The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light Trucks

Federal RegisterAug 24, 2018

Ask Donna

What actually matters in this document.

Text

DEPARTMENT OF TRANSPORTATION

National Highway Traffic Safety Administration

49 CFR Parts 523, 531, 533, 536, and 537

ENVIRONMENTAL PROTECTION AGENCY

40 CFR Parts 85 and 86

[NHTSA-2018-0067; EPA-HQ-OAR-2018-0283; FRL-9981-74-OAR]

RIN 2127-AL76; RIN 2060-AU09

The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light Trucks

AGENCY:

Environmental Protection Agency and National Highway Traffic Safety Administration.

ACTION:

Notice of proposed rulemaking.

SUMMARY:

The National Highway Traffic Safety Administration (NHTSA) and the Environmental Protection Agency (EPA) are proposing the “Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light Trucks” (SAFE Vehicles Rule). The SAFE Vehicles Rule, if finalized, would amend certain existing Corporate Average Fuel Economy (CAFE) and tailpipe carbon dioxide emissions standards for passenger cars and light trucks and establish new standards, all covering model years 2021 through 2026. More specifically, NHTSA is proposing new CAFE standards for model years 2022 through 2026 and amending its 2021 model year CAFE standards because they are no longer maximum feasible standards, and EPA is proposing to amend its carbon dioxide emissions standards for model years 2021 through 2025 because they are no longer appropriate and reasonable in addition to establishing new standards for model year 2026. The preferred alternative is to retain the model year 2020 standards (specifically, the footprint target curves for passenger cars and light trucks) for both programs through model year 2026, but comment is sought on a range of alternatives discussed throughout this document. Compared to maintaining the post-2020 standards set forth in 2012, current estimates indicate that the proposed SAFE Vehicles Rule would save over 500 billion dollars in societal costs and reduce highway fatalities by 12,700 lives (over the lifetimes of vehicles through MY 2029). U.S. fuel consumption would increase by about half a million barrels per day (2-3 percent of total daily consumption, according to the Energy Information Administration) and would impact the global climate by 3/1000th of one degree Celsius by 2100, also when compared to the standards set forth in 2012.

DATES:

Comments:

Comments are requested on or before October 23, 2018. Under the Paperwork Reduction Act, comments on the information collection provisions must be received by the Office of Management and Budget (OMB) on or before October 23, 2018. See the

SUPPLEMENTARY INFORMATION

section on “Public Participation,” below, for more information about written comments.

Public Hearings:

NHTSA and EPA will jointly hold three public hearings in Washington, DC; the Detroit, MI area; and in the Los Angeles, CA area. The agencies will announce the specific dates and addresses for each hearing location in a supplemental

Federal Register

notice. The agencies will accept oral and written comments to the rulemaking documents, and NHTSA will also accept comments to the Draft Environmental Impact Statement (DEIS) at these hearings. The hearings will start at 10 a.m. local time and continue until everyone has had a chance to speak. See the

SUPPLEMENTARY INFORMATION

section on “Public Participation,” below, for more information about the public hearings.

ADDRESSES:

You may send comments, identified by Docket No. EPA-HQ-OAR-2018-0283 and/or NHTSA-2018-0067, by any of the following methods:

•

Federal eRulemaking Portal:

http://www.regulations.gov

. Follow the instructions for sending comments.

•

Fax:

EPA:

(202) 566-9744;

NHTSA:

(202) 493-2251.

•

Mail:

○

EPA:

Environmental Protection Agency, EPA Docket Center (EPA/DC), Air and Radiation Docket, Mail Code 28221T, 1200 Pennsylvania Avenue NW, Washington, DC 20460, Attention Docket ID No. EPA-HQ-OAR-2018-0283. In addition, please mail a copy of your comments on the information collection provisions for the EPA proposal to the Office of Information and Regulatory Affairs, Office of Management and Budget (OMB), Attn: Desk Officer for EPA, 725 17th St. NW, Washington, DC 20503.

○

NHTSA:

Docket Management Facility, M-30, U.S. Department of Transportation, West Building, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue SE, Washington, DC 20590.

•

Hand Delivery:

○

EPA:

Docket Center (EPA/DC), EPA West, Room B102, 1301 Constitution Avenue NW, Washington, DC, Attention Docket ID No. EPA-HQ-OAR-2018-0283. Such deliveries are only accepted during the Docket's normal hours of operation, and special arrangements should be made for deliveries of boxed information.

○

NHTSA:

West Building, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue SE, Washington, DC 20590, between 9 a.m. and 4 p.m. Eastern Time, Monday through Friday, except Federal holidays.

Instructions:

All submissions received must include the agency name and docket number or Regulatory Information Number (RIN) for this rulemaking. All comments received will be posted without change to

http://www.regulations.gov

, including any personal information provided. For detailed instructions on sending comments and additional information on the rulemaking process, see the “Public Participation” heading of the

SUPPLEMENTARY INFORMATION

section of this document.

Docket:

For access to the dockets to read background documents or comments received, go to

http://www.regulations.gov

, and/or:

•

For EPA:

EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301 Constitution Avenue NW, Washington, DC 20460. The Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday, excluding legal holidays. The telephone number for the Public Reading Room is (202) 566-1744.

•

For NHTSA:

Docket Management Facility, M-30, U.S. Department of Transportation, West Building, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue SE, Washington, DC 20590. The Docket Management Facility is open between 9 a.m. and 4 p.m. Eastern Time, Monday through Friday, except Federal holidays.

FOR FURTHER INFORMATION CONTACT:

EPA:

Christopher Lieske, Office of Transportation and Air Quality, Assessment and Standards Division, Environmental Protection Agency, 2000 Traverwood Drive, Ann Arbor, MI 48105; telephone number: (734) 214-4584; fax number: (734) 214-4816; email address:

lieske.christopher@epa.gov

, or contact the Assessment and Standards Division, email address:

otaqpublicweb@epa.gov

NHTSA:

James Tamm, Office of Rulemaking, Fuel Economy Division, National Highway Traffic Safety Administration, 1200 New Jersey Avenue SE, Washington, DC 20590; telephone number: (202) 493-0515.

SUPPLEMENTARY INFORMATION:

I. Overview of Joint NHTSA/EPA Proposal

II. Technical Foundation for NPRM Analysis

III. Proposed CAFE and CO

Standards for MYs 2021-2026

IV. Alternative CAFE and GHG Standards Considered for MYs 2021/22-2026

V. Proposed Standards, the Agencies' Statutory Obligations, and Why the Agencies Propose To Choose Them Over the Alternatives

VI. Preemption of State and Local Laws

VII. Impacts of the Proposed CAFE and CO

Standards

VIII. Impacts of Alternative CAFE and CO

Standards Considered for MYs 2021/22-2026

IX. Vehicle Classification

X. Compliance and Enforcement

XI. Public Participation

XII. Regulatory Notices and Analyses

I. Overview of Joint NHTSA/EPA Proposal

A. Executive Summary

In this notice, the National Highway Traffic Safety Administration (NHTSA) and the Environmental Protection Agency (EPA) (collectively, “the agencies”) are proposing the “Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light Trucks” (SAFE Vehicles Rule). The proposed SAFE Vehicles Rule would set Corporate Average Fuel Economy (CAFE) and carbon dioxide (CO

) emissions standards, respectively, for passenger cars and light trucks manufactured for sale in the United States in model years (MYs) 2021 through 2026.

CAFE and CO

standards have the power to transform the vehicle fleet and affect Americans' lives in significant, if not always immediately obvious, ways. The proposed SAFE Vehicles Rule seeks to ensure that government action on these standards is appropriate, reasonable, consistent with law, consistent with current and foreseeable future economic realities, and supported by a transparent assessment of current facts and data.

NHTSA sets CAFE standards under the Energy Policy and Conservation Act of 1975 (EPCA), as amended by the Energy Independence and Security Act of 2007 (EISA). EPA sets CO

standards under the Clean Air Act (CAA).

The agencies must act to propose and finalize these standards and do not have discretion to decline to regulate. Congress requires NHTSA to set CAFE standards for each model year.

Congress also requires EPA to set emissions standards for light-duty vehicles if EPA has made an “endangerment finding” that the pollutant in question—in this case, CO

—“cause[s] or contribute[s] to air pollution which may reasonably be anticipated to endanger public health or welfare.”

NHTSA and EPA are proposing these standards concurrently because tailpipe CO

emissions standards are directly and inherently related to fuel economy standards,

and if finalized, these rules would apply concurrently to the same fleet of vehicles. By working together to develop these proposals, the agencies reduce regulatory burden on industry and improve administrative efficiency.

49 U.S.C. 32902.

42 U.S.C. 7521,

see also

74 FR 66495 (Dec. 15, 2009) (“Endangerment and Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act”).

See, e.g.,

75 FR 25324, at 25327 (May 7, 2010) (“The National Program is both needed and possible because the relationship between improving fuel economy and reducing tailpipe CO

emissions is a very direct and close one. The amount of those CO

emissions is essentially constant per gallon combusted of a given type of fuel. Thus, the more fuel efficient a vehicle is, the less fuel it burns to travel a given distance. The less fuel it burns, the less CO

it emits in traveling that distance. [citation omitted] While there are emission control technologies that reduce the pollutants (

e.g.,

carbon monoxide) produced by imperfect combustion of fuel by capturing or converting them to other compounds, there is no such technology for CO

. Further, while some of those pollutants can also be reduced by achieving a more complete combustion of fuel, doing so only increases the tailpipe emissions of CO

. Thus, there is a single pool of technologies for addressing these twin problems,

i.e.,

those that reduce fuel consumption and thereby reduce CO

emissions as well.”)

Consistent with both agencies' statutes, this proposal is entirely

de novo,

based on an entirely new analysis reflecting the best and most up-to-date information available to the agencies at the time of this rulemaking. The agencies worked together in 2012 to develop CAFE and CO

standards for MYs 2017 and beyond; in that rulemaking action, EPA set CO

standards for MYs 2017-2025, while NHTSA set final CAFE standards for MYs 2017-2021 and also put forth “augural” CAFE standards for MYs 2022-2025, consistent with EPA's CO

standards for those model years. EPA's CO

standards for MYs 2022-2025 were subject to a “mid-term evaluation,” by which EPA bound itself through regulation to re-evaluate the CO

standards for those model years and to undertake to develop new CO

standards through a regulatory process if it concluded that the previously finalized standards were no longer appropriate. EPA regulations on the mid-term evaluation process required EPA to issue a Final Determination no later than April 1, 2018 on whether the GHG standards for MY 2022-2025 light-duty vehicles remain appropriate under section 202(a) of the Clean Air Act.

The regulations also required the issuance of a draft Technical Assessment Report (TAR) by November 15, 2017, an opportunity for public comment on the draft TAR, and, before making a Final Determination, an opportunity for public comment on whether the GHG standards for MY 2022-2025 remain appropriate. In July 2016, the draft TAR was issued for public comment jointly by the EPA, NHTSA, and the California Air Resources Board (CARB).

Following the draft TAR, EPA published a Proposed Determination for public comment on December 6, 2016 and provided less than 30 days for public comments over major holidays.

EPA published the January 2017 Determination on EPA's website and

regulations.gov

finding that the MY 2022-2025 standards remained appropriate.

40 CFR 86.1818-12(h)(1)

; see also

77 FR 62624 (Oct. 15, 2012).

81 FR 49217 (Jul. 27, 2016).

81 FR 87927 (Dec. 6, 2016).

Docket item EPA-HQ-OAR-2015-0827-6270 (EPA-420-R-17-001). This conclusion generated a significant amount of public concern.

See, e.

g.,

Letter from Auto Alliance to Scott Pruitt, Administrator, Environmental Protection Agency (Feb. 21, 2017); Letter from Global Automakers to Scott Pruitt, Administrator, Environmental Protection Agency (Feb. 21, 2017).

On March 15, 2017, President Trump announced a restoration of the original mid-term review timeline. The President made clear in his remarks, “[i]f the standards threatened auto jobs, then commonsense changes” would be made in order to protect the economic viability of the U.S. automotive industry.”

In response to the President's direction, EPA announced in a March 22, 2017,

Federal Register

notice, its intention to reconsider the Final Determination of the mid-term evaluation of GHGs emissions standards for MY 2022-2025 light-duty vehicles.

The Administrator stated that EPA would coordinate its reconsideration with the rulemaking process to be undertaken by NHTSA regarding CAFE standards for cars and light trucks for the same model years.

See

https://www.whitehouse.gov/briefings-statements/remarks-president-trump-american-center-mobility-detroit-mi/

82 FR 14671 (Mar. 22, 2017).

On August 21, 2017, EPA published a notice in the

Federal Register

announcing the opening of a 45-day public comment period and inviting stakeholders to submit any additional comments, data, and information they believed were relevant to the Administrator's reconsideration of the

January 2017 Determination.

EPA held a public hearing in Washington DC on September 6, 2017.

EPA received more than 290,000 comments in response to the August 21, 2017 notice.

82 FR 39551 (Aug. 21, 2017).

82 FR 39976 (Aug. 23, 2017).

The public comments, public hearing transcript, and other information relevant to the Mid-term Evaluation are available in docket EPA-HQ-OAR-2015-0827.

EPA has since concluded, based on more recent information, that those standards are no longer appropriate.

NHTSA's “augural” CAFE standards for MYs 2022-2025 were not final in 2012 because Congress prohibits NHTSA from finalizing new CAFE standards for more than five model years in a single rulemaking.

NHTSA was therefore obligated from the beginning to undertake a new rulemaking to set CAFE standards for MYs 2022-2025.

83 FR 16077 (Apr. 2, 2018).

49 U.S.C. 32902.

The proposed SAFE Vehicles Rule begins the rulemaking process for both agencies to establish new standards for MYs 2022-2025 passenger cars and light trucks. Standards are concurrently being proposed for MY 2026 in order to provide regulatory stability for as many years as is legally permissible for both agencies together.

Separately, the proposed SAFE Vehicles Rule includes revised standards for MY 2021 passenger cars and light trucks. The information now available and the current analysis suggest that the CAFE standards previously set for MY 2021 are no longer maximum feasible, and the CO

standards previously set for MY 2021 are no longer appropriate. Agencies always have authority under the Administrative Procedure Act to revisit previous decisions in light of new facts, as long as they provide notice and an opportunity for comment, and it is plainly the best practice to do so when changed circumstances so warrant.

See FCC

Fox Television,

556 U.S. 502 (2009).

Thus, the proposed SAFE Vehicles Rule would maintain the CAFE and CO

standards applicable in MY 2020 for MYs 2021-2026, while taking comment on a wide range of alternatives, including different stringencies and retaining existing CO

standards and the augural CAFE standards.

Table I-4 below presents those alternatives. We note further that prior to MY 2021, CO

targets include adjustments reflecting the use of automotive refrigerants with reduced global warming potential (GWP) and/or the use of technologies that reduce the refrigerant leaks, and optionally offsets for nitrous oxide and methane emissions. In the interests of harmonizing with the CAFE program, EPA is proposing to exclude air conditioning refrigerants and leakage, and nitrous oxide and methane emissions for compliance with CO

standards after model year 2020 but seeks comment on whether to retain these element, and reinsert A/C leakage offsets, and remain disharmonized with the CAFE program. EPA also seeks comment on whether to change existing methane and nitrous oxide standards that were finalized in the 2012 rule. Specifically, EPA seeks information from the public on whether those existing standards are appropriate, or whether they should be revised to be less stringent or more stringent based on any updated data.

