NMOG average, the manufacturer may be required to artificially limit sales of 

certain California certified vehicles that Maryland consumers prefer in order to comply with 

Maryland’s fleet average requirement. Such a limitation on the sale of California certified 

vehicles would, at a minimum, be an indirect limit on the sale of a motor vehicle that is certified

to California standards and thus would violate Section 177.

This Section 177 problem does not arise if Maryland only requires manufacturers to 

report fleet NMOG averages. 

2. Maryland’s Proposed ZEV Credit Bank 

The Alliance appreciates Maryland’s efforts to include proportional ZEV credits into §.10 

of the regulation. However, one change is needed to properly account for the Section 177 

provision of California’s regulation (Title 13, 1962, §(d)(3)(D), “Counting a Type III ZEV 

Placed in a Section 177 State”). In developing its ZEV standards, the California Air Resources 

Board (“CARB”) recognized that in light of current technology, mandating a large number of 
Alliance of Automobile Manufacturers Page 5 of 33 October 3, 2007

ZEV vehicles would hamper, rather than help, technology. To accommodate this conclusion, the 

California regulation included a “Section 177 Provision” that effectively counts all “Type III” 

ZEVs (fuel cell vehicles) in any state that adopts the California regulation as if it was placed in 

service in all California states. Thus, under the California regulation manufacturers need to only 

produce the number specified by California regardless of how many states adopt the California 

regulation. To account for the Section 177 provision of the California regulation, the 

Department should:

a. Type III Credit Establishment:

Remove the Type III credits from the manufacturer’s ZEV credit 

bank and establish those credits in the Maryland ZEV credit bank 

directly and without proportionality, since these credits count as if 

they were earned in Maryland.

b. Non-Type III Credit Establishment

Establish the remaining ZEV credits in the Maryland ZEV credit 

bank using the proportionality requirement specified in the 

proposed regulation.

II. The California Greenhouse Gas Regulation 

The motor vehicle greenhouse gas regulation under consideration by the Department was 

adopted by CARB in 2004. This section of the Alliance’s comments begins by providing some 

necessary background on the requirements of the California rule, drawn from the CARB 
Alliance of Automobile Manufacturers Page 6 of 33 October 3, 2007

rulemaking record. It then presents some specific technical issues that the Department should 

address in evaluating the proposal to adopt the California rule in Maryland.

A. Regulatory Background 

Emissions from a wide variety of sources, including power plants, manufacturing 

facilities and automobiles, contribute to air quality concerns. In the case of motor vehicles, the 

principal emissions of concern are unburned hydrocarbons (“HC”) and oxides of nitrogen 

(“NOx”). HC and NOx undergo photochemical reactions in the atmosphere in the presence of 

sunlight to produce ozone, a respiratory system irritant and the principal ingredient of “smog.” 

Carbon monoxide (“CO”) is another pollutant caused by incomplete combustion. Although CO 

slightly contributes to ozone formation, it is primarily regulated because of its direct effect on 

human health, which includes increased stress on the cardiovascular system. 

In order to protect public health, the U.S. Environmental Protection Agency (“EPA”) has 

established primary National Ambient Air Quality Standards (“NAAQS”) for ozone, CO and 

other pollutants.3 These standards define the level of these pollutants that EPA has determined 

to be consistent with the protection of human health with a margin of safety. 

Another byproduct of the combustion of carbon-based fuels, such as wood, coal and 

gasoline, is carbon dioxide (“CO2”). Carbon dioxide is a naturally occurring gas in the air, is 

exhaled by all animals, and is essential to life as we know it. Exposure to carbon dioxide is not 

harmful to human health at concentrations found in the ambient air, and EPA has established no 

 

3 NOx emissions from motor vehicles also form nitrogen dioxide (“NO2”), a pollutant that 

causes a brownish atmospheric coloration and is associated with an increased risk of respiratory 

infection. Emissions of HC and NOx also may be converted to particulate matter (“PM”) in the 

atmosphere.
Alliance of Automobile Manufacturers Page 7 of 33 October 3, 2007

NAAQS for carbon dioxide. The level of carbon dioxide in the atmosphere is an environmental 

issue because it is considered a greenhouse gas. Carbon dioxide and other greenhouse gases in 

the atmosphere reduce the dispersal of solar heat that reaches the surface of the earth. This effect 

is suspected of causing or contributing to global warming. 

In the case of motor vehicles, carbon dioxide emissions are directly related to fuel 

consumption. The only method for significantly reducing carbon dioxide emissions from a 

gasoline-powered motor vehicle is to reduce fuel consumption. The official test procedure used 

to determine compliance with the federal corporate average fuel economy (“CAFE”) standards 

depends on the measurement of carbon dioxide emissions, which is the primary greenhouse gas 

emitted from motor vehicles. The combustion of gasoline is the only source of carbon dioxide 

emissions from motor vehicles, and carbon dioxide emissions constitute the vast majority of 

greenhouse gas emissions from motor vehicles. The table below shows the various categories of 

greenhouse gas emissions from a typical passenger car, adjusted to account for the “global 

warming potential” of each category.4 The adjusted value is expressed in the last column of the 

table in “CO2 equivalent emissions,” as specified in the CARB regulation. 

Baseline Greenhouse Gas Emissions from a Typical Passenger Car

Source Emissions CO2 equivalent emissions

Exhaust CO2 322.48 g/mi 322.48 g/mi

 

4 “Global warming potential” (or “GWP”) is a measure of the heat-trapping potential of a 

particular compound relative to the heat trapping potential of the same mass of carbon dioxide. 

For example, if one pound of the air conditioning refrigerant HFC-134a traps 1300 times more 

heat than one pound of carbon dioxide, then HFC-134a has a GWP of 1300.
Alliance of Automobile Manufacturers Page 8 of 33 October 3, 2007

Exhaust Methane 0.005 g/mi 0.12 g/mi

Exhaust Nitrous Oxide 0.006 g/mi 1.78 g/mi

Direct HFC-134a Emissions 0.007 g/mi 9.00 g/mi

“Indirect” A/C Emissions (CO2) 15.40 g/mi 15.40 g/mi

TOTAL 337.90 348.78 g/mi

CO2 as a Percent of Total 99.99% 96.87%

As indicated on the table, when the estimated greenhouse gas emissions of a typical 

passenger car are weighted for global warming potential, carbon dioxide emissions account for 

nearly 97 percent of the greenhouse gas emissions from passenger cars and light-duty trucks on a 

CO2-equivalent basis. Based on the table, the maximum reduction in CO2-equivalent 

greenhouse gas emissions that can be accomplished without improving fuel economy is just over 

3 percent (100% - 96.87% = 3.13%). The CARB standards require a reduction in CO2-

equivalent greenhouse gas emissions from passenger cars of more than 30 percent.5 For typical 

gasoline-powered vehicles, it will therefore be impossible to meet the CARB regulation without 

reliance on higher fuel economy. 

The de facto fuel economy standards being set by CARB are much more stringent than 

the average fuel economy levels required by the federal fuel economy standards. For example, 

CARB has set a “mid-term” CO2-equivalent (“CO2e”) standard for passenger cars and some 

light-duty trucks of 205 grams per mile (“g/mi”) CO2e. Converted to fuel economy as measured 

 

5 The CARB staff estimated in 2004 that the average CO2-equivalent emissions for passenger 

cars produced by the largest six manufacturers were 312 g/mi for model year 2002. The 

205 g/mi standard applicable in 2016 is 34 percent lower.
Alliance of Automobile Manufacturers Page 9 of 33 October 3, 2007

by the federal regulations, which is equivalent to 43.7 miles per gallon (“mpg”) for a vehicle that 

uses a conventional air conditioning system and that is not designed to reduce nitrous oxide 

(N2O) or methane tailpipe emissions. CARB’s rule mandates 59 percent higher fuel economy 

than required under the Corporate Average Fuel Economy (“CAFE”) standards for passenger 

cars, which is 27.5 mpg. CARB’s regulatory analysis assumes that, but for its new greenhouse 

gas standards, there would be no change in the fuel economy of passenger cars or light-duty 

trucks in the absence of its regulation, through at least 2030.

B. Issues of Controversy

The foregoing summary of the California rule covers the main features of the regulation 

that cannot be considered controversial. Much of the underlying analysis used to support the 

regulation in California, however, involves issues that are in dispute in federal courts in 

California, Vermont, and Rhode Island. The Department needs to take a definitive and fullyexplained position on those issues as they relate to Maryland. Three issues of particular 

importance to the proposal under consideration by the Department are identified below.

1. Nationwide Deployment of the California Greenhouse Gas 

Technologies 

CARB has assumed that once its greenhouse gas rule is implemented, the automobile 

industry will choose to deploy the technologies needed to meet the California standards on at 

least a nationwide (if not global) basis. That assumption is critical to CARB’s estimates of the 

costs for compliance with the California regulation in California and in other states that enforce 

the California rule. If CARB’s assumption is incorrect, then the costs of the California rule for 

consumers in California and other states that enforce the California rule will be much higher than 
Alliance of Automobile Manufacturers Page 10 of 33 October 3, 2007

estimated by CARB. Because the costs of new regulation is important in Maryland, the 

Department needs to make an independent assessment of CARB’s assumption that the industry 

will respond to the regulation by producing vehicles that use all the necessary greenhouse gas 

technologies nationwide. 

CARB’s assumption that the industry would deploy greenhouse gas control technologies 

nationwide, to an extent approaching full penetration of those technologies across the country, is 

certainly not entitled to deference. As CARB has recognized, the greenhouse gas rule will raise 

new-vehicle costs and prices, and will also reduce demand for new vehicles. In one regulatory 

analysis that CARB published prior to its decision to approve the greenhouse gas rule in 

September 2004, the CARB staff estimated that once the greenhouse gas standards were fully 

implemented, new-vehicle sales in California would decline by four to five percent. Other 

estimates predicted larger reductions in sales. 

It would be illogical and contrary to their customers’ interests for automobile 

manufacturers to produce vehicles for which there is less demand, in the absence of a regulatory 

requirement to do so. For that reason, it is unlikely that the industry will try to comply with the 

California greenhouse gas rule by producing all or even most of the necessary technologies at 

nationwide volumes. This means that the cost of the regulation for Maryland consumers will be 

substantially higher than estimated by CARB. 

The Department needs to examine this issue in more detail. Because the industry will not 

pursue nationwide deployment of the greenhouse gas technologies, the Department should 

develop more accurate estimates of the costs of compliance with the regulation for residents of 

Maryland. 
Alliance of Automobile Manufacturers Page 11 of 33 October 3, 2007

2. Reliance on the NESCCAF and CARB Technological Assessments

The Department also needs to confront serious errors in some analyses of the California 

rule arising from the technological assessment prepared by the Northeast States Center for a 

Clean Air Future (“NESCCAF”), on which CARB has relied in part. Significant 

misunderstandings have arisen in the debate about the California rule and its costs. These are 

among the points that the Department needs to consider: 

• To date, neither NESCCAF nor the CARB staff have specifically assessed (1) the 

performance of any specific vehicle actually expected to be in the market when the new rule 

would take effect, or (2) the full range of vehicle types expected in the market. The 

NESCCAF/CARB analysis was limited to vehicle types that the CARB staff or NESCCAF 

considered “representative.” This point was acknowledged in the CARB staff’s Final Statement 

of Reasons, published in August 2005, which stated that “the agency could not reasonably model 

all vehicles with all of the potential climate change emission reduction technologies” identified 

by CARB staff or NESCCAF. The predicted costs and fuel economy impacts of the regulation 

estimated by the CARB staff and NESCCAF are thus no better than the selection of vehicle types 

that the CARB staff or NESCCAF considered “representative.”

• The vehicles that the CARB staff and NESCCAF decided to include in their analysis 

were hardly “representative” of the U.S. motor vehicle fleet, either today or in the future. All or 

nearly all the vehicles included in the analysis had significantly downsized, turbocharged 

engines, which sacrifice reserve power, launch feel and some acceleration performance features, 

and which were based on tests of engines operated on European-specification premium gasoline. 

The hypothetical vehicles were also equipped with automatic manual transmissions. Such 
Alliance of Automobile Manufacturers Page 12 of 33 October 3, 2007

vehicles are hardly typical of the U.S. fleet today or in the future. In particular, it is unrealistic to 

suppose that in the future, most Americans will buy vehicles designed for optimal performance 

on gasoline grades higher than regular unleaded. 

• The principal contractor for the vehicle performance analysis prepared for NESCCAF 

and then used by CARB, a firm called AVL Powertrain Engineering, has confirmed that it was 

not asked to undertake, nor did it undertake, any detailed consideration of launch feel, drive 

quality or the transient response of the engine, transmission and turbocharger, in connection with 

the work for NESCCAF and CARB. The only reported metric for performance was 0-60 mph 

acceleration, and it appears the CARB staff ignored available information from AVL involving 

other acceleration metrics. The Department can confirm the limitations placed on AVL’s work 

by contacting AVL.6 

• Some confusion may arise from the fact that the CARB staff has not always fully 

presented the impact of the regulation on the vehicle powertrain or vehicle performance. For 

example, the CARB staff’s Final Statement of Reasons asserts that in the CARB staff’s 

regulatory analysis, “technology packages that included engine downsizing were not generally 

considered for the truck classes,” and “engine downsizing [was] used primarily for the small car, 

large car, and minivan vehicle classes where vehicle performance can be maintained under all 

driving conditions.” To the contrary, CARB’s regulatory scenario assumed the use of downsized 

 

6 The only apparent issue in controversy with AVL is whether the test data on which its 

modeling is based is representative of vehicles operated on U.S. regular unleaded gasoline as 

well as higher-specification European gasoline. While AVL claims that the modeling is 

representative of operation on U.S. regular unleaded, neither NESCCAF, AVL nor the CARB 

staff has provided data to demonstrate this. The Department should request any such data if it 

plans to rely on the NESCCAF or CARB work. 
Alliance of Automobile Manufacturers Page 13 of 33 October 3, 2007

engines for the truck engines included in the CARB analysis. For one set of standards, the large 

truck engines were assumed to be downsized by 9 to 11 percent. For another set of standards, 

large truck engines were assumed to be downsized by 11 to 15 percent. Small truck engines 

were assumed to be downsized by as much as 19 percent. But common sense indicates that truck 

purchasers are generally not willing to accept downsized engines at the same price as full-size 

engines. If it wants to rely on the analyses prepared in California, the Department needs to 

examine this issue further because it cannot rely on the summary statements from the CARB 

staff.

• Along the same lines, the CARB staff’s Final Statement of Reasons claims that “[i]n 

assessing smoothness and refinement ... staff assumed in the analysis that 6 cylinder engines 

would be replaced by 5 cylinder turbocharged models rather than 4 cylinder versions in order to 

preserve 6 cylinder-like characteristics.” That is incorrect. For the “Large Car” analysis 

performed for NESCCAF, a three-liter, six-cylinder was replaced by a four-cylinder engine with 

a much smaller displacement of 1.77 liters. For the “Minivan” case, a 3.3 liter, six-cylinder was 

replaced by another much smaller 1.85 liter four-cylinder engine. For the “Small Truck” case in 

the NESCCAF study, a 3.4 liter six-cylinder engine was replaced by a smaller 1.64 liter fourcylinder. In addition to “smoothness and refinement,” engines need sufficient reserve power for 

responsive acceleration, full cargo loads, towing, and acceptable “launch” at the start of driving. 

Neither NESCCAF, its contractors, nor the CARB staff, can credibly claim that such radical 

downsizing would have no impact on consumer demand for the redesigned engines.

Elsewhere in the Final Statement of Reasons, however, the CARB staff admits that some 

of the technologies that were evaluated would degrade vehicle performance. This is an 
Alliance of Automobile Manufacturers Page 14 of 33 October 3, 2007

important admission that any proponent of the California rule or any regulatory agency 

considering the California rule needs to address. The assumptions that were actually made in the 

development of the California regulatory analysis are critical because consumer demand will be 

affected by losses in various performance features that are important in the market. The 

consumer demand model used by California in its analysis assumed no loss in any performance 

attribute, which is clearly an invalid assumption for the reasons summarized above. The 

Department therefore cannot appropriately rely on the consumer impacts projected by the CARB 

staff in the California rulemaking -- who, it should be noted, predicted a reduction in consumer 

demand and in sales.7 Because the CARB consumer demand model would have predicted even 

larger reductions in demand and in sales if the degradations in performance had been considered, 

the Department should begin its analysis of the issue by treating the existing CARB estimates as 

the floor, not the ceiling, for cost impacts.8

 

7 Regarding the consumer demand model used by CARB, see pp. 28-30 below. 

8 Some proponents of the California rule rely on simplistic assumptions that all or nearly all 

consumers will apply an estimated long-term cost reduction analysis to a new-car purchase 

decision. The appropriateness of the discount rate assumed in such an analysis needs careful 

review, as explained on pages 28-30 of these comments. Equally important, however, CARB 

commissioned studies for its own rulemaking that demonstrated that such a simplistic analysis is 

not realistic for the new-vehicle market. There is no uniform or average “pay-back” period that 

can be assumed in assessing how this regulation will affect the new-vehicle market -- hence the 

need for the consumer demand models like CARBITS and the models developed for the 

Alliance. If, on the other hand, the Department believes that simple “pay-back” analyses are 

valid or useful, it should supply any available empirical evidence supporting the use of such 

analyses. 
Alliance of Automobile Manufacturers Page 15 of 33 October 3, 2007

3. Credits and Alternative Compliance Mechanisms

Another issue of controversy involves the portions of the CARB rule that describe the 

provisions that supposedly add flexibility for the industry in developing compliance strategies. 

The implication is that the industry can use those features of the California regulation to reduce 

the costs of compliance with the regulation and ease the burden for Maryland consumers. 

While the Alliance does not have access to confidential compliance plans of its members 

or other manufacturers, it questions the assumption that the inter-manufacturer credit provisions 

and alternative compliance features of the California rule will play a significant role in 

compliance with the regulation, either in California or in Maryland. Indeed, the alternative 

compliance features of the California greenhouse gas rule exist in name only -- they are so 

stringent that they appear designed to discourage efforts to comply using any means other than 

the types of fuel economy technologies envisioned in CARB’s main regulatory analysis, and they 

probably could not be used by any major full-line manufacturer. If the Department believes that 

alternative compliance plans will be part of the compliance strategy for manufacturers in 

Maryland, it should provide examples of the types of plans that are both economically 

practicable and approvable under the regulation. 

With regard to inter-company trading, the notion that companies that can accumulate 

credits will sell those credits to other companies is illogical. Such companies will use any such 

credits to reduce their own future compliance costs. Because the regulation will be ultimately 

constraining for all large-volume manufacturers, each such credit-generating company will 

certainly need to use those credits for that purpose in order to minimize its costs of compliance. 
Alliance of Automobile Manufacturers Page 16 of 33 October 3, 2007

It is also critical to note that vehicle manufacturers must plan their fuel economy and 

emissions compliance strategies for a given model year many years in advance. While that 

planning is under way, a manufacturer has no access to the fuel economy strategy or planning 

activities of other unaffiliated manufacturers. Given the competitive nature of the industry, the 

uncertainty that any specific company would have a specific number of credits available to sell, 

and the lead-times required to develop and produce new technologies, it is implausible to 

suppose that any company will be able to include a plan to acquire credits from another company 

in its CO2 compliance strategy. If the Department believes that the industry will be able to 

reduce its compliance burdens significantly with inter-company trading, it should explain why.

4. Grid-Connected Hybrid Vehicles

A third and more technically complex issue of controversy involves the use of a 

particular type of technology to meet the CARB standards. The relevant technology is called 

grid-connected hybrid vehicle technology, or “GHEV” technology. The CARB regulation 

defines a grid-connected hybrid electric vehicle as “a hybrid electric vehicle that has the capacity 

for the battery to be recharged from an off-board source of electricity and has some all-electric 

range.” Such vehicles can be driven without the use of gasoline to the extent that their batteries 

are recharged from the electrical grid and the distance they are driven between recharging is 

equal to or less than their “all electric range” (i.e., the driving range available from the battery 

alone). Beyond the all electric range, the combustion engine is used. 

Under the CARB rule, the formula for calculating the CO2-equivalent emissions of 

GHEVs is [A*E*B*C] + [(1 – A*E*B)*D], where A is the percentage of the vehicles that are 

operated on electricity from the grid; E is 0.9; B is the percent of miles travelled using electricity 
Alliance of Automobile Manufacturers Page 17 of 33 October 3, 2007

from the grid; C is the CO2-equivalent value when the vehicle is operating on electricity from the 

grid; and D is the CO2-equivalent value when the vehicle is operating on gasoline. Although the 

CARB regulation is not clear, it appears that grid-connected HEVs are able to use a value of 130 

g/mi CO2-equivalent when running on battery power (which is the value specified in the 

regulation for “electric vehicles”). Nothing in the regulation provides guidance on the value of 

“B.” The average value of B will be less than 100% because motorists will not be willing to pay 

for a combustion engine if it were never used. Nevertheless, a value of 100% can be used to 

establish a “best case” estimate of the economic feasibility of grid-connected HEVs. One can

estimate the battery size required for a grid-connected HEV assuming a relatively short 20-mile 

all electric range, at 0.34 kWh per mile as the energy requirement for a compact size vehicle. 

That would require a battery capacity of 7 kWh. 

Recently, Tom Austin, Senior Partner of Sierra Research, provided an expert critique of 

various vehicle technology costs for submittal in the litigation before the U.S. District Court. 

This analysis, enclosed as Attachment 2, explains that the retail price increase needed to cover 

the cost of such a battery in a GHEV is about $5,812. Combined with a 100 kW 

motor/generator, inverter, brake-by-wire, electric power steering, electric accessory drive, highvoltage wiring system, and weight reduction measures, the total retail price increase to cover the 

cost for a GHEV would be approximately $12,634.9 This is far greater than the cost of other 

technologies that CARB has identified as capable of meeting the California standards. 

The available evidence thus indicates that grid-connected hybrid vehicles will be 

commercially infeasible for anything other than niche markets that receive substantial public 

 

9 Attachment 2, Expert Rebuttal Report of Thomas C. Austin, p. 12.
Alliance of Automobile Manufacturers Page 18 of 33 October 3, 2007

subsidies.

10 If the Department believes that GHEVs will be a significant factor in 

manufacturers’ compliance plans, it needs to explain why; if not, it should so indicate. To the 

extent that the Department believes that GHEVs will play a significant role, the Department 

should explain why the cost estimates presented above are inaccurate or unpersuasive, or why it 

believes that there will be sufficient public subsidies to support the use of GHEVs. 

III. Environmental Assessment of the Greenhouse Gas Rule in Maryland

It is also important for the Department to address some basic issues about the 

environmental impacts of the California greenhouse gas rule in Maryland. At the outset, it is 

important for the Department to recognize that it cannot attribute any significant reduction in 

global warming, or any other discrete impact on climate, to the implementation of the California 

greenhouse gas rule in Maryland. Even under very optimistic assumptions about the impact of 

the proposed greenhouse gas rule in Maryland, there would be no significant impact on the 

global or Maryland climate. Any theoretical change in temperatures that a rule of this nature 

could produce would, in turn, have no measurable effect on ozone levels in Maryland -- even if 

the proposed greenhouse gas rule were implemented nationwide, if only because the rule will not 

 

10 Others have claimed that GHEVs would provide economic benefits to motorists because they 

can be used to store electrical energy and sell it back to the utilities during periods of peak 

demand. However, analyses of this concept have failed to account for the cost of reducing 

battery life by exposing it to additional charge/discharge cycles. Those analyses also ignore the 

effect of charging/discharging efficiency, which would further increase the cost. In addition, the 

fact that periods of peak electricity demand coincide with peak commute periods means that 

vehicles will be unavailable to sell power back to the grid.
Alliance of Automobile Manufacturers Page 19 of 33 October 3, 2007

have any measurable effect on temperatures. If the Department believes that there is any 

evidence of a positive impact on climate or ozone levels, it needs to identify that evidence. 

A. Increases in Air Pollutants

In addition to having no identifiable impact on global warming, the California rule will 

have adverse impacts on Maryland’s efforts to reduce criteria and precursor pollutants. Two 

important factors will cause the proposed rule to have the unintended effect of increasing 

pollution. The first factor is called the “rebound effect.” When vehicle fuel economy increases, 

the cost of driving declines and vehicle operation increases. That increase in vehicle operation 

increases fleet-wide emissions of criteria and precursor pollutants. The other important factor 

that must be considered is the “fleet turnover effect.” When vehicle prices are increased as a 

result of additional regulation, older vehicles with less effective pollution controls than new 

vehicles remain in operation for longer periods of time than if there were no additional 

regulation. 

Analyses conducted by Sierra Research, NERA, and AIR, filed with U.S. EPA by the 

Alliance on California’s request for a waiver of federal preemption for the AB 1493 regulation, 

and included as Attachment 1, demonstrate that, in the aggregate, California's vehicle emission 

program increases air pollution and is therefore less protective of public health than the federal 

program. Any emissions increases should be unacceptable as a matter of policy, particularly 

when there is no scientific or other evidence that the greenhouse gas rule will have any 

measurable positive effect on the climate of Maryland or any other predictable public-health 

benefit. 
Alliance of Automobile Manufacturers Page 20 of 33 October 3, 2007

B. Safety Issues Related to the Rebound Effect

The Alliance recently challenged Vermont’s adoption of the California greenhouse gas 

rule. Expert testimony at that trial demonstrated that a major impact of the regulation is the 

increased traffic safety risk associated with increased driving -- the “rebound effect.” Dr. 

Laurentius Marais testified that the regulations would have the unintended effect of increasing 

travel congestion, and thus highway accidents, serious injuries and fatalities. Dr. Marais’ expert 

report is included at Attachment 3.

IV. Economic Issues Raised by the Proposed Regulation

The Department appears to have done no analysis of the major cost of compliance with 

the California rule. Other states have incorrectly assumed that cost increases will be confined to 

the increase in the retail price of a new vehicle, and that future savings from reduced gasoline 

consumption will exceed the up-front costs for the purchaser of a new vehicle. Other states have 

also mistakenly assumed that the only costs incurred by consumers will be reflected in higher 

retail prices. 

A. Consumer Valuation of Future Operating Cost Reductions

Proponents of the greenhouse gas rule sometimes claim that increases in initial purchase 

prices for new automobiles subject to the regulation might be offset by the reduced operating 

cost, such as fuel savings, and thus could result in a net savings to the purchaser. Such an 

assumption is not consistent with mainstream economic analysis of how consumers value energy 

cost savings, which recognizes that most consumers apply steep discount rates to the value of 
Alliance of Automobile Manufacturers Page 21 of 33 October 3, 2007

future energy cost reductions. One of the most detailed empirical studies indicates that “only 35 

percent of the present-value cost savings provided by improved energy efficiency is capitalized 

in the purchase price of vehicles.”11 The discount rate used in some of the fuel economy benefit 

calculations in the National Research Council study published in 2002 was 12 percent.12 None 

of these studies has been specifically addressed by the Department or (to the Alliance’s 

knowledge) by the proponents of the proposed regulation in Maryland. If the Department 

believes that a lower discount than one in the 12-percent range is appropriate, it should explain 

why, and should address each of the studies cited here in detail.

Assuming that a new-vehicle purchaser is behaving rationally, the new-vehicle purchaser 

will not assume that when she is ready to sell the vehicle into the used-vehicle market, the 

prospective purchasers will be able to obtain credit at the same loan rate that she can obtain in 

the new-vehicle market. Particularly in the used-vehicle market, “many automobile purchasers 

are liquidity constrained, and therefore face implicit discount rates higher than the market 

level.”13 She will therefore discount the future value of her vehicle in the used-vehicle market 

using a rate higher than the prevailing rates in the new-vehicle market. 

 

11 Howarth, “Fuel Economy Standards,” in Journal of Economic Perspectives, vol. 18 at 272 

(2004), describing Dreyfus et al., “Rates of Time Preference and Consumer Valuations of 

Automobile Safety and Fuel Efficiency,” Journal of Law & Economics, vol. 38, at 79-105 

(1995). According to Prof. Howarth, Dreyfus and Viscusi calculate implicit discount rates for 

safety and fuel economy attributes that range from 11 to 17 percent. 

12 National Research Council, “Effectiveness and Impact of Corporate Average Fuel Economy 

(CAFE) Standards,” Washington D.C. National Academy Press (2002) at 66. The NRC notes 

that its calculations and their results “are not recommended fuel economy goals.” Id. (Emphasis

in original). 

13 Kleit et al., “Increasing CAFE Standards; Still a Very Bad Idea” at 4 (Brookings, June 2004). 
Alliance of Automobile Manufacturers Page 22 of 33 October 3, 2007

B. Opportunity Costs and Losses in Vehicle Utility

The proponents of the greenhouse gas rule also ignore opportunity costs, which are 

important in any mainstream economic analysis of measures like the California rule. The total 

costs of such a rule include, for example, the value of the foregone opportunity to purchase a 

vehicle which may be less fuel-efficient but has other features that a consumer desires more than 

enhanced fuel efficiency. Such features obviously include vehicle performance, safety, capacity, 

comfort and aesthetics. The mainstream economic studies that consider these costs are identified 

in an Attachment 4 to these comments (see pp. 8-13). Those studies are the work of leading 

analysts in the field of environmental regulation. They establish the importance of estimating 

consumer welfare losses when assessing the costs of regulations related to fuel consumption. 

The Department cannot properly ignore such costs that will be borne by Maryland residents. 

Consumers who buy a vehicle, but who are forced to purchase technology or other features 

added or subtracted from the vehicle to meet standards that they would not otherwise prefer, 

incur costs that are real and quantifiable. The Department needs to account for those costs in its 

regulatory assessment. 

V. Legal Issues Presented by the Greenhouse Gas Regulation

The California rule also raises important legal issues that need to be addressed by the 

Department as it decides what action to take. As explained below, adoption of the California 

rule in Maryland would not be consistent with federal law.
Alliance of Automobile Manufacturers Page 23 of 33 October 3, 2007

The Alliance recently challenged Vermont’s adoption of the California greenhouse gas 

rule. The federal legal issues in Maryland are identical to those recently litigated in Vermont.

The main issues arising under federal law are briefly summarized below.

A. The Energy Policy and Conservation Act.

The federal fuel economy statute, the Energy Policy and Conservation Act (“EPCA”), 

provides that “no state ... shall have authority to adopt or enforce any law or regulation related to 

fuel economy standards” once the federal regulations are in place, 49 U.S.C. § 32919(a). The 

Supreme Court has authoritatively construed such use of the term “standards” to mean “that 

which ‘is established by authority, custom, or general consent, as a model or example; criterion; 

test,’” Engine Mfrs. Ass’n v. S. Coast Air Quality Mgmt. Dist., 541 U.S. 246, 252-53 (quoting

Webster’s Second New International Dictionary 2455 (1945)). Thus, any regulation “related to” 

a fuel economy “model,” “criterion” or “test” is expressly preempted by EPCA. The California 

greenhouse gas standard is such a regulation.

The attempts by some proponents to respond to EPCA’s preemption provisions generally 

emphasize the claim that the intent of the California rule is not to regulate fuel economy directly, 

but instead to achieve other objectives. Those arguments ignore the practical, real-world impacts 

of the regulations on the industry and on consumers. In this connection, the Department needs to 

take a position on several fundamental issues, and explain its position in full. 

First, the Department needs to state whether it does or does not expect the California rule 

to require any change in the fuel economy of vehicles that will be sold in Maryland -- either on 

an individual model basis, or fleet-wide. The Alliance assumes from the work performed to date 

that the Department expects such changes because the Department is predicting reductions in 

greenhouse gases. In addition, the Department needs to explain whether it expects such 
Alliance of Automobile Manufacturers Page 24 of 33 October 3, 2007

reductions in the future from both passenger cars and truck models or fleets. Again, it appears 

that the Department expects such changes from both cars and trucks.

Second, the Department needs to take a position on the scope of preemption under the 

federal fuel economy statute. In particular, the Department needs to explain whether it believes 

that the federal law permits a state to establish requirements that have the effect of creating more 

stringent fuel economy requirements within a state than those that would obtain in the absence of 

the state requirements. In addition, the Department would need to explain under what 

circumstances, if any, the federal fuel economy could impliedly, rather than expressly, preempt a 

state regulation that had the effect of requiring fuel economy levels different from those that 

would obtain under federal law. 

The issues presented above are important because some proponents of the California rule 

have suggested that California’s authority under the Clean Air Act, and Section 177 of the Clean 

Air Act, permit adoption of a rule denominated as an “emission standard” so long as the rule 

does not refer expressly to fuel economy standards, and/or if the rule only sets requirements 

more stringent than those under the federal fuel economy law. Those proponents of the 

California rule -- or the Department, if it decides to proceed with the regulation -- need to 

indicate whether federal preemption under the fuel economy statute can be avoided simply by the 

terminology used in the rule or by a determination by the relevant state agency that the rule is no 

less stringent than federal standards. 

B. Other Provisions of Federal Law

Because greenhouse gas emissions pose a global problem, the United States has 

recognized the need for a global solution. Over the past two decades, the United States, through 
Alliance of Automobile Manufacturers Page 25 of 33 October 3, 2007

statutes, treaties, and executive action, has determined that international commitments represent 

the only effective way to reduce the global production of CO2 emissions and to share that burden 

fairly throughout the world. Unilateral efforts by individual states to reduce motor vehicle CO2

emissions will frustrate established foreign policy. The foreign affairs power and the Supremacy 

Clause of the U.S. Constitution therefore preempt the proposed regulation. In addition, the 

California motor vehicle greenhouse gas regulation is invalid under the Dormant Commerce 

Clause of the U.S. Constitution because it excessively burdens interstate commerce in “relation 

to [its] putative local benefits,” Pike v. Bruce Church, Inc. 397 U.S. 137, 142 (1970). In Pike, 

the Supreme Court held that when a state regulation -- even a facially neutral regulation -- effects 

interstate commerce, the detriments to interstate commerce cannot “clearly outweigh the benefits 

to legitimate local public interests.” Id. The question becomes one of degree: “the extent of the 

burden that will be tolerated will of course depend on the nature of the local interest involved.” 

Id. The California greenhouse gas standards would not pass the test in Pike. 

Conclusion

The proposed amendment to Maryland’s motor vehicle emissions regulation will not 

have any significant effect on the condition of concern -- global climate change -- and would 

unlawfully interfere with the CAFE program and with national management of the country’s 

efforts to coordinate greenhouse gas policies at the international level. In addition, 

implementation of the rule would substantially increase emissions of criteria pollutants from 

motor vehicles in Maryland, and would conflict with state and federal law. For the foregoing 
Alliance of Automobile Manufacturers Page 26 of 33 October 3, 2007

reasons, the Alliance recommends that the Department withdraw the proposed regulation, and 

rely instead on the federal motor vehicle control program. 

Respectfully submitted,

ALLIANCE OF AUTOMOBILE MANUFACTURERS
October 3, 2007 

Ms. Debra Rabin 

Regulations Coordinator 

Department of Environment 

1800 Washington Boulevard, Ste 730 

Baltimore, MD 212 30-1720 

Subject:	 Public Hearing to Consider Adoption of Regulations to 

Control Greenhouse Gas Emissions from Motor Vehicles 

Dear Ms. Rabin: 

The Alliance of Automobile Manufacturers (Alliance)! respectfully submits the att ached 

comments in response to the Notice of Public Action to consider adoption of the Low 

Emissions Vehicle Program, Subtitle 11, Section 26.11.34, dated August 31 ,2007. 

Although much of the att ached comments address the prudence of adopting the Low 

Emissions Vehicle Program (e.g., the costs, benefits, legal concerns, etc .), we recognize the 

Maryl and legislature directed the Department of Environment (the Department) to implement 

the Low Emission Vehicle Program rather than det ermine whether to implement the program . 

Recognizing this , we sincerely appreciate the Department's effort to work with the Alli ance 

member companies to develop regulations that incorporate automaker comments, but still 

comply with the dir ection given the Department. With perhaps only one exception (and this 

is not an issue of controversy but rather one of clarification in Section I.B .2 of the attached), 

the department has incorporated all of the issue s raised by manufacturers during the 

regulatory development. The corporation and the resulting regul ations should ensure a 

smoother transiti on for both manufacturers and the Department. 

[ The members of the Alliance of Automobile Manufacturers ("the Alliance") are BMW Group of North 

America, Inc., DaimlerChr ysler Corporation , Ford Motor Company , General Motors Corporation , Mazda North 

American Operation s, Mitsubishi Motor Sales of America, Inc., Porsche Cars North America, Inc., Toyota 

Motor North America, Inc., and Volkswagen of America. Inc. 
Alliance of Automobile Manufacturers Page 2of2 October 3, 2007 

If you have any questions or need additional information, please do not he sitate to call me at 

(20 2) 326 -5538 or Ste ve Douglas at (9 16) 266-4532. 

\S:=t c.: 

Cole 

Manager, State Go vernment Affairs 

Alliance of Automobile Manufacturers 

1401 Eye Street, NW 

Suite 900 

Wa shington, DC 20005 

Enclosures 

2
 
June 15, 2007 

Effectiveness of the California Light 

Duty Vehicle Regulations As 

Compared to Federal Regulations 

 

Prepared for: 

Alliance of Automobile Manufacturers 
Project Team 

This NERA/Sierra/AIR study was directed by David Harrison, Jr., Ph.D., at NERA 

Economic Consulting, Inc. (“NERA”), by James Lyons at Sierra Research, Inc. 

(“Sierra”), and by Thomas Darlington at Air Improvement Resource, Inc. (“AIR”). 

Other NERA participants (in alphabetical order) are James Johndrow, Daniel Radov, 

Bernard Reddy, Ph.D., Paul Reschke, and Svetla Tzenova, Ph.D. Other Sierra 

participants (in alphabetical order) are Tom Carlson, Jeremy Heiken, and Philip 

Heirigs. The other AIR participant is Dennis Kahlbaum. 

Air Improvement Resource, Inc. 