Note: This does not mean that the miles per gallon and grams per mile levels that were estimated for the MY 2020 fleet in 2012 would be the “standards” going forward into MYs 2021-2026. Both NHTSA and EPA set CAFE and CO

standards, respectively, as mathematical functions based on vehicle footprint. These mathematical functions that are the actual standards are defined as “curves” that are separate for passenger cars and light trucks, under which each vehicle manufacturer's compliance obligation varies depending on the footprints of the cars and trucks that it ultimately produces for sale in a given model year. It is the MY 2020 CAFE and CO

curves which we propose would continue to apply to the passenger car and light truck fleets for MYs 2021-2026. The mpg and g/mi values which those curves would eventually require of the fleets in those model years would be known for certain only at the ends of each of those model years. While it is convenient to discuss CAFE and CO

standards as a set “mpg,” “g/mi,” or “mpg-e” number, attempting to define those values today will end up being inaccurate.

While actual requirements will ultimately vary for automakers depending upon their individual fleet mix of vehicles, many stakeholders will likely be interested in the current estimate of what the MY 2020 CAFE and CO

curves would translate to, in terms of miles per gallon (mpg) and grams per mile (g/mi), in MYs 2021-2026. These estimates are shown in the following tables.

BILLING CODE 4910-59-P

EP24AU18.000

EP24AU18.001

BILLING CODE 4910-59-C

In the tables above, estimated required CO

increases between MY 2020 and MY 2021 because, again, EPA is proposing to exclude CO

-equivalent emission improvements associated with air conditioning refrigerants and leakage (and, optionally, offsets for nitrous oxide and methane emissions) after model year 2020.

As explained above, the agencies are taking comment on a wide range of alternatives and have specifically modeled eight alternatives (including the proposed alternative) and the current requirements (

i.e.,

baseline/no-action). The modeled alternatives are provided below:

Carbon dioxide equivalent of air conditioning refrigerant leakage, nitrous oxide and methane emissions are included for compliance with the EPA standards for all MYs under the baseline/no action alternative. Carbon dioxide equivalent is calculated using the Global Warming Potential (GWP) of each of the emissions.

Beginning in MY 2021, the proposal provides that the GWP equivalents of air conditioning refrigerant leakage, nitrous oxide and methane emissions would no longer be able to be included with the tailpipe CO

for compliance with tailpipe CO

standards.

EP24AU18.002

Summary of Rationale

Since finalizing the agencies' previous joint rulemaking in 2012 titled “Final Rule for Model Year 2017 and Later Light-Duty Vehicle Greenhouse Gas Emission and Corporate Average Fuel Economy Standards,” and even since EPA's 2016 and early 2017 “mid-term evaluation” process, the agencies have gathered new information, and have performed new analysis. That new information and analysis has led the

agencies to the tentative conclusion that holding standards constant at MY 2020 levels through MY 2026 is maximum feasible, for CAFE purposes, and appropriate, for CO

purposes.

Technologies have played out differently in the fleet from what the agencies assumed in 2012.

The technology to improve fuel economy and reduce CO

emissions has not changed dramatically since prior analyses were conducted: A wide variety of technologies are still available to accomplish the goals of the programs, and a wide variety of technologies would likely be used by industry to accomplish these goals. There remains no single technology that the majority of vehicles made by the majority of manufacturers can implement at low cost without affecting other vehicle attributes that consumers value more than fuel economy and CO

emissions. Even when used in combination, technologies that can improve fuel economy and reduce CO

emissions still need to (1) actually work together and (2) be acceptable to consumers and avoid sacrificing other vehicle attributes while also avoiding undue increases in vehicle cost. Optimism about the costs and effectiveness of many individual technologies, as compared to recent prior rounds of rulemaking, is somewhat tempered; a clearer understanding of what technologies are already on vehicles in the fleet and how they are being used, again as compared to recent prior rounds of rulemaking, means that technologies that previously appeared to offer significant “bang for the buck” may no longer do so. Additionally, in light of the reality that vehicle manufacturers may choose the relatively cost-effective technology option of vehicle lightweighting for a wide array of vehicles and not just the largest and heaviest, it is now recognized that as the stringency of standards increases, so does the likelihood that higher stringency will increase on-road fatalities. As it turns out, there is no such thing as a free lunch.

Mankiw, N. Gregory, Principles of Macroeconomics, Sixth Edition, 2012, at 4.

Technology that can improve both fuel economy and/or performance may not be dedicated solely to fuel economy.

As fleet-wide fuel efficiency has improved over time, additional improvements have become both more complicated and more costly. There are two primary reasons for this phenomenon. First, as discussed, there is a known pool of technologies for improving fuel economy and reducing CO

emissions. Many of these technologies, when actually implemented on vehicles, can be used to improve other vehicle attributes such as “zero to 60” performance, towing, and hauling, etc., either instead of or in addition to improving fuel economy and reducing CO

emissions. As one example, a V6 engine can be turbocharged and downsized so that it consumes only as much fuel as an inline 4-cylinder engine,

it can be turbocharged and downsized so that it consumes less fuel than it would originally have consumed (but more than the inline 4-cylinder would) while also providing more low-end torque. As another example, a vehicle can be lightweighted so that it consumes less fuel than it would originally have consumed,

so that it consumes the same amount of fuel it would originally have consumed but can carry more content, like additional safety or infotainment equipment. Manufacturers employing “fuel-saving/emissions-reducing” technologies in the real world make decisions regarding how to employ that technology such that fewer than 100% of the possible fuel-saving/emissions-reducing benefits result. They do this because this is what consumers want, and more so than exclusively fuel economy improvements.

This makes actual fuel economy gains more expensive.

Thus, even though the technologies may be largely the same, previous assumptions about how much fuel can be saved or how much emissions can be reduced by employing various technologies may not have played out as prior analyses suggested, meaning that previous assumptions about how much it would cost to save that much fuel or reduce that much in emissions fall correspondingly short. For example, the agencies assumed in the 2010 final rule that dual clutch transmissions would be widely used to improve fuel economy due to expectations of strong effectiveness and very low cost: In practice, dual clutch transmissions had significant customer acceptance issues, and few manufacturers employ them in the U.S. market today.

The agencies included some “technologies” in the 2012 final rule analysis that were defined ambiguously and/or in ways that precluded observation in the known (MYs 2008 and 2010) fleets, likely leading to double counting in cases where the known vehicles already reflected the assumed efficiency improvement. For example, the agencies assumed that transmission “shift optimizers” would be available and fairly widely used in MYs 2017-2025, but involving software controls, a “technology” not defined in a way that would be observed in the fleet (unlike, for example, a dual clutch transmission).

In fact, one manufacturer saw enough customer pushback that it launched a buyback program.

See, e.g.,

Steve Lehto, “What you need to know about the settlement for Ford Powershift owners,” Road and Track, Oct. 19, 2017.

Available at

https://www.roadandtrack.com/car-culture/a10316276/what-you-need-to-know-about-the-proposed-settlement-for-ford-powershift-owners/

(last accessed Jul. 2, 2018).

To be clear, this is no one's “fault”—the CAFE and CO

standards do not require manufacturers to use particular technologies in particular ways, and both agencies' past analyses generally sought to illustrate technology paths to compliance that were assumed to be as cost-effective as possible. If manufacturers choose different paths for reasons not accounted for in regulatory analysis, or choose to use technologies differently from what the agencies previously assumed, it does not necessarily mean that the analyses were unreasonable when performed. It

does

mean, however, that the fleet ought to be reflected as it stands today, with the technology it has and as that technology has been used, and consider what technology remains on the table at this point, whether and when it can realistically be available for widespread use in production, and how much it would cost to implement.

Incremental additional fuel economy benefits are subject to diminishing returns.

As fleet-wide fuel efficiency improves and CO

emissions are reduced, the incremental benefit of continuing to improve/reduce inevitably decreases. This is because, as the base level of fuel economy improves, fewer gallons are saved from subsequent incremental improvements. Put simply, a one mpg increase for vehicles with low fuel economy will result in far greater savings than an identical 1 mpg increase for vehicles with higher fuel economy, and the cost for achieving a one-mpg increase for low fuel economy vehicles is far less than for higher fuel economy vehicles. This means that improving fuel economy is subject to diminishing returns. Annual fuel consumption can be calculated as follows:

EP24AU18.003

For purposes of illustration, assume a vehicle owner who drives a light vehicle 15,000 miles per year (a typical assumption for analytical purposes).

If that owner trades in a vehicle with fuel economy of 15 mpg for one with fuel economy of 20 mpg, the owner's annual fuel consumption would drop from 1,000 gallons to 750 gallons—saving 250 gallons annually. If, however, that owner were to trade in a vehicle with fuel economy of 30 mpg for one with fuel economy of 40 mpg, the owner's annual gasoline consumption would drop from 500 gallons/year to 375 gallons/year—only 125 gallons even though the mpg improvement is twice as large. Going from 40 to 50 mpg would save only 75 gallons/year. Yet, each additional fuel economy improvement becomes much more expensive as the low-hanging fruit of low-cost technological improvement options are picked.

Automakers, who must nonetheless continue adding technology to improve fuel economy and reduce CO

emissions, will either sacrifice other performance attributes or raise the price of vehicles—neither of which is attractive to most consumers.

A different vehicle-miles-traveled (VMT) assumption would change the absolute numbers in the example, but would not change the mathematical principles. Today's analysis uses mileage accumulation schedules that average about 15,000 miles annually over the first six years of vehicle operation.

The examples in the text above are presented in mpg because that is a metric which should be readily understandable to most readers, but the example would hold true for grams of CO

per mile as well. If a vehicle emits 300 g/mi CO

, a 20 percent improvement is 60 g/mi, so that the vehicle would emit 240 g/mi. At 180 g/mi, a 20% improvement is 36 g/mi, so the vehicle would get 144 g/mi. In order to continue achieving similarly large (on an absolute basis) emissions reductions, mathematics require the percentage reduction to continue increasing.

If fuel prices are high, the value of those gallons may be enough to offset the cost of further fuel economy improvements, but (1) the most recent reference case projections in the Energy Information Administration's (EIA's) Annual Energy Outlook (AEO 2017 and AEO 2018) do not indicate particularly high fuel prices in the foreseeable future, given underlying assumptions,

and (2) as the baseline level of fuel economy continues to increase, the marginal cost of the next gallon saved similarly increases with the cost of the technologies required to meet the savings. The following figure illustrates the fact that fuel savings and corresponding avoided costs diminish with increasing fuel economy, showing the same basic pattern as a 2014 illustration developed by EIA.

The U.S. Energy Information Administration (EIA) is the statistical and analytical agency within the U.S. Department of Energy (DOE). EIA is the nation's premiere source of energy information, and every fuel economy rulemaking since 2002 (and every joint CAFE and CO

rulemaking since 2009) has applied fuel price projections from EIA's Annual Energy Outlook (AEO). AEO projections, documentation, and underlying data and estimates are available at

https://www.eia.gov/outlooks/aeo/

Today in Energy: Fuel economy improvements show diminishing returns in fuel savings,

U.S. Energy Information Administration (Jul. 11, 2014),

https://www.eia.gov/todayinenergy/detail.php?id=17071

EP24AU18.004

This effect is mathematical in nature and long-established, but when combined with relatively low fuel prices potentially through 2050, and the likelihood that a large majority of American consumers could consequently continue to place a higher value on vehicle attributes other than fuel economy, it makes manufacturers' ability to sell light vehicles with ever-higher fuel economy and ever-lower carbon dioxide emissions increasingly difficult. Put more simply, if gas is cheap and each additional improvement saves less gas anyway, most consumers would rather spend their money on attributes other than fuel economy when they are considering a new vehicle purchase, whether that is more safety technology, a better infotainment package, a more powerful powertrain, or other features (or, indeed, they may prefer to spend the savings on something other than automobiles). Manufacturers trying to sell consumers more fuel economy in such circumstances may convince consumers who place weight on efficiency and reduced carbon emissions, but consumers decide for themselves what attributes are worth to them. And while some contend that consumers do not sufficiently consider or value future fuel savings when making vehicle purchasing decisions,

information regarding the benefits of higher fuel economy has never been made more readily available than today, with a host of online tools and mandatory prominent disclosures on new vehicles on the Monroney label showing fuel savings compared to average vehicles. This is not a question of “if you build it, they will come.” Despite the widespread availability of fuel economy information, and despite manufacturers building and marketing vehicles with higher fuel economy and increasing their offerings of hybrid and electric vehicles, in the past several years as gas prices have remained low, consumer preferences have shifted markedly away from higher-fuel-economy smaller and midsize passenger vehicles toward crossovers and truck-based utility vehicles.

Some consumers plainly value fuel economy and low CO

emissions above other attributes, and thanks in part to CAFE and CO

standards, they have a plentiful selection of high-fuel economy and low CO

-emitting vehicles to choose from, but those consumers represent a relatively small percentage of buyers.

In docket numbers EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068, see comments submitted by,

e.g.,

Consumer Federation of America (NHTSA-2016-0068-0054, at p. 57,

et seq

.) and the Environmental Defense Fund (EPA-HQ-OAR-2015-0827-4086, at p. 18,

et seq

.).

Carey, N.

Lured by rising SUV sales, automakers flood market with models,

Reuters (Mar. 29, 2018),

available at

https://www.reuters.com/article/us-autoshow-new-york-suvs/lured-by-rising-suv-sales-automakers-flood-market-with-models-idUSKBN1H50KI

(last accessed Jun. 13, 2018). Many commentators have recently argued that manufacturers are deliberately increasing vehicle footprint size in order to get “easier” CAFE and CO

standards. This misunderstands, somewhat, how the footprint-based standards work. While it is correct that larger-footprint vehicles have less stringent “targets,” the difficulty of compliance rests in how far above or below those vehicles are

as compared to

their targets, and more specifically, whether the manufacturer is selling so many vehicles that are far short of their targets that they cannot average out to compliant levels through other vehicles sold that beat their targets. For example, under the CAFE program, a manufacturer building a fleet of larger-footprint vehicles may have an objectively lower mpg-value compliance obligation than a manufacturer building a more mixed fleet, but it may still be more challenging for the first manufacturer to reach its compliance obligation if it is selling only very-low-mpg variants at any given footprint. There is only so much that increasing footprint makes it “easier” for a manufacturer to reach compliance.

Changed petroleum market has supported a shift in consumer preferences.

In 2012, the agencies projected fuel prices would rise significantly, and the United States would continue to rely heavily upon imports of oil, subjecting the country to heightened risk of price shocks.

Things have changed significantly since 2012, with fuel prices significantly lower than anticipated, and projected to remain low through 2050. Furthermore, the global petroleum market has shifted dramatically with the United States taking advantage of its own oil supplies through technological advances that allow for cost-effective extraction of shale oil. The U.S. is now the world's largest oil producer and expected to become a net petroleum exporter in the next decade.

The 2012 final rule analysis relied on the Energy Information Administration's Annual Energy Outlook 2012 Early Release, which assumed significantly higher fuel prices than the AEO 2017 (or AEO 2018) currently available.

See

77 FR 62624, 62715 (Oct. 15, 2012) for the 2012 final rule's description of the fuel price estimates used.

Annual Energy Outlook 2018, U.S. Energy Information Administration, at 53 (Feb. 6, 2018),

https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf

At least partially in response to lower fuel prices, consumers have moved more heavily into crossovers, sport utility vehicles and pickup trucks, than anticipated at the time of the last rulemaking. Because standards are based on footprint and specified separately for passenger cars and light trucks, these shifts do not necessarily pose compliance challenges by themselves, but they tend to reduce the overall average fuel economy rates and increase the overall average CO

emission rates of the new vehicle fleet. Consumers are also demonstrating a preference for more powerful engines and vehicles with higher seating positions and ride height (and accompanying mass increase relative to footprint)

—all of which present challenges for achieving increased fuel economy levels and lower CO

emission rates.