47298 Sunnybrook Lane 

Novi, MI 

48374. 

NERA Economic Consulting 

200 Clarendon Street 

35th Floor 

Boston, Massachusetts 

02116 

Sierra Research, Inc. 

1801 J Street 

Sacramento, California 

95811 
A-1 

Abstract 

This study compares the protectiveness of California’s current light-duty vehicle emission 

regulations (the “California Program”) to analogous federal regulations (the “Federal Program”) 

promulgated by the U.S. Environmental Protection Agency (“U.S. EPA”). The California 

Program and the Federal Program specify similar requirements for exhaust and evaporative 

emissions. There are two primary differences between the California Program and the Federal 

Program: (1) California’s Zero Emission Vehicle (“ZEV”) Standards (“ZEV Standards” or “ZEV 

Mandate”), which require that manufacturers produce and sell specified amounts of vehicles 

certified to specific standards for air pollutants (the Federal Program does not set ZEV 

Standards); and (2) California’s greenhouse gas (“GHG”) exhaust emission standards (“GHG 

Standards”), which establish limits on GHG emission rates for new vehicles in accordance with 

California Assembly Bill 1493 (“AB 1493”). To evaluate the ZEV and GHG Standards, we rely 

on documentation developed by California Air Resources Board (“CARB”) staff describing the 

specific requirements and implementation processes of the Standards. Thus, for the purposes of 

this study, the California Program includes the exhaust and evaporative emission standards, the 

ZEV Standards, and the GHG Standards. In contrast, the Federal Program includes only the 

exhaust and evaporative emission standards. 

We analyze the combined effects of the ZEV and GHG standards, along with all other provisions 

of the California Program, on criteria pollutant emissions from light-duty vehicles in California 

over the period from 2009 to 2023. Emissions under the California Program are compared to a 

fleet and emissions “baseline” that reflects implementation of the Federal Program. Determining 

the effects of the California Program relative to the Federal Program is important, as one of the 

necessary conditions for the U.S. EPA to grant a waiver to California to adopt different vehicle 

emission standards—under Section 209 of the Clean Air Act—is that the California standards be 

“... in the aggregate at least as protective of public health as applicable Federal standards.” 

Our results indicate that the California Program, in the aggregate, is less protective of public 

health than the Federal Program with respect to emissions of ozone precursors and several 

other criteria pollutants.

The emissions results in this report are based upon models that evaluate, among other things, the 

effects of the California Program on the California motor vehicle fleet and on vehicle miles 

traveled (“VMT”) by the fleet relative to conditions that would exist with the Federal Program in 

effect in California. The modeling begins with detailed assessments of ZEV-credit-generating 

technologies and GHG-reducing technologies that could be applied to various types of motor 

vehicles to achieve compliance with the California Program. These assessments result in 

estimates of the impacts of the California Program on costs, prices, emission rates, and other 

attributes (e.g., fuel economy) of new vehicles sold in each year from 2009 to 2023. These 

estimates are based upon a detailed model of the markets for new motor vehicles in California. 

In performing these assessments, we have used conservative assumptions that likely understate 

the impacts of the California Program on both new vehicle prices and vehicle fleet emissions. 

Changes in new vehicle prices and attributes due to the California Program will lead to decreases 

in the rates at which used vehicles are retired from service (“scrapped”). Our analysis of this 
A-2 

effect is based upon the results of a detailed statistical model linking vehicle scrappage rates for 

different vintages to new vehicle prices (among other factors). A decrease in scrappage of used 

vehicles leads to an increase in the average age of the vehicle fleet and thus to increased 

emissions, since older vehicles have higher emission rates than newer vehicles. The modeling 

also takes into account the effect of improvements in fuel economy on VMT (an effect known as 

the “rebound effect”) that leads to increases in emissions due to the greater number of miles 

traveled. The emissions estimates also include effects on emissions of changes in gasoline 

consumption associated with the extraction, processing, and transport of gasoline (referred to as 

“upstream” emissions). 

Figure A-1 shows the results of our analyses of the effect of the California Program relative to 

the Federal Program on emissions of ozone precursors—the sum of volatile organic compounds 

(“VOC”) and nitrogen oxides (“NOx”)—for the State of California from 2009 to 2023. These 

results were developed using the U.S. EPA’s MOBILE6.2 emission factor model. As Figure A-1

shows, our analysis indicates that the California Program will result in higher VOC+NOx

emissions in California than would occur under the Federal Program. We performed the same 

analysis using CARB’s EMFAC2007 emission inventory model, and generated similar results. 

Results for the South Coast Air Basin also show the same effect, modeled with either 

MOBILE6.2 or EMFAC2007. In addition to VOC+NOx, we analyzed emissions of several other 

criteria air pollutants and air toxics. In general, we found that these emissions would be higher 

under the California Program, modeled with either MOBILE6.2 or EMFAC2007. The only 

exception is emissions of sulfur oxides, which decrease as a result of lower gasoline 

consumption under the California Program. 

These results reflect the higher costs associated with compliance with the California Program 

relative to the costs required to comply with the Federal Program, which lead to higher new 

Statewide VOC + NOx (MOBILE)

0

5

10

15

20

25

30

35

40

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure A-1. Change in emissions of VOC + NOx under the combined California Program, relative to 

emissions under the Federal Program. 
A-3 

vehicle prices, reduced new vehicle sales, and increased retention of used vehicles. The results 

also reflect the improvements in fuel economy due to the California Program that result in 

increased VMT and thus increased emissions. 

In summary, our results indicate that the California Program, in the aggregate, is less 

protective of public health than the Federal Program with respect to emissions of ozone 

precursors and several other criteria pollutants.
Contents

i 

Contents 

I. Introduction.............................................................................................................................1 

A. Background......................................................................................................................1 

B. Objectives.........................................................................................................................3 

C. Outline of Report..............................................................................................................4 

II. Methodologies and Data.........................................................................................................5 

A. Overview of ZEV and GHG Standards.............................................................................5 

1. ZEV Standards............................................................................................................6 

2. GHG Standards ...........................................................................................................9 

B. Overview of Methodology.............................................................................................. 11 

C. Compliance Plans and Cost Estimates............................................................................. 12 

1. PZEV Costs............................................................................................................... 12 

2. ATPZEV Costs.......................................................................................................... 13 

3. Pure ZEV Costs......................................................................................................... 13 

4. Selection of Compliance Plans................................................................................... 14 

D. New Vehicle Market Model............................................................................................ 15 

1. Effects Modeled ........................................................................................................ 15 

2. Nested Logit Model................................................................................................... 16 

3. Pricing Decisions by Manufacturers .......................................................................... 18 

E. Scrappage Model ............................................................................................................ 18 

F. Fleet Population Model................................................................................................... 19 

G. Modeling of Effects on Vehicle Miles Traveled (“VMT”) .............................................. 20 

H. Pollutant Emissions Models............................................................................................ 20 

1. Emissions Increases due to Fleet Population Effects.................................................. 21 

2. Emissions Increases Due to Rebound Effect .............................................................. 21 

III. Study Results...................................................................................................................... 22 

A. Motor Vehicle Fleet Effects............................................................................................ 22 

B. VMT Effects................................................................................................................... 24 

C. Fuel Consumption and Upstream Emissions Effects ....................................................... 24 

D. Overall Pollutant Emissions Effects................................................................................ 25 

IV. Conclusions........................................................................................................................ 29 

Appendix A. Compliance Plans and Cost Estimates.................................................................. 30 

Appendix B. New Vehicle Market Model ................................................................................. 36 

Appendix C. Scrappage Model.................................................................................................. 47 

Appendix D. Rebound Effect Analysis...................................................................................... 56 

Appendix E. EMFAC2007 Pollutant Emissions Modeling ........................................................ 63 
Contents

ii 

Appendix F. MOBILE6.2 Pollutant Emissions Modeling.......................................................... 84 

Appendix G. Emissions Impacts Associated with Reduced Gasoline Consumption ................. 101 
List of Figures

iii 

List of Figures 

Figure A-1. Change in emissions of VOC + NOx under the combined California Program, 

relative to emissions under the Federal Program. .............................................................2 

Figure 1. Diagram of modeling framework and process. ...........................................................11 

Figure 2. Hierarchy of NVMM nesting structure. .....................................................................17 

Figure 3. Effects of changes in new vehicle prices on prices of used vehicles...........................19 

Figure 4. Change in statewide 2020 vehicle population estimates as a result of the combined 

California Program, relative to populations under the Federal Program..........................22 

Figure 5. Impacts of the combined California Program on South Coast 2020 Vehicle Population, 

relative to populations under the Federal Program. ........................................................23 

Figure 6. Change in vehicle miles traveled under combined California Program relative to VMT 

under Federal Program. .................................................................................................24 

Figure 7. Change in statewide upstream emissions of NMOG + NOx due to the upstream 

emissions effect under combined California Program (relative to upstream emissions 

under Federal Program). ................................................................................................25 

Figure 8. Change in statewide emissions of VOC+NOx (EMFAC2007 modeling) under 

combined California Program, relative to emissions under Federal Program..................26 

Figure 9. Change in South Coast emissions of VOC+NOx (EMFAC2007 modeling) under 

combined California Program, relative to emissions under Federal Program..................26 

Figure 10. Change in statewide emissions of VOC + NOx (MOBILE6.2 modeling) under the 

combined California Program, relative to emissions under the Federal Program. ...........27 

Figure 11. Change in statewide emissions of South Coast VOC + NOx (MOBILE6.2 modeling)

under combined California Program relative to Federal Program...................................28 

Figure B-1. Nesting structure for NVMM .................................................................................37 

Figure C-1. Vehicle Survival Rates by Age and Model Year.....................................................48 

Figure E-1. EMFAC2007 Passenger Car VOC and NOx Emission Rates (VOC Includes 

Evaporative Emissions).................................................................................................64 

Figure E-2. Example of the Change in Statewide 2020 Vehicle Population Estimates as a Result 

of the Combined California Program.............................................................................72 

Figure E-3. Estimates of the Per-Vehicle Increase in VMT from the Rebound Effect. ..............73 
List of Figures

iv 

Figure E-4. Difference in Statewide emissions of VOC + NOx under combined California 

Program (relative to emissions under Federal Program).................................................76 

Figure E-5. Difference in statewide emissions of NOx under combined California Program 

(relative to emissions under Federal Program). ..............................................................76 

Figure E-6. Difference in statewide emissions of VOC under combined California Program 

(relative to emissions under Federal Program). ..............................................................77 

Figure E-7. Difference in Statewide emissions of CO under combined California Program 

(relative to emissions under Federal Program). ..............................................................77 

Figure E-8. Difference in Statewide emissions of exhaust PM2.5 under combined California 

Program (relative to emissions under Federal Program).................................................78 

Figure E-9. Difference in Statewide sum of emissions of five toxic species under combined 

California Program (relative to emissions under Federal Program). ...............................78 

Figure E-10. Difference in Statewide emissions of SOx under combined California Program 

(relative to emissions under Federal Program). ..............................................................79 

Figure E-11. Difference in South Coast emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program).................................................80 

Figure E-12. Difference in South Coast emissions of NOx under combined California Program 

(relative to emissions under Federal Program). ..............................................................81 

Figure E-13. Difference in South Coast emissions of VOC under combined California Program 

(relative to emissions under Federal Program). ..............................................................81 

Figure E-14. Difference in South Coast emissions of CO under combined California Program 

(relative to emissions under Federal Program). ..............................................................82 

Figure E-15. Difference in South Coast exhaust emissions of PM2.5 under combined California 

Program (relative to emissions under Federal Program).................................................82 

Figure E-16. Difference in South Coast sum of emissions of five toxic species under combined 

California Program (relative to emissions under Federal Program). ...............................83 

Figure E-17. Difference in South Coast emissions of SOx under combined California Program 

(relative to emissions under Federal Program. ...............................................................83 

Figure F-1. Difference in South Coast emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program), not accounting for fuel cycle 

effects ...........................................................................................................................92 

Figure F-2. Difference in South Coast emissions of CO under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......93 
List of Figures

v 

Figure F-3. Difference in South Coast emissions of PM2.5 under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......93 

Figure F-4. Difference in South Coast emissions of SOx under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......94 

Figure F-5. Difference in South Coast emissions of 5 air toxics under combined California 

Program (relative to emissions under Federal Program), not accounting for fuel cycle 

effects. ..........................................................................................................................94 

Figure F-6. Difference in South Coast emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program), accounting for fuel cycle effects.

......................................................................................................................................95 

Figure F-7. Difference in South Coast emissions of CO under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects............95 

Figure F-8. Difference in South Coast emissions of PM2.5 under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects............96 

Figure F-9. Difference in California emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program), not accounting for fuel cycle 

effects. ..........................................................................................................................96 

Figure F-10. Difference in California emissions of CO under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......97 

Figure F-11. Difference in California emissions of PM2.5 under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......97 

Figure F-12. Difference in California emissions of SOx under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects......98 

Figure F-13. Difference in California emissions of 5 air toxics under combined California 

Program (relative to emissions under Federal Program), not accounting for fuel cycle 

effects. ..........................................................................................................................98 

Figure F-14. Difference in California emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program), accounting for fuel cycle effects.

......................................................................................................................................99 

Figure F-15. Difference in California emissions of CO under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects............99 

Figure F-16. Difference in California emissions of VOC+NOx under combined California 

Program (relative to emissions under Federal Program), accounting for fuel cycle effects.

....................................................................................................................................100 
List of Figures

vi 

Figure G-1. Reduction in Summer Season California Fuel Cycle Emissions Due to the 

California Program (California Statewide)...................................................................107 

Figure G-2. Reduction in Summer Season California Fuel Cycle Emissions Due to the 

California Program (South Coast Air Basin)................................................................108 
List of Tables

vii 

List of Tables 

Table 1. Categorization of large and intermediate volume manufacturers included in this 

analysis. ..........................................................................................................................6 

Table 2. Categories of ZEV-credit-generating vehicles, and range of credit values in the years 

2009 - 2030. ....................................................................................................................7 

Table 3. Requirements for large volume manufacturers under the Alternative Compliance Path. 9 

Table 4. Requirements for large volume manufacturers under Primary Compliance Path. ........10 

Table 5. GHG Standards. .........................................................................................................10 

Table A-1. Cost Estimates for ZEV Program Vehicles..............................................................33 

Table A-2. Dollars per ZEV Credit during the period 2009-2023 ..............................................35 

Table C-1. Coefficient estimates for model of age-specific vehicle scrappage rates..................52 

Table C-2. Scrappage elasticities with respect to new car price by car age................................53 

Table D-1. Variables Used in the Irvine Study ..........................................................................58 

Table D-2. Estimation of the VMT Equation.............................................................................61 

Table D-3. California Short- and Long-Run Rebound Effects ...................................................61 

Table E-1. Summary of 2020 Statewide Passenger Car Exhaust VOC Inventory Calculation ...65 

Table E-2. MOBILE6.2 Tier 2 2009 Mix. ................................................................................67 

Table E-3. 2009+ Mix Used in EMFAC2007 to Model Tier 2..................................................68 

Table E-4. Technology Fractions Used for Modeling the California Program...........................68 

Table E-5 Exhaust Toxics Fractions Used to Estimate Toxics for EMFAC2007 (Obtained from 

MOBILE6-MSAT)........................................................................................................71 

Table G-1. California Fuel Cycle Emission Factors (grams/gallon) ........................................102 

Table G-2. Percent Increase in Model Year Fuel Economy California Program Over the Federal 

Program ......................................................................................................................103 

Table G-3. California Statewide Fuel Consumption (Gallons/Day) Vehicles at or below 8,500 

Lbs GVRW, Summer Season ......................................................................................104 
List of Tables

viii 

Table G-4. South Coast Air Basin Fuel Consumption (Gallons/Day) Vehicles at or below 8,500 

Lbs GVRW, Summer Season ......................................................................................104 

Table G-5. California Statewide Fuel Cycle Emissions Reduction (Tons/Day) Due to the 

California Program, Low-End and High-End Values...................................................106 

Table G-6. South Coast Air Basin Fuel Cycle Emissions Reduction (Tons/Day) Due to the 

California Program, Low-End and High-End Values...................................................106 
Introduction 

1 

I. Introduction 

This study evaluates the emissions impacts of the California regulations, including California’s 

exhaust and evaporative emission standards, the ZEV Standards and the GHG Standards, 

(together, the “California Program”) on emissions from new light-duty vehicles in California 

over the period from 2009 to 2023, relative to those that would occur in California under federal 

regulations on emissions from new light-duty vehicles (the “Federal Program”). The ZEV 

Standards and the GHG Standards are the two primary differences between the California 

Program and the Federal Program. To evaluate the ZEV and GHG Standards, we rely on 

documentation developed by California Air Resources Board (“CARB”) staff describing the 

specific requirements and implementation processes of the Standards. The 2009 model-year was 

selected as the starting point for our analysis because that will be the first model-year affected by 

the GHG Standards as well as, according to CARB staff, the model-year by which, for the most 

part, manufacturers will have exhausted previously banked credits used for compliance with the 

ZEV Standards. The 2023 model-year was selected as the ending point for our analysis because 

2023 is the year by which the South Coast Air Basin and all other areas of California must be in 

compliance with National Ambient Air Quality Standard for ozone. 

A. Background 

Emissions from motor vehicles were first associated with air pollution in the early 1950s when 

Professor A.J. Haagen-Smit determined that ozone is formed in the atmosphere by emitted 

volatile organic compounds (“VOC”) and nitrogen oxides (“NOx”) reacting with one another in 

the presence of sunlight. This discovery precipitated the first motor vehicle emission controls 

aimed at reducing emissions of ozone precursors, which were put in place in the early 1960s, 

first by the State of California, and shortly thereafter by the federal government. Motor vehicles 

have also been identified as sources of carbon monoxide (“CO”) and particulate matter (“PM”), 

as well as several air toxic emissions. 

Concerns about “patchwork” state and local regulation of emissions from new motor vehicles led 

to the inclusion of Section 209 in the Clean Air Act of 1970. Section 209 prevents states other 

than California from adopting emission standards for new motor vehicles that differ from federal 

standards, and allows California to do so only if a waiver is granted by the U.S. Environmental 
Introduction 

2 

Protection Agency (“U.S. EPA”). Over the past forty years, CARB has, under the provisions of 

Section 209, established its own control program for emissions from new motor vehicles. One of 

the necessary conditions for the granting of a waiver established in Section 209 is that the 

California standards be “... in the aggregate at least as protective of public health as applicable 

Federal standards.” 

While the federal and California vehicle control programs have differed in a number of ways in 

the past, many aspects, particularly those addressing on-road, heavy-duty, diesel engines have 

recently come into alignment. Moreover, the exhaust and evaporative emission standards under 

Lev II in the California Program are similar to those under Tier 2 in the Federal Program. 

Nonetheless, there are currently two major differences between the California and Federal 

Programs for light-duty vehicles (i.e., vehicles with gross vehicle weight ratings of 8,500 pounds 

or less): 

1. California’s Zero Emission Vehicle (“ZEV”) Standards (“ZEV Standards” or “ZEV 

Mandate”), which require that manufacturers produce and sell specified quanities of vehicles 

certified to CARB’s Partial Zero Emission Vehicle (“PZEV”), Advanced Technology Partial 

Zero Emission Vehicle (“AT PZEV”) and Zero Emission Vehicle ratings; and 

2. California’s Greenhouse Gas (“GHG”) Exhaust Emission Standards (“GHG Standards”) 

which establish limits on GHG emission rates for new vehicles in terms of carbon-dioxide-

(“CO2”)-equivalent emissions. 

The costs imposed on manufacturers to comply with both the ZEV and GHG Standards are 

considerable, and, as documented in a number of studies, these high compliance costs result in 

decreased demand for new vehicles, increased retention of older vehicles, and increased 

emissions of criteria pollutants.

1

 However, our previous studies have not analyzed the combined 

impacts of the entire California Program compared to the Federal Program. 

 

1 That both the ZEV and GHG standards result in higher emissions of criteria pollutants has been extensively 

documented in previous studies submitted to CARB and attached to this study as Attachments A, B and C. 

Attachment A is a January, 2001 report by NERA and Sierra, Impacts of Alternative ZEV Sales Mandates on 

California Motor Vehicle Emissions: a Comprehensive Study. Attachment B is a March 23, 2003 report by NERA 

and Sierra, Impacts of ZEV Sales Mandate on California Motor Vehicle Emissions: Implications of March 2003 
Introduction 

3 

B. Objectives 

This study utilizes a set of sophisticated models that allow for a quantitative comparison of the 

relative efficacy of the California and Federal Programs. The emission estimates presented in 

this study account for six categories of effects resulting from the implementation of the ZEV and 

GHG Standards. 

1. Effects on costs of new motor vehicles. These effects include costs for manufacturing, new 

parts, and other expenses associated with compliance with the California Program, 

incremental to those required to comply with the Federal Program. 

2. Effects on the market for new vehicles. Increases in production costs and modifications to 

vehicle characteristics necessary to comply with the California Program will affect new 

vehicle sales through price increases and changes in vehicle attributes. 

3. Effects on scrappage rates for existing vehicles. Increases in new vehicle prices will result in 

changes in used vehicle markets that will decrease the rates at which used vehicles are retired 

from service (“scrapped”). Decreases in scrappage rates will lead to an increase in the 

average age of the vehicle fleet and to increased emissions, since older vehicles, on average, 

have higher emission rates than new vehicles. 

4. Fleet population effects. The combination of lower new vehicle sales and increased retention 

of older vehicles will affect the overall composition of the motor vehicle fleet in California, 

relative to the fleet composition with the Federal Standards in place. 

5. Effects on vehicle miles traveled (“VMT”). The GHG Standards and the ZEV Standards will 

both result in the implementation of various technologies that improve the fuel economy of 

new vehicles. Improved fuel economy will lower the cost of driving, leading vehicle owners 

to drive more miles each year. This effect, referred to as the “rebound effect,” will tend to 

increase emissions, as emissions are directly related to VMT. 

 

Proposal. Attachment C is a September, 2004 report by NERA and Sierra, Environmental and Economic Impacts 

of the ARB Staff Proposal to Control Greenhouse Gas Emissions from Motor Vehicles. 
Introduction 

4 

6. Emissions effects. Changes in the composition of the motor vehicle fleet, fleet VMT, and fuel 

consumption resulting from the California Program will result in changes in vehicle 

emissions in California, relative to those that would occur if the Federal Program were in 

effect. 

C. Outline of Report 

The remainder of this report is organized as follows: Chapter II provides an overview of the 

methodologies and data that are used in this study; Chapter III presents the results of the 

analyses; and Chapter IV provides brief conclusions. The appendices provide details on the 

methodologies and data, as well as supplemental results. 
Methodologies and Data 

5 

II. Methodologies and Data 

This chapter provides summary information on the methodologies and data used to estimate the 

effects of the California Program. This chapter focuses only on the primary differences between 

the California Program and the Federal Program—namely the ZEV and GHG Standards; 

however, all modeling of the California and Federal Programs includes the full set of applicable 

light-duty vehicle emission standards. As noted, the appendices to this report provide details on 

the methodologies and data. 

A. Overview of ZEV and GHG Standards 

This section summarizes the requirements of the ZEV and GHG Standards, and the implications 

of these standards for the per-vehicle cost and fuel economy of new vehicles sold in California. 

In this study, we assume, based on recent statements by CARB staff,2that manufacturers will 

not, in general, incur significant compliance costs (beyond any already incurred) due to the ZEV 

Standards prior to the 2009 model-year. The GHG Standards do not cover vehicles before the 

2009 model-year. Therefore, for the purposes of this study, we have modeled both the ZEV and 

GHG Standards as taking effect with the 2009 model-year. 

The requirements of both the ZEV Mandate and the GHG standards vary depending on the 

number of vehicles a manufacturer sells annually in California. Although the requirements are 

complicated, in general, large volume manufacturers are defined as those that sell more than 

60,000 vehicles per year in California, intermediate volume manufacturers are defined as those 

that sell between 3,001 and 60,000 vehicles per year and small volume manufacturers are defined 

as those that sell 3,000 vehicles per year or less. The provisions of the ZEV and GHG Standards 

that will lead to substantial compliance costs generally apply only to large volume 

manufacturers. However, those manufacturers account for the vast majority of vehicle sales in 

California. Based on 2003 California vehicle sales data from R.L. Polk, and anticipated growth 

in vehicle sales between then and the 2009 model-year, we have used the manufacturer 

designations shown in Table 1 to determine compliance obligations. Note that small volume 

manufacturers have no obligations under the ZEV or GHG Standards. 

 

2 California Air Resources Board, 2007, “Status Report on the California Air Resources Board’s Zero Emission 

Vehicle Program.” 
Methodologies and Data 

6 

1. ZEV Standards 

The ZEV Standards require that manufacturers “produce, deliver for sale, and place in service” a 

sufficient number of ZEV-credit-generating vehicles to meet the ZEV obligation specified by the 

ZEV Mandate for every year after the ZEV Mandate takes effect. The ZEV Mandate defines 

three categories of vehicles capable of generating ZEV credits: 

1. Partial Zero Emission Vehicles (“PZEVs”), which include conventional vehicles that meet 

very stringent exhaust and evaporative emission requirements and warranty requirements; 

2. Advanced Technology PZEVs (“ATPZEVs”), which consist of various types of hybrid 

electric vehicles;3and 

3. Zero Emissions Vehicles (“ZEVs”), which include battery electric and hydrogen fuel cell 

vehicles. 

Credits generated by PZEVs, AT PZEVs, and ZEVs are referred to as “Bronze,” “Silver,” and 

“Gold” credits, respectively. Table 2 provides some examples of the levels of ZEV credits and 

credit designations associated with specific types of vehicles over the period from 2009 to 2023. 

 

3

It should be noted that other types of vehicle technologies such has hydrogen fueled spark ignition and compressed 

natural gas could be certified as AT PZEVs. However, based on confidential information we have received from 

vehicle manufacturers, we do not believe that any manufacturer plans to market such vehicles in significant 

quantities. 

Table 1. Categorization of large and intermediate volume manufacturers included in this analysis. 

Manufacturer Category

BMW Large Volume

Daimler-Chrysler Large Volume

Ford Large Volume

General Motors Large Volume

Honda Large Volume

Hyundai Large Volume

Mitsubishi Intermediate Volume

Nissan Large Volume

Subaru Intermediate Volume

Toyota Large Volume

Volkswagen* Large Volume

 

* Note that Volkswagen includes Porsche vehicles. 
Methodologies and Data 

7 

The ZEV Mandate specifies two ways in which manufacturers may determine their ZEV credit 

obligation. The ZEV obligation is the minimum number of ZEV credits that a manufacturer is 

required to generate in any given year, and is expressed as a percentage of the manufacturer’s 

total sales volume of covered vehicles, which may either be current year sales (current year 

method) or the average of sales in fixed blocks of three earlier years (prior year method). The 

covered vehicle sales volume always includes 100% of the sales of Passenger Cars (“PCs”) and 

Class 1 Light Duty Trucks (“LDT1s”), while the coverage of Class 2 Light Duty Trucks 

(“LDT2s”) increases nearly linearly from 51% in 2009 to 100% in 2012 and beyond. 

In calculating their ZEV obligations for each year, large volume manufacturers may either use 

the “Primary Requirements” (or “Primary Compliance Path”) or the “Alternative Requirements” 

(or “Alternative Compliance Path”). The Alternative Compliance Path sunsets with the 2017 

model-year, and thereafter the Primary Requirements apply to all large volume manufacturers. 

Both compliance options set the same fixed percentage ZEV obligation in each year, and specify 

a minimum portion of the required ZEV credits that must be generated by pure ZEVs, and a 

Table 2. Categories of ZEV-credit-generating vehicles, and range of credit values in the years 2009 - 2030. 

Technology Category

Credit Range

(2009 - 2030)

PZEV Bronze 0.2

Class A Hybrid Electric Vehicle (AHEV) Silver 0

Class B Hybrid Electric Vehicle (BHEV) Silver 0

Class C Hybrid Electric Vehicle (CHEV) Silver 0 - 0.4

Class D Hybrid Electric Vehicle (DHEV) Silver 0.6 - 0.45

Class E Hybrid Electric Vehicle (EHEV) Silver 0.7 - 0.55

Plug-in Hybrid Electric Vehicle (PHEV) 10 Silver 1.88 - 2.03

Plug-in Hybrid Electric Vehicle (PHEV) 20 Silver 2.05 - 2.20

Plug-in Hybrid Electric Vehicle (PHEV) 40 Silver 2.34 - 2.49

Neighborhood Electric Vehicle (NEV) Gold 0.15

TYPE 0 Electric Vehicle Gold 1.0

Type I (City Electric Vehcile, "CEV") Gold 2.0

Type II (Full Performance Battery Electric Vehicle, "FPBEV") Gold 3.0

Type III (Fuel Cell Electric Vehicle, "FCEV") Gold 3.0 - 4.0

 

Source: Calculated from CARB documentation of ZEV Standards. 
Methodologies and Data 

8 

maximum portion that may be generated by PZEVs. The difference between the sum of the ZEV 

and PZEV credits and the total ZEV requirement may be made up by credits generated by AT 

PZEVs. There are three major differences between the Primary Requirements and the 

Alternative Requirements: 

1. The minimum ZEV requirement is a fixed percentage of the total covered sales volume under 

the Primary Requirements. For example, under the Primary Compliance Path, if a 

manufacturer’s average yearly sales of covered vehicles from 2006-2008 is 200,000 (roughly 

ten percent of yearly industry-wide sales of covered vehicles in California), then that 

manufacturer would need to generate 6,000 Gold ZEV credits (three percent of its covered 

sales) in each year from 2012-2014 (using the prior year method to determine obligation), 

which equates to 2,000 pure ZEVs per year. However, under the Alternative Requirements, a 

target number of total Gold ZEV credits for the industry is specified for each three-year 

period, and each manufacturer’s Gold ZEV credit obligation is calculated as the ratio of the 

manufacturer’s total ZEV obligation in that period to the sum of the ZEV obligations for all 

manufacturers during that period, multiplied by the target number of total Gold ZEV credits 

for the industry for that period. For example, under the Alternative Compliance Path, if a 

manufacturer’s sales of covered vehicles from 2006-2008 account for ten percent of industrywide sales of covered vehicles from 2006-2008, then that manufacturer would need to 

generate 7,500 Gold ZEV credits (ten percent of the Gold ZEV credit target for the industry) 

during the entire period from 2012-2014 (using the prior year method to determine 

obligation), which equates to 2,500 pure ZEVs over the period, or about 833 pure ZEVs per 

year. In general, the Alternative Requirements require fewer pure ZEV sales than the 

Primary Requirements. Under the Alternative Compliance Path, manufacturers can make up 

the reduced Gold ZEV credit obligation with credits generated by AT PZEVs to meet their 

total ZEV obligation. 

2. Under the Primary Requirements, manufacturers are permitted to satisfy their Gold credit 

requirements using any of the Gold category vehicles listed in Table 2. Under the alternative 

requirements, Gold credits must be obtained from Fuel Cell Electric Vehicles (“FCEVs”). 
Methodologies and Data 

9 

3. The Primary Requirements permit the use of either the prior year or current year method for 

determining ZEV obligations. The Alternative Requirements require use of the prior year 

method. 

Based on the high costs associated with generating Gold ZEV credits with either battery electric 

or fuel cell vehicles, and based on discussions with vehicle manufacturers regarding their ZEV 

compliance plans, we have assumed, for the purposes of this study, that all large volume 

manufacturers would choose to meet the Alternative Requirements until they sunset with the 

2017 model-year (see Appendix A for a full analysis of compliance plan options and choices). 

The requirements for large volume manufacturers using the Alternative Compliance Path are 

summarized in Table 3. Intermediate volume manufacturers may meet their entire ZEV 

obligation with credits generated by PZEVs, and small manufacturers are not covered by the 

ZEV mandate. 

The Primary Requirements also set a fixed percentage ZEV obligation in each year. However, 

under the Primary Requirements, the Gold ZEV credit obligation is more stringent than under the 

Alternative Requirements. Table 4 summarizes the Primary Requirements. 

2. GHG Standards 

The GHG Standards establish a set of CO2 emission rate standards for large volume 

manufacturers that apply to 2009 and subsequent model-year vehicles, with a “near-term” 

standard phased in from 2009 to 2012 and a “mid-term” standard phased in from 2013 to 2016. 

 

4 Note that the Pure ZEV credit requirement is given as a total number of credits required, rather than as a share of 

prior year production volume. Each manufacturer’s share of the total number of credits is calculated for each 

three-year block in accordance with the methodology described in CARB documentation of the ZEV Standards. 

Table 3. Requirements for large volume manufacturers under the Alternative Compliance Path. 

Model Years

Minimum ZEV Requirement 

(as share of prior year 

production volume)

Percentage LDT2 Included 

in ZEV Obligation (Range)

Target Number of 

FCEV Credits

Maximum PZEV Credits 

(as share of prior year 

production volume)

2009 - 2011 11% 51% - 85% 10,000 6.00%

2012 - 2014 12% 100% 75,000 6.00%

2015 - 2017 14% 100% 150,000 6.00%

2018 - 16% 100% Sunsets 6.00%

Source: CARB documentation of ZEV Standards.4
Methodologies and Data 

10 

Table 5 shows the CO2-equivalent standards for the two categories of vehicles to which they 

apply: PC/LDT1 and LDT2+. Note that “LDT2+” includes LDT2s and certain medium duty 

vehicles (“MDVs”). 

This study estimates the effects of the GHG Standards based upon a detailed analysis of 

manufacturer technology choices and their costs and effectiveness that was submitted to CARB 

in 2004, and which formed the basis of our previous analysis of the emissions impacts associated 

with the GHG standards (see Attachment C for details). Our estimates of the per-vehicle costs of 

the GHG Standards were developed based on the assumption that each covered manufacturer 

minimizes its costs (for all of its covered vehicles) of meeting the final 2016 mid-term standard. 

The costs for intervening years are based upon assessments of the mix of the final compliance 

technologies that would be employed by each manufacturer for different vehicle types. We 

developed a separate trajectory of per-vehicle costs and fuel economy changes for each of four 

vehicle types: (1) passenger cars; (2) minivans; (3) pick-up trucks; and (4) sport-utility vehicles 

(“SUVs”). 

Table 4. Requirements for large volume manufacturers under Primary Compliance Path. 

Model Years

Minimum ZEV Requirement 

(as share of prior or same 

year production volume)

Percentage LDT2 

Included in ZEV 

Obligation (Range)

Pure ZEV Requirement (as 

share of prior or same year 

production volume)

Maximum PZEV Credits (as 

share of prior year production 

volume)

2009 - 2011 11% 51% - 85% 2.50% 6.00%

2012 - 2014 12% 100% 3.00% 6.00%

2015 - 2017 14% 100% 4.00% 6.00%

2018 - 16% 100% 5.00% 6.00%

Source: CARB documentation of ZEV Standards. 

Table 5. GHG Standards. 

Tier Year

PC/LDT1 LDT2+

2009 323 439

Near-term 2010 301 420

2011 267 390

2012 233 361

2013 227 355

Mid-term 2014 222 350

2015 213 341

2016 205 332

CO2 - Equivalent Emission 

Standard by Vehicle Category 

(g/mi)

Source: CARB documentation of GHG Standards. 
Methodologies and Data 

11 

B. Overview of Methodology 

The overall methodology developed for this study consists of a set of inter-related models 

designed to evaluate the effects of the California Program on the California vehicle fleet and on 

California fleet emissions. Figure 1 shows the primary components of the modeling framework. 

These components include: (1) the Engineering Cost Model, which develops expected 

compliance plans for individual manufacturers based on information on the available 

technologies and strategies for compliance with the ZEV and GHG Standards, including data on 

the costs and emissions reductions, as well as the ZEV credit value, of each technology; (2) the 

New Vehicle Market Model (“NVMM”), which estimates the impacts of the regulations on the 

prices and quantities of various new motor vehicle models, taking as inputs the costs and vehicle 

characteristic (e.g., fuel economy) effects, as well as the ZEV credit value, of the various 

technologies in manufacturers’ compliance plans; (3) the Scrappage Model, which estimates the 

effects of changes in the prices of new vehicles on the rate at which used vehicles are scrapped; 

(4) the Fleet Population Model, which estimates the effects of changes in new vehicle sales and 

the scrappage rates of existing vehicles on overall vehicle fleet populations over time; (5) the 

VMT Model, which assesses effects on vehicle miles traveled; and (6) the Emissions Model 

which assesses effects on pollutant emissions. The following sections provide summaries of the 

New Vehicle 

Market Model

Scrappage

Model

VMT and 

Emissions 

Models

Outputs from 

Engineering 

Cost Model

Engineering 

Cost

Model

Costs and 

emissions 

reductions of 

universe of 

potential 

compliance 

technologies

Set of Optimal

Compliance 

Technologies

Prices and

Quantities of

New Vehicles

Fleet Turnover 

Effects 

(Scrappage)

Fleet VMT 

and Criteria 

Emissions

Outputs from 

New Vehicle 

Market Model

Fleet 

Population

Model

§Outputs from 

New Vehicle 

Market Model 

and Scrappage

Model. 

§ Baseline Fleet 

Populations.

Composition/ 

Size of Fleet 

Over Time

Outputs from 

Fleet 

Population 

Model

Inputs

Model

O

utputs

Figure 1. Diagram of modeling framework and process. 
Methodologies and Data 

12 

six models, including various subcomponents and related data. 