See id.

The Consequence of Unreasonable Fuel Economy and CO

Standards: Increased vehicle prices keep consumers in older, dirtier, and less safe vehicles.

Consumers tend to avoid purchasing things that they neither want or need. The analysis in today's proposal moves closer to being able to represent this fact through an improved model for vehicle scrappage rates. While neither this nor a sales response model, also included in today's analysis, nor the combination of the two, are consumer choice models, today's analysis illustrates market-wide impacts on the sale of new vehicles and the retention of used vehicles. Higher vehicle prices, which result from more-stringent fuel economy standards, have an effect on consumer purchasing decisions. As prices increase, the market-wide incentive to extract additional travel from used vehicles increases. The average age of the in-service fleet has been increasing, and when fleet turnover slows, not only does it take longer for fleet-wide fuel economy and CO

emissions to improve, but also safety improvements, criteria pollutant emissions improvements, many other vehicle attributes that also provide societal benefits take longer to be reflected in the overall U.S. fleet as well because of reduced turnover. Raising vehicle prices too far, too fast, such as through very stringent fuel economy and CO

emissions standards (especially considering that, on a fleet-wide basis, new vehicle sales and turnover do not appear strongly responsive to fuel economy), has effects beyond simply a slowdown in sales. Improvements over time have better longer-term effects simply by not alienating consumers, as compared to great leaps forward that drive people out of the new car market or into vehicles that do not meet their needs. The industry has achieved tremendous gains in fuel economy over the past decade, and these increases will continue at least through 2020.

Along with these gains, there have also been tremendous increases in vehicle prices, as new vehicles become increasingly unaffordable—with the average new vehicle transaction price

recently exceeding $36,000—up by more than $3,000 since 2014 alone.

In fact, a recent independent study indicated that the average new car price is unaffordable to median-income families in every metropolitan region in the United States except one: Washington, DC.

That analysis used the historically accepted approach that consumers should make a down-payment of at least 20% of a vehicle's purchase price, finance for no longer than four years, and make payments of 10% or less of the consumer's annual income to car payments and insurance. But the market looks nothing like that these days, with average financing terms of 68 months, and an increasing proportion exceeding 72 or even 84 months.

Longer financing terms may allow a consumer to keep their monthly payment affordable but can have serious potential financial consequences. Longer-term financing leads (generally) to higher interest rates, larger finance charges and total consumer costs, and a longer period of time with negative equity. In 2012, the agencies expected prices to increase under the standards announced at that time. The agencies estimated that, compared to a continuation of the model year 2016 standards, the standards issued through model year 2025 would eventually increase average prices by about $1,500-$1,800.

Circumstances have changed, the analytical methods and inputs have been updated (including updates to address issues still present in analyses published in 2016, 2017, and early 2018), and today, the analysis suggests that, compared to the proposed standards today, the previously-issued standards would increase average vehicle prices by about $2,100. While today's estimate is similar in magnitude to the 2012 estimate, it is relative to a baseline that includes increases in stringency between MY 2016 and MY 2020. Compared to leaving vehicle technology at MY 2016 levels, today's analysis shows the previously-issued standards through model year 2025 could eventually increase average vehicle prices by approximately $2,700. A pause in continued increases in fuel economy standards, and cost increases attributable thereto, is appropriate.

See, e.g.,

Average New-Car Prices Rise Nearly 4 Percent for January 2018 On Shifting Sales Mix, According To Kelley Blue Book,

Kelley Blue Book,

https://mediaroom.kbb.com/2018-02-01-Average-New-Car-Prices-Rise-Nearly-4-Percent-For-January-2018-On-Shifting-Sales-Mix-According-To-Kelley-Blue-Book

(last accessed Jun. 15, 2018).

Bell, C.

What's an `affordable' car where you live? The answer may surprise you,

Bankrate.com

(Jun. 28, 2017),

available at

https://www.bankrate.com/auto/new-car-affordability-survey/

(last accessed Jun. 15, 2018).

Average Auto Loan Interest Rates: 2018 Facts and Figures,

ValuePenguin,

available at

https://www.valuepenguin.com/auto-loans/average-auto-loan-interest-rates

(last accessed Jun. 15, 2018).

77 FR 62624, 62666 (Oct. 15, 2012).

The $1,500 figure reported in 2012 by NHTSA reflected application of carried-forward credits in model year 2025, rather than an achieved CAFE level that could be sustainably compliant beyond 2025 (with standards remaining at 2025 levels). As for the 2016 draft TAR, NHTSA has since updated its modeling approach to extend far enough into the future that any unsustainable credit deficits are eliminated. Like analyses published by EPA in 2016, 2017, and early 2018, the $1,800 figure reported in 2012 by EPA did not reflect either simulation of manufacturers' multiyear plans to progress from the initial MY 2008 fleet to the MY 2025 fleet or any accounting for manufacturers' potential application of banked credits. Today's analysis of both CAFE and CO

standards accounts explicitly for multiyear planning and credit banking.

While EPA did not refer to the reported $1,800 as an estimate of the increase in average prices, because EPA did not assume that manufacturers would reduce profit margins, the $1,800 estimate is appropriately interpreted as an estimate of the average increase in vehicle prices.

EP24AU18.005

Preferred Alternative

For all of these reasons, the agencies are proposing to maintain the MY 2020 fuel economy and CO

emissions standards for MYs 2021-2026. Our goal is to establish standards that promote both energy conservation and safety, in light of what is technologically feasible and economically practicable, as directed by Congress.

Data on new vehicle prices are from U.S. Bureau of Economic Analysis, National Income and Product Accounts, Supplemental Table 7.2.5S, Auto and Truck Unit Sales, Production, Inventories, Expenditures, and Price (

https://www.bea.gov/iTable/iTable.cfm?reqid=19&step=2#reqid=19&step=3&isuri=1&1921=underlying&1903=2055

, last accessed Jul. 20, 2018). Median Household Income data are from U.S. Census Bureau, Table A-1, Households by Total Money Income, Race, and Hispanic Origin of Householder: 1967 to 2016 (

https://www.census.gov/data/tables/2017/demo/income-poverty/p60-259.html

, last accessed Jul. 20, 2018).

Energy Conservation

EPCA requires that NHTSA, when determining the maximum feasible levels of CAFE standards, consider the need of the Nation to conserve energy. However, EPCA also requires that NHTSA consider other factors, such as technological feasibility and economic practicability. The analysis suggests that, compared to the standards issued previously for MYs 2021-2025, today's proposed rule will eventually (by the early 2030s) increase U.S. petroleum consumption by about 0.5 million barrels per day—about two to three percent of projected total U.S. consumption. While significant, this additional petroleum consumption is, from an economic perspective, dwarfed by the cost savings also projected to result from today's proposal, as indicated by the consideration of net benefits appearing below.

Safety Benefits From Preferred Alternative

Today's proposed rule is anticipated to prevent more than 12,700 on-road fatalities

and significantly more injuries as compared to the standards set forth in the 2012 final rule over the lifetimes of vehicles as more new, safer vehicles are purchased than the current (and augural) standards. A large portion of these safety benefits will come from improved fleet turnover as more consumers will be able to afford newer and safer vehicles.

Over the lifetime of vehicles through MY 2029.

Recent NHTSA analysis shows that the proportion of passengers killed in a vehicle 18 or more model years old is nearly double that of a vehicle three model years old or newer.

As the average car on the road is approaching 12 years old, apparently the oldest in our history,

major safety benefits will occur by reducing fleet age. Other safety benefits will occur from other areas such as avoiding the increased driving

that would otherwise result from higher fuel efficiency (known as the rebound effect) and avoiding the mass reductions in passenger cars that might otherwise be required to meet the standards established in 2012.

Together these and other factors lead to estimated annual fatalities under the proposed standards that are significantly reduced

relative to those that would occur under current (and augural) standards.

Passenger Vehicle Occupant Injury Severity by Vehicle Age and Model Year in Fatal Crashes, Traffic Safety Facts Research Note, DOT HS 812 528. Washington, DC: National Highway Traffic Safety Administration. April 2018.

See, e.g., IHS Markit, Vehicles Getting Older: Average Age of Light Cars and Trucks in U.S. Rises Again in 2016 to 11.5 years, IHS Markit Says,

IHS Markit (Nov. 22, 2016),

http://news.ihsmarkit.com/press-release/automotive/vehicles-getting-older-average-age-light-cars-and-trucks-us-rises-again-201

(“. . . consumers are continuing the trend of holding onto their vehicles longer than ever. As of the end of 2015, the average length of ownership measured a record 79.3 months, more than 1.5 months longer than reported in the previous year. For used vehicles, it is nearly 66 months. Both are significantly longer lengths of ownership since the same measure a decade ago.”).

The agencies are specifically requesting comment on the appropriateness and level of the effects of the rebound effect. The agencies also seek comment on changes as compared to the 2012 modeling relating to mass reduction assumptions. During that rulemaking, the analysis limited the amount of mass reduction assumed for certain vehicles, which impacted the results regarding potential for adverse safety effects, even while acknowledging that manufacturers would not necessarily choose to avoid mass reductions in the ways that the agencies assumed.

See,

77 FR 623624, 62763 (Oct. 15, 2012). By choosing where and how to limit assumed mass reduction, the 2012 rule's safety analysis reduced the projected apparent risk to safety associated with aggressive fuel economy and CO

targets. That specific assumption has been removed for today's analysis.

The reduction in annual fatalities varies each calendar year, averaging 894 fewer fatalities annually for the CAFE program and 1,150 fewer fatalities for the CO

program over calendar years 2036-2045.

The Preferred Alternative Would Have Negligible Environmental Impacts on Air Quality

Improving fleet turnover will result in consumers getting into newer and cleaner vehicles, accelerating the rate at which older, more-polluting vehicles are removed from the roadways. Also, reducing fuel economy (relative to levels that would occur under previously-issued standards) would increase the marginal cost of driving newer vehicles, reducing mileage accumulated by those vehicles, and reducing corresponding emissions. On the other hand, increasing fuel consumption would increase emissions resulting from petroleum refining and related “upstream” processes. Our analysis shows that none of the regulatory alternatives considered in this proposal would noticeably impact net emissions of smog-forming or other “criteria” or toxic air pollutants, as illustrated by the following graph. That said, the resultant tailpipe emissions reductions should be especially beneficial to highly trafficked corridors.

EP24AU18.006

Climate Change Impacts From Preferred Alternative

The estimated effects of this proposal in terms of fuel savings and CO

emissions, again perhaps somewhat counter-intuitively, is relatively small as compared to the 2012 final rule.

NHTSA's Environmental Impact Statement performed for this rulemaking shows that the preferred alternative would result in 3/1,000ths of a degree Celsius increase in global average temperatures by 2100, relative to the standards finalized in 2012. On a net CO

basis, the results are similarly minimal. The following graph compares the estimated atmospheric CO

concentration (789.76 ppm) in 2100 under the proposed standards to the estimated level (789.11 ppm) under the standards set forth in 2012—or an 8/100ths of a percentage increase:

Counter-intuitiveness is relative, however. The estimated effects of the 2012 final rule on climate were similarly small in magnitude, as shown in the Final EIS accompanying that rule and available on NHTSA's website.

EP24AU18.007

Net Benefits From Preferred Alternative

Maintaining the MY 2020 curves for MYs 2021-2026 will save American consumers, the auto industry, and the public a considerable amount of money as compared to if EPA retained the previously-set CO

standards and NHTSA finalized the augural standards. This was identified as the preferred alternative, in part, because it maximizes net benefits compared to the other alternatives analyzed, recognizing the statutory considerations for both agencies. Comment is sought on whether this is an appropriate basis for selection.

EP24AU18.008

These estimates, reported as changes relative to impacts under the standards issued in 2012, account for impacts on vehicles produced during model years 2016-2029, as well as (through changes in utilization) vehicles produced in earlier model years, throughout those vehicles' useful lives. Reported values are in 2016 dollars, and reflect three-percent and seven-percent discount rates. Under CAFE standards, costs are estimated to decrease by $502 billion overall at a three-percent discount rate ($335 billion at a seven-percent discount rate); benefits are estimated to decrease by $326 billion at a three-percent discount rate ($204 billion at a seven-percent discount rate). Thus, net benefits are estimated to increase by $176 billion at a three-percent discount rate and $132 billion at a seven-percent discount rate. The estimated impacts under CO

standards are similar, with net benefits estimated to increase by $201 billion at a three-percent discount rate and $141 billion at a seven-percent discount rate.

Compliance Flexibilities

This proposal also seeks comment on a variety of changes to NHTSA's and EPA's compliance programs for CAFE and CO

as well as related programs. Compliance flexibilities can generally be grouped into two categories. The first category are those compliance flexibilities that reduce unnecessary compliance costs and provide for a more efficient program. The second category of compliance flexibilities are those that distort the market—such as by incentivizing the implementation of one type of technology by providing credit for compliance in excess of real-world fuel savings.

Both programs provide for the generation of credits based upon fleet-wide over-compliance, provide for adjustments to the test measured value of each individual vehicle based upon the implementation of certain fuel saving technologies, and provide additional incentives for the implementation of certain preferred technologies (regardless of actual fuel savings). Auto manufacturers and others have petitioned for a host of additional adjustment- and incentive-type flexibilities, where there is not always consumer interest in the technologies to be incentivized nor is there necessarily clear fuel-saving and emissions-reducing benefit to be derived from that incentivization. The agencies seek comment on all of those requests as part of this proposal.

Over-compliance credits, which can be built up in part through use of the above-described per-vehicle adjustments and incentives, can be saved and either applied retroactively to accounts for previous non-compliance, or carried forward to mitigate future non-compliance. Such credits can also be traded to other automakers for cash or for other credits for different fleets. But such trading is not pursued openly. Under the CAFE program, the public is not made aware of inter-automaker trades, nor are shareholders. And even the agencies are not informed of the price of credits. With the exception of statutorily-mandated credits, the agencies seek comment on all aspects of the current system. The agencies are particularly interested in comments on flexibilities that may distort the market.

The agencies seek comment as to whether some adjustments and non-statutory incentives and other provisions should be eliminated and stringency levels adjusted accordingly. In general, well-functioning banking and trading provisions increase market efficiency and reduce the overall costs of compliance with regulatory objectives. The agencies request comment on whether the current system as implemented might need improvements to achieve greater efficiencies. We seek comment on specific programmatic changes that could improve compliance with current standards in the most efficient way, ranging from requiring public disclosure of some or all aspects of credit trades, to potentially eliminating credit trading in the CAFE program. We request commenters to provide any data, evidence, or existing literature to help agency decision-making.

One National Standard

Setting appropriate and maximum feasible fuel economy and tailpipe CO

emissions standards requires regulatory efficiency. This proposal addresses a fundamental and unnecessary complication in the currently-existing regulatory framework, which is the regulation of GHG emissions from passenger cars and light trucks by the State of California through its GHG standards and Zero Emission Vehicle (ZEV) mandate and subsequent adoption of these standards by other States. Both EPCA and the CAA preempt State regulation of motor vehicle emissions (in EPCA's case, standards that are related to fuel economy standards). The CAA gives EPA the authority to waive preemption for California under certain circumstances. EPCA does not provide for a waiver of preemption under any circumstances. In short, the agencies propose to maintain one national standard—a standard that is set exclusively by the Federal government.