C. Compliance Plans and Cost Estimates5

The starting point for this study was the development of estimates of vehicle costs 

associated with the ZEV and GHG Standards. As discussed below (and in more detail in 

Appendix A), these cost estimates are incremental to the costs associated with the production of 

a conventional gasoline-fueled Super-Ultra Low Emission Vehicle (“SULEV”); the incremental 

costs of SULEVs relative to federal Tier 2 vehicles were ignored. To the extent that SULEVs 

cost more than equivalent Tier 2 vehicles, this would tend to understate vehicle costs under the 

California Program relative to the Federal Program. Estimates of costs for compliance with the 

ZEV Mandate were developed for the three categories of vehicles capable of generating ZEV 

credits: (1) Partial Zero Emission Vehicles (PZEVs); (2) Advanced Technology Partial Zero 

Emission Vehicles (ATPZEVs), and; (3) Zero Emission Vehicles. Within these categories, 

separate cost estimates were developed for vehicles employing different technologies and for 

distinct vehicle classes (PC+LDT1 and LDT2). Compliance costs associated with the GHG 

Standards used in this analysis were developed previously by Sierra and supplied to CARB at the 

time the GHG regulations were adopted in Sierra’s 2004 report.6

In estimating the costs of vehicles required for the ZEV mandate, a number of different sources 

of information were used, including the recently published “Report of the ARB Independent 

Expert Panel 2007,” confidential cost information supplied by individual auto manufacturers, 

and cost estimates provided by The Martec Group and Harbour Consulting. As described below, 

we elected to make conservative assumptions in preparing these cost estimates that likely 

underestimate the true costs. 

1. PZEV Costs 

Incremental cost estimates for PZEV technology of $350 and $500 per vehicle were used for 

PC+LDT1 and LDT2 vehicles, respectively. The PC+LDT1 value reflects the lower range of the 

 

5 All costs referred to in this section and in Appendix A are in year 2004 dollars. The NVMM escalates these to 

year 2005 dollars using the Consumer Price Index in order to be consistent with other data used in the modeling. 

6 Austin, T.C., et al., 2004, “Review of the August 2004 Proposed CARB Regulations to Control Greenhouse Gas 

Emissions from Motor Vehicles: Cost Effectiveness for the Vehicle Owner or Operator”, Sierra Research Report 

No. SR2004-09-04, September, 2004. 
Methodologies and Data 

13 

cost data supplied by vehicle manufacturers, while the LDT2 value reflects the middle of that 

range. The use of the higher value for LDT2 reflects the higher expenses of achieving the zeroevaporative emission standard for PZEVs under the ZEV Mandate on vehicles with larger fuel 

tanks and the higher expenses of achieving the exhaust emission standard for PZEVs under the 

ZEV Mandate on larger vehicles with V8 engines. 

2. ATPZEV Costs 

Incremental cost estimates for Type C, D and E hybrid electric vehicles were $1,800, $2,200 and 

$5,500, respectively. These are based on the methodology documented in Sierra’s 2004 report, 

with the estimates for Type D and E vehicles reflecting additional costs associated with high 

voltage electrical systems, nickel-metal hydride batteries, electric motors and control systems. 

The cost of plug-in hybrid electric vehicles (PHEVs) with 10, 20 and 40 mile electric range in 

the PC+LDT1 category was estimated using component cost estimates provided by The Martec 

Group (the consulting firm relied on by CARB to provide cost information in support of the 

GHG rulemaking), and data from the report of the Independent Expert Panel. Incremental cost 

estimates ranged from about $10,500 for a 10 mile all electric range to about $15,000 for a 40 

mile all electric range. Costs for LDT2 vehicles were again estimated by scaling the PC+LDT1 

values by the relative sales-weighed average weights of 2003 model-year vehicles in these 

classes. Estimates for Type C, D and E hybrid electric vehicles are based on the methodology 

documented in Sierra’s 2004 report, but have been updated to reflect the latest available cost 

data. The cost of plug-in hybrid electric vehicles (PHEVs) in the PC+LDT1 category has been 

estimated using component cost estimates provided by The Martec Group (the consulting firm 

relied on by CARB to provide cost information in support of the rulemaking for the GHG 

Standards), and data from the report of the Independent Expert Panel. Costs for LDT2 vehicles 

were estimated by scaling the PC+LDT1 values by the relative sales-weighed average weights of 

2003 model-year vehicles in these classes. 

3. Pure ZEV Costs 

We estimate a cost for Neighborhood Electric Vehicles (“NEVs”) of $8,000, based on the 

nominal $8,000 price of NEVs produced by Global Electric Motors. Because of their limited 

range and performance, NEVs are unlikely to be general replacements for conventional vehicles, 

although they would displace some conventional vehicle travel. Therefore, NEV purchase was 
Methodologies and Data 

14 

viewed as a cost in addition to owning a conventional vehicle. Incremental costs for City 

Electric Vehicles were assumed to be equal to $13,122 which is the cost of the vehicle battery. 

Utility EV costs were assumed to be 2/3 that of a city electric vehicle given the respective range 

requirements of 50 and 75 miles. 

The cost of full performance battery electric vehicles (FPBEV) was also estimated using data 

from Martec. In the case of pure electric vehicles, the cost of electric motors and power 

electronics is sometimes assumed to be offset by the cost savings associated with elimination of 

the internal combustion engine and transmission. However, using cost information provided by 

Martec and Harbour Consulting, the net cost of the non-battery changes is about $2,500 for a 

full-function EV with a 100 mile range. Using the simple assumption that only the battery cost 

need be accounted for, the incremental cost increase associated with a full-function EV is 

$26,400. If the range is reduced to 75 miles, the cost increase drops to about $19,900. For this 

study, we replaced the more realistic Martec battery cost estimates with the Expert Panel’s 

average cost estimates for lithium-ion batteries, and then added the net cost of the non-battery 

changes described above. We used the lower volume cost estimate through the 2012 model-year 

and then linearly transitioned to the high volume cost estimate for 2015 and later model-years. 

This resulted in a near term incremental cost estimate of about $23,000 for a FPBEV and a 

longer term incremental cost of about $17,000. 

The incremental cost of fuel cell electric vehicles (FCEVs) was estimated using the average of 

the Expert Panel’s best case current and 2015 estimates for fuel cell system costs in high volume 

production, and an assumed stack rating of 100 kW. The current best-case costs were used 

through the 2012 model-year, and then linearly transitioned to the 2015 value in that year and 

beyond. Thus, the incremental costs assumed for FCEVs were about $60,000 in the short term 

and about $11,000 in the longer term. 

4. Selection of Compliance Plans 

Using the cost estimates described above, we estimated the costs per ZEV credit for a wide 

variety of vehicles (as described in detail in Appendix A). Based on this, we determined that the 

most cost-effective approach for compliance with the ZEV Standards would be for large volume 

manufacturers to pursue the Alternative Compliance Pathway through the 2017 model-year, and 

then to continue production of FCEVs to meet their “Gold” ZEV credit obligations thereafter. 
Methodologies and Data 

15 

We also determined that, under the conservative (e.g., low-cost) assumptions used in this study, 

manufacturers would not be required to deploy advanced (Type E) hybrid electric vehicles in 

order to comply with the GHG standards. As a result, we assumed that manufacturers would 

produce Type D HEVs that comply with the AT PZEV requirements in order to generate 

“Silver” ZEV credits. We also assumed that manufacturers would use PZEVs to generate 

“Bronze” ZEV credits to the extent allowed under the ZEV Standards. 

We assume that manufacturers preferentially incorporate AT PZEV and PZEV technologies into 

PCs and LDT1s because the costs of doing so are lower than the costs of incorporating them into 

LDT2s. However, some manufacturers with a relatively high percentage of sales from LDT2s 

must develop some LDT2 PZEV and AT PZEV platforms in order to comply with the ZEV 

Standards. We model the penetration of PZEV and AT PZEV technologies into LDT2s to the 

extent necessary for manufacturers to achieve compliance.

As noted above, the Alternative Compliance Path requires Large Volume Manufacturers to 

generate ZEV credits by producing Fuel Electric Cell Vehicles (“FCEVs”) based on hydrogen 

fuel cells. FCEVs face major challenges associated with the lack of a hydrogen refueling 

infrastructure in addition to the high costs associated with FCEV development and production. 

As stated above, we have relied upon highly optimistic (“best case”) assumptions regarding the 

costs of FCEVs. In addition, we have also made optimistic assumptions about the demand for 

FCEVs (see Appendix B). 

D. New Vehicle Market Model 

This section summarizes the major data and methodologies used to develop the New Vehicle 

Market Model (“NVMM”). A detailed description of the New Vehicle Market Model is 

provided in Appendix B. 

1. Effects Modeled 

The ZEV and GHG standards will affect the market for new vehicles in California in several 

ways. Our modeling framework includes the elements listed below. 

§ Relevant additional costs incurred by manufacturers to modify motor vehicles to achieve the 

GHG emission reductions required for compliance with the GHG standards and/or relevant 
Methodologies and Data 

16 

additional costs incurred to modify vehicles to qualify as PZEVs, AT PZEVs, or ZEVs as 

required by the ZEV standards. 

§ Benefits to consumers of improvements to vehicle fuel economy.

7

§ Shifts in the mix of new motor vehicles due to these additional costs, which differ by type of 

vehicle, model, and manufacturer. 

§ Substitution towards vehicles produced by Intermediate Volume Manufacturers and Small 

Volume Manufacturers. This is relevant for both the GHG Standards, which do not require 

Intermediate Volume Manufacturers to meet the 2012 standards until 2016, and for the ZEV 

Standards, which allow Intermediate Volume Manufacturers to fulfill their ZEV 

requirements using PZEVs. (Neither regulation imposes requirements on Small Volume 

Manufacturers).

2. Nested Logit Model 

The NVMM is a nested logit model. Appendix B provides details of the nested logit framework 

and the data used to develop the model. Economists and other analysts have used nested logit 

models to evaluate factors affecting the demand for motor vehicles and other goods.8 Nested 

logit models have also have been used in court proceedings to evaluate the effects of mergers and 

other changes in market conditions (see, e.g., Werden, Froeb and Tardiff 1996), and in various 

settings to evaluate the potential market demand for new products and services (see, e.g., Tardiff 

1998). 

The “nests” in the nested logit model refer to the structure assumed for consumer choices in the 

new vehicle market. Our model assumes that consumers face decisions structured regarding the 

purchase of a new motor vehicle, as shown in Figure 2 (described in more detail in Appendix B). 

Consumers choose whether to purchase a new vehicle or not. Conditional on the choice to 

 

7 The NVMM does not attempt to account for losses to consumers due to weight reductions that could result if 

manufacturers comply with the GHG Standards by intentionally reducing vehicle weight; such weight reductions 

would be viewed negatively by consumers, assuming other attributes are held constant, and therefore would be 

expected to increase the fleet impacts due to the GHG Standards. 

8 Dr. Daniel McFadden was awarded the 2000 Nobel Prize in Economics largely for his development of the logit 

model. 
Methodologies and Data 

17 

purchase a new vehicle, they select the type of vehicle from among three major vehicle types—

cars, SUVs/minivans, and trucks. Conditional on the choice of a vehicle type, they select a 

specific vehicle category. Our model includes a total of 15 vehicle categories, including six 

passenger cars, six SUVs/minivans, and three trucks/vans (e.g., pick-ups and full vans). Finally, 

conditional on the choice of a vehicle class, consumers choose from the vehicle models that are 

available in that class. 

This structure provides for a rich pattern of own- and cross-price elasticities for different vehicle 

models. The empirical estimates provide information on more than 200 separate vehicle models 

in each year. The aggregate new vehicle price elasticity is assumed to be –1.0, a value consistent 

with the empirical literature.9 New vehicle manufacturers are assumed to be profit-maximizing 

firms. The empirical formulation of the logit model used in this study is based upon new vehicle 

sales, price, and characteristics information for the years 2001 through 2005. 

The NVMM estimates the effects of the ZEV and GHG standards on new vehicle prices and 

sales.10 The model allows for consumer substitution among vehicles that are affected 

differentially by the regulations. Vehicles produced by manufacturers with lower sales volumes 

are subject to less stringent emissions standards under the GHG standards in the early years of 

the regulation and thus have lower cost increases and corresponding fuel economy changes 

during those years. Under the ZEV Standards, intermediate volume manufacturers may meet 

 

9

c.f. Gruenspecht (2000) in Appendix B. 

10 All nine large volume manufacturers, as well as the intermediate volume manufacturers in Table 1, are modeled in 

the NVMM using the cost estimates and compliance plans described above. 

Buy/Don’t Buy

Vehicle Type

Vehicle Class

Vehicle Model

Figure 2. Hierarchy of NVMM nesting structure. 
Methodologies and Data 

18 

their entire ZEV obligation with credits generated by PZEVs. The model allows for these 

differences to be reflected in changes in vehicle sales by model and manufacturer. 

3. Pricing Decisions by Manufacturers 

The California Program imposes several requirements on intermediate and large volume 

manufacturers that influence their profit-maximizing pricing strategies. For example, 

manufacturers must generate at least some number of ZEV credits each year, and some share of 

these credits must be generated using specific technologies (e.g. PZEV, AT PZEV, or ZEVqualifying technology choices). Moreover, the number of credits required is dependent on 

vehicle sales in prior years. The NVMM accounts for these influences and their lagged structure 

in forecasting the effects of the ZEV and GHG standards. 

E. Scrappage Model 

The Scrappage Model estimates the effect of changes in the new vehicle market—including 

prices and quantities of different types of vehicles sold—on the rate at which used vehicles are 

retired from service (“scrapped”). It is a statistical model that estimates how scrappage rates 

respond to changes in the prices of new vehicles, as well as to changes in a variety of other 

variables. 

Previous research has established that new vehicle prices affect used vehicle scrappage rates.

11

When the prices of new vehicles increase, the values of used vehicles also increase, and vehicle 

owners retain them for a longer period of time. Figure 3 illustrates how a change in new vehicle 

prices causes an increase in the demand for (and thus the value of) used vehicles. This increased 

demand results in a decrease in the scrappage rates of older vehicles. 

The scrappage model is a detailed empirical model of the effect of changes in new vehicle prices 

on existing vehicle scrappage rates. The scrappage model is described in detail in Appendix C. 

Using a conceptual framework developed by previous researchers, we have developed an 

updated statistical model relating used vehicles’ scrappage rates to new vehicle prices. The 

model includes statistically estimated relationships between scrappage rates for vehicles of 

different model year vintages at each age during their lifetimes to new vehicle prices and other 

relevant factors. 
Methodologies and Data 

19 

F. Fleet Population Model 

The Fleet Population Model combines the results of the NVMM and the Scrappage Model, and 

projects changes in the relevant fleet populations over time. 

The empirical results from the Scrappage Model are used in combination with the new vehicle 

sales effects from the NVMM to assess the net effects of the California Program on the 

California vehicle fleet. We develop a detailed baseline forecast of the California vehicle fleet 

population based upon the vehicle populations in the CARB’s EMFAC2007 emission inventory 

model.12 Fleet population effects are measured relative to the baseline vehicle populations. In 

this study, both the EMFAC2007 emission modeling and MOBILE6.2 emission modeling use 

the same baseline populations and fleet effects. 

As described above, the NVMM estimates the effects of the California on new vehicle sales, 

while the Scrappage Model estimates the effects on existing vehicle stocks. Applying the results 

of both of these models to the baselines in the Fleet Population Model allows us to simulate the 

effects of the regulations on the vehicle populations in California through the year 2023. 

 

11 c.f. Gruenspecht in Appendix C. 

12 The EMFAC2007 model includes the LEV1 program, the LEV2 program, and the ZEV mandate. We utilize the 

populations by vehicle class in the EMFAC2007 model as our baseline (with emission rates appropriate for the 

federal Tier 2 program), and we estimate fleet effects relative to these populations. 

Demand

Price 

Increase

Sales 

Decrease

Quantity

Price

Quantity

Price

New Vehicle Market

Original

Demand

New

Demand

Increased

Quantity

Used Vehicle Market

Figure 3. Effects of changes in new vehicle prices on prices of used vehicles. 
Methodologies and Data 

20 

G. Modeling of Effects on Vehicle Miles Traveled (“VMT”) 

The results of the Fleet Population Model provide an important component for estimating the 

overall effects of the regulations on motor vehicle emissions. In addition to fleet effects, the 

emissions of the motor vehicle fleet also depend on VMT. We developed a model to explain 

overall VMT in order to provide estimates of changes in VMT due to the California Program 

(relative to baseline VMT). 

Increasing the fuel economy of a vehicle (with all else equal) can lower the vehicle’s emission 

rates. However, it also lowers the cost per mile of driving, leading drivers to travel more miles. 

Thus, increasing fuel economy also raises VMT. Since total emissions depend on both emission 

rates (i.e., emissions per mile) and VMT, the effect of a decrease in emissions rates is partially 

offset by an increase in VMT. This offset is known as the “rebound effect.” 

The VMT Model evaluates the effect on VMT of changes in the cost per mile of travel in 

California. (The VMT model is described in detail in Appendix D.) Based on a framework 

developed by researchers at the University of California, Irvine, we estimate relationships 

between cost-per-mile of travel, miles traveled, and other relevant factors. Using the results of 

this analysis, we develop estimates of the rebound effect for California, both in the short run and 

in the long run. We then use these estimates to determine the total change in VMT due to the 

California Program.13

H. Pollutant Emissions Models 

We performed emission modeling with both EMFAC2007 emission rates and MOBILE6.2 

emission rates. Baseline vehicle populations, baseline scrappage rates, and baseline vehicle miles 

traveled for both models used information from the EMFAC2007 model. Effects of fleet 

turnover and rebound VMT were identical in both emission modeling approaches. Emission 

rates by model year and vehicle class, however, were dependent on the different emission factors 

for each model. 

 

13 Note that the rebound effect is relevant to both the ZEV Standards and the GHG Standards. The Type D Hybrid 

Electric Vehicles that manufacturers will produce to generate AT PZEV credits have higher fuel economy than 

conventional gasoline vehicles. Reducing CO2 emissions from motor vehicles as called for in the GHG Standards 

results in improvements in fuel economy. 
Methodologies and Data 

21 

Below we describe how fleet turnover effects and rebound effects were incorporated into the two 

emissions modeling approaches. Appendix E provides further information about the 

EMFAC2007 emission rates and contains detailed results from the EMFAC2007 modeling, 

while Appendix F provides detailed information about the MOBILE6.2 modeling and detailed 

MOBILE6.2 results. Appendix G describes emissions effects associated with reduced gasoline 

consumption under the California Program. 

1. Emissions Increases due to Fleet Population Effects 

As noted earlier, the new vehicle price increases resulting from the ZEV and GHG standards will 

affect fleet turnover by reducing new vehicle sales and inducing higher rates of retention of 

older, higher-emitting vehicles. These effects lead to increases in criteria pollutant emissions, as 

older vehicles in the fleet often have emission rates that are many times higher than those of new 

vehicles. Our estimates assume that overall VMT is not affected by these shifts in the age of the 

vehicle fleet. 

2. Emissions Increases Due to Rebound Effect 

The rebound effect only affects vehicles for which fuel economy under the California program is 

improved relative to fuel economy under the Federal Program. The rebound effect is accounted 

for after the effects of fleet turnover are incorporated into the modeling. The rebound effect is 

modeled by employing the VMT model described in Appendix D to generate the increased VMT 

(above baseline VMT) for vehicles with improved fuel economy. 
Study Results 

22 

III. Study Results 

This chapter summarizes the results of our analyses of the effects of the California Program. The 

results are grouped into three categories: 

1. Motor vehicle market effects; 

2. Effects on vehicles miles of travel; and 

3. Emissions effects. 

The graphs presented below reflect changes in various quantities under the California Program 

relative to what these quantities would have been under the Federal Program. Accordingly, 

positive values indicate that the quantity under the California Program is greater than under the 

Federal Program, whereas negative quantities indicate the converse. Detailed emission results 

are provided in Appendix E and Appendix F. 

A. Motor Vehicle Fleet Effects 

In this section, we present results of our analysis of motor vehicle fleet effects under the 

California Program. Figure 4 provides an illustrative snapshot of the changes in age distribution 

-100

-80

-60

-40

-20

0

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Tho

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s

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19801982198419861988199019921994199619982

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PC/LDT1 LDT2+

Figure 4. Change in statewide 2020 vehicle population estimates as a result of the combined California 

Program, relative to populations under the Federal Program. 
Study Results 

23 

of the vehicle fleet under the California Program relative to baseline populations consistent with 

the Federal Program for both the PC+LDT1 vehicle category and the LDT2+ vehicle category. 

The California Program has the effect of changing the age distributions of the fleets in both 

vehicle categories. In 2020, sales of new vehicles in the regulated fleet are significantly lower 

than baseline sales in California as a result of the California Program. In contrast, the number of 

vehicles in the fleet that were purchased before the effective date of the regulations (i.e., pre2009 vintages) is significantly higher than the baseline number in 2020. In the year 2020, the 

number of vehicles of vintages 2008 and older is higher than the baseline number because 

consumers opt to retain their existing vehicles longer, rather than replacing them with more 

expensive newer vehicles. 

Results are similar for the South Coast Air basin, as shown in Figure 5. As a result of the 

California Program, the population of motor vehicles of older vintages (those produced before 

2009) in the South Coast vehicle fleet in the year 2020 is larger, and the population of motor 

vehicles of more recent vintages (those produced after 2009) in the fleet in 2020 is smaller than it 

would be under the Federal Program. In 2020, new vehicle sales of PC/LDT1’s and LDT2+’s 

combined are about 40,000 fewer as a result of the California Program. In contrast, the number 

of vehicles in the fleet produced prior to the effective date of the ZEV and GHG Regulations 

-40

-30

-20

-10

0

10

20

Tho

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s

a

n

d

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Model Year

PC/LDT1 LDT2+

Figure 5. Impacts of the combined California Program on South Coast 2020 Vehicle Population, relative to 

populations under the Federal Program. 
Study Results 

24 

(i.e., pre-2009 model year vehicles) is more than 250,000 greater in 2020 than it otherwise would 

be under the Federal Program. 

B. VMT Effects 

Figure 6 shows the change in vehicle miles traveled statewide under the California Program, 

relative to baseline VMT under the Federal Program. By 2023, motorists are projected to drive 

approximately 14 million additional miles per day due to the California Program. This increase 

in VMT partially offsets any emission decreases due to improved fuel economy. 

C. Fuel Consumption and Upstream Emissions Effects 

Due to the fuel economy improvements resulting from the California Program, consumption of 

gasoline decreases (although this decrease is partly offset by the increase in VMT). The net 

decrease in gasoline consumption leads to a small decrease in emissions associated with the 

refining and transport of gasoline (upstream emissions). Figure 7 shows the change in statewide 

emissions of NMOG + NOx due to the upstream emissions effect. 

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2

009

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Calendar Year

Thousand

s

of Miles/Day

Change in VMT Under California Program

Figure 6. Change in vehicle miles traveled under combined California Program relative to VMT under 

Federal Program. 
Study Results 

25 

D. Overall Pollutant Emissions Effects 

Below we provide overall assessments of the effects of the California Program on emissions of 

ozone precursors (VOC+NOx) in the State of California and the South Coast Air Basin. 

Additional results for VOC+NOx, VOC, NOx, CO, Toxics, Exhaust PM2.5, and SOx, for both 

California and the South Coast Air Basin, are shown in Appendix E and Appendix F. As noted, 

our assessments are based on two different emission models. The first sub-section presents 

results generated using CARB’s EMFAC2007 emission inventory model, and the second subsection presents analogous results generated using the U.S. EPA’s MOBILE 6.2 emission factor 

model. 

a. EMFAC2007 Model Results 

The differences in emissions under the California Program relative to the Federal Program based 

on summer season inventories from EMFAC2007 for calendar years 2006 through 2023—after 

accounting for the fleet turnover, rebound, and upstream emissions effects—for the state and 

South Coast Air Basin are shown in Figure 8 and Figure 9, respectively. As shown, the EMFAC 

2007 results indicate that emissions of ozone precursors, both on a statewide basis and in the 

Statewide Upstream Emissions of NMOG+NOx 

-1.8

-1.6

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Fuel Cycle Emissions Benefit (tons/day)

Low-End Estimate High-End Estimate

Figure 7. Change in statewide upstream emissions of NMOG + NOx due to the upstream emissions effect 

under combined California Program (relative to upstream emissions under Federal Program). 
Study Results 

26 

Statewide VOC + NOx(EMFAC)

0

2

4

6

8

10

12

14

16

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure 8. Change in statewide emissions of VOC+NOx (EMFAC2007 modeling) under 

combined California Program, relative to emissions under Federal Program. 

South Coast VOC + NOx(EMFAC)

0

0.5

1

1.5

2

2.5

3

3.5

4

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

State

wide Invent

ory Difference (tpd)

Difference in Emissions Under California Program

Figure 9. Change in South Coast emissions of VOC+NOx (EMFAC2007 modeling) under combined 

California Program, relative to emissions under Federal Program. 
Study Results 

27 

South Coast Air Basin (SCAB), are higher as a result of the California Program relative to the 

Federal Program in every year from 2009 through 2023. Similar results are observed for CO and 

PM2.5 emissions. Emissions for toxic air contaminants are generally higher under the California 

Program through about 2018 and then decrease to essentially the same level as the federal 

program, or, in some cases, to a somewhat lower than the federal program (see Appendix E for 

additional results of EMFAC modeling). It must be noted, however, that the emission estimates 

for the Federal Program do not reflect U.S. EPA’s recently adopted rules that will further reduce 

emissions of air toxics from motor vehicles. Emissions of SOx are lower under the California 

Program than under the Federal Program due to reductions in gasoline consumption that result 

from the GHG standards. 

b. MOBILE 6.2 Model Results 

The results of the analysis performed using the MOBILE6.2 model are qualitatively similar to 

the results of the EMFAC2007 modeling, but the emission differences between the California 

and Federal Programs are larger in magnitude (as are the emission inventories themselves). As 

shown in Figure 10 and Figure 11, the California Program leads to an increase in emissions of 

ozone precursors (VOC+NOx) over the entire period from 2009 through 2023, both on a 

Statewide VOC + NOx (MOBILE)

0

5

10

15

20

25

30

35

40

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure 10. Change in statewide emissions of VOC + NOx (MOBILE6.2 modeling) under the combined 

California Program, relative to emissions under the Federal Program. 
Study Results 

28 

statewide basis and in the South Coast. The MOBILE6.2 results for the other critieria and toxic 

pollutants considered are also similar to those obtained with EMFAC 2007. (See Appendix G 

for additional results of MOBILE 6.2 modeling.) 

South Coast VOC + NOx (MOBILE)

0

2

4

6

8

10

12

14

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Invent

ory Difference (tpd)

Change in Emissions Under California Program

Figure 11. Change in statewide emissions of South Coast VOC + NOx (MOBILE6.2 modeling) under 

combined California Program relative to Federal Program. 
Conclusions 

29 

IV. Conclusions 

The California Program will have substantial impacts on the age and composition of the 

California vehicle fleet. Increased costs incurred by manufacturers in order to comply with the 

ZEV and GHG Standards will result in higher prices (and decreased demand) for new vehicles. 

This will lead to increased retention of used vehicles. Increased fuel economy for new vehicles 

that are sold will lead to an increase in vehicle miles traveled. The increased age of the vehicle 

fleet and the increased vehicle miles traveled resulting from the implementation of the California 

Program will result in substantially greater emissions of ozone precursors (VOC and NOx) 

compared to emissions under the Federal Program. In addition, emissions of other criteria 

pollutants and air toxics, at both the statewide level and in the South Coast Air Basin, will 

generally be higher under the California Program than under the Federal Program (see Appendix 

E and Appendix F). The higher level of ozone precursor emissions under the California Program 

relative to the Federal baseline persists through the year 2023, at which time the South Coast Air 

Basin is required to achieve compliance with the National Ambient Air Quality Standard for 

ozone. 

Thus, our results indicate that the California Program, in the aggregate, is less protective of 

public health than the Federal Program with respect to emissions of ozone precursors and 

several other criteria pollutants. 
Appendix A Compliance Plans and Cost Estimates 

30 

Appendix A. Compliance Plans and Cost Estimates14

Cost estimates were developed for a number of vehicle technologies capable of generating ZEV 

credits that have been or are likely to be considered by vehicle manufacturers and these were in 

turn used with the regulatory credit structure to determine the most likely manufacturer 

compliance pathway with the ZEV Standards. Compliance costs and associated compliance 

plans for the GHG Standards used in this analysis were developed previously by Sierra in 

Sierra’s 2004 report and supplied to CARB at the time the GHG Standards were adopted.15 As 

described below and in the documents submitted to CARB during the regulatory proceeding 

leading to adoption of the GHG Standards, we believe that the cost estimates used in this study 

likely understate the actual costs of compliance. Given that higher incremental costs for 

California vehicles would increase the magnitude of the fleet turnover effect (i.e., further reduce 

new vehicle sales and further increase retention of used vehicles), our use of this approach is 

conservative in that it also understates the likely differences in emissions under the California 

Program relative to the Federal Program. 

Cost estimates for compliance with the ZEV standards represent incremental increases relative to 

gasoline-fueled vehicles certified to California’s Super-Ultra Low Emission Vehicle (SULEV) 

standards. Although there are incremental costs for SULEVs relative to vehicles certified to 

federal emission standards, these costs were not quantified. Estimates of costs for compliance 

with the ZEV Mandate were developed for the three categories of vehicles capable of generating 

ZEV credits: (1) Partial Zero Emission Vehicles (PZEVs); (2) Advanced Technology Partial 

Zero Emission Vehicles (ATPZEVs), and; (3) Zero Emission Vehicles. Within these categories, 

separate cost estimates were developed for vehicles employing different technologies and for 

distinct vehicle classes (PC+LDT1 and LDT2). 

In estimating the costs of vehicles required for the ZEV mandate, a number of different sources 

of information were used, including the recently published “Report of the ARB Independent 

 

14 All costs referred to in this appendix are in year 2004 dollars. The NVMM escalates these to year 2005 dollars 

using the Consumer Price Index in order to be consistent with other data used in the modeling. 

15 Austin, T.C., et al., 2004, “Review of the August 2004 Proposed CARB Regulations to Control Greenhouse Gas 

Emissions from Motor Vehicles: Cost Effectiveness for the Vehicle Owner or Operator”, Sierra Research Report 

No. SR2004-09-04, September, 2004. 
Appendix A Compliance Plans and Cost Estimates 

31 

Expert Panel 2007,”16 confidential cost information supplied by individual auto manufacturers, 

and cost estimates provided by The Martec Group and Harbour Consulting. As described below, 

we elected to make conservative assumptions in preparing these cost estimates that likely 

underestimate the true costs. 

A.1. PZEV Costs 

Incremental cost estimates for PZEV technology of $350 and $500 per vehicle were used for 

PC+LDT1 and LDT2 vehicles, respectively. The PC+LDT1 value reflects the lower range of the 

cost data supplied by vehicle manufacturers, while the LDT2 value reflects the middle of that 

range. The use of the higher value for LDT2 reflects the higher expenses of achieving the zeroevaporative emission standard for PZEVs under the ZEV Mandate on vehicles with larger fuel 

tanks and the higher expenses of achieving the exhaust emission standard for PZEVs under the 

ZEV Mandate on larger vehicles with V8 engines. 

A.2. ATPZEV Costs 

Incremental cost estimates for Type C, D and E hybrid electric vehicles were $1,800, $2,200 and 

$5,500, respectively. These are based on the methodology documented in Sierra’s 2004 report, 

with the estimates for Type D and E vehicles reflecting additional costs associated with high 

voltage electrical systems, nickel-metal hydride batteries, electric motors, and control systems. 

The costs of plug-in hybrid electric vehicles (PHEVs) with 10, 20 and 40 mile electric range in 

the PC+LDT1 category were estimated using component cost estimates provided by The Martec 

Group (the consulting firm relied on by CARB to provide cost information in support of the 

GHG rulemaking), and data from the report of the Independent Expert Panel. Incremental cost 

estimates ranged from about $10,500 for a 10 mile all electric range to about $15,000 for a 40 

mile all electric range. Costs for LDT2 vehicles were again estimated by scaling the PC+LDT1 

values by the relative sales-weighed average weights of 2003 model-year vehicles in these 

classes. Estimates for Type C, D and E hybrid electric vehicles are based on the methodology 

documented in Sierra’s 2004 report, but have been updated to reflect the latest available cost 

data. The cost of plug-in hybrid electric vehicles (PHEVs) in the PC+LDT1 category has been 

 

16 Kalhammer, F.R., et. Al, 2007, “Status and Prospects for Zero Emission Vehicle Technology, Report of the ARB 

Independent Expert Panel 2007” April 13, 2007. 
Appendix A Compliance Plans and Cost Estimates 

32 

estimated using component cost estimates provided by The Martec Group (the consulting firm 

relied on by CARB to provide cost information in support of the rulemaking for the GHG 

Standards), and data from the report of the Independent Expert Panel. Costs for LDT2 vehicles 

were estimated by scaling the PC+LDT1 values by the relative sales-weighed average weights of 

2003 model-year vehicles in these classes. 

A.3. ZEV Costs 

We estimate a cost for Neighborhood Electric Vehicles (“NEVs”) of $8,000, based on the 

nominal $8,000 price of NEVs produced by Global Electric Motors.17 Because of their limited 

range and performance, NEVs are unlikely to be general replacements for conventional vehicles, 

although they would displace some conventional vehicle travel. Therefore, NEV purchase was 

viewed as a cost in addition to owning a conventional vehicle. Incremental costs for City 

Electric Vehicles were assumed to be equal to $13,122 which is the RPE of the vehicle battery, 

the cost of which ($8,150) was taken from the Independent Expert Panel and scaled using a 

multiplier of 1.61. This multiplier is used to adjust supplier costs to RPE and is derived from 

work performed by the U.S. Department of Energy.

18

 Utility EV costs were assumed to be 2/3 

that of a city electric vehicle given the respective range requirements of 50 and 75 miles. 

The cost of full performance battery electric vehicles (FPBEV) was also estimated using data 

from Martec. In the case of pure electric vehicles, the cost of electric motors and power 

electronics is sometimes assumed to be offset by the cost savings associated with elimination of 

the internal combustion engine and transmission. However, using cost information provided by 

Martec and Harbour Consulting, the net cost of the non-battery changes is about $2,500 for a 

full-function EV with a 100 mile range. Using the simple assumption that only the battery cost 

need be accounted for, the incremental cost increase associated with a full-function EV is 

$26,400. If the range is reduced to 75 miles, the cost increase drops to about $19,900. For this 

study, we replaced the more realistic Martec battery cost estimates with the Expert Panel’s 

average cost estimates for lithium-ion batteries scaled to RPE using the 1.61 multiplier, and then 

added the net cost of the non-battery changes described above. We used the lower volume cost 

 

17 See http://www.gemcar.com/affordability/default.asp?ID=355 

18 Vyas, a., Santini, D., and Cuenca, R., 2000, “Comparison of Indirect Cost Multipliers for Vehicle Manufacturing,” 

Argonne Naional Laboratory, April, 2000. 
Appendix A Compliance Plans and Cost Estimates 

33 

estimate through the 2012 model-year and then linearly transitioned to the high volume cost 

estimate for 2015 and later model-years. This resulted in a near term incremental cost estimate 

of about $23,000 for a FPBEV and a longer term incremental cost of about $17,000. 

The incremental cost of fuel cell electric vehicles (FCEVs) was estimated using the average of 

the Expert Panel’s best case current and 2015 estimates for fuel cell system costs in high volume 

production, and an assumed stack rating of 100 kW. These values were marked up to RPE using 

a 1.61 multiplier. The current best-case costs were used through the 2012 model-year, and then 

linearly transitioned to the 2015 value in that year and beyond. Thus, the incremental costs 

assumed for FCEVs were about $60,000 in the short term and about $11,000 in the longer term. 

A.4. Summary of Cost Estimates 

Cost estimates for all of the ZEV vehicle technologies considered are shown in Table A-1 for the 

PC+LDT1 and LDT2 categories, respectively. 

A.5. Per-Credit Cost Estimates and Manufacturer Compliance Strategies 

Using the cost estimates in Table A-1 and the information regarding ZEV credits generated by 

vehicles utilizing various technologies from the ZEV regulations, we estimated the effective cost 

of each technology in terms of the dollars required per ZEV credit generated. These results are 

shown in Table A-2. 

PZEVs generate ZEV credits at the lowest dollar per credit value of any of the technologies 

considered in both the PC+LDT1 and LDT2 categories. Given this and the fact that PZEVs are 

Table A-1. Cost Estimates for ZEV Program Vehicles 

Type Credit Level PC+LDT1 LDT2 

PZEV Bronze 350 500 

Type C HEV Silver 1,800 2,718 

Type D HEV Silver 2,200 3,322 

Type E HEV Silver 5,500 8,305 

PHEV10 Silver 10,576 15,970 

PHEV20 Silver 11,654 17,597 

PHEV40 Silver 14,977 22,616 

NEV Gold 8,000 8,000 

Type 0 ZEV Gold 8,748 8,748 

Type 1 ZEV (CEV) Gold 13,122 19,813 

Type 2 ZEV (FPBEV) Gold 23,366/16,732a 35,282/25,266a 

Type 3 ZEV (FCEV) Gold 60,375/10,868a 91,166/16,410a 

a First value represents near term costs while second reflects long term cost. 
Appendix A Compliance Plans and Cost Estimates 

34 

conventional, gasoline-powered vehicles, we expect that manufacturers will generate the 

maximum amount of Bronze ZEV credits allowed under the regulations. Turning to vehicles 

capable of generating Silver ZEV credits, Table A-2 indicates that, except during the period from 

2009 through 2011, Type D HEVs provide credits at the lowest per-credit cost. During 2009 to 

2011, PHEV credit costs are lower owing to the credit multipliers provided in the ZEV 

regulations. However, as noted by the Independent Expert Panel, batteries capable of handling 

the number of deep discharge cycles required for PHEV applications are not currently 

commercially available. Given this, and the fact that the incremental cost of Type D HEVs is 

lower than that of PHEVs and that Type D HEVs ultimately yield Silver ZEV credits at a lower 

per vehicle cost than PHEVs in later years, we have assumed that manufacturers would select 

Type D HEVs over PHEVs for generating Sliver ZEV credits. 