Proposed Withdrawal of California's Clean Air Act Preemption Waiver

EPA granted a waiver of preemption to California in 2013 for its “Advanced Clean Car” regulations, composed of its GHG standards, its “Low Emission Vehicle (LEV)” program and the ZEV program,

and, as allowed under the CAA, a number of other States adopted California's standards.

The CAA states that EPA shall not grant a waiver of preemption if EPA finds that California's determination that its standards are, in the aggregate, at least as protective of public health and welfare as applicable Federal standards, is arbitrary and capricious; that California does not need its own standards to meet compelling or extraordinary conditions; or that such California standards and accompanying enforcement procedures are not consistent with Section 202(a) of the CAA. In this proposal, EPA is proposing to withdraw the waiver granted to California in 2013 for the GHG and ZEV requirements of its Advanced Clean Cars program, in light of all of these factors.

78 FR 2112 (Jan. 9, 2013).

CAA Section 177, 42 U.S.C. 7507.

Attempting to solve climate change, even in part, through the Section 209 waiver provision is fundamentally different from that section's original purpose of addressing smog-related air quality problems. When California was merely trying to solve its air quality issues, there was a relatively-straightforward technology solution to the problems, implementation of which did not affect how consumers lived and drove. Section 209 allowed California to pursue additional reductions to address its notorious smog problems by requiring more stringent standards, and allowed California and other States that failed to comply with Federal air quality standards to make progress toward compliance. Trying to reduce carbon emissions from motor vehicles in any significant way involves changes to the entire vehicle, not simply the addition of a single or a handful of control technologies. The greater the emissions reductions are sought, the greater the likelihood that the characteristics and capabilities of the vehicle currently sought by most American consumers will have to change significantly. Yet, even decades later, California continues to be in widespread non-attainment with Federal air quality standards.

In the past decade, California has disproportionately focused on GHG emissions. Parts of California have a real and significant local air pollution problem, but CO

is not part of that local problem.

See

California Nonattainment/Maintenance Status for Each County by Year for All Criteria Pollutants, current as of May 31, 2018, at

https://www3.epa.gov/airquality/greenbook/anayo_ca.html

(last accessed June 15, 2018).

California's Tailpipe CO

Emissions Standards and ZEV Mandate Conflict With EPCA

Moreover, California regulation of tailpipe CO

emissions, both through its GHG standards and ZEV program, conflicts directly and indirectly with EPCA and the CAFE program. EPCA expressly preempts State standards related to fuel economy. Tailpipe CO

standards, whether in the form of fleet-wide CO

limits or in the form of requirements that manufacturers selling vehicles in California sell a certain number of low- and no-tailpipe-CO

emissions vehicles as part of their overall sales, are unquestionably related to fuel economy standards. Standards that control tailpipe CO

emissions are

de facto

fuel economy standards because CO

is a direct and inevitable byproduct of the combustion of carbon-based fuels to make energy, and the vast majority of the energy that powers passenger cars and light trucks comes from carbon-based fuels.

Improving fuel economy means getting the vehicle to go farther on a gallon of gas; a vehicle that goes farther on a gallon of gas produces less CO

per unit of distance; therefore, improving fuel economy necessarily reduces tailpipe CO

emissions, and reducing CO

emissions necessarily improves fuel economy. EPCA therefore necessarily preempts California's Advanced Clean Cars program to the extent that it regulates or prohibits tailpipe CO

emissions. Section VI of this proposal, below, discusses the CAA waiver and EPCA preemption in more detail.

Eliminating California's regulation of fuel economy pursuant to Congressional direction will provide benefits to the American public. The automotive industry will, appropriately, deal with fuel economy standards on a national basis—eliminating duplicative regulatory requirements. Further, elimination of California's ZEV program will allow automakers to develop such vehicles in response to consumer demand instead of regulatory mandate. This regulatory mandate has required automakers to spend tens of billions of dollars to develop products that a significant majority of consumers have not adopted, and consequently to sell such products at a loss. All of this is paid for through cross subsidization by increasing prices of other vehicles not just in California and other States that have adopted California's ZEV mandate, but throughout the country.

Request for Comment

The agencies look forward to all comments on this proposal, and wish to emphasize that obtaining public input is extremely important to us in selecting from among the alternatives in a final rule. While the agencies and the Administration met with a variety of stakeholders prior to issuance of this proposal, those meetings have not resulted in a predetermined final rule outcome. The Administrative Procedure Act requires that agencies provide the

public with adequate notice of a proposed rule followed by a meaningful opportunity to comment on the rule's content. The agencies are committed to following that directive.

II. Technical Foundation for NPRM Analysis

A. Basics of CAFE and CO

Standards Analysis

The agencies' analysis of CAFE and CO

standards involves two basic elements: first, estimating ways each manufacturer could potentially respond to a given set of standards in a manner that considers potential consumer response; and second, estimating various impacts of those responses. Estimating manufacturers' potential responses involves simulating manufacturers' decision-making processes regarding the year-by-year application of fuel-saving technologies to specific vehicles. Estimating impacts involves calculating resultant changes in new vehicle costs, estimating a variety of costs (

e.g.,

for fuel) and effects (

e.g.,

emissions from fuel combustion) occurring as vehicles are driven over their lifetimes before eventually being scrapped, and estimating the monetary value of these effects. Estimating impacts also involves consideration of the response of consumers—

e.g.,

whether consumers will purchase the vehicles and in what quantities. Both of these basic analytical elements involve the application of many analytical inputs.

The agencies' analysis uses the CAFE model to estimate manufacturers' potential responses to new CAFE and CO

standards and to estimate various impacts of those responses. The model makes use of many inputs, values of which are developed

outside

of the model and not

the model. For example, the model applies fuel prices; it does not estimate fuel prices. The model does not determine the form or stringency of the standards; instead, the model applies inputs specifying the form and stringency of standards to be analyzed and produces outputs showing effects of manufacturers working to meet those standards, which become the basis for comparing between different potential stringencies.

DOT's Volpe National Transportation Systems Center (often simply referred to as the “Volpe Center”) develops, maintains, and applies the model for NHTSA. NHTSA has used the CAFE model to perform analyses supporting every CAFE rulemaking since 2001, and the 2016 rulemaking regarding heavy-duty pickup and van fuel consumption and GHG emissions also used the CAFE model for analysis.

While this rulemaking employed the CAFE model for analysis, EPA and DOT used different versions of the CAFE model for establishing their respective standards, and EPA also used the EPA MOVES model.

See

81 FR 73478, 73743 (Oct. 25, 2016).

DOT recently arranged for a formal peer review of the model. In general, reviewers' comments strongly supported the model's conceptual basis and implementation, and commenters provided several specific recommendations. DOT staff agreed with many of these recommendations and have worked to implement them wherever practicable. Implementing some of them would require considerable further research, development, and testing, and will be considered going forward. For a handful of other recommendations, DOT staff disagreed, often finding the recommendations involved considerations (

e.g.,

other policies, such as those involving fuel taxation) beyond the model itself or were based on concerns with inputs rather than how the model itself functioned. A report available in the docket for this rulemaking presents peer reviewers' detailed comments and recommendations, and provides DOT's detailed responses.

Docket No. NHTSA-2018-0067.

The agencies also use four DOE and DOE-sponsored models to develop inputs to the CAFE model, including three developed and maintained by DOE's Argonne National Laboratory. The agencies use the DOE Energy Information Administration's (EIA's) National Energy Modeling System (NEMS) to estimate fuel prices,

and used Argonne's Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model to estimate emissions rates from fuel production and distribution processes.

DOT also sponsored DOE/Argonne to use their Autonomie full-vehicle simulation system to estimate the fuel economy impacts for roughly a million combinations of technologies and vehicle types.

See https://www.eia.gov/outlooks/aeo/info_nems_archive.php

. Today's notice uses fuel prices estimated using the Annual Energy Outlook (AEO) 2017 version of NEMS (see

https://www.eia.gov/outlooks/archive/aeo17/

and

https://www.eia.gov/outlooks/aeo/data/browser/#/?id=3-AEO2017&cases=ref2017&sourcekey=0

Information regarding GREET is available at

https://greet.es.anl.gov/index.php

. Availability of NEMS is discussed at

https://www.eia.gov/outlooks/aeo/info_nems_archive.php

. Today's notice uses fuel prices estimated using the AEO 2017 version of NEMS.

As part of the Argonne simulation effort, individual technology combinations simulated in Autonomie were paired with Argonne's BatPAC model to estimate the battery cost associated with each technology combination based on characteristics of the simulated vehicle and its level of electrification. Information regarding Argonne's BatPAC model is available at

http://www.cse.anl.gov/batpac/

Additionally, the impact of engine technologies on fuel consumption, torque, and other metrics was characterized using GT POWER simulation modeling in combination with other engine modeling that was conducted by IAV Automotive Engineering, Inc. (IAV). The engine characterization “maps” resulting from this analysis were used as inputs for the Autonomie full-vehicle simulation modeling. Information regarding GT Power is available at

https://www.gtisoft.com/gt-suite-applications/propulsion-systems/gt-power-engine-simulation-software

EPA developed two models after 2009, referred to as the “ALPHA” and “OMEGA” models, which provide some of the same capabilities as the Autonomie and CAFE models. EPA applied the OMEGA model to conduct analysis of GHG standards promulgated in 2010 and 2012, and the ALPHA and OMEGA models to conduct analysis discussed in the above-mentioned 2016 Draft TAR and Proposed and Final Determinations regarding standards beyond 2021. In an August 2017 notice, the agencies requested comments on, among other things, whether EPA should use alternative methodologies and modeling, including DOE/Argonne's Autonomie full-vehicle simulation tool and DOT's CAFE model.

82 FR 39533 (Aug. 21, 2017).

Having reviewed comments on the subject and having considered the matter fully, the agencies have determined it is reasonable and appropriate to use DOE/Argonne's model for full-vehicle simulation, and to use DOT's CAFE model for analysis of regulatory alternatives. EPA interprets Section 202(a) of the CAA as giving the agency broad discretion in how it develops and sets GHG standards for light-duty vehicles. Nothing in Section 202(a) mandates that EPA use any specific model or set of models for analysis of potential CO

standards for light-duty vehicles. EPA weighs many factors when determining appropriate levels for CO

standards, including the cost of compliance (see Section 202(a)(2)), lead time necessary for compliance (also Section 202(a)(2)), safety (see

NRDC

EPA,

655 F.2d 318, 336 n. 31 (D.C. Cir. 1981) and other impacts on consumers,

and energy impacts associated with use of the technology.

Using the CAFE model

allows consideration of the following factors: the CAFE model explicitly evaluates the cost of compliance for each manufacturer, each fleet, and each model year; it accounts for lead time necessary for compliance by directly incorporating estimated manufacturer production cycles for every vehicle in the fleet, ensuring that the analysis does not assume vehicles can be redesigned to incorporate more technology without regard to lead time considerations; it provides information on safety effects associated with different levels of standards and information about many other impacts on consumers, and it calculates energy impacts (

i.e.,

fuel saved or consumed) as a primary function, besides being capable of providing information about many other factors within EPA's broad CAA discretion to consider.

Since its earliest Title II regulations, EPA has considered the safety of pollution control technologies.

See

45 FR 14496, 14503 (1980).

See George E. Warren Corp.

v. EPA, 159 F.3d 616, 623-624 (D.C. Cir. 1998) (ordinarily permissible for EPA to consider factors not specifically enumerated in the Act).

Because the CAFE model simulates a wide range of actual constraints and practices related to automotive engineering, planning, and production, such as common vehicle platforms, sharing of engines among different vehicle models, and timing of major vehicle redesigns, the analysis produced by the CAFE model provides a transparent and realistic basis to show pathways manufacturers could follow over time in applying new technologies, which helps better assess impacts of potential future standards. Furthermore, because the CAFE model also accounts fully for regulatory compliance provisions (now including CO

compliance provisions), such as adjustments for reduced refrigerant leakage, production “multipliers” for some specific types of vehicles (

e.g.,

PHEVs), and carried-forward (

i.e.,

banked) credits, the CAFE model provides a transparent and realistic basis to estimate how such technologies might be applied over time in response to CAFE or CO

standards.

There are sound reasons for the agencies to use the CAFE model going forward in this rulemaking. First, the CAFE and CO

fact analyses are inextricably linked. Furthermore, the analysis produced by the CAFE model and DOE/Argonne's Autonomie addresses several analytical needs. The CAFE model provides an explicit year-by-year simulation of manufacturers' application of technology to their products in response to a year-by-year progression of CAFE standards and accounts for sharing of technologies and the implications for timing, scope, and limits on the potential to optimize powertrains for fuel economy. In the real world, standards actually are specified on a year-by-year basis, not simply some single year well into the future, and manufacturers' year-by-year plans involve some vehicles “carrying forward” technology from prior model years and some other vehicles possibly applying “extra” technology in anticipation of standards in ensuing model years, and manufacturers' planning also involves applying credits carried forward between model years. Furthermore, manufacturers cannot optimize the powertrain for fuel economy on every vehicle model configuration—for example, a given engine shared among multiple vehicle models cannot practicably be split into different versions for each configuration of each model, each with a slightly different displacement. The CAFE model is designed to account for these real-world factors.

Considering the technological heterogeneity of manufacturers' current product offerings, and the wide range of ways in which the many fuel economy-improving/CO

emissions-reducing technologies included in the analysis can be combined, the CAFE model has been designed to use inputs that provide an estimate of the fuel economy achieved for many tens of thousands of different potential combinations of fuel-saving technologies. Across the range of technology classes encompassed by the analysis fleet, today's analysis involves more than a million such estimates. While the CAFE model requires no specific approach to developing these inputs, the National Academy of Sciences (NAS) has recommended, and stakeholders have commented, that full-vehicle simulation provides the best balance between realism and practicality. DOE/Argonne has spent several years developing, applying, and expanding means to use distributed computing to exercise its Autonomie full-vehicle simulation tool over the scale necessary for realistic analysis of CAFE or average CO

standards. This scalability and related flexibility (in terms of expanding the set of technologies to be simulated) makes Autonomie well-suited for developing inputs to the CAFE model.

Additionally, DOE/Argonne's Autonomie also has a long history of development and widespread application by a much wider range of users in government, academia, and industry. Many of these users apply Autonomie to inform funding and design decisions. These real-world exercises have contributed significantly to aspects of Autonomie important to producing realistic estimates of fuel economy levels and CO

emission rates, such as estimation and consideration of performance, utility, and driveability metrics (

e.g.,

towing capability, shift business, frequency of engine on/off transitions). This steadily increasing realism has, in turn, steadily increased confidence in the appropriateness of using Autonomie to make significant investment decisions. Notably, DOE uses Autonomie for analysis supporting budget priorities and plans for programs managed by its Vehicle Technologies Office (VTO). Considering the advantages of DOE/Argonne's Autonomie model, it is reasonable and appropriate to use Autonomie to estimate fuel economy levels and CO

emission rates for different combinations of technologies as applied to different types of vehicles.

Commenters have also suggested that the CAFE model's graphical user interface (GUI) facilitates others' ability to use the model quickly—and without specialized knowledge or training—and to comment accordingly.

For today's proposal, DOT has significantly expanded and refined this GUI, providing the ability to observe the model's real-time progress much more closely as it simulates year-by-year compliance with either CAFE or CO

standards.

Although the model's ability to produce realistic results is independent of the model's GUI, it is anticipated the CAFE model's GUI will facilitate stakeholders' meaningful review and comment during the comment period.

From Docket Number EPA-HQ-OAR-2015-0827, see Comment by Global Automakers, Docket ID EPA-HQ-OAR-2015-0827-9728, at 34.

The updated GUI provides a range of graphs updated in real time as the model operates. These graphs can be used to monitor fuel economy or CO

ratings of vehicles in manufacturers' fleets and to monitor year-by-year CAFE (or average CO

ratings), costs, avoided fuel outlays, and avoided CO

-related damages for specific manufacturers and/or specific fleets (

e.g.,

domestic passenger car, light truck). Because these graphs update as the model progresses, they should greatly increase users' understanding of the model's approach to considerations such as multiyear planning, payment of civil penalties, and credit use.

Beyond these general considerations, several specific related technical comments and considerations underlie the agencies' decision in this area, as discussed, where applicable, in the remainder of this Section.

Other commenters expressed a number of concerns with whether DOT's CAFE model could be used for CAA analysis. Many of these concerns focused on inputs used by the CAFE model for prior rulemaking analyses.

Because inputs are

exogenous to any model, they do not determine whether it would be reasonable and appropriate for EPA to use DOT's model for analysis. Other concerns focused on characteristics of the CAFE model that were developed to better align the model with EPCA and EISA; the model has been revised to accommodate both EPCA/EISA and CAA analysis, as explained further below. Some commenters also argued that use of any models other than ALPHA and OMEGA for CAA analysis would constitute an arbitrary and capricious delegation of EPA's decision-making authority to DOT, if DOT models are used for analysis instead. These comments were made prior to the development of the CAA analysis function in the CAFE model, and, moreover, appear to conflate the analytical tool used to inform decision-making with the action of making the decision. As explained elsewhere in this document and as made repeatedly clear over the past several rulemakings, the CAFE model neither sets standards nor dictates where and how to set standards; it simply informs as to the effects of setting different levels of standards. In this rulemaking, EPA will be making its own decisions regarding what CO

standards would be appropriate under the CAA. The CAA does not require EPA to create a specific model or use a specific model of its own creation in setting GHG standards. The fact EPA's decision may be informed by non-EPA-created models does not, in any way, constitute a delegation of its statutory power to set standards or decision-making authority.

Arguing to the contrary would suggest, for example, that EPA's decision would be invalid because it relied on EIA's Annual Energy Outlook for fuel prices rather than developing its own model for estimating future trends in fuel prices. Yet, all Federal agencies that have occasion to use forecasts of future fuel prices regularly (and appropriately) defer to EIA's expertise in this area and rely on EIA's NEMS-based analysis in the AEO, even when those same agencies are using EIA's forecasts to inform their own decision-making.

For example, EDF's recent comments (EDF at 12, Docket ID. EPA-HQ-OAR-2015-0827-9203) stated “the data that NHTSA needs to input into its model is sensitive confidential business information that is not transparent and cannot be independently verified . . .” and claimed “the

OMEGA model's focus on direct technological inputs and costs—as opposed to industry self-reported data—ensures the model more accurately characterizes the true feasibility and cost effectiveness of deploying greenhouse gas reducing technologies.” Neither statement is correct, as nothing about either the CAFE or OMEGA model either obviates or necessitates the use of CBI to develop inputs.

In recent comments (CARB at 28, Docket ID. EPA-HQ-OAR-2015-0827-9197), CARB stated “another promising technology entering the market was not even included in the NHTSA compliance modeling” and that EPA assumes a five-year redesign cycle, whereas NHTSA assumes a six to seven-year cycle.” Though presented as criticisms of the models, these comments—at least with respect to the CAFE model—actually concern model

inputs.

NHTSA did not agree with CARB about the commercialization potential of the engine technology in question (“Atkinson 2”) and applied model

inputs

accordingly. Also, rather than applying a one-size-fits-all assumption regarding redesign cadence, NHTSA developed estimates specific to each vehicle model and applied these as model

inputs.

NRDC's recent comments (NRDC at 37, Docket ID. EPA-HQ-OAR-2015-0827-9826) state EPA should not use the CAFE model because it “allows manufacturers to pay civil penalties in lieu of meeting the standards, an alternative compliance pathway currently allowed under EISA and EPCA.” While the CAFE model can simulate civil penalty payment, NRDC's comment appears to overlook the fact that this result depends on model

inputs;

the inputs can easily be specified such that the CAFE model will set aside civil penalty payment as an alternative to compliance.

“[A] federal agency may turn to an outside entity for advice and policy recommendations, provided the agency makes the final decisions itself.”

U.S. Telecom. Ass'n

FCC,

359 F.3d 554, 565-66 (D.C. Cir. 2004). To the extent commenters meant to suggest outside parties have a reliance interest in EPA using ALPHA and OMEGA to set standards, EPA does not agree a reliance interest is properly placed on an analytical methodology (as opposed to on the standards themselves). Even if it were, all parties that closely examined ALPHA and OMEGA-based analyses in the past either also simultaneously closely examined CAFE and Autonomie-based analyses in the past, or were fully capable of doing so, and thus, should face no additional difficulty now they have only one set of models and inputs/outputs to examine.

Moreover, DOT's CAFE model with inputs from DOE/Argonne's Autonomie model has produced analysis supporting rulemaking under the CAA. In 2015, EPA proposed new GHG standards for MY 2021-2027 heavy-duty pickups and vans, finalizing standards in 2016. Supporting the NPRM and final rule, EPA relied on analysis implemented by DOT using DOT's CAFE model, and DOT used inputs developed by DOE/Argonne using DOE/Argonne's Autonomie model.

The following sections provide a brief technical overview of the CAFE model, including changes NHTSA made to the model since 2012, before discussing inputs to the model and then diving more deeply into how the model works. For more information on the latter topic, see the CAFE model documentation July 2018 draft, available in the docket for this rulemaking and on NHTSA's website.

1. Brief Technical Overview of the Model

The CAFE model is designed to simulate compliance with a given set of CAFE or CO

standards for each manufacturer selling vehicles in the United States. The model begins with a representation of the current (for today's analysis, model year 2016) vehicle model offerings for each manufacturer that includes the specific engines and transmissions on each model variant, observed sales volumes, and all fuel economy improvement technology that is already present on those vehicles. From there it adds technology, in response to the standards being considered, in a way that minimizes the cost of compliance and reflects many real-world constraints faced by automobile manufacturers. After simulating compliance, the model calculates impacts of the simulated standard: technology costs, fuel savings (both in gallons and dollars), CO

reductions, social costs and benefits, and safety impacts.

Today's analysis reflects several changes made to the CAFE model since 2012, when NHTSA used the model to estimate the effects, costs, and benefits of final CAFE standards for light-duty vehicles produced during MYs 2017-2021 and augural standards for MYs 2022-2025. Key changes relevant to this analysis include the following:

• Expansion of model inputs, procedures, and outputs to accommodate technologies not included in prior analyses,

• Updated approach to estimating the combined effect of fuel-saving technologies using large scale simulation modeling,

• Modules that dynamically estimate new vehicle sales and existing vehicle scrappage in response to changes to new vehicle prices that result from manufacturers' compliance actions,

• A safety module that estimates the changes in light-duty traffic fatalities resulting from changes to vehicle exposure, vehicle retirement rates, and reductions in vehicle mass to improve fuel economy,

• Disaggregation of each manufacturer's fleet into separate “domestic” passenger car and “import” passenger car fleets to better represent the statutory requirements of the CAFE program,

• Changes to the algorithm used to apply technologies, enabling more explicit accounting of shared vehicle components (engines, transmissions, platforms) and “inheritance” of major technology within or across powertrains and/or platforms over time,

• An industry labor quantity module, which estimates net changes in the amount of U.S. automobile labor for dealerships, Tier 1 and 2 supplier companies, and original equipment manufacturers (OEMs),

• Cost estimation of batteries for electrification technologies incorporates an updated version of Argonne National Laboratory's BatPAC (battery) model for hybrid electric vehicles (HEVs), plug-in

hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), consistent with how we estimate effectiveness for those values,

• Expanded accounting for CAFE credits carried over from years prior to those included in the analysis (a.k.a. “banked” credits) and application to future CAFE deficits to better evaluate anticipated manufacturer responses to proposed standards,

While EPCA/EISA precludes NHTSA from considering manufacturers' potential use of credits in model years for which the agency is establishing new standards, NHTSA considers credit use in earlier model years. Also, as allowed by NEPA, NHTSA's EISs present results of analysis that considers manufacturers' potential use of credits in all model years, including those for which the agency is establishing new standards.

• The ability to represent a manufacturer's preference for fine payment (rather than achieving full compliance exclusively through fuel economy improvements) on a year-by-year basis,

• Year-by-year simulation of how manufacturers could comply with EPA's CO

standards, including

○ Calculation of vehicle models' CO

emission rates before and after application of fuel-saving (and, therefore, CO

-reducing) technologies,

○ Calculation of manufacturers' fleet average CO

emission rates,

○ Calculation of manufacturers' fleet average CO

emission rates under attribute-based CO

standards,

○ Accounting for adjustments to average CO

emission rates reflecting reduction of air conditioner refrigerant leakage,

○ Accounting for the treatment of alternative fuel vehicles for CO

compliance,

○ Accounting for production “multipliers” for PHEVs, BEVs, compressed natural gas (CNG) vehicles, and fuel cell vehicles (FCVs),

○ Accounting for transfer of CO

credits between regulated fleets,

○ Accounting for carried-forward (a.k.a. “banked”) CO

credits, including credits from model years earlier than modeled explicitly.

2. Sensitivity Cases and Why We Examine Them

Today's notice presents estimated impacts of the proposed CAFE and CO

standards defining the proposals, relative to a baseline “no action” regulatory alternative under which the standards announced in 2012 remain in place through MY 2025 and continue unchanged thereafter. Relative to this same baseline, today's notice also presents analysis estimating impacts under a range of other regulatory alternatives the agencies are considering. All but one involve different standards, and three involve a gradual discontinuation of CAFE and GHG adjustments reflecting the application of technologies that improve air conditioner efficiency or, in other ways, improve fuel economy under conditions not represented by long-standing fuel economy test procedures. Like the baseline no action alternative, all of these alternatives are more stringent than the preferred alternative. Section III and Section IV describe the preferred and other regulatory alternatives, respectively.

These alternatives were examined because they will be considered as options for the final rule. The agencies seek comment on these alternatives, seek any relevant data and information, and will review responses. That review could lead to the selection of one of the other regulatory alternatives for the final rule or some combination of the other regulatory alternatives (

e.g.,

combining passenger cars standards from one alternative with light truck standards from a different alternative).

Because outputs depend on inputs (

e.g.,

the results of the analysis in terms of quantities and kinds of technologies required to meet different levels of standards, and the societal and private benefits associated with manufacturers meeting different levels of standards depend on input data, estimates, and assumptions), the analysis also explores the sensitivity of results to many of these inputs. For example, the net benefits of any regulatory alternative will depend strongly on fuel prices well beyond 2025. Fuel prices a decade and more from now are not knowable with certainty. The sensitivity analysis involves repeating the “central” or “reference case” analysis under alternative inputs (

e.g.,

higher fuel prices in one case, lower fuel prices in another case), and exploring changes in analytical results, which is discussed further in the agencies' Preliminary Regulatory Impact Analysis (PRIA) accompanying today's notice.

B. Developing the Analysis Fleet for Assessing Costs, Benefits, and Effects of Alternative CAFE Standards

The following sections describe what the analysis fleet is and why it is used, how it was developed for this NPRM, and the analysis-fleet-related topics on which comment is sought.

1. Purpose of Developing and Using an Analysis Fleet

The starting point for the evaluation of the potential feasibility of different stringency levels for future CAFE and CO

standards is the analysis fleet, which is a snapshot of the recent vehicle market. The analysis fleet provides a snapshot to project what vehicles will exist in future model years covered by the standards and what technologies they will have, and then evaluate what additional technologies can feasibly be applied to those vehicles in a cost-effective way to raise their fuel economy and lower their CO

emission levels.

The CAFE model does not generate compliance paths a manufacturer should, must, or will deploy. It is intended as a tool to demonstrate a compliance pathway a manufacturer

could

choose. It is almost certain all manufacturers will make compliance choices differing from those projected in the CAFE model.

Part of reflecting what vehicles will exist in future model years is knowing which vehicles are produced by which manufacturers, how many of each are sold, and whether they are passenger cars or light trucks. This is important because it improves our understanding of the overall impacts of different levels of CAFE and CO

standards; overall impacts result from industry's response to standards, and industry's response is made up of individual manufacturer responses to the standards in light of the overall market and their individual assessment of consumer acceptance. Having an accurate picture of manufacturers' existing fleets (and the vehicle models in them) that will be subject to future standards helps us better understand individual manufacturer responses to those future standards in addition to potential changes in those standards.

Another part of reflecting what vehicles will exist in future model years is knowing what technologies are already on those vehicles. Accounting for technologies already being on vehicles helps avoid “double-counting” the value of those technologies, by assuming they are still available to be applied to improve fuel economy and reduce CO

emissions. It also promotes more realistic determinations of what additional technologies can feasibly be applied to those vehicles: if a manufacturer has already started down a technological path to fuel economy or performance improvements, we do not assume it will completely abandon that path because that would be unrealistic and would not accurately represent manufacturer responses to standards. Each vehicle model (and configurations of each model) in the analysis fleet, therefore, has a comprehensive list of its technologies, which is important because different configurations may have different technologies applied to

them.

Additionally, the analysis accounts for platforms within manufacturers' fleets, recognizing platforms will share technologies, and the vehicles that make up that platform should receive (or not receive) additional technological improvements together. The specific engineering characteristics of each model/configuration are available in the aforementioned input file.

For the regulatory alternatives considered in today's proposal, estimates of rates at which various technologies might be expected to penetrate manufacturers' fleets (and the overall market) are summarized below in Sections VI and VII, and in Chapter 6 of the accompanying PRIA and in detailed model output files available at NHTSA's website. A solid characterization of a recent model year as an analytical starting point helps to realistically estimate ways manufacturers could potentially respond to different levels of standards, and the modeling strives to realistically simulate how manufacturers could progress from that starting point. Nevertheless, manufacturers can respond in many ways beyond those represented in the analysis (

e.g.,

applying other technologies, shifting production volumes, changing vehicle footprint), such that it is impossible to predict with any certainty exactly how each manufacturer

will

respond. Therefore, recent trends in manufacturer performance and technology application, although of interest in terms of understanding manufacturers' current compliance positions, are not in themselves innately indicative of future potential.

Considering each vehicle model/configuration also improves the ability to consider the differential impacts of different levels of potential standards on different manufacturers, since all vehicle model/configurations “start” at different places, in terms of the technologies they already have and how those technologies are used.

Available with the model and other input files supporting today's announcement at

https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system

Yet, another part of reflecting what vehicles will exist in future model years is having reasonable real-world assumptions about when certain technologies can be applied to vehicles. Each vehicle model/configuration in the analysis fleet also has information about its redesign schedule,

i.e.,

the last year it was redesigned and when the agencies expect it to be redesigned again. Redesign schedules are a key part of manufacturers' business plans, as each new product can cost more than $1.0B and involve a significant portion of a manufacturer's scarce research, development, and manufacturing and equipment budgets and resources.