A similar analysis for technologies capable of generating Gold ZEV credits indicates that CEVs 

generate credits at the lowest per-credit cost in the near term while FCEVs do so in the longer 

term. Further, through 2014, the cost of generating Silver ZEV credits with Type D HEVs will 

be at least 50% lower than the cost of generating Gold ZEV credits with any technology. Given 

this, we have assumed that manufacturers will elect to pursue the Alternative Compliance Path 

provided in the ZEV Mandate and use extra Silver credits generated by Type D HEVs to fulfill 

their ZEV obligation as provided for under the regulation. Beginning in 2015, FCEVs are 

estimated to provide Gold ZEV credits at a lower per credit cost than Type D HEVs. However, 

that estimate is based on what appear to be highly optimistic “best-case” estimates by the 

Independent Review Panel of the costs of fuel cell systems in 2015 and the Panel estimated that 

high volume production of fuel cell vehicles would be delayed relative to CARB’s previous 

expectations. Therefore, we assumed that manufacturers would continue to pursue the 

Alternative Compliance Path through the 2017 model-year. Beyond 2017, we made the very 

optimistic assumption that manufacturers would be capable of complying with the requirements 

to generate Gold ZEV credits using FCEVs. Again this assumption was conservative in that it 

likely understates the actual costs of compliance with the California Program and therefore 

understates the emissions increases associated with the California Program relative to the Federal 

Program. 
Appendix A Compliance Plans and Cost Estimates 

35 

Table A-2. Dollars per ZEV Credit during the period 2009-2023 

Type Credit Level PC+LDT1 LDT2 

PZEV Bronze 1,750 2,500 

Type C HEVa Silver 4,500 6,795 

Type D HEV Silver 3,667/4,889 5,537/7,382 

Type E HEV Silver 7,857/10,000 11,864/15,100 

PHEV10 Silver 1,738/5,630 2,624/8,501 

PHEV20 Silver 1,765/5,681 2,665/8578 

PHEV40 Silver 2,700/6,408 3,031/9677 

NEV Gold 53,333 53,333 

Type 0 ZEV Gold 8,748 8,748 

Type 1 ZEV (CEV) Gold 5,249/6561 7,925/9,907 

Type 2 ZEV (FPBEV) Gold 5,577/7,789 8,422/11,761 

Type 3 ZEV (FCEV) Gold 3,623/20,125 5,470/30,389 

a Type C HEVs are allowed to generate ZEV credits only through the 2011 model-year. 
Appendix B New Vehicle Market Model 

36 

Appendix B. New Vehicle Market Model 

This appendix provides information regarding the New Vehicle Market Model. 

B.1. Conceptual Approach: Nested Logit Model 

Logit discrete choice analysis provides a method for predicting consumer choices, and therefore 

demand, based on previously observed consumer behavior and other assumptions about demand 

(see, e.g., Ben-Akiva and Lerman 1985). The most basic logit model, also referred to as the 

simple logit, groups all product alternatives together and therefore allows only limited patterns of 

own-price and cross-price elasticity between different alternatives. This limitation is often 

referred to as the “Independence of Irrelevant Alternatives” (“IIA”) problem. The nested logit 

model builds on this simple framework, while allowing for a much richer pattern of crosssubstitution between different alternatives through the nesting structure. 

B.1.1. Basic Framework 

In our new vehicle market model, consumers choose among a set of vehicle models, and may 

also choose not to purchase a vehicle at all. For alternative i, the utility that a given consumer 

obtains from choosing that alternative can be written as a function of an alternative-specific 

parameter and the price for the alternative: 

Ui i Pi i = a − b + e (1) 

Alternative “0” is defined as the no-purchase alternative, and the remaining alternatives represent 

decisions to purchase individual vehicle models. The parameter ai measures the attractiveness of 

good i to consumers. We assume that the price for the outside good is zero. Pi is the price of 

alternative i, and b is a positive coefficient. The random error terms ei are assumed to be 

distributed as a multivariate generalization of the standard extreme value distribution. 

The potential purchaser is assumed to choose the alternative that yields the highest utility, taking 

into account both the deterministic and random components of utility. Given the logit demand 

assumptions, we determine the expected market share for each vehicle model. Conditional upon 

the consumer’s decision to purchase a vehicle model within a vehicle group (or “nest”) A (as 

described below), the expected share for vehicle model alternative i can be written as: 
Appendix B New Vehicle Market Model 

37 

∑∈

−

−

=

j A

j j A

i i A

i A

P

P

s

exp(( )/ )

exp(( ) / )

|

a b l

a b l

(2) 

where lA is the “nesting parameter” for the appropriate vehicle group, or “nest” (as described 

below).19

B.1.2. Nesting Assumptions 

Our logit model assumes the nesting structure shown in Figure B-1. We divide the choice 

problem first into the decision of whether to buy a new vehicle. Conditional upon the choice to 

purchase a new vehicle, consumers choose the vehicle type—in this case, passenger cars, pickup 

 

19 Because terms that are constant across all alternatives do not affect the choice of alternatives, it is common to 

normalize the alternative-specific term ai. As a normalization rule, we set ai equal to zero for one vehicle model. 

Adding or subtracting a common amount to all the aiterms leaves the choice of alternatives unchanged, so any 

other normalization rule would yield identical results.

Consumer Decisons

Sports Wagon SUV

Buy Don’t Buy

Car

Truck/Van

SUV/Minivan

Premium SUV

Minivan

Large SUV

Mid-Range SUV

Small SUV

Small Pickup

Full Pickup

Full Van

Small Car

Mid-Range Car

Upscale Car

Sporty Car

Traditional Car

ZEV

Figure B-1. Nesting structure for NVMM 
Appendix B New Vehicle Market Model 

38 

trucks or full-size vans, and SUVs or minivans. Conditional on the choice of vehicle type, 

consumers choose the vehicle class—for example, small cars or mid-range cars (among others) 

in the passenger car group. Conditional on the vehicle class (e.g., mid-range car, small SUV, 

etc.), consumers choose one of the individual vehicle models available. The bottom level of the 

nesting structure includes over 200 vehicle models from which consumers may choose. 

The market model allows the utility that consumers derive from the purchase of different models 

to depend on the vehicle category and class via the nesting parameters (lA), which take values 

between zero and one.20 One nesting parameter applies to the purchase decision (buy or don’t 

buy); another nesting parameter applies to the choice of vehicle type; and a third applies to the 

choice of vehicle classes. The nesting parameter for the purchase decision must be at least as 

large as the nesting parameter for vehicle type. For each nest, the nesting parameter must be at 

least as large as the nesting parameter for all vehicle nests contained within the “parent” nest. 

The nesting structure implies that vehicles within one group are closer substitutes for each other 

than they are for vehicles in different groups. The cross-price elasticities between vehicles within 

the same group are therefore higher than the cross-price elasticities for vehicles in different 

groups. 

As noted above, one advantage of the nested logit model over the simple logit model is that it 

provides for a richer pattern of own- and cross-price elasticities. In the nested logit model, the 

IIA property need not hold across groups. That is, the ratio of the share for a particular car model 

in one bottom-level nest to the share of a vehicle in a different bottom-level nest, for example, 

depends not only on the characteristics of those two vehicle models, but also on the substitution 

patterns implied by the nesting structure and nesting parameters. The nesting parameters 

therefore enrich the simple logit model. If all nesting parameters equal one, then the nested logit 

model becomes a simple logit model. 

The inclusive value term IA for bottom-level group A (the vehicle class) is defined as: 













= ∑ −

j∈A

A j Pj A

I ln exp((a b ) / l )

(3) 

The inclusive value term IX for the top-level group X (the vehicle type) is defined as: 
Appendix B New Vehicle Market Model 

39 













= ∑∈ln exp( / )

A X

X A A X

I I l l

(4) 

Finally, the inclusive value term IBuy for the purchase alternative is defined as: 













= ∑

X

buy X X buy I ln exp(I l / l )

(5) 

The share of the bottom-level group A in purchases within the top-level group X to which A

belongs can be written as: 

∑∈

=

B X

B B X

A A X

A X

I

I

s

exp( / )

exp( / )

|

l l

l l

(6) 

The share of top-level group X in total purchases can be written as: 

∑

=

Y

Y Y buy

X X buy

X buy I

I

s

exp( / )

exp( / )

|

l l

l l

(7) 

The logit framework gives an expression for the share of potential buyers who choose to 

purchase a vehicle: 

exp( ) exp( )

exp( )

l a0

l

+

=

buy buy

buy buy

buy I

I

s (8) 

where a0 is the value derived by the consumer from a no-purchase decision. 

The unconditional share for alternative i can be written as the product of the purchase probability 

and the conditional probabilities: 

i i i Ai

i buy X buy A X i

s s s s s = | | | (9) 

where Ai is the bottom-level group to which i belongs and Xi is the top-level group to which Ai

belongs. 

 

20 The nesting parameters are sometimes called “inclusive value coefficients.” 
Appendix B New Vehicle Market Model 

40 

B.2. Market Simulation 

In a simple logit model, the own-price elasticity of demand for alternative i can be written as: 

(1 ) i i i h = −bP − s (10) 

where si is the unconditional share of alternative i (i.e., its share over all potential consumers, not 

only those who choose to purchase a new vehicle). 

In a nested logit model, the own-price elasticity of demand for alternative i is more complicated, 

including terms that reflect substitution possibilities within the bottom-level group, across 

bottom-level groups that are within the same top-level group, and across top-level groups. 

Taking the natural logarithm of Equation 9, and differentiating with respect to the natural 

logarithm of Pi yields an expression for the own-price elasticity for the nested logit model: 

ln( )

ln( )

ln( )

ln( )

ln( )

ln( )

ln( )

ln( ) | | |

i

i A

i

A X

i

X buy

i

buy

i

P

s

P

s

P

s

P

s

i i i i

∂

∂

+

∂

∂

+

∂

∂

+

∂

∂

h = (11) 

The aggregate price elasticity of demand can be calculated by increasing the prices of all goods 

by a common percentage, finding the percentage change in total demand, and taking the limit of 

this percentage change in demand as the percentage change in price goes to zero. The aggregate 

price elasticity of demand can be written as 

(1 )

buy E = −b P − s (12) 

where P is the share-weighted average price of new vehicles. 

We assume that the motor vehicle market is characterized by Bertrand competition where each 

manufacturer sets prices to maximize its overall profits, taking into account the fact that it is a 

multi-product firm. In a Nash equilibrium for this Bertrand competition, the profit-maximizing 

price for a single-product firm can be written as follows (where MCi is the marginal cost for 

alternative i, assumed to be constant):21

i i

i i

P

P MC

h

1

=

−

, or 

i

i

i i

P

P MC

h

= + . (13) 

 

21

 See, e.g., Carlton and Perloff (1999) for a discussion of the Bertrand-Nash assumptions.
Appendix B New Vehicle Market Model 

41 

If one observes Pi, then knowing either the marginal cost or the elasticity provides enough 

information to calculate the other. 

For a multi-product firm (as is the case for all major auto firms in the United States), the pricing 

equations include additional terms that reflect the unit profits on other products made by the firm 

and the cross-elasticities of demand between good i and these other products. The basic logic is 

that as the price of good i increases, some of the lost sales of that good will be replaced by 

increased sales of other goods sold by the same firm. Our model takes these effects into account. 

Additionally, we modified the methodology to take into account how the requirements under the 

ZEV Mandate would affect manufacturers’ profit maximizing pricing decisions. 

B.3. Solving for Parameters 

As described above, the nested logit choice framework provides a method to estimate consumer 

demand for differentiated products, using as data the prices and parameters that measure the 

relative attractiveness of each product. Using the logit framework, we solve simultaneously for 

the beta parameters and “alternative-specific” parameters that are consistent with the observed 

market shares and prices. If two products in the same group have the same price but different 

market shares, then the one with the higher share must be more attractive to consumers. 

Similarly, if two products in the same group have the same market share but different prices, 

then the one with the higher price must be more attractive to consumers, since consumers are 

observed to pay a premium for it. 

We use the logit framework to estimate alternative-specific parameters for each vehicle model. 

We make assumptions concerning the nesting parameters, the aggregate price elasticity of 

demand, and the price elasticity of demand for one specific alternative. Given the structure of our 

nested logit model, these assumptions, the observed prices, and the observed market shares are 

sufficient to derive estimates of the alternative-specific parameters (including those for the 

outside good). 

The model estimates marginal costs for each vehicle model based on the profit-maximization 

conditions outlined above. This condition assumes that each manufacturer chooses the price for 

a given vehicle that will maximize its profits, taking into account the new vehicle marginal costs, 

the sensitivity of consumer demand to changes in vehicle prices, and the availability to 

consumers of substitute vehicles offered by that manufacturer and its competitors. The model 
Appendix B New Vehicle Market Model 

42 

uses vehicle prices and assumptions about consumer responses to changes in those prices to 

calculate marginal costs that are consistent with both profit-maximizing behavior and the 

observed market shares. Marginal costs for each vehicle are calculated based on each vehicle’s 

calculated elasticity. 

B.4. Estimating Consumer Valuations of Vehicle Attributes 

Once the alternative-specific parameters implied by the observed vehicle shares and prices are 

calculated, we estimate the extent to which consumers value each vehicle attribute through a 

“second-stage” regression for the alternative specific parameters. For each vehicle in the sample, 

the alternative specific parameters are regressed on vehicle characteristics such as horsepower, 

weight, and fuel economy. 

We assume each vehicle’s alternative-specific parameter depends upon the vehicle’s model and 

attributes according to the following model: 

a = j + +d +f + e X year Dyear model Dmodel (14) 

where 

a is the alternative-specific coefficient, 

X are vehicle characteristics, 

Dyear are dummy variables corresponding to vehicle model years, 

Dmodel are dummy variables corresponding to the vehicle model, 

e is an error term capturing unobserved characteristics, and 

j, dyear, and fmodel are estimated parameters.

B.4.1. Effects of California Program 

The California Program will lead to higher vehicle costs and increased fuel economy (miles per 

gallon) for various models. The marginal costs of covered vehicles for each manufacturer are 

adjusted to reflect the relevant cost increases for covered vehicles. The new vehicle market 

model calculates each manufacturer’s response to the additional costs in each year. 
Appendix B New Vehicle Market Model 

43 

B.4.2. Calculating Quality-Adjusted Price Changes 

Given the assumptions of the nested logit model, the expected maximum utility available for a 

given set of prices, automobile models, and parameters can be written as: 

ln(exp( ) exp( )) total = buylbuy + a0 U I (15) 

The consumer welfare (per potential purchaser) is calculated as the ratio of the maximum 

expected utility to the price coefficient: 

b

Utotal Consumer Welfare = (16) 

As defined above, the inclusive value for the “buy” alternative depends on the prices and 

alternative-specific constants for each car model. 

This utility can be calculated twice--first with the prices and parameters for the baseline 

conditions, and again with the prices and parameters for the California Program. That is: 

( , )

( , )

CAL CAL

total

CAL

total

base base

total

base

total

U U P

U U P

a

a

=

=

(17) 

To calculate the quality-adjusted aggregate percentage price change for the California Program 

analyzed relative to the baseline, we solve for a common percentage price change that, if applied 

to the base prices, with the base parameters, would yield the same utility as under the relevant 

regulatory scenario. That is: 

find such that ((1 ) , )

base base

total

CAL q Utotal =U +q P a (18) 

B.5. Specific Implementation Parameters and Data 

B.5.1. Vehicle Sales 

We use California-specific vehicle sales data from R.L. Polk and Company to determine the 

market share for each vehicle model, aggregated across trim levels, for the years 2001-2005. For 

each model year, we use sales over the period October – September to reflect as accurately as 

possible the timing of new model availability. If a vehicle sold less than 500 units in California, 
Appendix B New Vehicle Market Model 

44 

the vehicle model was eliminated from the dataset.22 To avoid under-valuation of models that 

were either discontinued or that were first introduced during the middle of a model year because 

the actual sales would not be good estimates of their annual sales, we eliminated observations 

where the number of vehicles sold was dramatically smaller than in the previous or subsequent 

year for the same model. 

B.5.2. Vehicle Prices 

We use data on transaction prices for each model from J.D. Power and Associates for the United 

States and specifically for California. The transaction prices are sales weighted and reflect the 

different prices charged for different trim levels. 

B.5.3. Vehicle Fuel Economy Data and Other Vehicle Characteristics 

We use vehicle characteristic data from Ward’s to determine the fuel economy of each model. 

The fuel economy used in this analysis is the EPA adjusted combined (city and highway 

combined) miles per gallon. We also rely on data from Ward’s for data on other vehicle 

attributes, including engine size, number of cylinders, curb or test weight, horsepower, length, 

and height. 

B.5.4. Categorization of Vehicle Models into Nests 

We use vehicle categorizations from the 2005 Automotive News Market Data Book to define the 

vehicle nesting structure depicted in Figure B-1. Where the appropriate category for a particular 

model could not be determined based on the 2005 Automotive News Market Data Book, we used 

older Automotive News Market Data Books or Ward’s categorizations. 

B.5.5. Price Elasticity 

Consistent with various literature sources, we assume an aggregate elasticity for the new vehicle 

market of –1.0.23 We set the own-price elasticity of the “normalized” vehicle model (whose 

 

22 The one exception to this is the case of pure ZEVs. We utilize the same sales data on the Toyota RAV4 EV that 

was used in our previous analysis (see NERA/Sierra, 2003, Attachment B), with the exception that, rather than 

assuming initially an inflated demand for ZEVs, we use the RAV 4 EV sales data to develop initial demand for 

ZEVs. We then linearly increase the attractiveness of ZEVs each year in two phases: first from 2005 to 2009, 

then from 2009 to 2018. By 2018, the attractiveness of ZEVs in our model is such that, all else being equal, the 

demand for ZEVs would be 40 times greater than the demand for the RAV4 EV. 

23 See, for example, Gruenspecht (2000). 
Appendix B New Vehicle Market Model 

45 

alternative-specific parameter is normalized to zero) to be –4.0, which is consistent with various 

other literature estimates of individual model own-price elasticities.

24

The nesting parameters for nested logit models represent the similarity between choices for 

vehicles falling within the same “nest.” The nesting parameters influence the relative 

substitutability within each nest, and also between different nests. Nesting parameters may take 

any value between zero and one, with lower values indicating greater similarity between the 

alternatives within the respective nest. For the “Buy” nest we use a nesting parameter equal to 

0.9, for vehicle types we use a nesting parameter equal to 0.6 and for vehicle classes we use a 

nesting parameter equal to 0.3. 

References 

Air Resources Board. 2000. “Staff Report: Proposed Amendments to the California Zero 

Emission Vehicle Program Regulations.” December 8. 

Automotive News. 2001. 2001 Market Data Book. Crain Communications, Inc. May. 

Automotive News. 2002. 2002 Market Data Book. Crain Communications, Inc. May. 

Automotive News. 2003. 2003 Market Data Book. Crain Communications, Inc. May. 

Automotive News. 2005. 2005 Market Data Book. Crain Communications, Inc. May. 

Ben-Akiva, Moshe and Steven R. Lerman. 1985. Discrete Choice Analysis. MIT Press, 

Cambridge. 

Berry, Steven, James Levinsohn, and Ariel Pakes. 1995. “Automobile Prices in Market 

Equilibrium,” Econometrica, Vol. 63, No. 4, July 1995, pp. 841-890. 

Carlton, Dennis W. and Jeffrey M. Perloff. 1999. Modern Industrial Organization. Third 

Edition. Addison-Wesley: New York. 

Goldberg, Pinelopi K. 1995. “Product Differentiation and Oligopoly in International Markets: 

The Case of the U.S. Automobile Industry,” Econometrica, pp. 891-951. 

Gruenspecht, Howard K. 2000. Comments on 2000 Biennial Review of Zero Emission Vehicle 

Program before the California Air Resources Board. September 5. 

J.D. Power and Associates, Power Information Network. PIN Markets: National, CaliforniaSouth, and California-North. Purchase of proprietary data, February 2006. 

 

24 See, for example, Berry, Levinsohn, and Pakes (1995). 
Appendix B New Vehicle Market Model 

46 

R.L. Polk and Company. New Retail and Fleet Car and Light Truck (GVW 1-3) Registrations for 

the State of California, 2001-2005. Purchase of proprietary data, February 2006. 

United States Environmental Protection Agency (EPA). 2004. Fuel Economy Fact Sheet, 

EPA420-F-04-053. October. http://www.epa.gov/fueleconomy/420f04053.htm, accessed April 

20, 2006. 

United States Department of Labor, Bureau of Labor Statistics (BLS). Consumer Price Index—

All Urban Consumers, U.S. All Items, 1966-2001. http://www.bls.gov/cpi/home.htm, accessed 

April 20, 2006. 

Ward’s Communications. 2001. Ward’s ’01 Model U.S. Car and Light Truck Specifications and 

Prices. Subscription service. 

Ward’s Communications. 2002. Ward’s ’02 Model U.S. Car and Light Truck Specifications and 

Prices. Subscription service. 

Ward’s Communications. 2003. Ward’s ’03 Model U.S. Car and Light Truck Specifications and 

Prices. Subscription service. 

Ward’s Communications. 2004. Ward’s ’04 Model U.S. Car and Light Truck Specifications and 

Prices. Subscription service. 

Ward’s Communications. 2005. Ward’s ’05 Model U.S. Car and Light Truck Specifications and 

Prices. Subscription service. 

Ward’s Communications. 2006. Ward’s ’06 Light Vehicle U.S. Market Segmentation and Prices. 

Subscription service. 
Appendix C Scrappage Model 

47 

Appendix C. Scrappage Model 

This appendix provides information on the scrappage model used in this study. 

C.1. Vehicle Prices and Scrappage Behavior 

The idea that economic as well as technical considerations can influence the life spans of 

durable capital goods such as motor vehicles has long been recognized. Specifically, the link 

between a vehicle’s market value and its service lifetime was first explicitly recognized more 

than three decades ago. This logic is straightforward: a vehicle is retired from service (or 

scrapped) when it is no longer worth the expense of keeping it in working condition. That 

is, when the difference between the vehicle’s resale price (in working condition) and the 

cost of keeping it in this condition is less than its scrap value, the vehicle is scrapped. 

Building on this basic insight, early research by Walker (1968) and Parks (1977) 

investigated the influence of a vehicle’s market value, as well as characteristics such as its age, 

on the vehicle owner’s decision to retire the vehicle from service rather than maintain it in 

working condition. Both authors present statistical evidence of the influence of vehicle prices 

on the scrappage rates of used vehicles of different model year vintages and ages, 

demonstrating that variation in automobile prices exerts a detectable influence on scrappage 

rates of used cars. Berkovec (1985) later incorporated the framework developed in this 

earlier research in a model encompassing new automobile production and sales activity, vehicle 

pricing behavior, and scrappage of used autos. 

Also drawing on previous results, Gruenspecht (1982) recognized that the connection between 

new and used vehicle prices—whereby rising prices for new models exert an upward “pull” on 

resale prices for used vehicles—meant that changes in prices for new automobiles could 

influence scrappage decisions by older cars’ owners. As a result, he hypothesized, 

emissions regulations that raised production costs and sales prices of new vehicles might retard 

the scrappage and replacement of older models sufficiently to offset the reduction in 

conventional emissions from introducing cleaner new models into the vehicle fleet. 

Gruenspecht’s research produced evidence that the increase in new car prices resulting from 

manufacturers’ compliance with the 1980-81 federal emissions standards could be sufficient to 
Appendix C Scrappage Model 

48 

have this effect. This study can be considered an updated version of Gruenspecht’s statistical 

model relating used vehicles’ scrappage rates to new vehicle prices. 

C.2. Model Used in this Study 

The vehicle scrappage model used here is based on well-established economic theory and 

empirical evidence on the response of owners’ decisions about retiring (or “scrapping”) used 

vehicles to changes in economic factors. The model estimates a relationship between scrappage 

or retirement rates for vehicles of different model year vintages at each age during their 

lifetimes and macroeconomic conditions (e.g., unemployment rate), factors affecting total 

motor vehicle ownership and use, and other factors influencing scrappage rates of used 

vehicles. This relationship was developed using various data and statistical procedures 

appropriate for these data. 

This study estimates a “reduced-form” scrappage model using aggregate scrappage rates for the 

individual vehicle model years making up the U.S. passenger vehicle fleet over the 1970-2005 

period (rather than the scrappage rates for individual vehicle models originally employed by 

Gruenspecht). Updating results from Gruenspecht’s earlier model is necessitated by dramatic 

increases in the expected lifetimes and average ages of passenger vehicles that have occurred 

since his original work was published. Figure C-1, which displays yearly survival rates of 

vehicles manufactured during different model years, illustrates these changes. 

75%

85%

95%

3 4 5 6 7 8 9 10 11 12 13 14 15

2000

1995

1990

1985

1980

1975

1970

1965

Vehicle age in years

Model year:

Percent vehicles surviving to the following year

Source: R.L.Polk & Company. 

Figure C-1. Vehicle Survival Rates by Age and Model Year 
Appendix C Scrappage Model 

49 

C.2.1. Basic Theory of the Model 

A vehicle’s owner will retire the vehicle from service and sell it for its scrap value if its value in 

working condition exceeds its scrap value by less than the expected cost of repairs necessary to 

maintain it in working condition. Since the expected cost of these repairs depends on how long a 

vehicle has been in service as well as on the materials and manufacturing technology employed 

when it was produced, the probability that it will be scrapped is likely to depend on both its 

original model year and its age. To some extent, a vehicle’s age may simply be a surrogate 

measure of its accumulated usage, although its age per se may also affect its sale value in 

working condition and thus the likelihood that it will be retired. 

At the aggregate or fleet-wide level, the scrappage rate among a “cohort” of vehicles in service 

(measured by the proportion of those in service at the beginning of a year that are retired or 

scrapped before it ends) will thus depend on both their model year and their age during that year. 

The scrappage rate also will reflect the effects of vehicles involved in motor vehicle accidents 

that remove vehicles from service. Because prices for new vehicles are in turn an important 

influence on prices for used vehicles of different ages, scrappage rates for vehicles of each model 

year in the fleet during a calendar year are likely to be affected by changes in new vehicle prices 

and the myriad factors that determine them (including manufacturers’ costs for complying with 

government regulations). 

Finally, scrappage rates for all model years in service are also likely to be affected - although not 

necessarily uniformly - by changes in other economic variables such as employment or personal 

incomes. This occurs because keeping used vehicles in service longer provides a temporary 

mechanism for accommodating increases in total demand for motor vehicle travel that result 

from changes in economy-wide conditions. Extending the service lifetime of a used vehicle in 

order to accommodate increased travel demand is accomplished by deferring its retirement 

beyond the age at which it would otherwise have occurred, a response that reduces the aggregate 

scrappage rate for vehicles of various ages. 

C.2.2. Model Variables and Data Sources 

The data used to develop this model of these empirical relationships include scrappage rates 

calculated from U.S. annual vehicle registration data for the years 1970 through 2005. During 

each calendar year of this period, we use registration data for passenger vehicles reported by R.L. 
Appendix C Scrappage Model 

50 

Polk & Company to calculate scrappage rates for vehicles of ages 4 through 14 years, and an 

overall scrappage rate for vehicles that are 15 years and older.25 The scrappage rate is measured 

as the decrease in registered cars over the year divided by the number of registered cars at the 

beginning of the year.26 While the specific types of vehicles included in these registration data - 

and thus in the scrappage rates used to develop this model - vary over the extended period 

covered by this study, for most of those periods they closely match those encompassed by the 

GHG and ZEV Standards, and the federal government’s Corporate Average Fuel Economy 

(“CAFE”) standards. 

Each of the scrappage model variables is summarized below, along with the specific rationale for 

including it and a brief description of the specific data source used to measure it. 

1. Vehicles per Driver (Lagged). This variable represents the average number of vehicles per 

licensed driver in the previous year. It is intended to measure the effect of previously postponed 

scrappage and replacement of older vehicles due to macroeconomic and other conditions on 

scrappage in subsequent periods; higher values of this lagged variable are expected to lead to 

increased scrappage in the current year. The measure is calculated from the R.L. Polk data 

on vehicles in each year (as discussed above) and information on licensed drivers in each 

year obtained from the U.S. Federal Highway Administration in its annual Highway Statistics. 

2. New Car Price-Age Interactions. This set of variables is measured as the interaction of the average 

new car price (in real terms) times the set of dummy variables for vehicle age. Average new car 

price is measured as the average real (2005 dollar) price, based upon average nominal expenditure 

per car reported by the Bureau of Economic Analysis and conversion of 2005 dollars using the CPI 

 

25 R.L. Polk reports that prior to the 1993 release, which as noted below is for registrations as of July 1, 1992, it 

double-counted used vehicles sold by a resident of one state to a resident of a different state that were then 

simultaneously registered in two states. This double-counting for some registered vehicles was corrected for the 

1993 release and subsequent data releases. R.L. Polk did not adjust data from prior years when it made the 

correction. To avoid calculating inaccurate scrappage rates for years affected by this change in methodology, we 

dropped observations whose scrappage rates could be calculated using different methods (three years worth of 

observations). We also allowed for a structural change related to the effect of the lagged vehicles per driver on 

scrappage rates by interacting it with a dummy variable that took the value of one for observations after 1992. 

26 R.L. Polk reports registrations as of July 1 of each year. To calculate the scrappage rate for each calendar year 

(i.e., over the period from January 1 to December 31), we calculated two scrappage rates, one based upon the 

change from the previous year to the current year (e.g., for 2000, from July 1, 1999 to July 1, 2000) and one based 

upon the change from the current year to the subsequent year (e.g., for 2000, from July 1, 2000 to July 1, 2001); 

the scrappage rate we used for each year was the average of these two values. 
Appendix C Scrappage Model 

51 

deflator reported by the Bureau of Labor Statistics (as presented in the Economic Report of the 

President (2006)). 

3. Unemployment Rate. This variable measures the effect of macroeconomic conditions on vehicle 

scrappage; higher unemployment during periods of slow economic growth or recession may cause 

vehicle owners to delay scrappage and replacement of older vehicles. It is measured by the 

annual unemployment rate among males aged 19-65 years of age, as reported by the U.S. 

Bureau of Labor Statistics. 

4. Fatal Crashes per VMT. This variable measures scrappage due to accidents. The variable is 

calculated as the number of passenger cars involved in crashes in which a person is killed, 

divided by the annual vehicle miles traveled. This variable is intended to measure vehicles 

lost in major accidents. The data were obtained from the National Highway Traffic Safety 

Administration. 

Recognizing the “panel” nature of the data used to develop it, the scrappage model also includes 

categorical, age specific variables (termed “fixed effects” in statistical analysis). 

C.2.3. Model Form and Estimation 

The specific mathematical form of the scrappage model employs the measure 













− s

s

1

ln (1) 

as its dependent variable, where s is the aggregate scrappage rate for vehicles of an individual 

model year at a specific age, and ln(.) denotes the natural logarithm. This transformation of the 

scrappage rate, sometimes called the “logit” of the scrappage rate, converts a measure bounded 

by the values zero and one—and in practice varying over a much narrower range—to one 

spanning a wider range of values. Using the transformed value of the scrappage rate as the 

model’s dependent variable allows the estimated coefficients to exhibit desirable statistical 

properties. (Note that the results of the regression model using the logit transformation can be 

transformed back into an estimated relationship between the scrappage rate itself and the 

explanatory variables.) 
Appendix C Scrappage Model 

52 

C.3. Statistical Results 

The resulting model performs well in explaining variation among scrappage rates across the 

wide range of model years and extended historical period spanned by the underlying data. 

Table C-1 presents the statistical coefficient estimates and other results of the estimated model in 

Table C-1. Coefficient estimates for model of age-specific vehicle scrappage rates. 

Dependent variable R-squared 0.9963

Sample period F(34,351) 2901.1

Number of observations Root MSE 0.1839

Coefficient Std. Error t-Statistic

(dropped)

1.1443 0.4285 2.67

1.8092 0.431 4.2

2.6862 0.4334 6.2

3.8674 0.4363 8.86

4.7986 0.4402 10.9

5.4719 0.4452 12.29

5.6934 0.4518 12.6

5.5689 0.4632 12.02

5.0569 0.4747 10.65

4.352 0.4869 8.94

4.1254 0.4995 8.26

0.0238 0.0198 1.2

-0.0234 0.0198 -1.19

-0.0363 0.0197 -1.84

-0.0618 0.0197 -3.14

-0.1037 0.0197 -5.27

-0.1326 0.0197 -6.74

-0.15 0.0197 -7.61

-0.1474 0.0199 -7.42

-0.1307 0.02 -6.54

-0.0972 0.0202 -4.82

-0.0571 0.0205 -2.79

-0.0434 0.0208 -2.09

-10.3183 0.8248 -12.51

-10.4191 0.8136 -12.81

-10.2789 0.8067 -12.74

-10.4061 0.8076 -12.89

-10.5713 0.7902 -13.38

-9.9982 0.7874 -12.7

-6.7999 1.0061 -6.76

0.2697 0.0407 6.63

7.7761 1.0999 7.07

0.1722 0.0952 1.81

Last period vehicles per driver

Last period vehicles per driver × Post 1992 dummy

Model year dummy - 1990's

Model year dummy - 2000 and later

Unemployment rate

Vehicles in fatal crashes/VMT

Model year dummy - 1950's

Model year dummy - 1960's

Model year dummy - 1970's

Model year dummy - 1980's

New car price × Age dummy - 12 yrs

New car price × Age dummy - 13 yrs

New car price × Age dummy - 14 yrs

New car price × Age dummy - 15+ yrs

New car price × Age dummy - 8 yrs

New car price × Age dummy - 9 yrs

New car price × Age dummy - 10 yrs

New car price × Age dummy - 11 yrs

New car price × Age dummy - 4 yrs

New car price × Age dummy - 5 yrs

New car price × Age dummy - 6 yrs

New car price × Age dummy - 7 yrs

Age dummy - 12 yrs

Age dummy - 13 yrs

Age dummy - 14 yrs

Age dummy - 15 and older

Age dummy - 8 yrs

Age dummy - 9 yrs

Age dummy - 10 yrs

Age dummy - 11 yrs

Age dummy - 4 yrs

Age dummy - 5 yrs

Age dummy - 6 yrs

Age dummy - 7 yrs

ln[s/(1-s)]

1970-1990, 1994-2005

385

Variable
Appendix C Scrappage Model 

53 

detail. The signs of the estimated coefficients for all of the model’s variables reflect the 

effects on scrappage rates anticipated in the preceding discussion. Most of the coefficient 

estimates for vehicle age and new car price-age interactions are statistically significant; all 

have the expected sign except for the coefficient on the age 4 x new vehicle price interaction 

variable, which is positive but not significant. 

 The model shows the sensitivity of scrappage rates to changes in new vehicle prices. Rising 

prices for new models significantly reduce scrappage rates for vehicles five years of age and 

older. This model allows new vehicle prices to have different effects on scrappage of used 

vehicles of different ages. The effect gradually increases with age until age 10, and then slightly 

decreases. Table C-2 shows the elasticity of scrappage for 2004 with respect to new car price 

calculated at the mean scrappage rate for each age group. 

C.4. Using the Scrappage Model 

We use the estimates of the effects of changes in prices (adjusted for utility as described in 

Appendix B) due to the California Program in conjunction with the age-specific effects of new 

vehicle prices on scrappage rates produced by this model to simulate future changes in the age 

distribution of these vehicles in California. Specifically, we calculate the changes in scrappage 

rates for vehicles of each age from four to 15+ predicted by the model’s coefficients to result 

Table C-2. Scrappage elasticities with respect to new car price by car age. 

AgeSpecific 

Scrappage 

Rates

Elasticity of 

Scrappage with 

Respect to New 

Car Price

Age 4 0.0136 0.5073

Age 5 0.0144 -0.4997

Age 6 0.018 -0.7712

Age 7 0.0213 -1.3093

Age 8 0.0244 -2.1889

Age 9 0.0288 -2.7853

Age 10 0.0352 -3.1296

Age 11 0.0407 -3.0596

Age 12 0.048 -2.6916

Age 13 0.0549 -1.9875

Age 14 0.0672 -1.153

Age 15 and up 0.0787 -0.8648
Appendix C Scrappage Model 

54 

from the specified increases in the average sales price of new vehicles. We assume that 

scrappage rates for vehicles three years old and less would not change in response to higher 

prices for new vehicles. Since changes in new vehicle prices affect the number of vehicles per 

driver, we also calculate changes in scrappage rates for vehicles of each age due to lagged 

changes in vehicles per driver. Specifically, we use the estimated elasticities, by age, of 

scrappage with respect to lagged vehicles per driver to calculate changes in scrappage rates in 

each calendar year due to changes in vehicles per driver in the previous calendar year. 

These overall age-specific changes in scrappage rates due to each of the scenarios are then 

applied to scrappage rates for vehicles of each age in the baseline projected vehicle populations 

for California to produce estimates of the changes in vehicle populations due to the California 

Program. 

References 

Berkovec, James, 1985. “New Car Sales and Used Car Stocks: A Model of the Automobile Market,” 

Rand Journal of Economics, Vol. 16, pp. 195-236. 

Bureau of Economic Analysis, National Income and Product Accounts, Table 7.2.5S. 

http://www.bea.gov/bea/dn/nipaweb/nipa_underlying/SelectTable.asp?Benchmark=P

Federal Highway Safety Administration, Highway Statistics 2004, Section III: Driver Licensing. 

http://www.fhwa.dot.gov/policy/ohim/hs04/dl.htm. 

Gruenspecht, Howard, K., 1982. “Differentiated Regulation: The Case of Automobile Emissions 

Standards,” American Economic Review, Vol. 72, No.2, pp. 328-331. 

Parks, R.W., 1977. “Determinants of Scrapping Rate for Postwar Vintage Automobiles,” 

Econometrica, Vol. 45, No. 5, pp. 1099-1115. 

R.L. Polk and Company. National Vehicle Population Profile, 1969-2005. Purchase of 

proprietary data, February 2006. 

Walker, F.V., 1968. “Determinants of Auto Scrappage,” The Review of Economics and Statistics, 

Vol. 50, pp. 503-506. 