Manufacturers have repeatedly told the agencies that sustainable business plans require careful management of resources and capital spending, and that the length of time each product remains in production is crucial to recouping the upfront product development and plant/equipment costs, as well as the capital needed to fund the development and manufacturing equipment needed for future products. Because the production volume of any given vehicle model varies within a manufacturer's product line and also varies among different manufacturers, redesign schedules typically vary for each model and manufacturer. Some (relatively few) technological improvements are small enough they can be applied in any model year; others are major enough they can only be cost-effectively applied at a vehicle redesign, when many other things about the vehicle are already changing. Ensuring the CAFE model makes technological improvements to vehicles only when it is feasible to do so also helps the analysis better represent manufacturer responses to different levels of standards.

Shea, T.

Why Does It Cost So Much For Automakers To Develop New Models?,

Autoblog (Jul. 27, 2010),

https://www.autoblog.com/2010/07/27/why-does-it-cost-so-much-for-automakers-to-develop-new-models/

A final important aspect of reflecting what vehicles will exist in future model years and potential manufacturer responses to standards is estimating how future sales might change in response to different potential standards. If potential future standards appear likely to have major effects in terms of shifting production from cars to trucks (or vice versa), or in terms of shifting sales between manufacturers or groups of manufacturers, that is important for the agencies to consider. For previous analyses, the CAFE model used a static forecast contained in the analysis fleet input file, which specified changes in production volumes over time for each vehicle model/configuration. This approach yielded results that, in terms of production volumes, did not change between scenarios or with changes in important model inputs. For example, very stringent standards with very high technology costs would result in the same estimated production volumes as less stringent standards with very low technology costs.

New for today's proposal, the CAFE model begins with the first-year production volumes (

i.e.,

MY 2016 for today's analysis) and adjusts ensuing sales mix year by year (between cars and trucks, and between manufacturers) endogenously as part of the analysis, rather than using external forecasts of future car/truck split and future manufacturer sales volumes. This leads the model to produce different estimates of future production volumes under different standards and in response to different inputs, reflecting the expectation that regulatory standards and other external factors will, in fact, impact the market.

The input file for the CAFE model characterizing the analysis fleet

includes a large amount of data about vehicle models/configurations, their technological characteristics, the manufacturers and fleets to which they belong, and initial prices and production volumes which provide the starting points for projection (by the sales model) to ensuing model years. The following sections discuss aspects of how the analysis fleet was built for this proposal and seek comment on those topics.

Available with the model and other input files supporting today's announcement at

https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system

2. Source Data for Building the Analysis Fleet

The source data for the vehicle models/configurations in the analysis fleet and their technologies is a central input for the analysis. The sections below discuss pros and cons of different potential sources and what was used for this proposal.

(a) Use of Confidential Business Information Versus Publicly-Releasable Sources

Since 2001, CAFE analysis has used either confidential, forward-estimating product plans from manufacturers, or publicly available data on vehicles already sold, as a starting point for determining what technologies can be applied to what vehicles in response to potential different levels of standards. These two sources present a tradeoff. Confidential product plans comprehensively represent what vehicles a manufacturer expects to produce in coming years, accounting for plans to introduce new vehicles and fuel-saving technologies and, for example, plans to discontinue other vehicles and even brands. This information can be very thorough and can improve the accuracy of the analysis, but for competitive reasons, most of this information must be redacted prior to publication with rulemaking documentation. This makes it difficult for public commenters to reproduce the analysis for themselves as

they develop their comments. Some non-industry commenters have also expressed concern manufacturers would have an incentive in the submitted plans to (deliberately or not) underestimate their future fuel economy capabilities and overstate their expectations about, for example, the levels of performance of future vehicle models in order to affect the analysis. Since 2010, EPA and NHTSA have based analysis fleets almost exclusively on information from commercial and public sources, starting with CAFE compliance data and adding information from other sources.

An analysis fleet based primarily on public sources can be released to the public, solving the issue of commenters being unable to reproduce the overall analysis when they want to. However, industry commenters have argued such an analysis fleet cannot accurately reflect manufacturers actual plans to apply fuel-saving technologies (

e.g.,

manufacturers may apply turbocharging to improve not just fuel economy, but also to improve vehicle performance) or manufacturers' plans to change product offerings by introducing some vehicles and brands and discontinuing other vehicles and brands, precisely because that information is typically confidential business information (CBI). A fully-publicly-releasable analysis fleet holds vehicle characteristics unchanged over time and arguably lacks some level of accuracy when projected into the future. For example, over time, manufacturers introduce new products and even entire brands. On the other hand, plans announced in press releases do not always ultimately bear out, nor do commercially-available third-party forecasts. Assumptions could be made about these issues to improve the accuracy of a publicly-releasable analysis fleet, but concerns include that this information would either be largely incorrect, or information would be released that manufacturers would consider CBI. We seek comment on how to address this issue going forward, recognizing the competing interests involved and also recognizing typical timeframes for CAFE and CO

standards rulemakings.

(b) Use of MY 2016 CAFE Compliance Data Versus Other Starting Points

Based on the assumption that a publicly-available analysis fleet continues to be desirable, for this NPRM, an analysis fleet was constructed starting with CAFE compliance information from manufacturers.

Information from MY 2016 was chosen as the foundation for today's analysis fleet because, at the time the rulemaking analysis was initiated, the 2016 fleet represented the most up-to-date information available in terms of individual vehicle models and configurations, production technology levels, and production volumes. If MY 2017 data had been used while this analysis was being developed, the agencies would have needed to use product planning information that could not be made available to the public until a later date.

emissions rates are directly related to fuel economy levels, and the CAFE model uses the latter to calculate the former.

The analysis fleet was initially developed with 2016 mid-model year compliance data because final compliance data was not available at that time, and the timing provided manufacturers the opportunity to review and comment on the characterization of their vehicles in the fleet. With a view toward developing an accurate characterization of the 2016 fleet to serve as an analytical starting point, corrections and updates to mid-year data (

e.g.,

to production estimates) were sought, in addition to corroboration or correction of technical information obtained from commercial and other sources (to the extent that information was not included in compliance data), although future product planning information from manufacturers (

e.g.,

future product offerings, products to be discontinued) was not requested, as most manufacturers view such information as CBI. Manufacturers offered a range of corrections to indicate engineering characteristics (

e.g.,

footprint, curb weight, transmission type) of specific vehicle model/configurations, as well as updates to fuel economy and production volume estimates in mid-year reporting. After following up on a case-by-case basis to investigate significant differences, the analysis fleet was updated.

Sales, footprint, and fuel economy values with final compliance data were also updated if that data was available. In a few cases, final production and fuel economy values may be slightly different for specific model year 2016 vehicle models and configurations than are indicated in today's analysis; however, other vehicle characteristics (

e.g.,

footprint, curb weight, technology content) important to the analysis should be accurate. While some commenters have, in the past, raised concerns that non-final CAFE compliance data is subject to change, the potential for change is likely not significant enough to merit using final data from an earlier model year reflecting a more outdated fleet. Moreover, even ostensibly final CAFE compliance data can sometimes be subject to later revision (

e.g.,

if errors in fuel economy tests are discovered), and the purpose of today's analysis is not to support enforcement actions but rather to provide a realistic assessment of manufacturers' potential responses to future standards.

Manufacturers integrated a significant amount of new technology in the MY 2016 fleet, and this was especially true for newly-designed vehicles launched in MY 2016. While subsequent fleets will involve even further application of technology, using available data for MY 2016 provides the most realistic detailed foundation for analysis that can be made available publicly in full detail, allowing stakeholders to independently reproduce the analysis presented in this proposal. Insofar as future product offerings are likely to be more similar to vehicles produced in 2016 than to vehicles produced in earlier model years, using available data regarding the 2016 model year provides the most realistic, publicly releasable foundation for constructing a forecast of the future vehicle market for this proposal.

A number of comments to the Draft TAR, EPA's Proposed Determination, and EPA's 2017 Request for Comment

stated that the most up-to-date analysis fleet possible should be used, because a more up-to-date analysis fleet will better capture how manufacturers apply technology and will account better for vehicle model/configuration introductions and deletions.

On the other hand, some commenters suggested that because manufacturers continue improving vehicle performance and utility over time, an older analysis fleet should be used to estimate how the fleet could have evolved had manufacturers applied all technological potential to

fuel economy rather than continuing to improve vehicle performance and utility.

Because manufacturers change and improve product offerings over time, conducting analysis with an older analysis fleet (or with a fleet using fuel economy levels and CO

emissions rates that have been adjusted to reflect an assumed return to levels of performance and utility typical of some past model year) would miss this real-world trend. While such an analysis could demonstrate what industry

could

do if, for example, manufacturers devoted all technological improvements toward raising fuel economy and reducing CO

emissions (and if consumers decided to purchase these vehicles), we do not believe it would be consistent with a transparent examination of what effects different levels of standards would have on individual manufacturers and the fleet as a whole.

82 FR 39551 (Aug. 21, 2017).

For example, in 2016 comments to dockets EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068, the Alliance of Automobile Manufacturers commented that “the Alliance supports the use of the most recent data available in establishing the baseline fleet, and therefore believes that NHTSA's selection [of, at the time, model year 2015] was more appropriate for the Draft TAR.” (Alliance at 82, Docket ID. EPA-HQ-OAR-2015-0827-4089) Global Automakers commented that “a one-year difference constitutes a technology change-over for up to 20% of a manufacturer's fleet. It was also generally understood by industry and the agencies that several new, and potentially significant, technologies would be implemented in MY 2015. The use of an older, outdated baseline can have significant impacts on the modeling of subsequent Reference Case and Control Case technologies.” (Global Automakers at A-10, Docket ID. EPA-HQ-OAR-2015-0827-4009).

For example, in 2016 comments to dockets EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068, UCS stated “in modeling technology effectiveness and use, the agencies should use 2010 levels of performance as the baseline.” (UCS at 4, Docket ID. EPA-HQ-OAR-2015-0827-4016).

Generally, all else being equal, using a newer analysis fleet will produce more realistic estimates of impacts of potential new standards than using an outdated analysis fleet. However, among relatively current options, a balance must be struck between, on one hand, inputs' freshness, and on the other, inputs' completeness and accuracy.

During assembly of the inputs for today's analysis, final compliance data was available for the MY 2015 model year but not in a few cases for MY 2016. However, between mid-year compliance information and manufacturers' specific updates discussed above, a robust and detailed characterization of the MY 2016 fleet was developed. However, while information continued to develop regarding the MY 2017 and, to a lesser extent MY 2018 and even MY 2019 fleets, this information was—even in mid-2017—too incomplete and inconsistent to be assembled with confidence into an analysis fleet for modeling supporting deliberations regarding today's proposal.

Comments provided through a recent peer review of the CAFE model recognize the need for this balance. For example, referring to NHTSA's 2016 analysis documented in the draft TAR, one of the peer reviewers commented as follows: “The NHTSA decision to use MY 2015 data is wise. In the TAR they point out that a MY 2016 foundation would require the use of confidential data, which is less desirable. Clearly they would also have a qualitative vision of the MY 2016 landscape while employing MY 2015 as a foundation. Although MY 2015 data may still be subject to minor revision, this is unlikely to impact the predictive ability of the model . . . A more complex alternative approach might be to employ some 2016 changes in technology, and attempt a blend of MY 2015 and MY 2016, while relying of estimation gained from only MY 2015 for sales. This approach may add some relevancy in terms of technology, but might introduce substantial error in terms of sales.”

In short, the 2016 fleet was, in fact, the most up-to-date fleet that could be produced for this NPRM. Moreover, during late 2016 and early 2017, nearly all manufacturers provided comments on the characterization of their vehicles in the analysis fleet, and many provided specific feedback about their vehicles, including aerodynamic drag coefficients, tire rolling resistance values, transmission efficiencies, and other information used in the analysis. NHTSA worked with manufacturers to clarify and correct some information and integrated the information into a single input file for use in the CAFE model. Accordingly, the current analysis fleet is reasonable to use for purposes of the NPRM analysis.

As always, however, ways to improve the analysis fleet used for subsequent modeling to evaluate potential new CAFE and CO

standards will undergo continuous consideration. As described above, the compliance data is only the starting point for developing the analysis fleet; much additional information comes directly from manufacturers (such as details about technologies, platforms, engines, transmissions, and other vehicle information, that may not be present in compliance data), and other information must come from commercial and public sources (for example, fleet-wide information like market share, because individual manufacturers do not provide this kind of information). If newer compliance data (

i.e.,

MY 2017) becomes available and can be analyzed during the pendency of this rulemaking, and if all of the other necessary steps can be performed, the analysis fleet will be updated, as feasible, and made publicly available. The agencies seek comment on the option used today and any other options, as well as on the tradeoffs between, on one hand, fidelity with manufacturers' actual plans and, on the other, the ability to make detailed analysis inputs and outputs publicly available.

As explained above, the analysis fleet is defined not only by the vehicle models/configurations it contains but also by the technologies on those vehicles. Each vehicle model/configuration in the analysis fleet has an associated list of observed technologies and equipment that can improve fuel economy and reduce CO

emissions.

With a portfolio of descriptive technologies arranged by manufacturer and model, the analysis fleet can be summarized and project how vehicles in that fleet may improve over time via the application of additional technology.

These technologies are generally grouped into the following categories: Vehicle technologies include mass reduction, aerodynamic drag reduction, low rolling resistance tires, and others. Engine technologies include engine attributes describing fuel type, engine aspiration, valvetrain configuration, compression ratio, number of cylinders, size of displacement, and others. Transmission technologies include different transmission arrangements like manual, 6-speed automatic, 8-speed automatic, continuously variable transmission, and dual-clutch transmissions. Hybrid and electric powertrains may complement traditional engine and transmission designs or replace them entirely.

In many cases, vehicle technology is clearly observable from the 2016 compliance data (

e.g.,

compliance data indicates clearly which vehicles have turbochargers and which have continuously variable transmissions), but in some cases technology levels are less observable. For the latter, like levels of mass reduction, the analysis categorized levels of technology already used in a given vehicle. Similarly, engineering judgment was used to determine if higher mass reduction levels may be used practicably and safely in a given vehicle.

Either in mid-year compliance data for MY 2016 or, separately and at the agencies' invitation (as discussed above), most manufacturers identified most of the technology already present in each of their MY 2016 vehicle model/configurations. This information was not as complete for all manufacturers' products as needed for today's analysis, so in some cases, information was supplemented with publicly available data, typically from manufacturer media sites. In limited cases, manufacturers did not supply information, and information from commercial and publicly available sources was used.

(d) Mapping Technology Content of 2016 Fleet to Argonne Technology Effectiveness Simulation Work

While each vehicle model/configuration in the analysis fleet has its list of observed technologies and equipment, the ways in which manufacturers apply technologies and equipment do not always coincide perfectly with how the analysis characterizes the various technologies that improve fuel economy and reduce CO

emissions. To improve how the observed vehicle fleet “fits into” the analysis, each vehicle model/configuration is “mapped” to the full-

vehicle simulation modeling

by Argonne National Laboratory that is used to estimate the effectiveness of the fuel economy-improving/CO

emissions-reducing technologies considered. Argonne produces full-vehicle simulation modeling for many combinations of technologies, on many types of vehicles, but it did not simulate literally every single vehicle model/configuration in the analysis fleet because it would be impractical to assemble the requisite detailed information—much of which would likely only be provided on a confidential basis—specific to each vehicle model/configuration and because the scale of the simulation effort would correspondingly increase by at least two orders of magnitude. Instead, Argonne simulated 10 different vehicle types, corresponding to the “technology classes” generally used in CAFE analysis over the past several rulemakings (

e.g.,

small car, small performance car, pickup truck, etc.). Each of those 10 different vehicle types was assigned a set of “baseline characteristics,” to which Argonne added combinations of fuel-saving technologies and then ran simulations to determine the fuel economy achieved when applying each combination of technologies to that vehicle type given its baseline characteristics. These inputs, discussed at greater length in Sections II.D and II.G, provide the basis for the CAFE model's estimation of fuel economy levels and CO

emission rates.