United States Government Printing Office, “Economic Report of the President 2006,” 

Washington, DC. February. 

United States Department of Transportation, National Highway Traffic Safety Administration 

(NHTSA). 2002. “Traffic Safety Facts 2001: A Compilation of Motor Vehicle Crash Data from 
Appendix C Scrappage Model 

55 

the Fatality Analysis Reporting System and the General Estimates System.” Washington, DC. 

December. 

United States Department of Transportation, National Highway Traffic Safety Administration 

(NHTSA). 2005. “Traffic Safety Facts 2004: A Compilation of Motor Vehicle Crash Data from 

the Fatality Analysis Reporting System and the General Estimates System.” Washington, DC. 
Appendix D Rebound Effect Analysis 

56 

Appendix D. Rebound Effect Analysis 

This appendix provides information on the “rebound” effect that is relevant for determining the 

effects of changes in the fuel economy of the vehicle fleet on vehicle miles traveled in 

California. The rebound effect is measured as the effect of changes in the cost per mile of travel 

(e.g., fuel costs) on vehicle miles traveled; the effect is traditionally measured as an elasticity—

the percentage increase in vehicle miles traveled that would results from a one percent decrease 

in the cost per mile of travel. The model we develop to estimate the rebound effect is based upon 

the general methodology and data employed by researchers at the University of California at 

Irvine (hereafter, “Irvine study”).27

This appendix consists of the following three parts: 

§ Overview of Irvine study; 

§ Modifications to Irvine study data and estimation procedures; and 

§ Estimated Rebound Effect in California. 

D.1. Overview of Irvine Study 

The Irvine study develops a model that posits simultaneous determination of three variables 

(using three equations) related to vehicle use: fleetwide vehicle miles traveled (“VMT”); 

fleetwide vehicle stock (number of vehicles); and fleetwide vehicle fuel intensity (the inverse of 

fuel economy).28 In the model, VMT and vehicle stock depend on lagged dependent variables, 

several exogenous variables, and cost per mile of travel, pm—defined as the price of fuel (dollars 

per gallon) divided by fuel economy miles per gallon). 29 The variable pm is endogenous because 

it depends on fuel economy. The VMT equation also includes the endogenous vehicle stock 

variable as well as interaction terms of pm with income, pm with urbanization, and pm with itself 

(i.e., pm

2

). 

 

27 See Small and Van Dender 2006 and 2006a and Small 2006 and 2006a. 

28 The authors use the natural logarithm of VMT per adult as one of the three endogenously determined variables. 

For simplicity, we refer to this variable as VMT. 
Appendix D Rebound Effect Analysis 

57 

The fuel intensity equation includes a lagged dependent variable, several exogenous explanatory 

variables, a Corporate Average Fuel Economy (“CAFE”) variable, and the endogenous VMT 

variable. The Irvine study treats CAFE regulation as a factor that contributes to actual fuel 

economy rather than as a measure of observed fuel economy. Thus the intent of the CAFE 

variable to measure the ratio of fuel economy under CAFE to what fuel economy would have 

been without CAFE. The Irvine study uses fuel economy data for years prior to CAFE to predict 

what fuel economy would have been without CAFE in later years. 

The estimated short-run national rebound effect in the Irvine study depends most importantly on 

the estimated elasticity of VMT with respect to the cost of travel, pm. The estimated long run

national rebound effect in the Irvine study depends most importantly on the estimated short-run 

elasticity of VMT with respect to pm and the estimated coefficient of lagged VMT in the VMT 

equation. 

D.1.1. Irvine Study Variables and Data Set 

The Irvine study uses a cross-sectional time-series dataset with data on all fifty U.S. states and 

the District of Columbia over the years 1966 through 2001. Table D-1 provides an overview of 

the variables used in the Irvine study. The description of each variable explains the data used to 

construct it. Though the study uses a cross-sectional time-series dataset, not every variable has 

state-specific values (e.g., only national data were obtained on new car loan interest rates, so the 

variable interest differs over time but not across states). In addition, some variables mix national 

and state-specific elements. For example, income (inc) and the price of fuel (pf) come statespecific data on nominal values, but are translated into real terms with national deflators. 

D.1.2. Irvine Study Estimation Procedures 

The Irvine study estimates the three equations described above using several different 

approaches: ordinary least squares (“OLS”); two-stage least squares (“2SLS”); three-stage least 

squares (“3SLS”); and generalized method of moments (“GMM”). The authors conclude that the 

most appropriate estimator is 3SLS. 

 

29 Most of the variables in the Irvine study are expressed as natural logarithms for the estimation. Following the 

notation used in the Irvine study, we denote these variables in lower case and we denote non-logarithmic variables 

in upper case. 
Appendix D Rebound Effect Analysis 

58 

D.2. Modifications to Irvine Study Data and Estimation Procedure 

We develop an estimated rebound effect in California based upon modifications to several data 

series as well as the primary estimation procedure of the Irvine study. 

We have received all of the underlying data and programs (Small 2006a) used in most recent 

versions of the Irvine study (Small and Van Dender 2006 and 2006a). To develop more 

appropriate results for the rebound in effect in California, we have made several modifications in 

the data and estimation methodology developed in the Irvine study. 

Table D-1. Variables Used in the Irvine Study 

Variable Name Description Detail Level

Endogenous

vma VMT per adult State

vehstock Registered vehicles per adult State

fint Fuel intensity (fuel use per mile) State

Exogenous

adrm Adults per mile of roadway State

Cafe The ratio of CAFE regulated fuel efficiency to desired fuel efficiency National

D7479 Dummy variable for years 1974 and 1979 National

inc Per capita personal income (deflated by national CPI) State/National

interest National new car loan interest rate National

licad Licensed drivers per adult State

pf Price of gasoline (deflated by national CPI) State/National

pm=pf+fint Cost of travel State

pm 2 Cost of travel squared State

pm*(inc-minc): Interaction of p m and inc variable, where minc is the mean of inc State

pm*(UrbanmUrban)Interaction of p m and Urban , where mUrba n is the mean of Urban State

popratio Population per adult State

pv Index of new car prices National

Trend, Trend66-73, 

Trend74-79, 

Trend80+

Linear time trends National

Railpop Fraction of state’s population living in MSAs with heavy rail transit State

Urban Fraction of state’s population living in metropolitan areas State

Z1, . . ., Z51 Dummy variable for each state State

Notes: Lower-case variables are in natural logarithms. 

Source: Small and Van Dender (2006). 
Appendix D Rebound Effect Analysis 

59 

§ State dummy variables. The code for the VMT equation restricted the coefficients of the 

dummy variables for the States of Nevada and Nebraska to be the same. We edited the 

estimation code so that the two states had separate coefficients. 

§ Income and gasoline prices. We adjusted the income and gasoline price data to reflect state 

differences in cost of living. With these data, we were able to update the estimation of the 

VMT equation and other equations 

§ Trend variable. We modified the Trend variable to provide a superior and more consistent 

specification. Rather than using a single Trend variable for the VMT and vehicle stock 

equations, we used three separate Trend variables, the first covering the years 1966 through 

1973, the second covering the years 1974 through 1979, and the third covering the years 

1980 through 2001. 

§ Dummy variables for 1974 and 1979. We split the joint indicator variable for 1974 and 1979 

into two separate dummy variables to allow the effects of these two independent shocks to 

differ from one another. 

§ Estimation. We estimated the VMT equation using 2SLS (rather than 3SLS). 

D.2.1. Income and Gasoline Prices 

The Irvine study uses nominal state-level income data from the U.S. Bureau of Economic 

Analysis (“BEA”) and state population data from the U.S. Census Bureau to derive nominal 

income per capita estimates. For the gas price data, the authors use state-level nominal data from 

the U.S. Energy Information Administration (“EIA”). The authors deflated both of these data 

series to 1987 dollars using the national consumer price index for all urban consumers (“CPI”) 

from the U.S. Bureau of Labor Statistics (“BLS”). These values do not account for differences in 

the cost of living across states. To account for these differences, we developed state-specific cost 

of living indices based on city-level data from ACCRA (formerly “American Chamber of 

Commerce Researchers Association”) and the BLS. These indices are used to calculate real 

income and gas price data that reflect differences in purchasing power across states and over 

time. 
Appendix D Rebound Effect Analysis 

60 

D.2.2. Trend Variable 

The Irvine study incorporates different trend variables in different equations. In the VMT and 

vehicle stock equations, the Irvine study uses a linear time trend (Trend). In the fuel economy 

equation, the Irvine study uses three separate linear trends—one for the period from 1966 to 

1973 (Trend66-73) to cover the years before the OPEC embargo in 1974, one from 1974 to 1979 

(Trend74-79) to cover the years between the OPEC embargo and the Iranian revolution in 1979, 

and one from 1980 to 2001 (Trend80+) to cover the period after the Iranian revolution. To test 

for the possibility that driving behavior was also affected differently in these three periods, we 

performed a Wald test for the inclusion of Trend66-73 and Trend74-79 in addition to Trend. 

(This specification is econometrically equivalent to including the three trends from the fuel 

economy equation since Trend80+ is constructed as a linear combination of the other trend 

variables.) The Wald test produced evidence that a nonlinear three-part trend in the VMT 

equation is superior to the simple linear trend used by the authors. Another Wald test produced 

similar evidence for the vehicle stock equation. So we modified the trend variable in the VMT 

and vehicle stock equations to correspond to the three-period trend variable used by the authors 

in their fuel economy equation. 

D.2.3. Dummy Variables for 1974 and 1979 

The Irvine study provides a single dummy variable in the VMT and fuel economy equations for 

1974 and 1979 (D7479) to “represent gasoline supply disruptions in 1974 and 1979,” presumably 

referring to the 1974 oil embargo and the 1979 Iranian revolution. We used two separate dummy 

variables to allow the effects of these two “shock years” to differ from one another. There is no a 

priori reason to expect that the effects of these two events were identical. A Wald test produced 

evidence that separating the two effects provides a superior specification. 

D.2.4. Estimation 

We used 2SLS to estimate the VMT equation because it is a non-system estimator that prevents 

specification errors in one equation from affecting parameter estimates for other equations. We 

concluded that 3SLS was less appropriate for this model, due to concerns about the data used to 

construct some variables, and, in particular, concerns about the construction of the CAFE 

variable. 
Appendix D Rebound Effect Analysis 

61 

D.3. Estimated Rebound Effect in California 

Table D-2 shows the results of our estimation of the VMT equation. Because the estimated 

coefficient of the interaction term of pm with income (i.e., pm*(inc-minc)) was statistically 

insignificant, we excluded that variable from our final estimation of the VMT equation. The 

estimated coefficient on pm in the VMT equation gives the short-run national rebound effect at 

the sample mean of the dataset used in the analysis. The long-run effect is a function of the 

coefficient on lagged VMT. 

Notes: t-statistics in parenthesis; rebound effects calculated using only coefficients from the VMT equation. 

By substituting California-specific values for Urban and pm and using the estimated coefficients 

on the interaction terms, we develop rebound effect estimates for California at the sample mean 

of the California dataset used in the analysis. Table D-3 shows these estimates. 

We use the estimated short- and long- run rebound effects in California to estimate the effects of 

changes in vehicle fleet fuel economy in each year under the scenarios analyzed in this report. 

We estimate changes in vehicle miles traveled by vehicle class (PC, LDT1, and LDT2+). The 

change in fleetwide fuel economy in a given year is a function of the change in new vehicle fuel 

Table D-2. Estimation of the VMT Equation 

Variables Coefficients from 

2SLS Estimation

pm=pf+fint -0.0497 (-8.41)

pm 2

-0.0280 (-3.32)

pm*(inc-minc):

pm*(Urban-mUrban) 0.0523 (3.95)

vma (t-1) 0.7933 (53.79)

Sample Average 

Rebound Effect

Short-Run 4.97%

Long-Run 24.03%

Table D-3. California Short- and Long-Run Rebound Effects 

Rebound Effect

Short-Run 2.76%

Long-Run 13.36%
Appendix D Rebound Effect Analysis 

62 

economy in that year as well as the changes in new vehicle fuel economy in previous years. The 

change in VMT in a given year is a function of the change in fleetwide fuel economy in that year 

as well as the change in VMT in previous years. 

References 

Small, Kenneth A. 2006. Expert Report of Kenneth A. Small in Central Valley Chrysler-Jeep, 

Inc. v. Witherspoon; U.S.D.C. (E.D. Cal.) No. CIV-F-04-6663 REC LJO, April 19. 

Small, Kenneth A. 2006a. Data received in conjunction with Expert Report of Kenneth A. Small 

in Central Valley Chrysler-Jeep, Inc. v. Witherspoon; U.S.D.C. (E.D. Cal.) No. CIV-F-04-6663 

REC LJO, April 19. 

Small, Kenneth and Kurt Van Dender. 2006. “Fuel Efficiency and Motor Vehicle Travel: The 

Declining Rebound Effect,” Department of Economics, University of California Irvine, March 

21. 

Small, Kenneth and Kurt Van Dender. 2006a. “Fuel Efficiency and Motor Vehicle Travel: The 

Declining Rebound Effect,” Department of Economics, University of California, Irvine, April 10 

(corrected July 17). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

63 

Appendix E. EMFAC2007 Pollutant Emissions Modeling 

This appendix describes the development and use in this study of the EMFAC2007 Fleet 

Emissions Model, an Excel spreadsheet model used by CARB in analyses of emissions effects in 

California. This study uses the November 1, 2006, version of EMFAC2007 to generate estimates 

of the impacts of the California Program on criteria pollutants in California.30 The model 

accounts for the impact of the “fleet-turnover” effect and “rebound” effect on emissions of VOC, 

NOx, CO, SOx, PM10, and five air toxics. The discussion below summarizes the methodology 

used to develop model-year specific grams-per-mile (g/mi) emission factors, vehicle populations, 

and vehicle miles traveled (“VMT”), and how those parameters were adjusted to account for the 

emissions impacts of the various scenarios investigated in this study. 

E.1. Baseline Model-Year Specific Emissions, Population, and VMT 

The baseline model-year-specific emission rates, vehicle populations, and VMT were generated 

by running EMFAC2007 for each individual model year included in EMFAC2007 for the 

calendar year being evaluated. For example, a calendar year 2020 EMFAC2007 run includes 

vehicles from the 1976 model year through the 2020 model year (45 model years total). The 

model output consists of ton-per-day emissions results, which are divided by the estimated daily 

VMT by vehicles of that model year to arrive at g/mi emission rates for each model year. The 

model runs were configured to output summer-average emissions and also emissions, both at the 

statewide level and specifically for the South Coast Air Basin (“SCAB”), and estimates were 

prepared separately for the passenger car (PC), light-duty truck 1 (LDT1), light-duty truck 2 

(LDT2), and medium-duty vehicle (MDV) classes (which cover all light-duty vehicles through 

8,500 lbs. gross vehicle weight rating). 

The VOC (exhaust and evaporative emissions combined) and NOx emission rates developed in 

this manner are illustrated in Figure E-1 for passenger cars. Of particular interest in this figure is 

the relatively high g/mi emissions for the older model year vehicles relative to the newer 

vehicles, which holds true for both pollutants. For this reason, relatively small shifts in the age 

 

30 The EMFAC2007 model can be downloaded from CARB’s internet website at http://www.arb.ca.gov/msei/onroad/latest_version.htm. Note that the executable version of the model used by AIR was recompiled from the 

Fortran code to allow reporting of the ton-per-day emissions estimates to four digits past the decimal point rather 

than two. This is necessary when calculating gram-per-mile emission rates for some vehicle classes and model 

years that have a relatively small population. 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

64 

distribution of vehicles in the fleet can result in a significant increase in the fleet average 

emission factor. Such shifts in the age distribution are the result of the “Fleet Turnover” effect. 

The model year specific g/mi emission rates developed as described above were used in 

conjunction with vehicle populations and daily VMT by vehicle age to generate ton-per-day 

(tpd) emissions estimates. Emission inventory estimates for the state were generated by 

multiplying the vehicle population (by model year) by the per-vehicle average daily VMT (by 

model year) and the g/mi emission rate (by model year). These products were then summed 

over all model year vehicles in the fleet (e.g., 1976 through 2020 for a calendar year 2020 

analysis) to obtain the inventory for the scenario being analyzed. A sample of the calculation for 

baseline exhaust VOC emissions from passenger cars is shown in Figure E-1, and a comparison 

of the results directly from EMFAC2007 versus those obtained with the emissions model 

developed for this effort is shown below. 

PC Exhaust VOC Directly from EMFAC2007: 31.90 tpd 

PC Exhaust VOC from Fleet Emissions Model: 31.90 tpd 

EMFAC2007 Passenger Car VOC and NOx Emission Rates

0

2

4

6

8

10

12

14

16

18

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Model Year

VOC NOx

Figure E-1. EMFAC2007 Passenger Car VOC and NOx Emission Rates (VOC Includes Evaporative 

Emissions) 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

65 

PC NOx Directly from EMFAC2007: 63.28 tpd 

PC NOx from Fleet Emissions Model: 63.28 tpd 

As observed above, the Fleet Emissions Model agrees exactly with the EMFAC2007 emission 

model for both VOC and NOx. 

Table E-1. Summary of 2020 Statewide Passenger Car Exhaust VOC Inventory Calculation 

Model 

Year 

Total 

Passenger 

Cars 

Daily 

VMT 

(mi/day) Exhaust VOC (g/mi) 

Exhaust 

VOC 

(tpd) 

2020 996,373 55.8 0.011 0.67 

2019 984,117 48.3 0.013 0.66 

2018 942,424 43.9 0.014 0.63 

2017 911,735 40.8 0.015 0.62 

2016 882,463 38.4 0.017 0.65 

2015 886,284 36.4 0.019 0.68 

2014 852,640 34.8 0.020 0.66 

2013 827,749 33.3 0.021 0.65 

2012 785,071 32.0 0.023 0.62 

2011 740,260 30.9 0.024 0.59 

2010 700,575 29.9 0.026 0.59 

2009 655,833 28.9 0.028 0.58 

2008 613,086 28.0 0.028 0.53 

2007 569,920 27.2 0.031 0.54 

2006 530,455 26.5 0.035 0.54 

2005 502,630 25.8 0.051 0.73 

2004 416,920 25.1 0.088 1.02 

2003 390,251 24.5 0.105 1.11 

2002 333,449 24.0 0.115 1.01 

2001 305,670 23.4 0.124 0.98 

2000 280,392 22.9 0.140 0.99 

1999 204,643 22.4 0.208 1.05 

1998 172,099 21.9 0.279 1.16 

1997 147,974 21.4 0.301 1.05 

1996 115,108 21.0 0.326 0.87 

1995 122,526 20.6 0.375 1.04 

1994 100,700 20.2 0.441 0.99 

1993 90,423 19.8 0.627 1.24 

1992 80,816 19.4 0.731 1.26 

1991 89,396 19.0 0.741 1.39 

1990 84,727 18.7 0.711 1.24 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

66 

1989 79,655 18.4 0.676 1.09 

1988 67,569 18.0 0.638 0.86 

1987 60,002 17.7 0.632 0.74 

1986 46,731 17.4 0.636 0.57 

1985 36,213 17.1 0.678 0.46 

1984 26,612 16.8 0.810 0.40 

1983 15,311 16.6 0.915 0.26 

1982 10,327 16.2 0.946 0.17 

1981 7,956 16.0 0.913 0.13 

1980 6,181 15.7 1.227 0.13 

1979 8,140 15.4 1.957 0.27 

1978 6,318 15.2 1.963 0.21 

1977 4,410 14.9 2.003 0.15 

1976 3,208 14.7 2.563 0.13 

 Total Exhaust VOC: 31.90 

E.2. Scenarios 

As discussed elsewhere in this report, emission inventories for the state of California and for the 

SCAB are estimated for two scenarios: 

1. Federal Tier 2 Program (baseline); and 

2. California Program (including exhaust and evaporative emission standards, ZEV 

Standards, and GHG Standards). 

Inventories for the two cases are estimated by generating by-model-year emission factors using 

EMFAC2007, and multiplying these by populations and vehicle miles traveled per day. For the 

Federal Program, there are no population or VMT adjustments, but for the California Program, 

which includes both the ZEV Standards and the GHG Standards, there are adjustments to 

populations and vehicle miles traveled, since both cases will result in increased costs and 

reduced new vehicle purchases relative to the Federal Program. Also, there are additional 

adjustments to vehicle miles traveled for newer vehicles due to rebound effects. 

E.3. Emission Rates by Vehicle Class and Model Year 

Emission factors for the Federal Program are generated using EMFAC2007 and modifying the 

EMFAC Tech Groups in 2009 and later model years to match EPA’s predicted Tier 2 Bin 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

67 

percentages. The Tier 2 2009+ mix for MOBILE6.2 is shown in Table E-3. Also shown in Table 

E-3 are the EMFAC Technology Groups that are the same as these bins. 

Table E-2. MOBILE6.2 Tier 2 2009 Mix. 

Bin EMFAC

Tech Grp 

LDV/T1 LDT2 LDT3 LDT4 Total 

8 35 0.0% 0.0% 26.0% 100.0% 7.5% 

7 N/A 0.0% 30.0% 0.0% 0.0% 10.3% 

6 N/A 0.0% 30.0% 0.0% 0.0% 10.3% 

5 28 10.0% 20.0% 74.0% 0.0% 19.5% 

4 33 10.0% 20.0% 0.0% 0.0% 11.9% 

3 32 55.0% 0.0% 0.0% 0.0% 27.9% 

2 30 25.0% 0.0% 0.0% 0.0% 12.7% 

Total 100% 100% 100% 100% 100% 

NOx Avg 0.033 0.097 0.104 0.200 0.070 

NMOG Avg 0.049 0.086 0.099 0.125 0.070 

N/A= not available 

As noted in Table E-3, there are Tech groups for Bins 6 and 7, which are used only for LDT2s in 

EMFAC. Instead of creating new Technology Groups in EMFAC, the analysis used percentages 

of vehicles in Bins 4, 5, and 8 to simulate the Tier 2 percentages. This results in the same 

NMOG, but slightly higher fleet-weighted NOx, as shown in Table E-4. Thus, the EMFAC 

analysis for Tier 2 has slightly less benefit than it should, which is a conservative assumption for 

this anlysis. 

Also, LDT3s and LDT4s must be combined into a single EMFAC Medium Duty Vehicle 

(“MDV”) category. This analysis assumed 68% of MDVs are LDT3s, and 32% are LDT4s, 

which is consistent with MOBILE6.2. For Tier 2 evaporative emissions, the 2009+ model year 

Technology group assignments are 100% Technology Group 15 for passenger cars, and 100% 

Technology Group 35 for LDT1s, LDT2s, and MDVs. These technology groups correspond to 

the LEVII Near Zero evaporative standards for these vehicle classes. 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

68 

Table E-3. 2009+ Mix Used in EMFAC2007 to Model Tier 2 

Bin EMFAC

Tech Grp 

LDV/T1 LDT2 LDT3 LDT4 Total 

8 35 0.0% 25.4% 26.0% 100.0% 16.1% 

7 N/A 0.0% 0.0% 0.0% 0.0% 0.0% 

6 N/A 0.0% 0.0% 0.0% 0.0% 0.0% 

5 28 10.0% 54.6% 74.0% 0.0% 31.3% 

4 33 10.0% 20.0% 0.0% 0.0% 11.9% 

3 32 55.0% 0.0% 0.0% 0.0% 27.9% 

2 30 25.0% 0.0% 0.0% 0.0% 12.7% 

Total 100% 100% 100% 100.0% 100% 

NOx Avg 0.033 0.097 0.104 0.200 0.070 

NMOG Avg 0.049 0.095 0.099 0.125 0.073 

N/A = not available 

For the California Program, the emissions analysis relies on estimates of the percentages of 

ZEVs, PZEVs, and AT-PZEVs that would be sold by manufacturers, based on the regulatory 

requirements and compliance plans described elsewhere in this report. Then, the percent of 

LEVIIs and ULEVIIs are selected in order to meet ARB’s NMOG requirements. These new 

technology fractions are input into EMFAC2007, and the model is re-run for both the state and 

for the SCAB to produce emissions by model year and vehicle class. The technology fractions 

for the California program are shown in Table E-4. 

Table E-4. Technology Fractions Used for Modeling the California Program. 

Technology Groups for Modeling the California Program 

Tech Grp 28 29 31 37 25 32 33 

NMOG 0.075 0.04 0.0085 0.0085 0 0.04 0.04 

Model Yr LEV II ULEV II PZEV AT PZEV ZEV Bin3 Bin 4 

 PCs 

2009 0.091 0.050 0.365 0.103 0.001 0.290 0.100 

2010 0.000 0.135 0.408 0.112 0.001 0.244 0.100 

2011 0.081 0.050 0.449 0.121 0.001 0.198 0.100 

2012 0.171 0.000 0.487 0.138 0.004 0.100 0.100 

2013 0.161 0.000 0.494 0.140 0.005 0.100 0.100 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

69 

2014 0.148 0.000 0.501 0.142 0.009 0.100 0.100 

2015 0.197 0.000 0.493 0.193 0.017 0.000 0.100 

2016 0.186 0.000 0.500 0.196 0.018 0.000 0.100 

2017 0.185 0.000 0.500 0.196 0.019 0.000 0.100 

2018 0.212 0.000 0.481 0.173 0.034 0.000 0.100 

2019 0.172 0.000 0.481 0.173 0.034 0.040 0.100 

2020 0.172 0.000 0.481 0.173 0.034 0.040 0.100 

2021 0.160 0.000 0.462 0.165 0.033 0.080 0.100 

2022 0.160 0.000 0.462 0.165 0.033 0.080 0.100 

2023 0.159 0.000 0.463 0.165 0.033 0.080 0.100 

 LDT1s 

2009 0.171 0.000 0.377 0.062 0.000 0.290 0.100 

2010 0.165 0.000 0.422 0.069 0.000 0.244 0.100 

2011 0.157 0.000 0.468 0.077 0.000 0.198 0.100 

2012 0.153 0.000 0.511 0.094 0.000 0.142 0.100 

2013 0.144 0.000 0.519 0.095 0.000 0.142 0.100 

2014 0.177 0.000 0.527 0.096 0.000 0.100 0.100 

2015 0.228 0.000 0.523 0.149 0.000 0.000 0.100 

2016 0.219 0.000 0.530 0.151 0.000 0.000 0.100 

2017 0.219 0.000 0.530 0.151 0.000 0.000 0.100 

2018 0.249 0.000 0.521 0.130 0.000 0.000 0.100 

2019 0.208 0.000 0.522 0.130 0.000 0.040 0.100 

2020 0.208 0.000 0.522 0.130 0.000 0.040 0.100 

2021 0.194 0.000 0.504 0.122 0.000 0.080 0.100 

2022 0.194 0.000 0.504 0.122 0.000 0.080 0.100 

2023 0.193 0.000 0.505 0.122 0.000 0.080 0.100 

 LDT2s 

2009 0.7100 0.0000 0.0710 0.0190 0.0000 0.0000 0.2000 

2010 0.6960 0.0000 0.0820 0.0220 0.0000 0.0000 0.2000 

2011 0.6840 0.0000 0.0920 0.0240 0.0000 0.0000 0.2000 

2012 0.6690 0.0000 0.1020 0.0290 0.0000 0.0000 0.2000 

2013 0.6680 0.0000 0.1030 0.0290 0.0000 0.0000 0.2000 

2014 0.6650 0.0000 0.1050 0.0300 0.0000 0.0000 0.2000 

2015 0.6590 0.0000 0.1010 0.0400 0.0000 0.0000 0.2000 

2016 0.6560 0.0000 0.1030 0.0410 0.0000 0.0000 0.2000 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

70 

2017 0.6560 0.0000 0.1030 0.0410 0.0000 0.0000 0.2000 

2018 0.6630 0.0000 0.1000 0.0370 0.0000 0.0000 0.2000 

2019 0.6630 0.0000 0.1000 0.0370 0.0000 0.0000 0.2000 

2020 0.6630 0.0000 0.1000 0.0370 0.0000 0.0000 0.2000 

2021 0.6690 0.0000 0.0960 0.0350 0.0000 0.0000 0.2000 

2022 0.6690 0.0000 0.0960 0.0350 0.0000 0.0000 0.2000 

2023 0.6690 0.0000 0.0960 0.0350 0.0000 0.0000 0.2000 

 MDVs 

2009 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2010 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2011 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2012 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2013 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2014 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2015 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2016 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2017 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2018 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2019 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2020 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2021 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2022 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

2023 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 

E.3.1. Toxics Estimates 

Unlike MOBILE6, the EMFAC2007 model does not include estimates of the toxic species 

benzene, 1,3 butadiene, acrolein, formaldehyde, and acetaldehyde. To obtain toxics emissions 

from the EMFAC2007, the following process was used. First, the MOBILE6-MSAT model was 

modified to output the air toxics fractions (i.e., the ratio of the particular toxic emissions to VOC 

emissions) by vehicle class and model year. The model was run from 2003-2023, using the flat 

limits for California summer fuel parameters. While these limits are somewhat higher than the 

actual values for in-use gasoline, the in-use properties vary somewhat from year-to-year, and the 

use of the flat limits instead of in-use properties is not expected to have a significant effect on the 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

71 

toxic ratios for this analysis. Next, the fractions were averaged by age and vehicle class. The 

final exhaust toxics fractions, which are multiplied by the exhaust VOC emissions from each 

class, are shown in Table E-5. 

For evaporative toxics (benzene), the following MOBILE6 fractions were used for all ages and 

vehicle classes: 

Hot Soak Emission Fraction: 0.00675 

Diurnal Emission Fraction: 0.00610 

Running Loss Emission Fraction: 0.00675 

Table E-5 Exhaust Toxics Fractions Used to Estimate Toxics for EMFAC2007 (Obtained from MOBILE6-

MSAT) 

Age PC LDT1/2 MDV PC LDT1/2 MDV PC LDT1/2 MDV PC LDT1/2 MDV PC LDT1/2 MDV

1 0.06414 0.06424 0.06424 0.00494 0.00486 0.00486 0.01396 0.01414 0.01414 0.00817 0.00793 0.00793 0.00060 0.00060 0.00060

2 0.06414 0.06424 0.06424 0.00494 0.00486 0.00486 0.01396 0.01414 0.01414 0.00817 0.00793 0.00793 0.00060 0.00060 0.00060

3 0.06412 0.06419 0.06400 0.00495 0.00488 0.00492 0.01395 0.01413 0.01407 0.00817 0.00793 0.00792 0.00060 0.00060 0.00060

4 0.06392 0.06392 0.06372 0.00499 0.00493 0.00498 0.01389 0.01404 0.01398 0.00815 0.00792 0.00791 0.00060 0.00060 0.00060

5 0.06372 0.06367 0.06344 0.00503 0.00499 0.00504 0.01383 0.01397 0.01389 0.00814 0.00791 0.00790 0.00060 0.00060 0.00060

6 0.06354 0.06340 0.06315 0.00506 0.00505 0.00510 0.01378 0.01388 0.01381 0.00813 0.00790 0.00788 0.00060 0.00060 0.00060

7 0.06335 0.06314 0.06288 0.00510 0.00510 0.00516 0.01372 0.01380 0.01372 0.00811 0.00789 0.00787 0.00060 0.00060 0.00060

8 0.06316 0.06289 0.06263 0.00514 0.00516 0.00521 0.01366 0.01373 0.01364 0.00810 0.00788 0.00786 0.00060 0.00060 0.00060

9 0.06297 0.06265 0.06240 0.00518 0.00521 0.00526 0.01360 0.01365 0.01357 0.00808 0.00787 0.00785 0.00060 0.00060 0.00060

10 0.06276 0.06244 0.06219 0.00522 0.00525 0.00531 0.01355 0.01359 0.01351 0.00807 0.00786 0.00784 0.00060 0.00060 0.00060

11 0.06255 0.06223 0.06198 0.00526 0.00530 0.00535 0.01349 0.01353 0.01345 0.00805 0.00785 0.00783 0.00060 0.00060 0.00060

12 0.06232 0.06201 0.06176 0.00530 0.00533 0.00539 0.01343 0.01348 0.01340 0.00804 0.00784 0.00783 0.00060 0.00060 0.00060

13 0.06210 0.06182 0.06157 0.00534 0.00537 0.00542 0.01337 0.01343 0.01335 0.00802 0.00784 0.00782 0.00060 0.00060 0.00060

14 0.06187 0.06160 0.06135 0.00538 0.00540 0.00545 0.01331 0.01339 0.01331 0.00801 0.00783 0.00781 0.00060 0.00060 0.00060

15 0.06169 0.06140 0.06113 0.00542 0.00543 0.00548 0.01326 0.01336 0.01328 0.00800 0.00782 0.00781 0.00060 0.00060 0.00060

16 0.06151 0.06120 0.06093 0.00546 0.00546 0.00552 0.01321 0.01333 0.01324 0.00798 0.00782 0.00781 0.00060 0.00060 0.00060

17 0.06122 0.06084 0.06054 0.00552 0.00552 0.00558 0.01312 0.01325 0.01315 0.00796 0.00781 0.00779 0.00060 0.00060 0.00060

18 0.06093 0.05999 0.05966 0.00558 0.00553 0.00560 0.01304 0.01327 0.01316 0.00794 0.00784 0.00783 0.00060 0.00060 0.00060

19 0.06059 0.05903 0.05869 0.00565 0.00553 0.00560 0.01294 0.01331 0.01320 0.00792 0.00789 0.00787 0.00060 0.00060 0.00060

20 0.06022 0.05798 0.05761 0.00572 0.00552 0.00560 0.01283 0.01338 0.01326 0.00789 0.00795 0.00792 0.00060 0.00060 0.00060

21 0.05972 0.05684 0.05645 0.00579 0.00550 0.00558 0.01274 0.01348 0.01335 0.00788 0.00801 0.00799 0.00060 0.00060 0.00060

22 0.05915 0.05560 0.05520 0.00586 0.00547 0.00555 0.01265 0.01360 0.01347 0.00786 0.00809 0.00806 0.00060 0.00060 0.00060

23 0.05842 0.05431 0.05389 0.00601 0.00543 0.00552 0.01260 0.01375 0.01361 0.00786 0.00817 0.00815 0.00060 0.00060 0.00060

24 0.05714 0.05300 0.05257 0.00597 0.00542 0.00546 0.01275 0.01395 0.01376 0.00794 0.00826 0.00823 0.00060 0.00060 0.00060

25 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

26 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

27 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

28 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

29 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

30 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

31 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

32 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

33 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

34 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

35 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

36 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

37 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

38 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

39 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

40 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

41 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

42 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

43 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

44 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

45 0.05581 0.05170 0.05128 0.00594 0.00541 0.00541 0.01293 0.01415 0.01393 0.00801 0.00834 0.00832 0.00060 0.00060 0.00060

Acrolein

Exhaust Air Toxics Fractions

Benzene 1,3 Butadiene Formaldehyde Acetaldehyde
Appendix E EMFAC2007 Pollutant Emissions Modeling 

72 

Resting Loss Emission Fraction: 0.00610 

E.4. Impacts of the California Program 

There are two primary effects from implementing the California program that impact criteria 

pollutant emissions: fleet-turnover effects and rebound effects. These are discussed below. 

E.4.1. Fleet-Turnover Effects 

As noted elsewhere in this report, the new vehicle price increases as a result of the ZEV and 

GHG Standards will have a significant impact on fleet turnover, causing reduced new vehicle 

sales and the retention of older, higher-emitting vehicles. This can have a substantial impact on 

the criteria pollutant emissions inventory, as older vehicles in the fleet can have emission rates 

that are a hundred times higher than those of new vehicles (see Figure E-1). Obviously, any 

increase in travel from these vehicles has a negative impact on the emissions inventory and air 

quality. 

An example of the change in the distribution of vehicles in the fleet as a result of the California 

Program is shown in Figure E-2. This figure illustrates the change in the statewide vehicle 

-100

-80

-60

-40

-20

0

20

40

T

h

o

u

sand

s

of Vehicles

19801982198419861988199019921994199619982

000

2

002

2

004

2

006

2

008

2

010

2

012

2

014

2

016

2

018

2

020

Model Year

PC/LDT1 LDT2+

Figure E-2. Example of the Change in Statewide 2020 Vehicle Population Estimates as a Result of the 

Combined California Program 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

73 

population in 2020, where a positive number reflects more vehicles than in the baseline case and 

a negative number reflects fewer vehicles than in the baseline case. As observed in the figure, 

the population of pre-2011 model year vehicles is increased and the population of 2011 and 

newer model year vehicles has decreased relative to the base case. This change in vehicle 

population, which results in an older vehicle fleet, also results in increased VOC, CO, NOx, 

PM2.5, and toxics emissions compared to the baseline fleet. 

E.4.2. Rebound Effects 

Also as noted elsewhere in this report, a secondary outcome of the improved fuel economy 

required by both the ZEV and GHG Standards is additional VMT being accumulated by those 

vehicles subject to the regulations, due to their increased fuel economy (i.e., the “rebound 

effect”). In general, as the cost of travel decreases, total VMT increases. An example of this 

effect is illustrated in Figure E-3, which shows that VMT accrual is estimated to increase from 

the 2009 model year (the first year of the regulation) to the 2016 model year (when the 

regulation is fully phased in). 

Estimates of the 2020 Per-Vehicle Increase in VMT from the Rebound Effect

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Model Year

PC LDT1 LDT2 MDV

Figure E-3. Estimates of the Per-Vehicle Increase in VMT from the Rebound Effect. 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

74 

E.4.3. Emissions Impacts of Fleet-Turnover and Rebound Effects 

The emissions impacts of the fleet-turnover and rebound effects were calculated by modifying 

the baseline vehicle population estimates and the baseline per-vehicle VMT estimates in the 

spreadsheet model developed for this effort. Fleet turnover impacts all model year vehicles, 

while the rebound effect is only applied to vehicles subject to the regulation (i.e., 2009 and 

newer model years). 

The revised population files for each of the scenarios outlined above were input into the 

EMFAC2007 Fleet Emissions Model developed for this study. For each scenario, the total VMT 

(absent rebound effects) was held constant. This was accomplished by making slight 

modifications to the baseline daily VMT per vehicle for all vehicles. This was necessary because 

the total vehicle population (and the age distribution) changed under each scenario; thus, if the 

baseline VMT per vehicle was applied to each model year, the total VMT under the control cases 

would not be equal to the total VMT under the baseline case. Once this initial VMT adjustment 

was made, the VMT from 2009 and newer vehicles was increased to account for the rebound 

effect. This second adjustment results in higher total VMT for each vehicle class. 

E.5. Results 

Here we present results of the EMFAC 2007 emissions modeling, both for the entire state of 

California and specifically for the South Coast Air Basin.31

E.5.1. Statewide Results 

The following are statewide plots of the difference in emissions under the California Program 

relative to emissions under the Federal Program, for the summer season, in tons per day, for all 

vehicles under 8500 lbs GVW. Thus, positive values indicate that the inventories under the 

California Program are higher than under the Federal Program, while negative values indicate 

that the inventories under the California Program are lower than under the Federal Program. Put 

another way, a value of zero in any of the following charts indicates that emissions are identical 

under the two programs, a positive value indicates emissions are higher under the California 

Program than under the Federal Program, and a negative value indicates that emissions are lower 

under the California Program than under the Federal Program. The following charts are shown: 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

75 

§ VOC+NOx (Figure E-4); 

§ NOx (Figure E-5); 

§ VOC (Figure E-6); 

§ CO (Figure E-7); 

§ Exhaust PM2.5 (Figure F-8); 

§ 5 Toxics Summed (Figure E-9); and, 

§ SOx (Figure E-10). 

The VOC+ NOx, VOC, NOx, CO, and PM2.5 charts have been adjusted for fuel cycle effects 

consistent with the discussion in Appendix G. The toxics and SOx charts have not been adjusted 

for fuel cycle effects. 

 

31 All results shown in this section, except results for SOx and 5 Toxics Summed, include fuel cycle effects. 

Statewide VOC + NOx(EMFAC)

0

2

4

6

8

10

12

14

16

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-4. Difference in Statewide emissions of VOC + NOx under combined California Program (relative 

to emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

76 

Statewide NOx (EMFAC)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-5. Difference in statewide emissions of NOx under combined California Program (relative to 

emissions under Federal Program). 

Statewide VOC (EMFAC)

0

1

2

3

4

5

6

7

8

9

10

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

State

wide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-6. Difference in statewide emissions of VOC under combined California Program (relative to 

emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

77 

Statewide CO (EMFAC)

0

5

10

15

20

25

30

35

40

45

50

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-7. Difference in Statewide emissions of CO under combined California Program (relative to 

emissions under Federal Program). 

Exhaust PM2.5 (EMFAC)

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-8. Difference in Statewide emissions of exhaust PM2.5 under combined California Program 

(relative to emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

78 

Statewide Sum of Five Toxic Emissions (EMFAC)

0

0.05

0.1

0.15

0.2

0.25

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

State

wide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-9. Difference in Statewide sum of emissions of five toxic species under combined California 

Program (relative to emissions under Federal Program). 

Statewide SOx (EMFAC)

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-10. Difference in Statewide emissions of SOx under combined California Program (relative to 

emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

79 

E.5.2. South Coast Air Basin Results 

The following pages show plots of the difference in emissions of the California Program over the 

Federal Program, for the summer season, in tons per day, for all vehicles under 8500 lbs Gross 

Vehicle Weight Rating, in the South Coast Air Basin. Positive values indicate that the 

inventories under the California Program are higher than under the Federal Program. Negative 

values indicate that the inventories under the California Program are less than the Federal 

Program. The following charts are shown: 

§ VOC+NOx (Figure E-11); 

§ VOC (Figure E-12); 

§ NOx (Figure E-13); 

§ CO (Figure E-14); 

§ Exhaust PM2.5 (Figure E-15); 

§ SOx (Figure E-16); and, 

§ 5 Toxics Summed (Figure E-17). 

The VOC+ NOx, VOC, NOx, CO, and PM2.5 charts have been adjusted for fuel cycle effects 

consistent with the discussion in Appendix G. The toxics and SOx charts have not been adjusted 

for fuel cycle effects. 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

80 

South Coast VOC + NOx(EMFAC)

0

0.5

1

1.5

2

2.5

3

3.5

4

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-11. Difference in South Coast emissions of VOC+NOx under combined California Program 

(relative to emissions under Federal Program). 

South Coast NOx (EMFAC)

0

0.2

0.4

0.6

0.8

1

1.2

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-12. Difference in South Coast emissions of NOx under combined California Program (relative to 

emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

81 

South Coast VOC (EMFAC)

0

0.5

1

1.5

2

2.5

3

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-13. Difference in South Coast emissions of VOC under combined California Program (relative to 

emissions under Federal Program). 

South Coast CO (EMFAC)

0

2

4

6

8

10

12

14

16

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-14. Difference in South Coast emissions of CO under combined California Program (relative to 

emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

82 

South Coast Exhaust PM2.5 (EMFAC)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-15. Difference in South Coast exhaust emissions of PM2.5 under combined California Program 

(relative to emissions under Federal Program). 

South Coast Sum of Five Toxic Species (EMFAC)

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-16. Difference in South Coast sum of emissions of five toxic species under combined California 

Program (relative to emissions under Federal Program). 
Appendix E EMFAC2007 Pollutant Emissions Modeling 

83 

South Coast SOx (EMFAC)

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure E-17. Difference in South Coast emissions of SOx under combined California Program (relative to 

emissions under Federal Program. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

84 

Appendix F. MOBILE6.2 Pollutant Emissions Modeling 

The impacts of the California Program on California statewide and South Coast Air Basin 

(“SCAB”) light-duty vehicle emissions were evaluated using U.S. EPA’s MOBILE6.2 model.32 

Summer season inventory impacts were evaluated for calendar years 2006 to 2023 as, by that 

time, both the ZEV Standards and the GHG Standards programs will be fully phased-in and 2023 

is the attainment deadline for the South Coast Air Basin with the ozone NAAQS. Emission 

inventories of ozone precursors (VOC and NOx) were prepared as well as those of other criteria 

pollutants (CO, SOx and PM2.5) and five key air toxics (benzene, 1,3-butadiene, formaldehyde, 

acetaldehyde, and acrolein). 

Emissions impacts were estimated by evaluating and comparing the following two regulatory 

scenarios: 

1. Federal Tier 2 Program (baseline); and 

2. California Program (including exhaust and evaporative emission standards, ZEV 

Standards, and GHG Standards). 

The analysis and reported results of this document only include light-duty vehicles at or below 

8,500 lbs. GVRW. These include the federal vehicle classes of passenger car (PC), light-duty 

truck 1 (LDT1), light-duty truck 2 (LDT2), light-duty truck 3 (LDT3) and light-duty truck 4 

(LDT4). In this document we also define the term “medium duty vehicle” (MDV) as the sum of 

LDT3 and LDT4.33 

The method and results of the MOBILE6.2 analysis are described in the following sections. 

F.1. Method 

The MOBILE6.2 modeling approach for the two regulatory scenarios was intended to emulate 

the parallel analysis completed with the EMFAC2007 model – described in Appendix E. 

However, unlike EMFAC2007, MOBILE6.2 is not a “self-contained” model, i.e., it does not 

contain vehicle population and VMT estimates that are needed to generate an emissions 

inventory in the units of tons per day. Instead, MOBILE6.2 provides gram-per-mile (g/mi) 

 

32

 Version MOBILE6.2.03 dated 24 September 2003. 

33 This MDV definition is consistent with vehicle categorization of the EMFAC2007 model. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

85 

emissions estimates that are then combined with VMT estimates outside of the model. Thereby, 

the combination of MOBILE6.2 emission rates with VMT data (i.e., the calculation of emission 

inventories) was handled within a spreadsheet post-processor for this analysis. 

Overall, the application of two models (EMFAC2007 and MOBILE6.2) was implemented to 

determine if both models predict consistent results in quantifying the relative emissions impact 

of the California Program relative to the Federal Program.34 In both models’ analyses, the 

vehicle population and VMT assumptions were kept uniform, and therefore any resulting 

inventory differences would be due to differences in predicted emission rates from each model. 

The baseline VMT and vehicle populations used in the MOBILE6.2 analysis were those of the 

EMFAC2007 model, where “baseline” signifies the conditions in the absence of the fleet 

turnover and rebound effects resulting from the California Program—that is, conditions under 

the Federal Program. The extraction of these baseline data from EMFAC2007 are documented 

in Appendix E. 

Notably, MOBILE6.2 is not structured to model any one specific geographic area, but rather has 

been structured to allow users to input numerous parameters to tailor the model to any 

geographic area of interest. Thus, in applying the MOBILE6.2 model for this analysis, it was 

necessary to develop the detailed modeling inputs specific to the South Coast Air Basin 

(“SCAB”) and to California as a whole. The development of these MOBILE6.2 inputs is 

described next and is followed by the description of the approaches for modeling the fleet 

turnover and rebound effects with MOBILE6.2. 

F.2. MOBILE6.2 Inputs 

For consistency, the MOBILE6.2 input data were generally developed from the input data used 

in the EMFAC2007 model. The details of the MOBILE6.2 modeling input development are as 

described in the following sub-sections (identical values for each input parameter were used for 

both the California Program and the Federal Program except where specifically noted). 

 

34 The MOBILE and EMFAC models have developed and evolved separately over several years, and the current 

versions of these models contain numerous structural, methodological and data differences. Therefore, the two 

models can produce distinct emission rate predictions under the same set of modeling conditions. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

86 

F.2.1. Vehicle Regulatory Standards 

Assumed vehicle regulatory standards were modified accordingly to match the requirements of 

the California and Federal Programs. As noted earlier, the starting point for this analysis was the 

2009 model year, and therefore for 2008-and-earlier model year vehicles, both scenarios relied 

on identical regulatory assumptions. The following describes the MOBILE6.2 regulatory 

assumptions used. 

1. 2009-and-later model year vehicles (California program) – The proportion of ZEV Mandate 

vehicles (i.e., PZEV, AT-PZEV and ZEV) by model year was based on the results of the 

New Vehicle Market Model. The remaining non-ZEV vehicles were assumed to follow the 

regulatory assumptions of the EMFAC2007 model. Adjustments were made to the 

proportions of the remaining vehicles to ensure compliance with fleet average NMOG 

standards in California. The resulting exhaust and evaporative compliance schedules by 

model year were incorporated into the MOBILE6.2 inputs files. These schedules are those 

also used in the EMFAC2007 analysis and are shown in Appendix E. 

2. 2009-and-later model year vehicles (federal program) – The MOBILE6.2 defaults for the 

federal Tier II program were used. 

3. 2003 through 2008 model year vehicles – The modeling of California standards with 

MOBILE6.2 was completed following EPA guidelines for those states opting into the 

California LEV II program (EPA 2002). California exhaust and evaporative standards were 

based on the MOBILE6.2 modeling inputs that accompany these guidelines. These 

regulatory assumptions and guidance are consistent with the regulatory assumptions in 

EMFAC2007. 

4. 1994 through 2002 model year vehicles – The modeling of California standards was 

completed by extracting out the assumed model year exhaust standards and technology 

groups from EMFAC2007 and placing these into the corresponding MOBILE6.2 input file 

for adjusting 1994-and-later model year vehicle exhaust standards. This input file allows for 

adjusting model year populations to assumed proportions meeting Tier 0, Tier 1, TLEV, 

LEV, ULEV and ZEV standards. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

87 

Prior to the 1994 model year, MOBILE6.2 does not allow for modifying vehicle regulatory 

standards through the model’s input files, and no adjustments were made for these model years 

to account for differences between the California standards and the corresponding assumptions 

of the MOBILE6.2 model. 

F.2.2. Ambient Conditions 

Ambient conditions, consisting of hourly temperature and humidity values assumed by the model 

for summer season modeling, were extracted from EMFAC2007. The hourly data were 

incorporated into the MOBILE6.2 input files. Separate values were obtained for South Coast 

and statewide modeling. For the statewide values, EMFAC2007 uses a VMT-weighted average 

to generate the California-wide assumptions. 

F.2.3. Fuel Parameters 

California gasoline parameters were taken from the summer 2005 gasoline survey published by 

the Alliance of Automobile Manufacturers. Survey results by grade were weighted into a single 

composite based on California gasoline sales by grade published in the Petroleum Marketing 

Annual 2005 (EIA 2006). MOBILE6.2 inputs for sulfur content, RVP, aromatic content, 

benzene content, olefin content, oxygenate content, E200 and E300 were obtained in this 

manner. 

The Los Angeles survey data was used to define MOBILE6.2 fuel properties for the South Coast 

Air Basin. The California statewide properties were estimated by combining the Los Angles and 

San Francisco survey data in proportion to VMT.35 The resulting MOBILE6.2 gasoline 

properties for the two modeling areas were nearly identical (e.g., RVP of 7.0 psi, sulfur content 

less than 9 ppm, benzene content of about 0.5%, and 100 percent ethanol-blend market share at 

5.7 volume percent ethanol). 

F.2.4. Vehicle Operation Characteristics 

Several vehicle operating characteristics were extracted from EMFAC2007 output files from 

specifically designed model runs to define corresponding MOBILE6.2 input parameters. 

 

35 The Los Angeles survey was used to represent those California areas covered by federal reformulated gasoline 

regulations (representing 89 percent of the state VMT) and San Francisco was used to represent the areas not 

covered by this federal requirement (11 percent of state VMT). 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

88 

EMFAC2007 results were compiled for both statewide and South Coast operation for calendar 

year 2006 – including results detailed by speed, hour-of-day and vehicle age – as needed to 

process into specific MOBILE6.2 parameters under summer weekday conditions. The following 

MOBILE6.2 input parameters were defined in this manner:36

1. Speed Distributions – the normalized proportion of VMT by 5-mph speed bin for each hour 

of day, 

2. Starts per Day - the average number of engine starts per vehicle per day as a function of 

vehicle class and vehicle age, 

3. Hourly VMT Distributions – the normalized proportion of VMT by hour of day, and 

4. Hourly Trip Distributions – the normalized proportion of trips by hour of day. 

F.2.5. Mileage Accumulation Rates and Registration Distributions 

MOBILE6.2 mileage accumulation rates and registration distributions were also based on data 

extracted from EMFAC2007. Mileage accumulation rates are average annual miles driven by 

vehicle class by vehicle age; registration distributions are the normalized age distributions of 

vehicle populations by vehicle class. For these two parameters, the values modeled varied by 

regulatory scenarios. 

For the Federal Program the baseline EMFAC2007 data were used. For the California Program, 

the rebound and fleet turnover effects were factored into the registration distribution and mileage 

accumulation rates of the scenario. The method for making these adjustments is described 

below. Notably, for these two parameters, the values incorporated into MOBILE6.2 were 

specific to each calendar year (2006 through 2023). 

F.2.6. I/M Program Parameters 

The MOBILE6.2 I/M program modeling parameters were taken from those used by the U.S. 

EPA for the 2002 National Emission Inventory (NEI) effort (EPA 2005). The 2002 NEI based 

 

36 EMFAC2007 data for calendar year 2006 were used to define the parameters listed. These were then used for 

modeling all calendar years in the MOBILE6.2 analysis (2006 through 2023); of these parameters only the speed 

distribution of EMFAC2007 can vary by calendar year for some areas of California. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

89 

inputs were reviewed for consistency with the EMFAC2007 modeling assumptions. The 

program includes an anti-tampering inspection, ASM tailpipe testing and OBD testing 

requirements. 

F.2.7. Particulate Matter Emission Rates 

MOBILE6.2 default PM emission rates have been carried over from successive versions of EPA 

models for some time and have not been updated significantly in 20 years (mid-1980’s test data). 

EPA recognized the need to potentially update the PM emission rate assumptions in MOBILE6.2 

and made PM the only criteria pollutant for which alternate emission rate assumptions can be 

handled through the model input. However, EPA has not provided to date any updates to the 

PM emission rates of MOBILE6.2. 

Sierra Research developed updated light-duty vehicle PM emission rates for the Western 

Regional Air Partnership. These were based on more recently collected test data – much of 

which was California-based (Sierra 2001). These PM emission rate updates were used in this 

analysis as well and were incorporated into the MOBILE6.2 PM emission rate inputs files. 

Notably, the PM emission rates included a deterioration rate based on the assumption that 9 

percent of the fleet would be high emitters at the 10 year-old mark (equal to about 150,000 

accumulated miles based on the mileage accumulation rates of EMFAC2007). 

F.3. Fleet Turnover Effects 

The fleet turnover effect impacts only the California program scenario resulting in changes to the 

fleet composition as determined by the New Vehicle Market Model and the Scrappage Model. 

The vehicle population changes due to the fewer new sales and a greater retention of older 

vehicles (relative to the Federal Program). Overall, there is typically a net loss in the total 

number of vehicles of one to two percent or less. These impacts were incorporated into the 

MOBILE6.2 analysis as follows. 

1. Registration Distributions – The registration distributions of the California program scenario 

were recalculated based on the scenario fleet composition data factoring in the fleet turnover 

effect. 

2. VMT – Overall, the fleet turnover effect results in the conservation of VMT in that total VMT 

demand would be unaffected remains unchanged from the baseline (federal program 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

90 

scenario). However, the proportions of VMT by vehicle class and vehicle age are adjusted to 

account for the changes in fleet composition. These changes were incorporated into the 

spreadsheet post-processor used to calculate emission inventories in the MOBILE6.2 

analysis. All vehicles were assumed to make up any VMT shortfall (due to a net reduction in 

overall fleet population) by driving a bit more per vehicle – but the relative proportions 

between mileage accumulation rates were retained so that newer vehicles are driven more 

than older vehicles in making up any additional VMT per vehicle. 

F.4. Rebound Effects 

The rebound effect is relevant only for the California Program—resulting in increased VMT for 

those vehicles with increased fuel economy over the baseline (because these vehicles are less 

expensive to operate). The rebound effect was incorporated into the MOBILE6.2 analysis as 

follows. 

1. VMT – The VMT driven by 2009-and-later model year vehicles under the California Program 

were modified to include the estimated rebound VMT. This change was made to the 

spreadsheet post-processor model. 

2. Mileage Accumulation Rates – For 2009-and-later model year vehicles only, the MOBILE6.2 

mileage accumulation rates were modified for consistency of the rebound VMT resulting is 

slightly greater mileage accumulation rates for this model year group in the California 

program scenario. 

F.5. Results 

The MOBILE6.2 analysis inventory results are discussed in the following sub-sections. South 

Coast Air Basin results are presented first, followed by the California statewide results. The 

inventory results are presented as the difference between the California Program and the Federal 

Program, where a positive difference signifies an increase in emissions under the California 

program. Results shown are summer season tons per day for light-duty vehicles (<8500 lbs 

GVWR). 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

91 

F.5.1. South Coast Air Basin 

The following inventory difference plots are presented for the South Coast Air Basin including 

the rebound and fleet turnover effects: 

Figure F-1: ozone precursor emissions (VOC & NOx), 

Figure F-2: CO emissions, 

Figure F-3: PM2.5 emissions, 

Figure F-4: SOx emissions, and 

Figure F-5: toxics emissions (sum of 5 species). 

These results show that the California program results in higher emissions for all pollutants 

except SOx. SOx emissions are lower due to reduced fuel consumption under the California 

Program. 

The results shown in Figures F-1 through F-5 do not factor in the fuel cycle emissions, which are 

generally lower under the California Program. The following figures include the fuel cycle 

effects (as estimated in Appendix G for ozone precursors, CO and PM). 

Figure F-6: ozone precursor emissions (VOC & NOx), 

Figure F-7: CO emissions, and 

Figure F-8: PM2.5 emissions. 

When the fuel cycle effects are included, the inventory results for the California program 

scenario are still greater than those of the federal program. 

F.5.2. California 

A corresponding set of inventory difference plots are also presented for the California statewide 

results including the rebound and fleet turnover effects: 

Figure F-9: ozone precursor emissions (VOC & NOx), 

Figure F-10: CO emissions, 

Figure F-11: PM2.5 emissions, 

Figure F-12: SOx emissions, and 

Figure F-13: toxics emissions (sum of 5 species). 

These results show similar results to those of the South Coast Air Basin. The California program 

scenario emissions are generally greater than those of the federal scenario. The exceptions to 

this are SOx emissions and toxics (calendar year 2023 only). 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

92 

The following figures incorporate the fuel cycle effects (as estimated in Appendix G for ozone 

precursors, CO and PM) into the California statewide results. 

Figure F-14: ozone precursor emissions (VOC & NOx), 

Figure F-15: CO emissions, and 

Figure F-16: PM2.5 emissions. 

When the fuel cycle effects are included, the inventory results for the California program 

scenario are still greater than those of the federal program. 

South Coast VOC + NOx (MOBILE, Excludes Fuel Cycle 

Effects)

0

2

4

6

8

10

12

14

16

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-1. Difference in South Coast emissions of VOC+NOx under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

93 

South Coast CO (MOBILE, Excludes Fuel Cycle Effects)

0

20

40

60

80

100

120

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-2. Difference in South Coast emissions of CO under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 

South Coast PM2.5 (MOBILE, Excludes Fuel Cycle Effects)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-3. Difference in South Coast emissions of PM2.5 under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

94 

South Coast SOx(MOBILE, Excludes Fuel Cycle Effects)

-0.5

-0.45

-0.4

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-4. Difference in South Coast emissions of SOx under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 

South Coast Sum of Five Toxic Species (MOBILE, Excludes 

Fuel Cycle Effects)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-5. Difference in South Coast emissions of 5 air toxics under combined California Program 

(relative to emissions under Federal Program), not accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

95 

South Coast VOC + NOx (MOBILE, Includes Fuel Cycle Effects)

0

2

4

6

8

10

12

14

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Change in Emissions Under California Program

Figure F-6. Difference in South Coast emissions of VOC+NOx under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects. 

South Coast CO (MOBILE, Includes Fuel Cycle Effects)

0

20

40

60

80

100

120

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Change in Emissions Under California Program

Figure F-7. Difference in South Coast emissions of CO under combined California Program (relative to 

emissions under Federal Program), accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

96 

South Coast Exhaust PM2.5 (MOBILE, Includes Fuel Cycle 

Effects)

0

0.02

0.04

0.06

0.08

0.1

0.12

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Change in Emissions Under California Program

Figure F-8. Difference in South Coast emissions of PM2.5 under combined California Program (relative to 

emissions under Federal Program), accounting for fuel cycle effects. 

Statewide VOC + NOx (MOBILE, Excludes Fuel Cycle Effects)

0

5

10

15

20

25

30

35

40

45

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

State

wide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-9. Difference in California emissions of VOC+NOx under combined California Program (relative 

to emissions under Federal Program), not accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

97 

Statewide CO (MOBILE, Excludes Fuel Cycle Effects)

0

50

100

150

200

250

300

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

State

wide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-10. Difference in California emissions of CO under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 

Statewide PM2.5 (MOBILE, Excludes Fuel Cycle Effects) 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-11. Difference in California emissions of PM2.5 under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

98 

Statewide SOx (MOBILE, Excludes Fuel Cycle Effects)

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-12. Difference in California emissions of SOx under combined California Program (relative to 

emissions under Federal Program), not accounting for fuel cycle effects. 

Statewide Sum of Five Toxic Species (MOBILE, Excludes Fuel 

Cycle Effects)

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-13. Difference in California emissions of 5 air toxics under combined California Program (relative 

to emissions under Federal Program), not accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

99 

Statewide VOC + NOx (MOBILE, Includes Fuel Cycle Effects)

0

5

10

15

20

25

30

35

40

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-14. Difference in California emissions of VOC+NOx under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects. 

Statewide CO (MOBILE, Includes Fuel Cycle Effects)

0

50

100

150

200

250

300

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-15. Difference in California emissions of CO under combined California Program (relative to 

emissions under Federal Program), accounting for fuel cycle effects. 
Appendix F MOBILE6.2 Pollutant Emissions Modeling 

100

References 

U.S. EPA, Modeling Alternative NLEV Implementation and Adoption of California Standards in 

MOBILE, guidance memorandum from Assessment and Modeling Division, Office of 

Transportation and Air Quality, U.S. Environmental Protection Agency, June 2002. 

U.S. Energy Information Administration, Petroleum Marketing Annual 2005, DOE/EIA0487(2005), August 2006. 

U.S. EPA, Documentation for the Final 2002 Mobile National Emissions Inventory, Assessment 

and Standards Division, Office of Transportation and Air Quality, U.S. Environmental Protection 

Agency, September 2005. 

Sierra Research, Methodologies Used to Develop the On-Road Mobile Source Emissions 

Inventories, memorandum prepared for the Western Regional Air Partnership, October 2001. 

Statewide Exhaust PM2.5 (MOBILE, Includes Fuel Cycle 

Effects)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

200620072008200920102011201220132014201520162017201820192020202120222023

Calendar Year

Statewide Inventory Difference (tpd)

Difference in Emissions Under California Program

Figure F-16. Difference in California emissions of VOC+NOx under combined California Program 

(relative to emissions under Federal Program), accounting for fuel cycle effects. 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

101

Appendix G. Emissions Impacts Associated with Reduced Gasoline 

Consumption 

The term “fuel cycle emissions” (sometimes called “upstream emissions”) is related to a concept 

whereby the criteria emissions associated with the use of different types of vehicular fuels (e.g., 

gasoline) are assessed starting at the point that production of the fuel begins--in this case, a 

petroleum well--and continuing through the delivery of the fuel to a vehicle. The following are 

potential sources of fuel cycle emissions associated with the use of gasoline: 

1. Extraction of petroleum; 

2. Transport of petroleum to a refinery; 

3. Production of gasoline at a refinery; 

4. Transport and storage of gasoline; and 

5. Gasoline marketing. 

In analyzing fuel cycle emissions differences between the two regulatory scenarios of interest, 

the key factor is the effect of the California regulation on the fuel economy of new vehicles. 

Reduced fuel consumption translates into reduced fuel cycle emissions. The following sections 

examine the upstream criteria emissions associated with gasoline consumption of the federal and 

California regulatory scenarios.37 

G.1. Method 

The primary regulatory driver affecting gasoline consumption is the GHG Standard. The method 

used in this study generally follows that of CARB in its Initial Statement of Reasons (ISOR) 

(CARB 2004) with significant changes to the fuel cycle emission factors to correct for errors 

made by CARB. 

We have already completed an extensive review of the fuel cycle methods employed by CARB 

in the regulatory process for the GHG Standards, which is not repeated here (Sierra 2005). In 

brief, CARB staff estimates of fuel cycle emissions changed multiple times as updates were 

published to correct for staff errors (CARB 2004a), with the staff’s final assessment being that 

 

37 Note that we do not account for fuel cycle emissions associated with the production and delivery of hydrogen. 

Thus, our estimates overstate the emissions reductions of the California program due to fuel cycle effects. 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

102

published on October 19, 2004 in CARB’s first 15-Day Notice for the California GHG 

regulations (CARB 2004b). Specifically, final estimates were contained in Attachment II to the 

15-Day Notice entitled “Additional Supporting Documents and Information.” We found that 

significant flaws continued to exist in the 15-Day Notice version of the staff’s emission factor 

estimates – most significant were the assumed fleet characteristics of fuel delivery trucks and 

assumed transit distances traveled. These assumptions conflicted with both other CARB 

regulatory estimates as well as those used by the South Coast Air Quality Management District 

(“SCAQMD”) and resulted in a significant overestimate of fuel cycle emissions (up to a factor of 

4). 

We have estimated revised gasoline fuel cycle emission factors correcting for the errors made in 

CARB’s assessments of the GHG Standards. These factors, specific to California gasoline 

production and delivery, are presented in Table G-1 and represent the criteria emissions in grams 

of pollutant per gallon of fuel delivered. Emission factors are reported as a range reflecting the 

valid range of underlying assumptions. 

Table G-1. California Fuel Cycle Emission Factors (grams/gallon) 

Pollutant 

Low-End 

Estimate 

High-End 

Estimate 

NOX 0.010 0.035

CO 0.006 0.009

NMOG 0.190 0.213

PM 0.0003 0.0008

Fuel cycle emissions were estimated from the combination of emission factors and estimated 

gasoline consumption under two scenarios (the Federal Program and the California Program). 

Fuel consumption was estimated in two ways: first, following the methods of the EMFAC2007 

model, and second, following the methods of MOBILE6.2. Fuel consumption was calculated as 

part of each model’s emission inventory assessment of the two regulatory scenarios (as described 

in Appendix E and Appendix F, respectively). For the California Program, the fuel economy of 

2009-and-later model year vehicles increases over that under the Federal Program. The percent 

change in model year fuel economy is shown in Table G-2 and includes the impacts of both the 

ZEV Standards and the GHG Standards. These fuel economy changes were incorporated into 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

103

the emission inventory analysis of each model, fuel economy was converted to fuel consumption 

using VMT data, and the resulting fuel consumption estimates included both the rebound and 

fleet turnover effects of the California program. 

Table G-2. Percent Increase in Model Year Fuel Economy California Program Over the Federal Program 

Model 

Year PC LDT1 LDT2 MDV 

2009 4.21% 0.88% 0.45% 0.42% 

2010 7.25% 2.53% 2.32% 2.30% 

2011 8.83% 3.44% 2.99% 2.96% 

2012 10.43% 4.36% 3.66% 3.63% 

2013 17.40% 7.54% 7.56% 7.53% 

2014 24.70% 10.77% 11.56% 11.54% 

2015 32.62% 14.29% 15.70% 15.65% 

2016 40.61% 17.62% 19.90% 19.86% 

2017 40.59% 17.61% 19.90% 19.86% 

2018 40.54% 17.63% 19.90% 19.86% 

2019 40.53% 17.62% 19.90% 19.86% 

2020 40.51% 17.60% 19.90% 19.86% 

2021 40.52% 17.64% 19.90% 19.86% 

2022 40.50% 17.63% 19.90% 19.86% 

2023 40.49% 17.61% 19.90% 19.86% 

G.2. Results 

The estimated summer season daily fuel consumption is presented in Table G-3 and Table G-4 

for California statewide and the South Coast Air Basin, respectively. For the statewide total, the 

California program is estimated to result in a reduction of about 6 to 7 million gallons by 2023. 

In general, the fuel consumption estimates for EMFAC2007 are greater than those of 

MOBILE6.2 as the underlying fuel economy of a given model year vehicle is less in the EMFAC 

model. For the South Coast, the results are similar to those reported for the state where the 

district makes up between 38 and 42 percent of the statewide fuel consumption – depending on 

calendar year. 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

104

Table G-3. California Statewide Fuel Consumption (Gallons/Day) Vehicles at or below 8,500 Lbs GVRW, 

Summer Season 

MOBILE6.2 Model Results EMFAC2007 Model Results 

Calendar 

Year Federal 

Program 

California 

Program 

Difference 

(California 

Program 

Reduction) 

Federal 

Program 

California 

Program 

Difference 

(California 

Program 

Reduction) 

2006 41,345,835 41,345,835 0 48,362,184 48,362,184 0 

2007 40,892,899 40,892,899 0 47,712,624 47,712,624 0 

2008 41,234,450 41,234,450 0 47,926,581 47,926,581 0 

2009 41,734,053 41,652,604 81,449 48,357,727 48,263,761 93,966 

2010 42,275,427 42,040,716 234,712 48,932,238 48,661,616 270,622

2011 42,817,673 42,412,982 404,691 49,681,856 49,213,577 468,279

2012 43,430,712 42,834,934 595,778 50,306,258 49,617,299 688,960

2013 44,121,678 43,182,355 939,323 51,015,386 49,928,172 1,087,213 

2014 44,769,097 43,368,974 1,400,123 51,736,997 50,111,993 1,625,004 

2015 45,425,477 43,449,581 1,975,897 52,473,466 50,178,603 2,294,863 

2016 45,974,687 43,370,552 2,604,135 53,278,925 50,234,473 3,044,453 

2017 46,536,490 43,339,924 3,196,566 53,906,595 50,168,629 3,737,966 

2018 47,172,230 43,406,066 3,766,164 54,582,716 50,175,377 4,407,339 

2019 47,822,658 43,514,333 4,308,325 55,290,638 50,246,275 5,044,363 

2020 48,465,572 43,637,284 4,828,288 56,025,925 50,373,053 5,652,872 

2021 49,049,620 43,745,545 5,304,075 57,023,110 50,772,275 6,250,835 

2022 49,635,646 43,869,393 5,766,253 57,698,418 50,905,087 6,793,332 

2023 50,301,298 44,096,362 6,204,936 58,402,067 51,087,087 7,314,980 

Table G-4. South Coast Air Basin Fuel Consumption (Gallons/Day) Vehicles at or below 8,500 Lbs GVRW, 

Summer Season 

MOBILE6.2 Model Results EMFAC2007 Model Results 

Calendar 

Year Federal 

Program 

California 

Program 

Difference 

(California 

Program 

Reduction) 

Federal 

Program 

California 

Program 

Difference 

(California 

Program 

Reduction) 

2006 17,225,854 17,225,854 0 20,433,167 20,433,167 0 

2007 16,696,744 16,696,744 0 19,745,178 19,745,178 0 

2008 16,824,126 16,824,126 0 19,748,543 19,748,543 0 

2009 16,938,564 16,903,372 35,192 19,849,687 19,808,576 41,110 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

105

2010 17,051,054 16,953,648 97,406 19,957,842 19,844,056 113,786

2011 17,196,138 17,032,733 163,405 20,235,288 20,043,377 191,912

2012 17,367,352 17,131,287 236,065 20,405,868 20,128,931 276,937

2013 17,576,114 17,208,789 367,325 20,617,685 20,186,643 431,042

2014 17,720,304 17,184,076 536,228 20,800,821 20,169,214 631,606

2015 17,881,368 17,133,238 748,130 20,979,770 20,097,840 881,929

2016 17,984,445 17,008,457 975,988 21,176,940 20,018,920 1,158,020 

2017 18,104,588 16,912,277 1,192,311 21,311,890 19,896,455 1,415,435 

2018 18,259,336 16,857,394 1,401,942 21,474,472 19,808,673 1,665,799 

2019 18,426,840 16,823,765 1,603,076 21,657,424 19,751,473 1,905,951 

2020 18,598,760 16,801,682 1,797,078 21,856,886 19,719,989 2,136,897 

2021 18,706,077 16,740,797 1,965,280 22,078,440 19,729,218 2,349,222 

2022 18,824,076 16,693,977 2,130,100 22,215,541 19,669,682 2,545,859 

2023 18,972,281 16,685,619 2,286,663 22,366,452 19,631,570 2,734,882 

The reduction in fuel consumption under the California program was converted into a reduction 

in fuel cycle emissions. The results are presented in Table G-5 and Table G-6 for California and 

the South Coast Air Basin, respectively. Results are reported as a range where the low-end 

estimate is based on the low-end emission factor (see Table G-2) and the MOBILE6.2-based fuel 

consumption differences. Accordingly, the high-end estimate is based on the high-end emission 

factor and EMFAC2007-based fuel consumption differences. By 2023, the statewide reduction 

is estimated between 1.3 and 1.6 tpd for NMOG, between 0.07 and 0.28 tpd for NOx, between 

0.04 and 0.07 tpd for CO, and between 0.002 and 0.006 tpd for PM. For the South Coast, the 

results are similar to those reported for the state with reported reductions in approximate 

proportion to the district’s share of the state fuel consumption (between 38 and 42 percent of the 

state total). 

Finally, the reduction in fuel cycle emissions for the sum of ozone precursors (NMOG and NOx) 

is presented graphically in Figure G-1 and Figure G-2 for California and the South Coast Air 

Basin, respectively. For California, the ozone precursor reduction due to the California program 

reaches a maximum of 1.4 to 2.0 tpd in 2023. Comparatively, the South Coast reduction in fuel 

cycle emissions is estimated to range from 0.5 to 0.7 tpd by 2023. 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

106

Table G-5. California Statewide Fuel Cycle Emissions Reduction (Tons/Day) Due to the California Program, 

Low-End and High-End Values 

Calendar NMOG NOX CO PM 

Year Low High Low High Low High Low High 

2009 0.017 0.022 0.001 0.004 0.001 0.001 0.0000 0.0001 

2010 0.049 0.064 0.003 0.010 0.002 0.003 0.0001 0.0002 

2011 0.085 0.110 0.004 0.018 0.003 0.005 0.0001 0.0004 

2012 0.125 0.162 0.007 0.027 0.004 0.007 0.0002 0.0006 

2013 0.197 0.255 0.010 0.042 0.006 0.011 0.0003 0.0010 

2014 0.293 0.382 0.015 0.063 0.009 0.016 0.0005 0.0014 

2015 0.414 0.539 0.022 0.089 0.013 0.023 0.0007 0.0020 

2016 0.545 0.715 0.029 0.117 0.017 0.030 0.0009 0.0027 

2017 0.669 0.878 0.035 0.144 0.021 0.037 0.0011 0.0033 

2018 0.789 1.035 0.042 0.170 0.025 0.044 0.0012 0.0039 

2019 0.902 1.184 0.047 0.195 0.028 0.050 0.0014 0.0044 

2020 1.011 1.327 0.053 0.218 0.032 0.056 0.0016 0.0050 

2021 1.111 1.468 0.058 0.241 0.035 0.062 0.0018 0.0055 

2022 1.208 1.595 0.064 0.262 0.038 0.067 0.0019 0.0060 

2023 1.300 1.718 0.068 0.282 0.041 0.073 0.0021 0.0065 

Table G-6. South Coast Air Basin Fuel Cycle Emissions Reduction (Tons/Day) Due to the California 

Program, Low-End and High-End Values 

Calendar NMOG NOX CO PM 

Year Low High Low High Low High Low High 

2009 0.007 0.010 0.000 0.002 0.000 0.000 0.0000 0.0000 

2010 0.020 0.027 0.001 0.004 0.001 0.001 0.0000 0.0001 

2011 0.034 0.045 0.002 0.007 0.001 0.002 0.0001 0.0002 

2012 0.049 0.065 0.003 0.011 0.002 0.003 0.0001 0.0002 

2013 0.077 0.101 0.004 0.017 0.002 0.004 0.0001 0.0004 

2014 0.112 0.148 0.006 0.024 0.004 0.006 0.0002 0.0006 

2015 0.157 0.207 0.008 0.034 0.005 0.009 0.0002 0.0008 

2016 0.204 0.272 0.011 0.045 0.006 0.011 0.0003 0.0010 

2017 0.250 0.332 0.013 0.055 0.008 0.014 0.0004 0.0012 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

107

2018 0.294 0.391 0.015 0.064 0.009 0.017 0.0005 0.0015 

2019 0.336 0.448 0.018 0.074 0.011 0.019 0.0005 0.0017 

2020 0.376 0.502 0.020 0.082 0.012 0.021 0.0006 0.0019 

2021 0.412 0.552 0.022 0.091 0.013 0.023 0.0006 0.0021 

2022 0.446 0.598 0.023 0.098 0.014 0.025 0.0007 0.0022 

2023 0.479 0.642 0.025 0.106 0.015 0.027 0.0008 0.0024 

Ozone Precursor Emissions (NMOG+NOx)

0

0.5

1

1.5

2

2.5

2006 2008 2010 2012 2014 2016 2018 2020 2022

Calendar Year

Fuel Cycle Emissions Reduction (tons/day)

High-End Estimate

Low-End Estimate

Figure G-1. Reduction in Summer Season California Fuel Cycle Emissions Due to the California Program 

(California Statewide) 
Appendix G Emissions Impacts Associated with Reduced Gasoline Consumption 

108

References 

California Air Resources Board, Initial Statement of Reasons for Proposed Rulemaking, Public 

Hearing to Consider Adoption of Regulations to Control Greenhouse Gas Emissions from Motor 

Vehicles, August 6, 2004. 