Full-vehicle simulation modeling uses software and physics models to compute and estimate energy use of a vehicle during explicit driving conditions. Section II.D below contains more information on the Argonne work for this analysis.

In the analysis fleet, inputs assign each specific vehicle model/configuration to a technology class, and once there, map to the simulation within that technology class most closely matching the combination of observed technologies and equipment on that vehicle.

This mapping to a specific simulation result most closely representing a given vehicle model/configuration's initial technology “state” enables the CAFE model to estimate the same vehicle model/configuration's fuel economy after application of some other combination of technologies, leading to an alternative technology state.

Mapping vehicle model/configurations in the analysis fleet to Argonne simulations was generally straightforward, but occasionally the mapping was complicated by factors like a vehicle model/configuration being a great match for simulations within more than one technology class (in which case, the model/configuration was assigned to the technology class that it best matched), or when technologies on the model/configuration were difficult to observe directly (like friction reduction or parasitic loss characteristics of a transmission, in which case the agencies relied on manufacturer-reported data or CBI to help map the vehicle to a simulation).

BILLING CODE 4910-59-P

EP24AU18.009

EP24AU18.010

EP24AU18.011

BILLING CODE 4910-59-C

(e) Shared Vehicle Platforms, Engines, and Transmissions

Another aspect of characterizing vehicle model/configurations in the analysis fleet is based on whether they share a “platform” with other vehicle model/configurations. A “platform” refers to engineered underpinnings shared on several differentiated products. Manufacturers share and standardize components, systems, tooling, and assembly processes within their products (and occasionally with the products of another manufacturer) to cost-effectively maintain vibrant portfolios.

The concept of platform sharing has evolved with time. Years ago, manufacturers rebadged vehicles and offered luxury options only on premium nameplates (and manufacturers shared some vehicle platforms in limited cases). Today, manufacturers share parts across highly differentiated vehicles with different body styles, sizes, and capabilities that may share the same platform. For instance, the Honda Civic and Honda CR-V share many parts and are built on the same platform. Engineers design chassis platforms with the ability to vary wheelbase, ride height, and even driveline configuration. Assembly lines can produce hatchbacks and sedans to cost-effectively utilize manufacturing capacity and respond to shifts in market demand. Engines made on the same line may power small cars or mid-size sport utility vehicles. Additionally, although the agencies' analysis, like past CAFE analyses, considers vehicles produced for sale in the U.S., the agency notes these platforms are not constrained to vehicle models built for sale in the United States; many manufacturers have developed, and use, global platforms, and the total number of platforms is decreasing across the industry. Several automakers (for example, General Motors and Ford) either plan to, or already have, reduced their number of platforms to less than 10 and account for the overwhelming majority of their production volumes on that small number of platforms.

Vehicle model/configurations derived from the same platform are so identified in the analysis fleet. Many manufacturers' use of vehicle platforms is well documented in the public record and widely recognized among the vehicle engineering community. Engineering knowledge, information from trade publications, and feedback from manufacturers and suppliers was also used to assign vehicle platforms in the analysis fleet.

When the CAFE model is deciding where and how to add technology to vehicles, if one vehicle on the platform receives new technology, other vehicles on the platform also receive the technology as part of their next major redesign or refresh.

Similar to vehicle platforms, manufacturers create engines that share parts.

One engine family may appear on many vehicles on a platform, and changes to that engine may or may not carry through to all the vehicles. Some engines are shared across a range of different vehicle platforms. Vehicle model/configurations in the analysis fleet that share engines belonging to the same platform are also identified as such.

The CAFE model assigns mass reduction technology at a platform level, but many other technologies may be assigned and shared at a vehicle nameplate or vehicle model level.

For instance, manufacturers may use different piston strokes on a common engine block or bore out common engine block castings with different diameters to create engines with an array of displacements. Head assemblies for different displacement engines may share many components and manufacturing processes across the engine family. Manufacturers may finish crankshafts with the same tools, to similar tolerances. Engines on the same architecture may share pistons, connecting rods, and the same engine architecture may include both six and eight cylinder engines.

It is important to note that manufacturers define common engines differently. Some manufacturers consider engines as “common” if the engines shared an architecture, components, or manufacturing processes. Other manufacturers take a narrower definition, and only assume “common” engines if the parts in the engine assembly are the same. In some cases, manufacturers designate each engine in each application as a unique powertrain.

Engine families for each manufacturer were tabulated and assigned

based on data-driven criteria. If engines shared a common cylinder count and configuration, displacement, valvetrain, and fuel type, those engines may have been considered together. Additionally, if the compression ratio, horsepower, and displacement of engines were only slightly different, those engines were considered to be the same for the purposes of redesign and sharing. Vehicles in the analysis fleet with the same engine family will therefore adopt engine technology in a coordinated fashion.

By grouping engines together, the CAFE model controls future engine families to retain reasonable powertrain complexity.

For instance, a manufacturer may have listed two engines for a pair that share designs for the engine block, the crank shaft, and the head because the accessory drive components, oil pans, and engine calibrations differ between the two. In practice, many engines share parts, tooling, and assembly resources, and manufacturers often coordinate design updates between two similar engines.

Engine family is referred to in the analysis as an “engine code.”

Specifically, if such vehicles have different design schedules (

i.e.,

refresh and redesign schedules), and a subset of vehicles using a given engine add engine technologies in the course of a redesign or refresh that occurs in an early model year (

e.g.,

2018), other vehicles using the same engine “inherit” these technologies at the soonest ensuing refresh or redesign. This is consistent with a view that, over time, most manufacturers are likely to find it more practicable to shift production to a new version of an engine than to indefinitely continue production of both the new engine and a “legacy” engine.

This does mean, however, that for manufacturers that submitted highly atomized engine and transmission portfolios, there is a practical cap on powertrain complexity and the ability of the manufacturer to optimize the displacement of (a.k.a. “right size”) engines perfectly for each vehicle configuration.

Like with engines, manufacturers often use transmissions that are the same or similar on multiple vehicles.

To reflect this reality, shared transmissions were considered for manufacturers as appropriate. To define common transmissions, the agencies considered transmission type (manual, automatic, dual-clutch, continuously variable), number of gears, and vehicle architecture (front-wheel-drive, rear-wheel-drive, all-wheel-drive based on a front-wheel-drive platform, or all-wheel-drive based on a rear-wheel-drive platform). If vehicles shared these attributes, these transmissions were grouped for the analysis. Vehicles in the analysis fleet with the same transmission configuration

will adopt transmission technology together, as described above.

Manufacturers may produce transmissions that have nominally different machining to castings, or manufacturers may produce transmissions that are internally identical, except for final output gear ratio. In some cases, manufacturers sub-contract with suppliers that deliver whole transmissions. In other cases, manufacturers form joint-ventures to develop shared transmissions, and these transmission platforms may be offered in many vehicles across manufacturers. Manufacturers use supplier and joint-venture transmissions to a greater extent than engines.

Transmission configurations are referred to in the analysis as “transmission codes.”

Similar to the inheritance approach outlined for engines, if one vehicle application of a shared transmission family upgraded the transmission, other vehicle applications also upgraded the transmission at the next refresh or redesign year.

Having all vehicles that share a platform (or engines that are part of a family) adopt fuel economy-improving/CO

emissions-reducing technologies together, subject to refresh/redesign constraints, reflects the real-world considerations described above but also overlooks some decisions manufacturers might make in the real world in response to market pull, meaning that even though the analysis fleet is incredibly complex, it is also over-simplified in some respects compared to the real world. For example, the CAFE model does not currently attempt to simulate the potential for a manufacturer to shift the application of technologies to improve performance rather than fuel economy. Therefore, the model's representation of the “inheritance” of technology can lead to estimates a manufacturer might eventually exceed fuel economy

standards as technology continues to propagate across shared platforms and engines. In the past, there were some examples of extended periods during which some manufacturers exceeded one or both of the CAFE and/or GHG standards, but in plenty of other examples, manufacturers chose to introduce (or even reintroduce) technological complexity into their vehicle lineups in response to buyer preferences. Going forward, and recognizing the recent trend for consolidating platforms, it seems likely manufacturers will be more likely to choose efficiency over complexity in this regard; therefore, the potential should be lower that today's analysis turns out to be over-simplified compared to the real world.

Options will be considered to further refine the representation of sharing and inheritance of technology, possibly including model revisions to account for tradeoffs between fuel economy and performance when applying technology. Please provide comments on the sharing and inheritance-related aspects of the analysis fleet and the CAFE model along with information that would support refinement of the current approach or development and implementation of alternative approaches.

(f) Estimated Product Design Cycles

Another aspect of characterizing vehicle model/configurations in the analysis fleet is based on when they can next be refreshed or redesigned. Redesign schedules play an important role in determining when new technologies may be applied. Many technologies that improve fuel economy and reduce CO

emissions may be difficult to incorporate without a major product redesign. Therefore, each vehicle model in the analysis fleet has an associated redesign schedule, and the CAFE model uses that schedule to restrict significant advances in some technologies (like major mass reduction) to redesign years, while allowing manufacturers to include minor advances (such as improved tire rolling resistance) during a vehicle “refresh,” or a smaller update made to a vehicle, which can happen between redesigns. In addition to refresh and redesign schedules associated with vehicle model/configurations, vehicles that share a platform subsequently have platform-wide refresh and redesign schedules for mass reduction technologies.

To develop the refresh/redesign cycles used for the MY 2016 vehicles in the analysis fleet, information from commercially available sources was used to project redesign cycles through MY 2022, as for NHTSA's analysis for the Draft TAR published in 2016.

Commercially available sources' estimates through MY 2022 are generally supported by detailed consideration of public announcements plus related intelligence from suppliers and other sources, and recognize that uncertainty increases considerably as the forecasting horizon is extended. For MYs 2023-2035, in recognition of that uncertainty, redesign schedules were extended considering past pacing for each product, estimated schedules through MY 2022, and schedules for other products in the same technology classes. As mentioned above, potentially confidential forward-looking information was not requested from manufacturers; nevertheless, all manufacturers had an opportunity to review the estimates of product-specific redesign schedules, a few manufacturers provided related forecasts and, for the most part, that information corroborated the estimates.

In some cases, data from commercially available sources was found to be incomplete or inconsistent with other available information. For instance, commercially available sources identified some newly imported vehicles as new platforms, but the international platform was midway through the product lifecycle. While new to the U.S. market, treating these vehicles as new entrants would have resulted in artificially short redesign cycles if carried forward, in some cases. Similarly, commercially available sources labeled some product refreshes as redesigns, and vice versa. In these limited cases, the data was revised to be consistent with other available information or typical redesign and refresh schedules, for the purpose of the CAFE modeling. In these limited cases, the forecast time between redesigns and refreshes was updated to match the observed past product timing.

Some commenters suggested supplanting these estimated redesign schedules with estimates applying faster cycles (

e.g.,

four to five years), and this approach was considered for the analysis.

Some manufacturers tend to operate with faster redesign cycles and may continue to do so, and manufacturers tend to redesign some products more frequently than others. However, especially considering that information presented by manufacturers largely supports estimates discussed above, applying a “one size fits all” acceleration of redesign cycles would likely not improve the analysis; instead, doing so would likely reduce consistency with the real world, especially for light trucks. Moreover, if some manufacturers accelerate redesigns in response to new standards, doing so would likely involve costs (greater levels of stranded capital, reduced opportunity to benefit from “learning”-related cost reductions) greater than reflected in other inputs to the analysis. However, a wider range of technologies can practicably be applied during mid-cycle “freshenings” than has been represented by past analyses, and this part of the analysis has been expanded, as discussed below in Section II.D.

Also, in the sensitivity analysis supporting today's proposal and presented in Chapter 13 of the PRIA, one case involving faster redesign schedules and one involving slower redesign schedules has been analyzed.

In response to the EPA's August 21, 2017, Request for Comments (docket numbers EPA-HQ-OAR-2015-0827 and NHTSA-2016-0068), see,

e.g.,

CARB at 28 (Docket ID. EPA-HQ-OAR-2015-0827-9197), EDF at 12 (Docket ID. EPA-HQ-OAR-2015-0827-9203), and NRDC, et. al. at 29-33 (Docket ID. EPA-HQ-OAR-2015-0827-9826).

NRDC,

et al.

, at 32.

Manufacturers use diverse strategies with respect to when, and how often they update vehicle designs. While most vehicles have been redesigned sometime in the last five years, many vehicles have not. In particular, vehicles with lower annual sales volumes tend to be redesigned less frequently, perhaps giving manufacturers more time to amortize the investment needed to bring the product to market. In some cases, manufacturers continue to produce and sell vehicles designed more than a decade ago.

EP24AU18.012

BILLING CODE 4910-59-P

Each manufacturer may use different strategies throughout their product portfolio, and a component of each strategy may include the timing of refresh and redesign cycles. Table II-3 below summarizes the average time between redesigns, by manufacturer, by vehicle technology class.

Dashes mean the manufacturer has no volume in that vehicle technology class in the MY 2016 analysis fleet. Across the industry, manufacturers average 6.5 years between product redesigns.

Technology class, or tech class, refers to a group of fuel-economy simulations of similar vehicles. As explained, each vehicle is assigned to a representative simulation to estimate technology effectiveness for purposes of the analysis.

EP24AU18.013

There are a few notable observations from this table. Pick-up trucks have much longer redesign schedules (7.8 years on average) than small cars (5.5 years on average). Some manufacturers redesign vehicles often (every 5.2 years in the case of Hyundai), while other manufacturers redesign vehicles less often (FCA waits on average 8.6 years between vehicle redesigns). Across the industry, light-duty vehicle designs last for about 6.5 years.

Even if two manufacturers have similar redesign cadence, the model years in which the redesigns occur may still be different and dependent on where each of the manufacturer's products are in their life cycle.

Table II-4 summarizes the average age of manufacturers' offering by vehicle technology class. A value of “0.0” means that every vehicle for a manufacturer in that vehicle technology class, represented in the MY 2016 analysis fleet was new in MY 2016. Across the industry, manufacturers redesigned MY 2016 vehicles an average of 3.2 years earlier.

EP24AU18.014

BILLING CODE 4910-59-C

Based on historical observations and refresh/redesign schedule forecasts, careful consideration to redesign cycles for each manufacturer and each vehicle is important. Simply assuming every vehicle is redesigned by 2021 and by 2025 is not appropriate, as this would misrepresent both the likely timing of redesigns and the likely time between redesigns in most cases.

C. Development of Footprint-Based Curve Shapes

As in the past four CAFE rulemakings, the most recent two of which included related standards for CO

emissions, NHTSA and EPA are proposing to set attribute-based CAFE standards that are defined by a mathematical function of vehicle footprint, which has observable correlation with fuel economy and vehicle emissions. EPCA, as amended by EISA, expressly requires that CAFE standards for passenger cars and light trucks be based on one or more vehicle attributes related to fuel economy and be expressed in the form of a mathematical function.

While the CAA includes no specific requirements regarding GHG regulation, EPA has chosen to adopt standards consistent with the EPCA/EISA requirements in the interest of simplifying compliance for the industry since 2010.