Sierra Research, Evaluation of Vermont’s Adoption of California’s Greenhouse Gas Regulations 

on Criteria Pollutants and Precursor Emissions, September 19, 2005. 

California Air Resources Board, Addendum to Initial Statement of Reasons, Public Hearing to 

Consider Adoption of Regulations to Control Greenhouse Gas Emissions from Motor Vehicles, 

September 10, 2004a. 

California Air Resources Board, Public Hearing to Consider Adoption of Regulations to Control 

Greenhouse Gas Emissions from Motor Vehicles, October 19, 2004b, 

http://www.arb.ca.gov/regact/grnhsgas/15day.pdf. 

Ozone Precursor Emissions (NMOG+NOx)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

2006 2008 2010 2012 2014 2016 2018 2020 2022

Calendar Year

Fuel Cycle Emissions Benefit (tons/day)

High-End Estimate

Low-End Estimate

Figure G-2. Reduction in Summer Season California Fuel Cycle Emissions Due to the California Program 

(South Coast Air Basin) 

























 

STATE OF CALIFORNIA 

AIR RESOURCES BOARD

Comments of the Alliance of Automobile Manufacturers 

On the Proposed Rulemaking to Adopt Regulations to 

Control Greenhouse Gas Emissions from Motor Vehicles 

September 23, 2004 
 i 

Executive Summary

 This is a rulemaking required by Assembly Bill 1493, enacted in 2002 in order to address 

concerns about the global climate. A.B. 1493 directed the Air Resources Board to consider 

adoption of regulations that would control greenhouse gases from motor vehicles, on the premise 

that such rules might help reduce global warming. 

 The regulations proposed by the Executive Officer on August 6, 2004, and now before 

the Board for review would not serve the ultimate purpose of the legislation, or any other 

environmental goal. Instead, as explained in these comments, the proposed rules would increase 

pollution levels in California’s cities and create safety risks for the motoring public. Increases in 

smog-forming emissions from the California motor vehicle fleet could surpass 30 tons per day in 

2020. Depending on assumptions about how the proposed rule might affect the weight of the 

California fleet and the total number of vehicle miles traveled in the state, the regulation could 

result in hundreds of additional deaths on California’s roads. 

 The proposed rules would also add substantially to the costs of purchasing a new vehicle 

and would reduce the variety of different vehicle models that are currently available in 

California. The costs of the technologies identified by the Executive Officer for use in 

complying with the proposed rules would be more than double the possible savings in reduced 

operating costs. The proposed rules would cost California motor vehicle purchasers roughly $14 

billion by 2016 and substantially reduce employment in the automobile industry in California. 

California would become the only State in the country attempting to regulate motor vehicle fuel 

economy, which is the responsibility of the national government under federal law. For those 

reasons, the Alliance of Automobile Manufacturers does not support adoption of the proposed 

rules. 

 Few of the adverse effects of the proposed rule have been considered, and none have 

been fully addressed, in the documents published by the Executive Officer to support the 

proposal. The Board needs to hear from the Executive Officer on each of those adverse effects 

and permit adequate time for the public to respond. We hope that the Board will decline the 

Executive Officer’s proposal, and will request that the staff (1) analyze the serious issues raised 

in these comments, and (2) develop one or more alternatives that would address the problems 

with the current proposal. 
 ii 

Table of Contents

Page

I. The Analytical Framework for the Current Rulemaking..............................................2

A. The General Role of “Cost Effectiveness” Analysis in the Greenhouse Gas 

Rulemaking..............................................................................................................4 

B. Total Costs of the Proposed Regulation for the Consumer......................................8 

C. Valuation of Future Cost Savings from Reduced Gasoline Consumption ............13 

II. Technical and Economic Analysis of the Proposed Regulations .................................17

A. Engineering Cost and Benefit Assessment ............................................................18 

B. Likely Industry Response to the Proposed Regulation..........................................22 

III. Environmental and Other Health-Related Impacts of the Proposed 

Regulation.........................................................................................................................25

IV. The Board’s Options on the Current Record................................................................31

V. Conclusion ........................................................................................................................39
 1 

Comments of the Alliance of Automobile Manufacturers 

On the Proposed Rulemaking to Adopt Regulations to Control 

Greenhouse Gas Emissions from Motor Vehicles 

The Alliance of Automobile Manufacturers respectfully submits these comments on the 

proposal to adopt State regulations for the control of greenhouse gas emissions from new motor 

vehicles, starting in model year 2009.1 Our comments begin with an analysis of the framework 

established by the Legislature for this rulemaking. This includes a review of the unique criteria 

that the statute requires ARB to use in deciding whether and, if so, how to establish specific 

control limits for greenhouse gases. (See pp. 2-17 below.) 

 Our comments next examine the technology analysis and compliance strategies 

presented in the August 2004 staff report and later documents released by the Executive Officer, 

and summarize several independent studies prepared since August to analyze the technical and 

economic aspects of the staff report. (See pp. 17-25 below.) The comments then briefly 

addresses the impact of the proposed rules on the environment and on vehicle safety, which are 

examined in detail in other parts of the Alliance’s comments. (See pp. 25-31 below.) We next 

outline the options presented by the current rulemaking record for the Board, and outline 

alternatives to the action proposed by the Executive Officer that warrant consideration. (See pp. 

31-39 below.) In addition, we comment to the extent possible on the document placed on the 

 

1 The members of the Alliance of Automobile Manufacturers (“the Alliance”) are BMW Group 

of North America, Inc., DaimlerChrysler Corporation, Ford Motor Company, General Motors 

Corporation, Mazda North American Operations, Mitsubishi Motor Sales of America, Inc., 

Porsche Cars North America, Inc., Toyota Motor North America, Inc., and Volkswagen of 

America, Inc. 
 2 

ARB web-site yesterday, reporting on various extramural reviews of the ARB staff’s analysis. 

(See pp. 13-17, 20, 25-29, 31, 37-38 below.) 

 Separate documents included with these comments evaluate many of the specific 

economic, environmental, safety and legal issues raised by the current rulemaking. The Alliance 

requests a detailed response by the Executive Officer to each of the issues and all the evidence 

and analysis contained in the attached comments, as well as comments being filed by our 

members and other participants in this rulemaking. 

I. The Analytical Framework for the Current Rulemaking 

This rulemaking results from passage of Assembly Bill 1493 (“A.B. 1493”) by the 

California Legislature in the summer of 2002. The purpose of A.B. 1493 was to require ARB to 

consider adoption of rules that would provide the “maximum feasible and cost effective 

reduction of greenhouse gas emissions from motor vehicles,” consistent with federal law and 

subject to specified other limitations.2 

 It is important at the outset to establish the analytical process that A.B. 1493 establishes 

for this rulemaking. Among other steps, the statute appears to require the Board to consider 

whether any vehicular greenhouse gas regulation would be “cost-effective” for vehicle owners or 

operators. Assuming that the Board determines that such a cost-effective regulation exists, and 

can be implemented given the test for “feasibility” in A.B. 1493, ARB then needs to compare the 

“maximum feasible and cost effective” requirement for California with federal regulations. 

 

2 Health & Safety Code § 43018.5(a). See id. § 43013(a) (authorizing vehicle emissions rules 

“unless preempted by federal law”) and Cal. Stats. 2002, c.200 (A.B. 1493 -- Pavley) § 1(h) 

(requiring that ARB’s greenhouse gas rulemaking authority conform to “any limitations that may 

be imposed pursuant to the federal Clean Air Act ... and the waiver provisions of the federal act”) 
 3 

Specifically, the statute directs the Board to consider whether for any particular greenhouse gas, 

“the federal government [has] adopt[ed] a standard ... in substantially the same timeframe, and of 

equivalent or greater effectiveness as the regulations that would be adopted” under A.B. 1493. If 

such a federal standard exists, A.B. 1493 requires no separate California regulation.3 

 The rulemaking process envisioned by A.B. 1493 is thus a two-step process: it begins 

with a determination of the “maximum feasible and cost effective” regulation within California, 

but then also requires an evaluation of the effectiveness of separate California rules within a 

national context. Consideration of related federal programs is critical, both because the 

Legislature required it and because proposals to control greenhouse gases from motor vehicles 

generally focus on the control of carbon dioxide (“CO2”). Controls on CO2 emissions from 

motor vehicles when measured on a per-mile basis are functionally the same as motor vehicle 

fuel economy standards. Motor vehicle fuel economy is currently regulated in California and 

nationwide by the National Highway Traffic Safety Administration (“NHTSA”), under a federal 

statute that also establishes controls at the “maximum feasible” levels.4 

 The August 2004 staff report reflects great effort to analyze the technologies that could 

be used to control greenhouse gas emissions. But the staff report fails to consider how the rules 

it proposes would fit into the federal regulatory program. Indeed, the Executive Officer’s 

rulemaking notice does not acknowledge the existence of any related federal regulations. The 

legal significance of that omission is considered in Appendix H to these comments. Below in this 

 

3 Health & Safety Code § 43018.5(h). 

4 See Appendix H to these comments and the accompanying Declaration of S. Kingsley 

Macomber. 
 4 

section of these comments, we examine how the staff report approached the first step in the 

rulemaking process, which is the determination of what rules would be “cost-effective” and 

therefore worthy of further consideration. 

A. The General Role of “Cost Effectiveness” Analysis in the Greenhouse Gas 

Rulemaking 

As noted above, A.B. 1493 requires ARB to consider establishing a regulation that it 

would find to be “cost effective.” Normally, the Board attempts to determine the costeffectiveness of a regulation by estimating the costs of the rule and then quantifying the level of 

environmental protection that the rule will achieve, along with the rule’s other positive and 

negative effects.5 That approach is intended to establish a rule having an appropriate level of 

stringency. 

 The typical approach to standard-setting for mobile-source regulations cannot be applied 

in the current rulemaking. The greenhouse gases identified for possible control in A.B. 1493 

have not been identified by California or the federal government as criteria pollutants or 

precursor emissions. While climate change is a matter of local, national and international 

interest, there are no health-based criteria for greenhouse gases that can be used to determine an 

appropriate level of stringency in controls on various sources in California, such as automobiles 

and trucks. 

 

5 The conventional method of cost-effectiveness analysis is described in Cal-EPA’s December 

1996 memorandum entitled, “Economic Analysis Requirements for the Adoption of 

Administrative Regulations.” The Cal-EPA memorandum is available on the ARB web-site at 

www.arb.ca.gov/research/econprog/econmemo.txt. 
 5 

 There is another salient difference between this rulemaking and other ARB rulemakings 

involving mobile sources. In contrast to measures that apply to criteria or precursor pollutants, 

it is unlikely that California could impose a control measure for greenhouse gases that would 

actually achieve significant reductions of the emissions of concern (in this case, greenhouse 

gases) in the California biosphere.6 Two factors account for this. First, the growth in 

greenhouse gas emissions in other parts of the world would more than offset any reductions from 

CO2 from vehicles in California that has been estimated by the ARB staff. That is a reality that 

the August 6 staff report for this rulemaking appears to recognize. 

 Second, the national program for fuel economy regulation, combined with the economics 

of the automobile industry, make it very unlikely that a greenhouse gas rule like that proposed 

here would reduce greenhouse gases from the overall United States transportation sector. 

Compliance with the federal average fuel economy standards is based on national sales-weighted 

averages of a manufacturer’s production of passenger cars and trucks up to a specified weight. 

Even if California could mandate specific reductions in CO2 emissions and fuel consumption by 

California vehicles, the State could not directly constrain manufacturers from selling greater 

numbers of vehicles with higher levels of CO2 emissions outside California. Absent a 

regulation, no prudent manufacturer will attempt to force customers to buy hardware of any 

type, including hardware needed to control greenhouse gases, if the costs of the hardware are not 

fully valued in the market. If the costs of the California regulation are high compared to the 

estimated customer benefits, and if manufacturers follow a strategy that minimizes the impact on 

 

6 See Appendix B, Attachment B-5. 
 6 

the market, the amount of gasoline consumed nationwide -- and the level of CO2 in the 

atmosphere over California -- will not significantly change.7 

 As explained below and in separate materials being filed with these comments, it is clear 

that in order to remain competitive, the industry would use the fuel economy gains required by 

the proposed rules to permit the sale of more fuel-intensive vehicles elsewhere in the United 

States.8 The practical result will be no significant impact on the atmospheric concentrations of 

carbon dioxide believed to contribute to global climate change. The Board’s review of the 

evidence should confirm this point, and it should be expressed in ARB’s report to the Legislature 

on this rulemaking.9 It is difficult to see how a rule can be “cost effective” if it will have no 

effectiveness in the real world. 

 

7 California-specific fuel economy or CO2 regulations will lead to national reductions in CO2 

only if the California standards are so stringent that they generate more credit than manufacturers 

can use to satisfy demand for fuel-intensive vehicles in the market outside of California. ARB 

staff’s analysis raises a different possibility, which is that the vehicle technologies discussed in 

the staff report may be deployed nationwide. That scenario rests on an analysis of the costs and 

fuel savings from specific technologies that are examined in Appendix C to these comments, 

which is summarized below at pp. 17-23. 

8 Certainly, there is no general demand in the market for the types of greenhouse gas controls 

envisioned by the proposed rules, nor is such a demand likely under any plausible estimate of 

future gasoline prices. Even at gasoline prices in the $4.00 to $5.00 per gallon range, fuel 

economy levels in Europe fall short of the ARB staff’s proposed mid-term requirements for 

passenger cars. 

9 Based on their comments in the document released to the public on the ARB web-site 

yesterday, the lack of any connection between the proposed rules and the global-climate 

conditions of concern to the Legislature in A.B.1493 appears to be understood by ARB’s 

extramural reviewers, a position shared by the Alliance. If the Board finds that adoption of the 

proposed rules would have more than symbolic impact in mitigating global climate change, it 

presumably could and should make specific findings that demonstrate and quantify the effects of 

the rules using some appropriate metric, such as concentrations of greenhouse gases in the 

California biosphere or globally, net changes in energy flux, reduced pollution levels, or 

(Continued...) 
 7 

 Perhaps because they recognized that no standards that California could establish would 

meet any conventional test of cost-effectiveness, the framers of A.B. 1493 established a special 

test for cost-effectiveness to be used in determining what standards to consider under A.B. 1493. 

Under that special test, a rule can be considered “cost effective” if it is found to be “[e]conomical 

to an owner or operator of a vehicle, taking into account the full life-cycle costs of a vehicle.”10 

As one participant at the July 7, 2004 public meeting to discuss the proposed rules indicated, the 

statutory criterion to be used in setting CO2 standards is thus more an economic test than an 

environmental test.11 

 Much of the staff report is devoted to an analysis of various combinations of control 

systems in order to determine which combinations would pay for themselves over the life of the 

vehicle. As explained in the next sections of these comments, however, the staff report’s 

approach has two major shortcomings, when considered within the statutory framework. First, 

the staff report’s cost analysis fails to consider all the relevant costs of the proposed regulations 

from the perspective of the vehicle purchaser. Second, the staff report makes unrealistic 

assumptions about the value that a typical vehicle purchaser would place on future gasoline 

savings. 

 

economic benefits from reducing the need for adaptation to possible global warming. The 

August 2004 staff report contains no such demonstration or quantification; if any is developed, 

the Board should permit adequate time for public review and comment before it decides to act on 

the currently proposed rules. 

10 Health & Safety Code § 43018.5(i)(2)(B). 

11 The Alliance has included a copy of an electronic audio recording of the July 7 public meeting 

that it obtained from ARB in Appendix I of these comments, which also contain a number of 

electronic files related to other Appendices. 
 8 

B. Total Costs of the Proposed Regulation for the Consumer 

 The economic analysis in the August 2004 staff report and its supporting materials 

assume that the major cost that would be incurred by a consumer who purchases a vehicle 

certified to the proposed CO2 requirements would be the cost of the hardware needed to meet 

those requirements. The staff ignores opportunity costs, which are important in mainstream 

economic analysis of measures like that proposed in this rulemaking. The total costs of a rule 

like that proposed in the staff report include, for example, the value of the foregone opportunity 

to purchase a vehicle which may be less fuel-efficient but has other features that a consumer 

desires more than enhanced fuel efficiency. Such features obviously include vehicle 

performance, safety, capacity, comfort and aesthetics. 

 The leading studies all consider these costs, unlike the staff report. The relevant studies 

come from many quarters, including work funded by ARB but not considered in the August 2004 

staff report.12 Several recent studies in this area not already in the rulemaking file are 

summarized below. 

 Congressional Budget Office. A recent study of the federal fuel economy standards by 

the nonpartisan Congressional Budget Office (“the CBO”) identifies two types of costs that must 

be compared with fuel economy savings flowing from a mandated increase in fuel economy 

levels. These are (1) the “higher prices paid by purchasers of new vehicles and [(2)] a loss in the 

well-being of consumers who would be discouraged from buying a new vehicle because of the 

higher prices.” Applying estimates of the engineering or hardware costs and fuel savings that 

 

12 See note 17 below (studies funded by ARB). 
 9 

were assumed in the National Research Council’s study of fuel economy standards, the CBO 

found that a proposal to increase the nation’s fuel economy standards by 3.8 miles per gallon for 

both cars and light trucks over the next 14 years (far short of the proposal before the Board) 

would cost the nation’s consumers some $2.4 billion per year, or $153 per vehicle and 33 cents 

per gallon of fuel conserved.13 

 Portney, Parry, Gruenspecht and Harrington. In a recent survey article, the former Chair 

of the National Research Council (NRC) and several co-authors examine the issue of consumer 

costs as it should be examined, by including the opportunity costs of not using fuel saving 

technologies for other vehicle enhancements that consumers would prefer over increased fuel 

economy. Those opportunity costs include the value of the improved performance, increased 

weight and carrying capacity and other vehicle attributes that a consumer must forego when she 

purchases or operates a vehicle designed to meet a regulatory fuel economy target that is higher 

than what she would choose for herself. The authors of the survey article conclude that those 

opportunity costs must be compared with the fuel economy savings achieved by fuel economy 

 

13 Congressional Budget Office, “The Economic Costs of Fuel Economy Standards Versus a 

Gasoline Tax,” (December 2003), Chapter 2, pages 1 to 5. These cost estimates are net of CBO’s 

estimates of the value of reduced fuel consumption associated with such a mandate. The 

3.8 mpg increase that CBO models is off a base of 27.5 mpg for cars and 21.7 mpg for light 

trucks. CBO notes that the costs would be somewhat lower if a program of CAFE credit trading 

is adopted. However, CBO also notes that the costs could be substantially higher if it had 

estimated the adverse impacts of CAFE regulations on labor and capital markets. Id., Chapter 3, 

pages 3 to 5. The 33 cents per gallon is “the marginal cost of reaching the benchmark target (that 

is, the cost of saving the ‘final’ gallon of gasoline” and it ignores “the external costs resulting 

from the increase in driving.” (Note 8, page 11) See also National Research Council, 

“Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards,” 

Washington D.C. National Academy Press (2002). 
 10 

standards.14 The survey concludes that the costs of any further regulation of fuel economy, when 

fully considered to comprehend consumers’ opportunity costs, are likely to “significantly” 

exceed any benefits associated with reduced fuel consumption. Addressing the specific issue 

presented by the approach taken by the ARB staff in this rulemaking, the authors of the survey 

article state: 

“Engineering studies alone may give a very unreliable guide to the actual costs of 

mandated increases in fuel economy. They may not capture many important costs 

of actually implementing a new technology . . . Moreover, auto manufacturers 

have for the past several decades devoted their technological skills principally to 

the introduction of technologies that improve vehicle performance (like 

acceleration and towing capacity) rather than fuel economy; therefore, the real 

cost of devoting technology to improving fuel economy is the foregone 

performance enhancements that might have resulted. . . . When we account for the 

existing taxes on gasoline and the likelihood of a rebound effect, it appears that 

tightening CAFE could significantly reduce social welfare overall.” 

 

14 Portney and his colleagues write: 

“[E]ngineering studies [may] underestimate the true economic costs of actually 

adopting fuel-saving technologies. The true economic cost is probably larger than 

... engineering cost estimates ... for two reasons. First, it ignores the possible 

opportunity cost of not using fuel saving technologies for other vehicle 

enhancements. That is, by forcing automakers to apply their technical expertise to 

more fuel-efficient engines, tighter [fuel economy] standards could mean fewer of 

the improvements to which consumers have responded enthusiastically in the 

past—including such things as enhanced acceleration, towing capacity and so on. 

It is the implicit values of these foregone improvements that ought to be 

compared with the fuel economy savings that tighter [fuel economy] standards 

would bring. A second point is that engineering studies may exclude various 

costs of actually implementing a new technology that are difficult to observe—for 

example, marketing, consumer unfamiliarity and retraining of mechanics.”

Portney et al., Comment, in Journal of Economic Perspectives, vol. 18 at 273, 274 (Spring 

2004). 
 11 

Paul Portney, Ian W. H. Parry, Howard K. Gruenspecht and Winston Harrington, “The 

Economics of Fuel Economy Standards,” Journal of Economic Perspectives (Fall 2003), pages 

209, 212 (emphasis added).

 Kleit, Lutter, and Kravitz. The same basic points about the economics of vehicle 

regulation involving fuel consumption and fuel economy are mirrored by two other recent 

studies. Andrew Kleit, at the time a member of the faculty of The Pennsylvania State University, 

found that a “long-range” CAFE increase of 3 miles per gallon for both cars and light trucks 

would impose consumer and producer welfare losses summing to about $4 billion per year, for a 

“hidden tax” of $0.78 per gallon of fuel conserved.15 Randall Lutter of the American Enterprise 

Institute and Troy Kravitz of the Brookings Institution found that “mandatory fuel economy 

standards cannot benefit informed consumers” and “that there is little reason to believe that 

consumers systematically underestimate the price of gasoline.” Lutter and Kravitz also note that 

engineering-based estimates overstate the net benefits of fuel economy standards because they 

“exclude the foregone value to the consumer of the declines in performance associated with 

better fuel economy.”16

 The studies summarized above are the work of leading analysts in the field of 

environmental regulation. They establish the importance of estimating consumer welfare losses 

 

15 Andrew N. Kleit, “Impacts of Long-Range Increases in the Fuel Economy (CAFE) Standard,” 

Economic Inquiry (April 2004), pages 279-294. 

16 Randall Lutter and Troy Kravitz, “Do Regulations Requiring Light Trucks To Be more Fuel 

Efficient Make Sense? An Evaluation of NHTSA’s Proposed Standards,” AEI-Brookings Joint 

Center for Regulatory Studies, Regulatory Analysis 03-2, (February 2003), pages 6, 7, and 10. 
 12 

when assessing the costs of regulations related to fuel consumption. 17 Nothing in the text of 

A.B. 1493 permits the Board to ignore any category of costs. The statute’s requirement to 

consider what is “economical” to the consumer must be understood as a mandate to consider all

relevant costs to the consumer, not just the costs of additional hardware.18 Consumers who buy 

 

17 There can be no serious question that welfare losses can be quantified. A draft paper by 

Kenneth Small and Kurt Van Dender of the University of California (Irvine) dated March 11, 

2004, develops estimates of the “tightness of CAFE regulation starting in 1978,” which indicates 

that the national standards “have been binding since their introduction,” and calculates a gap 

between “[d]esired and mandated fuel efficiency for new passenger vehicles.” See Small et al., 

“The Effect of Improved Fuel Efficiency on Vehicle Miles Traveled and on Carbon dioxide 

Emissions” Estimating the Rebound Effect using U.S. State Date, 1966-2001 -- Second Interim 

Report to the California Air Resources Board and the California Energy Commission” at 12, 20 -

21. Presumably such a gap can be used to help measure the welfare loss when consumers are 

forced to buy fuel economy attributes they would not otherwise purchase. In addition, a draft 

paper prepared for by researchers at the Institute for Transportation Studies, reviewed in 

Appendix G of these comments, notes that historically, there was “market resistance to 

downsizing” by purchasers of cars produced by U.S.-based manufacturers. Burke et al. “The 

Response of the Auto Industry and Consumers to Changes in the Exhaust Emission and Fuel 

Economy Standards (1975-2003): A Historical Review of Changes in Technology, Prices, and 

Sales of Various Classes of Vehicles (March 2004). The ITS paper sponsored by ARB thus 

recognizes consumer welfare losses from fuel economy standards. (Although it recently 

commissioned both these studies, ARB decided not to place them in the rulemaking file.) See 

also Kleit, “Impacts of Long-Range Increases in the Corporate Average Fuel Economy 

Standards,” AEI-Brookings Joint Center for Regulatory Studies Working Paper 02-10 (2002) 

(current federal CAFE standards set targets above consumer demand for fuel economy by about 

1.5 miles per gallon) and Appendix G to these comments. 

18 For example, the statute does not say that the Board is supposed merely to sum up the 

estimated fuel consumption savings that a proposed standard will achieve, and then compare 

them with the costs of the technologies and other steps needed to obtain those savings. If that is 

how the Board intends to construe the statute, it should explain why it is making that choice, and 

why it is not giving consideration to mainstream economic analysis of what is “economical” for 

participants in the new-vehicle market. It is also important to note that the statute requires that 

the Board’s report to the Legislature consider economic impacts. See Health & Safety Code 

§ 43018.5(g)(2). The opportunity costs and welfare losses imposed by the regulation would 

certainly be part of the “economic ... impact[] ... on the state.” It would be implausible for A.B. 

1493 to require a report on economic impact, but permit ARB to ignore that impact in 

determining what standards to consider. 
 13 

a vehicle, but who are forced to purchase technology or other features added or subtracted from 

the vehicle to meet standards that they would not otherwise prefer, incur costs that are real and 

quantifiable, as demonstrated by the literature reviewed above.19 In view of the staff report’s 

failure to consider all the relevant types of costs of the proposed regulation to vehicle purchasers, 

the Board lacks sufficient analysis, and the public has not been properly advised of the total 

estimated costs of the proposed rule. On such a record ARB cannot adopt the proposed rule. 

C. Valuation of Future Cost Savings from Reduced Gasoline Consumption 

 One premise of the staff report is that future savings from reduced gasoline consumption 

will exceed up-front costs to the purchaser of a new vehicle. Of course, a dollar today is worth 

more than a dollar three, five or ten years hence. Within the limited economic analysis contained 

in the staff report, it is critical to apply a realistic estimate of the value of future fuel economy 

savings for today’s vehicle purchaser. While the use of such a realistic valuation would not save 

the overall analysis from the problems of omitting total costs noted above, the failure to use 

realistic estimates for the value of future savings would, standing alone, make the economic 

analysis unreliable. Here as well, the approach taken in the August 2004 staff report does not 

reflect mainstream economic analysis. This is underscored in the extramural review document 

added to the ARB web-site yesterday.20 

 

19 For example, vehicles that are down-weighted or that have less capacity or comfort, or that 

have lower towing capacity or performance, would have less value for many consumers than 

vehicles that do not have those reduced features or lower weight. That diminished value is not 

captured in the type of cost assessment contained in the staff report, but it is a real cost 

nonetheless. 

20 See “Peer Review Comments and Responses” (Sept. 2004) (hereafter “Sept. 22 Document”) at 

71-75. 
 14 

 The staff report attempts to address the issue of consumers’ valuation of future fuel 

economy savings by assigning a type of private discount rate to the reduced operating costs it 

attributes to the technologies it identifies. The discount rate assumed in the staff report, which is 

five percent, has no support in any independent empirical analysis. ARB’s designated external 

reviewer considers this issue to be “key” to the economic analysis in the staff report and 

recommends that it be re-examined.21 The peer-reviewed literature -- some of which the Board’s 

external reviewer considered, but all of which the staff documents ignore -- indicates that the 

private discount rate applied in the market for personal-use vehicles is far above five percent. 

One of the most detailed empirical studies indicates that “only 35 percent of the present-value 

cost savings provided by improved energy efficiency is capitalized in the purchase price of 

vehicles.”22 The rate used in some of the fuel economy benefit calculations in the National 

Research Council study published in 2002, which was 12%, is more than twice that used in 

August 6 staff report.23 Those key studies are ignored in the staff report, which refers only to 

 

21 See Sept. 22 Document at 71. In addition, the external reviewer concurs with the Alliance 

declarant on the importance of differences in loan rates for new and used vehicles, which is 

completely ignored in the staff’s analysis. See Declaration of Steven P. Douglas ¶¶ 14-17. 

22 Howarth, “Fuel Economy Standards,” in Journal of Economic Perspectives, vol. 18 at 272 

(2004), describing Dreyfus et al., “Rates of Time Preference and Consumer Valuations of 

Automobile Safety and Fuel Efficiency,” Journal of Law & Economics, vol. 38, at 79-105 

(1995). According to Prof. Howarth, Dreyfus and Viscusi calculate implicit discount rates for 

safety and fuel economy attributes that range from 11 to 17 percent. 

23 National Research Council, “Effectiveness and Impact of Corporate Average Fuel Economy 

(CAFE) Standards,” Washington D.C.” National Academy Press (2002) at 66. The NRC notes 

that its calculations and their results “are not recommended fuel economy goals.” Id. (emphasis 

in original). 
 15 

undocumented “trends” concerning automobile interest loan rates that conflict with the real 

evidence in the marketplace.24 

 In addition, the staff report does not take proper account of the fact that very few 

individuals who purchase a new vehicle plan to retain it for the vehicle’s full service life. For 

example, the staff report suggests that a new-vehicle owner who obtained financing would find 

the cost of interest and principal for the additional technology required by the proposed rule 

would be far less than her monthly “decreases in operating costs.”25 But that is not how a 

rational consumer would value future fuel savings. Particularly in the used-vehicle market, 

“many automobile purchasers are liquidity constrained, and therefore face implicit discount rates 

higher than the market level.”26 This has consequences not just for someone buying a used 

vehicle, but for the purchaser of a new vehicle who does not plan to keep the vehicle for its full 

service life. Assuming she considers loan rates in valuing future fuel savings, the new-vehicle 

purchaser will not apply the relatively low loan rate that she can command for the new vehicle 

when valuing the entire future stream of fuel economy savings that a vehicle will provide. In the 

used vehicle market, the value of future fuel economy savings will be discounted at higher rates 

 

24 The staff report’s reference to “historical trends” and a “ten-year averages of automobile 

interest rate and the general inflation rate” (Staff Report at 100) cites no sources, and is 

contradicted by the facts. Yet, as one of ARB’s external reviewers’ has noted, “real interest rates 

over the past few years have been at historic lows.” See Sept. 22 Document at 72. An Alliance 

member with a large vehicle finance business reports an average difference of more than one full 

percentage point between new- and used-vehicle loan rates for non-commercial customers; the 

new-vehicle rate has averaged about eight percent and the used vehicle rate has averaged above 

9.5 percent. See Douglas Declaration ¶ 17. 

25 See Staff Report at v. 

26 Kleit et al., “Increasing CAFE Standards; Still a Very Bad Idea” at 4 (Brookings, June 2004). 
 16 

than in the new-vehicle market, due to the liquidity constraints recognized in the literature and 

greater uncertainty about the value of the collateral. 

 There is an even more basic empirical problem with the discount rate applied by the ARB 

staff’s analysis in what appears to be that analysis’ version of the new-vehicle (i.e., first retail 

sale) market. Suppose, for example, that a new vehicle purchaser does plan to keep her vehicle 

for its full service life (which very few new vehicle purchasers do). As the ARB staff’s analysis 

apparently recognizes, a discount rate is essentially the opportunity cost of capital. A five 

percent discount rate implies that the average new car buyer is willing to spend or borrow money 

in order to obtain a five percent return over time. Current unsubsidized new car loan real interest 

rates in the non-commercial market are in the range of eight percent. Even if consumers valued 

fuel economy savings over the full service life assumed by the ARB staff’s analysis, no rational 

consumer would borrow money at eight percent in order to obtain a return on investment of five 

percent.27 Indeed, the five percent rate is not consistent with other discount rates used by ARB 

staff in other recent rulemaking in which it was necessary to select a discount rate, and its 

realism has been questioned in ARB’s extramural review of the staff report.28 In the extramural 

review document, one reviewer properly recognizes this as a “crucial consideration,” and the 

ARB staff agrees with him that “real interest rates will be higher over the next 5-10 years than 

 

27 If the ARB analysis is based on a study of the loan or discount rates that actually obtain in the 

retail new-vehicle market in California, and that are anticipated in the future, it should have been 

included in the staff publications. Absent such a study, the only evidence available to ARB on 

this point is the evidence that is supported by the accompanying Declaration of Steven P. 

Douglas. 

28 See Sept. 22 Document at 72. 
 17 

they were over the past 5-10 years.”29 A discount rate that is too low will, in an analysis like 

that performed in the staff report, overstate the benefits of future fuel savings; that is why 

selection of discount rates is “crucial.” The Board cannot adopt a rule based on a costeffectiveness assessment when a “crucial” input like the discount rate has been conceded by the 

ARB staff to be incorrect. 

 If it considers the use of loan discount rates to be an appropriate method for estimating 

cost-effectiveness, the Board should direct the staff to identify a range of realistic discount rates, 

based on the published literature or some other sources that can be fully examined by the public, 

and then should invite public comment on the new staff analysis. Only at that point would it be 

appropriate for ARB to attempt to determine what levels of control might be appropriate, based 

on the value of future cost savings to the consumer. 

II. Technical and Economic Analysis of the Proposed Regulations 

 In addition to seeking a more systematic analysis of the cost-effectiveness of the 

proposed rules consistent with Part I of these comments, the Alliance also recommends that ARB 

examine carefully the estimates for the costs of producing and selling vehicles that meet the 

proposed standards contained in the staff report, along with the specific fuel economy benefits 

estimated in the staff report. A realistic assessment of those engineering issues is also critical in 

determining whether the proposed standards will be cost-effective for the consumer, as well as in 

assessing the broader economic impacts of the proposed rules. 

 

29 See Sept. 22 Document at 71, 75. 
 18 

 A detailed examination of the engineering cost and benefit analysis contained in the 

August 6 staff report appears in Appendix C of these comments. In this section of our 

comments, we briefly review the main conclusions in Appendix C, and then provide an 

assessment of how the industry might attempt to comply with the proposed rules. 

A. Engineering Cost and Benefit Assessment 

 As explained in detail in Appendix C to these comments, the staff report has substantially 

underestimated the costs of the technologies it examines, and has substantially overestimated the 

theoretical operating cost savings associated with the proposed regulation. When the 

shortcomings in the staff analysis are corrected, the costs of the regulations for the average 

consumer, and indeed for nearly any Californian, will be more than double the potential fuel 

economy savings that the requisite technologies could provide. In the report contained in 

Appendix C, Sierra Research, Inc. (“Sierra Research”) draws these conclusions, after stating a 

number of important assumptions detailed in the report: 

“[T]he cost of the technology [to comply with the proposed rules] is more than 

double the net present value (“NPV”) of the gasoline savings. ... [O]ur analysis 

indicates that the proposed regulation will not come close to providing fuel 

savings that are sufficient to offset the increase in vehicle prices required to 

achieve compliance under any plausible assumptions about the typical vehicle 

ownership period in California and the value normally placed on future operating 

cost savings. The proposed rules will therefore not be cost-effective for the 

average California driver, and there is no evidence ... to indicate whether the 

proposed rules will be cost-effective for any California drivers. 

See Appendix C at 2. Some of the problems in the staff report’s analysis reviewed in Appendix 

C include the following: 

 • The price of passenger cars in the 2009 baseline case was inflated by the use of 

unrealistic assumptions about technology changes that will be made in the absence of a 

regulation. 
 19 

 • The staff report’s analysis assumes the use of regular unleaded gasoline for 

technologies that require more expensive, higher-octane gasoline; once this inconsistency is 

corrected, those technologies do not provide the assumed economic benefit. 30

 • The staff report’s vehicle cost estimates were based on an unrealistic 40% markup 

factor to vendor-supplied parts prices, which is less than half of the markup required to account 

for manufacturer costs for research, development, engineering, warranty, overhead, sales and 

marketing, profit, and dealer margin. 