Section II.C.1 describes the advantages of attribute standards, generally. Section II.C.2 explains the agencies' specific decision to use vehicle footprint as the attribute over which to vary stringency for past and current rules. Section II.C.3 discusses the policy considerations in selecting the specific mathematical function. Section II.C.4 discusses the methodologies used to develop current attribute-based standards, and the agencies' current proposal to continue to do so for MYs 2022-2026. Section II.C.5 discusses the methodologies used to reconsider the mathematical function for the proposed standards.

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

Such an approach is permissible under section 202(a) of the CAA, and EPA has used the attribute-based approach in issuing standards under analogous provisions of the CAA.

1. Why attribute-based standards, and what are the benefits?

Under attribute-based standards, every vehicle model has fuel economy and CO

targets, the levels of which depend on the level of that vehicle's determining attribute (for this proposed rule, footprint is the determining attribute, as discussed below). The manufacturer's fleet average performance is calculated by the harmonic production-weighted average of those targets, as defined below:

EP24AU18.015

Here,

represents a given model

in a manufacturer's fleet,

Production

represents the U.S. production of that model, and

Target

represents the target as defined by the attribute-based standards. This means no vehicle is required to meet its target; instead, manufacturers are free to balance improvements however they deem best within (and, given credit transfers, at least partially across) their fleets.

If a model has more than one footprint variant, here each of those variants is treated as a unique model,

since each footprint variant will have a unique target.

The idea is to select the shape of the mathematical function relating the standard to the fuel economy-related attribute to reflect the trade-offs manufacturers face in producing more of that attribute over fuel efficiency (due to technological limits of production and relative demand of each attribute). If the shape captures these trade-offs, every manufacturer is more likely to continue adding fuel efficient technology across the distribution of the attribute within their fleet, instead of potentially changing the attribute—and other correlated attributes, including fuel economy—as a part of their compliance strategy. Attribute-based standards that achieve this have several advantages.

First, assuming the attribute is a measurement of vehicle size, attribute-based standards reduce the incentive for manufacturers to respond to CAFE standards by reducing vehicle size in ways harmful to safety.

Larger vehicles, in terms of mass and/or crush space, generally consume more fuel, but are also generally better able to protect occupants in a crash.

Because each vehicle model has its own target (determined by a size-related attribute), properly fitted attribute-based standards provide little, if any, incentive to build smaller vehicles simply to meet a fleet-wide average, because smaller vehicles are subject to more stringent compliance targets.

The 2002 NAS Report described at length and quantified the potential safety problem with average fuel economy standards that specify a single numerical requirement for the entire industry.

See

Transportation Research Board and National Research Council. 2002.

Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards,

Washington, DC: The National Academies Press (“2002 NAS Report”) at 5, finding 12,

available at

https://www.nap.edu/catalog/10172/effectiveness-and-impact-of-corporate-average-fuel-economy-cafe-standards

(last accessed June 15, 2018). Ensuing analyses, including by NHTSA, support the fundamental conclusion that standards structured to minimize incentives to downsize all but the largest vehicles will tend to produce better safety outcomes than flat standards.

Bento, A., Gillingham, K., & Roth, K. (2017). The Effect of Fuel Economy Standards on Vehicle Weight Dispersion and Accident Fatalities. NBER Working Paper No. 23340.

Available at

http://www.nber.org/papers/w23340

(last accessed June 15, 2018).

Second, attribute-based standards, if properly fitted, better respect heterogeneous consumer preferences than do single-valued standards. As discussed above, a single-valued standard encourages a fleet mix with a larger share of smaller vehicles by creating incentives for manufacturers to use downsizing the average vehicle in their fleet (possibly through fleet mixing) as a compliance strategy, which may result in manufacturers building vehicles for compliance reasons that consumers do not want. Under a size-related, attribute-based standard, reducing the size of the vehicle is a less viable compliance strategy because smaller vehicles have more stringent regulatory targets. As a result, the fleet mix under such standards is more likely to reflect aggregate consumer demand for the size-related attribute used to determine vehicle targets.

Third, attribute-based standards provide a more equitable regulatory framework across heterogeneous manufacturers who may each produce different shares of vehicles along attributes correlated with fuel economy.

A single, industry-wide CAFE standard imposes disproportionate cost burden and compliance challenges on manufacturers who produce more vehicles with attributes inherently correlated with lower fuel economy—

i.e.

manufacturers who produce, on average, larger vehicles. As discussed above, retaining the ability for manufacturers to produce vehicles which respect heterogeneous market preferences is an important consideration. Since manufacturers may target different markets as a part of their business strategy, ensuring that these manufacturers do not incur a disproportionate share of the regulatory cost burden is an important part of conserving consumer choices within the market.

2002 NAS Report at 4-5, finding 10.

2. Why footprint as the attribute?

It is important that the CAFE and CO

standards be set in a way that does not encourage manufacturers to respond by selling vehicles that are less safe. Vehicle size is highly correlated with vehicle safety—for this reason, it is important to choose an attribute correlated with vehicle size (mass or some dimensional measure). Given this consideration, there are several policy and technical reasons why footprint is considered to be the most appropriate attribute upon which to base the standards, even though other vehicle size attributes (notably, curb weight) are more strongly correlated with fuel economy and emissions.

First, mass is strongly correlated with fuel economy; it takes a certain amount of energy to move a certain amount of mass. Footprint has some positive correlation with frontal surface area, likely a negative correlation with aerodynamics, and therefore fuel economy, but the relationship is less deterministic. Mass and crush space (correlated with footprint) are both important safety considerations. As discussed below and in the accompanying PRIA, NHTSA's research of historical crash data indicates that holding footprint constant, and decreasing the mass of the largest vehicles, will have a net positive safety impact to drivers overall, while holding footprint constant and decreasing the mass of the smallest vehicles will have a net decrease in fleetwide safety. Properly fitted footprint-based standards provide little, if any, incentive to build smaller vehicles to meet CAFE and CO

standards, and therefore help minimize the impact of standards on overall fleet safety.

Second, it is important that the attribute not be easily manipulated in a manner that does not achieve the goals of EPCA or other goals, such as safety. Although weight is more strongly correlated with fuel economy than footprint, there is less risk of manipulation (changing the attribute(s) to achieve a more favorable target) by increasing footprint under footprint-based standards than there would be by increasing vehicle mass under weight-based standards. It is relatively easy for a manufacturer to add enough weight to a vehicle to decrease its applicable fuel economy target a significant amount, as compared to increasing vehicle

footprint, which is a much more complicated change that typically takes place only with a vehicle redesign.

Further, some commenters on the MY 2011 CAFE rulemaking were concerned that there would be greater potential for gaming under multi-attribute standards, such as those that also depend on weight, torque, power, towing capability, and/or off-road capability. As discussed in NHTSA's MY 2011 CAFE final rule,

it is anticipated that the possibility of gaming is lowest with footprint-based standards, as opposed to weight-based or multi-attribute-based standards. Specifically, standards that incorporate weight, torque, power, towing capability, and/or off-road capability in addition to footprint would not only be more complex, but by providing degrees of freedom with respect to more easily-adjusted attributes, they could make it less certain that the future fleet would actually achieve the projected average fuel economy and CO

levels. This is not to say that a footprint-based system will eliminate gaming, or that a footprint-based system will eliminate the possibility that manufacturers will change vehicles in ways that compromise occupant protection, but footprint-based standards achieve the best balance among affected considerations. Please provide comments on whether vehicular footprint is the most suitable attribute upon which to base standards.

See

74 FR at 14359 (Mar. 30, 2009).

3. What mathematical function should be used to specify footprint-based standards?

In requiring NHTSA to “prescribe by regulation separate average fuel economy standards for passenger and non-passenger automobiles based on 1 or more vehicle attributes related to fuel economy and express each standard in the form of a mathematical function”, EPCA/EISA provides ample discretion regarding not only the selection of the attribute(s), but also regarding the nature of the function. The CAA provides no specific direction regarding CO

regulation, and EPA has continued to harmonize this aspect of its CO

regulations with NHTSA's CAFE regulations. The relationship between fuel economy (and GHG emissions) and footprint, though directionally clear (

i.e.,

fuel economy tends to decrease and CO2 emissions tend to increase with increasing footprint), is theoretically vague, and quantitatively uncertain; in other words, not so precise as to

a priori

yield only a single possible curve.

The decision of how to specify this mathematical function therefore reflects some amount of judgment. The function can be specified with a view toward achieving different environmental and petroleum reduction goals, encouraging different levels of application of fuel-saving technologies, avoiding any adverse effects on overall highway safety, reducing disparities of manufacturers' compliance burdens, and preserving consumer choice, among other aims. The following are among the specific technical concerns and resultant policy tradeoffs the agencies have considered in selecting the details of specific past and future curve shapes:

• Flatter standards (

i.e.,

curves) increase the risk that both the size of vehicles will be reduced, potentially compromising highway safety, and reducing any utility consumers would have gained from a larger vehicle.

• Steeper footprint-based standards may create incentives to upsize vehicles, potentially oversupplying vehicles of certain footprints beyond what consumers would naturally demand, and thus increasing the possibility that fuel savings and CO

reduction benefits will be forfeited artificially.

• Given the same industry-wide average required fuel economy or CO

standard, flatter standards tend to place greater compliance burdens on full-line manufacturers.

• Given the same industry-wide average required fuel economy or CO

standard, dramatically steeper standards tend to place greater compliance burdens on limited-line manufacturers (depending of course, on which vehicles are being produced).

• If cutpoints are adopted, given the same industry-wide average required fuel economy, moving small-vehicle cutpoints to the left (

i.e.,

up in terms of fuel economy, down in terms of CO

emissions) discourages the introduction of small vehicles, and reduces the incentive to downsize small vehicles in ways that could compromise overall highway safety.

• If cutpoints are adopted, given the same industry-wide average required fuel economy, moving large-vehicle cutpoints to the right (

i.e.,

down in terms of fuel economy, up in terms of CO

emissions) better accommodates the design requirements of larger vehicles — especially large pickups — and extends the size range over which downsizing is discouraged.

4. What mathematical functions have been used previously, and why?

Notwithstanding the aforementioned discretion under EPCA/EISA, data should inform consideration of potential mathematical functions, but how relevant data is defined and interpreted, and the choice of methodology for fitting a curve to that data, can and should include some consideration of specific policy goals. This section summarizes the methodologies and policy concerns that were considered in developing previous target curves (for a complete discussion see the 2012 FRIA).

As discussed below, the MY 2011 final curves followed a constrained logistic function defined specifically in the final rule.

The MYs 2012-2021 final standards and the MYs 2022-2025 augural standards are defined by constrained linear target functions of footprint, as shown below:

See

74 FR 14196, 14363-14370 (Mar. 30, 2009) for NHTSA discussion of curve fitting in the MY 2011 CAFE final rule.

The right cutpoint for the light truck curve was moved further to the right for MYs 2017-2021, so that more possible footprints would fall on the sloped part of the curve. In order to ensure that, for all possible footprints, future standards would be at least as high as MY 2016 levels, the final standards for light trucks for MYs 2017-2021 is the maximum of the MY 2016 target curves and the target curves for the give MY standard. This is defined further in the 2012 final rule.

See

77 FR 62624, at 62699-700 (Oct. 15, 2012).

EP24AU18.016

Here,

Target

is the fuel economy target applicable to vehicles of a given footprint in square feet (

Footprint

). The upper asymptote,

and the lower asymptote,

are specified in mpg; the reciprocal of these values represent the lower and upper asymptotes, respectively, when the curve is instead specified in gallons per mile (gpm). The

slope,

and the intercept,

of the linear portion of the curve are specified as gpm per change in square feet, and gpm, respectively.

The min and max functions will take the minimum and maximum values within their associated parentheses. Thus, the max function will first find the maximum of the fitted line at a given footprint value and the lower asymptote from the perspective of gpm. If the fitted line is below the lower asymptote it is replaced with the floor, which is also the minimum of the floor and the ceiling by definition, so that the target in mpg space will be the reciprocal of the floor in mpg space, or simply,

If, however, the fitted line is not below the lower asymptote, the fitted value is returned from the max function and the min function takes the minimum value of the upper asymptote (in gpm space) and the fitted line. If the fitted value is below the upper asymptote, it is between the two asymptotes and the fitted value is appropriately returned from the min function, making the overall target in mpg the reciprocal of the fitted line in gpm. If the fitted value is above the upper asymptote, the upper asymptote is returned is returned from the min function, and the overall target in mpg is the reciprocal of the upper asymptote in gpm space, or

In this way curves specified as constrained linear functions are specified by the following parameters:

= upper limit (mpg)

= lower limit (mpg)

= slope (gpm per sq. ft.)

= intercept (gpm)

The slope and intercept are specified as gpm per sq. ft. and gpm instead of mpg per sq. ft. and mpg because fuel consumption and emissions appear roughly linearly related to gallons per mile (the reciprocal of the miles per gallon).

(a) NHTSA in MY 2008 and MY 2011 CAFE (Constrained Logistic)

For the MY 2011 CAFE rule, NHTSA estimated fuel economy levels by footprint from the MY 2008 fleet after normalization for differences in technology,

but did not make adjustments to reflect other vehicle attributes (

e.g.,

power-to-weight ratios). Starting with the technology-adjusted passenger car and light truck fleets, NHTSA used minimum absolute deviation (MAD) regression without sales weighting to fit a logistic form as a starting point to develop mathematical functions defining the standards. NHTSA then identified footprints at which to apply minimum and maximum values (rather than letting the standards extend without limit) and transposed these functions vertically (

i.e.,

on a gallons-per-mile basis, uniformly downward) to produce the promulgated standards. In the preceding rule, for MYs 2008-2011 light truck standards, NHTSA examined a range of potential functional forms, and concluded that, compared to other considered forms, the constrained logistic form provided the expected and appropriate trend (decreasing fuel economy as footprint increases), but avoided creating “kinks” the agency was concerned would provide distortionary incentives for vehicles with neighboring footprints.

100

See

74 FR 14196, 14363-14370 (Mar. 30, 2009) for NHTSA discussion of curve fitting in the MY 2011 CAFE final rule.

100

See

71 FR 17556, 17609-17613 (Apr. 6, 2006) for NHTSA discussion of “kinks” in the MYs 2008-2011 light truck CAFE final rule (there described as “edge effects”). A “kink,” as used here, is a portion of the curve where a small change in footprint results in a disproportionally large change in stringency.

(b) MYs 2012-2016 Standards (Constrained Linear)

For the MYs 2012-2016 rule, potential methods for specifying mathematical functions to define fuel economy and CO

standards were reevaluated. These methods were fit to the same MY 2008 data as the MY 2011 standard. Considering these further specifications, the constrained logistic form, if applied to post-MY 2011 standards, would likely contain a steep mid-section that would provide undue incentive to increase the footprint of midsize passenger cars.

101

A range of methods to fit the curves would have been reasonable, and a minimum absolute deviation (MAD) regression without sales weighting on a technology-adjusted car and light truck fleet was used to fit a linear equation. This equation was used as a starting point to develop mathematical functions defining the standards. Footprints were then identified at which to apply minimum and maximum values (rather than letting the standards extend without limit). Finally, these constrained/piecewise linear functions were transposed vertically (

i.e.,

on a gpm or CO

basis, uniformly downward) by multiplying the initial curve by a single factor for each MY standard to

This text is long and has been trimmed here. Open the source document for the complete record.

This is a copy of a public record, reproduced as it was published. It is not legal advice, and it may not be the version a court would rely on. Check the official source before you cite it.