 • The staff report failed to account for the integration costs of certain vendor-supplied 

components that cannot merely be added without other design changes. 

 • Cost estimates for technology changes provided by a third party, Martec, were 

arbitrarily discounted by 30% to account for “unforeseen innovations in design and 

manufacturing.” 

 • Credit was claimed for significant reductions in aerodynamic drag and rolling 

resistance despite evidence that customers will not accept such changes and despite the fact that 

customers do not routinely use original equipment replacement tires. 

 • The fuel economy benefits of automatic transmission improvements were inadvertently 

assigned to manual transmissions as well. 

 

30 This error is notable in part because the advisors for the underlying project used in the staff 

report’s analysis, affiliated with Martec Inc., cautioned against it in communications with the 

ARB engineering staff. See Douglas Decl. Exhibit D. At the July 2004 public consultation 

meeting to review the draft staff report, the ARB staff noted the high level of trust they placed on 

guidance from Martec, and so the failure to take Martec’s advice on this point is surprising. 
 20 

 • Fuel cost savings were estimated as if the federal test procedures for fuel economy 

reflect real-world consumption of fuel under actual driving conditions. That assumption is not 

supported in the record and is inconsistent with assumptions applied by ARB in other regulatory 

analyses and in emissions compliance testing.31

 • Fuel cost savings were apparently based on inflated estimates of vehicle service life, 

which may have resulted from a significant mathematical error in the analysis of odometer data 

from the State’s vehicle inspection and maintenance program. 

 Some of those same problems were identified in the extramural review document that the 

Executive Officer made available yesterday.32 The Board and the public need a specific, and 

properly documented, response to each element in the analysis of the staff report contained in 

Appendix C, with references to the data sources that support the response. If it intends to rely 

on extramural reviews, it is obviously also important that the reviewers be given current 

information. 

 As also indicated in Appendix C, there are additional and perhaps even more fundamental 

problems with the analysis of costs and benefits in the staff report. One of the most significant 

of those problems is the assumption that the technologies described in the report will be 

 

31 The federal government recognizes the difference between fuel economy as measured in the 

federal test procedures and the fuel economy actually exhibited by vehicles in normal operation, 

and applies an adjustment to the test measurements in the fuel economy estimates placed on new 

vehicle mileage labels. See Appendix C, Attachment C-2 at C2-2. 

32 See Sept. 22 Document at 6 (questioning use of driving cycles used in ARB staff’s analysis), 

20 (same). Remarkably, the ARB staff responses in the September 22 Document agree on this, 

but the staff presentation posted on ARB’s web-site yesterday does not make the necesary 

change in the staff’s benefit assessment. 
 21 

implemented nationwide, in the absence of any rule that requires such a result. If the market 

actually demanded the relevant technologies, they would be in general use today, or the industry 

as a whole would be planning to introduce them now on a full-product-line basis. There are no 

plausible future estimates for gasoline prices in this country that suggest that such a demand will 

exist, within the time horizon of this proposed regulation.33 If the technologies envisioned in 

the staff report were to be deployed mainly in the markets covered by the regulation, the 

engineering costs discussed in Appendix C would grow many-fold. 

 In addition, the ARB staff report assumes that the automotive industry has the economic 

and human resources necessary to develop and produce the technology changes outlined in the 

staff report in the time envisioned by the staff’s proposal. That assumption is not consistent with 

any evidence in the record before ARB or the independent analysis performed by Sierra 

Research, Inc., which is contained in Appendix C. As stated in Sierra Research’s analysis: 

“[The ARB staff report] assumes that the automotive industry has the economic 

and human resources necessary to develop and produce the required technology 

changes by 2016. [The staff report ] provides no support for this assumption and 

[Sierra’s] analysis indicates that vehicle design changes would need to occur at a 

rate that substantially exceeds historical practice, unless compliance is achieved 

by shifting motorists into smaller, lower performance vehicles. Information we 

received from some manufacturers indicates that compliance with the proposed 

regulations is not feasible in the absence of an increase in consumer preferences 

for such vehicles. ... Prudent engineering practice dictates that new technologies 

be phased into production in a manner that provides some manufacturing and 

customer service experience with a single car line. This allows unforeseeable 

problems to be resolved without the economic and product reputation risk 

associated with simultaneous deployment of a new technology across multiple car 

lines. However, this practice could not be followed if manufacturers are to 

 

33 Even markets overseas that face much higher gasoline prices and different consumer 

preferences have not seen 100 percent deployment of the technologies that the staff report 

envisions to be found nationwide within a relatively short period of time. See note 8 above. 
 22 

comply with the proposed regulations on a normal product development 

schedule.” 

See Appendix C at 1. Sierra Research’s observations are borne out by the experience of the 

manufacturers who have begun to deploy some of the technologies discussed in the staff report. 

For example, the automated manual transmissions and advanced valve-train systems that have 

been a particular focus of the ARB staff’s analysis have generally been first introduced in limited 

volumes on premium products after many years of development. 

In sum, the assessment of engineering costs and fuel economy savings contained in the 

staff report presents an incorrect picture of the impact the proposed rules would have on the 

average new-vehicle purchaser in California. Only the segment of the population that applies a 

very high personal value to operating cost savings -- higher than most consumers -- or that has a 

stronger than typical preference for particular vehicle designs or new technology will find the 

technology packages that the staff report presents as cost-effective to be truly “economical” for 

that consumer over the life of the vehicle. This indicates that there is a basic need for 

reconsideration of the analysis taken in the staff report to the basic issue of cost-effectiveness, as 

that term was defined by the Legislature for purposes of greenhouse gas regulation. 

B. Likely Industry Response to the Proposed Regulation 

 Because it does not have and cannot obtain access to the specific business plans of its 

members, the Alliance requested an independent “best case” analysis of how the industry as a 

whole might attempt to comply with the proposed regulation. The preliminary results of the 

analysis are presented in appendices to these comments. The basic approach taken in that 

analysis was to assume, as did the ARB staff, that various bundles of technologies, when applied 

to a hypothetical or “average” vehicle, would result in changes in both fuel consumption and 

retail prices. 
 23 

 The preliminary analysis in Appendix B had to be completed in the very short period of 

time permitted by the current hearing date. For that reason, the only corrective adjustments to 

some of the most obvious shortcomings in the staff report’s engineering cost and benefit analysis 

are those described in Appendices B and C. It bears emphasizing that neither the authors of the 

study in Appendix B nor the Alliance can represent that the response to the proposed regulation 

in Appendix B is a “compliance strategy” for the proposed rule.34 To the contrary, confidential 

submissions to Sierra Research from some members of the Alliance indicate the following: 

 • Some manufacturers deem the risk of customer resistance to some of the key 

technologies identified in the staff report to be too large to permit deployment of those 

technologies at the level assumed in the ARB staff’s analysis. 

 

34 Owing to the limited time available to prepare the analysis, Appendix B does not contain an 

assessment of how the proposed standards would affect employment or financial conditions in 

the automobile industry outside California. The impact of the proposed rules outside the State 

are likely to be severe for the companies subject to those rules and their employees. Also 

omitted from Appendix B are sensitivity analyses that would demonstrate how events beyond the 

control of California would ensure the failure of even an aggressive technology strategy in 

meeting the proposed rules. Those scenarios include significant reductions in gasoline prices, 

and customer resistance to some of the relevant technologies that the ARB staff forecasts as 

needed to meet the proposed standards, but which would degrade performance or other attributes 

to an extent not tolerated by California or other U.S. customers. The result would be an increase 

in used-vehicle sales and increased market share for companies that are not subject to the same 

requirements as those who must comply prior to model year 2016. The history of federal fuel 

economy regulation demonstrates that full-line vehicle manufacturers who have been constrained 

by the CAFE standards cannot force the market to accept the higher fuel economy vehicles that 

federal regulations have required, and as a result, the CAFE standards for some vehicles have 

required relaxation in light of market conditions. See Declaration of S. Kingsley Macomber 

(adjustment of CAFE standards when required by conditions beyond the control of 

manufacturers). The historical record does not document the adverse impact of the CAFE 

standards on consumers and on some manufacturers that could not be prevented by a timely 

adjustment of the standards. 
 24 

 • In addition, some vehicle manufacturers face capital constraints that will limit their 

ability to invest in new technology and have insufficient engineering resources to implement 

changes at the pace required by the proposed regulation. 

 • As a result, the likely response by some of the manufacturers who would be regulated 

by the proposed rules would involve the discontinuation of many products from the fleet 

regulated by the California rule -- even though that strategy (so-called “mix shifting”) is very 

costly from a business perspective. This approach will be needed because no combination of 

technologies and other vehicle changes will be sufficient to bring the relevant manufacturers into 

compliance with the regulation when fully implemented, and because sufficient credits will not 

be available to permit manufacturers in a deficit position to avoid mix-shifting. 

 • Equally important, once the proposed standards would be fully implemented, vehicle 

manufacturers will generally not attempt to sell “California” vehicles in jurisdictions where the 

proposed rules would not apply. This means that the cost analysis contained in the Sierra 

Research study understates the likely costs of vehicles meeting the new standards, because there 

will be no nationwide production economies of scale once the rules took full effect.35 

 Significantly, each of the Board’s external reviewers whose views were made available 

just prior to today’s hearing, and who commented on the compliance issues, concurs that 

strategies like mix-shifting and other approaches different from the use of new technologies must 

be considered in a complete analysis of the impacts of the proposed rules.36 Like the Alliance, 

 

35 See Declaration of Thomas C. Austin, included in Appendix C. The Alliance has received no 

confidential information from any source, including any member of the Alliance. 

36 See, e.g., Sept. 22 Document at 13, 79-80 
 25 

those reviewers were not given enough time fully to evaluate compliance strategies in a fully 

systematic way. Even given its necessary simplifications, however, the study submitted in 

Appendix B demonstrates severe adverse effects on the California economy, which warrant 

careful consideration by the Board. The main findings in the study regarding the California 

economy can be summarized as follows: 

 1. By raising vehicle ownership costs above the value of any fuel savings, the proposed 

regulations would lead to almost 100,000 fewer jobs in 2016. The cumulative effect would mean 

that by 2016, more than 300,000 person-years of employment would have been sacrificed over 

an 8-year period. (See Appendix B at 33-35.) 

 2. The California Gross Regional Product would be reduced by more than $11.6 billion 

in 2016, with a cumulative loss from 2009 to 2016 of more than $36 billion (in 2003 dollars). 

Disposable personal income losses would be similar, peaking at $7.9 billion in 2016 with a 

cumulative total of more than $25 billion by 2016. (See Appendix B at 31-32.) 

 3. Tax revenues in 2016 would be almost $1 billion less in California, with a 

cumulative loss of more than $3.2 billion from 2009 to 2016. (See Appendix B at 36.) 

 Against those negative effects of the proposed regulation should be weighed their 

environmental benefits, if any. The environmental effects of the proposed rule are outlined in 

the next section of these comments. 

III. Environmental and Other Health-Related Impacts of the Proposed Regulation 

 The August 6 staff report also includes a discussion of the environmental effects that the 

staff and its consultants attribute to the proposed regulation. As the staff report appears to 

recognize, it would be incorrect to attribute any significant reduction in global warming, or any 

other discrete impact on climate, to the implementation of the proposed rules. The best available 
 26 

evidence demonstrates that even under very optimistic assumptions about the impact of the 

proposed greenhouse gas rules in California, there would be no significant impact on the global 

or California climate. Any theoretical change in temperatures that a rule of this nature could 

produce would, in turn, have no measurable effect on ozone levels in California -- even if the 

proposed greenhouse gas rule were implemented nationwide.37 There is, in sum, no reliable 

evidence that implementation of the proposed regulation will reduce global warming or have any 

impact on ozone levels, or any other air pollution levels. If the staff believes that there is any 

such evidence, it needs to identify it and then permit public comment on the evidence before 

submitting it to the Board for consideration. As the record now stands, there is no quantification 

of any particular environmental benefit from the proposed rules, or any reasoned explanation of 

how such a benefit could be estimated. 

 This crucial point -- which is that there is no real connection between the proposed rule 

and the global climate conditions of concern to the framers of A.B. 1493 -- was apparently 

recognized by one of the ARB’s external reviewers, whose assessment was finally released 

yesterday: in the September 22 review document, he states that any impact of the proposed 

 

37 See Appendix B, Attachment B-5 . Any claim that the proposed rule would reduce ozone 

levels in California to a measurable extent is therefore “baseless.” Id. at B5-4. In a separate 

submission to the record, the Principal Scientist of Air Improvement Resource, Inc. (“AIR”), an 

air quality research firm, also addresses claims concerning climate scientific issues in the 

August 2004 staff report. AIR’s review of the evidence should be fully addressed by the 

Executive Officer, insofar as she relies to any extent on the claims concerning climate science in 

Chapter 2 of the staff report and its related documents to support the proposed regulatory action. 

One key point is that the staff report makes no credible connection, even at a qualitative level, 

between the greenhouse gas reductions attributed to this proposed rule and the environmental 

evidence reviewed in staff report. For example, there is no connection between the greenhouse 

gas reductions that are being sought in this rulemaking and daily peak temperatures, which are of 

primary importance in smog formation. See Declaration of Jon M. Heuss (AIR). 
 27 

regulation on ozone “is not quantified to any real extent” in the staff’s document. (Sept. 22 

Document at 22.) The ARB staff’s response on that point is to agree, but then to try to dismiss 

its relevance by claiming that their focus is on “the proposed regulation and the supporting 

technologies.” (Id.) That response appears to treat the issue of global climate as having no role 

in the writing of a rule intended to force technology for its own sake. 

 The Board itself should not give such little attention to the overall environmental and 

public-health risks and benefits involved in this rulemaking. Although the proposed rule by the 

staff’s own admission will have no quantified benefits in reducing global warming or smog, 

there are clear adverse environmental effects that would result from implementation of the 

proposed rule. This is largely conceded in the “Addendum” to the August 6 staff report, which 

was published on September 10, 2004 (and which apparently was not provided to ARB’s 

external reviewers). Once the staff’s estimated rebound and fleet turnover effects are included, 

the proposed rule will under the staff’s own estimates result in increases in overall smog-forming 

pollutants from the regulated vehicle fleet, as vehicles are driven more and the age of the fleet 

increases. The staff’s estimates appear in Table 12.4-1 of the September 10 Addendum, and are 

discussed in detail in Appendix B of these comments. The staff’s estimates were based on 

unrealistic estimates of the engineering costs and fuel savings benefits of the proposed rule, as 

noted above and explained in detail in Appendix C, but even those estimates show pollution 

increases. When more realistic estimates are used (estimates which still understate the total costs 

of the proposed rules), the excess smog-forming emissions in 2020 could surpass 30 tons per day 

in California, depending on the predictive models used in the analysis, as demonstrated in 

Appendix B. 
 28 

 The 2002 legislation directing ARB to consider greenhouse gas regulations did not give 

the Board any authority to adopt measures that might increase emissions of precursor or criteria 

pollutants -- a key point explained in Appendix H. Before this rulemaking can proceed further, 

it is critical for the staff to review and respond to the analytical problems in their estimates, as 

well as to address the estimates of adverse effects in the independent studies that are being filed 

in the record. The staff reviews would then require public comment, before the Board could 

consider taking any action. 

 The only method by which the proposed rule can be suggested not to have those adverse 

effects on smog-forming pollution levels is by accepting at face value the September 10 

Addendum’s claims that the proposed rules might indirectly reduce “upstream” emissions. 

Because the staff did not present those claims and their basis in its August 6 publications, it 

would be improper for the Board to accept those claims without allowing proper public review, 

in the manner outlined elsewhere in these comments.38 To the extent that those claimed indirect 

upstream emissions estimates can be understood, however, they appear to be inconsistent with 

the studies on which they are supposedly based. When partially corrected to conform with the 

prior studies, the upstream emissions benefits are minor, compared to the excess emissions from 

the vehicle fleet itself. In fact, even if the Addendum’s estimated upstream emissions benefits 

 

38 The extramural review document released yesterday indicates that one of the relevant 

documents is “now ... available for public review,” but the Alliance is not aware of when or how 

it was made available, despite diligent efforts to try to obtain it. (Sept. 22 Document at 14.) 
 29 

are taken at face value, the net effect of the proposed regulation will still be an increase in smogforming emissions.39 

 Perhaps even more importantly, the proposed rules will compromise traffic safety. This 

increased risk will result from two separate effects from the proposed rule, neither of which is 

considered in the staff’s publications. First, the rebound effect will result in increased driving, as 

explained in Appendix B of these comments.40 This will increased exposure to the risk of 

 

39 See Appendix B Attachment B-6. The Addendum projects a small net reduction in emissions 

when fleet emissions increases are combined with upstream emissions decreases. But that result 

is fragile: it depends on (1) the use of a computer model whose details have been withheld from 

public scrutiny, and (2) the use of the unrealistic cost and price estimates discussed above and in 

Appendix C of these comments. (By the ARB staff’s own admission, in the extramural review 

document finally released yesterday, the relevant computer model is in an “early stage of 

development.” See Sept. 22 Document at 77.) When one uses either a realistic set of cost 

assumptions, or the only predictive model whose full details are being put in the public record 

(i.e., the model described in Appendix B of these comments and detailed in Appendix I) the 

result is a net emissions increase. As a legal matter, when there is so much evidence of possible 

emissions increases, it is critical for the Board to conduct a much more detailed environmental 

review than the current rulemaking process and schedule allows. See also Sept. 22 Document at 

85 (external reviewer calling ARB’s consumer choice model whose details have not been 

released to the public “important” to the overall analysis). 

40 Analyses of the rebound effect in California that are contained in the staff report are 

thoroughly critiqued and corrected in several different filings in the record. Those include an 

independent analysis by NERA, a separate independent analysis by Sierra Research, and two 

additional reviews of Robert Crawford and Laurentius Marais. As the NERA reviewers 

indicate, the “ad hoc approach” taken in the rebound study for ARB on some key analytical 

issues “is not defensible.” See Appendix D at 43. The ARB external review of the staff’s 

rebound analysis was apparently not completed. Under the California Environmental Quality 

Act and the Board’s implementing regulations, the work by NERA, Crawford and Marais must 

be fully considered by the ARB staff, addressed in a written document for public review, and 

then considered by the Board, if the intent is to continue the rulemaking process. See Appendix 

H at 19-32. 
 30 

accidents, including fatal accidents and accidents involving serious injuries, which is quantified 

in a preliminary manner in Appendix F of these comments.41 

 Second, the proposed rule will result in the overall down-weighting of the California 

motor vehicle fleet in order to comply with the proposed standards, as well as weight reductions 

in some vehicles in order to reduce fuel consumption. This issue is completely ignored by the 

staff report, which simply assumes for purposes of its analysis that the fleet will not lose weight 

(while conceding that it may). If the proposed rules do not result in reduced weight and an 

increase in safety risk, they would be the first fuel-economy-related rules in history not to have 

such an effect, and the study contained in Appendix C explains why weight reductions are 

inevitable. The effects of weight reduction are “clear,” according to a report by the National 

Research Council: 

“[P]ast downweighting and downsizing of the light-duty fleet, while resulting in 

significant fuel savings, has also resulted in a safety penalty. In 1993, it would 

appear that the safety penalty included between 1,300 and 2,600 motor vehicle 

crash deaths that would not have occurred had vehicles been as large and heavy as 

in 1976.” 

National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy 

(CAFE) Standards (2002) at 28. To evaluate the related possible effect of the proposed CO2 

rules on California traffic safety, a researcher with expertise in the use of current National 

Highway Traffic Safety Administration and other predictive models performed a preliminary 

 

41 Only preliminary quantifications of the safety risks are possible at this point, given the limited 

time allowed to review the proposed rule and to prepare comments. But even that preliminary 

analysis is more than sufficient to require additional review of the issue in the manner required 

by the California Environmental Quality Act, which requires the evaluation of safety risks just as 

it does other threats to public health. See Appendix H at 24-25, 30. 
 31 

analysis that assumed some down-weighting of the California fleet to meet the proposed rules. 

The results, reported in Appendix F, suggest that the proposed rules may cause hundreds of 

additional deaths once the California fleet is fully populated by vehicles meeting the proposed 

CO2 requirements.42 Tellingly, when one of ARB’s external reviewers raised the issue of 

weight reduction with the ARB staff as one of several important issues the ARB staff needed to 

consider, the staff chose not to focus on the weight issue in its response.43

 ARB must consider all the evidence bearing on the environmental and safety risks of the 

proposed regulations before it decides what action to take. The Alliance urges the Board to 

instruct the staff to respond specifically to all the issues of environmental and safety risk raised 

in the attached reports, and to permit public review of those responses, before ARB decides 

whether to approve the Executive Officer’s recommendation. 

IV. The Board’s Options on the Current Record 

 The Alliance recognizes the tremendous level of effort that the ARB staff has expended 

to date in preparing a recommendation for the Board’s review. As our review of the record 

above indicates, however, the Alliance cannot support the proposed regulations. We urge ARB 

to consider carefully its options before committing the State to the proposed regulation. Several 

key points stand out in the record. 

 

42 See Appendix F. 

43 See Sept. 22 Document at 79-81 (reviewer notes that “manufacturers might respond” to the 

rule by “lowering motor vehicle weight;” staff responds that the “industry’s response to the 

regulations may be very different from those [sic] identified by the staff” but does not respond to 

the specific comment from the reviewer on weight reductions). 
 32 

 First, the record indicates that some supporters of the A.B. 1493 legislation may have 

developed unrealistic assumptions about the efficacy of any rule that ARB could adopt, insofar 

as the goal is actually to reduce greenhouse gases to any significant degree. The staff report 

largely agrees that action by ARB will have little or no effect on greenhouse gas levels, and it 

does not attempt to connect those minor estimated reduction to any impact on the California 

climate. Instead, the staff report attempts to develop four different reasons to proceed with the 

regulation. It states as follows: 

“Greenhouse gas emissions from California light duty vehicles are a small 

fraction of the global total.... It does not necessarily follow, however, that 

California should do nothing. Rather, there are several compelling reasons to 

move forward with the proposed regulation, even while recognizing that by itself 

it will not solve the climate change problem. First of all, the proposed regulation 

is a “no regrets” policy that addresses climate change emissions but at the same 

time provides economic benefit to the state. Second, California would not be 

acting in isolation. Other states in the United States, and other countries 

internationally, have already taken or are contemplating steps to reduce GHG 

emissions from a variety of sectors and sources. Moreover, California action 

specifically to control GHGs is strongly supported by the public.... Finally, the 

longstanding technology-forcing role of California regulation should not be 

understated. There have been many instances where other jurisdictions have 

adopted motor vehicle controls that were pioneered in California. Thus there is 

potential for the proposed regulation to spread to other jurisdictions and thereby 

add momentum to the already existing set of measures that are underway around 

the globe.” 

Staff Report at vii-viii. In light of that rationale for implementing a greenhouse gas regulation, it 

is fair to ask what evidence actually supports each justification for the rulemaking. 

Economic benefit to the State. There is no legitimate basis for the suggestion that 

additional regulation will provide economic benefit to the state. The economic impact analysis 

in the staff report ultimately rests on conjecture that any reduction in the number of vehicles sold 

by California dealers will be offset by an increase in net revenue (or profit) that will result from 

the higher prices for the technology-enhanced vehicles that the staff report predicts will enter the 
 33 

market. California new-vehicle dealers already operate in a highly competitive market, in which 

they can respond quickly to changes in consumer demand and advances in technology that will 

increase demand and revenue. The record contains no evidence to support the premise that the 

proposed regulation will somehow move in a permanent manner the market into vehicle classes 

that will produce higher dealer profits.44 On the contrary, the available evidence indicates that 

the proposed rules would create new hardships for the state’s auto dealers and other automotiverelated businesses, with no offsetting environmental benefit. 

California would not be acting alone. The staff report predicts that if ARB takes 

regulatory action, other States will follow. This is a speculative claim that suggested that the 

wisdom of adopting the proposed rules depends on the unknown future actions of other 

 

44 ARB commissioned a number of studies on the pricing issues, which are mentioned in the 

staff report and related documents, but since the publication of the 45-day notice the ARB staff 

has indicated that it is not relying on those studies to support its proposal. The studies have not 

been properly identified and placed in the record, in any event, and so it would not be proper for 

ARB to rely on them to support regulation. Some drafts of apparently similar reports provided 

informally to the Alliance are discussed in Appendix G. 

 The only sector-specific economic analysis in the August 6 staff report on which the 

proposal is apparently based is a brief review of the possible effects of the regulation in a single 

portion of the State (the San Diego area) using unsupported assumptions rather than a validated 

economic model. That review shows injury to the automotive sector. For that reason if no other, 

the Board should not approve the staff proposal because the staff report and related documents 

did not present a complete analysis of the potential impact of the proposed regulation on the 

affected business sectors in all areas of the State. This is important both as a matter of sound 

public policy and because such a statewide analysis is required both by A.B. 1493 and other 

directions from the Legislature. 

 Some of the ARB staff’s estimates rely on the CARBITS consumer choice model. 

CARBITS is, according to the ARB staff, not in the possession or subject to the control of ARB. 

For that reason its source code and its specifications have not and cannot be properly scrutinized 

by ARB or the public. The only fully documented consumer choice model in the record is the 

model prepared by Sierra Research and NERA. 
 34 

independent states. Even if other States follow California’s lead, the staff report does not claim, 

nor could it, that there would be any effect on the California biosphere. In any case, if the 

reaction of other states is to become the basis for regulatory action, the Board needs a full report 

indicating how and why action in other States would benefit the California environment or serve 

the purposes of the statute. 

Public support. The claim that the public supports the regulation of greenhouse gas 

emissions from motor vehicles appears to rest primarily on a recent public poll. The Board is 

supposed to exercise its own expertise based on a full record of all the relevant issues. Such a 

poll is not entitled to any weight in the Board’s analysis, because among other reasons the 

participants in the survey did not have full information about the specific costs and benefits of 

the proposed regulation, and also lacked an awareness of all the legal and policy constraints on 

the Board’s decision-making. It should also be noted that the survey participants presumably 

were polled before the discovery of the error in the staff report that necessitated a nearly 70 

percent increase in the estimated engineering costs of full-size trucks. Of course, the most 

significant shortcoming in the staff’s reliance upon a public poll is that the actual purchasing 

decisions by Californian’s is a far more reliable measure of the vehicles Californians desire. 

Regulatory momentum. The claim that regulation should be pursued in California 

because it might also be pursued elsewhere appears either to be circular and ultimately irrelevant 

to the Board’s evaluation of the specific proposal from the staff, or is just a restatement of the 

claim that California would not be acting alone, which is discussed above. 

 In addition, it should be clear from the record that the proposed rule will impose 

additional costs on consumers when they purchase automobiles. While the staff report greatly 

understates those costs, the fact that the regulation will impose costs is undeniable. Unlike 
 35 

regulatory costs that are imposed to improve air quality, enhance vehicle safety or promote 

recycling, however, the costs of this regulation cannot be justified by reference to any specific 

public goal, other than those listed in the preceding excerpt from the staff report and discussed 

above. As noted in other parts of the Alliance’s comments, the staff report’s examination of how 

those costs will affect the California automobile industry is limited to a study of industry impacts 

in a single portion of the state -- which hardly complies with the Legislature’s expectation that 

the Board would consider statewide economic impacts. 

 There are also significant potential adverse effects of the proposed regulation on the 

environment and public safety. In the most recent staff analysis of the impacts of the proposed 

rule on criteria and precursor pollutants, released only on September 10, the staff concedes that 

smog-forming emissions from the vehicle fleet itself will increase as a result of the proposed 

rule. The revised estimate projects a net decrease in the emissions of conern only by introducing 

a completely new, undocumented and highly questionable set of assumptions about how the 

proposed rule might affect upstream emissions, mainly related to emissions from tanker ships 

that will supposedly be reduced indirectly by the regulation. As recently as last week, the ARB 

staff had still not documented its analysis of those upstream emissions, and in particular the 

shipping-related emissions. The critical question of whether a proposed rule will increase 

regulated emissions should not be decided on an undocumented basis that has not allowed any 

member of the public an adequate opportunity for review and comment. 

 Likewise, the staff report’s conclusion that the proposed regulation will not cause a 

“rebound” effect that will increase vehicle miles traveled, local emissions from automobiles, and 
 36 

accidents and injuries rests mainly on a model prepared by researchers who madefundamental 

errors in their analysis.45 An analysis of the data that the ARB’s consultant essentially said was 

too resource-intensive -- the California Smog-Check data -- demonstrates a significant rebound 

effect, consistent with the published literature.46 In addition, once the errors in the ARB 

consultant’s model are corrected, that model itself confirms the existence of a significant 

rebound effect. 

 Perhaps most importantly of all, the staff report simply ignores, without any explanation, 

the likely effect of the proposed rule on the weight and crashworthiness of the California motor 

vehicle fleet.47 There is no evidence of any serious attempt to consult the federal, State and local 

agencies with expertise on such safety issues. The issues raised by likely vehicle weight changes 

induced by the proposed rule need to be carefully evaluated in a public process, and then 

presented to the Board, before ARB is asked to take regulatory action. 

 All the relevant issues need more study. This is underscored by the document that the 

Executive Officer apparently posted on the ARB web-site yesterday, called “Peer Review 

Comments and Responses.”48 Several features of that document, in addition to the specific 

 

45 See Appendix B, Attachment B-3. 

46 See Appendices C and D. 

47 See Appendix F. 

48 Presumably the intent, and certainly the result, of the Executive Officer’s action has been to 

provide additional information or analysis that she considers to be relevant to the merits of the 

staff’s proposal. Her action was substantially noncompliant with the California Administrative 

Procedure Act. See Gov’t Code §§ 11347.1 (requiring at least 15 days for public comment on 

“any ... study, report or other document” added to the rulemaking file) and 11347.3 (contents of 

rulemaking file must include “all” materials submitted to the agency or relied upon by the 

(Continued...) 
 37 

points it makes that are noted above, are important to note. The September 22 document states at 

the beginning that “[n]o reviewer found that ARB failed to demonstrate that a scientific portion 

of the proposed rule was based upon sound scientific knowledge, methods and practices.” (Sept. 

22 Document at ii.) The “Major Conclusions” section of the document (whose authorship is not 

disclosed) is crafted to be generally supportive of some parts of the staff analysis. But as noted 

above, in key areas, the extramural reviewers find fault with that analysis. 

 Second, the September 22 document is the work of several reviewers. The only common 

version of the staff analysis given to all of them appears to have been the June 14 draft staff 

analysis, not the “final’ version of the staff report released in August 2004. Some reviewers 

were provided with the August 2004 staff report, but all were not. None of the reviewers were 

apparently asked to comment for present purposes on the September 10 “Addendum,” which 

contained the modified engineering cost estimates. That omission is fatal to any reliance on 

significant portions of the September 22 document, if not the entire document, because ARB’s 

reviewers frequently relied on the cost estimates in the earlier documents.49 

 Third, the September 22 document is by it own admission incomplete. There is, for 

example, no treatment of the critical “rebound” issue: the relevant section of the document ends 

 

agency in a rulemaking) (emphasis added). The Alliance believes that observance of those 

provisions of the APA are particularly important here because the contents of the September 22 

document support its assessment of the staff analysis in important respects, and therefore 

adequate time should be allowed to examine the implications of the review documents. This 

cannot be done literally overnight, which is all that the current schedule appears to allow. 

49 See, e.g., Sept. 22 Document at 71-79. The reviewer does not indicate what his position 

would be if he was advised that the staff had dramatically increased the incremental cost 

estimates for vehicles subject to the new rules. The effects he surmises to be “minor” or “small” 

became much larger after the ARB staff revised their cost estimates. 
 38 

with a sentence fragment, and the note “TO BE COMPLETED.” (Sept. 22 Document at 78.) It 

would be inappropriate to place reliance on any general conclusions from the review based on an 

analysis that was incomplete overall. 

 The incompleteness and inconsistencies in the September 22 document, and our overall 

review of the record presented here and in the appendices to these comments, underscore this 

basic point: the current record does not support the action proposed by the staff report, and 

instead warrants rejection of the proposal. Approval of that proposal under the current 

circumstances would certainly deprive the public of the full and fair hearing that the public needs 

in a rulemaking of this importance. 

 Nevertheless, there are a number of other actions that ARB can properly consider, other 

than approval of the staff’s proposal. One such action, recommended by the Association of 

International Automobile Manufacturers at the July 7, 2004, public consultation meeting, was 

the use of incentive programs to encourage wide use of fuel-efficient technologies. The Alliance 

supports consideration of that alternative, provided that any regulatory program adopted by ARB 

of this nature is confined to public fleets that are directly owned by the State and operated by 

executive-department agencies. The other options that are worthy of consideration by the Board 

following a staff evaluation and proper public notice include the following: 

 • Recommendations to encourage the use of fuel efficient GF-3 or GF-4 engine oil. 

 • Sponsorship of driver education programs to promote efficient driving as outlined by 

the U.S. Environmental Protection Agency, and public education programs on the importance of 

proper vehicle maintenance to enhance fuel economy. If the public has a better understanding of 

how its driving and maintenance practices can affect operating costs, households will be able 

better to manage their vehicle operating costs. 
 39 

 • Development of a voluntary vehicle repair, retrofit and retirement program. The 

legislature specifically authorized this program as part of Carl Moyer (A.B. 923 (Firebaugh)). A 

well-designed gross-polluter repair, retrofit, and retirement program could not only improve fuel 

efficiency but also dramatically reduce gross polluting vehicle emissions. 

 Such alternatives to the proposed regulation could serve the long-run purposes of A.B. 

1493 as effectively as the proposed regulation, without the significant adverse environmental and 

economic consequences of the current proposal. 

V. Conclusion 

 The Alliance supports California’s efforts to improve air quality and to enhance 

consumer value. The rule proposed by the ARB staff would not serve those objectives, and 

would require consumers to pay more than the residents of other States, with no environmental 

gain for the State or the nation. The Alliance urges the Board to disapprove the proposed rule 

and to direct the staff to undertake further analysis, with the goal of developing one or more 

alternative proposals that avoid the problems discussed above and in other comments being 

submitted to ARB. 

 Respectfully submitted,s 

 ALLIANCE OF AUTOMOBILE MANUFACTURERS 






Debbie Rabin - Clean Cars Regulations Page 1

From: "Betsy Johnson" <betsy_johnson@comcast.net>

To: <drabin@mde.state.md.us>

Date: 9/30/07 4:03PM

Subject: Clean Cars Regulations

I'm writing to urge MDE not to make any changes to the Clean Cars

regulations as currently proposed. 

With transportation causing 30% or more of global warming emissions it's

imperative that we take strong action now. We're relying on this

administration to do the right thing on this issue..

Thanks.

Betsy Johnson

MD Sierra Club


Debbie Rabin - Cleans Cars regulations Page 1

From: dave o'leary <daveol@earthlink.net>

To: <drabin@mde.state.md.us>

Date: 10/2/07 5:23PM

Subject: Cleans Cars regulations

Hello,

I am writing to encourage that the proposed Clean Cars regulations

be implemented as proposed. Thank you.

David O'Leary

Maryland Chapter, Sierra Club

CC: <dave.oleary@mdsierra.org>
Debbie Rabin - Clean Cars Act Regulations Page 1

From: David/Cindy Hackett <hackett_hale@yahoo.com>

To: <drabin@mde.state.md.us>

Date: 9/29/07 6:11PM

Subject: Clean Cars Act Regulations

Dear Mr. Secretary

It is vital to m, my family and to MD that the

Clean Cars Act regulations published in draft for

puoblic comment be implemented as published;

without changes. My family needs clenaer air and

more fuel efficient vehicles. Hold the line

against the endless industry foot dragging

resisting pollution control, carbon emissions

reduction and better fuel efficiency.

Thanks for all you do to make our energy sector

cleaner and more efficient. I look foward to

actions requiring and providing financial

incentives for very rapid development of

renewable energy sources for Maryland.

David Hackett

1303 Redwood Ave

Annapolis, MD 21403

 

___________________________________________________________________________________

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Debbie Rabin - Page 1

From: <joeadams@comcast.net>

To: <drabin@mde.state.md.us>

Date: 9/30/07 9:51PM

re: Clean Cars Act regulations

To Whom it may concern, 

This is a note from a concerned citizen asking the MDE not to change anything of substance in the 

proposed regulations of the clean cars act. That is, nothing should be done that would have the effect of 

weakening the law. 

I wish the Act could have gone farther than it did. The need to limit emissions and especially to improve 

fuel efficiency is urgent. 

Please keep these crucial protections strong as the regulations are drafted. 

Sincerely, 

Joseph A. Adams, M.D., F.A.C.P.

1405 Berwick Rd.

Towson, MD 21204

home phone: 410-296-6338

cell: 410-812-1447







Debbie Rabin - Clean Cars Act supporter Page 1

From: "MaryEllen Kustin" <maryellenkustin@gmail.com>

To: <drabin@mde.state.md.us>

Date: 10/2/07 4:01PM

Subject: Clean Cars Act supporter

Hello,

I am a resident of Riverdale Park, MD but will not be able to make it to the

public hearing on the regulations to implement the Clean Cars Act this

Wednesday, Oct 3, at 10:00 at MDE. But I would like to urge MDE not to make

any changes to the regulations as proposed.

Thank you!

-Mary Ellen M. Kustin

(301) 448.2056

maryellenkustin@gmail.com






Debbie Rabin - Clean cars Page 1

From: Sue Chapelle <suechapelle@yahoo.com>

To: <drabin@mde.state.md.us>

Date: 9/29/07 3:17PM

Subject: Clean cars

Hello,

 I understand that you all will be holding

hearings next week about implementing the new clean

car regulations passed by the General Assembly. I

strongly support these measures to make our air

cleaner and healthier and to lessen our causing global

warming. Please make sure that the regualtions don't

weaken the law or allow people to get out of following

the intent of the law.

 Sincerely,

 Sue Chapelle

 Baltimore County

 

___________________________________________________________________________________

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